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

Author: Mack, Taralynn M, Raddatz, Michael A, Pershad, Yash, Nachun, Daniel C, Taylor, Kent D, Guo, Xiuqing, Shuldiner, Alan R, O’Connell, Jeffrey R, Kenny, Eimear E, Loos, Ruth JF, Redline, Susan, Cade, Brian E, Psaty, Bruce M, Bis, Joshua C, Brody, Jennifer A, Silverman, Edwin K, Yun, Jeong H, Cho, Michael H, DeMeo, Dawn L, Levy, Daniel, Johnson, Andrew D, Mathias, Rasika A, Yanek, Lisa R, Heckbert, Susan R, Smith, Nicholas L, Wiggins, Kerri L, Raffield, Laura M, Carson, April P, Rotter, Jerome I, Rich, Stephen S, Manichaikul, Ani W, Gu, C Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M Benjamin, Roden, Dan M, Kooperberg, Charles, Auer, Paul L, Desai, Pinkal, Blackwell, Thomas W, Smith, Albert V, Reiner, Alexander P, Jaiswal, Siddhartha, Weinstock, Joshua S, and Bick, Alexander G
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Hematology, Genetics, Biotechnology, Aging, Human Genome, Stem Cell Research, Precision Medicine, Aetiology, 2.1 Biological and endogenous factors, Cancer, Good Health and Well Being, Clinical sciences
Abstract: Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.
Published: 2024

2. Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

Author: Liu, Shuai, Zhu, Jingjing, Zhong, Hua, Wu, Chong, Xue, Haoran, Darst, Burcu F., Guo, Xiuqing, Durda, Peter, Tracy, Russell P., Liu, Yongmei, Johnson, W. Craig, Taylor, Kent D., Manichaikul, Ani W., Goodarzi, Mark O., Gerszten, Robert E., Clish, Clary B., Chen, Yii-Der Ida, Highland, Heather, Haiman, Christopher A., Gignoux, Christopher R., Lange, Leslie, Conti, David V., Raffield, Laura M., Wilkens, Lynne, Marchand, Loïc Le, North, Kari E., Young, Kristin L., Loos, Ruth J., Buyske, Steve, Matise, Tara, Peters, Ulrike, Kooperberg, Charles, Reiner, Alexander P., Yu, Bing, Boerwinkle, Eric, Sun, Quan, Rooney, Mary R., Echouffo-Tcheugui, Justin B., Daviglus, Martha L., Qi, Qibin, Mancuso, Nicholas, Li, Changwei, Deng, Youping, Manning, Alisa, Meigs, James B., Rich, Stephen S., Rotter, Jerome I., and Wu, Lang
Published: 2024
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3. Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate

Author: Mack, Taralynn M., Raddatz, Michael A., Pershad, Yash, Nachun, Daniel C., Taylor, Kent D., Guo, Xiuqing, Shuldiner, Alan R., O’Connell, Jeffrey R., Kenny, Eimear E., Loos, Ruth J. F., Redline, Susan, Cade, Brian E., Psaty, Bruce M., Bis, Joshua C., Brody, Jennifer A., Silverman, Edwin K., Yun, Jeong H., Cho, Michael H., DeMeo, Dawn L., Levy, Daniel, Johnson, Andrew D., Mathias, Rasika A., Yanek, Lisa R., Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Raffield, Laura M., Carson, April P., Rotter, Jerome I., Rich, Stephen S., Manichaikul, Ani W., Gu, C. Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Shoemaker, M. Benjamin, Roden, Dan M., Kooperberg, Charles, Auer, Paul L., Desai, Pinkal, Blackwell, Thomas W., Smith, Albert V., Reiner, Alexander P., Jaiswal, Siddhartha, Weinstock, Joshua S., and Bick, Alexander G.
Published: 2024
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4. Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes

Author: Keener, Rebecca, Chhetri, Surya B, Connelly, Carla J, Taub, Margaret A, Conomos, Matthew P, Weinstock, Joshua, Ni, Bohan, Strober, Benjamin, Aslibekyan, Stella, Auer, Paul L, Barwick, Lucas, Becker, Lewis C, Blangero, John, Bleecker, Eugene R, Brody, Jennifer A, Cade, Brian E, Celedon, Juan C, Chang, Yi-Cheng, Cupples, L Adrienne, Custer, Brian, Freedman, Barry I, Gladwin, Mark T, Heckbert, Susan R, Hou, Lifang, Irvin, Marguerite R, Isasi, Carmen R, Johnsen, Jill M, Kenny, Eimear E, Kooperberg, Charles, Minster, Ryan L, Naseri, Take, Viali, Satupa’itea, Nekhai, Sergei, Pankratz, Nathan, Peyser, Patricia A, Taylor, Kent D, Telen, Marilyn J, Wu, Baojun, Yanek, Lisa R, Yang, Ivana V, Albert, Christine, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Bis, Joshua C, Blackwell, Thomas W, Boerwinkle, Eric, Burchard, Esteban G, Carson, April P, Chen, Zhanghua, Chen, Yii-Der Ida, Darbar, Dawood, de Andrade, Mariza, Ellinor, Patrick T, Fornage, Myriam, Gelb, Bruce D, Gilliland, Frank D, He, Jiang, Islam, Talat, Kaab, Stefan, Kardia, Sharon LR, Kelly, Shannon, Konkle, Barbara A, Kumar, Rajesh, Loos, Ruth JF, Martinez, Fernando D, McGarvey, Stephen T, Meyers, Deborah A, Mitchell, Braxton D, Montgomery, Courtney G, North, Kari E, Palmer, Nicholette D, Peralta, Juan M, Raby, Benjamin A, Redline, Susan, Rich, Stephen S, Roden, Dan, Rotter, Jerome I, Ruczinski, Ingo, Schwartz, David, Sciurba, Frank, Shoemaker, M Benjamin, Silverman, Edwin K, Sinner, Moritz F, Smith, Nicholas L, Smith, Albert V, Tiwari, Hemant K, Vasan, Ramachandran S, Weiss, Scott T, Williams, L Keoki, Zhang, Yingze, Ziv, Elad, Raffield, Laura M, Reiner, Alexander P, Arvanitis, Marios, Greider, Carol W, Mathias, Rasika A, and Battle, Alexis
Subjects: Biological Sciences, Genetics, Human Genome, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Genome-Wide Association Study, Telomere, K562 Cells, Telomere Homeostasis, Polymorphism, Single Nucleotide, Gene Expression Regulation, CRISPR-Cas Systems, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
Abstract: Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.
Published: 2024

5. Heterogeneity-aware integrative regression for ancestry-specific association studies

Author: Molstad, Aaron J., Cai, Yanwei, Reiner, Alexander P., Kooperberg, Charles, Sun, Wei, and Hsu, Li
Subjects: Statistics - Applications, Statistics - Methodology
Abstract: Ancestry-specific proteome-wide association studies (PWAS) based on genetically predicted protein expression can reveal complex disease etiology specific to certain ancestral groups. These studies require ancestry-specific models for protein expression as a function of SNP genotypes. In order to improve protein expression prediction in ancestral populations historically underrepresented in genomic studies, we propose a new penalized maximum likelihood estimator for fitting ancestry-specific joint protein quantitative trait loci models. Our estimator borrows information across ancestral groups, while simultaneously allowing for heterogeneous error variances and regression coefficients. We propose an alternative parameterization of our model which makes the objective function convex and the penalty scale invariant. To improve computational efficiency, we propose an approximate version of our method and study its theoretical properties. Our method provides a substantial improvement in protein expression prediction accuracy in individuals of African ancestry, and in a downstream PWAS analysis, leads to the discovery of multiple associations between protein expression and blood lipid traits in the African ancestry population.
Published: 2023

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

Author: Jakubek, Yasminka, Zhou, Ying, Stilp, Adrienne, Bacon, Jason, Wong, Justin, Ozcan, Zuhal, Arnett, Donna, Barnes, Kathleen, Bis, Joshua, Boerwinkle, Eric, Brody, Jennifer, Carson, April, Chasman, Daniel, Chen, Jiawen, Cho, Michael, Conomos, Matthew, Cox, Nancy, Doyle, Margaret, Fornage, Myriam, Guo, Xiuqing, Kardia, Sharon, Lewis, Joshua, Loos, Ruth, Ma, Xiaolong, Machiela, Mitchell, Mack, Taralynn, Mathias, Rasika, Mitchell, Braxton, Mychaleckyj, Josyf, North, Kari, Pankratz, Nathan, Peyser, Patricia, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Vasan, Ramachandran, Redline, Susan, Rich, Stephen, Silverman, Edwin, Smith, Jennifer, Smith, Aaron, Taub, Margaret, Taylor, Kent, Yun, Jeong, Li, Yun, Desai, Pinkal, Bick, Alexander, Reiner, Alexander, Scheet, Paul, Auer, Paul, and Rotter, Jerome
Subjects: Humans, Black People, Genome-Wide Association Study, Hispanic or Latino, Precision Medicine, Mosaicism, Genome, Human
Abstract: Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.
Published: 2023

7. Association Between Whole Blood–Derived Mitochondrial DNA Copy Number, Low‐Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Author: Liu, Xue, Sun, Xianbang, Zhang, Yuankai, Jiang, Wenqing, Lai, Meng, Wiggins, Kerri L, Raffield, Laura M, Bielak, Lawrence F, Zhao, Wei, Pitsillides, Achilleas, Haessler, Jeffrey, Zheng, Yinan, Blackwell, Thomas W, Yao, Jie, Guo, Xiuqing, Qian, Yong, Thyagarajan, Bharat, Pankratz, Nathan, Rich, Stephen S, Taylor, Kent D, Peyser, Patricia A, Heckbert, Susan R, Seshadri, Sudha, Boerwinkle, Eric, Grove, Megan L, Larson, Nicholas B, Smith, Jennifer A, Vasan, Ramachandran S, Fitzpatrick, Annette L, Fornage, Myriam, Ding, Jun, Carson, April P, Abecasis, Goncalo, Dupuis, Josée, Reiner, Alexander, Kooperberg, Charles, Hou, Lifang, Psaty, Bruce M, Wilson, James G, Levy, Daniel, Rotter, Jerome I, Bis, Joshua C, Consortium, TOPMed mtDNA Working Group in NHLBI Trans‐Omics for Precision Medicine, Satizabal, Claudia L, Arking, Dan E, and Liu, Chunyu
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Obesity, Prevention, Heart Disease, Atherosclerosis, Heart Disease - Coronary Heart Disease, Aging, Cardiovascular, Genetics, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Humans, DNA, Mitochondrial, Risk Factors, Cardiovascular Diseases, Cholesterol, LDL, DNA Copy Number Variations, Cross-Sectional Studies, Coronary Disease, Cholesterol, HDL, Diabetes Mellitus, Hypertension, cardiometabolic risk factors, cardiovascular disease, low-density lipoprotein cholesterol, Mendelian randomization, mitochondrial DNA copy number, vascular atherosclerosis, TOPMed mtDNA Working Group in NHLBI Trans‐Omics for Precision Medicine (TOPMed) Consortium, low‐density lipoprotein cholesterol, Cardiorespiratory Medicine and Haematology, Cardiovascular medicine and haematology
Abstract: Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P
Published: 2023

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

Author: Wang, Yuxuan, Selvaraj, Margaret, Li, Xihao, Li, Zilin, Holdcraft, Jacob, Arnett, Donna, Bis, Joshua, Blangero, John, Boerwinkle, Eric, Bowden, Donald, Cade, Brian, Carlson, Jenna, Carson, April, Chen, Yii-Der, Curran, Joanne, de Vries, Paul, Dutcher, Susan, Ellinor, Patrick, Floyd, James, Fornage, Myriam, Freedman, Barry, Gabriel, Stacey, Germer, Soren, Gibbs, Richard, Guo, Xiuqing, He, Jiang, Heard-Costa, Nancy, Hildalgo, Bertha, Hou, Lifang, Irvin, Marguerite, Joehanes, Roby, Kaplan, Robert, Kardia, Sharon, Kelly, Tanika, Kim, Ryan, Kooperberg, Charles, Kral, Brian, Levy, Daniel, Li, Changwei, Liu, Chunyu, Lloyd-Jone, Don, Loos, Ruth, Mahaney, Michael, Martin, Lisa, Mathias, Rasika, Minster, Ryan, Mitchell, Braxton, Montasser, May, Morrison, Alanna, Murabito, Joanne, Naseri, Take, OConnell, Jeffrey, Palmer, Nicholette, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Rao, Dabeeru, Redline, Susan, Reiner, Alexander, Rich, Stephen, Ruepena, Muagututia, Sheu, Wayne, Smith, Jennifer, Smith, Albert, Tiwari, Hemant, Tsai, Michael, Viaud-Martinez, Karine, Wang, Zhe, Yanek, Lisa, Zhao, Wei, Lin, Xihong, Natarajan, Pradeep, Peloso, Gina, and Rotter, Jerome
Subjects: association, blood lipid, cholesterol, lncRNA, rare variants, whole-genome sequencing, Humans, RNA, Long Noncoding, Genome-Wide Association Study, Precision Medicine, Whole Genome Sequencing, Lipids, Polymorphism, Single Nucleotide
Abstract: Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.
Published: 2023

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

Author: Leiser, Claire L, Whitsel, Eric A, Reiner, Alexander, Rich, Stephen S, Rotter, Jerome I, Taylor, Kent D, Tracy, Russel P, Kooperberg, Charles, Smith, Albert Vernon, Manson, JoAnn E, Mychaleckyj, Josyf C, Bick, Alexander G, Szpiro, Adam A, and Kaufman, Joel D
Subjects: Epidemiology, Health Sciences, Aging, Cancer, Hematology, Climate-Related Exposures and Conditions, Prevention, Atherosclerosis, Genetics, 2.2 Factors relating to the physical environment, Humans, Female, Air Pollutants, Environmental Pollutants, Nitrogen Dioxide, Clonal Hematopoiesis, Cross-Sectional Studies, Environmental Exposure, Air Pollution, Particulate Matter, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract: BackgroundClonal hematopoiesis of indeterminate potential (CHIP) is an age-related somatic mutation associated with incident hematologic cancer. Environmental stressors which, like air pollution, generate oxidative stress at the cellular level, may induce somatic mutations and some mutations may provide a selection advantage for persistence and expansion of specific clones.MethodsWe used data from the Multi-Ethnic Study of Atherosclerosis (MESA) N = 4,379 and the Women's Health Initiative (WHI) N = 7,701 to estimate cross-sectional associations between annual average air pollution concentrations at participant address the year before blood draw using validated spatiotemporal models. We used covariate-adjusted logistic regression to estimate risk of CHIP per interquartile range increases in particulate matter (PM2.5; 4 μg/m3) and nitrogen dioxide (NO2; 10 ppb) as ORs (95% confidence intervals).ResultsPrevalence of CHIP at blood draw (variant allele fraction > 2%) was 4.4% and 8.7% in MESA and WHI, respectively. The most common CHIP driver mutation was in DNMT3A. Neither pollutant was associated with CHIP: ORMESA PM2.5 = 1.00 (0.68-1.45), ORMESA NO2 = 1.05 (0.69-1.61), ORWHI PM2.5 = 0.97 (0.86-1.09), ORWHI NO2 = 0.98 (0.88-1.10); or with DNMT3A-driven CHIP.ConclusionsWe did not find evidence that air pollution contributes to CHIP prevalence in two large observational cohorts.ImpactThis is the first study to estimate associations between air pollution and CHIP.
Published: 2023

10. A comprehensive map of the aging blood methylome in humans

Author: Seale, Kirsten, Teschendorff, Andrew, Reiner, Alexander P., Voisin, Sarah, and Eynon, Nir
Published: 2024
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11. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI

Author: Sun, Quan, Rowland, Bryce T., Chen, Jiawen, Mikhaylova, Anna V., Avery, Christy, Peters, Ulrike, Lundin, Jessica, Matise, Tara, Buyske, Steve, Tao, Ran, Mathias, Rasika A., Reiner, Alexander P., Auer, Paul L., Cox, Nancy J., Kooperberg, Charles, Thornton, Timothy A., Raffield, Laura M., and Li, Yun
Published: 2024
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12. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Author: Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J., Yin, Xianyong, Lorenz, Kim M., Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E. M., Kanoni, Stavroula, Rayner, Nigel W., Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S. K., Preuss, Michael H., Petty, Lauren E., Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A., Cook, James P., Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J., Chai, Jin-Fang, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj S., Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Brody, Jennifer A., Kabagambe, Edmond, An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Broadaway, K. Alaine, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Ahluwalia, Tarunveer S., Anand, Sonia S., Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas A., Burant, Charles F., Butterworth, Adam S., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Danesh, John, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Gordon-Larsen, Penny, Gross, Myron, Guare, Lindsay A., Hackinger, Sophie, Hakaste, Liisa, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Horikoshi, Momoko, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md. Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Torben, Kamanu, Frederick K., Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Kyung Min, Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lynch, Julie A., Lyssenko, Valeriya, Maeda, Shiro, Mamakou, Vasiliki, Mansuri, Sohail Rafik, Matsuda, Koichi, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mo, Huan, Morris, Andrew D., Moura, Filipe A., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Patil, Snehal, Pei, Pei, Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Polikowsky, Hannah G., Porneala, Bianca, Prasad, Gauri, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Katheryn, Sabanayagam, Charumathi, Sandow, Kevin, Sankareswaran, Alagu, Sattar, Naveed, Schönherr, Sebastian, Shahriar, Mohammad, Shen, Botong, Shi, Jinxiu, Shin, Dong Mun, Shojima, Nobuhiro, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Steinthorsdottir, Valgerdur, Stilp, Adrienne M., Strauch, Konstantin, Taylor, Kent D., Thorand, Barbara, Thorsteinsdottir, Unnur, Tomlinson, Brian, Tran, Tam C., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Wacher-Rodarte, Niels, Wheeler, Eleanor, Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamamoto, Kenichi, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zawistowski, Matthew, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Fornage, Myriam, Hanis, Craig L., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Yokota, Mitsuhiro, Kardia, Sharon L. R., Peyser, Patricia A., Pankow, James S., Engert, James C., Bonnefond, Amélie, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Mook-Kanamori, Dennis O., Tuomi, Tiinamaija, Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, Chen, Yii-Der Ida, Rich, Stephen S., McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Ghanbari, Mohsen, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Bowden, Donald W., Palmer, Colin N. A., Kooner, Jaspal S., Kooperberg, Charles, Liu, Simin, North, Kari E., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Wareham, Nicholas J., Lee, Juyoung, Kim, Bong-Jo, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Ahlqvist, Emma, Goodarzi, Mark O., Mohlke, Karen L., Langenberg, Claudia, Haiman, Christopher A., Loos, Ruth J. F., Florez, Jose C., Rader, Daniel J., Ritchie, Marylyn D., Zöllner, Sebastian, Mägi, Reedik, Marston, Nicholas A., Ruff, Christian T., van Heel, David A., Finer, Sarah, Denny, Joshua C., Yamauchi, Toshimasa, Kadowaki, Takashi, Chambers, John C., Ng, Maggie C. Y., Sim, Xueling, Below, Jennifer E., Tsao, Philip S., Chang, Kyong-Mi, McCarthy, Mark I., Meigs, James B., Mahajan, Anubha, Spracklen, Cassandra N., Mercader, Josep M., Boehnke, Michael, Rotter, Jerome I., Vujkovic, Marijana, Voight, Benjamin F., Morris, Andrew P., and Zeggini, Eleftheria
Published: 2024
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13. Age at Menopause, Leukocyte Telomere Length, and Coronary Artery Disease in Postmenopausal Women.

Author: Schuermans, Art, Nakao, Tetsushi, Uddin, Md, Hornsby, Whitney, Ganesh, Shriie, Shadyab, Aladdin, Liu, Simin, Haring, Bernhard, Shufelt, Chrisandra, Taub, Margaret, Mathias, Rasika, Kooperberg, Charles, Reiner, Alexander, Bick, Alexander, Manson, JoAnn, Natarajan, Pradeep, and Honigberg, Michael
Subjects: aging, cardiovascular disease, menopause, telomere, women, Adult, Female, Humans, Coronary Artery Disease, Leukocytes, Menopause, Menopause, Premature, Postmenopause, Telomere
Abstract: BACKGROUND: Premature menopause is a risk factor for accelerated cardiovascular aging, but underlying mechanisms remain incompletely understood. This study investigated the role of leukocyte telomere length (LTL), a marker of cellular aging and genomic instability, in the association of premature menopause with cardiovascular disease. METHODS: Participants from the UK Biobank and Womens Health Initiative with complete reproductive history and LTL measurements were included. Primary analyses tested the association between age at menopause and LTL using multivariable-adjusted linear regression. Secondary analyses stratified women by history of gynecologic surgery. Mendelian randomization was used to infer causal relationships between LTL and age at natural menopause. Multivariable-adjusted Cox regression and mediation analyses tested the joint associations of premature menopause and LTL with incident coronary artery disease. RESULTS: This study included 130 254 postmenopausal women (UK Biobank: n=122 224; Womens Health Initiative: n=8030), of whom 4809 (3.7%) had experienced menopause before age 40. Earlier menopause was associated with shorter LTL (meta-analyzed ß=-0.02 SD/5 years of earlier menopause [95% CI, -0.02 to -0.01]; P=7.2×10-12). This association was stronger and significant in both cohorts for women with natural/spontaneous menopause (meta-analyzed ß=-0.04 SD/5 years of earlier menopause [95% CI, -0.04 to -0.03]; P
Published: 2023

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

Author: Westerman, Kenneth E, Walker, Maura E, Gaynor, Sheila M, Wessel, Jennifer, DiCorpo, Daniel, Ma, Jiantao, Alonso, Alvaro, Aslibekyan, Stella, Baldridge, Abigail S, Bertoni, Alain G, Biggs, Mary L, Brody, Jennifer A, Chen, Yii-Der Ida, Dupuis, Joseé, Goodarzi, Mark O, Guo, Xiuqing, Hasbani, Natalie R, Heath, Adam, Hidalgo, Bertha, Irvin, Marguerite R, Johnson, W Craig, Kalyani, Rita R, Lange, Leslie, Lemaitre, Rozenn N, Liu, Ching-Ti, Liu, Simin, Moon, Jee-Young, Nassir, Rami, Pankow, James S, Pettinger, Mary, Raffield, Laura M, Rasmussen-Torvik, Laura J, Selvin, Elizabeth, Senn, Mackenzie K, Shadyab, Aladdin H, Smith, Albert V, Smith, Nicholas L, Steffen, Lyn, Talegakwar, Sameera, Taylor, Kent D, de Vries, Paul S, Wilson, James G, Wood, Alexis C, Yanek, Lisa R, Yao, Jie, Zheng, Yinan, Boerwinkle, Eric, Morrison, Alanna C, Fornage, Miriam, Russell, Tracy P, Psaty, Bruce M, Levy, Daniel, Heard-Costa, Nancy L, Ramachandran, Vasan S, Mathias, Rasika A, Arnett, Donna K, Kaplan, Robert, North, Kari E, Correa, Adolfo, Carson, April, Rotter, Jerome I, Rich, Stephen S, Manson, JoAnn E, Reiner, Alexander P, Kooperberg, Charles, Florez, Jose C, Meigs, James B, Merino, Jordi, Tobias, Deirdre K, Chen, Han, and Manning, Alisa K
Subjects: Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Diabetes, Human Genome, Minority Health, Genetics, Cardiovascular, Health Disparities, Prevention, Precision Medicine, Clinical Research, Metabolic and endocrine, Good Health and Well Being, Humans, Glycated Hemoglobin, Diet, Diabetes Mellitus, Eating, Guanine Nucleotide Dissociation Inhibitors, Genome-Wide Association Study, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract: Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.Article highlightsWe aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.
Published: 2023

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

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

16. 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

17. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.

Author: Young, William J, Haessler, Jeffrey, Benjamins, Jan-Walter, Repetto, Linda, Yao, Jie, Isaacs, Aaron, Harper, Andrew R, Ramirez, Julia, Garnier, Sophie, van Duijvenboden, Stefan, Baldassari, Antoine R, Concas, Maria Pina, Duong, ThuyVy, Foco, Luisa, Isaksen, Jonas L, Mei, Hao, Noordam, Raymond, Nursyifa, Casia, Richmond, Anne, Santolalla, Meddly L, Sitlani, Colleen M, Soroush, Negin, Thériault, Sébastien, Trompet, Stella, Aeschbacher, Stefanie, Ahmadizar, Fariba, Alonso, Alvaro, Brody, Jennifer A, Campbell, Archie, Correa, Adolfo, Darbar, Dawood, De Luca, Antonio, Deleuze, Jean-François, Ellervik, Christina, Fuchsberger, Christian, Goel, Anuj, Grace, Christopher, Guo, Xiuqing, Hansen, Torben, Heckbert, Susan R, Jackson, Rebecca D, Kors, Jan A, Lima-Costa, Maria Fernanda, Linneberg, Allan, Macfarlane, Peter W, Morrison, Alanna C, Navarro, Pau, Porteous, David J, Pramstaller, Peter P, Reiner, Alexander P, Risch, Lorenz, Schotten, Ulrich, Shen, Xia, Sinagra, Gianfranco, Soliman, Elsayed Z, Stoll, Monika, Tarazona-Santos, Eduardo, Tinker, Andrew, Trajanoska, Katerina, Villard, Eric, Warren, Helen R, Whitsel, Eric A, Wiggins, Kerri L, Arking, Dan E, Avery, Christy L, Conen, David, Girotto, Giorgia, Grarup, Niels, Hayward, Caroline, Jukema, J Wouter, Mook-Kanamori, Dennis O, Olesen, Morten Salling, Padmanabhan, Sandosh, Psaty, Bruce M, Pattaro, Cristian, Ribeiro, Antonio Luiz P, Rotter, Jerome I, Stricker, Bruno H, van der Harst, Pim, van Duijn, Cornelia M, Verweij, Niek, Wilson, James G, Orini, Michele, Charron, Philippe, Watkins, Hugh, Kooperberg, Charles, Lin, Henry J, Wilson, James F, Kanters, Jørgen K, Sotoodehnia, Nona, Mifsud, Borbala, Lambiase, Pier D, Tereshchenko, Larisa G, and Munroe, Patricia B
Subjects: Humans, Cardiovascular Diseases, Electrocardiography, Risk Factors, Arrhythmias, Cardiac, Atrioventricular Block, Genome-Wide Association Study, Biomarkers, Human Genome, Cardiovascular, Genetics, Heart Disease
Abstract: The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
Published: 2023

18. Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies

Author: Li, Xihao, Quick, Corbin, Zhou, Hufeng, Gaynor, Sheila M, Liu, Yaowu, Chen, Han, Selvaraj, Margaret Sunitha, Sun, Ryan, Dey, Rounak, Arnett, Donna K, Bielak, Lawrence F, Bis, Joshua C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, de Vries, Paul S, Duggirala, Ravindranath, Freedman, Barry I, Göring, Harald HH, Guo, Xiuqing, Haessler, Jeffrey, Kalyani, Rita R, Kooperberg, Charles, Kral, Brian G, Lange, Leslie A, Manichaikul, Ani, Martin, Lisa W, McGarvey, Stephen T, 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, Sitlani, Colleen M, Smith, Jennifer A, Taylor, Kent D, Vasan, Ramachandran S, Willer, Cristen J, Wilson, James G, Yanek, Lisa R, Zhao, Wei, Rotter, Jerome I, Natarajan, Pradeep, Peloso, Gina M, Li, Zilin, and Lin, Xihong
Subjects: Biological Sciences, Genetics, Biotechnology, Human Genome, Generic health relevance, Good Health and Well Being, Genome-Wide Association Study, Whole Genome Sequencing, Exome Sequencing, Phenotype, Lipids, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract: Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.
Published: 2023

19. Assessment of immune cell profiles among post-menopausal women in the Women’s Health Initiative using DNA methylation-based methods

Author: Nissen, Emily, Reiner, Alexander, Liu, Simin, Wallace, Robert B, Molinaro, Annette M, Salas, Lucas A, Christensen, Brock C, Wiencke, John K, Koestler, Devin C, and Kelsey, Karl T
Subjects: Biological Sciences, Genetics, Clinical Research, Aging, Inflammatory and immune system, Good Health and Well Being, Humans, Female, Middle Aged, Aged, Aged, 80 and over, DNA Methylation, Postmenopause, Leukocytes, CD8-Positive T-Lymphocytes, Women's Health, Population, WHI, Immune cell reference limits, Reference values, Immune cell phenotyping, Methylation cytometry, Immunomethylomics, DNA methylation, Deconvolution, Clinical Sciences, Paediatrics and Reproductive Medicine
Abstract: BackgroundOver the past decade, DNA methylation (DNAm)-based deconvolution methods that leverage cell-specific DNAm markers of immune cell types have been developed to provide accurate estimates of the proportions of leukocytes in peripheral blood. Immune cell phenotyping using DNAm markers, termed immunomethylomics or methylation cytometry, offers a solution for determining the body's immune cell landscape that does not require fresh blood and is scalable to large sample sizes. Despite significant advances in DNAm-based deconvolution, references at the population level are needed for clinical and research interpretation of these additional immune layers. Here we aim to provide some references for immune populations in a group of multi-ethnic post-menopausal American women.ResultsWe applied DNAm-based deconvolution to a large sample of post-menopausal women enrolled in the Women's Health Initiative (baseline, N = 58) or the ancillary Long Life Study (WHI-LLS, N = 1237) to determine the reference ranges of 58 immune parameters, including proportions and absolute counts for 19 leukocyte subsets and 20 derived cell ratios. Participants were 50-94 years old at the time of blood draw, and N = 898 (69.3%) self-identified as White. Using linear regression models, we observed significant associations between age at blood draw and absolute counts and proportions of naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ memory, neutrophils, and natural killer cells. We also assessed the same immune profiles in a subset of paired longitudinal samples collected 14-18 years apart across N = 52 participants. Our results demonstrate high inter-individual variability in rates of change of leukocyte subsets over this time. And, when conducting paired t tests to test the difference in counts and proportions between the baseline visit and LLS visit, there were significant changes in naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ cells and neutrophils, similar to the results seen when analyzing the association with age in the entire cohort.ConclusionsHere, we show that derived cell counts largely reflect the immune profile associated with proportions and that these novel methods replicate the known immune profiles associated with age. Further, we demonstrate the value this methylation cytometry approach can add as a potential application in epidemiological studies.
Published: 2023

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

Author: Young, Kristin L, Fisher, Virginia, Deng, Xuan, Brody, Jennifer A, Graff, Misa, Lim, Elise, Lin, Bridget M, Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E, Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G, Buth, Erin J, Heavner, Benjamin D, Jain, Deepti, Smith, Albert V, Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R, Kalyani, Rita R, Kardia, Sharon LR, Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A, McDonald, Merry-Lynn, Mitchell, Braxton D, Peyser, Patricia A, Regan, Elizabeth A, Redline, Susan, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Weiss, Scott, Wiggins, Kerri L, Yanek, Lisa R, Arnett, Donna, Heard-Costa, Nancy L, Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M, North, Kari E, Cupples, L Adrienne, and Liu, Ching-Ti
Subjects: Biological Sciences, Genetics, Clinical Research, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Humans, Genome-Wide Association Study, Exome, Body Mass Index, Quantitative Trait Loci, Anthropometry, Intercellular Signaling Peptides and Proteins, Cell Cycle Proteins, body mass index, central obesity, exome sequencing, height
Abstract: Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.
Published: 2023

21. An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling

Author: Kurniansyah, Nuzulul, Wallace, Danielle A, Zhang, Ying, Yu, Bing, Cade, Brian, Wang, Heming, Ochs-Balcom, Heather M, Reiner, Alexander P, Ramos, Alberto R, Smith, Joshua D, Cai, Jianwen, Daviglus, Martha, Zee, Phyllis C, Kaplan, Robert, Kooperberg, Charles, Rich, Stephen S, Rotter, Jerome I, Gharib, Sina A, Redline, Susan, and Sofer, Tamar
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Genetics, Cardiovascular, Clinical Research, Neurosciences, Lung, Mental Health, Prevention, Sleep Research, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Humans, Hispanic or Latino, Multiomics, Sleep, Sleep Apnea Syndromes, Oxyhemoglobins, Receptors, Purinergic P2X7, Multifactorial Inheritance, Biological sciences, Biomedical and clinical sciences
Abstract: Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women's Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.
Published: 2023

22. 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

23. Rare genetic variants explain missing heritability in smoking.

Author: Jang, Seon-Kyeong, Evans, Luke, Fialkowski, Allison, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Becker, Diane M, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Boorgula, Meher Preethi, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Jenkins, Brenda W Campbell, Carson, April P, Chavan, Sameer, Cupples, L Adrienne, Custer, Brian, Damrauer, Scott M, David, Sean P, de Andrade, Mariza, Dinardo, Carla L, Fingerlin, Tasha E, Fornage, Myriam, Freedman, Barry I, Garrett, Melanie E, Gharib, Sina A, Glahn, David C, Haessler, Jeffrey, Heckbert, Susan R, Hokanson, John E, Hou, Lifang, Hwang, Shih-Jen, Hyman, Matthew C, Judy, Renae, Justice, Anne E, Kaplan, Robert C, Kardia, Sharon LR, Kelly, Shannon, Kim, Wonji, Kooperberg, Charles, Levy, Daniel, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani W, Gladwin, Mark T, Martin, Lisa Warsinger, Nouraie, Mehdi, Melander, Olle, Meyers, Deborah A, Montgomery, Courtney G, North, Kari E, Oelsner, Elizabeth C, Palmer, Nicholette D, Payton, Marinelle, Peljto, Anna L, Peyser, Patricia A, Preuss, Michael, Psaty, Bruce M, Qiao, Dandi, Rader, Daniel J, Rafaels, Nicholas, Redline, Susan, Reed, Robert M, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Schwartz, David A, Shadyab, Aladdin H, Silverman, Edwin K, Smith, Nicholas L, Smith, J Gustav, Smith, Albert V, Smith, Jennifer A, Tang, Weihong, Taylor, Kent D, Telen, Marilyn J, Vasan, Ramachandran S, Gordeuk, Victor R, Wang, Zhe, Wiggins, Kerri L, Yanek, Lisa R, Yang, Ivana V, Young, Kendra A, Young, Kristin L, Zhang, Yingze, Liu, Dajiang J, Keller, Matthew C, and Vrieze, Scott
Subjects: Smoking, Gene Frequency, Phenotype, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Tobacco, Genetics, Tobacco Smoke and Health, Human Genome, Cancer
Abstract: Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
Published: 2022

24. Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas

Author: Borda, Victor, Loesch, Douglas P., Guo, Bing, Laboulaye, Roland, Veliz-Otani, Diego, French, Jennifer N., Leal, Thiago Peixoto, Gogarten, Stephanie M., Ikpe, Sunday, Gouveia, Mateus H., Mendes, Marla, Abecasis, Gonçalo R., Alvim, Isabela, Arboleda-Bustos, Carlos E., Arboleda, Gonzalo, Arboleda, Humberto, Barreto, Mauricio L., Barwick, Lucas, Bezzera, Marcos A., Blangero, John, Borges, Vanderci, Caceres, Omar, Cai, Jianwen, Chana-Cuevas, Pedro, Chen, Zhanghua, Custer, Brian, Dean, Michael, Dinardo, Carla, Domingos, Igor, Duggirala, Ravindranath, Dieguez, Elena, Fernandez, Willian, Ferraz, Henrique B., Gilliland, Frank, Guio, Heinner, Horta, Bernardo, Curran, Joanne E., Johnsen, Jill M., Kaplan, Robert C., Kelly, Shannon, Kenny, Eimear E., Konkle, Barbara A., Kooperberg, Charles, Lescano, Andres, Lima-Costa, M. Fernanda, Loos, Ruth J.F., Manichaikul, Ani, Meyers, Deborah A., Naslavsky, Michel S., Nickerson, Deborah A., North, Kari E., Padilla, Carlos, Preuss, Michael, Raggio, Victor, Reiner, Alexander P., Rich, Stephen S., Rieder, Carlos R., Rienstra, Michiel, Rotter, Jerome I., Rundek, Tatjana, Sacco, Ralph L., Sanchez, Cesar, Sankaran, Vijay G., Santos-Lobato, Bruno Lopes, Schumacher-Schuh, Artur Francisco, Scliar, Marilia O., Silverman, Edwin K., Sofer, Tamar, Lasky-Su, Jessica, Tumas, Vitor, Weiss, Scott T., Mata, Ignacio F., Hernandez, Ryan D., Tarazona-Santos, Eduardo, and O’Connor, Timothy D.
Published: 2024
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25. Contributions of the Womens Health Initiative to Cardiovascular Research: JACC State-of-the-Art Review.

Author: LaMonte, Michael, Manson, JoAnn, Anderson, Garnet, Baker, Laura, Bea, Jennifer, Eaton, Charles, Follis, Shawna, Hayden, Kathleen, Kooperberg, Charles, LaCroix, Andrea, Limacher, Marian, Neuhouser, Marian, Odegaard, Andrew, Perez, Marco, Prentice, Ross, Reiner, Alexander, Stefanick, Marcia, Van Horn, Linda, Wells, Gretchen, Whitsel, Eric, and Rossouw, Jacques
Subjects: cardiovascular disease, epidemiology, menopause, prevention, randomized trial, women’s health, Aged, Calcium, Cardiovascular Diseases, Female, Hormone Replacement Therapy, Humans, Middle Aged, Observational Studies as Topic, United States, Vitamin D, Womens Health
Abstract: The WHI (Womens Health Initiative) enrolled 161,808 racially and ethnically diverse postmenopausal women, ages 50-79 years, from 1993 to 1998 at 40 clinical centers across the United States. In its clinical trial component, WHI evaluated 3 randomized interventions (menopausal hormone therapy; diet modification; and calcium/vitamin D supplementation) for the primary prevention of major chronic diseases, including cardiovascular disease, in older women. In the WHI observational study, numerous clinical, behavioral, and social factors have been evaluated as predictors of incident chronic disease and mortality. Although the original interventions have been completed, the WHI data and biomarker resources continue to be leveraged and expanded through ancillary studies to yield novel insights regarding cardiovascular disease prevention and healthy aging in women.
Published: 2022

26. Transcriptome-wide association study and Mendelian randomization in pancreatic cancer identifies susceptibility genes and causal relationships with type 2 diabetes and venous thromboembolism

Author: Lindstrom, Sara, Wang, Lu, Smith, Erin, Gordon, William, Van Hylckama Vlieg, Astrid, De Andrade, Mariza, Brody, Jennifer, Pattee, Jack, Haessler, Jeffrey, Brumpton, Ben, Chasman, Daniel, Suchon, Pierre, Chen, Ming-Huei, Turman, Constance, Germain, Marine, Wiggins, Kerri, MacDonald, James, Braekkan, Sigrid, Armasu, Sebastian, Pankratz, Nathan, Jackson, Rabecca, Nielsen, Jonas, Giulianini, Franco, Puurunen, Marja, Ibrahim, Manal, Heckbert, Susan, Bammler, Theo, Frazer, Kelly, McCauley, Bryan, Taylor, Kent, Pankow, James, Reiner, Alexander, Gabrielsen, Maiken, Deleuze, Jean-François, O'Donnell, Chris, Kim, Jihye, McKnight, Barbara, Kraft, Peter, Hansen, John-Bjarne, Rosendaal, Frits, Heit, John, Psaty, Bruce, Tang, Weihong, Kooperberg, Charles, Hveem, Kristian, Ridker, Paul, Morange, Pierre-Emmanuel, Johnson, Andrew, Kabrhel, Christopher, Trégouët, David-Alexandre, Smith, Nicholas, Tan, Marcus C.B., Isom, Chelsea A., Liu, Yangzi, Wu, Lang, Zhou, Dan, and Gamazon, Eric R.
Published: 2024
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27. Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Author: Keshawarz, Amena, Bui, Helena, Joehanes, Roby, Ma, Jiantao, Liu, Chunyu, Huan, Tianxiao, Hwang, Shih-Jen, Tejada, Brandon, Sooda, Meera, Courchesne, Paul, Munson, Peter J., Demirkale, Cumhur Y., Yao, Chen, Heard-Costa, Nancy L., Pitsillides, Achilleas N., Lin, Honghuang, Liu, Ching-Ti, Wang, Yuxuan, Peloso, Gina M., Lundin, Jessica, Haessler, Jeffrey, Du, Zhaohui, Cho, Michael, Hersh, Craig P., Castaldi, Peter, Raffield, Laura M., Wen, Jia, Li, Yun, Reiner, Alexander P., Feolo, Mike, Sharopova, Nataliya, Vasan, Ramachandran S., DeMeo, Dawn L., Carson, April P., Kooperberg, Charles, and Levy, Daniel
Published: 2023
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28. Clonal Hematopoiesis Is Associated With Higher Risk of Stroke

Author: Bhattacharya, Romit, Zekavat, Seyedeh M, Haessler, Jeffrey, Fornage, Myriam, Raffield, Laura, Uddin, Mesbah, Bick, Alexander G, Niroula, Abhishek, Yu, Bing, Gibson, Christopher, Griffin, Gabriel, Morrison, Alanna C, Psaty, Bruce M, Longstreth, William T, Bis, Joshua C, Rich, Stephen S, Rotter, Jerome I, Tracy, Russell P, Correa, Adolfo, Seshadri, Sudha, Johnson, Andrew, Collins, Jason M, Hayden, Kathleen M, Madsen, Tracy E, Ballantyne, Christie M, Jaiswal, Siddhartha, Ebert, Benjamin L, Kooperberg, Charles, Manson, JoAnn E, Whitsel, Eric A, Program, NHLBI Trans-Omics for Precision Medicine, Natarajan, Pradeep, and Reiner, Alexander P
Subjects: Epidemiology, Health Sciences, Human Genome, Prevention, Brain Disorders, Neurosciences, Stroke, Genetics, Aging, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Clonal Hematopoiesis, DNA Methyltransferase 3A, DNA-Binding Proteins, Dioxygenases, Female, Hemorrhagic Stroke, Humans, Incidence, Ischemic Stroke, Male, Middle Aged, Prevalence, Repressor Proteins, Risk, NHLBI Trans-Omics for Precision Medicine Program, brain ischemia, cardiovascular diseases, clonal hematopoiesis, humans, prospective studies, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Neurology & Neurosurgery, Clinical sciences, Allied health and rehabilitation science
Abstract: Background and purposeClonal hematopoiesis of indeterminate potential (CHIP) is a novel age-related risk factor for cardiovascular disease-related morbidity and mortality. The association of CHIP with risk of incident ischemic stroke was reported previously in an exploratory analysis including a small number of incident stroke cases without replication and lack of stroke subphenotyping. The purpose of this study was to discover whether CHIP is a risk factor for ischemic or hemorrhagic stroke.MethodsWe utilized plasma genome sequence data of blood DNA to identify CHIP in 78 752 individuals from 8 prospective cohorts and biobanks. We then assessed the association of CHIP and commonly mutated individual CHIP driver genes (DNMT3A, TET2, and ASXL1) with any stroke, ischemic stroke, and hemorrhagic stroke.ResultsCHIP was associated with an increased risk of total stroke (hazard ratio, 1.14 [95% CI, 1.03-1.27]; P=0.01) after adjustment for age, sex, and race. We observed associations with CHIP with risk of hemorrhagic stroke (hazard ratio, 1.24 [95% CI, 1.01-1.51]; P=0.04) and with small vessel ischemic stroke subtypes. In gene-specific association results, TET2 showed the strongest association with total stroke and ischemic stroke, whereas DMNT3A and TET2 were each associated with increased risk of hemorrhagic stroke.ConclusionsCHIP is associated with an increased risk of stroke, particularly with hemorrhagic and small vessel ischemic stroke. Future studies clarifying the relationship between CHIP and subtypes of stroke are needed.
Published: 2022

29. 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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30. Clonal hematopoiesis in sickle cell disease.

Author: Liggett, L, Cato, Liam, Weinstock, Joshua, Zhang, Yingze, Nouraie, S, Gladwin, Mark, Garrett, Melanie, Ashley-Koch, Allison, Telen, Marilyn, Custer, Brian, Kelly, Shannon, Dinardo, Carla, Sabino, Ester, Loureiro, Paula, Carneiro-Proietti, Anna, Maximo, Cláudia, Reiner, Alexander, Abecasis, Gonçalo, Williams, David, Natarajan, Pradeep, Bick, Alexander, and Sankaran, Vijay
Subjects: Hematology, Leukemias, Anemia, Sickle Cell, Clonal Hematopoiesis, Female, Humans, Male, Whole Genome Sequencing
Abstract: BACKGROUNDCurative gene therapies for sickle cell disease (SCD) are currently undergoing clinical evaluation. The occurrence of myeloid malignancies in these trials has prompted safety concerns. Individuals with SCD are predisposed to myeloid malignancies, but the underlying causes remain undefined. Clonal hematopoiesis (CH) is a premalignant condition that also confers significant predisposition to myeloid cancers. While it has been speculated that CH may play a role in SCD-associated cancer predisposition, limited data addressing this issue have been reported.METHODSHere, we leveraged 74,190 whole-genome sequences to robustly study CH in SCD. Somatic mutation calling methods were used to assess CH in all samples and comparisons between individuals with and without SCD were performed.RESULTSWhile we had sufficient power to detect a greater than 2-fold increased rate of CH, we found no detectable variation in rate or clone properties between individuals affected by SCD and controls. The rate of CH in individuals with SCD was unaltered by hydroxyurea use.CONCLUSIONSWe did not observe an increased risk for acquiring detectable CH in SCD, at least as measured by whole-genome sequencing. These results should help guide ongoing efforts and further studies that seek to better define the risk factors underlying myeloid malignancy predisposition in SCD and help ensure that curative therapies can be more safely applied.FUNDINGNew York Stem Cell Foundation and the NIH.
Published: 2022

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

Author: Little, Amarise, Hu, Yao, Sun, Quan, Jain, Deepti, Broome, Jai, Chen, Ming-Huei, Thibord, Florian, McHugh, Caitlin, Surendran, Praveen, Blackwell, Thomas W, Brody, Jennifer A, Bhan, Arunoday, Chami, Nathalie, de Vries, Paul S, Ekunwe, Lynette, Heard-Costa, Nancy, Hobbs, Brian D, Manichaikul, Ani, Moon, Jee-Young, Preuss, Michael H, Ryan, Kathleen, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Abecasis, Goncalo R, Almasy, Laura, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Choquet, Hélène, Correa, Adolfo, Curran, Joanne E, Faraday, Nauder, Fornage, Myriam, Glahn, David C, Hou, Lifang, Jorgenson, Eric, Kooperberg, Charles, Lewis, Joshua P, Lloyd-Jones, Donald M, Loos, Ruth JF, Min, Yuan-I, Mitchell, Braxton D, Morrison, Alanna C, Nickerson, Deborah A, North, Kari E, O'Connell, Jeffrey R, Pankratz, Nathan, Psaty, Bruce M, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Smith, Albert V, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Conomos, Matthew P, Laurie, Cecelia A, Mathias, Rasika A, Li, Yun, Auer, Paul L, Consortium, NHLBI Trans-Omics for Precision Medicine, Thornton, Timothy, Reiner, Alexander P, Johnson, Andrew D, and Raffield, Laura M
Subjects: Biological Sciences, Genetics, Hematology, Biotechnology, Clinical Research, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Platelets, Genome-Wide Association Study, Humans, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Precision Medicine, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract: Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.
Published: 2022

32. The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations.

Author: Wang, Zhe, Choi, Shing, Chami, Nathalie, Boerwinkle, Eric, Fornage, Myriam, Redline, Susan, Bis, Joshua, Brody, Jennifer, Psaty, Bruce, Kim, Wonji, McDonald, Merry-Lynn, Regan, Elizabeth, Silverman, Edwin, Liu, Ching-Ti, Vasan, Ramachandran, Kalyani, Rita, Mathias, Rasika, Yanek, Lisa, Arnett, Donna, Justice, Anne, North, Kari, Kaplan, Robert, Heckbert, Susan, de Andrade, Mariza, Guo, Xiuqing, Lange, Leslie, Rich, Stephen, Rotter, Jerome, Ellinor, Patrick, Lubitz, Steven, Blangero, John, Shoemaker, M, Darbar, Dawood, Gladwin, Mark, Albert, Christine, Chasman, Daniel, Jackson, Rebecca, Kooperberg, Charles, Reiner, Alexander, OReilly, Paul, and Loos, Ruth
Subjects: BMI - body mass index, C+T, PRS-CS, burden score, lassosum, obesity risk, polygenic risk score, rare variants, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Humans, Obesity, Whole Genome Sequencing
Abstract: Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.
Published: 2022

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

Author: Selvaraj, Margaret Sunitha, Li, Xihao, Li, Zilin, Pampana, Akhil, Zhang, David Y, Park, Joseph, Aslibekyan, Stella, Bis, Joshua C, Brody, Jennifer A, Cade, Brian E, Chuang, Lee-Ming, Chung, Ren-Hua, Curran, Joanne E, de las Fuentes, Lisa, de Vries, Paul S, Duggirala, Ravindranath, Freedman, Barry I, Graff, Mariaelisa, Guo, Xiuqing, Heard-Costa, Nancy, Hidalgo, Bertha, Hwu, Chii-Min, Irvin, Marguerite R, Kelly, Tanika N, Kral, Brian G, Lange, Leslie, Li, Xiaohui, Lisa, Martin, Lubitz, Steven A, Manichaikul, Ani W, Michael, Preuss, Montasser, May E, Morrison, Alanna C, Naseri, Take, O’Connell, Jeffrey R, Palmer, Nicholette D, Peyser, Patricia A, Reupena, Muagututia S, Smith, Jennifer A, Sun, Xiao, Taylor, Kent D, Tracy, Russell P, Tsai, Michael Y, Wang, Zhe, Wang, Yuxuan, Bao, Wei, Wilkins, John T, Yanek, Lisa R, Zhao, Wei, Arnett, Donna K, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Dutcher, Susan K, Ellinor, Patrick T, Fornage, Myriam, Gabriel, Stacey, Germer, Soren, Gibbs, Richard, He, Jiang, Kaplan, Robert C, Kardia, Sharon LR, Kim, Ryan, Kooperberg, Charles, Loos, Ruth JF, Viaud-Martinez, Karine A, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Nickerson, Deborah, North, Kari E, Psaty, Bruce M, Redline, Susan, Reiner, Alexander P, Vasan, Ramachandran S, Rich, Stephen S, Willer, Cristen, Rotter, Jerome I, Rader, Daniel J, Lin, Xihong, Peloso, Gina M, and Natarajan, Pradeep
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Biotechnology, Heart Disease - Coronary Heart Disease, Cardiovascular, Heart Disease, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Alleles, Cholesterol, LDL, Genome-Wide Association Study, Humans, Lipids, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract: Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.
Published: 2022

34. Upregulated heme biosynthesis increases obstructive sleep apnea severity: a pathway-based Mendelian randomization study

Author: Wang, Heming, Kurniansyah, Nuzulul, Cade, Brian E, Goodman, Matthew O, Chen, Han, Gottlieb, Daniel J, Gharib, Sina A, Purcell, Shaun M, Lin, Xihong, Saxena, Richa, Zhu, Xiaofeng, Durda, Peter, Tracy, Russel, Liu, Yongmei, Taylor, Kent D, Johnson, W Craig, Gabriel, Stacey, Smith, Joshua D, Aguet, François, Ardlie, Kirstin, Blackwell, Tom, Reiner, Alexander P, Rotter, Jerome I, Rich, Stephen S, Redline, Susan, and Sofer, Tamar
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Cardiovascular Medicine and Haematology, Health Sciences, Human Genome, Lung, Sleep Research, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Good Health and Well Being, Aged, Datasets as Topic, Female, Genetic Predisposition to Disease, Heme, Humans, Iron, Male, Mendelian Randomization Analysis, Metabolic Networks and Pathways, Middle Aged, Polysomnography, Quantitative Trait Loci, Severity of Illness Index, Sleep Apnea, Obstructive, Up-Regulation, TOPMed Sleep Traits Working Group
Abstract: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Iron and heme metabolism, implicated in ventilatory control and OSA comorbidities, was associated with OSA phenotypes in recent admixture mapping and gene enrichment analyses. However, its causal contribution was unclear. In this study, we performed pathway-level transcriptional Mendelian randomization (MR) analysis to investigate the causal relationships between iron and heme related pathways and OSA. In primary analysis, we examined the expression level of four iron/heme Reactome pathways as exposures and four OSA traits as outcomes using cross-tissue cis-eQTLs from the Genotype-Tissue Expression portal and published genome-wide summary statistics of OSA. We identify a significant putative causal association between up-regulated heme biosynthesis pathway with higher sleep time percentage of hypoxemia (p = 6.14 × 10-3). This association is supported by consistency of point estimates in one-sample MR in the Multi-Ethnic Study of Atherosclerosis using high coverage DNA and RNA sequencing data generated by the Trans-Omics for Precision Medicine project. Secondary analysis for 37 additional iron/heme Gene Ontology pathways did not reveal any significant causal associations. This study suggests a causal association between increased heme biosynthesis and OSA severity.
Published: 2022

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

Author: DiCorpo, Daniel, Gaynor, Sheila M, Russell, Emily M, Westerman, Kenneth E, Raffield, Laura M, Majarian, Timothy D, Wu, Peitao, Sarnowski, Chloé, Highland, Heather M, Jackson, Anne, Hasbani, Natalie R, de Vries, Paul S, Brody, Jennifer A, Hidalgo, Bertha, Guo, Xiuqing, Perry, James A, O’Connell, Jeffrey R, Lent, Samantha, Montasser, May E, Cade, Brian E, Jain, Deepti, Wang, Heming, D’Oliveira Albanus, Ricardo, Varshney, Arushi, Yanek, Lisa R, Lange, Leslie, Palmer, Nicholette D, Almeida, Marcio, Peralta, Juan M, Aslibekyan, Stella, Baldridge, Abigail S, Bertoni, Alain G, Bielak, Lawrence F, Chen, Chung-Shiuan, Chen, Yii-Der Ida, Choi, Won Jung, Goodarzi, Mark O, Floyd, James S, Irvin, Marguerite R, Kalyani, Rita R, Kelly, Tanika N, Lee, Seonwook, Liu, Ching-Ti, Loesch, Douglas, Manson, JoAnn E, Minster, Ryan L, Naseri, Take, Pankow, James S, Rasmussen-Torvik, Laura J, Reiner, Alexander P, Reupena, Muagututi’a Sefuiva, Selvin, Elizabeth, Smith, Jennifer A, Weeks, Daniel E, Xu, Huichun, Yao, Jie, Zhao, Wei, Parker, Stephen, Alonso, Alvaro, Arnett, Donna K, Blangero, John, Boerwinkle, Eric, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Duggirala, Ravindranath, He, Jiang, Heckbert, Susan R, Kardia, Sharon LR, Kim, Ryan W, Kooperberg, Charles, Liu, Simin, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Morrison, Alanna C, Peyser, Patricia A, Psaty, Bruce M, Redline, Susan, Shuldiner, Alan R, Taylor, Kent D, Vasan, Ramachandran S, Viaud-Martinez, Karine A, Florez, Jose C, Wilson, James G, Sladek, Robert, Rich, Stephen S, Rotter, Jerome I, Lin, Xihong, Dupuis, Josée, Meigs, James B, Wessel, Jennifer, and Manning, Alisa K
Subjects: Biological Sciences, Genetics, Human Genome, Biotechnology, Diabetes, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Good Health and Well Being, Diabetes Mellitus, Type 2, Fasting, Glucose, Humans, Insulin, National Heart, Lung, and Blood Institute (U.S.), Nerve Tissue Proteins, Polymorphism, Single Nucleotide, Precision Medicine, Receptors, Immunologic, United States, Biological sciences, Biomedical and clinical sciences
Abstract: The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.
Published: 2022

36. Epigenome-wide association study of mitochondrial genome copy number.

Author: Wang, Penglong, Castellani, Christina A, Yao, Jie, Huan, Tianxiao, Bielak, Lawrence F, Zhao, Wei, Haessler, Jeffrey, Joehanes, Roby, Sun, Xianbang, Guo, Xiuqing, Longchamps, Ryan J, Manson, JoAnn E, Grove, Megan L, Bressler, Jan, Taylor, Kent D, Lappalainen, Tuuli, Kasela, Silva, Van Den Berg, David J, Hou, Lifang, Reiner, Alexander, Liu, Yongmei, Boerwinkle, Eric, Smith, Jennifer A, Peyser, Patricia A, Fornage, Myriam, Rich, Stephen S, Rotter, Jerome I, Kooperberg, Charles, Arking, Dan E, Levy, Daniel, and Liu, Chunyu
Subjects: Heart Disease, Human Genome, Genetics, Cardiovascular, Generic health relevance, Aged, DNA Copy Number Variations, DNA Methylation, DNA, Mitochondrial, Epigenome, Female, Genome, Mitochondrial, Humans, Male, Middle Aged, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract: We conducted cohort- and race-specific epigenome-wide association analyses of mitochondrial deoxyribonucleic acid (mtDNA) copy number (mtDNA CN) measured in whole blood from participants of African and European origins in five cohorts (n = 6182, mean age = 57-67 years, 65% women). In the meta-analysis of all the participants, we discovered 21 mtDNA CN-associated DNA methylation sites (CpG) (P
Published: 2021

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

Author: Hu, Yao, Bien, Stephanie A, Nishimura, Katherine K, Haessler, Jeffrey, Hodonsky, Chani J, Baldassari, Antoine R, Highland, Heather M, Wang, Zhe, Preuss, Michael, Sitlani, Colleen M, Wojcik, Genevieve L, Tao, Ran, Graff, Mariaelisa, Huckins, Laura M, Sun, Quan, Chen, Ming-Huei, Mousas, Abdou, Auer, Paul L, Lettre, Guillaume, Tang, Weihong, Qi, Lihong, Thyagarajan, Bharat, Buyske, Steve, Fornage, Myriam, Hindorff, Lucia A, Li, Yun, Lin, Danyu, Reiner, Alexander P, North, Kari E, Loos, Ruth JF, Raffield, Laura M, Peters, Ulrike, Avery, Christy L, and Kooperberg, Charles
Subjects: Clinical Research, Hematology, Genetics, American Indian or Alaska Native, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Leukocytes, Phenotype, Polymorphism, Single Nucleotide, GWAS, White blood cells, Platelets, Multi-ethnic, Blood Cell Consortium, Biological Sciences, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics
Abstract: BackgroundCirculating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.ResultsWe performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.ConclusionsOur results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.
Published: 2021

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

Author: Mikhaylova, Anna V, McHugh, Caitlin P, Polfus, Linda M, Raffield, Laura M, Boorgula, Meher Preethi, Blackwell, Thomas W, Brody, Jennifer A, Broome, Jai, Chami, Nathalie, Chen, Ming-Huei, Conomos, Matthew P, Cox, Corey, Curran, Joanne E, Daya, Michelle, Ekunwe, Lynette, Glahn, David C, Heard-Costa, Nancy, Highland, Heather M, Hobbs, Brian D, Ilboudo, Yann, Jain, Deepti, Lange, Leslie A, Miller-Fleming, Tyne W, Min, Nancy, Moon, Jee-Young, Preuss, Michael H, Rosen, Jonathon, Ryan, Kathleen, Smith, Albert V, Sun, Quan, Surendran, Praveen, de Vries, Paul S, Walter, Klaudia, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Zhong, Xue, Abecasis, Goncalo R, Almasy, Laura, Barnes, Kathleen C, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Chavan, Sameer, Cho, Michael H, Choquet, Hélène, Correa, Adolfo, Cox, Nancy, DeMeo, Dawn L, Faraday, Nauder, Fornage, Myriam, Gerszten, Robert E, Hou, Lifang, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kooperberg, Charles, Kundu, Kousik, Laurie, Cecelia A, Lettre, Guillaume, Lewis, Joshua P, Li, Bingshan, Li, Yun, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani, Meyers, Deborah A, Mitchell, Braxton D, Morrison, Alanna C, Ngo, Debby, Nickerson, Deborah A, Nongmaithem, Suraj, North, Kari E, O’Connell, Jeffrey R, Ortega, Victor E, Pankratz, Nathan, Perry, James A, Psaty, Bruce M, Rich, Stephen S, Soranzo, Nicole, Rotter, Jerome I, Silverman, Edwin K, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Thornton, Timothy A, Vasan, Ramachandran S, Zein, Joe, Mathias, Rasika A, Consortium, NHLBI Trans-Omics for Precision Medicine, Reiner, Alexander P, and Auer, Paul L
Subjects: Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, blood-cell counts, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract: Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.
Published: 2021

39. Whole-genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles

Author: Huffman, Jennifer E., Nicholas, Jayna, Hahn, Julie, Heath, Adam S., Raffield, Laura M., Yanek, Lisa R., Brody, Jennifer A., Thibord, Florian, Almasy, Laura, Bartz, Traci M., Bielak, Lawrence F., Bowler, Russell P., Carrasquilla, Germán D., Chasman, Daniel I., Chen, Ming-Huei, Emmert, David B., Ghanbari, Mohsen, Haessler, Jeffrey, Hottenga, Jouke-Jan, Kleber, Marcus E., Le, Ngoc-Quynh, Lee, Jiwon, Lewis, Joshua P., Li-Gao, Ruifang, Luan, Jian'an, Malmberg, Anni, Mangino, Massimo, Marioni, Riccardo E., Martinez-Perez, Angel, Pankratz, Nathan, Polasek, Ozren, Richmond, Anne, Rodriguez, Benjamin A. T., Rotter, Jerome I., Steri, Maristella, Suchon, Pierre, Trompet, Stella, Weiss, Stefan, Zare, Marjan, Auer, Paul, Cho, Michael H., Christofidou, Paraskevi, Davies, Gail, de Geus, Eco, Deleuze, Jean-François, Delgado, Graciela E., Ekunwe, Lynette, Faraday, Nauder, Gögele, Martin, Greinacher, Andreas, Gao, He, Howard, Tom, Joshi, Peter K., Kilpeläinen, Tuomas O., Lahti, Jari, Linneberg, Allan, Naitza, Silvia, Noordam, Raymond, Paüls-Vergés, Ferran, Rich, Stephen S., Rosendaal, Frits R., Rudan, Igor, Ryan, Kathleen A., Souto, Juan Carlos, van Rooij, Frank J. A., Wang, Heming, Zhao, Wei, Becker, Lewis C., Beswick, Andrew, Brown, Michael R., Cade, Brian E., Campbell, Harry, Cho, Kelly, Crapo, James D., Curran, Joanne E., de Maat, Moniek P. M., Doyle, Margaret, Elliott, Paul, Floyd, James S., Fuchsberger, Christian, Grarup, Niels, Guo, Xiuqing, Harris, Sarah E., Hou, Lifang, Kolcic, Ivana, Kooperberg, Charles, Menni, Cristina, Nauck, Matthias, O'Connell, Jeffrey R., Orrù, Valeria, Psaty, Bruce M., Räikkönen, Katri, Smith, Jennifer A., Soria, Jose Manuel, Stott, David J., van Hylckama Vlieg, Astrid, Watkins, Hugh, Willemsen, Gonneke, Wilson, Peter W. F., Ben-Shlomo, Yoav, Blangero, John, Boomsma, Dorret, Cox, Simon R., Dehghan, Abbas, Eriksson, Johan G., Fiorillo, Edoardo, Fornage, Myriam, Hansen, Torben, Hayward, Caroline, Ikram, M. Arfan, Jukema, J. Wouter, Kardia, Sharon L. R., Lange, Leslie A., März, Winfried, Mathias, Rasika A., Mitchell, Braxton D., Mook-Kanamori, Dennis O., Morange, Pierre-Emmanuel, Pedersen, Oluf, Pramstaller, Peter P., Redline, Susan, Reiner, Alexander, Ridker, Paul M., Silverman, Edwin K., Spector, Tim D., Völker, Uwe, Wareham, Nicholas J., Wilson, James F., Yao, Jie, Trégouët, David-Alexandre, Johnson, Andrew D., Wolberg, Alisa S., de Vries, Paul S., Sabater-Lleal, Maria, Morrison, Alanna C., and Smith, Nicholas L.
Published: 2024
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40. Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis

Author: Weinstock, Joshua S., Gopakumar, Jayakrishnan, Burugula, Bala Bharathi, Uddin, Md Mesbah, Jahn, Nikolaus, Belk, Julia A., Bouzid, Hind, Daniel, Bence, Miao, Zhuang, Ly, Nghi, Mack, Taralynn M., Luna, Sofia E., Prothro, Katherine P., Mitchell, Shaneice R., Laurie, Cecelia A., Broome, Jai G., Taylor, Kent D., Guo, Xiuqing, Sinner, Moritz F., von Falkenhausen, Aenne S., Kääb, Stefan, Shuldiner, Alan R., O’Connell, Jeffrey R., Lewis, Joshua P., Boerwinkle, Eric, Barnes, Kathleen C., Chami, Nathalie, Kenny, Eimear E., Loos, Ruth J. F., Fornage, Myriam, Hou, Lifang, Lloyd-Jones, Donald M., Redline, Susan, Cade, Brian E., Psaty, Bruce M., Bis, Joshua C., Brody, Jennifer A., Silverman, Edwin K., Yun, Jeong H., Qiao, Dandi, Palmer, Nicholette D., Freedman, Barry I., Bowden, Donald W., Cho, Michael H., DeMeo, Dawn L., Vasan, Ramachandran S., Yanek, Lisa R., Becker, Lewis C., Kardia, Sharon L. R., Peyser, Patricia A., He, Jiang, Rienstra, Michiel, Van der Harst, Pim, Kaplan, Robert, Heckbert, Susan R., Smith, Nicholas L., Wiggins, Kerri L., Arnett, Donna K., Irvin, Marguerite R., Tiwari, Hemant, Cutler, Michael J., Knight, Stacey, Muhlestein, J. Brent, Correa, Adolfo, Raffield, Laura M., Gao, Yan, de Andrade, Mariza, Rotter, Jerome I., Rich, Stephen S., Tracy, Russell P., Konkle, Barbara A., Johnsen, Jill M., Wheeler, Marsha M., Smith, J. Gustav, Melander, Olle, Nilsson, Peter M., Custer, Brian S., Duggirala, Ravindranath, Curran, Joanne E., Blangero, John, McGarvey, Stephen, Williams, L. Keoki, Xiao, Shujie, Yang, Mao, Gu, C. Charles, Chen, Yii-Der Ida, Lee, Wen-Jane, Marcus, Gregory M., Kane, John P., Pullinger, Clive R., Shoemaker, M. Benjamin, Darbar, Dawood, Roden, Dan M., Albert, Christine, Kooperberg, Charles, Zhou, Ying, Manson, JoAnn E., Desai, Pinkal, Johnson, Andrew D., Mathias, Rasika A., Blackwell, Thomas W., Abecasis, Goncalo R., Smith, Albert V., Kang, Hyun M., Satpathy, Ansuman T., Natarajan, Pradeep, Kitzman, Jacob O., Whitsel, Eric A., Reiner, Alexander P., Bick, Alexander G., and Jaiswal, Siddhartha
Published: 2023
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41. Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Author: Goodrich, Julia K, Singer-Berk, Moriel, Son, Rachel, Sveden, Abigail, Wood, Jordan, England, Eleina, Cole, Joanne B, Weisburd, Ben, Watts, Nick, Caulkins, Lizz, Dornbos, Peter, Koesterer, Ryan, Zappala, Zachary, Zhang, Haichen, Maloney, Kristin A, Dahl, Andy, Aguilar-Salinas, Carlos A, Atzmon, Gil, Barajas-Olmos, Francisco, Barzilai, Nir, Blangero, John, Boerwinkle, Eric, Bonnycastle, Lori L, Bottinger, Erwin, Bowden, Donald W, Centeno-Cruz, Federico, Chambers, John C, Chami, Nathalie, Chan, Edmund, Chan, Juliana, Cheng, Ching-Yu, Cho, Yoon Shin, Contreras-Cubas, Cecilia, Córdova, Emilio, Correa, Adolfo, DeFronzo, Ralph A, Duggirala, Ravindranath, Dupuis, Josée, Garay-Sevilla, Ma Eugenia, García-Ortiz, Humberto, Gieger, Christian, Glaser, Benjamin, González-Villalpando, Clicerio, Gonzalez, Ma Elena, Grarup, Niels, Groop, Leif, Gross, Myron, Haiman, Christopher, Han, Sohee, Hanis, Craig L, Hansen, Torben, Heard-Costa, Nancy L, Henderson, Brian E, Hernandez, Juan Manuel Malacara, Hwang, Mi Yeong, Islas-Andrade, Sergio, Jørgensen, Marit E, Kang, Hyun Min, Kim, Bong-Jo, Kim, Young Jin, Koistinen, Heikki A, Kooner, Jaspal Singh, Kuusisto, Johanna, Kwak, Soo-Heon, Laakso, Markku, Lange, Leslie, Lee, Jong-Young, Lee, Juyoung, Lehman, Donna M, Linneberg, Allan, Liu, Jianjun, Loos, Ruth JF, Lyssenko, Valeriya, Ma, Ronald CW, Martínez-Hernández, Angélica, Meigs, James B, Meitinger, Thomas, Mendoza-Caamal, Elvia, Mohlke, Karen L, Morris, Andrew D, Morrison, Alanna C, Ng, Maggie CY, Nilsson, Peter M, O'Donnell, Christopher J, Orozco, Lorena, Palmer, Colin NA, Park, Kyong Soo, Post, Wendy S, Pedersen, Oluf, Preuss, Michael, Psaty, Bruce M, Reiner, Alexander P, Revilla-Monsalve, Cristina, Rich, Stephen S, Rotter, Jerome I, Saleheen, Danish, Schurmann, Claudia, Sim, Xueling, Sladek, Rob, and Small, Kerrin S
Subjects: AMP-T2D-GENES Consortia, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Risk Assessment, Genotype, Multifactorial Inheritance, Penetrance, Adult, Dyslipidemias, Exome, Biomarkers, Biological Variation, Population
Abstract: Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
Published: 2021

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

Author: Kwong, Alan M, Blackwell, Thomas W, LeFaive, Jonathon, de Andrade, Mariza, Barnard, John, Barnes, Kathleen C, Blangero, John, Boerwinkle, Eric, Burchard, Esteban G, Cade, Brian E, Chasman, Daniel I, Chen, Han, Conomos, Matthew P, Cupples, L Adrienne, Ellinor, Patrick T, Eng, Celeste, Gao, Yan, Guo, Xiuqing, Irvin, Marguerite Ryan, Kelly, Tanika N, Kim, Wonji, Kooperberg, Charles, Lubitz, Steven A, Mak, Angel CY, Manichaikul, Ani W, Mathias, Rasika A, Montasser, May E, Montgomery, Courtney G, Musani, Solomon, Palmer, Nicholette D, Peloso, Gina M, Qiao, Dandi, Reiner, Alexander P, Roden, Dan M, Shoemaker, M Benjamin, Smith, Jennifer A, Smith, Nicholas L, Su, Jessica Lasky, Tiwari, Hemant K, Weeks, Daniel E, Weiss, Scott T, Consortium, TOPMed Analysis Working Group NHLBI Trans-Omics for Precision Medicine, Scott, Laura J, Smith, Albert V, Abecasis, Gonçalo R, Boehnke, Michael, and Kang, Hyun Min
Subjects: Genetics, Alleles, Gene Frequency, Genetics, Population, Genotype, Humans, Linkage Disequilibrium, Models, Genetic, Models, Statistical, Phenotype, Software, population structure, principal components analysis, next-generation sequencing, genotype likelihoods, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Analysis Working Group, Developmental Biology
Abstract: Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.
Published: 2021

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

Author: Hu, Yao, Stilp, Adrienne M, McHugh, Caitlin P, Rao, Shuquan, Jain, Deepti, Zheng, Xiuwen, Lane, John, de Bellefon, Sébastian Méric, Raffield, Laura M, Chen, Ming-Huei, Yanek, Lisa R, Wheeler, Marsha, Yao, Yao, Ren, Chunyan, Broome, Jai, Moon, Jee-Young, de Vries, Paul S, Hobbs, Brian D, Sun, Quan, Surendran, Praveen, Brody, Jennifer A, Blackwell, Thomas W, Choquet, Hélène, Ryan, Kathleen, Duggirala, Ravindranath, Heard-Costa, Nancy, Wang, Zhe, Chami, Nathalie, Preuss, Michael H, Min, Nancy, Ekunwe, Lynette, Lange, Leslie A, Cushman, Mary, Faraday, Nauder, Curran, Joanne E, Almasy, Laura, Kundu, Kousik, Smith, Albert V, Gabriel, Stacey, Rotter, Jerome I, Fornage, Myriam, Lloyd-Jones, Donald M, Vasan, Ramachandran S, Smith, Nicholas L, North, Kari E, Boerwinkle, Eric, Becker, Lewis C, Lewis, Joshua P, Abecasis, Goncalo R, Hou, Lifang, O’Connell, Jeffrey R, Morrison, Alanna C, Beaty, Terri H, Kaplan, Robert, Correa, Adolfo, Blangero, John, Jorgenson, Eric, Psaty, Bruce M, Kooperberg, Charles, Walton, Russell T, Kleinstiver, Benjamin P, Tang, Hua, Loos, Ruth JF, Soranzo, Nicole, Butterworth, Adam S, Nickerson, Debbie, Rich, Stephen S, Mitchell, Braxton D, Johnson, Andrew D, Auer, Paul L, Li, Yun, Mathias, Rasika A, Lettre, Guillaume, Pankratz, Nathan, Laurie, Cathy C, Laurie, Cecelia A, Bauer, Daniel E, Conomos, Matthew P, Reiner, Alexander P, and Consortium, NHLBI Trans-Omics for Precision Medicine
Subjects: Epidemiology, Biological Sciences, Health Sciences, Genetics, Biotechnology, Clinical Research, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, base editing, red blood cell traits, whole-genome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract: Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.
Published: 2021

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

Author: Natarajan, Pradeep, Pampana, Akhil, Graham, Sarah E, Ruotsalainen, Sanni E, Perry, James A, de Vries, Paul S, Broome, Jai G, Pirruccello, James P, Honigberg, Michael C, Aragam, Krishna, Wolford, Brooke, Brody, Jennifer A, Antonacci-Fulton, Lucinda, Arden, Moscati, Aslibekyan, Stella, Assimes, Themistocles L, Ballantyne, Christie M, Bielak, Lawrence F, Bis, Joshua C, Cade, Brian E, Do, Ron, Doddapaneni, Harsha, Emery, Leslie S, Hung, Yi-Jen, Irvin, Marguerite R, Khan, Alyna T, Lange, Leslie, Lee, Jiwon, Lemaitre, Rozenn N, Martin, Lisa W, Metcalf, Ginger, Montasser, May E, Moon, Jee-Young, Muzny, Donna, O'Connell, Jeffrey R, Palmer, Nicholette D, Peralta, Juan M, Peyser, Patricia A, Stilp, Adrienne M, Tsai, Michael, Wang, Fei Fei, Weeks, Daniel E, Yanek, Lisa R, Wilson, James G, Abecasis, Goncalo, Arnett, Donna K, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Chang, Yi-Cheng, Chen, Yii-Der I, Choi, Won Jung, Correa, Adolfo, Curran, Joanne E, Daly, Mark J, Dutcher, Susan K, Ellinor, Patrick T, Fornage, Myriam, Freedman, Barry I, Gabriel, Stacey, Germer, Soren, Gibbs, Richard A, He, Jiang, Hveem, Kristian, Jarvik, Gail P, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear, Kim, Ryan W, Kooperberg, Charles, Laurie, Cathy C, Lee, Seonwook, Lloyd-Jones, Don M, Loos, Ruth JF, Lubitz, Steven A, Mathias, Rasika A, Martinez, Karine A Viaud, McGarvey, Stephen T, Mitchell, Braxton D, Nickerson, Deborah A, North, Kari E, Palotie, Aarno, Park, Cheol Joo, Psaty, Bruce M, Rao, DC, Redline, Susan, Reiner, Alexander P, Seo, Daekwan, Seo, Jeong-Sun, Smith, Albert V, Tracy, Russell P, Vasan, Ramachandran S, Kathiresan, Sekar, Cupples, L Adrienne, Rotter, Jerome I, Morrison, Alanna C, Rich, Stephen S, Ripatti, Samuli, and Willer, Cristen
Subjects: NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, FinnGen, Subcutaneous Tissue, Chromosomes, Human, X, Humans, Genetic Predisposition to Disease, Lipids, Eye Proteins, Nerve Tissue Proteins, Gene Expression Regulation, Genotype, Polymorphism, Single Nucleotide, Middle Aged, Female, Male, Genetic Loci, Genetic Association Studies, Whole Genome Sequencing, Phenomics, Cardiometabolic Risk Factors, Chromosomes, Human, X, Polymorphism, Single Nucleotide
Abstract: Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
Published: 2021

45. Genetic examination of hematological parameters in SARS-CoV-2 infection and COVID-19

Author: Sun, Quan, Rowland, Bryce, Wang, Wanjiang, Miller-Fleming, Tyne W., Cox, Nancy, Graff, Misa, Faucon, Annika, Shuey, Megan M., Blue, Elizabeth E., Auer, Paul, Li, Yun, Sankaran, Vijay G., Reiner, Alexander P., and Raffield, Laura M.
Published: 2023
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46. Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

Author: Wen, Jia, Xie, Munan, Rowland, Bryce, Rosen, Jonathan D, Sun, Quan, Chen, Jiawen, Tapia, Amanda L, Qian, Huijun, Kowalski, Madeline H, Shan, Yue, Young, Kristin L, Graff, Marielisa, Argos, Maria, Avery, Christy L, Bien, Stephanie A, Buyske, Steve, Yin, Jie, Choquet, Hélène, Fornage, Myriam, Hodonsky, Chani J, Jorgenson, Eric, Kooperberg, Charles, Loos, Ruth JF, Liu, Yongmei, Moon, Jee-Young, North, Kari E, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Zhao, Wei, Shang, Lulu, Wang, Tao, Zhou, Xiang, Reiner, Alexander P, Raffield, Laura M, and Li, Yun
Subjects: Biological Sciences, Genetics, Biotechnology, Hematology, Human Genome, Atherosclerosis, Clinical Research, Good Health and Well Being, Black or African American, Blood Cells, Cohort Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Transcriptome, White People, TWAS, non-European populations, ancestry, expression analysis
Abstract: BackgroundThousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed.MethodsTo derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants.ResultsOur results revealed 24 suggestive signals (p < 1 × 10-4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN.ConclusionsThese analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.
Published: 2021

47. Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease.

Author: Nielsen, Jonas B, Rom, Oren, Surakka, Ida, Graham, Sarah E, Zhou, Wei, Roychowdhury, Tanmoy, Fritsche, Lars G, Gagliano Taliun, Sarah A, Sidore, Carlo, Liu, Yuhao, Gabrielsen, Maiken E, Skogholt, Anne Heidi, Wolford, Brooke, Overton, William, Zhao, Ying, Chen, Jin, Zhang, He, Hornsby, Whitney E, Acheampong, Akua, Grooms, Austen, Schaefer, Amanda, Zajac, Gregory JM, Villacorta, Luis, Zhang, Jifeng, Brumpton, Ben, Løset, Mari, Rai, Vivek, Lundegaard, Pia R, Olesen, Morten S, Taylor, Kent D, Palmer, Nicholette D, Chen, Yii-Der, Choi, Seung H, Lubitz, Steven A, Ellinor, Patrick T, Barnes, Kathleen C, Daya, Michelle, Rafaels, Nicholas, Weiss, Scott T, Lasky-Su, Jessica, Tracy, Russell P, Vasan, Ramachandran S, Cupples, L Adrienne, Mathias, Rasika A, Yanek, Lisa R, Becker, Lewis C, Peyser, Patricia A, Bielak, Lawrence F, Smith, Jennifer A, Aslibekyan, Stella, Hidalgo, Bertha A, Arnett, Donna K, Irvin, Marguerite R, Wilson, James G, Musani, Solomon K, Correa, Adolfo, Rich, Stephen S, Guo, Xiuqing, Rotter, Jerome I, Konkle, Barbara A, Johnsen, Jill M, Ashley-Koch, Allison E, Telen, Marilyn J, Sheehan, Vivien A, Blangero, John, Curran, Joanne E, Peralta, Juan M, Montgomery, Courtney, Sheu, Wayne H-H, Chung, Ren-Hua, Schwander, Karen, Nouraie, Seyed M, Gordeuk, Victor R, Zhang, Yingze, Kooperberg, Charles, Reiner, Alexander P, Jackson, Rebecca D, Bleecker, Eugene R, Meyers, Deborah A, Li, Xingnan, Das, Sayantan, Yu, Ketian, LeFaive, Jonathon, Smith, Albert, Blackwell, Tom, Taliun, Daniel, Zollner, Sebastian, Forer, Lukas, Schoenherr, Sebastian, Fuchsberger, Christian, Pandit, Anita, Zawistowski, Matthew, Kheterpal, Sachin, Brummett, Chad M, Natarajan, Pradeep, Schlessinger, David, Lee, Seunggeun, Kang, Hyun Min, Cucca, Francesco, and Holmen, Oddgeir L
Subjects: Liver, Humans, Cardiovascular Diseases, Lipids, Receptors, LDL, Gene Targeting, Gene Silencing, Genome, Human, Biological Specimen Banks, Genome-Wide Association Study, Molecular Targeted Therapy, United Kingdom, Loss of Function Mutation, Phenomics
Abstract: Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of the protein. This includes ZNF529:p.K405X, which is associated with decreased low-density-lipoprotein (LDL) cholesterol (P = 1.3 × 10-8) without being associated with liver enzymes or non-fasting blood glucose. Silencing of ZNF529 in human hepatoma cells results in upregulation of LDL receptor and increased LDL uptake in the cells. This suggests that inhibition of ZNF529 or its gene product should be prioritized as a novel candidate drug target for treating dyslipidemia and associated CVD.
Published: 2020

48. Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

Author: Yaghootkar, Hanieh, Zhang, Yiying, Spracklen, Cassandra N, Karaderi, Tugce, Huang, Lam Opal, Bradfield, Jonathan, Schurmann, Claudia, Fine, Rebecca S, Preuss, Michael H, Kutalik, Zoltan, Wittemans, Laura BL, Lu, Yingchang, Metz, Sophia, Willems, Sara M, Li-Gao, Ruifang, Grarup, Niels, Wang, Shuai, Molnos, Sophie, Sandoval-Zárate, América A, Nalls, Mike A, Lange, Leslie A, Haesser, Jeffrey, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Feitosa, Mary F, Sitlani, Colleen M, Venturini, Cristina, Mahajan, Anubha, Kacprowski, Tim, Wang, Carol A, Chasman, Daniel I, Amin, Najaf, Broer, Linda, Robertson, Neil, Young, Kristin L, Allison, Matthew, Auer, Paul L, Blüher, Matthias, Borja, Judith B, Bork-Jensen, Jette, Carrasquilla, Germán D, Christofidou, Paraskevi, Demirkan, Ayse, Doege, Claudia A, Garcia, Melissa E, Graff, Mariaelisa, Guo, Kaiying, Hakonarson, Hakon, Hong, Jaeyoung, Ida Chen, Yii-Der, Jackson, Rebecca, Jakupović, Hermina, Jousilahti, Pekka, Justice, Anne E, Kähönen, Mika, Kizer, Jorge R, Kriebel, Jennifer, LeDuc, Charles A, Li, Jin, Lind, Lars, Luan, Jian'an, Mackey, David A, Mangino, Massimo, Männistö, Satu, Martin Carli, Jayne F, Medina-Gomez, Carolina, Mook-Kanamori, Dennis O, Morris, Andrew P, de Mutsert, Renée, Nauck, Matthias, Prokic, Ivana, Pennell, Craig E, Pradhan, Arund D, Psaty, Bruce M, Raitakari, Olli T, Scott, Robert A, Skaaby, Tea, Strauch, Konstantin, Taylor, Kent D, Teumer, Alexander, Uitterlinden, Andre G, Wu, Ying, Yao, Jie, Walker, Mark, North, Kari E, Kovacs, Peter, Ikram, M Arfan, van Duijn, Cornelia M, Ridker, Paul M, Lye, Stephen, Homuth, Georg, Ingelsson, Erik, Spector, Tim D, McKnight, Barbara, Province, Michael A, Lehtimäki, Terho, Adair, Linda S, Rotter, Jerome I, Reiner, Alexander P, and Wilson, James G
Subjects: Genetics, Nutrition, Prevention, Obesity, Aetiology, 2.1 Biological and endogenous factors, Oral and gastrointestinal, Metabolic and endocrine, Cardiovascular, Stroke, Cancer, Adiposity, Gene Expression Regulation, Developmental, Genetic Variation, Genotype, Humans, Leptin, Models, Molecular, Protein Conformation, Racial Groups, Medical and Health Sciences, Endocrinology & Metabolism
Abstract: Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.
Published: 2020

49. Association of CD14 with incident dementia and markers of brain aging and injury.

Author: Pase, Matthew P, Himali, Jayandra J, Beiser, Alexa S, DeCarli, Charles, McGrath, Emer R, Satizabal, Claudia L, Aparicio, Hugo J, Adams, Hieab HH, Reiner, Alexander P, Longstreth, WT, Fornage, Myriam, Tracy, Russell P, Lopez, Oscar, Psaty, Bruce M, Levy, Daniel, Seshadri, Sudha, and Bis, Joshua C
Subjects: Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Alzheimer's Disease, Clinical Research, Cardiovascular, Dementia, Acquired Cognitive Impairment, Aging, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Neurological, Aged, Aged, 80 and over, Atrophy, Biomarkers, Brain, Cognitive Dysfunction, Female, Humans, Incidence, Lipopolysaccharide Receptors, Longitudinal Studies, Male, Middle Aged, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract: ObjectiveTo test the hypothesis that the inflammatory marker plasma soluble CD14 (sCD14) associates with incident dementia and related endophenotypes in 2 community-based cohorts.MethodsOur samples included the prospective community-based Framingham Heart Study (FHS) and Cardiovascular Health Study (CHS) cohorts. Plasma sCD14 was measured at baseline and related to the incidence of dementia, domains of cognitive function, and MRI-defined brain volumes. Follow-up for dementia occurred over a mean of 10 years (SD 4) in the FHS and a mean of 6 years (SD 3) in the CHS.ResultsWe studied 1,588 participants from the FHS (mean age 69 ± 6 years, 47% male, 131 incident events) and 3,129 participants from the CHS (mean age 72 ± 5 years, 41% male, 724 incident events) for the risk of incident dementia. Meta-analysis across the 2 cohorts showed that each SD unit increase in sCD14 was associated with a 12% increase in the risk of incident dementia (95% confidence interval 1.03-1.23; p = 0.01) following adjustments for age, sex, APOE ε4 status, and vascular risk factors. Higher levels of sCD14 were associated with various cognitive and MRI markers of accelerated brain aging in both cohorts and with a greater progression of brain atrophy and a decline in executive function in the FHS.ConclusionsCD14 is an inflammatory marker related to brain atrophy, cognitive decline, and incident dementia.
Published: 2020

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

Author: Raffield, Laura M, Iyengar, Apoorva K, Wang, Biqi, Gaynor, Sheila M, Spracklen, Cassandra N, Zhong, Xue, Kowalski, Madeline H, Salimi, Shabnam, Polfus, Linda M, Benjamin, Emelia J, Bis, Joshua C, Bowler, Russell, Cade, Brian E, Choi, Won Jung, Comellas, Alejandro P, Correa, Adolfo, Cruz, Pedro, Doddapaneni, Harsha, Durda, Peter, Gogarten, Stephanie M, Jain, Deepti, Kim, Ryan W, Kral, Brian G, Lange, Leslie A, Larson, Martin G, Laurie, Cecelia, Lee, Jiwon, Lee, Seonwook, Lewis, Joshua P, Metcalf, Ginger A, Mitchell, Braxton D, Momin, Zeineen, Muzny, Donna M, Pankratz, Nathan, Park, Cheol Joo, Rich, Stephen S, Rotter, Jerome I, Ryan, Kathleen, Seo, Daekwan, Tracy, Russell P, Viaud-Martinez, Karine A, Yanek, Lisa R, Zhao, Lue Ping, Lin, Xihong, Li, Bingshan, Li, Yun, Dupuis, Josée, Reiner, Alexander P, Mohlke, Karen L, Auer, Paul L, Group, TOPMed Inflammation Working, and Consortium, NHLBI Trans-Omics for Precision Medicine
Subjects: Human Genome, Clinical Research, Biotechnology, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Asian People, Black People, C-Reactive Protein, Cohort Studies, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, White People, Whole Genome Sequencing, TOPMed Inflammation Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, c-reactive protein, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract: Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (∼38× coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (∼10% and ∼1% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23 mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97 mg/L and major allele homozygotes with mean CRP of 4.11 mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.
Published: 2020

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