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

Author

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

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

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

Published
2024

2. Determinants of mosaic chromosomal alteration fitness.

Author

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

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

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

Published
2024

4. A methylation risk score for chronic kidney disease: a HyperGEN study

Author

Jones, Alana C, Patki, Amit, Srinivasasainagendra, Vinodh, Hidalgo, Bertha A, Tiwari, Hemant K, Limdi, Nita A, Armstrong, Nicole D, Chaudhary, Ninad S, Minniefield, Bré, Absher, Devin, Arnett, Donna K, Lange, Leslie A, Lange, Ethan M, Young, Bessie A, Diamantidis, Clarissa J, Rich, Stephen S, Mychaleckyj, Josyf C, Rotter, Jerome I, Taylor, Kent D, Kramer, Holly J, Tracy, Russell P, Durda, Peter, Kasela, Silva, Lappalinen, Tuuli, Liu, Yongmei, Johnson, W Craig, Van Den Berg, David J, Franceschini, Nora, Liu, Simin, Mouton, Charles P, Bhatti, Parveen, Horvath, Steve, Whitsel, Eric A, and Irvin, Marguerite R

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Prevention, Clinical Research, Human Genome, Health Disparities, Kidney Disease, Minority Health, Women's Health, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Renal and urogenital, Humans, Renal Insufficiency, Chronic, DNA Methylation, Male, Female, Middle Aged, Glomerular Filtration Rate, CpG Islands, Risk Factors, Black or African American, Aged, Genome-Wide Association Study, Epigenesis, Genetic, Adult, Genetic Predisposition to Disease, Chronic kidney disease, eGFR, Methylation risk score, Epigenetics
Abstract

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

Published
2024

5. Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Author

Hughes, Odessica, Bentley, Amy R, Breeze, Charles E, Aguet, Francois, Xu, Xiaoguang, Nadkarni, Girish, Sun, Quan, Lin, Bridget M, Gilliland, Thomas, Meyer, Mariah C, Du, Jiawen, Raffield, Laura M, Kramer, Holly, Morton, Robert W, Gouveia, Mateus H, Atkinson, Elizabeth G, Valladares-Salgado, Adan, Wacher-Rodarte, Niels, Dueker, Nicole D, Guo, Xiuqing, Hai, Yang, Adeyemo, Adebowale, Best, Lyle G, Cai, Jianwen, Chen, Guanjie, Chong, Michael, Doumatey, Ayo, Eales, James, Goodarzi, Mark O, Ipp, Eli, Irvin, Marguerite Ryan, Jiang, Minzhi, Jones, Alana C, Kooperberg, Charles, Krieger, Jose E, Lange, Ethan M, Lanktree, Matthew B, Lash, James P, Lotufo, Paulo A, Loos, Ruth JF, My, Vy Thi Ha, Peralta-Romero, Jesús, Qi, Lihong, Raffel, Leslie J, Rich, Stephen S, Rodriquez, Erik J, Tarazona-Santos, Eduardo, Taylor, Kent D, Umans, Jason G, Wen, Jia, Young, Bessie A, Yu, Zhi, Zhang, Ying, Chen, Yii-Der Ida, Rundek, Tanja, Rotter, Jerome I, Cruz, Miguel, Fornage, Myriam, Lima-Costa, Maria Fernanda, Pereira, Alexandre C, Paré, Guillaume, Natarajan, Pradeep, Cole, Shelley A, Carson, April P, Lange, Leslie A, Li, Yun, Perez-Stable, Eliseo J, Do, Ron, Charchar, Fadi J, Tomaszewski, Maciej, Mychaleckyj, Josyf C, Rotimi, Charles, Morris, Andrew P, and Franceschini, Nora

Subjects
Biological Sciences, Genetics, Kidney Disease, Prevention, Human Genome, Renal and urogenital, Good Health and Well Being, Humans, Genome-Wide Association Study, Renal Insufficiency, Chronic, Glomerular Filtration Rate, Multifactorial Inheritance, Kidney, admixed populations, chronic kidney disease, eGFR, expression quantitative trait locus, fine-mapping, genome-wide association study, kidney function, multi-ancestry, polygenic scores
Abstract

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p

Published
2024

6. Association of the gut microbiome with kidney function and damage in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Author

Peters, Brandilyn A, Qi, Qibin, Usyk, Mykhaylo, Daviglus, Martha L, Cai, Jianwen, Franceschini, Nora, Lash, James P, Gellman, Marc D, Yu, Bing, Boerwinkle, Eric, Knight, Rob, Burk, Robert D, and Kaplan, Robert C

Subjects
Microbiology, Biological Sciences, Clinical Research, Diabetes, Nutrition, Kidney Disease, Renal and urogenital, Good Health and Well Being, Humans, Cross-Sectional Studies, Gastrointestinal Microbiome, Hispanic or Latino, Kidney, Public Health, Renal Insufficiency, Chronic, Gut microbiome, chronic kidney disease, glomerular filtration rate, metabolites
Abstract

BackgroundThe gut microbiome is altered in chronic kidney disease (CKD), potentially contributing to CKD progression and co-morbidities, but population-based studies of the gut microbiome across a wide range of kidney function and damage are lacking.MethodsIn the Hispanic Community Health Study/Study of Latinos, gut microbiome was assessed by shotgun sequencing of stool (n = 2,438; 292 with suspected CKD). We examined cross-sectional associations of estimated glomerular filtration rate (eGFR), urinary albumin:creatinine (UAC) ratio, and CKD with gut microbiome features. Kidney trait-related microbiome features were interrogated for correlation with serum metabolites (n = 700), and associations of microbiome-related serum metabolites with kidney trait progression were examined in a prospective analysis (n = 3,635).ResultsHigher eGFR was associated with overall gut microbiome composition, greater abundance of species from Prevotella, Faecalibacterium, Roseburia, and Eubacterium, and microbial functions related to synthesis of long-chain fatty acids and carbamoyl-phosphate. Higher UAC ratio and CKD were related to lower gut microbiome diversity and altered overall microbiome composition only in participants without diabetes. Microbiome features related to better kidney health were associated with many serum metabolites (e.g., higher indolepropionate, beta-cryptoxanthin; lower imidazole propionate, deoxycholic acids, p-cresol glucuronide). Imidazole propionate, deoxycholic acid metabolites, and p-cresol glucuronide were associated with prospective reductions in eGFR and/or increases in UAC ratio over ~6 y.ConclusionsKidney function is a significant correlate of the gut microbiome, while the relationship of kidney damage with the gut microbiome depends on diabetes status. Gut microbiome metabolites may contribute to CKD progression.

Published
2023

7. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification.

Author

de Vries, Paul, Conomos, Matthew, Singh, Kuldeep, Nicholson, Christopher, Jain, Deepti, Hasbani, Natalie, Jiang, Wanlin, Lee, Sujin, Cardenas, Christian, Lutz, Sharon, Wong, Doris, Guo, Xiuqing, Yao, Jie, Young, Erica, Tcheandjieu, Catherine, Hilliard, Austin, Bis, Joshua, Bielak, Lawrence, Brown, Michael, Musharoff, Shaila, Clarke, Shoa, Terry, James, Palmer, Nicholette, Yanek, Lisa, Xu, Huichun, Heard-Costa, Nancy, Wessel, Jennifer, Selvaraj, Margaret, Li, Rebecca, Sun, Xiao, Turner, Adam, Stilp, Adrienne, Khan, Alyna, Newman, Anne, Rasheed, Asif, Freedman, Barry, Kral, Brian, McHugh, Caitlin, Hodonsky, Chani, Saleheen, Danish, Herrington, David, Jacobs, David, Nickerson, Deborah, Boerwinkle, Eric, Wang, Fei, Heiss, Gerardo, Jun, Goo, Kinney, Greg, Sigurslid, Haakon, Doddapaneni, HarshaVardhan, Hall, Ira, Bensenor, Isabela, Broome, Jai, Crapo, James, Wilson, James, Smith, Jennifer, Blangero, John, Vargas, Jose, Mosquera, Jose, Smith, Joshua, Viaud-Martinez, Karine, Ryan, Kathleen, Young, Kendra, Taylor, Kent, Lange, Leslie, Emery, Leslie, Bittencourt, Marcio, Montasser, May, Yu, Miao, Mahaney, Michael, Mahamdeh, Mohammed, Fornage, Myriam, Franceschini, Nora, Lotufo, Paulo, Natarajan, Pradeep, Wong, Quenna, Mathias, Rasika, Gibbs, Richard, Do, Ron, Mehran, Roxana, Tracy, Russell, Kim, Ryan, Nelson, Sarah, Damrauer, Scott, Kardia, Sharon, Rich, Stephen, Fuster, Valentin, Napolioni, Valerio, Zhao, Wei, Tian, Wenjie, Yin, Xianyong, Min, Yuan-I, Manning, Alisa, Peloso, Gina, Kelly, Tanika, ODonnell, Christopher, Morrison, Alanna, Curran, Joanne, Zapol, Warren, and Bowden, Donald

Abstract

Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.

Published
2023

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

Author

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

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

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

Published
2023

9. Clonal hematopoiesis of indeterminate potential is associated with acute kidney injury

Author

Vlasschaert, Caitlyn, Robinson-Cohen, Cassianne, Chen, Jianchun, Akwo, Elvis, Parker, Alyssa C., Silver, Samuel A., Bhatraju, Pavan K., Poisner, Hannah, Cao, Shirong, Jiang, Ming, Wang, Yinqiu, Niu, Aolei, Siew, Edward, Van Amburg, Joseph C., Kramer, Holly J., Kottgen, Anna, Franceschini, Nora, Psaty, Bruce M., Tracy, Russell P., Alonso, Alvaro, Arking, Dan E., Coresh, Josef, Ballantyne, Christie M., Boerwinkle, Eric, Grams, Morgan, Zhang, Ming-Zhi, Kestenbaum, Bryan, Lanktree, Matthew B., Rauh, Michael J., Harris, Jr, Raymond C., and Bick, Alexander G.

Published
2024
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10. Whole-exome sequencing study identifies four novel gene loci associated with diabetic kidney disease.

Author

Pan, Yang, Sun, Xiao, Mi, Xuenan, Huang, Zhijie, Hsu, Yenchih, Hixson, James, Munzy, Donna, Metcalf, Ginger, Franceschini, Nora, Tin, Adrienne, Köttgen, Anna, Francis, Michael, Brody, Jennifer, Kestenbaum, Bryan, Sitlani, Colleen, Mychaleckyj, Josyf, Kramer, Holly, Lange, Leslie, Guo, Xiuqing, Hwang, Shih-Jen, Irvin, Marguerite, Smith, Jennifer, Yanek, Lisa, Vaidya, Dhananjay, Chen, Yii-Der, Fornage, Myriam, Lloyd-Jones, Donald, Hou, Lifang, Mathias, Rasika, Mitchell, Braxton, Peyser, Patricia, Kardia, Sharon, Arnett, Donna, Correa, Adolfo, Raffield, Laura, Vasan, Ramachandran, Cupple, L, Levy, Daniel, Kaplan, Robert, North, Kari, Kooperberg, Charles, Reiner, Alexander, Psaty, Bruce, Tracy, Russell, Gibbs, Richard, Morrison, Alanna, Feldman, Harold, Boerwinkle, Eric, He, Jiang, Kelly, Tanika, and Rotter, Jerome

Subjects
Humans, Aminopeptidases, Diabetes Mellitus, Diabetic Nephropathies, Exome Sequencing, Kidney, Renal Insufficiency, Chronic
Abstract

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease and diabetes. Our two-stage WES study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort and Atherosclerosis Risk in Communities studies (stage 1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine participants (stage 2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single-variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds [95% confidence interval (CI): 33.6, 1105] of DKD compared with noncarriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% CI: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

Published
2023

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

Author

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

Published
2024
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12. Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program.

Author

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

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

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

Published
2023

13. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups

Author

Kurniansyah, Nuzulul, Goodman, Matthew O, Khan, Alyna T, Wang, Jiongming, Feofanova, Elena, Bis, Joshua C, Wiggins, Kerri L, Huffman, Jennifer E, Kelly, Tanika, Elfassy, Tali, Guo, Xiuqing, Palmas, Walter, Lin, Henry J, Hwang, Shih-Jen, Gao, Yan, Young, Kendra, Kinney, Gregory L, Smith, Jennifer A, Yu, Bing, Liu, Simin, Wassertheil-Smoller, Sylvia, Manson, JoAnn E, Zhu, Xiaofeng, Chen, Yii-Der Ida, Lee, I-Te, Gu, C Charles, Lloyd-Jones, Donald M, Zöllner, Sebastian, Fornage, Myriam, Kooperberg, Charles, Correa, Adolfo, Psaty, Bruce M, Arnett, Donna K, Isasi, Carmen R, Rich, Stephen S, Kaplan, Robert C, Redline, Susan, Mitchell, Braxton D, Franceschini, Nora, Levy, Daniel, Rotter, Jerome I, Morrison, Alanna C, and Sofer, Tamar

Subjects
Human Genome, Genetics, Clinical Research, Cardiovascular, Good Health and Well Being, Male, Female, Humans, Blood Pressure, Population Health, Risk Factors, Multifactorial Inheritance, Ethnicity, Genome-Wide Association Study, Genetic Predisposition to Disease
Abstract

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

Published
2023

14. Correlations between complex human phenotypes vary by genetic background, gender, and environment

Author

Elgart, Michael, Goodman, Matthew O, Isasi, Carmen, Chen, Han, Morrison, Alanna C, de Vries, Paul S, Xu, Huichun, Manichaikul, Ani W, Guo, Xiuqing, Franceschini, Nora, Psaty, Bruce M, Rich, Stephen S, Rotter, Jerome I, Lloyd-Jones, Donald M, Fornage, Myriam, Correa, Adolfo, Heard-Costa, Nancy L, Vasan, Ramachandran S, Hernandez, Ryan, Kaplan, Robert C, Redline, Susan, Consortium, The Trans-Omics for Precision Medicine, and Sofer, Tamar

Subjects
Biomedical and Clinical Sciences, Genetic Testing, Clinical Research, Genetics, Good Health and Well Being, Humans, Male, Female, Phenotype, Genetic Background, Trans-Omics for Precision Medicine (TOPMed) Consortium, Haseman-Elston regression, Hispanic Community Health Study/Study of Latinos, Trans-Omics in Precision Medicine, admixed population, genetic architecture, genetic background, genetic correlation, heritability, household correlation, multi-ethnic, Biomedical and clinical sciences
Abstract

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

Published
2022

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

Author

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

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

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

Published
2022

16. 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

17. Lipidomic profiling in the Strong Heart Study identified American Indians at risk of chronic kidney disease.

Author

Zeng, Wenjie, Beyene, Habtamu, Kuokkanen, Mikko, Miao, Guanhong, Magliano, Dianna, Umans, Jason, Franceschini, Nora, Cole, Shelley, Michailidis, George, Lee, Elisa, Howard, Barbara, Curran, Joanne, Blangero, John, Meikle, Peter, Zhao, Jinying, and Fiehn, Oliver

Subjects
American Indians, AusDiab, Mexican Americans, San Antonio Family Heart Study, Strong Heart Study, chronic kidney disease, lipidomics, Humans, Lipidomics, Australia, Renal Insufficiency, Chronic, Dyslipidemias, Glomerular Filtration Rate, Diabetes Mellitus, Glycerophospholipids, Biomarkers, Sphingolipids, American Indian or Alaska Native
Abstract

Dyslipidemia associates with and usually precedes the onset of chronic kidney disease (CKD), but a comprehensive assessment of molecular lipid species associated with risk of CKD is lacking. Here, we sought to identify fasting plasma lipids associated with risk of CKD among American Indians in the Strong Heart Family Study, a large-scale community-dwelling of individuals, followed by replication in Mexican Americans from the San Antonio Family Heart Study and Caucasians from the Australian Diabetes, Obesity and Lifestyle Study. We also performed repeated measurement analysis to examine the temporal relationship between the change in the lipidome and change in kidney function between baseline and follow-up of about five years apart. Network analysis was conducted to identify differential lipid classes associated with risk of CKD. In the discovery cohort, we found that higher baseline level of multiple lipid species, including glycerophospholipids, glycerolipids and sphingolipids, was significantly associated with increased risk of CKD, independent of age, sex, body mass index, diabetes and hypertension. Many lipid species were replicated in at least one external cohort at the individual lipid species and/or the class level. Longitudinal change in the plasma lipidome was significantly associated with change in the estimated glomerular filtration rate after adjusting for covariates, baseline lipids and the baseline rate. Network analysis identified distinct lipidomic signatures differentiating high from low-risk groups. Thus, our results demonstrated that disturbed lipid metabolism precedes the onset of CKD. These findings shed light on the mechanisms linking dyslipidemia to CKD and provide potential novel biomarkers for identifying individuals with early impaired kidney function at preclinical stages.

Published
2022

18. 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

19. Systematic Review of Kidney Injury Biomarkers for the Evaluation of CKD of Uncertain Etiology

Author

Amador, Juan José, Bhalla, Vivek, Brooks, Daniel, Claudel, Sophie E., Crowe, Jennifer, Arias-Hidalgo, Mariela, Engel, Lawrence S., Franceschini, Nora, Friedman, David, García-Trabanino, Ramón, González-Quiroz, Marvin, Jarquín, Emmanuel, Jha, Vivekanand, Joubert, Bonnie, Kesler, Karen, Lebov, Jill, Levin, Adeera, Mendley, Susan, Mohan, Sumit, Navas-Acien, Ana, Parsa, Afshin, Scammell, Madeleine K., and Waikar, Sushrut S.

Published
2024
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22. Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteins on cardiovascular and non-cardiovascular outcomes

Author

Schmidt, Amand F., Joshi, Roshni, Gordillo-Marañón, Maria, Drenos, Fotios, Charoen, Pimphen, Giambartolomei, Claudia, Bis, Joshua C., Gaunt, Tom R., Hughes, Alun D., Lawlor, Deborah A., Wong, Andrew, Price, Jackie F., Chaturvedi, Nishi, Wannamethee, Goya, Franceschini, Nora, Kivimaki, Mika, Hingorani, Aroon D., and Finan, Chris

Published
2023
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23. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author

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

Published
2024
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24. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood

Author

Kurniansyah, Nuzulul, Goodman, Matthew O, Kelly, Tanika N, Elfassy, Tali, Wiggins, Kerri L, Bis, Joshua C, Guo, Xiuqing, Palmas, Walter, Taylor, Kent D, Lin, Henry J, Haessler, Jeffrey, Gao, Yan, Shimbo, Daichi, Smith, Jennifer A, Yu, Bing, Feofanova, Elena V, Smit, Roelof AJ, Wang, Zhe, Hwang, Shih-Jen, Liu, Simin, Wassertheil-Smoller, Sylvia, Manson, JoAnn E, Lloyd-Jones, Donald M, Rich, Stephen S, Loos, Ruth JF, Redline, Susan, Correa, Adolfo, Kooperberg, Charles, Fornage, Myriam, Kaplan, Robert C, Psaty, Bruce M, Rotter, Jerome I, Arnett, Donna K, Morrison, Alanna C, Franceschini, Nora, Levy, Daniel, and Sofer, Tamar

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Hypertension, Human Genome, Prevention, Cardiovascular, Aging, Aetiology, 2.1 Biological and endogenous factors, Adult, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Prevalence, Risk Factors, NHLBI Trans-Omics in Precision Medicine (TOPMed) Consortium
Abstract

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

Published
2022

25. Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci

Author

Breeze, Charles E, Batorsky, Anna, Lee, Mi Kyeong, Szeto, Mindy D, Xu, Xiaoguang, McCartney, Daniel L, Jiang, Rong, Patki, Amit, Kramer, Holly J, Eales, James M, Raffield, Laura, Lange, Leslie, Lange, Ethan, Durda, Peter, Liu, Yongmei, Tracy, Russ P, Van Den Berg, David, Evans, Kathryn L, Kraus, William E, Shah, Svati, Tiwari, Hermant K, Hou, Lifang, Whitsel, Eric A, Jiang, Xiao, Charchar, Fadi J, Baccarelli, Andrea A, Rich, Stephen S, Morris, Andrew P, Irvin, Marguerite R, Arnett, Donna K, Hauser, Elizabeth R, Rotter, Jerome I, Correa, Adolfo, Hayward, Caroline, Horvath, Steve, Marioni, Riccardo E, Tomaszewski, Maciej, Beck, Stephan, Berndt, Sonja I, London, Stephanie J, Mychaleckyj, Josyf C, and Franceschini, Nora

Subjects
Biological Sciences, Genetics, Kidney Disease, Human Genome, Renal and urogenital, CpG Islands, DNA Methylation, Epigenesis, Genetic, Epigenomics, Gene Expression Regulation, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Glomerular Filtration Rate, Humans, Kidney, Kidney Function Tests, Phenotype, Quantitative Trait Loci, Quantitative Trait, Heritable, Racial Groups, Epigenetic, Kidney function, Gene regulation, Kidney development, DNA methylation, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed MESA Multi-Omics Working Group, Clinical Sciences
Abstract

BackgroundDNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach.MethodsThe study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses.ResultsWe identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development.ConclusionsWe uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.

Published
2021

26. Multi-ancestry genome-wide gene–sleep interactions identify novel loci for blood pressure

Author

Wang, Heming, Noordam, Raymond, Cade, Brian E, Schwander, Karen, Winkler, Thomas W, Lee, Jiwon, Sung, Yun Ju, Bentley, Amy R, Manning, Alisa K, Aschard, Hugues, Kilpeläinen, Tuomas O, Ilkov, Marjan, Brown, Michael R, Horimoto, Andrea R, Richard, Melissa, Bartz, Traci M, Vojinovic, Dina, Lim, Elise, Nierenberg, Jovia L, Liu, Yongmei, Chitrala, Kumaraswamynaidu, Rankinen, Tuomo, Musani, Solomon K, Franceschini, Nora, Rauramaa, Rainer, Alver, Maris, Zee, Phyllis C, Harris, Sarah E, van der Most, Peter J, Nolte, Ilja M, Munroe, Patricia B, Palmer, Nicholette D, Kühnel, Brigitte, Weiss, Stefan, Wen, Wanqing, Hall, Kelly A, Lyytikäinen, Leo-Pekka, O’Connell, Jeff, Eiriksdottir, Gudny, Launer, Lenore J, de Vries, Paul S, Arking, Dan E, Chen, Han, Boerwinkle, Eric, Krieger, Jose E, Schreiner, Pamela J, Sidney, Stephen, Shikany, James M, Rice, Kenneth, Chen, Yii-Der Ida, Gharib, Sina A, Bis, Joshua C, Luik, Annemarie I, Ikram, M Arfan, Uitterlinden, André G, Amin, Najaf, Xu, Hanfei, Levy, Daniel, He, Jiang, Lohman, Kurt K, Zonderman, Alan B, Rice, Treva K, Sims, Mario, Wilson, Gregory, Sofer, Tamar, Rich, Stephen S, Palmas, Walter, Yao, Jie, Guo, Xiuqing, Rotter, Jerome I, Biermasz, Nienke R, Mook-Kanamori, Dennis O, Martin, Lisa W, Barac, Ana, Wallace, Robert B, Gottlieb, Daniel J, Komulainen, Pirjo, Heikkinen, Sami, Mägi, Reedik, Milani, Lili, Metspalu, Andres, Starr, John M, Milaneschi, Yuri, Waken, RJ, Gao, Chuan, Waldenberger, Melanie, Peters, Annette, Strauch, Konstantin, Meitinger, Thomas, Roenneberg, Till, Völker, Uwe, Dörr, Marcus, Shu, Xiao-Ou, Mukherjee, Sutapa, Hillman, David R, Kähönen, Mika, Wagenknecht, Lynne E, Gieger, Christian, Grabe, Hans J, and Zheng, Wei

Subjects
Human Genome, Sleep Research, Clinical Research, Biotechnology, Hypertension, Genetics, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Blood Pressure, Genetic Loci, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Sleep, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint

Published
2021

27. 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

28. Advancing Genetic Testing in Kidney Diseases: Report From a National Kidney Foundation Working Group

Author

Ars, Elisabet, Reza Bekheirnia, Mir, Bier, Louise, Bleyer, Anthony J., Sr., Fuller, Lindsey J., Halbritter, Jan, Harris, Peter C., Kiryluk, Krzysztof, Knoers, Nine V.A.M., Kopp, Jeffrey B., Kramer, Holly, Lagas, Sharon S., Lieske, John C., Lu, Weining, Mannon, Roslyn B., Markowitz, Glen, Moe, Orson W., Nadkarni, Girish N., Nast, Cynthia C., Parekh, Rulan S., Pei, York, Reed, Katie, Rehm, Heidi L., Richards, Denay J., Roberts, Mary-Beth, Sabatello, Maya, Salant, David J., Sampson, Matthew G., Sanna-Cherchi, Simone, Santoriello, Dominick, Sedor, John R., Sneddon, Tam P., Watnick, Terry, Wilfond, Benjamin S., Williams, Winfred W., Wong, Craig S., Franceschini, Nora, Feldman, David L., Berg, Jonathan S., Besse, Whitney, Chang, Alexander R., Dahl, Neera K., Gbadegesin, Rasheed, Pollak, Martin R., Rasouly, Hila Milo, Smith, Richard J.H., Winkler, Cheryl A., and Gharavi, Ali G.

Published
2024
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29. Genetic insights into biological mechanisms governing human ovarian ageing

Author

Ruth, Katherine S, Day, Felix R, Hussain, Jazib, Martínez-Marchal, Ana, Aiken, Catherine E, Azad, Ajuna, Thompson, Deborah J, Knoblochova, Lucie, Abe, Hironori, Tarry-Adkins, Jane L, Gonzalez, Javier Martin, Fontanillas, Pierre, Claringbould, Annique, Bakker, Olivier B, Sulem, Patrick, Walters, Robin G, Terao, Chikashi, Turon, Sandra, Horikoshi, Momoko, Lin, Kuang, Onland-Moret, N Charlotte, Sankar, Aditya, Hertz, Emil Peter Thrane, Timshel, Pascal N, Shukla, Vallari, Borup, Rehannah, Olsen, Kristina W, Aguilera, Paula, Ferrer-Roda, Mònica, Huang, Yan, Stankovic, Stasa, Timmers, Paul RHJ, Ahearn, Thomas U, Alizadeh, Behrooz Z, Naderi, Elnaz, Andrulis, Irene L, Arnold, Alice M, Aronson, Kristan J, Augustinsson, Annelie, Bandinelli, Stefania, Barbieri, Caterina M, Beaumont, Robin N, Becher, Heiko, Beckmann, Matthias W, Benonisdottir, Stefania, Bergmann, Sven, Bochud, Murielle, Boerwinkle, Eric, Bojesen, Stig E, Bolla, Manjeet K, Boomsma, Dorret I, Bowker, Nicholas, Brody, Jennifer A, Broer, Linda, Buring, Julie E, Campbell, Archie, Campbell, Harry, Castelao, Jose E, Catamo, Eulalia, Chanock, Stephen J, Chenevix-Trench, Georgia, Ciullo, Marina, Corre, Tanguy, Couch, Fergus J, Cox, Angela, Crisponi, Laura, Cross, Simon S, Cucca, Francesco, Czene, Kamila, Smith, George Davey, de Geus, Eco JCN, de Mutsert, Renée, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Dunning, Alison M, Dwek, Miriam, Eriksson, Mikael, Esko, Tõnu, Fasching, Peter A, Faul, Jessica D, Ferrucci, Luigi, Franceschini, Nora, Frayling, Timothy M, Gago-Dominguez, Manuela, Mezzavilla, Massimo, García-Closas, Montserrat, Gieger, Christian, Giles, Graham G, Grallert, Harald, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hayward, Caroline, He, Chunyan, He, Wei, and Heiss, Gerardo

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Estrogen, Prevention, Women's Health, Contraception/Reproduction, Aging, Infertility, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Good Health and Well Being, Adult, Alleles, Animals, Bone and Bones, Checkpoint Kinase 1, Checkpoint Kinase 2, Diabetes Mellitus, Type 2, Diet, Europe, Asia, Eastern, Female, Fertility, Fragile X Mental Retardation Protein, Genetic Predisposition to Disease, Genome-Wide Association Study, Healthy Aging, Humans, Longevity, Menopause, Menopause, Premature, Mice, Mice, Inbred C57BL, Middle Aged, Ovary, Primary Ovarian Insufficiency, Uterus, Biobank-based Integrative Omics Study (BIOS) Consortium, eQTLGen Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, kConFab Investigators, LifeLines Cohort Study, InterAct consortium, 23andMe Research Team, General Science & Technology
Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Published
2021

30. 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

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

Author

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

Published
2023
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33. 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

34. When the At-Risk Do Not Develop Heart Failure: Understanding Positive Deviance Among Postmenopausal African American and Hispanic Women

Author

Breathett, Khadijah, Kohler, Lindsay N, Eaton, Charles B, Franceschini, Nora, Garcia, Lorena, Klein, Liviu, Martin, Lisa W, Ochs-Balcom, Heather M, Shadyab, Aladdin H, and Cené, Crystal W

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Aging, Heart Disease, Clinical Research, Cardiovascular, Black or African American, Ethnicity, Female, Heart Failure, Hispanic or Latino, Humans, Postmenopause, Risk Factors, Heart failure, racial disparities, women, Cardiorespiratory Medicine and Haematology, Nursing, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

BackgroundAfrican American and Hispanic postmenopausal women have the highest risk for heart failure compared with other races, but heart failure prevalence is lower than expected in some national cohorts. It is unknown whether psychosocial factors are associated with lower risk of incident heart failure hospitalization among high-risk postmenopausal minority women.Methods and resultsUsing the Women's Health Initiative Study, African American and US Hispanic women were classified as high-risk for incident heart failure hospitalization with 1 or more traditional heart failure risk factors and the highest tertile heart failure genetic risk scores. Positive psychosocial factors (optimism, social support, religion) and negative psychosocial factors (living alone, social strain, depressive symptoms) were measured using validated survey instruments at baseline. Adjusted subdistribution hazard ratios of developing heart failure hospitalization were determined with death as a competing risk. Positive deviance indicated not developing incident heart failure hospitalization with 1 or more risk factors and the highest tertile for genetic risk. Among 7986 African American women (mean follow-up of 16 years), 27.0% demonstrated positive deviance. Among high-risk African American women, optimism was associated with modestly reduced risk of heart failure hospitalization (subdistribution hazard ratio 0.94, 95% confidence interval 0.91-0.99), and social strain was associated with modestly increased risk of heart failure hospitalization (subdistribution hazard ratio 1.07, 95% confidence interval 1.02-1.12) in the initial models; however, no psychosocial factors were associated with heart failure hospitalization in fully adjusted analyses. Among 3341 Hispanic women, 25.1% demonstrated positive deviance. Among high-risk Hispanic women, living alone was associated with increased risk of heart failure hospitalization (subdistribution hazard ratio 1.97, 95% confidence interval 1.06-3.63) in unadjusted analyses; however, no psychosocial factors were associated with heart failure hospitalization in fully adjusted analyses.ConclusionsAmong postmenopausal African American and Hispanic women, a significant proportion remained free from heart failure hospitalization despite having the highest genetic risk profile and 1 or more traditional risk factors. No observed psychosocial factors were associated with incident heart failure hospitalization in high-risk African Americans and Hispanics. Additional investigation is needed to understand protective factors among high-risk African American and Hispanic women.

Published
2021

35. 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

36. 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

37. 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

38. Genome-wide association study identifies novel loci for type 2 diabetes-attributed end-stage kidney disease in African Americans

Author

Guan, Meijian, Keaton, Jacob M, Dimitrov, Latchezar, Hicks, Pamela J, Xu, Jianzhao, Palmer, Nicholette D, Ma, Lijun, Das, Swapan K, Chen, Yii-Der I, Coresh, Josef, Fornage, Myriam, Franceschini, Nora, Kramer, Holly, Langefeld, Carl D, Mychaleckyj, Josyf C, Parekh, Rulan S, Post, Wendy S, Rasmussen-Torvik, Laura J, Rich, Stephen S, Rotter, Jerome I, Sedor, John R, Thornley-Brown, Denyse, Tin, Adrienne, Wilson, James G, Freedman, Barry I, Bowden, Donald W, and Ng, Maggie CY

Subjects
Biological Sciences, Genetics, Human Genome, Diabetes, Prevention, Kidney Disease, 2.1 Biological and endogenous factors, Aetiology, Renal and urogenital, Metabolic and endocrine, Good Health and Well Being, African Americans, Genome-wide association study, Type 2 diabetes, Diabetic kidney disease, End-stage kidney disease, FIND Consortium, Genetics & Heredity, Biochemistry and cell biology
Abstract

BackgroundEnd-stage kidney disease (ESKD) is a significant public health concern disproportionately affecting African Americans (AAs). Type 2 diabetes (T2D) is the leading cause of ESKD in the USA, and efforts to uncover genetic susceptibility to diabetic kidney disease (DKD) have had limited success. A prior genome-wide association study (GWAS) in AAs with T2D-ESKD was expanded with additional AA cases and controls and genotypes imputed to the higher density 1000 Genomes reference panel. The discovery analysis included 3432 T2D-ESKD cases and 6977 non-diabetic non-nephropathy controls (N = 10,409), followed by a discrimination analysis in 2756 T2D non-nephropathy controls to exclude T2D-associated variants.ResultsSix independent variants located in or near RND3/RBM43, SLITRK3, ENPP7, GNG7, and APOL1 achieved genome-wide significant association (P

Published
2019

40. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Author

Noordam, Raymond, Bos, Maxime M, Wang, Heming, Winkler, Thomas W, Bentley, Amy R, Kilpeläinen, Tuomas O, de Vries, Paul S, Sung, Yun Ju, Schwander, Karen, Cade, Brian E, Manning, Alisa, Aschard, Hugues, Brown, Michael R, Chen, Han, Franceschini, Nora, Musani, Solomon K, Richard, Melissa, Vojinovic, Dina, Aslibekyan, Stella, Bartz, Traci M, de Las Fuentes, Lisa, Feitosa, Mary, Horimoto, Andrea R, Ilkov, Marjan, Kho, Minjung, Kraja, Aldi, Li, Changwei, Lim, Elise, Liu, Yongmei, Mook-Kanamori, Dennis O, Rankinen, Tuomo, Tajuddin, Salman M, van der Spek, Ashley, Wang, Zhe, Marten, Jonathan, Laville, Vincent, Alver, Maris, Evangelou, Evangelos, Graff, Maria E, He, Meian, Kühnel, Brigitte, Lyytikäinen, Leo-Pekka, Marques-Vidal, Pedro, Nolte, Ilja M, Palmer, Nicholette D, Rauramaa, Rainer, Shu, Xiao-Ou, Snieder, Harold, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Adolfo, Correa, Ballantyne, Christie, Bielak, Larry, Biermasz, Nienke R, Boerwinkle, Eric, Dimou, Niki, Eiriksdottir, Gudny, Gao, Chuan, Gharib, Sina A, Gottlieb, Daniel J, Haba-Rubio, José, Harris, Tamara B, Heikkinen, Sami, Heinzer, Raphaël, Hixson, James E, Homuth, Georg, Ikram, M Arfan, Komulainen, Pirjo, Krieger, Jose E, Lee, Jiwon, Liu, Jingmin, Lohman, Kurt K, Luik, Annemarie I, Mägi, Reedik, Martin, Lisa W, Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Nalls, Mike A, O'Connell, Jeff, Peters, Annette, Peyser, Patricia, Raitakari, Olli T, Reiner, Alex P, Rensen, Patrick CN, Rice, Treva K, Rich, Stephen S, Roenneberg, Till, Rotter, Jerome I, Schreiner, Pamela J, Shikany, James, Sidney, Stephen S, Sims, Mario, Sitlani, Colleen M, Sofer, Tamar, Strauch, Konstantin, Swertz, Morris A, Taylor, Kent D, and Uitterlinden, André G

Subjects
Humans, Lipids, Chromosome Mapping, Sleep, Phylogeny, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Young Adult, Genetic Loci, Polymorphism, Single Nucleotide, and over
Abstract

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

Published
2019

41. HDAC9 is implicated in atherosclerotic aortic calcification and affects vascular smooth muscle cell phenotype

Author

Malhotra, Rajeev, Mauer, Andreas C, Lino Cardenas, Christian L, Guo, Xiuqing, Yao, Jie, Zhang, Xiaoling, Wunderer, Florian, Smith, Albert V, Wong, Quenna, Pechlivanis, Sonali, Hwang, Shih-Jen, Wang, Judy, Lu, Lingyi, Nicholson, Christopher J, Shelton, Georgia, Buswell, Mary D, Barnes, Hanna J, Sigurslid, Haakon H, Slocum, Charles, Rourke, Caitlin O’, Rhee, David K, Bagchi, Aranya, Nigwekar, Sagar U, Buys, Emmanuel S, Campbell, Catherine Y, Harris, Tamara, Budoff, Matthew, Criqui, Michael H, Rotter, Jerome I, Johnson, Andrew D, Song, Ci, Franceschini, Nora, Debette, Stephanie, Hoffmann, Udo, Kälsch, Hagen, Nöthen, Markus M, Sigurdsson, Sigurdur, Freedman, Barry I, Bowden, Donald W, Jöckel, Karl-Heinz, Moebus, Susanne, Erbel, Raimund, Feitosa, Mary F, Gudnason, Vilmundur, Thanassoulis, George, Zapol, Warren M, Lindsay, Mark E, Bloch, Donald B, Post, Wendy S, and O’Donnell, Christopher J

Subjects
Biological Sciences, Genetics, Human Genome, Heart Disease - Coronary Heart Disease, Heart Disease, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Aged, Animals, Aorta, Atherosclerosis, Cohort Studies, Female, GTPase-Activating Proteins, Genetic Predisposition to Disease, Genome-Wide Association Study, Histone Deacetylases, Humans, Male, Mice, Mice, Inbred C57BL, Mice, Knockout, Middle Aged, Muscle Contraction, Muscle, Smooth, Vascular, Phenotype, Polymorphism, Single Nucleotide, Repressor Proteins, Vascular Calcification, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Aortic calcification is an important independent predictor of future cardiovascular events. We performed a genome-wide association meta-analysis to determine SNPs associated with the extent of abdominal aortic calcification (n = 9,417) or descending thoracic aortic calcification (n = 8,422). Two genetic loci, HDAC9 and RAP1GAP, were associated with abdominal aortic calcification at a genome-wide level (P

Published
2019

42. Variants Associated with the Ankle Brachial Index Differ by Hispanic/Latino Ethnic Group: a genome-wide association study in the Hispanic Community Health Study/Study of Latinos.

Author

Sofer, Tamar, Emery, Leslie, Jain, Deepti, Ellis, Alicia M, Laurie, Cathy C, Allison, Matthew A, Lee, Jiwon, Kurniansyah, Nuzulul, Kerr, Kathleen F, González, Hector M, Tarraf, Wassim, Criqui, Michael H, Lange, Leslie A, Palmas, Walter R, Franceschini, Nora, and Wassel, Christina L

Subjects
Humans, Genetic Predisposition to Disease, Intracellular Signaling Peptides and Proteins, Dystrophin, Prospective Studies, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Middle Aged, African Americans, European Continental Ancestry Group, Hispanic Americans, United States, Female, Male, Genome-Wide Association Study, Ankle Brachial Index, Young Adult, Genetic Loci, Peripheral Arterial Disease, Polymorphism, Single Nucleotide
Abstract

Lower extremity peripheral artery disease (PAD) burden differs by race/ethnicity. Although familial aggregation and heritability studies suggest a genetic basis, little is known about the genetic susceptibility to PAD, especially in non-European descent populations. Genome-wide association studies (GWAS) of the ankle brachial index (ABI) and PAD (defined as an ABI 45 years from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We also performed GWAS for ABI stratified by Hispanic/Latino ethnic subgroups: Central American, Mexican, and South American (Mainland group), and Cuban, Dominican, and Puerto Rican (Caribbean group). We detected two genome-wide significant associations for the ABI in COMMD10 in Puerto Ricans, and at SYBU in the Caribbean group. The lead SNP rs4466200 in the COMMD10 gene had a replication p = 0.02 for the ABI in Multi-Ethnic Study of Atherosclerosis (MESA) African Americans, but it did not replicate in African Americans from the Cardiovascular Health Study (CHS). In a regional look-up, a nearby SNP rs12520838 had Bonferroni adjusted p = 0.05 (unadjusted p = 7.5 × 10-5) for PAD in MESA Hispanics. Among three suggestive associations (p

Published
2019

43. Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

Author

de Vries, Paul S, Brown, Michael R, Bentley, Amy R, Sung, Yun J, Winkler, Thomas W, Ntalla, Ioanna, Schwander, Karen, Kraja, Aldi T, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E, Musani, Solomon K, Li, Changwei, Feitosa, Mary F, Richard, Melissa A, Noordam, Raymond, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Deng, Xuan, Dorajoo, Rajkumar, Lohman, Kurt K, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Evangelou, Evangelos, Graff, Mariaelisa, Alver, Maris, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gandin, Ilaria, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea RVR, Hsu, Fang-Chi, Jackson, Anne U, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Lee, Joseph H, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M, Pietzner, Maik, Riaz, Muhammad, Said, M Abdullah, Scott, Robert A, Sofer, Tamar, Stančáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Wang, Yajuan, Ware, Erin B, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Aung, Tin, Ballantyne, Christie, Boerwinkle, Eric, Broeckel, Ulrich, Campbell, Archie, Canouil, Mickaël, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Connell, John M, de Faire, Ulf, de las Fuentes, Lisa, de Mutsert, Renée, de Silva, H Janaka, Ding, Jingzhong, Dominiczak, Anna F, Duan, Qing, Eaton, Charles B, Eppinga, Ruben N, Faul, Jessica D, Fisher, Virginia, Forrester, Terrence, Franco, Oscar H, Friedlander, Yechiel, Ghanbari, Mohsen, and Giulianini, Franco

Subjects
Epidemiology, Health Sciences, Substance Misuse, Alcoholism, Alcohol Use and Health, Human Genome, Prevention, Genetics, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Adolescent, Adult, Aged, Alcohol Drinking, Cholesterol, HDL, Cholesterol, LDL, Female, Genome-Wide Association Study, Genotype, Humans, Life Style, Lipids, Male, Middle Aged, Phenotype, Racial Groups, Triglycerides, Vascular Endothelial Growth Factor B, Young Adult, alcohol consumption, cholesterol, gene-environment interactions, gene-lifestyle interactions, genome-wide association studies, lipids, triglycerides, InterAct Consortium, Lifelines Cohort, Groningen, The Netherlands, Mathematical Sciences, Medical and Health Sciences
Abstract

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.

Published
2019

44. 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

45. Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Author

Kilpeläinen, Tuomas O, Bentley, Amy R, Noordam, Raymond, Sung, Yun Ju, Schwander, Karen, Winkler, Thomas W, Jakupović, Hermina, Chasman, Daniel I, Manning, Alisa, Ntalla, Ioanna, Aschard, Hugues, Brown, Michael R, de Las Fuentes, Lisa, Franceschini, Nora, Guo, Xiuqing, Vojinovic, Dina, Aslibekyan, Stella, Feitosa, Mary F, Kho, Minjung, Musani, Solomon K, Richard, Melissa, Wang, Heming, Wang, Zhe, Bartz, Traci M, Bielak, Lawrence F, Campbell, Archie, Dorajoo, Rajkumar, Fisher, Virginia, Hartwig, Fernando P, Horimoto, Andrea RVR, Li, Changwei, Lohman, Kurt K, Marten, Jonathan, Sim, Xueling, Smith, Albert V, Tajuddin, Salman M, Alver, Maris, Amini, Marzyeh, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Evangelou, Evangelos, Gao, Chuan, Graff, Mariaelisa, Harris, Sarah E, He, Meian, Hsu, Fang-Chi, Jackson, Anne U, Zhao, Jing Hua, Kraja, Aldi T, Kühnel, Brigitte, Laguzzi, Federica, Lyytikäinen, Leo-Pekka, Nolte, Ilja M, Rauramaa, Rainer, Riaz, Muhammad, Robino, Antonietta, Rueedi, Rico, Stringham, Heather M, Takeuchi, Fumihiko, van der Most, Peter J, Varga, Tibor V, Verweij, Niek, Ware, Erin B, Wen, Wanqing, Li, Xiaoyin, Yanek, Lisa R, Amin, Najaf, Arnett, Donna K, Boerwinkle, Eric, Brumat, Marco, Cade, Brian, Canouil, Mickaël, Chen, Yii-Der Ida, Concas, Maria Pina, Connell, John, de Mutsert, Renée, de Silva, H Janaka, de Vries, Paul S, Demirkan, Ayşe, Ding, Jingzhong, Eaton, Charles B, Faul, Jessica D, Friedlander, Yechiel, Gabriel, Kelley P, Ghanbari, Mohsen, Giulianini, Franco, Gu, Chi Charles, Gu, Dongfeng, Harris, Tamara B, He, Jiang, Heikkinen, Sami, Heng, Chew-Kiat, Hunt, Steven C, Ikram, M Arfan, Jonas, Jost B, Koh, Woon-Puay, Komulainen, Pirjo, and Krieger, Jose E

Subjects
Lifelines Cohort Study, Humans, Cholesterol, Lipids, Triglycerides, Calcium-Binding Proteins, Muscle Proteins, Microtubule-Associated Proteins, Membrane Proteins, Nerve Tissue Proteins, Transcription Factors, Exercise, Genotype, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, African Continental Ancestry Group, Asian Continental Ancestry Group, European Continental Ancestry Group, Hispanic Americans, Brazil, Female, Male, Lipid Metabolism, Cholesterol, LDL, Cholesterol, HDL, Genome-Wide Association Study, Young Adult, Genetic Loci, LIM-Homeodomain Proteins, and over, HDL, LDL
Abstract

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

Published
2019

46. Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies.

Author

Morris, Andrew P, Le, Thu H, Wu, Haojia, Akbarov, Artur, van der Most, Peter J, Hemani, Gibran, Smith, George Davey, Mahajan, Anubha, Gaulton, Kyle J, Nadkarni, Girish N, Valladares-Salgado, Adan, Wacher-Rodarte, Niels, Mychaleckyj, Josyf C, Dueker, Nicole D, Guo, Xiuqing, Hai, Yang, Haessler, Jeffrey, Kamatani, Yoichiro, Stilp, Adrienne M, Zhu, Gu, Cook, James P, Ärnlöv, Johan, Blanton, Susan H, de Borst, Martin H, Bottinger, Erwin P, Buchanan, Thomas A, Cechova, Sylvia, Charchar, Fadi J, Chu, Pei-Lun, Damman, Jeffrey, Eales, James, Gharavi, Ali G, Giedraitis, Vilmantas, Heath, Andrew C, Ipp, Eli, Kiryluk, Krzysztof, Kramer, Holly J, Kubo, Michiaki, Larsson, Anders, Lindgren, Cecilia M, Lu, Yingchang, Madden, Pamela AF, Montgomery, Grant W, Papanicolaou, George J, Raffel, Leslie J, Sacco, Ralph L, Sanchez, Elena, Stark, Holger, Sundstrom, Johan, Taylor, Kent D, Xiang, Anny H, Zivkovic, Aleksandra, Lind, Lars, Ingelsson, Erik, Martin, Nicholas G, Whitfield, John B, Cai, Jianwen, Laurie, Cathy C, Okada, Yukinori, Matsuda, Koichi, Kooperberg, Charles, Chen, Yii-Der Ida, Rundek, Tatjana, Rich, Stephen S, Loos, Ruth JF, Parra, Esteban J, Cruz, Miguel, Rotter, Jerome I, Snieder, Harold, Tomaszewski, Maciej, Humphreys, Benjamin D, and Franceschini, Nora

Subjects
Kidney, Humans, Kidney Calculi, Hypertension, Histones, Glomerular Filtration Rate, Histone Code, Blood Pressure, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, Ethnic Groups, Female, Male, Renal Insufficiency, Chronic, Genome-Wide Association Study, Genetic Loci, Polymorphism, Single Nucleotide, Renal Insufficiency, Chronic
Abstract

Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assemble genome-wide association studies of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals of diverse ancestry. We identify 127 distinct association signals with homogeneous effects on eGFR across ancestries and enrichment in genomic annotations including kidney-specific histone modifications. Fine-mapping reveals 40 high-confidence variants driving eGFR associations and highlights putative causal genes with cell-type specific expression in glomerulus, and in proximal and distal nephron. Mendelian randomisation supports causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure and hypertension. These results define novel molecular mechanisms and putative causal genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

Published
2019

47. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.

Author

Franceschini, Nora, Giambartolomei, Claudia, de Vries, Paul S, Finan, Chris, Bis, Joshua C, Huntley, Rachael P, Lovering, Ruth C, Tajuddin, Salman M, Winkler, Thomas W, Graff, Misa, Kavousi, Maryam, Dale, Caroline, Smith, Albert V, Hofer, Edith, van Leeuwen, Elisabeth M, Nolte, Ilja M, Lu, Lingyi, Scholz, Markus, Sargurupremraj, Muralidharan, Pitkänen, Niina, Franzén, Oscar, Joshi, Peter K, Noordam, Raymond, Marioni, Riccardo E, Hwang, Shih-Jen, Musani, Solomon K, Schminke, Ulf, Palmas, Walter, Isaacs, Aaron, Correa, Adolfo, Zonderman, Alan B, Hofman, Albert, Teumer, Alexander, Cox, Amanda J, Uitterlinden, André G, Wong, Andrew, Smit, Andries J, Newman, Anne B, Britton, Annie, Ruusalepp, Arno, Sennblad, Bengt, Hedblad, Bo, Pasaniuc, Bogdan, Penninx, Brenda W, Langefeld, Carl D, Wassel, Christina L, Tzourio, Christophe, Fava, Cristiano, Baldassarre, Damiano, O'Leary, Daniel H, Teupser, Daniel, Kuh, Diana, Tremoli, Elena, Mannarino, Elmo, Grossi, Enzo, Boerwinkle, Eric, Schadt, Eric E, Ingelsson, Erik, Veglia, Fabrizio, Rivadeneira, Fernando, Beutner, Frank, Chauhan, Ganesh, Heiss, Gerardo, Snieder, Harold, Campbell, Harry, Völzke, Henry, Markus, Hugh S, Deary, Ian J, Jukema, J Wouter, de Graaf, Jacqueline, Price, Jacqueline, Pott, Janne, Hopewell, Jemma C, Liang, Jingjing, Thiery, Joachim, Engmann, Jorgen, Gertow, Karl, Rice, Kenneth, Taylor, Kent D, Dhana, Klodian, Kiemeney, Lambertus ALM, Lind, Lars, Raffield, Laura M, Launer, Lenore J, Holdt, Lesca M, Dörr, Marcus, Dichgans, Martin, Traylor, Matthew, Sitzer, Matthias, Kumari, Meena, Kivimaki, Mika, Nalls, Mike A, Melander, Olle, Raitakari, Olli, Franco, Oscar H, Rueda-Ochoa, Oscar L, Roussos, Panos, Whincup, Peter H, Amouyel, Philippe, and Giral, Philippe

Subjects
MEGASTROKE Consortium, Humans, Coronary Disease, Genetic Predisposition to Disease, Amino Acid Oxidoreductases, Protein-Lysine 6-Oxidase, Risk Factors, Lod Score, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Plaque, Atherosclerotic, Carotid Intima-Media Thickness, ADAMTS9 Protein, Plaque, Atherosclerotic, Polymorphism, Single Nucleotide
Abstract

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Published
2018

49. Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Author

Köttgen, Anna, Cornec-Le Gall, Emilie, Halbritter, Jan, Kiryluk, Krzysztof, Mallett, Andrew J., Parekh, Rulan S., Rasouly, Hila Milo, Sampson, Matthew G., Tin, Adrienne, Antignac, Corinne, Ars, Elisabet, Bergmann, Carsten, Bleyer, Anthony J., Bockenhauer, Detlef, Devuyst, Olivier, Florez, Jose C., Fowler, Kevin J., Franceschini, Nora, Fukagawa, Masafumi, Gale, Daniel P., Gbadegesin, Rasheed A., Goldstein, David B., Grams, Morgan E., Greka, Anna, Gross, Oliver, Guay-Woodford, Lisa M., Harris, Peter C., Hoefele, Julia, Hung, Adriana M., Knoers, Nine V.A.M., Kopp, Jeffrey B., Kretzler, Matthias, Lanktree, Matthew B., Lipska-Ziętkiewicz, Beata S., Nicholls, Kathleen, Nozu, Kandai, Ojo, Akinlolu, Parsa, Afshin, Pattaro, Cristian, Pei, York, Pollak, Martin R., Rhee, Eugene P., Sanna-Cherchi, Simone, Savige, Judy, Sayer, John A., Scolari, Francesco, Sedor, John R., Sim, Xueling, Somlo, Stefan, Susztak, Katalin, Tayo, Bamidele O., Torra, Roser, van Eerde, Albertien M., Weinstock, André, Winkler, Cheryl A., Wuttke, Matthias, Zhang, Hong, King, Jennifer M., Cheung, Michael, Jadoul, Michel, Winkelmayer, Wolfgang C., and Gharavi, Ali G.

Published
2022
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