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Journal Article

Zhang X, Brody JA, Graff M, Highland HM, Chami N, Xu H, Wang Z, Ferrier K, Chittoor G, Josyula NS, et al. WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE. medRxiv. 2023 .

DiCorpo D, Gaynor SM, Russell EM, Westerman KE, Raffield LM, Majarian TD, Wu P, Sarnowski C, Highland HM, Jackson A, et al. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. Commun Biol. 2022 ;5(1):756.

Huffman JE, Nicolas J, Hahn J, Heath AS, Raffield LM, Yanek LR, Brody JA, Thibord F, Almasy L, Bartz TM, et al. Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles. medRxiv. 2023 .

Hasbani NR, Westerman KE, Kwak SHeon, Chen H, Li X, DiCorpo D, Wessel J, Bis JC, Sarnowski C, Wu P, et al. Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis. Circ Genom Precis Med. 2023 :e004176.

Liu C-T, Raghavan S, Maruthur N, Kabagambe EKato, Hong J, C Y Ng M, Hivert M-F, Lu Y, An P, Bentley AR, et al. Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin. Am J Hum Genet. 2016 ;99(1):56-75.

Stilp AM, Emery LS, Broome JG, Buth EJ, Khan AT, Laurie CA, Wang FFei, Wong Q, Chen D, D'Augustine CM, et al. A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. Am J Epidemiol. 2021 .

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.

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.

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.

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.

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.

Lu Y, Dimitrov L, Chen S-H, Bielak LF, Bis JC, Feitosa MF, Lu L, Kavousi M, Raffield LM, Smith AV, et al. Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes. Circ Genom Precis Med. 2021 ;14(4):e003258.

Natarajan P, Bis JC, Bielak LF, Cox AJ, Dörr M, Feitosa MF, Franceschini N, Guo X, Hwang S-J, Isaacs A, et al. Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis. Circ Cardiovasc Genet. 2016 .

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.

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 .

Kavousi M, Bos MM, Barnes HJ, Cardenas CLLino, Wong D, Lu H, Hodonsky CJ, Landsmeer LPL, Turner AW, Kho M, et al. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification. Nat Genet. 2023 ;55(10):1651-1664.

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.

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 .

Sun D, Richard M, Musani SK, Sung YJu, Winkler TW, Schwander K, Chai JFang, Guo X, Kilpeläinen TO, Vojinovic D, et al. Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. HGG Adv. 2021 ;2(1).

Mahajan A, Spracklen CN, Zhang W, C Y Ng M, Petty LE, Kitajima H, Yu GZ, Rüeger S, Speidel L, Kim YJin, et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat Genet. 2022 ;54(5):560-572.

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, Chasman DI, Sabater-Lleal M, Chen M-H, Huffman JE, Steri M, Tang W, Teumer A, Marioni RE, Grossmann V, et al. A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration. Hum Mol Genet. 2016 ;25(2):358-70.

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.

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