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Journal Article

Weinstock JS, Gopakumar J, Burugula BBharathi, Uddin MMesbah, Jahn N, Belk JA, Bouzid H, Daniel B, Miao Z, Ly N, et al. Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis. Nature. 2023 ;616(7958):755-763.

Georgakis MK, Malik R, Hasbani NR, Shakt G, Morrison AC, Tsao NL, Judy R, Mitchell BD, Xu H, Montasser ME, et al. Carriers of rare damaging genetic variants are at lower risk of atherosclerotic disease. medRxiv. 2023 .

Wuttke M, Li Y, Li M, Sieber KB, Feitosa MF, Gorski M, Tin A, Wang L, Chu AY, Hoppmann A, et al. A catalog of genetic loci associated with kidney function from analyses of a million individuals. Nat Genet. 2019 ;51(6):957-972.

Natarajan P, Pampana A, Graham SE, Ruotsalainen SE, Perry JA, de Vries PS, Broome JG, Pirruccello JP, Honigberg MC, Aragam K, et al. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. Nat Commun. 2021 ;12(1):2182.

Winkler TW, Rasheed H, Teumer A, Gorski M, Rowan BX, Stanzick KJ, Thomas LF, Tin A, Hoppmann A, Chu AY, et al. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals. Commun Biol. 2022 ;5(1):580.

Graff M, Justice AE, Young KL, Marouli E, Zhang X, Fine RS, Lim E, Buchanan V, Rand K, Feitosa MF, et al. Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. Am J Hum Genet. 2021 ;108(4):564-582.

Jian X, Satizabal CL, Smith AV, Wittfeld K, Bis JC, Smith JA, Hsu F-C, Nho K, Hofer E, Hagenaars SP, et al. Exome Chip Analysis Identifies Low-Frequency and Rare Variants in for White Matter Hyperintensities on Brain Magnetic Resonance Imaging. Stroke. 2018 .

Li Z, Li X, Zhou H, Gaynor SM, Selvaraj MSunitha, Arapoglou T, Quick C, Liu Y, Chen H, Sun R, et al. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. Nat Methods. 2022 ;19(12):1599-1611.

Fuentes Lde Las, Sung YJu, Noordam R, Winkler T, Feitosa MF, Schwander K, Bentley AR, Brown MR, Guo X, Manning A, et al. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. Mol Psychiatry. 2020 .

Fuentes Lde Las, Schwander KL, Brown MR, Bentley AR, Winkler TW, Sung YJu, Munroe PB, Miller CL, Aschard H, Aslibekyan S, et al. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. Front Genet. 2023 ;14:1235337.

Weinstock JS, Laurie CA, Broome JG, Taylor KD, Guo X, Shuldiner AR, O'Connell JR, Lewis JP, Boerwinkle E, Barnes KC, et al. The genetic determinants of recurrent somatic mutations in 43,693 blood genomes. Sci Adv. 2023 ;9(17):eabm4945.

Ehret GB, Munroe PB, Rice KM, Bochud M, Johnson AD, Chasman DI, Smith AV, Tobin MD, Verwoert GC, Hwang S-J, et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature. 2011 ;478(7367):103-9.

Bick AG, Weinstock JS, Nandakumar SK, Fulco CP, Bao EL, Zekavat SM, Szeto MD, Liao X, Leventhal MJ, Nasser J, et al. Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020 ;586(7831):763-768.

Nagarajan P, Winkler TW, Bentley AR, Miller CL, Kraja AT, Schwander K, Lee S, Wang W, Brown MR, Morrison JL, et al. A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations. medRxiv. 2024 .

Sung YJ, Winkler TW, Fuentes Lde Las, Bentley AR, Brown MR, Kraja AT, Schwander K, Ntalla I, Guo X, Franceschini N, et al. A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. Am J Hum Genet. 2018 ;102(3):375-400.

Wessel J, Chu AY, Willems SM, Wang S, Yaghootkar H, Brody JA, Dauriz M, Hivert M-F, Raghavan S, Lipovich L, et al. Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat Commun. 2015 ;6:5897.

Monda KL, Chen GK, Taylor KC, Palmer C, Edwards TL, Lange LA, C Y Ng M, Adeyemo AA, Allison MA, Bielak LF, et al. A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. Nat Genet. 2013 ;45(6):690-6.

C Y Ng M, Shriner D, Chen BH, Li J, Chen W-M, Guo X, Liu J, Bielinski SJ, Yanek LR, Nalls MA, et al. Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes. PLoS Genet. 2014 ;10(8):e1004517.

de Vries PS, Brown MR, Bentley AR, Sung YJ, Winkler TW, Ntalla I, Schwander K, Kraja AT, Guo X, Franceschini N, et al. Multi-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. Am J Epidemiol. 2019 .

Wang H, Noordam R, Cade BE, Schwander K, Winkler TW, Lee J, Sung YJu, Bentley AR, Manning AK, Aschard H, et al. Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. Mol Psychiatry. 2021 .

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.

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.

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.

Feitosa MF, Kraja AT, Chasman DI, Sung YJ, Winkler TW, Ntalla I, Guo X, Franceschini N, Cheng C-Y, Sim X, et al. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. PLoS One. 2018 ;13(6):e0198166.

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.

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