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1. Rare variant contribution to the heritability of coronary artery disease

Author

Ghislain Rocheleau, Shoa L. Clarke, Gaëlle Auguste, Natalie R. Hasbani, Alanna C. Morrison, Adam S. Heath, Lawrence F. Bielak, Kruthika R. Iyer, Erica P. Young, Nathan O. Stitziel, Goo Jun, Cecelia Laurie, Jai G. Broome, Alyna T. Khan, Donna K. Arnett, Lewis C. Becker, Joshua C. Bis, Eric Boerwinkle, Donald W. Bowden, April P. Carson, Patrick T. Ellinor, Myriam Fornage, Nora Franceschini, Barry I. Freedman, Nancy L. Heard-Costa, Lifang Hou, Yii-Der Ida Chen, Eimear E. Kenny, Charles Kooperberg, Brian G. Kral, Ruth J. F. Loos, Sharon M. Lutz, JoAnn E. Manson, Lisa W. Martin, Braxton D. Mitchell, Rami Nassir, Nicholette D. Palmer, Wendy S. Post, Michael H. Preuss, Bruce M. Psaty, Laura M. Raffield, Elizabeth A. Regan, Stephen S. Rich, Jennifer A. Smith, Kent D. Taylor, Lisa R. Yanek, Kendra A. Young, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Austin T. Hilliard, Catherine Tcheandjieu, Patricia A. Peyser, Ramachandran S. Vasan, Jerome I. Rotter, Clint L. Miller, Themistocles L. Assimes, Paul S. de Vries, and Ron Do

Subjects
Science
Abstract

Abstract Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Published
2024
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2. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups

Author

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

Subjects
Science
Abstract

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

Published
2023
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3. Perceptions of forensic scientists on statistical models, sequence data, and ethical implications for DNA evidence evaluations: A qualitative assessment

Author

Sanne E. Aalbers, Alyna T. Khan, and Bruce S. Weir

Subjects
Qualitative research, Next generation sequencing, Forensic statistics, DNA evidence Evaluations, Criminal law and procedure, K5000-5582
Abstract

With the introduction of next generation sequencing (NGS) technology in the forensic field, it will be of interest to assess if forensic scientists feel equipped to interpret and present DNA evidence for sequence data. Here, we describe perceptions of sixteen U.S.-based forensic scientists on statistical models, sequence data, and ethical implications for DNA evidence evaluations.To get an in-depth understanding of the current situation, we used a qualitative research approach with a cross-sectional study design. Semi-structured interviews (N = 16) were conducted with U.S. forensic scientists working with DNA evidence. Open-ended interview questions were used to explore participants’ views and needs surrounding the use of statistical models and sequence data for forensic purposes. We conducted a conventional content analysis using ATLAS. ti software and employed a second coder to ensure reliability of our results.Eleven themes emerged: 1) a statistical model that maximizes the value of the evidence is preferred; 2) a high-level understanding of the statistical model used is generally sufficient; 3) transparency is key in minimizing the risk of creating black boxes; 4) training and education should be an ongoing effort; 5) the effectiveness of presenting results in court can be improved; 6) NGS has the potential to become revolutionary; 7) some hesitations surrounding the use of sequence data remain; 8) there is a need for a concrete plan to alleviate barriers to the implementation of sequencing techniques; 9) ethics plays a major part in the role of a forensic scientist; 10) ethical barriers for sequence data depend on the application; 11) DNA evidence has its limitations.The results of this study give insight into the perceptions of forensic scientists regarding the use of statistical models and sequence data, providing valuable information in the move towards implementing sequencing methods for DNA evidence evaluations.

Published
2023
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4. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Author

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

Subjects
Science
Abstract

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

Published
2021
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5. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author

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

Subjects
Hypertension, Internal Medicine, Humans, Blood Pressure, Genomics, Precision Medicine, Polymorphism, Single Nucleotide, Genome-Wide Association Study
Abstract

Background: The 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. Methods: We 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. Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274 , was associated with lower systolic blood pressure in stage-1 (beta [SE]=−32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=−0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=−0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P -6 and P -4 , respectively). Discussion: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

Published
2023

6. Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: Experiences from the NHLBI TOPMed program

Author

Alyna T. Khan, Stephanie M. Gogarten, Caitlin P. McHugh, Adrienne M. Stilp, Tamar Sofer, Michael L. Bowers, Quenna Wong, L. Adrienne Cupples, Bertha Hidalgo, Andrew D. Johnson, Merry-Lynn N. McDonald, Stephen T. McGarvey, Matthew R.G. Taylor, Stephanie M. Fullerton, Matthew P. Conomos, and Sarah C. Nelson

Subjects
Article
Abstract

How race, ethnicity, and ancestry are used in genomic research has wide-ranging implications for how research is translated into clinical care and incorporated into public understanding. Correlation between race and genetic ancestry contributes to unresolved complexity for the scientific community, as illustrated by heterogeneous definitions and applications of these variables. Here, we offer commentary and recommendations on the use of race, ethnicity, and ancestry across the arc of genetic research, including data harmonization, analysis, and reporting. While informed by our experiences as researchers affiliated with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, these recommendations are applicable to basic and translational genomic research in diverse populations with genome-wide data. Moving forward, considerable collaborative effort will be required to ensure that race, ethnicity, and ancestry are described and used appropriately to generate scientific knowledge that yields broad and equitable benefit.

Published
2022

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

Author

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

Subjects
Multidisciplinary
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
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8. Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes

Author

George Hindy, Peter Dornbos, Mark D. Chaffin, Dajiang J. Liu, Minxian Wang, Margaret Sunitha Selvaraj, David Zhang, Joseph Park, Carlos A. Aguilar-Salinas, Lucinda Antonacci-Fulton, Diego Ardissino, Donna K. Arnett, Stella Aslibekyan, Gil Atzmon, Christie M. Ballantyne, Francisco Barajas-Olmos, Nir Barzilai, Lewis C. Becker, Lawrence F. Bielak, Joshua C. Bis, John Blangero, Eric Boerwinkle, Lori L. Bonnycastle, Erwin Bottinger, Donald W. Bowden, Matthew J. Bown, Jennifer A. Brody, Jai G. Broome, Noël P. Burtt, Brian E. Cade, Federico Centeno-Cruz, Edmund Chan, Yi-Cheng Chang, Yii-Der I. Chen, Ching-Yu Cheng, Won Jung Choi, Rajiv Chowdhury, Cecilia Contreras-Cubas, Emilio J. Córdova, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, John Danesh, Paul S. de Vries, Ralph A. DeFronzo, Harsha Doddapaneni, Ravindranath Duggirala, Susan K. Dutcher, Patrick T. Ellinor, Leslie S. Emery, Jose C. Florez, Myriam Fornage, Barry I. Freedman, Valentin Fuster, Ma. Eugenia Garay-Sevilla, Humberto García-Ortiz, Soren Germer, Richard A. Gibbs, Christian Gieger, Benjamin Glaser, Clicerio Gonzalez, Maria Elena Gonzalez-Villalpando, Mariaelisa Graff, Sarah E. Graham, Niels Grarup, Leif C. Groop, Xiuqing Guo, Namrata Gupta, Sohee Han, Craig L. Hanis, Torben Hansen, Jiang He, Nancy L. Heard-Costa, Yi-Jen Hung, Mi Yeong Hwang, Marguerite R. Irvin, Sergio Islas-Andrade, Gail P. Jarvik, Hyun Min Kang, Sharon L.R. Kardia, Tanika Kelly, Eimear E. Kenny, Alyna T. Khan, Bong-Jo Kim, Ryan W. Kim, Young Jin Kim, Heikki A. Koistinen, Charles Kooperberg, Johanna Kuusisto, Soo Heon Kwak, Markku Laakso, Leslie A. Lange, Jiwon Lee, Juyoung Lee, Seonwook Lee, Donna M. Lehman, Rozenn N. Lemaitre, Allan Linneberg, Jianjun Liu, Ruth J.F. Loos, Steven A. Lubitz, Valeriya Lyssenko, Ronald C.W. Ma, Lisa Warsinger Martin, Angélica Martínez-Hernández, Rasika A. Mathias, Stephen T. McGarvey, Ruth McPherson, James B. Meigs, Thomas Meitinger, Olle Melander, Elvia Mendoza-Caamal, Ginger A. Metcalf, Xuenan Mi, Karen L. Mohlke, May E. Montasser, Jee-Young Moon, Hortensia Moreno-Macías, Alanna C. Morrison, Donna M. Muzny, Sarah C. Nelson, Peter M. Nilsson, Jeffrey R. O’Connell, Marju Orho-Melander, Lorena Orozco, Colin N.A. Palmer, Nicholette D. Palmer, Cheol Joo Park, Kyong Soo Park, Oluf Pedersen, Juan M. Peralta, Patricia A. Peyser, Wendy S. Post, Michael Preuss, Bruce M. Psaty, Qibin Qi, D.C. Rao, Susan Redline, Alexander P. Reiner, Cristina Revilla-Monsalve, Stephen S. Rich, Nilesh Samani, Heribert Schunkert, Claudia Schurmann, Daekwan Seo, Jeong-Sun Seo, Xueling Sim, Rob Sladek, Kerrin S. Small, Wing Yee So, Adrienne M. Stilp, E. Shyong Tai, Claudia H.T. Tam, Kent D. Taylor, Yik Ying Teo, Farook Thameem, Brian Tomlinson, Michael Y. Tsai, Tiinamaija Tuomi, Jaakko Tuomilehto, Teresa Tusié-Luna, Miriam S. Udler, Rob M. van Dam, Ramachandran S. Vasan, Karine A. Viaud Martinez, Fei Fei Wang, Xuzhi Wang, Hugh Watkins, Daniel E. Weeks, James G. Wilson, Daniel R. Witte, Tien-Yin Wong, Lisa R. Yanek, Sekar Kathiresan, Daniel J. Rader, Jerome I. Rotter, Michael Boehnke, Mark I. McCarthy, Cristen J. Willer, Pradeep Natarajan, Jason A. Flannick, Amit V. Khera, Gina M. Peloso, NIH - National Heart, Lung, and Blood Institute (NHLBI) (Estados Unidos), Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institute for Molecular Medicine Finland, Leif Groop Research Group, Clinicum, Department of Medicine, HUS Internal Medicine and Rehabilitation, University of Helsinki, and Department of Public Health

Subjects
APOC3, Blood Glucose, Multifactorial Inheritance, gene-based association, Polymorphism, Single Nucleotide, Article, Open Reading Frames, ANGPTL3, lipid, OF-FUNCTION MUTATIONS, BINDING, Databases, Genetic, SEQUENCE VARIANTS, Genetics, Humans, Exome, Genetic Predisposition to Disease, SINUSOIDAL ENDOTHELIAL-CELLS, Genetics (clinical), Alleles, RISK, IDENTIFICATION, 1184 Genetics, developmental biology, physiology, association, cholesterol, Genetic Variation, Computational Biology, Molecular Sequence Annotation, PERILIPIN, Lipid Metabolism, Lipids, Genetics, Population, Phenotype, Diabetes Mellitus, Type 2, Liver, Case-Control Studies, exome sequencing, TRIGLYCERIDES, Genome-Wide Association Study
Abstract

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels. This work was supported by a grant from the Swedish Research Council (2016-06830) and grants from the National Heart, Lung, and Blood Institute (NHLBI): R01HL142711 and R01HL127564. Please refer to the supplemental information for the full acknowledgements. Sí

Published
2022
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9. Bidirectional Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of intermediate potential

Author

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

Subjects
Mendelian randomization, Locus (genetics), Telomerase reverse transcriptase, CAD, Computational biology, Biology, Causality, Germline, Telomere, Genetic association
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 Trans-Omics for Precision Medicine (TOPMed) program (N=63,302) and UK Biobank (N=48,658). Bidirectional Mendelian randomization studies were consistent with LTL lengthening increasing propensity to develop CHIP, but CHIP then in turn hastening LTL shortening. We also demonstrated evidence of modest mediation between CHIP and CAD by LTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Published
2021
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10. A system for phenotype harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) program

Author

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

Subjects
0301 basic medicine, Program evaluation, Computer science, Epidemiology, common data elements, hematologic disease, Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC], Medical and Health Sciences, Mathematical Sciences, 0302 clinical medicine, Documentation, cardiovascular disease, and Blood Institute (U.S.), 030212 general & internal medicine, Phenomics, Precision Medicine, Lung, lung diseases, Sleep-wake disorders, phenotypes, 92 Biology and other natural sciences::92B Mathematical biology in general [Classificació AMS], Common data elements, Cardiovascular disease, Phenotype, Phenotypes, Biomatemàtica, Information Dissemination, Harmonization, 62 Statistics::62D05 Sampling theory, sample surveys [Classificació AMS], Hematologic disease, 03 medical and health sciences, Data Aggregation, Clinical Research, Controlled vocabulary, Genetics, Humans, AcademicSubjects/MED00860, sleep-wake disorders, Sampling (Statistics), Genetic Association Studies, Lung diseases, Biomathematics, Data collection, Study Design, Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària [Àrees temàtiques de la UPC], Information dissemination, Human Genome, National Heart, Precision medicine, Data science, United States, 030104 developmental biology, Good Health and Well Being, National Heart, Lung, and Blood Institute (U.S.), Mostreig (Estadística), Program Evaluation
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

11. Rare coding variants in 35 genes associate with circulating lipid levels – a multi-ancestry analysis of 170,000 exomes

Author

Marju Orho-Melander, Humberto García-Ortiz, Xueling Sim, Amp-T D-Genes, Cheol Joo Park, Gina M. Peloso, Jason Flannick, Brian Tomlinson, Hyun Min Kang, Emilio J. Cordova, Stephen S. Rich, Richard A. Gibbs, Angélica Martínez-Hernández, Lorena Orozco, Harsha Doddapaneni, Lisa R. Yanek, Jiwon Lee, Namrata Gupta, Valeriya Lyssenko, Sohee Han, James B. Meigs, Bong-Jo Kim, Bruce M. Psaty, Leslie S. Emery, Kerrin S. Small, Pradeep Natarajan, May E. Montasser, Christian Gieger, Sharon L.R. Kardia, Sarah C. Nelson, Craig L. Hanis, Heikki A. Koistinen, María Elena González-Villalpando, Edmund Chan, Michael Y. Tsai, Benjamin Glaser, Thomas Meitinger, Matthew J. Bown, Mariaelisa Graff, John Danesh, Sekar Kathiresan, Tiinamaija Tuomi, Ramachandran S. Vasan, Gil Atzmon, Alyna T. Khan, Diego Ardissino, Yii-Der Ida Chen, David Zhang, Rob M. van Dam, Wendy S. Post, Barry I. Freedman, D. C. Rao, Michael Preuss, Donna M. Lehman, L. Adrienne Cupples, Colin N. A. Palmer, Claudia H. T. Tam, Hortensia Moreno-Macías, Markku Laakso, Peter Dornbos, Teresa Tusié-Luna, Stella Aslibekyan, Marguerite R. Irvin, Daniel J. Rader, Jee-Young Moon, Eimear E. Kenny, Lisa W. Martin, Jennifer A. Brody, Amit Khera, Erwin P. Bottinger, Sarah E. Graham, Myriam Fornage, Ruth McPherson, Nancy L. Heard-Costa, Michael Boehnke, Clicerio Gonzalez, Ryan W. Kim, Yi-Cheng Chang, Peter M. Nilsson, Yik Ying Teo, Robert Sladek, Cristen J. Willer, Fei Fei Wang, Donna K. Arnett, Mark Chaffin, Karine A. Viaud Martinez, Alanna C. Morrison, Leslie A. Lange, Ravindranath Duggirala, Donna M. Muzny, Kent D. Taylor, Niels Grarup, Soren Germer, Patricia A. Peyser, Brian E. Cade, Lewis C. Becker, Steven A. Lubitz, Nicholette D. Palmer, Susan K. Dutcher, Ronald C.W. Ma, Xuenan Mi, Xiuqing Guo, Hugh Watkins, Eric Boerwinkle, Qibin Qi, Johanna Kuusisto, Christie M. Ballantyne, Tanika N. Kelly, Rajiv Chowdhury, Elvia Mendoza-Caamal, Wing-Yee So, Tien Yin Wong, Torben Hansen, Cecilia Contreras-Cubas, Jeong-Sun Seo, Mi Yeong Hwang, Daekwan Seo, Dajiang J. Liu, Cristina Revilla-Monsalve, Paul S. de Vries, Daniel R. Witte, Yi-Jen Hung, Olle Melander, Karen L. Mohlke, Lucinda Antonacci-Fulton, Francisco Barajas-Olmos, Soo Heon Kwak, Daniel E. Weeks, Claudia Schurmann, Ginger A. Metcalf, Young-Jin Kim, Adrienne M. Stilp, Lori L. Bonnycastle, John Blangero, Ralph A. DeFronzo, Donald W. Bowden, Rasika A. Mathias, Oluf Pedersen, Rozenn N. Lemaitre, Stephen T. McGarvey, Heribert Schunkert, Jaakko Tuomilehto, Farook Thameem, Valentin Fuster, Joshua C. Bis, George Hindy, Allan Linneberg, James G. Wilson, Kyong Soo Park, Sergio A. Islas-Andrade, Ching-Yu Cheng, Won Jung Choi, Minxian X. Wang, Xuzhi Wang, Adolfo Correa, Jai G. Broome, Gail P. Jarvik, Alexander P. Reiner, E. Shyong Tai, Juyoung Lee, Mark I. McCarthy, Nilesh J. Samani, Susan Redline, Carlos A. Aguilar-Salinas, Jerome I. Rotter, Ma. Eugenia Garay-Sevilla, Jiang He, Patrick T. Ellinor, Joseph Park, Joanne E. Curran, Nir Barzilai, Federico Centeno-Cruz, Seonwook Lee, Lawrence F. Bielak, Jianjun Liu, Charles Kooperberg, Juan M. Peralta, Jose C. Florez, Leif Groop, Noël P. Burtt, Margaret Sunitha Selvaraj, Jeffrey R. O'Connell, and Ruth J. F. Loos

Subjects
Genetics, 0303 health sciences, education.field_of_study, Population, Single-nucleotide polymorphism, Genome-wide association study, Biology, DNA sequencing, Minor allele frequency, 03 medical and health sciences, 0302 clinical medicine, SNP, education, Gene, 030217 neurology & neurosurgery, Exome sequencing, 030304 developmental biology
Abstract

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels. Ten of these: ALB, SRSF2, JAK2, CREB3L3, TMEM136, VARS, NR1H3, PLA2G12A, PPARG and STAB1 have not been implicated for lipid levels using rare coding variation in population-based samples. We prioritize 32 genes identified in array-based genome-wide association study (GWAS) loci based on gene-based associations, of which three: EVI5, SH2B3, and PLIN1, had no prior evidence of rare coding variant associations. Most of the associated genes showed evidence of association in multiple ancestries. Also, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes, and for genes closest to GWAS index single nucleotide polymorphisms (SNP). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

Published
2020
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12. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Author

Pradeep Natarajan, Akhil Pampana, Sarah E. Graham, Sanni E. Ruotsalainen, James A. Perry, Paul S. de Vries, Jai G. Broome, James P. Pirruccello, Michael C. Honigberg, Krishna Aragam, Brooke Wolford, Jennifer A. Brody, Lucinda Antonacci-Fulton, Moscati Arden, Stella Aslibekyan, Themistocles L. Assimes, Christie M. Ballantyne, Lawrence F. Bielak, Joshua C. Bis, Brian E. Cade, Ron Do, Harsha Doddapaneni, Leslie S. Emery, Yi-Jen Hung, Marguerite R. Irvin, Alyna T. Khan, Leslie Lange, Jiwon Lee, Rozenn N. Lemaitre, Lisa W. Martin, Ginger Metcalf, May E. Montasser, Jee-Young Moon, Donna Muzny, Jeffrey R. O’Connell, Nicholette D. Palmer, Juan M. Peralta, Patricia A. Peyser, Adrienne M. Stilp, Michael Tsai, Fei Fei Wang, Daniel E. Weeks, Lisa R. Yanek, James G. Wilson, Goncalo Abecasis, Donna K. Arnett, Lewis C. Becker, John Blangero, Eric Boerwinkle, Donald W. Bowden, Yi-Cheng Chang, Yii-Der I. Chen, Won Jung Choi, Adolfo Correa, Joanne E. Curran, Mark J. Daly, Susan K. Dutcher, Patrick T. Ellinor, Myriam Fornage, Barry I. Freedman, Stacey Gabriel, Soren Germer, Richard A. Gibbs, Jiang He, Kristian Hveem, Gail P. Jarvik, Robert C. Kaplan, Sharon L. R. Kardia, Eimear Kenny, Ryan W. Kim, Charles Kooperberg, Cathy C. Laurie, Seonwook Lee, Don M. Lloyd-Jones, Ruth J. F. Loos, Steven A. Lubitz, Rasika A. Mathias, Karine A. Viaud Martinez, Stephen T. McGarvey, Braxton D. Mitchell, Deborah A. Nickerson, Kari E. North, Aarno Palotie, Cheol Joo Park, Bruce M. Psaty, D. C. Rao, Susan Redline, Alexander P. Reiner, Daekwan Seo, Jeong-Sun Seo, Albert V. Smith, Russell P. Tracy, Ramachandran S. Vasan, Sekar Kathiresan, L. Adrienne Cupples, Jerome I. Rotter, Alanna C. Morrison, Stephen S. Rich, Samuli Ripatti, Cristen Willer, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, FinnGen, Gina M. Peloso, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Centre of Excellence in Complex Disease Genetics, Research Programs Unit, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, Department of Public Health, Biostatistics Helsinki, Department of Clinical Chemistry and Hematology, Doctoral Programme in Social Sciences, HYKS erva, Päijät-Häme Welfare Consortium, Department of Medicine, HUS Inflammation Center, Clinicum, HUS Heart and Lung Center, Marja-Riitta Taskinen Research Group, Tiinamaija Tuomi Research Group, HUS Abdominal Center, Department of Oncology, Heikki Joensuu / Principal Investigator, HUS Comprehensive Cancer Center, Department of Medical and Clinical Genetics, Lauri Antti Aaltonen / Principal Investigator, HUS Head and Neck Center, Silmäklinikka, Department of Dermatology, Allergology and Venereology, Department of Food and Nutrition, Medicum, Data Science Genetic Epidemiology Lab, HUSLAB, Department of Mathematics and Statistics, University Management, Biosciences, Pregnancy and Genes, and HUS Gynecology and Obstetrics

Subjects
0301 basic medicine, Male, Apolipoprotein B, General Physics and Astronomy, Blood lipids, Adipose tissue, Genome-wide association study, 030204 cardiovascular system & hematology, Genome-wide association studies, PCSK9, 0302 clinical medicine, Subcutaneous Tissue, GENETIC-VARIANTS, Phenomics, X chromosome, RISK, Multidisciplinary, biology, 1184 Genetics, developmental biology, physiology, Middle Aged, Lipids, X-CHROMOSOME, CORONARY-ARTERY-DISEASE, Female, medicine.medical_specialty, CHOLESTEROL/APOLIPOPROTEIN-B RATIO, APOLIPOPROTEIN-B, Genotype, Science, Nerve Tissue Proteins, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Diabetes mellitus, Internal medicine, medicine, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Allele, Eye Proteins, Genetic Association Studies, Chromosomes, Human, X, DENSITY-LIPOPROTEIN-CHOLESTEROL, Whole Genome Sequencing, business.industry, Cardiometabolic Risk Factors, FAT DISTRIBUTION, General Chemistry, Cardiovascular genetics, medicine.disease, 030104 developmental biology, Endocrinology, Gene Expression Regulation, Genetic Loci, biology.protein, business
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., The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

Published
2020

13. A system for phenotype harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Author

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

Subjects
Data sharing, Documentation, Data collection, Computer science, Controlled vocabulary, Harmonization, Precision medicine, Omics, Data science, Phenotype, Domain (software engineering), Genetic association
Abstract

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase 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 >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 TOPMed studies per phenotype. We discuss the challenges faced 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 code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

Published
2020
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14. Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries

Author

Cashell E. Jaquish, Craig P. Hersh, Emily Barron-Casella, Larry Phillips, James S. Pankow, JoAnn E. Manson, Mariza de Andrade, Vivien A. Sheehan, Norann A. Zaghloul, Yongmei Liu, Sergei Nekhai, Russell P. Tracy, Bruce S. Weir, Pankaj Qasba, Adrienne M. Stilp, Tasha E. Fingerlin, Heather M. Ochs-Balcom, L. Adrienne Cupples, Rongze Yang, David A. Schwartz, Shannon Kelly, Scott E. Devine, Tanja Smith, G.L. Kinney, Beverly Snively, Kent D. Taylor, Manolis Kellis, Ruth J. F. Loos, Seth A. Ament, Kathleen C. Barnes, Robert C. Kaplan, Ulrich Broeckel, Hemant K. Tiwari, Karin F. Hoth, Peter Durda, Julie L. Mikulla, Charles B. Eaton, Cotton Seed, Merry Lynn McDonald, Eric Boerwinkle, Josh Smith, Honghuang Lin, Ingrid B. Borecki, Jeffrey L. Curtis, Emelia J. Benjamin, Kenneth Rice, Sharon L.R. Kardia, Nicholas L. Smith, Coleen M. Damcott, Jeffrey Haessler, Kimberly L. Jones, Elaine Cornell, Nona Sotoodehnia, Adolfo Correa, Rich Johnston, C. Charles Gu, Chii Min Hwu, Peter C. Anderson, Lesley F. Tinker, Colleen Davis, R. Graham Barr, Scott T. Weiss, Leanna Farnam, Chao Hsiung, Brian Silver, Patrick F. McArdle, Lisa W. Martin, Yii-Der Ida Chen, John Barnard, Holly Kramer, Sekar Kathiresan, Gonçalo R. Abecasis, Barry Make, Michael C. Mahaney, Marco V Perez, Donna K. Arnett, Mark Chaffin, Xiuqing Guo, Joshua C. Bis, Pamela Russell, Paul L. Auer, James G. Wilson, Marilyn J. Telen, David K. Levine, Jennifer A. Smith, Christopher Scheller, Meher Preethi Boorgula, Aakrosh Ratan, Kari E. North, Dan E. Arking, Elizabeth A. Regan, Margaret G. Parker, Andres Metspalu, Jai G. Broome, Daniel Taliun, Lynette Ekunwe, Alyna T. Khan, Hao Mei, Dhananjay Vaidya, Ellen M. Schmidt, Stanford Mwasongwe, Joshua P. Lewis, Stacey Gabriel, Christine E. Seidman, Margery Gass, Deborah A. Nickerson, Nicola L. Hawley, Rebecca L. Beer, Afshin Parsa, Steven L. Salzberg, Terri H. Beaty, Stella Aslibekyan, Girish N. Nadkarni, Wei Zhao, David L. Tirschwell, Karen Bunting, Dawn L. DeMeo, Laura J. Rasmussen-Torvik, Julia Powers Becker, Dmitry Prokopenko, Karen Schwander, Bruce D. Gelb, Stephanie Krauter, Laura M. Raffield, Michael E. Hall, Frank C. Sciurba, Lauren Margolin, Nora Franceschini, Daniel N. Harris, Seyedeh M. Zekavat, Dawood Darbar, Keng-Han Lin, Haley Huston, Steven A. Lubitz, Andrea Ganna, Carole Sztalryd, Cathy C. Laurie, Christy Chang, James E. Hixson, Steven A. McCarroll, Barbara A. Konkle, Michael D. Kessler, Scott I. Vrieze, Yingze Zhang, Sarah Ruuska, George J. Papanicolaou, Weiniu Gan, Maris Alver, Elizabeth A. Streeten, Fei Fei Wang, Lu-Chen Weng, Braxton D. Mitchell, Lee-Ming Chuang, Sean P. David, Wei-Min Chen, Susan R. Heckbert, Ryan D. Hernandez, Andrew D. Johnson, Cristen J. Willer, Ani Manichaikul, Jonathan M. Bloom, Timothy D. O’Connor, Sylvia Smoller, Marguerite R. Irvin, Seung Hoan Choi, Ida Surakka, Veikko Salomaa, Diane M. Becker, Ron Do, W. Craig Johnson, Cecelia A. Laurie, Meryl S. LeBoff, Aniket Shetty, Tõnu Esko, Michael C. Zody, Xiaoqi Geng, Da Wei Gong, Snow Xueyan Zhao, Esteban G. Burchard, Xiuwen Zheng, Cara L. Carty, Alexander P. Reiner, Tim Assimes, Deborah A. Meyers, Mina K. Chung, Harald H H Göring, Benjamin M. Neale, Pradeep Natarajan, Yan Gao, Stephen S. Rich, Yun Ju Sung, Susan K. Dutcher, Ferdouse Begum, Stephanie M. Gogarten, John Blangero, Jonathan Cardwell, Kayleen Williams, Rakhi P. Naik, Amol C. Shetty, Sayantan Das, Myriam Fornage, May E. Montasser, Michelle Daya, Edwin K. Silverman, Daniel E. Weeks, Laura J. Kaufman, Dimitrios Avramopoulos, Michael Y. Tsai, Christine M. Albert, Vijay G. Sankaran, Jeffrey R. O'Connell, Thomas W. Blackwell, Stephen T. McGarvey, Robert M. Reed, Leslie A. Lange, Qing Duan, Bruce M. Psaty, Leslie S. Emery, Bertha Hidalgo, Jennifer A. Brody, L. Keoki Williams, Soren Germer, Zhaohui S. Qin, Deepti Jain, Deborah Applebaum-Bowden, Carla Wilson, Degui Zhi, Christoph Lange, Elliott Hong, L.F. Bielak, Wen Jane Lee, Yue Guan, Tarik Walker, Rebecca D. Jackson, Charles R. Farber, Mark J. Daly, Stephanie M. Fullerton, John E. Hokanson, Karol E. Watson, James Luo, Richard Casaburi, Seunggeun Lee, Jill M. Johnsen, Margaret A. Taub, Ryan L. Minster, Ravi Duggirala, Susan K. Mathai, Yun Li, Quenna Wong, Matthew Flickinger, Huichun Xu, Susan Redline, Ulrike Peters, Ivana V. Yang, Jesse M. Engreitz, Sanni Ruotsalainen, Sean K. McFarland, Avram D Walts, Patricia A. Peyser, Allison E. Ashley-Koch, Lewis C. Becker, Nicholette Palmer Allred, James A. Perry, Jody S. Sylvia, Tamar Sofer, Vasan S. Ramachandran, Laura Almasy, Matthew J. Budoff, Ranjan Deka, David M. Herrington, Simeon I. Taylor, Daniel Levy, Chaojie Yang, Sameer Chavan, Kathleen A. Ryan, Josyf C. Mychaleckyj, Ingo Ruczinski, Sebastian Zoellner, Michael Preuss, Tim Poterba, Wendy S. Post, Amber L. Beitelshees, Ben Heavner, Carolina Roselli, Namiko Abe, Jonathon LeFaive, Mark T. Gladwin, Brian Custer, Robert B. Wallace, Simin Liu, Michael H. Cho, Robert E. Handsaker, Dabeeru C. Rao, Bo Juen Chen, Wayne Hui Heng Sheu, Xiang Zhou, Marcos Bezerra, Solomon K. Musani, Eimear E. Kenny, James F. Casella, Kathryn L. Lunetta, Nancy Min, Nicholas Rafaels, Lisa R. Yanek, Min A. Jhun, David C. Glahn, Rasika A. Mathias, Mollie A. Minear, Russell P. Bowler, Jason Ernst, Carolyn J. Crandall, Sara Penchev, Alvaro Alonso, Timothy A. Thornton, Toni I. Pollin, Charles Kooperberg, Ethan M. Lange, Juan M. Peralta, Pramod Anugu, Lucinda Fulton, Adam A. Szpiro, Michael R. DeBaun, M. Benjamin Shoemaker, Sam Phillips, Dan M. Roden, Mao Fu, Daniel I. Chasman, James D. Crapo, Hua Tang, Gina M. Peloso, Hyun Min Kang, Samuli Ripatti, Phuwanat Sakornsakolpat, Christopher R. Gignoux, Peter VandeHaar, Jerome I. Rotter, Dandi Qiao, Emily S. Wan, Shabnam Salimi, Kevin Sandow, Jiang He, Patrick T. Ellinor, Joanne E. Curran, Institute for Molecular Medicine Finland, Samuli Olli Ripatti / Principal Investigator, University of Helsinki, Centre of Excellence in Complex Disease Genetics, Clinicum, Doctoral Programme in Population Health, Department of Public Health, and Complex Disease Genetics

Subjects
0301 basic medicine, Apolipoprotein B, General Physics and Astronomy, Gene Expression, Genome-wide association study, 030204 cardiovascular system & hematology, Cardiovascular, Lipoprotein particle, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, GENETIC-VARIANTS, 2.1 Biological and endogenous factors, WIDE ASSOCIATION, Aetiology, lcsh:Science, African Continental Ancestry Group, Genetics, Multidisciplinary, Genome, biology, CHOLESTEROL, Adaptor Proteins, Lipoprotein(a), Single Nucleotide, NHLBI TOPMed Lipids Working Group, 3142 Public health care science, environmental and occupational health, 3. Good health, Cholesterol, Heart Disease, Cardiovascular Diseases, CARDIOVASCULAR-DISEASE, RARE VARIANTS, lipids (amino acids, peptides, and proteins), LOW-FREQUENCY, Human, DNA Copy Number Variations, Science, Quantitative Trait Loci, European Continental Ancestry Group, Black People, POPULATION-SCALE, Quantitative trait locus, Article, White People, General Biochemistry, Genetics and Molecular Biology, LDL, Structural variation, 03 medical and health sciences, COMPONENTS-ANALYSIS, RISK-FACTOR, Humans, CORONARY-HEART-DISEASE, Polymorphism, Whole Genome Sequencing, Prevention, Human Genome, General Chemistry, Atherosclerosis, Vesicular Transport, Good Health and Well Being, 030104 developmental biology, chemistry, biology.protein, lcsh:Q, 3111 Biomedicine, Lipoprotein, Genome-Wide Association Study
Abstract

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Published
2018
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