HRS Bibliography

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Journal Article

Sonnega A, Faul JD, Ofstedal MB, Langa KM, Phillips JWR, Weir DR. Cohort Profile: the Health and Retirement Study (HRS). International Journal of Epidemiology. 2014;43(2):576-585. doi:10.1093/ije/dyu067.PDF icon Download PDF (288.38 KB)
Langa KM, Larson EB, Crimmins EM, et al. A Comparison of the Prevalence of Dementia in the United States in 2000 and 2012. JAMA Internal Medicine. 2017;177(1):51-58. doi:10.1001/jamainternmed.2016.6807.
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.
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. Human Molecular Genetics. 2015;24(12):3582-94. doi:10.1093/hmg/ddv097.
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.
Faul JD, Mitchell CM, Zhao W. Estimating Telomere Length Heritability in an Unrelated Sample of Adults: Is Heritability of Telomere Length Modified by Life Course Socioeconomic Status?. Biodemography and Social Biology. 2016;62(1):73-86. doi:10.1080/19485565.2015.1120645.
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.
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.
Bihlmeyer NA, Brody JA, Smith AVernon, et al. Genetic diversity is a predictor of mortality in humans. BMC Genetics. 2014;15:159. doi:10.1186/s12863-014-0159-7.
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. Forthcoming. doi:10.1016/j.socscimed.2018.11.019.
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.
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. Nature Genetics. 2016;48(6):624-33. doi:10.1038/ng.3552.
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.
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. American Journal of Human Genetics. 2013;93(3):545-54. doi:10.1016/j.ajhg.2013.07.010.
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. Depression & Anxiety. 2016;33(4):265-80. doi:10.1002/da.22484.
Okbay A, Jonathan P. Beauchamp, Fontana MA, Chen G-B, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533(7604):539-42. doi:10.1038/nature17671.
Matteini AM, Tanaka T, Karasik D, et al. GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium. Aging Cell. 2016;15(5):792-800. doi:10.1111/acel.12468.
Rietveld CA, Medland SE, Derringer J, et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science. 2013;340(6139):1467-71. doi:10.1126/science.1235488.
Broer L, Aron S. Buchman, Deelen J, Smith JA, et al. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2015;70(1):110-8. doi:10.1093/gerona/glu166.
Ware EB, Schmitz LL, Faul JD, et al. Heterogeneity in polygenic scores for common human traits. bioRxiv. Forthcoming. doi:10.1101/106062.
Zhao W, Ware EB, He Z, Kardia SLR, Faul JD. Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting. International Journal of Environmental Research and Public Health. 2017;14(10):1153. doi:10.3390/ijerph14101153.
Day FR, Ruth KS, Thompson DJ, et al. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. Nat Genet. 2015;47(11):1294-303. doi:10.1038/ng.3412.
Heisler M, Faul JD, Hayward RA, Langa KM, Blaum CS, Weir DR. Mechanisms for Racial and Ethnic Disparities in Glycemic Control in Middle-aged and Older Americans in the Health and Retirement Study. Archives of Internal Medicine. 2007;167(17):1853-1860.
Fisher GG, Stachowski A, Infurna FJ, Faul JD, Grosch JW, Tetrick LE. Mental Work Demands, Retirement, and Longitudinal Trajectories of Cognitive Functioning. Journal of Occupational Health Psychology. 2014;19(2):231-242. doi:10.1037/a0035724.
Liu C, Kraja AT, Smith JA, Morrison A, et al. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. Nat Genet. 2016;48(10):1162-70. doi:10.1038/ng.3660.