Interactions between social/ behavioral factors and ADRB2 genotypes may be associated with health at advanced ages in China.
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BACKGROUND: Existing literature indicates that ADRB2 gene is associated with health and longevity, but none of previous studies investigated associations of carrying the ADRB2 minor alleles and interactions between ADRB2 genotypes and social/behavioral factors(GxE) with health outcomes at advanced ages. This study intends to fill in this research gap. METHOD: We conducted an exploratory analysis, using longitudinal survey phenotype/genotype data from 877 oldest-old aged 90+. To estimate association of GxE interactions with health outcome, adjusted for the potential correlation between genotypes and social/behavioral factors and various other potentially confounding factors, we develop and test an innovative three-step procedure which combines logistic regression and structural equation methods. RESULTS: Interaction between regular exercise and carrying rs1042718 minor allele is significantly and positively associated with good cognitive function; interaction between regular exercise and carrying rs1042718 or rs1042719 minor allele is significantly and positively associated with self-reported good health; and interaction between social-leisure activities and carrying rs1042719 minor allele is significantly and positively associated with self-reported good health. Carrying rs1042718 or rs1042719 minor alleles is significantly and negatively associated with negative emotion, but the ADRB2 SNPs are not significantly associated with cognitive function and self-reported health. Our structural equation analysis found that, adjusted for the confounding effects of correlation of the ADRB2 SNPs with negative emotion, interaction between negative emotion and carrying rs1042718 or rs1042719 minor allele is significantly and negatively associated with cognitive function. The positive association of regular exercise and social-leisure activities with cognitive function and self-reported health, and negative association of negative emotion with cognitive function, were much stronger among carriers of rs1042718 or rs1042719 alleles, compared to the non-carriers. CONCLUSIONS: The results indicate significant positive associations of interactions between social/behavioral factors and the ADRB2 genotypes with health outcomes of cognitive function and self-reported health, and negative associations of carrying rs1042718 or rs1042719 minor alleles with negative emotion, at advanced ages in China. Our findings are exploratory rather than causal conclusions. This study implies that near-future health promotion programs considering individuals' genetic profiles, with appropriate protection of privacy/confidentiality, would yield increased benefits and reduced costs to the programs and their participants.
Published Version (Please cite this version)
Zeng, Yi, Lingguo Cheng, Ling Zhao, Qihua Tan, Qiushi Feng, Huashuai Chen, Ke Shen, Jianxin Li, et al. (2013). Interactions between social/ behavioral factors and ADRB2 genotypes may be associated with health at advanced ages in China. BMC Geriatr, 13. p. 91. 10.1186/1471-2318-13-91 Retrieved from https://hdl.handle.net/10161/15374.
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(1) Socioeconomic, behavior, environmental and genetic determinants of healthy aging and healthy longevity;
(2) Factors related to elderly disability and mental health;
(3) Methods of family households and elderly living arrangements forecasting/analysis and their applications in health services and socioeconomic planning, and market studies;
(4) Policy analysis in population aging, social welfare, retirement, and fertility transitions.
Dr. Gregory is a tenured Professor and Director of the Brain Tumor Omics Program (BTOP) in the Duke Department of Neurosurgery, the Vice Chair of Research in the Department of Neurology, and Director of the Molecular Genomics Core at the Duke Molecular Physiology Institute.
As a neurogenomicist, Dr. Gregory applies the experience gained from leading the sequencing of chromosome 1 for the Human Genome Project to elucidating the mechanisms underlying multi-factorial diseases using genetic, genomic, and epigenetic approaches. Dr. Gregory’s primary areas of research involve understanding the molecular processes associated with disease development and progression in brain tumors and Alzheimer’s disease, novel drug induced white matter injury repair in multiple sclerosis, and social and behavioral response to oxytocin treatment animal models of autism.
He is broadly regarded across Duke as a leader in the development of novel single cell and spatial molecular technologies towards understanding the pathogenic mechanisms of disease development. Dr. Gregory is also the Section Chair of Genomics and Epigenetics at the DMPI and Director of the Duke Center of Autoimmunity and MS in the Department of Neurology.
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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