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Kooperberg, Charles

https://orcid.org/0000-0002-7986-8560

Mayo Clinic

University of Washington

Citations 42

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors
Thibord, Florian , Klarin, Derek , Brody, Jennifer A. , Chen, Ming‐Huei , Levin, Michael G. , Chasman, Daniel I. , Goode, Ellen L. , Teder‐Laving, Maris , Martínez-Pérez, Ángel , Daian-Bacq, Delphine, Ito, Kaoru , Natarajan, Pradeep , Lutsey, Pamela L. , Nadkarni, Girish N. , Vries, Paul S. de , Wolford, Brooke N. , Pattee, Jack , Brækkan, Sigrid K. , Li‐Gao, Ruifang , Saut, Noémie , Sept, Corriene, Judy, Renae , O’Donnell, Christopher J. , Giulianini, Franco, Boland, Anne , Empana, Jean‐Philippe , Gilliland, Thomas , Do, Ron , Wang, Xin , Zhou, Wei , Soria, José Manuel , Souto, Juan Carlos , Haessler, Jeffery, Hindberg, Kristian , Bartz, Traci M. , Heckbert, Susan R. , Armasu, Sebastian M. , Brumpton, Ben , Smadja, David M. , Jouven, Xavier , Loos, Ruth J. F. , Sabater‐Lleal, Maria , Pankow, James S. , Reiner, Alex P. , Vlieg, Astrid van Hylckama , Deleuze, Jean-François, Skogholt, Anne Heidi , Emmerich, Joseph , Tang, Weihong , Jackson, Rebecca D. , Hansen, John‐Bjarne , Morange, Pierre‐Emmanuel , Kabrhel, Christopher , Johnson, Andrew D. , Smith, Nicholas L. , Martinez-Perez, Angel , Aïssi, Dylan , Ito, Kaoru , Natarajan, Pradeep , Lutsey, Pamela L , Nadkarni, Girish N , de Vries, Paul S , Wolford, Brooke N , Kooperberg, Charles , Braekkan, Sigrid K , Li-Gao, Ruifang , Saut, Noemie , Germain, Marine , Wiggins, Kerri L , Ko, Darae , O'Donnell, Christopher J , Taylor, Kent D , de Andrade, Mariza , Nøst, Therese H , Boland, Anne , Empana, Jean Philippe , Gilliland, Thomas , Do, Ron , Wang, Xin , Manuel Soria, Jose , Carlos Souto, Juan , Pankratz, Nathan , Rosendaal, Frits R , Turman, Constance , Olaso, Robert , Bartz, Traci M , Lynch, Julie A , Heckbert, Susan R , Brumpton, Ben , Smadja, David M , Komuro, Issei , Clapham, Katharine R , Loos, Ruth J F , Willer, Cristen J , Sabater-Lleal, Maria , Pankow, James S , Reiner, Alexander P , Ridker, Paul M. , Rader, Daniel J , Min Lee, Kyung , Psaty, Bruce M , Rich, Stephen S , Vy, Ha My T , Tang, Weihong , Damrauer, Scott M , Johnson, Andrew D , Smith, Nicholas L , Chasman, Daniel I , Brody, Jennifer A , Hveem, Kristian , Cuéllar-Partida, Gabriel , Kooperberg, Charles , Germain, Marine , Wiggins, Kerri L. , Taylor, Kent D. , Andrade, Mariza de , Koyama, Satoshi , Huffman, Jennifer E. , Pankratz, Nathan , Turman, Constance , Kember, Rachel L. , Lynch, Julie A. , Morelli, Vânia Maris , Deleuze, Jean‐François , Kraft, Peter , Lee, Kyung Min , Psaty, Bruce M. , Suchon, Pierre , Rich, Stephen S. , Trégouët, David‐Alexandre

Circulation | October 17, 2022 | Volume: 146 | Issue: 16 | Pages: 1225-1242

10.1161/circulationaha.122.059675 Get It

Background: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. Methods: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. Results: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. Conclusions: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.
Genomic and phenomic landscape of clonal hematopoiesis in over a million ancestrally diverse participants
Uddin, Md Mesbah , Weinstock, Joshua S. , Niroula, Abhishek , Vlasschaert, Caitlyn , Koyama, Satoshi , Nakao, Tetsushi , Urbut, Sarah , Paruchuri, Kaavya , Silver, Alexander J. , Mack, Taralynn , Wong, Megan , Bhattacharya, Romit , Jorshery, Saman Doroodgar , Raddatz, Michael A. , Hornsby, Whitney , Kresge, Hailey A. , Cho, Kelly , Sun, Yan V. , Pyarajan, Saiju , Chen, Yii‐Der Ida , Sheu, Wayne H-H , Hung, Yi‐Jen , Hidalgo, Bertha , Fornage, Myriam , Kaplan, Robert C., Williams, L. Keoki , Province, Mike , Kardia, Sharon, Peyser, Patricia A., Yanek, Lisa R. , Becker, Lewis C. , Meyers, Deborah A. , Naseri, Take, Barnes, Kathleen C. , Redline, S S, Schwartz, D A, Shoemaker, M. Benjamin , Palmer, Nicholette D., Bowden, Donald W., Kumar, Rajesh, Nj, Smith, Floyd, James, Tracy, Russell, Bis, Joshua C. , SS, Rich, Boerwinkle, Eric, Wang, Zhe, Silverman, Edwin K. , Auer, Paul L. , Reiner, Alexander P. , Ebert, Benjamin L. , Natarajan, Pradeep , Uddin, Md M , Niroula, Abhishek , Weinstock, Joshua S , Bhattacharya, Romit , Ebert, Benjamin L , Natarajan, Pradeep , Yu, Zhi , Zekavat, Seyedeh M , Truong, Buu Minh Thanh , Haidermota, Sara , Honigberg, Michael C. , Zhang, Martin Jinye , Dron, Jacqueline S. , Heimlich, Jonathan Brett , Sankaran, Vijay G. , Griffin, Gabriel K. , Gibson, Christopher James , Wilson, Peter W.F. , Genovese, Giulio , Xu, Yaomin , Savona, Michael R. , Raffield, Laura M. , Arnett, Donna K. , Konkle, Barbara A. , Peyser, Patricia A. , Smith, Jennifer A. , Mathias, Rasika A. , Andrade, Mariza de , Darbar, Dawood , He, Jiang , Blangero, John , Weiss, Scott T. , Custer, Brian , Minster, Ryan L , Viali, Satupaitea , Mitchell, Braxton D. , Palmer, Nicholette D , Freedman, Barry I. , Bowden, Donald W. , Albert, Christine M. , Smith, Nicholas, Tracy, Russell P. , Psaty, Bruce M. , Taylor, Kent D. , Rotter, Jerome I. , Boerwinkle, Eric , Vasan, Ramachandran S. , Lubitz, Steven A. , Ellinor, Patrick T. , Loos, Ruth J. F. , Yun, Jeong H. , Cho, Michael H. , Abecasis, Gonçalo R. , Kooperberg, Charles , Reiner, Alex P. , Jaiswal, Siddhartha , Bick, Alexander G.

No container title available | July 31, 2022 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1101/2022.07.29.22278015 Get It

Abstract With aging, somatic mutations in hematopoietic stem and progenitor cells (HSPC) can give rise to clonal hematopoiesis of indeterminate potential (CHIP), a premalignant state associated with diverse age-related diseases. Here we report the largest multi-ancestry genome-wide analysis of CHIP to date (N = 1,018,305), including individuals of African (N = 85,978), Admixed American (N = 191,371), East Asian (N = 13,532), European (N = 694,015), and South Asian (N = 13,193) ancestry. Multi-ancestry meta-analyses identified 72 genome-wide significant loci, including 44 novel associations implicating genes such as AFF1 , ATF7IP , ATP8B4 , BCL2 , CEBPA , CYRIA , DNM2 , ELF1 , NKX2-3 , PIK3CB , PRDM16 , RPN1 , TERC , and TRIM4 . Notably, variants at MECOM and PHF20L1 showed opposite allelic effects between DNMT3A - and non- DNMT3A -driven CHIP, highlighting driver-specific germline influences. Implicated loci converge on pathways regulating telomere maintenance, cell-cycle control, hematopoietic transcription, DNA damage response and immune signaling. These findings support a model in which germline variation both expands the HSPC pool and biases clonal selection in a driver-dependent manner, providing a mechanistic basis for inter-individual heterogeneity in CHIP. Phenome-wide association analyses further linked CHIP to hematologic, neoplastic, and circulatory traits, with enrichment across hematopoietic and non-hematopoietic cell types. Together, this work expands the genomic and phenomic landscape of CHIP and reveals germline–somatic interactions that shape clonal evolution during aging.
Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential
Nakao, Tetsushi , Bick, Alexander G. , Taub, Margaret A. , Uddin, Md Mesbah , Niroula, Abhishek , Carty, Cara L. , Lane, John , Honigberg, Michael C. , Weinstock, Joshua S. , Pampana, Akhil , Griffin, Gabriel K. , Bhattacharya, Romit , Assimes, Themistocles L. , Emery, Leslie S. , Wong, Quenna , Broome, Jai , Laurie, Cecelia , Khan, Alyna , Smith, Albert V. , Blackwell, Thomas W. , Nelson, Christopher P. , Yoneda, Zachary T. , Peralta, Juan M. , Bowden, Donald W. , Irvin, Marguerite R. , Boorgula, Meher Preethi, Zhao, Wei , Yanek, Lisa R. , Roden, Dan M. , Reupena, Muagututi‘a Sefuiva , DeMeo, Dawn L. , Kelly, Shannon , Musani, Solomon K., Bis, Joshua C. , Lloyd‐Jones, Donald M. , Peyser, Patricia A. , Qiao, Dandi , Tiwari, Hemant K., Smith, Jennifer A. , Smith, Nicholas L. , Kelly, Tanika N. , Hidalgo, Bertha , Weeks, Daniel E. , Group, The Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA), Deka, Ranjan , Naseri, Take, Fuentes, Lisa de las , Raffield, Laura M. , Morrison, Alanna C. , Vries, Paul S. de , Shoemaker, M. Benjamin , Palmer, Nicholette D. , Barnes, Kathleen C. , Redline, Susan , Kardia, Sharon L.R., Becker, Lewis C. , Heckbert, Susan R. , He, Jiang , Post, Wendy S. , Arnett, Donna K. , McGarvey, Stephen T. , Chen, Yii‐Der Ida , Kaplan, Robert C. , Meyers, Deborah A. , Fornage, Myriam , Boerwinkle, Eric , Loos, Ruth J. F. , Silverman, Edwin K. , Danesh, John , Samani, Nilesh J. , Jaiswal, Siddhartha , Ebert, Benjamin L. , Reiner, Alex P. , Mathias, Rasika A. , Do, Ron , Natarajan, Pradeep , Zhao, Wei , Zekavat, Seyedeh M , Uddin, Md M , Niroula, Abhishek , Lane, John , Honigberg, Michael C , Weinstock, Joshua S , Pampana, Akhil , Griffin, Gabriel K , Clarke, Shoa L , Bhattacharya, Romit , Assimes, Themistocles L , Emery, Leslie S , Stilp, Adrienne M , Wong, Quenna , Broome, Jai , Khan, Alyna T , Smith, Albert V , Codd, Veryan , Nelson, Christopher P , Yoneda, Zachary T , Peralta, Juan M , Yanek, Lisa R , Wiggins, Kerri L , Gu, C Charles , Peloso, Gina M , Roden, Dan M. , Hwu, Chii-Min , North, Kari E. , Bis, Joshua C , Lloyd-Jones, Donald M , Johnsen, Jill M , Preuss, Michael , Tracy, Russell P , Peyser, Patricia A , Qiao, Dandi , Curran, Joanne E , Freedman, Barry I , Chavan, Sameer , Smith, Jennifer A , Kelly, Tanika N , Hidalgo, Bertha , Weeks, Daniel E , Hawley, Nicola L , Minster, Ryan L , de las Fuentes, Lisa , Raffield, Laura M , Ballantyne, Christie M , Kenny, Eimear E , Rich, Stephen S , Whitsel, Eric A , Cho, Michael H , Palmer, Nicholette D , Mitchell, Braxton D , Shuldiner, Alan R , Redline, Susan , Heckbert, Susan R , He, Jiang , Post, Wendy , Arnett, Donna K , Vasan, Ramachandran S , Weiss, Scott T , McGarvey, Stephen T , Custer, Brian S , Correa, Adolfo , Manson, JoAnn E , Konkle, Barbara A , Loos, Ruth J F , Rotter, Jerome I , Silverman, Edwin K , Kooperberg, Charles , Samani, Nilesh J , Jaiswal, Siddhartha , Libby, Peter , Ellinor, Patrick T , Pankratz, Nathan , Ebert, Benjamin L , Mathias, Rasika A , Do, Ron , Natarajan, Pradeep , Morrison, Alanna C , Bick, Alexander G , Gibson, Christopher James , Clarke, Shoa L. , Codd, Veryan , Wiggins, Kerri L. , Hixson, James E. , Peloso, Gina M. , Tracy, Russell P. , Desai, Pinkal , Curran, Joanne E. , Freedman, Barry I. , Cupples, L. Adrienne , Group, The Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA), Naseri, Take K. , Ballantyne, Christie M. , Rich, Stephen S. , Cho, Michael H. , Pace, Betty S. , Blangero, John , Mitchell, Braxton D. , Shuldiner, Alan R. , Abecasis, Gonçalo R. , Vasan, Ramachandran S. , Darbar, Dawood , Weiss, Scott T. , Andrade, Mariza de , Custer, Brian , Psaty, Bruce M. , Manson, JoAnn E. , Konkle, Barbara A. , Rotter, Jerome I. , Kooperberg, Charles , Libby, Peter , Ellinor, Patrick T. , Pankratz, Nathan

Science Advances | April 6, 2022 | Volume: 8 | Issue: 14 | Pages: No page available

10.1126/sciadv.abl6579 Get It

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.
Abstract 2385: Investigation Of Aromatase Gene (CYP19A1) Variations In Stroke Patients
Dueker, Nicole , Reiner, Alex P. , Cheng, Yu‐Ching, Bookman, Ebony, Chen, Wei‐Min , Doheny, Kimberly F. , Jackson, Rebecca D. , Mirel, Daniel B., Kittner, Steven J. , Sale, Michèle M. , Worrall, Bradford B. , Wang, Liewei , Southerland, Andrew M. , Chen, Fang , Udren, Jenna I. , Kooperberg, Charles , Mitchell, Braxton D. , Rexrode, Kathryn M.

Stroke | March 20, 2022 | Volume: 43 | Issue: suppl_1 | Pages: No page available

10.1161/str.43.suppl_1.a2385 Get It

Introduction: Estrogens have been associated with risk of stroke in both men and women. Estradiol and estrone are synthesized from testosterone via the aromatase enzyme in both men and postmenopausal women. Genetic variation affecting function of the aromatase gene (CYP19A1) has been linked to elevated estradiol levels. We tested the hypothesis that these variants, as well as a modifying gene, are associated with ischemic stroke in three cohorts: the Vitamin Intervention for Stroke Prevention trial (VISP), Women’s Health Initiative (WHI), and Genetic Susceptibility to Early-Onset Stroke study (GEOS). Methods: Genomic data for individuals of European descent with ischemic stroke was compared against an equal number of controls: VISP (1723 cases - 65% men), WHI (436 cases - all postmenopausal women), GEOS (557 cases - all men age <55). Genotyping was funded through the Genomics and Randomized Trials Network (GARNET) and Gene Environment Association Studies (GENEVA) consortia. All cohorts used the Illumina Omni1-Quad chip for genotyping with imputation as needed. Eight candidate single nucleotide polymorphisms (SNPs) in CYP19A1 on chromosome 15 and an additional regulatory SNP in a modifier locus on chromosome 8 were chosen for analysis due to coding status or previous association with estradiol levels. Analyses were adjusted for age, hormone therapy use (women), and the top three principal components. Association results were determined as odds ratios for individual SNPs (effect allele = minor), with significance level of p<0.05. Results: GWAS results are tabulated. There were no significant differences in allele frequency for four SNPs in CYP19A1 among stroke patients and controls. The additional four SNPs were monomorphic in all three populations. The modifier gene SNP (rs1864729) was less common among young men with prior stroke in GEOS, but not men in VISP or in women. Conclusions: Aromatase genetic variation was not associated with risk of stroke in these three cohorts. One SNP that modifies aromatase function was less common among young, but not older men with stroke. Replication in other studies is necessary.
Abstract P2-09-01: Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes
Yadav, Siddhartha , Huang, Hongyan , Yao, Song, Vachon, Celine M. , Martínez, Elena, Lindströem, Sara, Haiman, Christopher A. , Gaudet, Mia M. , Auer, Paul, Goldgar, David E. , Nathanson, Katherine L. , Yadav, Siddhartha , Nathanson, Katherine L , Hu, Chunling , Boddicker, Nicholas , Polley, Eric C. , Hart, Steven N. , Gnanaolivu, Rohan , Na, Jie , Yao, Song , Vachon, Celine M. , Teras, Lauren R. , Taylor, Jack A. , Sandler, Dale P. , Palmer, Julie R. , Olson, Janet E. , Neuhausen, Susan L. , Marchand, Loı̈c Le , Kooperberg, Charles , Lacey, James V. , Bertrand, Kimberly A. , Bernstein, Leslie , Ambrosone, Christine B. , Weitzel, Jeffrey N. , Kraft, Peter , Domchek, Susan M. , Couch, Fergus J.

Cancer Research | March 8, 2022 | Volume: 82 | Issue: 4_Supplement | Pages: P2-09-01-P2-09-01

10.1158/1538-7445.sabcs21-p2-09-01 Get It

Abstract Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) &gt;4) for all clinical subtypes of breast cancer, but the risk was highest (OR&gt;8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR&gt;4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR&gt;4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer. Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-01.
Breast Cancer Screening Strategies for Women With ATM, CHEK2, and PALB2 Pathogenic Variants
Lowry, Kathryn P. , Geuzinge, H. Amarens , Stout, Natasha K. , Alagöz, Oğuzhan , Hampton, John M. , Koning, Harry J. de , Miglioretti, Diana L. , Ravesteyn, Nicolien T. van , Sprague, Brian L. , Tosteson, Anna N.A. , Weaver, Donald L. , Yaffe, Martin J. , Mandelblatt, Jeanne S. , Kurian, Allison W. , Auer, Paul L. , Berstein, Leslie, Carter, Brian D., Gaudet, Mia M. , Haiman, Christopher, Jacobs, Eric J. , John, Esther M. , Lindström, Sara , Martínez, Elena, Patel, Alpa V. , Reid, Sonya , Taylor, Jack A. , Teras, Lauren R., Vachon, Celine M. , Yao, Song, Ziogas, Argyrios, Goldgar, David E. , Chen, Chen , Chen, C , Miglioretti, Diana L , John, Esther M , Taylor, Jack A , de Koning, Harry J , Kurian, Allison W , Kerlikowske, Karla , Schechter, Clyde B. , Trentham‐Dietz, Amy , Yeh, Jennifer M. , Couch, Fergus J. , Hu, Chunling , Kraft, Peter , Polley, Eric C. , Robson, Mark E. , Hart, Steven N. , Nathanson, Katherine L. , Domchek, Susan M. , Ambrosone, Christine B. , Anton‐Culver, Hoda , Bandera, Elisa V. , Bertrand, Kimberly A. , Burnside, Elizabeth S. , Eliassen, A. Heather , Hodge, James M. , Hunter, David J. , Kooperberg, Charles , Lacey, James V. , Marchand, Loı̈c Le , Ma, Huiyan , Neuhausen, Susan L. , Newcomb, Polly A. , O’Brien, Katie M. , Olson, Janet E. , Ong, Irene M. , Pal, Tuya , Palmer, Julie R. , Rosenberg, Lynn A. , Sandler, Dale P. , Tamimi, Rulla M. , Teras, Lauren R. , Vachon, Celine M. , Weinberg, Clarice R. , Yadav, Siddhartha , Yao, Song , Weitzel, Jeffrey N.

JAMA Oncology | February 17, 2022 | Volume: 8 | Issue: 4 | Pages: 587

10.1001/jamaoncol.2021.6204 Get It

Risk of Late-Onset Breast Cancer in Genetically Predisposed Women
Boddicker, Nicholas , Weitzel, Jeffrey N. , Kraft, Peter , Nathanson, Katherine L. , Goldgar, David E. , Na, Jie , Huang, Hongyan , Larson, Nicole L. , Yussuf, Amal , Vachon, Celine M. , Taylor, Jack A. , Scott, Christopher E., Pesaran, Tina , Patel, Alpa V. , Ong, Irene M. , Martínez, Elena, Ma, Huiyan , Lindström, Sara , Hodge, James M. , Haiman, Christopher A. , Gaudet, Mia M. , Gao, Chi , LaDuca, Holly , Dolinsky, Jill S. , Carter, Brian D., Auer, Paul, Yadav, Siddhartha , Chen, Chen , Boddicker, Nicholas J , Hu, Chunling , Weitzel, Jeffrey N , Kraft, Peter , Nathanson, Katherine L , Goldgar, David E , Na, Jie , Gnanaolivu, Rohan D., Yussuf, Amal , Yao, Song , Vachon, Celine M. , Trentham-Dietz, Amy , Teras, Lauren R , Taylor, Jack A , Sandler, Dale P , Pesaran, Tina , Palmer, Julie R , Ong, Irene M , Neuhausen, Susan L. , Martı́nez, Marı́a Elena , Karam, Rachid , Hodge, James M , Gaudet, Mia M , Gao, Chi , LaDuca, Holly , Dolinsky, Jill S , Burnside, Elizabeth S , Bertrand, Kimberly A , Bernstein, Leslie , Ambrosone, Christine B , Yadav, Siddhartha , Hart, Steven N , Polley, Eric C , Domchek, Susan M , Couch, Fergus J. , Chen, C , Hu, Chunling , Gnanaolivu, Rohan , Yao, Song , Trentham‐Dietz, Amy , Teras, Lauren R. , Sandler, Dale P. , Palmer, Julie R. , Olson, Janet E. , O’Brien, Katie M. , Marchand, Loı̈c Le , Kooperberg, Charles , Karam, Rachid , Hunter, David J. , Lacey, James V. , Chao, Elizabeth , Burnside, Elizabeth S. , Bertrand, Kimberly A. , Bernstein, Leslie , Ambrosone, Christine B. , Hart, Steven N. , Polley, Eric C. , Domchek, Susan M. , Couch, Fergus J.

Journal of Clinical Oncology | July 22, 2021 | Volume: 39 | Issue: 31 | Pages: 3430-3440

10.1200/jco.21.00531 Get It

PURPOSE The prevalence of germline pathogenic variants (PVs) in established breast cancer predisposition genes in women in the general population over age 65 years is not well-defined. However, testing guidelines suggest that women diagnosed with breast cancer over age 65 years might have < 2.5% likelihood of a PV in a high-penetrance gene. This study aimed to establish the frequency of PVs and remaining risks of breast cancer for each gene in women over age 65 years. METHODS A total of 26,707 women over age 65 years from population-based studies (51.5% with breast cancer and 48.5% unaffected) were tested for PVs in germline predisposition gene. Frequencies of PVs and associations between PVs in each gene and breast cancer were assessed, and remaining lifetime breast cancer risks were estimated for non-Hispanic White women with PVs. RESULTS The frequency of PVs in predisposition genes was 3.18% for women with breast cancer and 1.48% for unaffected women over age 65 years. PVs in BRCA1, BRCA2, and PALB2 were found in 3.42% of women diagnosed with estrogen receptor (ER)–negative, 1.0% with ER-positive, and 3.01% with triple-negative breast cancer. Frequencies of PVs were lower among women with no first-degree relatives with breast cancer. PVs in CHEK2, PALB2, BRCA2, and BRCA1 were associated with increased risks (odds ratio = 2.9-4.0) of breast cancer. Remaining lifetime risks of breast cancer were ≥ 15% for those with PVs in BRCA1, BRCA2, and PALB2. CONCLUSION This study suggests that all women diagnosed with triple-negative breast cancer or ER-negative breast cancer should receive genetic testing and that women over age 65 years with BRCA1 and BRCA2 PVs and perhaps with PALB2 and CHEK2 PVs should be considered for magnetic resonance imaging screening.
Abstract P252: Generalization and Fine Mapping of PR Interval Loci in Hispanics: The Population Architecture Using Genomics and Epidemiology (PAGE) Study
Seyerle, Amanda A. , Wassel, Christina L. , Carty, Cara L. , Fornage, Myriam , Duggan, David , Gong, Jian , Heckbert, Susan R. , Hindorff, Lucia A. , Jeff, Janina M., Okin, Peter M., Shohet, Ralph V. , Sotoodehnia, Nona, Wu, Chunyuan , Bielinski, Suzette J. , Buyske, Steven , Carnethon, Mercedes R. , Crawford, Dana C. , Lloyd‐Jones, Donald M. , Pérez, Marco , Psaty, Bruce M. , Rotter, Jerome I. , Shah, Sanjiv J , Soliman, Elsayed Z. , Kooperberg, Charles , Avery, Christy L.

Circulation | July 3, 2021 | Volume: 129 | Issue: suppl_1 | Pages: No page available

10.1161/circ.129.suppl_1.p252 Get It

PR interval (PR) prolongation is a predictor of atrial fibrillation, a common cardiac arrhythmia, and is an established risk factor for pacemaker implantation, heart failure, stroke, and all-cause mortality. Previous genome-wide association studies in European (EU) and African (AA) descent populations have identified multiple loci associated with PR. However, it is unclear whether these loci are relevant in other racial groups, including Hispanic/Latinos (HL). Extending studies to include admixed populations such as HL also provides the potential to narrow regions associated with PR and identify population specific variants. Therefore, we evaluated 1,135 SNPs from four previously identified PR loci ( SCN5A, SCN10A, CAV1-CAV2, and TBX5-TBX3 ), fine-mapped on the Illumina Metabochip for association with PR. Associations were examined using linear regression assuming an additive genetic model and adjusting for global ancestry and clinical covariates (age, sex, RR interval, body mass index, height, systolic blood pressure) in 11,800 HL participants from participating studies of the Population Architecture using Genomics and Epidemiology (PAGE) consortia. Three of the four loci ( SCN5A, SCN10A, and CAV1-CAV2 ) generalized to HL populations ( P <7.1E-4 based on the number of SNPs correlated at r 2 >0.2 with EU-identified index SNPs). At each of these loci, we identified SNPs with stronger evidence of association with PR than the EU-identified index SNP when examined in the HL population ( SCN5A : rs7374540; SCN10A : rs6801957; CAV-CAV2 : rs717957). Conditional analyses also identified two additional independent SNPs at each of the three generalized loci ( SCN5A : rs3796387, rs9861242; SCN10A : rs10428132, rs7433723; CAV1-CAV2 : rs3801995, rs3807994), representing potential secondary signals. Furthermore, linkage disequilibrium (LD) patterns in Hispanics enabled the narrowing of the regions flanking the EU-identified index SNPs. For example, at the CAV1-CAV2 locus, HL LD patterns indicated that seven SNPs were in LD with rs3807989, the EU-identified index SNP, compared to 17 SNPs that were in LD with rs3807989 when applying EU LD patterns, reducing the size of the region by 71 kilobases. Finally, we examined evidence for population specific signals outside of the specific regions identified in EU populations which were associated with PR in Hispanics by focusing on SNPs uncorrelated with the EU index signals. At all four loci, multiple SNPs had evidence of association independent of the signals examined based on EU results. In conclusion, the same genetic loci that influence PR in European descent populations are also important in Hispanic populations, although we detected evidence for population specific SNPs. These results emphasize the importance of examining genetic associations in diverse populations in order to narrow the genomic interval for future functional interrogation.
Abstract P212: Combined Analysis of Longitudinal Cohorts With Case-only Sample Sets for Detecting Genetic Effects on Venous Thromboembolism in Topmed
Seyerle, Amanda A. , Laurie, Cecelia , Smith, Nicholas L. , McKnight, Barbara, Laurie, Cathy C. , Coombes, Brandon J. , Sofer, Tamar , Tang, Weihong , Andrade, Mariza de , Kooperberg, Charles , Pankow, James S. , Rice, Kenneth

Circulation | July 2, 2021 | Volume: 137 | Issue: suppl_1 | Pages: No page available

10.1161/circ.137.suppl_1.p212 Get It

Background: The Trans-Omics for Precision Medicine (TOPMed) program is performing whole-genome sequencing across multiple studies, including longitudinal cohorts, case-control, and case-only sample sets. Detecting the effects of low frequency variants requires large sample sizes, which can only be achieved by combining data across diverse study designs, including matching of case-only sample sets with controls from other studies. Here we present a strategy for combined analysis of venous thromboembolism (VTE) case status in 3 longitudinal cohorts and 3 case-only sample sets, in the context of whole-genome association studies. Methods: For each cohort study, we sampled ‘pure’ controls (without replacement) from the risk set of each incident case, within strata defined by sex, ancestry and birth-cohort. Pure controls had no event throughout their period of observation. A case’s risk set was defined as controls with no prior VTE history and under observation through an age at least as old as the case. For case-only sample sets, controls for each case were sampled from a cohort study, using the same risk set definition. Because of limited overlap in birth years between the cohort studies and the case-only sample sets, this matching was done within strata defined only by sex and ancestry group. Mixed model logistic regression will be used to account for relatedness as a random effect. Although conditional logistic regression is not practical for whole-genome association studies, case-control matching is implicitly recognized by a fixed effect for age-at-event for each matched set (1 case and >=1 matched controls). Additional fixed effects will include sample set and sex. We will also adjust for variations in case-control ratio among the matched sets. Results: In two cohort studies, we matched 1,231 cases to 4,820 controls (overall ratio = 1:3.9); only 500 controls and 5 cases could not be matched. For the case-only sample sets we matched 2,141 cases to 2,780 controls from one cohort study (overall ratio = 1:1.3); zero controls and only 14 cases could not be matched. Conclusions: We were successfully able to match nearly all cases to controls, and more than 90% of controls were also matched. By matching controls to cases based on age at event, we can account for the different risk of VTE by age clusters. Although this strategy does not provide an asymptotically unbiased estimated of the hazard ratio, compared to classical risk set sampling, it uses a large portion of the available data, it provides odds ratio estimates yielding the correct sign of association, and it reduces the potential influence of resampling subjects with rare variants. This strategy also enables combined analysis of multiple studies with different designs.
Genetic architecture of smoking: Evaluating rare variant contribution from deep whole-genome sequencing of up to 26,000 individuals
Jang, Seon-Kyeong , Arnett, Donna K. , Becker, Diane M. , Bis, Joshua C. , Bleecker, Eugene R., Fingerlin, Tasha E. , Haessler, Jeffrey, Heckbert, Susan R. , Hokanson, John E. , Judy, Renae , Justice, Anne E. , Kaplan, Robert C. , Kim, Wonji , Gladwin, Mark T. , Melander, Olle , Meyers, Deborah A. , Peljto, Anna L. , Qiao, Dandi , Reed, Robert M. , Reiner, Alex P. , Silverman, Edwin K. , Smith, Nicholas L. , Smith, Gustav, Smith, Albert V. , Tang, Weihong, Gordeuk, Victor R. , Yanek, Lisa R. , Yang, Ivana V. , Young, Kendra A. , Vrieze, Scott , Martin, Lisa , Smith, Albert V , Arnett, Donna K , Evans, Luke M. , Fialkowski, Allison , Blangero, John , Brody, Jennifer A. , Cupples, L. Adrienne , Damrauer, Scott M , David, Sean P. , Andrade, Mariza de , Gharib, Sina A. , Glahn, David C , Hwang, Shih‐Jen , Hyman, Matthew Craig , Kooperberg, Charles , Levy, Dan , Loos, Ruth J. F. , Manichaikul, Ani , Martin, Lisa W. , Nouraie, Mehdi , North, Kari E. , Oelsner, Elizabeth C. , Preuss, Michael , Psaty, Bruce M. , Rader, Daniel J , Rich, Stephen S. , Rotter, Jerome I. , Schwartz, David A. , Shadyab, Aladdin H , Taylor, Kent D. , Vasan, Ramachandran S. , Wang, Zhe , Wiggins, Kerri L. , Young, Kristin L. , Zhang, Yingze , Liu, Dajiang J. , Keller, Matthew C.

No container title available | May 6, 2021 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-475149/v1 Get It

Abstract Background Across complex traits, common variants explain only a modest amount of variance, with SNP-heritability consistently below heritability estimates from close relatives. Here, we examined the contribution of rare variant to tobacco use risk in up to 26,000 individuals of European ancestry in the Trans-Omics for Precision Medicine (TOPMed) program with whole genome sequence (WGS;~30X coverage).Method We grouped about 35 million genetic variants by their minor allele frequencies (MAF) and linkage disequilibrium (LD) and estimated SNP-heritability for age of smoking initiation (N = 14,747), cigarettes smoked per day (N = 15,425), smoking cessation (N = 17,871) and initiation (N = 26,340) using linear mixed model. Rare variant population structure is detected and adjusted for by permutation procedure. We estimated an upper bound for narrow-sense heritability for tobacco use using available pedigrees consisting of close relatives in TOPMed.Results Rare variants with MAF 0.1–0.01%, mostly from non-protein altering region, accounted for 26% of variation in age of initiation and 15% for cessation. Follow-up analysis indicated that about one-third of these rare variants contribtion is potentially confounded with rare variants structure even after adjusting for principal components. After further conservative adjustment of population structure, we estimated SNP-based heritability to be 0.21 (SE = 0.08) for age of initiation, 0.15 (0.06) for cigarettes per day, 0.21 (0.09) for cessation, and 0.24 (0.07) for initiation, 1.8–4.5 times higher than previous SNP-based estimates. Our pedigree-based upper-bound for SNP-based heritability ranged from 0.18–0.35.Conclusion The substantial contribution of rare variants for several smoking phenotypes sheds light on the missing heritability and genetic etiology of tobacco use. It also informs fine-mapping strategies since the majority of the rare variant contribution was located in non-coding regulatory regions.