Genome-Wide Genetic Analysis of Dropout in a Controlled Exercise Intervention in Sedentary Adults With Overweight or Obesity and Cardiometabolic Disease
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<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Despite the benefits of exercise, many individuals are unable or unwilling to adopt an exercise intervention.</jats:p> </jats:sec> <jats:sec> <jats:title>Purpose</jats:title> <jats:p>The purpose of this analysis was to identify putative genetic variants associated with dropout from exercise training interventions among individuals in the STRRIDE trials.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>We used a genome-wide association study approach to identify genetic variants in 603 participants initiating a supervised exercise intervention. Exercise intervention dropout occurred when a subject withdrew from further participation in the study or was otherwise lost to follow-up.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Exercise intervention dropout was associated with a cluster of single-nucleotide polymorphisms with the top candidate being rs722069 (T/C, risk allele = C) (unadjusted p = 2.2 × 10−7, odds ratio = 2.23) contained within a linkage disequilibrium block on chromosome 16. In Genotype-Tissue Expression, rs722069 is an expression quantitative trait locus of the EARS2, COG7, and DCTN5 genes in skeletal muscle tissue. In subsets of the STRRIDE genetic cohort with available muscle gene expression (n = 37) and metabolic data (n = 82), at baseline the C allele was associated with lesser muscle expression of EARS2 (p < .002) and COG7 (p = .074) as well as lesser muscle concentrations of C2- and C3-acylcarnitines (p = .026).</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Our observations imply that exercise intervention dropout is genetically moderated through alterations in gene expression and metabolic pathways in skeletal muscle. Individual genetic traits may allow the development of a biomarker-based approach for identifying individuals who may benefit from more intensive counseling and other interventions to optimize exercise intervention adoption.</jats:p> </jats:sec> <jats:sec> <jats:title>Clinical Trial information</jats:title> <jats:p>STRRIDE I = NCT00200993; STRRIDE AT/RT = NCT00275145; STRRIDE-PD = NCT00962962.</jats:p> </jats:sec>
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Jiang, Rong, Katherine A Collins, Kim M Huffman, Elizabeth R Hauser, Monica J Hubal, Johanna L Johnson, Redford B Williams, Ilene C Siegler, et al. (n.d.). Genome-Wide Genetic Analysis of Dropout in a Controlled Exercise Intervention in Sedentary Adults With Overweight or Obesity and Cardiometabolic Disease. Annals of Behavioral Medicine. 10.1093/abm/kaae011 Retrieved from https://hdl.handle.net/10161/30401.
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Scholars@Duke
Rong Jiang
Katherine Collins
Katherine A. Collins-Bennett, PhD, NBC-HWC, is a Medical Instructor in the Department of Population Health Sciences and affiliated with the Duke Molecular Physiology Institute at Duke University School of Medicine, and is a board-certified health and wellness coach. She studies barriers and predictors of health-promoting behavior change. The ultimate goal of her translational research is to design trials to optimize health-promoting behaviors for those at risk for "relapse" or ceased behavioral modification, in order to improve long-term health and well-being.
Kim Marie Huffman
Determining the role of physical activity in modulating health outcomes (cardiovascular disease risk) in persons with rheumatologic diseases (rheumatoid arthritis, gout, osteoarthritis)
Integrating clinical rheumatology, basic immunology, metabolism, and exercise science in order to reduce morbidity in individuals with arthritis
Evaluating relationships between circulating and intra-muscular metabolic intermediates and insulin resistance in sedentary as well as individuals engaging in regular exercise
Addressing the role of physical activity in modulating inflammation, metabolism, and functional health in aging populations
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
Redford B. Williams
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.
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