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Archive for the ‘Genomic Endocrinology’ Category

Genders redefined by biology

Posted in Biological Engineering, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cell Biology, Cell Biology, Signaling & Cell Circuits, Gene Regulation, Gene Regulation and Evolution, Genetics & Pharmaceutical, Genome Biology, Genomic Endocrinology, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, tagged , , , , , , on March 10, 2018| Leave a Comment »


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Biologists may have been building a more nuanced view of sex, but society has yet to catch up. True, more than half a century of activism from members of the lesbian, gay, bisexual and transgender community has softened social attitudes to sexual orientation and gender. Many societies are now comfortable with men and women crossing conventional societal boundaries in their choice of appearance, career and sexual partner. But when it comes to sex, there is still intense social pressure to conform to the binary model.

 

This pressure has meant that people born with clear DSDs (difference/disorder of sex development) often undergo surgery to ‘normalize’ their genitals. Such surgery is controversial because it is usually performed on babies, who are too young to consent, and risks assigning a sex at odds with the child’s ultimate gender identity — their sense of their own gender. Intersex advocacy groups have therefore argued that doctors and parents should at least wait until a child is old enough to communicate their gender identity, which typically manifests around the age of three, or old enough to decide whether they want surgery at all.

 

As many as 1 person in 100 has some form of “DSD” with or without external manifestation. Diagnoses of DSDs previously relied on hormone tests, anatomical inspections and imaging, followed by painstaking tests of one gene at a time. Now, advances in genetic techniques mean that teams can analyze multiple genes at once, aiming straight for a genetic diagnosis and making the process less stressful for families. Children with DSDs are treated by multidisciplinary teams that aim to tailor management and support to each individual and their family, but this usually involves raising a child as male or female even if no surgery is done.

 

The simple scenario that all learn is that two X chromosomes make someone female, and an X and a Y chromosome make someone male. These are simplistic ways of thinking about what is scientifically very complex. Anatomy, hormones, cells, and chromosomes (and also personal identity convictions) are actually not usually aligned with this binary classification.

 

More than 25 genes that affect sex development have now been identified, and they have a wide range of variations that affect people in subtle ways. Many differences aren’t even noticed until incidental medical encounters, such as a forty-six-year-old woman pregnant with her third child, found after amniocentesis that half her cells carry male chromosomes. Or a seventy-year-old father of three who learns during a hernia repair that he has a uterus.

 

Furthermore, scientists now understood that everyone’s body is made up of a patchwork of genetically distinct cells, some of which may have a different sex than the rest. This “mosaicism” can have effects ranging from undetectable to extraordinary, such as “identical” twins of different sexes. An extremely common instance of mosaicism comes from cells passing over the placental barrier during pregnancy. Men often carry female cells from their mothers, and women carry male cells from their sons. Research has shown that these cells remain present for decades, but what effects they have on disease and behavior is an essentially unstudied question.

 

References:

 

https://www.theguardian.com/science/2017/mar/02/cambridge-scientists-create-first-self-developing-embryo-from-stem-cells

 

https://www.ncbi.nlm.nih.gov/pubmed/25693544

 

http://onlinelibrary.wiley.com/doi/10.1002/ajmg.a.34123/abstract;jsessionid=A330AD995EE25C7A0AD5EA478694ADD8.f04t01

 

https://www.ncbi.nlm.nih.gov/pubmed/25091731

 

https://www.ncbi.nlm.nih.gov/pubmed/1695712

 

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Knowing the genetic vulnerability of bladder cancer for therapeutic intervention

Posted in Anticancer Resistance, Apoptosis, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceuticall R&D Informatics, Clinical Genomics, Cancer Informatics, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell death pathways, Cell Processing System in Cell Therapy Process Development, Childhood cancer, Clinical Diagnostics, Clinical Genomics, Gene Regulation, Gene Therapy & Gene Editing Development, Genome Biology, Genomic Endocrinology, interventional oncology, Metabolic Immuno-Oncology, Metastasis Process, Microbiome and Responses to Cancer Therapy, mRNA Therapeutics, Mutagenesis, Personalized and Precision Medicine & Genomic Research, Population genetics, Population Health Management, Population Health Management, Genetics & Pharmaceutical, RNA Biology, RNA Biology, Cancer and Therapeutics, Signaling, tagged , , , , , , on November 21, 2017| Leave a Comment »


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

A mutated gene called RAS gives rise to a signalling protein Ral which is involved in tumour growth in the bladder. Many researchers tried and failed to target and stop this wayward gene. Signalling proteins such as Ral usually shift between active and inactive states.

 

So, researchers next tried to stop Ral to get into active state. In inacvtive state Ral exposes a pocket which gets closed when active. After five years, the researchers found a small molecule dubbed BQU57 that can wedge itself into the pocket to prevent Ral from closing and becoming active. Now, BQU57 has been licensed for further development.

 

Researchers have a growing genetic data on bladder cancer, some of which threaten to overturn the supposed causes of bladder cancer. Genetics has also allowed bladder cancer to be reclassified from two categories into five distinct subtypes, each with different characteristics and weak spots. All these advances bode well for drug development and for improved diagnosis and prognosis.

 

Among the groups studying the genetics of bladder cancer are two large international teams: Uromol (named for urology and molecular biology), which is based at Aarhus University Hospital in Denmark, and The Cancer Genome Atlas (TCGA), based at institutions in Texas and Boston. Each team tackled a different type of cancer, based on the traditional classification of whether or not a tumour has grown into the muscle wall of the bladder. Uromol worked on the more common, earlier form, non-muscle-invasive bladder cancer, whereas TCGA is looking at muscle-invasive bladder cancer, which has a lower survival rate.

 

The Uromol team sought to identify people whose non-invasive tumours might return after treatment, becoming invasive or even metastatic. Bladder cancer has a high risk of recurrence, so people whose non-invasive cancer has been treated need to be monitored for many years, undergoing cystoscopy every few months. They looked for predictive genetic footprints in the transcriptome of the cancer, which contains all of a cell’s RNA and can tell researchers which genes are turned on or off.

 

They found three subgroups with distinct basal and luminal features, as proposed by other groups, each with different clinical outcomes in early-stage bladder cancer. These features sort bladder cancer into genetic categories that can help predict whether the cancer will return. The researchers also identified mutations that are linked to tumour progression. Mutations in the so-called APOBEC genes, which code for enzymes that modify RNA or DNA molecules. This effect could lead to cancer and cause it to be aggressive.

 

The second major research group, TCGA, led by the National Cancer Institute and the National Human Genome Research Institute, that involves thousands of researchers across USA. The project has already mapped genomic changes in 33 cancer types, including breast, skin and lung cancers. The TCGA researchers, who study muscle-invasive bladder cancer, have looked at tumours that were already identified as fast-growing and invasive.

 

The work by Uromol, TCGA and other labs has provided a clearer view of the genetic landscape of early- and late-stage bladder cancer. There are five subtypes for the muscle-invasive form: luminal, luminal–papillary, luminal–infiltrated, basal–squamous, and neuronal, each of which is genetically distinct and might require different therapeutic approaches.

 

Bladder cancer has the third-highest mutation rate of any cancer, behind only lung cancer and melanoma. The TCGA team has confirmed Uromol research showing that most bladder-cancer mutations occur in the APOBEC genes. It is not yet clear why APOBEC mutations are so common in bladder cancer, but studies of the mutations have yielded one startling implication. The APOBEC enzyme causes mutations early during the development of bladder cancer, and independent of cigarette smoke or other known exposures.

 

The TCGA researchers found a subset of bladder-cancer patients, those with the greatest number of APOBEC mutations, had an extremely high five-year survival rate of about 75%. Other patients with fewer APOBEC mutations fared less well which is pretty surprising.

 

This detailed knowledge of bladder-cancer genetics may help to pinpoint the specific vulnerabilities of cancer cells in different people. Over the past decade, Broad Institute researchers have identified more than 760 genes that cancer needs to grow and survive. Their genetic map might take another ten years to finish, but it will list every genetic vulnerability that can be exploited. The goal of cancer precision medicine is to take the patient’s tumour and decode the genetics, so the clinician can make a decision based on that information.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/29117162

 

https://www.ncbi.nlm.nih.gov/pubmed/27321955

 

https://www.ncbi.nlm.nih.gov/pubmed/28583312

 

https://www.ncbi.nlm.nih.gov/pubmed/24476821

 

https://www.ncbi.nlm.nih.gov/pubmed/28988769

 

https://www.ncbi.nlm.nih.gov/pubmed/28753430

 

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Promising research for a male birth control pill

Posted in Affordable Care Act, Bioengineering & reverse engineering design, Biological Networks, Biological Networks, Gene Regulation and Evolution, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell Processing System in Cell Therapy Process Development, Chemical Genetics, Clinical & Translational, Clinical Genomics, CRISPR/Cas9 & Gene Editing, Developmental biology, Diagnostics and Lab Tests, Drug Development Process, Drug Discovery Chemistry, Gene Regulation, Gene Therapy & Gene Editing Development, Genetics & Innovations in Treatment, Genetics & Pharmaceutical, Genome Biology, Genomic Endocrinology, Genomic Testing: Methodology for Diagnosis, Genomics Pharmacy, Medical and Population Genetics, Pharmaceutical Drug Discovery, Population Health Management, Population Health Management, Genetics & Pharmaceutical, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, Reproductive Biology & Bio Instrumentation, tagged , , , , , on March 23, 2017| Leave a Comment »


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Scientists think excessive population growth is a cause of scarcity and environmental degradation. A male pill could reduce the number of unintended pregnancies, which accounts for 40 percent of all pregnancies worldwide.

 

But, big drug companies long ago dropped out of the search for a male contraceptive pill which is able to chemically intercept millions of sperm before they reach a woman’s egg. Right now the chemical burden for contraception relies solely on the female. There’s not much activity in the male contraception field because an effective solution is available on the female side.

 

Presently, male contraception means a condom or a vasectomy. But researchers from Center for Drug Discovery at Baylor College of Medicine, USA are renewing the search for a better option—an easy-to-take pill that’s safe, fast-acting, and reversible.

 

The scientists began with lists of genes active in the testes for sperm production and motility and then created knockout mice that lack those genes. Using the gene-editing technology called CRISPR, in collaboration with Japanese scientists, they have so far made more than 75 of these “knockout” mice.

 

They allowed these mice to mate with normal (wild type) female mice, and if their female partners don’t get pregnant after three to six months, it means the gene might be a target for a contraceptive. Out of 2300 genes that are particularly active in the testes of mice, the researchers have identified 30 genes whose deletion makes the male infertile. Next the scientists are planning a novel screening approach to test whether any of about two billion chemicals can disable these genes in a test tube. Promising chemicals could then be fed to male mice to see if they cause infertility.

 

Female birth control pills use hormones to inhibit a woman’s ovaries from releasing eggs. But hormones have side effects like weight gain, mood changes, and headaches. A trial of one male contraceptive hormone was stopped early in 2011 after one participant committed suicide and others reported depression. Moreover, some drug candidates have made animals permanently sterile which is not the goal of the research. The challenge is to prevent sperm being made without permanently sterilizing the individual.

 

As a better way to test drugs, Scientists at University of Georgia, USA are investigating yet another high-tech approach. They are turning human skin cells into stem cells that look and act like the spermatogonial cells in the testes. Testing drugs on such cells might provide more accurate leads than tests on mice.

 

The male pill would also have to start working quickly, a lot sooner than the female pill, which takes about a week to function. Scientists from University of Dundee, U.K. admitted that there are lots of challenges. Because, a women’s ovary usually release one mature egg each month, while a man makes millions of sperm every day. So, the male pill has to be made 100 percent effective and act instantaneously.

 

References:

 

https://www.technologyreview.com/s/603676/the-search-for-a-perfect-male-birth-control-pill/

 

https://futurism.com/videos/the-perfect-male-birth-control-pill-is-coming-soon/?utm_source=Digest&utm_campaign=c42fc7b9b6-EMAIL_CAMPAIGN_2017_03_20&utm_medium=email&utm_term=0_03cd0a26cd-c42fc7b9b6-246845533

 

http://www.telegraph.co.uk/women/sex/the-male-pill-is-coming—and-its-going-to-change-everything/

 

http://www.mensfitness.com/women/sex-tips/male-birth-control-pill-making

 

http://health.howstuffworks.com/sexual-health/contraception/male-bc-pill.htm

 

http://europe.newsweek.com/male-contraception-side-effects-study-pill-injection-518237?rm=eu

 

http://edition.cnn.com/2016/01/07/health/male-birth-control-pill/index.html

 

http://www.nhs.uk/Conditions/contraception-guide/Pages/male-pill.aspx

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MicroRNA in Reproduction

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Biomedical Measurement Science, Cargo, Cell Biology, Cell Biology, Signaling & Cell Circuits, Clinical Diagnostics, Clinical Genomics, Developmental biology, Disease Biology, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Exosomes, Gene Regulation, Gene Therapy & Gene Editing Development, Genetics & Innovations in Treatment, Genetics & Pharmaceutical, Genomic Endocrinology, Genomic Testing: Methodology for Diagnosis, Genomics Pharmacy, Personalized and Precision Medicine & Genomic Research, Population genetics, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, RNA Biology, tagged , , , , , , , on November 9, 2016| Leave a Comment »


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

MicroRNAs (miRNAs) are a group of small non-coding RNA molecules that play a major role in posttranscriptional regulation of gene expression and are expressed in an organ-specific manner. One miRNA can potentially regulate the expression of several genes, depending on cell type and differentiation stage. They control every cellular process and their altered regulation is involved in human diseases. miRNAs are differentially expressed in the male and female gonads and have an organ-specific reproductive function. Exerting their affect through germ cells and gonadal somatic cells, miRNAs regulate key proteins necessary for gonad development. The role of miRNAs in the testes is only starting to emerge though they have been shown to be required for adequate spermatogenesis. In the ovary, miRNAs play a fundamental role in follicles’ assembly, growth, differentiation, and ovulation.

 

Deciphering the underlying causes of idiopathic male infertility is one of the main challenges in reproductive medicine. This is especially relevant in infertile patients displaying normal seminal parameters and no urogenital or genetic abnormalities. In these cases, the search for additional sperm biomarkers is of high interest. This study was aimed to determine the implications of the sperm miRNA expression profiles in the reproductive capacity of normozoospermic infertile individuals. The expression levels of 736 miRNAs were evaluated in spermatozoa from normozoospermic infertile males and normozoospermic fertile males analyzed under the same conditions. 57 miRNAs were differentially expressed between populations; 20 of them was regulated by a host gene promoter that in three cases comprised genes involved in fertility. The predicted targets of the differentially expressed miRNAs unveiled a significant enrichment of biological processes related to embryonic morphogenesis and chromatin modification. Normozoospermic infertile individuals exhibit a specific sperm miRNA expression profile clearly differentiated from normozoospermic fertile individuals. This miRNA cargo has potential implications in the individuals’ reproductive competence.

 

Circulating or “extracellular” miRNAs detected in biological fluids, could be used as potential diagnostic and prognostic biomarkers of several disease, such as cancer, gynecological and pregnancy disorders. However, their contributions in female infertility and in vitro fertilization (IVF) remain unknown. Polycystic ovary syndrome (PCOS) is a frequent endocrine disorder in women. PCOS is associated with altered features of androgen metabolism, increased insulin resistance and impaired fertility. Furthermore, PCOS, being a syndrome diagnosis, is heterogeneous and characterized by polycystic ovaries, chronic anovulation and evidence of hyperandrogenism, as well as being associated with chronic low-grade inflammation and an increased life time risk of type 2 diabetes. Altered miRNA levels have been associated with diabetes, insulin resistance, inflammation and various cancers. Studies have shown that circulating miRNAs are present in whole blood, serum, plasma and the follicular fluid of PCOS patients and that these might serve as potential biomarkers and a new approach for the diagnosis of PCOS. Presence of miRNA in mammalian follicular fluid has been demonstrated to be enclosed within microvesicles and exosomes or they can also be associated to protein complexes. The presence of microvesicles and exosomes carrying microRNAs in follicular fluid could represent an alternative mechanism of autocrine and paracrine communication inside the ovarian follicle. The investigation of the expression profiles of five circulating miRNAs (let-7b, miR-29a, miR-30a, miR-140 and miR-320a) in human follicular fluid from women with normal ovarian reserve and with polycystic ovary syndrome (PCOS) and their ability to predict IVF outcomes showed that these miRNAs could provide new helpful biomarkers to facilitate personalized medical care for oocyte quality in ART (Assisted Reproductive Treatment) and during IVF (In Vitro Fertilization).

 

References:

 

http://link.springer.com/chapter/10.1007%2F978-3-319-31973-5_12

 

http://onlinelibrary.wiley.com/doi/10.1111/andr.12276/abstract;jsessionid=F805A89DCC94BDBD42D6D60C40AD4AB0.f03t03

 

http://www.sciencedirect.com/science/article/pii/S0009279716302241

 

http://link.springer.com/article/10.1007%2Fs10815-016-0657-9

 

http://www.nature.com/articles/srep24976

 

 

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Genomics Orientations for Personalized Medicine: Request for Book Review Writing on Amazon.com

Posted in CRISPR/Cas9 & Gene Editing, DNA repair, Epigenetics and Environmental Factors, FDA, FDA Regulatory Affairs, Gene Regulation, Gene Regulation and Evolution, Genetics & Innovations in Treatment, Genetics & Pharmaceutical, Genome Biology, Genomic Endocrinology, Genomic Testing: Methodology for Diagnosis, Personalized and Precision Medicine & Genomic Research, Pharmaceuticall R&D Informatics, Pharmacogenomics, Population genetics, Population Health Management, Population Health Management, Genetics & Pharmaceutical on September 11, 2016| Leave a Comment »


genomicsinpersonalizedmedicinecovervolumeone

Series B: Frontiers in Genomics Research

Content Consultant: Larry H Bernstein, MD, FCAP

Genomics Orientations for Personalized Medicine

Volume One

http://www.amazon.com/dp/B018DHBUO6

electronic Table of Contents

Chapter 1

1.1 Advances in the Understanding of the Human Genome The Initiation and Growth of Molecular Biology and Genomics – Part I

1.2 CRACKING THE CODE OF HUMAN LIFE: Milestones along the Way – Part IIA

1.3 DNA – The Next-Generation Storage Media for Digital Information

1.4 CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomic Analysis and Disease – Part IIC

1.5 Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

1.6 Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology

Chapter 2

2.1 2013 Genomics: The Era Beyond the Sequencing of the Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

2.2 DNA structure and Oligonucleotides

2.3 Genome-Wide Detection of Single-Nucleotide and Copy-Number Variation of a Single Human Cell 

2.4 Genomics and Evolution

2.5 Protein-folding Simulation: Stanford’s Framework for Testing and Predicting Evolutionary Outcomes in Living Organisms – Work by Marcus Feldman

2.6 The Binding of Oligonucleotides in DNA and 3-D Lattice Structures

2.7 Finding the Genetic Links in Common Disease: Caveats of Whole Genome Sequencing Studies

Chapter 3

3.1 Big Data in Genomic Medicine

3.2 CRACKING THE CODE OF HUMAN LIFE: The Birth of Bioinformatics & Computational Genomics – Part IIB 

3.3 Expanding the Genetic Alphabet and linking the Genome to the Metabolome

3.4 Metabolite Identification Combining Genetic and Metabolic Information: Genetic Association Links Unknown Metabolites to Functionally Related Genes

3.5 MIT Scientists on Proteomics: All the Proteins in the Mitochondrial Matrix identified

3.6 Identification of Biomarkers that are Related to the Actin Cytoskeleton

3.7 Genetic basis of Complex Human Diseases: Dan Koboldt’s Advice to Next-Generation Sequencing Neophytes

3.8 MIT Team Researches Regulatory Motifs and Gene Expression of Erythroleukemia (K562) and Liver Carcinoma (HepG2) Cell Lines

Chapter 4

4.1 ENCODE Findings as Consortium

4.2 ENCODE: The Key to Unlocking the Secrets of Complex Genetic Diseases

4.3 Reveals from ENCODE Project will Invite High Synergistic Collaborations to Discover Specific Targets  

4.4 Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence

4.5 Human Genome Project – 10th Anniversary: Interview with Kevin Davies, PhD – The $1000 Genome

4.6 Quantum Biology And Computational Medicine

4.7 The Underappreciated EpiGenome

4.8 Unraveling Retrograde Signaling Pathways

4.9  “The SILENCE of the Lambs” Introducing The Power of Uncoded RNA

4.10  DNA: One man’s trash is another man’s treasure, but there is no JUNK after all

Chapter 5

5.1 Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1 

5.2 Computational Genomics Center: New Unification of Computational Technologies at Stanford

5.3 Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

5.4 Cancer Genomics – Leading the Way by Cancer Genomics Program at UC Santa Cruz

5.5 Genome and Genetics: Resources @Stanford, @MIT, @NIH’s NCBCS

5.6 NGS Market: Trends and Development for Genotype-Phenotype Associations Research

5.7 Speeding Up Genome Analysis: MIT Algorithms for Direct Computation on Compressed Genomic Datasets

5.8  Modeling Targeted Therapy

5.9 Transphosphorylation of E-coli Proteins and Kinase Specificity

5.10 Genomics of Bacterial and Archaeal Viruses

Chapter 6

6.1  Directions for Genomics in Personalized Medicine

6.2 Ubiquinin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

6.3 Mitochondrial Damage and Repair under Oxidative Stress

6.4 Mitochondria: More than just the “Powerhouse of the Cell”

6.5 Mechanism of Variegation in Immutans

6.6 Impact of Evolutionary Selection on Functional Regions: The imprint of Evolutionary Selection on ENCODE Regulatory Elements is Manifested between Species and within Human Populations

6.7 Cardiac Ca2+ Signaling: Transcriptional Control

6.8 Unraveling Retrograde Signaling Pathways

6.9 Reprogramming Cell Fate

6.10 How Genes Function

6.11 TALENs and ZFNs

6.12 Zebrafish—Susceptible to Cancer

6.13 RNA Virus Genome as Bacterial Chromosome

6.14 Cloning the Vaccinia Virus Genome as a Bacterial Artificial Chromosome 

6.15 Telling NO to Cardiac Risk- DDAH Says NO to ADMA(1); The DDAH/ADMA/NOS Pathway(2)

6.16  Transphosphorylation of E-coli proteins and kinase specificity

6.17 Genomics of Bacterial and Archaeal Viruses

6.18  Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

Chapter 7

7.1 Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders @ http://pharmaceuticalintelligence.com

7.2 Consumer Market for Personal DNA Sequencing: Part 4

7.3 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”

7.4 Drugging the Epigenome

7.5 Nation’s Biobanks: Academic institutions, Research institutes and Hospitals – vary by Collections Size, Types of Specimens and Applications: Regulations are Needed

7.6 Personalized Medicine: Clinical Aspiration of Microarrays

Chapter 8

8.1 Personalized Medicine as Key Area for Future Pharmaceutical Growth

8.2 Inaugural Genomics in Medicine – The Conference Program, 2/11-12/2013, San Francisco, CA

8.3 The Way With Personalized Medicine: Reporters’ Voice at the 8th Annual Personalized Medicine Conference, 11/28-29, 2012, Harvard Medical School, Boston, MA

8.4 Nanotechnology, Personalized Medicine and DNA Sequencing

8.5 Targeted Nucleases

8.6 Transcript Dynamics of Proinflammatory Genes

8.7 Helping Physicians identify Gene-Drug Interactions for Treatment Decisions: New ‘CLIPMERGE’ program – Personalized Medicine @ The Mount Sinai Medical Center

8.8 Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing[1]

8.9 Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

Chapter 9

9.1 Personal Tale of JL’s Whole Genome Sequencing

9.2 Inspiration From Dr. Maureen Cronin’s Achievements in Applying Genomic Sequencing to Cancer Diagnostics

9.3 Inform Genomics Developing SNP Test to Predict Side Effects, Help MDs Choose among Chemo Regimens

9.4 SNAP: Predict Effect of Non-synonymous Polymorphisms: How Well Genome Interpretation Tools could Translate to the Clinic

9.5  LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2

9.6 The Initiation and Growth of Molecular Biology and Genomics – Part I

9.7 Personalized Medicine-based Cure for Cancer Might Not Be Far Away

9.8 Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

 Chapter 10

10.1 Pfizer’s Kidney Cancer Drug Sutent Effectively caused REMISSION to Adult Acute Lymphoblastic Leukemia (ALL)

10.2 Imatinib (Gleevec) May Help Treat Aggressive Lymphoma: Chronic Lymphocytic Leukemia (CLL)

10.3 Winning Over Cancer Progression: New Oncology Drugs to Suppress Passengers Mutations vs. Driver Mutations

10.4 Treatment for Metastatic HER2 Breast Cancer

10.5 Personalized Medicine in NSCLC

10.6 Gene Sequencing – to the Bedside

10.7 DNA Sequencing Technology

10.8 Nobel Laureate Jack Szostak Previews his Plenary Keynote for Drug Discovery Chemistry

Chapter 11

11.1 mRNA Interference with Cancer Expression

11.2 Angiogenic Disease Research Utilizing microRNA Technology: UCSD and Regulus Therapeutics

11.3 Sunitinib brings Adult acute lymphoblastic leukemia (ALL) to Remission – RNA Sequencing – FLT3 Receptor Blockade

11.4 A microRNA Prognostic Marker Identified in Acute Leukemia 

11.5 MIT Team: Microfluidic-based approach – A Vectorless delivery of Functional siRNAs into Cells.

11.6 Targeted Tumor-Penetrating siRNA Nanocomplexes for Credentialing the Ovarian Cancer Oncogene ID4

11.7 When Clinical Application of miRNAs?

11.8 How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis,

11.9 Potential Drug Target: Glycolysis Regulation – Oxidative Stress-responsive microRNA-320

11.10  MicroRNA Molecule May Serve as Biomarker

11.11 What about Circular RNAs?

Chapter 12

12.1 The “Cancer Establishments” Examined by James Watson, Co-discoverer of DNA w/Crick, 4/1953

12.2 Otto Warburg, A Giant of Modern Cellular Biology

12.3 Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

12.4 Hypothesis – Following on James Watson

12.5 AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

12.6 AKT signaling variable effects

12.7 Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers

12.8 Phosphatidyl-5-Inositol signaling by Pin1

Chapter 13

13.1 Nanotech Therapy for Breast Cancer

13.2 BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

13.3 Exome sequencing of serous endometrial tumors shows recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes

13.4 Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in serous endometrial tumors

13.5 Prostate Cancer: Androgen-driven “Pathomechanism” in Early onset Forms of the Disease

13.6 In focus: Melanoma Genetics

13.7 Head and Neck Cancer Studies Suggest Alternative Markers More Prognostically Useful than HPV DNA Testing

13.8 Breast Cancer and Mitochondrial Mutations

13.9  Long noncoding RNA network regulates PTEN transcription

Chapter 14

14.1 HBV and HCV-associated Liver Cancer: Important Insights from the Genome

14.2 Nanotechnology and HIV/AIDS treatment

14.3 IRF-1 Deficiency Skews the Differentiation of Dendritic Cells

14.4 Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control

14.5  Five Malaria Genomes Sequenced

14.6 Rheumatoid Arthritis Risk

14.7 Approach to Controlling Pathogenic Inflammation in Arthritis

14.8 RNA Virus Genome as Bacterial Chromosome

14.9 Cloning the Vaccinia Virus Genome as a Bacterial Artificial Chromosome

Chapter 15

15.1 Personalized Cardiovascular Genetic Medicine at Partners HealthCare and Harvard Medical School

15.2 Congestive Heart Failure & Personalized Medicine: Two-gene Test predicts response to Beta Blocker Bucindolol

15.3 DDAH Says NO to ADMA(1); The DDAH/ADMA/NOS Pathway(2)

15.4 Peroxisome Proliferator-Activated Receptor (PPAR-gamma) Receptors Activation: PPARγ Transrepression for Angiogenesis in Cardiovascular Disease and PPARγ Transactivation for Treatment of Diabetes

15.5 BARI 2D Trial Outcomes

15.6 Gene Therapy Into Healthy Heart Muscle: Reprogramming Scar Tissue In Damaged Hearts

15.7 Obstructive coronary artery disease diagnosed by RNA levels of 23 genes – CardioDx, a Pioneer in the Field of Cardiovascular Genomic  Diagnostics

15.8 Ca2+ signaling: transcriptional control

15.9 Lp(a) Gene Variant Association

15.9.1 Two Mutations, in the PCSK9 Gene: Eliminates a Protein involved in Controlling LDL Cholesterol

15.9.2. Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013

15.9.3 Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

15.9.4 The Implications of a Newly Discovered CYP2J2 Gene Polymorphism Associated with Coronary Vascular Disease in the Uygur Chinese Population

15.9.5  Gene, Meis1, Regulates the Heart’s Ability to Regenerate after Injuries.

15.10 Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

15.11 How Might Sleep Apnea Lead to Serious Health Concerns like Cardiac and Cancers?

Chapter 16

16.1 Can Resolvins Suppress Acute Lung Injury?

16.2 Lipoxin A4 Regulates Natural Killer Cell in Asthma

16.3 Biological Therapeutics for Asthma

16.4 Genomics of Bronchial Epithelial Dysplasia

16.5 Progression in Bronchial Dysplasia

Chapter 17

17.1 Breakthrough Digestive Disorders Research: Conditions Affecting the Gastrointestinal Tract.

17.2 Liver Endoplasmic Reticulum Stress and Hepatosteatosis

17.3 Biomarkers-identified-for-recurrence-in-hbv-related-hcc-patients-post-surgery

17.4  Usp9x: Promising Therapeutic Target for Pancreatic Cancer

17.5 Battle of Steve Jobs and Ralph Steinman with Pancreatic cancer: How We Lost

Chapter 18

18.1 Ubiquitin Pathway Involved in Neurodegenerative Disease

18.2 Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious Depression

18.3 Neuroprotective Therapies: Pharmacogenomics vs Psychotropic Drugs and Cholinesterase Inhibitors

18.4 Ustekinumab New Drug Therapy for Cognitive Decline Resulting from Neuroinflammatory Cytokine Signaling and Alzheimer’s Disease

18.5 Cell Transplantation in Brain Repair

18.6 Alzheimer’s Disease Conundrum – Are We Near the End of the Puzzle?

Chapter 19

19.1 Genetics and Male Endocrinology

19.2 Genomic Endocrinology and its Future

19.3 Commentary on Dr. Baker’s post “Junk DNA Codes for Valuable miRNAs: Non-coding DNA Controls Diabetes”

19.4 Therapeutic Targets for Diabetes and Related Metabolic Disorders

19.5 Secondary Hypertension caused by Aldosterone-producing Adenomas caused by Somatic Mutations in ATP1A1 and ATP2B3 (adrenal cortical; medullary or Organ of Zuckerkandl is pheochromocytoma)

19.6 Personal Recombination Map from Individual’s Sperm Cell and its Importance

19.7 Gene Trap Mutagenesis in Reproductive Research

19.8 Pregnancy with a Leptin-Receptor Mutation

19.9 Whole-genome Sequencing in Probing the Meiotic Recombination and Aneuploidy of Single Sperm Cells

19.10 Reproductive Genetic Testing

Chapter 20

20.1 Genomics & Ethics: DNA Fragments are Products of Nature or Patentable Genes?

20.2 Understanding the Role of Personalized Medicine

20.3 Attitudes of Patients about Personalized Medicine

20.4  Genome Sequencing of the Healthy

20.5   Genomics in Medicine – Tomorrow’s Promise

20.6  The Promise of Personalized Medicine

20.7 Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk

 20.8 Genomic Liberty of Ownership, Genome Medicine and Patenting the Human Genome

Chapter 21

Recent Advances in Gene Editing Technology Adds New Therapeutic Potential for the Genomic Era:  Medical Interpretation of the Genomics Frontier – CRISPR – Cas9

Introduction

21.1 Introducing CRISPR/Cas9 Gene Editing Technology – Works by Jennifer A. Doudna

21.1.1 Ribozymes and RNA Machines – Work of Jennifer A. Doudna

21.1.2 Evaluate your Cas9 gene editing vectors: CRISPR/Cas Mediated Genome Engineering – Is your CRISPR gRNA optimized for your cell lines?

21.1.3 2:15 – 2:45, 6/13/2014, Jennifer Doudna “The biology of CRISPRs: from genome defense to genetic engineering”

21.1.4  Prediction of the Winner RNA Technology, the FRONTIER of SCIENCE on RNA Biology, Cancer and Therapeutics  & The Start Up Landscape in BostonGene Editing – New Technology The Missing link for Gene Therapy?

21.2 CRISPR in Other Labs

21.2.1 CRISPR @MIT – Genome Surgery

21.2.2 The CRISPR-Cas9 System: A Powerful Tool for Genome Engineering and Regulation

Yongmin Yan and Department of Gastroenterology, Hepatology & Nutrition, University of Texas M.D. Anderson Cancer, Houston, USADaoyan Wei*

21.2.3 New Frontiers in Gene Editing: Transitioning From the Lab to the Clinic, February 19-20, 2015 | The InterContinental San Francisco | San Francisco, CA

21.2.4 Gene Therapy and the Genetic Study of Disease: @Berkeley and @UCSF – New DNA-editing technology spawns bold UC initiative as Crispr Goes Global

21.2.5 CRISPR & MAGE @ George Church’s Lab @ Harvard

21.3 Patents Awarded and Pending for CRISPR

21.3.1 Litigation on the Way: Broad Institute Gets Patent on Revolutionary Gene-Editing Method

21.3.2 The Patents for CRISPR, the DNA editing technology as the Biggest Biotech Discovery of the Century

2.4 CRISPR/Cas9 Applications

21.4.1  Inactivation of the human papillomavirus E6 or E7 gene in cervical carcinoma cells using a bacterial CRISPR/Cas 

21.4.2 CRISPR: Applications for Autoimmune Diseases @UCSF

21.4.3 In vivo validated mRNAs

21.4.4 Delineating a Role for CRISPR-Cas9 in Pharmaceutical Targeting
21.4.5 Where is the most promising avenue to success in Pharmaceuticals with CRISPR-Cas9?

21.4.6 Level of Comfort with Making Changes to the DNA of an Organism

21.4.7 Who will be the the First to IPO: Novartis bought in to Intellia (UC, Berkeley) as well as Caribou (UC, Berkeley) vs Editas (MIT)??

21.4.8 CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development

Summary

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Crowdsourcing Genetic Data Yields Discovery of DNA loci associated with Major Depressive Disorder (MDD) in European Descendants

Posted in Biological Networks, Gene Regulation and Evolution, Biomarkers & Medical Diagnostics, Computational Biology/Systems and Bioinformatics, Exosomes, Gene Regulation, Gene Regulation and Evolution, Genetics & Innovations in Treatment, Genome Biology, Genomic Endocrinology, Genomic Testing: Methodology for Diagnosis, Innovations in Neurophysiology & Neuropsychology, Neurological Diseases, Next Generation Sequencing (NGS), Personalized and Precision Medicine & Genomic Research, tagged , , , , , , , , , , , on August 9, 2016| Leave a Comment »


Crowdsourcing Genetic Data Yields Discovery of DNA loci associated with Major Depressive Disorder (MDD) in European Descendants

 

Reporter: Kelly Perlman, Life Sciences Student and Research Assistant, McGill University

 

Researchers from Pfizer Global Research and Development, 23andMe, and the Massachusetts General Hospital have published a study in Nature Genetics, pinpointing 15 genetic loci associated with the risk of developing major depressive disorder (MDD) in individuals of European ancestry. Evidence from previous research suggests that MDD is heritable, but the details of the specific gene correlates are unclear. The identification of loci where single nucleotide polymorphisms (SNPs) related to MDD exist could provide better insight into the neurobiology of depression, and therefore better treatment options.

23andMe, a private biotechnology company situated in California, offers a DNA sequencing service in which consumers send in a saliva swab for testing, and later receive a report listing the findings of the analysis related to ancestry, physical and behavioral traits, along with risk of inheriting certain diseases. The participants of this study had agreed to provide the results of their genetic testing for scientific research.

The results of 75,607 participants with self-reported diagnoses of depression were compared to the results of 231,747 participants reporting having never experienced depression. This data was combined with the results of previously published MDD genome-wide association studies (GWAS). To test the whether these results could be replicated, another set of results from 23andMe was analyzed, in which there were 45,773 MDD subjects, and 106,354 controls.

After the joint analysis, 17 SNPs were identified at 15 different loci. Tissue and gene enrichment assays showed that the genes that were over-expressed in the CNS were related to functions including neurodevelopment, histone methylation, neurogenesis and synaptic modification.

The team then created a weighted genetic risk score (GRS) in which they compared the 17 SNPs with factors including medication use, comorbid diseases and behavioral phenotypes, all of which were correlated with the GRS. Of note, the GRS was very highly correlated with age of onset of MDD.

The crowdsourcing of genetic data proves to be an efficient and powerful tool for large-scale MDD studies. Pooling large subject databases together is essential in order to account for the heterogeneous nature of the disease. Despite not being able to precisely assess each subject’s disease phenotype, scientists can make more rapid headway by collaborating with biotechnology companies in the quest to better understand the biological mechanisms of depression. Ron Perlis, M.D., M.Sc., of the Massachusetts General Hospital and co-author of this paper explained that “finding genes associated with depression should help make clear that this is a brain disease, which we hope will decrease the stigma still associated with these kinds of illnesses”.

 

Details on specific significant genes:

http://www.genecards.org/cgi-bin/carddisp.pl?gene=OLFM4

http://www.genecards.org/cgi-bin/carddisp.pl?gene=TMEM161B

http://www.genecards.org/cgi-bin/carddisp.pl?gene=MEF2C

http://www.genecards.org/cgi-bin/carddisp.pl?gene=MEIS2

http://www.genecards.org/cgi-bin/carddisp.pl?gene=TMCO5A

http://www.genecards.org/cgi-bin/carddisp.pl?gene=NEGR1

 

SOURCES

Hyde, C. L., Nagle, M. W., Tian, C., Chen, X., Paciga, S. A., Wendland, J. R., . . . Winslow, A. R. (2016). Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nature Genetics Nat Genet. doi:10.1038/ng.3623

Major Depressive Disorder Loci Discovered in Large GWAS Enabled by 23andMe Participants’ Data. (2016, August 01). Retrieved August 09, 2016, from https://www.genomeweb.com/microarrays-multiplexing/major-depressive-disorder-loci-discovered-large-gwas-enabled-23andme

 

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A genetic switch to control female sexual behavior

Posted in Behavior, Behavioral Genetics, Biological Networks, Gene Regulation and Evolution, Cell Biology, Cell Biology, Signaling & Cell Circuits, CRISPR/Cas9 & Gene Editing, Developmental biology, Genomic Endocrinology, Reproductive Andrology, Embryology, Genomic Endocrinology, Preimplantation Genetic Diagnosis and Reproductive Genomics, Reproductive Biology & Bio Instrumentation, Signaling & Cell Circuits, tagged , , , , , on May 16, 2016| Leave a Comment »


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

In an African cichlid fish, Astatotilapia burtoni, fertile females select a mate and perform a stereotyped spawning / mating routine, offering quantifiable behavioral outputs of neural circuits. A male fish attracts a fertile female by rapidly quivering his brightly colored body. If she chooses him, he guides her back to his territory, where he quivers some more as she pecks at fish egg–colored spots on his anal fin. Next, she lays eggs and quickly scoops them up in her mouth. With a mouthful of eggs, she continues pecking at the male’s spots, “believing” them to be eggs to be collected. As she does, he releases sperm from near his anal fin, which she also gathers. This fertilizes the eggs, and she carries the embryos in her mouth for two weeks as they develop.

 

But, the question was how these females can time their reproduction to coincide with when they are fertile. The female fish will not approach or choose males until they are ready to reproduce, so there must be something in their brains that signals when sexual behavior will be required. The scientists began by considering signaling molecules previously associated with sexual behavior and reproduction, and showed that PGF2α injection activates a naturalistic pattern of sexual behavior in female Astatotilapia burtoni. They would engage in mating behavior even if they were non-fertile, doing the quiver dance with males, but wouldn’t actually lay eggs since they had none.

 

The scientists also identified cells in the brain that transduce the prostaglandin signal to mate and showed that the gonadal steroid 17α, 20β-dihydroxyprogesterone modulates mRNA levels of the putative receptor for PGF2α. The scientists keyed in on a receptor for PGF2α in the preoptic area (POA) within the hypothalamus of the brain, a region involved in sexual behavior across animals. They suspected that when PGF2α levels elevated in the fish, the molecule attaches to this receptor and triggers sexual behavior. Then they used CRISPR/Cas9 to generate PGF2α receptor knockout fish. This gene deletion or knockout uncoupled the sexual behavior from fertility status to prove that the receptor of PGF2α is necessary for the initiation of sexual behavior.

 

The finding has parallels across all vertebrates, and might influence the understanding of social behavior in humans. The next steps for this work will involve understanding other behaviors that are regulated by this receptor, and the finding provides insight into both the evolution of reproduction and sexual behaviors. In mammals and other vertebrates, PGF2α promotes the onset of labor and motherly behaviors, and this present research, coupled with other studies, suggests that PGF2α signaling has a common ancestral function associated with birth and its related behaviors.

 

References:

 

http://www.ncbi.nlm.nih.gov/pubmed/26996507

 

http://news.stanford.edu/news/2016/march/fish-mating-behavior-031716.html

 

 

http://www.academia.edu/676252/The_Genetics_of_Female_Sexual_Behaviour

 

https://scifeeds.com/news/scientists-identify-genetic-switch-for-female-sexual-behavior/

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