Gene by stress genome-wide interaction analysis and path analysis identify EBF1 as a cardiovascular and metabolic risk gene.

Abstract

We performed gene-environment interaction genome-wide association analysis (G × E GWAS) to identify SNPs whose effects on metabolic traits are modified by chronic psychosocial stress in the Multi-Ethnic Study of Atherosclerosis (MESA). In Whites, the G × E GWAS for hip circumference identified five SNPs within the Early B-cell Factor 1 (EBF1) gene, all of which were in strong linkage disequilibrium. The gene-by-stress interaction (SNP × STRESS) term P-values were genome-wide significant (Ps = 7.14E-09 to 2.33E-08, uncorrected; Ps = 1.99E-07 to 5.18E-07, corrected for genomic control). The SNP-only (without interaction) model P-values (Ps = 0.011-0.022) were not significant at the conventional genome-wide significance level. Further analysis of related phenotypes identified gene-by-stress interaction effects for waist circumference, body mass index (BMI), fasting glucose, type II diabetes status, and common carotid intimal-medial thickness (CCIMT), supporting a proposed model of gene-by-stress interaction that connects cardiovascular disease (CVD) risk factor endophenotypes such as central obesity and increased blood glucose or diabetes to CVD itself. Structural equation path analysis suggested that the path from chronic psychosocial stress to CCIMT via hip circumference and fasting glucose was larger (estimate = 0.26, P = 0.033, 95% CI = 0.02-0.49) in the EBF1 rs4704963 CT/CC genotypes group than the same path in the TT group (estimate = 0.004, P = 0.34, 95% CI = -0.004-0.012). We replicated the association of the EBF1 SNPs and hip circumference in the Framingham Offspring Cohort (gene-by-stress term P-values = 0.007-0.012) as well as identified similar path relationships. This observed and replicated interaction between psychosocial stress and variation in the EBF1 gene may provide a biological hypothesis for the complex relationship between psychosocial stress, central obesity, diabetes, and cardiovascular disease.

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Citation

Published Version (Please cite this version)

10.1038/ejhg.2014.189

Publication Info

Singh, Abanish, Michael A Babyak, Daniel K Nolan, Beverly H Brummett, Rong Jiang, Ilene C Siegler, William E Kraus, Svati H Shah, et al. (2015). Gene by stress genome-wide interaction analysis and path analysis identify EBF1 as a cardiovascular and metabolic risk gene. European journal of human genetics : EJHG, 23(6). pp. 854–862. 10.1038/ejhg.2014.189 Retrieved from https://hdl.handle.net/10161/30354.

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Scholars@Duke

Singh

Abanish Singh

Assistant Professor in Psychiatry and Behavioral Sciences

With a unique skill set resulting from outstanding training, my sole aim was to help improve human health through cutting-edge translational research. Specifically, I have been interested in illuminating the mechanisms responsible for the causes and progression of the leading public health conditions, which may help with the development and enhancement of precision medicine.  As part of this endeavor, I also became interested in studying the measurement of biobehavioral risk factors and environmental stressors and their interactions with genes that may influence cardiovascular disease (CVD) risk factors and endophenotypes, adversely affecting the CVD pathways.

I joined medical research with my early research training on computational biology, high-throughput genomics, next-gen DNA sequencing, genome-wide studies, and big data analytics, which resulted in some of prominent findings on human genome (PMID: 18048317, PMID: 20223737, PMID: 20598109, PMID: 21703177). These findings included a significant contribution to the scientific community’s understanding that I made during my postdoctoral fellowship with Dr. David Goldstein at Duke Center for Human Genome Variation that how well RNA-Seq can identify human coding variants just using a small fraction of genome (transcriptome) as compared to whole genome (PMID: 20598109). This work was important not only scientifically, but also in pragmatic terms, given the high cost of sequencing.

In relatively recent work I discovered a novel CVD risk gene EBF1, where  a common genetic variant contributed to inter-individual differences in human central obesity, fasting blood glucose, diabetes, and CVD risk factors in the presence of chronic psychosocial stress (PMID: 25271088). This work demonstrated the genetic variant-specific significant path from chronic psychosocial stress to common carotid intimal–media thickness (CCIMT), a surrogate marker for atherosclerosis, via central obesity and fasting glucose. I also developed an algorithm to create a synthetic measure of stress using the proxy indicators of its components (PMID: 26202568).  Other more recent work has elucidated the race, sex, and age related differences in the EBF1 gene-by-stress interaction (PMID: 33077726), which suggests the need for careful evaluation of environmental measures in different ethnicities in cross-ethnic gene-by-stress interaction studies.

More recently, I have expanded my research interest in studying the genetic architecture of Alzheimer’s disease (AD) and the role of psychosocial stress in modifying the effect of genetic variants on the disease risks.

Babyak

Michael Alan Babyak

Professor Emeritus in Psychiatry and Behavioral Sciences

Since coming to Duke as an intern in 1994 I have collaborated as a biostatistician and co-investigator at Duke on numerous observational and experimental studies involving behavior, psychosocial factors, health, and disease. The substantive topics have ranged across questions concerning exercise and depression, hypertension, weight loss, the genetics of stress and heart disease, sickle cell disease, to name a few. I am particularly interested in the issue of improving reproducibility and transparency in data analysis.

Brummett

Beverly H. Brummett

Associate Professor Emeritus in Psychiatry and Behavioral Sciences

In the early part of my career, my work generally focused on examining psychosocial determinants or correlates (e.g., emotion, personality, and socioeconomic status) of cardiovascular disease.  However, in the past several years, my work has also expanded to include examining how stressful emotional responses, combined with proposed genetic markers, influence metabolic functioning, cognitive decline, functional capacity and quality of live in the elderly, depressive symptomology, and major depressive disorder.  I also have an interest in statistical methodology. 

Jiang

Rong Jiang

Assistant Professor in Head and Neck Surgery & Communication Sciences
Siegler

Ilene C. Siegler

Professor in Psychiatry and Behavioral Sciences

My research efforts are in the area of developmental health psychology and organized around understanding the role of personality in health and disease in middle and later life.

My primary research activity is as Principal Investigator of the UNC Alumni Heart Study (UNCAHS) a prospective epidemiologic study of 5000 middle aged men and women and 1200 of their spouses that evaluates the role of personality on coronary heart disease and coronary heart disease risk, cancer, and normal aging.

As head of Cancer Prevention Research Unit , I study the role of psychological factors related to mammography behavior and estrogen replacement therapy is being studied in UNCAHS women.








REPRESENTATIVE PUBLICATIONS

Siegler, I.C., Zonderman, A.B., Barefoot, J.C., Williams, R.B., Jr., Costa, P.T., Jr., & McCrae, R. R. (1990). Predicting personality from college MMPI scores: Implications for follow-up studies in psychosomatic medicine. Psychosomatic Medicine, 52, 644-652.

Siegler, I.C., Peterson, B.L., Barefoot, J.C., & Williams, R.B. (1992). Hostility during late adolescence predicts coronary risk factors at midlife. American Journal of Epidemiology, 138(2), 146-154.

Siegler, I.C., Peterson, B.L., Barefoot, J.C., Harvin, S.H. Dahlstrom, W.G., Kaplan, B.H., Costa, P.T. Jr., & Williams, R.B. (1992). Using college alumni populations in epidemiologic research: The UNC Alumni Heart Study. Journal of Clinical Epidemiology, 45(11), 1243-1250.

Siegler, I.C., Dawson, D.V., & Welsh, K.A. (1994). Caregiver ratings of personality change in Alzheimer's disease patients: A replication. Psychology and Aging, 9, 464-466.

Siegler, I.C., Feaganes, J.R., & Rimer, B.K. (1995). Predictors of adoption of mammography in women under age 50. Health Psychology, 14, 274-278.



1/13/99

Shah

Svati Hasmukh Shah

Ursula Geller Distinguished Professor of Research in Cardiovascular Diseases
Williams

Redford B. Williams

Professor Emeritus of Psychiatry and Behavioral Sciences

My research aims to identify psychosocial factors that are involved in the pathogenesis and course of major medical disorders, to characterize the biobehavioral mechanisms whereby such factors influence disease, and to develop both behavioral and pharmacologic means of preventing or ameliorating the adverse impact of psychosocial factors on health and disease. Specific projects that are currently active include: 1) The influence of hostile personality, social isolation, depression and other psychosocial risk factors upon the development and course of cardiometabolic disease; 2) Biological and genetic mechanisms whereby psychosocial risk factors influence disease development and course; and 3) Behavioral and pharmacologic approaches to ameliorate impact of psychosocial risk factors on disease risk and course.

Hauser

Elizabeth Rebecca Hauser

Professor of Biostatistics & Bioinformatics

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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