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542 results on '"Kenny, Eimear E."'

1. An Ethical Framework for Research Using Genetic Ancestry

Author: Lewis, Anna C. F., Molina, Santiago J., Appelbaum, Paul S., Dauda, Bege, Fuentes, Agustin, Fullerton, Stephanie M., Garrison, Nanibaa’ A., Ghosh, Nayanika, Green, Robert C., Hammonds, Evelynn M., Jeff, Janina M., Jones, David S., Kenny, Eimear E., Kraft, Peter, Mauro, Madelyn, Ori, Anil P. S., Panofsky, Aaron, Sohail, Mashaal, Neale, Benjamin M., and Allen, Danielle S.
Published: 2023

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. 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

4. 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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5. Physician and informal care use explained by the Pediatric Quality of Life Inventory (PedsQL) in children with suspected genetic disorders

Author: Berkalieva, Asem, Kelly, Nicole R., Fisher, Ashley, Hohmann, Samuel F., Abul-Husn, Noura S., Greally, John M., Horowitz, Carol R., Wasserstein, Melissa P., Kenny, Eimear E., Gelb, Bruce D., and Ferket, Bart S.
Published: 2024
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6. Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region

Author: Caggiano, Christa, Boudaie, Arya, Shemirani, Ruhollah, Mefford, Joel, Petter, Ella, Chiu, Alec, Ercelen, Defne, He, Rosemary, Tward, Daniel, Paul, Kimberly C, Chang, Timothy S, Pasaniuc, Bogdan, Kenny, Eimear E, Shortt, Jonathan A, Gignoux, Christopher R, Balliu, Brunilda, Arboleda, Valerie A, Belbin, Gillian, and Zaitlen, Noah
Subjects: Health Services and Systems, Health Sciences, Health Services, Clinical Research, Genetics, Prevention, Patient Safety, Minority Health, Human Genome, Health Disparities, Good Health and Well Being, Humans, Los Angeles, Iran, Delivery of Health Care, Patient Acceptance of Health Care, Ethnicity, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract: An individual's disease risk is affected by the populations that they belong to, due to shared genetics and environmental factors. The study of fine-scale populations in clinical care is important for identifying and reducing health disparities and for developing personalized interventions. To assess patterns of clinical diagnoses and healthcare utilization by fine-scale populations, we leveraged genetic data and electronic medical records from 35,968 patients as part of the UCLA ATLAS Community Health Initiative. We defined clusters of individuals using identity by descent, a form of genetic relatedness that utilizes shared genomic segments arising due to a common ancestor. In total, we identified 376 clusters, including clusters with patients of Afro-Caribbean, Puerto Rican, Lebanese Christian, Iranian Jewish and Gujarati ancestry. Our analysis uncovered 1,218 significant associations between disease diagnoses and clusters and 124 significant associations with specialty visits. We also examined the distribution of pathogenic alleles and found 189 significant alleles at elevated frequency in particular clusters, including many that are not regularly included in population screening efforts. Overall, this work progresses the understanding of health in understudied communities and can provide the foundation for further study into health inequities.
Published: 2023

7. Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations

Author: Lennon, Niall J., Kottyan, Leah C., Kachulis, Christopher, Abul-Husn, Noura S., Arias, Josh, Belbin, Gillian, Below, Jennifer E., Berndt, Sonja I., Chung, Wendy K., Cimino, James J., Clayton, Ellen Wright, Connolly, John J., Crosslin, David R., Dikilitas, Ozan, Velez Edwards, Digna R., Feng, QiPing, Fisher, Marissa, Freimuth, Robert R., Ge, Tian, Glessner, Joseph T., Gordon, Adam S., Patterson, Candace, Hakonarson, Hakon, Harden, Maegan, Harr, Margaret, Hirschhorn, Joel N., Hoggart, Clive, Hsu, Li, Irvin, Marguerite R., Jarvik, Gail P., Karlson, Elizabeth W., Khan, Atlas, Khera, Amit, Kiryluk, Krzysztof, Kullo, Iftikhar, Larkin, Katie, Limdi, Nita, Linder, Jodell E., Loos, Ruth J. F., Luo, Yuan, Malolepsza, Edyta, Manolio, Teri A., Martin, Lisa J., McCarthy, Li, McNally, Elizabeth M., Meigs, James B., Mersha, Tesfaye B., Mosley, Jonathan D., Musick, Anjene, Namjou, Bahram, Pai, Nihal, Pesce, Lorenzo L., Peters, Ulrike, Peterson, Josh F., Prows, Cynthia A., Puckelwartz, Megan J., Rehm, Heidi L., Roden, Dan M., Rosenthal, Elisabeth A., Rowley, Robb, Sawicki, Konrad Teodor, Schaid, Daniel J., Smit, Roelof A. J., Smith, Johanna L., Smoller, Jordan W., Thomas, Minta, Tiwari, Hemant, Toledo, Diana M., Vaitinadin, Nataraja Sarma, Veenstra, David, Walunas, Theresa L., Wang, Zhe, Wei, Wei-Qi, Weng, Chunhua, Wiesner, Georgia L., Yin, Xianyong, and Kenny, Eimear E.
Published: 2024
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8. Principles and methods for transferring polygenic risk scores across global populations

Author: Kachuri, Linda, Chatterjee, Nilanjan, Hirbo, Jibril, Schaid, Daniel J., Martin, Iman, Kullo, Iftikhar J., Kenny, Eimear E., Pasaniuc, Bogdan, Witte, John S., and Ge, Tian
Published: 2024
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9. A draft human pangenome reference

Author: Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian K, Monlong, Jean, Abel, Haley J, Buonaiuto, Silvia, Chang, Xian H, Cheng, Haoyu, Chu, Justin, Colonna, Vincenza, Eizenga, Jordan M, Feng, Xiaowen, Fischer, Christian, Fulton, Robert S, Garg, Shilpa, Groza, Cristian, Guarracino, Andrea, Harvey, William T, Heumos, Simon, Howe, Kerstin, Jain, Miten, Lu, Tsung-Yu, Markello, Charles, Martin, Fergal J, Mitchell, Matthew W, Munson, Katherine M, Mwaniki, Moses Njagi, Novak, Adam M, Olsen, Hugh E, Pesout, Trevor, Porubsky, David, Prins, Pjotr, Sibbesen, Jonas A, Sirén, Jouni, Tomlinson, Chad, Villani, Flavia, Vollger, Mitchell R, Antonacci-Fulton, Lucinda L, Baid, Gunjan, Baker, Carl A, Belyaeva, Anastasiya, Billis, Konstantinos, Carroll, Andrew, Chang, Pi-Chuan, Cody, Sarah, Cook, Daniel E, Cook-Deegan, Robert M, Cornejo, Omar E, Diekhans, Mark, Ebert, Peter, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L, Formenti, Giulio, Frankish, Adam, Gao, Yan, Garrison, Nanibaa’ A, Giron, Carlos Garcia, Green, Richard E, Haggerty, Leanne, Hoekzema, Kendra, Hourlier, Thibaut, Ji, Hanlee P, Kenny, Eimear E, Koenig, Barbara A, Kolesnikov, Alexey, Korbel, Jan O, Kordosky, Jennifer, Koren, Sergey, Lee, HoJoon, Lewis, Alexandra P, Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, McCartney, Ann, McDaniel, Jennifer, Mountcastle, Jacquelyn, Nattestad, Maria, Nurk, Sergey, Olson, Nathan D, Popejoy, Alice B, Puiu, Daniela, Rautiainen, Mikko, Regier, Allison A, Rhie, Arang, Sacco, Samuel, Sanders, Ashley D, Schneider, Valerie A, Schultz, Baergen I, Shafin, Kishwar, Smith, Michael W, Sofia, Heidi J, Abou Tayoun, Ahmad N, Thibaud-Nissen, Françoise, and Tricomi, Francesca Floriana
Subjects: Biological Sciences, Genetics, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Diploidy, Genome, Human, Haplotypes, Sequence Analysis, DNA, Genomics, Reference Standards, Cohort Studies, Alleles, Genetic Variation, General Science & Technology
Abstract: Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.
Published: 2023

10. The genetic determinants of recurrent somatic mutations in 43,693 blood genomes

Author: Weinstock, Joshua S, Laurie, Cecelia A, Broome, Jai G, Taylor, Kent D, Guo, Xiuqing, Shuldiner, Alan R, O’Connell, Jeffrey R, Lewis, Joshua P, Boerwinkle, Eric, Barnes, Kathleen C, Chami, Nathalie, Kenny, Eimear E, Loos, Ruth JF, Fornage, Myriam, Redline, Susan, Cade, Brian E, Gilliland, Frank D, Chen, Zhanghua, Gauderman, W James, Kumar, Rajesh, Grammer, Leslie, Schleimer, Robert P, Psaty, Bruce M, Bis, Joshua C, Brody, Jennifer A, Silverman, Edwin K, Yun, Jeong H, Qiao, Dandi, Weiss, Scott T, Lasky-Su, Jessica, DeMeo, Dawn L, Palmer, Nicholette D, Freedman, Barry I, Bowden, Donald W, Cho, Michael H, Vasan, Ramachandran S, Johnson, Andrew D, Yanek, Lisa R, Becker, Lewis C, Kardia, Sharon, He, Jiang, Kaplan, Robert, Heckbert, Susan R, Smith, Nicholas L, Wiggins, Kerri L, Arnett, Donna K, Irvin, Marguerite R, Tiwari, Hemant, Correa, Adolfo, Raffield, Laura M, Gao, Yan, de Andrade, Mariza, Rotter, Jerome I, Rich, Stephen S, Manichaikul, Ani W, Konkle, Barbara A, Johnsen, Jill M, Wheeler, Marsha M, Custer, Brian S, Duggirala, Ravindranath, Curran, Joanne E, Blangero, John, Gui, Hongsheng, Xiao, Shujie, Williams, L Keoki, Meyers, Deborah A, Li, Xingnan, Ortega, Victor, McGarvey, Stephen, Gu, C Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M Benjamin, Darbar, Dawood, Roden, Dan, Albert, Christine, Kooperberg, Charles, Desai, Pinkal, Blackwell, Thomas W, Abecasis, Goncalo R, Smith, Albert V, Kang, Hyun M, Mathias, Rasika, Natarajan, Pradeep, Jaiswal, Siddhartha, Reiner, Alexander P, Bick, Alexander G, and Consortium, NHLBI Trans-Omics for Precision Medicine
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Lung, Genetic Testing, Clinical Research, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Humans, Middle Aged, Hematopoiesis, Mutation, Germ-Line Mutation, Mutation, Missense, Phenotype, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract: Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.
Published: 2023

11. Gaps and complex structurally variant loci in phased genome assemblies

Author: Porubsky, David, Vollger, Mitchell R, Harvey, William T, Rozanski, Allison N, Ebert, Peter, Hickey, Glenn, Hasenfeld, Patrick, Sanders, Ashley D, Stober, Catherine, Consortium, Human Pangenome Reference, Korbel, Jan O, Paten, Benedict, Marschall, Tobias, Eichler, Evan E, Abel, Haley J, Antonacci-Fulton, Lucinda L, Asri, Mobin, Baid, Gunjan, Baker, Carl A, Belyaeva, Anastasiya, Billis, Konstantinos, Bourque, Guillaume, Buonaiuto, Silvia, Carroll, Andrew, Chaisson, Mark JP, Chang, Pi-Chuan, Chang, Xian H, Cheng, Haoyu, Chu, Justin, Cody, Sarah, Colonna, Vincenza, Cook, Daniel E, Cook-Deegan, Robert M, Cornejo, Omar E, Diekhans, Mark, Doerr, Daniel, Ebler, Jana, Eizenga, Jordan M, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L, Feng, Xiaowen, Fischer, Christian, Flicek, Paul, Formenti, Giulio, Frankish, Adam, Fulton, Robert S, Gao, Yan, Garg, Shilpa, Garrison, Erik, Garrison, Nanibaa’ A, Giron, Carlos Garcia, Green, Richard E, Groza, Cristian, Guarracino, Andrea, Haggerty, Leanne, Hall, Ira M, Haukness, Marina, Haussler, David, Heumos, Simon, Hoekzema, Kendra, Hourlier, Thibaut, Howe, Kerstin, Jain, Miten, Jarvis, Erich D, Ji, Hanlee P, Kenny, Eimear E, Koenig, Barbara A, Kolesnikov, Alexey, Kordosky, Jennifer, Koren, Sergey, Lee, HoJoon, Lewis, Alexandra P, Li, Heng, Liao, Wen-Wei, Lu, Shuangjia, Lu, Tsung-Yu, Lucas, Julian K, Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, Markello, Charles, Martin, Fergal J, McCartney, Ann, McDaniel, Jennifer, Miga, Karen H, Mitchell, Matthew W, Monlong, Jean, Mountcastle, Jacquelyn, Munson, Katherine M, Mwaniki, Moses Njagi, Nattestad, Maria, Novak, Adam M, and Nurk, Sergey
Subjects: Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Humans, DNA, Satellite, Polymorphism, Genetic, Haplotypes, Segmental Duplications, Genomic, Sequence Analysis, DNA, Human Pangenome Reference Consortium, Medical and Health Sciences, Bioinformatics
Abstract: There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.
Published: 2023

12. Rare coding variants in RCN3 are associated with blood pressure

Author: He, Karen Y, Kelly, Tanika N, Wang, Heming, Liang, Jingjing, Zhu, Luke, Cade, Brian E, Assimes, Themistocles L, Becker, Lewis C, Beitelshees, Amber L, Bielak, Lawrence F, Bress, Adam P, Brody, Jennifer A, Chang, Yen-Pei Christy, Chang, Yi-Cheng, de Vries, Paul S, Duggirala, Ravindranath, Fox, Ervin R, Franceschini, Nora, Furniss, Anna L, Gao, Yan, Guo, Xiuqing, Haessler, Jeffrey, Hung, Yi-Jen, Hwang, Shih-Jen, Irvin, Marguerite Ryan, Kalyani, Rita R, Liu, Ching-Ti, Liu, Chunyu, Martin, Lisa Warsinger, Montasser, May E, Muntner, Paul M, Mwasongwe, Stanford, Naseri, Take, Palmas, Walter, Reupena, Muagututi’a Sefuiva, Rice, Kenneth M, Sheu, Wayne H-H, Shimbo, Daichi, Smith, Jennifer A, Snively, Beverly M, Yanek, Lisa R, Zhao, Wei, Blangero, John, Boerwinkle, Eric, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Fornage, Myriam, He, Jiang, Hou, Lifang, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear E, Kooperberg, Charles, Lloyd-Jones, Donald, Loos, Ruth JF, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, North, Kari E, Peyser, Patricia A, Psaty, Bruce M, Raffield, Laura M, Rao, DC, Redline, Susan, Reiner, Alex P, Rich, Stephen S, Rotter, Jerome I, Taylor, Kent D, Tracy, Russell, Vasan, Ramachandran S, Morrison, Alanna C, Levy, Daniel, Chakravarti, Aravinda, Arnett, Donna K, and Zhu, Xiaofeng
Subjects: Biological Sciences, Genetics, Cardiovascular, Human Genome, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Pressure, Genetic Linkage, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Precision Medicine, Whole Genome Sequencing, Rare variant analysis, Blood pressure, Whole genome sequencing, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics, Biological sciences, Biomedical and clinical sciences
Abstract: BackgroundWhile large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries.ResultsAssociations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10- 7).ConclusionsLow frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
Published: 2022

13. Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts

Author: Anwar, Mohammad Yaser, Graff, Mariaelisa, Highland, Heather M., Smit, Roelof, Wang, Zhe, Buchanan, Victoria L., Young, Kristin L., Kenny, Eimear E., Fernandez-Rhodes, Lindsay, Liu, Simin, Assimes, Themistocles, Garcia, David O., Daeeun, Kim, Gignoux, Christopher R., Justice, Anne E., Haiman, Christopher A., Buyske, Steve, Peters, Ulrike, Loos, Ruth J. F., Kooperberg, Charles, and North, Kari E.
Published: 2023
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14. Strong protective effect of the APOL1 p.N264K variant against G2-associated focal segmental glomerulosclerosis and kidney disease

Author: Gupta, Yask, Friedman, David J., McNulty, Michelle T., Khan, Atlas, Lane, Brandon, Wang, Chen, Ke, Juntao, Jin, Gina, Wooden, Benjamin, Knob, Andrea L., Lim, Tze Y., Appel, Gerald B., Huggins, Kinsie, Liu, Lili, Mitrotti, Adele, Stangl, Megan C., Bomback, Andrew, Westland, Rik, Bodria, Monica, Marasa, Maddalena, Shang, Ning, Cohen, David J., Crew, Russell J., Morello, William, Canetta, Pietro, Radhakrishnan, Jai, Martino, Jeremiah, Liu, Qingxue, Chung, Wendy K., Espinoza, Angelica, Luo, Yuan, Wei, Wei-Qi, Feng, Qiping, Weng, Chunhua, Fang, Yilu, Kullo, Iftikhar J., Naderian, Mohammadreza, Limdi, Nita, Irvin, Marguerite R., Tiwari, Hemant, Mohan, Sumit, Rao, Maya, Dube, Geoffrey K., Chaudhary, Ninad S., Gutiérrez, Orlando M., Judd, Suzanne E., Cushman, Mary, Lange, Leslie A., Lange, Ethan M., Bivona, Daniel L., Verbitsky, Miguel, Winkler, Cheryl A., Kopp, Jeffrey B., Santoriello, Dominick, Batal, Ibrahim, Pinheiro, Sérgio Veloso Brant, Oliveira, Eduardo Araújo, Simoes e Silva, Ana Cristina, Pisani, Isabella, Fiaccadori, Enrico, Lin, Fangming, Gesualdo, Loreto, Amoroso, Antonio, Ghiggeri, Gian Marco, D’Agati, Vivette D., Magistroni, Riccardo, Kenny, Eimear E., Loos, Ruth J. F., Montini, Giovanni, Hildebrandt, Friedhelm, Paul, Dirk S., Petrovski, Slavé, Goldstein, David B., Kretzler, Matthias, Gbadegesin, Rasheed, Gharavi, Ali G., Kiryluk, Krzysztof, Sampson, Matthew G., Pollak, Martin R., and Sanna-Cherchi, Simone
Published: 2023
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15. Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome

Author: Barry, Alexandra, McNulty, Michelle T., Jia, Xiaoyuan, Gupta, Yask, Debiec, Hanna, Luo, Yang, Nagano, China, Horinouchi, Tomoko, Jung, Seulgi, Colucci, Manuela, Ahram, Dina F., Mitrotti, Adele, Sinha, Aditi, Teeninga, Nynke, Jin, Gina, Shril, Shirlee, Caridi, Gianluca, Bodria, Monica, Lim, Tze Y., Westland, Rik, Zanoni, Francesca, Marasa, Maddalena, Turudic, Daniel, Giordano, Mario, Gesualdo, Loreto, Magistroni, Riccardo, Pisani, Isabella, Fiaccadori, Enrico, Reiterova, Jana, Maringhini, Silvio, Morello, William, Montini, Giovanni, Weng, Patricia L., Scolari, Francesco, Saraga, Marijan, Tasic, Velibor, Santoro, Domenica, van Wijk, Joanna A. E., Milošević, Danko, Kawai, Yosuke, Kiryluk, Krzysztof, Pollak, Martin R., Gharavi, Ali, Lin, Fangmin, Simœs e Silva, Ana Cristina, Loos, Ruth J. F., Kenny, Eimear E., Schreuder, Michiel F., Zurowska, Aleksandra, Dossier, Claire, Ariceta, Gema, Drozynska-Duklas, Magdalena, Hogan, Julien, Jankauskiene, Augustina, Hildebrandt, Friedhelm, Prikhodina, Larisa, Song, Kyuyoung, Bagga, Arvind, Cheong, II, Hae, Ghiggeri, Gian Marco, Vachvanichsanong, Prayong, Nozu, Kandai, Lee, Dongwon, Vivarelli, Marina, Raychaudhuri, Soumya, Tokunaga, Katsushi, Sanna-Cherchi, Simone, Ronco, Pierre, Iijima, Kazumoto, and Sampson, Matthew G.
Published: 2023
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16. The TeleKidSeq pilot study: incorporating telehealth into clinical care of children from diverse backgrounds undergoing whole genome sequencing

Author: Sebastin, Monisha, Odgis, Jacqueline A., Suckiel, Sabrina A., Bonini, Katherine E., Di Biase, Miranda, Brown, Kaitlyn, Marathe, Priya, Kelly, Nicole R., Ramos, Michelle A., Rodriguez, Jessica E., Aguiñiga, Karla López, Lopez, Jessenia, Maria, Estefany, Rodriguez, Michelle A., Yelton, Nicole M., Cunningham-Rundles, Charlotte, Gallagher, Katie, McDonald, Thomas V., McGoldrick, Patricia E., Robinson, Mimsie, Rubinstein, Arye, Shulman, Lisa H., Wolf, Steven M., Yozawitz, Elissa, Zinberg, Randi E., Abul-Husn, Noura S., Bauman, Laurie J., Diaz, George A., Ferket, Bart S., Greally, John M., Jobanputra, Vaidehi, Gelb, Bruce D., Horowitz, Carol R., Kenny, Eimear E., and Wasserstein, Melissa P.
Published: 2023
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17. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author: Kelly, Tanika N, Sun, Xiao, He, Karen Y, Brown, Michael R, Taliun, Sarah A Gagliano, Hellwege, Jacklyn N, Irvin, Marguerite R, Mi, Xuenan, Brody, Jennifer A, Franceschini, Nora, Guo, Xiuqing, Hwang, Shih-Jen, de Vries, Paul S, Gao, Yan, Moscati, Arden, Nadkarni, Girish N, Yanek, Lisa R, Elfassy, Tali, Smith, Jennifer A, Chung, Ren-Hua, Beitelshees, Amber L, Patki, Amit, Aslibekyan, Stella, Blobner, Brandon M, Peralta, Juan M, Assimes, Themistocles L, Palmas, Walter R, Liu, Chunyu, Bress, Adam P, Huang, Zhijie, Becker, Lewis C, Hwa, Chii-Min, O’Connell, Jeffrey R, Carlson, Jenna C, Warren, Helen R, Das, Sayantan, Giri, Ayush, Martin, Lisa W, Johnson, W Craig, Fox, Ervin R, Bottinger, Erwin P, Razavi, Alexander C, Vaidya, Dhananjay, Chuang, Lee-Ming, Chang, Yen-Pei C, Naseri, Take, Jain, Deepti, Kang, Hyun Min, Hung, Adriana M, Srinivasasainagendra, Vinodh, Snively, Beverly M, Gu, Dongfeng, Montasser, May E, Reupena, Muagututi A Sefuiva, Heavner, Benjamin D, LeFaive, Jonathon, Hixson, James E, Rice, Kenneth M, Wang, Fei Fei, Nielsen, Jonas B, Huang, Jianfeng, Khan, Alyna T, Zhou, Wei, Nierenberg, Jovia L, Laurie, Cathy C, Armstrong, Nicole D, Shi, Mengyao, Pan, Yang, Stilp, Adrienne M, Emery, Leslie, Wong, Quenna, Hawley, Nicola L, Minster, Ryan L, Curran, Joanne E, Munroe, Patricia B, Weeks, Daniel E, North, Kari E, Tracy, Russell P, Kenny, Eimear E, Shimbo, Daichi, Chakravarti, Aravinda, Rich, Stephen S, Reiner, Alex P, Blangero, John, Redline, Susan, Mitchell, Braxton D, Rao, Dabeeru C, Chen, Yii-Der Ida, Kardia, Sharon LR, Kaplan, Robert C, Mathias, Rasika A, He, Jiang, Psaty, Bruce M, Fornage, Myriam, Loos, Ruth JF, Correa, Adolfo, Boerwinkle, Eric, Rotter, Jerome I, Kooperberg, Charles, and Edwards, Todd L
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Good Health and Well Being, Blood Pressure, Genome-Wide Association Study, Genomics, Humans, Hypertension, Polymorphism, Single Nucleotide, Precision Medicine, allele, blood pressure, genome, hypertension, whole genome sequencing, Samoan Obesity, Lifestyle, and Genetic Adaptations Study (OLaGA) Group, ‡ NHLBI Trans-Omics for Precision Medicine TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract: BackgroundThe availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.MethodsWe conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.ResultsTwo blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P
Published: 2022

18. 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

19. Evaluating parental personal utility of pediatric genetic and genomic testing in a diverse, multilingual population

Author: Marathe, Priya N., Suckiel, Sabrina A., Bonini, Katherine E., Kelly, Nicole R., Scarimbolo, Laura, Insel, Beverly J., Odgis, Jacqueline A., Sebastin, Monisha, Ramos, Michelle A., Di Biase, Miranda, Gallagher, Katie M., Brown, Kaitlyn, Rodriguez, Jessica E., Yelton, Nicole, Aguiñiga, Karla Lopez, Rodriguez, Michelle A., Maria, Estefany, Lopez, Jessenia, Zinberg, Randi E., Diaz, George A., Greally, John M., Abul-Husn, Noura S., Bauman, Laurie J., Gelb, Bruce D., Wasserstein, Melissa P., Kenny, Eimear E., and Horowitz, Carol R.
Published: 2024
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20. Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network

Author: Lewis, Anna C.F., Chisholm, Rex L., Connolly, John J., Esplin, Edward D., Glessner, Joe, Gordon, Adam, Green, Robert C., Hakonarson, Hakon, Harr, Margaret, Holm, Ingrid A., Jarvik, Gail P., Karlson, Elizabeth, Kenny, Eimear E., Kottyan, Leah, Lennon, Niall, Linder, Jodell E., Luo, Yuan, Martin, Lisa J., Perez, Emma, Puckelwartz, Megan J., Rasmussen-Torvik, Laura J., Sabatello, Maya, Sharp, Richard R., Smoller, Jordan W., Sterling, Rene, Terek, Shannon, Wei, Wei-Qi, and Fullerton, Stephanie M.
Published: 2024
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21. Genome-wide association analyses define pathogenic signaling pathways and prioritize drug targets for IgA nephropathy

Author: Kiryluk, Krzysztof, Sanchez-Rodriguez, Elena, Zhou, Xu-Jie, Zanoni, Francesca, Liu, Lili, Mladkova, Nikol, Khan, Atlas, Marasa, Maddalena, Zhang, Jun Y., Balderes, Olivia, Sanna-Cherchi, Simone, Bomback, Andrew S., Canetta, Pietro A., Appel, Gerald B., Radhakrishnan, Jai, Trimarchi, Hernan, Sprangers, Ben, Cattran, Daniel C., Reich, Heather, Pei, York, Ravani, Pietro, Galesic, Kresimir, Maixnerova, Dita, Tesar, Vladimir, Stengel, Benedicte, Metzger, Marie, Canaud, Guillaume, Maillard, Nicolas, Berthoux, Francois, Berthelot, Laureline, Pillebout, Evangeline, Monteiro, Renato, Nelson, Raoul, Wyatt, Robert J., Smoyer, William, Mahan, John, Samhar, Al-Akash, Hidalgo, Guillermo, Quiroga, Alejandro, Weng, Patricia, Sreedharan, Raji, Selewski, David, Davis, Keefe, Kallash, Mahmoud, Vasylyeva, Tetyana L., Rheault, Michelle, Chishti, Aftab, Ranch, Daniel, Wenderfer, Scott E., Samsonov, Dmitry, Claes, Donna J., Akchurin, Oleh, Goumenos, Dimitrios, Stangou, Maria, Nagy, Judit, Kovacs, Tibor, Fiaccadori, Enrico, Amoroso, Antonio, Barlassina, Cristina, Cusi, Daniele, Del Vecchio, Lucia, Battaglia, Giovanni Giorgio, Bodria, Monica, Boer, Emanuela, Bono, Luisa, Boscutti, Giuliano, Caridi, Gianluca, Lugani, Francesca, Ghiggeri, GianMarco, Coppo, Rosanna, Peruzzi, Licia, Esposito, Vittoria, Esposito, Ciro, Feriozzi, Sandro, Polci, Rosaria, Frasca, Giovanni, Galliani, Marco, Garozzo, Maurizio, Mitrotti, Adele, Gesualdo, Loreto, Granata, Simona, Zaza, Gianluigi, Londrino, Francesco, Magistroni, Riccardo, Pisani, Isabella, Magnano, Andrea, Marcantoni, Carmelita, Messa, Piergiorgio, Mignani, Renzo, Pani, Antonello, Ponticelli, Claudio, Roccatello, Dario, Salvadori, Maurizio, Salvi, Erica, Santoro, Domenico, Gembillo, Guido, Savoldi, Silvana, Spotti, Donatella, Zamboli, Pasquale, Izzi, Claudia, Alberici, Federico, Delbarba, Elisa, Florczak, Michał, Krata, Natalia, Mucha, Krzysztof, Pączek, Leszek, Niemczyk, Stanisław, Moszczuk, Barbara, Pańczyk-Tomaszewska, Malgorzata, Mizerska-Wasiak, Malgorzata, Perkowska-Ptasińska, Agnieszka, Bączkowska, Teresa, Durlik, Magdalena, Pawlaczyk, Krzysztof, Sikora, Przemyslaw, Zaniew, Marcin, Kaminska, Dorota, Krajewska, Magdalena, Kuzmiuk-Glembin, Izabella, Heleniak, Zbigniew, Bullo-Piontecka, Barbara, Liberek, Tomasz, Dębska-Slizien, Alicja, Hryszko, Tomasz, Materna-Kiryluk, Anna, Miklaszewska, Monika, Szczepańska, Maria, Dyga, Katarzyna, Machura, Edyta, Siniewicz-Luzeńczyk, Katarzyna, Pawlak-Bratkowska, Monika, Tkaczyk, Marcin, Runowski, Dariusz, Kwella, Norbert, Drożdż, Dorota, Habura, Ireneusz, Kronenberg, Florian, Prikhodina, Larisa, van Heel, David, Fontaine, Bertrand, Cotsapas, Chris, Wijmenga, Cisca, Franke, Andre, Annese, Vito, Gregersen, Peter K., Parameswaran, Sreeja, Weirauch, Matthew, Kottyan, Leah, Harley, John B., Suzuki, Hitoshi, Narita, Ichiei, Goto, Shin, Lee, Hajeong, Kim, Dong Ki, Kim, Yon Su, Park, Jin-Ho, Cho, BeLong, Choi, Murim, Van Wijk, Ans, Huerta, Ana, Ars, Elisabet, Ballarin, Jose, Lundberg, Sigrid, Vogt, Bruno, Mani, Laila-Yasmin, Caliskan, Yasar, Barratt, Jonathan, Abeygunaratne, Thilini, Kalra, Philip A., Gale, Daniel P., Panzer, Ulf, Rauen, Thomas, Floege, Jürgen, Schlosser, Pascal, Ekici, Arif B., Eckardt, Kai-Uwe, Chen, Nan, Xie, Jingyuan, Lifton, Richard P., Loos, Ruth J. F., Kenny, Eimear E., Ionita-Laza, Iuliana, Köttgen, Anna, Julian, Bruce A., Novak, Jan, Scolari, Francesco, Zhang, Hong, and Gharavi, Ali G.
Published: 2023
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22. Getting Genetic Ancestry Right for Science and Society

Author: Lewis, Anna C. F., Molina, Santiago J., Appelbaum, Paul S, Dauda, Bege, Di Rienzo, Anna, Fuentes, Agustin, Fullerton, Stephanie M., Garrison, Nanibaa' A., Ghosh, Nayanika, Hammonds, Evelynn M., Jones, David S., Kenny, Eimear E., Kraft, Peter, Lee, Sandra S. -J., Mauro, Madelyn, Novembre, John, Panofsky, Aaron, Sohail, Mashaal, Neale, Benjamin M., and Allen, Danielle S.
Subjects: Quantitative Biology - Populations and Evolution
Abstract: There is a scientific and ethical imperative to embrace a multidimensional, continuous view of ancestry and move away from continental ancestry categories
Published: 2021
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23. The Human Pangenome Project: a global resource to map genomic diversity

Author: Wang, Ting, Antonacci-Fulton, Lucinda, Howe, Kerstin, Lawson, Heather A, Lucas, Julian K, Phillippy, Adam M, Popejoy, Alice B, Asri, Mobin, Carson, Caryn, Chaisson, Mark JP, Chang, Xian, Cook-Deegan, Robert, Felsenfeld, Adam L, Fulton, Robert S, Garrison, Erik P, Garrison, Nanibaa’ A, Graves-Lindsay, Tina A, Ji, Hanlee, Kenny, Eimear E, Koenig, Barbara A, Li, Daofeng, Marschall, Tobias, McMichael, Joshua F, Novak, Adam M, Purushotham, Deepak, Schneider, Valerie A, Schultz, Baergen I, Smith, Michael W, Sofia, Heidi J, Weissman, Tsachy, Flicek, Paul, Li, Heng, Miga, Karen H, Paten, Benedict, Jarvis, Erich D, Hall, Ira M, Eichler, Evan E, and Haussler, David
Subjects: Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Biotechnology, Generic health relevance, Genome, Human, Genomics, Haplotypes, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Human Pangenome Reference Consortium, General Science & Technology
Abstract: The human reference genome is the most widely used resource in human genetics and is due for a major update. Its current structure is a linear composite of merged haplotypes from more than 20 people, with a single individual comprising most of the sequence. It contains biases and errors within a framework that does not represent global human genomic variation. A high-quality reference with global representation of common variants, including single-nucleotide variants, structural variants and functional elements, is needed. The Human Pangenome Reference Consortium aims to create a more sophisticated and complete human reference genome with a graph-based, telomere-to-telomere representation of global genomic diversity. Here we leverage innovations in technology, study design and global partnerships with the goal of constructing the highest-possible quality human pangenome reference. Our goal is to improve data representation and streamline analyses to enable routine assembly of complete diploid genomes. With attention to ethical frameworks, the human pangenome reference will contain a more accurate and diverse representation of global genomic variation, improve gene-disease association studies across populations, expand the scope of genomics research to the most repetitive and polymorphic regions of the genome, and serve as the ultimate genetic resource for future biomedical research and precision medicine.
Published: 2022

24. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential

Author: Nakao, Tetsushi, Bick, Alexander G, Taub, Margaret A, Zekavat, Seyedeh M, Uddin, Md M, Niroula, Abhishek, Carty, Cara L, Lane, John, Honigberg, Michael C, Weinstock, Joshua S, Pampana, Akhil, Gibson, Christopher J, Griffin, Gabriel K, Clarke, Shoa L, Bhattacharya, Romit, Assimes, Themistocles L, Emery, Leslie S, Stilp, Adrienne M, Wong, Quenna, Broome, Jai, Laurie, Cecelia A, Khan, Alyna T, Smith, Albert V, Blackwell, Thomas W, Codd, Veryan, Nelson, Christopher P, Yoneda, Zachary T, Peralta, Juan M, Bowden, Donald W, Irvin, Marguerite R, Boorgula, Meher, Zhao, Wei, Yanek, Lisa R, Wiggins, Kerri L, Hixson, James E, Gu, C Charles, Peloso, Gina M, Roden, Dan M, Reupena, Muagututi’a S, Hwu, Chii-Min, DeMeo, Dawn L, North, Kari E, Kelly, Shannon, Musani, Solomon K, Bis, Joshua C, Lloyd-Jones, Donald M, Johnsen, Jill M, Preuss, Michael, Tracy, Russell P, Peyser, Patricia A, Qiao, Dandi, Desai, Pinkal, Curran, Joanne E, Freedman, Barry I, Tiwari, Hemant K, Chavan, Sameer, Smith, Jennifer A, Smith, Nicholas L, Kelly, Tanika N, Hidalgo, Bertha, Cupples, L Adrienne, Weeks, Daniel E, Hawley, Nicola L, Minster, Ryan L, Deka, Ranjan, Naseri, Take T, de las Fuentes, Lisa, Raffield, Laura M, Morrison, Alanna C, Vries, Paul S, Ballantyne, Christie M, Kenny, Eimear E, Rich, Stephen S, Whitsel, Eric A, Cho, Michael H, Shoemaker, M Benjamin, Pace, Betty S, Blangero, John, Palmer, Nicholette D, Mitchell, Braxton D, Shuldiner, Alan R, Barnes, Kathleen C, Redline, Susan, Kardia, Sharon LR, Abecasis, Gonçalo R, Becker, Lewis C, Heckbert, Susan R, He, Jiang, Post, Wendy, Arnett, Donna K, Vasan, Ramachandran S, Darbar, Dawood, Weiss, Scott T, McGarvey, Stephen T, de Andrade, Mariza, Chen, Yii-Der Ida, Kaplan, Robert C, Meyers, Deborah A, Custer, Brian S, and Correa, Adolfo
Subjects: Cardiovascular, Genetics, Aging, Heart Disease, Heart Disease - Coronary Heart Disease, Human Genome, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract: Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.
Published: 2022

25. MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups

Author: Aslibekyan, Stella, Auton, Adam, Babalola, Elizabeth, Bell, Robert K., Bielenberg, Jessica, Bryc, Katarzyna, Bullis, Emily, Coker, Daniella, Cuellar Partida, Gabriel, Dhamija, Devika, Das, Sayantan, Elson, Sarah L., Eriksson, Nicholas, Filshtein, Teresa, Fitch, Alison, Fletez-Brant, Kipper, Fontanillas, Pierre, Freyman, Will, Granka, Julie M., Heilbron, Karl, Hernandez, Alejandro, Hicks, Barry, Hinds, David A., Jewett, Ethan M., Jiang, Yunxuan, Kukar, Katelyn, Kwong, Alan, Lin, Keng-Han, Llamas, Bianca A., Lowe, Maya, McCreight, Jey C., McIntyre, Matthew H., Micheletti, Steven J., Moreno, Meghan E., Nandakumar, Priyanka, Nguyen, Dominique T., Noblin, Elizabeth S., O’Connell, Jared, Petrakovitz, Aaron A., Poznik, G. David, Reynoso, Alexandra, Schumacher, Morgan, Shastri, Anjali J., Shelton, Janie F., Shi, Jingchunzi, Shringarpure, Suyash, Su, Qiaojuan Jane, Tat, Susana A., Tchakouté, Christophe Toukam, Tran, Vinh, Tung, Joyce Y., Wang, Xin, Wang, Wei, Weldon, Catherine H., Wilton, Peter, Wong, Corinna D., Jin, Jin, Zhan, Jianan, Zhang, Jingning, Zhao, Ruzhang, Buyske, Steven, Gignoux, Christopher, Haiman, Christopher, Kenny, Eimear E., Kooperberg, Charles, North, Kari, Koelsch, Bertram L., Wojcik, Genevieve, Zhang, Haoyu, and Chatterjee, Nilanjan
Published: 2024
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26. 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

27. Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis

Author: Weinstock, Joshua S., Gopakumar, Jayakrishnan, Burugula, Bala Bharathi, Uddin, Md Mesbah, Jahn, Nikolaus, Belk, Julia A., Bouzid, Hind, Daniel, Bence, Miao, Zhuang, Ly, Nghi, Mack, Taralynn M., Luna, Sofia E., Prothro, Katherine P., Mitchell, Shaneice R., Laurie, Cecelia A., Broome, Jai G., Taylor, Kent D., Guo, Xiuqing, Sinner, Moritz F., von Falkenhausen, Aenne S., Kääb, Stefan, Shuldiner, Alan R., O’Connell, Jeffrey R., Lewis, Joshua P., Boerwinkle, Eric, Barnes, Kathleen C., Chami, Nathalie, Kenny, Eimear E., Loos, Ruth J. F., Fornage, Myriam, Hou, Lifang, Lloyd-Jones, Donald M., Redline, Susan, Cade, Brian E., Psaty, Bruce M., Bis, Joshua C., Brody, Jennifer A., Silverman, Edwin K., Yun, Jeong H., Qiao, Dandi, Palmer, Nicholette D., Freedman, Barry I., Bowden, Donald W., Cho, Michael H., DeMeo, Dawn L., Vasan, Ramachandran S., Yanek, Lisa R., Becker, Lewis C., Kardia, Sharon L. R., Peyser, Patricia A., He, Jiang, Rienstra, Michiel, Van der Harst, Pim, Kaplan, Robert, Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Arnett, Donna K., Irvin, Marguerite R., Tiwari, Hemant, Cutler, Michael J., Knight, Stacey, Muhlestein, J. Brent, Correa, Adolfo, Raffield, Laura M., Gao, Yan, de Andrade, Mariza, Rotter, Jerome I., Rich, Stephen S., Tracy, Russell P., Konkle, Barbara A., Johnsen, Jill M., Wheeler, Marsha M., Smith, J. Gustav, Melander, Olle, Nilsson, Peter M., Custer, Brian S., Duggirala, Ravindranath, Curran, Joanne E., Blangero, John, McGarvey, Stephen, Williams, L. Keoki, Xiao, Shujie, Yang, Mao, Gu, C. Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Marcus, Gregory M., Kane, John P., Pullinger, Clive R., Shoemaker, M. Benjamin, Darbar, Dawood, Roden, Dan M., Albert, Christine, Kooperberg, Charles, Zhou, Ying, Manson, JoAnn E., Desai, Pinkal, Johnson, Andrew D., Mathias, Rasika A., Blackwell, Thomas W., Abecasis, Goncalo R., Smith, Albert V., Kang, Hyun M., Satpathy, Ansuman T., Natarajan, Pradeep, Kitzman, Jacob O., Whitsel, Eric A., Reiner, Alexander P., Bick, Alexander G., and Jaiswal, Siddhartha
Published: 2023
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28. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals

Author: Hou, Kangcheng, Ding, Yi, Xu, Ziqi, Wu, Yue, Bhattacharya, Arjun, Mester, Rachel, Belbin, Gillian M., Buyske, Steve, Conti, David V., Darst, Burcu F., Fornage, Myriam, Gignoux, Chris, Guo, Xiuqing, Haiman, Christopher, Kenny, Eimear E., Kim, Michelle, Kooperberg, Charles, Lange, Leslie, Manichaikul, Ani, North, Kari E., Peters, Ulrike, Rasmussen-Torvik, Laura J., Rich, Stephen S., Rotter, Jerome I., Wheeler, Heather E., Wojcik, Genevieve L., Zhou, Ying, Sankararaman, Sriram, and Pasaniuc, Bogdan
Published: 2023
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29. Physician services and costs after disclosure of diagnostic sequencing results in the NYCKidSeq program

Author: Berkalieva, Asem, Kelly, Nicole R., Fisher, Ashley, Hohmann, Samuel F., Sebastin, Monisha, Di Biase, Miranda, Bonini, Katherine E., Marathe, Priya, Odgis, Jacqueline A., Suckiel, Sabrina A., Ramos, Michelle A., Rhodes, Rosamond, Abul-Husn, Noura S., Greally, John M., Horowitz, Carol R., Wasserstein, Melissa P., Kenny, Eimear E., Gelb, Bruce D., and Ferket, Bart S.
Published: 2024
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30. The NYCKidSeq randomized controlled trial: Impact of GUÍA digitally enhanced genetic results disclosure in diverse families

Author: Suckiel, Sabrina A., Kelly, Nicole R., Odgis, Jacqueline A., Gallagher, Katie M., Sebastin, Monisha, Bonini, Katherine E., Marathe, Priya N., Brown, Kaitlyn, Di Biase, Miranda, Ramos, Michelle A., Rodriguez, Jessica E., Scarimbolo, Laura, Insel, Beverly J., Ferar, Kathleen D.M., Zinberg, Randi E., Diaz, George A., Greally, John M., Abul-Husn, Noura S., Bauman, Laurie J., Gelb, Bruce D., Horowitz, Carol R., Wasserstein, Melissa P., and Kenny, Eimear E.
Published: 2023
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31. Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics

Author: Chan, Tsz Fung, Rui, Xinyue, Conti, David V., Fornage, Myriam, Graff, Mariaelisa, Haessler, Jeffrey, Haiman, Christopher, Highland, Heather M., Jung, Su Yon, Kenny, Eimear E., Kooperberg, Charles, Le Marchand, Loic, North, Kari E., Tao, Ran, Wojcik, Genevieve, Gignoux, Christopher R., Chiang, Charleston W.K., and Mancuso, Nicholas
Published: 2023
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32. Molecular diagnostic yield of genome sequencing versus targeted gene panel testing in racially and ethnically diverse pediatric patients

Author: Abul-Husn, Noura S., Marathe, Priya N., Kelly, Nicole R., Bonini, Katherine E., Sebastin, Monisha, Odgis, Jacqueline A., Abhyankar, Avinash, Brown, Kaitlyn, Di Biase, Miranda, Gallagher, Katie M., Guha, Saurav, Ioele, Nicolette, Okur, Volkan, Ramos, Michelle A., Rodriguez, Jessica E., Rehman, Atteeq U., Thomas-Wilson, Amanda, Edelmann, Lisa, Zinberg, Randi E., Diaz, George A., Greally, John M., Jobanputra, Vaidehi, Suckiel, Sabrina A., Horowitz, Carol R., Wasserstein, Melissa P., Kenny, Eimear E., and Gelb, Bruce D.
Published: 2023
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33. Association of HSD17B13 and PNPLA3 With Liver Enzymes and Fibrosis in Hispanic/Latino Individuals of Diverse Genetic Ancestries

Author: Rutledge, Stephanie M., Soper, Emily R., Ma, Ning, Pejaver, Vikas, Friedman, Scott L., Branch, Andrea D., Kenny, Eimear E., Belbin, Gillian M., and Abul-Husn, Noura S.
Published: 2023
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34. 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

35. Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing

Author: Felker, Stephanie A., Lawlor, James M.J., Hiatt, Susan M., Thompson, Michelle L., Latner, Donald R., Finnila, Candice R., Bowling, Kevin M., Bonnstetter, Zachary T., Bonini, Katherine E., Kelly, Nicole R., Kelley, Whitley V., Hurst, Anna C.E., Rashid, Salman, Kelly, Melissa A., Nakouzi, Ghunwa, Hendon, Laura G., Bebin, E. Martina, Kenny, Eimear E., and Cooper, Gregory M.
Published: 2023
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36. Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Author: Bick, Alexander G, Weinstock, Joshua S, Nandakumar, Satish K, Fulco, Charles P, Bao, Erik L, Zekavat, Seyedeh M, Szeto, Mindy D, Liao, Xiaotian, Leventhal, Matthew J, Nasser, Joseph, Chang, Kyle, Laurie, Cecelia, Burugula, Bala Bharathi, Gibson, Christopher J, Niroula, Abhishek, Lin, Amy E, Taub, Margaret A, Aguet, Francois, Ardlie, Kristin, Mitchell, Braxton D, Barnes, Kathleen C, Moscati, Arden, Fornage, Myriam, Redline, Susan, Psaty, Bruce M, Silverman, Edwin K, Weiss, Scott T, Palmer, Nicholette D, Vasan, Ramachandran S, Burchard, Esteban G, Kardia, Sharon LR, He, Jiang, Kaplan, Robert C, Smith, Nicholas L, Arnett, Donna K, Schwartz, David A, Correa, Adolfo, de Andrade, Mariza, Guo, Xiuqing, Konkle, Barbara A, Custer, Brian, Peralta, Juan M, Gui, Hongsheng, Meyers, Deborah A, McGarvey, Stephen T, Chen, Ida Yii-Der, Shoemaker, M Benjamin, Peyser, Patricia A, Broome, Jai G, Gogarten, Stephanie M, Wang, Fei Fei, Wong, Quenna, Montasser, May E, Daya, Michelle, Kenny, Eimear E, North, Kari E, Launer, Lenore J, Cade, Brian E, Bis, Joshua C, Cho, Michael H, Lasky-Su, Jessica, Bowden, Donald W, Cupples, L Adrienne, Mak, Angel CY, Becker, Lewis C, Smith, Jennifer A, Kelly, Tanika N, Aslibekyan, Stella, Heckbert, Susan R, Tiwari, Hemant K, Yang, Ivana V, Heit, John A, Lubitz, Steven A, Johnsen, Jill M, Curran, Joanne E, Wenzel, Sally E, Weeks, Daniel E, Rao, Dabeeru C, Darbar, Dawood, Moon, Jee-Young, Tracy, Russell P, Buth, Erin J, Rafaels, Nicholas, Loos, Ruth JF, Durda, Peter, Liu, Yongmei, Hou, Lifang, Lee, Jiwon, Kachroo, Priyadarshini, Freedman, Barry I, Levy, Daniel, Bielak, Lawrence F, Hixson, James E, Floyd, James S, Whitsel, Eric A, Ellinor, Patrick T, Irvin, Marguerite R, Fingerlin, Tasha E, Raffield, Laura M, and Armasu, Sebastian M
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Biotechnology, Regenerative Medicine, Stem Cell Research, Human Genome, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Cardiovascular, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adult, Africa, Aged, Aged, 80 and over, Black People, Cell Self Renewal, Clonal Hematopoiesis, DNA-Binding Proteins, Dioxygenases, Female, Genetic Predisposition to Disease, Genome, Human, Germ-Line Mutation, Hematopoietic Stem Cells, Humans, Intracellular Signaling Peptides and Proteins, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Precision Medicine, Proto-Oncogene Proteins, Tripartite Motif Proteins, United States, Whole Genome Sequencing, alpha Karyopherins, NHLBI Trans-Omics for Precision Medicine Consortium, General Science & Technology
Abstract: Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.
Published: 2020

37. Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits

Author: Baldassari, Antoine R, Sitlani, Colleen M, Highland, Heather M, Arking, Dan E, Buyske, Steve, Darbar, Dawood, Gondalia, Rahul, Graff, Misa, Guo, Xiuqing, Heckbert, Susan R, Hindorff, Lucia A, Hodonsky, Chani J, Ida Chen, Yii-Der, Kaplan, Robert C, Peters, Ulrike, Post, Wendy, Reiner, Alex P, Rotter, Jerome I, Shohet, Ralph V, Seyerle, Amanda A, Sotoodehnia, Nona, Tao, Ran, Taylor, Kent D, Wojcik, Genevieve L, Yao, Jie, Kenny, Eimear E, Lin, Henry J, Soliman, Elsayed Z, Whitsel, Eric A, North, Kari E, Kooperberg, Charles, and Avery, Christy L
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Genetics, Clinical Research, Human Genome, Black or African American, CD36 Antigens, Cardiovascular Diseases, Electrocardiography, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genotype, Hispanic or Latino, Homeodomain Proteins, Humans, Membrane Glycoproteins, Molecular Chaperones, Phenotype, Polymorphism, Single Nucleotide, Transcription Factors, White People, cardiovascular diseases, electrophysiology, epidemiology, genome-wide association study, population, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract: BackgroundWe examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci.MethodsWe decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test.ResultsWe identified 6 novels (CD36, PITX2, EMB, ZNF592, YPEL2, and BC043580) and 87 known loci (adaptive sum of powered score test P
Published: 2020

38. Author Correction: Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations.

Author: Daya, Michelle, Rafaels, Nicholas, Brunetti, Tonya M, Chavan, Sameer, Levin, Albert M, Shetty, Aniket, Gignoux, Christopher R, Boorgula, Meher Preethi, Wojcik, Genevieve, Campbell, Monica, Vergara, Candelaria, Torgerson, Dara G, Ortega, Victor E, Doumatey, Ayo, Johnston, Henry Richard, Acevedo, Nathalie, Araujo, Maria Ilma, Avila, Pedro C, Belbin, Gillian, Bleecker, Eugene, Bustamante, Carlos, Caraballo, Luis, Cruz, Alvaro, Dunston, Georgia M, Eng, Celeste, Faruque, Mezbah U, Ferguson, Trevor S, Figueiredo, Camila, Ford, Jean G, Gan, Weiniu, Gourraud, Pierre-Antoine, Hansel, Nadia N, Hernandez, Ryan D, Herrera-Paz, Edwin Francisco, Jiménez, Silvia, Kenny, Eimear E, Knight-Madden, Jennifer, Kumar, Rajesh, Lange, Leslie A, Lange, Ethan M, Lizee, Antoine, Maul, Pissamai, Maul, Trevor, Mayorga, Alvaro, Meyers, Deborah, Nicolae, Dan L, O'Connor, Timothy D, Oliveira, Ricardo Riccio, Olopade, Christopher O, Olopade, Olufunmilayo, Qin, Zhaohui S, Rotimi, Charles, Vince, Nicolas, Watson, Harold, Wilks, Rainford J, Wilson, James G, Salzberg, Steven, Ober, Carole, Burchard, Esteban G, Williams, L Keoki, Beaty, Terri H, Taub, Margaret A, Ruczinski, Ingo, Mathias, Rasika A, Barnes, Kathleen C, and CAAPA
Subjects: CAAPA
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2019

39. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie-Julie, Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Mutaamba, Maasha, Partanen, Juulia J., Brumpton, Ben M., Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Palta, Priit, Pandit, Anita, Preuss, Michael H., Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Zawistowski, Matthew, Zhong, Xue, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H., Douville, Nicholas J., Finer, Sarah, Fritsche, Lars G., Griffiths, Christopher J., Guo, Yu, Hunt, Karen A., Konuma, Takahiro, Marioni, Riccardo E., Nomdo, Jansonius, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Shortt, Jonathan A., Straub, Peter, Tao, Ran, Vanderwerff, Brett, Barnes, Kathleen C., Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K., Franke, Lude, Gamazon, Eric R., Ganna, Andrea, Gaunt, Tom R., Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Koskela, Jukka T., Lajonchere, Clara, Law, Matthew H., Li, Liming, Lindgren, Cecilia M., Loos, Ruth J.F., MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M., Porteous, David J., Shavit, Jordan A., Snieder, Harold, Trembath, Richard C., Vonk, Judith M., Whiteman, David, Wicks, Stephen J., Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Cox, Nancy J., Geschwind, Daniel H., Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E., Lin, Yen-Feng, Mägi, Reedik, Martin, Hilary C., Medland, Sarah E., Okada, Yukinori, Palotie, Aarno V., Pasaniuc, Bogdan, Sanna, Serena, Smoller, Jordan W., Stefansson, Kari, van Heel, David A., Walters, Robin G., Zöllner, Sebastian, Martin, Alicia R., Willer, Cristen J., Daly, Mark J., Neale, Benjamin M., Lopera, Esteban, Kerminen, Sini, Wu, Kuan-Han, Bhatta, Laxmi, Brumpton, Ben, Deelen, Patrick, Murakami, Yoshinori, Willer, Cristen, and Hirbo, Jibril
Published: 2023
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40. Returning integrated genomic risk and clinical recommendations: The eMERGE study

Author: Gordon, Adam, Sobowale, Agboade, Allworth, Aimee, Patel, Akshar, DiVietro, Alanna, Strong, Alanna, Sherafati, Alborz, Sherfati, Alborz, Bick, Alex, Miller, Alexandra, Chandel, Alka, Rosenthal, Alyssa, Khera, Amit, Kontorovich, Amy, Beck, Andrew, Beck, Andy, Espinoza, Angelica, Lewis, Anna, Prince, Anya, Khan, Atlas, Iverson, Ayuko, Khales, Bahram Namjou, Benoit, Barbara, Hernan, Becca, Kallman, Ben, Kerman, Ben, Shoemaker, Ben, Satterfield, Benjamin, Devine, Beth, Etheridge, Bethany, Goff, Blake, Freimuth, Bob, Grundmeier, Bob, Collier, Brenae, Mutai, Brenda, Harnett, Brett, Chang, Brian, Piening, Brian, Davis, Brittney, Korf, Bruce, Patterson, Candace, Demetriou, Carmen, Ta, Casey, Hammack, Catherine, Nelson, Catrina, Gascoigne, Caytie, Dorn, Chad, Moretz, Chad, Kachulis, Chris, Hoell, Christie, Cowles, Christine, Lange, Christoph, Weng, Chunhua, Prows, Cindy, Brokamp, Cole, Liu, Cong, Scherr, Courtney, Gonzalez, Crystal, Ramirez, Cynthia, Shimbo, Daichi, Roden, Dan, Schaid, Daniel, Kaufman, Dave, Crosslin, David, Kochan, David, Veenstra, David, Singh, Davinder, Karavite, Dean, Abrams, Debbie, Absher, Devin, Edwards, Digna Velez, Haverfield, Eden, Morales, Eduardo, Esplin, Edward, Malolepsza, Edyta, Alipour, Ehsan, Kenny, Eimear, Rosenthal, Elisabeth, Duvall, Eliza, McNally, Elizabeth, Bhoj, Elizabeth, Cohn, Elizabeth, Hibler, Elizabeth, Karlson, Elizabeth, Clayton, Ellen, Chesnut, Emily, DeFranco, Emily, Gallagher, Emily, Soper, Emily, Perez, Emma, Cash, Erin, Berner, Eta, Wang, Fei, Wehbe, Firas, Ricci, Francisco, Mentch, Frank, Shaibi, Gabriel, Jarvik, Gail, Hahn, George, Hripcsak, George, Wiesner, Georgia, Belbin, Gillian, Davogustto, Gio, Nadkarni, Girish, Qiu, Haijun, Hakonarson, Hakon, Bangash, Hana, Beasley, Hannah, Liu, Hao, Aungst, Heide, Tiwari, Hemant, Duckham, Hillary, Thomas, Hope, Kullo, Iftikhar, Holm, Ingrid, Allen, Isabelle, Ionita-Laza, Iuliana, Hellwege, Jacklyn, Petrzelka, Jacob, Odgis, Jacqueline, Narula, Jahnavi, Petrzelka, Jake, Patel, Jalpa, Cimino, James, Meigs, James, Snyder, James, Olson, Janet, Zahner, Janet, Pennington, Jeff, Pacheco, Jen, Pacheco, Jennifer Allen, Morse, Jennifer, Corsmo, Jeremy, Thayer, Jeritt, Cimino, Jim, Chen, Jingheng, Fournier, Jocelyn, Jackson, Jodell, Glessner, Joe, Pacyna, Joel, Smith, Johanna, Connolly, John, Lynch, John, Shelley, John, Mosley, Jonathan, Nestor, Jordan, Smoller, Jordan, Alsip, Jorge, Kannry, Joseph, Sutton, Joseph, Peterson, Josh, Smith, Joshua, Galasso, Julia, Smith, Julia, Wynn, Julia, Gundelach, Justin, Starren, Justin, Choi, Karmel, Mittendorf, Kate, Anderson, Katherine, Bonini, Katherine, Leppig, Kathleen, Muenzen, Kathleen, Larkin, Katie, Stuttgen, Kelsey, Wiley, Ken, Nguyen, Kenny, Dufendach, Kevin, Atkins, Kiley, Sawicki, Konrad, Norland, Kristjan, Kiryluk, Krzysztof, Beskow, Laura, Rasmussen-Torvik, Laura, Kottyan, Leah, Hsu, Li, Tian, Lifeng, Mahanta, Lisa, Martin, Lisa, Wang, Lisa, Gomez, Lizbeth, Thompson, Lorenzo, Orlando, Lori, Richter, Lucas, Rasmussen, Luke, Petukhova, Lynn, Seabolt, Lynn, O’Brien, Madison, Harden, Maegan, Fullerton, Malia, Harr, Margaret, Beasley, Mark, Guindo, Marta, Horike, Martha, Horike-Pyne, Martha, Abdalla, Marwah, Hamed, Marwan, Terry, Mary Beth, Maradik, Mary, Wyatt, Matt, Davis, Matthew, Lebo, Matthew, Smith, Maureen, Rosario, Maya del, Sabatello, Maya, Behr, Meckenzie, Roy-Puckelwartz, Meg, Habrat, Mel, Myers, Melanie, Yetisgen, Meliha, Iris, Merve, DaSilva, Michael, Preuss, Michael, McGowan, Michelle, Shi, Mingjian, Perera, Minoli, Thomas, Minta, Elkind, Mitch, Abbass, Mohammad, Saadatagah, Mohammad, Hess, Molly, Maradik, Molly, Vaitinadin, Nataraja “RJ”, Vaitinadin, Nataraja, Muthu, Naveen, Netherly, Neil, Lennon, Niall, Shang, Ning, Limdi, Nita, Forrest, Noah, Romero, Noheli, Robinson, Nora, Abul-Husn, Noura, Elsekaily, Omar, Dikilitas, Ozan, Kovatch, Patricia, Davis, Patrick, Appelbaum, Paul, Francaviglia, Paul, O’Reilly, Paul, Chandler, Paulette, Caraballo, Pedro, Tarczy-Hornoch, Peter, Shum, Pierre, Marathe, Priya, Murali, Priyanka, Feng, Qiping, Wells, Quinn, Atchley, Rachel, Narla, Radhika, Barton, Rene, Sterling, Rene, Chisholm, Rex, Green, Richard, Sharp, Richard, Peters, Riki, Kukafka, Rita, Rowley, Robb, Freimuth, Robert, Green, Robert, Winter, Robert, Mueller, Roger, Loos, Ruth, Irvin, Ryan, Suckiel, Sabrina, Hussain, Sajjad, Sharba, Samer, Aronson, Sandy, Jones, Sarah, Knerr, Sarah, Nigbur, Scott, Weiss, Scott, Mooney, Sean, Terek, Shannon, Aufox, Sharon, Nirenberg, Sharon, Murphy, Shawn, O’Byrne, Sheila, Wang (Sam) Choi, Shing, Aguilar, Sienna, Bland, S.T., Rodrigues, Stefanie, Ledbetter, Stephanie, Rutledge, Stephanie, Booth, Stuart James, Xian, Su, Trinidad, Susan Brown, Bakken, Suzanne, Schmidlen, Tara, Rakhra-Burris, Tejinder, Manolio, Teri, Mersha, Tesfaye, Walunas, Theresa, Chandereng, Thevaa, May, Thomas, Ge, Tian, Edwards, Todd, Kaszemacher, Tom, Hernandez, Valentina, Willis, Valerie, Desai, Vemi, Desai, Vimi, Lorenzi, Virginia, Gainer, Vivian, Wei, Wei-Qi, Chung, Wendy, Su, Wu-Chen, Chang, Xiao, Zhao, Yiqing, Luo, Yuan, Shen, Yufeng, Linder, Jodell E., Bland, Sarah T., Caraballo, Pedro J., Chisholm, Rex L., Clayton, Ellen Wright, Crosslin, David R., Esplin, Edward D., Forman, Sophie, Freimuth, Robert R., Gordon, Adam S., Harden, Maegan V., Holm, Ingrid A., Jarvik, Gail P., Karlson, Elizabeth W., Labrecque, Sofia, Lennon, Niall J., Limdi, Nita A., Mittendorf, Kathleen F., Murphy, Shawn N., Prows, Cynthia A., Rasmussen, Luke V., Sawicki, Konrad Teodor, Velez Edwards, Digna R., Abul-Husn, Noura S., Below, Jennifer E., Berner, Eta S., Booth, James, Chung, Wendy K., Cimino, James J., Fullerton, Stephanie M., Guiducci, Candace, Habrat, Melissa L., Hain, Heather, Hoell, Christin, Irvin, Marguerite R., Kachulis, Christopher, Kenny, Eimear E., Kullo, Iftikhar J., Manolio, Teri A., McNally, Elizabeth M., Mooney, Sean D., Namjou, Bahram, Perez, Emma F., Puckelwartz, Megan J., Roden, Dan M., Rosenthal, Elisabeth A., Saadatagah, Seyedmohammad, Schaid, Dan J., Schultz, Baergen, Shaibi, Gabriel Q., Sharp, Richard R., Shirts, Brian, Smith, Maureen E., Smoller, Jordan W., Suckiel, Sabrina A., Tiwari, Hemant K., Trinidad, Susan B., Wells, Quinn S., Wiesner, Georgia L., and Peterson, Josh F.
Published: 2023
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41. Genome-wide polygenic score to predict chronic kidney disease across ancestries

Author: Khan, Atlas, Turchin, Michael C., Patki, Amit, Srinivasasainagendra, Vinodh, Shang, Ning, Nadukuru, Rajiv, Jones, Alana C., Malolepsza, Edyta, Dikilitas, Ozan, Kullo, Iftikhar J., Schaid, Daniel J., Karlson, Elizabeth, Ge, Tian, Meigs, James B., Smoller, Jordan W., Lange, Christoph, Crosslin, David R., Jarvik, Gail P., Bhatraju, Pavan K., Hellwege, Jacklyn N., Chandler, Paulette, Torvik, Laura Rasmussen, Fedotov, Alex, Liu, Cong, Kachulis, Christopher, Lennon, Niall, Abul-Husn, Noura S., Cho, Judy H., Ionita-Laza, Iuliana, Gharavi, Ali G., Chung, Wendy K., Hripcsak, George, Weng, Chunhua, Nadkarni, Girish, Irvin, Marguerite R., Tiwari, Hemant K., Kenny, Eimear E., Limdi, Nita A., and Kiryluk, Krzysztof
Published: 2022
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42. Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J., Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M., Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A., Guare, Lindsay A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Ismail, Said I., Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H., Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M., Al Thani, Asma, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H., Damrauer, Scott M., Douville, Nicholas J., Finer, Sarah, Fritsche, Lars G., Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J., Guo, Yu, Hunt, Karen A., Ioannidis, Alexander, Jansonius, Nomdo M., Konuma, Takahiro, Michael Lee, Ming Ta, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E., Moatamed, Babak, Nava-Aguilar, Marco A., Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A., Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C., Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K., Franke, Lude, Gamazon, Eric R., Ganna, Andrea, Gaunt, Tom R., Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Katsanis, Nicholas, Koskela, Jukka T., Lajonchere, Clara, Law, Matthew H., Li, Liming, Lindgren, Cecilia M., Loos, Ruth J.F., MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M., Porteous, David J., Shavit, Jordan A., Snieder, Harold, Takano, Tomohiro, Trembath, Richard C., Vonk, Judith M., Whiteman, David C., Wicks, Stephen J., Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Bustamante, Carlos D., Cox, Nancy J., Fatumo, Segun, Geschwind, Daniel H., Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E., Lee, Seunggeun, Lin, Yen-Feng, Mbarek, Hamdi, Mägi, Reedik, Martin, Hilary C., Medland, Sarah E., Okada, Yukinori, Palotie, Aarno V., Pasaniuc, Bogdan, Rader, Daniel J., Ritchie, Marylyn D., Sanna, Serena, Smoller, Jordan W., Stefansson, Kari, van Heel, David A., Walters, Robin G., Zöllner, Sebastian, Biobank of the Americas, Biobank Japan Project, BioMe, BioVU, CanPath - Ontario Health Study, China Kadoorie Biobank Collaborative Group, Colorado Center for Personalized Medicine, deCODE Genetics, Estonian Biobank, FinnGen, Generation Scotland, Genes & Health Research Team, LifeLines, Mass General Brigham Biobank, Michigan Genomics Initiative, National Biobank of Korea, Penn Medicine BioBank, Qatar Biobank, The Qskin Sun and Health Study, Taiwan Biobank, The Hunt Study, Ucla Atlas Community Health Initiative, Uganda Genome Resource, Uk Biobank, Martin, Alicia R., Willer, Cristen J., Daly, Mark J., Neale, Benjamin M., and Elzur, Roy
Published: 2022
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43. Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References

Author: Taylor, Dylan J., primary, Eizenga, Jordan M., additional, Li, Qiuhui, additional, Das, Arun, additional, Jenike, Katharine M., additional, Kenny, Eimear E., additional, Miga, Karen H., additional, Monlong, Jean, additional, McCoy, Rajiv C., additional, Paten, Benedict, additional, and Schatz, Michael C., additional
Published: 2024
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44. MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups

Author: Jin, Jin, primary, Zhan, Jianan, additional, Zhang, Jingning, additional, Zhao, Ruzhang, additional, O’Connell, Jared, additional, Jiang, Yunxuan, additional, Aslibekyan, Stella, additional, Auton, Adam, additional, Babalola, Elizabeth, additional, Bell, Robert K., additional, Bielenberg, Jessica, additional, Bryc, Katarzyna, additional, Bullis, Emily, additional, Coker, Daniella, additional, Cuellar Partida, Gabriel, additional, Dhamija, Devika, additional, Das, Sayantan, additional, Elson, Sarah L., additional, Eriksson, Nicholas, additional, Filshtein, Teresa, additional, Fitch, Alison, additional, Fletez-Brant, Kipper, additional, Fontanillas, Pierre, additional, Freyman, Will, additional, Granka, Julie M., additional, Heilbron, Karl, additional, Hernandez, Alejandro, additional, Hicks, Barry, additional, Hinds, David A., additional, Jewett, Ethan M., additional, Kukar, Katelyn, additional, Kwong, Alan, additional, Lin, Keng-Han, additional, Llamas, Bianca A., additional, Lowe, Maya, additional, McCreight, Jey C., additional, McIntyre, Matthew H., additional, Micheletti, Steven J., additional, Moreno, Meghan E., additional, Nandakumar, Priyanka, additional, Nguyen, Dominique T., additional, Noblin, Elizabeth S., additional, Petrakovitz, Aaron A., additional, Poznik, G. David, additional, Reynoso, Alexandra, additional, Schumacher, Morgan, additional, Shastri, Anjali J., additional, Shelton, Janie F., additional, Shi, Jingchunzi, additional, Shringarpure, Suyash, additional, Su, Qiaojuan Jane, additional, Tat, Susana A., additional, Tchakouté, Christophe Toukam, additional, Tran, Vinh, additional, Tung, Joyce Y., additional, Wang, Xin, additional, Wang, Wei, additional, Weldon, Catherine H., additional, Wilton, Peter, additional, Wong, Corinna D., additional, Buyske, Steven, additional, Gignoux, Christopher, additional, Haiman, Christopher, additional, Kenny, Eimear E., additional, Kooperberg, Charles, additional, North, Kari, additional, Koelsch, Bertram L., additional, Wojcik, Genevieve, additional, Zhang, Haoyu, additional, and Chatterjee, Nilanjan, additional
Published: 2024
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45. Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

Author: Ge, Tian, Irvin, Marguerite R., Patki, Amit, Srinivasasainagendra, Vinodh, Lin, Yen-Feng, Tiwari, Hemant K., Armstrong, Nicole D., Benoit, Barbara, Chen, Chia-Yen, Choi, Karmel W., Cimino, James J., Davis, Brittney H., Dikilitas, Ozan, Etheridge, Bethany, Feng, Yen-Chen Anne, Gainer, Vivian, Huang, Hailiang, Jarvik, Gail P., Kachulis, Christopher, Kenny, Eimear E., Khan, Atlas, Kiryluk, Krzysztof, Kottyan, Leah, Kullo, Iftikhar J., Lange, Christoph, Lennon, Niall, Leong, Aaron, Malolepsza, Edyta, Miles, Ayme D., Murphy, Shawn, Namjou, Bahram, Narayan, Renuka, O’Connor, Mark J., Pacheco, Jennifer A., Perez, Emma, Rasmussen-Torvik, Laura J., Rosenthal, Elisabeth A., Schaid, Daniel, Stamou, Maria, Udler, Miriam S., Wei, Wei-Qi, Weiss, Scott T., Ng, Maggie C. Y., Smoller, Jordan W., Lebo, Matthew S., Meigs, James B., Limdi, Nita A., and Karlson, Elizabeth W.
Published: 2022
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46. CDH1 pathogenic variants and cancer risk in an unselected patient population

Author: Bar-Mashiah, Ariel, Soper, Emily R., Cullina, Sinead, Belbin, Gillian M., Kenny, Eimear E., Lucas, Aimee L., and Abul-Husn, Noura S.
Published: 2022
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47. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Author: Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H., Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B., Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N., Lo Faro, Valeria, Lopera-Maya, Esteban A., Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J., Chapman, Sinéad B., Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M., Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A., Guare, Lindsay A., Gignoux, Christopher R., Graham, Sarah E., Hornsby, Whitney E., Ingold, Nathan, Ismail, Said I., Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y., Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H., Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M., Al Thani, Asma, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H., Damrauer, Scott M., Douville, Nicholas J., Finer, Sarah, Fritsche, Lars G., Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J., Guo, Yu, Hunt, Karen A., Ioannidis, Alexander, Jansonius, Nomdo M., Konuma, Takahiro, Lee, Ming Ta Michael, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E., Moatamed, Babak, Nava-Aguilar, Marco A., Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A., Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C., Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K., Franke, Lude, Gamazon, Eric R., Ganna, Andrea, Gaunt, Tom R., Ge, Tian, Huang, Hailiang, Huffman, Jennifer, Katsanis, Nicholas, Koskela, Jukka T., Lajonchere, Clara, Law, Matthew H., Li, Liming, Lindgren, Cecilia M., Loos, Ruth J.F., MacGregor, Stuart, Matsuda, Koichi, Olsen, Catherine M., Porteous, David J., Shavit, Jordan A., Snieder, Harold, Takano, Tomohiro, Trembath, Richard C., Vonk, Judith M., Whiteman, David C., Wicks, Stephen J., Wijmenga, Cisca, Wright, John, Zheng, Jie, Zhou, Xiang, Awadalla, Philip, Boehnke, Michael, Bustamante, Carlos D., Cox, Nancy J., Fatumo, Segun, Geschwind, Daniel H., Hayward, Caroline, Hveem, Kristian, Kenny, Eimear E., Lee, Seunggeun, Lin, Yen-Feng, Mbarek, Hamdi, Mägi, Reedik, Martin, Hilary C., Medland, Sarah E., Okada, Yukinori, Palotie, Aarno V., Pasaniuc, Bogdan, Rader, Daniel J., Ritchie, Marylyn D., Sanna, Serena, Smoller, Jordan W., Stefansson, Kari, van Heel, David A., Walters, Robin G., Zöllner, Sebastian, Martin, Alicia R., Willer, Cristen J., Daly, Mark J., and Neale, Benjamin M.
Published: 2022
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48. Genetic analyses of diverse populations improves discovery for complex traits.

Author: Wojcik, Genevieve L, Graff, Mariaelisa, Nishimura, Katherine K, Tao, Ran, Haessler, Jeffrey, Gignoux, Christopher R, Highland, Heather M, Patel, Yesha M, Sorokin, Elena P, Avery, Christy L, Belbin, Gillian M, Bien, Stephanie A, Cheng, Iona, Cullina, Sinead, Hodonsky, Chani J, Hu, Yao, Huckins, Laura M, Jeff, Janina, Justice, Anne E, Kocarnik, Jonathan M, Lim, Unhee, Lin, Bridget M, Lu, Yingchang, Nelson, Sarah C, Park, Sung-Shim L, Poisner, Hannah, Preuss, Michael H, Richard, Melissa A, Schurmann, Claudia, Setiawan, Veronica W, Sockell, Alexandra, Vahi, Karan, Verbanck, Marie, Vishnu, Abhishek, Walker, Ryan W, Young, Kristin L, Zubair, Niha, Acuña-Alonso, Victor, Ambite, Jose Luis, Barnes, Kathleen C, Boerwinkle, Eric, Bottinger, Erwin P, Bustamante, Carlos D, Caberto, Christian, Canizales-Quinteros, Samuel, Conomos, Matthew P, Deelman, Ewa, Do, Ron, Doheny, Kimberly, Fernández-Rhodes, Lindsay, Fornage, Myriam, Hailu, Benyam, Heiss, Gerardo, Henn, Brenna M, Hindorff, Lucia A, Jackson, Rebecca D, Laurie, Cecelia A, Laurie, Cathy C, Li, Yuqing, Lin, Dan-Yu, Moreno-Estrada, Andres, Nadkarni, Girish, Norman, Paul J, Pooler, Loreall C, Reiner, Alexander P, Romm, Jane, Sabatti, Chiara, Sandoval, Karla, Sheng, Xin, Stahl, Eli A, Stram, Daniel O, Thornton, Timothy A, Wassel, Christina L, Wilkens, Lynne R, Winkler, Cheryl A, Yoneyama, Sachi, Buyske, Steven, Haiman, Christopher A, Kooperberg, Charles, Le Marchand, Loic, Loos, Ruth JF, Matise, Tara C, North, Kari E, Peters, Ulrike, Kenny, Eimear E, and Carlson, Christopher S
Subjects: Humans, Body Height, Cohort Studies, Genetics, Medical, Multifactorial Inheritance, Minority Groups, African Continental Ancestry Group, Asian Continental Ancestry Group, Hispanic Americans, Women's Health, United States, Female, Male, Health Status Disparities, Genome-Wide Association Study, Health Equity, Genetics, Medical, General Science & Technology
Abstract: Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.
Published: 2019

49. The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research

Author: Horowitz, Carol R, Orlando, Lori A, Slavotinek, Anne M, Peterson, Josh, Angelo, Frank, Biesecker, Barbara, Bonham, Vence L, Cameron, Linda D, Fullerton, Stephanie M, Gelb, Bruce D, Goddard, Katrina AB, Hailu, Benyam, Hart, Ragan, Hindorff, Lucia A, Jarvik, Gail P, Kaufman, Dave, Kenny, Eimear E, Knight, Sara J, Koenig, Barbara A, Korf, Bruce R, Madden, Ebony, McGuire, Amy L, Ou, Jeffrey, Wasserstein, Melissa P, Robinson, Mimsie, Leventhal, Howard, and Sanderson, Saskia C
Subjects: Health Services and Systems, Health Sciences, Genetics, Biological Sciences, Prevention, Human Genome, Clinical Research, Biotechnology, Good Health and Well Being, Biomedical Research, Delivery of Health Care, Integrated, Genetics, Medical, Genomics, Humans, Models, Theoretical, Precision Medicine, Rare Diseases, Research Design, conceptual, diversity, framework, genomics, implementation, model, translational research, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract: Conceptual frameworks are useful in research because they can highlight priority research domains, inform decisions about interventions, identify outcomes and factors to measure, and display how factors might relate to each other to generate and test hypotheses. Discovery, translational, and implementation research are all critical to the overall mission of genomic medicine and prevention, but they have yet to be organized into a unified conceptual framework. To fill this gap, our diverse team collaborated to develop the Genomic Medicine Integrative Research (GMIR) Framework, a simple but comprehensive tool to aid the genomics community in developing research questions, strategies, and measures and in integrating genomic medicine and prevention into clinical practice. Here we present the GMIR Framework and its development, along with examples of its use for research development, demonstrating how we applied it to select and harmonize measures for use across diverse genomic medicine implementation projects. Researchers can utilize the GMIR Framework for their own research, collaborative investigations, and clinical implementation efforts; clinicians can use it to establish and evaluate programs; and all stakeholders can use it to help allocate resources and make sure that the full complexity of etiology is included in research and program design, development, and evaluation.
Published: 2019

50. Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations.

Author: Daya, Michelle, Rafaels, Nicholas, Brunetti, Tonya M, Chavan, Sameer, Levin, Albert M, Shetty, Aniket, Gignoux, Christopher R, Boorgula, Meher Preethi, Wojcik, Genevieve, Campbell, Monica, Vergara, Candelaria, Torgerson, Dara G, Ortega, Victor E, Doumatey, Ayo, Johnston, Henry Richard, Acevedo, Nathalie, Araujo, Maria Ilma, Avila, Pedro C, Belbin, Gillian, Bleecker, Eugene, Bustamante, Carlos, Caraballo, Luis, Cruz, Alvaro, Dunston, Georgia M, Eng, Celeste, Faruque, Mezbah U, Ferguson, Trevor S, Figueiredo, Camila, Ford, Jean G, Gan, Weiniu, Gourraud, Pierre-Antoine, Hansel, Nadia N, Hernandez, Ryan D, Herrera-Paz, Edwin Francisco, Jiménez, Silvia, Kenny, Eimear E, Knight-Madden, Jennifer, Kumar, Rajesh, Lange, Leslie A, Lange, Ethan M, Lizee, Antoine, Maul, Pissamai, Maul, Trevor, Mayorga, Alvaro, Meyers, Deborah, Nicolae, Dan L, O'Connor, Timothy D, Oliveira, Ricardo Riccio, Olopade, Christopher O, Olopade, Olufunmilayo, Qin, Zhaohui S, Rotimi, Charles, Vince, Nicolas, Watson, Harold, Wilks, Rainford J, Wilson, James G, Salzberg, Steven, Ober, Carole, Burchard, Esteban G, Williams, L Keoki, Beaty, Terri H, Taub, Margaret A, Ruczinski, Ingo, Mathias, Rasika A, Barnes, Kathleen C, and CAAPA
Subjects: CAAPA, Chromosomes, Human, Pair 8, Chromosomes, Human, Pair 12, Chromosomes, Human, Pair 17, Humans, Asthma, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, African Americans, Hispanic Americans, United States, Genome-Wide Association Study, Genetic Loci, Chromosomes, Human, Pair 12, Pair 17, Pair 8, Polymorphism, Single Nucleotide
Abstract: Asthma is a complex disease with striking disparities across racial and ethnic groups. Despite its relatively high burden, representation of individuals of African ancestry in asthma genome-wide association studies (GWAS) has been inadequate, and true associations in these underrepresented minority groups have been inconclusive. We report the results of a genome-wide meta-analysis from the Consortium on Asthma among African Ancestry Populations (CAAPA; 7009 asthma cases, 7645 controls). We find strong evidence for association at four previously reported asthma loci whose discovery was driven largely by non-African populations, including the chromosome 17q12-q21 locus and the chr12q13 region, a novel (and not previously replicated) asthma locus recently identified by the Trans-National Asthma Genetic Consortium (TAGC). An additional seven loci reported by TAGC show marginal evidence for association in CAAPA. We also identify two novel loci (8p23 and 8q24) that may be specific to asthma risk in African ancestry populations.
Published: 2019

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