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

Author

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

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

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

Published
2024

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

Author

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

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

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

Published
2024

3. 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. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Author

Wang, Yuxuan, Selvaraj, Margaret, Li, Xihao, Li, Zilin, Holdcraft, Jacob, Arnett, Donna, Bis, Joshua, Blangero, John, Boerwinkle, Eric, Bowden, Donald, Cade, Brian, Carlson, Jenna, Carson, April, Chen, Yii-Der, Curran, Joanne, de Vries, Paul, Dutcher, Susan, Ellinor, Patrick, Floyd, James, Fornage, Myriam, Freedman, Barry, Gabriel, Stacey, Germer, Soren, Gibbs, Richard, Guo, Xiuqing, He, Jiang, Heard-Costa, Nancy, Hildalgo, Bertha, Hou, Lifang, Irvin, Marguerite, Joehanes, Roby, Kaplan, Robert, Kardia, Sharon, Kelly, Tanika, Kim, Ryan, Kooperberg, Charles, Kral, Brian, Levy, Daniel, Li, Changwei, Liu, Chunyu, Lloyd-Jone, Don, Loos, Ruth, Mahaney, Michael, Martin, Lisa, Mathias, Rasika, Minster, Ryan, Mitchell, Braxton, Montasser, May, Morrison, Alanna, Murabito, Joanne, Naseri, Take, OConnell, Jeffrey, Palmer, Nicholette, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Rao, Dabeeru, Redline, Susan, Reiner, Alexander, Rich, Stephen, Ruepena, Muagututia, Sheu, Wayne, Smith, Jennifer, Smith, Albert, Tiwari, Hemant, Tsai, Michael, Viaud-Martinez, Karine, Wang, Zhe, Yanek, Lisa, Zhao, Wei, Lin, Xihong, Natarajan, Pradeep, Peloso, Gina, and Rotter, Jerome

Subjects
association, blood lipid, cholesterol, lncRNA, rare variants, whole-genome sequencing, Humans, RNA, Long Noncoding, Genome-Wide Association Study, Precision Medicine, Whole Genome Sequencing, Lipids, Polymorphism, Single Nucleotide
Abstract

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

Published
2023

6. Associations between Ambient Air Pollutants and Clonal Hematopoiesis of Indeterminate Potential.

Author

Leiser, Claire L, Whitsel, Eric A, Reiner, Alexander, Rich, Stephen S, Rotter, Jerome I, Taylor, Kent D, Tracy, Russel P, Kooperberg, Charles, Smith, Albert Vernon, Manson, JoAnn E, Mychaleckyj, Josyf C, Bick, Alexander G, Szpiro, Adam A, and Kaufman, Joel D

Subjects
Epidemiology, Health Sciences, Aging, Cancer, Hematology, Climate-Related Exposures and Conditions, Prevention, Atherosclerosis, Genetics, 2.2 Factors relating to the physical environment, Humans, Female, Air Pollutants, Environmental Pollutants, Nitrogen Dioxide, Clonal Hematopoiesis, Cross-Sectional Studies, Environmental Exposure, Air Pollution, Particulate Matter, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundClonal hematopoiesis of indeterminate potential (CHIP) is an age-related somatic mutation associated with incident hematologic cancer. Environmental stressors which, like air pollution, generate oxidative stress at the cellular level, may induce somatic mutations and some mutations may provide a selection advantage for persistence and expansion of specific clones.MethodsWe used data from the Multi-Ethnic Study of Atherosclerosis (MESA) N = 4,379 and the Women's Health Initiative (WHI) N = 7,701 to estimate cross-sectional associations between annual average air pollution concentrations at participant address the year before blood draw using validated spatiotemporal models. We used covariate-adjusted logistic regression to estimate risk of CHIP per interquartile range increases in particulate matter (PM2.5; 4 μg/m3) and nitrogen dioxide (NO2; 10 ppb) as ORs (95% confidence intervals).ResultsPrevalence of CHIP at blood draw (variant allele fraction > 2%) was 4.4% and 8.7% in MESA and WHI, respectively. The most common CHIP driver mutation was in DNMT3A. Neither pollutant was associated with CHIP: ORMESA PM2.5 = 1.00 (0.68-1.45), ORMESA NO2 = 1.05 (0.69-1.61), ORWHI PM2.5 = 0.97 (0.86-1.09), ORWHI NO2 = 0.98 (0.88-1.10); or with DNMT3A-driven CHIP.ConclusionsWe did not find evidence that air pollution contributes to CHIP prevalence in two large observational cohorts.ImpactThis is the first study to estimate associations between air pollution and CHIP.

Published
2023

7. Genome-wide association meta-analysis identifies 17 loci associated with nonalcoholic fatty liver disease

Author

Chen, Yanhua, Du, Xiaomeng, Kuppa, Annapurna, Feitosa, Mary F, Bielak, Lawrence F, O’Connell, Jeffrey R, Musani, Solomon K, Guo, Xiuqing, Kahali, Bratati, Chen, Vincent L, Smith, Albert V, Ryan, Kathleen A, Eirksdottir, Gudny, Allison, Matthew A, Bowden, Donald W, Budoff, Matthew J, Carr, John Jeffrey, Chen, Yii-Der I, Taylor, Kent D, Oliveri, Antonino, Correa, Adolfo, Crudup, Breland F, Kardia, Sharon LR, Mosley, Thomas H, Norris, Jill M, Terry, James G, Rotter, Jerome I, Wagenknecht, Lynne E, Halligan, Brian D, Young, Kendra A, Hokanson, John E, Washko, George R, Gudnason, Vilmundur, Province, Michael A, Peyser, Patricia A, Palmer, Nicholette D, and Speliotes, Elizabeth K

Subjects
Biochemistry and Cell Biology, Genetics, Biological Sciences, Digestive Diseases, Liver Disease, Hepatitis, Chronic Liver Disease and Cirrhosis, Human Genome, Prevention, 2.1 Biological and endogenous factors, Humans, Non-alcoholic Fatty Liver Disease, Genome-Wide Association Study, Liver Cirrhosis, Acyltransferases, Phospholipases, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Liver, Protein Serine-Threonine Kinases, Intracellular Signaling Peptides and Proteins, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Nonalcoholic fatty liver disease (NAFLD) is common and partially heritable and has no effective treatments. We carried out a genome-wide association study (GWAS) meta-analysis of imaging (n = 66,814) and diagnostic code (3,584 cases versus 621,081 controls) measured NAFLD across diverse ancestries. We identified NAFLD-associated variants at torsin family 1 member B (TOR1B), fat mass and obesity associated (FTO), cordon-bleu WH2 repeat protein like 1 (COBLL1)/growth factor receptor-bound protein 14 (GRB14), insulin receptor (INSR), sterol regulatory element-binding transcription factor 1 (SREBF1) and patatin-like phospholipase domain-containing protein 2 (PNPLA2), as well as validated NAFLD-associated variants at patatin-like phospholipase domain-containing protein 3 (PNPLA3), transmembrane 6 superfamily 2 (TM6SF2), apolipoprotein E (APOE), glucokinase regulator (GCKR), tribbles homolog 1 (TRIB1), glycerol-3-phosphate acyltransferase (GPAM), mitochondrial amidoxime-reducing component 1 (MARC1), microsomal triglyceride transfer protein large subunit (MTTP), alcohol dehydrogenase 1B (ADH1B), transmembrane channel like 4 (TMC4)/membrane-bound O-acyltransferase domain containing 7 (MBOAT7) and receptor-type tyrosine-protein phosphatase δ (PTPRD). Implicated genes highlight mitochondrial, cholesterol and de novo lipogenesis as causally contributing to NAFLD predisposition. Phenome-wide association study (PheWAS) analyses suggest at least seven subtypes of NAFLD. Individuals in the top 10% and 1% of genetic risk have a 2.5-fold to 6-fold increased risk of NAFLD, cirrhosis and hepatocellular carcinoma. These genetic variants identify subtypes of NAFLD, improve estimates of disease risk and can guide the development of targeted therapeutics.

Published
2023

8. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification

Author

Kavousi, Maryam, Bos, Maxime M, Barnes, Hanna J, Lino Cardenas, Christian L, Wong, Doris, Lu, Haojie, Hodonsky, Chani J, Landsmeer, Lennart PL, Turner, Adam W, Kho, Minjung, Hasbani, Natalie R, de Vries, Paul S, Bowden, Donald W, Chopade, Sandesh, Deelen, Joris, Benavente, Ernest Diez, Guo, Xiuqing, Hofer, Edith, Hwang, Shih-Jen, Lutz, Sharon M, Lyytikäinen, Leo-Pekka, Slenders, Lotte, Smith, Albert V, Stanislawski, Maggie A, van Setten, Jessica, Wong, Quenna, Yanek, Lisa R, Becker, Diane M, Beekman, Marian, Budoff, Matthew J, Feitosa, Mary F, Finan, Chris, Hilliard, Austin T, Kardia, Sharon LR, Kovacic, Jason C, Kral, Brian G, Langefeld, Carl D, Launer, Lenore J, Malik, Shaista, Hoesein, Firdaus AA Mohamed, Mokry, Michal, Schmidt, Reinhold, Smith, Jennifer A, Taylor, Kent D, Terry, James G, van der Grond, Jeroen, van Meurs, Joyce, Vliegenthart, Rozemarijn, Xu, Jianzhao, Young, Kendra A, Zilhão, Nuno R, Zweiker, Robert, Assimes, Themistocles L, Becker, Lewis C, Bos, Daniel, Carr, J Jeffrey, Cupples, L Adrienne, de Kleijn, Dominique PV, de Winther, Menno, den Ruijter, Hester M, Fornage, Myriam, Freedman, Barry I, Gudnason, Vilmundur, Hingorani, Aroon D, Hokanson, John E, Ikram, M Arfan, Išgum, Ivana, Jacobs, David R, Kähönen, Mika, Lange, Leslie A, Lehtimäki, Terho, Pasterkamp, Gerard, Raitakari, Olli T, Schmidt, Helena, Slagboom, P Eline, Uitterlinden, André G, Vernooij, Meike W, Bis, Joshua C, Franceschini, Nora, Psaty, Bruce M, Post, Wendy S, Rotter, Jerome I, Björkegren, Johan LM, O’Donnell, Christopher J, Bielak, Lawrence F, Peyser, Patricia A, Malhotra, Rajeev, van der Laan, Sander W, and Miller, Clint L

Subjects
Biological Sciences, Genetics, Heart Disease - Coronary Heart Disease, Human Genome, Cardiovascular, Prevention, Heart Disease, Atherosclerosis, 2.1 Biological and endogenous factors, Aetiology, Humans, Black People, Coronary Artery Disease, Genome-Wide Association Study, Risk Factors, European People, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

Published
2023

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

Author

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

Published
2024
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10. Genetic insights into resting heart rate and its role in cardiovascular disease.

Author

van de Vegte, Yordi, Eppinga, Ruben, van der Ende, M, Hagemeijer, Yanick, Mahendran, Yuvaraj, Salfati, Elias, Smith, Albert, Tan, Vanessa, Arking, Dan, Ntalla, Ioanna, Appel, Emil, Schurmann, Claudia, Brody, Jennifer, Rueedi, Rico, Polasek, Ozren, Sveinbjornsson, Gardar, Lecoeur, Cecile, Ladenvall, Claes, Zhao, Jing, Isaacs, Aaron, Wang, Lihua, Luan, Jianan, Hwang, Shih-Jen, Mononen, Nina, Auro, Kirsi, Jackson, Anne, Bielak, Lawrence, Zeng, Linyao, Shah, Nabi, Nethander, Maria, Campbell, Archie, Rankinen, Tuomo, Pechlivanis, Sonali, Qi, Lu, Zhao, Wei, Rizzi, Federica, Tanaka, Toshiko, Robino, Antonietta, Cocca, Massimiliano, Lange, Leslie, Müller-Nurasyid, Martina, Roselli, Carolina, Zhang, Weihua, Kleber, Marcus, Guo, Xiuqing, Lin, Henry, Pavani, Francesca, Galesloot, Tessel, Noordam, Raymond, Milaneschi, Yuri, Schraut, Katharina, den Hoed, Marcel, Degenhardt, Frauke, Trompet, Stella, van den Berg, Marten, Pistis, Giorgio, Tham, Yih-Chung, Weiss, Stefan, Sim, Xueling, Li, Hengtong, van der Most, Peter, Nolte, Ilja, Lyytikäinen, Leo-Pekka, Said, M, Witte, Daniel, Iribarren, Carlos, Launer, Lenore, Ring, Susan, de Vries, Paul, Sever, Peter, Linneberg, Allan, Bottinger, Erwin, Padmanabhan, Sandosh, Psaty, Bruce, Sotoodehnia, Nona, Kolcic, Ivana, Arnar, David, Gudbjartsson, Daniel, Holm, Hilma, Balkau, Beverley, Silva, Claudia, Newton-Cheh, Christopher, Nikus, Kjell, Salo, Perttu, Mohlke, Karen, Peyser, Patricia, Schunkert, Heribert, Lorentzon, Mattias, Lahti, Jari, Rao, Dabeeru, Cornelis, Marilyn, Faul, Jessica, Smith, Jennifer, Stolarz-Skrzypek, Katarzyna, Bandinelli, Stefania, Concas, Maria, Sinagra, Gianfranco, Meitinger, Thomas, Waldenberger, Melanie, and Sinner, Moritz

Subjects
Humans, Cardiovascular Diseases, Risk Factors, Heart Rate, Genetic Predisposition to Disease, Atrial Fibrillation, Mendelian Randomization Analysis, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Published
2023

11. Idiopathic Pulmonary Fibrosis Is Associated with Common Genetic Variants and Limited Rare Variants.

Author

Peljto, Anna L, Blumhagen, Rachel Z, Walts, Avram D, Cardwell, Jonathan, Powers, Julia, Corte, Tamera J, Dickinson, Joanne L, Glaspole, Ian, Moodley, Yuben P, Vasakova, Martina Koziar, Bendstrup, Elisabeth, Davidsen, Jesper R, Borie, Raphael, Crestani, Bruno, Dieude, Philippe, Bonella, Francesco, Costabel, Ulrich, Gudmundsson, Gunnar, Donnelly, Seamas C, Egan, Jim, Henry, Michael T, Keane, Michael P, Kennedy, Marcus P, McCarthy, Cormac, McElroy, Aoife N, Olaniyi, Joshua A, O'Reilly, Katherine MA, Richeldi, Luca, Leone, Paolo M, Poletti, Venerino, Puppo, Francesco, Tomassetti, Sara, Luzzi, Valentina, Kokturk, Nurdan, Mogulkoc, Nesrin, Fiddler, Christine A, Hirani, Nikhil, Jenkins, R Gisli, Maher, Toby M, Molyneaux, Philip L, Parfrey, Helen, Braybrooke, Rebecca, Blackwell, Timothy S, Jackson, Peter D, Nathan, Steven D, Porteous, Mary K, Brown, Kevin K, Christie, Jason D, Collard, Harold R, Eickelberg, Oliver, Foster, Elena E, Gibson, Kevin F, Glassberg, Marilyn, Kass, Daniel J, Kropski, Jonathan A, Lederer, David, Linderholm, Angela L, Loyd, Jim, Mathai, Susan K, Montesi, Sydney B, Noth, Imre, Oldham, Justin M, Palmisciano, Amy J, Reichner, Cristina A, Rojas, Mauricio, Roman, Jesse, Schluger, Neil, Shea, Barry S, Swigris, Jeffrey J, Wolters, Paul J, Zhang, Yingze, Prele, Cecilia MA, Enghelmayer, Juan I, Otaola, Maria, Ryerson, Christopher J, Salinas, Mauricio, Sterclova, Martina, Gebremariam, Tewodros H, Myllärniemi, Marjukka, Carbone, Roberto G, Furusawa, Haruhiko, Hirose, Masaki, Inoue, Yoshikazu, Miyazaki, Yasunari, Ohta, Ken, Ohta, Shin, Okamoto, Tsukasa, Kim, Dong Soon, Pardo, Annie, Selman, Moises, Aranda, Alvaro U, Park, Moo Suk, Park, Jong Sun, Song, Jin Woo, Molina-Molina, Maria, Planas-Cerezales, Lurdes, Westergren-Thorsson, Gunilla, Smith, Albert V, Manichaikul, Ani W, and Kim, John S

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Autoimmune Disease, Lung, Rare Diseases, Genetics, Human Genome, Prevention, Precision Medicine, 2.1 Biological and endogenous factors, Good Health and Well Being, Humans, Idiopathic Pulmonary Fibrosis, Whole Genome Sequencing, Exome, whole-genome sequencing, interstitial lung disease, TOPMed, genetic association studies, telomerase, Medical and Health Sciences, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract

Rationale: Idiopathic pulmonary fibrosis (IPF) is a rare, irreversible, and progressive disease of the lungs. Common genetic variants, in addition to nongenetic factors, have been consistently associated with IPF. Rare variants identified by candidate gene, family-based, and exome studies have also been reported to associate with IPF. However, the extent to which rare variants, genome-wide, may contribute to the risk of IPF remains unknown. Objectives: We used whole-genome sequencing to investigate the role of rare variants, genome-wide, on IPF risk. Methods: As part of the Trans-Omics for Precision Medicine Program, we sequenced 2,180 cases of IPF. Association testing focused on the aggregated effect of rare variants (minor allele frequency ⩽0.01) within genes or regions. We also identified individual rare variants that are influential within genes and estimated the heritability of IPF on the basis of rare and common variants. Measurements and Main Results: Rare variants in both TERT and RTEL1 were significantly associated with IPF. A single rare variant in each of the TERT and RTEL1 genes was found to consistently influence the aggregated test statistics. There was no significant evidence of association with other previously reported rare variants. The SNP heritability of IPF was estimated to be 32% (SE = 3%). Conclusions: Rare variants within the TERT and RTEL1 genes and well-established common variants have the largest contribution to IPF risk overall. Efforts in risk profiling or the development of therapies for IPF that focus on TERT, RTEL1, common variants, and environmental risk factors are likely to have the largest impact on this complex disease.

Published
2023

12. Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

Author

Westerman, Kenneth E, Walker, Maura E, Gaynor, Sheila M, Wessel, Jennifer, DiCorpo, Daniel, Ma, Jiantao, Alonso, Alvaro, Aslibekyan, Stella, Baldridge, Abigail S, Bertoni, Alain G, Biggs, Mary L, Brody, Jennifer A, Chen, Yii-Der Ida, Dupuis, Joseé, Goodarzi, Mark O, Guo, Xiuqing, Hasbani, Natalie R, Heath, Adam, Hidalgo, Bertha, Irvin, Marguerite R, Johnson, W Craig, Kalyani, Rita R, Lange, Leslie, Lemaitre, Rozenn N, Liu, Ching-Ti, Liu, Simin, Moon, Jee-Young, Nassir, Rami, Pankow, James S, Pettinger, Mary, Raffield, Laura M, Rasmussen-Torvik, Laura J, Selvin, Elizabeth, Senn, Mackenzie K, Shadyab, Aladdin H, Smith, Albert V, Smith, Nicholas L, Steffen, Lyn, Talegakwar, Sameera, Taylor, Kent D, de Vries, Paul S, Wilson, James G, Wood, Alexis C, Yanek, Lisa R, Yao, Jie, Zheng, Yinan, Boerwinkle, Eric, Morrison, Alanna C, Fornage, Miriam, Russell, Tracy P, Psaty, Bruce M, Levy, Daniel, Heard-Costa, Nancy L, Ramachandran, Vasan S, Mathias, Rasika A, Arnett, Donna K, Kaplan, Robert, North, Kari E, Correa, Adolfo, Carson, April, Rotter, Jerome I, Rich, Stephen S, Manson, JoAnn E, Reiner, Alexander P, Kooperberg, Charles, Florez, Jose C, Meigs, James B, Merino, Jordi, Tobias, Deirdre K, Chen, Han, and Manning, Alisa K

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Diabetes, Human Genome, Minority Health, Genetics, Cardiovascular, Health Disparities, Prevention, Precision Medicine, Clinical Research, Metabolic and endocrine, Good Health and Well Being, Humans, Glycated Hemoglobin, Diet, Diabetes Mellitus, Eating, Guanine Nucleotide Dissociation Inhibitors, Genome-Wide Association Study, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.Article highlightsWe aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Published
2023

13. 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

14. Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program.

Author

Armstrong, Nicole, Srinivasasainagendra, Vinodh, Ammous, Farah, Assimes, Themistocles, Beitelshees, Amber, Brody, Jennifer, Cade, Brian, Ida Chen, Yii-Der, Chen, Han, de Vries, Paul, Floyd, James, Franceschini, Nora, Guo, Xiuqing, Hellwege, Jacklyn, House, John, Hwu, Chii-Min, Kardia, Sharon, Lange, Ethan, Lange, Leslie, McDonough, Caitrin, Montasser, May, OConnell, Jeffrey, Shuey, Megan, Sun, Xiao, Tanner, Rikki, Wang, Zhe, Zhao, Wei, Carson, April, Edwards, Todd, Kelly, Tanika, Kenny, Eimear, Kooperberg, Charles, Loos, Ruth, Morrison, Alanna, Motsinger-Reif, Alison, Psaty, Bruce, Rao, Dabeeru, Redline, Susan, Rich, Stephen, Rotter, Jerome, Smith, Jennifer, Smith, Albert, Irvin, Marguerite, and Arnett, Donna

Subjects
TOPMed, antihypertensive response, blood pressure, treatment resistant hypertension, whole genome sequencing
Abstract

Introduction: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data. Methods: Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP (n = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg (n = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg (n = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American). Results: One variant in the known HTN locus, KCNK3, was a top finding in the multi-ethnic analysis (p = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74-0.88)]. This variant was replicated in the Vanderbilt University Medical Centers DNA repository data. Aggregate gene-based signals included the genes AGTPBP, MYL4, PDCD4, BBS9, ERG, and IER3. Discussion: Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.

Published
2023

15. Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Author

Young, Kristin L, Fisher, Virginia, Deng, Xuan, Brody, Jennifer A, Graff, Misa, Lim, Elise, Lin, Bridget M, Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E, Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G, Buth, Erin J, Heavner, Benjamin D, Jain, Deepti, Smith, Albert V, Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R, Kalyani, Rita R, Kardia, Sharon LR, Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A, McDonald, Merry-Lynn, Mitchell, Braxton D, Peyser, Patricia A, Regan, Elizabeth A, Redline, Susan, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Weiss, Scott, Wiggins, Kerri L, Yanek, Lisa R, Arnett, Donna, Heard-Costa, Nancy L, Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M, North, Kari E, Cupples, L Adrienne, and Liu, Ching-Ti

Subjects
Biological Sciences, Genetics, Clinical Research, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Humans, Genome-Wide Association Study, Exome, Body Mass Index, Quantitative Trait Loci, Anthropometry, Intercellular Signaling Peptides and Proteins, Cell Cycle Proteins, body mass index, central obesity, exome sequencing, height
Abstract

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Published
2023

16. FixItFelix: improving genomic analysis by fixing reference errors

Author

Behera, Sairam, LeFaive, Jonathon, Orchard, Peter, Mahmoud, Medhat, Paulin, Luis F, Farek, Jesse, Soto, Daniela C, Parker, Stephen CJ, Smith, Albert V, Dennis, Megan Y, Zook, Justin M, and Sedlazeck, Fritz J

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Humans, Genomics, Genome, Human, High-Throughput Nucleotide Sequencing, Sequence Analysis, DNA, Reference, GRCh38, T2T-CHM13, Variant, SNV, INDEL, Medically relevant genes, Remapping, GIAB, eQTL, Environmental Sciences, Information and Computing Sciences, Bioinformatics
Abstract

The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.

Published
2023

17. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Author

Lahti, Jari, Tuominen, Samuli, Yang, Qiong, Pergola, Giulio, Ahmad, Shahzad, Amin, Najaf, Armstrong, Nicola J, Beiser, Alexa, Bey, Katharina, Bis, Joshua C, Boerwinkle, Eric, Bressler, Jan, Campbell, Archie, Campbell, Harry, Chen, Qiang, Corley, Janie, Cox, Simon R, Davies, Gail, De Jager, Philip L, Derks, Eske M, Faul, Jessica D, Fitzpatrick, Annette L, Fohner, Alison E, Ford, Ian, Fornage, Myriam, Gerring, Zachary, Grabe, Hans J, Grodstein, Francine, Gudnason, Vilmundur, Simonsick, Eleanor, Holliday, Elizabeth G, Joshi, Peter K, Kajantie, Eero, Kaprio, Jaakko, Karell, Pauliina, Kleineidam, Luca, Knol, Maria J, Kochan, Nicole A, Kwok, John B, Leber, Markus, Lam, Max, Lee, Teresa, Li, Shuo, Loukola, Anu, Luck, Tobias, Marioni, Riccardo E, Mather, Karen A, Medland, Sarah, Mirza, Saira S, Nalls, Mike A, Nho, Kwangsik, O’Donnell, Adrienne, Oldmeadow, Christopher, Painter, Jodie, Pattie, Alison, Reppermund, Simone, Risacher, Shannon L, Rose, Richard J, Sadashivaiah, Vijay, Scholz, Markus, Satizabal, Claudia L, Schofield, Peter W, Schraut, Katharina E, Scott, Rodney J, Simino, Jeannette, Smith, Albert V, Smith, Jennifer A, Stott, David J, Surakka, Ida, Teumer, Alexander, Thalamuthu, Anbupalam, Trompet, Stella, Turner, Stephen T, van der Lee, Sven J, Villringer, Arno, Völker, Uwe, Wilson, Robert S, Wittfeld, Katharina, Vuoksimaa, Eero, Xia, Rui, Yaffe, Kristine, Yu, Lei, Zare, Habil, Zhao, Wei, Ames, David, Attia, John, Bennett, David A, Brodaty, Henry, Chasman, Daniel I, Goldman, Aaron L, Hayward, Caroline, Ikram, M Arfan, Jukema, J Wouter, Kardia, Sharon LR, Lencz, Todd, Loeffler, Markus, Mattay, Venkata S, Palotie, Aarno, Psaty, Bruce M, and Ramirez, Alfredo

Subjects
Biological Psychology, Psychology, Genetics, Human Genome, Dementia, Behavioral and Social Science, Brain Disorders, Acquired Cognitive Impairment, Mental Health, Biotechnology, Aging, Clinical Research, Neurosciences, Basic Behavioral and Social Science, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Memory, Short-Term, Learning, Verbal Learning, Multifactorial Inheritance, Brain, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

Published
2022

18. Rare genetic variants explain missing heritability in smoking.

Author

Jang, Seon-Kyeong, Evans, Luke, Fialkowski, Allison, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Becker, Diane M, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Boorgula, Meher Preethi, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Jenkins, Brenda W Campbell, Carson, April P, Chavan, Sameer, Cupples, L Adrienne, Custer, Brian, Damrauer, Scott M, David, Sean P, de Andrade, Mariza, Dinardo, Carla L, Fingerlin, Tasha E, Fornage, Myriam, Freedman, Barry I, Garrett, Melanie E, Gharib, Sina A, Glahn, David C, Haessler, Jeffrey, Heckbert, Susan R, Hokanson, John E, Hou, Lifang, Hwang, Shih-Jen, Hyman, Matthew C, Judy, Renae, Justice, Anne E, Kaplan, Robert C, Kardia, Sharon LR, Kelly, Shannon, Kim, Wonji, Kooperberg, Charles, Levy, Daniel, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani W, Gladwin, Mark T, Martin, Lisa Warsinger, Nouraie, Mehdi, Melander, Olle, Meyers, Deborah A, Montgomery, Courtney G, North, Kari E, Oelsner, Elizabeth C, Palmer, Nicholette D, Payton, Marinelle, Peljto, Anna L, Peyser, Patricia A, Preuss, Michael, Psaty, Bruce M, Qiao, Dandi, Rader, Daniel J, Rafaels, Nicholas, Redline, Susan, Reed, Robert M, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Schwartz, David A, Shadyab, Aladdin H, Silverman, Edwin K, Smith, Nicholas L, Smith, J Gustav, Smith, Albert V, Smith, Jennifer A, Tang, Weihong, Taylor, Kent D, Telen, Marilyn J, Vasan, Ramachandran S, Gordeuk, Victor R, Wang, Zhe, Wiggins, Kerri L, Yanek, Lisa R, Yang, Ivana V, Young, Kendra A, Young, Kristin L, Zhang, Yingze, Liu, Dajiang J, Keller, Matthew C, and Vrieze, Scott

Subjects
Smoking, Gene Frequency, Phenotype, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Tobacco, Genetics, Tobacco Smoke and Health, Human Genome, Cancer
Abstract

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

Published
2022

20. Interpreting NMR dynamic parameters via the separation of reorientational motion in MD simulation

Author

Smith, Albert A.

Subjects
Physics - Chemical Physics, Physics - Computational Physics
Abstract

Reorientational dynamics-motion defined by changes in the direction of a vector or tensor-determine relaxation behavior in nuclear magnetic resonance (NMR). However, if multiple processes exist that result in reorientation, then analyzing the net effects becomes a complex task, so that one ideally would separate those motions to simplify analysis. The model-free and two-step approaches have established the separability of the total correlation function of reorientation motion into contributions from statistically independent motions. Separability has been used to justify the analysis of experimental relaxation rate constants by fitting data to a total correlation function resulting from the product of two or three individual correlation functions, each representing an independent motion. The resulting parameters are used to describe motion in the molecule, but if multiple internal motions are present, interpreting those parameters is not trivial. We suggest an alternative approach: quantitative and timescale-specific comparison of experiment and simulation, as previously established using the detector analysis. This is followed by separation of simulated correlation functions into independent motions, and timescale-specific parameterization of the results, such that one may determine how each motion contributes to experimental parameters. We establish protocols for the separation of the correlation function into components using coordinates from molecular dynamics simulation. Separation is achieved by defining a series of frames, where the frames iteratively split the total motion into contributions from motion within each frame and of each frame. Then timescale specific parameters (e.g. detector responses) describing the total motion may be interpreted in terms of the timescale-specific parameterization of the individual motions., Comment: 60 pages, 8 figures

Published
2021

21. 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

22. 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

23. Prioritization of Kidney Cell Types Highlights Myofibroblast Cells in Regulating Human Blood Pressure

Author

Evangelou, Evangelos, Warren, Helen R., Gao, He, Ntritsos, Georgios, Dimou, Niki, Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stéphanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G., Jackson, Anne U., Li -Gao, Ruifang, Lin, Wei -Yu, Luan, Jian'an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram Peter, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M., Zhao, Jing -Hua, Amouyel, Philippe, Connell, John, de Mutsert, Renée, Doney, Alex S.F., Farrall, Martin, Menni, Cristina, Morris, Andrew D., Noordam, Raymond, Paré, Guillaume, Poulter, Neil R., Shields, Denis C., Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E., Ayers, Kristin L., Barbieri, Caterina M., Batini, Chiara, Bis, Joshua C., Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I., Bottinger, Erwin P., Braund, Peter S., Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C., Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J., Davies, Gail, de Borst, Martin H., de Geus, Eco J., Deary, Ian J., Deelen, Joris, Del Greco M, Fabiola, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B., Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A. Mesut, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H., Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J., Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B., Harris, Sarah E., Hartman, Catharina A., Havulinna, Aki S., Hicks, Andrew A., Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E., Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo -Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D., Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D., Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S., Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J., Lehne, Benjamin, Lehtimäki, Terho, Liewald, David C.M., Lin, Li, Lind, Lars, Lindgren, Cecilia M., Liu, YongMei, Loos, Ruth J.F., Lopez, Lorna M., Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P., Morrison, Alanna C., Munson, Peter J., Nalls, Mike A., Nandakumar, Priyanka, Nelson, Christopher P., Niiranen, Teemu, Nolte, Ilja M., Nutile, Teresa, Oldehinkel, Albertine J., Oostra, Ben A., O'Reilly, Paul F., Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, Penninx, Brenda W.J.H., Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P., Nguyen, Quang Tri, Raitakari, Olli T., Rettig, Rainer, Rice, Kenneth, Ridker, Paul M., Ried, Janina S., Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M., Rotter, Jerome I., Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F., Salomaa, Veikko, Samani, Nilesh J., Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V., Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M., Stott, David J., Strachan, David P., Strawbridge, Rona J., Sundström, Johan, Swertz, Morris A., Taylor, Kent D., Teumer, Alexander, Tobin, Martin D., Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G., Vaez, Ahmad, van der Most, Peter J., van Duijn, Cornelia M., Verwoert, Germaine C., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H., Willemsen, Gonneke, Wilson, James F., Wright, Alan F., Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R., Butterworth, Adam S., Chasman, Daniel I., Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna M.M., Laakso, Markku, Lakatta, Edward G., Langenberg, Claudia, Melander, Olle, Mook-Kanamori, Dennis O., Palmer, Colin N.A., Risch, Lorenz, Scott, Robert A., Scott, Rodney J., Sever, Peter, Spector, Tim D., van der Harst, Pim, Wareham, Nicholas J., Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B., Newton-Cheh, Christopher, Brown, Morris J., Metspalu, Andres, Psaty, Bruce M., Wain, Louise V., Elliott, Paul, Caulfield, Mark J., Ganji-Arjenaki, Mahboube, Kamali, Zoha, Sardari, Soroush, and de Borst, Martin

Published
2024
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24. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

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

Published
2024
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26. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Author

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

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

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

Published
2022

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

Author

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

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

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

Published
2022

28. Gene Set Enrichment Analsyes Identiify Pathways Involved in Genetic Risk for Diabetic Retinopathy

Author

Sobrin, Lucia, Susarla, Gayatri, Stanwyck, Lynn, Rouhana, John M, Li, Ashley, Pollack, Samuela, Igo, Robert P, Jensen, Richard A, Li, Xiaohui, Ng, Maggie CY, Smith, Albert V, Kuo, Jane Z, Taylor, Kent D, Freedman, Barry I, Bowden, Donald W, Penman, Alan, Chen, Ching J, Craig, Jamie E, Adler, Sharon G, Chew, Emily Y, Cotch, Mary Frances, Yaspan, Brian, Mitchell, Paul, Wang, Jie Jin, Klein, Barbara EK, Wong, Tien Y, Rotter, Jerome I, Burdon, Kathyrn P, Iyengar, Sudha K, and Segrè, Ayellet V

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Diabetes, Genetics, Human Genome, 2.1 Biological and endogenous factors, Diabetes Mellitus, Type 2, Diabetic Retinopathy, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors, Clinical Sciences, Opthalmology and Optometry, Public Health and Health Services, Ophthalmology & Optometry, Ophthalmology and optometry
Abstract

To identify functionally related genes associated with diabetic retinopathy (DR) risk using gene set enrichment analyses applied to genome-wide association study meta-analyses.MethodsWe analyzed DR GWAS meta-analyses performed on 3246 Europeans and 2611 African Americans with type 2 diabetes. Gene sets relevant to 5 key DR pathophysiology processes were investigated: tissue injury, vascular events, metabolic events and glial dysregulation, neuronal dysfunction, and inflammation. Keywords relevant to these processes were queried in 4 pathway and ontology databases. Two GSEA methods, Meta-Analysis Gene set Enrichment of variaNT Associations (MAGENTA) and Multi-marker Analysis of GenoMic Annotation (MAGMA), were used. Gene sets were defined to be enriched for gene associations with DR if the P value corrected for multiple testing (Pcorr) was

Published
2022

29. 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

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

Author

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

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

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

Published
2021

33. A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response

Author

Luo, Yang, Kanai, Masahiro, Choi, Wanson, Li, Xinyi, Sakaue, Saori, Yamamoto, Kenichi, Ogawa, Kotaro, Gutierrez-Arcelus, Maria, Gregersen, Peter K, Stuart, Philip E, Elder, James T, Forer, Lukas, Schönherr, Sebastian, Fuchsberger, Christian, Smith, Albert V, Fellay, Jacques, Carrington, Mary, Haas, David W, Guo, Xiuqing, Palmer, Nicholette D, Chen, Yii-Der Ida, Rotter, Jerome I, Taylor, Kent D, Rich, Stephen S, Correa, Adolfo, Wilson, James G, Kathiresan, Sekar, Cho, Michael H, Metspalu, Andres, Esko, Tonu, Okada, Yukinori, Han, Buhm, McLaren, Paul J, and Raychaudhuri, Soumya

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Alleles, Amino Acids, Gene Frequency, Genetic Variation, Genetics, Population, HIV Infections, HIV-1, HLA Antigens, Haplotypes, Host-Pathogen Interactions, Humans, Linkage Disequilibrium, Physical Chromosome Mapping, Reference Standards, Selection, Genetic, Viral Load, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large (n = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population-specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide-binding groove, explaining 12.9% of trait variance.

Published
2021

34. Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes

Author

Lu, Yingchang, Dimitrov, Latchezar, Chen, Shyh-Huei, Bielak, Lawrence F, Bis, Joshua C, Feitosa, Mary F, Lu, Lingyi, Kavousi, Maryam, Raffield, Laura M, Smith, Albert V, Wang, Lihua, Weiss, Stefan, Yao, Jie, Zhu, Jiaxi, Gudmundsson, Elias F, Gudmundsdottir, Valborg, Bos, Daniel, Ghanbari, Mohsen, Ikram, M Arfan, Hwang, Shih-Jen, Taylor, Kent D, Budoff, Matthew J, Gíslason, Gauti K, O’Donnell, Christopher J, An, Ping, Franceschini, Nora, Freedman, Barry I, Fu, Yi-Ping, Guo, Xiuqing, Heiss, Gerardo, Kardia, Sharon LR, Wilson, James G, Langefeld, Carl D, Schminke, Ulf, Uitterlinden, André G, Lange, Leslie A, Peyser, Patricia A, Gudnason, Vilmundur G, Psaty, Bruce M, Rotter, Jerome I, Bowden, Donald W, and Ng, Maggie CY

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Genetics, Diabetes, Biotechnology, Heart Disease, Atherosclerosis, Biomedical Imaging, Aging, Prevention, Heart Disease - Coronary Heart Disease, Cardiovascular, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Black People, Diabetes Complications, Diabetes Mellitus, Type 2, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, White People, atherosclerosis, carotid intima-media thickness, coronary artery disease, genetics, genome-wide association study, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundCoronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis.MethodsWe performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium.ResultsWe replicated 2 loci (rs9369640 and rs9349379 near PHACTR1 and rs10757278 near CDKN2B) for CAC and one locus for cIMT (rs7412 and rs445925 near APOE-APOC1) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near CSNK1A1L/LINC00547/POSTN at 13q13.3) at P=2.0×10-8 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints POSTN, encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations (P

Published
2021

35. Allele-specific variation at APOE increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer’s disease and myocardial infarction

Author

Palmer, Nicholette D, Kahali, Bratati, Kuppa, Annapurna, Chen, Yanhua, Du, Xiaomeng, Feitosa, Mary F, Bielak, Lawrence F, O’Connell, Jeffrey R, Musani, Solomon K, Guo, Xiuqing, Smith, Albert V, Ryan, Kathleen A, Eirksdottir, Gudny, Allison, Matthew A, Bowden, Donald W, Budoff, Matthew J, Carr, J Jeffrey, Chen, Yii-Der I, Taylor, Kent D, Correa, Adolfo, Crudup, Breland F, Halligan, Brian, Yang, Jian, Kardia, Sharon LR, Launer, Lenore J, Fu, Yi-Ping, Mosley, Thomas H, Norris, Jill M, Terry, James G, O’Donnell, Christopher J, Rotter, Jerome I, Wagenknecht, Lynne E, Gudnason, Vilmundur, Province, Michael A, Peyser, Patricia A, and Speliotes, Elizabeth K

Subjects
Biological Sciences, Genetics, Digestive Diseases, Brain Disorders, Prevention, Aging, Chronic Liver Disease and Cirrhosis, Obesity, Neurosciences, Alzheimer's Disease, Liver Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Neurodegenerative, Human Genome, Hepatitis, Dementia, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Alanine Transaminase, Alleles, Alzheimer Disease, Apolipoproteins E, Databases, Genetic, Exome, Gene Frequency, Genome-Wide Association Study, Humans, Liver, Liver Cirrhosis, Myocardial Infarction, Non-alcoholic Fatty Liver Disease, Phenotype, Polymorphism, Single Nucleotide, Prognosis, Risk Factors, Triglycerides, Medical and Health Sciences, Genetics & Heredity
Abstract

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P

Published
2021

36. Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Author

Shrine, Nick, Izquierdo, Abril G., Chen, Jing, Packer, Richard, Hall, Robert J., Guyatt, Anna L., Batini, Chiara, Thompson, Rebecca J., Pavuluri, Chandan, Malik, Vidhi, Hobbs, Brian D., Moll, Matthew, Kim, Wonji, Tal-Singer, Ruth, Bakke, Per, Fawcett, Katherine A., John, Catherine, Coley, Kayesha, Piga, Noemi Nicole, Pozarickij, Alfred, Lin, Kuang, Millwood, Iona Y., Chen, Zhengming, Li, Liming, Wijnant, Sara R. A., Lahousse, Lies, Brusselle, Guy, Uitterlinden, Andre G., Manichaikul, Ani, Oelsner, Elizabeth C., Rich, Stephen S., Barr, R. Graham, Kerr, Shona M., Vitart, Veronique, Brown, Michael R., Wielscher, Matthias, Imboden, Medea, Jeong, Ayoung, Bartz, Traci M., Gharib, Sina A., Flexeder, Claudia, Karrasch, Stefan, Gieger, Christian, Peters, Annette, Stubbe, Beate, Hu, Xiaowei, Ortega, Victor E., Meyers, Deborah A., Bleecker, Eugene R., Gabriel, Stacey B., Gupta, Namrata, Smith, Albert Vernon, Luan, Jian’an, Zhao, Jing-Hua, Hansen, Ailin F., Langhammer, Arnulf, Willer, Cristen, Bhatta, Laxmi, Porteous, David, Smith, Blair H., Campbell, Archie, Sofer, Tamar, Lee, Jiwon, Daviglus, Martha L., Yu, Bing, Lim, Elise, Xu, Hanfei, O’Connor, George T., Thareja, Gaurav, Albagha, Omar M. E., Suhre, Karsten, Granell, Raquel, Faquih, Tariq O., Hiemstra, Pieter S., Slats, Annelies M., Mullin, Benjamin H., Hui, Jennie, James, Alan, Beilby, John, Patasova, Karina, Hysi, Pirro, Koskela, Jukka T., Wyss, Annah B., Jin, Jianping, Sikdar, Sinjini, Lee, Mikyeong, May-Wilson, Sebastian, Pirastu, Nicola, Kentistou, Katherine A., Joshi, Peter K., Timmers, Paul R. H. J., Williams, Alexander T., Free, Robert C., Wang, Xueyang, Morrison, John L., Gilliland, Frank D., Chen, Zhanghua, Wang, Carol A., Foong, Rachel E., Harris, Sarah E., Taylor, Adele, Redmond, Paul, Cook, James P., Mahajan, Anubha, Lind, Lars, Palviainen, Teemu, Lehtimäki, Terho, Raitakari, Olli T., Kaprio, Jaakko, Rantanen, Taina, Pietiläinen, Kirsi H., Cox, Simon R., Pennell, Craig E., Hall, Graham L., Gauderman, W. James, Brightling, Chris, Wilson, James F., Vasankari, Tuula, Laitinen, Tarja, Salomaa, Veikko, Mook-Kanamori, Dennis O., Timpson, Nicholas J., Zeggini, Eleftheria, Dupuis, Josée, Hayward, Caroline, Brumpton, Ben, Langenberg, Claudia, Weiss, Stefan, Homuth, Georg, Schmidt, Carsten Oliver, Probst-Hensch, Nicole, Jarvelin, Marjo-Riitta, Morrison, Alanna C., Polasek, Ozren, Rudan, Igor, Lee, Joo-Hyeon, Sayers, Ian, Rawlins, Emma L., Dudbridge, Frank, Silverman, Edwin K., Strachan, David P., Walters, Robin G., Morris, Andrew P., London, Stephanie J., Cho, Michael H., Wain, Louise V., Hall, Ian P., and Tobin, Martin D.

Published
2023
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37. Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin.

Author

Champion, Candide, Lehner, Marc, Smith, Albert A., Ferrage, Fabien, Bolik-Coulon, Nicolas, and Riniker, Sereina

Subjects
MOLECULAR dynamics, UBIQUITIN, NUCLEAR magnetic resonance, JUMP processes, RELAXATION techniques, PROTEINS
Abstract

Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Author

Shrine, Nick, Izquierdo, Abril G., Chen, Jing, Packer, Richard, Hall, Robert J., Guyatt, Anna L., Batini, Chiara, Thompson, Rebecca J., Pavuluri, Chandan, Malik, Vidhi, Hobbs, Brian D., Moll, Matthew, Kim, Wonji, Tal-Singer, Ruth, Bakke, Per, Fawcett, Katherine A., John, Catherine, Coley, Kayesha, Piga, Noemi Nicole, Pozarickij, Alfred, Lin, Kuang, Millwood, Iona Y., Chen, Zhengming, Li, Liming, Wijnant, Sara R. A., Lahousse, Lies, Brusselle, Guy, Uitterlinden, Andre G., Manichaikul, Ani, Oelsner, Elizabeth C., Rich, Stephen S., Barr, R. Graham, Kerr, Shona M., Vitart, Veronique, Brown, Michael R., Wielscher, Matthias, Imboden, Medea, Jeong, Ayoung, Bartz, Traci M., Gharib, Sina A., Flexeder, Claudia, Karrasch, Stefan, Gieger, Christian, Peters, Annette, Stubbe, Beate, Hu, Xiaowei, Ortega, Victor E., Meyers, Deborah A., Bleecker, Eugene R., Gabriel, Stacey B., Gupta, Namrata, Smith, Albert Vernon, Luan, Jian’an, Zhao, Jing-Hua, Hansen, Ailin F., Langhammer, Arnulf, Willer, Cristen, Bhatta, Laxmi, Porteous, David, Smith, Blair H., Campbell, Archie, Sofer, Tamar, Lee, Jiwon, Daviglus, Martha L., Yu, Bing, Lim, Elise, Xu, Hanfei, O’Connor, George T., Thareja, Gaurav, Albagha, Omar M. E., Suhre, Karsten, Granell, Raquel, Faquih, Tariq O., Hiemstra, Pieter S., Slats, Annelies M., Mullin, Benjamin H., Hui, Jennie, James, Alan, Beilby, John, Patasova, Karina, Hysi, Pirro, Koskela, Jukka T., Wyss, Annah B., Jin, Jianping, Sikdar, Sinjini, Lee, Mikyeong, May-Wilson, Sebastian, Pirastu, Nicola, Kentistou, Katherine A., Joshi, Peter K., Timmers, Paul R. H. J., Williams, Alexander T., Free, Robert C., Wang, Xueyang, Morrison, John L., Gilliland, Frank D., Chen, Zhanghua, Wang, Carol A., Foong, Rachel E., Harris, Sarah E., Taylor, Adele, Redmond, Paul, Cook, James P., Mahajan, Anubha, Lind, Lars, Palviainen, Teemu, Lehtimäki, Terho, Raitakari, Olli T., Kaprio, Jaakko, Rantanen, Taina, Pietiläinen, Kirsi H., Cox, Simon R., Pennell, Craig E., Hall, Graham L., Gauderman, W. James, Brightling, Chris, Wilson, James F., Vasankari, Tuula, Laitinen, Tarja, Salomaa, Veikko, Mook-Kanamori, Dennis O., Timpson, Nicholas J., Zeggini, Eleftheria, Dupuis, Josée, Hayward, Caroline, Brumpton, Ben, Langenberg, Claudia, Weiss, Stefan, Homuth, Georg, Schmidt, Carsten Oliver, Probst-Hensch, Nicole, Jarvelin, Marjo-Riitta, Morrison, Alanna C., Polasek, Ozren, Rudan, Igor, Lee, Joo-Hyeon, Sayers, Ian, Rawlins, Emma L., Dudbridge, Frank, Silverman, Edwin K., Strachan, David P., Walters, Robin G., Morris, Andrew P., London, Stephanie J., Cho, Michael H., Wain, Louise V., Hall, Ian P., and Tobin, Martin D.

Published
2023
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40. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Author

de Las Fuentes, Lisa, Sung, Yun Ju, Noordam, Raymond, Winkler, Thomas, Feitosa, Mary F, Schwander, Karen, Bentley, Amy R, Brown, Michael R, Guo, Xiuqing, Manning, Alisa, Chasman, Daniel I, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Campbell, Archie, Cheng, Ching-Yu, Dorajoo, Rajkumar, Hartwig, Fernando P, Horimoto, ARVR, Li, Changwei, Li-Gao, Ruifang, Liu, Yongmei, Marten, Jonathan, Musani, Solomon K, Ntalla, Ioanna, Rankinen, Tuomo, Richard, Melissa, Sim, Xueling, Smith, Albert V, Tajuddin, Salman M, Tayo, Bamidele O, Vojinovic, Dina, Warren, Helen R, Xuan, Deng, Alver, Maris, Boissel, Mathilde, Chai, Jin-Fang, Chen, Xu, Christensen, Kaare, Divers, Jasmin, Evangelou, Evangelos, Gao, Chuan, Girotto, Giorgia, Harris, Sarah E, He, Meian, Hsu, Fang-Chi, Kühnel, Brigitte, Laguzzi, Federica, Li, Xiaoyin, Lyytikäinen, Leo-Pekka, Nolte, Ilja M, Poveda, Alaitz, Rauramaa, Rainer, Riaz, Muhammad, Rueedi, Rico, Shu, Xiao-Ou, Snieder, Harold, Sofer, Tamar, Takeuchi, Fumihiko, Verweij, Niek, Ware, Erin B, Weiss, Stefan, Yanek, Lisa R, Amin, Najaf, Arking, Dan E, Arnett, Donna K, Bergmann, Sven, Boerwinkle, Eric, Brody, Jennifer A, Broeckel, Ulrich, Brumat, Marco, Burke, Gregory, Cabrera, Claudia P, Canouil, Mickaël, Chee, Miao Li, Chen, Yii-Der Ida, Cocca, Massimiliano, Connell, John, de Silva, H Janaka, de Vries, Paul S, Eiriksdottir, Gudny, Faul, Jessica D, Fisher, Virginia, Forrester, Terrence, Fox, Ervin F, Friedlander, Yechiel, Gao, He, Gigante, Bruna, Giulianini, Franco, Gu, Chi Charles, Gu, Dongfeng, Harris, Tamara B, He, Jiang, Heikkinen, Sami, Heng, Chew-Kiat, Hunt, Steven, Ikram, M Arfan, Irvin, Marguerite R, Kähönen, Mika, and Kavousi, Maryam

Subjects
Lifelines Cohort Study, Psychiatry, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P

Published
2021

41. Robust, flexible, and scalable tests for Hardy-Weinberg Equilibrium across diverse ancestries

Author

Kwong, Alan M, Blackwell, Thomas W, LeFaive, Jonathon, de Andrade, Mariza, Barnard, John, Barnes, Kathleen C, Blangero, John, Boerwinkle, Eric, Burchard, Esteban G, Cade, Brian E, Chasman, Daniel I, Chen, Han, Conomos, Matthew P, Cupples, L Adrienne, Ellinor, Patrick T, Eng, Celeste, Gao, Yan, Guo, Xiuqing, Irvin, Marguerite Ryan, Kelly, Tanika N, Kim, Wonji, Kooperberg, Charles, Lubitz, Steven A, Mak, Angel CY, Manichaikul, Ani W, Mathias, Rasika A, Montasser, May E, Montgomery, Courtney G, Musani, Solomon, Palmer, Nicholette D, Peloso, Gina M, Qiao, Dandi, Reiner, Alexander P, Roden, Dan M, Shoemaker, M Benjamin, Smith, Jennifer A, Smith, Nicholas L, Su, Jessica Lasky, Tiwari, Hemant K, Weeks, Daniel E, Weiss, Scott T, Consortium, TOPMed Analysis Working Group NHLBI Trans-Omics for Precision Medicine, Scott, Laura J, Smith, Albert V, Abecasis, Gonçalo R, Boehnke, Michael, and Kang, Hyun Min

Subjects
Genetics, Alleles, Gene Frequency, Genetics, Population, Genotype, Humans, Linkage Disequilibrium, Models, Genetic, Models, Statistical, Phenotype, Software, population structure, principal components analysis, next-generation sequencing, genotype likelihoods, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Analysis Working Group, Developmental Biology
Abstract

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

Published
2021

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

Author

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

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

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

Published
2021

43. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.

Author

Natarajan, Pradeep, Pampana, Akhil, Graham, Sarah E, Ruotsalainen, Sanni E, Perry, James A, de Vries, Paul S, Broome, Jai G, Pirruccello, James P, Honigberg, Michael C, Aragam, Krishna, Wolford, Brooke, Brody, Jennifer A, Antonacci-Fulton, Lucinda, Arden, Moscati, Aslibekyan, Stella, Assimes, Themistocles L, Ballantyne, Christie M, Bielak, Lawrence F, Bis, Joshua C, Cade, Brian E, Do, Ron, Doddapaneni, Harsha, Emery, Leslie S, Hung, Yi-Jen, Irvin, Marguerite R, Khan, Alyna T, Lange, Leslie, Lee, Jiwon, Lemaitre, Rozenn N, Martin, Lisa W, Metcalf, Ginger, Montasser, May E, Moon, Jee-Young, Muzny, Donna, O'Connell, Jeffrey R, Palmer, Nicholette D, Peralta, Juan M, Peyser, Patricia A, Stilp, Adrienne M, Tsai, Michael, Wang, Fei Fei, Weeks, Daniel E, Yanek, Lisa R, Wilson, James G, Abecasis, Goncalo, Arnett, Donna K, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Chang, Yi-Cheng, Chen, Yii-Der I, Choi, Won Jung, Correa, Adolfo, Curran, Joanne E, Daly, Mark J, Dutcher, Susan K, Ellinor, Patrick T, Fornage, Myriam, Freedman, Barry I, Gabriel, Stacey, Germer, Soren, Gibbs, Richard A, He, Jiang, Hveem, Kristian, Jarvik, Gail P, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear, Kim, Ryan W, Kooperberg, Charles, Laurie, Cathy C, Lee, Seonwook, Lloyd-Jones, Don M, Loos, Ruth JF, Lubitz, Steven A, Mathias, Rasika A, Martinez, Karine A Viaud, McGarvey, Stephen T, Mitchell, Braxton D, Nickerson, Deborah A, North, Kari E, Palotie, Aarno, Park, Cheol Joo, Psaty, Bruce M, Rao, DC, Redline, Susan, Reiner, Alexander P, Seo, Daekwan, Seo, Jeong-Sun, Smith, Albert V, Tracy, Russell P, Vasan, Ramachandran S, Kathiresan, Sekar, Cupples, L Adrienne, Rotter, Jerome I, Morrison, Alanna C, Rich, Stephen S, Ripatti, Samuli, and Willer, Cristen

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, FinnGen, Subcutaneous Tissue, Chromosomes, Human, X, Humans, Genetic Predisposition to Disease, Lipids, Eye Proteins, Nerve Tissue Proteins, Gene Expression Regulation, Genotype, Polymorphism, Single Nucleotide, Middle Aged, Female, Male, Genetic Loci, Genetic Association Studies, Whole Genome Sequencing, Phenomics, Cardiometabolic Risk Factors, Chromosomes, Human, X, Polymorphism, Single Nucleotide
Abstract

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

Published
2021

44. 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

45. Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium

Author

Lin, Bridget M, Grinde, Kelsey E, Brody, Jennifer A, Breeze, Charles E, Raffield, Laura M, Mychaleckyj, Josyf C, Thornton, Timothy A, Perry, James A, Baier, Leslie J, de las Fuentes, Lisa, Guo, Xiuqing, Heavner, Benjamin D, Hanson, Robert L, Hung, Yi-Jen, Qian, Huijun, Hsiung, Chao A, Hwang, Shih-Jen, Irvin, Margaret R, Jain, Deepti, Kelly, Tanika N, Kobes, Sayuko, Lange, Leslie, Lash, James P, Li, Yun, Liu, Xiaoming, Mi, Xuenan, Musani, Solomon K, Papanicolaou, George J, Parsa, Afshin, Reiner, Alex P, Salimi, Shabnam, Sheu, Wayne H-H, Shuldiner, Alan R, Taylor, Kent D, Smith, Albert V, Smith, Jennifer A, Tin, Adrienne, Vaidya, Dhananjay, Wallace, Robert B, Yamamoto, Kenichi, Sakaue, Saori, Matsuda, Koichi, Kamatani, Yoichiro, Momozawa, Yukihide, Yanek, Lisa R, Young, Betsi A, Zhao, Wei, Okada, Yukinori, Abecasis, Gonzalo, Psaty, Bruce M, Arnett, Donna K, Boerwinkle, Eric, Cai, Jianwen, Chen, Ida Yii-Der, Correa, Adolfo, Cupples, L Adrienne, He, Jiang, Kardia, Sharon LR, Kooperberg, Charles, Mathias, Rasika A, Mitchell, Braxton D, Nickerson, Deborah A, Turner, Steve T, Ramachandran, Vasan S, Rotter, Jerome I, Levy, Daniel, Kramer, Holly J, Köttgen, Anna, Consortium, NHLBI Trans-Omics for Precision Medicine, Group, TOPMed Kidney Working, Rich, Stephen S, Lin, Dan-Yu, Browning, Sharon R, and Franceschini, Nora

Subjects
Epidemiology, Health Sciences, Biotechnology, Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Alleles, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Glomerular Filtration Rate, Humans, Male, National Heart, Lung, and Blood Institute (U.S.), Polymorphism, Single Nucleotide, Precision Medicine, Public Health Surveillance, Quantitative Trait, Heritable, United States, Whole Genome Sequencing, Whole genome sequencing, Kidney traits, Rare variants, Ancestry-specific variants, Clinical Sciences, Public Health and Health Services, Clinical sciences
Abstract

BackgroundGenetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.MethodsWe combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.FindingsWhen testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10-11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10-9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10-9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10-9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10-9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.InterpretationThis study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

Published
2021

46. Multi-ancestry genome-wide association study accounting for gene-psychosocial factor interactions identifies novel loci for blood pressure traits

Author

Sun, Daokun, Richard, Melissa A, Musani, Solomon K, Sung, Yun Ju, Winkler, Thomas W, Schwander, Karen, Chai, Jin Fang, Guo, Xiuqing, Kilpeläinen, Tuomas O, Vojinovic, Dina, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Brown, Michael R, Chitrala, Kumaraswamy, Hartwig, Fernando P, Horimoto, Andrea RVR, Liu, Yongmei, Manning, Alisa K, Noordam, Raymond, Smith, Albert V, Harris, Sarah E, Kühnel, Brigitte, Lyytikäinen, Leo-Pekka, Nolte, Ilja M, Rauramaa, Rainer, van der Most, Peter J, Wang, Rujia, Ware, Erin B, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Arking, Dan E, Arnett, Donna K, Barac, Ana, Boerwinkle, Eric, Broeckel, Ulrich, Chakravarti, Aravinda, Chen, Yii-Der Ida, Cupples, L Adrienne, Davigulus, Martha L, de las Fuentes, Lisa, de Mutsert, Renée, de Vries, Paul S, Delaney, Joseph AC, Roux, Ana V Diez, Dörr, Marcus, Faul, Jessica D, Fretts, Amanda M, Gallo, Linda C, Grabe, Hans Jörgen, Gu, C Charles, Harris, Tamara B, Hartman, Catharina CA, Heikkinen, Sami, Ikram, M Arfan, Isasi, Carmen, Johnson, W Craig, Jonas, Jost Bruno, Kaplan, Robert C, Komulainen, Pirjo, Krieger, Jose E, Levy, Daniel, Study, Lifelines Cohort, Liu, Jianjun, Lohman, Kurt, Luik, Annemarie I, Martin, Lisa W, Meitinger, Thomas, Milaneschi, Yuri, O’Connell, Jeff R, Palmas, Walter R, Peters, Annette, Peyser, Patricia A, Pulkki-Råback, Laura, Raffel, Leslie J, Reiner, Alex P, Rice, Kenneth, Robinson, Jennifer G, Rosendaal, Frits R, Schmidt, Carsten Oliver, Schreiner, Pamela J, Schwettmann, Lars, Shikany, James M, Shu, Xiao-ou, Sidney, Stephen, Sims, Mario, Smith, Jennifer A, Sotoodehnia, Nona, Strauch, Konstantin, Tai, E Shyong, Taylor, Kent D, Uitterlinden, André G, van Duijn, Cornelia M, Waldenberger, Melanie, Wee, Hwee-Lin, Wei, Wen-Bin, Wilson, Gregory, Xuan, Deng, and Yao, Jie

Subjects
Hypertension, Mental Health, Genetics, Cardiovascular, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Lifelines Cohort Study
Abstract

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value

Published
2021

47. Association of low-frequency and rare coding variants with information processing speed

Author

Bressler, Jan, Davies, Gail, Smith, Albert V, Saba, Yasaman, Bis, Joshua C, Jian, Xueqiu, Hayward, Caroline, Yanek, Lisa, Smith, Jennifer A, Mirza, Saira S, Wang, Ruiqi, Adams, Hieab HH, Becker, Diane, Boerwinkle, Eric, Campbell, Archie, Cox, Simon R, Eiriksdottir, Gudny, Fawns-Ritchie, Chloe, Gottesman, Rebecca F, Grove, Megan L, Guo, Xiuqing, Hofer, Edith, Kardia, Sharon LR, Knol, Maria J, Koini, Marisa, Lopez, Oscar L, Marioni, Riccardo E, Nyquist, Paul, Pattie, Alison, Polasek, Ozren, Porteous, David J, Rudan, Igor, Satizabal, Claudia L, Schmidt, Helena, Schmidt, Reinhold, Sidney, Stephen, Simino, Jeannette, Smith, Blair H, Turner, Stephen T, van der Lee, Sven J, Ware, Erin B, Whitmer, Rachel A, Yaffe, Kristine, Yang, Qiong, Zhao, Wei, Gudnason, Vilmundur, Launer, Lenore J, Fitzpatrick, Annette L, Psaty, Bruce M, Fornage, Myriam, Arfan Ikram, M, van Duijn, Cornelia M, Seshadri, Sudha, Mosley, Thomas H, and Deary, Ian J

Subjects
Genetics, Brain Disorders, Aging, Human Genome, Adult, Cognition, Genome-Wide Association Study, Geroscience, Humans, Polymorphism, Single Nucleotide, Ubiquitin-Protein Ligases, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10-6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.

Published
2021

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

Author

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

Published
2023
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50. Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease.

Author

Nielsen, Jonas B, Rom, Oren, Surakka, Ida, Graham, Sarah E, Zhou, Wei, Roychowdhury, Tanmoy, Fritsche, Lars G, Gagliano Taliun, Sarah A, Sidore, Carlo, Liu, Yuhao, Gabrielsen, Maiken E, Skogholt, Anne Heidi, Wolford, Brooke, Overton, William, Zhao, Ying, Chen, Jin, Zhang, He, Hornsby, Whitney E, Acheampong, Akua, Grooms, Austen, Schaefer, Amanda, Zajac, Gregory JM, Villacorta, Luis, Zhang, Jifeng, Brumpton, Ben, Løset, Mari, Rai, Vivek, Lundegaard, Pia R, Olesen, Morten S, Taylor, Kent D, Palmer, Nicholette D, Chen, Yii-Der, Choi, Seung H, Lubitz, Steven A, Ellinor, Patrick T, Barnes, Kathleen C, Daya, Michelle, Rafaels, Nicholas, Weiss, Scott T, Lasky-Su, Jessica, Tracy, Russell P, Vasan, Ramachandran S, Cupples, L Adrienne, Mathias, Rasika A, Yanek, Lisa R, Becker, Lewis C, Peyser, Patricia A, Bielak, Lawrence F, Smith, Jennifer A, Aslibekyan, Stella, Hidalgo, Bertha A, Arnett, Donna K, Irvin, Marguerite R, Wilson, James G, Musani, Solomon K, Correa, Adolfo, Rich, Stephen S, Guo, Xiuqing, Rotter, Jerome I, Konkle, Barbara A, Johnsen, Jill M, Ashley-Koch, Allison E, Telen, Marilyn J, Sheehan, Vivien A, Blangero, John, Curran, Joanne E, Peralta, Juan M, Montgomery, Courtney, Sheu, Wayne H-H, Chung, Ren-Hua, Schwander, Karen, Nouraie, Seyed M, Gordeuk, Victor R, Zhang, Yingze, Kooperberg, Charles, Reiner, Alexander P, Jackson, Rebecca D, Bleecker, Eugene R, Meyers, Deborah A, Li, Xingnan, Das, Sayantan, Yu, Ketian, LeFaive, Jonathon, Smith, Albert, Blackwell, Tom, Taliun, Daniel, Zollner, Sebastian, Forer, Lukas, Schoenherr, Sebastian, Fuchsberger, Christian, Pandit, Anita, Zawistowski, Matthew, Kheterpal, Sachin, Brummett, Chad M, Natarajan, Pradeep, Schlessinger, David, Lee, Seunggeun, Kang, Hyun Min, Cucca, Francesco, and Holmen, Oddgeir L

Subjects
Liver, Humans, Cardiovascular Diseases, Lipids, Receptors, LDL, Gene Targeting, Gene Silencing, Genome, Human, Biological Specimen Banks, Genome-Wide Association Study, Molecular Targeted Therapy, United Kingdom, Loss of Function Mutation, Phenomics
Abstract

Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of the protein. This includes ZNF529:p.K405X, which is associated with decreased low-density-lipoprotein (LDL) cholesterol (P = 1.3 × 10-8) without being associated with liver enzymes or non-fasting blood glucose. Silencing of ZNF529 in human hepatoma cells results in upregulation of LDL receptor and increased LDL uptake in the cells. This suggests that inhibition of ZNF529 or its gene product should be prioritized as a novel candidate drug target for treating dyslipidemia and associated CVD.

Published
2020

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