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2024

Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Melloni GEM, Kanoni S, et al. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. 2024 .

Yu Z, Vromman A, Nguyen NQuynh H, Schuermans A, Rentz T, Vellarikkal SK, Uddin MMesbah, Niroula A, Griffin G, Honigberg MC, et al. Human Plasma Proteomic Profile of Clonal Hematopoiesis. bioRxiv. 2024 .

Jones AC, Patki A, Srinivasasainagendra V, Tiwari HK, Armstrong ND, Chaudhary NS, Limdi NA, Hidalgo BA, Davis B, Cimino JJ, et al. Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations. J Am Soc Nephrol. 2024 .

Kwak SHeon, Hernandez-Cancela RB, DiCorpo DA, Condon DE, Merino J, Wu P, Brody JA, Yao J, Guo X, Ahmadizar F, et al. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People With Type 2 Diabetes. Diabetes Care. 2024 .

Scholz M, Horn K, Pott J, Wuttke M, Kühnapfel A, M Nasr K, Kirsten H, Li Y, Hoppmann A, Gorski M, et al. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements. Nat Commun. 2024 ;15(1):586.

2023

Tobias DK, Manning AK, Wessel J, Raghavan S, Westerman KE, Bick AG, DiCorpo D, Whitsel EA, Collins J, Correa A, et al. Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk. Diabetes Care. 2023 .

Willems SM, Ng NHJ, Fernandez J, Fine RS, Wheeler E, Wessel J, Kitajima H, Marenne G, Sim X, Yaghootkar H, et al. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization. Wellcome Open Res. 2023 ;8:483.

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.

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 .

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.

Kwak SHeon, Hernandez-Cancela RB, DiCorpo DA, Condon DE, Merino J, Wu P, Brody JA, Yao J, Guo X, Ahmadizar F, et al. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus. 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.

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 .

Armstrong ND, Srinivasasainagendra V, Ammous F, Assimes TL, Beitelshees AL, Brody J, Cade BE, Chen Y-DIda, Chen H, de Vries PS, et al. Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program. Front Genet. 2023 ;14:1278215.

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 .

de Vries PS, Conomos MP, Singh K, Nicholson CJ, Jain D, Hasbani NR, Jiang W, Lee S, Cardenas CLLino, Lutz SM, et al. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification. Nat Cardiovasc Res. 2023 ;2(12):1159-1172.

2022

Wainschtein P, Jain D, Zheng Z, Cupples AL, Shadyab AH, McKnight B, Shoemaker BM, Mitchell BD, Psaty BM, Kooperberg C, et al. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. Nat Genet. 2022 ;54(3):263-273.

Durda P, Raffield LM, Lange EM, Olson NC, Jenny NSwords, Cushman M, Deichgraeber P, Grarup N, Jonsson A, Hansen T, et al. Circulating Soluble CD163, Associations With Cardiovascular Outcomes and Mortality, and Identification of Genetic Variants in Older Individuals: The Cardiovascular Health Study. J Am Heart Assoc. 2022 ;11(21):e024374.

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.

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.

Gorski M, Rasheed H, Teumer A, Thomas LF, Graham SE, Sveinbjornsson G, Winkler TW, Günther F, Stark KJ, Chai J-F, et al. Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies. Kidney Int. 2022 .

Tcheandjieu C, Zhu X, Hilliard AT, Clarke SL, Napolioni V, Ma S, Lee KMin, Fang H, Chen F, Lu Y, et al. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med. 2022 ;28(8):1679-1692.

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.

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.

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 .

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