Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci.
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2021-04-30
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Abstract
Background
DNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach.Methods
The study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses.Results
We identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development.Conclusions
We uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.Type
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Breeze, Charles E, Anna Batorsky, Mi Kyeong Lee, Mindy D Szeto, Xiaoguang Xu, Daniel L McCartney, Rong Jiang, Amit Patki, et al. (2021). Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci. Genome medicine, 13(1). p. 74. 10.1186/s13073-021-00877-z Retrieved from https://hdl.handle.net/10161/23248.
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Scholars@Duke
Rong Jiang
Yongmei Liu
Dr. Yongmei Liu is a genetic epidemiologist with appointments in Cardiology/Medicine and Neurology. Her primary interests are to better understand the molecular mechanisms of aging-related inflammatory diseases including diabetes, atherosclerosis, and Alzheimer’s disease by studying genome, the interplay of genetic and environmental factors, and epigenomic and transcriptomic profiles. The combination of an unbiased genome-wide search in large sample sizes of disease relevant tissues/cells with longitudinal and randomized clinical trial designs, followed up by in vitro and in vivo experiments, is providing novel biomarkers for risk prediction and new insights into mechanisms that are involved in inflammatory diseases.
William Erle Kraus
My training, expertise and research interests range from human integrative physiology and genetics to animal exercise models to cell culture models of skeletal muscle adaptation to mechanical stretch. I am trained clinically as an internist and preventive cardiologist, with particular expertise in preventive cardiology and cardiac rehabilitation. My research training spans molecular biology and cell culture, molecular genetics, and integrative human exercise physiology and metabolism. I practice as a preventive cardiologist with a focus on cardiometabolic risk and exercise physiology for older athletes. My research space has both a basic wet laboratory component and a human integrative physiology one.
One focus of our work is an integrative physiologic examination of exercise effects in human subjects in clinical studies of exercise training in normal individuals, in individuals at risk of disease (such as pre-diabetes and metabolic syndrome; STRRIDE), and in individuals with disease (such as coronary heart disease, congestive heart failure and cancer).
A second focus of my research group is exploration of genetic determinates of disease risk in human subjects. We conduct studies of early onset cardiovascular disease (GENECARD; CATHGEN), congestive heart failure (HF-ACTION), peripheral arterial disease (AMNESTI), and metabolic syndrome. We are exploring analytic models of predicting disease risk using established and innovative statistical methodology.
A third focus of my group’s work is to understand the cellular signaling mechanisms underlying the normal adaptive responses of skeletal muscle to physiologic stimuli, such as occur in exercise conditioning, and to understand the abnormal maladaptive responses that occur in response to pathophysiologic stimuli, such as occur in congestive heart failure, aging and prolonged exposure to microgravity.
Recently we have begun to investigate interactions of genes and lifestyle interventions on cardiometabolic outcomes. We have experience with clinical lifestyle intervention studies, particularly the contributions of genetic variants to interventions responses. We call this Lifestyle Medicopharmacogenetics.
KEY WORDS:
exercise, skeletal muscle, energy metabolism, cell signaling, gene expression, cell stretch, heart failure, aging, spaceflight, human genetics, early onset cardiovascular disease, lifestyle medicine
Svati Hasmukh Shah
Elizabeth Rebecca Hauser
The incorporation of personalized medicine to all areas of human health represents a turning point for human genetics studies, a point at which the discoveries made have real implications for clinical medicine. It is important for students to gain experience in how human genetics studies are conducted and how results of those studies may be used. As a statistical geneticist and biostatistician my research interests are focused on developing and applying statistical methods to search for genes causing common human diseases. My research programs combine development and application of statistical methods for genetic studies, with a particular emphasis on understanding the joint effects of genes and environment.
These studies I work on cover diverse areas in biomedicine but are always collaborative, with the goal of bringing robust data science and statistical methods to the project. Collaborative studies include genetic and ‘omics studies of cardiovascular disease, health effects of air pollution, genetic analysis of adherence to an exercise program, genetic analysis in evaluating colon cancer risk, genetic analysis of suicide, and systems biology analysis of Gulf War Illness.
Keywords: human genetics, genetic association, gene mapping, genetic epidemiology, statistical genetics, biostatistics, cardiovascular disease, computational biology, diabetes, aging, colon cancer, colon polyps, kidney disease, Gulf War Illness, exercise behavior, suicide
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