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S

Li X, Chen H, Selvaraj MSunitha, Van Buren E, Zhou H, Wang Y, Sun R, McCaw ZR, Yu Z, Arnett DK, et al. A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. bioRxiv. 2023 .

Magnani JW, Brody JA, Prins BP, Arking DE, Lin H, Yin X, Liu C-T, Morrison AC, Zhang F, Spector TD, et al. Sequencing of SCN5A identifies rare and common variants associated with cardiac conduction: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Circ Cardiovasc Genet. 2014 ;7(3):365-73.

Taliun D, Harris DN, Kessler MD, Carlson J, Szpiech ZA, Torres R, Taliun SAGagliano, Corvelo A, Gogarten SM, Kang HMin, et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021 ;590(7845):290-299.

Liang J, Cade BE, He KY, Wang H, Lee J, Sofer T, Williams S, Li R, Chen H, Gottlieb DJ, et al. Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level. Am J Hum Genet. 2019 ;105(5):1057-1068.

R

Wang Z, Chen H, Bartz TM, Bielak LF, Chasman DI, Feitosa MF, Franceschini N, Guo X, Lim E, Noordam R, et al. Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels. Circ Genom Precis Med. 2020 ;13(4):e002772.

Mahajan A, Wessel J, Willems SM, Zhao W, Robertson NR, Chu AY, Gan W, Kitajima H, Taliun D, N Rayner W, et al. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat Genet. 2018 ;50(4):559-571.

Wang Y, Selvaraj MSunitha, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, et al. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. medRxiv. 2023 .

Jang S-K, Evans L, Fialkowski A, Arnett DK, Ashley-Koch AE, Barnes KC, Becker DM, Bis JC, Blangero J, Bleecker ER, et al. Rare genetic variants explain missing heritability in smoking. Nat Hum Behav. 2022 .

Hindy G, Dornbos P, Chaffin MD, Liu DJ, Wang M, Selvaraj MSunitha, Zhang D, Park J, Aguilar-Salinas CA, Antonacci-Fulton L, et al. Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. Am J Hum Genet. 2022 ;109(1):81-96.

Auer PL, Nalls M, Meschia JF, Worrall BB, Longstreth WT, Seshadri S, Kooperberg C, Burger KM, Carlson CS, Carty CL, et al. Rare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project. JAMA Neurol. 2015 ;72(7):781-8.

Q

Gordon AS, Tabor HK, Johnson AD, Snively BM, Assimes TL, Auer PL, Ioannidis JPA, Peters U, Robinson JG, Sucheston LE, et al. Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset. Hum Mol Genet. 2014 ;23(8):1957-63.

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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.

Hu X, Qiao D, Kim W, Moll M, Balte PP, Lange LA, Bartz TM, Kumar R, Li X, Yu B, et al. Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program. Am J Hum Genet. 2022 .

Vuckovic D, Bao EL, Akbari P, Lareau CA, Mousas A, Jiang T, Chen M-H, Raffield LM, Tardaguila M, Huffman JE, et al. The Polygenic and Monogenic Basis of Blood Traits and Diseases. Cell. 2020 ;182(5):1214-1231.e11.

Eicher JD, Chami N, Kacprowski T, Nomura A, Chen M-H, Yanek LR, Tajuddin SM, Schick UM, Slater AJ, Pankratz N, et al. Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals. Am J Hum Genet. 2016 ;99(1):40-55.

O

Xu J, Gaddis NC, Bartz TM, Hou R, Manichaikul AW, Pankratz N, Smith AV, Sun F, Terzikhan N, Markunas CA, et al. Omega-3 Fatty Acids and Genome-wide Interaction Analyses Reveal DPP10-Pulmonary Function Association. Am J Respir Crit Care Med. 2018 .

N

Elgart M, Lyons G, Romero-Brufau S, Kurniansyah N, Brody JA, Guo X, Lin HJ, Raffield L, Gao Y, Chen H, et al. Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations. Commun Biol. 2022 ;5(1):856.

M

Kurniansyah N, Goodman MO, Kelly TN, Elfassy T, Wiggins KL, Bis JC, Guo X, Palmas W, Taylor KD, Lin HJ, et al. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. Nat Commun. 2022 ;13(1):3549.

Wyss AB, Sofer T, Lee MKyeong, Terzikhan N, Nguyen JN, Lahousse L, Latourelle JC, Smith AVernon, Bartz TM, Feitosa MF, et al. Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function. Nat Commun. 2018 ;9(1):2976.

Musunuru K, Romaine SPR, Lettre G, Wilson JG, Volcik KA, Tsai MY, Taylor HA, Schreiner PJ, Rotter JI, Rich SS, et al. Multi-ethnic analysis of lipid-associated loci: the NHLBI CARe project. PLoS One. 2012 ;7(5):e36473.

Chen F, Wang X, Jang S-K, Quach BC, J Weissenkampen D, Khunsriraksakul C, Yang L, Sauteraud R, Albert CM, Allred NDD, et al. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. Nat Genet. 2023 ;55(2):291-300.

Kilpeläinen TO, Bentley AR, Noordam R, Sung YJu, Schwander K, Winkler TW, Jakupović H, Chasman DI, Manning A, Ntalla I, et al. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. Nat Commun. 2019 ;10(1):376.

Noordam R, Bos MM, Wang H, Winkler TW, Bentley AR, Kilpeläinen TO, de Vries PS, Sung YJu, Schwander K, Cade BE, et al. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. Nat Commun. 2019 ;10(1):5121.

Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Rayner NW, Bocher O, et al. Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. medRxiv. 2023 .

Bentley AR, Sung YJ, Brown MR, Winkler TW, Kraja AT, Ntalla I, Schwander K, Chasman DI, Lim E, Deng X, et al. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. Nat Genet. 2019 ;51(4):636-648.

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