HRS Bibliography

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2021

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.
Bakulski KM, Vadari HS, Faul J, et al. Cumulative Genetic Risk and APOE ε4 Are Independently Associated With Dementia Status in a Multiethnic, Population-Based Cohort. Neurology Genetics. 2021;7(2):e576. doi:10.1212/NXG.0000000000000576.
Graff M, Justice AE, Young KL, et al. Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. The American Journal of Human Genetics. 2021;108(4):564-582. doi:10.1016/j.ajhg.2021.02.011.
Faul J, Ware EB, Kabeto MU, Fisher J, Langa KM. The Effect of Childhood Socioeconomic Position and Social Mobility on Cognitive Function and Change Among Older Adults: A Comparison Between the United States and England. The Journals of Gerontology: Series B . 2021;76(Supplement_1):S51-S63. doi:10.1093/geronb/gbaa138.
Fuentes Lde Las, Sung YJu, Noordam R, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2021;26(6):2111-2125. doi:10.1038/s41380-020-0719-3.
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.
Fu M, Bakulski KM, Higgins C, Ware EB. Mendelian Randomization of Dyslipidemia on Cognitive Impairment Among Older Americans. Frontiers in Neurology. 2021;12(660212). doi:10.3389/fneur.2021.660212.
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.
Gard AM, Ware EB, Hyde LW, Schmitz LL, Faul J, Mitchell C. Phenotypic and genetic markers of psychopathology in a population-based sample of older adults. Translational Psychiatry. 2021;11(1):239. doi:10.1038/s41398-021-01354-2.
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.

2019

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.
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
Deelen J, Evans DS, Arking DE, et al. A meta-analysis of genome-wide association studies identifies multiple longevity genes. Nature Communications. 2019;10(1):3669. doi:10.1038/s41467-019-11558-2.
http://www.ncbi.nlm.nih.gov/pubmed/31413261?dopt=Abstract
Kilpeläinen TO, Bentley AR, Noordam R, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nature Communications. 2019;10(1):376. doi:10.1038/s41467-018-08008-w.