HRS Bibliography

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2018

Papageorge N, Thom K. Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study. Cambridge, MA: National Bureau of Economic Research; 2018. doi:10.3386/w25114.
Hupfeld KE, Vaillancourt DE, Seidler RD. Genetic markers of dopaminergic transmission predict performance for older males but not females. Neurobiology of Aging. 2018;66(180):.e11-180.e21. doi:10.1016/j.neurobiolaging.2018.02.005.
http://www.ncbi.nlm.nih.gov/pubmed/29525179?dopt=Abstract
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
Yashin AI, 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
Yashin AI, Fang F, Kovtun M, et al. Hidden heterogeneity in Alzheimer's disease: Insights from genetic association studies and other analyses. Experimental Gerontology. 2018;107:148-160. doi:10.1016/j.exger.2017.10.020.
Wu Y, Zeng J, Zhang F, et al. Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-03371-0.
Van Dam A. It’s better to be born rich than gifted. The Washington Post. https://www.washingtonpost.com/business/2018/10/09/its-better-be-born-rich-than-talented/?noredirect=on&utm_term=.e6c0cc49f545. Published 2018.
Yengo L, Sidorenko J, Kemper KE, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Human Molecular Genetics. 2018;27(20):3641-3649. doi:10.1093/hmg/ddy271.
Yengo L, Sidorenko J, Kemper KE, et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Human Molecular Genetics. 2018;27(20):3641-3649. doi:10.1093/hmg/ddy271.
http://www.ncbi.nlm.nih.gov/pubmed/30124842?dopt=Abstract
Qiao Z, Powell J. MHC-Dependent Mate Selection within 872 Spousal Pairs of European Ancestry from the Health and Retirement Study. Genes. 2018;9(2):53. doi:10.3390/genes9010053.
Primes G, Fieder M. Real-life helping behaviours in North America: A genome-wide association approach. PLoS One. 2018;13(1):e0190950. doi:10.1371/journal.pone.0190950.
http://www.ncbi.nlm.nih.gov/pubmed/29324852?dopt=Abstract
Wolf DA, Middleton FA. A role for genes in the ‘caregiver stress process’?. Translational Psychiatry. 2018;8(1). doi:10.1038/s41398-018-0275-7.
Liu H. Social and Genetic Pathways in Multigenerational Transmission of Educational Attainment. American Sociological Review. 2018;83(2):278-304. doi:10.1177/0003122418759651.
Mills MC, Barban N, Tropf FC. The Sociogenomics of Polygenic Scores of Reproductive Behavior and Their Relationship to Other Fertility Traits. RSF: The Russell Sage Foundation Journal of the Social Sciences. 2018;4(4):122-136. doi:10.7758/rsf.2018.4.4.07.

2017

Mez J, Marden JR, Mukherjee S, et al. Alzheimer's disease genetic risk variants beyond APOE ε4 predict mortality. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring. 2017;8:188-195. doi:10.1016/j.dadm.2017.07.002.
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
Levine ME, Crimmins EM, Weir DR, Cole SW. Contemporaneous Social Environment and the Architecture of Late-Life Gene Expression Profiles. American Journal of Epidemiology. 2017;186(5):503-509. doi:10.1093/aje/kwx147.
http://www.ncbi.nlm.nih.gov/pubmed/28911009?dopt=Abstract
Rehkopf DH, Rosero-Bixby L, Dow WH. A cross-national comparison of 12 biomarkers finds no universal biomarkers of aging among individuals aged 60 and older. Lutz W, ed. Vienna Yearbook of Population Research. 2017;1:255-277. doi:10.1553/populationyearbook10.1553/populationyearbook201610.1553/populationyearbook2016s255.
Schmitz LL, Dalton C. Conley. The Effect of Vietnam-Era Conscription and Genetic Potential for Educational Attainment on Schooling Outcomes. Economics of Education Review. 2017;61:85-97. doi:10.1016/j.econedurev.2017.10.001.
http://www.ncbi.nlm.nih.gov/pubmed/29375175?dopt=Abstract
Boyle EA, Li YI, Pritchard JK. An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell. 2017;169(7):1177-1186. doi:10.1016/j.cell.2017.05.038.
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
Lu AT, Hannon E, Levine ME, et al. Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. Nature Communications. 2017;8. doi:10.1038/ncomms15353.
Domingue BW, Liu H, Okbay A, Belsky DW. Genetic Heterogeneity in Depressive Symptoms Following the Death of a Spouse: Polygenic Score Analysis of the U.S. Health and Retirement Study. American Journal of Psychiatry. 2017;174(10):963-970. doi:10.1176/appi.ajp.2017.16111209.
Wehby GL, Domingue BW, Ullrich F, 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)
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