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

Author

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

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

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

Published
2023

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

Author

de Vries, Paul S., Conomos, Matthew P., Singh, Kuldeep, Nicholson, Christopher J., Jain, Deepti, Hasbani, Natalie R., Jiang, Wanlin, Lee, Sujin, Lino Cardenas, Christian L., Lutz, Sharon M., Wong, Doris, Guo, Xiuqing, Yao, Jie, Young, Erica P., Tcheandjieu, Catherine, Hilliard, Austin T., Bis, Joshua C., Bielak, Lawrence F., Brown, Michael R., Musharoff, Shaila, Clarke, Shoa L., Terry, James G., Palmer, Nicholette D., Yanek, Lisa R., Xu, Huichun, Heard-Costa, Nancy, Wessel, Jennifer, Selvaraj, Margaret Sunitha, Li, Rebecca H., Sun, Xiao, Turner, Adam W., Stilp, Adrienne M., Khan, Alyna, Newman, Anne B., Rasheed, Asif, Freedman, Barry I., Kral, Brian G., McHugh, Caitlin P., Hodonsky, Chani, Saleheen, Danish, Herrington, David M., Jacobs, Jr, David R., Nickerson, Deborah A., Boerwinkle, Eric, Wang, Fei Fei, Heiss, Gerardo, Jun, Goo, Kinney, Greg L., Sigurslid, Haakon H., Doddapaneni, HarshaVardhan, Hall, Ira M., Bensenor, Isabela M., Broome, Jai, Crapo, James D., Wilson, James G., Smith, Jennifer A., Blangero, John, Vargas, Jose D., Mosquera, Jose Verdezoto, Smith, Joshua D., Viaud-Martinez, Karine A., Ryan, Kathleen A., Young, Kendra A., Taylor, Kent D., Lange, Leslie A., Emery, Leslie S., Bittencourt, Marcio S., Budoff, Matthew J., Montasser, May E., Yu, Miao, Mahaney, Michael C., Mahamdeh, Mohammed S., Fornage, Myriam, Franceschini, Nora, Lotufo, Paulo A., Natarajan, Pradeep, Wong, Quenna, Mathias, Rasika A., Gibbs, Richard A., Do, Ron, Mehran, Roxana, Tracy, Russell P., Kim, Ryan W., Nelson, Sarah C., Damrauer, Scott M., Kardia, Sharon L. R., Rich, Stephen S., Fuster, Valentin, Napolioni, Valerio, Zhao, Wei, Tian, Wenjie, Yin, Xianyong, Min, Yuan-I, Manning, Alisa K., Peloso, Gina, Kelly, Tanika N., O’Donnell, Christopher J., Morrison, Alanna C., Curran, Joanne E., Zapol, Warren M., Bowden, Donald W., Becker, Lewis C., Correa, Adolfo, Mitchell, Braxton D., Psaty, Bruce M., Carr, John Jeffrey, Pereira, Alexandre C., Assimes, Themistocles L., Stitziel, Nathan O., Hokanson, John E., Laurie, Cecelia A., Rotter, Jerome I., Vasan, Ramachandran S., Post, Wendy S., Peyser, Patricia A., Miller, Clint L., and Malhotra, Rajeev

Published
2023
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4. Rare coding variants in RCN3 are associated with blood pressure

Author

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

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

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

Published
2022

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

Author

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

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

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

Published
2022

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

Author

Nakao, Tetsushi, Bick, Alexander G, Taub, Margaret A, Zekavat, Seyedeh M, Uddin, Md M, Niroula, Abhishek, Carty, Cara L, Lane, John, Honigberg, Michael C, Weinstock, Joshua S, Pampana, Akhil, Gibson, Christopher J, Griffin, Gabriel K, Clarke, Shoa L, Bhattacharya, Romit, Assimes, Themistocles L, Emery, Leslie S, Stilp, Adrienne M, Wong, Quenna, Broome, Jai, Laurie, Cecelia A, Khan, Alyna T, Smith, Albert V, Blackwell, Thomas W, Codd, Veryan, Nelson, Christopher P, Yoneda, Zachary T, Peralta, Juan M, Bowden, Donald W, Irvin, Marguerite R, Boorgula, Meher, Zhao, Wei, Yanek, Lisa R, Wiggins, Kerri L, Hixson, James E, Gu, C Charles, Peloso, Gina M, Roden, Dan M, Reupena, Muagututi’a S, Hwu, Chii-Min, DeMeo, Dawn L, North, Kari E, Kelly, Shannon, Musani, Solomon K, Bis, Joshua C, Lloyd-Jones, Donald M, Johnsen, Jill M, Preuss, Michael, Tracy, Russell P, Peyser, Patricia A, Qiao, Dandi, Desai, Pinkal, Curran, Joanne E, Freedman, Barry I, Tiwari, Hemant K, Chavan, Sameer, Smith, Jennifer A, Smith, Nicholas L, Kelly, Tanika N, Hidalgo, Bertha, Cupples, L Adrienne, Weeks, Daniel E, Hawley, Nicola L, Minster, Ryan L, Deka, Ranjan, Naseri, Take T, de las Fuentes, Lisa, Raffield, Laura M, Morrison, Alanna C, Vries, Paul S, Ballantyne, Christie M, Kenny, Eimear E, Rich, Stephen S, Whitsel, Eric A, Cho, Michael H, Shoemaker, M Benjamin, Pace, Betty S, Blangero, John, Palmer, Nicholette D, Mitchell, Braxton D, Shuldiner, Alan R, Barnes, Kathleen C, Redline, Susan, Kardia, Sharon LR, Abecasis, Gonçalo R, Becker, Lewis C, Heckbert, Susan R, He, Jiang, Post, Wendy, Arnett, Donna K, Vasan, Ramachandran S, Darbar, Dawood, Weiss, Scott T, McGarvey, Stephen T, de Andrade, Mariza, Chen, Yii-Der Ida, Kaplan, Robert C, Meyers, Deborah A, Custer, Brian S, and Correa, Adolfo

Subjects
Cardiovascular, Genetics, Aging, Heart Disease, Heart Disease - Coronary Heart Disease, Human Genome, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Published
2022

10. Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study

Author

Rhee, Eugene P, Surapaneni, Aditya, Zheng, Zihe, Zhou, Linda, Dutta, Diptavo, Arking, Dan E, Zhang, Jingning, Duong, ThuyVy, Chatterjee, Nilanjan, Luo, Shengyuan, Schlosser, Pascal, Mehta, Rupal, Waikar, Sushrut S, Saraf, Santosh L, Kelly, Tanika N, Hamm, Lee L, Rao, Panduranga S, Mathew, Anna V, Hsu, Chi-yuan, Parsa, Afshin, Vasan, Ramachandran S, Kimmel, Paul L, Clish, Clary B, Coresh, Josef, Feldman, Harold I, Grams, Morgan E, and Investigators, CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort Study

Subjects
Human Genome, Genetics, Kidney Disease, Aetiology, 2.1 Biological and endogenous factors, Renal and urogenital, Cohort Studies, Ethnicity, Female, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Polymorphism, Single Nucleotide, Renal Insufficiency, Chronic, GWAS, metabolomics, trans-ethnic meta-analysis, CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators, Clinical Sciences, Urology & Nephrology
Abstract

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

Published
2022

11. Whole-Genome Sequencing Association Analyses of Stroke and Its Subtypes in Ancestrally Diverse Populations From Trans-Omics for Precision Medicine Project

Author

Hu, Yao, Haessler, Jeffrey W, Manansala, Regina, Wiggins, Kerri L, Moscati, Arden, Beiser, Alexa, Heard-Costa, Nancy L, Sarnowski, Chloe, Raffield, Laura M, Chung, Jaeyoon, Marini, Sandro, Anderson, Christopher D, Rosand, Jonathan, Xu, Huichun, Sun, Xiao, Kelly, Tanika N, Wong, Quenna, Lange, Leslie A, Rotter, Jerome I, Correa, Adolfo, Vasan, Ramachandran S, Seshadri, Sudha, Rich, Stephen S, Do, Ron, Loos, Ruth JF, Longstreth, William T, Bis, Joshua C, Psaty, Bruce M, Tirschwell, David L, Assimes, Themistocles L, Silver, Brian, Liu, Simin, Jackson, Rebecca, Wassertheil-Smoller, Sylvia, Mitchell, Braxton D, Fornage, Myriam, Auer, Paul L, Reiner, Alex P, Kooperberg, Charles, and Group, the NHLBI Trans-Omics for Precision Medicine Consortium the Trans-Omics for Precision Medicine Stroke Working

Subjects
Epidemiology, Health Sciences, Human Genome, Neurosciences, Brain Disorders, Stroke, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Aged, Aged, 80 and over, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Precision Medicine, Racial Groups, Whole Genome Sequencing, atherosclerosis, blood pressure, cause of death, embolic stroke, sample size, Trans-Omics for Precision Medicine (TOPMed) Stroke Working Group, the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Neurology & Neurosurgery, Clinical sciences, Allied health and rehabilitation science
Abstract

Background and purposeStroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid).MethodsWhole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis.ResultsIn the single variant association analysis in TOPMed, we identified one novel locus 13q33 for large artery at whole-genome-wide significance (P

Published
2022

12. 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

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

Author

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

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

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

Published
2022

14. 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

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

Author

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

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

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

Published
2021

16. Atherosclerotic cardiovascular disease events among statin eligible individuals with and without long-term healthy arterial aging

Author

Razavi, Alexander C, Kelly, Tanika N, Budoff, Matthew J, Bazzano, Lydia A, He, Jiang, Fernandez, Camilo, Lima, Joao, Nasir, Khurram, Blumenthal, Roger S, Blaha, Michael J, and Whelton, Seamus P

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Clinical Research, Heart Disease - Coronary Heart Disease, Aging, Heart Disease, Patient Safety, Prevention, Cardiovascular, Atherosclerosis, Good Health and Well Being, Cardiovascular Diseases, Coronary Artery Disease, Female, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Middle Aged, Risk Assessment, Risk Factors, Vascular Calcification, Coronary artery calcium, Cardiovascular diseases, Multidetector computed tomography, Statins, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

Background and aimsA large proportion of statin eligible candidates have a baseline absence of coronary artery calcium (CAC) and low 10-year atherosclerotic cardiovascular disease (ASCVD) risk. We sought to determine the proportion of statin eligible individuals who had long-term healthy arterial aging (persistent CAC = 0) and their examined 15-year ASCVD outcomes.MethodsWe included 561 statin eligible candidates from the Multi-Ethnic Study of Atherosclerosis who were not on statin therapy with CAC = 0 at Visit 1 (2000-02) and underwent a subsequent CAC scan at Visit 5 (2010-11). Adjusted Cox proportional hazards regression assessed the association between persistent CAC = 0 and ASCVD events over 15.9 years.ResultsParticipants were on average 61.7 years old, 50% were women, and 43% maintained long-term CAC = 0. Individuals with an LDL-C ≥190 mg/dL (54%) and those with an ASCVD risk ≥20% (33%) had the highest and lowest proportion of persistent CAC = 0, respectively. There were 57 ASCVD events, and 15-year ASCVD event rates were low for individuals with and without healthy arterial aging (4.3 versus 8.6 per 1,000 persons-years), but the 10-year number needed to treat to prevent one ASCVD event differed by more than two fold (117 versus 54). In multivariable modeling, persistent CAC = 0 conferred a 51% lower risk of ASCVD compared to those with incident CAC (HR = 0.49, 95% CI: 0.27-0.90, p=0.02).ConclusionsMore than 40% of statin eligible individuals with baseline CAC = 0 had long-term healthy arterial aging. Statin eligible candidates with persistent CAC = 0 had a very low 15-year ASCVD risk, suggesting that statin therapy may be of limited benefit among this group of individuals.

Published
2021

17. 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

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

Author

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

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

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

Published
2021

20. Predicting Long-Term Absence of Coronary Artery Calcium in Metabolic Syndrome and Diabetes The MESA Study

Author

Razavi, Alexander C, Wong, Nathan, Budoff, Matthew, Bazzano, Lydia A, Kelly, Tanika N, He, Jiang, Fernandez, Camilo, Lima, Joao, Polak, Joseph F, Mongraw-Chaffin, Morgana, deFilippi, Chris, Szklo, Moyses, Bertoni, Alain G, Blumenthal, Roger S, Blaha, Michael J, and Whelton, Seamus P

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Clinical Research, Heart Disease - Coronary Heart Disease, Cardiovascular, Obesity, Atherosclerosis, Heart Disease, Nutrition, Aging, Prevention, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, Calcium, Coronary Artery Disease, Coronary Vessels, Diabetes Mellitus, Type 2, Female, Humans, Male, Metabolic Syndrome, Middle Aged, Predictive Value of Tests, Risk Factors, Vascular Calcification, aging, atherosclerosis, cardiovascular diseases, coronary artery calcium, diabetes mellitus, type 2, healthy lifestyle, metabolic syndrome, multidetector computed tomography, prevention, risk, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

ObjectivesThe purpose of this study was to identify predictors of healthy arterial aging (long-term coronary artery calcification [CAC] of 0) among individuals with metabolic syndrome (MetS) or type 2 diabetes (T2D), which may improve primary prevention strategies.BackgroundIndividuals with MetS or T2D have a heterogeneously increased risk of atherosclerotic cardiovascular disease and not all have a high-intermediate risk.MethodsWe included 574 participants from the MESA (Multi-Ethnic Study of Atherosclerosis) with MetS or T2D who had CAC=0 at baseline and a repeat CAC scan 10 years later. Multivariable logistic regression assessed the association of traditional and novel atherosclerotic cardiovascular disease risk factors and the MetS severity score (based on the 5 MetS criteria) with healthy arterial aging.ResultsThe mean age of participants was 58.9 years, 67% were women, 422 participants had MetS, and 152 had T2D. The proportion with long-term CAC=0 was similar for MetS (42%) and T2D (44%). A younger age was the only individual low/normal traditional risk factor associated with an increased likelihood of long-term CAC=0 (odds ratio [OR]: 1.50; 95% confidence interval [CI]: 1.22 to 1.85 per 10-years younger). The strongest associations of nontraditional risk factors were observed for an absence of thoracic calcification (OR: 2.42; 95% CI: 1.24 to 4.72), absence of carotid plaque (OR: 1.81; 95% CI: 1.25 to 2.61), and among persons with a high sensitivity troponin

Published
2021

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

Author

Saunders, Gretchen R. B., Wang, Xingyan, Chen, Fang, Jang, Seon-Kyeong, Liu, Mengzhen, Wang, Chen, Gao, Shuang, Jiang, Yu, Khunsriraksakul, Chachrit, Otto, Jacqueline M., Addison, Clifton, Akiyama, Masato, Albert, Christine M., Aliev, Fazil, Alonso, Alvaro, Arnett, Donna K., Ashley-Koch, Allison E., Ashrani, Aneel A., Barnes, Kathleen C., Barr, R. Graham, Bartz, Traci M., Becker, Diane M., Bielak, Lawrence F., Benjamin, Emelia J., Bis, Joshua C., Bjornsdottir, Gyda, Blangero, John, Bleecker, Eugene R., Boardman, Jason D., Boerwinkle, Eric, Boomsma, Dorret I., Boorgula, Meher Preethi, Bowden, Donald W., Brody, Jennifer A., Cade, Brian E., Chasman, Daniel I., Chavan, Sameer, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Iona, Cho, Michael H., Choquet, Hélène, Cole, John W., Cornelis, Marilyn C., Cucca, Francesco, Curran, Joanne E., de Andrade, Mariza, Dick, Danielle M., Docherty, Anna R., Duggirala, Ravindranath, Eaton, Charles B., Ehringer, Marissa A., Esko, Tõnu, Faul, Jessica D., Silva, Lilian Fernandes, Fiorillo, Edoardo, Fornage, Myriam, Freedman, Barry I., Gabrielsen, Maiken E., Garrett, Melanie E., Gharib, Sina A., Gieger, Christian, Gillespie, Nathan, Glahn, David C., Gordon, Scott D., Gu, Charles C., Gu, Dongfeng, Gudbjartsson, Daniel F., Guo, Xiuqing, Haessler, Jeffrey, Hall, Michael E., Haller, Toomas, Harris, Kathleen Mullan, He, Jiang, Herd, Pamela, Hewitt, John K., Hickie, Ian, Hidalgo, Bertha, Hokanson, John E., Hopfer, Christian, Hottenga, JoukeJan, Hou, Lifang, Huang, Hongyan, Hung, Yi-Jen, Hunter, David J., Hveem, Kristian, Hwang, Shih-Jen, Hwu, Chii-Min, Iacono, William, Irvin, Marguerite R., Jee, Yon Ho, Johnson, Eric O., Joo, Yoonjung Y., Jorgenson, Eric, Justice, Anne E., Kamatani, Yoichiro, Kaplan, Robert C., Kaprio, Jaakko, Kardia, Sharon L. R., Keller, Matthew C., Kelly, Tanika N., Kooperberg, Charles, Korhonen, Tellervo, Kraft, Peter, Krauter, Kenneth, Kuusisto, Johanna, Laakso, Markku, Lasky-Su, Jessica, Lee, Wen-Jane, Lee, James J., Levy, Daniel, Li, Liming, Li, Kevin, Li, Yuqing, Lin, Kuang, Lind, Penelope A., Liu, Chunyu, Lloyd-Jones, Donald M., Lutz, Sharon M., Ma, Jiantao, Mägi, Reedik, Manichaikul, Ani, Martin, Nicholas G., Mathur, Ravi, Matoba, Nana, McArdle, Patrick F., McGue, Matt, McQueen, Matthew B., Medland, Sarah E., Metspalu, Andres, Meyers, Deborah A., Millwood, Iona Y., Mitchell, Braxton D., Mohlke, Karen L., Moll, Matthew, Montasser, May E., Morrison, Alanna C., Mulas, Antonella, Nielsen, Jonas B., North, Kari E., Oelsner, Elizabeth C., Okada, Yukinori, Orrù, Valeria, Palmer, Nicholette D., Palviainen, Teemu, Pandit, Anita, Park, S. Lani, Peters, Ulrike, Peters, Annette, Peyser, Patricia A., Polderman, Tinca J. C., Rafaels, Nicholas, Redline, Susan, Reed, Robert M., Reiner, Alex P., Rice, John P., Rich, Stephen S., Richmond, Nicole E., Roan, Carol, Rotter, Jerome I., Rueschman, Michael N., Runarsdottir, Valgerdur, Saccone, Nancy L., Schwartz, David A., Shadyab, Aladdin H., Shi, Jingchunzi, Shringarpure, Suyash S., Sicinski, Kamil, Skogholt, Anne Heidi, Smith, Jennifer A., Smith, Nicholas L., Sotoodehnia, Nona, Stallings, Michael C., Stefansson, Hreinn, Stefansson, Kari, Stitzel, Jerry A., Sun, Xiao, Syed, Moin, Tal-Singer, Ruth, Taylor, Amy E., Taylor, Kent D., Telen, Marilyn J., Thai, Khanh K., Tiwari, Hemant, Turman, Constance, Tyrfingsson, Thorarinn, Wall, Tamara L., Walters, Robin G., Weir, David R., Weiss, Scott T., White, Wendy B., Whitfield, John B., Wiggins, Kerri L., Willemsen, Gonneke, Willer, Cristen J., Winsvold, Bendik S., Xu, Huichun, Yanek, Lisa R., Yin, Jie, Young, Kristin L., Young, Kendra A., Yu, Bing, Zhao, Wei, Zhou, Wei, Zöllner, Sebastian, Zuccolo, Luisa, Batini, Chiara, Bergen, Andrew W., Bierut, Laura J., David, Sean P., Gagliano Taliun, Sarah A., Hancock, Dana B., Jiang, Bibo, Munafò, Marcus R., Thorgeirsson, Thorgeir E., Liu, Dajiang J., and Vrieze, Scott

Published
2022
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23. Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Author

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

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

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

Published
2020

24. Coronary Artery Calcium and the Age-Specific Competing Risk of Cardiovascular Versus Cancer Mortality: The Coronary Artery Calcium Consortium

Author

Whelton, Seamus P, Rifai, Mahmoud Al, Marshall, Catherine Handy, Dardari, Zeina, Shaw, Leslee J, Al-Mallah, Mouaz H, Rozanski, Alan, Mortensen, Martin B, Dzaye, Omar, Bazzano, Lydia, Kelly, Tanika N, Matsushita, Kunihiro, Rumberger, John A, Berman, Daniel S, Budoff, Matthew J, Miedema, Michael D, Nasir, Khurram, and Blaha, Michael J

Subjects
Biomedical and Clinical Sciences, Epidemiology, Public Health, Health Sciences, Clinical Sciences, Cardiovascular, Cancer, Prevention, Heart Disease - Coronary Heart Disease, Aging, Heart Disease, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Adult, Aged, Cardiac-Gated Imaging Techniques, Cardiovascular Diseases, Cause of Death, Coronary Artery Disease, Female, Humans, Male, Middle Aged, Neoplasms, Risk Assessment, Severity of Illness Index, Tomography, X-Ray Computed, Vascular Calcification, Age, Competing risk, Coranary artery calcium, Risk prediction, Coronary artery calcium, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundCoronary artery calcium (CAC) is a guideline recommended cardiovascular disease (CVD) risk stratification tool that increases with age and is associated with non-cardiovascular disease outcomes including cancer. We sought to define the age-specific change in the association between CAC and cause-specific mortality.MethodsThe Coronary Artery Calcium Consortium includes 59,502 asymptomatic patients age 40-75 without known CVD. Age-stratified mortality rates and parametric survival regression modeling was performed to estimate the age-specific CAC score at which CVD and cancer mortality risk were equal.ResultsThe mean age was 54±8 years (67% men) and there were 2,423 deaths over a mean 12±3 years follow-up. Among individuals with CAC = 0, cancer was the leading cause of death, with low CVD mortality rates for both younger (40-54 years) 0.2/1,000 person-years and older participants (65-75 years) 1.3/1,000 person-years. When CAC ≥400, CVD was consistently the leading cause of death among younger (71% of deaths) and older participants (56% of deaths). The CAC score at which CVD overtook cancer as the leading cause of death increased exponentially with age and was approximately 115 at age 50 and 380 at age 65.ConclusionsRegardless of age, when CAC = 0 cancer was the leading cause of death and the cardiovascular disease mortality rate was low. Our age-specific estimate for the CAC score at which CVD overtakes cancer mortality allows for a more precise approach to synergistic prediction and prevention strategies for CVD and cancer.

Published
2020

25. Metabolomic Markers of Kidney Function Decline in Patients With Diabetes: Evidence From the Chronic Renal Insufficiency Cohort (CRIC) Study.

Author

Kwan, Brian, Fuhrer, Tobias, Zhang, Jing, Darshi, Manjula, Van Espen, Benjamin, Montemayor, Daniel, de Boer, Ian H, Dobre, Mirela, Hsu, Chi-Yuan, Kelly, Tanika N, Raj, Dominic S, Rao, Panduranga S, Saraf, Santosh L, Scialla, Julia, Waikar, Sushrut S, Sharma, Kumar, Natarajan, Loki, and CRIC Study Investigators

Subjects
CRIC Study Investigators, Humans, Diabetic Nephropathies, Disease Progression, Glomerular Filtration Rate, Cohort Studies, Prospective Studies, Aged, Middle Aged, Female, Male, Renal Insufficiency, Chronic, Metabolomics, Biomarkers, Biomarker, Chronic Renal Insufficiency Cohort, chronic kidney disease, diabetes, end-stage renal disease, estimated glomerular filtration rate, incident kidney failure, kidney disease progression, kidney function decline, longitudinal study, metabolomics, multivariate model, prediction, prognosis, risk factor, Prevention, Clinical Research, Diabetes, Kidney Disease, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, Renal and urogenital, Metabolic and endocrine, Good Health and Well Being, Clinical Sciences, Public Health and Health Services, Urology & Nephrology
Abstract

Rationale & objectiveBiomarkers that provide reliable evidence of future diabetic kidney disease (DKD) are needed to improve disease management. In a cross-sectional study, we previously identified 13 urine metabolites that had levels reduced in DKD compared with healthy controls. We evaluated associations of these 13 metabolites with future DKD progression.Study designProspective cohort.Setting & participants1,001 Chronic Renal Insufficiency Cohort (CRIC) participants with diabetes with estimated glomerular filtration rates (eGFRs) between 20 and 70mL/min/1.73m2 were followed up prospectively for a median of 8 (range, 2-10) years.Predictors13 urine metabolites, age, race, sex, smoked more than 100 cigarettes in lifetime, body mass index, hemoglobin A1c level, blood pressure, urinary albumin, and eGFR.OutcomesAnnual eGFR slope and time to incident kidney failure with replacement therapy (KFRT; ie, initiation of dialysis or receipt of transplant).Analytical approachSeveral clinical metabolite models were developed for eGFR slope as the outcome using stepwise selection and penalized regression, and further tested on the time-to-KFRT outcome. A best cross-validated (final) prognostic model was selected based on high prediction accuracy for eGFR slope and high concordance statistic for incident KFRT.ResultsDuring follow-up, mean eGFR slope was-1.83±1.92 (SD) mL/min/1.73m2 per year; 359 (36%) participants experienced KFRT. Median time to KFRT was 7.45 years from the time of entry to the CRIC Study. In our final model, after adjusting for clinical variables, levels of metabolites 3-hydroxyisobutyrate (3-HIBA) and 3-methylcrotonyglycine had a significant negative association with eGFR slope, whereas citric and aconitic acid were positively associated. Further, 3-HIBA and aconitic acid levels were associated with higher and lower risk for KFRT, respectively (HRs of 2.34 [95% CI, 1.51-3.62] and 0.70 [95% CI, 0.51-0.95]).LimitationsSubgroups for whom metabolite signatures may not be optimal, nontargeted metabolomics by flow-injection analysis, and 2-stage modeling approaches.ConclusionsUrine metabolites may offer insights into DKD progression. If replicated in future studies, aconitic acid and 3-HIBA could identify individuals with diabetes at high risk for GFR decline, potentially leading to improved clinical care and targeted therapies.

Published
2020

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

Author

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

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

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

Published
2019

27. Novel serum metabolites associate with cognition phenotypes among Bogalusa Heart Study participants

Author

Shi, Mengyao, Bazzano, Lydia A, He, Jiang, Gu, Xiaoying, Li, Changwei, Li, Shengxu, Yaffe, Kristine, Kinchen, Jason M, Stuchlik, Patrick, Mi, Xuenan, Nierenberg, Jovia L, Razavi, Alexander C, and Kelly, Tanika N

Subjects
Digestive Diseases, Good Health and Well Being, Cognition, Cross-Sectional Studies, Female, Humans, Longitudinal Studies, Male, Metabolome, Metabolomics, Middle Aged, Phenotype, metabolomics, metabolite network, dementia, Alzheimer's disease, cognition, Alzheimer’s disease, Biochemistry and Cell Biology, Physiology, Oncology and Carcinogenesis, Developmental Biology
Abstract

BackgroundMetabolomics study provides an opportunity to identify novel molecular determinants of altered cognitive function.MethodsDuring 2013 to 2016 Bogalusa Heart Study (BHS) visit, 1,177 participants underwent untargeted, ultrahigh performance liquid chromatography-tandem mass spectroscopy metabolomics profiling. Global cognition and five cognition domains were also assessed. The cross-sectional associations of single metabolites with cognition were tested using multiple linear regression models. Weighted correlation network analysis was used to examine the covariable-adjusted correlations of modules of co-abundant metabolites with cognition. Analyses were conducted in the overall sample and according to both ethnicity and sex.ResultsFive known metabolites and two metabolite modules robustly associated with cognition across overall and stratified analyses. Two metabolites were from lipid sub-pathways including fatty acid metabolism [9-hydroxystearate; minimum P-value (min-P)=1.11×10-5], and primary bile acid metabolism (glyco-alpha-muricholate; min-P=4.10×10-5). One metabolite from the glycogen metabolism sub-pathway (maltose; min-P=9.77×10-6), one from the polyamine metabolism sub-pathway (N-acetyl-isoputreanine; min-P=1.03×10-5), and one from the purine metabolism sub-pathway (7-methylguanine; min-P=1.19×10-5) were also identified. Two metabolite modules reflecting bile acid metabolism and androgenic steroids correlated with cognition (min-P=5.00×10-4 and 3.00×10-3, respectively).ConclusionThe novel associations of 5 known metabolites and 2 metabolite modules with cognition provide insights into the physiological mechanisms regulating cognitive function.

Published
2019

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

Author

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

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

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

Published
2019

30. Novel Metabolites Associated With Blood Pressure After Dietary Interventions.

Author

Yixi Sun, Ruiyuan Zhang, Ling Tian, Yang Pan, Xiao Sun, Zhijie Huang, Jia Fan, Jing Chen, Kai Zhang, Shengxu Li, Wei Chen, Bazzano, Lydia A., Kelly, Tanika N., Jiang He, Bundy, Joshua D., and Changwei Li

Abstract

BACKGROUND: The blood pressure (BP) etiologic study is complex due to multifactorial influences, including genetic, environmental, lifestyle, and their intricate interplays. We used a metabolomics approach to capture internal pathways and external exposures and to study BP regulation mechanisms after well-controlled dietary interventions. METHODS: In the ProBP trail (Protein and Blood Pressure), a double-blinded crossover randomized controlled trial, participants underwent dietary interventions of carbohydrate, soy protein, and milk protein, receiving 40 g daily for 8 weeks, with 3-week washout periods. We measured plasma samples collected at baseline and at the end of each dietary intervention. Multivariate linear models were used to evaluate the association between metabolites and systolic/diastolic BP. Nominally significant metabolites were examined for enriching biological pathways. Significant ProBP findings were evaluated for replication among 1311 participants of the BHS (Bogalusa Heart Study), a population-based study conducted in the same area as ProBP. RESULTS: After Bonferroni correction for 77 independent metabolite clusters (α=6.49x10-4), 18 metabolites were significantly associated with BP at baseline or the end of a dietary intervention, of which 11 were replicated in BHS. Seven emerged as novel discoveries, which are as follows: 1-linoleoyl-GPE (18:2), 1-oleoyl-GPE (18:1), 1-stearoyl-2-linoleoyl-GPC (18:0/18:2), 1-palmitoyl-2-oleoyl-GPE (16:0/18:1), maltose, N-stearoyl-sphinganine (d18:0/18:0), and N6-carbamoylthreonyladenosine. Pathway enrichment analyses suggested dietary protein intervention might reduce BP through pathways related to G protein--coupled receptors, incretin function, selenium micronutrient network, and mitochondrial biogenesis. CONCLUSIONS: Seven novel metabolites were identified to be associated with BP at the end of different dietary interventions. The beneficial effects of protein interventions might be mediated through specific metabolic pathways. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Multi-ancestry genome-wide gene–sleep interactions identify novel loci for blood pressure

Author

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

Published
2021
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37. Genome-Wide Association Study Meta-Analysis of Long-Term Average Blood Pressure in East Asians

Author

Li, Changwei, Kim, Yun Kyoung, Dorajoo, Rajkumar, Li, Huaixing, Lee, I-Te, Cheng, Ching-Yu, He, Meian, Sheu, Wayne H-H, Guo, Xiuqing, Ganesh, Santhi K, He, Jiang, Lee, Juyoung, Liu, Jianjun, Hu, Yao, Rao, Dabeeru C, Tsai, Fuu-Jen, Koh, Jia Yu, Hu, Hua, Liang, Kae-Woei, Palmas, Walter, Hixson, James E, Han, Sohee, Teo, Yik-Ying, Wang, Yiqin, Chen, Jing, Lu, Chieh Hsiang, Zheng, Yingfeng, Gui, Lixuan, Lee, Wen-Jane, Yao, Jie, Gu, Dongfeng, Han, Bok-Ghee, Sim, Xueling, Sun, Liang, Zhao, Jinying, Chen, Chien-Hsiun, Kumari, Neelam, He, Yunfeng, Taylor, Kent D, Raffel, Leslie J, Moon, Sanghoon, Rotter, Jerome I, Ida Chen, Yii-der, Wu, Tangchun, Wong, Tien Yin, Wu, Jer-Yuarn, Lin, Xu, Tai, E-Shyong, Kim, Bong-Jo, and Kelly, Tanika N

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Biotechnology, Genetics, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Asian People, Blood Pressure, Asia, Eastern, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Phenotype, Polymorphism, Single Nucleotide, arterial pressure, blood pressure, epidemiology, genome-wide association study, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundGenome-wide single marker and gene-based meta-analyses of long-term average (LTA) blood pressure (BP) phenotypes may reveal novel findings for BP.Methods and resultsWe conducted genome-wide analysis among 18 422 East Asian participants (stage 1) followed by replication study of ≤46 629 participants of European ancestry (stage 2). Significant single-nucleotide polymorphisms and genes were determined by a P

Published
2017

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

Author

Armstrong, Nicole D., primary, Srinivasasainagendra, Vinodh, additional, Ammous, Farah, additional, Assimes, Themistocles L., additional, Beitelshees, Amber L., additional, Brody, Jennifer, additional, Cade, Brian E., additional, Ida Chen, Yii-Der, additional, Chen, Han, additional, de Vries, Paul S., additional, Floyd, James S., additional, Franceschini, Nora, additional, Guo, Xiuqing, additional, Hellwege, Jacklyn N., additional, House, John S., additional, Hwu, Chii-Min, additional, Kardia, Sharon L. R., additional, Lange, Ethan M., additional, Lange, Leslie A., additional, McDonough, Caitrin W., additional, Montasser, May E., additional, O’Connell, Jeffrey R., additional, Shuey, Megan M., additional, Sun, Xiao, additional, Tanner, Rikki M., additional, Wang, Zhe, additional, Zhao, Wei, additional, Carson, April P., additional, Edwards, Todd L., additional, Kelly, Tanika N., additional, Kenny, Eimear E., additional, Kooperberg, Charles, additional, Loos, Ruth J. F., additional, Morrison, Alanna C., additional, Motsinger-Reif, Alison, additional, Psaty, Bruce M., additional, Rao, Dabeeru C., additional, Redline, Susan, additional, Rich, Stephen S., additional, Rotter, Jerome I., additional, Smith, Jennifer A., additional, Smith, Albert V., additional, Irvin, Marguerite R., additional, and Arnett, Donna K., additional

Published
2023
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41. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study

Author

Wang, Yuxuan, primary, Selvaraj, Margaret Sunitha, additional, Li, Xihao, additional, Li, Zilin, additional, Holdcraft, Jacob A., additional, Arnett, Donna K., additional, Bis, Joshua C., additional, Blangero, John, additional, Boerwinkle, Eric, additional, Bowden, Donald W., additional, Cade, Brian E., additional, Carlson, Jenna C., additional, Carson, April P., additional, Chen, Yii-Der Ida, additional, Curran, Joanne E., additional, de Vries, Paul S., additional, Dutcher, Susan K., additional, Ellinor, Patrick T., additional, Floyd, James S., additional, Fornage, Myriam, additional, Freedman, Barry I., additional, Gabriel, Stacey, additional, Germer, Soren, additional, Gibbs, Richard A., additional, Guo, Xiuqing, additional, He, Jiang, additional, Heard-Costa, Nancy, additional, Hildalgo, Bertha, additional, Hou, Lifang, additional, Irvin, Marguerite R., additional, Joehanes, Roby, additional, Kaplan, Robert C., additional, Kardia, Sharon LR., additional, Kelly, Tanika N., additional, Kim, Ryan, additional, Kooperberg, Charles, additional, Kral, Brian G., additional, Levy, Daniel, additional, Li, Changwei, additional, Liu, Chunyu, additional, Lloyd-Jone, Don, additional, Loos, Ruth JF., additional, Mahaney, Michael C., additional, Martin, Lisa W., additional, Mathias, Rasika A., additional, Minster, Ryan L., additional, Mitchell, Braxton D., additional, Montasser, May E., additional, Morrison, Alanna C., additional, Murabito, Joanne M., additional, Naseri, Take, additional, O'Connell, Jeffrey R., additional, Palmer, Nicholette D., additional, Preuss, Michael H., additional, Psaty, Bruce M., additional, Raffield, Laura M., additional, Rao, Dabeeru C., additional, Redline, Susan, additional, Reiner, Alexander P., additional, Rich, Stephen S., additional, Ruepena, Muagututi’a Sefuiva, additional, Sheu, Wayne H.-H., additional, Smith, Jennifer A., additional, Smith, Albert, additional, Tiwari, Hemant K., additional, Tsai, Michael Y., additional, Viaud-Martinez, Karine A., additional, Wang, Zhe, additional, Yanek, Lisa R., additional, Zhao, Wei, additional, Rotter, Jerome I., additional, Lin, Xihong, additional, Natarajan, Pradeep, additional, and Peloso, Gina M., additional

Published
2023
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48. Novel associations between blood metabolites and kidney function among Bogalusa Heart Study and Multi-Ethnic Study of Atherosclerosis participants

Author

Nierenberg, Jovia L., He, Jiang, Li, Changwei, Gu, Xiaoying, Shi, Mengyao, Razavi, Alexander C., Mi, Xuenan, Li, Shengxu, Bazzano, Lydia A., Anderson, Amanda H., He, Hua, Chen, Wei, Kinchen, Jason M., Rebholz, Casey M., Coresh, Josef, Levey, Andrew S., Inker, Lesley A., Shlipak, Michael, and Kelly, Tanika N.

Published
2019
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49. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Author

Noordam, Raymond, Bos, Maxime M., Wang, Heming, Winkler, Thomas W., Bentley, Amy R., Kilpeläinen, Tuomas O., de Vries, Paul S., Sung, Yun Ju, Schwander, Karen, Cade, Brian E., Manning, Alisa, Aschard, Hugues, Brown, Michael R., Chen, Han, Franceschini, Nora, Musani, Solomon K., Richard, Melissa, Vojinovic, Dina, Aslibekyan, Stella, Bartz, Traci M., de las Fuentes, Lisa, Feitosa, Mary, Horimoto, Andrea R., Ilkov, Marjan, Kho, Minjung, Kraja, Aldi, Li, Changwei, Lim, Elise, Liu, Yongmei, Mook-Kanamori, Dennis O., Rankinen, Tuomo, Tajuddin, Salman M., van der Spek, Ashley, Wang, Zhe, Marten, Jonathan, Laville, Vincent, Alver, Maris, Evangelou, Evangelos, Graff, Maria E., He, Meian, Kühnel, Brigitte, Lyytikäinen, Leo-Pekka, Marques-Vidal, Pedro, Nolte, Ilja M., Palmer, Nicholette D., Rauramaa, Rainer, Shu, Xiao-Ou, Snieder, Harold, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R., Adolfo, Correa, Ballantyne, Christie, Bielak, Larry, Biermasz, Nienke R., Boerwinkle, Eric, Dimou, Niki, Eiriksdottir, Gudny, Gao, Chuan, Gharib, Sina A., Gottlieb, Daniel J., Haba-Rubio, José, Harris, Tamara B., Heikkinen, Sami, Heinzer, Raphaël, Hixson, James E., Homuth, Georg, Ikram, M. Arfan, Komulainen, Pirjo, Krieger, Jose E., Lee, Jiwon, Liu, Jingmin, Lohman, Kurt K., Luik, Annemarie I., Mägi, Reedik, Martin, Lisa W., Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Nalls, Mike A., O’Connell, Jeff, Peters, Annette, Peyser, Patricia, Raitakari, Olli T., Reiner, Alex P., Rensen, Patrick C. N., Rice, Treva K., Rich, Stephen S., Roenneberg, Till, Rotter, Jerome I., Schreiner, Pamela J., Shikany, James, Sidney, Stephen S., Sims, Mario, Sitlani, Colleen M., Sofer, Tamar, Strauch, Konstantin, Swertz, Morris A., Taylor, Kent D., Uitterlinden, André G., van Duijn, Cornelia M., Völzke, Henry, Waldenberger, Melanie, Wallance, Robert B., van Dijk, Ko Willems, Yu, Caizheng, Zonderman, Alan B., Becker, Diane M., Elliott, Paul, Esko, Tõnu, Gieger, Christian, Grabe, Hans J., Lakka, Timo A., Lehtimäki, Terho, North, Kari E., Penninx, Brenda W. J. H., Vollenweider, Peter, Wagenknecht, Lynne E., Wu, Tangchun, Xiang, Yong-Bing, Zheng, Wei, Arnett, Donna K., Bouchard, Claude, Evans, Michele K., Gudnason, Vilmundur, Kardia, Sharon, Kelly, Tanika N., Kritchevsky, Stephen B., Loos, Ruth J. F., Pereira, Alexandre C., Province, Mike, Psaty, Bruce M., Rotimi, Charles, Zhu, Xiaofeng, Amin, Najaf, Cupples, L. Adrienne, Fornage, Myriam, Fox, Ervin F., Guo, Xiuqing, Gauderman, W. James, Rice, Kenneth, Kooperberg, Charles, Munroe, Patricia B., Liu, Ching-Ti, Morrison, Alanna C., Rao, Dabeeru C., van Heemst, Diana, and Redline, Susan

Published
2019
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