HRS Bibliography

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West BT, Little RJA, Andridge RR, et al. Assessing selection bias in regression coefficients estimated from nonprobability samples with applications to genetics and demographic surveys. The Annals of Applied Statistics. 2021;15(3):1556-1581. doi:https://doi.org/10.1214/21-AOAS1453.
Weiss J, Puterman E, Prather AA, Ware EB, Rehkopf D. A data-driven prospective study of dementia among older adults in the United States. PLoS One. 2020;15(10). doi:10.1371/journal.pone.0239994.
Weiss J, Puterman E, Prather AA, Ware EB, Rehkopf D. A data-driven prospective study of incident dementia among older adults in the United States. Ithaca, NY: Cornell University; 2020.
Ware EB, Morataya C, Fu M, Bakulski KM. Type 2 Diabetes and Cognitive Status in the Health and Retirement Study: A Mendelian Randomization Approach. Frontiers in Genetics. 2021;12:634767. doi:10.3389/fgene.2021.634767.
Ware EB, Mukherjee B, Sun YV, Diez-Roux AV, Kardia SLR. Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the Multi-Ethnic Study of Atherosclerosis. BMC Genet. 2015;16:118. doi:10.1186/s12863-015-0274-0.
http://www.ncbi.nlm.nih.gov/pubmed/26459564?dopt=Abstract
Ware EB, Schmitz LL, Faul J. HRS Polygenic Scores: 2006-2010 Genetic Data. Ann Arbor, Michigan: Survey Research Center, Institute for Social Research, University of Michigan; 2017.PDF icon Download PDF (599.95 KB)
Ware EB, Faul J. Genomic data measures and methods: a primer for social scientists. In: Ferraro KF, Carr D, eds. Handbook of Aging and the Social Sciences (Ninth Edition)Handbooks of Aging. Handbook of Aging and the Social Sciences (Ninth Edition)Handbooks of Aging. Academic Press; 2021:49-62. doi:https://doi.org/10.1016/B978-0-12-815970-5.00004-8.
Ware EB, Schmitz LL, Faul J, et al. Heterogeneity in polygenic scores for common human traits. bioRxiv. Forthcoming. doi:10.1101/106062.
Ware EB, Faul J, Mitchell C, Bakulski KM. Considering the APOE locus in Alzheimer's disease polygenic scores in the Health and Retirement Study: a longitudinal panel study. BMC Medical Genomics. 2020;13(1):164. doi:10.1186/s12920-020-00815-9.
Wang H, Nandakumar P, Tekola-Ayele F, et al. Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31. European Journal of Human Genetics. 2019;27(2):269-277. doi:10.1038/s41431-018-0277-1.

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Turcot V, Lu Y, Highland HM, et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018;50(1):26-41. doi:10.1038/s41588-017-0011-x.
http://www.ncbi.nlm.nih.gov/pubmed/29273807?dopt=Abstract

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Sun D, Richard M, Musani SK, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. Human Genetics and Genomics Advances. 2021;2(1):100013. doi:10.1016/j.xhgg.2020.100013.
Schmitz LL, Gard AM, Ware EB. Examining sex differences in pleiotropic effects for depression and smoking using polygenic and gene-region aggregation techniques. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics. 2019;180(6):448 - 468. doi:10.1002/ajmg.v180.610.1002/ajmg.b.32748.
Schmitz LL, Gard AM, Ware EB. Examining sex differences in pleiotropic effects for depression and smoking using polygenic and gene-region aggregation techniques. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics. 2019. doi:10.1002/ajmg.b.32748.
http://www.ncbi.nlm.nih.gov/pubmed/31219244?dopt=Abstract

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Okbay A, Beauchamp JP, Fontana MAlan, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533(7604):539-42. doi:10.1038/nature17671.
http://www.ncbi.nlm.nih.gov/pubmed/27225129?dopt=Abstract

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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