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4 results on '"Rouel Lanche"'

1. Thrombotic Risk Determined by STAB 2 Variants in a Population-Based Cohort Study

Author

Eric Manderstedt, Christer Halldén, Christina Lind-Halldén, Johan Elf, Peter J. Svensson, Gunnar Engström, Olle Melander, Aris Baras, Luca A Lotta, Bengt Zöller, Goncalo Abecasis, Michael Cantor, Giovanni Coppola, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Katia Karalis, Katherine Siminovitch, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Andrew Blumenfeld, Boris Boutkov, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, Mrunali Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Niek Verweij, Jonas Nielsen, Tanima De, Marcus B. Jones, Jason Mighty, Michelle G. LeBlanc, and Lyndon J. Mitnaul

Subjects
Thrombotic risk, medicine.medical_specialty, education.field_of_study, business.industry, Population, General Medicine, medicine.disease, Thrombosis, Population based cohort, Internal medicine, Medicine, business, education, Venous thromboembolism
Published
2021
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2. Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank

Author

Lukas Habegger, Max Orelus, Marcus B. Jones, Anurag Verma, Aris Economides, Shareef Khalid, William J Salerno, Adam J. Mansfield, Luca A. Lotta, Maria Sotiropoulos Padilla, Louis Widom, Michael Cantor, Giovanni Coppola, Katherine L. Nathanson, Suganthi Balasubramanian, Razvan Panea, John D. Overton, Alicia Hawes, Anh D. Le, Jeffrey C. Staples, Danielle L. Mowery, Jason Mighty, Kara N. Maxwell, Renae Judy, Andrew Blumenfeld, Manasi Pradhan, Peter Gabriel, Heena Desai, Caitlin Forsythe, Jeffrey G. Reid, Lyndon J. Mitnaul, Christina Beechert, Xiaodong Bai, Olga Krasheninina, Zhenhua Gu, Abigail Doucette, Mrunali Nafde, Boris Boutkov, Kia Manoochehri, Marylyn D. Ritchie, Tommy Polanco, Rouel Lanche, Alexander E. Lopez, Ryan Hausler, Alan R. Shuldiner, Sarah E. Wolf, Thomas D. Schleicher, Gisu Eom, Shefali S. Verma, Sean O’Keeffe, Ayesha Rasool, Rachel L. Kember, Evan Maxwell, Michael Lattari, Erin D. Fuller, Scott M. Damrauer, Ricardo H. Ulloa, Gonçalo R. Abecasis, Louise Wang, and Aris Baras

Subjects
Gerontology, business.industry, Medicine, Cancer, Polygenic risk score, business, medicine.disease, Biobank
Abstract

PurposeGenome-wide association studies (GWAS) have identified hundreds of single nucleotide polymorphisms (SNPs) significantly associated with several cancers, but the predictive ability of polygenic risk scores (PRS) is unclear, especially among non-Whites.MethodsGenome-wide genotype data was available for 20,079 individuals enrolled in an academic biobank. PRS were derived from significant DNA variants for 15 cancers. We determined the discriminatory accuracy of each cancer-specific PRS in patients of genetically-determined African and European ancestry separately.ResultsAmong individuals of European genetic ancestry, PRS for breast, colon, melanoma, and prostate were significantly associated with their respective cancers (OR 1.25-1.47). Among individuals of African genetic ancestry, PRS for breast, colon, and prostate were significantly associated with their respective cancers. The AUC of a model comprised of age, sex, and principal components was 0.617–0.709 and increased by 1-4% with the PRS in individuals of European genetic ancestry. In individuals of African genetic ancestry, AUC was overall higher in the model without PRS (0.740-0.811) but increased < 1% with the PRS in the majority of cancers.ConclusionPRS constructed from SNPs moderately increased discriminatory ability for cancer status in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors in non-White populations to incorporate PRS into cancer risk assessment.

Published
2021
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3. Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease

Author

Marie V. Coignet, Dylan Sun, Lukas Habegger, Evan Maxwell, Daniel J. Rader, David J. Carey, Katherine A. Siminovitch, Giorgio Sirugo, Anne E. Justice, Joelle Mbatchou, Eli A. Stahl, Gonçalo R. Abecasis, Alexander H. Li, David A. Turissini, Adam E. Locke, Kristin A. Rand, Aris Baras, Joseph B. Leader, Genevieve H.L. Roberts, Ahna R. Girshick, Deepika Sharma, Nilanjana Banerjee, Fabricio S. P. Kury, John D. Overton, Shane McCarthy, Jonathan Marchini, Xiaodong Bai, Eurie L. Hong, Rouel Lanche, Amy Damask, Ashish Yadav, Raghavendran Partha, Shannon R. McCurdy, Miao Zhang, Suganthi Balasubramanian, Hyun Min Kang, Anurag Verma, Marcus B. Jones, Marylyn D. Ritchie, Colm O'Dushlaine, Manuel A. R. Ferreira, Adam J. Mansfield, Anthony Marcketta, Joshua D. Backman, Alan R. Shuldiner, Michael N. Cantor, Tooraj Mirshahi, Lee Dobbyn, Spencer C. Knight, William J Salerno, Harenda Guturu, Jeffrey G. Reid, Julie E. Horowitz, Lauren Gurski, Danny S. Park, Kyoko Watanabe, Catherine A. Ball, Asher K. Haug Baltzell, and Jack A. Kosmicki

Subjects
2019-20 coronavirus outbreak, Increased risk, Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Genetic variants, MEDLINE, Severe disease, Medicine, Bioinformatics, business
Abstract

SARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5x10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.

Published
2020
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4. A catalog of associations between rare coding variants and COVID-19 outcomes

Author

Anurag Verma, Anne E. Justice, Guillaume Butler-Laporte, E. N. Smith, Lukas Habegger, Joelle Mbatchou, Susan P. Walker, Albert Tenesa, Joseph D. Szustakowski, Konrad Rawlik, Dylan Sun, Loukas Moutsianas, Shane McCarthy, Richard H Scott, Aris Baras, Evan Maxwell, Aldo Cordova-Palomera, Tooraj Mirshahi, Dorota Pasko, David J. Carey, Sahar Esmaeli, Adam J. Mansfield, Quanli Wang, Jeffrey S. Reid, Nilanjana Banerjee, Joshua D. Backman, Athanasios Kousathanas, Ashish Yadav, Mark J. Caulfield, Alison M. Meynert, Rouel Lanche, Jack A. Kosmicki, James F. Wilson, J. Brent Richards, Heiko Runz, Gonçalo R. Abecasis, Adam E. Locke, Justin W. Davis, Mark Lathrop, Alan R. Shuldiner, Lauren Gurski, J Kenneth Baillie, Michael N. Cantor, David Goldstein, John D. Overton, Kyoko Watanabe, Amanda O'Neill, Yunfeng Huang, Jonathan Marchini, Xiaodong Bai, Krzysztof Kiryluk, Slavé Petrovski, Sean O'Keeffe, Erika Kvikstad, Anthony Marcketta, Margaret M. Parker, Giorgio Sirugo, Julie E. Horowitz, Emily Wong, Olympe Chazara, Paul Nioi, Manuel A. R. Ferreira, Sándor Szalma, Joseph B. Leader, Shareef Khalid, William J Salerno, Deepika Sharma, Tomoko Nakanishi, Marcus B. Jones, Gundula Povysil, Marylyn D. Ritchie, Colm O'Dushlaine, Xiuwen Zheng, Daniel J. Rader, Suganthi Balasubramanian, Hyun Min Kang, Yi-Pin Lai, Alexander H. Li, Xing Chen, and Erola Pairo-Castineira

Subjects
Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Genome-wide association study, medicine.disease_cause, Biobank, Article, Genetic association analysis, Immunology, Multiple comparisons problem, Medicine, business, Gene, Coronavirus
Abstract

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable athttps://rgc-covid19.regeneron.com.

Published
2020
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