HRS Bibliography

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2019

Liu M, Jiang Y, Wedow R, et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nature Genetics. 2019;51(2):237-244. doi:10.1038/s41588-018-0307-5.
McGrath RP, Snih SAl, Markides KS, et al. The burden of health conditions across race and ethnicity for aging Americans: Disability-adjusted life years. Medicine . 2019;98(46):e17964. doi:10.1097/MD.0000000000017964.
Vivek S, Thyagarajan B, Nelson HHammond, Prizment A, Crimmins EM, Faul J. COMBINED EFFECT OF CMV SEROPOSITIVITY AND SYSTEMIC INFLAMMATION ON DEMENTIA PREVALENCE IN CANCER SURVIVORS. Innovation in Aging. 2019;3:S461-S461. doi:10.1093/geroni/igz038.1724.
Brazel DM, Jiang Y, Hughey JM, et al. Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use. Biological Psychiatry. 2019;85(11):946-955. doi:10.1016/j.biopsych.2018.11.024.
Thyagarajan B, Shippee N, Parsons H, et al. How Does Subjective Age Get “Under the Skin”? The Association Between Biomarkers and Feeling Older or Younger Than One’s Age: The Health and Retirement Study. Innovation in Aging. 2019;3(4):igz035. doi:10.1093/geroni/igz035.
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.
Evangelou E, Gao H, Chu C, et al. New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders. Nature Human Behaviour. 2019;3(9):950-961. doi:10.1038/s41562-019-0653-z.
Blue L, Gill L, Faul J, Bradway K, Stapleton D. Predicting Receipt of Social Security Administration Disability Benefits Using Biomarkers and Other Physiological Measures: Evidence From the Health and Retirement Study. Journal of Aging and Health. 2019;31(4):555-579. doi:10.1177/0898264317737893.
http://www.ncbi.nlm.nih.gov/pubmed/29254420?dopt=Abstract

2017

Direk N, Williams S, Smith JA, et al. An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype. Biological Psychiatry. 2017;82(5):322-329. doi:10.1016/j.biopsych.2016.11.013.
Langa KM, Larson EB, Crimmins EM, et al. A Comparison of the Prevalence of Dementia in the United States in 2000 and 2012. JAMA Intern Med. 2017;177(1):51-58. doi:10.1001/jamainternmed.2016.6807.
http://www.ncbi.nlm.nih.gov/pubmed/27893041?dopt=Abstract
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
C Y Ng M, Graff M, Lu Y, et al. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genetics. 2017;13(4):e1006719. doi:10.1371/journal.pgen.1006719.
Crimmins EM, Faul J, Kim JKi, Weir DR. Documentation of Blood-Based Biomarkers in the 2014 Health and Retirement Study. Ann Arbor, MI: Survey Research Center, Institute for Social Research, University of Michigan; 2017.PDF icon Download PDF (247.04 KB)
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
Joshi PK, Pirastu N, Kentistou KA, et al. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity. Nature Communications. 2017;8(1):910. doi:10.1038/s41467-017-00934-5.
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)