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Posts Tagged ‘Parkinsons disease’


Lesson 5 Cell Signaling And Motility: Cytoskeleton & Actin: Curations and Articles of reference as supplemental information: #TUBiol3373

Curator: Stephen J. Williams, Ph.D.

Cell motility or migration is an essential cellular process for a variety of biological events. In embryonic development, cells migrate to appropriate locations for the morphogenesis of tissues and organs. Cells need to migrate to heal the wound in repairing damaged tissue. Vascular endothelial cells (ECs) migrate to form new capillaries during angiogenesis. White blood cells migrate to the sites of inflammation to kill bacteria. Cancer cell metastasis involves their migration through the blood vessel wall to invade surrounding tissues.

Please Click on the Following Powerpoint Presentation for Lesson 4 on the Cytoskeleton, Actin, and Filaments

CLICK ON LINK BELOW

cell signaling 5 lesson

This post will be updated with further information when we get into Lesson 6 and complete our discussion on the Cytoskeleton

Please see the following articles on Actin and the Cytoskeleton in Cellular Signaling

Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility

This article, constitutes a broad, but not complete review of the emerging discoveries of the critical role of calcium signaling on cell motility and, by extension, embryonic development, cancer metastasis, changes in vascular compliance at the junction between the endothelium and the underlying interstitial layer.  The effect of calcium signaling on the heart in arrhtmogenesis and heart failure will be a third in this series, while the binding of calcium to troponin C in the synchronous contraction of the myocardium had been discussed by Dr. Lev-Ari in Part I.

Universal MOTIFs essential to skeletal muscle, smooth muscle, cardiac syncytial muscle, endothelium, neovascularization, atherosclerosis and hypertension, cell division, embryogenesis, and cancer metastasis. The discussion will be presented in several parts:
1.  Biochemical and signaling cascades in cell motility
2.  Extracellular matrix and cell-ECM adhesions
3.  Actin dynamics in cell-cell adhesion
4.  Effect of intracellular Ca++ action on cell motility
5.  Regulation of the cytoskeleton
6.  Role of thymosin in actin-sequestration
7.  T-lymphocyte signaling and the actin cytoskeleton

 

Identification of Biomarkers that are Related to the Actin Cytoskeleton

In this article the Dr. Larry Bernstein covers two types of biomarker on the function of actin in cytoskeleton mobility in situ.

  • First, is an application in developing the actin or other component, for a biotarget and then, to be able to follow it as

(a) a biomarker either for diagnosis, or

(b) for the potential treatment prediction of disease free survival.

  • Second, is mostly in the context of MI, for which there is an abundance of work to reference, and a substantial body of knowledge about

(a) treatment and long term effects of diet, exercise, and

(b) underlying effects of therapeutic drugs.

Microtubule-Associated Protein Assembled on Polymerized Microtubules

(This article has a great 3D visualization of a microtuble structure as well as description of genetic diseases which result from mutations in tubulin and effects on intracellular trafficking of proteins.

A latticework of tiny tubes called microtubules gives your cells their shape and also acts like a railroad track that essential proteins travel on. But if there is a glitch in the connection between train and track, diseases can occur. In the November 24, 2015 issue of PNAS, Tatyana Polenova, Ph.D., Professor of Chemistry and Biochemistry, and her team at the University of Delaware (UD), together with John C. Williams, Ph.D., Associate Professor at the Beckman Research Institute of City of Hope in Duarte, California, reveal for the first time — atom by atom — the structure of a protein bound to a microtubule. The protein of focus, CAP-Gly, short for “cytoskeleton-associated protein-glycine-rich domains,” is a component of dynactin, which binds with the motor protein dynein to move cargoes of essential proteins along the microtubule tracks. Mutations in CAP-Gly have been linked to such neurological diseases and disorders as Perry syndrome and distal spinal bulbar muscular dystrophy.

 

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New Imaging Application for Parkinson’s

Larry H. Bernstein, Md, FCAP, Curator

LPBI

 

Brain imaging technology offers new approach for studying Parkinsonian syndromes

http://www.bioopticsworld.com/articles/pt/2016/01/brain-imaging-technology-offers-new-approach-for-studying-parkinsonian-syndromes.html

 

file

 

The prefrontal cortex, highlighted in red, is responsible for high-level functions like memory, attention and problem solving.
Credit: Life Science Databases

http://www.bioopticsworld.com/content/bow/en/articles/pt/2016/01/brain-imaging-technology-offers-new-approach-for-studying-parkinsonian-syndromes/_jcr_content/leftcolumn/article/headerimage.img.jpg

Using a portable device, researchers have identified differences in brain activation patterns associated with postural stability in people with Parkinsonian syndromes and healthy adults. The findings describe the critical role of the prefrontal cortex in balance control and may have implications with respect to detecting and treating Parkinsonian symptoms in the elderly.

The BioOptics World take on this story:

A newly developed portable device that employs functional near-infrared (fNIR) spectroscopy (a light-based technique to monitor changes in blood oxygenation in the brain) can identify differences in brain activation patterns associated with postural stability in people with Parkinson’s disease and healthy adults. The development allows scientists to better understand the role of the brain’s prefrontal cortex during standing and walking.

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Related: New fluorescence imaging reagent targets degenerative diseases

Brain imaging technology offers new approach for studying Parkinsonian syndromes
 Drexel University

Parkinson’s disease is a neurological disorder that arises when brain cells that control movement die, leaving many patients in the late stages of the disease unable to take a few steps before falling. Parkinsonian syndromes, which are common in older adults, are conditions that do not rise to a Parkinson’s diagnosis but encompass many symptoms of the disease, like rigidity, tremor and difficulty walking.

Past attempts to compare brain activity and stability in people with Parkinsonian syndromes have been limited, because neuroimaging tools could only be used when a study participant was lying flat, rather than walking or standing. In these cases, the person undergoing the brain scan could only imagine that he or she was performing the tasks.

A portable system created by researchers in Drexel’s School of Biomedical Engineering and Health Systems overcomes this challenge. It has allowed scientists, for the first time, to better understand the role of the brain’s prefrontal cortex during standing and walking.

The device employs functional near-infrared, or fNIR, spectroscopy, which uses light to monitor changes in blood oxygenation in the brain as individuals perform tasks, take tests or receive stimulation. The prefrontal cortex is the area responsible for higher-level processing, such as memory, attention, problem solving and decision-making. When a person is learning a new skill, for instance, neural activity is greater in this region.

Unlike fMRI (functional magnetic resonance imaging), the fNIR system is fully portable: Participants wear a headband, allowing them to talk and move around while a computer collects data in real time.

“Postural instability is a major risk factor for older adults. If we can monitor the cognitive component of staying balanced, then this could eventually lead to better treatment options for people with Parkinsonian syndromes or even Parkinson’s disease,” said Meltem Izzetoglu, PhD, an assistant research professor of biomedical engineering at Drexel who co-authored the study.

Researchers at Albert Einstein College of Medicine used the fNIR technology to compare 126 healthy adults to 117 individuals with mild Parkinson’s symptoms and 26 with more severe symptoms. While wearing the fNIR headband, the participants were asked to stand and look straight ahead while counting for 10 seconds. They then walked on a mat that captured their gait speed, pace and stride length. The fNIR system recorded their brain oxygen levels during the entire testing period.

The researchers found that those with Parkinsonian symptoms demonstrated significantly higher prefrontal oxygenation levels to maintain stability when standing than participants with mild and no symptoms.

“In fact, brain activity in the frontal brain region was nearly twice as large,” said Jeannette R. Mahoney, PhD, assistant professor of neurology at Einstein and the study’s lead author.

“This initial study allowed us to measure brain activity in real-time, in a realistic setting. It shows that there are indeed differences in the prefrontal cortex of healthy and Parkinsonian syndrome patients, and those differences relate to their performance in maintaining stability while standing,” Izzetoglu said. “It opens up new fields of research.”

In an upcoming clinical trial, the researchers will use a computerized cognitive training program and the fNIR system to identify how cognitive training affects brain activation during walking.

The portable technology could aid in diagnosing Parkinsonian syndromes or developing interventions.

“Our goal is to be able to intervene with Parkinsonian symptoms and develop novel remediation in the not-so-distant future to improve elders’ quality of life,” Mahoney said.

Jeannette R. Mahoney, Roee Holtzer, Meltem Izzetoglu, Vance Zemon, Joe Verghese, Gilles Allali. The role of prefrontal cortex during postural control in Parkinsonian syndromes a functional near-infrared spectroscopy study. Brain Research, 2015; DOI:10.1016/j.brainres.2015.10.053

Drexel University. “Brain imaging technology offers new approach for studying Parkinsonian syndromes.” ScienceDaily. ScienceDaily, 18 December 2015. <www.sciencedaily.com/releases/2015/12/151218113326.htm>.
New imaging test gives physicians better tool to diagnose Parkinson’s disease
August 25, 2011    Source:  Northwestern Memorial Hospital
Summary:
Physicians now have an objective test to evaluate patients for Parkinsonian syndromes, such as Parkinson’s disease. DaTscan™ is the only FDA-approved imaging agent for assessment of movement disorders. Until now, there were no definitive tests to identify the disease, forcing physicians to rely on clinical examinations to make a diagnosis. This technology allows doctors to differentiate Parkinson’s from other movement disorders.

Until now, there were no definitive tests to identify the disease, forcing physicians to rely on clinical examinations to make a diagnosis. This technology allows doctors to differentiate Parkinson’s from other movement disorders.

“The scan by itself does not make the diagnosis of Parkinson’s but it allows us to identify patients who have loss of dopamine, the major chemical responsible for the symptoms, from those who have no dopamine deficiency,” said Tanya Simuni, MD, a neurologist at Northwestern Memorial and director of Northwestern’s Parkinson’s Disease and Movement Disorders Center. “This is a very important step in being able to accurately identify and treat movement disorders and hopefully allow us to better understand these diseases over time.”

Parkinson’s disease is a neurodegenerative disorder that afflicts nearly 1.5 million Americans, with an additional 50,000 to 60,000 new cases identified each year. People with Parkinson’s lack dopamine in the brain, which leads to tremor, slowness of movement, muscle stiffness and balance problems. Clinical examinations, particularly early in the disease when symptoms are slight, can be inconclusive or lead to misdiagnosis of another movement disorder, such as essential tremor, which share similar symptoms to Parkinson’s, but require different treatment.

Developed by GE Healthcare, DaTscan is a substance used to detect the presence of dopamine transporters (DaT) in the brain. A patient is injected with the contrast agent and then undergoes a single-photon emission computed tomography (SPECT) scan. The test captures detailed pictures of the brain’s dopamine system and can provide visual evidence of the presence of dopamine transporters. Scans of patients with Parkinson’s disease or another parkinsonian syndrome will show very low dopamine levels. A SPECT scan examines brain function, rather than structure, and can show change in the brain’s chemistry.

“In Parkinson’s patients the brain’s anatomy remains largely normal, unlike other conditions such as stroke, where damage to the brain is visible,” explained Simuni, who is also an associate professor of neurology at Northwestern University Feinberg School of Medicine. “DaTscan attaches to dopamine neurons which illuminate on the SPECT scan; the more light areas that exist, the more healthy dopamine brain cells remain. If the areas of the brain that should show dopamine remain dark, it may indicate the patient has some type of parkinsonian syndrome.”

An accurate clinical diagnosis for patients with neurodegenerative movement disorders, such as Parkinson’s, can take up to six years. While symptoms often mimic Parkinson’s, other movement disorders, such as essential tremor, occur in different areas of the brain and do not involve the dopamine system.

“Even though they may appear similar, other movement disorders require different management. DaTscan allows us to confirm our diagnosis earlier and start the correct course of treatment sooner,” said Simuni. “We are hopeful that this will lead to improved quality of life for these patients with better long term outcomes, as well as protection from unnecessary treatments initiated because of misdiagnosis.”

While Simuni does not believe it is necessary for every patient to confirm their Parkinson’s diagnosis with DaTscan, she does see it as a valuable tool for patients with uncertain syndromes, or those who have not responded to treatment. She also sees it as a means for improving Parkinson’s research by ensuring those enrolled in studies actually have the disease. DaTscan is already being used by the Michael J. Fox Foundation for its landmark biomarkers study, the Parkinson’s Progression Markers Initiative (PPMI), to validate that the subjects have Parkinson’s disease. Northwestern is one of the 14 U.S. medical centers enrolling for the PPMI, which is among the first clinical trials using DaTscan in this way.

“Currently, we are not able to say with certainty that those enrolled in Parkinson’s studies have the disease,” said Simuni. “With the addition of DaTscan, we can be much more confident in the status of research subjects in both the control and experimental groups. By having a better understanding of these populations, we should be able to have clearer outcomes and hopefully that will translate sooner into treatments and eventually a cure.”

Researchers are also hopeful that DaTscan will prove to be useful in following the progression of Parkinson’s throughout a patient’s lifetime. “The disease is clinically measured at certain points of time to help physicians understand its development,” said Simuni. “A lot of questions about how Parkinson’s disease progresses can be answered if DaTscan is able to show us changes in the brain’s chemistry over time.”

 Northwestern Memorial Hospital. “New imaging test gives physicians better tool to diagnose Parkinson’s disease.” ScienceDaily. ScienceDaily, 25 August 2011. <www.sciencedaily.com/releases/2011/08/110825105029.htm>.
Abnormal oscillation in the brain causes motor deficits in Parkinson’s disease
November 1, 2011    National Institute for Physiological Sciences
Summary:   Scientists have shown that the ‘oscillatory’ nature of electrical signals in subcortical nuclei, the basal ganglia, causes severe motor deficits in Parkinson’s disease, by disturbing the information flow of motor commands.

The research group headed by Professor Atsushi Nambu (The National Institute for Physiological Sciences) and Professor Masahiko Takada (Primate Research Institute,Kyoto University) has shown that the ‘oscillatory’ nature of electrical signals in subcortical nuclei, the basal ganglia, causes severe motor deficits in Parkinson’s disease, by disturbing the information flow of motor commands. The group also found that chemical inactivation of the subthalamic nucleus (a structure of the basal ganglia) in parkinsonian monkeys improved the motor impairments by reducing the ‘oscillations.’

The results of this study were reported in European Journal of Neuroscience,November 2011 issue.

A member of the research group, Assistant Professor Yoshihisa Tachibana, succeeded to record electrical signals in monkey basal ganglia neurons under unanesthetized conditions. The group found that neurons in the parkinsonian basal ganglia showed abnormal ‘oscillatory’ activity, which was rarely seen in normal subjects. The abnormal rhythm was completely eliminated by systemic administration of a dopamine precursor (L-DOPA), which is clinically used for human parkinsonian patients. The group considered that loss of dopamine induced the ‘oscillations’ in the basal ganglia and that the following disturbances in information flow of motor commands impaired motor performances.

Abnormal neuronal oscillations were already reported in parkinsonian patients and animal models, but this report has provided the direct evidence that ‘oscillations’ are associated with motor abnormalities. Moreover, it was also shown that the injection of a chemical inhibitor, muscimol, into the subthalamic nucleus silenced the oscillatory signals, and eventually reversed parkinsonian motor signs.

Professor Nambu claims, “By investigating the ‘oscillatory’ nature of electrical signals in the basal ganglia, we can advance our understanding of the pathophysiology of Parkinson’s disease. We improved motor deficits by means of infusion of the chemical inhibitor (muscimol) into the subthalamic nucleus to silence the ‘oscillatory’ signals in the brain structure. This may provide us important clues to developing new treatments for Parkinson’s disease.”

This study was supported by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan, the Japan Intractable Diseases Research Foundation and Hori Information Science Promotion Foundation to Y. Tachibana and A. Nambu, and NIH grants (NS-47085 and NS-57236) to H. Kita.

Yoshihisa Tachibana, Hirokazu Iwamuro, Hitoshi Kita, Masahiko Takada, Atsushi Nambu. Subthalamo-pallidal interactions underlying parkinsonian neuronal oscillations in the primate basal ganglia.European Journal of Neuroscience, 2011; 34 (9): 1470 DOI:10.1111/j.1460-9568.2011.07865.x

National Institute for Physiological Sciences. “Abnormal oscillation in the brain causes motor deficits in Parkinson’s disease.” ScienceDaily. ScienceDaily, 1 November 2011. <www.sciencedaily.com/releases/2011/11/111101095306.htm>.
Mental picture of others can be seen using fMRI, finds new study 
March 5, 2013
Source:  Cornell University
Summary:
It is possible to tell who a person is thinking about by analyzing images of his or her brain. Our mental models of people produce unique patterns of brain activation, which can be detected using advanced imaging techniques according to a new study.

“When we looked at our data, we were shocked that we could successfully decode who our participants were thinking about based on their brain activity,” said Spreng, assistant professor of human development in Cornell’s College of Human Ecology.

Understanding and predicting the behavior of others is a key to successfully navigating the social world, yet little is known about how the brain actually models the enduring personality traits that may drive others’ behavior, the authors say. Such ability allows us to anticipate how someone will act in a situation that may not have happened before.

To learn more, the researchers asked 19 young adults to learn about the personalities of four people who differed on key personality traits. Participants were given different scenarios (i.e. sitting on a bus when an elderly person gets on and there are no seats) and asked to imagine how a specified person would respond. During the task, their brains were scanned using functional magnetic resonance imaging (fMRI), which measures brain activity by detecting changes in blood flow.

They found that different patterns of brain activity in the medial prefrontal cortex (mPFC) were associated with each of the four different personalities. In other words, which person was being imagined could be accurately identified based solely on the brain activation pattern.

The results suggest that the brain codes the personality traits of others in distinct brain regions and this information is integrated in the medial prefrontal cortex (mPFC) to produce an overall personality model used to plan social interactions, the authors say.

The study, “Imagine All the People: How the Brain Creates and Uses Personality Models to Predict Behavior,” published online March 5 in the journal Cerebral Cortex and was coauthored by Demis Hassabis, University College London, Andrie Rusu, Vrije Univesiteit, Clifford Robbins, Harvard University, Raymond Mar, York University, and Daniel L. Schacter, Harvard University

Demis Hassabis, R. Nathan Spreng, Andrei A. Rusu, Clifford A. Robbins, Raymond A. Mar, and Daniel L. Schacter. Imagine All the People: How the Brain Creates and Uses Personality Models to Predict Behavior.Cerebral Cortex, 2013; DOI: 10.1093/cercor/bht042

Cornell University. “Mental picture of others can be seen using fMRI, finds new study.” ScienceDaily. ScienceDaily, 5 March 2013. <www.sciencedaily.com/releases/2013/03/130305091000.htm>.

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Retromer in neurological disorders

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

Retromer in Alzheimer disease, Parkinson disease and other neurological disorders.

Scott A. Small and Gregory A. Petsko
Nature Reviews Neuroscience 16; 126–132 (2015)      http://dx.doi.org:/10.1038/nrn3896

 

As discussed in the forum (see video here), there are many cellular pathways which are believed to be perturbed in Alzheimer’s Disease. Recent work has suggested that deficits in retromer complex function may underlie impairment of endosomal trafficking in neurons and may contribute to AD pathogenesis. This recent review illustrates the function of the retromer complex and discusses how its dysfunction may contribute to neurodegeneration.

By Tim Spencer on 24 Nov, 2015

 

Retromer is a protein assembly that has a central role in endosomal trafficking, and retromer dysfunction has been linked to a growing number of neurological disorders. First linked to Alzheimer disease, retromer dysfunction causes a range of pathophysiological consequences that have been shown to contribute to the core pathological features of the disease. Genetic studies have established that retromer dysfunction is also pathogenically linked to Parkinson disease, although the biological mechanisms that mediate this link are only now being elucidated. Most recently, studies have shown that retromer is a tractable target in drug discovery for these and other disorders of the nervous system.

 

Yeast has proved to be an informative model organism in cell biology and has provided early insight into much of the molecular machinery that mediates the intracellular transport of proteins1,2. Indeed, the term ‘retromer’ was first introduced in a yeast study in 1998 (Ref. 3). In this study, retromer was referred to as a complex of proteins that was dedicated to transporting cargo in a retrograde direction, from the yeast endosome back to the Golgi.

By 2004, a handful of studies had identified the molecular4 and the functional5, 6 homologies of the mammalian retromer, and in 2005 retromer was linked to its first human disorder, Alzheimer disease (AD)7. At the time, the available evidence suggested that the mammalian retromer might match the simplicity of its yeast homologue. Since then, a dramatic and exponential rise in research focusing on retromer has led to more than 300 publications. These studies have revealed the complexity of the mammalian retromer and its functional diversity in endosomal transport, and have implicated retromer in a growing number of neurological disorders.

New evidence indicates that retromer is a ‘master conductor’ of endosomal sorting and trafficking8. Synaptic function heavily depends on endosomal trafficking, as it contributes to the presynaptic release of neurotransmitters and regulates receptor density in the postsynaptic membrane, a process that is crucial for neuronal plasticity9. Therefore, it is not surprising that a growing number of studies are showing that retromer has an important role in synaptic biology10, 11, 12, 13. These observations may account for why the nervous system seems particularly sensitive to genetic and other defects in retromer. In this Progress article, we briefly review the molecular organization and the functional role of retromer, before discussing studies that have linked retromer dysfunction to several neurological diseases — notably, AD and Parkinson disease (PD).

 

The endosome is considered a hub for intracellular transport. From the endosome, transmembrane proteins can be actively sorted and trafficked to various intracellular sites via distinct transport routes (Fig. 1a). Studies have shown that the mammalian retromer mediates two of the three transport routes out of endosomes. First, retromer is involved in the retrieval of cargos from endosomes and in their delivery, in a retrograde direction, to the trans-Golgi network (TGN)5,6. Retrograde transport has many cellular functions but, as we describe, it is particularly important for the normal delivery of hydrolases and proteases to the endosomal–lysosomal system. The second transport route in which retromer functions is the recycling of cargos from endosomes back to the cell surface14, 15 (Fig. 1a). It is this transport route that is particularly important for neurons, as it mediates the normal delivery of glutamate and other receptors to the plasma membrane during synaptic remodelling and plasticity10, 11, 12, 13.

Figure 1: Retromer’s endosomal transport function and molecular organization.
Retromer's endosomal transport function and molecular organization.

a | Retromer mediates two transport routes out of endosomes via tubules that extend out of endosomal membranes. The first is the retrograde pathway in which cargo is retrieved from the endosome and trafficked to the trans-Golgi network (TGN). The second is the recycling pathway in which cargo is trafficked back from the endosome to the cell surface. The degradation pathway, which is not mediated by retromer, involves the trafficking of cargo from endosomes to lysosomes for degradation. b | The retromer assembly of proteins can be organized into distinct functional modules, all of which work together as part of retromer’s transport role. The ‘cargo-recognition core’ is the central module of the retromer assembly and comprises a trimer of proteins, in which vacuolar protein sorting-associated protein 26 (VPS26) and VPS29 bind VPS35. The ‘tubulation’ module includes protein complexes that bind the cargo-recognition core and aid in the formation and stabilization of tubules that extend out of endosomes, directing the transport of cargos towards their final destinations. The ‘membrane-recruiting’ proteins recruit the cargo-recognition core to the endosomal membrane. The WAS protein family homologue (WASH) complex of proteins also binds the cargo-recognition core and is involved in endosomal ‘actin remodelling’ to form actin patches, which are important for directing cargos towards retromer’s transport pathways. Retromer cargos includes a range of receptors — which bind the cargo-recognition core — and their ligands. PtdIns3P, phosphatidylinositol-3-phosphate.

As well as extending the endosomal transport routes, recent studies have considerably expanded the number of molecular constituents and what is known about the functional organization of the mammalian retromer. Following this expansion in knowledge of the molecular diversity and organizational complexity, retromer might be best described as a multimodular protein assembly. The protein or group of proteins that make up each module can vary, but each module is defined by its distinct function, and the modules work in unison in support of retromer’s transport role.

Two modules are considered central to the retromer assembly. First and foremost is a trimeric complex that functions as a ‘cargo-recognition core’, which selects and binds to the transmembrane proteins that need to be transported and that reside in endosomal membranes5, 6. This trimeric core comprises vacuolar protein sorting-associated protein 26 (VPS26), VPS29 and VPS35; VPS35 functions as the core’s backbone to which the other two proteins bind16. VPS26 is the only member of the core that has been found to have two paralogues, VPS26a and VPS26b17,18, and studies suggest that VPS26b might be differentially expressed in the brain19, 20. Some studies suggest that VPS26a and VPS26b are functionally redundant21, whereas others suggest that they might form distinct cargo-recognition cores20, 22.

The second central module of the retromer assembly is the ‘tubulation’ module, which is made up of proteins that work together in the formation and the stabilization of tubules that extend out of endosomes and that direct the transport of cargo towards its final destination (Fig. 1b). The proteins in this module, which directly binds the cargo-recognition core, are members of the subgroup of the sorting nexin (SNX) family that are characterized by the inclusion of a carboxy-terminal BIN–amphiphysin–RVS (BAR) domain23. These members include SNX1, SNX2, SNX5 and SNX6 (Refs 24,25). As part of the tubulation module, these SNX-BAR proteins exist in different dimeric combinations, but typically SNX1 interacts with SNX5 or SNX6, and SNX2 interacts with SNX5 or SNX6 (Refs 26,27). The EPS15-homology domain 1 (EHD1) protein can be included in this module, as it is involved in stabilizing the tubules formed by the SNX-BAR proteins28.

A third module of the retromer assembly functions to recruit the cargo-recognition core to endosomal membranes and to stabilize the core once it is there (Fig. 1b). Proteins that are part of this ‘membrane-recruiting’ module include SNX3 (Ref. 29), the RAS-related protein RAB7A30, 31,32 and TBC1 domain family member 5 (TBC1D5), which is a member of the TRE2–BUB2–CDC16 (TBC) family of RAB GTPase-activating proteins (GAPs)28. In addition, the lipid phosphatidylinositol-3-phosphate (PtdIns3P), which is found on endosomal membranes, contributes to recruiting most of the retromer-related SNXs through their phox homology domains33. Interestingly, another SNX with a phox homology domain, SNX27, was recently linked to retromer and its function15, 34. SNX27 functions as an adaptor for binding to PDZ ligand-containing cargos that are destined for transport to the cell surface via the recycling pathway. Thus, according to the functional organization of the retromer assembly, SNX27 belongs to the module that engages in cargo recognition and selection.

Recent studies have identified a fourth module of the retromer assembly. The five proteins in this module — WAS protein family homologue 1 (WASH1), FAM21, strumpellin, coiled-coil domain-containing protein 53 (CCDC53) and KIAA1033 (also known as WASH complex subunit 7) — form the WASH complex and function as an ‘actin-remodelling’ module28, 35, 36 (Fig. 1b). Specifically, the WASH complex functions in the rapid polymerization of actin to create patches of actin filaments on endosomal membranes. The complex is recruited to endosomal membranes by binding VPS35 (Ref. 28), and together they divert cargo towards retromer transport pathways and away from the degradation pathway.

The cargos that are transported by retromer include the receptors that directly bind the cargo-recognition core and the ligands of these receptors that are co-transported with the receptors. The receptors that are transported by retromer that have so far been identified to be the most relevant to neurological diseases are the family of VPS10 domain-containing receptors (including sortilin-related receptor 1 (SORL1; also known as SORLA), sortilin, and SORCS1, SORCS2 and SORCS3)7; the cation-independent mannose-6-phosphate receptor (CIM6PR)6, 5; glutamate receptors10; and phagocytic receptors that mediate the clearing function of microglia37. The most disease-relevant ligand to be identified that is trafficked as retromer cargo is the β-amyloid precursor protein (APP)7, 38, 39, 40, 41, which binds SORL1 and perhaps other VPS10 domain-containing receptors42 at the endosomal membrane.

Retromer dysfunction

Guided by retromer’s established function, and on the basis of empirical evidence, there are three well-defined pathophysiological consequences of retromer dysfunction that have proven to be relevant to AD and nervous system disorders. First, retromer dysfunction can cause cargos that typically transit rapidly through the endosome to reside in the endosome for longer than normal durations, such that they can be pathogenically processed into neurotoxic fragments (for example, APP, when stalled in the endosome, is more likely to be processed into amyloid-β, which is implicated in AD43 (Fig. 2a)). Second, by reducing endosomal outflow via impairment of the recycling pathway, retromer dysfunction can lead to a reduction in the number of cell surface receptors that are important for brain health (for example, microglia phagocytic receptors37 (Fig. 2b)).

Figure 2: The pathophysiology of retromer dysfunction.
The pathophysiology of retromer dysfunction.

Retromer dysfunction has three established pathophysiological consequences. In the examples shown, the left graphic represents a cell with normal retromer function and the right graphic represents a cell with a deficit in retromer function. a | Retromer dysfunction causes increased levels of cargo to reside in endosomes. For example, in primary neurons, retromer transports the β-amyloid precursor protein (APP) out of endosomes. Accordingly, retromer dysfunction increases APP levels in endosomes, leading to accelerated APP processing, resulting in an accumulation of neurotoxic fragments of APP (namely, β-carboxy-terminal fragment (βCTF) and amyloid-β) that are pathogenic in Alzheimer disease. b | Retromer dysfunction causes decreased cargo levels at the cell surface. For example, in microglia, retromer mediates the transport of phagocytic receptors to the cell surface and retromer dysfunction results in a decrease in the delivery of these receptors. Studies suggest that this cellular phenotype might have a pathogenic role in Alzheimer disease. c | Retromer dysfunction causes decreased delivery of proteases to the endosome. Retromer is required for the normal retrograde transport of the cation-independent mannose-6-phosphate receptor (CIM6PR) from the endosome back to the trans-Golgi network (TGN). It is in the TGN that this receptor binds cathepsin D and other proteases, and transports them to the endosome, to support the normal function of the endosomal–lysosomal system. By impairing the retrograde transport of the receptor, retromer dysfunction ultimately leads to reduced delivery of cathepsin D to this system. Cathepsin D deficiency has been shown to disrupt the endosomal–lysosomal system and to trigger tau pathology either within endosomes or secondarily in the cytosol.

The third consequence (Fig. 2c) is a result of the established role that retromer has in the retrograde transport of receptors, such as CIM6PR5, 6 or sortilin44, after these receptors transport proteases from the TGN to the endosome. Once at the endosome, the proteases disengage from the receptors, are released into endosomes and migrate to lysosomes. These proteases function in the endosomal–lysosomal system to degrade proteins, protein oligomers and aggregates45. Retromer functions to transfer the ‘naked’ receptor from the endosome back to the TGN via the retrograde pathway5, 6, allowing the receptors to continue in additional rounds of protease delivery. Accordingly, by reducing the normal retrograde transport of these receptors, retromer dysfunction has been shown to reduce the proper delivery of proteases to the endosomal–lysosomal system5,6, which, as discussed below, is a pathophysiological state linked to several brain disorders.

Although requiring further validation, recent studies suggest that retromer dysfunction might be involved in two other mechanisms that have a role in neurological disease. One study suggested that retromer might be involved in trafficking the transmembrane protein autophagy-related protein 9A (ATG9A) to recycling endosomes, from where it can then be trafficked to autophagosome precursors — a trafficking step that is crucial in the formation and the function of autophagosomes46. Autophagy is an important mechanism by which neurons clear neurotoxic aggregates that accumulate in numerous neurodegenerative diseases47. A second study has suggested that retromer dysfunction might enhance the seeding and the cell-to-cell spread of intracellular neurotoxic aggregates48, which have emerged as novel pathophysiological mechanisms that are relevant to AD49, PD50 and other neurodegenerative diseases.

Alzheimer disease

Retromer was first implicated in AD in a molecular profiling study that relied on functional imaging observations in patients and animal models to guide its molecular analysis7. Collectively, neuroimaging studies confirmed that the entorhinal cortex is the region of the hippocampal circuit that is affected first in AD, even in preclinical stages, and suggested that this effect was independent of ageing (as reviewed in Ref. 51). At the same time, neuroimaging studies identified a neighbouring hippocampal region, the dentate gyrus, that is relatively unaffected in AD52. Guided by this information, a study was carried out in which the two regions of the brain were harvested post mortem from patients with AD and from healthy individuals, intentionally covering a broad range of ages. A statistical analysis was applied to the determined molecular profiles of the regions that was designed to address the following question: among the thousands of profiled molecules, which are the ones that are differentially affected in the entorhinal cortex versus the dentate gyrus, in patients versus controls, but that are not affected by age? The final results led to the determination that the brains of patients with AD are deficient in two core retromer proteins — VPS26 and VPS35 (Ref. 7).

Little was known about the receptors of the neuronal retromer, so to understand how retromer deficiency might be mechanistically linked to AD, an analysis was carried out on the molecular data set that looked for transmembrane molecules for which expression levels correlated with VPS35 expression. The top ‘hit’ was the transcript encoding the transmembrane protein SORL1 (Ref. 43). As SORL1 belongs to the family of VPS10-containing receptors and as VPS10 is the main retromer receptor in yeast3, it was postulated that SORL1 and the family of other VPS10-containing proteins (sortillin, SORCS1, SORCS2 and SORCS3) might function as retromer receptors in neurons7. In addition, SORL1 had recently been reported to bind APP53, so if SORL1 was assumed to be a receptor that is trafficked by retromer, then APP might be the cargo that is co-trafficked by retromer. This led to a model in which retromer traffics APP out of endosomes7, which are the organelles in which APP is most likely to be cleaved by βAPP-cleaving enzyme 1 (BACE1; also known as β-secretase 1)43; this is the initial enzymatic step in the pathogenic processing of APP.

Subsequent studies were required to further establish the pathogenic link between retromer and AD, and to test the proposed model. The pathogenic link was further supported by human genetic studies. First, a genetic study investigating the association between AD, the genes encoding the components of the retromer cargo-recognition core and the family of VPS10-containing receptors found that variants of SORL1 increase the risk of developing AD38. This finding was confirmed by numerous studies, including a recent large-scale AD genome-wide association study54. Other genetic studies identified AD-associated variants in genes encoding proteins that are linked to nearly all modules of the retromer assembly55, including genes encoding proteins of the retromer tubulation module (SNX1), genes encoding proteins of the retromer membrane-recruiting module (SNX3 and RAB7A) and genes encoding proteins of the retromer actin-remodelling module (KIAA1033). In addition, nearly all of the genes encoding the family of VPS10-containing retromer receptors have been found to have variants that associate with AD56. Finally, a study found that brain regions that are differentially affected in AD are deficient in PtdIns3P, which is the phospholipid required for recruiting many sorting nexins to endosomal membranes57. Thus, together with the observation that the brains of patients with AD are deficient in VPS26a and VPS35 (Refs 7,37), all modules in the retromer assembly are implicated in AD.

Studies in mice39, 58, 59, flies39 and cells in culture34, 40, 41, 60, 61 have investigated how retromer dysfunction leads to the pathogenic processing of APP. Although rare discrepancies have been observed among these studies62, when viewed in total, the most consistent findings are that retromer dysfunction causes increased pathogenic processing of APP by increasing the time that APP resides in endosomes. Moreover, these studies have confirmed that SORL1 and other VPS10-containing proteins function as APP receptors that mediate APP trafficking out of endosomes.

Retromer has unexpectedly been linked to microglial abnormalities37 — another core feature of AD — which, on the basis of recent genetic findings, seem to have an upstream role in disease pathogenesis54, 63. A recent study found that microglia harvested from the brains of individuals with AD are deficient in VPS35 and provided evidence suggesting that retromer’s recycling pathway regulates the normal delivery of various phagocytic receptors to the cell surface of microglia37, including the phagocytic receptor triggering receptor expressed on myeloid cells 2 (TREM2) (Fig. 2b). Mutations in TREM2 have been linked to AD63, and a recent study indicates that these mutations cause a reduction in its cell surface delivery and accelerate TREM2 degradation, which suggests that the mutations are linked to a recycling defect64. While they are located at the microglial cell surface, these phagocytic receptors function in the clearance of extracellular proteins and other molecules from the extracellular space65. Taken together, these recent studies suggest that defects in the retromer’s recycling pathway can, at least in part, account for the microglial defects observed in the disease.

The microtubule-associated protein tau is the key element of neurofibrillary tangles, which are the other hallmark histological features of AD. Although a firm link between retromer dysfunction and tau toxicity remains to be established, recent insight into tau biology suggests several plausible mechanisms that are worth considering. Tau is a cytosolic protein, but nonetheless, through mechanisms that are still undetermined, it is released into the extracellular space from where it gains access to neuronal endosomes via endocytosis66, 67. In fact, recent studies suggest that the pathogenic processing of tau is triggered after it is endocytosed into neurons and while it resides in endosomes67. Of note, it still remains unknown which specific tau processing step — its phosphorylation, cleavage or aggregation — is an obligate step towards tau-related neurotoxicity. Accordingly, if defects in microglia or in other phagocytic cells reduce their capacity to clear extracellular tau, this would accelerate tau endocytosis in neurons and its pathogenic processing.

A second possibility comes from the established role retromer has in the proper delivery of cathepsin D and other proteases to the endosomal–lysosomal system via CIM6PR or sortilin (Fig. 2c). Studies in sheep, mice and flies68 have shown that cathepsin D deficiency can enhance tau toxicity and that this is mediated by a defective endosomal–lysosomal system68. Whether this mechanism leads to abnormal processing of tau within endosomes or in the cytosol via caspase activation68 remains unclear. As discussed above, retromer dysfunction will lead to a decrease in the normal delivery of cathepsin D to the endosome and will result in endosomal–lysosomal system defects. Retromer dysfunction can therefore be considered as a functional phenocopy of cathepsin D deficiency, which suggests a plausible link between retromer dysfunction and tau toxicity. Nevertheless, although these recent insights establish plausibility and support further investigation into the link between retromer and tau toxicity, whether this link exists and how it may be mediated remain open and outstanding questions.

Parkinson disease

The pathogenic link between retromer and PD is singular and straightforward: exome sequencing has identified autosomal-dominant mutations in VPS35 that cause late-onset PD69, 70, one of a handful of genetic causes of late-onset disease. However, the precise mechanism by which these mutations cause the disease is less clear.

Among a group of recent studies, all46, 48, 71, 72, 73, 74, 75, 76 but one77 strongly suggest that these mutations cause a loss of retromer function. At the molecular level, the mutations do not seem to disrupt mutant VPS35 from interacting normally with VPS26 and VPS29, and from forming the cargo-recognition core. Rather, two studies suggest that the mutations have a restricted effect on the retromer assembly but reduce the ability of VPS35 to associate with the WASH complex46, 75. Studies disagree about the pathophysiological consequences of the mutations. Four studies suggest that the mutations affect the normal retrograde transport of CIM6PR71, 73, 75, 76 from the endosome back to the TGN (Fig. 2c). In this scenario, the normal delivery of cathepsin D to the endosomal–lysosomal system should be reduced and this has been empirically shown73. Cathepsin D has been shown to be the dominant endosomal–lysosomal protease for the normal processing of α-synuclein76, and mutations could therefore lead to abnormal α-synuclein processing and to the formation of α-synuclein aggregates, which are thought to have a key pathogenic role in PD.

A separate study suggested that the mutation might cause a mistrafficking of ATG9, and thereby, as discussed above, reduce the formation and the function of autophagosomes46. Autophagosomes have also been implicated as an intracellular site in which α-synuclein aggregates are cleared. Thus, although future studies are needed to resolve these discrepant findings (which may in fact not be mutually exclusive), these studies are generally in agreement that retromer defects will probably increase the neurotoxic levels of α-synuclein aggregates48.

Several studies in flies71, 74 and in rat neuronal cultures71 provide strong evidence that increasing retromer function by overexpressing VPS35 rescues the neurotoxic effects of the most common PD-causing mutations in leucine-rich repeat kinase 2 (LRRK2). Moreover, a separate study has shown that increasing retromer levels rescues the neurotoxic effect of α-synuclein aggregates in a mouse model48. These findings have immediate therapeutic implications for drugs that increase VPS35 and retromer function, as discussed in the next section, but they also offer mechanistic insight. LRRK2 mutations were found to phenocopy the transport defects caused either by theVPS35 mutations or by knocking down VPS35 (Ref. 71). Together, this and other studies78suggest that LRRK2 might have a role in retromer-dependent transport, but future studies are required to clarify this role.

Other neurological disorders

Besides AD and PD, in which a convergence of findings has established a strong pathogenic link, retromer is being implicated in an increasing number of other neurological disorders. Below, we briefly review three disorders for which the evidence of the involvement of retromer in their pathophysiology is currently the most compelling.

The first of these disorders is Down syndrome (DS), which is caused by an additional copy of chromosome 21. Given the hundreds of genes that are duplicated in DS, it has been difficult to identify which ones drive the intellectual impairments that characterize this condition. A recent elegant study provides strong evidence that a deficiency in the retromer cargo-selection protein SNX27 might be a primary driver for some of these impairments79. This study found that the brains of individuals with DS were deficient in SNX27 and that this deficiency may be caused by an extra copy of a microRNA (miRNA) encoded by human chromosome 21 (the miRNA is produced at elevated levels and thereby decreases SNX27 expression). Consistent with the known role of SNX27 in retromer function, decreased expression of this protein in mice disrupted glutamate receptor recycling in the hippocampus and led to dendritic dysfunction. Importantly, overexpression of SNX27 rescued cognitive and other defects in animal models79, which not only strengthens the causal link between retromer dysfunction and cognitive impairment in DS but also has important therapeutic implications.

Hereditary spastic paraplegia (HSP) is another disorder linked to retromer. HSP is caused by genetic mutations that affect upper motor neurons and is characterized by progressive lower limb spasticity and weakness. Although there are numerous mutations that cause HSP, most are unified by their effects on intracellular transport80. One HSP-associated gene in particular encodes strumpellin81, which is a member of the WASH complex.

The third disorder linked to retromer is neuronal ceroid lipofuscinosis (NCL). NCL is a young-onset neurodegenerative disorder that is part of a larger family of lysosomal storage diseases and is caused by mutations in one of ten identified genes — nine neuronal ceroid lipofuscinosis (CLN) genes and the gene encoding cathepsin D82. Besides cathepsin D, for which the link to retromer has been discussed above, CLN3 seems to function in the normal trafficking of CIM6PR83. However, the most direct link to retromer has been recently described for CLN5, which seems to function, at least in part, as a retromer membrane-recruiting protein84.

Retromer as a therapeutic target

As suggested by the first study implicating retromer in AD7, and in several subsequent studies71,85, increasing the levels of retromer’s cargo-recognition core enhances retromer’s transport function. Motivated by this observation and after a decade-long search86, we identified a novel class of ‘retromer pharmacological chaperones’ that can bind and stabilize retromer’s cargo-recognition core and increase retromer levels in neurons61.

Validating the motivating hypothesis, the chaperones were found to enhance retromer function, as shown by the increased transport of APP out of endosomes and a reduction in the accumulation of APP-derived neurotoxic fragments61. Although there are numerous other pharmacological approaches for enhancing retromer function, this success provides the proof-of-principle that retromer is a tractable therapeutic target.

As retromer functions in all cells, a general concern is whether enhancing its function will have toxic adverse effects. However, studies have found that in stark contrast to even mild retromer deficiencies, increasing retromer levels has no obvious negative consequences in yeast, neuronal cultures, flies or mice40, 48, 61, 71. This might make sense because unlike drugs that, for example, function as inhibitors, simply increasing the normal flow of transport through the endosome might not be cytotoxic.

If retromer drugs are safe and can effectively enhance retromer function in the nervous system — which are still outstanding issues — there are two general indications for considering their clinical application. One rests on the idea that these agents will only be efficacious in patients who have predetermined evidence of retromer dysfunction. The most immediate example is that of individuals with PD that is caused by LRRK2 mutations. As discussed above, several ‘preclinical’ studies in flies and neuronal cultures have already established that increasing retromer levels71, 74can reverse the neurotoxic effects of such mutations and, thus, if this approach is proven to be safe, LRRK2-linked PD might be an appropriate indication for clinical trials.

Alternatively, the pathophysiology of a disease might be such that retromer-enhancing drugs would be efficacious regardless of whether there is documented evidence of retromer dysfunction. AD illustrates this point. As reviewed above, current evidence suggests that retromer-enhancing drugs will, at the very least, decrease pathogenic processing of APP in neurons and enhance microglial function, even if there are no pre-existing defects in retromer.

More generally, histological studies comparing the entorhinal cortex of patients with sporadic AD to age-matched controls have documented that enlarged endosomes are a defining cellular abnormality in AD87, 88. Importantly, enlarged endosomes are uniformly observed in a broad range of patients with sporadic AD, which suggests that enlarged endosomes reflect an intracellular site at which molecular aetiologies converge87. In addition, because they are observed in early stages of the disease in regions of the brain without evidence of amyloid pathology87, enlarged endosomes are thought to be an upstream event. Mechanistically, the most likely cause of enlarged endosomes is either too much cargo flowing into endosomes — as occurs, for example, with apolipoprotein E4 (APOE4), which has been shown to accelerate endocytosis89, 90 — or too little cargo flowing out, as observed in retromer dysfunction40, 61 and related transport defects57. By any mechanism, retromer-enhancing drugs might correct this unifying cellular defect and might be expected to be beneficial regardless of the specific aetiology.

Conclusions

The fact that retromer defects, including those derived from bona fide genetic mutations, seem to differentially target the nervous system suggests that the nervous system is differentially dependent on retromer for its normal function. We think that this reflects the unique cellular properties of neurons and how synaptic biology heavily depends on endosomal transport and trafficking. Although plausible, future studies are required to confirm and to test the details of this hypothesis.

However, currently, it is the clinical rather than the basic neuroscience of retromer that is much better understood, with the established pathophysiological consequences of retromer dysfunction providing a mechanistic link to the disorders in which retromer has been implicated. Nevertheless, many questions remain. The two most interesting questions, which are in fact inversions of each other, relate to regional vulnerability in the nervous system. First, why does retromer dysfunction target specific neuronal populations? Second, how can retromer dysfunction cause diseases that target different regions of the nervous system? Recent evidence hints at answers to both questions, which must somehow be rooted in the functional and molecular diversity of retromer.

The type and the extent of retromer defects linked to different disorders might provide pathophysiological clues as well as reasons for differential vulnerability. As discussed, in AD there seem to be across-the-board defects in retromer, such that each module of the retromer assembly as well as multiple retromer cargos have been pathogenically implicated. By contrast, the profile of retromer defects in PD seems to be more circumscribed, involving selective disruption of the interaction between VPS35 and the WASH complex. These insights might agree with histological87, 88 and large-scale genetic studies54 that suggest that endosomal dysfunction is a unifying focal point in the cellular pathogenesis of AD. In contrast, genetics and other studies91suggest that the cellular pathobiology of PD is more distributed, implicating the endosome but other organelles as well, in particular the mitochondria.

Interestingly, studies suggest that the entorhinal cortex — a region that is differentially vulnerable to AD — has unique dendritic structure and function92, which are highly dependent on endosomal transport. We speculate that it is the unique synaptic biology of the entorhinal cortex that can account for why it might be particularly sensitive to defects in endosomal transport in general and retromer dysfunction in particular, and for why this region is the early site of disease. Future studies are required to investigate this hypothesis, as well as to understand why the substantia nigra or other regions that are differentially vulnerable to PD would be particularly sensitive to the more circumscribed defect in retromer.

Perhaps the most important observation for clinical neuroscience is the now well-established fact that increasing levels of retromer proteins enhances retromer function and has already proved capable of reversing defects associated with AD, PD and DS in either cell culture or in animal models. The relationships between protein levels and function are not always simple, but emerging pharmaceutical technologies that selectively and safely increase protein levels are now a tractable goal in drug discovery93. With the evidence mounting that retromer has a pathogenic role in two of the most common neurodegenerative diseases, we think that targeting retromer to increase its functional activity is an important goal that has strong therapeutic promise.

References

  1. Schekman, R. Charting the secretory pathway in a simple eukaryote. Mol. Biol. Cell 21,37813784 (2010).
  2. Henne, W. M., Buchkovich, N. J. & Emr, S. D. The ESCRT pathway. Dev. Cell 21, 7791(2011).
  3. Seaman, M. N., McCaffery, J. M. & Emr, S. D. A membrane coat complex essential for endosome-to-Golgi retrograde transport in yeast. J. Cell Biol. 142, 665681 (1998).
  4. Haft, C. R. et al. Human orthologs of yeast vacuolar protein sorting proteins Vps26, 29, and 35: assembly into multimeric complexes. Mol. Biol. Cell 11, 41054116 (2000).
  5. Seaman, M. N. Cargo-selective endosomal sorting for retrieval to the Golgi requires retromer. J. Cell Biol. 165, 111122 (2004).

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Human Genetics and Childhood Diseases

Curator: Larry H. Bernstein, MD, FCAP

 

 

 

Publication Roundup: HGMD

HGMD®, the Human Gene Mutation Database is used by scientists around the world to find information on reported genetic mutations. The papers below use the database to advance our understanding of disease, DNA dynamics, and more.

https://www.qiagenbioinformatics.com/blog/translational/publication-roundup-hgmd

Local DNA dynamics shape mutational patterns of mononucleotide repeats in human genomes
First author: Albino Bacolla

Scientists in the US and UK published results in Nucleic Acids Research of a detailed analysis of single-base substitutions and indels in the human genome. Their findings show that certain base positions are more susceptible to mutagenesis than others. They used HGMD Professional to find mutations in specific genomic regions for analysis; the paper includes charts showing mutation patterns, germline SNPs, and more from HGMD data.

High prevalence of CDH23 mutations in patients with congenital high-frequency sporadic or recessively inherited hearing loss
First author: Kunio Mizutari

This Orphanet Journal of Rare Diseases paper from scientists in Japan sequenced 72 patients with unexplained hearing loss, finding several CDH23 mutations, some of which were novel. Mutations in the gene have been linked to Usher syndrome and other forms of hereditary hearing loss. The scientists used HGMD to find all known CDH23 mutations within nearly 70 coding regions.

Mutation analyses and prenatal diagnosis in families of X-linked severe combined immunodeficiency caused by IL2Rγ gene novel mutation
First author: Q.L. Bai

In Genetics and Molecular Research, scientists report the utility of mutation analysis of the interleukin-2 receptor gamma gene to assess carrier status and perform prenatal diagnosis for X-linked severe combined immunodeficiency. They studied two high-risk families, along with 100 controls, to evaluate the approach. Sequence variation was determined using HGMD Professional and an X-SCID database, and a new mutation was discovered in the project.

Impact of glucocerebrosidase mutations on motor and nonmotor complications in Parkinson’s disease
First author: Tomoko Oeda

Researchers from three hospitals in Japan published this Neurobiology of Aging report that may help stratify Parkinson’s disease patients by prognosis. They sequenced mutations in the GBA gene in 215 patients, finding that those who had mutations associated with Gaucher disease suffered dementia and psychosis much earlier than those who didn’t. The team found previously reported GBA mutations using HGMD Professional.

Comprehensive Genetic Characterization of a Spanish Brugada Syndrome Cohort
First author: Elisabet Selga

In this PLoS One publication, scientists from a number of institutions in Spain examined genetic variation among patients with Brugada syndrome, a rare genetic cardiac arrhythmia. They sequenced 14 genes in 55 patients, identifying 61 variants and finding the subset that appear pathogenic. Variants were filtered against a number of databases, including HGMD.

 

 

Local DNA dynamics shape mutational patterns of mononucleotide repeats in human genomes

Albino Bacolla1Xiao Zhu2Hanning Chen3Katy Howells4David N. Cooper4 and Karen M. Vasquez1

Nucl. Acids Res. (26 May 2015) 43(10): 5065-5080.   http://dx.doi.org:/10.1093/nar/gkv364

Single base substitutions (SBSs) and insertions/deletions are critical for generating population diversity and can lead both to inherited disease and cancer. Whereas on a genome-wide scale SBSs are influenced by cellular factors, on a fine scale SBSs are influenced by the local DNA sequence-context, although the role of flanking sequence is often unclear. Herein, we used bioinformatics, molecular dynamics and hybrid quantum mechanics/molecular mechanics to analyze sequence context-dependent mutagenesis at mononucleotide repeats (A-tracts and G-tracts) in human population variation and in cancer genomes. SBSs and insertions/deletions occur predominantly at the first and last base-pairs of A-tracts, whereas they are concentrated at the second and third base-pairs in G-tracts. These positions correspond to the most flexible sites along A-tracts, and to sites where a ‘hole’, generated by the loss of an electron through oxidation, is most likely to be localized in G-tracts. For A-tracts, most SBSs occur in the direction of the base-pair flanking the tracts. We conclude that intrinsic features of local DNA structure, i.e. base-pair flexibility and charge transfer, render specific nucleotides along mononucleotide runs susceptible to base modification, which then yields mutations. Thus, local DNA dynamics contributes to phenotypic variation and disease in the human population.

INTRODUCTION

Changes in human genomic DNA in the form of base substitutions and insertions/deletions (indels) are essential to ensure population diversity, adaptation to the environment, defense from pathogens and self-recognition; they are also a critical source of human inherited disease and cancer. On a genome-wide scale, base substitutions result from the combined action of several factors, including replication fidelity, lagging versus leading strand DNA synthesis, repair, recombination, replication timing, transcription, nucleosome occupancy, etc., both in the germline and in cancer (14). On a much finer scale [(over a few base pairs (bp)], rates of base substitutions may be strongly influenced by interrelationships between base–protein and base–base interactions. For example, the mutator role of activation-induced deaminase (AID) in B-cells during class-switch recombination and somatic hypermutation (5) targets preferentially cytosines within WRC (W: A|T; R: A|G) sequences (6), whereas apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) overexpression displays a preference for base substitutions at cytosines in TCW contexts (7). Other examples, such as the induction of C→T transitions at CG:CG dinucleotides by cytosine-5-methylation and the role of UV light in promoting base substitutions at pyrimidine dimers have been well documented (reviewed in (4,8)). More recently, complex patterns of base substitution at guanosines in cancer genomes have been found to correlate with changes in guanosine ionization potentials as a result of electronic interactions with flanking bases (9), suggesting a role for electron transfer and oxidation reactions in sequence-dependent mutagenesis. However, despite these advances, the increasing number of sequence-dependent patterns of mutation noted in genome-wide sequencing studies has met with a lack of understanding of most of the underlying mechanisms (10). Thus, a picture is emerging in which mutations are often heavily dependent on sequence-context, but for which our comprehension is limited.

Mononucleotide repeats comprise blocks of identical base pairs (A|T or C|G; hereafter referred to as A-tracts and G-tracts) and display distinct features: they are abundant in vertebrate genomes; mutations within the tracts occur more frequently than the genome-wide average; mutations generally increase with increasing tract length; length instability is a hallmark of mismatch repair-deficiency in cancers; and sequence polymorphism within the general population has been linked to phenotypic diversity (1115). Thus, mononucleotide repeats appear ideal for addressing the question of sequence-dependent mutagenesis since base pairs within the tracts are flanked by identical neighbors. Both historic and recent investigations concur with the conclusion that a major source of mononucleotide repeat polymorphism is the occurrence of slippage (i.e. repeat misalignment) during semiconservative DNA replication, which gives rise to the addition or deletion of repeat units (11,12). An additional and equally important source of mutation has recently been suggested to arise from errors in DNA replication by translesion synthesis DNA polymerases, such as pol η and pol κ (13), also on slipped intermediates, leading to single base substitutions.

A key question that remains unanswered in these studies and which is relevant to the issue of sequence context-dependent mutagenesis is whether all base pairs within mononucleotide repeats display identical susceptibility to single base changes and whether indels (which are consequent to DNA breakage) occur randomly within the tracts.

Herein, we combine bioinformatics analyses on mononucleotide repeat variants from the 1000 Genomes Project and cancer genomes with molecular dynamics simulations and hybrid quantum mechanics/molecular mechanics calculations to address the question of sequence-dependent mutagenesis within these tracts. We show that mutations along both A-tracts and G-tracts are highly non-uniform. Specifically, both base substitutions and indels occur preferentially at the first and last bp of A-tracts, whereas they are concentrated between the second and third G:C base pairs in G-tracts. These positions coincide with the most flexible base pairs for A-tracts and with the preferential localization of a ‘hole’ that results when one electron is lost due to an oxidation reaction anywhere along G-tracts. Thus, despite the uniformity of sequence composition, mutations occur in a sequence-dependent context at homopolymeric runs according to a hierarchy that is imposed by both local DNA structural features and long-range base–base interactions. We also show that the repair processes leading to base substitution must differ between A- and G-tracts, since in the former, but not in the latter, base substitutions occur predominantly in the direction of the base immediately flanking the tracts. Additional sequence-dependent patterns of mutation are likely to arise from studies of more heterogeneous sequence combinations, possibly involving other aspects intrinsic to the structure of DNA.

 

RESULTS

Mononucleotide repeat variation is defined by tract length and flanking base composition

We define mononucleotide repeats in the GRCh37/hg19 (hg19) human genome assembly as uninterrupted runs of A:T and G:C base pairs (hereafter referred to as A-tracts and G-tracts, respectively) from 4 to 13 base pairs in length (Figure 1A). We retrieved a total of 48,767,945 A-tracts and 13,633,781 G-tracts, both of which displayed a biphasic distribution with an inflection point between tract lengths of 8 and 9 (bp) and with the number of runs declining with length more dramatically for G-tracts than for A-tracts (Figure 1B), as noted previously (29). Both the number of short tracts and the extent of decline varied with flanking base composition, TA[n]T runs being two- to three-fold more abundant than CA[n]Cs (Supplementary Figure S1A) and AG[n]As declining the most rapidly (Supplementary Figure S1B). Thus, mononucleotide runs exist as a collection of separate pools of sequences in extant human genomes, each maintained at distinctive rates of sequence stability, as determined by factors such as bp composition (A:T versus G:C), tract length and flanking sequence composition.

Figure 1.

Mononucleotide repeat variation, evolutionary conservation and association with transcription. (A) The search algorithm was designed to retrieve runs of As or Ts (A-tracts) and Gs or Cs (G-tracts) length n (n = 4 to 13), along with their 5′ (n = 0) and 3′ (n = n + 1) nearest neighbors from hg19. Tract bases were numbered 5′ to 3′ with respect to the purine-rich sequence. The panel exemplifies the nomenclature for A- and G-tracts of length 4. (B) Logarithmic plot of the number of A-tracts (closed circles) and G-tracts (open circles) in hg19 as a function of length. (C) Normalized fractions of polymorphic tracts (F SNV) (number of SNVs divided by both hg19 number of tracts and n) from the 1KGP for A-tracts (closed circles) and G-tracts (open circles). (D) Radial plot of SNVs in the 1KGP at the 5′ and 3′ nearest neighbors of A-tracts. Periphery, tract length; horizontal axis, scale for the fraction of SNVs (F SNV). (E) Radial plot of SNVs in the 1KGP at the 5′ and 3′ nearest neighbors of G-tracts. (F) Percent difference in the numbers of A-tracts (closed circles) and G-tracts (open circles) between syntenic regions of hg19 and HN genomes. (G) The exponents of Benjamini-corrected P-values for A-tract-containing genes enriched in transcription-factor binding sites plotted as a function of A-tract length (triangles); each value represents the median of the top 11 USCS_TFBS terms. The percent A-tracts (closed circles) and G-tracts (open circles) intersecting genomic regions pulled-down by chromatin immunoprecipitation using antibodies against transcription factors are plotted as a function of tract length. (H) List of gene enrichment terms with a Benjamini-corrected P-value of <0.05 in common between genes containing A- and G-tracts of lengths 4–13, excluding the UCSC_TFBS terms.

 We examined the extent of sequence variation in the human population by mapping 38,878,546 single nucleotide variants (SNVs) from 1092 haplotype-resolved genomes (the 1000 Genomes Project, 1KGP) (30) to the hg19 A- and G-tracts. The normalized fractions of polymorphic tracts (F SNV) were greater for G-tracts than A-tracts and both displayed Gaussian-type distributions, with maxima of 0.067 for G-tracts of length 8 and 0.017 for A-tracts of length 9 (Figure 1C). CA[n]C and AG[n]A runs displayed the highest F SNV values for A- and G-tracts, respectively (Supplementary Figure S1C and D), with F SNV values for AG[n]As attaining ∼0.10 at length 8. We conclude that flanking base composition influences the rates of SNV within mononucleotide runs and, as a consequence, their representation in the reference human genome.

F SNV values at the flanking 5′ and 3′ bp were similar between A- and G-tracts, except for minor differences for the least represented (i.e. longest) tracts and did not exceed 0.02 (Supplementary Figure S1E). These fractions are expected to be greater than at more distant positions from the tracts, based on previous data (29). SNVs at G-tracts, but not at A-tracts, were more frequent than at flanking base pairs. F SNVs for base pairs flanking short (≤8 bp) tracts were at least twice as high as those flanking long tracts; F SNVs also displayed distinct sequence preference with most (∼0.1) variants occurring at Ts 3′ of G-tracts (Figure 1D and E). In summary, SNVs at mononucleotide runs do not increase monotonically with length but peak at 8–9 bp. This behavior mirrors the genomic distributions, both with respect to the total number of tracts (Figure 1B) and the subsets flanked by specific-sequence combinations (Supplementary Figure S1A–D). Variation at flanking base pairs also displayed a biphasic pattern centered at a length of 8–9 bp, with a greater chance of variation adjacent to G- than A-tracts and with characteristic sequence preferences.

Long tracts are evolutionarily conserved and associated with high transcription

To assess whether more variable monosatellite runs (Figure 1C) might have undergone a greater reduction in number in extant humans relative to extinct hominids, we compared the number of A- and G-tracts between syntenic regions of five individuals comprising hg19 and three Neanderthal (HN) specimens (31). The difference between hg19 and HN was very small (<±2%) for the short tracts, but it displayed more negative values in hg19 with increasing tract length, which reached a maximum of −11.8 and −32.7% for A- and G-tracts, respectively, of length 9. Beyond this threshold, the numbers of tracts converged for A-tracts, whereas they were more abundant in hg19 for G-tracts >11 bp (Figure 1F). In summary, the largest difference in the number of mononucleotide runs between hg19 and HN sequences was centered at 9 bp for both A- and G-tracts, suggesting that the length distributions (Figure 1A and Supplementary Figure S1A and B) reflect distinct rates of evolutionary gains and losses due to differential sequence mutability (Figure 1C) as a function of length and flanking sequence composition (12).

The fact that long (>9 bp) mononucleotide runs display low variability in the human population (Figure 1C) and sequence conservation during evolutionary divergence (Figure 1F) raises the possibility that they might serve functional roles. Through gene enrichment analyses, we found that genes containing A- and G-tracts were enriched for genes associated with the term ‘UCSC_TFBS’, which pertains to transcripts harboring frequent transcription factor binding sites (32,33). For A-tract-containing genes, the median P-values for the top 11 UCSC_TFBS terms decreased from 2.95E-26 for tracts of length 4 to 5.22E-241 for tracts of length 13 (Figure 1G). The percent of A-tracts intersecting genomic fragments amplified from chromatin immunoprecipitation using transcription-factor binding antibodies (32,33) also increased from 8.7 to 9.9 from length 6 to 13, whereas it was constant (mean ± SD, 22.4 ± 1.1) for G-tracts (Figure1G). For gene classes excluding ‘UCSC_TFBS’, a search for categories enriched at P < 0.05 and common to all A- and G-tract-containing genes returned a set of 25 terms, 22 of which were associated with high levels of tissue-specific gene expression (Figure 1H). In summary, these analyses extend prior work (14) supporting a role for mononucleotide tracts in enhancing gene expression, a function that for A-tracts appears to increase with increasing tract length.

Repeat variability is highly skewed

Next we addressed whether bp along A- and G-tracts display equal probability and type of variation. In the 1KGP dataset, the number of SNVs at each position along both A- and G-tracts of length 4 was within a two-fold difference (144,000–240,000); for both types of sequence, transitions (i.e. A→G and G→A) were the predominant (51–78%) type of base substitution (Supplementary Figure S2A and B). However, with increasing length, the number of SNVs decreased up to 30-fold more drastically for G-tracts than for A-tracts, with increasing numbers of transversions (A→T and G→C|T) being predominant. Normalizing the data for the number of tracts genome-wide revealed that the extent of SNV varied by up to 10-fold, depending upon tract length and bp position. Specifically, the highest degree of variation was observed at the first and last A within the A-tracts (i.e. A1 and An), which underwent up to 61% A→T and 43% A→C transversions, respectively, at length 9 (Figure 2A). Likewise, for G-tracts, the most polymorphic sites were G3, followed by G2, for mid-size tracts of 8–10 bp, with 44% G→C transversions at G3 for tracts of length 8 (Figure2B). Thus, the extent of SNV at mononucleotide runs is grossly skewed in human genomes, both along the sequence itself and across tract length, which must account for the bell-shape behavior in F SNV for the tracts as a whole (Figure 1C).

Figure 2.

Population variation spectra. (A) Variation spectra of A-tracts. Percent (number of SNVs at each position divided by the number of tracts in hg19 × 100) of A→T (black), A→C (red) and A→G (green) SNVs in the 1KGP dataset (left). Percent SNVs at A1 as a function of tract length (right). (B) Variation spectra of G-tracts. As in panel A with G→T (black), G→C (red) and G→A (cyan) (left). Percent SNVs at G3 as a function of tract length (right). (C) Percent A→T, A→C and A→G transitions at each position along A-tracts (stars) preceded and followed by a T (TA[n]T, left), C (CA[n]C), center) and G (GA[n]G, right) as a function of tract length. (D) Percent G→T, G→C and G→A transitions at each position along G-tracts (stars) preceded and followed by a T (TG[n]T, left), C (CG[n]C), center) and A (AG[n]A, right) as a function of tract length. (E) Percent transitions at base pairs (stars) preceding or following A-tracts (left) and G-tracts (right) as a function of tract length (n). *, mutated position.

We assessed whether SNV hypervariability was associated with specific combinations of nearest neighbors. For A-tracts flanked 5′ by a T, C or G, the highest percentage of SNVs was observed at A1 when preceded by a T, which reached 7.9% for TA[n] tracts of length 9 (Supplementary Figure S2C). By contrast, for 3′ T, C or G, the greatest effect was elicited by a C, with the highest percentage (7.1%) of SNVs at An for A[n]C tracts of length 9 (Supplementary Figure S2D). Therefore, flanking base pairs play a critical role both in the spectra and frequencies of SNVs at A-tracts. More detailed plots along A-tracts either preceded (Supplementary Figure S2E), followed (Supplementary Figure S2F) or preceded and followed (Figure 2C) by a T, C or G revealed the dramatic and long-range (up to 9–10 bp for the longest tracts, higher than the value of 4 bp predicted by mathematical models of slippage (11)) influence of flanking base pairs on variation spectra, in which up to 95% of the changes were in the direction of the base flanking the tract. Because the number of A-tracts preceded or followed by a specific base varies by up to three-fold (Supplementary Figure S2G), we conclude that for A-tracts, the overall mutation fractions and spectra are the result of at least three variables; length, position along the tract, and base composition of the 5′ and 3′ nearest-neighbors.

For G-tracts flanked 5′ by a T, C or A, high percentages (10–12%) of SNVs were observed at G1 for tracts preceded by a C, an effect that decreased with increasing tract length (Supplementary Figure S3A). This result, together with an exceedingly low number of G→A transitions at G1 for tracts not preceded by a C (Supplementary Figure S3C) relative to all tracts (Supplementary Figure S2B), is consistent with the known high mutability of CG:CG dinucleotides as a result of cytosine-5 methylation (9). The hypermutability at G2 was observed preferentially for tracts preceded by an A, and to a lesser extent T, whereas that at G3 was insensitive to flanking sequence composition. Likewise, G-tracts flanked 3′ by a T, C or A did not display marked sequence-dependent effects (Supplementary Figure S3B). Detailed plots of the SNV spectra along G-tracts either preceded (Supplementary Figure S3D), followed (Supplementary Figure S3E), or preceded and followed (Figure 2D) by a T, C or A revealed a noticeable effect only for 5′ T in association with G→T substitutions at G1for tracts of length ≥8. Thus, despite a consistent over-representation of G-tracts flanked 5′ by a T (Supplementary Figures S3F and S1B), which must account for the high absolute number of SNVs at G1 for TG[n] relative to AG[n] and CG[n] (Supplementary Figure S3G), nearest-neighbor base composition seems to play a lesser role in SNV spectra at G-tracts than at A-tracts.

With respect to SNVs at the flanking 5′ and 3′ nearest positions, no B→A or H→G substitutions (Figure 1A) were found above a length threshold of 9 for A-tracts and 8 for G-tracts (Figure 2E, gray shading) out of 5969 SNVs, implying that tract expansion by recruiting flanking base pairs is disfavored at these lengths. In summary, base substitution along mononucleotide repeats is strongly skewed towards the edges of A-tracts and within the 5′ half of G-tracts, with frequencies that peak at midsize lengths (8–9 bp). For A-tracts ≥7 bp, base substitution occurred almost exclusively in the direction of the flanking nearest-neighbors. Finally, base substitution at flanking bases did not contribute to tract expansion for mononucleotide runs longer than 8–9 bp.

Insertions and deletions display length and positional preference

In addition to SNVs, mononucleotide runs are polymorphic in length as a result of indels. Herein, we consider separately two types of indels: one in which tract length changes by ±1 and flanking bp composition is not altered (slippage); the other comprising all other cases involving the addition or removal of 1–200 bp (indels). Slippage is a widely accepted mutational mechanism (1112,34), whereby DNA replication errors at reiterated DNA motifs cause changes in the number of motifs (most often +/−1). The normalized fractions of slippage in the 1KGP dataset peaked at lengths of 8 bp for A-tracts and 9 bp for G-tracts (Figure 3A), generating bell-shaped curves similar to those observed for SNVs (Figure1C) and with no differences in the highest fraction of ‘slipped’ tracts, which peaked at ∼0.02. By contrast, +1 slippage occurred more frequently than −1 slippage at A-tracts (Figure 3B). These results support recent studies on microsatellite repeats (12) and contrast with previous conclusions that slippage increases monotonically with tract length, and that the extent of slippage differs between A- and G-tracts (35,36).

Figure 3.

Population insertions and deletions. (A) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage in the 1KGP dataset as a function of tract length. Data were obtained by dividing the number of events by both the number of hg19 tracts and tract length (n). (B) Ratio of the number of +1 to −1 slippage for A-tracts (closed circles) and G-tracts (open circles). (C) Indels at A-tracts. For positions along the tracts (‘Tract’), ‘F Indel’ is the ratio between the number of indels and the number of tracts in hg19 multiplied by tract length. For the positions immediately flanking the tracts genomic coordinates (‘Before tract’ and ‘After tract’), ‘F Indel’ is the ratio between the number of indels and the number of tracts in hg19. (D) Indels at G-tracts, calculated as described in panel C. (E) Heatmap representation of insertions along A-tracts. The percent insertions (i.e. the number of insertions at each position divided by the number of tracts in hg19) (y-axis) plotted as a function of location (x-axis) from position 0 (insertion between the bp 5′ to the tract and the first bp of the tract) to position n + 1 (insertion between the bp 3′ to the last bp of the tract and the following bp) (see Figure 1A) and as a function of tract length (z-axis). (F) Heatmap representation of insertions along G-tracts.

With respect to indels, the normalized fractions were low (<1 × 10−3) along short (4–6 bp) A- and G-tracts, but rose to a plateau for longer tracts as reported earlier (11); this plateau was 10-fold higher for G-tracts (∼0.03) than for A-tracts (∼0.003) (Figure 3C and D). Indels also occurred more frequently (up to six-fold for A-tracts of length 11) at nearest-neighboring base pairs (‘Before tract’ and ‘After tract’ in Figure 3C and D) than along the tracts. Thus, contrary to SNVs and slippage, indels increased to a plateau with mononucleotide tract length.

We analyzed in detail the locations of insertions along the tracts and the flanking positions with respect to the 5′ to 3′ orientation of the tracts (Figure 1A). The normalized fractions demonstrated that insertions peaked at the 3′, and to a lesser extent 5′, ends of the longest A-tracts (Figure 3E), but remained low. For G-tracts, insertions occurred most efficiently at two locations (G2–3 and G5) (Figure 3F), they increased with tract length (up to ∼0.04), and attained ∼10-fold higher values than for A-tracts. In conclusion, insertion sites at A- and G-tracts followed the patterns observed for SNVs (Figure 2A and B), suggesting that factors associated with local DNA dynamics sensitize specific bases along the tracts to genetic alteration, inducing both SBS and indels.

Base pair flexibility and charge localization map to sites of sequence changes

To elucidate elements of intrinsic DNA dynamics that may be responsible for the biases in SNV and insertion sites, we performed molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations on model A[6], A[9], G[6] and G[9] duplex DNA fragments. We focused on water bridge coordination (Figure 4A), bp step flexibility, and for the G[6] and G[9], charge localization, as these properties are known to impact the susceptibility of DNA to base damage, repair and mutation. The fractions of one water coordination increased along the A[9] and A[6] structures in a 5′ to 3′ direction, irrespective of flanking sequence composition, in concert with a decrease in minor groove width (Figure 4B and Supplementary Figure S4A) as predicted (37). Vstep, a measure of bp structural fluctuation, displayed a prominent peak of ∼40 Å3deg3 at the 5′-TA-3′ step for both structures (Figure 4C and Supplementary Figure S4B), which together with low water occupancy points to 5′-TA-3′ being a preferred location for base modification and mutation. In the G[9] and G[6] structures water coordination involved mostly two-water bridges due to wide (∼14 Å) minor grooves (Figure 4Dand Supplementary Figure S4C), whereas flexibility was modest (∼20–22 Å3deg3, Figure 4E and Supplementary Figure S4D). Thus, bp dynamics are likely to impact mutations at A-tracts to a greater extent than at G-tracts. Guanine has the lowest ionization potential (IP) of all four bases and IP further decreases at guanine runs, rendering them targets for electron loss, charge localization, oxidation and eventually mutation (4,38). Because after electron loss the ensuing charge (hole) can migrate along the DNA double-helix and relocalize at specific guanines, we addressed whether the preferred sites of mutation along G-tracts, i.e. G2–3 and G5, would also be preferred sites for charge localization. The QM/MM determinations indicated that whereas for the short G[6] fragment the difference in the density-derived atomic partial charges (DDAPC) (i.e. the hole) localized most often (∼50%) to the first position (Figure 4F), for the long G[9] fragment charge localization shifted downstream (mostly to the second, but also to positions 6–7, Figure 4G). Importantly, the charge was found exclusively around the guanine rings (Figure 4H). Thus, the two main sites of sequence change along G-tracts, i.e. G2–3 and G5, coincide with positions where charge localization and hence one-electron oxidation reactions is predicted to occur most frequently. In summary, bp flexibility at A-tracts and charge transfer at G-tracts likely represent intrinsic DNA features underlying the bias in SNV and insertions at mononucleotide runs in human genomes.

Figure 4.

MD and QM/MM simulations. (A) Molecular modeling of one (left) and two (right) minor groove water bridge coordination. (B) Fraction of one-water bridge occupancy (left axis) at A[9] DNA sequences flanked 5′ and 3′ by a T (black circles), C (red circles) or G (green circles). Minor groove widths (right axis), as determined from intrastrand phosphate-to-phosphate distances. (C) Vstep for A[9] DNA sequences, determined as the product of the square root of the eigenvalues (λi) described by the six bp step parameters shift, slide, rise, tilt, roll and twist; i.e. Vstep=6i=1λi−−√. (D) Fraction of one- (black circles) and two-water (red circles) bridge occupancy (left axis) at G[9] DNA sequences. Minor groove widths (right axis), as assessed from intrastrand phosphate-to-phosphate distances. (E) Vstep for G9 DNA sequences. (F) Average charge redistribution (open circles and right axis) for G[6] DNA structures upon vertical ionization, examined by calculating the difference on the density-derived atomic partial charges (DDAPC) for the neutral and negatively charged states. Histogram of the number of instances (left axis) in which the largest charge redistribution occurred at a specific position along the G[6] structures. (G) DDAPC for G[9] DNA structures (open circles and right axis) and histogram of the number of instances (left axis) in which the largest charge redistribution occurred at a specific position. (H) VMD rendering of a G[9] DNA structure displaying hole localization at G2. Capped base pairs were removed for clarity.

Position and orientation along nucleosome core particles modulate sequence variation

DNA wrapped around histones in nucleosomes is subject to local deformation (39), which may impact mutation. Thus, we analyzed the 1KGP SNVs at A- and G-tracts predicted to overlap with well-positioned nucleosome core particles (NCPs) (16). In hg19, the percentage of tracts that overlap with NCPs decreased moderately from ∼90% at length of 4 to 81% and 71% for A- and G-tracts of length 13, respectively (Figure 5A), suggesting that mononucleotide runs are not depleted in NCPs in human genomes as previously proposed (40). A-tracts of lengths 4–8 base pairs displayed distinctive peaks along the NCP surface in phase with the helical repeat of DNA (10.5 bp) and with minor grooves facing toward the inner protein core (lengths 4–5) (16) (Figure 5B and Supplementary Figure S5A). A-tracts of length of 9–13 bp exhibited only half (six) the peaks evident for the shorter tracts. For the G-tracts, only small peaks with no clear minor groove-inward-facing regions were detected (Supplementary Figure S5B).

Figure 5.

Positioning along nucleosome core particles. (A) Percent of A-tract (open circles) and G-tract (closed circles) base pairs in hg19 overlapping with well-positioned NCP genomic coordinates as a function of tract length. (B) Counts of base pairs in hg19 A-tracts of length 5 overlapping with NCPs genomic regions as a function of distance from the histone octamer dyad axis. Minor groove-inward-facing regions (gray) were derived from the X-ray crystal structure of NCP147 (41). (C) Percent SNVs in the 1KGP dataset (left axis) at every bp along A-tracts of length 5 for tracts centered at maxima (black) and minima (gray) along NCPs (Figure 5B). Percent increase (right axis) of SNVs at minima relative to maxima (green). P-values for paired t-tests: 0.013 (*), 0.002 (**) and 4.7 × 10−6 (***). (D) Whisker plots of%SNVs (left axis) at A1 for A-tracts of length 5 centered at maxima and minima (black) along NCPs (Figure 5B). Percent difference (right axis) in the number of A-tracts of length 5 in hg19 preceded by C, T or G (red) between those centered at minima and those centered at maxima (Figure5B). (E) C-containing/G-containing ratios (see text) for G-tracts of length 5 in hg19 as a function of distance from the NCP dyad axis (black) and location of core histones (maroon and green). Peaks correspond to negative iSAT (i.e. tilt parameters multiplied by the corresponding sin θ) values (gray) (39). Ratios of%SNV at G1 (upshifted by 0.5 for clarity) between C-containing (5′-CCCCCG-3′ sequences on the hg19 forward strand) and G-containing (5′-CGGGGG-3′ sequences on the hg19 forward strand) (Figure 1A) CG[5] tracts mapping NCP Chip-seq genomic intervals (red) fitted by a non-parametric local regression (loess; sampling proportion, 0.100; polynomial degree, 3). (F) VMD rendering (top) of TATTT residues 34–38 (yellow) and the complementary AAATA residues 672–753 (pink) from the 1EQZ pdb nucleosomal crystal structure, corresponding to peak area from −40 to −36 in Figure 5E. The switch in G-tract (lengths of 5 and 7) orientation along NCPs (bottom) serves to position the C-containing strand on the outside (yellow) and, correspondingly, the G-containing strand on the inside (pink).

 To assess if tract-positioning along NCPs influences SNVs, we selected A-tracts of lengths 5, 7 and 9 bp and G-tracts of lengths 5 and 7 bp whose central positions coincided with either the maxima or minima (41) (Figure 5B and Supplementary Figure S5A and B) and conducted pair-wiset-tests (330 total) between permutations of ‘categories’, including ‘tracts centered at maxima versus minima’, ‘position along the tracts’, ‘flanking sequence composition’, ‘specific NCP locations’ and ‘tract orientation’. For A-tracts, 79/207 (38%) significant pairs were found, 68 (86%) of which were related to differences between tracts centered at maxima versus minima, with a preponderance (63%) of tests displaying increased %SNVs at minima (Supplementary Figure S5C and E). For example, %SNVs at length 5 bp were greater at minima than at maxima at each position along the A-tracts (Figure 5C). A→C substitutions at A1 were more abundant at maxima than at minima (mean ± SD, 18.7 ± 0.7% at max and 17.6 ± 0.8% at min; P-value 0.001), whereas A→T substitutions at the same position displayed the opposite trend (mean ± SD, 18.4 ± 0.5% at max and 19.8 ± 1.1% at min; P-value 0.0005) (Figure 5D). A-tracts of length 7 also exhibited a similar pattern at A7 (Supplementary Figure S5H). The percentages of CA[5] and A[7]C tracts in hg19 centered at maxima were greater than at minima and the reverse was observed for the TA[5] and A[7T] tracts (Figure 5D and Supplementary Figure S5H). Thus, we conclude that positioning along the NCP surface of both the double-helical grooves and junctions with flanking base pairs influence SNVs along A-tracts. However, this influence is complex and for the most part, difficult to predict.

For G-tracts, most pairwise comparisons (18/34, 53%) indicated SNV variation according to sequence orientation (Supplementary Figure S5F and G). In hg19, the ratio of the numbers of G-tracts of lengths 5 and 7 for which the C-containing strand coincided with the forward sequence (downstream example sequence in Figure 1A) to the numbers of G-tracts for which the G-containing strand coincided with the forward sequence (upstream example sequence in Figure 1A) (C-containing/G-containing ratios) displayed a prominent 10.5-bp oscillation in phase with iSAT (Figure 5E), a measure of ‘inside’ and ‘outside’ bases, according to the bp step tilt parameter (39). Analysis of the helical path of a 146-bp DNA fragment wrapped around histones showed that the oscillation in the C-containing/G-containing ratios corresponds to a preference for guanine bases to face the protein core (Figure 5F). We analyzed the subset of G-tracts preceded by a 5′ C (i.e. CG[5]) to assess whether SNVs at G1, the position known to be mutable due to CpG methylation also oscillated with the C-containing/G-containing ratios. Oscillation in SNV-C-containing/SNV-G-containing values was evident, with peaks aligning to the hg19 troughs (Figure 5E) implying that the cytosines facing the protein surface harbor more variants than those facing away. We conclude that A- and G-tracts display preferential positioning (the former) and orientation (the latter) along NCPs, which in turn modulate the rate of sequence variation.

Mutations associated with human disease

Knowing that the first and last As of long A-tracts and G2–3 in G-tracts are the major sites of SNV in the human population, we addressed whether these features are also discernible in mutated mononucleotide tracts associated with human genetic disease. We collected 9,450,456 unique SBSs (both SBSs and SNVs refer to single base changes) from sequenced cancer genomes and normalized the percent mutations along A- and G-tracts to enable a direct comparison with the 1KGP dataset. For A-tracts (Figure 6A and Supplementary Figure S6A), SBSs displayed the same trend as the 1KGP data (Figure 2A) with respect to the bell-shape increase in mutations at A1 and An and the mutation spectra, although the susceptibility to mutation as a function of tract length attained greater values (6.36% for length 11 in cancer versus 4.15% for length 9 in the 1KGP datasets at A1). The first and last 3 bp also harbored more SBSs than in the 1KGP dataset for tracts >7 bp, a feature that we found to be due exclusively to a large cancer dataset (42) containing high-level microsatellite instability (MSI) samples (Supplementary Figure S6B and C), which are known to result from mismatch-repair deficiency (15). Thus, A-tracts display similar patterns of base substitution between the germline and somatic cancer tissues. For G-tracts, mutation spectra were characterized by G→T transversions at tract lengths >7, particularly at G1, the most frequently mutated position for tracts lengths up to 11 bp (Figure 6B and Supplementary Figure S6D). This trend persisted even when the high rates of methylation-mediated deamination mutations at the CG dinucleotide were removed (Supplementary Figure S6E). Thus, mutation patterns in cancer genomes contrast with those observed in the germline, both with respect to the most mutable position (G1 versus G2–3) and the types of base substitution (G→T in cancer genomes versus G→T and G→C in the germline).

Figure 6.

Mutation patterns in cancer genomes. (A) Mutation spectra for SBSs at A-tracts. Percent values were obtained by dividing the total number of SBSs at each position by the number of tracts in hg19 and then multiplying by 3.2516 to equalize the percentage of A-tracts of length 4 between the cancer genomes and the 1KGP datasets. (B) Mutation spectra for SBSs at G-tracts in cancer genomes. Percent values were obtained as in (A) using a multiplication factor of 3.7419. (C) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage, obtained by dividing the number of events by both the number of tracts in hg19 and tract length. (D) Indels at A-tracts, calculated as described in Figure 3C. (E) Indels at G-tracts, calculated as described in Figure3C. (F) Heatmap representation of insertions along G-tracts, as described in Figure 3E.

 With respect to slippage, the fractions for A-tracts elicited an excess at lengths 9 and 10 bp relative to the 1KGP dataset, which was also due to the MSI-containing dataset. For G-tracts, the fractions peaked at length 8, as for the 1KGP dataset (Figures 3A and 6C), implying that the propensity to undergo slippage is indistinguishable between the germline and soma. Indels were also more abundant at flanking base pairs than along the tracts (Figure 6D and E), particularly for G-tracts of length >7, similar to the 1KGP dataset (Figure 3C and D). Detailed analyses of insertions revealed that both G1 and the preceding position were the most significant sites of mutation (F-values up to 0.08 at G1 for tracts of length 8) (Figure 6F). Thus, the 5′ end of long G-tracts is the most susceptible site for both SBSs and insertions in cancer genomes, in contrast to the germline where these occur within the runs, typically at G2–3.

We also extracted the mutated A- and G-tracts from the Human Gene Mutation Database (HGMD), a collection of >150,000 germline gene mutations associated with human inherited disease. A total of 1519 genes were mutated at A- or G-tracts out of a total of 3972 (38%); 3480 SBSs and 2866 slippage events were noted within these tracts, 85 and 46% of which were predicted to be disease-causing, respectively (Figure 7A and Supplementary Table S1). Ranking genes by the number of literature reports indicated that among the top 10 entries three were associated with cancer (BRCA1, BRCA2 and APC), two with hemophilia (F8 and F9), four with debilitating lesions of the skin (COL71A), muscle (DMD), lung (CFTR) and kidney (PKD1), with one causing hypercholesterolemia (LDLR) (Figure 7B). Thus, mutations within A- and G-tracts carry a high social burden by contributing to some of the most common human pathological conditions.

Figure 7.

Mutation patterns in HGMD and model for sequence context-dependent changes. (A) Number of germline SBSs and slippage events (Slip.) at A- and G-tracts in HGMD. Gene alterations were classified as disease-causing mutation (DM), likely disease-causing mutation (DM?), disease-associated and putatively functional polymorphism (DFP), disease-associated polymorphism with additional supporting functional evidence (DP) and invitro/laboratory orinvivo functional polymorphism (FP). Codon changes (SIFT predictor) were classified as damaging (d), null (n), tolerated (t) and low-confidence prediction (l). (B) The 10 most commonly reported genes in HGMD with mutations at A- and G-tracts. Various mutated tracts were generally reported for the same gene in different reports. (C) Mutation spectra for SBSs at A- (left) and G-tracts (right) in HGMD. Percent values were obtained by dividing the total number of SBSs at each position by the number of tracts in hg19 exons. A|G→T (black), A|G→C (red), A→G (green), G→A (cyan). (D) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage, obtained by dividing the total number of events by the number of tracts in hg19 exons and by tract length. (E) Model for sequence context-dependent changes at A-tracts (left) and G-tracts (right). *, site of base modification.

 For both A- and G-tracts, SBSs occurred mostly at tract lengths of 4–7, with patterns more similar to those in the 1KGP than in the cancer datasets, both with respect to the location of the most mutable positions (first and last As and first/second Gs) and the types of base substitution (A→T and G→H) (Figure 7C and Supplementary Figure S6F). Likewise, slippage events peaked at tract lengths of 7–9 as observed in the 1KGP dataset (Figure 7D). In summary, the patterns of both SBSs and slippage in the HGMD dataset followed the trend observed in the 1KGP dataset, suggesting that germline variants at mononucleotide repeats leading to either population variation or human inherited disease may have arisen through similar mechanisms.
DISCUSSION

Why are specific A:T and G:C base pairs within A- and G-tracts more susceptible to sequence changes than their identical neighbors? For A-tracts, bp flexibility may play a role. Chemical damage to DNA, such as by hydroxyl radicals has been shown to be proportional to the geometrical solvent-accessible surface of the atomic groups, which increases with DNA flexibility (43). Along A-tracts flexibility is restricted, but it is high at both the 5′ and 3′ junctions. Thus, the fact that the highest rates of mutation coincide with the highest degree of flexibility at the 5′-TA-3′ bp step is consistent with the view that this position may be susceptible to DNA damage as a result of flexibility. Other sources of DNA dynamics are also likely to be relevant, such as sugar flexibility at the junctions, which increases with tract length (44). Chemical modification at these junctions may then lead to base substitution and indels, the latter as a result of strand breaks.

With respect to SNV mutation spectra, these were found mostly in the direction of flanking base composition above a length of 7–8 bp. We interpret this behavior in terms of DNA slippage along A-tracts when attempts are made during translesion synthesis (TLS) to bypass a damaged site (Figure 7Ei). Two scenarios may be considered to account for A→T transitions at A1. In the first, the last tract-template base would loop out into the polymerase active site permitting base-pairing and strand elongation (Figure 7Eii) using the tract-flanking base as a template (34,4546). In the second (Figure 7Eiii), slippage would occur behind the polymerase, prompting extension past the newly created A*:T mispair generated by primer/template misalignment. Either pathway would yield a common intermediate (Figure 7Eiv) that contains the base complementary to the junction across from the damaged site upon slippage resolution (34). Following DNA synthesis (S) and/or repair (R) (Figure 7Ev and vi), this mispair will generate a base change that is always identical to the tract-flanking base.

For G-tracts, the high rates of G→T transversions at G1 in cancer genomes are also consistent with preferred chemical attack at this site due to high flexibility (Figure 7F top). Direct chemical attack at a guanine is known to result in stable products, such as 8-oxo-G and Fapy-G, both of which are known to yield G→T transversions (4750). Thus, G1 may be the most susceptible site for such reactions for G-tracts of lengths ≥7 (Figure 7Fright), which in cancer genomes would become a mutation hotspot. In the germline, SNVs peaked inside G-tract base pairs, while mutational spectra were insensitive to flanking base composition; these events are inconsistent with a role for template misalignment and slippage as noted for A-tracts. Rather, the correspondence between hotspot mutations at G2–3 and G5 and the QM/MM simulations suggest a role for charge transfer. A large body of work during the past 20 years using computational, theoretical chemistry and biophysical techniques on short oligonucleotides, has shown that guanine is the most easily oxidizable base in DNA and that indeed a guanine radical cation can be generated through long-range hole transfer from an oxidant via one-electron oxidation mechanisms (5155). GGG triplets were found to act as the most effective traps in hole transfer by both experimental and theoretical work (5659), demonstrating that the resulting guanine radical cation (or its neutral deprotonated form) became rather delocalized, but it preferentially centered at the first and second G. These well-established patterns of chemical reactivity are consistent with our experimental observation of high mutation frequencies at G1 for short G-tracts and the results from QM/MM simulations on G6. For longer tracts, the downstream shift in mutation hotspots, i.e., G2–3 and G5, also correlate well with the charge localization predicted from QM/MM simulations, which explicitly included solvent effects and structural fluctuations. Thus, in conjunction with the constrained density functional theory (60), both the neutral and oxidized forms of a guanine nucleobase can be reliably constructed to infer the accurate determination of mutational patterns of mononucleotide repeats in human genomic DNA.

The compact organization of the sperm genome (61), and presumably low levels of oxidative stress in the germline, may enable guanine oxidization through one-electron oxidation reactions rather than by direct chemical attack, thereby favoring the formation of radical cations. A charge injected at G1 by electron loss would then migrate to neighboring guanines and localize at sites of low IP, such as G2 (Figure 7F left). Guanine radical cations are known to readily undergo further chemical modification leading to products such as 8-oxo-G, oxazolone, imidazolone, guanidinohydantoin, and spiroiminodyhydantoin (62) (M in Figure 7F), to yield G→T, G→C and G→A substitutions (4,63). Our model is in line with recent observations in which mutations at guanines within short G-runs (1–4 bp) correlate with sequence-dependent IPs at the target guanine in cancer genomes (9). Interestingly, these correlations were not observed in the germline (9). We interpret these composite observations as follows. The IP values for G-runs have been shown to decrease asymptotically with tract length, although the absolute values vary according to the methods and assumptions used (we obtained a value of 5.43 eV for both G[6] and G[9]) (64,65). We suggest that short G-runs with high IPs undergo one-electron oxidation reactions in the oxidative environment of cancer cells but would be refractory to such a mechanism in the germline (Figure 7Fright yellow and left white sectors). As length increases and IP values fall, G-runs would be attacked directly by oxidants abundant in tumor cells (Figure 7F orange sector), whereas oxidation will be limited to electron loss in the germline environment (Figure 7F left yellow sector).

These models (template misalignment for A-tracts and charge transfer for G-tracts) suggest a more complex scenario for mechanisms underlying mononucleotide repeat polymorphism in the human population than recently proposed (13), in which nucleotide misincorporation by error-prone polymerases is proposed as a primary source of mutations at both A- and G-tracts. As already stated, the directionality of SNVs toward tract-flanking bases in A-tracts and the hotspot mutations at G2–3, supports multiple and distinct mechanisms of base substitution at mononucleotide repeats.

Our analyses highlight additional information, including the lack of mutations in the direction of tract-base composition for base pairs flanking long tracts, the association with gene expression and the preference of guanines for the inner NCP surface, and extend prior observations (12) such as the bell-shape character of base substitution and slippage, whose mechanisms remain to be fully clarified. Finally, we document the contribution of mononucleotide mutagenesis to key aspects of human pathology beyond the well-established MSI instability in cancer (15), including hemophilia and tissue degeneration. Our collective work supports the conclusion that as the human genome undergoes evolutionary diversification and along the way suffers disease-associated mutations, oxidation reactions including charge transfer may play a prominent role.

SUPPLEMENTARY DATA

Supplementary Data are available at NAR Online.

 

 

Mutation analyses and prenatal diagnosis in families of X-linked severe combined immunodeficiency caused by IL2Rγ gene novel mutation

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Genet. Mol. Res. 14 (2): 6164 – 6172   DOI: 10.4238/2015.June.9.2
Severe combined immunodeficiency diseases (SCIDs) are a group of primary immunodeficiency diseases characterized by a severe lack of T cells (or T cell dysfunction) caused by various gene abnormalities and accompanied by B cell dysfunction (WHO, 1992; Buckley et al., 1997). The incidence rates in infants were 1/75,000-1/10,0000 (WHO, 1992), but no morbidity statistics are available in China. The 2 genetic modes of SCID include X-linked recessive and autosomal recessive genetic inheritance. X-linked severe combined immunodeficiency (X-SCID) is the most common form, accounting for 50-60% of SCID cases (Noguchi et al., 1993). Immune system abnormalities in patients with X-SCID include T-B+NK-, in which T cells (CD3+) and natural killer (NK) cells (CD16+/CD56+) are absent or significantly reduced, and the number of B cells (CD19+) is normal or increased, causing reduced immunoglobulin production and class switching disorder (Buckley, 2004; Fischer et al., 2005). The IL- 2Rg gene mutation has been confirmed to be a major cause of X-SCID (Noguchi et al., 1993). In recent years, great progress has been made in understanding the pathogenesis of primary immunodeficiency disease and its application in clinical treatment, particularly regarding the development of critical care medicine and immune reconstruction technology. With timely control of infection and early bone marrow or stem cell transplantation, X-SCID patients can be treated, prolonging survival time. Therefore, early diagnosis of X-SCID is very important for patient treatment. Gene diagnosis has become a better early diagnosis or differential diagnosis method. In addition, familial X-SCID brings a great psychological burden to the relatives of patients. Ordinary chromosome analysis and immunological evaluation cannot be used for female carrier identification and fetal diagnosis, and gene diagnosis is the most effective method of carrier detection and prenatal diagnosis. In this study, we detected mutations in 2 families with X-SCID and identified 2 novel mutations, confirming the X-SCID pedigrees. Prenatal diagnosis was performed for the pregnant fetus in the mother of one of the probands based on gene diagnosis. Female individuals in this family were subjected to carrier detection.
IL2Rg gene mutation test Direct sequencing of 1-8 exons and the flanking region of the IL2Rg gene by PCR in family 1 showed that the 3rd exon of the proband contained the c.361-363delGAG heterozygous deletion mutation, which led to deletion of the 121st amino acid glutamate (p.E121del) in its coding product. There were no sequence variations in other coding regions or in the shear zone. The proband’s mother carried the same heterozygous mutation, while his father did not carry the mutation site (Figure 2a, b, c). This mutation was not observed in any cases of the control group, and this family was identified as an X-SCID family. The c.510-511insGAACT insertion heterozygous mutation was present in the 4th exon of the proband’s mother in family 2. This mutation was a 5-base repeat of GAACT, resulting in a change in amino acid 173 from tryptophan into a stop codon (p.W173X). While there were no sequence variations in other coding regions or in the shear zone, the patient’s father did not carry the mutation (see Figure 2d, e). We did not find this mutation in the healthy control group. We presumed that the 4th exon of the deceased child in family 2 contained the c.510-511insGAACT insertion mutation, leading to X-SCID symptoms, and thus we speculated that this family was an X-SCID pedigree. Prenatal diagnosis We verified the chorionic villus status of the fetus in family 1 using the PowerPlex 16 HS System kit. The results of prenatal diagnosis showed that the fetal tissue contained no maternal contamination and that this fetus was female. The results of prenatal diagnosis showed that there was no c.361-363delGAG (p.E121del) heterozygous mutation in the female fetus of family 1.
Figure 2. Sequencing graph of IL2Rg gene in 2 pedigrees with X-chain severe combined immunodeficiency. a.-c. Family 1. a. Normal control (rectangle indicates 3 edentulous bases of this patient). b. Proband carrying the c.361- 363delGAG (p.E121del) mutation (arrow indicates deletion of fragment connection sites). c. The proband’s mother contained a c.361-363delGAG (p.E121del) heterozygous mutation (arrow). d.-e. Family 2. d. The proband’s mother carried the c.510-511insGAACT (p.W173X) heterozygous mutation (arrow indicates that the reverse sequencing graph was positive). e. Normal control (rectangular box indicates 2 normal copies of GAACT (the mutation fragment was 3 copies). Carrier detection results For the c.361-363delGAG (p.E121del) site, the gene analysis results of the female individual in family 1 showed that I2 (proband’s grandmother) was a heterozygous carrier and that II3 (proband’s aunt) was a non-carrier and had no mutations.
IL-2 can combine with the IL-2 receptor (IL-2R) of the immune cell membrane. IL-2R is composed of 3 subunits, including the IL-2Ra chain (CD25), IL-2Rb chain (CD122), and IL- 2Rg chain (CD132). IL-2Rg functional units in common with IL-4, IL-7, IL-9, IL-15, IL-21, and other cytokine receptors, and these regions are referred to as the total chain (Li et al., 2000). The IL-2Rg chain can maintain the integrity of the IL-2R complex and is required for the internalization of the IL-2/IL-2R complex; it is also the link that contacts the cell membrane surface factor region and downstream cell signal transduction molecules. Therefore, the integrity of the IL-2Rg chain is vital for the immune function of an organism (Malka et al., 2008; Shi et al., 2009).
Mutations in the IL2Rg gene, which encodes IL-2Rg, were identified to be a major cause of X-SCID in 1993 (Noguchi et al., 1993). The IL2Rg gene is located on chromosome X q21.3-22, is 37.5 kb length, and contains 8 exons, which encode 369 IL-2Rg amino acids. The IL2Rg chain exhibits varying structural regions, such as the signal peptide [amino acids (AA) 1-22], extracellular domain (AA 23-262), transmembrane region (AA 263-283), and intracellular region (AA 284-369). The WSXWS motif is located in the extracellular region (AA 237-241), while Box 1 is located in the intracellular region (AA 286-294).
By the end of 2013, the Human Gene Mutation Database contained a total of 200 mutations in the IL2Rg gene (HGMD Professional 2013.4). The most common mutation types in the IL2Rg gene were the missense or nonsense mutations, which result from single base changes. A total of 100 missense or nonsense mutations have been identified, followed by insertion or deletion mutations in a total of 50 species. The 3rd most common type of mutations includes shear mutations in approximately 30 species. Eight exons contained mutations, and mutations in 3rd or 4th exons were the highest, accounting for a total mutation rate of 43% (86/200). According to the X-SCID gene database (IL2RGbase) (http://research.nhgri. nih.gov/scid/), the gene mutations in IL2Rg mainly occurred in the extracellular region of the IL2Rg chain (Fugmann et al., 1998). Zhang et al. (2013) reported that the IL2Rg gene mutations in 10 patients with X-SCID in China were located in the extracellular region. Two mutations reported in our study were also located in the extracellular region. The mutation of IL2Rg gene in family 1 was a codon mutation in the 3rd exon, resulting in a 3-base deletion. The c.361-363delGAG (p.E121del) mutation was located in the extracellular area of the IL- 2Rg subunit, and we inferred that the 121 glutamate deletion caused by the mutation would lead to changes in the structure of the peptide chain, affecting signal transmission and resulting in serious symptoms. The mutation of family 2 was a GAACT repeat of ILR2g gene; this repeat of 5 bases resulted in 173 codon changes from tryptophan into a stop codon. Generation of the peptide chain with the mutation lacked 196 amino acids compared to the normal chain, including the intracellular, transmembrane, and some extracellular regions, directly affecting the structure and function of receptors and causing disease. No studies have been reported regarding these 2 mutations. We combined with the mutation characteristics and clinical manifestations and diagnosed family 1 as X-SCID pedigrees. Although the patient in family 2 was deceased, it can be speculated that the 2 deceased patients in family 2 were X-SCID pedigrees caused by c.510-511insGAACT (W173X).
Prenatal diagnosis can accurately identify fetal situations and be used to avoid birth defects, which can also ease the anxiety of the pregnant mother. Gene diagnosis for pedigrees of patients based on DNA samples has advanced recently, particularly with the application of high-throughput sequencing technology (Alsina et al., 2013). We can now perform gene analysis for varied clinical infectious diseases for differential diagnosis. However, the effectiveness of prenatal diagnosis for pedigrees in which the proband is dead remains unclear. Because the gene mutations in the proband is unknown in these cases, the patient’s situation was only inferred by his mother’s genotypes. However, we considered that for the deceased, if we can define the mother was a pathogenic gene carrier, even if the proband is not X-SCID, the woman also has a risk of having X-SCID children and this pedigree may be X-linked recessive inheritance. Prenatal diagnosis may provide a choice for preventing the birth of patients in these families in the premise of informed consent.
Gene diagnosis of IL2Rg can also be used for carrier detection of suspected females in the family.
In the present study, we performed carrier detection of the patient’s grandmother and aunt in family 1 and determined that the patient’s pathogenic mutations were from his grandmother. His aunt did not inherit the pathogenic gene, and thus she was a non-carrier and her fertility will not be affected. In this study, we used direct sequencing of PCR products and identified IL2Rg gene mutations in 2 pedigrees with X-SCID. We found 2 unreported mutations in the IL2Rg gene, and prenatal diagnosis and carrier detection were conducted in 1 X-SCID family. Because the incidence rate of X-SCID is extremely low, it is difficult to promote the widespread use and application of genetic diagnosis. However, this study may provide some implications for the diagnosis of infants with immunodeficiency, and gene diagnosis techniques such as conventional or high-throughput sequencing should be used as soon as possible during pregnancy, which can be used to guide treatment. This method can also provide reliable prenatal diagnosis and carrier detection service for these families.
MEF2A gene mutations and susceptibility to coronary artery disease in the Chinese population
J. Li1 , H.-X. Chen2 , J.-G. Yang3 , W. Li3 , R. Du3 and L. Tian3       DOI http://dx.doi.org/10.4238/2014.October.20.15
Coronary artery disease (CAD) has high morbidity and mortality rates worldwide. Thus, the pathogenesis of CAD has long been the focus of medical studies. Myocyte enhancer factor 2A (MEF2A) was first discovered as a CAD-related gene by Wang (2005) and Wang et al. (2003, 2005). Three mutation points in exon 7 of MEF2A were subsequently identified by Bhagavatula et al. (2004); however, Altshuler and Hirschhorn (2005) and Weng et al. (2005) predicted that the MEF2A gene lacked mutations. Zhou et al. (2006a,b) analyzed the mutations and polymorphisms in exons 7 and 11 of the MEF2A gene in the Han population in Beijing, and various rare mutations were found in exon 11 rather than in exon 7. The clinical significance of specific 21-bp deletions in MEF2A was also explored, and previous studies have shown mixed results. In this study, polymerase chain reaction-singlestrand conformation polymorphism (PCR-SSCP) and DNA sequencing were used to detect exon 11 of the MEF2A gene in samples collected from 210 CAD patients and 190 healthy controls and to investigate the function of the MEF2A gene in CAD pathogenesis and their correlation.
CAD, a common disease in China, is induced by multiple factors, such as genetics, the environment, and lifestyle. Thus, a multi-faceted approach is necessary in the study of CAD pathogenesis, particularly in molecular biology research, which is important for developing comprehensive treatment of CAD based on gene therapy. The MEF2A gene was first identified as a CAD-related gene through linkage analysis of a large family with CAD (9 of 13 patients developed MI) in 2003.
In this study, we found the following mutations: 1) codon 451G/T (147191) heterozygous or homozygous mutation; 2) loss of 1 (Q), 2 (QQ), 3 (QQP), 6 (425QQQQQQ430), and 7 (424QQQQQQQ430) amino acids (147108-147131); and 3) codon 435G/A (147143) heterozygous mutation. Among these mutations, the synonymous mutation at locus 147191 was confirmed by reference to the National Center for Biotechnology Information (NCBI) database to be a single nucleotide polymorphism, which was also demonstrated in our study by the extensive presence of this polymorphism in healthy controls. However, the heterozygous mutation at locus 147143 was only found in the genomes of CAD patients, and was therefore identified as a mutation.
Given that MEF2A is a CAD-related gene, the results of various studies are controversial among several countries. Weng et al. (2005) screened gene mutations in exon 11 of the MEF2A gene from 300 CAD patients and 1500 healthy controls. They hypothesized that the changes in 5-12 CAG repeats are genetic polymorphisms and that the 21-base deletion in exon 11 of the MEF2A gene did not induce autosomal dominant genetic CAD. Gonzalez et al. (2006) suggested that the CAG repeat polymorphism was independent of MI susceptibility in Spanish patients. Kajimoto et al. (2005) reported that the CAG repeat sequence was not correlated with MI susceptibility in Japanese patients. Horan et al. (2006) also found that the CAG repeat sequence was not associated with the susceptibility to early-onset familial CAD in an Irish population. Hsu et al. (2010) identified no correlation between the CAG repeat sequence and CAD susceptibility in the Taiwanese population. Dai et al. (2010) found that the structural change in exon 11 was not related to CAD in the Chinese Han population. Lieb et al. (2008) and Guella et al. (2009) hypothesized that MEF2A was independent of CAD. However, Yuan et al. (2006) and Han et al. (2007) suggested that the CAG repeat sequence was correlated with CAD because 9 CAG repeats was an independent predictor of CAD. Elhawari et al. (2010) and Maiolino et al. (2011) suggested that MEF2A is a susceptibility gene for CAD. Dai et al. (2013) showed that mutations in exon 12 are associated with the early onset of CAD in the Chinese population. Liu et al. (2012) failed to demonstrate a correlation between the CAG repeat sequence and CAD through case-control analysis, systematic review, and meta-analysis, but found that the 21- base deletion in exon 11 was strongly associated with CAD, and that genetic variations in MEF2A may be a relatively rare, but specific, pathogenic gene for CAD/MI. Kajimoto et al. (2005) reported 4-15 CAG repeats. However, only 4-11 CAG repeats were observed in our study, possibly because of genetic differences in patients in this study. Eleven CAG repeats were observed in most samples from the control group, and the proportion of 10, 9, and 8 repeats exceeded 1%. The heterozygous mutation at 147143, as well as the 4 and 5 CAG repeats, was only observed in CAD patients. Thus, we speculated that the CAG repeat sequence is correlated with CAD susceptibility, and the presence of 4 or 5 repeats may be a risk factor for CAD, which was inconsistent with the results obtained by Han et al. (2007). The inconsistency in these results may be explained by the differences in subjects and sample sizes among studies.
Impact of glucocerebrosidase mutations on motor and nonmotor complications in Parkinson’s disease

Homozygous and compound heterozygous mutations in GBA encoding glucocerebrosidase lead to Gaucher disease (GD). A link between heterozygous GBAmutations and Parkinson’s disease (PD) has been suggested ( Bembi et al., 2003,Goker-Alpan et al., 2004, Halperin et al., 2006, Machaczka et al., 1999, Neudorfer et al., 1996, Tayebi et al., 2001 and Tayebi et al., 2003). In 2009, a 16-center worldwide analysis of GBA revealed that heterozygous GBA mutation carriers have a strong risk of PD ( Sidransky et al., 2009).

In addition, heterozygote GBA mutations not only carry a risk for PD development but also the possibility of some risk burden on the progression of PD clinical course. In cross-sectional analyses of GBA mutations in PD patients, earlier disease onset, increased cognitive impairment, a greater family history of PD, and more frequent pain were reported in patients with mutations, compared with no mutations ( Chahine et al., 2013,Clark et al., 2007, Gan-Or et al., 2008, Kresojevic et al., 2015, Lwin et al., 2004, Malec-Litwinowicz et al., 2014, Mitsui et al., 2009, Neumann et al., 2009, Nichols et al., 2009,Seto-Salvia et al., 2012, Sidransky et al., 2009, Swan and Saunders-Pullman, 2013 and Wang et al., 2012). Recently, a few prospective studies have investigated clinical features of PD with GBA and showed a more rapid progression of motor impairment and cognitive decline in GBA mutation cases than in PD controls ( Beavan et al., 2015, Brockmann et al., 2015 and Winder-Rhodes et al., 2013). However, in terms of motor complications such as wearing-off and dyskinesia, no studies exist in the longitudinal course of PD with GBA mutations.

Here, we conducted a multicenter retrospective cohort analysis, and the data were investigated by survival time analysis to show the impact of GBA mutations on PD clinical course. We also investigated regional cerebral blood flow (rCBF) and cardiac sympathetic nerve degeneration of subjects with GBA mutations, compared with matched PD controls.

3.1. Subjects

Among the 224 eligible PD patients (the subjects were not related to each other), 9 subjects were excluded from the analysis (4 due to multiple system atrophy findings on subsequent brain MRI and 5 because of insufficient clinical information). Therefore, 215 PD patients [female, 52.1%; age, 66.7 ± 10.8 (mean ± standard deviation)] were analyzed. For non-PD healthy controls, 126 patients’ spouses (female, 58.7%; age, 67.3 ± 10.3) without a family history of PD or GD were enrolled.

3.2. GBA mutations and risk ratios for PD

In the PD subjects, we identified 10 nonsynonymous and 2 synonymous GBA variants. Within the nonsynonymous variants, 7 mutations were previously reported in GD [R120W, L444P-A456P-V460 (RecNciI), L444P, D409H, A384D, D380N, and444L(1447-1466 del 20, insTG)] as GD-associated mutations. Three nonsynonymous mutations have never been reported in GD patients [I(-20)V, I489V, and there was one novel mutation (Y11H)].

GD-associated GBA mutations were found in 19 of the 215 (8.8%) PD patients but none in the healthy controls. The risk of PD development relative to these GD-associated mutations was estimated as an OR of 25.1 [95% confidence interval (CI), 1.50–420,p = 0.0001] with 0-cell correction. The nonsynonymous mutations that were not reported in GD patients had no association with PD development (p = 0.506; OR, 1.3; 95% CI, 0.7–2.6) ( Table 1). Four subjects had double mutations. For subsequent analyses, 2 subjects with double mutations of I (-20)V and K466K were adopted to the group of mutations unreported in GD, and 2 subjects with double mutations of R120W and I(-20)V, and of R120W and L336L were adopted to the group of GD-associated mutations.

Table 1.Frequency of glucocerebrosidase gene allele in Parkinson’s disease patients and controls

Allele name PD (n = 215) Controls (n = 126) p Odds ratio (95% CI)
GD-associated mutations
 R120W 7a 0 0.050 9.1 (0.5–160.8)
 RecNciI (L444P-A456P-V460) 4 0
 L444P 4 0
 D409H 1 0
 A384D 1 0
 D380N 1 0
444L(1447-1466 del 20, insTG) 1 0
 Subtotal, n (%) 19 (8.8%) 0 (0%) <0.001 25.1 (1.5–419.8)b
Nonsynonymous mutations not reported in GD
 I(-20)V 27a 13 0.603 1.3 (0.6–2.5)
 I489V 3 0
 Y11Hc 0 1
 Subtotal, n (%) 30 (14.0%) 14 (11.1%) 0.506 1.3 (0.7–2.6)
Synonymous, n
 K466K 2a 1
 L336L 1a 0
Allele names refer to the processed protein (excluding the 39-residue signal peptide).

Key: CI, confidence interval; GD, Gaucher disease; PD, Parkinson’s disease.

a Four subjects had double mutations; 2 of I(-20)V and K466K, 1 of I(-20)V and R120W, and 1 of R120W and L336L.
b Odds ratio was calculated by adding 0.5 to each value.
c Novel mutation.
3.3. Clinical features of PD patients by GBA mutation groups

The clinical features of PD patients with GD-associated mutations, those with mutations unreported in GD, and those without mutations are shown in Table 2. In the GD-associated mutation group, females, those with a family history and those with dementia (DSM IV) were significantly more frequent than those in the no-mutation group (p = 0.047, 0.012, and 0.020, respectively). The age of PD onset was lower in patients with GD-associated mutations (55.2 ± 9.9 years ± standard deviation), compared with those without mutations (59.3 ± 11.5), although the statistical difference was not significant. There were no differences in clinical manifestations between subjects with mutations unreported in GD and those without mutations, except for dopamine agonist dosage (p = 0.026) ( Table 2).

Table 2.Epidemiological and clinical features of PD patients with Gaucher disease–associated GBA mutations, those with mutations previously unreported in GD and those without mutations

Variables Total n = 215 Mutation (-) GD-associated mutations


Mutations unreported in GD


167 19a pb 29c pd
Sex Female, n (%) 83 (49.7) 14 (73.7) 0.047 15 (51.7) ns
Age Mean (SD) 67.0 (10.8) 62.2 (10.7) 0.063e 67.5 (11.2) nsf
Disease duration (y) Mean (SD) 7.7 (5.5) 6.9 (4.6) nsf 7.2 (4.9) nsf
Onset age Mean (SD) 59.3 (11.5) 55.2 (9.9) ns 60.3 (11.8) ns
Family history Yes, n (%) 17 (11.0)g 6 (31.6) 0.012 0 (0.0) ns
Dementia (DSM-IV) Yes, n (%) 29 (17.4) 9 (47.4) 0.020 5 (17.2) ns
MMSE Mean (SD) 25.8 (5.4)h 23.3 (7.7) nsf 27.0 (3.4)i nsf
Onset symptom (tremor vs. others) Tremor, n (%) 78 (46.8) 9 (47.4) ns 15 (51.7) ns
Modified H-Y on (<3 vs. ≥3) ≥3, n (%) 82 (49.1) 14 (73.7) 0.042 16 (55.2) ns
UPDRS part 3 Mean (SD) 23.6 (12.2)j 28.5 (13.8) nsf 21.9 (8.7) nsf
Wearing off Yes, n (%) 70 (41.9) 9 (47.4) ns 13 (44.8) ns
Dyskinesia Yes, n (%) 49 (29.3) 8 (42.1) ns 8 (27.6) ns
Mood disorder Yes, n (%) 43 (25.7) 8 (42.1) ns 7 (24.1) ns
Orthostatic hypotension symptom Yes, n (%) 21 (12.6) 5 (26.3) ns 7 (24.1) ns
Psychosis history Yes, n (%) 59 (35.3) 10 (52.6) ns 7 (24.1) ns
ICD history Yes, n (%) 8 (4.8) 1 (5.3) ns 1 (3.4) ns
Stereotactic brain surgery for PD Yes, n (%) 4 (2.4) 0 (0.0) ns 0 (0.0) ns
Agonist LED mg/d Mean (SD) 92.8 (114.2) 72.1 (137.7) nse 163.7 (155.6) 0.026e
Levodopa LED mg/d Mean (SD) 400.7 (184.2) 456.7 (206.9) nsf 369.2 (230.3) nse
Total LED mg/d Mean (SD) 496.4 (233.7) 537.9 (258.9) nsf 525.7 (287.4) nsf
Categorical data were examined by Fisher’s exact test.

Key: DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; GBA, glucocerebrosidase gene; GD, Gaucher disease; H-Y, Hoehn and Yahr; ICD, impulse control disorder; LED, levodopa equivalent dose; ns, not significant; MMSE, Mini-Mental State Examination; PD, Parkinson’s disease; SD, standard deviation; UPDRS, Unified Parkinson’s Disease Rating Scale.

a Including a double-mutation subject (with a mutation unreported in GD).
b GD-associated mutations versus mutation (-).
c Two subjects with double mutation, including GD-associated mutations, were assigned to GD-associated mutation group.
d Other mutations versus mutation (-).
e Examined by Student t test after Levene’s test for equality of variances.
f Examined by Mann-Whitney U-test because of non-Gaussian distribution.
g    n = 155 due to 10 missing data.
h    n = 164 due to 3 missing data.
i     n = 28 due to 1 missing datum.
j     n = 165 due to 2 missing data.

3.4. Survival time analyses to develop dementia, psychosis, dyskinesia, and wearing-off

Time to develop clinical outcomes (dementia, psychosis, dyskinesia, and wearing-off) was compared in 19 subjects with GD-associated mutations, 29 with mutations unreported in GD, and 167 without mutation. The median observation time was 6.0 years. The subjects with GD-associated mutations showed a significantly earlier development of dementia and psychosis, compared with subjects without mutation (p < 0.001 and p = 0.017) ( Supplementary Table e-1, Fig. 1A and B). We rereviewed the clinical record of the subject who showed early dementia (defined by DSM IV) ( Fig. 1A) and made sure it did not satisfy the criteria of DLB ( McKeith et al., 2005).

Kaplan–Meier curves of dementia and psychosis in Parkinson's disease (PD) ...

Fig. 1.

Kaplan–Meier curves of dementia and psychosis in Parkinson’s disease (PD) patients with Gaucher disease (GD)-associated glucocerebrosidase gene (GBA) mutations and those without mutations. PD patients with GD-associated GBA mutations and those without GBA mutations were compared to investigate the time taken to develop dementia (A) and psychosis (B). Because of insufficient information in several patients, the numbers in each analysis were different. The patients with and without mutations were 17 and 165 (A), 18 and 165 (B) against a total of 19 and 167. DSM IV, Diagnostic and Statistical Manual of Mental Disorders, revised fourth edition. p-Values were calculated by log-rank tests.

The associations of GBA mutations and these symptoms were estimated as HRs, adjusting for sex and age at PD onset. HRs were 8.3 for dementia (95% CI, 3.3–20.9; p < 0.001) and 3.1 for psychosis (95% CI, 1.5–6.4; p = 0.002). The time until development of wearing-off and dyskinesia complications was not statistically significant, with HRs of 1.5 (95% CI, 0.8–3.1; p = 0.219) and 1.9 (95% CI, 0.9–4.1; p = 0.086) ( Table 3).

Table 3.Hazard ratios of GBA pathogenic mutations for clinical symptoms

Model Clinical feature Hazard ratio 95% CI p
1 Dementia (DSM-IV) 8.3 3.3–20.9 <0.001
2 Psychosis 3.1 1.5–6.4 0.002
3 Wearing-off 1.5 0.8–3.1 0.219
4 Dyskinesia 1.9 0.9–4.1 0.086
Each model was adjusted for sex and age at onset.

Key: CI, confidence interval; DSM-IV; The Diagnostic and Statistical Manual of Mental Disorders part 1IV; GBA, glucocerebrosidase.

Subjects with mutations unreported in GD did not show significant differences in time to develop all 4 outcomes, compared with no mutation subjects. Therefore, subjects with GD-unreported mutations were regarded as subjects without GBA mutations in further analyses.

3.5. rCBF on SPECT in patients with GD-associated GBA mutations

We conducted pixel-by-pixel comparisons of rCBF on SPECT between PD subjects with mutations (cases) and sex-, age-, and disease duration-matched PD subjects without any mutations in GBA (controls). Four controls were adopted for each case (except for a 34-year-old female case who was matched to a control), and in total 12 cases (female 50%, age at SPECT mean ± standard error (SE); 58.9 ± 3.3 years, disease duration at SPECT 7.3 ± 1.5 years) and 45 controls (female 64.4%, age at SPECT mean ± SE; 61.0 ± 1.3 years, disease duration at SPECT 7.1 ± 0.7 years) were analyzed. As a result, a significantly lower rCBF was seen in the cases compared to the controls in the bilateral parietal cortex, including the precuneus ( Fig. 2).

Regional cerebral blood flow in the group with GD-associated mutations compared ...

Fig. 2.

Regional cerebral blood flow in the group with GD-associated mutations compared with the matched Parkinson’s disease group without mutations. Regions with lower regional cerebral blood flow in the group with GD-associated mutations displayed on an anatomic reference map. Abbreviation: GD, Gaucher disease.

3.6. H/M ratios on MIBG scintigraphy in patients with GD-associated GBA mutations

Cardiac MIBG scintigraphy visualizes catecholaminergic terminals in vivo that are reduced as well as brain dopaminergic neurons in PD patients. We also investigated MIBG scintigraphy between 16 cases (female 68.8%, age at examination mean ± SE; 60.2 ± 2.6 years, disease duration at examination 6.2 ± 1.2 years) and sex-, age- and disease duration-matched 61 controls [(63.8 %, age 62.0 ± 1.1 years, disease duration 5.5 ± 0.6 years) (1:4 except for 1 young 34-year-old female case who was matched to a control)]. In the results, both early and late H/M ratios declined in both groups and did not show any significant differences (p = 0.309 and 0.244) ( Supplementary Table e-2).

4. Discussion

4.1. Contributions of GD-associated GBA mutations to the development of PD

In the analysis of 215 PD patients and 126 non-PD controls, we identified 10 nonsynonymous heterozygous GBA mutations, including 1 novel mutation. Among these mutations, 7 were GD-associated, and the patients carrying these mutations represented 8.8% of the PD cohort. No significant association was found between the GD-unreported mutations and PD development, which suggests that only the GD-associated mutations are a genetic risk for PD. According to a worldwide multicenter analysis of 1883 fully sequenced PD patients, 7% of the GD-associated mutations are found in non-Ashkenazi Jewish PD patients ( Sidransky et al., 2009). Although the mutation frequency in the present study was similar to previous results, the OR of GD-associated heterozygous mutations (25.1) was significantly greater than the OR (5.43) of other ethnic cohorts (Sidransky et al., 2009) and was consistent with an OR of 28.0 from a previous Japanese report ( Mitsui et al., 2009). These results, taken together, suggest the possibility thatGBA mutations are at a distinct risk for PD in the Japanese population. However, a larger Japanese cohort study is required to confirm this.

4.2. Cross-sectional clinical figures of PD with GBA mutations

Before the survival time analyses, we investigated clinical features at enrollment between mutation groups. The lower onset age, more frequent family history and dementia, and worse disease severity of PD in patients with GBA mutations, compared with those without mutations, were consistent with previous cross-sectional case-control reports ( Anheim et al., 2012, Brockmann et al., 2011, Chahine et al., 2013, Lesage et al., 2011, Li et al., 2013, Mitsui et al., 2009, Neumann et al., 2009, Seto-Salvia et al., 2012 and Sidransky et al., 2009). In contrast, female-predominance (73.7%, p = 0.047) in patients with mutations observed in the present study is inconsistent ( Neumann et al., 2009 and Seto-Salvia et al., 2012).

4.3. Impact of GBA mutations on the clinical course of PD

To investigate the impact of GBA mutations on the clinical course of PD, a prospective-designed study over a long period is preferred. Although there has been a few longitudinally designed study to date, follow-up clinical data for a median of 6 years of 121 PD cases from a community-based incident cohort was recently reanalyzed; results demonstrate that progression to dementia defined by DSM IV (HR 5.7) and Hoehn and Yahr stage 3 (HR 3.2) are significantly earlier in 4 GBA mutation-carrier patients compared with 117 patients with wild-type GBA ( Winder-Rhodes et al., 2013). A 2-year follow-up clinical report of 28 heterozygous GBA carriers who were recruited from relatives of GD-patients shows slight but significant deterioration of cognition and smelling, compared to healthy controls ( Beavan et al., 2015). Brockmann et al. (2015)assessed motor and nonmotor symptoms including cognitive and mood disturbances for 3 years in 20 PD patients with GBA mutations and showed a more rapid disease progression of motor impairment and cognitive decline in GBA mutation cases comparing to sporadic PD controls. The current long-term retrospective cohort study up to 12 years reinforced these results. It revealed that dementia and psychosis developed significantly earlier in subjects with GD-associated mutations compared with those without mutation, and the HRs of GBA mutations were estimated at 8.3 for dementia and 23.1 for psychosis, with adjustments for sex and PD onset age. In contrast, the results showed no significant difference in developing wearing-off and dyskinesia.

In this study, we also investigated whether GD-unreported mutations affected the clinical course of PD. In both cross-sectional and survival time analyses, the mutations unreported in GD carried no increased burden on clinical symptoms such as dementia, psychosis, wearing-off, and dyskinesia.

4.4. Reduced rCBF in PD with GBA mutations compared with matched PD controls

We found a significantly decreased rCBF, reflecting decreased synaptic activity, in the bilateral parietal cortex including the precuneus, in subjects with GD-associated mutations compared with matched subjects without mutations. The pattern of reduced rCBF was very similar to the pattern of H215O positron-emission tomography that Goker-Alpan et.al. (2012) reported, showing decreased resting rCBF in the lateral parietal association cortex and the precuneus bilaterally in GD subjects with parkinsonism (7 subjects with homozygous or compound heterozygous GBA mutations), compared with 11 PD without GBA mutations. Results suggest that PD with heterozygous GBAmutations and GD patients presenting parkinsonism had a common reduced pattern of rCBF. Interestingly, in their study, rCBF in the precuneus—but not in the lateral parietal cortex—correlated with IQ, suggesting that the involvement of the precuneus is critical for defining GBA-associated patterns.

4.5. Reduced cardiac MIBG H/M ratios as well as matched PD controls

We also showed that cardiac MIBG H/M ratios in subjects with GD-associated mutations were lower than the cutoff point for PD discrimination (Sawada et al., 2009), suggesting that postganglionic sympathetic nerve terminals to the epicardium were denervated, as well as in PD without mutations.

4.6. Mechanisms of impact on PD clinical course by GD-associated GBA mutations

Experimental studies suggesting a bidirectional pathogenic loop between α-synuclein and glucocerebrosidase have been accumulated (Fishbein et al., 2014, Gegg et al., 2012, Mazzulli et al., 2011, Noelker et al., 2015, Schondorf et al., 2014 and Uemura et al., 2015). Loss of glucocerebrosidase function compromises α-synuclein degradation in lysosome, whereas aggregated α-synuclein inhibits normal lysosomal function of glucocerebrosidase. The pathogenic loop may facilitate neurodegeneration in GD-associated PD brain, resulting in early development of dementia or psychosis as shown in the present study. Several recent researches propose the possibility that the similar mechanism as in PD with GBA mutations exists even in idiopathic PD brain ( Alcalay et al., 2015, Chiasserini et al., 2015, Gegg et al., 2012 and Murphy et al., 2014). On the other hand, the impacts of GD-associated GBA mutations for the development of motor complications such as wearing-off and dyskinesia were not statistically significant, suggesting other pathophysiological mechanisms in the striatal circuit brought out after long-term therapy especially by l-dopa.

4.7. Limitations

Our study has several limitations. In the design of the study, we assumed that the sample size was 215 (PD patients) for survival time analyses and investigated 224 PD patients. We assumed that the mutation prevalence would be 9.4%, and in fact, we found 19 patients with mutations (8.5%) of the 224 patients. Based on these figures, we estimated the risk ratios of heterozygous GBA mutations for the risk of PD development and PD clinical symptoms as ORs in the cross-sectional multivariate analyses, although the 95% CIs were broad. More of subject numbers will be needed to determine robust risk ratios.

Comprehensive Genetic Characterization of a Spanish Brugada Syndrome Cohort

PLOS   Published: July 14, 2015   DOI: http://dx.doi.org:/10.1371/journal.pone.0132888

Brugada syndrome (BrS) was identified as a new clinical entity in 1992 [1]. Six years later, the first genetic basis for the disease was identified, with the discovery of genetic variations inSCN5A [2]. Nowadays, more than 300 pathogenic variations in this first gene are known to be associated with BrS [3]. SCN5A encodes for the α subunit of the cardiac voltage-dependent sodium channel (Nav1.5), which is responsible for inward sodium current (INa), and thus plays an essential role in phase 0 of the cardiac action potential (AP). Genetic variations in this gene can explain around 20–25% of BrS cases [3].

Since BrS was classified as a genetic disease, several other genes have been described to confer BrS-susceptibility [47]. Pathogenic variations have been mainly described in: 1) genes encoding proteins that modulate Nav1.5 function, and 2) other calcium and potassium channels and their regulatory subunits. All these proteins participate, either directly or indirectly, in the development of the cardiac AP. Although the incidence of pathogenic variations in these BrS-associated genes is low [6], it is considered that, among all of them, they could provide a genetic diagnosis for up to an extra 5–10% of BrS cases. Hence, altogether, a genetic diagnosis can be achieved approximately in 35% of clinically diagnosed BrS patients.
Other types of genetic abnormalities have been suggested to explain the remaining percentage of undiagnosed patients. Indeed, multiplex ligation-dependent probe amplification (MLPA) has allowed the detection of large-scale gene rearrangements involving one or several exons ofSCN5A in BrS cases. However, the low proportion of BrS patients carrying large genetic imbalances identified to date suggests that this type of rearrangements will provide a genetic diagnosis for a modest percentage of BrS cases [810].
BrS has been associated with an increased risk of sudden cardiac death (SCD), despite the reported variability in disease penetrance and expressivity [11]. The prevalence of BrS is estimated at about 1.34 cases per 100 000 individuals per year, with a higher incidence in Asia than in the United States and Europe [12]. However, the dynamic nature of the typical electrocardiogram (ECG) and the fact that it is often concealed, hinder the diagnosis of BrS. Therefore, an exhaustive genetic testing and subsequent family screening may prove to be crucial in identifying silent carriers. A large percentage of these pathogenic variation carriers are clinically asymptomatic, and may be at risk of SCD, which is, sometimes, the first manifestation of the disease [13].
In the present work, we aimed to determine the spectrum and prevalence of genetic variations in BrS-susceptibility genes in a Spanish cohort diagnosed with BrS, and to identify variation carriers among relatives, which would enable the adoption of preventive measures to avoid SCD in their families.

Results  
Study population 

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Table 1. Demographics of the 55 Spanish BrS patients included in the study.

The table shows the demographic characteristics of all the patients included in the study. Numbers in parentheses represent the relative percentages for each condition. T1 ECG refers to Type 1 BrS diagnostic electrocardiogram (ECG), obtained either spontaneously, or after drug challenge. The information regarding both the electrophysiological studies (EPS) and the treatment was not available for all the patients. Two of the patients that didn’t receive any treatment died, and were not taken into account for the calculations of percentages (+2 dead). ICD, intracardiac cardioverter defibrillator.

http://dx.doi.org:/10.1371/journal.pone.0132888.t001

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Table 2. Characteristics of the Spanish BrS patients carrying rare genetic variations.

The table shows the clinical characteristics of the probands who carried rare genetic variations in SCN5A, SCN2B, or RANGRF. All of them are potentially pathogenic except that found in RANGRF, which is of unknown significance (see discussion). All the potentially pathogenic variations (PPVs) that had been previously reported, except p.P1725L and p.R1898C, had been identified in BrS patients. p.P1725L had been associated with Long QT Syndrome and p.R1898C was found in Exome Variant Server with a MAF of 0.0079%. No rare variations were identified in the control population. Patient’s age is expressed in years. Bold identifies the patients carrying variations that had not been described previously. M, male; F, female; S, syncope; ICD, intracardiac cardioverter defibrillator; UK, unknown; EPS, electrophysiological studies (+, positive response;-, negative response; N/P, not performed). The two patients who carried two PPVs each are identified by a and b, respectively.

http://dx.doi.org:/10.1371/journal.pone.0132888.t002

Sequencing of genes associated with BrS

We performed a genetic screening of 14 genes (SCN5A, CACNA1C, CACNB2, GPD1L,SCN1B, SCN2B, SCN3B, SCN4B, KCNE3, RANGRF, HCN4, KCNJ8, KCND3, and KCNE1L), which allowed the identification of 61 genetic variations in our cohort. Of these, 20 were classified as potentially pathogenic variations (PPVs), one variation of unknown significance, and 40 common or synonymous variants considered benign.

The 20 PPVs were found in 18 of the 55 patients (32.7% of the patients, 83.3% males; Table 2). Sixteen patients (88.9%) carried one PPV, and two patients (11.1%) carried two different PPVs each. Nineteen out of the 20 PPVs identified were localized in SCN5A and one in SCN2B.

The vast majority of the PPVs identified were missense (70%). We also detected 2 nonsense variations (10%), 3 insertions or deletions causing frameshifts (15%), and one splicing variation (5%). The three frameshifts (p.R569Pfs*151, p.E625Rfs*95 and p.R1623Efs*7) were identified in SCN5A. These were not found in any of the databases consulted (see Methods), and were thus considered potentially pathogenic (see below). The other 16 rare variations identified inSCN5A had been previously described, and hence were also considered potentially pathogenic. Fourteen of them had been identified in BrS patients. Of these, 6 had also been identified in individuals diagnosed with other cardiac electric diseases (i.e. Sick Sinus Syndrome, Long QT Syndrome, Sudden Unexplained Nocturnal Death Syndrome or Idiopathic Ventricular Fibrillation [2,15,16,20,21,25]). The other 2, p.P1725L and p.R1898C, had only been associated with Long QT Syndrome or found in Exome Variant Server with a MAF of 0.0079%, respectively. Furthermore, we identified a variation in SCN2B (c.632A>G in exon 4 of the gene, resulting in p.D211G) which was considered pathogenic. This patient was included within our cohort, but the functional characterization of channels expressing SCN2B p.D211G was object of a previous study from our group [7]. We also identified a nonsense variation in RANGRFwhich has been formerly reported as rare genetic variation of unknown significance [29].

Additionally, we screened the relatives of those probands carrying a PPV. We analysed a total of 129 relatives, 69 of which (53.5%) were variation carriers. Genotype-phenotype correlations evidenced that 8 of the families displayed complete penetrance (S3 Table). Additionally, no relatives were available for one of the probands carrying a PPV, thus hampering genotype-phenotype correlation assessment. The other 12 families showed incomplete penetrance.

 

MLPA analysis

The 37 patients with negative results after the genetic screening of the 14 BrS-associated genes underwent MLPA analyses of SCN5A. This technique did not reveal any large exon deletion or duplication in this gene for any of the patients.

 

SCN5A p.R569Pfs*151 (c.1705dupC), a novel PPV

A 41-year-old asymptomatic male presented a type 3 BrS ECG which was suggestive of BrS. Flecainide challenge unmasked a type 1 BrS ECG (Fig 1A, left), which was also spontaneously observed sometimes during medical follow up. Sequencing of SCN5A revealed a duplication of a cytosine at position 1705 (c.1705dupC; Fig 1A, right), which originated a frameshift that lead to a truncated Nav1.5 channel (p.R569Pfs*151). The proband’s sister also carried this duplication, but had never presented signs of arrhythmogenesis. The proband’s twin daughters were also variation carriers, displayed normal ECGs and, to date, are asymptomatic (Fig 1A, middle). Thus, p.R569Pfs*151 represents a novel genetic alteration in the Nav1.5 channel that could potentially lead to BrS, but with incomplete penetrance.

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Fig 1. Characteristics of the probands carrying non-reported potentially pathogenic variations (PPVs) in SCN5A and their families.

Left: Electrocardiograms of the probands: (A) patient carrying the p.R569Pfs*151 variation, showing the ST elevation characteristic of BrS in V1 at the time of the flecainide test; (B) patient carrying the p.E625Rfs*95 variation, showing the spontaneous ST elevation characteristic of BrS in V1 and V2; and (C) patient carrying the p.R1623Efs*7 variation, showing the spontaneous ST elevation characteristic of BrS in V1 and V2. Middle: Family pedigrees. Open symbols designate clinically normal subjects, filled symbols mark clinically affected individuals and question marks identify subjects without an available clinical diagnosis. Plus signs indicate the carriers of the PPVs and minus signs, non-carriers. The crosses mark deceased individuals and arrows identify the proband. Right: Detail of the electropherograms obtained after SCN5Asequence analysis of a control subject (left panels) and of the probands (right panels).

http://dx.doi.org:/10.1371/journal.pone.0132888.g001

SCN5A p.E625Rfs*95 (c.1872dupA), a novel PPV

A 51-year-old asymptomatic male was diagnosed with BrS since he presented a spontaneous ST segment elevation in leads V1 and V2 characteristic of type 1 BrS ECG (Fig 1B, left). The sequencing of SCN5A evidenced an adenine duplication at position 1872 (c.1872dupA, Fig 1B, right). This genetic variation results in a truncated Nav1.5 channel (p.E625Rfs*95). The genetic analysis of the proband’s relatives proved that only her mother carried the variation (Fig 1B, middle). She was asymptomatic, but a BrS ECG was unmasked upon ajmaline challenge. The proband’s sister was found dead in her crib at 6 months of age, which suggests that her death might be compatible with BrS. Therefore, the p.E625Rfs*95 variation in the Nav1.5 channel represents a novel genetic alteration potentially causing BrS.

SCN5A p.R1623Efs*7 (c.4867delC), a novel PPV

The proband, a 31-year-old male, was admitted to hospital after suffering a syncope. His baseline 12-lead ECG showed a ST segment elevation in leads V1 and V2 that strongly suggested BrS type 1 (Fig 1C, left). A deletion of the cytosine at position 4867 (c.4867delC) was observed upon SCN5A sequencing (Fig 1C, right). This base deletion leads to a frameshift that originates a truncated Nav1.5 channel (p.R1623Efs*7). Genetic screening of his parents and sisters evidenced that none of them carried this novel variation (Fig 1C, middle). None of them had presented any signs of arrhythmogenicity, nor had a BrS ECG. Nevertheless, in uterogenetic analysis of one of his daughters proved that she had inherited the variation. She died when she was 1 year of age of non-arrhythmogenic causes. Hence, the p.R1623Efs*7 variation in the Nav1.5 channel is a novel genetic alteration originated de novo in the proband that could potentially lead to BrS.

Synonymous and common genetic variations portrayal

In our cohort, we identified 40 single nucleotide variations which were common genetic variants and/or synonymous variants (S2 Table). Twenty-nine had a minor allele frequency (MAF) over 1%, and were thus considered common genetic variants.

We also identified 11 variants with MAF less than 1%. Of them, 9 were synonymous variants, what made us assume that they were not disease-causing. Four of these synonymous variants were not found in any of the databases consulted, and thus their MAF was considered to be less than 1%. Each of these synonymous variations was identified in 1 patient of the cohort. A similar proportion of individuals carrying these novel variations was detected upon sequencing of 300 healthy Spanish individuals (600 alleles). The remaining 2 variants were missense, and although they had either a MAF of less than 1% or an unknown MAF according to the Exome Variant Server and dbSNP websites, they were common in our cohort (29.2 and 50%, respectively; S2 Table), and a similar MAF was detected in a Spanish cohort of healthy individuals (26.7% and 48.8%, respectively).

Influence of phenotype and age on PPV discovery

To assess if a connection existed between the probands’ phenotype and the PPV detection yield, we classified the patients in our cohort according to their ECG (spontaneous or induced type 1), the presence of BrS cases within their families, and the presence/absence of symptoms. Even though the overall PPV detection yield was 32.7%, it was even higher for symptomatic patients (Fig 2). Indeed, in this group of patients, having a family history of BrS was identified as a factor for increased PPV discovery yield. In the case of absence of BrS in the family, the variation discovery yield was almost double for those patients having a spontaneous type 1 BrS ECG than for patients with drug-induced type 1 ECG (45.5% vs 25%, respectively). In addition, we identified a PPV in 44.4% of the asymptomatic patients who presented family history of BrS and a spontaneous type 1 BrS ECG. When the patient presented drug-induced type 1 ECG or in the absence of family history of BrS, the PPV discovery yield was of around 15%.

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Fig 2. Influence of the phenotype on PPV discovery yield.

Bar graph comparing the PPV detection yield in 8 different clinical categories (stated below the graph). Each bar shows the total number of patients for each clinical category divided in those with a PPV (black) and those without an identified PPV (white). The number of patients (in brackets) and percentages are given. Pos, positive; Neg, negative; Spont, spontaneous type 1 BrS ECG; Drug, drug-induced type 1 BrS ECG; n, number of patients.

http://dx.doi.org/:10.1371/journal.pone.0132888.g002

We also investigated the role of age on the PPV occurrence. No significant age differences were observed between variation carriers and non-carriers (38.6±10.3 and 43.5±14.4, respectively, p = 0.16). However, the PPV discovery yield was higher for patients with ages between 30 and 50 years: out of the total of patients carrying a PPV, 83.3% of the patients were in this age range, while 11.1% were younger and 5.6% were older patients (Fig 3A, upper panel). The PPV discovery yield was significantly higher for symptomatic than for asymptomatic patients (42.3% vs 24.1%, respectively; Fig 3A, lower panels).

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Fig 3. Influence of the age on PPVs discovery yield.

(A) Pie charts showing the distribution of patients in the overall population as well as in the categories of symptomatic and asymptomatic patients regarding PPV discovery. The percentage and the number of patients (in brackets) are given for each group. The small pie charts correspond to the age distribution of patients with an identified PPV. (B) Bar graphs of the PPV detection yields obtained for each of the age groups (< 30 years, 30–50 years and > 50 years). Numbers inside each bar correspond to the number of patients carrying a PPV for each category and the percentages represent the variation detection yield.

http://dx.doi.org:/10.1371/journal.pone.0132888.g003

Noteworthy, in the 30–50 age range, 52.9% (9/17) of the symptomatic patients and 35.3% (6/17) of asymptomatic patients carried one PPV (Fig 3B, middle). Additionally, 40% (2/5) of the symptomatic young patients (< 30 years) were variation carriers, while no PPVs were identified in asymptomatic patients within this age range.

Overall, 55 unrelated Spanish patients clinically diagnosed with BrS were included in our study.Table 1 shows the demographics of this cohort, and Table 2 and S1 Table show the clinical and genetic characteristics of all the patients included in the study. The mean age at clinical diagnosis was of 41.9±13.3 years. Although the majority of patients were males (74.5%), their age at diagnosis was not different than that of females (41.8±12.1 years and 42.3±16.3 years, respectively; p = 0.92). A type 1 BrS ECG was present spontaneously in 37 patients (67.3%), and drug challenge revealed a type 1 BrS ECG for the remaining 18 patients (32.7%). Almost half of the patients had experienced symptoms, including 2 SCD and 4 aborted SCD. Patients who had not previously experienced any signs of arrhythmogenicity despite having a BrS ECG were considered asymptomatic. Comparison of symptomatic vs asymptomatic patients evidenced a similar percentage of males (73.1% and 75.9%, respectively). However, the mean age at diagnosis was different between the two groups of patients (37.7±14.3 and 45.7±11.4, respectively; p<0.05).

Discussion

To the best of our knowledge, this is the first comprehensive genetic evaluation of 14 BrS-susceptibility genes and MLPA of SCN5A in a Spanish cohort. Well delimited BrS cohorts from Japan, China, Greece and even Spain have been genetically studied [24,3032]. Additionally, an international compendium of BrS genetic variations identified in more than 2100 unrelated patients from different countries was published in 2010 [3]. However, all these studies screenedSCN5A exclusively. In 2012, Crotti et al. reported the spectrum and prevalence of genetic variations in 12 BrS-susceptibility genes in a BrS cohort [5]. However, this study included patients of different ethnicity. Here, we report the analysis of 14 genes which has been conducted on a well-defined BrS cohort of the same ethnicity.

Our results confirm that SCN5A is still the most prevalent gene associated with BrS. Indeed,SCN5A-mediated BrS in our cohort (30.9%) is higher than the proportion described in other European reports [3,23], where a potentially causative variation is identified in only 20–25% of BrS patients. The reason for this discrepancy is unclear but could point towards a higher prevalence of SCN5A PPVs in the Spanish population or to selection bias. Additionally, we identified a genetic variation in SCN2B (c.632A>G, which results in p.D211G). We have formerly published the comprehensive electrophysiological characterization of this variation, and showed that indeed this variation could be responsible of the phenotype of the patient, thus linking SCN2B with BrS for the first time [7]. Also, we identified a variation in RANGRF. This variation (c.181G>T leading to p.E61X) had been previously reported in a Danish atrial fibrillation cohort [33]. Surprisingly, the authors reported an incidence of 0.4% for this variation in the healthy Danish population, which brought into question its pathogenicity. Our finding of this variation in an asymptomatic patient displaying a type 2 BrS ECG also points toward considering it as a rare genetic variation with a potential modifier effect on the phenotype but not clearly responsible for the disease [29].

No PPVs were identified in the other genes tested. Certainly, it is well accepted that the contribution of these genes to the disease is minor, and thus should only be considered under special circumstances [13,34]. In addition, recent studies have questioned the causality of variations identified in some of these minority genes [35].

We also used the MLPA technique for the detection of large exon duplications and/or deletions in SCN5A in patients without PPVs, and no large rearrangements were identified. This is in accordance with previous reports, which revealed that such imbalances are uncommon [810].

Kapplinger et al. [3] reported a predominance of PPVs in transmembrane regions of Nav1.5. Indeed, it has been proposed that most rare genetic variations in interdomain linkers may be considered as non-pathogenic [36]. In contrast, PPVs identified in this study are mainly located in extracellular loops and cytosolic linker regions of Nav1.5 (Fig 4). Additionally, 2 of our non-previously reported frameshifts are located in the DI-DII linker. These 2 genetic variations lead to truncated proteins, which would lack around 75% of the protein sequence, and thus are presupposed to be pathogenic.

thumbnail

Fig 4. Nav1.5 channel scheme showing the relative position of the SCN5A PPVs identified in our cohort.

Open symbols indicate already described variations and closed symbols locate novel variations reported in this study. DI to DIV designate the 4 domains of the protein, and numbers 1–6 identify the different segments within each domain. Crosses mark the voltage sensor.

http://dx.doi.org:/10.1371/journal.pone.0132888.g004

In our cohort, we have identified 40 synonymous or common genetic variations, 4 of which have not been previously reported. These variations are gradually becoming more and more important in the explanation of certain phenotypes of genetic diseases. Only a few common variations identified here are already published as phenotypic modifiers [37,38]. The effect of these and other common variants identified in our cohort on BrS phenotype should be further studied.

Unexpectedly, almost 40% (7/18) of the PPV carriers did not present signs of arrhythmogenicity. We also performed genotype-phenotype correlations of the PPVs identified in the families (S3 Table). These studies uncovered relatives, most of whom were young individuals, who carried a familial variation but had never exhibited any clinical manifestations of the disease. This is in agreement with Crotti et al. and Priori et al. [5,23], who postulated that a positive genetic testing result is not always associated with the presence of symptoms. Indeed, the existence of asymptomatic patients carrying genetic variations described to cause a severe Nav1.5 channel dysfunction has been reported [39]. The identification of silent carriers is of paramount importance since it allows the adoption of preventive measures before any lethal episode takes place. Unknown environmental factors, medication and modifier genes have been suggested to influence and/or predispose to arrhythmogenesis [11]. Hence, this group of patients has to be cautiously followed in order to avoid fatal events.

Our studies on the connection between patients’ phenotype and the PPV detection yield highlighted the presence of symptoms as a factor for an increased variation discovery yield. Within the group of symptomatic individuals, a PPV was identified in a higher proportion of patients displaying a spontaneous type 1 BrS ECG than for patients showing a drug-induced ECG. Likewise, within the asymptomatic patients with family history of BrS, those who presented spontaneous type 1 BrS ECG carried a PPV more often than those with a drug-induced ECG (Fig 2). Referring to age, the vast majority (17/20, 85%) of the PPVs were identified in patients around their fourth decade of age (30–50 years). This is in accordance with the accepted mean age of disease manifestation. Moreover, in this age range, more than 50% of the patients who presented symptoms carried a variation that could be pathogenic (Fig 3). Importantly, 35.3% of asymptomatic patients of around 40 years of age also carried one of such variations. These data highlight the importance of performing a genetic test even in the absence of clinical manifestations of the disease, and particularly when in the 30–50 years range, which is in accordance with consensus recommendations [13,34].

In conclusion, we have analysed for the first time 14 BrS-susceptibility genes and performed MLPA of SCN5A in a Spanish BrS cohort. Our cohort showed male prevalence with a mean age of disease manifestation around 40 years. BrS in this cohort was almost exclusivelySCN5A-mediated. The mean PPV discovery yield in our Spanish BrS patients is higher than that described for other BrS cohorts (32.7% vs 20–25%, respectively), and is even higher for patients in the 30–50 years age range (up to 53% for symptomatic patients). All these evidences support the genetic testing, at least of SCN5A, in all clinically well diagnosed BrS patients.

 

Study Limitations

First of all, drug challenge tests were not performed for all the relatives who were asymptomatic variation carriers. This fact hampered their clinical diagnosis and represents an impediment to definitely assess the link between PPVs and BrS. These patients are nowadays under follow-up.

New PPVs have been identified in our cohort. The clinical information available for the families suggests that these new variations could be pathogenic. Still, in vitro studies of these variations are required in order to evaluate their functional effects and verify their pathogenic role. Additionally, genotyping in an independent cohort would help reduce the likelihood of type I (false positive) error in genetic variant discovery.

We have to acknowledge that the study set is relatively small. Consequently, the classification of patients according to the different clinical categories rendered rather small sub-groups, which may lead to over-interpretation of the results. Future studies will be directed to the genetic screening of additional Spanish BrS patients, which will probably reinforce the significance of the tendencies observed here.

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Role of the basal ganglia

Larry H Bernstein, MD, FCAP, Curator

Leaders in Pharmaceutical Intelligence

 

Series E. 2; 5.8

 

Ann Graybiel
Investigator, McGovern Institute
Professor, Department of Brain and Cognitive Science

Ann Martin Graybiel (born 1942) is an Institute Professor and a faculty member in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology. She is also an investigator at the McGovern Institute for Brain Research. She is an expert on the basal ganglia and the neurophysiology of habit formation, and her work is relevant to Parkinson’s disease, Huntington’s disease, obsessive–compulsive disorder, substance abuse and other disorders that affect the basal ganglia.

Graybiel’s work is uncovering neural deficits related to these disorders, as well as the role the basal ganglia play in guiding normal behavior.

Graybiel receives the Medal of Science

For much of her career, Graybiel has focused on the physiology of the striatum, a basal ganglia structure implicated in the control of movement, cognition, habit formation, and decision-making. In the late 1970s, Graybiel discovered that while striatal neurons appeared to be an amorphous mass, they were in fact organized into chemical compartments, which she termed striosomes.[1] Later research revealed links between striosomal abnormalities and neurological disorders, such as mood dysfunction in Huntingdon’s disease[2] and depletion of dopamine in Parkinson’s disease.[3]

Graybiel’s subsequent research demonstrated how modular organization of the striatum relates to cognition, learning, and habit formation. She found that neurons project from areas in the sensory and motor cortices governing the same body part and cluster together in the striatum, forming matrisomes.[4] Graybiel went on to show that matrisomes exist for each body part and were organized into loops connecting the neocortex, a region responsible for cognition, perception and motor control, to the brain stem, a region coordinating movement.[5]Studies of rodents and primates revealed that matrisomes were crucial to habit formation.[6][7]

In later work, Graybiel demonstrated, first in the striatum and later in the infralimbic cortex, that a task-bracket or “chunking” pattern of neuronal activity emerges when a habit is formed, wherein neurons activate when a habitual task is initiated, show little activity during the task, and reactivate when the task is completed.[7][8]

In more recent work, Graybiel has focused on identifying specific pathways underlying aspects of behavior such as habit formation, learning and cognition, and decision-making, including being the first to analyze the effect of dopamine depletion on the activity of neurons affected by Parkinson’s disease during behavioral tasks.[9][10]

Beyond movement

The basal ganglia are best known for their control of movement. Parkinson’s disease, for example, results from the degeneration of neurons that release the neurotransmitter dopamine within the striatum, the largest part of the basal ganglia. It is becoming clear, however, that the basal ganglia do more than just control movement. These structures have been implicated in psychiatric diseases and addiction, and damage to the basal ganglia can affect not only movement but also mood and cognition. Graybiel believes that this broad range of functions reflects the capacity of the basal ganglia to influence how we select actions–motor actions as well as actions of thought.

Career

Graybiel majored in biology and chemistry at Harvard University, receiving her bachelor’s degree in 1964.[11] After receiving an MA in biology from Tufts University in 1966, she began doctoral study in psychology and brain science at MIT under the direction of Hans-Lukas Teuber and Walle Nauta.[11] She received her PhD in 1971 and joined the MIT faculty in 1973.[12]

In 1994, she was named the Walter A. Rosenblith Professor Neuroscience in the Department of Brain and Cognitive Science and was named an Investigator at the MIT McGovern Institute for Brain research in 2001.[12] She was named Institute Professor in 2008.[13]

In 2001, Graybiel was awarded the President’s National Medal of Science for “her pioneering contributions to the understanding of the anatomy and physiology of the brain, including the structure, chemistry, and function of the pathways subserving thought and movement.”[14] In 2012, she was awarded the Kavli Prize in Neuroscience, along with Cornelia Bargmann and Winfried Denk, “for elucidating basic neuronal mechanisms underlying perception and decision.” [15]

She is a member of the US National Academy of Sciences, the American Academy of Arts and Sciences, and the Institute of Medicine.[12]

References[edit]

Wikimedia Commons has media related to Ann Graybiel.
  1. Jump up^ Graybiel, AM; Ragsdale, Jr., CW (November 1978). “Histochemically distinct compartments in the striatum of human, monkey, and cat demonstrated by acetylthiocholinesterase staining”. Proc Natl Acad Sci U S A (1978) 75 (11): 5723–26. doi:10.1073/pnas.75.11.5723. PMID 103101. Retrieved 23 October 2014.
  2. Jump up^ Tippet, LJ; Waldvogel, HJ; Thomas, SJ; Hogg, VM; van Roon-Mom, W; Synek, BJ; Graybiel, AM; Faull, RL (Jan 2007). “Striosomes and mood dysfunction in Huntington’s disease”.Brain 130 (1): 206–21. doi:10.1093/brain/awl243. PMID 17040921. Retrieved 23 October 2014.
  3. Jump up^ Roffler-Tarlov, S; Graybiel, AM (5 Jan 1984). “Weaver mutation has differential effects on the dopamine-containing innervation of the limbic and nonlimbic striatum”. Nature 307: 62–66. doi:10.1038/307062a0. Retrieved23 October 2014.
  4. Jump up^ Flaherty, AW; Graybiel, AM (1991). “Corticostriatal transformations in the primate somatosensory system. Projections from physiologically mapped body-part representations.”. J Neurophysiol 66: 1249–63. Retrieved 23 October2014.
  5. Jump up^ Graybiel, AM; Toshihiko, A; Flaherty, AW; Kimura, M (1994). “The basal ganglia and adaptive motor control”. Science 265 (5180): 1826–31. doi:10.1126/science.8091209. JSTOR 2884650.
  6. Jump up^ Illing, R.-B.; Graybiel, AM (1994). “Pattern formation in the developing superior colliculus: Ontogeny of the periodic architecture in the intermediate layers”. Journal of Comparative Neurology 340 (3): 311–27.doi:10.1002/cne.903400303. Retrieved 23 October 2014.
  7. ^ Jump up to:a b Graybiel, AM (1998). “The Basal Gangila and Chunking of Action Repertoires”. Neurobiology of Learning and Memory 340 (3): 119–36. doi:10.1006/nlme.1998.3843. PMID 9753592. Retrieved 23 October 2014.
  8. Jump up^ Smith, KS; Graybiel, AM (July 2013). “A dual operator view of habitual behavior reflecting cortical and striatal dynamics”. Neuron 79 (2): 361–74. doi:10.1016/j.neuron.2013.05.038. Retrieved 23 October 2014.
  9. Jump up^ Hernandez, LF; Kubota, Y; Hu, D; Howe, MW; Lemaire, N; Graybiel, AM (2013). “Selective effects of dopamine depletion and L-DOPA therapy on learning-related firing dynamics of striatal neurons”. Journal of Neuroscience 33(11): 4782–95. doi:10.1523/JNEUROSCI.3746-12.2013. Retrieved 23 October 2014.
  10. Jump up^ Trafton, Anne (12 March 2013). “MIT News”. Breaking down the Parkinson’s pathway. Retrieved 23 October 2014.
  11. ^ Jump up to:a b “Neuroscience Laureate Biographies”. The Kavli Foundation. Retrieved 23 October 2014.
  12. ^ Jump up to:a b c “Ann Graybiel”. McGovern Institute for Brain Research at MIT. Retrieved 23 October 2014.
  13. Jump up^ Ann Graybiel named Institute Professor – MIT News Office. Web.mit.edu (2008-11-03). Retrieved on 2012-06-25.
  14. Jump up^ US NSF – The President’s National Medal of Science: Recipient Details. Nsf.gov. Retrieved on 2012-06-25.
  15. Jump up^ The Kavli Prize. Kavliprize.no. Retrieved on 2012-06-25.

Ann Graybiel: McGovern Institute Investigator

https://www.youtube.com/user/mittechtv

http://www.youtube.com/watch%3Fv%3D0Qi0B_jAMmw

 

https://www.youtube.com/playlist%3Flist%3DPL6D9E1BD5963BBF0C

 

Why We Do What We Do

http://www.technologyreview.com/article/522521/why-we-do-what-we-do/

Institute Professor Ann Graybiel, PhD ’71, has transformed our understanding of a “primitive” area of the brain.

Institute Professor Ann Graybiel, PhD ’71, is at the forefront of this research, having devoted much of a career now in its fifth decade to understanding a seemingly humble set of brain structures called the basal ganglia. Once known only for helping to control movement, this region deep within the brain is now believed to play fundamental roles in how we learn, process emotions, make decisions, and adopt habits. And that shift in thinking is due in no small part to the research done in Graybiel’s lab.

Her work has already yielded insights into patterns of brain activity associated with movement disorders and psychiatric diseases. Recent studies using light to control individual brain cells, for instance, show how shutting off some of this activity can control habit formation or pessimistic decision-­making. Although this technique, known as optogenetics, is still just a research tool, she is convinced that such technological advances hold therapeutic promise—and that learning about these deep patterns in the brain will also be important for everyone who wonders: What makes me do what I do?

http://www.scientificamerican.com/author/ann-m-graybiel/

 

QnAs with Ann M. Graybiel

Nicholette ZeliadtScience Writer

PNAS Oct 2013; 110(43).17166, http://dx.doi.org:/10.1073/pnas.1315012110

Ann M. Graybiel, a neuroscientist at the Massachusetts Institute of Technology and a National Academy of Sciences member, uncovers the neurobiological basis of how habits form and provides clues as to how habits can be changed.

PNAS: What is a habit?

Graybiel: A habit is something that we do routinely, that seems almost automatic, and that is fairly repetitive under certain circumstances. There are also extreme habits—such as addictions—and it’s an unresolved issue in the field whether the mechanisms underlying these are similar to those of our normal habits. Psychologists define habits as the kinds of behavior that a person does when acting as though no longer mindful of the outcome of the behavior. If we get to the point in a behavior at which it doesn’t matter whether the outcome is good or bad, then the behavior is almost automatic, not outcome-determined. We are using this outcome-sensitivity index to try to help us “define” a habit in our experiments.

 

PNAS: Many of your studies have involved recording the electrical activity in the striatum (a region of the basal ganglia) in rodents as they learn to navigate a maze to reach a reward and eventually develop a habit. What have you learned from these experiments?

Graybiel: We recorded in the part of the striatum that is active during motor behaviors and found that as animals learn to run mazes habitually, the neurons in this part of the striatum at first are active pretty much all during the runs; but then, as the animals become more automatic, the striatal neurons are mainly active at the beginning and end of the maze runs. It’s as though that entire habitual behavior becomes packaged in the neural representation, as though these beginning and end signals form a bracketing code for the learned behavior. And that reminded me of a very famous analogy that the psychologist George Miller made years ago. He said that it’s hard for us to remember long sequences of letters or numbers—for example, a really long phone number—and so what we do is “chunk” all those numbers together, and then all we have to do is remember the package. We think that the task-bracketing pattern we see might be a sign that once the behavior becomes habitual, it becomes chunked by the sensorimotor part of the striatum.

When we then recorded neural activity in the part of the striatum that former researchers had found to function in relation to being mindful of outcome, we didn’t find that bracketing pattern. Instead, what Katy Thorn in the laboratory found was that the strongest activity occurred when the animals had to make a decision about which way to turn in the maze. So we gradually built up the idea that there are different striatum-based neural circuits; some of them take care of one control feature, like forming the chunking pattern, at the same time that another circuit is encoding the deliberative part. Most interesting, these functional assignments actually have signatures in the spike patterns of the neurons. We hope that we are beginning to be able to link global population activation patterns to behaviors, and that this could turn out to be quite important when we face the issue of how to modify habits.

PNAS :In a 2012 PNAS paper, you disrupted the activity in one of these circuits. What did you find?

Graybiel: Kyle Smith and I recorded in two regions of the brain that are known to be habit-related: one was in the striatum, in its sensorimotor part where we had found that task-bracketing pattern, and the other one was in the prefrontal cortex. We found the same task-bracketing pattern in the sensorimotor striatum that we’ve now found over and over. However, in the prefrontal cortex we found that a bracketing pattern only formed very late in the learning process, when the behavioral habit became engrained. This made us think that the final settling of the bracketing pattern in the cortex might be necessary for the behavior to get set as a habit. So we tried to inhibit that small cortical zone to see whether the animals still would have a habit. We found they didn’t. Then, when we allowed the animal to develop a new habit, and we again inhibited that piece of cortex, the animal reverted to the original habit—it wasn’t gone after all! What the paper shows is that even though a behavior seems to be automatic, there is a bit of brain—in the case of our paper, it’s in the medial prefrontal cortex—that is monitoring things online. So, in fact, a behavior that seems automatic isn’t really automatic, because there’s a piece of brain that cannot only monitor the habit but also can veto the performance of the habit.

PNAS: How does understanding the neurobiology of the habit system advance our understanding of neurologic and psychiatric disorders?

Graybiel: In a number of neuropsychiatric conditions—for example, obsessive-compulsive disorder, Tourette syndrome, many forms of autism, schizophrenia—patients can develop repetitive behaviors, and these stereotyped behaviors are classic features of these disorders. These are behaviors that are repeated, semiautomatically, and they are under very poor volitional, deliberative, attentional control. These repetitive, overly focused behaviors may not rely on exactly the same circuits as “normal” habits, but the fundamental operation of the involved circuits may be similar. This is something we are intensely interested in.

 

2012 Neuroscience Laureate Biographies – CI Bargmann

Cornelia Isabella Bargmann was born in 1961 in Virginia and raised in Athens, Georgia, where she attended the University of Georgia. She then went north to study cancer-signalling genes and cloned the oncogene HER2, a key factor in breast cancer, in the laboratory of Robert Weinberg at the Whitehead Institute, Massachusetts Institute of Technology.

After receiving her Ph.D. in 1987, Professor Bargmann transferred to the laboratory of H. Robert Horvitz, at MIT, where she became acquainted with the tiny worm C. elegans. Professor Horvitz had already made major contributions to understanding neural development using C. elegans as a simple model organism. For this he shared the 2002 Nobel Prize in Physiology or Medicine with Sydney Brenner and John Sulston “for their discoveries concerning genetic regulation of organ development and programmed cell death”. Professor Bargmann then embarked upon what was to become a lifetime mission to define how genes and the environment influence behavior by dissecting the neural circuitry of C. elegans and the genes, receptors and signaling molecules involved in such behaviour as feeding and responses to odours.

In 1995 California beckoned, and Cornelia Bargmann took up an appointment as assistant professor at the University of California, San Francisco. In 1998, she was promoted to Professor, and in 1999 was named vice chair of the Department of Anatomy. In 2004 she returned to the east coast to take up the position of head of the Lulu and Anthony Wang Laboratory of Neural Circuits and Behaviour at Rockefeller University, New York, where she is now Torsten N. Weasel Professor and a Howard Hughes Medical Investigator. Rockefeller University president Paul Nurse welcomed her arrival saying, “Cori Bargmann typifies the Rockefeller scientist: she is bold and highly original in her thinking and her approach to studying the brain and other components of the nervous system”.

Professor Bargmann has received numerous awards, including the Charles Judson Herrick Award for comparative neurology in 2000, the Dargut and Milena Kemali International Prize for Research in the Field of Basic and Clinical Neurosciences in 2004, and the Richard Lounsbery Award from the US and French National Academies of Sciences in 2009. She is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the European Molecular Biology Organisation.

Professor Bargmann has trained many students and postdocs in cutting-edge techniques and encouraged them to share her enthusiasm for research. She is as renowned for the quality of her presentations and breadth of knowledge as for her research.

 

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Writer and curator: Larry H. Bernstein, MD, FCAP and
Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013-01-23/larryhbern/Regulation-of-somatic-stem-cell-function/

There is an explosion of work-in-progress in applications to regenerative medicine using inducible pluripotent stem cells in both endothelial and cardiomyocyte postischemic repair, and also in post bone marrow radiation restoration, with benefits and hazards.  The following article is quite novel in that it deals with stem cell regulation by DNA methylation.  Therefore, it deals with the essentiality of methylation of DNA in epigenetic regulation.

This is the fourth discussion of a several part series leading from the genome, to protein synthesis (1), posttranslational modification of proteins (2), examples of protein effects on metabolism and signaling pathways (3), and leading to disruption of signaling pathways in disease (4), and effects leading to mutagenesis.

1.  A Primer on DNAand DNA Replication

2.  Overview of translational medicine

3.  Genes, proteomes, and their interaction

4. Regulation of somatic stem cell Function

5.  Proteomics – The Pathway to Understanding and Decision-making in Medicine

6.  Genomics, Proteomics and standards

7.  Long Non-coding RNAs Can Encode Proteins After All

8.  Proteins and cellular adaptation to stress

9.  Loss of normal growth regulation

 

Posttranslational modification is a step in protein biosynthesis. Proteins are created by ribosomes translating mRNA into polypeptide chains. These polypeptide chains undergo
PTM before becoming the mature protein product.

Regulation of somatic stem cell Function by DNA Methylation and Genomic Imprinting

Mo Li1, Na Young Kim1, Shigeo Masuda1 and Juan Carlos izpisua Belmonte1,2 1Salk institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA 92037, USA. 2Center of Regenerative Medicine in Barcelona, Dr Aiguader, 88, 08003 Barcelona, Spain. Corresponding author email: mli@salk.edu

Cell & Tissue Transplantation & Therapy 2013:5 19–23
http://dx.doi.org/10.4137/CTTT.S12142
This article is available from http://www.la-press.com

Abstract:

Epigenetic regulation is essential for self-renewal and differentiation of somatic stem cells, including

  • hematopoietic stem cells (HSCs) and
  • neural stem cells (NSCs).

The role of DNA methylation, a key epigenetic pathway,

  • in regulating somatic stem cell function
    • under physiological conditions and during aging

has been intensively investigated.

Accumulating evidence highlights the dynamic nature of

  • the DNAmethylome
    • during lineage commitment of somatic stem cells and
  • the pivotal role of DNAmethyltransferases in
    • stem cell self-renewal and differentiation.

Recent studies on genomic imprinting have shed light on

  • the imprinted gene network (IGN) in somatic stem cells,
  1. where a subset of imprinted genes remain expressed and
  2. are important for maintaining self-renewal of these cells.

Together with emerging technologies, elucidation of the epigenetic mechanisms regulating somatic stem cells with normal or pathological functions may contribute to the development of regenerative medicine.

Keywords: somatic stem cells, epigenetics, DNA methylation, genomic imprinting, hematopoietic stem cells, neural stem cells

Introduction

In adult animals, somatic stem cells (also known as adult stem cells) are responsible for maintaining tissue homeostasis and participate in tissue regeneration under injury conditions. Self-renewal and differentiation are two important aspects of somatic stem cell function. Epigenetic mechanisms underlying these processes have been intensively investigated. With the increasing ability

  • to identify and manipulate somatic stem cell populations from diverse tissues,
  • it is possible to dissect the epigenetic pathways that are
  1. either unique for a specific tissue or
  2. universally important in regulating stemness and differentiation.

Epigenetic control of somatic stem cell function exists at various levels, including

  • DNA methylation,
  • histone modification, and
  • higher-order chromatin structure dynamics.

Here, we focus on recent progress in our understanding of how

  • DNA methylation regulates somatic stem cell function.

DNA Methylation and stem cell Function

The role of DNA methylation in somatic stem cell compartments has gained increasing attention. Recent  evidence has shown that

  • DNA methylation is dynamically regulated during somatic stem cell differentiation and aging.1

A study of methylomes of human hematopoietic stem cells (HSCs) and two mature hematopoietic lineages,

  • including B cells and neutrophils, showed that
    • hypomethylated regions of lineage-specific genes often become methylated in opposing lineages, and that
    • progenitors display an intermediate methylation pattern

that is poised for lineage-specific resolution.2

Another study compared genome-wide promoter DNA methylation in human cord blood hematopoietic progenitor cells (HPCs) with

  • that in mobilized peripheral blood HPCs from aged individuals.

It was found that aged HPCs lose DNA methylation in a subset of genes that are hypomethylated in differentiated myeloid cells and

  • gain de novo DNA methylation at polycomb repressive complex 2 (PRC2) target sites.3

It was hypothesized that such epigenetic changes contribute to age-related loss of HSC function, such as a bias toward myeloid lineages. Recently, Beerman et al. studied the global DNA methylation landscape of HSCs in the context of

  • age-associated decline of HSC function.4

Over- all, the DNA methylation landscape remains stable during HSC ontogeny. However, HSCs isolated from old mice display higher global DNA methylation. Interestingly, they observed

  • localized DNA methylation changes in genomic regions associated with hematopoietic lineage differentiation.

These methylation changes preferentially map to genes

  • that are expressed in downstream progenitor and effector cells.

For example, genes that are important for the lymphoid and erythroid lineages

  • become methylated in “old” HSCs,

which is consistent with

  • the decline of lymphopoiesis and erythropoiesis during aging.

Additionally, inducing HSC proliferation by 5-fluorouracil treatment or

  • by limiting the number of transplantedHSCs
    • recapitulates the functional decline and DNA methylation changes during physiological aging.

A closer examination of the overlapping genes with significant DNA methylation changes during aging or enforced proliferation showed

  • an enrichment of DNA hypermethylation at PRC2 target loci,

echoing the observation by Bocker et al. in human HSCs.

Interestingly, a recent report showed that epigenetic alterations such as DNA hypermethylation that are accrued during aging,

  • can be fully reset by somatic reprogramming,

raising an interesting possibility that these aging-related epigenetic defects may be reserved by small molecules.5

Methylation of cytosines at CpG dinucleotides is catalyzed by three key enzymes.

DNA (cytosine-5)- methyltransferase 1 (DNMT1) is responsible for maintaining DNA methylation patterns during DNA replication

  • by methylating the newly synthesized hemi-methylated DNA.

The other two DNA methyltransferases, DNMT3a and DNMT3b,

  • are not DNA replication-dependent and can methylate fully unmethylated DNA de novo.

They are responsible for establishing new DNA methylation patterns during development.

DNMT3a, a gene required for neurogenesis,

  • is expressed in postnatal neural stem cells (NSCs).

In NSCs, DNMT3a methylates non-proximal promoter regions, such as gene bodies and intergenic regions. Surprisingly, rather than silencing gene expression,

DNMT3a-mediated DNA methylation in gene bodies antagonizes Polycomb-dependent repression and

  • facilitates the expression of neurogenic genes.6

The role of DNMT3a in HSCs has also been investigated. Both Dnmt3a and Dnmt3b are expressed in HSCs. An earlier study did not identify any defects in HSC function when Dnmt3a or Dnmt3b was removed.  However,

  • HSCs lackingboth of these de novomethyltransferases
    • fail to self-renew, yet retain the capacity to differentiate.7

A more recent study re-examined

  • the consequences of Dnmt3a loss in HSCs and
  • uncovered a progressive defect in differentiation that is only manifested during serial transplantation.8

At the molecular level, while Dnmt3a loss results in the expected hypomethylation at some loci,

  • it counterintuitively causes hypermethylation in even more regions.8

This seemingly paradoxical result echoes the  unconventional role of Dnmt3a in transcriptional  activation in NSCs (as discussed above). Both cases suggest a more complex regulatory function of DNMT3a that is

  • beyond simply methylating DNA.

In contrast, the loss of Dnmt1 produces more dramatic and immediate phenotypes in HSCs, manifested

  • in premature HSC exhaustion and
  • block of lymphoid differentiation,

highlighting the distinct requirements for different DNA methyltransferases in HSCs.9,10

Genomic Imprinting and stemness

DNA methylation also underlies genomic imprinting, which is an

  • evolutionarily conserved epigenetic mechanism of ensuring appropriate gene dosage during development.

One allele of the imprinted genes is

  • epigenetically marked by DNA methylation to be silenced according to the parental origin.

The pattern of imprinting

  • is established in germ cells and maintained in somatic cells.

Imprinted genes are thought to play critical roles in organismal growth and are relatively downregulated after birth.11 Recently, a series of reports demonstrated that

  • a subset of imprinted genes belonging to the purported imprinted gene network (IGN)12
  • remain expressed in somatic stem cells and
  • are important for maintaining self-renewal of these cells.

Through gene expression profiling, one group identified that several members of the IGN are expressed in

  1. murine muscle,
  2. epidermal, and
  3. long-term hematopoietic stem cells
  4. as well as in human epidermal and hematopoietic stem cells.13

In particular, the paternally expressed gene 3 (Peg3) gene was shown by another group

  • to mark cycling and quiescent stem cells in a wide variety of mouse tissues.14

The role of imprinted genes in regulating somatic stem cell function has been examined in two types of tissues.

In bronchioalveolar stem cells (BASCs), a lung epithelial stem cell population,

  • expression of IGN members is required for their self-renewal.

Bmi1, a polycomb repressive  complex 1 (PRC1) subunit,

  • is essential for controlling the expression of imprinted genes in BASCs without affecting their imprinting status.15

In Bmi1 mutant BASCs,  many members of the IGN become derepressed,

  • including p57, H19, Dlk1, Peg3, Ndn, Mest, Gtl2, Grb10, Plagl1, and Igf2.

Knockdown of p57, which is the most differentially expressed imprinted gene between normal and mutant BASCs,

  • partially rescues the self-renewal defect of lung stem cells.

Interestingly, insufficient levels of p57 also inhibit self-renewal of lung stem cells. Because p57 expression

  • remains monoallelic in Bmi1 knockdown cells,
  • Bmi1 is thought to maintain an appropriate level of expression from the expressed allele of p57.15

Another IGN member- delta-like homologue 1 (Dlk1) has been shown to be important for postnatal neurogenesis. Interestingly, in this context,

  • Dlk1 loses its imprinting in postnatal neural stem cells and niche astrocytes.16

These studies suggest that modulating IGN may represent another

  • epigenetic mechanism for balancing self-renewal and differentiation in somatic stem cells.

Thus, somatic stem cells either co-opt or remodel these developmental pathways involving the IGN

  • to fulfill the needs of tissue homeostasis during the adult stage.

In summary, several factors participate in regulating the epigenome of somatic stem cells.

Perturbations in the epigenome of somatic stem cells,

  • either during organismal aging or under pathological conditions,

will tip the balance between self-renewal and differentiation of somatic stem cells (Fig. 1). A detailed understanding of the mechanisms underlying these changes will likely result in novel therapeutic approaches targeting somatic stem cells.

Figure 1. The epigenome of somatic stem cells is regulated by diverse factors.

Future perspectives The epigenetic mechanisms governing self-renewal and differentiation of somatic stem cells are likely to be complex because of the diverse needs of different tissues. It would be interesting to determine whether a common mechanism, such as the IGN, exists across different somatic stem cells. Additionally, study- ing epigenetic pathways that are specific to one type of somatic stem cell requires the isolation of these cells and their differentiated progeny, which is more practical in model organisms than in humans. Along these lines, developing robust in vitro culture methods for human somatic stem cells and protocols for differentiating these cells into specific lineages are critical for uncovering epigenetic pathways that are unique to human somatic stem cells. In recent years, the field has seen a great improvement in methods of directed differentiation of human embryonic stem cells and induced pluripotent stem cells (iPSCs). For example, it is relatively straightforward to produce high-purity cell populations that resemble neural stem cells or mesenchymal stem cells from iPSCs.17

These methodologies not only are useful for studying the normal function of somatic stem cells, but also provide an exciting opportunity for understanding the role of somatic stem cells in disease pathology and a platform to screen for drugs. A recent study under- scored the usefulness of this approach. Liu et al. studied neural stem cells derived from Parkinson’s disease human iPSCs and uncovered previously unknown defects in nuclear morphology and epigenetic regulation in these derived NSCs.18 The cellular defects only menifest in “aged” neural stem cells, which is consistent with the fact that Parkinson’s disease pri- marily manifests in old age. More  importantly, this study identified neural stem cell as a potential target of therapeutic intervention for Parkinson’s disease.

Targeted modification of the human genome is  another technological advancement that is on the horizon to greatly facilitate the dissection of epige- netic pathways in somatic stem cells. Although gene targeting in somatic stem cells has been historically challenging, there have been encouraging successful reports following development of new genome-e diting technologies, such as Helper-dependent adenovi- ral vectors, TALENs, and CAS9/CRISPR. With the development of these new technologies, it seems that the stage has been set for a new wave of discoveries in epigenetic mechanisms of somatic stem cells.

References

1. Li M, Liu GH, Izpisua Belmonte JC. Navigating the epigenetic landscape of pluripotent stem cells. Nat Rev Mol Cell Biol. 2012;13(8):524–535.

2. Hodges E, Molaro A, Dos Santos CO, et al. Directional DNA methylation changes and complex intermediate states accompany lineage specificity in the adult hematopoietic compartment. Mol Cell. 2011;44(1):17–28.

3. Bocker MT, Hellwig I, Breiling A, Eckstein V, Ho AD, Lyko F. Genome- wide promoter DNA methylation dynamics of human hematopoietic progen- itor cells during differentiation and aging. Blood. 2011;117(19):e182–e189.

4. Beerman I, Bock C, Garrison BS, et al. Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging. Cell Stem Cell. 2013;12(4):413–425.

5. Wahlestedt M, Norddahl GL, Sten G, et al. An epigenetic component of hematopoietic stem cell aging amenable to reprogramming into a young state. Blood. 2013;121(21):4257–4264.

6. Wu H, Coskun V, Tao J, et al. Dnmt3a-dependent nonpromoter DNA methylation facilitates transcription of neurogenic genes. Science. 2010; 329(5990):444–448.

7. Tadokoro Y, Ema H, Okano M, Li E, Nakauchi H. De novo DNA meth- yltransferase is essential for self-renewal, but not for differentiation, in hematopoietic stem cells. J Exp Med. 2007;204(4):715–722.

8. Challen GA, Sun D, Jeong M, et al. Dnmt3a is essential for hematopoietic stem cell differentiation. Nat Genet. 2011;44(1):23–31.

9. Broske AM, Vockentanz L, Kharazi S, et al. DNA methylation protects hematopoietic stem cell multipotency from myeloerythroid restriction. Nat Genet. 2009;41(11):1207–1215.

10. Trowbridge JJ, Snow JW, Kim J, Orkin SH. DNA methyltransferase 1 is essential for and uniquely regulates hematopoietic stem and progenitor cells. Cell Stem Cell. 2009;5(4):442–449.

11. Wood AJ, Oakey RJ. Genomic imprinting in mammals: emerging themes and established theories. PLoS Genet. 2006;2(11):e147.

12. Lui JC, Finkielstain GP, Barnes KM, Baron J. An imprinted gene network that controls mammalian somatic growth is down-regulated during postna- tal growth deceleration in multiple organs. Am J Physiol Regul Integr Comp Physiol. 2008;295(1):R189–R196.

13. Berg JS, Lin KK, Sonnet C, et al. Imprinted genes that regulate early mam- malian growth are coexpressed in somatic stem cells. PLoS One. 2011; 6(10):e26410.

14. Besson V, Smeriglio P, Wegener A, et al. PW1 gene/paternally expressed gene 3 (PW1/Peg3) identifies multiple adult stem and progenitor cell popu- lations. Proc Natl Acad Sci U S A. 2011;108(28):11470–11475.

15. Zacharek SJ, Fillmore CM, Lau AN, et al. Lung stem cell self-renewal relies on BMI1-dependent control of expression at imprinted loci. Cell Stem Cell. 2011;9(3):272–281.

16. Ferron SR, Charalambous M, Radford E, et al. Postnatal loss of Dlk1 imprinting in stem cells and niche astrocytes regulates neurogenesis. Nature. 2011;475(7356):381–385.

17. Li W, Sun W, Zhang Y, et al. Rapid induction and long-term self-renewal of primitive neural precursors from human embryonic stem cells by small molecule inhibitors. Proc Natl Acad Sci U S A. 2011;108(20):8299–8304.

18. Liu GH, Qu J, Suzuki K, et al. Progressive degeneration of human neural stem cells caused by pathogenic LRRK2. Nature. 2012;491(7425):603–607.

 

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Larry H Bernstein, MD, FCAP, Curator

https://pharmaceuticalintelligence.com/6/7/2014/Health benefit of anthocyanins from apples and berries noted for men

After significant studies have been completed, particularly on a relationship between anthocyanins consumption and decreasd risk of Parkinson’s Disease in men, it is unclear why a comparable effect is not seen in women.  This would lead one to ask questions about predominant time course of development in relationship to androgen activity.  Pre- and postmenopausal status would seem to make no difference. It is reported that the anthocyanins cross the blood brain barrier.  There are other questions that need to be raised.  There is a decline in the production of transthyretin by the choroid plexus in the elderly – not sex related – with an elevation of homocysteine that is reciprocal to decline in transthyretin-RBP complex, that is related to AD.  This is mediated by cystathionine-beta synthase, and involves matrix metalloproteinases.  A mechanism for Parkinson’s Disease has been postulated to be related to Parkin gene expression, but how does this work, and why do we see the sex assymetry?

Eating flavonoids protects men against Parkinson’s disease

General DietMissed – Medical Breakthroughs • Tags: AnthocyaninFlavonoidHarvard University,HealthNeurologyParkinsonParkinson DiseaseUniversity of East Anglia

http://healthresearchreport.me/       07 Apr 2012

Men who eat flavonoid-rich foods such as berries, tea, apples and red wine significantly reduce their risk of developing Parkinson’s disease, according to new research by Harvard University and the University of East Anglia (UEA).

Published today in the journal Neurology ®, the findings add to the growing body of evidence that regular consumption of some flavonoids can have a marked effect on human health. Recent studies have shown that these compounds can offer protection against a wide range of diseases including heart disease, hypertension, some cancers and dementia.

This latest study is the first study in humans to show that flavonoids can protect neurons against diseases of the brain such as Parkinson’s.

Around 130,000 men and women took part in the research. More than 800 had developed Parkinson’s disease within 20 years of follow-up. After a detailed analysis of their diets and adjusting for age and lifestyle, male participants who ate the most flavonoids were shown to be 40 per cent less likely to develop the disease than those who ate the least. No similar link was found for total flavonoid intake in women.

The research was led by Dr Xiang Gao of Harvard School of Public Health in collaboration with Prof Aedin Cassidy of the Department of Nutrition, Norwich Medical School at UEA.

“These exciting findings provide further confirmation that regular consumption of flavonoids can have potential health benefits,” said Prof Cassidy.

“This is the first study in humans to look at the associations between the range of flavonoids in the diet and the risk of developing Parkinson’s disease and our findings suggest that a sub-class of flavonoids called anthocyanins may have neuroprotective effects.”

Prof Gao said: “Interestingly, anthocyanins and berry fruits, which are rich in anthocyanins, seem to be associated with a lower risk of Parkinson’s disease in pooled analyses. Participants who consumed one or more portions of berry fruits each week were around 25 per cent less likely to develop Parkinson’s disease, relative to those who did not eat berry fruits. Given the other potential health effects of berry fruits, such as lowering risk of hypertension as reported in our previous studies, it is good to regularly add these fruits to your diet.”

Flavonoids are a group of naturally occurring, bioactive compunds found in many plant-based foods and drinks. In this study the main protective effect was from higher intake of anthocyanins, which are present in berries and other fruits and vegetables including aubergines, blackcurrants and blackberries. Those who consumed the most anthocyanins had a 24 per cent reduction in risk of developing Parkinson’s disease and strawberries and blueberries were the top two sources in the US diet.

The findings must now be confirmed by other large epidemiological studies and clinical trials.

Parkinson’s disease is a progresssive neurological condition affecting one in 500 people, which equates to 127,000 people in the UK. There are few effective drug therapies available.  Dr Kieran Breen, director of research at Parkinson’s UK said: “This study raises lots of interesting questions about how diet may influence our risk of Parkinson’s…   there are still a lot of questions to answer and much more research to do before we really know how important diet might be for people with Parkinson’s.”

 

Eating berries may lower risk of Parkinson’s

Missed – Medical Breakthroughs • Tags: BerryDoctor of PhilosophyFlavonoidParkinson,Parkinson DiseaseXiang Gao

http://healthresearchreport.me/    Public release date: 13-Feb-2011

ST. PAUL, Minn. –New research shows men and women who regularly eat berries may have a lower risk of developing Parkinson’s disease, while men may also further lower their risk by regularly eating apples, oranges and other sources rich in dietary components called flavonoids. The study was released today and will be presented at the American Academy of Neurology’s 63rd Annual Meeting in Honolulu April 9 to April 16, 2011.

Flavonoids are found in plants and fruits and are also known collectively as vitamin P and citrin. They can also be found in berry fruits, chocolate, and citrus fruits such as grapefruit.

The study involved 49,281 men and 80,336 women. Researchers gave participants questionnaires and used a database to calculate intake amount of flavonoids. They then analyzed the association between flavonoid intakes and risk of developing Parkinson’s disease. They also analyzed consumption of five major sources of foods rich in flavonoids: tea, berries, apples, red wine and oranges or orange juice. The participants were followed for 20 to 22 years.

During that time, 805 people developed Parkinson’s disease. In men, the top 20 percent who consumed the most flavonoids were about 40 percent less likely to develop Parkinson’s disease than the bottom 20 percent of male participants who consumed the least amount of flavonoids. In women, there was no relationship between overall flavonoid consumption and developing Parkinson’s disease. However, when sub-classes of flavonoids were examined, regular consumption of anthocyanins, which are mainly obtained from berries, were found to be associated with a lower risk of Parkinson’s disease in both men and women.

“This is the first study in humans to examine the association between flavonoids and risk of developing Parkinson’s disease,” said study author Xiang Gao, MD, PhD, with the Harvard School of Public Health in Boston. “Our findings suggest that flavonoids, specifically a group called anthocyanins, may have neuroprotective effects. If confirmed, flavonoids may be a natural and healthy way to reduce your risk of developing Parkinson’s disease.”
May 10, 2013

Could eating peppers prevent Parkinson’s?

Missed – Medical Breakthroughs • Tags: American Neurological AssociationAnnals of Neurology,Group Health CooperativeNicotineParkinsonParkinson’s diseaseSolanaceaeUniversity of Washington

Contact: Dawn Peters sciencenewsroom@wiley.com 781-388-8408 Wiley

Dietary nicotine may hold protective key

New research reveals that Solanaceae—a flowering plant family with some species producing foods that are edible sources of nicotine—may provide a protective effect against Parkinson’s disease. The study appearing today inAnnals of Neurology, a journal of the American Neurological Association and Child Neurology Society, suggests that eating foods that contain even a small amount of nicotine, such as peppers and tomatoes, may reduce risk of developing Parkinson’s.

Parkinson’s disease is a movement disorder caused by a loss of brain cells that produce dopamine. Symptoms include facial, hand, arm, and leg tremors, stiffness in the limbs, loss of balance, and slower overall movement. Nearly one million Americans have Parkinson’s, with 60,000 new cases diagnosed in the U.S. each year, and up to ten million individuals worldwide live with this disease according to the Parkinson’s Disease Foundation. Currently, there is no cure for Parkinson’s, but symptoms are treated with medications and procedures such as deep brain stimulation.

Previous studies have found that cigarette smoking and other forms of tobacco, also a Solanaceae plant, reduced relative risk of Parkinson’s disease. However, experts have not confirmed if nicotine or other components in tobacco provide a protective effect, or if people who develop Parkinson’s disease are simply less apt to use tobacco because of differences in the brain that occur early in the disease process, long before diagnosis.

For the present population-based study Dr. Susan Searles Nielsen and colleagues from the University of Washington in Seattle recruited 490 patients newly diagnosed with Parkinson’s disease at the university’s Neurology Clinic or a regional health maintenance organization, Group Health Cooperative. Another 644 unrelated individuals without neurological conditions were used as controls. Questionnaires were used to assess participants’ lifetime diets and tobacco use, which researchers defined as ever smoking more than 100 cigarettes or regularly using cigars, pipes or smokeless tobacco.

Vegetable consumption in general did not affect Parkinson’s disease risk, but as consumption of edible Solanaceae increased, Parkinson’s disease risk decreased, with peppers displaying the strongest association. Researchers noted that the apparent protection from Parkinson’s occurred mainly in men and women with little or no prior use of tobacco, which contains much more nicotine than the foods studied.

“Our study is the first to investigate dietary nicotine and risk of developing Parkinson’s disease,” said Dr. Searles Nielsen. “Similar to the many studies that indicate tobacco use might reduce risk of Parkinson’s, our findings also suggest a protective effect from nicotine, or perhaps a similar but less toxic chemical in peppers and tobacco.” The authors recommend further studies to confirm and extend their findings, which could lead to possible interventions that prevent Parkinson’s disease.

###

This study is published in Annals of Neurology. Media wishing to receive a PDF of this article may contact sciencenewsroom@wiley.com.

Full citation: “Nicotine from Edible Solanaceae and Risk of Parkinson Disease.” Susan Searles Nielsen, Gary M. Franklin, W.T. Longstreth Jr, Phillip D. Swanson and Harvey Checkoway. Annals of Neurology; Published May 9, 2013 (DOI:10.1002/ana.23884).

URL Upon Publication: http://doi.wiley.com/10.1002/ana.23884

Author Contact: To arrange an interview with Dr. Susan Searles Nielsen, please contact Leila Gray with the University of Washington Health Sciences News Office at +1 206-685-0381 or at leilag@uw.edu.

About the Journal

Annals of Neurology, the official journal of the American Neurological Association and the Child Neurology Society, publishes articles of broad interest with potential for high impact in understanding the mechanisms and treatment of diseases of the human nervous system. All areas of clinical and basic neuroscience, including new technologies, cellular and molecular neurobiology, population sciences, and studies of behavior, addiction, and psychiatric diseases are of interest to the journal. The journal is published by Wiley on behalf of the
American Neurological Association and Child Neurology Society. For more information, please visit http://onlinelibrary.wiley.com/journal/10.1002/ana.

Flavonoids from berries shown to protect men against Parkinson’s disease

December 19, 2013 · by MrT

by: John Phillip, John is a Certified Nutritional Consultant and Health Researcher

(NaturalNews) Past research bodies have confirmed the health-protective effect of a natural diet rich in flavonoids to protect against a wide range of diseases including heart disease, hypertension, some cancers, and dementia. Researchers from Harvard University and the University of East Anglia have published the result of a study in the journalNeurology that demonstrates how these plant-based phytonutrients can significantly lower the risk of developing Parkinson’s disease, especially in men.

Flavonoids from healthy foods such as berries, tea, apples, and red wine cross the delicate blood-brain barrier to protect neurons against neurologic diseases such as Parkinson’s. This large scale study included more than 130,000 men and women participants that were followed for a period of twenty years. During this time, more than 800 individuals developed Parkinson’s disease.

A diet high in flavonoids from berries lowers Parkinson’s disease risk by forty percent

After a detailed analysis of their diets and adjusting for age and lifestyle, male participants who ate the most flavonoids were shown to be forty percent  less likely to develop the disease than those who ate the least. No similar link was found for total flavonoid intake in women.

This was the first study to examine the connection between flavonoid consumption and the development of Parkinson’s disease. The findings suggest that a sub-class of flavonoids called anthocyanins may exhibit neuroprotective effects. Participants consuming one or more portions of berry fruits each week were around twenty-five percent less likely to develop Parkinson’s disease, relative to those who did not eat berry fruits.

Flavonoids are the bioactive, naturally occurring chemical compounds found in many plant-based foods and drinks.

This study demonstrated the main protective effect was from the consumption of anthocyanins, which are present in berries and other fruits and vegetables including aubergines, blackcurrants, and blackberries. Strawberries and blueberries are the two most common sources of flavonoids in the US diet, contributing to a twenty-four percent lowered risk in this research.

Parkinson’s disease is among a group of chronic diseases presently affecting one in 500 people, with new cases on the rise. Drug therapies are ineffective and bear significant side effects.

Nutrition experts recommend adding a minimum of three to five servings of flavonoids to your diet each week. Include all varieties of berries, apples, and green tea to guard against Parkinson’s disease and other neurodegenerative illnesses.

 

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