You are here

Biblio

Search

Show only items where

Author

Type

Term

Year

Keyword

Export 41 results:

Author Title Type [ Year

]

Filters: Author is Sofer, Tamar [Clear All Filters]

2024

Huang Y-J, Kurniansyah N, Goodman MO, Spitzer BW, Wang J, Stilp A, Laurie C, de Vries PS, Chen H, Min Y-I, et al. The expected polygenic risk score (ePRS) framework: an equitable metric for quantifying polygenetic risk via modeling of ancestral makeup. medRxiv. 2024 .

Nagarajan P, Kurniansyah N, Lee J, Gharib SA, Xu Y, Zhang Y, Spitzer B, Faquih T, Zhou H, Boerwinkle E, et al. Gene-Excessive Sleepiness Interactions Suggest Treatment Targets for Obstructive Sleep Apnea Subtype. medRxiv. 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 .

Wang H, Nagarajan P, Winkler T, Bentley A, Miller C, Kraja A, Schwander K, Lee S, Wang W, Brown M, et al. A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations. Res Sq. 2024 .

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 .

Hrytsenko Y, Shea B, Elgart M, Kurniansyah N, Lyons G, Morrison AC, Carson AP, Haring B, Mitchell BD, Psaty BM, et al. Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores. Sci Rep. 2024 ;14(1):12436.

2023

Zhang Y, Liu X, Wiggins KL, Kurniansyah N, Guo X, Rodrigue AL, Zhao W, Yanek LR, Ratliff SM, Pitsillides A, et al. Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts. Neurology. 2023 .

Kurniansyah N, Goodman MO, Khan AT, Wang J, Feofanova E, Bis JC, Wiggins KL, Huffman JE, Kelly T, Elfassy T, et al. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. Nat Commun. 2023 ;14(1):3202.

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.

Hrytsenko Y, Shea B, Elgart M, Kurniansyah N, Lyons G, Morrison AC, Carson AP, Haring B, Mitchel BD, Psaty BM, et al. Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores. medRxiv. 2023 .

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 .

Seyerle AA, Laurie CA, Coombes BJ, Jain D, Conomos MP, Brody J, Chen M-H, Gogarten SM, Beutel KM, Gupta N, et al. Whole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program. Circ Genom Precis Med. 2023 :e003532.

2022

Elgart M, Goodman MO, Isasi C, Chen H, Morrison AC, de Vries PS, Xu H, Manichaikul AW, Guo X, Franceschini N, et al. Correlations between complex human phenotypes vary by genetic background, gender, and environment. Cell Rep Med. 2022 ;3(12):100844.

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.

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.

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 .

Liang J, Wang H, Cade BE, Kurniansyah N, He KY, Lee J, Sands SA, Brody J, Chen H, Gottlieb DJ, et al. Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea. Am J Respir Crit Care Med. 2022 .

2021

Liu X, Longchamps RJ, Wiggins KL, Raffield LM, Bielak LF, Zhao W, Pitsillides A, Blackwell TW, Yao J, Guo X, et al. Association of mitochondrial DNA copy number with cardiometabolic diseases. Cell Genom. 2021 ;1(1).

Sofer T, Lee J, Kurniansyah N, Jain D, Laurie CA, Gogarten SM, Conomos MP, Heavner B, Hu Y, Kooperberg C, et al. BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion. HGG Adv. 2021 ;2(3).

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 .

Cade BE, Lee J, Sofer T, Wang H, Zhang M, Chen H, Gharib SA, Gottlieb DJ, Guo X, Lane JM, et al. Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program. Genome Med. 2021 ;13(1):136.

2020

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 .

Pages