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A gene crucial for learning, called Arc can send genetic material from one neuron to another by using viruses was discovered by two independent team of scientist from University of Massachusetts Medical School and University of Utah which was published in Cell. According to Dr. Edmund Talley, a program director at National Institute of Neurological Disorders and Stroke “this work is a great example of the importance of basic neuroscience research”.
Arc plays an important role in the brain’s ability to store new information, however little is known of how it works. According to the University of Utah scientists, research into the examination of the Arc gene began by introducing it into bacterial cells. When the cells made the Arc protein, it clumped together into a form that resembled a viral capsid, the shell that contains a virus’ genetic information. The Arc “capsids” appeared to mirror viral capsids in their physical structure in addition as their behavior and other properties.
At the same time, University of Massachusetts scientist led by Vivian Budnik, Ph. D and Travis Thomson, Ph.D. set out to scrutinize the contents of tiny sacks released by cells called extracellular vesicles. Their experiments in fruit flies revealed that motor neurons that control the flies’ muscles release vesicles containing a high concentration of the Arcgene’s messenger RNA (mRNA), the DNA-like intermediary molecule cells use to create the protein encoded by a DNA sequence.
Both groups similarly found evidence that Arc capsids contain Arc mRNA and that the capsids are released from neurons inside those vesicles. Also, both groups suggest that Arc capsids act like viruses by delivering mRNA to nearby cells. Furthermore, Dr. Shepherd’s team presented that the more active neurons are, the more of those vesicles they release. Dr. Shepherd’s group grew mouse neurons lacking the Arc gene in petri dishes filled with Arc-containing vesicles or Arc capsids alone. They revealed that the formerly Arc-less neurons took in the vesicles and capsids and used the Arc mRNA contained within to produce the Arc protein themselves. Finally, just like neurons that naturally manufacture the Arc protein, those cells made more of it when their electrical activity increased.
Both groups of scientists plan to examine why cells use this virus-like strategy to shuttle Arc mRNA between cells and which might allow the toxic proteins responsible for Alzheimer’s disease to spread through the brain.
FDA Cellular & Gene Therapy Guidances: Implications for CRSPR/Cas9 Trials, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair
FDA Cellular & Gene Therapy Guidances: Implications for CRSPR/Cas9 Trials
Reporter: Stephen J. Williams, PhD
The recent announcement by Editas CEO Katrine Bosley to pursue a CRSPR/Cas9 gene therapy trial to correct defects in an yet to be disclosed gene to treat one form of a rare eye disease called Leber congenital amaurosis (multiple mutant genes have been linked to the disease) have put an interesting emphasis on the need for a regulatory framework to initiate these trials. Indeed at the 2015 EmTechMIT Conference Editas CEO Katrine Bosley had mentioned this particular issue: the need for discourse with FDA and regulatory bodies to establish guidelines for design of clinical trials using the CRSPR gene editing tool.
To this effect, I have listed below, the multiple FDA Guidance Documents surrounding gene therapy to show that, in the past year, the FDA has shown great commitment to devise a regulatory framework for this therapeutic area.
This e-Book is a comprehensive review of recent Original Research on METABOLOMICS and related opportunities for Targeted Therapy written by Experts, Authors, Writers. This is the first volume of the Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases. It is written for comprehension at the third year medical student level, or as a reference for licensing board exams, but it is also written for the education of a first time baccalaureate degree reader in the biological sciences. Hopefully, it can be read with great interest by the undergraduate student who is undecided in the choice of a career. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation.The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012. All new articles on this subject, will continue to be incorporated, as published with periodical updates.
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Table of Contents forMetabolic Genomics & Pharmaceutics, Vol. I
Chapter 1: Metabolic Pathways
Chapter 2: Lipid Metabolism
Chapter 3: Cell Signaling
Chapter 4: Protein Synthesis and Degradation
Chapter 5: Sub-cellular Structure
Chapter 6: Proteomics
Chapter 7: Metabolomics
Chapter 8: Impairments in Pathological States: Endocrine Disorders; Stress
Hypermetabolism and Cancer
Chapter 9: Genomic Expression in Health and Disease
Variant ASGR1 Associated with a Reduced Risk of Coronary Artery Disease
Paul Nioi, Ph.D., Asgeir Sigurdsson, B.Sc., Gudmar Thorleifsson, Ph.D., Hannes Helgason, Ph.D., Arna B. Agustsdottir, B.Sc., Gudmundur L. Norddahl, Ph.D., Anna Helgadottir, M.D., Audur Magnusdottir, Ph.D., Aslaug Jonasdottir, M.Sc., Solveig Gretarsdottir, Ph.D., Ingileif Jonsdottir, Ph.D., Valgerdur Steinthorsdottir, Ph.D., Thorunn Rafnar, Ph.D., Dorine W. Swinkels, M.D., Ph.D., Tessel E. Galesloot, Ph.D., Niels Grarup, Ph.D., Torben Jørgensen, D.M.Sc., Henrik Vestergaard, D.M.Sc., Torben Hansen, Ph.D., Torsten Lauritzen, D.M.Sc., Allan Linneberg, Ph.D., Nele Friedrich, Ph.D., Nikolaj T. Krarup, Ph.D., Mogens Fenger, Ph.D., Ulrik Abildgaard, D.M.Sc., Peter R. Hansen, D.M.Sc., Anders M. Galløe, Ph.D., Peter S. Braund, Ph.D., Christopher P. Nelson, Ph.D., Alistair S. Hall, F.R.C.P., Michael J.A. Williams, M.D., Andre M. van Rij, M.D., Gregory T. Jones, Ph.D., Riyaz S. Patel, M.D., Allan I. Levey, M.D., Ph.D., Salim Hayek, M.D., Svati H. Shah, M.D., Muredach Reilly, M.B., B.Ch., Gudmundur I. Eyjolfsson, M.D., Olof Sigurdardottir, M.D., Ph.D., Isleifur Olafsson, M.D., Ph.D., Lambertus A. Kiemeney, Ph.D., Arshed A. Quyyumi, F.R.C.P., Daniel J. Rader, M.D., William E. Kraus, M.D., Nilesh J. Samani, F.R.C.P., Oluf Pedersen, D.M.Sc., Gudmundur Thorgeirsson, M.D., Ph.D., Gisli Masson, Ph.D., Hilma Holm, M.D., Daniel Gudbjartsson, Ph.D., Patrick Sulem, M.D., Unnur Thorsteinsdottir, Ph.D., and Kari Stefansson, M.D., Ph.D.
N Engl J Med 2016; 374:2131-2141June 2, 2016DOI: 10.1056/NEJMoa1508419
Several sequence variants are known to have effects on serum levels of non–high-density lipoprotein (HDL) cholesterol that alter the risk of coronary artery disease.
We sequenced the genomes of 2636 Icelanders and found variants that we then imputed into the genomes of approximately 398,000 Icelanders. We tested for association between these imputed variants and non-HDL cholesterol levels in 119,146 samples. We then performed replication testing in two populations of European descent. We assessed the effects of an implicated loss-of-function variant on the risk of coronary artery disease in 42,524 case patients and 249,414 controls from five European ancestry populations. An augmented set of genomes was screened for additional loss-of-function variants in a target gene. We evaluated the effect of an implicated variant on protein stability.
We found a rare noncoding 12-base-pair (bp) deletion (del12) in intron 4 of ASGR1, which encodes a subunit of the asialoglycoprotein receptor, a lectin that plays a role in the homeostasis of circulating glycoproteins. The del12 mutation activates a cryptic splice site, leading to a frameshift mutation and a premature stop codon that renders a truncated protein prone to degradation. Heterozygous carriers of the mutation (1 in 120 persons in our study population) had a lower level of non-HDL cholesterol than noncarriers, a difference of 15.3 mg per deciliter (0.40 mmol per liter) (P=1.0×10−16), and a lower risk of coronary artery disease (by 34%; 95% confidence interval, 21 to 45; P=4.0×10−6). In a larger set of sequenced samples from Icelanders, we found another loss-of-function ASGR1 variant (p.W158X, carried by 1 in 1850 persons) that was also associated with lower levels of non-HDL cholesterol (P=1.8×10−3).
ASGR1 haploinsufficiency was associated with reduced levels of non-HDL cholesterol and a reduced risk of coronary artery disease. (Funded by the National Institutes of Health and others.)
Amgen’s deCODE Genetics Publishes Largest Human Genome Population Study to Date
Mark Terry, BioSpace.com Breaking News Staff reported on results of one of the largest genome sequencing efforts to date, sequencing of the genomes of 2,636 people from Iceland by deCODE genetics, Inc., a division of Thousand Oaks, Calif.-based Amgen (AMGN).
There were a total of four studies, published on March 25, 2015 on the online version of Nature Genetics; titled “Large-scale whole-genome sequencing of the Icelandic population[1],” “Identification of a large set of rare complete human knockouts[2],” “The Y-chromosome point mutation rate in humans[3]” and “Loss-of-function variants in ABCA7 confer risk of Alzheimer’s disease[4].”
The project identified some new genetic variants which increase risk of Alzheimer’s disease and confirmed some variants known to increase risk of diabetes and atrial fibrillation. A more in-depth post will curate these findings but there was an interesting discrete geographic distribution of certain rare variants located around Iceland. The dataset offers a treasure trove of meaningful genetic information not only about the Icelandic population but offers numerous new targets for breast, ovarian cancer as well as Alzheimer’s disease.
“This work is a demonstration of the unique power sequencing gives us for learning more about the history of our species,” said Kari Stefansson, founder and chief executive officer of deCode and one of the lead authors in a statement, “and for contributing to new means of diagnosing, treating and preventing disease.”
The scale and ambition of the study is impressive, but perhaps more important, the research identified a new genetic variant that increases the risk of Alzheimer’s disease and already had identified an APP variant that is associated with decreased risk of Alzheimer’s Disease. It also confirmed variants that increase the risk of diabetes and a variant that results in atrial fibrillation.
The database of human genetic variation (dbSNP) contained over 50 million unique sequence variants yet this database only represents a small proportion of single nucleotide variants which is thought to exist. These “private” or rare variants undoubtedly contribute to important phenotypes, such as disease susceptibility. Non-SNV variants, like indels and structural variants, are also under-represented in public databases. The only way to fully elucidate the genetic basis of a trait is to consider all of these types of variants, and the only way to find them is by large-scale sequencing.
Curation of Population Genomic Sequencing Programs/Corporate Partnerships
Click on “Curation of genomic studies” below for full Table
Gudbjartsson DF, Helgason H, Gudjonsson SA, Zink F, Oddson A, Gylfason A, Besenbacher S, Magnusson G, Halldorsson BV, Hjartarson E et al: Large-scale whole-genome sequencing of the Icelandic population. Nature genetics 2015, advance online publication.
Sulem P, Helgason H, Oddson A, Stefansson H, Gudjonsson SA, Zink F, Hjartarson E, Sigurdsson GT, Jonasdottir A, Jonasdottir A et al: Identification of a large set of rare complete human knockouts. Nature genetics 2015, advance online publication.
Helgason A, Einarsson AW, Gumundsdottir VB, Sigursson A, Gunnarsdottir ED, Jagadeesan A, Ebenesersdottir SS, Kong A, Stefansson K: The Y-chromosome point mutation rate in humans. Nature genetics 2015, advance online publication.
Steinberg S, Stefansson H, Jonsson T, Johannsdottir H, Ingason A, Helgason H, Sulem P, Magnusson OT, Gudjonsson SA, Unnsteinsdottir U et al: Loss-of-function variants in ABCA7 confer risk of Alzheimer’s disease. Nature genetics 2015, advance online publication.
Other post related to DECODE, population genomics, and NGS on this site include:
In the future, George Church believes, almost everything will be better because of genetics. If you have a medical problem, your doctor will be able to customize a treatment based on your specific DNA pattern. When you fill up your car, you won’t be draining the world’s dwindling supply of crude oil, because the fuel will come from microbes that have been genetically altered to produce biofuel. When you visit the zoo, you’ll be able to take your children to the woolly mammoth or passenger pigeon exhibits, because these animals will no longer be extinct. You’ll be able to do these things, that is, if the future turns out the way Church envisions it—and he’s doing everything he can to see that it does.
UPDATED 12/05/2020
George Church backs a startup solution to the massive gene therapy manufacturing bottleneck
Source: https://endpts.com/george-church-backs-a-startup-solution-to-the-massive-gene-therapy-manufacturing-bottleneck/ Jason Mast: Associate Editor George Church and his graduate students have spent the last decade seeding startups on the razor’s edge between biology and science fiction: gene therapy to prevent aging, CRISPRed pigs that can be used to harvest organs for transplant, and home kits to test your poop for healthy or unhealthy bacteria. (OK, maybe they’re not all on that razor’s edge.)
But now a new spinout from the Department of Genetics’ second floor is tackling a far humbler problem — one that major company after major company has stumbled over as they tried to get cures for rare diseases and other gene therapies into the clinic and past regulators: How the hell do you build these?
CEO Lex Vovner of 64x Bio
“There’s a lot happening for new therapies but not enough attention around this problem,” Lex Rovner, who was a post-doc at Church’s lab from 2015 to 2018, told Endpoints News. “And if we don’t figure out how to fix this, many of these therapies won’t even reach patients.”
This week, with Church and a couple other prominent scientists as co-founders, Rovner launched 64x Bio to tackle one key part of the manufacturing bottleneck. They won’t be looking to retrofit plants or build gene therapy factories, as Big Pharma and big biotech are now spending billions to do. Instead, with $4.5 million in seed cash, they will try to engineer the individual cells that churn out a critical component of the therapies.
George Church The goal is to build cells that are fine-tuned to do nothing but spit out the viral vectors that researchers and drug developers use to shuttle gene therapies into the body. Different vectors have different demands; 64x Bio will look to make efficient cellular factories for each.
“While a few general ways to increase vector production may exist, each unique vector serotype and payload poses a specific challenge,” Church said in an emailed statement. “Our platform enables us to fine tune custom solutions for these distinct combinations that are particularly hard to overcome.”
Before joining Church’s lab, Rovner did her graduate work at Yale, where she studied how to engineer bacteria to produce new kinds of protein for drugs or other purposes. And after leaving Church’s lab in 2018, she initially set out to build a manufacturing startup with a broad focus.
Yet as she spoke with hundreds of biotech executives on LinkedIn and in coffee shops around Cambridge, the same issue kept popping up: They liked their gene therapy technology in the lab but they didn’t know how to scale it up.
“Everyone kept saying the same thing,” Rovner said. “We basically realized there’s this huge problem.”
The issue would soon make headlines in industry publications: bluebird delaying the launch of Zynteglo, Novartis delaying the launch of Zolgensma in the EU, Axovant delaying the start of their Parkinson’s trial.
Part of the problem, Rovner said, is that gene therapies are delivered on viral vectors. You can build these vectors in mammalian cell lines by feeding them a small circular strand of DNA called a plasmid. The problem is that mammalian cells have, over billions of years, evolved tools and defenses precisely to avoid making viruses. (Lest the mammal they live in die of infection).
There are genetic mutations that can turn off some of the internal defenses and unleash a cell’s ability to produce virus, but they’re rare and hard to find. Other platforms, Rovner said, try to find these mutations by using CRISPR to knock out genes in different cells and then screening each of them individually, a process that can require hundreds of thousands of different 100-well plates, with each well containing a different group of mutant cells.
“It’s just not practical, and so these platforms never find the cells,” Rovner said.
64x Bio will try to find them by building a library of millions of mutant mammalian cells and then using a molecular “barcoding” technique to screen those cells in a single pool. The technique, Rovner said, lets them trace how much vector any given cell produces, allowing researchers to quickly identify super-producing cells and their mutations.
The technology was developed partially in-house but draws from IP at Harvard and the Wyss Institute. Harvard’s Pam Silver and Wyss’s Jeffrey Way are co-founders.
The company is now based in SoMa in San Francisco. With the seed cash from Fifty Years, Refactor and First Round Capital, Rovner is recruiting and looking to raise a Series A soon. They’re in talks with pharma and biotech partners, while they try to validate the first preclinical and clinical applications.
Gene therapy is one focus, but Rovner said the platform works for anything that involves viral vector, including vaccines and oncolytic viruses. You just have to find the right mutation.
“It’s the rare cell you’re looking for,” she said.
AUTHOR Jason Mast Associate Editor jason@endpointsnews.com @JasonMMast Jason Mas
In 2005 he launched the Personal Genome Project, with the goal of sequencing and sharing the DNA of 100,000 volunteers. With an open-source database of that size, he believes, researchers everywhere will be able to meaningfully pursue the critical task of correlating genetic patterns with physical traits, illnesses, and exposure to environmental factors to find new cures for diseases and to gain basic insights into what makes each of us the way we are. Church, tagged as subject hu43860C, was first in line for testing. Since then, more than 13,000 people in the U.S., Canada, and the U.K. have volunteered to join him, helping to establish what he playfully calls the Facebook of DNA.
Church has made a career of defying the impossible. Propelled by the dizzying speed of technological advancement since then, the Personal Genome Project is just one of Church’s many attempts to overcome obstacles standing between him and the future.
“It’s not for everyone,” he says. “But I see a trend here. Openness has changed since many of us were young. People didn’t use to talk about sexuality or cancer in polite society. This is the Facebook generation.” If individuals were told which diseases or medical conditions they were genetically predisposed to, they could adjust their behavior accordingly, he reasoned. Although universal testing still isn’t practical today, the cost of sequencing an individual genome has dropped dramatically in recent years, from about $7 million in 2007 to as little as $1,000 today.
“It’s all too easy to dismiss the future,” he says. “People confuse what’s impossible today with what’s impossible tomorrow.”, especially through the emerging discipline of “synthetic” biology. The basic idea behind synthetic biology, he explained, was that natural organisms could be reprogrammed to do things they wouldn’t normally do, things that might be useful to people. In pursuit of this, researchers had learned not only how to read the genetic code of organisms but also how to write new code and insert it into organisms. Besides making plastic, microbes altered in this way had produced carpet fibers, treated wastewater, generated electricity, manufactured jet fuel, created hemoglobin, and fabricated new drugs. But this was only the tip of the iceberg, Church wrote. The same technique could also be used on people.
“Every cell in our body, whether it’s a bacterial cell or a human cell, has a genome,” he says. “You can extract that genome—it’s kind of like a linear tape—and you can read it by a variety of methods. Similarly, like a string of letters that you can read, you can also change it. You can write, you can edit it, and then you can put it back in the cell.”
This April, the Broad Institute, where Church holds a faculty appointment, was awarded a patent for a new method of genome editing called CRISPR (clustered regularly interspersed short palindromic repeats), which Church says is one of the most effective tools ever developed for synthetic biology. By studying the way that certain bacteria defend themselves against viruses, researchers figured out how to precisely cut DNA at any location on the genome and insert new material there to alter its function. Last month, researchers at MIT announced they had used CRISPR to cure mice of a rare liver disease that also afflicts humans. At the same time, researchers at Virginia Tech said they were experimenting on plants with CRISPR to control salt tolerance, improve crop yield, and create resistance to pathogens.
The possibilities for CRISPR technology seem almost limitless, Church says. If researchers have stored a genetic sequence in a computer, they can order a robot to produce a piece of DNA from the data. That piece can then be put into a cell to change the genome. Church believes that CRISPR is so promising that last year he co-founded a genome-editing company, Editas, to develop drugs for currently incurable diseases.
It is estimated that the medical imaging market will exceed $30 billion in 2014 (FierceMedicalImaging). To put this amount in perspective; the global pharmaceutical market size for the same year is expected to be ~$1 trillion (IMS) while the global health care spending as a percentage of Gross Domestic Product (GDP) will average 10.5% globally in 2014 (Deloitte); it will reach ~$3 trillion in the USA.
Recent technology-advances, mainly miniaturization and improvement in electronic-processing components is driving increased introduction of innovative medical-imaging devices into critical nodes of major-diseases’ management pathways. Consequently, in contrast to it’s very small contribution to global health costs, medical imaging bears outstanding potential to reduce the future growth in spending on major segments in this market mainly: Drugs development and regulation (e.g. companion diagnostics and imaging surrogate markers); Disease management (e.g. non-invasive diagnosis, guided treatment and non-invasive follow-ups); and Monitoring aging-population (e.g. Imaging-based domestic sensors).
In; The Role of Medical Imaging in Personalized Medicine I discussed in length the role medical imaging assumes in drugs development. Integrating imaging into drug development processes, specifically at the early stages of drug discovery, as well as for monitoring drug delivery and the response of targeted processes to the therapy is a growing trend. A nice (and short) review highlighting the processes, opportunities, and challenges of medical imaging in new drug development is: Medical imaging in new drug clinical development.
The following is dedicated to the role of imaging in guiding treatment.
Precise treatment is a major pillar of modern medicine. An important aspect to enable accurate administration of treatment is complementing the accurate identification of the organ location that needs to be treated with a system and methods that ensure application of treatment only, or mainly to, that location. Imaging is off-course, a major component in such composite systems. Amongst the available solution, functional-imaging modalities are gaining traction. Specifically, molecular imaging (e.g. PET, MRS) allows the visual representation, characterization, and quantification of biological processes at the cellular and subcellular levels within intact living organisms. In oncology, it can be used to depict the abnormal molecules as well as the aberrant interactions of altered molecules on which cancers depend. Being able to detect such fundamental finger-prints of cancer is key to improved matching between drugs-based treatment and disease. Moreover, imaging-based quantified monitoring of changes in tumor metabolism and its microenvironment could provide real-time non-invasive tool to predict the evolution and progression of primary tumors, as well as the development of tumor metastases.
A recent review-paper: Image-guided interventional therapy for cancer with radiotherapeutic nanoparticles nicely illustrates the role of imaging in treatment guidance through a comprehensive discussion of; Image-guided radiotherapeutic using intravenous nanoparticles for the delivery of localized radiation to solid cancer tumors.
Abstract
One of the major limitations of current cancer therapy is the inability to deliver tumoricidal agents throughout the entire tumor mass using traditional intravenous administration. Nanoparticles carrying beta-emitting therapeutic radionuclides[DN: radioactive isotops that emits electrons as part of the decay process a list of β-emitting radionuclides used in radiotherapeutic nanoparticle preparation is given in table1 of this paper.) that are delivered using advanced image-guidance have significant potential to improve solid tumor therapy. The use of image-guidance in combination with nanoparticle carriers can improve the delivery of localized radiation to tumors. Nanoparticles labeled with certain beta-emitting radionuclides are intrinsically theranostic agents that can provide information regarding distribution and regional dosimetry within the tumor and the body. Image-guided thermal therapy results in increased uptake of intravenous nanoparticles within tumors, improving therapy. In addition, nanoparticles are ideal carriers for direct intratumoral infusion of beta-emitting radionuclides by convection enhanced delivery, permitting the delivery of localized therapeutic radiation without the requirement of the radionuclide exiting from the nanoparticle. With this approach, very high doses of radiation can bedelivered to solid tumors while sparing normal organs. Recent technological developments in image-guidance, convection enhanced delivery and newly developed nanoparticles carrying beta-emitting radionuclides will be reviewed. Examples will be shown describing how this new approach has promise for the treatment of brain, head and neck, and other types of solid tumors.
The challenges this review discusses
intravenously administered drugs are inhibited in their intratumoral penetration by high interstitial pressures which prevent diffusion of drugs from the blood circulation into the tumor tissue [1–5].
relatively rapid clearance of intravenously administered drugs from the blood circulation by kidneys and liver.
drugs that do reach the solid tumor by diffusion are inhomogeneously distributed at the micro-scale – This cannot be overcome by simply administering larger systemic doses as toxicity to normal organs is generally the dose limiting factor.
even nanoparticulate drugs have poor penetration from the vascular compartment into the tumor and the nanoparticles that do penetrate are most often heterogeneously distributed
How imaging could mitigate the above mentioned challenges
The inclusion of an imaging probe during drug development can aid in determining the clearance kinetics and tissue distribution of the drug non-invasively. Such probe can also be used to determine the likelihood of the drug reaching the tumor and to what extent.
Note:Drugs that have increased accumulation within the targeted site are likely to be more effective as compared with others. In that respect, Nanoparticle-based drugs have an additional advantage over free drugs with their potential to be multifunctional carriers capable of carrying both therapeutic and diagnostic imaging probes (theranostic) in the same nanocarrier. These multifunctional nanoparticles can serve as theranostic agents and facilitate personalized treatment planning.
Imaging can also be used for localization of the tumor to improve the placement of a catheter or external device within tumors to cause cell death through thermal ablation or oxidative stress secondary to reactive oxygen species.
Note: Image guided thermal ablation methods include radiofrequency (RF) ablation, microwave ablation or high intensity focused ultrasound (HIFU). Photodynamic therapy methods using external light devices to activate photosensitizing agents can also be used to treat superficial tumors or deeper tumors when used with endoscopic catheters.
Quality control during and post treatment
For example: The use of high intensity focused ultrasound (HIFU) combined with nanoparticle therapeutics: HIFU is applied to improve drug delivery and to trigger drug release from nanoparticles. Gas-bubbles are playing the role of the drug’s nano-carrier. These are used both to increase the drug transport into the cell and as ultrasound-imaging contrast material. The ultrasound is also used for processes of drug-release and ablation.
Additional example; Multifunctional nanoparticles for tracking CED (convection enhanced delivery) distribution within tumors: Nanoparticle that could serve as a carrier not only for the therapeutic radionuclides but simultaneously also for a therapeutic drug and 4 different types of imaging contrast agents including an MRI contrast agent, PET and SPECT nuclear diagnostic imaging agents and optical contrast agents as shown below. The ability to perform multiple types of imaging on the same nanoparticles will allow studies investigating the distribution and retention of nanoparticles initially in vivo using non-invasive imaging and later at the histological level using optical imaging.
Conclusions
Image-guided radiotherapeutic nanoparticles have significant potential for solid tumor cancer therapy. The current success of this therapy in animals is most likely due to the improved accumulation, retention and dispersion of nanoparticles within solid tumor following image-guided therapies as well as the micro-field of the β-particle which reduces the requirement of perfectly homogeneous tumor coverage. It is also possible that the intratumoral distribution of nanoparticles may benefit from their uptake by intratumoral macrophages although more research is required to determine the importance of this aspect of intratumoral radionuclide nanoparticle therapy. This new approach to cancer therapy is a fertile ground for many new technological developments as well as for new understandings in the basic biology of cancer therapy. The clinical success of this approach will depend on progress in many areas of interdisciplinary research including imaging technology, nanoparticle technology, computer and robot assisted image-guided application of therapies, radiation physics and oncology. Close collaboration of a wide variety of scientists and physicians including chemists, nanotechnologists, drug delivery experts, radiation physicists, robotics and software experts, toxicologists, surgeons, imaging physicians, and oncologists will best facilitate the implementation of this novel approach to the treatment of cancer in the clinical environment. Image-guided nanoparticle therapies including those with β-emission radionuclide nanoparticles have excellent promise to significantly impact clinical cancer therapy and advance the field of drug delivery.
Compilation of References by Leaders in Pharmaceutical Business Intelligence in the Journal http://pharmaceuticalintelligence.com about
Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation
Curator: Larry H Bernstein, MD, FCAP
Proteomics
The Human Proteome Map Completed
Reporter and Curator: Larry H. Bernstein, MD, FCAP
33. Cardiac Contractility & Myocardial Performance: Therapeutic Implications of Ryanopathy (Calcium Release- related Contractile Dysfunction) and Catecholamine Responses
Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC
Author and Curator: Larry H Bernstein, MD, FCAP
and Article Curator: Aviva Lev-Ari, PhD, RN
8. microRNA called miRNA-142 involved in the process by which the immature cells in the bone marrow give rise to all the types of blood cells, including immune cells and the oxygen-bearing red blood cells
36. Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders @http://pharmaceuticalintelligence.com
37. GSK for Personalized Medicine using Cancer Drugs needs Alacris systems biology model to determine the in silico
effect of the inhibitor in its “virtual clinical trial”
11. Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and
Cardiovascular Calcium Signaling Mechanism
Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to e-SERIES A:
Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and Curator: Aviva Lev-Ari, PhD, RN
12. The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and
Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia,
Similarities and Differences, and Pharmaceutical Targets
Author and Curator: Larry H Bernstein, MD, FCAP, Author, and Content Consultant to
e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC and
Curator: Aviva Lev-Ari, PhD, RN
I came across a few recent articles on the subject of US Patent Office guidance on patentability as well as on Supreme Court ruling on claims. I filed several patents on clinical laboratory methods early in my career upon the recommendation of my brother-in-law, now deceased. Years later, after both brother-in-law and patent attorney are no longer alive, I look back and ask what I have learned over $100,000 later, with many trips to the USPTO, opportunities not taken, and a one year provisional patent behind me.
My conclusion is
(1) that patents are for the protection of the innovator, who might realize legal protection, but the cost and the time investment can well exceed the cost of startup and building a small startup enterprize, that would be the next step.
(2) The other thing to consider is the capability of the lawyer or firm that represents you. A patent that is well done can be expected to take 5-7 years to go through with due diligence. I would not expect it to be done well by a university with many other competing demands. I might be wrong in this respect, as the climate has changed, and research universities have sprouted engines for change. Experienced and productive faculty are encouraged or allowed to form their own such entities.
(3) The emergence of Big Data, computational biology, and very large data warehouses for data use and integration has changed the landscape. The resources required for an individual to pursue research along these lines is quite beyond an individuals sole capacity to successfully pursue without outside funding. In addition, the changed designated requirement of first to publish has muddied the water.
Of course, one can propose without anything published in the public domain. That makes it possible for corporate entities to file thousands of patents, whether there is actual validation or not at the time of filing. It would be a quite trying experience for anyone to pursue in the USPTO without some litigation over ownership of patent rights. At this stage of of technology development, I have come to realize that the organization of research, peer review, and archiving of data is still at a stage where some of the best systems avalailable for storing and accessing data still comes considerably short of what is needed for the most complex tasks, even though improvements have come at an exponential pace.
I shall not comment on the contested views held by physicists, chemists, biologists, and economists over the completeness of guiding theories strongly held. Only history will tell. Beliefs can hold a strong sway, and have many times held us back.
I am not an expert on legal matters, but it is incomprehensible to me that issues concerning technology innovation can be adjudicated in the Supreme Court, as has occurred in recent years. I have postgraduate degrees in Medicine, Developmental Anatomy, and post-medical training in pathology and laboratory medicine, as well as experience in analytical and research biochemistry. It is beyond the competencies expected for these type of cases to come before the Supreme Court, or even to the Federal District Courts, as we see with increasing frequency, as this has occurred with respect to the development and application of the human genome.
I’m not sure that the developments can be resolved for the public good without a more full development of an open-access system of publishing. Now I present some recent publication about, or published by the USPTO.
DR ANTHONY MELVIN CRASTO
Dr. Melvin Castro – Organic Chemistry and New Drug Development
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USPTO Guidance On Patentable Subject Matter: Impediment to Biotech Innovation
Joanna T. Brougher, David A. FazzolareJ Commercial Biotechnology 2014 20(3):Brougher
jcbiotech-patents
Abstract In June 2013, the U.S. Supreme Court issued a unanimous decision upending more than three decades worth of established patent practice when it ruled that isolated gene sequences are no longer patentable subject matter under 35 U.S.C. Section 101.While many practitioners in the field believed that the USPTO would interpret the decision narrowly, the USPTO actually expanded the scope of the decision when it issued its guidelines for determining whether an invention satisfies Section 101.
The guidelines were met with intense backlash with many arguing that they unnecessarily expanded the scope of the Supreme Court cases in a way that could unduly restrict the scope of patentable subject matter, weaken the U.S. patent system, and create a disincentive to innovation. By undermining patentable subject matter in this way, the guidelines may end up harming not only the companies that patent medical innovations, but also the patients who need medical care. This article examines the guidelines and their impact on various technologies.
35 U.S.C. Section 101 states “Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
” Prometheus Laboratories, Inc. v. Mayo Collaborative Services, 566 U.S. ___ (2012)
Association for Molecular Pathology et al., v. Myriad Genetics, Inc., 569 U.S. ___ (2013).
Parke-Davis & Co. v. H.K. Mulford Co., 189 F. 95, 103 (C.C.S.D.N.Y. 1911)
USPTO. Guidance For Determining Subject Matter Eligibility Of Claims Reciting Or Involving Laws of Nature, Natural Phenomena, & Natural Products.
A 2013 Supreme Court decision that barred human gene patents is scrambling patenting policies.
PHOTO: MLADEN ANTONOV/AFP/GETTY IMAGES
A year after the U.S. Supreme Court issued a landmark ruling that human genes cannot be patented, the biotech industry is struggling to adapt to a landscape in which inventions derived from nature are increasingly hard to patent. It is also pushing back against follow-on policies proposed by the U.S. Patent and Trademark Office (USPTO) to guide examiners deciding whether an invention is too close to a natural product to deserve patent protection. Those policies reach far beyond what the high court intended, biotech representatives say.
“Everything we took for granted a few years ago is now changing, and it’s generating a bit of a scramble,” says patent attorney Damian Kotsis of Harness Dickey in Troy, Michigan, one of more than 15,000 people who gathered here last week for the Biotechnology Industry Organization’s (BIO’s) International Convention.
At the meeting, attorneys and executives fretted over the fate of patent applications for inventions involving naturally occurring products—including chemical compounds, antibodies, seeds, and vaccines—and traded stories of recent, unexpected rejections by USPTO. Industry leaders warned that the uncertainty could chill efforts to commercialize scientific discoveries made at universities and companies. Some plan to appeal the rejections in federal court.
USPTO officials, meanwhile, implored attendees to send them suggestions on how to clarify and improve its new policies on patenting natural products, and even announced that they were extending the deadline for public comment by a month. “Each and every one of you in this room has a moral duty … to provide written comments to the PTO,” patent lawyer and former USPTO Deputy Director Teresa Stanek Rea told one audience.
At the heart of the shake-up are two Supreme Court decisions: the ruling last year in Association for Molecular Pathology v. Myriad Genetics Inc. that human genes cannot be patented because they occur naturally (Science, 21 June 2013, p. 1387); and the 2012 Mayo v. Prometheus decision, which invalidated a patent on a method of measuring blood metabolites to determine drug doses because it relied on a “law of nature” (Science, 12 July 2013, p. 137).
Myriad and Mayo are already having a noticeable impact on patent decisions, according to a study released here. It examined about 1000 patent applications that included claims linked to natural products or laws of nature that USPTO reviewed between April 2011 and March 2014. Overall, examiners rejected about 40%; Myriad was the basis for rejecting about 23% of the applications, and Mayo about 35%, with some overlap, the authors concluded. That rejection rate would have been in the single digits just 5 years ago, asserted Hans Sauer, BIO’s intellectual property counsel, at a press conference. (There are no historical numbers for comparison.) The study was conducted by the news service Bloomberg BNA and the law firm Robins, Kaplan, Miller & Ciseri in Minneapolis, Minnesota.
USPTO is extending the decisions far beyond diagnostics and DNA?
The numbers suggest USPTO is extending the decisions far beyond diagnostics and DNA, attorneys say. Harness Dickey’s Kotsis, for example, says a client recently tried to patent a plant extract with therapeutic properties; it was different from anything in nature, Kotsis argued, because the inventor had altered the relative concentrations of key compounds to enhance its effect. Nope, decided USPTO, too close to nature.
In March, USPTO released draft guidance designed to help its examiners decide such questions, setting out 12 factors for them to weigh. For example, if an examiner deems a product “markedly different in structure” from anything in nature, that counts in its favor. But if it has a “high level of generality,” it gets dinged.
The draft has drawn extensive criticism. “I don’t think I’ve ever seen anything as complicated as this,” says Kevin Bastian, a patent attorney at Kilpatrick Townsend & Stockton in San Francisco, California. “I just can’t believe that this will be the standard.”
USPTO officials appear eager to fine-tune the draft guidance, but patent experts fear the Supreme Court decisions have made it hard to draw clear lines. “The Myriad decision is hopelessly contradictory and completely incoherent,” says Dan Burk, a law professor at the University of California, Irvine. “We know you can’t patent genetic sequences,” he adds, but “we don’t really know why.”
Get creative in using Draft Guidelines!
For now, Kostis says, applicants will have to get creative to reduce the chance of rejection. Rather than claim protection for a plant extract itself, for instance, an inventor could instead patent the steps for using it to treat patients. Other biotech attorneys may try to narrow their patent claims. But there’s a downside to that strategy, they note: Narrower patents can be harder to protect from infringement, making them less attractive to investors. Others plan to wait out the storm, predicting USPTO will ultimately rethink its guidance and ease the way for new patents.
Public comment period extended
USPTO has extended the deadline for public comment to 31 July, with no schedule for issuing final language. Regardless of the outcome, however, Stanek Rea warned a crowd of riled-up attorneys that, in the world of biopatents, “the easy days are gone.”
Manual of Patent Examining Procedure (MPEP)Ninth Edition, March 2014
The USPTO continues to offer an online discussion tool for commenting on selected chapters of the Manual. To participate in the discussion and to contribute your ideas go to: http://uspto-mpep.ideascale.com.
Manual of Patent Examining Procedure (MPEP)Ninth Edition, March 2014
The USPTO continues to offer an online discussion tool for commenting on selected chapters of the Manual. To participate in the discussion and to contribute your ideas go to:http://uspto-mpep.ideascale.com.
The documents updated in the Ninth Edition of the MPEP, dated March 2014, include changes that became effective in November 2013 or earlier.
All of the documents have been updated for the Ninth Edition except Chapters 800, 900, 1000, 1300, 1700, 1800, 1900, 2000, 2300, 2400, 2500, and Appendix P.
More information about the changes and updates is available from the “Blue Page – Introduction” of the Searchable MPEP or from the “Summary of Changes” link to the HTML and PDF versions provided below. Discuss the Manual of Patent Examining Procedure (MPEP) Welcome to the MPEP discussion tool!
We have received many thoughtful ideas on Chapters 100-600 and 1800 of the MPEP as well as on how to improve the discussion site. Each and every idea submitted by you, the participants in this conversation, has been carefully reviewed by the Office, and many of these ideas have been implemented in the August 2012 revision of the MPEP and many will be implemented in future revisions of the MPEP. The August 2012 revision is the first version provided to the public in a web based searchable format. The new search tool is available at http://mpep.uspto.gov. We would like to thank everyone for participating in the discussion of the MPEP.
We have some great news! Chapters 1300, 1500, 1600 and 2400 of the MPEP are now available for discussion. Please submit any ideas and comments you may have on these chapters. Also, don’t forget to vote on ideas and comments submitted by other users. As before, our editorial staff will periodically be posting proposed new material for you to respond to, and in some cases will post responses to some of the submitted ideas and comments.Recently, we have received several comments concerning the Leahy-Smith America Invents Act (AIA). Please note that comments regarding the implementation of the AIA should be submitted to the USPTO via email t aia_implementation@uspto.gov or via postal mail, as indicated at the America Invents Act Web site. Additional information regarding the AIA is available at www.uspto.gov/americainventsact We have also received several comments suggesting policy changes which have been routed to the appropriate offices for consideration. We really appreciate your thinking and recommendations!
After more than 5 years and two draft versions, the final version of the Guidance for
Industry (GfI) – “Electronic Source Data in Clinical Investigations” was published in
September 2013. This new FDA Guidance defines the FDA’s expectations for sponsors,
CROs, investigators and other persons involved in the capture, review and retention of
electronic source data generated in the context of FDA-regulated clinical trials.In an
effort to encourage the modernization and increased efficiency of processes in clinical
trials, the FDA clearly supports the capture of electronic source data and emphasizes
the agency’s intention to support activities aimed at ensuring the reliability, quality,
integrity and traceability of this source data, from its electronic source to the electronic
submission of the data in the context of an authorization procedure. The Guidance
addresses aspects as data capture, data review and record retention. When the
computerized systems used in clinical trials are described, the FDA recommends
that the description not only focus on the intended use of the system, but also on
data protection measures and the flow of data across system components and
interfaces. In practice, the pharmaceutical industry needs to meet significant
requirements regarding organisation, planning, specification and verification of
computerized systems in the field of clinical trials. The FDA also mentions in the
Guidance that it does not intend to apply 21 CFR Part 11 to electronic health records
(EHR). Author: Oliver Herrmann Q-Infiity Source: http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/
Guidances/UCM328691.pdf Webinar: https://collaboration.fda.gov/p89r92dh8wc
Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?
Author and Curator: Larry H Bernstein, MD, FCAP
The evolution of progress we have achieved in cancer research, diagnosis, and therapeutics has originated from an emergence of scientific disciplines and the focus on cancer has been recent. We can imagine this from a historical perspective with respect to two observations. The first is that the oldest concepts of medicine lie with the anatomic dissection of animals and the repeated recurrence of war, pestilence, and plague throughout the middle ages, and including the renaissance. In the awakening, architecture, arts, music, math, architecture and science that accompanied the invention of printing blossomed, a unique collaboration of individuals working in disparate disciplines occurred, and those who were privileged received an education, which led to exploration, and with it, colonialism. This also led to the need to increasingly, if not without reprisal, questioning long-held church doctrines.
It was in Vienna that Rokitansky developed the discipline of pathology, and his student Semelweis identified an association between then unknown infection and childbirth fever. The extraordinary accomplishments of John Hunter in anatomy and surgery came during the twelve years war, and his student, Edward Jenner, observed the association between cowpox and smallpox resistance. The development of a nursing profession is associated with the work of Florence Nightengale during the Crimean War (at the same time as Leo Tolstoy). These events preceded the work of Pasteur, Metchnikoff, and Koch in developing a germ theory, although Semelweis had committed suicide by infecting himself with syphilis. The first decade of the Nobel Prize was dominated by discoveries in infectious disease and public health (Ronald Ross, Walter Reed) and we know that the Civil War in America saw an epidemic of Yellow Fever, and the Armed Services Medical Museum was endowed with a large repository of osteomyelitis specimens. We also recall that the Russian physician and playwriter, Anton Checkov, wrote about the conditions in prison camps.
But the pharmacopeia was about to open with the discoveries of insulin, antibiotics, vitamins, thyroid action (Mayo brothers pioneered thyroid surgery in the thyroid iodine-deficient midwest), and pitutitary and sex hormones (isolatation, crystal structure, and synthesis years later), and Karl Landsteiner’s discovery of red cell antigenic groups (but he also pioneered in discoveries in meningitis and poliomyelitis, and conceived of the term hapten) with the introduction of transfusion therapy that would lead to transplantation medicine. The next phase would be heralded by the discovery of cancer, which was highlighted by the identification of leukemia by Rudolph Virchow, who cautioned about the limitations of microscopy. This period is highlighted by the classic work – “Microbe Hunters”.
John Hunter
Walter Reed
Robert Koch
goldberger 1916 Pellagra
Louis Pasteur
A multidisciplinary approach has led us to a unique multidisciplinary or systems view of cancer, with different fields of study offering their unique expertise, contributions, and viewpoints on the etiology of cancer. Diverse fields in immunology, biology, biochemistry, toxicology, molecular biology, virology, mathematics, social activism and policy, and engineering have made such important contributions to our understanding of cancer, that without cooperation among these diverse fields our knowledge of cancer would never had evolved as it has. In a series of posts “Heroes in Medical Research:” the work of researchers are highlighted as examples of how disparate scientific disciplines converged to produce seminal discoveries which propelled the cancer field, although, at the time, they seemed like serendipitous findings. In the post Heroes in Medical Research: Barnett Rosenberg and the Discovery of Cisplatin (Translating Basic Research to the Clinic) discusses the seminal yet serendipitous discoveries by bacteriologist Dr. Barnett Rosenberg, which eventually led to the development of cisplatin, a staple of many chemotherapeutic regimens. Molecular biologist Dr. Robert Ting, working with soon-to-be Nobel Laureate virologist Dr. James Gallo on AIDS research and the associated Karposi’s sarcoma identified one of the first retroviral oncogenes, revolutionizing previous held misconceptions of the origins of cancer (described in Heroes in Medical Research: Dr. Robert Ting, Ph.D. and Retrovirus in AIDS and Cancer). Located here will be a MONTAGE of PHOTOS of PEOPLE who made seminal discoveries and contributions in every field to cancer Each of these paths of discovery in cancer research have led to the unique strategies of cancer therapeutics and detection for the purpose of reducing the burden of human cancer. However, we must recall that this work has come at great cost, while it is indeed cause for celebration. The current failure rate of clinical trials at over 70 percent, has been a cause for disappointment, and has led to serious reconsideration of how we can proceed with greater success. The result of the evolution of the cancer field is evident in the many parts and chapters of this ebook. Volume 4 contains chapters that are in a predetermined order:
The concepts of neoplasm, malignancy, carcinogenesis, and metastatic potential, which encompass:
(a) How cancer cells bathed in an oxygen rich environment rely on anaerobic glycolysis for energy, and the secondary consequences of cachexia and sarcopenia associated with progression
invasion
ARTS protein and cancer
Glycolysis
Krebs cycle
Metabolic control analysis of respiration in human cancer tissue
akip1-expression-modulates-mitochondrial-function
(b) How advances in genetic analysis, molecular and cellular biology, metabolomics have expanded our basic knowledge of the mechanisms which are involved in cellular transformation to the cancerous state.
nucleotides
Methylation of adenine
ampk-and-ampk-related-kinase-ark-family-
ubiquitylation
(c) How molecular techniques continue to advance our understanding of how genetics, epigenetics, and alterations in cellular metabolism contribute to cancer and afford new pathways for therapeutic intervention.
genomic effects
LKB1AMPK pathway
mutation-frequencies-across-12-cancer-types
AMPK-activating drugs metformin or phenformin might provide protection against cancer
2. The distinct features of cancers of specific tissue sites of origin
3. The diagnosis of cancer by
(a) Clinical presentation
(b) Age of onset and stage of life
(c) Biomarker features
hairy cell leukemia
lymphoma leukemia
(d) Radiological and ultrasound imaging
Treatments
Prognostic differences within and between cancer types
We have introduced the emergence of a disease of great complexity that has been clouded in more questions than answers until the emergence of molecular biology in the mid 20th century, and then had to await further discoveries going into the 21st century. What gave the research impetus was the revelation of
1 the mechanism of transcription of the DNA into amino acid sequences
Proteins in Disease
2 the identification of stresses imposed on cellular function
NO beneficial effects
3 the elucidation of the substructure of the cell – cell membrane, mitochondria, ribosomes, lysosomes – and their functions, respectively
AKIP1 Expression Modulates Mitochondrial Function
4 the elucidation of oligonucleotide sequences
nucleotides
dna-replication-unwinding
dna-replication-ligation
dna-replication-primer-removal
dna-replication-leading-strand
dna-replication-lagging-strand
dna-replication-primer-synthesis
dna-replication-termination
5 the further elucidation of functionally relevant noncoding lncDNA
6 the technology to synthesis mRNA and siRNA sequences
Figure. RNAi and gene silencing
7 the repeated discovery of isoforms of critical enzymes and their pleiotropic properties
8. the regulatory pathways involved in signaling
Figure. Signaling Pathways Map
This is a brief outline of the modern progression of advances in our understanding of cancer. Let us go back to the beginning and check out a sequence of Nobel Prizes awarded and related discoveries that have a historical relationship to what we know. The first discovery was the finding by Louis Pasteur that fungi that grew in an oxygen poor environment did not put down filaments. They did not utilize oxygen and they produced used energy by fermentation. This was the basis for Otto Warburg sixty years later to make the comparison to cancer cells that grew in the presence of oxygen, but relied on anaerobic glycolysis. He used a manometer to measure respiration in tissue one cell layer thick to measure CO2 production in an adiabatic system.
Lavoisier Antoine-Laurent and Laplace Pierre-Simon (1783) Memoir on heat. Mémoirs de l’Académie des sciences. Translated by Guerlac H, Neale Watson Academic Publications, New York, 1982.
The Warburg apparatus is a manometric respirometer which was used for decades in biochemistry for measuring oxygen consumption of tissue homogenates or tissue slices.
The aqueous phase is vigorously shaken to equilibrate with a gas phase, from which oxygen is consumed while the evolved carbon dioxide is trapped, such that the pressure in the constant-volume gas phase drops proportional to oxygen consumption. The Warburg apparatus was introduced to study cell respiration, i.e. the uptake of molecular oxygen and the production of carbon dioxide by cells or tissues. Its applications were extended to the study of fermentation, when gas exchange takes place in the absence of oxygen. Thus the Warburg apparatus became established as an instrument for both aerobic and anaerobic biochemical studies [2, 3].
The respiration chamber was a detachable glass flask (F) equipped with one or more sidearms (S) for additions of chemicals and an open connection to a manometer (M; pressure gauge). A constant temperature was provided by immersion of the Warburg chamber in a constant temperature water bath. At thermal mass transfer equilibrium, an initial reading is obtained on the manometer, and the volume of gas produced or absorbed is determined at specific time intervals. A limited number of ‘titrations’ can be performed by adding the liquid contained in a side arm into the main reaction chamber. A Warburg apparatus may be equipped with more than 10 respiration chambers shaking in a common water bath. Since temperature has to be controlled very precisely in a manometric approach, the early studies on mammalian tissue respiration were generally carried out at a physiological temperature of 37 °C.
The Warburg apparatus has been replaced by polarographic instruments introduced by Britton Chance in the 1950s. Since Chance and Williams (1955) measured respiration of isolated mitochondria simultaneously with the spectrophotometric determination of cytochrome redox states, a water chacket could not be used, and measurements were carried out at room temperature (or 25 °C). Thus most later studies on isolated mitochondria were shifted to the artifical temperature of 25 °C.
Today, the importance of investigating mitochondrial performance at in vivo temperatures is recognized again in mitochondrial physiology. Incubation times of 1 hour were typical in experiments with the Warburg apparatus, but were reduced to a few or up to 20 min, following Chance and Williams, due to rapid oxygen depletion in closed, aqueous phase oxygraphs with high sample concentrations. Today, incubation times of 1 hour are typical again in high-resolution respirometry, with low sample concentrations and the option of reoxygenations.
Oesper P (1964) The history of the Warburg apparatus: Some reminiscences on its use. J Chem Educ 41: 294.
Koppenol WH, Bounds PL, Dang CV (2011) Otto Warburg’s contributions to current concepts of cancer metabolism. Nature Reviews Cancer 11: 325-337.
Gnaiger E, Kemp RB (1990) Anaerobic metabolism in aerobic mammalian cells: information from the ratio of calorimetric heat flux and respirometric oxygen flux. Biochim Biophys Acta 1016: 328-332. – “At high fructose concentrations, respiration is inhibited while glycolytic end products accumulate, a phenomenon known as the Crabtree effect. It is commonly believed that this effect is restricted to microbial and tumour cells with uniquely high glycolytic capacities (Sussman et al, 1980). However, inhibition of respiration and increase of lactate production are observed under aerobic conditions in beating rat heart cell cultures (Frelin et al, 1974) and in isolated rat lung cells (Ayuso-Parrilla et al, 1978). Thus, the same general mechanisms responsible for the integration of respiration and glycolysis in tumour cells (Sussman et al, 1980) appear to be operating to some extent in several isolated mammalian cells.”
Mitochondria are sometimes described as “cellular power plants” because they generate most of the cell’s supply of adenosine triphosphate (ATP), used as a source of chemical energy.[2] In addition to supplying cellular energy, mitochondria are involved in other tasks such as signaling, cellular differentiation, cell death, as well as the control of the cell cycle and cell growth.[3] The organelle is composed of compartments that carry out specialized functions. These compartments or regions include the outer membrane, the intermembrane space, the inner membrane, and the cristae and matrix. Mitochondrial proteins vary depending on the tissue and the species. In humans, 615 distinct types of proteins have been identified from cardiac mitochondria,[9Leonor Michaelis discovered that Janus green can be used as a supravital stain for mitochondria in 1900. Benjamin F. Kingsbury, in 1912, first related them with cell respiration, but almost exclusively based on morphological observations.[13] In 1913 particles from extracts of guinea-pig liver were linked to respiration by Otto Heinrich Warburg, which he called “grana”. Warburg and Heinrich Otto Wieland, who had also postulated a similar particle mechanism, disagreed on the chemical nature of the respiration. It was not until 1925 when David Keilin discovered cytochromes that the respiratory chain was described.[13]
The Clark Oxygen Sensor
Dr. Leland Clark – inventor of the “Clark Oxygen Sensor” (1954); the Clark type polarographic oxygen sensor remains the gold standard for measuring dissolved oxygen in biomedical, environmental and industrial applications . ‘The convenience and simplicity of the polarographic ‘oxygen electrode’ technique for measuring rapid changes in the rate of oxygen utilization by cellular and subcellular systems is now leading to its more general application in many laboratories. The types and design of oxygen electrodes vary, depending on the investigator’s ingenuity and specific requirements of the system under investigation.’Estabrook R (1967) Mitochondrial respiratory control and the polarographic measurement of ADP:O ratios. Methods Enzymol. 10: 41-47. “one approach that is underutilized in whole-cell bioenergetics, and that is accessible as long as cells can be obtained in suspension, is the oxygen electrode, which can obtain more precise information on the bioenergetic status of the in situ mitochondria than more ‘high-tech’ approaches such as fluorescent monitoring ofΔψm.” Nicholls DG, Ferguson S (2002) Bioenergetics 3. Academic Press, London.
Great Figures in Cancer
Dr. Elizabeth Blackburn,
j_michael_bishop onogene
Harold Varmus
Potts and Habener (PTH mRNA, Harvard MIT) JCI
JCI Fuller Albright and hPTH AA sequence
Dr. E. Donnall Thomas Bone Marrow Transplants
Dr Haraldzur Hausen EBV HPV
Dr. Craig Mello
Lee Hartwell – Hutchinson Cancer Res Center
Judah Folkman, MD
Gertrude B. Elien (1918-1999)
The Nobel Prize in Physiology or Medicine 1922
Archibald V. Hill, Otto Meyerhof
AV Hill –
“the production of heat in the muscle” Hill started his research work in 1909. It was due to J.N. Langley, Head of the Department of Physiology at that time that Hill took up the study on the nature of muscular contraction. Langley drew his attention to the important (later to become classic) work carried out by Fletcher and Hopkins on the problem of lactic acid in muscle, particularly in relation to the effect of oxygen upon its removal in recovery. In 1919 he took up again his study of the physiology of muscle, and came into close contact with Meyerhof of Kiel who, approaching the problem differently, arrived at results closely analogous to his study. In 1919 Hill’s friend W. Hartree, mathematician and engineer, joined in the myothermic investigations – a cooperation which had rewarding results.
Otto Meyerhof –
otto-fritz-meyerhof
lactic acid production in muscle contraction Under the influence of Otto Warburg, then at Heidelberg, Meyerhof became more and more interested in cell physiology. In 1923 he was offered a Professorship of Biochemistry in the United States, but Germany was unwilling to lose him. In 1929 he was he was placed in charge of the newly founded Kaiser Wilhelm Institute for Medical Research at Heidelberg. From 1938 to 1940 he was Director of Research at the Institut de Biologie physico-chimique at Paris, but in 1940 he moved to the United States, where the post of Research Professor of Physiological Chemistry had been created for him by the University of Pennsylvania and the Rockefeller Foundation. Meyerhof’s own account states that he was occupied chiefly with oxidation mechanisms in cells and with extending methods of gas analysis through the calorimetric measurement of heat production, and especially the respiratory processes of nitrifying bacteria. The physico-chemical analogy between oxygen respiration and alcoholic fermentation caused him to study both these processes in the same subject, namely, yeast extract. By this work he discovered a co-enzyme of respiration, which could be found in all the cells and tissues up till then investigated. At the same time he also found a co-enzyme of alcoholic fermentation. He also discovered the capacity of the SH-group to transfer oxygen; after Hopkins had isolated from cells the SH bodies concerned, Meyerhof showed that the unsaturated fatty acids in the cell are oxidized with the help of the sulfhydryl group. After studying closer the respiration of muscle, Meyerhof investigated the energy changes in muscle. Considerable progress had been achieved by the English scientists Fletcher and Hopkins by their recognition of the fact that lactic acid formation in the muscle is closely connected with the contraction process. These investigations were the first to throw light upon the highly paradoxical fact, already established by the physiologist Hermann, that the muscle can perform a considerable part of its external function in the complete absence of oxygen.
But it was indisputable that in the last resort the energy for muscle activity comes from oxidation, so the connection between activity and combustion must be an indirect one, and observed that in the absence of oxygen in the muscle, lactic acid appears, slowly in the relaxed state and rapidly in the active state, disappearing in the presence of oxygen. Obviously, then, oxygen is involved when muscle is in the relaxed state. http://upload.wikimedia.org/wikipedia/commons/e/e1/Glycolysis.jpg
The Nobel Prize committee had been receiving nominations intermittently for the previous 14 years (for Eijkman, Funk, Goldberger, Grijns, Hopkins and Suzuki but, strangely, not for McCollum in this period). Tthe Committee for the 1929 awards apparently agreed that it was high time to honor the discoverer(s) of vitamins; but who were they? There was a clear case for Grijns, but he had not been re-nominated for that particular year, and it could be said that he was just taking the relatively obvious next steps along the new trail that had been laid down by Eijkman, who was also now an old man in poor health, but there was no doubt that he had taken the first steps in the use of an animal model to investigate the nutritional basis of a clinical disorder affecting millions. Goldberger had been another important contributor, but his recent death put him out of consideration. The clearest evidence for lack of an unknown “something” in a mammalian diet was presented by Gowland Hopkins in 1912. This Cambridge biochemist was already well known for having isolated the amino acid tryptophan from a protein and demonstrated its essential nature. He fed young rats on an experimental diet, half of them receiving a daily milk supplement, and only those receiving milk grew well, Hopkins suggested that this was analogous to human diseases related to diet, as he had suggested already in a lecture published in 1906. Hopkins, the leader of the “dynamic biochemistry” school in Britain and an influential advocate for the importance of vitamins, was awarded the prize jointly with Eijkman. A door was opened. Recognition of work on the fat-soluble vitamins begun by McCollum. The next award related to vitamins was given in 1934 to George Whipple, George Minot and William Murphy “for their discoveries concerning liver therapy in cases of [then incurable pernicious] anemia,” The essential liver factor (cobalamin, or vitamin B12) was isolated in 1948, and Vitamin B12 was absent from plant foods. But William Castle in 1928 had demonstrated that the stomachs of pernicious anemia patients were abnormal in failing to secrete an “intrinsic factor”.
Szent-Györgyi was a Hungarian biochemist who had worked with Otto Warburg and had a special interest in oxidation-reduction mechanisms. He was invited to Cambridge in England in 1927 after detecting an antioxidant compound in the adrenal cortex, and there, he isolated a compound that he named hexuronic acid. Charles Glen King of the University of Pittsburgh reported success In isolating the anti-scorbutic factor in 1932, and added that his crystals had all the properties reported by Szent-Györgyi for hexuronic acid. But his work on oxidation reactions was also important. Fumarate is an intermediate in the citric acid cycle used by cells to produce energy in the form of adenosine triphosphate (ATP) from food. It is formed by the oxidation of succinate by the enzyme succinate dehydrogenase. Fumarate is then converted by the enzyme fumarase to malate. An enzyme adds water to the fumarate molecule to form malate. The malate is created by adding one hydrogen atom to a carbon atom and then adding a hydroxyl group to a carbon next to a terminal carbonyl group.
In the same year, Norman Haworth from the University of Birmingham in England received a Nobel prize from the Chemistry Committee for having advanced carbohydrate chemistry and, specifically, for having worked out the structure of Szent-Györgyi’s crystals, and then been able to synthesize the vitamin. This was a considerable achievement. The Nobel Prize in Chemistry was shared with the Swiss organic chemist Paul Karrer, cited for his work on the structures of riboflavin and vitamins A and E as well as other biologically interesting compounds. This was followed in 1938 by a further Chemistry award to the German biochemist Richard Kuhn, who had also worked on carotenoids and B-vitamins, including riboflavin and pyridoxine. But Karrer was not permitted to leave Germany at that time by the Nazi regime. However, the American work with radioisotopes at Lawrence Livermore Laboratory, UC Berkeley, was already ushering in a new era of biochemistry that would enrich our studies of metabolic pathways. The importance of work involving vitamins was acknowledged in at least ten awards in the 20th century.
1. Carpenter, K.J., Beriberi, White Rice and Vitamin B, University of California Press, Berkeley (2000).
2. Weatherall, M.W. and Kamminga, H., The making of a biochemist: the construction of Frederick Gowland Hopkins’ reputation. Medical History vol.40, pp. 415-436 (1996).
3. Becker, S.L., Will milk make them grow? An episode in the discovery of the vitamins. In Chemistry and Modern Society (J. Parascandela, editor) pp. 61-83, American Chemical Society,
Washington, D.C. (1983).
4. Carpenter, K.J., The History of Scurvy and Vitamin C, Cambridge University Press, New York (1986).
Transport and metabolism of exogenous fumarate and 3-phosphoglycerate in vascular smooth muscle.
The keto (linear) form of exogenous fructose 1,6-bisphosphate, a highly charged glycolytic intermediate, may utilize a dicarboxylate transporter to cross the cell membrane, support glycolysis, and produce ATP anaerobically. We tested the hypothesis that fumarate, a dicarboxylate, and 3-phosphoglycerate (3-PG), an intermediate structurally similar to a dicarboxylate, can support contraction in vascular smooth muscle during hypoxia. 3-PG improved maintenance of force (p < 0.05) during the 30-80 min period of hypoxia. Fumarate decreased peak isometric force development by 9.5% (p = 0.008) but modestly improved maintenance of force (p < 0.05) throughout the first 80 min of hypoxia. 13C-NMR on tissue extracts and superfusates revealed 1,2,3,4-(13)C-fumarate (5 mM) metabolism to 1,2,3,4-(13)C-malate under oxygenated and hypoxic conditions suggesting uptake and metabolism of fumarate. In conclusion, exogenous fumarate and 3-PG readily enter vascular smooth muscle cells, presumably by a dicarboxylate transporter, and support energetically important pathways.
Comparison of endogenous and exogenous sources of ATP in fueling Ca2+ uptake in smooth muscle plasma membrane vesicles.
A smooth muscle plasma membrane vesicular fraction (PMV) purified for the (Ca2+/Mg2+)-ATPase has endogenous glycolytic enzyme activity. In the presence of glycolytic substrate (fructose 1,6-diphosphate) and cofactors, PMV produced ATP and lactate and supported calcium uptake. The endogenous glycolytic cascade supports calcium uptake independent of bath [ATP]. A 10-fold dilution of PMV, with the resultant 10-fold dilution of glycolytically produced bath [ATP] did not change glycolytically fueled calcium uptake (nanomoles per milligram protein). Furthermore, the calcium uptake fueled by the endogenous glycolytic cascade persisted in the presence of a hexokinase-based ATP trap which eliminated calcium uptake fueled by exogenously added ATP. Thus, it appears that the endogenous glycolytic cascade fuels calcium uptake in PMV via a membrane-associated pool of ATP and not via an exchange of ATP with the bulk solution. To determine whether ATP produced endogenously was utilized preferentially by the calcium pump, the ATP production rates of the endogenous creatine kinase and pyruvate kinase were matched to that of glycolysis and the calcium uptake fueled by the endogenous sources was compared with that fueled by exogenous ATP added at the same rate. The rate of calcium uptake fueled by endogenous sources of ATP was approximately twice that supported by exogenously added ATP, indicating that the calcium pump preferentially utilizes ATP produced by membrane-bound enzymes.
Evidence for succinate production by reduction of fumarate during hypoxia in isolated adult rat heart cells.
Archives of Biochemistry and Biophysics (Impact Factor: 3.37). 01/1988; 259(2):527-35. http://dx.doi.org:/10.1016/0003-9861(87)90519-4 It has been demonstrated that perfusion of myocardium with glutamic acid or tricarboxylic acid cycle intermediates during hypoxia or ischemia, improves cardiac function, increases ATP levels, and stimulates succinate production. In this study isolated adult rat heart cells were used to investigate the mechanism of anaerobic succinate formation and examine beneficial effects attributed to ATP generated by this pathway. Myocytes incubated for 60 min under hypoxic conditions showed a slight loss of ATP from an initial value of 21 +/- 1 nmol/mg protein, a decline of CP from 42 to 17 nmol/mg protein and a fourfold increase in lactic acid production to 1.8 +/- 0.2 mumol/mg protein/h. These metabolite contents were not altered by the addition of malate and 2-oxoglutarate to the incubation medium nor were differences in cell viability observed; however, succinate release was substantially accelerated to 241 +/- 53 nmol/mg protein. Incubation of cells with [U-14C]malate or [2-U-14C]oxoglutarate indicates that succinate is formed directly from malate but not from 2-oxoglutarate. Moreover, anaerobic succinate formation was rotenone sensitive.
We conclude that malate reduction to succinate occurs via the reverse action of succinate dehydrogenase in a coupled reaction where NADH is oxidized (and FAD reduced) and ADP is phosphorylated.Furthermore, by transaminating with aspartate to produce oxaloacetate, 2-oxoglutarate stimulates cytosolic malic dehydrogenase activity, whereby malate is formed and NADH is oxidized.
In the form of malate, reducing equivalents and substrate are transported into the mitochondria where they are utilized for succinate synthesis.
1953 Hans Adolf Krebs –
” discovery of the citric acid cycle” and In the course of the 1920’s and 1930’s great progress was made in the study of the intermediary reactions by which sugar is anaerobically fermented to lactic acid or to ethanol and carbon dioxide. The success was mainly due to the joint efforts of the schools of Meyerhof, Embden, Parnas, von Euler, Warburg and the Coris, who built on the pioneer work of Harden and of Neuberg. This work brought to light the main intermediary steps of anaerobic fermentations.
In contrast, very little was known in the earlier 1930’s about the intermediary stages through which sugar is oxidized in living cells. When, in 1930, I left the laboratory of Otto Warburg (under whose guidance I had worked since 1926 and from whom I have learnt more than from any other single teacher), I was confronted with the question of selecting a major field of study and I felt greatly attracted by the problem of the intermediary pathway of oxidations.
These reactions represent the main energy source in higher organisms, and in view of the importance of energy production to living organisms (whose activities all depend on a continuous supply of energy) the problem seemed well worthwhile studying. http://www.johnkyrk.com/krebs.html
Interactive Krebs cycle
There are different points where metabolites enter the Krebs’ cycle. Most of the products of protein, carbohydrates and fat metabolism are reduced to the molecule acetyl coenzyme A that enters the Krebs’ cycle. Glucose, the primary fuel in the body, is first metabolized into pyruvic acid and then into acetyl coenzyme A. The breakdown of the glucose molecule forms two molecules of ATP for energy in the Embden Meyerhof pathway process of glycolysis.
On the other hand, amino acids and some chained fatty acids can be metabolized into Krebs intermediates and enter the cycle at several points. When oxygen is unavailable or the Krebs’ cycle is inhibited, the body shifts its energy production from the Krebs’ cycle to the Embden Meyerhof pathway of glycolysis, a very inefficient way of making energy.
Fritz Albert Lipmann –
“discovery of co-enzyme A and its importance for intermediary metabolism”.
In my development, the recognition of facts and the rationalization of these facts into a unified picture, have interplayed continuously. After my apprenticeship with Otto Meyerhof, a first interest on my own became the phenomenon we call the Pasteur effect, this peculiar depression of the wasteful fermentation in the respiring cell. By looking for a chemical explanation of this economy measure on the cellular level, I was prompted into a study of the mechanism of pyruvic acid oxidation, since it is at the pyruvic stage where respiration branches off from fermentation.
For this study I chose as a promising system a relatively simple looking pyruvic acid oxidation enzyme in a certain strain of Lactobacillus delbrueckii1. In 1939, experiments using minced muscle cells demonstrated that one oxygen atom can form two adenosine triphosphate molecules, and, in 1941, the concept of phosphate bonds being a form of energy in cellular metabolism was developed by Fritz Albert Lipmann.
In the following years, the mechanism behind cellular respiration was further elaborated, although its link to the mitochondria was not known.[13]The introduction of tissue fractionation by Albert Claude allowed mitochondria to be isolated from other cell fractions and biochemical analysis to be conducted on them alone. In 1946, he concluded that cytochrome oxidase and other enzymes responsible for the respiratory chain were isolated to the mitchondria. Over time, the fractionation method was tweaked, improving the quality of the mitochondria isolated, and other elements of cell respiration were determined to occur in the mitochondria.[13]
The most important event during this whole period, I now feel, was the accidental observation that in the L. delbrueckii system, pyruvic acid oxidation was completely dependent on the presence of inorganic phosphate. This observation was made in the course of attempts to replace oxygen by methylene blue. To measure the methylene blue reduction manometrically, I had to switch to a bicarbonate buffer instead of the otherwise routinely used phosphate. In bicarbonate, pyruvate oxidation was very slow, but the addition of a little phosphate caused a remarkable increase in rate. The phosphate effect was removed by washing with a phosphate free acetate buffer. Then it appeared that the reaction was really fully dependent on phosphate.
A coupling of this pyruvate oxidation with adenylic acid phosphorylation was attempted. Addition of adenylic acid to the pyruvic oxidation system brought out a net disappearance of inorganic phosphate, accounted for as adenosine triphosphate. The acetic acid subunit of acetyl CoA is combined with oxaloacetate to form a molecule of citrate. Acetyl coenzyme A acts only as a transporter of acetic acid from one enzyme to another. After Step 1, the coenzyme is released by hydrolysis to combine with another acetic acid molecule and begin the Krebs’ Cycle again.
Hugo Theorell –
“the nature and effects of oxidation enzymes”
From 1933 until 1935 Theorell held a Rockefeller Fellowship and worked with Otto Warburg at Berlin-Dahlem, and here he became interested in oxidation enzymes. At Berlin-Dahlem he produced, for the first time, the oxidation enzyme called «the yellow ferment» and he succeeded in splitting it reversibly into a coenzyme part, which was found to be flavin mononucleotide, and a colourless protein part. On return to Sweden, he was appointed Head of the newly established Biochemical Department of the Nobel Medical Institute, which was opened in 1937.
Succinate is oxidized by a molecule of FAD (Flavin Adenine Dinucleotide). The FAD removes two hydrogen atoms from the succinate and forms a double bond between the two carbon atoms to create fumarate.
They followed the path that became clear from intense collaborative work in California by George Beadle, by Avery and McCarthy, Max Delbruck, TH Morgan, Max Delbruck and by Chargaff that indicated that genetics would be important.
1965
François Jacob, André Lwoff and Jacques Monod –
” genetic control of enzyme and virus synthesis”.
In 1958 the remarkable analogy revealed by genetic analysis of lysogeny and that of the induced biosynthesis of ß-galactosidase led François Jacob, with Jacques Monod, to study the mechanisms responsible for the transfer of genetic information as well as the regulatory pathways which, in the bacterial cell, adjust the activity and synthesis of macromolecules. Following this analysis, Jacob and Monod proposed a series of new concepts, those of messenger RNA, regulator genes, operons and allosteric proteins.
Francois Jacob
Having determined the constants of growth in the presence of different carbohydrates, it occurred to me that it would be interesting to determine the same constants in paired mixtures of carbohydrates. From the first experiment on, I noticed that, whereas the growth was kinetically normal in the presence of certain mixtures (that is, it exhibited a single exponential phase), two complete growth cycles could be observed in other carbohydrate mixtures, these cycles consisting of two exponential phases separated by a-complete cessation of growth.
Lwoff, after considering this strange result for a moment, said to me, “That could have something to do with enzyme adaptation.”
“Enzyme adaptation? Never heard of it!” I said.
Lwoff’s only reply was to give me a copy of the then recent work of Marjorie Stephenson, in which a chapter summarized with great insight the still few studies concerning this phenomenon, which had been discovered by Duclaux at the end of the last century. Studied by Dienert and by Went as early as 1901 and then by Euler and Josephson, it was more or less rediscovered by Karström, who should be credited with giving it a name and attracting attention to its existence.
Lwoff’s intuition was correct. The phenomenon of “diauxy” that I had discovered was indeed closely related to enzyme adaptation, as my experiments, included in the second part of my doctoral dissertation, soon convinced me. It was actually a case of the “glucose effect” discovered by Dienert as early as 1900. That agents that uncouple oxidative phosphorylation, such as 2,4-dinitrophenol, completely inhibit adaptation to lactose or other carbohydrates suggested that “adaptation” implied an expenditure of chemical potential and therefore probably involved the true synthesis of an enzyme.
With Alice Audureau, I sought to discover the still quite obscure relations between this phenomenon and the one Massini, Lewis, and others had discovered: the appearance and selection of “spontaneous” mutants. We showed that an apparently spontaneous mutation was allowing these originally “lactose-negative” bacteria to become “lactose-positive”. However, we proved that the original strain (Lac-) and the mutant strain (Lac+) did not differ from each other by the presence of a specific enzyme system, but rather by the ability to produce this system in the presence of lactose. This mutation involved the selective control of an enzyme by a gene, and the conditions necessary for its expression seemed directly linked to the chemical activity of the system.
1974
Albert Claude, Christian de Duve and George E. Palade –
” the structural and functional organization of the cell”.
I returned to Louvain in March 1947 after a period of working with Theorell in Sweden, the Cori’s, and E Southerland in St. Louis, fortunate in the choice of my mentors, all sticklers for technical excellence and intellectual rigor, those prerequisites of good scientific work. Insulin, together with glucagon which I had helped rediscover, was still my main focus of interest, and our first investigations were accordingly directed on certain enzymatic aspects of carbohydrate metabolism in liver, which were expected to throw light on the broader problem of insulin action. But I became distracted by an accidental finding related to acid phosphatase, drawing most of my collaborators along with me. The studies led to the discovery of the lysosome, and later of the peroxisome.
In 1962, I was appointed a professor at the Rockefeller Institute in New York, now the Rockefeller University, the institution where Albert Claude had made his pioneering studies between 1929 and 1949, and where George Palade had been working since 1946. In New York, I was able to develop a second flourishing group, which follows the same general lines of research as the Belgian group, but with a program of its own.
1968
Robert W. Holley, Har Gobind Khorana and Marshall W. Nirenberg –
“interpretation of the genetic code and its function in protein synthesis”.
1969
Max Delbrück, Alfred D. Hershey and Salvador E. Luria –
” the replication mechanism and the genetic structure of viruses”.
1975 David Baltimore, Renato Dulbecco and Howard Martin Temin –
” the interaction between tumor viruses and the genetic material of the cell”.
1976
Baruch S. Blumberg and D. Carleton Gajdusek –
” new mechanisms for the origin and dissemination of infectious diseases” The editors of the Nobelprize.org website of the Nobel Foundation have asked me to provide a supplement to the autobiography that I wrote in 1976 and to recount the events that happened after the award. Much of what I will have to say relates to the scientific developments since the last essay. These are described in greater detail in a scientific memoir first published in 2002 (Blumberg, B. S., Hepatitis B. The Hunt for a Killer Virus, Princeton University Press, 2002, 2004).
1980
Baruj Benacerraf, Jean Dausset and George D. Snell
” genetically determined structures on the cell surface that regulate immunological reactions”.
1992
Edmond H. Fischer and Edwin G. Krebs
“for their discoveries concerning reversible protein phosphorylation as a biological regulatory mechanism”
1994
Alfred G. Gilman and Martin Rodbell –
“G-proteins and the role of these proteins in signal transduction in cells”
2011
Bruce A. Beutler and Jules A. Hoffmann –
” the activation of innate immunity“and the other half to Ralph M. Steinman – “the dendritic cell and its role in adaptive immunity”.
Renato L. Baserga, M.D.
Kimmel Cancer Center and Keck School of Medicine
Dr. Baserga’s research focuses on the multiple roles of the type 1 insulin-like growth factor receptor (IGF-IR) in the proliferation of mammalian cells. The IGF-IR activated by its ligands is mitogenic, is required for the establishment and the maintenance of the transformed phenotype, and protects tumor cells from apoptosis. It, therefore, serves as an excellent target for therapeutic interventions aimed at inhibiting abnormal growth. In basic investigations, this group is presently studying the effects that the number of IGF-IRs and specific mutations in the receptor itself have on its ability to protect cells from apoptosis.
This investigation is strictly correlated with IGF-IR signaling, and part of this work tries to elucidate the pathways originating from the IGF-IR that are important for its functional effects. Baserga’s group has recently discovered a new signaling pathway used by the IGF-IR to protect cells from apoptosis, a unique pathway that is not used by other growth factor receptors. This pathway depends on the integrity of serines 1280-1283 in the C-terminus of the receptor, which bind 14.3.3 and cause the mitochondrial translocation of Raf-1.
Another recent discovery of this group has been the identification of a mechanism by which the IGF-IR can actually induce differentiation in certain types of cells. When cells have IRS-1 (a major substrate of the IGF-IR), the IGF-IR sends a proliferative signal; in the absence of IRS-1, the receptor induces cell differentiation. The extinction of IRS-1 expression is usually achieved by DNA methylation.
Janardan Reddy, MD
Northwestern University
The central effort of our research has been on a detailed analysis at the cellular and molecular levels of the pleiotropic responses in liver induced by structurally diverse classes of chemicals that include fibrate class of hypolipidemic drugs, and phthalate ester plasticizers, which we designated hepatic peroxisome proliferators. Our work has been central to the establishment of several principles, namely that hepatic peroxisome proliferation is associated with increases in fatty acid oxidation systems in liver, and that peroxisome proliferators, as a class, are novel nongenotoxic hepatocarcinogens.
We introduced the concept that sustained generation of reactive oxygen species leads to oxidative stress and serves as the basis for peroxisome proliferator-induced liver cancer development. Furthermore, based on the tissue/cell specificity of pleiotropic responses and the coordinated transcriptional regulation of fatty acid oxidation system genes, we postulated that peroxisome proliferators exert their action by a receptor-mediated mechanism. This receptor concept laid the foundation for the discovery of
a three member peroxisome proliferator-activated receptor (PPARalpha-, ß-, and gamma) subfamily of nuclear receptors.
PPARalpha is responsible for peroxisome proliferator-induced pleiotropic responses, including
hepatocarcinogenesis and energy combustion as it serves as a fatty acid sensor and regulates fatty acid oxidation.
Our current work focuses on the molecular mechanisms responsible for PPAR action and generation of fatty acid oxidation deficient mouse knockout models. Transcription of specific genes by nuclear receptors is a complex process involving the participation of multiprotein complexes composed of transcription coactivators.
Jose Delgado de Salles Roselino, Ph.D.
Leloir Institute, Brazil
Warburg effect, in reality “Pasteur-effect” was the first example of metabolic regulation described. A decrease in the carbon flux originated at the sugar molecule towards the end metabolic products, ethanol and carbon dioxide that was observed when yeast cells were transferred from anaerobic environmental condition to an aerobic one. In Pasteur´s works, sugar metabolism was measured mainly by the decrease of sugar concentration in the yeast growth media observed after a measured period of time. The decrease of the sugar concentration in the media occurs at great speed in yeast grown in anaerobiosis condition and its speed was greatly reduced by the transfer of the yeast culture to an aerobic condition. This finding was very important for the wine industry of France in Pasteur time, since most of the undesirable outcomes in the industrial use of yeast were perceived when yeasts cells took very long time to create a rather selective anaerobic condition. This selective culture media was led by the carbon dioxide higher levels produced by fast growing yeast cells and by a great alcohol content in the yeast culture media. This finding was required to understand Lavoisier’s results indicating that chemical and biological oxidation of sugars produced the same calorimetric results. This observation requires a control mechanism (metabolic regulation) to avoid burning living cells by fast heat released by the sugar biological oxidative processes (metabolism). In addition, Lavoisier´s results were the first indications that both processes happened inside similar thermodynamics limits.
In much resumed form, these observations indicates the major reasons that led Warburg to test failure in control mechanisms in cancer cells in comparison with the ones observed in normal cells. Biology inside classical thermo dynamics poses some challenges to scientists. For instance, all classical thermodynamics must be measured in reversible thermodynamic conditions. In an isolated system, increase in P (pressure) leads to decrease in V (volume) all this in a condition in which infinitesimal changes in one affects in the same way the other, a continuum response. Not even a quantic amount of energy will stand beyond those parameters. In a reversible system, a decrease in V, under same condition, will led to an increase in P.
In biochemistry, reversible usually indicates a reaction that easily goes from A to B or B to A. This observation confirms the important contribution of E Schrodinger in his What´s Life: “This little book arose from a course of public lectures, delivered by a theoretical physicist to an audience of about four hundred which did not substantially dwindle, though warned at the outset that the subject-matter was a difficult one and that the lectures could not be termed popular, even though the physicist’s most dreaded weapon, mathematical deduction, would hardly be utilized. The reason for this was not that the subject was simple enough to be explained without mathematics, but rather that it was much too involved to be fully accessible to mathematics.”
Hans Krebs describes the cyclic nature of the citrate metabolism. Two major research lines search to understand the mechanism of energy transfer that explains how ADP is converted into ATP. One followed the organic chemistry line of reasoning and therefore, searched how the breakdown of carbon-carbon link could have its energy transferred to ATP synthesis. A major leader of this research line was B. Chance who tried to account for two carbon atoms of acetyl released as carbon dioxide in the series of Krebs cycle reactions. The intermediary could store in a phosphorylated amino acid the energy of carbon-carbon bond breakdown. This activated amino acid could transfer its phosphate group to ADP producing ATP. Alternatively, under the possible influence of the excellent results of Hodgkin and Huxley a second line of research appears.
The work of Hodgkin & Huxley indicated the storage of electrical potential energy in transmembrane ionic asymmetries and presented the explanation for the change from resting to action potential in excitable cells. This second line of research, under the leadership of P Mitchell postulated a mechanism for the transfer of oxide/reductive power of organic molecules oxidation through electron transfer as the key for energetic transfer mechanism required for ATP synthesis. Paul Boyer could present how the energy was transduced by a molecular machine that changes in conformation in a series of 3 steps while rotating in one direction in order to produce ATP and in opposite direction in order to produce ADP plus Pi from ATP (reversibility). Nonetheless, a victorious Peter Mitchell obtained the correct result in the conceptual dispute, over the B. Chance point of view, after he used E. Coli mutants to show H gradients in membrane and its use as energy source.
However, this should not detract from the important work of Chance. B. Chance got the simple and rapid polarographic assay method of oxidative phosphorylation and the idea of control of energy metabolism that bring us back to Pasteur. This second result seems to have been neglected in searching for a single molecular mechanism required for the understanding of the buildup of chemical reserve in our body. In respiring mitochondria the rate of electron transport, and thus the rate of ATP production, is determined primarily by the relative concentrations of ADP, ATP and phosphate in the external media (cytosol) and not by the concentration of respiratory substrate as pyruvate. Therefore, when the yield of ATP is high as is in aerobiosis and the cellular use of ATP is not changed, the oxidation of pyruvate and therefore of glycolysis is quickly (without change in gene expression), throttled down to the resting state. The dependence of respiratory rate on ADP concentration is also seen in intact cells. A muscle at rest and using no ATP has very low respiratory rate.
I have had an ongoing discussion with Jose Eduardo de Salles Roselino, inBrazil. He has made important points that need to be noted.
The constancy of composition which animals maintain in the environment surrounding their cells is one of the dominant features of their physiology. Although this phenomenon, homeostasis, has held the interest of biologists over a long period of time, the elucidation of the molecular basis for complex processes such as temperature control and the maintenance of various substances at constant levels in the blood has not yet been achieved. By comparison, metabolic regulation in microorganisms is much better understood, in part because the microbial physiologist has focused his attention on enzyme-catalyzed reactions and their control, as these are among the few activities of microorganisms amenable to quantitative study. Furthermore, bacteria are characterized by their ability to make rapid and efficient adjustments to extensive variations in most parameters of their environment; therefore, they exhibit a surprising lack of rigid requirements for their environment, and appears to influence it only as an incidental result of their metabolism. Animal cells on the other hand have only a limited capacity for adjustment and therefore require a constant milieu. Maintenance of such constancy appears to be a major goal in their physiology (Regulation of Biosynthetic Pathways H.S. Moyed and H EUmbarger Phys Rev,42 444 (1962)).
A living cell consists in a large part of a concentrated mixture of hundreds of different enzymes, each a highly effective catalyst for one or more chemical reactions involving other components of the cell. The paradox of intense and highly diverse chemical activity on the one hand and strongly poised chemical stability (biological homeostasis) on the other is one of the most challenging problems of biology (Biological feedback Control at the molecular Level D.E. Atkinson Science vol. 150: 851, 1965). Almost nothing is known concerning the actual molecular basis for modulation of an enzyme`s kinetic behavior by interaction with a small molecule. (Biological feedback Control at the molecular Level D.E. Atkinson Science vol. 150: 851, 1965). In the same article, since the core of Atkinson´s thinking seems to be strongly linked with Adenylates as regulatory effectors, the previous phrases seems to indicate a first step towards the conversion of homeostasis to an intracellular phenomenon and therefore, one that contrary to Umbarger´s consideration could be also studied in microorganisms.
Most biochemical studies using bacteria, were made before the end of the third upper part of log growth phase. Therefore, they could be considered as time-independent as S Luria presented biochemistry in Life an Unfinished Experiment. The sole ingredient on the missing side of the events that led us into the molecular biology construction was to consider that proteins, a macromolecule, would never be affected by small molecules translational kinetic energy. This, despite the fact that in a catalytic environment and its biological implications S Grisolia incorporated A K Balls observation indicating that the word proteins could be related to Proteus an old sea god that changed its form whenever he was subjected to inquiry (Phys Rev v 4,657 (1964).
In D.E. Atkinson´s work (Science vol 150 p 851, 1965), changes in protein synthesis acting together with factors that interfere with enzyme activity will lead to “fine-tuned” regulation better than enzymatic activity regulation alone. Comparison of glycemic regulation in granivorous and carnivorous birds indicate that when no important nutritional source of glucose is available, glycemic levels can be kept constant in fasted and fed birds. The same was found in rats and cats fed on high protein diets. Gluconeogenesis is controlled by pyruvate kinase inhibition. Therefore, the fact that it can discriminate between fasting alone and fasting plus exercise (carbachol) requirement of gluconeogenic activity (correspondent level of pyruvate kinase inhibition) the control of enzyme activity can be made fast and efficient without need for changes in genetic expression (20 minute after stimulus) ( Migliorini,R.H. et al Am J. Physiol.257 (Endocrinol. Met. 20): E486, 1989). Regrettably, this was not discussed in the quoted work. So, when the control is not affected by the absorption of nutritional glucose it can be very fast, less energy intensive and very sensitive mechanism of control despite its action being made in the extracellular medium (homeostasis).
This article is a followup of the wonderful study of the effect of oxidation of a methionine residue in calcium dependent-calmodulin kinase Ox-CaMKII on stabilizing the atrial cardiomyocyte, giving protection from atrial fibrillation. It is also not so distant from the work reviewed, mostly on the ventricular myocyte and the calcium signaling by initiation of the ryanodyne receptor (RyR2) in calcium sparks and the CaMKII d isoenzyme.
We refer to the following related articles published in pharmaceutical Intelligence:
The material presented is very focused, and cannot be found elsewhere in Pharmaceutical Intelligence with respedt to genetics and heart disease. However, there are other articles that may be of interest to the reader.
PART 3. Determinants of Cardiovascular Diseases: Genetics, Heredity and Genomics Discoveries
3.2 Leading DIAGNOSES of Cardiovascular Diseases covered in Circulation: Cardiovascular Genetics, 3/2010 – 3/2013
The Diagnoses covered include the following – relevant to this discussion
MicroRNA in Serum as Bimarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis, diastolic dysfunction, and acute heart failure
Genomics of Ventricular arrhythmias, A-Fib, Right Ventricular Dysplasia, Cardiomyopathy
Heredity of Cardiovascular Disorders Inheritance
3.2.1: Heredity of Cardiovascular Disorders Inheritance
The implications of heredity extend beyond serving as a platform for genetic analysis, influencing diagnosis,
prognostication, and
treatment of both index cases and relatives, and
enabling rational targeting of genotyping resources.
This review covers acquisition of a family history, evaluation of heritability and inheritance patterns, and the impact of inheritance on subsequent components of the clinical pathway.
3.2.2.1 MicroRNA in Serum as Biomarker for Cardiovascular Pathologies: acute myocardial infarction, viral myocarditis, diastolic dysfunction, and acute heart failure
Increased MicroRNA-1 and MicroRNA-133a Levels in Serum of Patients With Cardiovascular Disease Indicate Myocardial Damage
Y Kuwabara, Koh Ono, T Horie, H Nishi, K Nagao, et al.
SOURCE: Circulation: Cardiovascular Genetics. 2011; 4: 446-454 http://dx.doi.org/10.1161/CIRCGENETICS.110.958975
3.2.2.2 Circulating MicroRNA-208b and MicroRNA-499 Reflect Myocardial Damage in Cardiovascular Disease
3.2.4.2 Large-Scale Candidate Gene Analysis in Whites and African Americans Identifies IL6R Polymorphism in Relation to Atrial Fibrillation
The National Heart, Lung, and Blood Institute’s Candidate Gene Association Resource (CARe) Project
RB Schnabel, KF Kerr, SA Lubitz, EL Alkylbekova, et al.
SOURCE: Circulation: Cardiovascular Genetics.2011; 4: 557-564 http://dx.doi.org/10.1161/CIRCGENETICS.110.959197
Weighted Gene Coexpression Network Analysis of Human Left Atrial Tissue Identifies Gene Modules Associated With Atrial Fibrillation
N Tan, MK Chung, JD Smith, J Hsu, D Serre, DW Newton, L Castel, E Soltesz, G Pettersson, AM Gillinov, DR Van Wagoner and J Barnard
From the Cleveland Clinic Lerner College of Medicine (N.T.), Department of Cardiovascular Medicine (M.K.C., D.W.N.), and Department of Thoracic & Cardiovascular Surgery (E.S., G.P., A.M.G.); and Department of Cellular & Molecular Medicine (J.D.S., J.H.), Genomic Medicine Institute (D.S.), Department of Molecular Cardiology (L.C.), and Department of Quantitative Health Sciences (J.B.), Cleveland Clinic Lerner Research Institute, Cleveland, OH
Circ Cardiovasc Genet. 2013;6:362-371; http://dx.doi.org/10.1161/CIRCGENETICS.113.000133 http://circgenetics.ahajournals.org/content/6/4/362The online-only Data Supplement is available at http://circgenetics.ahajournals.org/lookup/suppl/doi:10.1161/CIRCGENETICS.113.000133/-/DC1
Background—Genetic mechanisms of atrial fibrillation (AF) remain incompletely understood. Previous differential expression studies in AF were limited by small sample size and provided limited understanding of global gene networks, prompting the need for larger-scale, network-based analyses.
Methods and Results—Left atrial tissues from Cleveland Clinic patients who underwent cardiac surgery were assayed using Illumina Human HT-12 mRNA microarrays. The data set included 3 groups based on cardiovascular comorbidities: mitral valve (MV) disease without coronary artery disease (n=64), coronary artery disease without MV disease (n=57), and lone AF (n=35). Weighted gene coexpression network analysis was performed in the MV group to detect modules of correlated genes. Module preservation was assessed in the other 2 groups. Module eigengenes were regressed on AF severity or atrial rhythm at surgery. Modules whose eigengenes correlated with either AF phenotype were analyzed for gene content. A total of 14 modules were detected in the MV group; all were preserved in the other 2 groups. One module (124 genes) was associated with AF severity and atrial rhythm across all groups. Its top hub gene, RCAN1, is implicated in calcineurin-dependent signaling and cardiac hypertrophy. Another module (679 genes) was associated with atrial rhythm in the MV and coronary artery disease groups. It was enriched with cell signaling genes and contained cardiovascular developmental genes including TBX5.
Conclusions—Our network-based approach found 2 modules strongly associated with AF. Further analysis of these modules may yield insight into AF pathogenesis by providing novel targets for functional studies. (Circ Cardiovasc Genet. 2013;6:362-371.)
trial fibrillation (AF) is the most common sustained cardiac arrhythmia, with a prevalence of ≈1% to 2% in the general population.1,2 Although AF may be an isolated condition (lone AF [LAF]), it often occurs concomitantly with other cardiovascular diseases, such as coronary artery disease (CAD) and valvular heart disease.1 In addition, stroke risk is increased 5-fold among patients with AF, and ischemic strokes attributed to AF are more likely to be fatal.1 Current antiarrhythmic drug therapies are limited in terms of efficacy and safety.1,3,4 Thus, there is a need to develop better risk prediction tools as well as mechanistically targeted therapies for AF. Such developments can only come about through a clearer understanding of its pathogenesis.
Family history is an established risk factor for AF. A Danish Twin Registry study estimated AF heritability at 62%, indicating a significant genetic component.5 Substantial progress has been made to elucidate this genetic basis. For example, genome-wide association studies (GWASs) have identified several susceptibility loci and candidate genes linked with AF. Initial studies performed in European populations found 3 AF-associated genomic loci.6–9 Of these, the most significant single-nucleotide polymor-phisms (SNPs) mapped to an intergenic region of chromosome 4q25. The closest gene in this region, PITX2, is crucial in left-right asymmetrical development of the heart and thus seems promising as a major player in initiating AF.10,11 A large-scale GWAS meta-analysis discovered 6 additional susceptibility loci, implicating genes involved in cardiopulmonary development, ion transport, and cellular structural integrity.12
Differential expression studies have also provided insight into the pathogenesis of AF. A study by Barth et al13 found that about two-thirds of the genes expressed in the right atrial appendage were downregulated during permanent AF, and that many of these genes were involved in calcium-dependent signaling pathways. In addition, ventricular-predominant genes were upregulated in right atrial appendages of subjects with AF.13 Another study showed that inflammatory and transcription-related gene expression was increased in right atrial appendages of subjects with AF versus controls.14 These results highlight the adaptive responses to AF-induced stress and ischemia taking place within the atria.
Despite these advances, much remains to be discovered about the genetic mechanisms of AF. The AF-associated SNPs found thus far only explain a fraction of its heritability15; furthermore, the means by which the putative candidate genes cause AF have not been fully established.9,15,16 Additionally, previous differential expression studies in human tissue were limited to the right atrial appendage, had small sample sizes, and provided little understanding of global gene interactions.13,14 Weighted gene coexpression network analysis (WGCNA) is a technique to construct gene modules within a network based on correlations in gene expression (ie, coexpression).17,18 WGCNA has been used to study genetically complex diseases, such as metabolic syndrome,19 schizophrenia,20 and heart failure.21 Here, we obtained mRNA expression profiles from human left atrial appendage tissue and implemented WGCNA to identify gene modules associated with AF phenotypes.
Methods
Subject Recruitment
From 2001 to 2008, patients undergoing cardiac surgery at the Cleveland Clinic were prospectively screened and recruited. Informed consent for research use of discarded atrial tissues was obtained from each patient by a study coordinator during the presurgical visit. Demographic and clinical data were obtained from the Cardiovascular Surgery Information Registry and by chart review. Use of human atrial tissues was approved by the Institutional Review Board of the Cleveland Clinic.
Table S1: Clinical definitions of cardiovascular phenotype groups
Criterion Type
Mitral Valve (MV) Disease
Coronary Artery Disease (CAD)
Lone Atrial Fibrillation (LAF)
Inclusion Criteria
Surgical indication –
Surgical indication –
History of atrial fibrillation
mitral valve repair or replacement
coronary artery bypass graft
Surgical indication
– MAZE procedure
Preserved ejection fraction (≥50%)
Exclusion Criteria
Significant coronary artery disease:
Significant mitral valve disease:
Significant
coronary artery
– Significant (≥50%) stenosis
– Documented echocardiography
disease:
in at least
finding of
– Significant
one coronary artery
mitral regurgitation (≥3) or
(≥50%) stenosis in
via cardiac catheterization
mitral stenosis
at least one
– History of revascularization
– History of mitral valve
coronary artery via
(percutaneous coronary intervention or coronary artery bypass graft surgery)
repair or replacement
cardiac catheterization
– History of revascularization
(percutaneous coronary intervention or coronary artery bypass graft surgery)
Significant valvular heart disease:
-Documented echocardiography finding of valvular regurgitation (≥3) or stenosis
-History of valve repair or replacement
RNA Microarray Isolation and Profiling
Left atria appendage specimens were dissected during cardiac surgery and stored frozen at −80°C. Total RNA was extracted using the Trizol technique. RNA samples were processed by the Cleveland Clinic Genomics Core. For each sample, 250-ng RNA was reverse transcribed into cRNA and biotin-UTP labeled using the TotalPrep RNA Amplification Kit (Ambion, Austin, TX). cRNA was quantified using a Nanodrop spectrophotometer, and cRNA size distribution was assessed on a 1% agarose gel. cRNA was hybridized to Illumina Human HT-12 Expression BeadChip arrays (v.3). Arrays were scanned using a BeadArray reader.
Expression Data Preprocessing
Raw expression data were extracted using the beadarray package in R, and bead-level data were averaged after log base-2 transformation. Background correction was performed by fitting a normal-gamma deconvolution model using the NormalGamma R package.22 Quantile normalization and batch effect adjustment with the ComBat method were performed using R.23 Probes that were not detected (at a P<0.05 threshold) in all samples as well as probes with relatively lower variances (interquartile range ≤log2[1.2]) were excluded.
The WGCNA approach requires that genes be represented as singular nodes in such a network. However, a small proportion of the genes in our data have multiple probe mappings. To facilitate the representation of singular genes within the network, a probe must be selected to represent its associated gene. Hence, for genes that mapped to multiple probes, the probe with the highest mean expression level was selected for analysis (which often selects the splice isoform with the highest expression and signal-to-noise ratio), resulting in a total of 6168 genes.
Defining Training and Test Sets
Currently, no large external mRNA microarray data from human left atrial tissues are publicly available. To facilitate internal validation of results, we divided our data set into 3 groups based on cardiovascular comorbidities: mitral valve (MV) disease without CAD (MV group; n=64), CAD without MV disease (CAD group; n=57), and LAF (LAF group; n=35). LAF was defined as the presence of AF without concomitant structural heart disease, according to the guidelines set by the European Society of Cardiology.1 The MV group, which was the largest and had the most power for detecting significant modules, served as the training set for module derivation, whereas the other 2 groups were designated test sets for module reproducibility. To minimize the effect of population stratification, the data set was limited to white subjects. Differences in clinical characteristics among the groups were assessed using Kruskal–Wallis rank-sum tests for continuous variables and Pearson x2 test for categorical variables.
Weight Gene Coexpression Network Analysis
WGCNA is a systems-biology method to identify and characterize gene modules whose members share strong coexpression. We applied previously validated methodology in this analysis.17 Briefly, pair-wise gene (Pearson) correlations were calculated using the MV group data set. A weighted adjacency matrix was then constructed. I is a soft-thresholding parameter that provides emphasis on stronger correlations over weaker and less meaningful ones while preserving the continuous nature of gene–gene relationships. I=3 was selected in this analysis based on the criterion outlined by Zhang and Horvath17 (see the online-only Data Supplement).
Next, the topological overlap–based dissimilarity matrix was computed from the weighted adjacency matrix. The topological overlap, developed by Ravasz et al,24 reflects the relative interconnectedness (ie, shared neighbors) between 2 genes.17 Hence, construction of the network dendrogram based on this dissimilarity measure allows for the identification of gene modules whose members share strong intercon-nectivity patterns. The WGCNA cutreeDynamic R function was used to identify a suitable cut height for module identification via an adaptive cut height selection approach.18 Gene modules, defined as branches of the network dendrogram, were assigned colors for visualization.
Network Preservation Analysis
Module preservation between the MV and CAD groups as well as the MV and LAF groups was assessed using network preservation statistics as described in Langfelder et al.25 Module density–based statistics (to assess whether genes in each module remain highly connected in the test set) and connectivity-based statistics (to assess whether connectivity patterns between genes in the test set remain similar compared with the training set) were considered in this analysis.25 In each comparison, a Z statistic representing a weighted summary of module density and connectivity measures was computed for every module (Zsummary). The Zsummary score was used to evaluate module preservation, with values ≥8 indicating strong preservation, as proposed by Langfelder et al.25 The WGCNA R function network preservation was used to implement this analysis.25
Table S2: Network preservation analysis between the MV and CAD groups – size and Zsummary scores of gene modules detected.
Module
Module Size
ZSummary
Black
275
15.52
Blue
964
44.79
Brown
817
12.80
Cyan
119
13.42
Green
349
14.27
Green-Yellow
215
19.31
Magenta
239
15.38
Midnight-Blue
83
15.92
Pink
252
23.31
Purple
224
16.96
Red
278
17.30
Salmon
124
13.84
Tan
679
28.48
Turquoise
1512
44.03
Table S3: Network preservation analysis between the MV and LAF groups – size and Zsummary scores of gene modules detected
Module
Module Size
ZSummary
Black
275
13.14
Blue
964
39.26
Brown
817
14.98
Cyan
119
11.46
Green
349
14.91
Green-Yellow
215
20.99
Magenta
239
18.58
Midnight-Blue
83
13.87
Pink
252
19.10
Purple
224
8.80
Red
278
16.62
Salmon
124
11.57
Tan
679
28.61
Turquoise
1512
42.07
Clinical Significance of Preserved Modules
Principal component analysis of the expression data for each gene module was performed. The first principal component of each module, designated the eigengene, was identified for the 3 cardiovascular disease groups; this served as a summary expression measure that explained the largest proportion of the variance of the module.26 Multivariate linear regression was performed with the module ei-gengenes as the outcome variables and AF severity (no AF, paroxysmal AF, persistent AF, permanent AF) as the predictor of interest (adjusting for age and sex). A similar regression analysis was performed with atrial rhythm at surgery (no AF history, AF history in sinus rhythm, AF history in AF rhythm) as the predictor of interest. The false discovery rate method was used to adjust for multiple comparisons. Modules whose eigengenes associated with AF severity and atrial rhythm were identified for further analysis.
In addition, hierarchical clustering of module eigengenes and selected clinical traits (age, sex, hypertension, cholesterol, left atrial size, AF state, and atrial rhythm) was used to identify additional module–trait associations. Clusters of eigengenes/traits were detected based on a dissimilarity measure D, as given by
D=1−cor(Vi,Vj),i≠j (3)
where V=the eigengene or clinical trait.
Enrichment Analysis
Gene modules significantly associated with AF severity and atrial rhythm were submitted to Ingenuity Pathway Analysis (IPA) to determine enrichment for functional/disease categories. IPA is an application of gene set over-representation analysis; for each dis-ease/functional category annotation, a P value is calculated (using Fisher exact test) by comparing the number of genes from the module of interest that participate in the said category against the total number of participating genes in the background set.27 All 6168 genes in the current data set served as the background set for the enrichment analysis.
Hub Gene Analysis
Hub genes are defined as genes that have high intramodular connectivity17,20
Alternatively, they may also be defined as genes with high module membership21,25
Both definitions were used to identify the hub genes of modules associated with AF phenotype.
To confirm that the hub genes identified were themselves associated with AF phenotype, the expression data of the top 10 hub genes (by intramodular connectivity) were regressed on atrial rhythm (adjusting for age and sex). In addition, eigengenes of AF-associated modules were regressed on their respective (top 10) hub gene expression profiles, and the model R2 indices were computed.
Membership of AF-Associated Candidate Genes From Previous Studies
Previous GWAS studies identified multiple AF-associated SNPs.8,9,12,15,28 We selected candidate genes closest to or containing these SNPs and identified their module locations as well as their closest within-module partners (absolute Pearson correlations).
Sensitivity Analysis of Soft-Thresholding Parameter
To verify that the key results obtained from the above analysis were robust with respect to the chosen soft-thresholding parameter (I=3), we repeated the module identification process using I=5. The eigen-genes of the detected modules were computed and regressed on atrial rhythm (adjusting for age and sex). Modules significantly associated with atrial rhythm in ≥2 groups of data set were compared with the AF phenotype–associated modules from the original analysis.
Results
Subject Characteristics
Table 1 describes the clinical characteristics of the cardiac surgery patients who were recruited for the study. Subjects in the LAF group were generally younger and less likely to be a current smoker (P=2.0×10−4 and 0.032, respectively). Subjects in the MV group had lower body mass indices (P=2.7×10−6), and a larger proportion had paroxysmal AF compared with the other 2 groups (P=0.033).
Table 1. Clinical Characteristics of Study Subjects
A total of 14 modules were detected using the MV group data set (Figure 1), with module sizes ranging from 83 genes to 1512 genes; 38 genes did not share similar coexpression with the other genes in the network and were therefore not included in any of the identified modules
Figure 1. Network dendrogram (top) and colors of identified modules (bottom). The dendrogram was constructed using the topological overlap matrix as the similarity measure. Modules corresponded to branches of the dendrogram and were assigned colors for visualization.
Network Preservation Analysis Revealed Strong Preservation of All Modules Between the Training and Test Sets
All 14 modules showed strong preservation across the CAD and LAF groups in both comparisons, with Z [summary] scores of >10 in most modules (Figure 2). No major deviations in the Z [summary] score distributions for the 2 comparisons were noted, indicating that modules were preserved to a similar extent across the 2 groups
Figure 2. Preservation of modules between mitral valve (MV) and coronary artery disease (CAD) groups (left), and MV and lone atrial fibrillation (LAF) groups (right). A Zsummary statistic was computed for each module as an overall measure of its preservation relating to density and connectivity. All modules showed strong preservation in both comparisons with Zsummary scores >8 (red dotted line).
Regression Analysis of Module Eigengene Profiles Identified 2 Modules Associated With AF Severity and Atrial Rhythm
Table IV in the online-only Data Supplement summarizes the proportion of variance explained by the first 3 principal components for each module. On average, the first principal component (ie, the eigengene) explained ≈18% of the total variance of its associated module. For each group, the module eigengenes were extracted and regressed on AF severity (with age and sex as covariates). The salmon module (124 genes) eigengene was strongly associated with AF severity in the MV and CAD groups (P=1.7×10−6 and 5.2×10−4, respectively); this association was less significant in the LAF group (P=9.0×10−2). Eigengene levels increased with worsening AF severity across all 3 groups, with the greatest stepwise change taking place between the paroxysmal AF and persistent AF categories (Figure 3A). When the module eigen-genes were regressed on atrial rhythm, the salmon module eigengene showed significant association in all groups (MV: P=1.1×10−14; CAD: P=1.36×10−6; LAF: P=2.1×10−4). Eigen-gene levels were higher in the AF history in AF rhythm category (Figure 3B).
Table S4:Proportion of variance explained by the principal components for each module.
Dataset
Group
Principal
Component
Black
Blue
Brown
Cyan
Green
Green-
Yellow
Magenta
Mitral
1
20.5%
22.2%
20.1%
21.8%
21.4%
22.8%
19.6%
2
4.1%
3.6%
4.8%
5.7%
4.5%
5.9%
3.9%
3
3.4%
3.1%
3.8%
4.4%
3.9%
3.7%
3.7%
CAD
1
12.5%
18.6%
7.1%
16.8%
12.2%
20.3%
12.8%
2
6.0%
5.5%
5.0%
7.0%
5.5%
6.1%
6.4%
3
4.9%
4.1%
4.4%
6.5%
4.8%
4.4%
4.8%
LAF
1
14.0%
16.6%
11.7%
14.3%
14.7%
20.8%
20.2%
2
8.9%
8.5%
7.6%
9.3%
7.3%
11.1%
6.9%
3
6.5%
6.3%
5.5%
8.2%
6.1%
5.3%
6.2%
Dataset
Group
Principal
Component
Midnight- Blue
Pink
Purple
Red
Salmon
Tan
Turquoise
Mitral
1
28.5%
22.6%
18.7%
20.5%
22.3%
19.0%
25.8%
2
4.6%
6.0%
4.7%
4.1%
6.9%
4.0%
3.5%
3
4.2%
4.2%
4.2%
3.5%
4.0%
3.6%
3.3%
CAD
1
23.4%
17.1%
15.5%
15.0%
18.0%
14.6%
18.2%
2
7.4%
8.6%
6.0%
6.4%
7.2%
5.8%
6.6%
3
5.1%
5.4%
5.3%
5.4%
6.2%
5.1%
4.5%
LAF
1
23.5%
18.4%
12.0%
15.9%
16.9%
13.7%
16.5%
2
7.9%
8.5%
9.8%
9.4%
9.5%
9.1%
9.6%
3
6.7%
7.0%
6.6%
6.0%
6.9%
6.8%
6.3%
Figure 3. Boxplots of salmon module eigengene expression levels with respect to atrial fibrillation (AF) severity (A) and atrial rhythm (B).
A, Eigengene expression correlated positively with AF severity, with the largest stepwise increase between the paroxysmal AF and permanent AF categories. B, Eigengene expression was highest in the AF history in AF rhythm category in all 3 groups. CAD indicates coronary artery disease; LAF, lone AF; and MV, mitral valve.
The regression analysis also revealed statistically significant associations between the tan module (679 genes) eigengene and atrial rhythm in the MV and CAD groups (P=5.8×10−4 and 3.4×10−2, respectively). Eigengene levels were lower in the AF history in AF rhythm category compared with the AF history in sinus rhythm category (Figure 4); this trend was also observed in the LAF group, albeit with weaker statistical evidence (P=0.15).
Figure 4. Boxplots of tan module eigengene expression levels with respect to atrial rhythm. Eigengene expression levels were lower in the atrial fibrillation (AF) history in AF rhythm category compared with the AF history in sinus rhythm category. CAD indicates coronary artery disease; LAF, lone AF; and MV, mitral valve
Hierarchical Clustering of Eigengene Profiles With Clinical Traits
Hierarchical clustering was performed to identify relationships between gene modules and selected clinical traits. The salmon module clustered with AF severity and atrial rhythm; in addition, left atrial size was found in the same cluster, suggesting a possible relationship between salmon module gene expression and atrial remodeling (Figure 5A). Although the tan module was in a separate cluster from the salmon module, it was negatively correlated with both atrial rhythm and AF severity (Figure 5B).
Figure 5. Dendrogram (A) and correlation heatmap (B) of module eigengenes and clinical traits.
A, The salmon module eigengene but not the tan module eigengene clustered with atrial fibrillation (AF) severity, atrial rhythm, and left atrial size. B, AF severity and atrial rhythm at surgery correlated positively with the salmon module eigengene and negatively with the tan module eigengene. Arhythm indicates atrial rhythm at surgery; Chol, cholesterol; HTN, hypertension; and LASize, left atrial size.
IPA Enrichment Analysis of Salmon and Tan Modules
The salmon module was enriched in genes involved in cardiovascular function and development (smallest P=4.4×10−4) and organ morphology (smallest P=4.4×10−4). In addition, the top disease categories identified included endocrine system disorders (smallest P=4.4×10−4) and cardiovascular disease (smallest P=2.59×10−3).
The tan module was enriched in genes involved in cell-to-cell signaling and interaction (smallest P=8.9×10−4) and cell death and survival (smallest P=1.5×10−3). Enriched disease categories included cancer (smallest P=2.2×10−4) and cardiovascular disease (smallest P=4.5×10−4).
We identified hub genes in the 2 modules based on intramod-ular connectivity and module membership. For the salmon module, the gene RCAN1 exhibited the highest intramodular connectivity and module membership. The top 10 hub genes (by intramodular connectivity) were significantly associated with atrial rhythm, with false discovery rate–adjusted P values ranging from 1.5×10−5 to 4.2×10−12. These hub genes accounted for 95% of the variation in the salmon module eigengene.
In the tan module, the top hub gene was CPEB3. The top 10 hub genes (by intramodular connectivity) correlated with atrial rhythm as well, although the statistical associations in the lower-ranked hub genes were relatively weaker (false discovery rate–adjusted P values ranging from 1.1×10−1 to 3.4×10−4). These hub genes explained 94% of the total variation in the tan module eigengene.
The names and connectivity measures of the hub genes found in both modules are presented in Table 2.
Table 2. Top 10 Hub Genes in the Salmon (Left) and Tan (Right) Modules as Defined by Intramodular Connectivity and Module Membership
Salmon Module
Tan Module
Gene
IMC
Gene
MM
Gene
IMC
Gene
MM
RCAN1
8.2
RCAN1
0.81
CPEB3
43.3
CPEB3
0.85
DNAJA4
7.7
DNAJA4
0.81
CPLX3
42.4
CPLX3
0.84
PDE8B
7.7
PDE8B
0.80
NEDD4L
40.8
NEDD4L
0.83
PRKAR1A
6.9
PRKAR1A
0.77
SGSM1
40.7
SGSM1
0.82
PTPN4
6.7
PTPN4
0.75
UCKL1
39.0
UCKL1
0.81
SORBS2
6.0
FHL2
0.69
SOSTDC1
37.2
SOSTDC1
0.79
ADCY6
5.7
ADCY6
0.69
PRDX1
35.5
RCOR2
0.78
FHL2
5.7
SORBS2
0.68
RCOR2
35.4
EEF2K
0.77
BVES
5.4
DHRS9
0.67
NPPB
35.3
PRDX1
0.76
TMEM173
5.3
LAPTM4B
0.65
LRRN3
34.6
MMP11
0.76
A visualization of the salmon module is shown using the Cytoscape tool (Figure 6). A full list of the genes in the salmon and tan modules is provided in the online-only Data Supplement.
Figure 6. Cytoscape visualization of genes in the salmon module.
Nodes representing genes with high intramodu-lar connectivities, such as RCAN1 and DNAJA4, appear larger in the network. Strong connections are visualized with darker lines, whereas weak connections appear more translucent
Membership of AF-Associated Candidate Genes From Previous Studies
The tan module contained MYOZ1, which was identified as a candidate gene from the recent AF meta-analysis. PITX2 was located in the green module (n=349), and ZFHX3 was located in the turquoise module (n=1512). The locations of other candidate genes (and their closest partners) are reported in the online-only Data Supplement.
Sensitivity Analysis of Key Results
We repeated the WGCNA module identification approach using a different soft-thresholding parameter (β=5). One module (n=121) was found to be strongly associated with atrial rhythm at surgery across all 3 groups of data set, whereas another module (n=244) was associated with atrial rhythm at surgery in the MV and CAD groups. The first module overlapped significantly with the salmon module in terms of gene membership, whereas most of the second modules’ genes were contained within the tan module. The top hub genes found in the salmon and tan modules remained present and highly connected in the 2 new modules identified with the different soft-thresholding parameter.
Discussion
To our knowledge, our study is the first implementation of an unbiased, network-based analysis in a large sample of human left atrial appendage gene expression profiles. We found 2 modules associated with AF severity and atrial rhythm in 2 to 3 of our cardiovascular comorbidity groups. Functional analyses revealed significant enrichment of cardiovascular-related categories for both modules. In addition, several of the hub genes identified are implicated in cardiovascular disease and may play a role in AF initiation and progression.
In our study, WGCNA was used to construct modules based on gene coexpression, thereby reducing the net-work’s dimensionality to a smaller set of elements.17,21 Relating modulewise changes to phenotypic traits allowed statistically significant associations to be detected at a lower false discovery rate compared with traditional differential expression studies. Furthermore, shared functions and pathways among genes in the modules could be inferred via enrichment analyses.
We divided our data set into 3 groups to verify the reproducibility of the modules identified by WGCNA; 14 modules were identified in the MV group in our gene network. All were strongly preserved in the CAD and LAF groups, suggesting that gene coexpression patterns are robust and reproducible despite differences in cardiovascular comorbidities.
The use of module eigengene profiles as representative summary measures has been validated in a number of studies.20,26 Additionally, we found that the eigengenes accounted for a significant proportion (average 18%) of gene expression variability in their respective modules. Regression analysis of the module eigengenes found 2 modules associated with AF severity and atrial rhythm in ≥2 groups of data set. The association between the salmon module eigengene and AF severity was statistically weaker in the LAF group (adjusted P=9.0×10−2). This was probably because of its significantly smaller sample size compared with the MV and CAD groups. Despite this weaker association, the relationship between the salmon module eigengene and AF severity remained consistent among the 3 groups (Figure 3A). Similarly, the lack of statistical significance for the association between the tan module eigengene and atrial rhythm at surgery in the LAF group was likely driven by the smaller sample size and (by definition) lack of samples in the no AF category.
A major part of our analysis focused on the identification of module hub genes. Hubs are connected with a large number of nodes; disruption of hubs therefore leads to widespread changes within the network. This concept has powerful applications in the study of biology, genetics, and disease.29,30 Although mutations of peripheral genes can certainly lead to disease, gene network changes are more likely to be motivated by changes in hub genes, making them more biologically interesting targets for further study.17,29,31 Indeed,
the hub genes of the salmon and tan modules accounted for the vast majority of the variation in their respective module eigengenes, signaling their importance in driving gene module behavior.
The hub genes identified in the salmon and tan modules were significantly associated with AF phenotype overall. It was noted that this association was statistically weaker for the lower-ranked hub genes in the tan module. This highlights an important aspect and strength of WGCNA—to be able to capture module-wide changes with respect to disease despite potentially weaker associations among individual genes.
The implementation of WGCNA necessitated the selection of a soft-thresholding parameter 13. Unlike hard-thresholding (where gene correlations below a certain value are shrunk to zero), the soft-thresholding approach gives greater weight to stronger correlations while maintaining the continuous nature of gene–gene relationships. We selected a 13 value of 3 based on the criteria outlined by Zhang and Horvath.17 His team and other investigators have demonstrated that module identification is robust with respect to the 13 parameter.17,19–21 In our data, we were also able to reproduce the key findings reported with a different, larger 13 value, thereby verifying the stability of our results relating to 13.
The salmon module (124 genes) was associated with both AF phenotypes; furthermore, IPA analysis of its gene contents suggested enrichment in cardiovascular development as well as disease. Its eigengene increased with worsening AF severity, with the largest stepwise change occurring between the paroxysmal AF and persistent AF categories (Figure 3). Hence,
the gene expression changes within the salmon module may reflect the later stages of AF pathophysiology.
The top hub gene of the salmon module was RCAN1 (regulator of calcineurin 1). Calcineurin is a cytoplasmic Ca2+/ calmodulin-dependent protein phosphatase that stimulates cardiac hypertrophy via its interactions with NFAT and L-type Ca2+ channels.32,33RCAN1 is known to inhibit calcineurin and its associated pathways.32,34 However, some data suggest that RCAN1 may instead function as a calcineurin activator when highly expressed and consequently potentiate hypertrophic signaling.35 Thus,
perturbations in RCAN1 levels (attributable to genetic variants or mutations) may cause an aberrant switching in function, which in turn triggers atrial remodeling and arrhythmogenesis.
Other hub genes found in the salmon module are also involved in cardiovascular development and function and may be potential targets for further study.
DNAJA4 (DnaJ homolog, subfamily A, member 4) regulates the trafficking and maturation of KCNH2 potassium channels, which have a prominent role in cardiac repolarization and are implicated in the long-QT syndromes.36
FHL2 (four-and-a-half LIM domain protein 2) interacts with numerous cellular components, including
actin cytoskeleton,
transcription machinery, and
ion channels.37
FHL2 was shown to enhance the hypertrophic effects of isoproterenol, indicating that
FHL2 may modulate the effect of environmental stress on cardiomyocyte growth.38
FHL2 also interacts with several potassium channels in the heart, such as KCNQ1, KCNE1, and KCNA5.37,39
Additionally, blood vessel epicardial substance (BVES) and other members of its family were shown to be highly expressed in cardiac pacemaker cells. BVES knockout mice exhibited sinus nodal dysfunction, suggesting that BVES regulates the development of the cardiac pacemaking and conduction system40 and may therefore be involved in the early phase of AF development.
The tan module (679 genes) eigengene was negatively correlated with atrial rhythm in the MV and CAD groups (Figure 4); this may indicate a general decrease in gene expression of its members in fibrillating atrial tissue. IPA analysis revealed enrichment in genes involved in cell signaling as well as apoptosis. The top-ranked hub gene, cytoplasmic polyade-nylation element binding protein 3 (CPEB3), regulates mRNA translation and has been associated with synaptic plasticity and memory formation.41 The role of CPEB3 in the heart is currently unknown, so further exploration via animal model studies may be warranted.
Natriuretic peptide-precursor B (NPPB), another highly interconnected hub gene, produces a precursor peptide of brain natriuretic peptide, which
regulates blood pressure through natriuresis and vasodilation.42
(NPPB) gene variants have been linked with diabetes mellitus, although associations with cardiac phenotypes are less clear.42 TBX5 and GATA4, which play important roles in the embryonic heart development,43 were members of the tan module. Although not hub genes, they may also contribute toward developmental susceptibility of AF. In addition, TBX5 was previously reported to be near an SNP associated with PR interval and AF in separate large-scale GWAS studies.12,28 MYOZ1, another candidate gene identified in the recent AF GWAS meta-analysis, was found to be a member as well; it associates with proteins found in the Z-disc of skeletal and cardiac muscle and may suppress calcineurin-dependent hypertrophic signaling.12
Some, but not all, of the candidate genes found in previous GWAS studies were located in the AF-associated modules. One possible explanation for this could be the difference in sample sizes. The meta-analysis involved thousands of individuals, whereas the current study had <100 in each group of data set, which limited the power to detect significant differences between levels of AF phenotype even with the module-wise approach. Additionally, transcription factors like PITX2 are most highly expressed during the fetal phase of development. Perturbations in these genes (attributable to genetic variants or mutations) may therefore initiate the development of AF at this stage and play no significant role in adults (when we obtained their tissue samples).
Limitations in Study
We noted several limitations in this study. First, no human left atrial mRNA data set of adequate size currently exists publicly. Hence, we were unable to validate our results with an external, independent data set. However, the network preservation assessment performed within our data set showed strong preservation in all modules, indicating that our findings are robust and reproducible.
Although the module eigengenes captured a significant proportion of module variance, a large fraction of variability did remain unaccounted for, which may limit their use as representative summary measures.
We extracted RNA from human left atrial appendage tissue, which consists primarily of cardiomyocytes and fibroblasts. Atrial fibrosis is known to occur with AF-associated remodeling.44 As such, the cardiomyocyte to fibroblast ratio is likely to change with different levels of AF severity, which in turn influences the amount of RNA extracted from each cell type. Hence, true differences in gene expression (and coexpression) within cardiomyocytes may be confounded by changes in cellular composition attributable to atrial remodeling. Also, there may be significant regional heterogeneity in the left atrium with respect to structure, cellular composition, and gene expression,45 which may limit the generaliz-ability of our results to other parts of the left atrium.
All subjects in the study were whites to minimize the effects of population stratification. However, it is recognized that the genetic basis of AF may differ among ethnic groups.9 Thus, our results may not be generalizable to other ethnicities.
Finally, it is possible for genes to be involved in multiple processes and functions that require different sets of genes. However, WGCNA does not allow for overlapping modules to be formed. Thus,
this limits the method’s ability to characterize such gene interactions.
Conclusions
In summary, we constructed a weighted gene coexpression network based on RNA expression data from the largest collection of human left atrial appendage tissue specimens to date. We identified 2 gene modules significantly associated with AF severity or atrial rhythm at surgery. Hub genes within these modules may be involved in the initiation or progression of AF and may therefore be candidates for functional studies.
Refererences
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2. Lemmens R, Hermans S, Nuyens D, Thijs V. Genetics of atrial fibrillation and possible implications for ischemic stroke. Stroke Res Treat. 2011;2011:208694.
3. Wann LS, Curtis AB, January CT, Ellenbogen KA, Lowe JE, Estes NA III, et al; ACCF/AHA/HRS. 2011 ACCF/AHA/HRS focused update on the management of patients with atrial fibrillation (Updating the 2006 Guideline): a report of the American College of Cardiology Foundation/ American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2011;57:223–242.
4. Dobrev D, Carlsson L, Nattel S. Novel molecular targets for atrial fibrillation therapy. Nat Rev Drug Discov. 2012;11:275–291.
5. Christophersen IE, Ravn LS, Budtz-Joergensen E, Skytthe A, Haunsoe S, Svendsen JH, et al. Familial aggregation of atrial fibrillation: a study in Danish twins. Circ Arrhythm Electrophysiol. 2009;2:378–383.
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7. Ellinor PT, Lunetta KL, Glazer NL, Pfeufer A, Alonso A, Chung MK, et al. Common variants in KCNN3 are associated with lone atrial fibrillation. Nat Genet. 2010;42:240–244.
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11. Kirchhof P, Kahr PC, Kaese S, Piccini I, Vokshi I, Scheld HH, et al. PITX2c is expressed in the adult left atrium, and reducing Pitx2c expression promotes atrial fibrillation inducibility and complex changes in gene expression. Circ Cardiovasc Genet. 2011;4:123–133.
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Atrial fibrillation is the most common sustained cardiac arrhythmias in the United States. The genetic and molecular mechanisms governing its initiation and progression are complex, and our understanding of these mechanisms remains incomplete despite recent advances via genome-wide association studies, animal model experiments, and differential expression studies. In this study, we used weighted gene coexpression network analysis to identify gene modules significantly associated with atrial fibrillation in a large sample of human left atrial appendage tissues. We further identified highly interconnected genes (ie, hub genes) within these gene modules that may be novel candidates for functional studies. The discovery of the atrial fibrillation-associated gene modules and their corresponding hub genes provide novel insight into the gene network changes that occur with atrial fibrillation, and closer study of these findings can lead to more effective targeted therapies for disease management.
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