HRS Bibliography

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Journal Article

Plassman BL, Langa KM, McCammon RJ, et al. Incidence of dementia and cognitive impairment, not dementia in the United States. Ann Neurol. 2011;70(3):418-26. doi:10.1002/ana.22362.
http://www.ncbi.nlm.nih.gov/pubmed/21425187?dopt=Abstract
Sakshaug JW, Weir DR, Nicholas LHersch. Identifying diabetics in Medicare claims and survey data: implications for health services research. BMC Health Serv Res. 2014;14:150. doi:10.1186/1472-6963-14-150.
http://www.ncbi.nlm.nih.gov/pubmed/24693862?dopt=Abstract
Ware EB, Schmitz LL, Faul J, et al. Heterogeneity in polygenic scores for common human traits. bioRxiv. Forthcoming. doi:10.1101/106062.
Levy HG, Ubel PA, Dillard AJ, Weir DR, Fagerlin A. Health numeracy: the importance of domain in assessing numeracy. Med Decis Making. 2014;34(1):107-15. doi:10.1177/0272989X13493144.
http://www.ncbi.nlm.nih.gov/pubmed/23824401?dopt=Abstract
Langa KM, Ryan LH, McCammon RJ, et al. The Health and Retirement Study Harmonized Cognitive Assessment Protocol Project: Study Design and Methods. Neuroepidemiology. 2020. doi:10.1159/000503004.
Sonnega A, Weir DR. The Health and Retirement Study: A Public Data Resource for Research on Aging. Open Health Data. 2014;2(1). doi:10.5334/ohd.am.
Gross AL, LI CHIHUA, Briceño EM, et al. Harmonization of Later-Life Cognitive Function Across National Contexts: Results from the Harmonized Cognitive Assessment Protocols (HCAPs). medRxiv. Forthcoming. doi:10.1101/2023.06.09.23291217.
Broer L, Buchman AS, Deelen J, et al. GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy. J Gerontol A Biol Sci Med Sci. 2015;70(1):110-8. doi:10.1093/gerona/glu166.
http://www.ncbi.nlm.nih.gov/pubmed/25199915?dopt=Abstract
Rietveld CA, Medland SE, Derringer J, et al. GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science. 2013;340(6139):1467-71. doi:10.1126/science.1235488.
http://www.ncbi.nlm.nih.gov/pubmed/23722424?dopt=Abstract
Matteini AM, Tanaka T, Karasik D, et al. GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium. Aging Cell. 2016;15(5):792-800. doi:10.1111/acel.12468.
http://www.ncbi.nlm.nih.gov/pubmed/27325353?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.
Lahti J, Tuominen S, Yang Q, et al. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning. Molecular Psychiatry. 2022. doi:10.1038/s41380-022-01710-8.
Jian X, Sofer T, Tarraf W, et al. Genome-wide association study of cognitive function in diverse Hispanics/Latinos: results from the Hispanic Community Health Study/Study of Latinos. Translational Psychiatry. 2020;10(1):245. doi:10.1038/s41398-020-00930-2.
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
Dunn EC, Wiste A, Radmanesh F, et al. GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN. Depress Anxiety. 2016;33(4):265-80. doi:10.1002/da.22484.
http://www.ncbi.nlm.nih.gov/pubmed/27038408?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
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
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
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
Bihlmeyer NA, Brody JA, Smith AVernon, et al. Genetic diversity is a predictor of mortality in humans. BMC Genet. 2014;15:159. doi:10.1186/s12863-014-0159-7.
http://www.ncbi.nlm.nih.gov/pubmed/25543667?dopt=Abstract
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.
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
Jones RN, Manly JJ, Langa KM, et al. Factor structure of the Harmonized Cognitive Assessment Protocol neuropsychological battery in the Health and Retirement Study. Neuropsychology. Forthcoming. doi:10.31234/osf.io/rvmhj.
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.
Xu H, Nguyen K, Gaynor BJ, et al. Exome Array Analysis of 9721 Ischemic Stroke Cases from the SiGN Consortium. Genes . 2022;14(1):61. doi:10.3390/genes14010061.