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Journal Article

Newman AB, Foster G, Givelber R, F Nieto J, Redline S, Young T. Progression and regression of sleep-disordered breathing with changes in weight: the Sleep Heart Health Study. Arch Intern Med. 2005 ;165(20):2408-13.

Ried JS, M JJeff, Chu AY, Bragg-Gresham JL, van Dongen J, Huffman JE, Ahluwalia TS, Cadby G, Eklund N, Eriksson J, et al. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nat Commun. 2016 ;7:13357.

Sheifer SE, Gersh BJ, Yanez ND, Ades PA, Burke GL, Manolio TA. Prevalence, predisposing factors, and prognosis of clinically unrecognized myocardial infarction in the elderly. J Am Coll Cardiol. 2000 ;35(1):119-26.

Briceño EM, Gross AL, Giordani BJ, Manly JJ, Gottesman RF, Elkind MSV, Sidney S, Hingtgen S, Sacco RL, Wright CB, et al. Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS. J Alzheimers Dis. 2021 ;83(4):1803-1813.

Young T, Shahar E, F Nieto J, Redline S, Newman AB, Gottlieb DJ, Walsleben JA, Finn L, Enright P, Samet JM. Predictors of sleep-disordered breathing in community-dwelling adults: the Sleep Heart Health Study. Arch Intern Med. 2002 ;162(8):893-900.

Lorenz MW, Gao L, Ziegelbauer K, Norata GDanilo, Empana JPhilippe, Schmidtmann I, Lin H-J, McLachlan S, Bokemark L, Ronkainen K, et al. Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk - Results from the PROG-IMT collaboration. PLoS One. 2018 ;13(4):e0191172.

Barnes DE, Covinsky KE, Whitmer RA, Kuller LH, Lopez OL, Yaffe K. Predicting risk of dementia in older adults: The late-life dementia risk index. Neurology. 2009 ;73(3):173-9.

Diehr P, Diehr M, Arnold A, Yee LM, Odden MC, Hirsch CH, Thielke S, Psaty BM, W Johnson C, Md JRKizer, et al. Predicting Future Years of Life, Health, and Functional Ability: A Healthy Life Calculator for Older Adults. Gerontol Geriatr Med. 2015 ;1:2333721415605989.

van Setten J, Brody JA, Jamshidi Y, Swenson BR, Butler AM, Campbell H, Del Greco FM, Evans DS, Gibson Q, Gudbjartsson DF, et al. PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity. Nat Commun. 2018 ;9(1):2904.

Li X, Quick C, Zhou H, Gaynor SM, Liu Y, Chen H, Selvaraj MSunitha, Sun R, Dey R, Arnett DK, et al. Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. Nat Genet. 2023 ;55(1):154-164.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Graham SE, Clarke SL, Wu KH, Kanoni S, Zajac GJM, Ramdas S, Surakka I, Ntalla I, Vedantam S, Winkler TW, et al. {The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021 ;600:675–679.

Gonzales MM, Wiedner C, Wang CP, Liu Q, Bis JC, Li Z, Himali JJ, Ghosh S, Thomas EA, Parent DM, et al. {A population-based meta-analysis of circulating GFAP for cognition and dementia risk. Ann Clin Transl Neurol. 2022 ;9:1574–1585.

Yu F, Lu J, Liu X, Gazave E, Chang D, Raj S, Hunter-Zinck H, Blekhman R, Arbiza L, Van Hout C, et al. Population genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions. PLoS One. 2015 ;10(3):e0121644.

Yu F, Lu J, Liu X, Gazave E, Chang D, Raj S, Hunter-Zinck H, Blekhman R, Arbiza L, Van Hout C, et al. Population genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions. PLoS One. 2015 ;10(3):e0121644.

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