HRS Bibliography

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G

Dunn EC, Wiste A, Radmanesh F, et al. GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN. Depress Anxiety. 2016;33(4):265-80. doi:10.1002/da.22484.
http://www.ncbi.nlm.nih.gov/pubmed/27038408?dopt=Abstract
Franceschini N, Fox E, Zhang Z, et al. Genome-wide association analysis of blood-pressure traits in African-ancestry individuals reveals common associated genes in African and non-African populations. Am J Hum Genet. 2013;93(3):545-54. doi:10.1016/j.ajhg.2013.07.010.
http://www.ncbi.nlm.nih.gov/pubmed/23972371?dopt=Abstract
Barban N, Jansen R, de Vlaming R, et al. Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nat Genet. 2016;48(12):1462-1472. doi:10.1038/ng.3698.
http://www.ncbi.nlm.nih.gov/pubmed/27798627?dopt=Abstract
Okbay A, Baselmans BML, De Neve J-E, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48(6):624-33. doi:10.1038/ng.3552.
http://www.ncbi.nlm.nih.gov/pubmed/27089181?dopt=Abstract
Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197-206. doi:10.1038/nature14177.
http://www.ncbi.nlm.nih.gov/pubmed/25673413?dopt=Abstract
Smith JA, Kho M, Zhao W, Yu M, Mitchell CM, Faul JD. Genetic effects and gene-by-education interactions on episodic memory performance and decline in an aging population. Social Science & Medicine. 2018. doi:10.1016/j.socscimed.2018.11.019.
http://www.ncbi.nlm.nih.gov/pubmed/30449520?dopt=Abstract
Bihlmeyer NA, Brody JA, Smith AVernon, et al. Genetic diversity is a predictor of mortality in humans. BMC Genet. 2014;15:159. doi:10.1186/s12863-014-0159-7.
http://www.ncbi.nlm.nih.gov/pubmed/25543667?dopt=Abstract
Pattaro C, Teumer A, Gorski M, et al. Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function. Nat Commun. 2016;7:10023. doi:10.1038/ncomms10023.
http://www.ncbi.nlm.nih.gov/pubmed/26831199?dopt=Abstract
Zhao W, Yasutake K, August C, et al. Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies. Int J Environ Res Public Health. 2017;14(12). doi:10.3390/ijerph14121596.
http://www.ncbi.nlm.nih.gov/pubmed/29258278?dopt=Abstract

D

Crimmins EM, Zhang YS, Kim JKi, et al. Dried blood spots: Effects of less than optimal collection, shipping time, heat, and humidity. American Journal of Human Biology. 2020;n/a:e23390. doi:10.1002/ajhb.23390.
Fisher GG, Faul JD, Weir DR, Wallace RB. Documentation of Chronic Disease Measures in the Health and Retirement Study. Ann Arbor, Michigan: Institute for Social Research, University of Michigan; 2005.PDF icon Download PDF (460.3 KB)
Crimmins EM, Faul JD, Kim JKi, Weir DR. Documentation of Blood-Based Biomarkers in the 2014 Health and Retirement Study. Ann Arbor, MI: Survey Research Center, Institute for Social Research, University of Michigan; 2017.PDF icon Download PDF (247.04 KB)
Crimmins EM, Faul JD, Kim JKi, Weir DR. Documentation of Biomarkers in the 2010 and 2012 Health and Retirement Study. Ann Arbor, Michigan: Survey Research Center, University of Michigan; 2015:15.PDF icon Download PDF (198.27 KB)
Crimmins EM, Faul JD, Kim JKi, et al. Documentation of Biomarkers in the 2006 and 2008 Health and Retirement Study. Ann Arbor, Michigan: Institute for Social Research, University of Michigan; 2013.PDF icon Download PDF (364.89 KB)
Joshi PK, Esko T, Mattsson H, et al. Directional dominance on stature and cognition in diverse human populations. Nature. 2015;523(7561):459-62. doi:10.1038/nature14618.
http://www.ncbi.nlm.nih.gov/pubmed/26131930?dopt=Abstract

C

Nead KT, Li A, Wehner MR, et al. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Hum Mol Genet. 2015;24(12):3582-94. doi:10.1093/hmg/ddv097.
http://www.ncbi.nlm.nih.gov/pubmed/25784503?dopt=Abstract
Ben-Avraham D, Karasik D, Verghese J, et al. The complex genetics of gait speed: genome-wide meta-analysis approach. Aging (Albany NY). 2017;9(1):209-246. doi:10.18632/aging.101151.
http://www.ncbi.nlm.nih.gov/pubmed/28077804?dopt=Abstract
Langa KM, Larson EB, Crimmins EM, et al. A Comparison of the Prevalence of Dementia in the United States in 2000 and 2012. JAMA Intern Med. 2017;177(1):51-58. doi:10.1001/jamainternmed.2016.6807.
http://www.ncbi.nlm.nih.gov/pubmed/27893041?dopt=Abstract
Vivek S, Thyagarajan B, Nelson H, Prizment A, Crimmins EM, Faul JD. COMBINED EFFECT OF CMV SEROPOSITIVITY AND SYSTEMIC INFLAMMATION ON DEMENTIA PREVALENCE IN CANCER SURVIVORS. Innovation in Aging. 2019;3:S461-S461. doi:10.1093/geroni/igz038.1724.
Sonnega A, Faul JD, Ofstedal MBeth, Langa KM, Phillips JWR, Weir DR. Cohort Profile: the Health and Retirement Study (HRS). Int J Epidemiol. 2014;43(2):576-85. doi:10.1093/ije/dyu067.
http://www.ncbi.nlm.nih.gov/pubmed/24671021?dopt=Abstract
PDF icon Download PDF (288.38 KB)

B

McGrath RP, Snih SAl, Markides KS, et al. The burden of health conditions across race and ethnicity for aging Americans: Disability-adjusted life years. Medicine (Baltimore). 2019;98(46). doi:10.1097/MD.0000000000017964.
http://www.ncbi.nlm.nih.gov/pubmed/31725658?dopt=Abstract