You are here

Biblio

Search

Show only items where

Author

Type

Term

Year

Keyword

Export 134 results:

Author Title [ Type

] Year

Filters: Author is Rich, Stephen S [Clear All Filters]

Journal Article

Postmus I, Warren HR, Trompet S, Arsenault BJ, Avery CL, Bis JC, Chasman DI, de Keyser CE, Deshmukh HA, Evans DS, et al. Meta-analysis of genome-wide association studies of HDL cholesterol response to statins. J Med Genet. 2016 ;53(12):835-845.

Lundin JI, Peters U, Hu Y, Ammous F, Avery CL, Benjamin EJ, Bis JC, Brody JA, Carlson C, Cushman M, et al. Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations. Epigenetics. 2024 ;19(1):2333668.

Nauffal V, Morrill VN, Jurgens SJ, Choi SHoan, Hall AW, Weng L-C, Halford JL, Austin-Tse C, Haggerty CM, Harris SL, et al. Monogenic and Polygenic Contributions to QTc Prolongation in the Population. Circulation. 2022 .

Jakubek YA, Zhou Y, Stilp A, Bacon J, Wong JW, Ozcan Z, Arnett D, Barnes K, Bis JC, Boerwinkle E, et al. Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing. Nat Genet. 2023 ;55(11):1912-1919.

Demenais F, Margaritte-Jeannin P, Barnes KC, Cookson WOC, Altmüller J, Ang W, R Barr G, Beaty TH, Becker AB, Beilby J, et al. Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks. Nat Genet. 2018 ;50(1):42-53.

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.

Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese A-K, van der Laan SW, Gretarsdottir S, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018 ;50(4):524-537.

Malik R, Chauhan G, Traylor M, Sargurupremraj M, Okada Y, Mishra A, Rutten-Jacobs L, Giese A-K, van der Laan SW, Gretarsdottir S, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018 ;50(4):524-537.

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.

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 .

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.

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.

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.

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.

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.

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 .

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.

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.

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 .

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.

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.

Pages