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1. Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author

Kentistou, Katherine, Kaisinger, Lena, Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin, Liu, Xiaoxi, Busch, Alexander, Helgason, Hannes, Thompson, Deborah, Santoni, Federico, Petricek, Konstantin, Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel, Bratland, Eirik, Lin, Kuang, Gardner, Eugene, Zhao, Yajie, Jia, Raina, Terao, Chikashi, Riggan, Marjorie, Bolla, Manjeet, Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan, Broer, Linda, Campbell, Archie, Chasman, Daniel, Cousminer, Diana, Franceschini, Nora, Franke, Lude, Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter, Kamatani, Yoichiro, Karlsson, Robert, Luan, Jianan, Lunetta, Kathryn, Mägi, Reedik, Mangino, Massimo, Medland, Sarah, Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria, Polašek, Ozren, Porcu, Eleonora, Ring, Susan, Sala, Cinzia, Smith, Albert, Tanaka, Toshiko, van der Most, Peter, Vitart, Veronique, Wang, Carol, Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas, Andrulis, Irene, Anton-Culver, Hoda, Antoniou, Antonis, Auer, Paul, Barnes, Catriona, Beckmann, Matthias, Berrington de Gonzalez, Amy, Bogdanova, Natalia, Bojesen, Stig, Brenner, Hermann, Buring, Julie, Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus, Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary, Demerath, Ellen, Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison, Dwek, Miriam, Eriksson, Johan, Fasching, Peter, Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José, González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher, Hall, Per, Hamann, Ute, and Hakonarson, Hakon

Subjects
Humans, Female, Menarche, Puberty, Gene Frequency, Animals, Multifactorial Inheritance, Mice, Genome-Wide Association Study, Adolescent, Puberty, Precocious, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled, Puberty, Delayed, Child
Abstract

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.

Published
2024

2. Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate

Author

Mack, Taralynn M, Raddatz, Michael A, Pershad, Yash, Nachun, Daniel C, Taylor, Kent D, Guo, Xiuqing, Shuldiner, Alan R, O’Connell, Jeffrey R, Kenny, Eimear E, Loos, Ruth JF, Redline, Susan, Cade, Brian E, Psaty, Bruce M, Bis, Joshua C, Brody, Jennifer A, Silverman, Edwin K, Yun, Jeong H, Cho, Michael H, DeMeo, Dawn L, Levy, Daniel, Johnson, Andrew D, Mathias, Rasika A, Yanek, Lisa R, Heckbert, Susan R, Smith, Nicholas L, Wiggins, Kerri L, Raffield, Laura M, Carson, April P, Rotter, Jerome I, Rich, Stephen S, Manichaikul, Ani W, Gu, C Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M Benjamin, Roden, Dan M, Kooperberg, Charles, Auer, Paul L, Desai, Pinkal, Blackwell, Thomas W, Smith, Albert V, Reiner, Alexander P, Jaiswal, Siddhartha, Weinstock, Joshua S, and Bick, Alexander G

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Hematology, Genetics, Biotechnology, Aging, Human Genome, Stem Cell Research, Precision Medicine, Aetiology, 2.1 Biological and endogenous factors, Cancer, Good Health and Well Being, Clinical sciences
Abstract

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Published
2024

3. Determinants of mosaic chromosomal alteration fitness.

Author

Pershad, Yash, Mack, Taralynn, Poisner, Hannah, Jakubek, Yasminka, Stilp, Adrienne, Mitchell, Braxton, Lewis, Joshua, Boerwinkle, Eric, Loos, Ruth, Chami, Nathalie, Wang, Zhe, Barnes, Kathleen, Pankratz, Nathan, Fornage, Myriam, Redline, Susan, Psaty, Bruce, Bis, Joshua, Shojaie, Ali, Silverman, Edwin, Cho, Michael, Yun, Jeong, DeMeo, Dawn, Levy, Daniel, Johnson, Andrew, Mathias, Rasika, Taub, Margaret, Arnett, Donna, North, Kari, Raffield, Laura, Carson, April, Doyle, Margaret, Rich, Stephen, Guo, Xiuqing, Cox, Nancy, Roden, Dan, Franceschini, Nora, Desai, Pinkal, Reiner, Alex, Auer, Paul, Scheet, Paul, Jaiswal, Siddhartha, Weinstock, Joshua, Bick, Alexander, and Rotter, Jerome

Subjects
Humans, Mosaicism, Chromosome Aberrations, Clonal Hematopoiesis, Male, Female, Genome-Wide Association Study, Janus Kinase 2, Telomerase, Loss of Heterozygosity, Cross-Sectional Studies, Mutation, Middle Aged, Hematopoietic Stem Cells, Polymorphism, Single Nucleotide, Aged
Abstract

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

Published
2024

4. Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes

Author

Keener, Rebecca, Chhetri, Surya B, Connelly, Carla J, Taub, Margaret A, Conomos, Matthew P, Weinstock, Joshua, Ni, Bohan, Strober, Benjamin, Aslibekyan, Stella, Auer, Paul L, Barwick, Lucas, Becker, Lewis C, Blangero, John, Bleecker, Eugene R, Brody, Jennifer A, Cade, Brian E, Celedon, Juan C, Chang, Yi-Cheng, Cupples, L Adrienne, Custer, Brian, Freedman, Barry I, Gladwin, Mark T, Heckbert, Susan R, Hou, Lifang, Irvin, Marguerite R, Isasi, Carmen R, Johnsen, Jill M, Kenny, Eimear E, Kooperberg, Charles, Minster, Ryan L, Naseri, Take, Viali, Satupa’itea, Nekhai, Sergei, Pankratz, Nathan, Peyser, Patricia A, Taylor, Kent D, Telen, Marilyn J, Wu, Baojun, Yanek, Lisa R, Yang, Ivana V, Albert, Christine, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Bis, Joshua C, Blackwell, Thomas W, Boerwinkle, Eric, Burchard, Esteban G, Carson, April P, Chen, Zhanghua, Chen, Yii-Der Ida, Darbar, Dawood, de Andrade, Mariza, Ellinor, Patrick T, Fornage, Myriam, Gelb, Bruce D, Gilliland, Frank D, He, Jiang, Islam, Talat, Kaab, Stefan, Kardia, Sharon LR, Kelly, Shannon, Konkle, Barbara A, Kumar, Rajesh, Loos, Ruth JF, Martinez, Fernando D, McGarvey, Stephen T, Meyers, Deborah A, Mitchell, Braxton D, Montgomery, Courtney G, North, Kari E, Palmer, Nicholette D, Peralta, Juan M, Raby, Benjamin A, Redline, Susan, Rich, Stephen S, Roden, Dan, Rotter, Jerome I, Ruczinski, Ingo, Schwartz, David, Sciurba, Frank, Shoemaker, M Benjamin, Silverman, Edwin K, Sinner, Moritz F, Smith, Nicholas L, Smith, Albert V, Tiwari, Hemant K, Vasan, Ramachandran S, Weiss, Scott T, Williams, L Keoki, Zhang, Yingze, Ziv, Elad, Raffield, Laura M, Reiner, Alexander P, Arvanitis, Marios, Greider, Carol W, Mathias, Rasika A, and Battle, Alexis

Subjects
Biological Sciences, Genetics, Human Genome, Clinical Research, Underpinning research, 2.1 Biological and endogenous factors, Aetiology, 1.1 Normal biological development and functioning, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group, K562 Cells, Telomere, Humans, Gene Expression Regulation, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Telomere Homeostasis, CRISPR-Cas Systems
Abstract

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Published
2024

5. Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate

Author

Mack, Taralynn M., Raddatz, Michael A., Pershad, Yash, Nachun, Daniel C., Taylor, Kent D., Guo, Xiuqing, Shuldiner, Alan R., O’Connell, Jeffrey R., Kenny, Eimear E., Loos, Ruth J. F., Redline, Susan, Cade, Brian E., Psaty, Bruce M., Bis, Joshua C., Brody, Jennifer A., Silverman, Edwin K., Yun, Jeong H., Cho, Michael H., DeMeo, Dawn L., Levy, Daniel, Johnson, Andrew D., Mathias, Rasika A., Yanek, Lisa R., Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Raffield, Laura M., Carson, April P., Rotter, Jerome I., Rich, Stephen S., Manichaikul, Ani W., Gu, C. Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M. Benjamin, Roden, Dan M., Kooperberg, Charles, Auer, Paul L., Desai, Pinkal, Blackwell, Thomas W., Smith, Albert V., Reiner, Alexander P., Jaiswal, Siddhartha, Weinstock, Joshua S., and Bick, Alexander G.

Published
2024
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6. Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Author

Jakubek, Yasminka, Zhou, Ying, Stilp, Adrienne, Bacon, Jason, Wong, Justin, Ozcan, Zuhal, Arnett, Donna, Barnes, Kathleen, Bis, Joshua, Boerwinkle, Eric, Brody, Jennifer, Carson, April, Chasman, Daniel, Chen, Jiawen, Cho, Michael, Conomos, Matthew, Cox, Nancy, Doyle, Margaret, Fornage, Myriam, Guo, Xiuqing, Kardia, Sharon, Lewis, Joshua, Loos, Ruth, Ma, Xiaolong, Machiela, Mitchell, Mack, Taralynn, Mathias, Rasika, Mitchell, Braxton, Mychaleckyj, Josyf, North, Kari, Pankratz, Nathan, Peyser, Patricia, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Vasan, Ramachandran, Redline, Susan, Rich, Stephen, Silverman, Edwin, Smith, Jennifer, Smith, Aaron, Taub, Margaret, Taylor, Kent, Yun, Jeong, Li, Yun, Desai, Pinkal, Bick, Alexander, Reiner, Alexander, Scheet, Paul, Auer, Paul, and Rotter, Jerome

Subjects
Humans, Black People, Genome-Wide Association Study, Hispanic or Latino, Precision Medicine, Mosaicism, Genome, Human
Abstract

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

Published
2023

7. Publisher Correction: Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Author

Kentistou, Katherine A., Kaisinger, Lena R., Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin G., Liu, Xiaoxi, Busch, Alexander S., Helgason, Hannes, Thompson, Deborah J., Santoni, Federico, Petricek, Konstantin M., Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel F., Bratland, Eirik, Lin, Kuang, Gardner, Eugene J., Zhao, Yajie, Jia, Raina Y., Terao, Chikashi, Riggan, Marjorie J., Bolla, Manjeet K., Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan P., Broer, Linda, Campbell, Archie, Chasman, Daniel I., Cousminer, Diana L., Franceschini, Nora, Franke, Lude H., Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter K., Kamatani, Yoichiro, Karlsson, Robert, Luan, Jian’an, Lunetta, Kathryn L., Mägi, Reedik, Mangino, Massimo, Medland, Sarah E., Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria Pina, Polašek, Ozren, Porcu, Eleonora, Ring, Susan M., Sala, Cinzia, Smith, Albert V., Tanaka, Toshiko, van der Most, Peter J., Vitart, Veronique, Wang, Carol A., Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antoniou, Antonis C., Auer, Paul L., Barnes, Catriona L. K., Beckmann, Matthias W., Berrington de Gonzalez, Amy, Bogdanova, Natalia V., Bojesen, Stig E., Brenner, Hermann, Buring, Julie E., Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus J., Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary B., Demerath, Ellen W., Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison M., Dwek, Miriam, Eriksson, Johan G., Fasching, Peter A., Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A., González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher A., Hall, Per, Hamann, Ute, Hakonarson, Hakon, Hart, Roger J., Hickey, Martha, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Hottenga, Jouke-Jan, Hu, Frank B., Huebner, Hanna, Hunter, David J., Jernström, Helena, John, Esther M., Karasik, David, Khusnutdinova, Elza K., Kristensen, Vessela N., Lacey, James V., Lambrechts, Diether, Launer, Lenore J., Lind, Penelope A., Lindblom, Annika, Magnusson, Patrik K. E., Mannermaa, Arto, McCarthy, Mark I., Meitinger, Thomas, Menni, Cristina, Michailidou, Kyriaki, Millwood, Iona Y., Milne, Roger L., Montgomery, Grant W., Nevanlinna, Heli, Nolte, Ilja M., Nyholt, Dale R., Obi, Nadia, O’Brien, Katie M., Offit, Kenneth, Oldehinkel, Albertine J., Ostrowski, Sisse R., Palotie, Aarno, Pedersen, Ole B., Peters, Annette, Pianigiani, Giulia, Plaseska-Karanfilska, Dijana, Pouta, Anneli, Pozarickij, Alfred, Radice, Paolo, Rennert, Gad, Rosendaal, Frits R., Ruggiero, Daniela, Saloustros, Emmanouil, Sandler, Dale P., Schipf, Sabine, Schmidt, Carsten O., Schmidt, Marjanka K., Small, Kerrin, Spedicati, Beatrice, Stampfer, Meir, Stone, Jennifer, Tamimi, Rulla M., Teras, Lauren R., Tikkanen, Emmi, Turman, Constance, Vachon, Celine M., Wang, Qin, Winqvist, Robert, Wolk, Alicja, Zemel, Babette S., Zheng, Wei, van Dijk, Ko W., Alizadeh, Behrooz Z., Bandinelli, Stefania, Boerwinkle, Eric, Boomsma, Dorret I., Ciullo, Marina, Chenevix-Trench, Georgia, Cucca, Francesco, Esko, Tõnu, Gieger, Christian, Grant, Struan F. A., Gudnason, Vilmundur, Hayward, Caroline, Kolčić, Ivana, Kraft, Peter, Lawlor, Deborah A., Martin, Nicholas G., Nøhr, Ellen A., Pedersen, Nancy L., Pennell, Craig E., Ridker, Paul M., Robino, Antonietta, Snieder, Harold, Sovio, Ulla, Spector, Tim D., Stöckl, Doris, Sudlow, Cathie, Timpson, Nic J., Toniolo, Daniela, Uitterlinden, André, Ulivi, Sheila, Völzke, Henry, Wareham, Nicholas J., Widen, Elisabeth, Wilson, James F., Pharoah, Paul D. P., Li, Liming, Easton, Douglas F., Njølstad, Pål R., Sulem, Patrick, Murabito, Joanne M., Murray, Anna, Manousaki, Despoina, Juul, Anders, Erikstrup, Christian, Stefansson, Kari, Horikoshi, Momoko, Chen, Zhengming, Farooqi, I. Sadaf, Pitteloud, Nelly, Johansson, Stefan, Day, Felix R., Perry, John R. B., and Ong, Ken K.

Published
2024
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10. Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival

Author

Lopes Cardozo, Josephine MN, Andrulis, Irene L, Bojesen, Stig E, Dörk, Thilo, Eccles, Diana M, Fasching, Peter A, Hooning, Maartje J, Keeman, Renske, Nevanlinna, Heli, Rutgers, Emiel JT, Easton, Douglas F, Hall, Per, Pharoah, Paul DP, van 't Veer, Laura J, Schmidt, Marjanka K, Ahearn, Thomas U, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Augustinsson, Annelie, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bolla, Manjeet K, Bonanni, Bernardo, Boyle, Terry, Brenner, Hermann, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Camp, Nicola J, Canzian, Federico, Cardoso, Fatima, Castelao, Jose E, Cessna, Melissa H, Chan, Tsun L, Chang-Claude, Jenny, Chenevix-Trench, Georgia, Choi, Ji-Yeob, Colonna, Sarah V, Copson, Ellen, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Drukker, Caroline A, Dunning, Alison M, Dwek, Miriam, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Genkinger, Jeanine, Giles, Graham G, González-Neira, Anna, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Hartman, Mikael, Heemskerk-Gerritsen, Bernadette AM, Hein, Alexander, Ho, Weang-Kee, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ito, Hidemi, Jakubowska, Anna, Jernström, Helena, John, Esther M, Johnson, Nichola, Jones, Michael E, Joseph, Vijai, Kaaks, Rudolf, Kang, Daehee, Kim, Sung-Won, Kitahara, Cari M, Koppert, Linetta B, Kosma, Veli-Matti, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, and Koutros, Stella

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Breast Cancer, Cancer, Good Health and Well Being, Female, Humans, Breast Neoplasms, Risk Factors, Prognosis, Proportional Hazards Models, Breast, Breast Cancer Association Consortium and MINDACT Collaborators, Clinical Sciences, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

PurposeA polygenic risk score (PRS) consisting of 313 common genetic variants (PRS313) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS313 with clinicopathologic characteristics of, and survival following, breast cancer.MethodsWomen with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS313 (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment.ResultsThe PRS313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS313 was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent.ConclusionAn increased PRS313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS313 as increasing PRS313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.

Published
2023

12. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J. F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A, Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L, Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C, Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S, Pleiness, Jacob, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D. C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Hui-Heng Sheu, Wayne, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent D., Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T, Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Lindstrom, Sara, Wang, Lu, Smith, Erin N., Gordon, William, van Hylckama Vlieg, Astrid, Brody, Jennifer A., Pattee, Jack W., Haessler, Jeffrey, Brumpton, Ben M., Chasman, Daniel I., Suchon, Pierre, Chen, Ming-Huei, Turman, Constance, Germain, Marine, Wiggins, Kerri L., MacDonald, James, Braekkan, Sigrid K., Armasu, Sebastian M., Pankratz, Nathan, Jackson, Rabecca D., Nielsen, Jonas B., Giulianini, Franco, Puurunen, Marja K., Ibrahim, Manal, Heckbert, Susan R., Bammler, Theo K., Frazer, Kelly A., McCauley, Bryan M., Taylor, Kent, Pankow, James S., Reiner, Alexander P., Gabrielsen, Maiken E., Deleuze, Jean-François, O'Donnell, Chris J., Kim, Jihye, McKnight, Barbara, Kraft, Peter, Hansen, John-Bjarne, Rosendaal, Frits R., Heit, John A., Psaty, Bruce M., Tang, Weihong, Hveem, Kristian, Ridker, Paul M., Morange, Pierre-Emmanuel, Johnson, Andrew D., Kabrhel, Christopher, AlexandreTrégouët, David, Smith, Nicholas L., de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc-Quynh, Bebo, Allison, Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Lewis, Joshua P., Rodriguez, Benjamin A. T., Polasek, Ozren, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David-Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Davies, Gail, Delgado, Graciela E., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., Osburn, William O., O'Connell, Jeffrey R., Beswick, Andrew, Kolcic, Ivana, Souto, Juan Carlos, Becker, Lewis C., Hansen, Torben, Doyle, Margaret F., Harris, Sarah E., Moissl, Angela P., Rich, Stephen S., Campbell, Harry, Stott, David J., Soria, Jose Manuel, de Maat, Moniek P. M., Brody, Lawrence C., Auer, Paul L., Ben-Shlomo, Yoav, Hayward, Caroline, Mathias, Rasika A., Kilpeläinen, Tuomas O., Lange, Leslie A., Cox, Simon R., März, Winfried, Rotter, Jerome I., Mook-Kanamori, Dennis O., Wilson, James F., van der Harst, Pim, Jukema, J. Wouter, Ikram, M. Arfan, Desch, Karl C., Sabater-Lleal, Maria, Lowenstein, Charles J., and Morrison, Alanna C.

Published
2024
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13. Deleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality

Author

Hong, Yun Soo, Battle, Stephanie L, Shi, Wen, Puiu, Daniela, Pillalamarri, Vamsee, Xie, Jiaqi, Pankratz, Nathan, Lake, Nicole J, Lek, Monkol, Rotter, Jerome I, Rich, Stephen S, Kooperberg, Charles, Reiner, Alex P, Auer, Paul L, Heard-Costa, Nancy, Liu, Chunyu, Lai, Meng, Murabito, Joanne M, Levy, Daniel, Grove, Megan L, Alonso, Alvaro, Gibbs, Richard, Dugan-Perez, Shannon, Gondek, Lukasz P, Guallar, Eliseo, and Arking, Dan E

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Cancer, Human Genome, Hematology, 2.1 Biological and endogenous factors, Good Health and Well Being, Humans, Mitochondria, DNA, Mitochondrial, Heteroplasmy, Leukemia, Mutation
Abstract

Mitochondria carry their own circular genome and disruption of the mitochondrial genome is associated with various aging-related diseases. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1000 s to 10,000 s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbors a particular variant. We quantify mtDNA heteroplasmy in 194,871 participants in the UK Biobank and find that heteroplasmy is associated with a 1.5-fold increased risk of all-cause mortality. Additionally, we functionally characterize mtDNA single nucleotide variants (SNVs) using a constraint-based score, mitochondrial local constraint score sum (MSS) and find it associated with all-cause mortality, and with the prevalence and incidence of cancer and cancer-related mortality, particularly leukemia. These results indicate that mitochondria may have a functional role in certain cancers, and mitochondrial heteroplasmic SNVs may serve as a prognostic marker for cancer, especially for leukemia.

Published
2023

14. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Middha, Pooja, Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baert, Thaïs, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Benitez, Javier, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dossus, Laure, Dugué, Pierre-Antoine, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G, González-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Holleczek, Bernd, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ingvar, Christian, Isaksson, Karolin, Jernström, Helena, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Larson, Nicole L, Larsson, Susanna, Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Norman, Aaron, O’Brien, Katie M, Olson, Janet E, Patel, Alpa V, Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J, and Sandler, Dale P

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer Genomics, Human Genome, Estrogen, Cancer, Women's Health, Genetics, Prevention, Aging, Breast Cancer, 2.1 Biological and endogenous factors, Adult, Female, Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Breast Neoplasms, Bayes Theorem, Genome-Wide Association Study, Risk Factors, Polymorphism, Single Nucleotide, Case-Control Studies, Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, CTS Consortium, ABCTB Investigators, kConFab Investigators, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundGenome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.MethodsAnalyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.ResultsAssuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Published
2023

15. A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies

Author

Li, Zilin, Li, Xihao, Zhou, Hufeng, Gaynor, Sheila M, Selvaraj, Margaret Sunitha, Arapoglou, Theodore, Quick, Corbin, Liu, Yaowu, Chen, Han, Sun, Ryan, Dey, Rounak, Arnett, Donna K, Auer, Paul L, Bielak, Lawrence F, Bis, Joshua C, Blackwell, Thomas W, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Conomos, Matthew P, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, de Vries, Paul S, Duggirala, Ravindranath, Franceschini, Nora, Freedman, Barry I, Göring, Harald HH, Guo, Xiuqing, Kalyani, Rita R, Kooperberg, Charles, Kral, Brian G, Lange, Leslie A, Lin, Bridget M, Manichaikul, Ani, Manning, Alisa K, Martin, Lisa W, Mathias, Rasika A, Meigs, James B, Mitchell, Braxton D, Montasser, May E, Morrison, Alanna C, Naseri, Take, O’Connell, Jeffrey R, Palmer, Nicholette D, Peyser, Patricia A, Psaty, Bruce M, Raffield, Laura M, Redline, Susan, Reiner, Alexander P, Reupena, Muagututi’a Sefuiva, Rice, Kenneth M, Rich, Stephen S, Smith, Jennifer A, Taylor, Kent D, Taub, Margaret A, Vasan, Ramachandran S, Weeks, Daniel E, Wilson, James G, Yanek, Lisa R, Zhao, Wei, Rotter, Jerome I, Willer, Cristen J, Natarajan, Pradeep, Peloso, Gina M, and Lin, Xihong

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Generic health relevance, Good Health and Well Being, Humans, Genome-Wide Association Study, Whole Genome Sequencing, Genome, Phenotype, Genetic Variation, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Technology, Medical and Health Sciences, Developmental Biology, Biological sciences
Abstract

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Published
2022

17. TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data

Author

Huang, Le, Rosen, Jonathan D, Sun, Quan, Chen, Jiawen, Wheeler, Marsha M, Zhou, Ying, Min, Yuan-I, Kooperberg, Charles, Conomos, Matthew P, Stilp, Adrienne M, Rich, Stephen S, Rotter, Jerome I, Manichaikul, Ani, Loos, Ruth JF, Kenny, Eimear E, Blackwell, Thomas W, Smith, Albert V, Jun, Goo, Sedlazeck, Fritz J, Metcalf, Ginger, Boerwinkle, Eric, Consortium, NHLBI Trans-Omics for Precision Medicine, Raffield, Laura M, Reiner, Alex P, Auer, Paul L, and Li, Yun

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Biotechnology, Human Genome, Good Health and Well Being, Asian People, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Precision Medicine, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.

Published
2022

20. Whole-Genome Sequencing Association Analyses of Stroke and Its Subtypes in Ancestrally Diverse Populations From Trans-Omics for Precision Medicine Project

Author

Hu, Yao, Haessler, Jeffrey W, Manansala, Regina, Wiggins, Kerri L, Moscati, Arden, Beiser, Alexa, Heard-Costa, Nancy L, Sarnowski, Chloe, Raffield, Laura M, Chung, Jaeyoon, Marini, Sandro, Anderson, Christopher D, Rosand, Jonathan, Xu, Huichun, Sun, Xiao, Kelly, Tanika N, Wong, Quenna, Lange, Leslie A, Rotter, Jerome I, Correa, Adolfo, Vasan, Ramachandran S, Seshadri, Sudha, Rich, Stephen S, Do, Ron, Loos, Ruth JF, Longstreth, William T, Bis, Joshua C, Psaty, Bruce M, Tirschwell, David L, Assimes, Themistocles L, Silver, Brian, Liu, Simin, Jackson, Rebecca, Wassertheil-Smoller, Sylvia, Mitchell, Braxton D, Fornage, Myriam, Auer, Paul L, Reiner, Alex P, Kooperberg, Charles, and Group, the NHLBI Trans-Omics for Precision Medicine Consortium the Trans-Omics for Precision Medicine Stroke Working

Subjects
Epidemiology, Health Sciences, Human Genome, Neurosciences, Brain Disorders, Stroke, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Aged, Aged, 80 and over, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Precision Medicine, Racial Groups, Whole Genome Sequencing, atherosclerosis, blood pressure, cause of death, embolic stroke, sample size, Trans-Omics for Precision Medicine (TOPMed) Stroke Working Group, the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Neurology & Neurosurgery, Clinical sciences, Allied health and rehabilitation science
Abstract

Background and purposeStroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid).MethodsWhole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis.ResultsIn the single variant association analysis in TOPMed, we identified one novel locus 13q33 for large artery at whole-genome-wide significance (P

Published
2022

21. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Author

Little, Amarise, Hu, Yao, Sun, Quan, Jain, Deepti, Broome, Jai, Chen, Ming-Huei, Thibord, Florian, McHugh, Caitlin, Surendran, Praveen, Blackwell, Thomas W, Brody, Jennifer A, Bhan, Arunoday, Chami, Nathalie, de Vries, Paul S, Ekunwe, Lynette, Heard-Costa, Nancy, Hobbs, Brian D, Manichaikul, Ani, Moon, Jee-Young, Preuss, Michael H, Ryan, Kathleen, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Abecasis, Goncalo R, Almasy, Laura, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Choquet, Hélène, Correa, Adolfo, Curran, Joanne E, Faraday, Nauder, Fornage, Myriam, Glahn, David C, Hou, Lifang, Jorgenson, Eric, Kooperberg, Charles, Lewis, Joshua P, Lloyd-Jones, Donald M, Loos, Ruth JF, Min, Yuan-I, Mitchell, Braxton D, Morrison, Alanna C, Nickerson, Deborah A, North, Kari E, O'Connell, Jeffrey R, Pankratz, Nathan, Psaty, Bruce M, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Smith, Albert V, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Conomos, Matthew P, Laurie, Cecelia A, Mathias, Rasika A, Li, Yun, Auer, Paul L, Consortium, NHLBI Trans-Omics for Precision Medicine, Thornton, Timothy, Reiner, Alexander P, Johnson, Andrew D, and Raffield, Laura M

Subjects
Biological Sciences, Genetics, Hematology, Biotechnology, Clinical Research, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Platelets, Genome-Wide Association Study, Humans, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Precision Medicine, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Published
2022

22. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

Author

Katz, Daniel H, Tahir, Usman A, Bick, Alexander G, Pampana, Akhil, Ngo, Debby, Benson, Mark D, Yu, Zhi, Robbins, Jeremy M, Chen, Zsu-Zsu, Cruz, Daniel E, Deng, Shuliang, Farrell, Laurie, Sinha, Sumita, Schmaier, Alec A, Shen, Dongxiao, Gao, Yan, Hall, Michael E, Correa, Adolfo, Tracy, Russell P, Durda, Peter, Taylor, Kent D, Liu, Yongmei, Johnson, W Craig, Guo, Xiuqing, Yao, Jie, Ida Chen, Yii-Der, Manichaikul, Ani W, Jain, Deepti, Bouchard, Claude, Sarzynski, Mark A, Rich, Stephen S, Rotter, Jerome I, Wang, Thomas J, Wilson, James G, Natarajan, Pradeep, Gerszten, Robert E, Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April, Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, and Chavan, Sameer

Subjects
Epidemiology, Health Sciences, Aging, Heart Disease - Coronary Heart Disease, Human Genome, Genetics, Prevention, Cardiovascular, Heart Disease, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Black People, Cardiovascular Diseases, Female, Genome-Wide Association Study, Humans, Male, Proteome, cardiovascular disease, genetics, proteomics, race and ethnicity, National Heart, Lung, and Blood Institute TOPMed (Trans-Omics for Precision Medicine) Consortium†, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Sports science and exercise
Abstract

BackgroundPlasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.MethodsProteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).ResultsWe identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.ConclusionsTaken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Published
2022

23. Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program

Author

Wheeler, Marsha M, Stilp, Adrienne M, Rao, Shuquan, Halldórsson, Bjarni V, Beyter, Doruk, Wen, Jia, Mihkaylova, Anna V, McHugh, Caitlin P, Lane, John, Jiang, Min-Zhi, Raffield, Laura M, Jun, Goo, Sedlazeck, Fritz J, Metcalf, Ginger, Yao, Yao, Bis, Joshua B, Chami, Nathalie, de Vries, Paul S, Desai, Pinkal, Floyd, James S, Gao, Yan, Kammers, Kai, Kim, Wonji, Moon, Jee-Young, Ratan, Aakrosh, Yanek, Lisa R, Almasy, Laura, Becker, Lewis C, Blangero, John, Cho, Michael H, Curran, Joanne E, Fornage, Myriam, Kaplan, Robert C, Lewis, Joshua P, Loos, Ruth JF, Mitchell, Braxton D, Morrison, Alanna C, Preuss, Michael, Psaty, Bruce M, Rich, Stephen S, Rotter, Jerome I, Tang, Hua, Tracy, Russell P, Boerwinkle, Eric, Abecasis, Goncalo R, Blackwell, Thomas W, Smith, Albert V, Johnson, Andrew D, Mathias, Rasika A, Nickerson, Deborah A, Conomos, Matthew P, Li, Yun, Þorsteinsdóttir, Unnur, Magnússon, Magnús K, Stefansson, Kari, Pankratz, Nathan D, Bauer, Daniel E, Auer, Paul L, and Reiner, Alex P

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Good Health and Well Being, Humans, Genome-Wide Association Study, Whole Genome Sequencing, Blood Cells
Abstract

Genome-wide association studies have identified thousands of single nucleotide variants and small indels that contribute to variation in hematologic traits. While structural variants are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of structural variants to quantitative blood cell trait variation is unknown. Here we utilized whole genome sequencing data in ancestrally diverse participants of the NHLBI Trans Omics for Precision Medicine program (N = 50,675) to detect structural variants associated with hematologic traits. Using single variant tests, we assessed the association of common and rare structural variants with red cell-, white cell-, and platelet-related quantitative traits and observed 21 independent signals (12 common and 9 rare) reaching genome-wide significance. The majority of these associations (N = 18) replicated in independent datasets. In genome-editing experiments, we provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

Published
2022

24. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Author

Taub, Margaret A, Conomos, Matthew P, Keener, Rebecca, Iyer, Kruthika R, Weinstock, Joshua S, Yanek, Lisa R, Lane, John, Miller-Fleming, Tyne W, Brody, Jennifer A, Raffield, Laura M, McHugh, Caitlin P, Jain, Deepti, Gogarten, Stephanie M, Laurie, Cecelia A, Keramati, Ali, Arvanitis, Marios, Smith, Albert V, Heavner, Benjamin, Barwick, Lucas, Becker, Lewis C, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Burchard, Esteban G, Celedón, Juan C, Chang, Yen Pei C, Custer, Brian, Darbar, Dawood, de las Fuentes, Lisa, DeMeo, Dawn L, Freedman, Barry I, Garrett, Melanie E, Gladwin, Mark T, Heckbert, Susan R, Hidalgo, Bertha A, Irvin, Marguerite R, Islam, Talat, Johnson, W Craig, Kaab, Stefan, Launer, Lenore, Lee, Jiwon, Liu, Simin, Moscati, Arden, North, Kari E, Peyser, Patricia A, Rafaels, Nicholas, Seidman, Christine, Weeks, Daniel E, Wen, Fayun, Wheeler, Marsha M, Williams, L Keoki, Yang, Ivana V, Zhao, Wei, Aslibekyan, Stella, Auer, Paul L, Bowden, Donald W, Cade, Brian E, Chen, Zhanghua, Cho, Michael H, Cupples, L Adrienne, Curran, Joanne E, Daya, Michelle, Deka, Ranjan, Eng, Celeste, Fingerlin, Tasha E, Guo, Xiuqing, Hou, Lifang, Hwang, Shih-Jen, Johnsen, Jill M, Kenny, Eimear E, Levin, Albert M, Liu, Chunyu, Minster, Ryan L, Naseri, Take, Nouraie, Mehdi, Reupena, Muagututi A Sefuiva, Sabino, Ester C, Smith, Jennifer A, Smith, Nicholas L, Lasky-Su, Jessica, Taylor, James G, Telen, Marilyn J, Tiwari, Hemant K, Tracy, Russell P, White, Marquitta J, Zhang, Yingze, Wiggins, Kerri L, Weiss, Scott T, Vasan, Ramachandran S, Taylor, Kent D, Sinner, Moritz F, Silverman, Edwin K, Shoemaker, M Benjamin, Sheu, Wayne H-H, Sciurba, Frank, Schwartz, David A, Rotter, Jerome I, Roden, Daniel, Redline, Susan, and Raby, Benjamin A

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, NHLBI CARE Network, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
Abstract

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value

Published
2022

25. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author

Ahearn, Thomas U, Zhang, Haoyu, Michailidou, Kyriaki, Milne, Roger L, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Lush, Michael, Wang, Qin, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baten, Adinda, Becher, Heiko, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Collée, J Margriet, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Floris, Giuseppe, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Alnæs, Grethe I Grenaker, Grip, Mervi, Guénel, Pascal, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Heemskerk-Gerritsen, Bernadette AM, Holleczek, Bernd, Hollestelle, Antoinette, Hooning, Maartje J, Hoover, Robert N, Hopper, John L, Howell, Anthony, Jakimovska, Milena, Jakubowska, Anna, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Kauppila, Saila, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kristensen, Vessela N, Krüger, Ute, Kubelka-Sabit, Katerina, Kurian, Allison W, Kyriacou, Kyriacos, Lambrechts, Diether, Lee, Derrick G, Lindblom, Annika, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, MacInnis, Robert J, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martinez, Maria Elena, and McLean, Catriona

Subjects
Human Genome, Cancer, Genetics, Clinical Research, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Biomarkers, Tumor, Breast Neoplasms, Female, Genome-Wide Association Study, Humans, Receptor, ErbB-2, Receptors, Estrogen, Receptors, Progesterone, Risk, Breast cancer, Etiologic heterogeneity, Genetic predisposition, Common breast cancer susceptibility variants, NBCS Collaborators, ABCTB Investigators, kConFab/AOCS Investigators, Receptor, erbB-2, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate

Published
2022

26. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Author

Wang, Xiaoliang, Kapoor, Pooja Middha, Auer, Paul L, Dennis, Joe, Dunning, Alison M, Wang, Qin, Lush, Michael, Michailidou, Kyriaki, Bolla, Manjeet K, Aronson, Kristan J, Murphy, Rachel A, Brooks-Wilson, Angela, Lee, Derrick G, Cordina-Duverger, Emilie, Guénel, Pascal, Truong, Thérèse, Mulot, Claire, Teras, Lauren R, Patel, Alpa V, Dossus, Laure, Kaaks, Rudolf, Hoppe, Reiner, Lo, Wing-Yee, Brüning, Thomas, Hamann, Ute, Czene, Kamila, Gabrielson, Marike, Hall, Per, Eriksson, Mikael, Jung, Audrey, Becher, Heiko, Couch, Fergus J, Larson, Nicole L, Olson, Janet E, Ruddy, Kathryn J, Giles, Graham G, MacInnis, Robert J, Southey, Melissa C, Le Marchand, Loic, Wilkens, Lynne R, Haiman, Christopher A, Olsson, Håkan, Augustinsson, Annelie, Krüger, Ute, Wagner, Philippe, Scott, Christopher, Winham, Stacey J, Vachon, Celine M, Perou, Charles M, Olshan, Andrew F, Troester, Melissa A, Hunter, David J, Eliassen, Heather A, Tamimi, Rulla M, Brantley, Kristen, Andrulis, Irene L, Figueroa, Jonine, Chanock, Stephen J, Ahearn, Thomas U, García-Closas, Montserrat, Evans, Gareth D, Newman, William G, van Veen, Elke M, Howell, Anthony, Wolk, Alicja, Håkansson, Niclas, Anton-Culver, Hoda, Ziogas, Argyrios, Jones, Michael E, Orr, Nick, Schoemaker, Minouk J, Swerdlow, Anthony J, Kitahara, Cari M, Linet, Martha, Prentice, Ross L, Easton, Douglas F, Milne, Roger L, Kraft, Peter, Chang-Claude, Jenny, and Lindström, Sara

Subjects
Genetics, Cancer, Aging, Human Genome, Breast Cancer, Prevention, Estrogen, 2.1 Biological and endogenous factors, Aetiology, Breast, Breast Neoplasms, Estrogen Replacement Therapy, Female, Hormone Replacement Therapy, Humans, Male, Menopause, Risk Factors
Abstract

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values

Published
2022

27. Germline Pathogenic Variants in Cancer Predisposition Genes Among Women With Invasive Lobular Carcinoma of the Breast

Author

Yadav, Siddhartha, Hu, Chunling, Nathanson, Katherine L, Weitzel, Jeffrey N, Goldgar, David E, Kraft, Peter, Gnanaolivu, Rohan D, Na, Jie, Huang, Hongyan, Boddicker, Nicholas J, Larson, Nicole, Gao, Chi, Yao, Song, Weinberg, Clarice, Vachon, Celine M, Trentham-Dietz, Amy, Taylor, Jack A, Sandler, Dale R, Patel, Alpa, Palmer, Julie R, Olson, Janet E, Neuhausen, Susan, Martinez, Elena, Lindstrom, Sara, Lacey, James V, Kurian, Allison W, John, Esther M, Haiman, Christopher, Bernstein, Leslie, Auer, Paul W, Anton-Culver, Hoda, Ambrosone, Christine B, Karam, Rachid, Chao, Elizabeth, Yussuf, Amal, Pesaran, Tina, Dolinsky, Jill S, Hart, Steven N, LaDuca, Holly, Polley, Eric C, Domchek, Susan M, and Couch, Fergus J

Subjects
Breast Cancer, Clinical Research, Genetics, Cancer, 2.1 Biological and endogenous factors, Aetiology, Adolescent, Adult, Aged, Aged, 80 and over, Biomarkers, Tumor, Breast Neoplasms, Carcinoma, Ductal, Breast, Carcinoma, Lobular, Case-Control Studies, Female, Follow-Up Studies, Genetic Predisposition to Disease, Genetic Testing, Germ-Line Mutation, Humans, Middle Aged, Prognosis, Young Adult, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeTo determine the contribution of germline pathogenic variants (PVs) in hereditary cancer testing panel genes to invasive lobular carcinoma (ILC) of the breast.Materials and methodsThe study included 2,999 women with ILC from a population-based cohort and 3,796 women with ILC undergoing clinical multigene panel testing (clinical cohort). Frequencies of germline PVs in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, and TP53) were compared between women with ILC and unaffected female controls and between women with ILC and infiltrating ductal carcinoma (IDC).ResultsThe frequency of PVs in breast cancer predisposition genes among women with ILC was 6.5% in the clinical cohort and 5.2% in the population-based cohort. In case-control analysis, CDH1 and BRCA2 PVs were associated with high risks of ILC (odds ratio [OR] > 4) and CHEK2, ATM, and PALB2 PVs were associated with moderate (OR = 2-4) risks. BRCA1 PVs and CHEK2 p.Ile157Thr were not associated with clinically relevant risks (OR < 2) of ILC. Compared with IDC, CDH1 PVs were > 10-fold enriched, whereas PVs in BRCA1 were substantially reduced in ILC.ConclusionThe study establishes that PVs in ATM, BRCA2, CDH1, CHEK2, and PALB2 are associated with an increased risk of ILC, whereas BRCA1 PVs are not. The similar overall PV frequencies for ILC and IDC suggest that cancer histology should not influence the decision to proceed with genetic testing. Similar to IDC, multigene panel testing may be appropriate for women with ILC, but CDH1 should be specifically discussed because of low prevalence and gastric cancer risk.

Published
2021

28. Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study

Author

Hu, Yao, Bien, Stephanie A, Nishimura, Katherine K, Haessler, Jeffrey, Hodonsky, Chani J, Baldassari, Antoine R, Highland, Heather M, Wang, Zhe, Preuss, Michael, Sitlani, Colleen M, Wojcik, Genevieve L, Tao, Ran, Graff, Mariaelisa, Huckins, Laura M, Sun, Quan, Chen, Ming-Huei, Mousas, Abdou, Auer, Paul L, Lettre, Guillaume, Tang, Weihong, Qi, Lihong, Thyagarajan, Bharat, Buyske, Steve, Fornage, Myriam, Hindorff, Lucia A, Li, Yun, Lin, Danyu, Reiner, Alexander P, North, Kari E, Loos, Ruth JF, Raffield, Laura M, Peters, Ulrike, Avery, Christy L, and Kooperberg, Charles

Subjects
Clinical Research, Hematology, Genetics, American Indian or Alaska Native, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Leukocytes, Phenotype, Polymorphism, Single Nucleotide, GWAS, White blood cells, Platelets, Multi-ethnic, Blood Cell Consortium, Biological Sciences, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics
Abstract

BackgroundCirculating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.ResultsWe performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.ConclusionsOur results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

Published
2021

29. Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

Author

Morra, Anna, Escala-Garcia, Maria, Beesley, Jonathan, Keeman, Renske, Canisius, Sander, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Augustinsson, Annelie, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Brüning, Thomas, Buys, Saundra S, Caan, Bette, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Cheng, Ting-Yuan David, Clarke, Christine L, Colonna, Sarah V, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Dörk, Thilo, Dossus, Laure, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fritschi, Lin, Gago-Dominguez, Manuela, García-Sáenz, José A, Giles, Graham G, Grip, Mervi, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hart, Steven N, Hartikainen, Jaana M, Hartmann, Arndt, He, Wei, Hooning, Maartje J, Hoppe, Reiner, Hopper, John L, Howell, Anthony, Hunter, David J, Jager, Agnes, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey Y, Kaaks, Rudolf, Keupers, Machteld, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Linet, Martha, Luben, Robert N, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martens, John WM, Martinez, Maria Elena, Mavroudis, Dimitrios, Michailidou, Kyriaki, Milne, Roger L, Mulligan, Anna Marie, Muranen, Taru A, Nevanlinna, Heli, Newman, William G, and Nielsen, Sune F

Subjects
Clinical Research, Cancer, Breast Cancer, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, Female, Genome-Wide Association Study, Germ-Line Mutation, Humans, Polymorphism, Single Nucleotide, Prognosis, Survival Analysis, Common germline genetic variants, Breast cancer-specific survival, Patient subgroups, Tumor biology, Systemic treatment, NBCS Collaborators, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundGiven the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.MethodsWe performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP

Published
2021

30. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program

Author

Mikhaylova, Anna V, McHugh, Caitlin P, Polfus, Linda M, Raffield, Laura M, Boorgula, Meher Preethi, Blackwell, Thomas W, Brody, Jennifer A, Broome, Jai, Chami, Nathalie, Chen, Ming-Huei, Conomos, Matthew P, Cox, Corey, Curran, Joanne E, Daya, Michelle, Ekunwe, Lynette, Glahn, David C, Heard-Costa, Nancy, Highland, Heather M, Hobbs, Brian D, Ilboudo, Yann, Jain, Deepti, Lange, Leslie A, Miller-Fleming, Tyne W, Min, Nancy, Moon, Jee-Young, Preuss, Michael H, Rosen, Jonathon, Ryan, Kathleen, Smith, Albert V, Sun, Quan, Surendran, Praveen, de Vries, Paul S, Walter, Klaudia, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Zhong, Xue, Abecasis, Goncalo R, Almasy, Laura, Barnes, Kathleen C, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Chavan, Sameer, Cho, Michael H, Choquet, Hélène, Correa, Adolfo, Cox, Nancy, DeMeo, Dawn L, Faraday, Nauder, Fornage, Myriam, Gerszten, Robert E, Hou, Lifang, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kooperberg, Charles, Kundu, Kousik, Laurie, Cecelia A, Lettre, Guillaume, Lewis, Joshua P, Li, Bingshan, Li, Yun, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani, Meyers, Deborah A, Mitchell, Braxton D, Morrison, Alanna C, Ngo, Debby, Nickerson, Deborah A, Nongmaithem, Suraj, North, Kari E, O’Connell, Jeffrey R, Ortega, Victor E, Pankratz, Nathan, Perry, James A, Psaty, Bruce M, Rich, Stephen S, Soranzo, Nicole, Rotter, Jerome I, Silverman, Edwin K, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Thornton, Timothy A, Vasan, Ramachandran S, Zein, Joe, Mathias, Rasika A, Consortium, NHLBI Trans-Omics for Precision Medicine, Reiner, Alexander P, and Auer, Paul L

Subjects
Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, blood-cell counts, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Published
2021

31. Genome-Wide Interaction Analysis of Menopausal Hormone Therapy Use and Breast Cancer Risk Among 62,370 Women

Author

Wang, Xiaoliang, Kapoor, Pooja Middha, Auer, Paul L, Dennis, Joe, Dunning, Alison M, Wang, Qin, Lush, Michael, Michailidou, Kyriaki, Bolla, Manjeet K, Aronson, Kristan J, Murphy, Rachel A, Brooks-Wilson, Angela, Lee, Derrick G, Cordina-Duverger, Emilie, Guénel, Pascal, Truong, Thérèse, Mulot, Claire, Teras, Lauren R, Patel, Alpa V, Dossus, Laure, Kaaks, Rudolf, Hoppe, Reiner, Lo, Wing-Yee, Brüning, Thomas, Hamann, Ute, Czene, Kamila, Gabrielson, Marike, Hall, Per, Eriksson, Mikael, Jung, Audrey, Becher, Heiko, Couch, Fergus J, Larson, Nicole L, Olson, Janet E, Ruddy, Kathryn J, Giles, Graham G, MacInnis, Robert J, Southey, Melissa C, Marchand, Loic Le, Wilkens, Lynne R, Haiman, Christopher A, Olsson, Håkan, Augustinsson, Annelie, Krüger, Ute, Wagner, Philippe, Scott, Christopher, Winham, Stacey J, Vachon, Celine M, Perou, Charles M, Olshan, Andrew F, Troester, Melissa A, Hunter, David J, Eliassen, A Heather, Tamimi, Rulla M, Brantley, Kristen, Andrulis, Irene L, Figueroa, Jonine, Chanock, Stephen J, Ahearn, Thomas U, García-Closas, Montserrat, Evans, Gareth D, Newman, William G, Veen, Elke M van, Howell, Anthony, Wolk, Alicja, Håkansson, Niclas, Anton-Culver, Hoda, Ziogas, Argyrios, Jones, Michael E, Orr, Nick, Schoemaker, Minouk J, Swerdlow, Anthony J, Kitahara, Cari M, Linet, Martha, Prentice, Ross L, Easton, Douglas F, Milne, Roger L, Kraft, Peter, Chang-Claude, Jenny, and Lindström, Sara

Subjects
Cancer, Prevention, Breast Cancer, Genetics, Human Genome, Aging, Estrogen, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being
Abstract

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values

Published
2021

32. Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Author

Hu, Yao, Stilp, Adrienne M, McHugh, Caitlin P, Rao, Shuquan, Jain, Deepti, Zheng, Xiuwen, Lane, John, de Bellefon, Sébastian Méric, Raffield, Laura M, Chen, Ming-Huei, Yanek, Lisa R, Wheeler, Marsha, Yao, Yao, Ren, Chunyan, Broome, Jai, Moon, Jee-Young, de Vries, Paul S, Hobbs, Brian D, Sun, Quan, Surendran, Praveen, Brody, Jennifer A, Blackwell, Thomas W, Choquet, Hélène, Ryan, Kathleen, Duggirala, Ravindranath, Heard-Costa, Nancy, Wang, Zhe, Chami, Nathalie, Preuss, Michael H, Min, Nancy, Ekunwe, Lynette, Lange, Leslie A, Cushman, Mary, Faraday, Nauder, Curran, Joanne E, Almasy, Laura, Kundu, Kousik, Smith, Albert V, Gabriel, Stacey, Rotter, Jerome I, Fornage, Myriam, Lloyd-Jones, Donald M, Vasan, Ramachandran S, Smith, Nicholas L, North, Kari E, Boerwinkle, Eric, Becker, Lewis C, Lewis, Joshua P, Abecasis, Goncalo R, Hou, Lifang, O’Connell, Jeffrey R, Morrison, Alanna C, Beaty, Terri H, Kaplan, Robert, Correa, Adolfo, Blangero, John, Jorgenson, Eric, Psaty, Bruce M, Kooperberg, Charles, Walton, Russell T, Kleinstiver, Benjamin P, Tang, Hua, Loos, Ruth JF, Soranzo, Nicole, Butterworth, Adam S, Nickerson, Debbie, Rich, Stephen S, Mitchell, Braxton D, Johnson, Andrew D, Auer, Paul L, Li, Yun, Mathias, Rasika A, Lettre, Guillaume, Pankratz, Nathan, Laurie, Cathy C, Laurie, Cecelia A, Bauer, Daniel E, Conomos, Matthew P, Reiner, Alexander P, and Consortium, NHLBI Trans-Omics for Precision Medicine

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Biotechnology, Clinical Research, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, base editing, red blood cell traits, whole-genome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Published
2021

34. Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

Author

Kapoor, Pooja Middha, Mavaddat, Nasim, Choudhury, Parichoy Pal, Wilcox, Amber N, Lindström, Sara, Behrens, Sabine, Michailidou, Kyriaki, Dennis, Joe, Bolla, Manjeet K, Wang, Qin, Jung, Audrey, Abu-Ful, Zomoroda, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bernstein, Leslie, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brüning, Thomas, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chatterjee, Nilanjan, Chenevix-Trench, Georgia, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Earp, H Shelton, Ekici, Arif B, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gao, Chi, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hatse, Sigrid, Heyworth, Jane, Holleczek, Bernd, Hoover, Robert N, Hopper, John L, Howell, Anthony, Hunter, David J, ABCTB Investigators, kConFab/AOCS Investigators, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, MacInnis, Robert J, Martinez, Maria Elena, Maurer, Tabea, McLean, Catriona, Neuhausen, Susan L, Newman, William G, Norman, Aaron, O'Brien, Katie M, Olshan, Andrew F, Olson, Janet E, Olsson, Håkan, and Orr, Nick

Subjects
ABCTB Investigators, kConFab/AOCS Investigators, Oncology & Carcinogenesis, Oncology and Carcinogenesis
Abstract

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Published
2021

35. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Author

Taliun, Daniel, Harris, Daniel N, Kessler, Michael D, Carlson, Jedidiah, Szpiech, Zachary A, Torres, Raul, Taliun, Sarah A Gagliano, Corvelo, André, Gogarten, Stephanie M, Kang, Hyun Min, Pitsillides, Achilleas N, LeFaive, Jonathon, Lee, Seung-been, Tian, Xiaowen, Browning, Brian L, Das, Sayantan, Emde, Anne-Katrin, Clarke, Wayne E, Loesch, Douglas P, Shetty, Amol C, Blackwell, Thomas W, Smith, Albert V, Wong, Quenna, Liu, Xiaoming, Conomos, Matthew P, Bobo, Dean M, Aguet, François, Albert, Christine, Alonso, Alvaro, Ardlie, Kristin G, Arking, Dan E, Aslibekyan, Stella, Auer, Paul L, Barnard, John, Barr, R Graham, Barwick, Lucas, Becker, Lewis C, Beer, Rebecca L, Benjamin, Emelia J, Bielak, Lawrence F, Blangero, John, Boehnke, Michael, Bowden, Donald W, Brody, Jennifer A, Burchard, Esteban G, Cade, Brian E, Casella, James F, Chalazan, Brandon, Chasman, Daniel I, Chen, Yii-Der Ida, Cho, Michael H, Choi, Seung Hoan, Chung, Mina K, Clish, Clary B, Correa, Adolfo, Curran, Joanne E, Custer, Brian, Darbar, Dawood, Daya, Michelle, de Andrade, Mariza, DeMeo, Dawn L, Dutcher, Susan K, Ellinor, Patrick T, Emery, Leslie S, Eng, Celeste, Fatkin, Diane, Fingerlin, Tasha, Forer, Lukas, Fornage, Myriam, Franceschini, Nora, Fuchsberger, Christian, Fullerton, Stephanie M, Germer, Soren, Gladwin, Mark T, Gottlieb, Daniel J, Guo, Xiuqing, Hall, Michael E, He, Jiang, Heard-Costa, Nancy L, Heckbert, Susan R, Irvin, Marguerite R, Johnsen, Jill M, Johnson, Andrew D, Kaplan, Robert, Kardia, Sharon LR, Kelly, Tanika, Kelly, Shannon, Kenny, Eimear E, Kiel, Douglas P, Klemmer, Robert, Konkle, Barbara A, Kooperberg, Charles, Köttgen, Anna, Lange, Leslie A, Lasky-Su, Jessica, Levy, Daniel, Lin, Xihong, Lin, Keng-Han, Liu, Chunyu, and Loos, Ruth JF

Subjects
Genetics, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Cytochrome P-450 CYP2D6, Genetic Variation, Genome, Human, Genomics, Haplotypes, Heterozygote, Humans, INDEL Mutation, Loss of Function Mutation, Mutagenesis, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Population Density, Precision Medicine, Quality Control, Sample Size, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, General Science & Technology
Abstract

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

Published
2021

36. A Population-Based Study of Genes Previously Implicated in Breast Cancer

Author

Hu, Chunling, Hart, Steven N, Gnanaolivu, Rohan, Huang, Hongyan, Lee, Kun Y, Na, Jie, Gao, Chi, Lilyquist, Jenna, Yadav, Siddhartha, Boddicker, Nicholas J, Samara, Raed, Klebba, Josh, Ambrosone, Christine B, Anton-Culver, Hoda, Auer, Paul, Bandera, Elisa V, Bernstein, Leslie, Bertrand, Kimberly A, Burnside, Elizabeth S, Carter, Brian D, Eliassen, Heather, Gapstur, Susan M, Gaudet, Mia, Haiman, Christopher, Hodge, James M, Hunter, David J, Jacobs, Eric J, John, Esther M, Kooperberg, Charles, Kurian, Allison W, Le Marchand, Loic, Lindstroem, Sara, Lindstrom, Tricia, Ma, Huiyan, Neuhausen, Susan, Newcomb, Polly A, O'Brien, Katie M, Olson, Janet E, Ong, Irene M, Pal, Tuya, Palmer, Julie R, Patel, Alpa V, Reid, Sonya, Rosenberg, Lynn, Sandler, Dale P, Scott, Christopher, Tamimi, Rulla, Taylor, Jack A, Trentham-Dietz, Amy, Vachon, Celine M, Weinberg, Clarice, Yao, Song, Ziogas, Argyrios, Weitzel, Jeffrey N, Goldgar, David E, Domchek, Susan M, Nathanson, Katherine L, Kraft, Peter, Polley, Eric C, and Couch, Fergus J

Subjects
Breast Cancer, Genetic Testing, Prevention, Cancer, Clinical Research, Genetics, 2.1 Biological and endogenous factors, Aetiology, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Adult, Aged, Aged, 80 and over, Breast Neoplasms, Case-Control Studies, Female, Genetic Predisposition to Disease, Genetic Variation, Humans, Middle Aged, Mutation, Odds Ratio, Risk, Sequence Analysis, DNA, Young Adult, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundPopulation-based estimates of the risk of breast cancer associated with germline pathogenic variants in cancer-predisposition genes are critically needed for risk assessment and management in women with inherited pathogenic variants.MethodsIn a population-based case-control study, we performed sequencing using a custom multigene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and 32,544 unaffected women (controls) from population-based studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Associations between pathogenic variants in each gene and the risk of breast cancer were assessed.ResultsPathogenic variants in 12 established breast cancer-predisposition genes were detected in 5.03% of case patients and in 1.63% of controls. Pathogenic variants in BRCA1 and BRCA2 were associated with a high risk of breast cancer, with odds ratios of 7.62 (95% confidence interval [CI], 5.33 to 11.27) and 5.23 (95% CI, 4.09 to 6.77), respectively. Pathogenic variants in PALB2 were associated with a moderate risk (odds ratio, 3.83; 95% CI, 2.68 to 5.63). Pathogenic variants in BARD1, RAD51C, and RAD51D were associated with increased risks of estrogen receptor-negative breast cancer and triple-negative breast cancer, whereas pathogenic variants in ATM, CDH1, and CHEK2 were associated with an increased risk of estrogen receptor-positive breast cancer. Pathogenic variants in 16 candidate breast cancer-predisposition genes, including the c.657_661del5 founder pathogenic variant in NBN, were not associated with an increased risk of breast cancer.ConclusionsThis study provides estimates of the prevalence and risk of breast cancer associated with pathogenic variants in known breast cancer-predisposition genes in the U.S. population. These estimates can inform cancer testing and screening and improve clinical management strategies for women in the general population with inherited pathogenic variants in these genes. (Funded by the National Institutes of Health and the Breast Cancer Research Foundation.).

Published
2021

37. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthma

Author

Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K., Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P., Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Daniel, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J.F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A., Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L., Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C., Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S., Pleiness, Jacob, Pollin, Toni, Post, Wendy, Powers Becker, Julia, Preethi Boorgula, Meher, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D.C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Sheu, Wayne Hui-Heng, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent, Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T., Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Williams, Scott, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Recto, Kathryn, Kachroo, Priyadarshini, Huan, Tianxiao, Lee, Gha Young, Bui, Helena, Lee, Dong Heon, Gereige, Jessica, Yao, Chen, Hwang, Shih-Jen, Joehanes, Roby, O’Connor, George T., and DeMeo, Dawn L.

Published
2023
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38. Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

Author

Yaghootkar, Hanieh, Zhang, Yiying, Spracklen, Cassandra N, Karaderi, Tugce, Huang, Lam Opal, Bradfield, Jonathan, Schurmann, Claudia, Fine, Rebecca S, Preuss, Michael H, Kutalik, Zoltan, Wittemans, Laura BL, Lu, Yingchang, Metz, Sophia, Willems, Sara M, Li-Gao, Ruifang, Grarup, Niels, Wang, Shuai, Molnos, Sophie, Sandoval-Zárate, América A, Nalls, Mike A, Lange, Leslie A, Haesser, Jeffrey, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Feitosa, Mary F, Sitlani, Colleen M, Venturini, Cristina, Mahajan, Anubha, Kacprowski, Tim, Wang, Carol A, Chasman, Daniel I, Amin, Najaf, Broer, Linda, Robertson, Neil, Young, Kristin L, Allison, Matthew, Auer, Paul L, Blüher, Matthias, Borja, Judith B, Bork-Jensen, Jette, Carrasquilla, Germán D, Christofidou, Paraskevi, Demirkan, Ayse, Doege, Claudia A, Garcia, Melissa E, Graff, Mariaelisa, Guo, Kaiying, Hakonarson, Hakon, Hong, Jaeyoung, Ida Chen, Yii-Der, Jackson, Rebecca, Jakupović, Hermina, Jousilahti, Pekka, Justice, Anne E, Kähönen, Mika, Kizer, Jorge R, Kriebel, Jennifer, LeDuc, Charles A, Li, Jin, Lind, Lars, Luan, Jian'an, Mackey, David A, Mangino, Massimo, Männistö, Satu, Martin Carli, Jayne F, Medina-Gomez, Carolina, Mook-Kanamori, Dennis O, Morris, Andrew P, de Mutsert, Renée, Nauck, Matthias, Prokic, Ivana, Pennell, Craig E, Pradhan, Arund D, Psaty, Bruce M, Raitakari, Olli T, Scott, Robert A, Skaaby, Tea, Strauch, Konstantin, Taylor, Kent D, Teumer, Alexander, Uitterlinden, Andre G, Wu, Ying, Yao, Jie, Walker, Mark, North, Kari E, Kovacs, Peter, Ikram, M Arfan, van Duijn, Cornelia M, Ridker, Paul M, Lye, Stephen, Homuth, Georg, Ingelsson, Erik, Spector, Tim D, McKnight, Barbara, Province, Michael A, Lehtimäki, Terho, Adair, Linda S, Rotter, Jerome I, Reiner, Alexander P, and Wilson, James G

Subjects
Genetics, Nutrition, Prevention, Obesity, Aetiology, 2.1 Biological and endogenous factors, Oral and gastrointestinal, Metabolic and endocrine, Cardiovascular, Stroke, Cancer, Adiposity, Gene Expression Regulation, Developmental, Genetic Variation, Genotype, Humans, Leptin, Models, Molecular, Protein Conformation, Racial Groups, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Published
2020

40. Transcriptome‐wide association study of breast cancer risk by estrogen‐receptor status

Author

Feng, Helian, Gusev, Alexander, Pasaniuc, Bogdan, Wu, Lang, Long, Jirong, Abu‐full, Zomoroda, Aittomäki, Kristiina, Andrulis, Irene L, Anton‐Culver, Hoda, Antoniou, Antonis C, Arason, Adalgeir, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Asseryanis, Ella, Auer, Paul L, Azzollini, Jacopo, Balmaña, Judith, Barkardottir, Rosa B, Barnes, Daniel R, Barrowdale, Daniel, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Białkowska, Katarzyna, Blanco, Ana, Blomqvist, Carl, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Broeks, Annegien, Brüning, Thomas, Burwinkel, Barbara, Cai, Qiuyin, Caldés, Trinidad, Caligo, Maria A, Campbell, Ian, Canisius, Sander, Campa, Daniele, Carter, Brian D, Carter, Jonathan, Castelao, Jose E, Chang‐Claude, Jenny, Chanock, Stephen J, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, Collaborators, GEMO Study, Collaborators, EMBRACE, Collaborators, GC‐HBOC study, Couch, Fergus J, Cox, Angela, Cross, Simon S, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, de la Hoya, Miguel, De Leeneer, Kim, Dennis, Joe, Devilee, Peter, Diez, Orland, Domchek, Susan M, Dörk, Thilo, dos‐Santos‐Silva, Isabel, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Ejlertsen, Bent, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Fostira, Florentia, Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gabrielson, Marike, Ganz, Patricia A, Gapstur, Susan M, Garber, Judy, García‐Closas, Montserrat, García‐Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González‐Neira, Anna, and Greene, Mark H

Subjects
Biological Sciences, Health Sciences, Genetics, Cancer, Biotechnology, Prevention, Clinical Research, Human Genome, Estrogen, Breast Cancer, Aetiology, 2.1 Biological and endogenous factors, Breast Neoplasms, Estrogens, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Receptors, Estrogen, Risk Assessment, Transcriptome, Vesicular Transport Proteins, breast cancer subtype, causal gene, GWAS, TWAS, GEMO Study Collaborators, EMBRACE Collaborators, GC-HBOC study Collaborators, ABCTB Investigators, HEBON Investigators, BCFR Investigators, OCGN Investigators, Public Health and Health Services, Epidemiology
Abstract

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

Published
2020

41. Comparison of Proteomic Assessment Methods in Multiple Cohort Studies

Author

Raffield, Laura M, Dang, Hong, Pratte, Katherine A, Jacobson, Sean, Gillenwater, Lucas A, Ampleford, Elizabeth, Barjaktarevic, Igor, Basta, Patricia, Clish, Clary B, Comellas, Alejandro P, Cornell, Elaine, Curtis, Jeffrey L, Doerschuk, Claire, Durda, Peter, Emson, Claire, Freeman, Christine M, Guo, Xiuqing, Hastie, Annette T, Hawkins, Gregory A, Herrera, Julio, Johnson, W Craig, Labaki, Wassim W, Liu, Yongmei, Masters, Brett, Miller, Michael, Ortega, Victor E, Papanicolaou, George, Peters, Stephen, Taylor, Kent D, Rich, Stephen S, Rotter, Jerome I, Auer, Paul, Reiner, Alex P, Tracy, Russell P, Ngo, Debby, Gerszten, Robert E, O'Neal, Wanda K, Bowler, Russell P, and Consortium, NHLBI Trans‐Omics for Precision Medicine

Subjects
Biological Sciences, Clinical Research, Chronic Obstructive Pulmonary Disease, Lung, Biotechnology, Adult, Aged, Aged, 80 and over, Cohort Studies, Female, Humans, Immunoassay, Male, Middle Aged, Myocardial Infarction, Proteome, Proteomics, Pulmonary Disease, Chronic Obstructive, Smokers, antibody microarrays, biomarkers, multiplexings, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Information and Computing Sciences, Medical and Health Sciences, Biochemistry & Molecular Biology, Biological sciences, Biomedical and clinical sciences
Abstract

Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.

Published
2020

42. Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Author

Zhang, Haoyu, Ahearn, Thomas U, Lecarpentier, Julie, Barnes, Daniel, Beesley, Jonathan, Qi, Guanghao, Jiang, Xia, O'Mara, Tracy A, Zhao, Ni, Bolla, Manjeet K, Dunning, Alison M, Dennis, Joe, Wang, Qin, Ful, Zumuruda Abu, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Auer, Paul L, Azzollini, Jacopo, Barrowdale, Daniel, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bialkowska, Katarzyna, Blanco, Ana, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Bondavalli, Davide, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Broeks, Annegien, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Byers, Helen, Caldés, Trinidad, Caligo, Maria A, Calvello, Mariarosaria, Campa, Daniele, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Christiaens, Melissa, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, Cornelissen, Sten, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Diez, Orland, Domchek, Susan M, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Foretova, Lenka, Fostira, Florentia, Friedman, Eitan, Frost, Debra, Gago-Dominguez, Manuela, Gapstur, Susan M, Garber, Judy, García-Sáenz, José A, Gaudet, Mia M, Gayther, Simon A, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Gronwald, Jacek, Guénel, Pascal, Häberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Hake, Christopher R, Hall, Per, Hamann, Ute, Harkness, Elaine F, Heemskerk-Gerritsen, Bernadette AM, and Hillemanns, Peter

Subjects
kConFab Investigators, ABCTB Investigators, EMBRACE Study, GEMO Study Collaborators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, BRCA1 Protein, Case-Control Studies, Linkage Disequilibrium, Mutation, Female, Genome-Wide Association Study, Triple Negative Breast Neoplasms, Human Genome, Cancer, Prevention, Genetics, Breast Cancer, 2.1 Biological and endogenous factors, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P

Published
2020

43. De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

Author

Kessler, Michael D, Loesch, Douglas P, Perry, James A, Heard-Costa, Nancy L, Taliun, Daniel, Cade, Brian E, Wang, Heming, Daya, Michelle, Ziniti, John, Datta, Soma, Celedón, Juan C, Soto-Quiros, Manuel E, Avila, Lydiana, Weiss, Scott T, Barnes, Kathleen, Redline, Susan S, Vasan, Ramachandran S, Johnson, Andrew D, Mathias, Rasika A, Hernandez, Ryan, Wilson, James G, Nickerson, Deborah A, Abecasis, Goncalo, Browning, Sharon R, Zöllner, Sebastian, O’Connell, Jeffrey R, Mitchell, Braxton D, Lung, and Blood Institute Trans-Omics for Precision Medicine Consortium National Heart, Group, TOPMed Population Genetics Working, O’Connor, Timothy D, Aalbers, Sanne, Abdalla, Moustafa, Abdul-Rahman, Omar, Abecasis, Gonçalo, Abhyankar, Avinash, Adrianto, Indra, Aguet, Francois, Akers, Rachel, Al-Tobasei, Rafet, Albert, Christine, Aldred, Micheala, Almasy, Laura, Almeida, Marcio, Alonso, Alvaro, Ament, Seth, Ampleford, Elizabeth, An, Ping, Anderson, Christopher D, Andersson, Charlotte, Anugu, Pramod, Appelbaum, Elizabeth, Ardlie, Kristin, Arking, Dan, Armasu, Sebastian M, Arnett, Donna K, Arruda, Heather, Arvanitis, Marios, Ashley-Koch, Allison, Ashrani, Aneel, Aslibekyan, Stella, Assimes, Tim, Atkinson, Elizabeth, Auer, Paul, Austin, Thomas R, Avery, Christy, Avila-Pacheco, Julian, Avillach, Paul, Aviv, Abraham, Avramopoulos, Dimitrios, Ballantyne, Christie, Balte, Pallavi, Bamshad, Michael, Bancks, Mike, Barnard, John, Barr, R Graham, Barron-Casella, Emily, Bartz, Traci, Barwick, Lucas, Basu, Saonli, Battle, Alexis, Baumann, Michael, Beame, David, Beaty, Terri, Beck, Gerald, Becker, Lewis, Becker, Diane, Beer, Rebecca, Begum, Ferdouse, Beiser, Alexa, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Berk-Rauch, Hanna, Besich, Zachary M, Bezerra, Marcos, Bhatt, Surya, Bi, Wenjian, Bick, Alexander, and Bielak, Larry

Subjects
Biological Sciences, Genetics, Human Genome, Good Health and Well Being, Adult, Amish, Cohort Studies, DNA Mutational Analysis, Female, Genetics, Population, Genome, Human, Heterozygote, Humans, Male, Mutation, Pedigree, Whole Genome Sequencing, Young Adult, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Population Genetics Working Group, de novo mutations, diversity, mutation rate, recombination
Abstract

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains

Published
2020

44. Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

Author

Kapoor, Pooja Middha, Lindström, Sara, Behrens, Sabine, Wang, Xiaoliang, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Dunning, Alison M, Pharoah, Paul DP, Schmidt, Marjanka K, Kraft, Peter, García-Closas, Montserrat, Easton, Douglas F, Milne, Roger L, Chang-Claude, Jenny, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bernstein, Leslie, Berrandou, Takiy, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brock, Ian W, Broeks, Annegien, Brooks-Wilson, Angela, Butterbach, Katja, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Clarke, Christine L, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Dite, Gillian S, Earp, H Shelton, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Harstad, Tricia, He, Wei, Heyworth, Jane, Hoover, Robert N, Hopper, John L, Humphreys, Keith, Hunter, David J, Marrón, Pablo Isidro, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Krüger, Ute, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, and Makalic, Enes

Subjects
Genetics, Estrogen, Clinical Research, Cancer, Breast Cancer, Prevention, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Europe, Factor XIII, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Risk Factors, White People, Breast Cancer Association Consortium, Europeans, Gene-environment interaction, breast cancer, epidemiology, risk factors, single nucleotide polymorphism, Statistics, Public Health and Health Services, Epidemiology
Abstract

BackgroundPrevious gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.MethodsAnalyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.ResultsNoteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.ConclusionsOverall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

Published
2020

45. A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Author

Escala-Garcia, Maria, Abraham, Jean, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Ashworth, Alan, Auer, Paul L, Auvinen, Päivi, Beckmann, Matthias W, Beesley, Jonathan, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Blot, William, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brucker, Sara Y, Burwinkel, Barbara, Caldas, Carlos, Canzian, Federico, Chang-Claude, Jenny, Chanock, Stephen J, Chin, Suet-Feung, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Dunn, Janet A, Dunning, Alison M, Dwek, Miriam, Earl, Helena M, Eccles, Diana M, Eliassen, A Heather, Ellberg, Carolina, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, George, Angela, Giles, Graham G, Goldgar, David E, González-Neira, Anna, Grip, Mervi, Guénel, Pascal, Guo, Qi, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Harrington, Patricia A, Hiller, Louise, Hooning, Maartje J, Hopper, John L, Howell, Anthony, Huang, Chiun-Sheng, Huang, Guanmengqian, Hunter, David J, Jakubowska, Anna, John, Esther M, Kaaks, Rudolf, Kapoor, Pooja Middha, Keeman, Renske, Kitahara, Cari M, Koppert, Linetta B, Kraft, Peter, Kristensen, Vessela N, Lambrechts, Diether, Le Marchand, Loic, Lejbkowicz, Flavio, Lindblom, Annika, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Maurer, Tabea, Mavroudis, Dimitrios, Meindl, Alfons, Milne, Roger L, Mulligan, Anna Marie, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Olshan, Andrew F, Olson, Janet E, and Olsson, Håkan

Subjects
Germ Cells, Humans, Breast Neoplasms, GTP-Binding Protein alpha Subunits, GTP-Binding Protein alpha Subunits, Gq-G11, Receptors, Estrogen, Prognosis, Computational Biology, Signal Transduction, Apoptosis, Genotype, Female, Gene Regulatory Networks, Genetic Variation, Genome-Wide Association Study, Circadian Clocks, Gq-G11, Receptors, Estrogen, Cancer, Breast Cancer, Genetics, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies
Abstract

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

Published
2020

46. Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Author

Fachal, Laura, Aschard, Hugues, Beesley, Jonathan, Barnes, Daniel R, Allen, Jamie, Kar, Siddhartha, Pooley, Karen A, Dennis, Joe, Michailidou, Kyriaki, Turman, Constance, Soucy, Penny, Lemaçon, Audrey, Lush, Michael, Tyrer, Jonathan P, Ghoussaini, Maya, Moradi Marjaneh, Mahdi, Jiang, Xia, Agata, Simona, Aittomäki, Kristiina, Alonso, M Rosario, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arason, Adalgeir, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Auber, Bernd, Auer, Paul L, Azzollini, Jacopo, Balmaña, Judith, Barkardottir, Rosa B, Barrowdale, Daniel, Beeghly-Fadiel, Alicia, Benitez, Javier, Bermisheva, Marina, Białkowska, Katarzyna, Blanco, Amie M, Blomqvist, Carl, Blot, William, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Borg, Ake, Bosse, Kristin, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Brock, Ian W, Brooks-Wilson, Angela, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Cai, Qiuyin, Caldés, Trinidad, Caligo, Maria A, Camp, Nicola J, Campbell, Ian, Canzian, Federico, Carroll, Jason S, Carter, Brian D, Castelao, Jose E, Chiquette, Jocelyne, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, GEMO Study Collaborators, EMBRACE Collaborators, Collée, J Margriet, Cornelissen, Sten, Couch, Fergus J, Cox, Angela, Cross, Simon S, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, de la Hoya, Miguel, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Dite, Gillian S, Domchek, Susan M, Dörk, Thilo, Dos-Santos-Silva, Isabel, Droit, Arnaud, Dubois, Stéphane, Dumont, Martine, Duran, Mercedes, Durcan, Lorraine, Dwek, Miriam, Eccles, Diana M, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Fletcher, Olivia, Floris, Giuseppe, and Flyger, Henrik

Subjects
GEMO Study Collaborators, EMBRACE Collaborators, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, Bayes Theorem, Risk Factors, Chromosome Mapping, Regulatory Sequences, Nucleic Acid, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Female, Genome-Wide Association Study, Biomarkers, Tumor, Genetic Testing, Prevention, Genetics, Cancer, Breast Cancer, Human Genome, Biotechnology, 2.1 Biological and endogenous factors, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Published
2020

47. Allelic Heterogeneity at the CRP Locus Identified by Whole-Genome Sequencing in Multi-ancestry Cohorts

Author

Raffield, Laura M, Iyengar, Apoorva K, Wang, Biqi, Gaynor, Sheila M, Spracklen, Cassandra N, Zhong, Xue, Kowalski, Madeline H, Salimi, Shabnam, Polfus, Linda M, Benjamin, Emelia J, Bis, Joshua C, Bowler, Russell, Cade, Brian E, Choi, Won Jung, Comellas, Alejandro P, Correa, Adolfo, Cruz, Pedro, Doddapaneni, Harsha, Durda, Peter, Gogarten, Stephanie M, Jain, Deepti, Kim, Ryan W, Kral, Brian G, Lange, Leslie A, Larson, Martin G, Laurie, Cecelia, Lee, Jiwon, Lee, Seonwook, Lewis, Joshua P, Metcalf, Ginger A, Mitchell, Braxton D, Momin, Zeineen, Muzny, Donna M, Pankratz, Nathan, Park, Cheol Joo, Rich, Stephen S, Rotter, Jerome I, Ryan, Kathleen, Seo, Daekwan, Tracy, Russell P, Viaud-Martinez, Karine A, Yanek, Lisa R, Zhao, Lue Ping, Lin, Xihong, Li, Bingshan, Li, Yun, Dupuis, Josée, Reiner, Alexander P, Mohlke, Karen L, Auer, Paul L, Group, TOPMed Inflammation Working, and Consortium, NHLBI Trans-Omics for Precision Medicine

Subjects
Human Genome, Clinical Research, Biotechnology, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Asian People, Black People, C-Reactive Protein, Cohort Studies, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, White People, Whole Genome Sequencing, TOPMed Inflammation Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, c-reactive protein, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (∼38× coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (∼10% and ∼1% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23 mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97 mg/L and major allele homozygotes with mean CRP of 4.11 mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.

Published
2020

48. Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Author

Kowalski, Madeline H, Qian, Huijun, Hou, Ziyi, Rosen, Jonathan D, Tapia, Amanda L, Shan, Yue, Jain, Deepti, Argos, Maria, Arnett, Donna K, Avery, Christy, Barnes, Kathleen C, Becker, Lewis C, Bien, Stephanie A, Bis, Joshua C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Buyske, Steve, Cai, Jianwen, Cho, Michael H, Choi, Seung Hoan, Choquet, Hélène, Cupples, L Adrienne, Cushman, Mary, Daya, Michelle, de Vries, Paul S, Ellinor, Patrick T, Faraday, Nauder, Fornage, Myriam, Gabriel, Stacey, Ganesh, Santhi K, Graff, Misa, Gupta, Namrata, He, Jiang, Heckbert, Susan R, Hidalgo, Bertha, Hodonsky, Chani J, Irvin, Marguerite R, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kardia, Sharon LR, Kelly, Tanika N, Kooperberg, Charles, Lasky-Su, Jessica A, Loos, Ruth JF, Lubitz, Steven A, Mathias, Rasika A, McHugh, Caitlin P, Montgomery, Courtney, Moon, Jee-Young, Morrison, Alanna C, Palmer, Nicholette D, Pankratz, Nathan, Papanicolaou, George J, Peralta, Juan M, Peyser, Patricia A, Rich, Stephen S, Rotter, Jerome I, Silverman, Edwin K, Smith, Jennifer A, Smith, Nicholas L, Taylor, Kent D, Thornton, Timothy A, Tiwari, Hemant K, Tracy, Russell P, Wang, Tao, Weiss, Scott T, Weng, Lu-Chen, Wiggins, Kerri L, Wilson, James G, Yanek, Lisa R, Zöllner, Sebastian, North, Kari E, Auer, Paul L, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology & Hemostasis Working Group, Raffield, Laura M, Reiner, Alexander P, and Li, Yun

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology & Hemostasis Working Group, Humans, Genetic Predisposition to Disease, Computational Biology, Genetics, Population, Gene Frequency, Linkage Disequilibrium, Databases, Genetic, Adult, Aged, Aged, 80 and over, Middle Aged, African Americans, Hispanic Americans, United States, Female, Male, Genome-Wide Association Study, beta-Globins, Genotyping Techniques, Precision Medicine, Whole Genome Sequencing, Genetics, Population, Databases, Genetic, and over, Developmental Biology
Abstract

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count 86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Published
2019

49. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

Author

Kachroo, Priyadarshini, Hecker, Julian, Chawes, Bo L, Ahluwalia, Tarunveer S, Cho, Michael H, Qiao, Dandi, Kelly, Rachel S, Chu, Su H, Virkud, Yamini V, Huang, Mengna, Barnes, Kathleen C, Burchard, Esteban G, Eng, Celeste, Hu, Donglei, Celedón, Juan C, Daya, Michelle, Levin, Albert M, Gui, Hongsheng, Williams, L Keoki, Forno, Erick, Mak, Angel CY, Avila, Lydiana, Soto-Quiros, Manuel E, Cloutier, Michelle M, Acosta-Pérez, Edna, Canino, Glorisa, Bønnelykke, Klaus, Bisgaard, Hans, Raby, Benjamin A, Lange, Christoph, Weiss, Scott T, Lasky-Su, Jessica A, National Heart, Lung, Abe, Namiko, Abecasis, Goncalo, Albert, Christine, Allred, Nicholette Palmer, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Barnard, John, Barnes, Kathleen, Barr, R Graham, Barron-Casella, Emily, Beaty, Terri, Becker, Diane, Becker, Lewis, Beer, Rebecca, Begum, Ferdouse, Beitelshees, Amber, Benjamin, Emelia, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Borecki, Ingrid, Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Burchard, Esteban, Cardwell, Jonathan, Carty, Cara, Casaburi, Richard, Casella, James, Chaffin, Mark, Chang, Christy, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Chen, Yii-Der Ida, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, and Das, Sayantan

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Clinical Research, Asthma, Genetics, Pediatric, Biotechnology, Human Genome, Lung, 2.1 Biological and endogenous factors, Respiratory, Adolescent, Adult, Cell Adhesion Molecules, Child, Child, Preschool, Costa Rica, Female, Forced Expiratory Volume, Humans, Interferon Regulatory Factors, Male, Middle Aged, Respiratory Physiological Phenomena, Vital Capacity, Whole Genome Sequencing, Young Adult, airway hyperresponsiveness, asthma, lung function, whole genome sequencing, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract

BackgroundAsthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma.MethodsWGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician's diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes.ResultsA genome-wide significant association was identified between baseline FEV1/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10-8 in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10-6). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV1 (P = 3.3 × 10-3), postbronchodilator (PB) FEV1 (7.3 × 10-3), and PB FEV1/FVC ratio (P = 2.7 × 10-3). The identified baseline FEV1/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR.ConclusionsThese findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

Published
2019

50. Genetic associations of breast and prostate cancer are enriched for regulatory elements identified in disease-related tissues

Author

Chen, Hongjie, Kichaev, Gleb, Bien, Stephanie A, MacDonald, James W, Wang, Lu, Bammler, Theo K, Auer, Paul, Pasaniuc, Bogdan, and Lindström, Sara

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Oncology and Carcinogenesis, Human Genome, Aging, Prostate Cancer, Prevention, Urologic Diseases, Cancer, Breast Cancer, Aetiology, 2.1 Biological and endogenous factors, Biomarkers, Tumor, Breast Neoplasms, Cell Line, Tumor, Computational Biology, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, Molecular Sequence Annotation, Organ Specificity, Prostatic Neoplasms, Regulatory Sequences, Nucleic Acid, Complementary and Alternative Medicine, Paediatrics and Reproductive Medicine, Genetics & Heredity, Reproductive medicine
Abstract

Although genome-wide association studies (GWAS) have identified hundreds of risk loci for breast and prostate cancer, only a few studies have characterized the GWAS association signals across functional genomic annotations with a particular focus on single nucleotide polymorphisms (SNPs) located in DNA regulatory elements. In this study, we investigated the enrichment pattern of GWAS signals for breast and prostate cancer in genomic functional regions located in normal tissue and cancer cell lines. We quantified the overall enrichment of SNPs with breast and prostate cancer association p values

Published
2019

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