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287 results on '"Kardia, Sharon LR"'

1. 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, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Genome-Wide Association Study, Telomere, K562 Cells, Telomere Homeostasis, Polymorphism, Single Nucleotide, Gene Expression Regulation, CRISPR-Cas Systems, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
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

2. 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

3. 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

4. Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function

Author

Zhang, Yuankai, Liu, Xue, Wiggins, Kerri L, Kurniansyah, Nuzulul, Guo, Xiuqing, Rodrigue, Amanda L, Zhao, Wei, Yanek, Lisa R, Ratliff, Scott M, Pitsillides, Achilleas, Aguirre Patiño, Juan Sebastian, Sofer, Tamar, Arking, Dan E, Austin, Thomas R, Beiser, Alexa S, Blangero, John, Boerwinkle, Eric, Bressler, Jan, Curran, Joanne E, Hou, Lifang, Hughes, Timothy M, Kardia, Sharon LR, Launer, Lenore J, Levy, Daniel, Mosley, Thomas H, Nasrallah, Ilya M, Rich, Stephen S, Rotter, Jerome I, Seshadri, Sudha, Tarraf, Wassim, González, Kevin A, Ramachandran, Vasan, Yaffe, Kristine, Nyquist, Paul A, Psaty, Bruce M, DeCarli, Charles S, Smith, Jennifer A, Glahn, David C, González, Hector M, Bis, Joshua C, Fornage, Myriam, Heckbert, Susan R, Fitzpatrick, Annette L, Liu, Chunyu, Satizabal, Claudia L, Aguilera, Norma, Ament, Seth, Ammous, Farah, Arnett, Donna K, Becker, Diane, Bis, Joshua, Blue, Elizabeth, Breaux, Camille, Chaar, Dima, MHI, Clarkson-Townsend, Danielle, Cooper, Brigidann, Coresh, Josef, Correa, Adolfo, DeStefano, Anita, Ding, Jingzhong, Fardo, David, Fitzpatrick, Annette, French, Jennifer, Glahn, David, Gonzalez, Hector, Granot-Hershkovitz, Einat, Hanly, Patrick, Hayden, Kathleen, Heckbert, Susan, Heemann, Scott, Horvath, Steve, Hoth, Karin, Hughes, Timothy, Jaiswal, Sidd, Jian, Xueqiu, Katsumata, Yuriko, Kho, Minjung, Kooperberg, Charles, Launer, Lenore, Lin, Honghuang, Litkowski, Elizabeth, Longstreth, Will, Martin, Alexandra, Mayeux, Richard, Mikulla, Julie, Miller, Amy, Misra, Biswapriya, Mosley, Thomas, Nyquist, Paul, O'Connell, Jeff, Olivier, Michael, Peloso, Gina, Perry, James, Psaty, Bruce, Purcell, Shaun, and Raffield, Laura

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Behavioral and Social Science, Acquired Cognitive Impairment, Clinical Research, Alzheimer's Disease, Dementia, Precision Medicine, Biomedical Imaging, Aging, Genetics, Brain Disorders, 4.1 Discovery and preclinical testing of markers and technologies, 2.1 Biological and endogenous factors, Mental health, Neurological, Good Health and Well Being, Middle Aged, Humans, Female, Aged, Male, DNA, Mitochondrial, DNA Copy Number Variations, Prospective Studies, Cross-Sectional Studies, Alzheimer Disease, Magnetic Resonance Imaging, Cognition, Brain, NHLBI Trans-Omics for Precision Medicine (TOPMed) program, Mitochondrial and Neurocognitive Working Groups, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

Background and objectivesPrevious studies suggest that lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer disease (AD) and AD-related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.MethodsWe included dementia-free participants from 9 diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5-20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (

Published
2023

5. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI

Author

Yang, Yunju, Knol, Maria J, Wang, Ruiqi, Mishra, Aniket, Liu, Dan, Luciano, Michelle, Teumer, Alexander, Armstrong, Nicola, Bis, Joshua C, Jhun, Min A, Li, Shuo, Adams, Hieab HH, Aziz, Nasir Ahmad, Bastin, Mark E, Bourgey, Mathieu, Brody, Jennifer A, Frenzel, Stefan, Gottesman, Rebecca F, Hosten, Norbert, Hou, Lifang, Kardia, Sharon LR, Lohner, Valerie, Marquis, Pascale, Maniega, Susana Muñoz, Satizabal, Claudia L, Sorond, Farzaneh A, Valdés Hernández, Maria C, van Duijn, Cornelia M, Vernooij, Meike W, Wittfeld, Katharina, Yang, Qiong, Zhao, Wei, Boerwinkle, Eric, Levy, Daniel, Deary, Ian J, Jiang, Jiyang, Mather, Karen A, Mosley, Thomas H, Psaty, Bruce M, Sachdev, Perminder S, Smith, Jennifer A, Sotoodehnia, Nona, DeCarli, Charles S, Breteler, Monique MB, Ikram, M Arfan, Grabe, Hans J, Wardlaw, Joanna, Longstreth, WT, Launer, Lenore J, Seshadri, Sudha, Debette, Stephanie, and Fornage, Myriam

Subjects
Health Sciences, Genetics, Aging, Brain Disorders, Neurosciences, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Middle Aged, Humans, Aged, White Matter, Genome-Wide Association Study, Brain, DNA Methylation, Magnetic Resonance Imaging, Epigenesis, Genetic, Protein-Arginine N-Methyltransferases, Repressor Proteins, epigenome-wide association study, white matter hyperintensities, cerebral small vessel disease, integrative cross-omics analysis, blood-brain barrier dysfunction, blood–brain barrier dysfunction, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

Published
2023

6. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing

Author

Chen, Fang, Wang, Xingyan, Jang, Seon-Kyeong, Quach, Bryan C, Weissenkampen, J Dylan, Khunsriraksakul, Chachrit, Yang, Lina, Sauteraud, Renan, Albert, Christine M, Allred, Nicholette DD, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Barr, R Graham, Becker, Diane M, Bielak, Lawrence F, Bis, Joshua C, Blangero, John, Boorgula, Meher Preethi, Chasman, Daniel I, Chavan, Sameer, Chen, Yii-Der I, Chuang, Lee-Ming, Correa, Adolfo, Curran, Joanne E, David, Sean P, Fuentes, Lisa de las, Deka, Ranjan, Duggirala, Ravindranath, Faul, Jessica D, Garrett, Melanie E, Gharib, Sina A, Guo, Xiuqing, Hall, Michael E, Hawley, Nicola L, He, Jiang, Hobbs, Brian D, Hokanson, John E, Hsiung, Chao A, Hwang, Shih-Jen, Hyde, Thomas M, Irvin, Marguerite R, Jaffe, Andrew E, Johnson, Eric O, Kaplan, Robert, Kardia, Sharon LR, Kaufman, Joel D, Kelly, Tanika N, Kleinman, Joel E, Kooperberg, Charles, Lee, I-Te, Levy, Daniel, Lutz, Sharon M, Manichaikul, Ani W, Martin, Lisa W, Marx, Olivia, McGarvey, Stephen T, Minster, Ryan L, Moll, Matthew, Moussa, Karine A, Naseri, Take, North, Kari E, Oelsner, Elizabeth C, Peralta, Juan M, Peyser, Patricia A, Psaty, Bruce M, Rafaels, Nicholas, Raffield, Laura M, Reupena, Muagututi’a Sefuiva, Rich, Stephen S, Rotter, Jerome I, Schwartz, David A, Shadyab, Aladdin H, Sheu, Wayne H-H, Sims, Mario, Smith, Jennifer A, Sun, Xiao, Taylor, Kent D, Telen, Marilyn J, Watson, Harold, Weeks, Daniel E, Weir, David R, Yanek, Lisa R, Young, Kendra A, Young, Kristin L, Zhao, Wei, Hancock, Dana B, Jiang, Bibo, Vrieze, Scott, and Liu, Dajiang J

Subjects
Genetics, Tobacco, Drug Abuse (NIDA only), Tobacco Smoke and Health, Substance Misuse, Brain Disorders, Human Genome, Good Health and Well Being, Humans, Transcriptome, Drug Repositioning, Genome-Wide Association Study, Tobacco Use, Biology, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

Published
2023

7. 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

8. Genetic diversity fuels gene discovery for tobacco and alcohol use

Author

Saunders, Gretchen RB, Wang, Xingyan, Chen, Fang, Jang, Seon-Kyeong, Liu, Mengzhen, Wang, Chen, Gao, Shuang, Jiang, Yu, Khunsriraksakul, Chachrit, Otto, Jacqueline M, Addison, Clifton, Akiyama, Masato, Albert, Christine M, Aliev, Fazil, Alonso, Alvaro, Arnett, Donna K, Ashley-Koch, Allison E, Ashrani, Aneel A, Barnes, Kathleen C, Barr, R Graham, Bartz, Traci M, Becker, Diane M, Bielak, Lawrence F, Benjamin, Emelia J, Bis, Joshua C, Bjornsdottir, Gyda, Blangero, John, Bleecker, Eugene R, Boardman, Jason D, Boerwinkle, Eric, Boomsma, Dorret I, Boorgula, Meher Preethi, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Chasman, Daniel I, Chavan, Sameer, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Iona, Cho, Michael H, Choquet, Hélène, Cole, John W, Cornelis, Marilyn C, Cucca, Francesco, Curran, Joanne E, de Andrade, Mariza, Dick, Danielle M, Docherty, Anna R, Duggirala, Ravindranath, Eaton, Charles B, Ehringer, Marissa A, Esko, Tõnu, Faul, Jessica D, Fernandes Silva, Lilian, Fiorillo, Edoardo, Fornage, Myriam, Freedman, Barry I, Gabrielsen, Maiken E, Garrett, Melanie E, Gharib, Sina A, Gieger, Christian, Gillespie, Nathan, Glahn, David C, Gordon, Scott D, Gu, Charles C, Gu, Dongfeng, Gudbjartsson, Daniel F, Guo, Xiuqing, Haessler, Jeffrey, Hall, Michael E, Haller, Toomas, Harris, Kathleen Mullan, He, Jiang, Herd, Pamela, Hewitt, John K, Hickie, Ian, Hidalgo, Bertha, Hokanson, John E, Hopfer, Christian, Hottenga, JoukeJan, Hou, Lifang, Huang, Hongyan, Hung, Yi-Jen, Hunter, David J, Hveem, Kristian, Hwang, Shih-Jen, Hwu, Chii-Min, Iacono, William, Irvin, Marguerite R, Jee, Yon Ho, Johnson, Eric O, Joo, Yoonjung Y, Jorgenson, Eric, Justice, Anne E, Kamatani, Yoichiro, Kaplan, Robert C, Kaprio, Jaakko, Kardia, Sharon LR, and Keller, Matthew C

Subjects
Genetics, Alcoholism, Alcohol Use and Health, Prevention, Human Genome, Substance Misuse, Aetiology, 2.1 Biological and endogenous factors, Cancer, Good Health and Well Being, Humans, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Multifactorial Inheritance, Risk Factors, Tobacco Use, Alcohol Drinking, Transcriptome, Sample Size, Genetic Loci, Internationality, Europe, 23andMe Research Team, Biobank Japan Project, General Science & Technology
Abstract

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Published
2022

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

Author

He, Karen Y, Kelly, Tanika N, Wang, Heming, Liang, Jingjing, Zhu, Luke, Cade, Brian E, Assimes, Themistocles L, Becker, Lewis C, Beitelshees, Amber L, Bielak, Lawrence F, Bress, Adam P, Brody, Jennifer A, Chang, Yen-Pei Christy, Chang, Yi-Cheng, de Vries, Paul S, Duggirala, Ravindranath, Fox, Ervin R, Franceschini, Nora, Furniss, Anna L, Gao, Yan, Guo, Xiuqing, Haessler, Jeffrey, Hung, Yi-Jen, Hwang, Shih-Jen, Irvin, Marguerite Ryan, Kalyani, Rita R, Liu, Ching-Ti, Liu, Chunyu, Martin, Lisa Warsinger, Montasser, May E, Muntner, Paul M, Mwasongwe, Stanford, Naseri, Take, Palmas, Walter, Reupena, Muagututi’a Sefuiva, Rice, Kenneth M, Sheu, Wayne H-H, Shimbo, Daichi, Smith, Jennifer A, Snively, Beverly M, Yanek, Lisa R, Zhao, Wei, Blangero, John, Boerwinkle, Eric, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Fornage, Myriam, He, Jiang, Hou, Lifang, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear E, Kooperberg, Charles, Lloyd-Jones, Donald, Loos, Ruth JF, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, North, Kari E, Peyser, Patricia A, Psaty, Bruce M, Raffield, Laura M, Rao, DC, Redline, Susan, Reiner, Alex P, Rich, Stephen S, Rotter, Jerome I, Taylor, Kent D, Tracy, Russell, Vasan, Ramachandran S, Morrison, Alanna C, Levy, Daniel, Chakravarti, Aravinda, Arnett, Donna K, and Zhu, Xiaofeng

Subjects
Biological Sciences, Genetics, Cardiovascular, Human Genome, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Pressure, Genetic Linkage, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Precision Medicine, Whole Genome Sequencing, Rare variant analysis, Blood pressure, Whole genome sequencing, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundWhile large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries.ResultsAssociations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10- 7).ConclusionsLow frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.

Published
2022

10. 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

11. 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

12. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author

Kelly, Tanika N, Sun, Xiao, He, Karen Y, Brown, Michael R, Taliun, Sarah A Gagliano, Hellwege, Jacklyn N, Irvin, Marguerite R, Mi, Xuenan, Brody, Jennifer A, Franceschini, Nora, Guo, Xiuqing, Hwang, Shih-Jen, de Vries, Paul S, Gao, Yan, Moscati, Arden, Nadkarni, Girish N, Yanek, Lisa R, Elfassy, Tali, Smith, Jennifer A, Chung, Ren-Hua, Beitelshees, Amber L, Patki, Amit, Aslibekyan, Stella, Blobner, Brandon M, Peralta, Juan M, Assimes, Themistocles L, Palmas, Walter R, Liu, Chunyu, Bress, Adam P, Huang, Zhijie, Becker, Lewis C, Hwa, Chii-Min, O’Connell, Jeffrey R, Carlson, Jenna C, Warren, Helen R, Das, Sayantan, Giri, Ayush, Martin, Lisa W, Johnson, W Craig, Fox, Ervin R, Bottinger, Erwin P, Razavi, Alexander C, Vaidya, Dhananjay, Chuang, Lee-Ming, Chang, Yen-Pei C, Naseri, Take, Jain, Deepti, Kang, Hyun Min, Hung, Adriana M, Srinivasasainagendra, Vinodh, Snively, Beverly M, Gu, Dongfeng, Montasser, May E, Reupena, Muagututi A Sefuiva, Heavner, Benjamin D, LeFaive, Jonathon, Hixson, James E, Rice, Kenneth M, Wang, Fei Fei, Nielsen, Jonas B, Huang, Jianfeng, Khan, Alyna T, Zhou, Wei, Nierenberg, Jovia L, Laurie, Cathy C, Armstrong, Nicole D, Shi, Mengyao, Pan, Yang, Stilp, Adrienne M, Emery, Leslie, Wong, Quenna, Hawley, Nicola L, Minster, Ryan L, Curran, Joanne E, Munroe, Patricia B, Weeks, Daniel E, North, Kari E, Tracy, Russell P, Kenny, Eimear E, Shimbo, Daichi, Chakravarti, Aravinda, Rich, Stephen S, Reiner, Alex P, Blangero, John, Redline, Susan, Mitchell, Braxton D, Rao, Dabeeru C, Chen, Yii-Der Ida, Kardia, Sharon LR, Kaplan, Robert C, Mathias, Rasika A, He, Jiang, Psaty, Bruce M, Fornage, Myriam, Loos, Ruth JF, Correa, Adolfo, Boerwinkle, Eric, Rotter, Jerome I, Kooperberg, Charles, and Edwards, Todd L

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Good Health and Well Being, Blood Pressure, Genome-Wide Association Study, Genomics, Humans, Hypertension, Polymorphism, Single Nucleotide, Precision Medicine, allele, blood pressure, genome, hypertension, whole genome sequencing, Samoan Obesity, Lifestyle, and Genetic Adaptations Study (OLaGA) Group, ‡ NHLBI Trans-Omics for Precision Medicine TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

BackgroundThe availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.MethodsWe conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.ResultsTwo blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P

Published
2022

13. Gene-mapping study of extremes of cerebral small vessel disease reveals TRIM47 as a strong candidate

Author

Mishra, Aniket, Duplaà, Cécile, Vojinovic, Dina, Suzuki, Hideaki, Sargurupremraj, Muralidharan, Zilhão, Nuno R, Li, Shuo, Bartz, Traci M, Jian, Xueqiu, Zhao, Wei, Hofer, Edith, Wittfeld, Katharina, Harris, Sarah E, van der Auwera-Palitschka, Sandra, Luciano, Michelle, Bis, Joshua C, Adams, Hieab HH, Satizabal, Claudia L, Gottesman, Rebecca F, Gampawar, Piyush G, Bülow, Robin, Weiss, Stefan, Yu, Miao, Bastin, Mark E, Lopez, Oscar L, Vernooij, Meike W, Beiser, Alexa S, Völker, Uwe, Kacprowski, Tim, Soumare, Aicha, Smith, Jennifer A, Knopman, David S, Morris, Zoe, Zhu, Yicheng, Rotter, Jerome I, Dufouil, Carole, Hernández, Maria Valdés, Maniega, Susana Muñoz, Lathrop, Mark, Boerwinkle, Erik, Schmidt, Reinhold, Ihara, Masafumi, Mazoyer, Bernard, Yang, Qiong, Joutel, Anne, Tournier-Lasserve, Elizabeth, Launer, Lenore J, Deary, Ian J, Mosley, Thomas H, Amouyel, Philippe, DeCarli, Charles S, Psaty, Bruce M, Tzourio, Christophe, Kardia, Sharon LR, Grabe, Hans J, Teumer, Alexander, van Duijn, Cornelia M, Schmidt, Helena, Wardlaw, Joanna M, Ikram, M Arfan, Fornage, Myriam, Gudnason, Vilmundur, Seshadri, Sudha, Matthews, Paul M, Longstreth, William T, Couffinhal, Thierry, and Debette, Stephanie

Subjects
Epidemiology, Health Sciences, Acquired Cognitive Impairment, Genetics, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Stroke, Neurosciences, Human Genome, Biotechnology, Clinical Research, Dementia, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Cardiovascular, Animals, Brain Ischemia, Cerebral Small Vessel Diseases, Endothelial Cells, Genome-Wide Association Study, Mice, cerebral small vessel disease, endothelial cells, GWAS, TRIM47, whole-exome association study, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

Cerebral small vessel disease is a leading cause of stroke and a major contributor to cognitive decline and dementia, but our understanding of specific genes underlying the cause of sporadic cerebral small vessel disease is limited. We report a genome-wide association study and a whole-exome association study on a composite extreme phenotype of cerebral small vessel disease derived from its most common MRI features: white matter hyperintensities and lacunes. Seventeen population-based cohorts of older persons with MRI measurements and genome-wide genotyping (n = 41 326), whole-exome sequencing (n = 15 965), or exome chip (n = 5249) data contributed 13 776 and 7079 extreme small vessel disease samples for the genome-wide association study and whole-exome association study, respectively. The genome-wide association study identified significant association of common variants in 11 loci with extreme small vessel disease, of which the chr12q24.11 locus was not previously reported to be associated with any MRI marker of cerebral small vessel disease. The whole-exome association study identified significant associations of extreme small vessel disease with common variants in the 5' UTR region of EFEMP1 (chr2p16.1) and one probably damaging common missense variant in TRIM47 (chr17q25.1). Mendelian randomization supports the causal association of extensive small vessel disease severity with increased risk of stroke and Alzheimer's disease. Combined evidence from summary-based Mendelian randomization studies and profiling of human loss-of-function allele carriers showed an inverse relation between TRIM47 expression in the brain and blood vessels and extensive small vessel disease severity. We observed significant enrichment of Trim47 in isolated brain vessel preparations compared to total brain fraction in mice, in line with the literature showing Trim47 enrichment in brain endothelial cells at single cell level. Functional evaluation of TRIM47 by small interfering RNAs-mediated knockdown in human brain endothelial cells showed increased endothelial permeability, an important hallmark of cerebral small vessel disease pathology. Overall, our comprehensive gene-mapping study and preliminary functional evaluation suggests a putative role of TRIM47 in the pathophysiology of cerebral small vessel disease, making it an important candidate for extensive in vivo explorations and future translational work.

Published
2022

14. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J, Nivard, Michel G, Morris, Tim T, Hansen, Ailin F, Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A, Palviainen, Teemu, van der Zee, Matthijs D, Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M, Bielak, Lawrence F, Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A, Reynolds, Chandra A, Balbona, Jared V, Andreassen, Ole A, Ask, Helga, Baras, Aris, Bauer, Christopher R, Boomsma, Dorret I, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C, Dokuru, Deepika R, Evans, Luke M, de Geus, Eco JC, Giddaluru, Sudheer, Gordon, Scott D, Harden, K Paige, Hill, W David, Hughes, Amanda, Kerr, Shona M, Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A, Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik KE, Mallard, Travis T, Martikainen, Pekka, Mills, Melinda C, Njølstad, Pål Rasmus, Overton, John D, Pedersen, Nancy L, Porteous, David J, Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C, Stoltenberg, Camilla, Tucker-Drob, Elliot M, Wright, Margaret J, Hewitt, John K, Keller, Matthew C, Stallings, Michael C, Lee, James J, Christensen, Kaare, Kardia, Sharon LR, Peyser, Patricia A, Smith, Jennifer A, Wilson, James F, Hopper, John L, Hägg, Sara, Spector, Tim D, Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G, Oskarsson, Sven, Justice, Anne E, Millwood, Iona Y, Hveem, Kristian, Naess, Øyvind, Willer, Cristen J, Åsvold, Bjørn Olav, Koellinger, Philipp D, Kaprio, Jaakko, Medland, Sarah E, Walters, Robin G, Benjamin, Daniel J, Turley, Patrick, Evans, David M, Davey Smith, George, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M

Subjects
Human Genome, Genetics, Pediatric, 2.1 Biological and endogenous factors, Aetiology, Mental health, Generic health relevance, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Social Science Genetic Association Consortium, Within Family Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Published
2022

15. 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

16. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

Author

DiCorpo, Daniel, LeClair, Jessica, Cole, Joanne B, Sarnowski, Chloé, Ahmadizar, Fariba, Bielak, Lawrence F, Blokstra, Anneke, Bottinger, Erwin P, Chaker, Layal, Chen, Yii-Der I, Chen, Ye, de Vries, Paul S, Faquih, Tariq, Ghanbari, Mohsen, Gudmundsdottir, Valborg, Guo, Xiuqing, Hasbani, Natalie R, Ibi, Dorina, Ikram, M Arfan, Kavousi, Maryam, Leonard, Hampton L, Leong, Aaron, Mercader, Josep M, Morrison, Alanna C, Nadkarni, Girish N, Nalls, Mike A, Noordam, Raymond, Preuss, Michael, Smith, Jennifer A, Trompet, Stella, Vissink, Petra, Yao, Jie, Zhao, Wei, Boerwinkle, Eric, Goodarzi, Mark O, Gudnason, Vilmundur, Jukema, J Wouter, Kardia, Sharon LR, Loos, Ruth JF, Liu, Ching-Ti, Manning, Alisa K, Mook-Kanamori, Dennis, Pankow, James S, Picavet, H Susan J, Sattar, Naveed, Simonsick, Eleanor M, Verschuren, WM Monique, van Dijk, Ko Willems, Florez, Jose C, Rotter, Jerome I, Meigs, James B, Dupuis, Josée, and Udler, Miriam S

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Genetics, Obesity, Heart Disease - Coronary Heart Disease, Liver Disease, Heart Disease, Cardiovascular, Digestive Diseases, Diabetes, Nutrition, Prevention, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, Alleles, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Genetic Loci, Humans, Pharmaceutical Preparations, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveType 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed.Research design and methodsHere we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD).ResultsDespite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway.ConclusionsOur findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.

Published
2022

17. Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Author

Selvaraj, Margaret Sunitha, Li, Xihao, Li, Zilin, Pampana, Akhil, Zhang, David Y, Park, Joseph, Aslibekyan, Stella, Bis, Joshua C, Brody, Jennifer A, Cade, Brian E, Chuang, Lee-Ming, Chung, Ren-Hua, Curran, Joanne E, de las Fuentes, Lisa, de Vries, Paul S, Duggirala, Ravindranath, Freedman, Barry I, Graff, Mariaelisa, Guo, Xiuqing, Heard-Costa, Nancy, Hidalgo, Bertha, Hwu, Chii-Min, Irvin, Marguerite R, Kelly, Tanika N, Kral, Brian G, Lange, Leslie, Li, Xiaohui, Lisa, Martin, Lubitz, Steven A, Manichaikul, Ani W, Michael, Preuss, Montasser, May E, Morrison, Alanna C, Naseri, Take, O’Connell, Jeffrey R, Palmer, Nicholette D, Peyser, Patricia A, Reupena, Muagututia S, Smith, Jennifer A, Sun, Xiao, Taylor, Kent D, Tracy, Russell P, Tsai, Michael Y, Wang, Zhe, Wang, Yuxuan, Bao, Wei, Wilkins, John T, Yanek, Lisa R, Zhao, Wei, Arnett, Donna K, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Dutcher, Susan K, Ellinor, Patrick T, Fornage, Myriam, Gabriel, Stacey, Germer, Soren, Gibbs, Richard, He, Jiang, Kaplan, Robert C, Kardia, Sharon LR, Kim, Ryan, Kooperberg, Charles, Loos, Ruth JF, Viaud-Martinez, Karine A, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Nickerson, Deborah, North, Kari E, Psaty, Bruce M, Redline, Susan, Reiner, Alexander P, Vasan, Ramachandran S, Rich, Stephen S, Willer, Cristen, Rotter, Jerome I, Rader, Daniel J, Lin, Xihong, Peloso, Gina M, and Natarajan, Pradeep

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Biotechnology, Heart Disease - Coronary Heart Disease, Cardiovascular, Heart Disease, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Alleles, Cholesterol, LDL, Genome-Wide Association Study, Humans, Lipids, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

Published
2022

18. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

Author

DiCorpo, Daniel, Gaynor, Sheila M, Russell, Emily M, Westerman, Kenneth E, Raffield, Laura M, Majarian, Timothy D, Wu, Peitao, Sarnowski, Chloé, Highland, Heather M, Jackson, Anne, Hasbani, Natalie R, de Vries, Paul S, Brody, Jennifer A, Hidalgo, Bertha, Guo, Xiuqing, Perry, James A, O’Connell, Jeffrey R, Lent, Samantha, Montasser, May E, Cade, Brian E, Jain, Deepti, Wang, Heming, D’Oliveira Albanus, Ricardo, Varshney, Arushi, Yanek, Lisa R, Lange, Leslie, Palmer, Nicholette D, Almeida, Marcio, Peralta, Juan M, Aslibekyan, Stella, Baldridge, Abigail S, Bertoni, Alain G, Bielak, Lawrence F, Chen, Chung-Shiuan, Chen, Yii-Der Ida, Choi, Won Jung, Goodarzi, Mark O, Floyd, James S, Irvin, Marguerite R, Kalyani, Rita R, Kelly, Tanika N, Lee, Seonwook, Liu, Ching-Ti, Loesch, Douglas, Manson, JoAnn E, Minster, Ryan L, Naseri, Take, Pankow, James S, Rasmussen-Torvik, Laura J, Reiner, Alexander P, Reupena, Muagututi’a Sefuiva, Selvin, Elizabeth, Smith, Jennifer A, Weeks, Daniel E, Xu, Huichun, Yao, Jie, Zhao, Wei, Parker, Stephen, Alonso, Alvaro, Arnett, Donna K, Blangero, John, Boerwinkle, Eric, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Duggirala, Ravindranath, He, Jiang, Heckbert, Susan R, Kardia, Sharon LR, Kim, Ryan W, Kooperberg, Charles, Liu, Simin, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Morrison, Alanna C, Peyser, Patricia A, Psaty, Bruce M, Redline, Susan, Shuldiner, Alan R, Taylor, Kent D, Vasan, Ramachandran S, Viaud-Martinez, Karine A, Florez, Jose C, Wilson, James G, Sladek, Robert, Rich, Stephen S, Rotter, Jerome I, Lin, Xihong, Dupuis, Josée, Meigs, James B, Wessel, Jennifer, and Manning, Alisa K

Subjects
Biological Sciences, Genetics, Human Genome, Biotechnology, Diabetes, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Good Health and Well Being, Diabetes Mellitus, Type 2, Fasting, Glucose, Humans, Insulin, National Heart, Lung, and Blood Institute (U.S.), Nerve Tissue Proteins, Polymorphism, Single Nucleotide, Precision Medicine, Receptors, Immunologic, United States, Biological sciences, Biomedical and clinical sciences
Abstract

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

Published
2022

19. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author

McCartney, Daniel L, Min, Josine L, Richmond, Rebecca C, Lu, Ake T, Sobczyk, Maria K, Davies, Gail, Broer, Linda, Guo, Xiuqing, Jeong, Ayoung, Jung, Jeesun, Kasela, Silva, Katrinli, Seyma, Kuo, Pei-Lun, Matias-Garcia, Pamela R, Mishra, Pashupati P, Nygaard, Marianne, Palviainen, Teemu, Patki, Amit, Raffield, Laura M, Ratliff, Scott M, Richardson, Tom G, Robinson, Oliver, Soerensen, Mette, Sun, Dianjianyi, Tsai, Pei-Chien, van der Zee, Matthijs D, Walker, Rosie M, Wang, Xiaochuan, Wang, Yunzhang, Xia, Rui, Xu, Zongli, Yao, Jie, Zhao, Wei, Correa, Adolfo, Boerwinkle, Eric, Dugué, Pierre-Antoine, Durda, Peter, Elliott, Hannah R, Gieger, Christian, de Geus, Eco JC, Harris, Sarah E, Hemani, Gibran, Imboden, Medea, Kähönen, Mika, Kardia, Sharon LR, Kresovich, Jacob K, Li, Shengxu, Lunetta, Kathryn L, Mangino, Massimo, Mason, Dan, McIntosh, Andrew M, Mengel-From, Jonas, Moore, Ann Zenobia, Murabito, Joanne M, Ollikainen, Miina, Pankow, James S, Pedersen, Nancy L, Peters, Annette, Polidoro, Silvia, Porteous, David J, Raitakari, Olli, Rich, Stephen S, Sandler, Dale P, Sillanpää, Elina, Smith, Alicia K, Southey, Melissa C, Strauch, Konstantin, Tiwari, Hemant, Tanaka, Toshiko, Tillin, Therese, Uitterlinden, Andre G, Van Den Berg, David J, van Dongen, Jenny, Wilson, James G, Wright, John, Yet, Idil, Arnett, Donna, Bandinelli, Stefania, Bell, Jordana T, Binder, Alexandra M, Boomsma, Dorret I, Chen, Wei, Christensen, Kaare, Conneely, Karen N, Elliott, Paul, Ferrucci, Luigi, Fornage, Myriam, Hägg, Sara, Hayward, Caroline, Irvin, Marguerite, Kaprio, Jaakko, Lawlor, Deborah A, Lehtimäki, Terho, Lohoff, Falk W, Milani, Lili, Milne, Roger L, Probst-Hensch, Nicole, Reiner, Alex P, Ritz, Beate, and Rotter, Jerome I

Subjects
Prevention, Nutrition, Aging, Human Genome, Genetics, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adiposity, Biomarkers, C-Reactive Protein, CpG Islands, DNA Methylation, Educational Status, Epigenesis, Genetic, Genetic Loci, Genetic Markers, Genome, Human, Genome-Wide Association Study, Granulocytes, Humans, Immunity, Innate, Lipid Metabolism, Multifactorial Inheritance, Plasminogen Activator Inhibitor 1, DNA methylation, GWAS, Epigenetic clock, Genetics of DNA Methylation Consortium, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

BackgroundBiological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.ResultsLeveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Published
2021

20. A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program

Author

Stilp, Adrienne M, Emery, Leslie S, Broome, Jai G, Buth, Erin J, Khan, Alyna T, Laurie, Cecelia A, Wang, Fei Fei, Wong, Quenna, Chen, Dongquan, D'Augustine, Catherine M, Heard-Costa, Nancy L, Hohensee, Chancellor R, Johnson, William Craig, Juarez, Lucia D, Liu, Jingmin, Mutalik, Karen M, Raffield, Laura M, Wiggins, Kerri L, de Vries, Paul S, Kelly, Tanika N, Kooperberg, Charles, Natarajan, Pradeep, Peloso, Gina M, Peyser, Patricia A, Reiner, Alex P, Arnett, Donna K, Aslibekyan, Stella, Barnes, Kathleen C, Bielak, Lawrence F, Bis, Joshua C, Cade, Brian E, Chen, Ming-Huei, Correa, Adolfo, Cupples, L Adrienne, de Andrade, Mariza, Ellinor, Patrick T, Fornage, Myriam, Franceschini, Nora, Gan, Weiniu, Ganesh, Santhi K, Graffelman, Jan, Grove, Megan L, Guo, Xiuqing, Hawley, Nicola L, Hsu, Wan-Ling, Jackson, Rebecca D, Jaquish, Cashell E, Johnson, Andrew D, Kardia, Sharon LR, Kelly, Shannon, Lee, Jiwon, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Montasser, May E, Morrison, Alanna C, North, Kari E, Nouraie, Seyed Mehdi, Oelsner, Elizabeth C, Pankratz, Nathan, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Taylor, Kent D, Vasan, Ramachandran S, Weeks, Daniel E, Weiss, Scott T, Wilson, Carla G, Yanek, Lisa R, Psaty, Bruce M, Heckbert, Susan R, and Laurie, Cathy C

Subjects
Epidemiology, Health Sciences, Human Genome, Lung, Genetics, Clinical Research, Cardiovascular, Good Health and Well Being, Data Aggregation, Genetic Association Studies, Humans, Information Dissemination, National Heart, Lung, and Blood Institute (U.S.), Phenomics, Phenotype, Precision Medicine, Program Evaluation, United States, cardiovascular disease, common data elements, hematologic disease, information dissemination, lung diseases, phenotypes, sleep-wake disorders, Mathematical Sciences, Medical and Health Sciences
Abstract

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.

Published
2021

21. 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

22. Population sequencing data reveal a compendium of mutational processes in the human germ line.

Author

Seplyarskiy, Vladimir B, Soldatov, Ruslan A, Koch, Evan, McGinty, Ryan J, Goldmann, Jakob M, Hernandez, Ryan D, Barnes, Kathleen, Correa, Adolfo, Burchard, Esteban G, Ellinor, Patrick T, McGarvey, Stephen T, Mitchell, Braxton D, Vasan, Ramachandran S, Redline, Susan, Silverman, Edwin, Weiss, Scott T, Arnett, Donna K, Blangero, John, Boerwinkle, Eric, He, Jiang, Montgomery, Courtney, Rao, DC, Rotter, Jerome I, Taylor, Kent D, Brody, Jennifer A, Chen, Yii-Der Ida, de Las Fuentes, Lisa, Hwu, Chii-Min, Rich, Stephen S, Manichaikul, Ani W, Mychaleckyj, Josyf C, Palmer, Nicholette D, Smith, Jennifer A, Kardia, Sharon LR, Peyser, Patricia A, Bielak, Lawrence F, O'Connor, Timothy D, Emery, Leslie S, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Population Genetics Working Group, Gilissen, Christian, Wong, Wendy SW, Kharchenko, Peter V, and Sunyaev, Shamil

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Population Genetics Working Group, Germ Cells, Oocytes, Humans, DNA Damage, DNA Mutational Analysis, DNA Replication, Transcription, Genetic, Mutagenesis, CpG Islands, Long Interspersed Nucleotide Elements, Germ-Line Mutation, Genome, Human, Algorithms, Genetic Variation, DNA Demethylation, Human Genome, Genetics, 1.1 Normal biological development and functioning, Aetiology, Underpinning research, 2.1 Biological and endogenous factors, Generic health relevance, General Science & Technology
Abstract

Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.

Published
2021

23. 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

24. 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

25. 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

26. 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

27. 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

28. Cerebral small vessel disease genomics and its implications across the lifespan.

Author

Sargurupremraj, Muralidharan, Suzuki, Hideaki, Jian, Xueqiu, Sarnowski, Chloé, Evans, Tavia E, Bis, Joshua C, Eiriksdottir, Gudny, Sakaue, Saori, Terzikhan, Natalie, Habes, Mohamad, Zhao, Wei, Armstrong, Nicola J, Hofer, Edith, Yanek, Lisa R, Hagenaars, Saskia P, Kumar, Rajan B, van den Akker, Erik B, McWhirter, Rebekah E, Trompet, Stella, Mishra, Aniket, Saba, Yasaman, Satizabal, Claudia L, Beaudet, Gregory, Petit, Laurent, Tsuchida, Ami, Zago, Laure, Schilling, Sabrina, Sigurdsson, Sigurdur, Gottesman, Rebecca F, Lewis, Cora E, Aggarwal, Neelum T, Lopez, Oscar L, Smith, Jennifer A, Valdés Hernández, Maria C, van der Grond, Jeroen, Wright, Margaret J, Knol, Maria J, Dörr, Marcus, Thomson, Russell J, Bordes, Constance, Le Grand, Quentin, Duperron, Marie-Gabrielle, Smith, Albert V, Knopman, David S, Schreiner, Pamela J, Evans, Denis A, Rotter, Jerome I, Beiser, Alexa S, Maniega, Susana Muñoz, Beekman, Marian, Trollor, Julian, Stott, David J, Vernooij, Meike W, Wittfeld, Katharina, Niessen, Wiro J, Soumaré, Aicha, Boerwinkle, Eric, Sidney, Stephen, Turner, Stephen T, Davies, Gail, Thalamuthu, Anbupalam, Völker, Uwe, van Buchem, Mark A, Bryan, R Nick, Dupuis, Josée, Bastin, Mark E, Ames, David, Teumer, Alexander, Amouyel, Philippe, Kwok, John B, Bülow, Robin, Deary, Ian J, Schofield, Peter R, Brodaty, Henry, Jiang, Jiyang, Tabara, Yasuharu, Setoh, Kazuya, Miyamoto, Susumu, Yoshida, Kazumichi, Nagata, Manabu, Kamatani, Yoichiro, Matsuda, Fumihiko, Psaty, Bruce M, Bennett, David A, De Jager, Philip L, Mosley, Thomas H, Sachdev, Perminder S, Schmidt, Reinhold, Warren, Helen R, Evangelou, Evangelos, Trégouët, David-Alexandre, International Network against Thrombosis (INVENT) Consortium, International Headache Genomics Consortium (IHGC), Ikram, Mohammad A, Wen, Wei, DeCarli, Charles, Srikanth, Velandai K, Jukema, J Wouter, Slagboom, Eline P, and Kardia, Sharon LR

Subjects
International Network against Thrombosis (INVENT) Consortium, International Headache Genomics Consortium, Humans, Alzheimer Disease, Hypertension, Medical History Taking, Risk Assessment, Risk Factors, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Stroke, Genome-Wide Association Study, Young Adult, Diffusion Tensor Imaging, Genetic Loci, Mendelian Randomization Analysis, Cerebral Small Vessel Diseases, White Matter, and over
Abstract

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.

Published
2020

29. Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Author

Bick, Alexander G, Weinstock, Joshua S, Nandakumar, Satish K, Fulco, Charles P, Bao, Erik L, Zekavat, Seyedeh M, Szeto, Mindy D, Liao, Xiaotian, Leventhal, Matthew J, Nasser, Joseph, Chang, Kyle, Laurie, Cecelia, Burugula, Bala Bharathi, Gibson, Christopher J, Niroula, Abhishek, Lin, Amy E, Taub, Margaret A, Aguet, Francois, Ardlie, Kristin, Mitchell, Braxton D, Barnes, Kathleen C, Moscati, Arden, Fornage, Myriam, Redline, Susan, Psaty, Bruce M, Silverman, Edwin K, Weiss, Scott T, Palmer, Nicholette D, Vasan, Ramachandran S, Burchard, Esteban G, Kardia, Sharon LR, He, Jiang, Kaplan, Robert C, Smith, Nicholas L, Arnett, Donna K, Schwartz, David A, Correa, Adolfo, de Andrade, Mariza, Guo, Xiuqing, Konkle, Barbara A, Custer, Brian, Peralta, Juan M, Gui, Hongsheng, Meyers, Deborah A, McGarvey, Stephen T, Chen, Ida Yii-Der, Shoemaker, M Benjamin, Peyser, Patricia A, Broome, Jai G, Gogarten, Stephanie M, Wang, Fei Fei, Wong, Quenna, Montasser, May E, Daya, Michelle, Kenny, Eimear E, North, Kari E, Launer, Lenore J, Cade, Brian E, Bis, Joshua C, Cho, Michael H, Lasky-Su, Jessica, Bowden, Donald W, Cupples, L Adrienne, Mak, Angel CY, Becker, Lewis C, Smith, Jennifer A, Kelly, Tanika N, Aslibekyan, Stella, Heckbert, Susan R, Tiwari, Hemant K, Yang, Ivana V, Heit, John A, Lubitz, Steven A, Johnsen, Jill M, Curran, Joanne E, Wenzel, Sally E, Weeks, Daniel E, Rao, Dabeeru C, Darbar, Dawood, Moon, Jee-Young, Tracy, Russell P, Buth, Erin J, Rafaels, Nicholas, Loos, Ruth JF, Durda, Peter, Liu, Yongmei, Hou, Lifang, Lee, Jiwon, Kachroo, Priyadarshini, Freedman, Barry I, Levy, Daniel, Bielak, Lawrence F, Hixson, James E, Floyd, James S, Whitsel, Eric A, Ellinor, Patrick T, Irvin, Marguerite R, Fingerlin, Tasha E, Raffield, Laura M, and Armasu, Sebastian M

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Biotechnology, Regenerative Medicine, Stem Cell Research, Human Genome, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Cardiovascular, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adult, Africa, Aged, Aged, 80 and over, Black People, Cell Self Renewal, Clonal Hematopoiesis, DNA-Binding Proteins, Dioxygenases, Female, Genetic Predisposition to Disease, Genome, Human, Germ-Line Mutation, Hematopoietic Stem Cells, Humans, Intracellular Signaling Peptides and Proteins, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Precision Medicine, Proto-Oncogene Proteins, Tripartite Motif Proteins, United States, Whole Genome Sequencing, alpha Karyopherins, NHLBI Trans-Omics for Precision Medicine Consortium, General Science & Technology
Abstract

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

Published
2020

30. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.

Author

Li, Xihao, Li, Zilin, Zhou, Hufeng, Gaynor, Sheila M, Liu, Yaowu, Chen, Han, Sun, Ryan, Dey, Rounak, Arnett, Donna K, Aslibekyan, Stella, Ballantyne, Christie M, Bielak, Lawrence F, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Broome, Jai G, Conomos, Matthew P, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Freedman, Barry I, Guo, Xiuqing, Hindy, George, Irvin, Marguerite R, Kardia, Sharon LR, Kathiresan, Sekar, Khan, Alyna T, Kooperberg, Charles L, Laurie, Cathy C, Liu, X Shirley, Mahaney, Michael C, Manichaikul, Ani W, Martin, Lisa W, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Montasser, May E, Moore, Jill E, Morrison, Alanna C, O'Connell, Jeffrey R, Palmer, Nicholette D, Pampana, Akhil, Peralta, Juan M, Peyser, Patricia A, Psaty, Bruce M, Redline, Susan, Rice, Kenneth M, Rich, Stephen S, Smith, Jennifer A, Tiwari, Hemant K, Tsai, Michael Y, Vasan, Ramachandran S, Wang, Fei Fei, Weeks, Daniel E, Weng, Zhiping, Wilson, James G, Yanek, Lisa R, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Neale, Benjamin M, Sunyaev, Shamil R, Abecasis, Gonçalo R, Rotter, Jerome I, Willer, Cristen J, Peloso, Gina M, Natarajan, Pradeep, and Lin, Xihong

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Humans, Genetic Predisposition to Disease, Phenotype, Genome, Models, Genetic, Computer Simulation, Cholesterol, LDL, Genetic Variation, Genome-Wide Association Study, Molecular Sequence Annotation, Whole Genome Sequencing, Models, Genetic, Cholesterol, LDL, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

Published
2020

31. Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels

Author

Wang, Zhe, Chen, Han, Bartz, Traci M, Bielak, Lawrence F, Chasman, Daniel I, Feitosa, Mary F, Franceschini, Nora, Guo, Xiuqing, Lim, Elise, Noordam, Raymond, Richard, Melissa A, Wang, Heming, Cade, Brian, Cupples, L Adrienne, de Vries, Paul S, Giulanini, Franco, Lee, Jiwon, Lemaitre, Rozenn N, Martin, Lisa W, Reiner, Alex P, Rich, Stephen S, Schreiner, Pamela J, Sidney, Stephen, Sitlani, Colleen M, Smith, Jennifer A, van Dijk, Ko Willems, Yao, Jie, Zhao, Wei, Fornage, Myriam, Kardia, Sharon LR, Kooperberg, Charles, Liu, Ching-Ti, Mook-Kanamori, Dennis O, Province, Michael A, Psaty, Bruce M, Redline, Susan, Ridker, Paul M, Rotter, Jerome I, Boerwinkle, Eric, Morrison, Alanna C, and Group, on behalf of the CHARGE Gene-Lifestyle Interactions Working

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Substance Misuse, Human Genome, Genetics, Cardiovascular, Heart Disease, Alcoholism, Alcohol Use and Health, Aetiology, 2.1 Biological and endogenous factors, Stroke, Cancer, Oral and gastrointestinal, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, Alcohol Drinking, Apolipoproteins E, Cholesterol, HDL, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Humans, Lipids, Male, Middle Aged, Polymorphism, Single Nucleotide, Proprotein Convertase 9, Triglycerides, White People, Young Adult, exome, gene-environment interaction, genome-wide association study, lipids, self-report, CHARGE Gene-Lifestyle Interactions Working Group, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundAlcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.MethodsIn the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.ResultsWe discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (PCSK9, LPA, LPL, LIPG, ANGPTL4, APOB, APOC3, and CD300LG) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (P=6.65×10-6 for the interaction test) and replicated at nominal significance level (P=0.013) in SMC5.ConclusionsIn conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

Published
2020

32. Social regulation of inflammation related gene expression in the multi-ethnic study of atherosclerosis

Author

Brown, Kristen M, Diez-Roux, Ana V, Smith, Jennifer A, Needham, Belinda L, Mukherjee, Bhramar, Ware, Erin B, Liu, Yongmei, Cole, Steven W, Seeman, Teresa E, and Kardia, Sharon LR

Subjects
Biomedical and Clinical Sciences, Psychology, Atherosclerosis, Genetics, 2.1 Biological and endogenous factors, Aged, Female, Gene Expression, Gene Expression Profiling, Health Surveys, Humans, Inflammation, Loneliness, Male, Middle Aged, Social Determinants of Health, Social Discrimination, Stress, Psychological, Social stress, Gene expression, Human social genomics, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biomedical and clinical sciences
Abstract

BackgroundExposure to adverse social factors has been associated with an altered inflammatory profile, a risk factor for several acute and chronic diseases. Differential gene expression may be a biological mediator in the relationship. In this study, associations between a range of social factors and expression of inflammation-related genes were investigated.MethodsSocial factor and gene expression data were collected from 1,264 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA). Inflammation-related genes were identified from the Gene Ontology database. The associations between social factors and gene expression were first assessed using the Global Analysis of Covariance (Global ANCOVA) gene set enrichment test. When the global test was significant, linear regression and elastic net penalized regression were employed to identify the individual gene transcripts within each gene set associated with the social factor.ResultsLoneliness (p = 0.003), chronic burden (p = 0.002), and major or lifetime discrimination (p = 0.045) were significantly associated with global expression of the chronic inflammatory gene set. Of the 20 transcripts that comprise this gene set, elastic net selected 12 transcripts for loneliness, 8 for chronic burden, and 3 for major or lifetime discrimination. Major or lifetime discrimination was also associated with the inflammatory response (p = 0.029), regulation of the inflammatory response (p = 0.041), and immune response (p = 0.025) gene sets in global analyses, and 53, 136, and 26 transcripts were selected via elastic net for these gene sets respectively. There were no significant associations in linear regression analyses after adjustment for multiple testing.ConclusionsThis study highlights gene expression as a biological mechanism through which social factors may affect inflammation.

Published
2020

33. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Author

Wu, Peitao, Rybin, Denis, Bielak, Lawrence F, Feitosa, Mary F, Franceschini, Nora, Li, Yize, Lu, Yingchang, Marten, Jonathan, Musani, Solomon K, Noordam, Raymond, Raghavan, Sridharan, Rose, Lynda M, Schwander, Karen, Smith, Albert V, Tajuddin, Salman M, Vojinovic, Dina, Amin, Najaf, Arnett, Donna K, Bottinger, Erwin P, Demirkan, Ayse, Florez, Jose C, Ghanbari, Mohsen, Harris, Tamara B, Launer, Lenore J, Liu, Jingmin, Liu, Jun, Mook-Kanamori, Dennis O, Murray, Alison D, Nalls, Mike A, Peyser, Patricia A, Uitterlinden, André G, Voortman, Trudy, Bouchard, Claude, Chasman, Daniel, Correa, Adolfo, de Mutsert, Renée, Evans, Michele K, Gudnason, Vilmundur, Hayward, Caroline, Kao, Linda, Kardia, Sharon LR, Kooperberg, Charles, Loos, Ruth JF, Province, Michael M, Rankinen, Tuomo, Redline, Susan, Ridker, Paul M, Rotter, Jerome I, Siscovick, David, Smith, Blair H, van Duijn, Cornelia, Zonderman, Alan B, Rao, DC, Wilson, James G, Dupuis, Josée, Meigs, James B, Liu, Ching-Ti, and Vassy, Jason L

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Pharmacology and Pharmaceutical Sciences, Tobacco, Aging, Tobacco Smoke and Health, Human Genome, Nutrition, Diabetes, Clinical Research, Prevention, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Black People, Blood Glucose, Cigarette Smoking, Cohort Studies, Diabetes Mellitus, Type 2, Fasting, Feasibility Studies, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Incidence, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk, White People, General Science & Technology
Abstract

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p

Published
2020

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

Author

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

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

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

Published
2019

35. Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium

Author

Merino, Jordi, Dashti, Hassan S, Li, Sherly X, Sarnowski, Chloé, Justice, Anne E, Graff, Misa, Papoutsakis, Constantina, Smith, Caren E, Dedoussis, George V, Lemaitre, Rozenn N, Wojczynski, Mary K, Männistö, Satu, Ngwa, Julius S, Kho, Minjung, Ahluwalia, Tarunveer S, Pervjakova, Natalia, Houston, Denise K, Bouchard, Claude, Huang, Tao, Orho-Melander, Marju, Frazier-Wood, Alexis C, Mook-Kanamori, Dennis O, Pérusse, Louis, Pennell, Craig E, de Vries, Paul S, Voortman, Trudy, Li, Olivia, Kanoni, Stavroula, Rose, Lynda M, Lehtimäki, Terho, Zhao, Jing Hua, Feitosa, Mary F, Luan, Jian’an, McKeown, Nicola M, Smith, Jennifer A, Hansen, Torben, Eklund, Niina, Nalls, Mike A, Rankinen, Tuomo, Huang, Jinyan, Hernandez, Dena G, Schulz, Christina-Alexandra, Manichaikul, Ani, Li-Gao, Ruifang, Vohl, Marie-Claude, Wang, Carol A, van Rooij, Frank JA, Shin, Jean, Kalafati, Ioanna P, Day, Felix, Ridker, Paul M, Kähönen, Mika, Siscovick, David S, Langenberg, Claudia, Zhao, Wei, Astrup, Arne, Knekt, Paul, Garcia, Melissa, Rao, DC, Qi, Qibin, Ferrucci, Luigi, Ericson, Ulrika, Blangero, John, Hofman, Albert, Pausova, Zdenka, Mikkilä, Vera, Wareham, Nick J, Kardia, Sharon LR, Pedersen, Oluf, Jula, Antti, Curran, Joanne E, Zillikens, M Carola, Viikari, Jorma S, Forouhi, Nita G, Ordovás, José M, Lieske, John C, Rissanen, Harri, Uitterlinden, André G, Raitakari, Olli T, Kiefte-de Jong, Jessica C, Dupuis, Josée, Rotter, Jerome I, North, Kari E, Scott, Robert A, Province, Michael A, Perola, Markus, Cupples, L Adrienne, Turner, Stephen T, Sørensen, Thorkild IA, Salomaa, Veikko, Liu, Yongmei, Sung, Yun J, Qi, Lu, Bandinelli, Stefania, Rich, Stephen S, de Mutsert, Renée, Tremblay, Angelo, Oddy, Wendy H, Franco, Oscar H, and Paus, Tomas

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Obesity, Human Genome, Genetics, Prevention, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Metabolic and endocrine, Aged, Aging, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Cohort Studies, Energy Intake, Female, Fibroblast Growth Factors, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Genotype, Heart Diseases, Humans, Male, Membrane Proteins, Middle Aged, Nutrients, Polymorphism, Single Nucleotide, Receptors, Retinoic Acid, White People, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P

Published
2019

36. New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders

Author

Evangelou, Evangelos, Gao, He, Chu, Congying, Ntritsos, Georgios, Blakeley, Paul, Butts, Andrew R, Pazoki, Raha, Suzuki, Hideaki, Koskeridis, Fotios, Yiorkas, Andrianos M, Karaman, Ibrahim, Elliott, Joshua, Luo, Qiang, Aeschbacher, Stefanie, Bartz, Traci M, Baumeister, Sebastian E, Braund, Peter S, Brown, Michael R, Brody, Jennifer A, Clarke, Toni-Kim, Dimou, Niki, Faul, Jessica D, Homuth, Georg, Jackson, Anne U, Kentistou, Katherine A, Joshi, Peter K, Lemaitre, Rozenn N, Lind, Penelope A, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Milaneschi, Yuri, Nelson, Christopher P, Nolte, Ilja M, Perälä, Mia-Maria, Polasek, Ozren, Porteous, David, Ratliff, Scott M, Smith, Jennifer A, Stančáková, Alena, Teumer, Alexander, Tuominen, Samuli, Thériault, Sébastien, Vangipurapu, Jagadish, Whitfield, John B, Wood, Alexis, Yao, Jie, Yu, Bing, Zhao, Wei, Arking, Dan E, Auvinen, Juha, Liu, Chunyu, Männikkö, Minna, Risch, Lorenz, Rotter, Jerome I, Snieder, Harold, Veijola, Juha, Blakemore, Alexandra I, Boehnke, Michael, Campbell, Harry, Conen, David, Eriksson, Johan G, Grabe, Hans J, Guo, Xiuqing, van der Harst, Pim, Hartman, Catharina A, Hayward, Caroline, Heath, Andrew C, Jarvelin, Marjo-Riitta, Kähönen, Mika, Kardia, Sharon LR, Kühne, Michael, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lehtimäki, Terho, McIntosh, Andrew M, Mohlke, Karen L, Morrison, Alanna C, Martin, Nicholas G, Oldehinkel, Albertine J, Penninx, Brenda WJH, Psaty, Bruce M, Raitakari, Olli T, Rudan, Igor, Samani, Nilesh J, Scott, Laura J, Spector, Tim D, Verweij, Niek, Weir, David R, Wilson, James F, Levy, Daniel, Tzoulaki, Ioanna, Bell, Jimmy D, Matthews, Paul M, Rothenfluh, Adrian, Desrivières, Sylvane, Schumann, Gunter, and Elliott, Paul

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Epidemiology, Health Sciences, Psychology, Pharmacology and Pharmaceutical Sciences, Biotechnology, Substance Misuse, Brain Disorders, Mental Health, Neurosciences, Serious Mental Illness, Alcoholism, Alcohol Use and Health, Schizophrenia, Genetics, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Mental health, Stroke, Cancer, Oral and gastrointestinal, Good Health and Well Being, Adult, Aged, Alcohol Drinking, Alcoholism, Brain, Female, Genes, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Male, Mental Disorders, Middle Aged, Neuroimaging, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, Biomedical and clinical sciences, Health sciences
Abstract

Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d-1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.

Published
2019

37. A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Author

Deelen, Joris, Evans, Daniel S, Arking, Dan E, Tesi, Niccolò, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K, Biggs, Mary L, van der Spek, Ashley, Atzmon, Gil, Ware, Erin B, Sarnowski, Chloé, Smith, Albert V, Seppälä, Ilkka, Cordell, Heather J, Dose, Janina, Amin, Najaf, Arnold, Alice M, Ayers, Kristin L, Barzilai, Nir, Becker, Elizabeth J, Beekman, Marian, Blanché, Hélène, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C, Cubaynes, Sarah, Cummings, Steven R, Davies, Karen, Debrabant, Birgit, Deleuze, Jean-François, Duncan, Rachel, Faul, Jessica D, Franceschi, Claudio, Galan, Pilar, Gudnason, Vilmundur, Harris, Tamara B, Huisman, Martijn, Hurme, Mikko A, Jagger, Carol, Jansen, Iris, Jylhä, Marja, Kähönen, Mika, Karasik, David, Kardia, Sharon LR, Kingston, Andrew, Kirkwood, Thomas BL, Launer, Lenore J, Lehtimäki, Terho, Lieb, Wolfgang, Lyytikäinen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebel, Almut, Newman, Anne B, Nie, Chao, Nohr, Ellen A, Orwoll, Eric S, Perls, Thomas T, Province, Michael A, Psaty, Bruce M, Raitakari, Olli T, Reinders, Marcel JT, Robine, Jean-Marie, Rotter, Jerome I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild IA, Taylor, Kent D, Uitterlinden, André G, van der Flier, Wiesje, van der Lee, Sven J, van Duijn, Cornelia M, van Heemst, Diana, Vaupel, James W, Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P, Lunetta, Kathryn L, Slagboom, P Eline, and Murabito, Joanne M

Subjects
Humans, Heat-Shock Proteins, Longevity, Apolipoprotein E2, Apolipoprotein E4, Genome-Wide Association Study
Abstract

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Published
2019

38. Insulin Resistance Exacerbates Genetic Predisposition to Nonalcoholic Fatty Liver Disease in Individuals Without Diabetes

Author

Barata, Llilda, Feitosa, Mary F, Bielak, Lawrence F, Halligan, Brian, Baldridge, Abigail S, Guo, Xiuqing, Yerges‐Armstrong, Laura M, Smith, Albert V, Yao, Jie, Palmer, Nicholette D, VanWagner, Lisa B, Carr, J Jeffrey, Chen, Yii‐Der I, Allison, Matthew, Budoff, Matthew J, Handelman, Samuel K, Kardia, Sharon LR, Mosley, Thomas H, Ryan, Kathleen, Harris, Tamara B, Launer, Lenore J, Gudnason, Vilmundur, Rotter, Jerome I, Fornage, Myriam, Rasmussen‐Torvik, Laura J, Borecki, Ingrid B, O’Connell, Jeffrey R, Peyser, Patricia A, Speliotes, Elizabeth K, and Province, Michael A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Nutrition, Diabetes, Prevention, Genetics, Chronic Liver Disease and Cirrhosis, Digestive Diseases, Liver Disease, Obesity, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Oral and gastrointestinal, Clinical sciences
Abstract

The accumulation of excess fat in the liver (hepatic steatosis) in the absence of heavy alcohol consumption causes nonalcoholic fatty liver disease (NAFLD), which has become a global epidemic. Identifying metabolic risk factors that interact with the genetic risk of NAFLD is important for reducing disease burden. We tested whether serum glucose, insulin, insulin resistance, triglyceride (TG), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, body mass index (BMI), and waist-to-hip ratio adjusted for BMI interact with genetic variants in or near the patatin-like phospholipase domain containing 3 (PNPLA3) gene, the glucokinase regulatory protein (GCKR) gene, the neurocan/transmembrane 6 superfamily member 2 (NCAN/TM6SF2) gene, and the lysophospholipase-like 1 (LYPLAL1) gene to exacerbate hepatic steatosis, estimated by liver attenuation. We performed association analyses in 10 population-based cohorts separately and then meta-analyzed results in up to 14,751 individuals (11,870 of European ancestry and 2,881 of African ancestry). We found that PNPLA3-rs738409 significantly interacted with insulin, insulin resistance, BMI, glucose, and TG to increase hepatic steatosis in nondiabetic individuals carrying the G allele. Additionally, GCKR-rs780094 significantly interacted with insulin, insulin resistance, and TG. Conditional analyses using the two largest European ancestry cohorts in the study showed that insulin levels accounted for most of the interaction of PNPLA3-rs738409 with BMI, glucose, and TG in nondiabetic individuals. Insulin, PNPLA3-rs738409, and their interaction accounted for at least 8% of the variance in hepatic steatosis in these two cohorts. Conclusion: Insulin resistance, either directly or through the resultant elevated insulin levels, more than other metabolic traits, appears to amplify the PNPLA3-rs738409-G genetic risk for hepatic steatosis. Improving insulin resistance in nondiabetic individuals carrying PNPLA3-rs738409-G may preferentially decrease hepatic steatosis.

Published
2019

39. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Abstract

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Published
2019

40. Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data

Author

He, Karen Y, Li, Xiaoyin, Kelly, Tanika N, Liang, Jingjing, Cade, Brian E, Assimes, Themistocles L, Becker, Lewis C, Beitelshees, Amber L, Bress, Adam P, Chang, Yen-Pei Christy, Chen, Yii-Der Ida, de Vries, Paul S, Fox, Ervin R, Franceschini, Nora, Furniss, Anna, Gao, Yan, Guo, Xiuqing, Haessler, Jeffrey, Hwang, Shih-Jen, Irvin, Marguerite Ryan, Kalyani, Rita R, Liu, Ching-Ti, Liu, Chunyu, Martin, Lisa Warsinger, Montasser, May E, Muntner, Paul M, Mwasongwe, Stanford, Palmas, Walter, Reiner, Alex P, Shimbo, Daichi, Smith, Jennifer A, Snively, Beverly M, Yanek, Lisa R, Boerwinkle, Eric, Correa, Adolfo, Cupples, L Adrienne, He, Jiang, Kardia, Sharon LR, Kooperberg, Charles, Mathias, Rasika A, Mitchell, Braxton D, Psaty, Bruce M, Vasan, Ramachandran S, Rao, DC, Rich, Stephen S, Rotter, Jerome I, Wilson, James G, Chakravarti, Aravinda, Morrison, Alanna C, Levy, Daniel, Arnett, Donna K, Redline, Susan, and Zhu, Xiaofeng

Subjects
Biological Sciences, Genetics, Biotechnology, Heart Disease, Human Genome, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Alternative Splicing, Blood Pressure, Chromosomes, Human, Pair 16, Exome, Female, Follow-Up Studies, Genetic Linkage, Genetic Variation, Genome, Human, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Male, RNA Splicing Factors, Recombinases, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Blood Pressure Working Group, Complementary and Alternative Medicine, Paediatrics and Reproductive Medicine, Genetics & Heredity, Reproductive medicine
Abstract

In this study, we investigated low-frequency and rare variants associated with blood pressure (BP) by focusing on a linkage region on chromosome 16p13. We used whole genome sequencing (WGS) data obtained through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program on 395 Cleveland Family Study (CFS) European Americans (CFS-EA). By analyzing functional coding variants and non-coding rare variants with CADD score > 10 residing within the chromosomal region in families with linkage evidence, we observed 25 genes with nominal statistical evidence (burden or SKAT p

Published
2019

41. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Author

Liu, Mengzhen, Jiang, Yu, Wedow, Robbee, Li, Yue, Brazel, David M, Chen, Fang, Datta, Gargi, Davila-Velderrain, Jose, McGuire, Daniel, Tian, Chao, Zhan, Xiaowei, Choquet, Hélène, Docherty, Anna R, Faul, Jessica D, Foerster, Johanna R, Fritsche, Lars G, Gabrielsen, Maiken Elvestad, Gordon, Scott D, Haessler, Jeffrey, Hottenga, Jouke-Jan, Huang, Hongyan, Jang, Seon-Kyeong, Jansen, Philip R, Ling, Yueh, Mägi, Reedik, Matoba, Nana, McMahon, George, Mulas, Antonella, Orrù, Valeria, Palviainen, Teemu, Pandit, Anita, Reginsson, Gunnar W, Skogholt, Anne Heidi, Smith, Jennifer A, Taylor, Amy E, Turman, Constance, Willemsen, Gonneke, Young, Hannah, Young, Kendra A, Zajac, Gregory JM, Zhao, Wei, Zhou, Wei, Bjornsdottir, Gyda, Boardman, Jason D, Boehnke, Michael, Boomsma, Dorret I, Chen, Chu, Cucca, Francesco, Davies, Gareth E, Eaton, Charles B, Ehringer, Marissa A, Esko, Tõnu, Fiorillo, Edoardo, Gillespie, Nathan A, Gudbjartsson, Daniel F, Haller, Toomas, Harris, Kathleen Mullan, Heath, Andrew C, Hewitt, John K, Hickie, Ian B, Hokanson, John E, Hopfer, Christian J, Hunter, David J, Iacono, William G, Johnson, Eric O, Kamatani, Yoichiro, Kardia, Sharon LR, Keller, Matthew C, Kellis, Manolis, Kooperberg, Charles, Kraft, Peter, Krauter, Kenneth S, Laakso, Markku, Lind, Penelope A, Loukola, Anu, Lutz, Sharon M, Madden, Pamela AF, Martin, Nicholas G, McGue, Matt, McQueen, Matthew B, Medland, Sarah E, Metspalu, Andres, Mohlke, Karen L, Nielsen, Jonas B, Okada, Yukinori, Peters, Ulrike, Polderman, Tinca JC, Posthuma, Danielle, Reiner, Alexander P, Rice, John P, Rimm, Eric, Rose, Richard J, Runarsdottir, Valgerdur, Stallings, Michael C, Stančáková, Alena, Stefansson, Hreinn, Thai, Khanh K, Tindle, Hilary A, Tyrfingsson, Thorarinn, and Wall, Tamara L

Subjects
Substance Misuse, Human Genome, Brain Disorders, Tobacco, Tobacco Smoke and Health, Genetics, Alcoholism, Alcohol Use and Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Stroke, Cancer, Cardiovascular, Good Health and Well Being, Alcohol Drinking, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Phenotype, Risk, Smoking, Tobacco Use Disorder, 23andMe Research Team, HUNT All-In Psychiatry, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

Published
2019

42. Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease

Author

Ward-Caviness, Cavin K, de Vries, Paul S, Wiggins, Kerri L, Huffman, Jennifer E, Yanek, Lisa R, Bielak, Lawrence F, Giulianini, Franco, Guo, Xiuqing, Kleber, Marcus E, Kacprowski, Tim, Groß, Stefan, Petersman, Astrid, Smith, George Davey, Hartwig, Fernando P, Bowden, Jack, Hemani, Gibran, Müller-Nuraysid, Martina, Strauch, Konstantin, Koenig, Wolfgang, Waldenberger, Melanie, Meitinger, Thomas, Pankratz, Nathan, Boerwinkle, Eric, Tang, Weihong, Fu, Yi-Ping, Johnson, Andrew D, Song, Ci, de Maat, Moniek PM, Uitterlinden, André G, Franco, Oscar H, Brody, Jennifer A, McKnight, Barbara, Chen, Yii-Der Ida, Psaty, Bruce M, Mathias, Rasika A, Becker, Diane M, Peyser, Patricia A, Smith, Jennifer A, Bielinski, Suzette J, Ridker, Paul M, Taylor, Kent D, Yao, Jie, Tracy, Russell, Delgado, Graciela, Trompet, Stella, Sattar, Naveed, Jukema, J Wouter, Becker, Lewis C, Kardia, Sharon LR, Rotter, Jerome I, März, Winfried, Dörr, Marcus, Chasman, Daniel I, Dehghan, Abbas, O’Donnell, Christopher J, Smith, Nicholas L, Peters, Annette, and Morrison, Alanna C

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Heart Disease, Cardiovascular, Prevention, Human Genome, Heart Disease - Coronary Heart Disease, Alleles, Coronary Disease, Fibrinogen, Genetic Pleiotropy, Genetic Variation, Genome-Wide Association Study, Humans, Incidence, Mendelian Randomization Analysis, Models, Genetic, Multivariate Analysis, Myocardial Infarction, Odds Ratio, General Science & Technology
Abstract

BackgroundFibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.Methods and findingsWe evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.ConclusionsA small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.

Published
2019

43. Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging

Author

Jian, Xueqiu, Satizabal, Claudia L, Smith, Albert V, Wittfeld, Katharina, Bis, Joshua C, Smith, Jennifer A, Hsu, Fang-Chi, Nho, Kwangsik, Hofer, Edith, Hagenaars, Saskia P, Nyquist, Paul A, Mishra, Aniket, Adams, Hieab HH, Li, Shuo, Teumer, Alexander, Zhao, Wei, Freedman, Barry I, Saba, Yasaman, Yanek, Lisa R, Chauhan, Ganesh, van Buchem, Mark A, Cushman, Mary, Royle, Natalie A, Bryan, R Nick, Niessen, Wiro J, Windham, Beverly G, DeStefano, Anita L, Habes, Mohamad, Heckbert, Susan R, Palmer, Nicholette D, Lewis, Cora E, Eiriksdottir, Gudny, Maillard, Pauline, Mathias, Rasika A, Homuth, Georg, Valdés-Hernández, Maria del C, Divers, Jasmin, Beiser, Alexa S, Langner, Sönke, Rice, Kenneth M, Bastin, Mark E, Yang, Qiong, Maldjian, Joseph A, Starr, John M, Sidney, Stephen, Risacher, Shannon L, Uitterlinden, André G, Gudnason, Vilmundur G, Nauck, Matthias, Rotter, Jerome I, Schreiner, Pamela J, Boerwinkle, Eric, van Duijn, Cornelia M, Mazoyer, Bernard, von Sarnowski, Bettina, Gottesman, Rebecca F, Levy, Daniel, Sigurdsson, Sigurdur, Vernooij, Meike W, Turner, Stephen T, Schmidt, Reinhold, Wardlaw, Joanna M, Psaty, Bruce M, Mosley, Thomas H, DeCarli, Charles S, Saykin, Andrew J, Bowden, Donald W, Becker, Diane M, Deary, Ian J, Schmidt, Helena, Kardia, Sharon LR, Ikram, M Arfan, Debette, Stéphanie, Grabe, Hans J, Longstreth, WT, Seshadri, Sudha, Launer, Lenore J, and Fornage, Myriam

Subjects
Epidemiology, Health Sciences, Alzheimer's Disease Related Dementias (ADRD), Dementia, Human Genome, Cerebrovascular, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Stroke, Brain Disorders, Acquired Cognitive Impairment, Neurodegenerative, Aging, Minority Health, Genetics, Neurosciences, Biotechnology, 2.1 Biological and endogenous factors, Neurological, Brain, Cohort Studies, Exome, Genetic Variation, Humans, Magnetic Resonance Imaging, Mitochondrial Proteins, White Matter, cerebral small vessel disease, exome, magnetic resonance imaging, meta-analysis, white matter, neuroCHARGE Working Group, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Neurology & Neurosurgery, Clinical sciences, Allied health and rehabilitation science
Abstract

Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P

Published
2018

44. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Subjects
Humans, Neurodegenerative Diseases, Genetic Predisposition to Disease, Cognition, Reaction Time, Mental Disorders, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Young Adult, Genetic Loci, Neurodevelopmental Disorders, Prevention, Behavioral and Social Science, Mental Health, Neurosciences, Biotechnology, Genetics, Human Genome, Neurological, Mental health
Abstract

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P

Published
2018

45. Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies

Author

Smith, Jennifer A, Zhao, Wei, Yasutake, Kalyn, August, Carmella, Ratliff, Scott M, Faul, Jessica D, Boerwinkle, Eric, Chakravarti, Aravinda, Roux, Ana V Diez, Gao, Yan, Griswold, Michael E, Heiss, Gerardo, Kardia, Sharon LR, Morrison, Alanna C, Musani, Solomon K, Mwasongwe, Stanford, North, Kari E, Rose, Kathryn M, Sims, Mario, Sun, Yan V, Weir, David R, and Needham, Belinda L

Subjects
Mental Health, Behavioral and Social Science, Human Genome, Genetics, Depression, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Black or African American, Blood Pressure, Cohort Studies, Gene-Environment Interaction, Humans, Psychology, Risk Factors, Socioeconomic Factors, United States, White People, blood pressure, hypertension, genetics, gene-by-environment interaction, non-burden test, socioeconomic status, psychosocial factors, depression, chronic burden, Toxicology
Abstract

Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region (p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region (p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

Published
2017

46. DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation

Author

Richard, Melissa A, Huan, Tianxiao, Ligthart, Symen, Gondalia, Rahul, Jhun, Min A, Brody, Jennifer A, Irvin, Marguerite R, Marioni, Riccardo, Shen, Jincheng, Tsai, Pei-Chien, Montasser, May E, Jia, Yucheng, Syme, Catriona, Salfati, Elias L, Boerwinkle, Eric, Guan, Weihua, Mosley, Thomas H, Bressler, Jan, Morrison, Alanna C, Liu, Chunyu, Mendelson, Michael M, Uitterlinden, André G, van Meurs, Joyce B, Consortium, BIOS, Heijmans, Bastiaan T, Hoen, Peter AC ’t, van Meurs, Joyce, Isaacs, Aaron, Jansen, Rick, Franke, Lude, Boomsma, Dorret I, Pool, René, van Dongen, Jenny, Hottenga, Jouke J, van Greevenbroek, Marleen MJ, Stehouwer, Coen DA, van der Kallen, Carla JH, Schalkwijk, Casper G, Wijmenga, Cisca, Zhernakova, Alexandra, Tigchelaar, Ettje F, Slagboom, P Eline, Beekman, Marian, Deelen, Joris, van Heemst, Diana, Veldink, Jan H, van den Berg, Leonard H, van Duijn, Cornelia M, Hofman, Albert, Jhamai, P Mila, Verbiest, Michael, Suchiman, H Eka D, Verkerk, Marijn, van der Breggen, Ruud, van Rooij, Jeroen, Lakenberg, Nico, Mei, Hailiang, van Iterson, Maarten, van Galen, Michiel, Bot, Jan, van ’t Hof, Peter, Deelen, Patrick, Nooren, Irene, Moed, Matthijs, Vermaat, Martijn, Zhernakova, Dasha V, Luijk, René, Bonder, Marc Jan, van Dijk, Freerk, Arindrarto, Wibowo, Kielbasa, Szymon M, Swertz, Morris A, van Zwet, Erik W, Franco, Oscar H, Zhang, Guosheng, Li, Yun, Stewart, James D, Bis, Joshua C, Psaty, Bruce M, Chen, Yii-Der Ida, Kardia, Sharon LR, Zhao, Wei, Turner, Stephen T, Absher, Devin, Aslibekyan, Stella, Starr, John M, McRae, Allan F, Hou, Lifang, Just, Allan C, Schwartz, Joel D, Vokonas, Pantel S, Menni, Cristina, Spector, Tim D, Shuldiner, Alan, Damcott, Coleen M, Rotter, Jerome I, Palmas, Walter, Liu, Yongmei, and Paus, Tomáš

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Aged, Blood Pressure, CpG Islands, Cross-Sectional Studies, DNA Methylation, Epigenesis, Genetic, Genetic Variation, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Middle Aged, Nerve Tissue Proteins, Quantitative Trait Loci, Tetraspanins, BIOS Consortium, DNA methylation, Mendelian randomization, blood pressure, epigenome-wide association study, gene expression, sequence variation, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p  30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

Published
2017

47. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

Author

Liang, Jingjing, Le, Thu H, Edwards, Digna R Velez, Tayo, Bamidele O, Gaulton, Kyle J, Smith, Jennifer A, Lu, Yingchang, Jensen, Richard A, Chen, Guanjie, Yanek, Lisa R, Schwander, Karen, Tajuddin, Salman M, Sofer, Tamar, Kim, Wonji, Kayima, James, McKenzie, Colin A, Fox, Ervin, Nalls, Michael A, Young, J Hunter, Sun, Yan V, Lane, Jacqueline M, Cechova, Sylvia, Zhou, Jie, Tang, Hua, Fornage, Myriam, Musani, Solomon K, Wang, Heming, Lee, Juyoung, Adeyemo, Adebowale, Dreisbach, Albert W, Forrester, Terrence, Chu, Pei-Lun, Cappola, Anne, Evans, Michele K, Morrison, Alanna C, Martin, Lisa W, Wiggins, Kerri L, Hui, Qin, Zhao, Wei, Jackson, Rebecca D, Ware, Erin B, Faul, Jessica D, Reiner, Alex P, Bray, Michael, Denny, Joshua C, Mosley, Thomas H, Palmas, Walter, Guo, Xiuqing, Papanicolaou, George J, Penman, Alan D, Polak, Joseph F, Rice, Kenneth, Taylor, Ken D, Boerwinkle, Eric, Bottinger, Erwin P, Liu, Kiang, Risch, Neil, Hunt, Steven C, Kooperberg, Charles, Zonderman, Alan B, Laurie, Cathy C, Becker, Diane M, Cai, Jianwen, Loos, Ruth JF, Psaty, Bruce M, Weir, David R, Kardia, Sharon LR, Arnett, Donna K, Won, Sungho, Edwards, Todd L, Redline, Susan, Cooper, Richard S, Rao, DC, Rotter, Jerome I, Rotimi, Charles, Levy, Daniel, Chakravarti, Aravinda, Zhu, Xiaofeng, and Franceschini, Nora

Subjects
Animals, Humans, Mice, Hypertension, Cadherins, Membrane Proteins, Case-Control Studies, Blood Pressure, Multifactorial Inheritance, Polymorphism, Single Nucleotide, African Americans, Female, Male, Basic Helix-Loop-Helix Transcription Factors, Genome-Wide Association Study, Genetic Loci, Kidney Disease, Cardiovascular, Human Genome, Genetics, Biotechnology, Clinical Research, 2.1 Biological and endogenous factors, Developmental Biology
Abstract

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

Published
2017

48. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium.

Author

Ng, Maggie CY, Graff, Mariaelisa, Lu, Yingchang, Justice, Anne E, Mudgal, Poorva, Liu, Ching-Ti, Young, Kristin, Yanek, Lisa R, Feitosa, Mary F, Wojczynski, Mary K, Rand, Kristin, Brody, Jennifer A, Cade, Brian E, Dimitrov, Latchezar, Duan, Qing, Guo, Xiuqing, Lange, Leslie A, Nalls, Michael A, Okut, Hayrettin, Tajuddin, Salman M, Tayo, Bamidele O, Vedantam, Sailaja, Bradfield, Jonathan P, Chen, Guanjie, Chen, Wei-Min, Chesi, Alessandra, Irvin, Marguerite R, Padhukasahasram, Badri, Smith, Jennifer A, Zheng, Wei, Allison, Matthew A, Ambrosone, Christine B, Bandera, Elisa V, Bartz, Traci M, Berndt, Sonja I, Bernstein, Leslie, Blot, William J, Bottinger, Erwin P, Carpten, John, Chanock, Stephen J, Chen, Yii-Der Ida, Conti, David V, Cooper, Richard S, Fornage, Myriam, Freedman, Barry I, Garcia, Melissa, Goodman, Phyllis J, Hsu, Yu-Han H, Hu, Jennifer, Huff, Chad D, Ingles, Sue A, John, Esther M, Kittles, Rick, Klein, Eric, Li, Jin, McKnight, Barbara, Nayak, Uma, Nemesure, Barbara, Ogunniyi, Adesola, Olshan, Andrew, Press, Michael F, Rohde, Rebecca, Rybicki, Benjamin A, Salako, Babatunde, Sanderson, Maureen, Shao, Yaming, Siscovick, David S, Stanford, Janet L, Stevens, Victoria L, Stram, Alex, Strom, Sara S, Vaidya, Dhananjay, Witte, John S, Yao, Jie, Zhu, Xiaofeng, Ziegler, Regina G, Zonderman, Alan B, Adeyemo, Adebowale, Ambs, Stefan, Cushman, Mary, Faul, Jessica D, Hakonarson, Hakon, Levin, Albert M, Nathanson, Katherine L, Ware, Erin B, Weir, David R, Zhao, Wei, Zhi, Degui, Bone Mineral Density in Childhood Study (BMDCS) Group, Arnett, Donna K, Grant, Struan FA, Kardia, Sharon LR, Oloapde, Olufunmilayo I, Rao, DC, Rotimi, Charles N, Sale, Michele M, Williams, L Keoki, Zemel, Babette S, Becker, Diane M, and Borecki, Ingrid B

Subjects
Bone Mineral Density in Childhood Study (BMDCS) Group, Humans, Obesity, Genetic Predisposition to Disease, Serine Endopeptidases, Anthropometry, Body Mass Index, Waist-Hip Ratio, Chromosome Mapping, Gene Frequency, Linkage Disequilibrium, Polymorphism, Single Nucleotide, African Continental Ancestry Group, European Continental Ancestry Group, Female, Male, Adiposity, Genome-Wide Association Study, Transcription Factor 7-Like 2 Protein, Genetics, Human Genome, 2.1 Biological and endogenous factors, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (

Published
2017

49. Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Author

Chu, Audrey Y, Deng, Xuan, Fisher, Virginia A, Drong, Alexander, Zhang, Yang, Feitosa, Mary F, Liu, Ching-Ti, Weeks, Olivia, Choh, Audrey C, Duan, Qing, Dyer, Thomas D, Eicher, John D, Guo, Xiuqing, Heard-Costa, Nancy L, Kacprowski, Tim, Kent, Jack W, Lange, Leslie A, Liu, Xinggang, Lohman, Kurt, Lu, Lingyi, Mahajan, Anubha, O'Connell, Jeffrey R, Parihar, Ankita, Peralta, Juan M, Smith, Albert V, Zhang, Yi, Homuth, Georg, Kissebah, Ahmed H, Kullberg, Joel, Laqua, René, Launer, Lenore J, Nauck, Matthias, Olivier, Michael, Peyser, Patricia A, Terry, James G, Wojczynski, Mary K, Yao, Jie, Bielak, Lawrence F, Blangero, John, Borecki, Ingrid B, Bowden, Donald W, Carr, John Jeffrey, Czerwinski, Stefan A, Ding, Jingzhong, Friedrich, Nele, Gudnason, Vilmunder, Harris, Tamara B, Ingelsson, Erik, Johnson, Andrew D, Kardia, Sharon LR, Langefeld, Carl D, Lind, Lars, Liu, Yongmei, Mitchell, Braxton D, Morris, Andrew P, Mosley, Thomas H, Rotter, Jerome I, Shuldiner, Alan R, Towne, Bradford, Völzke, Henry, Wallaschofski, Henri, Wilson, James G, Allison, Matthew, Lindgren, Cecilia M, Goessling, Wolfram, Cupples, L Adrienne, Steinhauser, Matthew L, and Fox, Caroline S

Subjects
Nutrition, Human Genome, Genetics, Adipocytes, Animals, Body Fat Distribution, Cell Differentiation, Cohort Studies, Ethnicity, Female, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Mice, Mice, Inbred C57BL, Obesity, Phenotype, Polymorphism, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10-8; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Published
2017

50. Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis

Author

Natarajan, Pradeep, Bis, Joshua C, Bielak, Lawrence F, Cox, Amanda J, Dörr, Marcus, Feitosa, Mary F, Franceschini, Nora, Guo, Xiuqing, Hwang, Shih-Jen, Isaacs, Aaron, Jhun, Min A, Kavousi, Maryam, Li-Gao, Ruifang, Lyytikäinen, Leo-Pekka, Marioni, Riccardo E, Schminke, Ulf, Stitziel, Nathan O, Tada, Hayato, van Setten, Jessica, Smith, Albert V, Vojinovic, Dina, Yanek, Lisa R, Yao, Jie, Yerges-Armstrong, Laura M, Amin, Najaf, Baber, Usman, Borecki, Ingrid B, Carr, J Jeffrey, Chen, Yii-Der Ida, Cupples, L Adrienne, de Jong, Pim A, de Koning, Harry, de Vos, Bob D, Demirkan, Ayse, Fuster, Valentin, Franco, Oscar H, Goodarzi, Mark O, Harris, Tamara B, Heckbert, Susan R, Heiss, Gerardo, Hoffmann, Udo, Hofman, Albert, Išgum, Ivana, Jukema, J Wouter, Kähönen, Mika, Kardia, Sharon LR, Kral, Brian G, Launer, Lenore J, Massaro, Joe, Mehran, Roxana, Mitchell, Braxton D, Mosley, Thomas H, de Mutsert, Renée, Newman, Anne B, Nguyen, Khanh-Dung, North, Kari E, O'Connell, Jeffrey R, Oudkerk, Matthijs, Pankow, James S, Peloso, Gina M, Post, Wendy, Province, Michael A, Raffield, Laura M, Raitakari, Olli T, Reilly, Dermot F, Rivadeneira, Fernando, Rosendaal, Frits, Sartori, Samantha, Taylor, Kent D, Teumer, Alexander, Trompet, Stella, Turner, Stephen T, Uitterlinden, Andre G, Vaidya, Dhananjay, van der Lugt, Aad, Völker, Uwe, Wardlaw, Joanna M, Wassel, Christina L, Weiss, Stefan, Wojczynski, Mary K, Becker, Diane M, Becker, Lewis C, Boerwinkle, Eric, Bowden, Donald W, Deary, Ian J, Dehghan, Abbas, Felix, Stephan B, Gudnason, Vilmundur, Lehtimäki, Terho, Mathias, Rasika, Mook-Kanamori, Dennis O, Psaty, Bruce M, Rader, Daniel J, Rotter, Jerome I, Wilson, James G, van Duijn, Cornelia M, Völzke, Henry, Kathiresan, Sekar, Peyser, Patricia A, and O'Donnell, Christopher J

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease - Coronary Heart Disease, Aging, Human Genome, Atherosclerosis, Cardiovascular, Heart Disease, Clinical Research, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Apolipoprotein B-100, Apolipoprotein E2, Asymptomatic Diseases, Black People, Carotid Artery Diseases, Carotid Intima-Media Thickness, Cholesterol, LDL, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Exome, Gene Frequency, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Odds Ratio, Oligonucleotide Array Sequence Analysis, Phenotype, Prognosis, Risk Assessment, Risk Factors, Vascular Calcification, White People, carotid intima-media thickness, coronary artery calcification, exome, genome-wide association study, genomics, CHARGE Consortium, carotid intima–media thickness, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundThe burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease. We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent coronary heart disease.Methods and resultsWe studied a total of 25 109 European ancestry and African ancestry participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52 869 participants with common carotid intima-media thickness measured by ultrasonography within the CHARGE Consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology). Participants were genotyped for 247 870 DNA sequence variants (231 539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and carotid intima-media thickness. APOB p.Arg3527Gln was associated with 4-fold excess CAC (P=3×10-10). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3% reduced CAC (P=1×10-12) and 1.4% reduced carotid intima-media thickness (P=4×10-14) in carriers compared with noncarriers. In secondary analyses conditioning on low-density lipoprotein cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for coronary heart disease (odds ratio 0.77; P=1×10-11).ConclusionsExome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities, as well as clinical coronary heart disease.

Published
2016

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