HRS Bibliography

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Levine ME, Crimmins EM. A Genetic Network Associated With Stress Resistance, Longevity, and Cancer in Humans. J Gerontol A Biol Sci Med Sci. 2016;71(6):703-12. doi:10.1093/gerona/glv141.
http://www.ncbi.nlm.nih.gov/pubmed/26355015?dopt=Abstract
Wehby GL, Domingue BW, Ullrich FA, Wolinsky FD. Genetic Predisposition to Obesity and Medicare Expenditures. The Journals of Gerontology: Series A. 2017;73:66-72. doi:10.1093/gerona/glx062.PDF icon glx062.pdf (148.77 KB)
Slob E, Rietveld CA. Genetic predispositions moderate the effectiveness of tobacco excise taxes. PLoS One. 2021;16(11):e0259210. doi:10.1371/journal.pone.0259210.
Arpawong TEm, Huh J. GENETIC RISK FOR ADHD ON LATER LIFE EMOTIONAL AND COGNITIVE HEALTH: TESTING MECHANISMS OF EFFECT. Innovation in Aging. 2022;6(Suppl 1):431. doi:10.1093/geroni/igac059.1691.
Linnér RKarlsson, Koellinger PD. Genetic risk scores in life insurance underwriting. Journal of Health Economics. 2022;81:102556. doi:https://doi.org/10.1016/j.jhealeco.2021.102556.
Wehby GL, Domingue BW, Wolinsky FD. Genetic risks for chronic conditions: Implications for long-term wellbeing. Journals of Gerontology, Series A: Biological Sciences & Medical Sciences. 2018;73(4):477-483. doi:10.1093/gerona/glx154.
http://www.ncbi.nlm.nih.gov/pubmed/28958056?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
Zhang C, Pierce BL. Genetic susceptibility to accelerated cognitive decline in the US Health and Retirement Study. Neurobiol Aging. 2014;35(6):1512.e11-8. doi:10.1016/j.neurobiolaging.2013.12.021.
http://www.ncbi.nlm.nih.gov/pubmed/24468470?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
Lu AT, Hannon E, Levine ME, et al. Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum. Nat Commun. 2016;7:10561. doi:10.1038/ncomms10561.
http://www.ncbi.nlm.nih.gov/pubmed/26830004?dopt=Abstract
Arpawong TE, Pendleton N, Mekli K, et al. Genetic variants specific to aging-related verbal memory: Insights from GWASs in a population-based cohort. PLoS One. 2017;12(8):e0182448. doi:10.1371/journal.pone.0182448.
http://www.ncbi.nlm.nih.gov/pubmed/28800603?dopt=Abstract
Ward ME, McMahon G, St Pourcain B, et al. Genetic variation associated with differential educational attainment in adults has anticipated associations with school performance in children. Li Y, ed. PLoS One. 2014;9(7):e100248. doi:10.1371/journal.pone.0100248.
http://www.ncbi.nlm.nih.gov/pubmed/25032841?dopt=Abstract
Villa O, Stuhr NL, Yen C-A, Crimmins EM, Arpawong TEm, Curran SP. Genetic variation in ALDH4A1 is associated with muscle health over the lifespan and across species. Elife. 2022;11:e74308. doi:10.7554/eLife.74308.
Villa O, Stuhr NL, Yen C-A, Crimmins EM, Arpawong TE, Curran SP. Genetic variation in ALDH4A1 predicts muscle health over the lifespan and across species. Elife. 2022;11(e74308). doi:10.7554/eLife.74308.
Liu SY, Walter S, Marden JR, et al. Genetic vulnerability to diabetes and obesity: does education offset the risk?. Soc Sci Med. 2015;127:150-8. doi:10.1016/j.socscimed.2014.09.009.
http://www.ncbi.nlm.nih.gov/pubmed/25245452?dopt=Abstract
Ojalehto E, Zhan Y, Jylhava J, Reynolds C, Aslan AKDahl, Karlsson I. Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study. The Lancet. Forthcoming. doi:10.1016/j.eclinm.2023.101943.
Mukherjee S, Walter S, Kauwe JSK, et al. Genetically predicted body mass index and Alzheimer's disease-related phenotypes in three large samples: Mendelian randomization analyses. Alzheimers Dement. 2015;11(12):1439-1451. doi:10.1016/j.jalz.2015.05.015.
http://www.ncbi.nlm.nih.gov/pubmed/26079416?dopt=Abstract
Das A. Genetically-predicted trait-BMI, everyday discrimination and life satisfaction among older U.S. adults. Adaptive Human Behavior and Physiology. 2022;8:179–201. doi:10.1007/s40750-022-00189-5.
Barakatt M. Genetics and geography in admixed populations. School of Computer Science. 2016;Master of Science.
Belsky DW, Moffitt TE, Caspi A. Genetics in population health science: strategies and opportunities. Am J Public Health. 2013;103 Suppl 1:S73-83. doi:10.2105/AJPH.2012.301139.
http://www.ncbi.nlm.nih.gov/pubmed/23927511?dopt=Abstract
Yashin A, Arbeev KG, Wu D, et al. Genetics of human longevity from incomplete data: New findings from the long life family study. Journals of Gerontology, Series A: Biological Sciences & Medical Sciences. 2018;73(11):1472-1481. doi:10.1093/gerona/gly057.
http://www.ncbi.nlm.nih.gov/pubmed/30299504?dopt=Abstract
Thompson MD, Pirkle CM, Youkhana F, Wu YYan. Gene–obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study. International Journal of Obesity. 2020. doi:10.1038/s41366-020-0589-4.
Singer B. Genome-Phenome Linkages in Human Population Surveys, with Special Emphasis on the Health and Retirement Survey. Forum for Health Economics and Policy. 2011;14(3):6-6. doi:10.2202/1558-9544.1261.
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
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