Download or read book Genome Wide Association Studies written by Tatsuhiko Tsunoda and published by Springer Nature. This book was released on 2019-10-31 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the utility of genome-wide association studies (GWAS) in the era of next-generation sequencing and big data, identifies limitations and potential means of overcoming them, and looks to the future of GWAS and what may lay beyond. GWAS are among the most powerful tools for elucidating the genetic aspects of human and disease diversity. In Genome-Wide Association Studies, experts in the field explore in depth the impacts of GWAS on genomic research into a variety of common diseases, including cardiovascular, autoimmune, diabetic, cancer, and infectious diseases. The book will equip readers with a sound understanding both of the types of disease and phenotypes that are suited for GWAS and of the ways in which a road map resulting from GWAS can lead to the realization of personalized/precision medicine: functional analysis, drug seeds, pathway analysis, disease mechanism, risk prediction, and diagnosis.

Download or read book Beyond Genome wide Association Studies GWAS written by Molly Hall and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Genome-wide association studies (GWAS) have identified numerous loci associated with human phenotypes. This approach, however, does not consider the richly diverse and complex environment with which humans interact throughout the life course, nor does it allow for interrelationships among genetic loci and across traits. Methods that embrace pleiotropy (the effect of one locus on more than one trait), gene-environment (GxE) and gene-gene (GxG) interactions will further unveil the impact of alterations in biological pathways and identify genes that are only involved with disease in the context of the environment. This valuable information can be used to assess personal risk and choose the most appropriate medical interventions based on an individual's genotype and environment. Additionally, a richer picture of the genetic and environmental aspects that impact complex disease will inform environmental regulations to protect vulnerable populations. Three key limitations of GWAS lead to an inability to robustly model trait prediction in a manner that reflects biological complexity: 1) GWAS explore traits in isolation, one phenotype at a time, preventing investigators from uncovering relationships that exist among multiple traits; 2) GWAS do not account for the exposome; rather, they simply explore the effect of genetic loci on an outcome; and 3) GWAS do not allow for interactions between genetic loci, despite the complexity that exists in biology. The aims described in this dissertation address these limitations. Methods employed in each aim have the potential to: uncover genetic interactions, unveil complex biology behind phenotype networks, inform public policy decisions concerning environmental exposures, and ultimately assess individual disease-risk.

Download or read book Genome wide Association Studies written by Tatsuhiko Tsunoda and published by . This book was released on 2019 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the utility of genome-wide association studies (GWAS) in the era of next-generation sequencing and big data, identifies limitations and potential means of overcoming them, and looks to the future of GWAS and what may lay beyond. GWAS are among the most powerful tools for elucidating the genetic aspects of human and disease diversity. In Genome-Wide Association Studies, experts in the field explore in depth the impacts of GWAS on genomic research into a variety of common diseases, including cardiovascular, autoimmune, diabetic, cancer, and infectious diseases. The book will equip readers with a sound understanding both of the types of disease and phenotypes that are suited for GWAS and of the ways in which a road map resulting from GWAS can lead to the realization of personalized/precision medicine: functional analysis, drug seeds, pathway analysis, disease mechanism, risk prediction, and diagnosis.

Download or read book Beyond Genetics written by Glenn McGee and published by Harper Collins. This book was released on 2004-11-09 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic science is about to radically alter our lives. Sooner than you can imagine, human beings will be capable of diagnosing their own illnesses, designating the sex of their children, even designing the food they eat -- all as easily as using a cell phone. Now is the time for every one of us to take control of our DNA, and one man is uniquely qualified to show us how: Glenn McGee, bioethicist at the University of Pennsylvania, pioneer in the study of "home genetics," and the acknowledged wunderkind of the exciting world found at the nexus of life science and computer technology. One of the most respected authorities in the field of genomics -- the study of the genetic "software" inside plants, animals, and us -- McGee takes us on an eye-opening journey behind the headlines and into the heart of this formidable cutting-edge science. Probing the far-ranging ethical and legal implications of genomic research, McGee tackles its most controversial and hotly debated aspects -- from patenting your DNA to genetic engineering at the supermarket -- and explodes unnecessary fears about this wondrous new knowledge. We live in a brave new world. Beyond Genetics provides us with the knowledge we need to take the right steps forward into tomorrow ... and beyond.

Download or read book Beyond GWAS written by James Van Kampen and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As computational capacity and database size and complexity increase, genome wide association studies (GWAS) increase in power, allowing the identification of more potentially linked genome variants. While these methods are powerful on their own, they may be even more useful in the future in combination with other computational methods. Unfortunately, many of the identified variants are common and non-coding. It is possible that these variants are in linkage disequilibrium (LD) with rare variants. Modified computational methods that increase apparent sample size (meta-analysis), account for multiethnic backgrounds, or add in electronic health record or other phenotypic data, may provide further details as to the associations. Here, we report that integration of MRI GWAS data using TESLA to account for multiethnic sampling allows for the identification of novel significant genes in the context of smoking phenotypes, including age of initiation, smoking cessation, cigarettes per day, and smoking initiation. This technique allows us to identify genes that associate with the phenotype and with specific brain regions of interest. GWAS data-handling methods may also be useful in other areas, such as the use of pathway analysis to identify potential mechanisms of sensitivity and resistance to natural product derivatives with novel anticancer therapeutic profiles. For instance, pathway analysis of RNA sequencing data of cancer cells treated with schweinfurthin analogs revealed a differential expression of genes associated with the Sonic Hedgehog pathway in sensitive glioma (SF-295) and resistant lung (A549) cell lines. Although these computational methods are powerful, it is still important to validate findings via biological assays whenever possible. The identification of sonic hedgehog as a potentially important pathway was verified by inhibition of this pathway in the resistant cell line, second this was able to increase cell line sensitivity. Such findings suggest that co-treatment with Hedgehog pathway inhibitors may overcome cellular resistance to the iv anticancer effects of this class of natural compounds and derivatives, potentially increasing the usefulness of these compounds as future anticancer therapeutic agents. Similarly, many computational genomic studies have identified potential dysregulation of inflammation pathways and the hypothalamic-pituitary-adrenal (HPA) axis in bipolar disorder (BD), but biological assays were necessary to define the role of these potential alterations in the diurnal cortisol cycle, which regulates sleep and focus. Nighttime cortisol levels were significantly higher in BD patients, which may account for the well-documented sleep disturbances which patients commonly suffer. Such findings suggest that targeting cortisol patterns may be able to improve BD patient sleep and/or other outcomes. Clearly, computational genomic methods are a mainstay of modern research, but it is critical to continue to expand the area through the combination of data sets, new modeling methods, and biological validation. The present studies here investigate smoking phenotypes and common comorbid or risk diseases associated with smoking, bipolar disorder and cancer.

Download or read book Genes Behavior and the Social Environment written by Institute of Medicine and published by National Academies Press. This book was released on 2006-12-07 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, we have made great strides in reducing rates of disease and enhancing people's general health. Public health measures such as sanitation, improved hygiene, and vaccines; reduced hazards in the workplace; new drugs and clinical procedures; and, more recently, a growing understanding of the human genome have each played a role in extending the duration and raising the quality of human life. But research conducted over the past few decades shows us that this progress, much of which was based on investigating one causative factor at a time—often, through a single discipline or by a narrow range of practitioners—can only go so far. Genes, Behavior, and the Social Environment examines a number of well-described gene-environment interactions, reviews the state of the science in researching such interactions, and recommends priorities not only for research itself but also for its workforce, resource, and infrastructural needs.

Download or read book Beyond GWAS written by Daniel Schmitz and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book GWAS The Rise of Hypothesis Free Biomedical Science written by Igor Rudan and published by Academic Press. This book was released on 2016-08-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: GWAS: The Rise of Hypothesis-Free Biomedical Science: Could Genome-Wide Association Studies (GWAS) Transform Modern Medicine? focuses on the ideas that surround genome-wide association studies. Starting with the Human Genome Project in 2000, this book discusses how GWAS are finding the genes that underlie diseases by applying novel technologies and hypothesis-free science. Every new piece of information or technology has reshaped and changed the ideas addressed, leading to improved studies. In addition, the book also tracks down how results were generated and gathered, and the unique picture they are generating in our understanding of the genetic basis of human disease. The central theme of the book focuses on the development of ideas starting from The Human Genome Project in 2000, as they continually evolve in response to the results obtained through the application of GWAS on real data. While short, this book will guide readers through the turbulent and exciting history that has transformed biomedical science from the inside out.

Download or read book Beyond Summary Statistics written by Jie Yuan and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Using these methods we provide evidence of significant heterogeneity in GWAS cohorts for schizophrenia. Lastly, a major avenue of investigation beyond GWAS is identifying the genes through which associated SNPs mechanistically affect the presentation of phenotypes. We develop a method to improve estimation of expression quantitative trait loci by joint inference over gene expression reference data and GWAS data, incorporating insights from the liability threshold model. These methods will advance ongoing efforts to explain the complex etiology of genetic diseases as well as improve the accuracy of disease prediction models based on these insights.

Download or read book The Future of Genetics written by Russ Hodge and published by Infobase Publishing. This book was released on 2010 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Future of Genetics considers where research in genetics, molecular biology, and medicine is headed while trying to cleanly separate facts from fiction and ideologies. This new volume explores the last 150 years and how different strands of biological research have become interwoven to create a new kind of interdisciplinary science.

Download or read book Beyond Mendelian Inheritance GWAS Unveils the Complexities of Disease Genes written by Robirt and published by . This book was released on 2024-07-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Beyond the Human Genome written by and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Going Beyond GWAS written by David Felix Lamparter and published by . This book was released on 2017 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thèse. Biologie. Médecine. 2017

Download or read book Integrative Genomic Approaches to Understand Human Disease Mechanisms Applications to Cardiometabolic Traits written by Arthur Ko and published by . This book was released on 2018 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: With more efficient genotyping technologies and lower sequencing cost, genome-wide association studies (GWAS) have been broadly applied to many complex human traits. However, people of European descent remain the most prominent subjects in genetic research and other ethnic groups might not fully benefit from the effort of GWAS. In addition to expanding GWAS to include more diverse populations, new approaches that enable trans-ethnic or multi-ethnic analyses in GWAS will also be a crucial stepping stone for future genetic studies. To address this disparity and knowledge gap, we developed and applied a new approach, cross-population allele screen (CPAS) prior to GWAS, to identify population-specific variants that are associated with complex traits or diseases (Chapter 2). In our study, we identified novel genetic variants that are associated with serum triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and body mass index (BMI), exhibiting differential allele frequencies between Finns and Mexicans. Notably, one of the novel TGs-associated genes, SIK family kinase 3 (SIK3), harbors an Amerindian-specific common risk variant (allele frequency=18% in Mexicans), which is not observed in other continental populations, and the risk allele carriers also exhibit higher serum TG levels after a high-fat meal. In addition, this locus displays a signal of positive selection in Mexicans, suggesting that a delayed serum lipid clearance might have been evolutionally advantageous for ancient Amerindian people. While GWAS have uncovered many trait-associated loci, translating GWAS results to actionable medical information remains nontrivial due to the difficulty of pinpointing the true causal variants and genes. To understand the molecular mechanism of GWAS variants, many functional genomic approaches have been developed. In this dissertation, I will present two computational methods to integrate genetic and transcriptomic data to infer functional variants and possible underlying genes. First, we developed Functional Summary-based Imputation (FUSION) that can leverage GWAS summary statistics and a relatively small reference panel of transcriptomes to infer the association between gene expression and traits (Chapter 3). Using FUSION as well as subcutaneous adipose and whole blood RNA-sequence (RNA-seq) data, we performed transcript-wide associated studies (TWAS) and identified 69 novel genes associated with BMI, serum lipids, and height. With the constantly growing GWAS summary statistics and transcriptomic data, we can further utilize FUSION to apply TWAS to many different traits and tissues. To account for the increasing presence of large-scale RNA-seq cohorts, we created a new computational tool, ASElux, which can efficiently perform allele-specific expression (ASE) estimation that was previously prohibited due to excessive computing time (Chapter 4). We implemented a hybrid index system in ASElux to first build an individualized reference genome with available genotype data, and ASElux will then only align variant-carrying reads that are informative for ASE calculation. Thus, ASElux can correct for the reference allele bias during alignment with much shorter computing time. In our comparison test, ASElux is 4-33 times faster than other commonly used software or pipelines for ASE and obtain a similar or better accuracy. We applied ASElux to 273 lung RNA-seq samples, and uncovered a splice variant, rs11078928, which could explain the molecular mechanism of an asthma GWAS hit, rs11078927. We envision that the speed and efficiency of ASElux can facilitate ASE analysis in many RNA-seq datasets to uncover functional variants in the future. In Chapters 5 and 6, I will present our studies utilizing epigenomic and transcriptomic data to gain insight into the causal mechanisms of obesity and non-alcoholic fatty liver disease (NAFLD). To elucidate molecular mechanisms underlying obesity-related GWAS variants, we integrated promoter-enhancer interactions in human primary adipocytes with adipose cis expression quantitative trait locus (eQTL) variants (Chapter 5). Using promoter capture Hi-C, we first assayed chromosomal interactions in human primary adipocytes. In combination with human subcutaneous adipose transcriptomes, we then identified four genes associated with BMI or obesity-related traits that are also under cis regulation via chromosomal looping. We further performed electrophoretic mobility shift assays (EMSAs) to validate the allelic effect of a cis eQTL, rs4776984, regulating mitogen-activated protein kinase 5 (MAP2K5). The reference allele displayed a lower protein binding affinity than the alternative allele, in line with the computationally predicted disruptive effect. Finally, we also reported 38 additional BMI candidate genes under the regulation of chromosomal interactions for future studies of obesity. In our NAFLD study (Chapter 6), we tested the hypothesis that obesity may impair the function of adipose tissue, which can lead to ectopic fat accumulation in the liver, resulting in NAFLD. To understand the molecular pathogenesis of NAFLD driven by obesity, we examined the liver histology and subcutaneous adipose transcriptomes from 259 morbidly obese Finnish individuals that underwent a bariatric surgery. One year after the surgery, we re-profiled their adipose transcriptomes to assess the effect of the weight loss on adipose gene expression. At baseline, we identified adipose expression of 43 genes downregulated in non-alcoholic steatohepatitis (NASH) patients. Of these, the adipose expression of 17 genes was negatively correlated with liver steatosis and serum TGs. In a large panel of mouse strains, expression of five of the 17 genes was also correlated with a diet-induced liver steatosis. Specifically, the adipose expression of one of the five genes, death associated protein kinase 2 (DAPK2), recovered after the weight-loss at the one-year follow-up. Combining phenotype and longitudinal transcriptome data, we performed mediation analyses to demonstrate the causal effect of DAPK2 adipose expression on NAFLD. When DAPK2 expression was knocked down in human primary preadipocytes, five key genes involved in autophagy, of which two also function in adipocyte differentiation, were also downregulated. Our findings suggest an obesity-induced reduction of DAPK2 expression as a new pathogenic mechanism of NAFLD through impairment of autophagy pathway and adipocyte differentiation. In summary, our work presented in Chapters 5 and 6, employing functional genomic approaches and computational methods to decipher disease mechanisms of obesity and NAFLD, highlights strategies to understand the molecular pathogenesis of human disease beyond GWAS.

Download or read book Beyond the Low Hanging Fruit Leveraging Summary Data in Human Population and Statistical Genomics written by Michael Charles Turchin and published by . This book was released on 2017 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: A main goal of human genetics is to connect naturally occurring genotypic variation to naturally occurring phenotypic variation. Over the past three decades, human geneticists accomplished this through collecting cohorts of individuals and genotyping various kinds of DNA markers. Historically, human geneticists have been limited by the number of samples they could analyze, the breadth of genomic regions they could target at any one time, and the phenotypes available to them. However, these restrictions are now being rapidly mitigated -- advances in genotyping and sequencing technologies have made a vast majority of the genome accessible to researchers, and the increasing affordability of these technologies has made creating larger cohorts much more feasible. Additionally, a wide range of gene-regulatory phenotypes is now available to human geneticists, diversifying the questions researchers can pursue. As a result, the amount of data being produced now is unprecedented. But with this new wealth of information comes new challenges. The first waves of results from new technologies have been mixed, producing exciting, novel findings but also disappointment -- for many human traits there remains a large unexplained proportion of trait heritability. While some researchers have responded to this disappointment by collecting more samples and applying newer technologies, others have focused on how to make better use of the data we already have. In this dissertation, I present three projects that follow this latter theme, each attempting to use summary information from pre-existing data or first-stage analyses to better answer a research question. In Chapter 2 I present results from a study using pre-existing data (Exome Sequencing Project and 1000Genomes) to identify whether the deleterious mutational load in different between human populations. We show that despite the differing demographic histories of European-Americans and African-Americans these populations have similar mutational loads. We also show through simulations and theoretical predictions that this result is expected. In Chapter 3 I present the first stage results from a two-phase HIV candidate gene-exome sequencing study. In this study we sequenced the exomes of ~1,300 genes each with a priori experimental evidence of being functional related to HIV. Using ~750 individuals from the Multicenter Aids Cohort Study (MACS), we show an enrichment for marginal association signals among between candidate genes and HIV-Acquisition. We also show a proposed target list being used to conduct follow-up genotyping in the full MACS cohort; this list was heavily informed by summarizing the results from our first-stage analysis. Lastly, in Chapter 4 I present results from applying a Bayesian multivariate genome-wide association study method (bmass) on 13 different publicly available GWAS datasets. bmass runs on univariate GWAS summary statistics and identifies not only new significant variants but also the underlying multivariate patterns driving these results. We show that for many of the datasets analyzed we find additional variants, and we also display the multivariate patterns discovered for each dataset as well.

Download or read book Beyond GWAS written by Ken Yon Hui and published by . This book was released on 2014 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Genetic Dissection of Complex Traits written by D.C. Rao and published by Academic Press. This book was released on 2008-04-23 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of genetics is rapidly evolving and new medical breakthroughs are occuring as a result of advances in knowledge of genetics. This series continually publishes important reviews of the broadest interest to geneticists and their colleagues in affiliated disciplines. Five sections on the latest advances in complex traits Methods for testing with ethical, legal, and social implications Hot topics include discussions on systems biology approach to drug discovery; using comparative genomics for detecting human disease genes; computationally intensive challenges, and more