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1. Proteomics of left ventricular structure in the Multi‐Ethnic Study of Atherosclerosis

Author

Tess E. Peterson, Joao A.C. Lima, Sanjiv J. Shah, David A. Bluemke, Alain G. Bertoni, Yongmei Liu, Debby Ngo, Vinithra Varadarajan, Josyf C. Mychaleckyj, Craig W. Johnson, Bruce M. Psaty, Clary B. Clish, Kent D. Taylor, Peter Durda, Russell P. Tracy, Robert E. Gerszten, Stephen S. Rich, Jerome I. Rotter, Wendy S. Post, and James S. Pankow

Subjects
Biomarkers, Cardiovascular magnetic resonance imaging, Left ventricular remodelling, Proteomics, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract Aims Proteomic profiling offers an expansive approach to biomarker discovery and mechanistic hypothesis generation for LV remodelling, a critical component of heart failure (HF). We sought to identify plasma proteins cross‐sectionally associated with left ventricular (LV) size and geometry in a diverse population‐based cohort without known cardiovascular disease (CVD). Methods and results Among participants of the Multi‐Ethnic Study of Atherosclerosis (MESA), we quantified plasma abundances of 1305 proteins using an aptamer‐based platform at exam 1 (2000–2002) and exam 5 (2010–2011) and assessed LV structure by cardiac magnetic resonance (CMR) at the same time points. We used multivariable linear regression with robust variance to assess cross‐sectional associations between plasma protein abundances and LV structural characteristics at exam 1, reproduced findings in later‐life at exam 5, and explored relationships of associated proteins using annotated enrichment analysis. We studied 763 participants (mean age 60 ± 10 years at exam 1; 53% female; 19% Black race; 31% Hispanic ethnicity). Following adjustment for renal function and traditional CVD risk factors, plasma levels of 3 proteins were associated with LV mass index at both time points with the same directionality (FDR

Published
2025
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2. Genome-wide association analysis of composite sleep health scores in 413,904 individuals

Author

Matthew O. Goodman, Tariq Faquih, Valentina Paz, Pavithra Nagarajan, Jacqueline M. Lane, Brian Spitzer, Matthew Maher, Joon Chung, Brian E. Cade, Shaun M. Purcell, Xiaofeng Zhu, Raymond Noordam, Andrew J. K. Phillips, Simon D. Kyle, Kai Spiegelhalder, Michael N. Weedon, Deborah A. Lawlor, Jerome I. Rotter, Kent D. Taylor, Carmen R. Isasi, Tamar Sofer, Hassan S. Dashti, Martin K. Rutter, Susan Redline, Richa Saxena, and Heming Wang

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, so together may provide a more complete picture of sleep health, while illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches. GWASs of these six SHSs identify 28 significant novel loci adjusting for multiple testing on six traits (p

Published
2025
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3. Proteomic signature of HIV-associated subclinical left atrial remodeling and incident heart failure

Author

Tess E. Peterson, Virginia S. Hahn, Ruin Moaddel, Min Zhu, Sabina A. Haberlen, Frank J. Palella, Michael Plankey, Joel S. Bader, Joao A. C. Lima, Robert E. Gerszten, Jerome I. Rotter, Stephen S. Rich, Susan R. Heckbert, Gregory D. Kirk, Damani A. Piggott, Luigi Ferrucci, Joseph B. Margolick, Todd T. Brown, Katherine C. Wu, and Wendy S. Post

Subjects
Science
Abstract

Abstract People living with HIV are at higher risk of heart failure and associated left atrial remodeling compared to people without HIV. Mechanisms are unclear but have been linked to inflammation and premature aging. Here we obtain plasma proteomics concurrently with cardiac magnetic resonance imaging in two independent study populations to identify parallels between HIV-related and aging-related immune dysfunction that could contribute to atrial remodeling and clinical heart failure. We discover a plasma proteomic signature that may in part reflect or contribute to HIV-associated atrial remodeling, many features of which are associated with older age and time to incident heart failure among an independent community-based cohort without HIV. This proteomic profile was statistically enriched for immune checkpoint proteins, tumor necrosis factor signaling, ephrin signaling, and extracellular matrix organization, identifying possible shared pathways in HIV and aging that may contribute to risk of heart failure.

Published
2025
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4. 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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5. Association analysis between an epigenetic alcohol risk score and blood pressure

Author

Helena Bui, Amena Keshawarz, Mengyao Wang, Mikyeong Lee, Scott M. Ratliff, Lisha Lin, Kira S. Birditt, Jessica D. Faul, Annette Peters, Christian Gieger, Thomas Delerue, Sharon L. R. Kardia, Wei Zhao, Xiuqing Guo, Jie Yao, Jerome I. Rotter, Yi Li, Xue Liu, Dan Liu, Juliana F. Tavares, Gökhan Pehlivan, Monique M. B. Breteler, Irma Karabegovic, Carolina Ochoa-Rosales, Trudy Voortman, Mohsen Ghanbari, Joyce B. J. van Meurs, Mohamed Kamal Nasr, Marcus Dörr, Hans J. Grabe, Stephanie J. London, Alexander Teumer, Melanie Waldenberger, David R. Weir, Jennifer A. Smith, Daniel Levy, Jiantao Ma, and Chunyu Liu

Subjects
Epigenetic risk score, DNA methylation, Blood pressure, Hypertension, Alcohol, Medicine, Genetics, QH426-470
Abstract

Abstract Background Epigenome‐wide association studies have identified multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. This study aimed to test the hypothesis that an alcohol consumption epigenetic risk score (ERS) is associated with blood pressure (BP) traits. Results We implemented an ERS based on a previously reported epigenetic signature of 144 alcohol-associated CpGs in meta-analysis of participants of European ancestry. We found a one-unit increment of ERS was associated with eleven drinks of alcohol consumed per day, on average, across several cohorts (p

Published
2024
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6. GWAS of CRP response to statins further supports the role of APOE in statin response: A GIST consortium study

Author

Emma F. Magavern, Harshal Deshmukh, Geraldine Asselin, Elizabeth Theusch, Stella Trompet, Xiaohui Li, Raymond Noordam, Y.-D. Ida Chen, Teresa E. Seeman, Kent D. Taylor, Wendy S. Post, Jean-Claude Tardif, Dirk S. Paul, Emelia J. Benjamin, Nancy L. Heard-Costa, Ramachandran S. Vasan, Jerome I. Rotter, Ronald M. Krauss, J.Wouter Jukema, Paul M. Ridker, Patricia B. Munroe, Mark J. Caulfield, Daniel I. Chasman, Marie-Pierre Dubé, Graham A. Hitman, and Helen R. Warren

Subjects
Statins, C-Reactive Protein, Pharmacogenetics, GWAS, Treatment Response, Pharmacology, Therapeutics. Pharmacology, RM1-950
Abstract

Statins are first-line treatments in the primary and secondary prevention of cardiovascular disease. Clinical studies show statins act independently of lipid-lowering mechanisms to decrease C-reactive protein (CRP), an inflammation marker. We aim to elucidate genetic loci associated with CRP statin response.CRP statin response is the change in log-CRP between off-treatment and on-treatment measurements. Cohort-level Genome-Wide Association Studies (GWAS) of CRP response were performed using 1000 Genomes imputed data, testing ∼10 million common genetic variants. GWAS meta-analysis combined results from seven cohorts and clinical trials totalling 14,070 statin-treated individuals of European ancestry within the GIST consortium. Secondary analyses included statin-by-placebo interaction analyses, and lookups in African ancestry cohorts.Our GWAS identified two genome-wide significant (P

Published
2025
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7. Proteome-wide association studies for blood lipids and comparison with transcriptome-wide association studies

Author

Daiwei Zhang, Boran Gao, Qidi Feng, Ani Manichaikul, Gina M. Peloso, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Stacey Gabriel, Namrata Gupta, Joshua D. Smith, Francois Aguet, Kristin G. Ardlie, Thomas W. Blackwell, Robert E. Gerszten, Stephen S. Rich, Jerome I. Rotter, Laura J. Scott, Xiang Zhou, and Seunggeun Lee

Subjects
blood lipids, Multi-omics, proteome-wide association studies, transcriptome-wide association studies, Genetics, QH426-470
Abstract

Summary: Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWASs) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWASs) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWASs and TWASs can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p values across all the genes, which suggests high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Published
2025
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8. A protein risk score for all-cause and respiratory-specific mortality in non-Hispanic white and African American individuals who smoke

Author

Matthew Moll, Katherine A. Pratte, Catherine L. Debban, Congjian Liu, Steven A. Belinsky, Maria Picchi, Iain Konigsberg, Courtney Tern, Heena Rijhwani, Brian D. Hobbs, Edwin K. Silverman, Yohannes Tesfaigzi, Stephen S. Rich, Ani Manichaikul, Jerome I. Rotter, Russel P. Bowler, and Michael H. Cho

Subjects
Medicine, Science
Abstract

Abstract Protein biomarkers are associated with mortality in cardiovascular disease, but their effect on predicting respiratory and all-cause mortality is not clear. We tested whether a protein risk score (protRS) can improve prediction of all-cause mortality over clinical risk factors in smokers. We utilized smoking-enriched (COPDGene, LSC, SPIROMICS) and general population-based (MESA) cohorts with SomaScan proteomic and mortality data. We split COPDGene into training and testing sets (50:50) and developed a protRS based on respiratory mortality effect size and parsimony. We tested multivariable associations of the protRS with all-cause, respiratory, and cardiovascular mortality, and performed meta-analysis, area-under-the-curve (AUC), and network analyses. We included 2232 participants. In COPDGene, a penalized regression-based protRS was most highly associated with respiratory mortality (OR 9.2) and parsimonious (15 proteins). This protRS was associated with all-cause mortality (random effects HR 1.79 [95% CI 1.31–2.43]). Adding the protRS to clinical covariates improved all-cause mortality prediction in COPDGene (AUC 0.87 vs 0.82) and SPIROMICS (0.74 vs 0.6), but not in LSC and MESA. Protein–protein interaction network analyses implicate cytokine signaling, innate immune responses, and extracellular matrix turnover. A blood-based protein risk score predicts all-cause and respiratory mortality, identifies potential drivers of mortality, and demonstrates heterogeneity in effects amongst cohorts.

Published
2024
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9. A methylation risk score for chronic kidney disease: a HyperGEN study

Author

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

Subjects
Chronic kidney disease, eGFR, Methylation risk score, Epigenetics, Medicine, Science
Abstract

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

Published
2024
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10. Sexually dimorphic DNA methylation and gene expression patterns in human first trimester placenta

Author

Tania L. Gonzalez, Bryn E. Willson, Erica T. Wang, Kent D. Taylor, Allynson Novoa, Akhila Swarna, Juanita C. Ortiz, Gianna J. Zeno, Caroline A. Jefferies, Kate Lawrenson, Jerome I. Rotter, Yii-Der Ida Chen, John Williams, Jinrui Cui, Mark O. Goodarzi, and Margareta D. Pisarska

Subjects
Placenta, Early pregnancy, Healthy pregnancy, Fetal sex, DNA methylation, Total RNA-seq, Medicine, Physiology, QP1-981
Abstract

Abstract Background Fetal sex and placental development impact pregnancy outcomes and fetal–maternal health, but the critical timepoint of placenta establishment in first trimester is understudied in human pregnancies. Methods Pregnant subjects were recruited in late first trimester (weeks 10–14) at time of chorionic villus sampling, a prenatal diagnostic test. Leftover placenta tissue was collected and stored until birth outcomes were known, then DNA and RNA were isolated from singleton, normal karyotype pregnancies resulting in live births. DNA methylation was measured with the Illumina Infinium MethylationEPIC BeadChip array (n = 56). Differential methylation analysis compared 25 females versus 31 males using a generalized linear model on 743,461 autosomal probes. Gene expression sex differences were analyzed with RNA-sequencing (n = 74). An integrated analysis was performed using linear regression to correlate gene expression and DNA methylation in 51 overlapping placentas. Results Methylation analysis identified 151 differentially methylated probes (DMPs) significant at false discovery rate

Published
2024
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11. Participant-derived cell line transcriptomic analyses and mouse studies reveal a role for ZNF335 in plasma cholesterol statin response

Author

Elizabeth Theusch, Flora Y. Ting, Yuanyuan Qin, Kristen Stevens, Devesh Naidoo, Sarah M. King, Neil V. Yang, Joseph Orr, Brenda Y. Han, Jason G. Cyster, Yii-Der I. Chen, Jerome I. Rotter, Ronald M. Krauss, and Marisa W. Medina

Subjects
Statin, Cholesterol, RNA-sequencing, Lymphoblastoid cell lines, Mice, Zinc finger protein 335, Medicine, Genetics, QH426-470
Abstract

Abstract Background Statins lower circulating low-density lipoprotein cholesterol (LDLC) levels and reduce cardiovascular disease risk. Though highly efficacious in general, there is considerable inter-individual variation in statin efficacy that remains largely unexplained. Methods To identify novel genes that may modulate statin-induced LDLC lowering, we used RNA-sequencing data from 426 control- and 2 µM simvastatin-treated lymphoblastoid cell lines (LCLs) derived from European and African American ancestry participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial (ClinicalTrials.gov Identifier: NCT00451828). We correlated statin-induced changes in LCL gene expression with plasma LDLC statin response in the corresponding CAP participants. For the most correlated gene identified (ZNF335), we followed up in vivo by comparing plasma cholesterol levels, lipoprotein profiles, and lipid statin response between wild-type mice and carriers of a hypomorphic (partial loss of function) missense mutation in Zfp335 (the mouse homolog of ZNF335). Results The statin-induced expression changes of 147 human LCL genes were significantly correlated to the plasma LDLC statin responses of the corresponding CAP participants in vivo (FDR = 5%). The two genes with the strongest correlations were zinc finger protein 335 (ZNF335 aka NIF-1, rho = 0.237, FDR-adj p = 0.0085) and CCR4-NOT transcription complex subunit 3 (CNOT3, rho = 0.233, FDR-adj p = 0.0085). Chow-fed mice carrying a hypomorphic missense (R1092W; aka bloto) mutation in Zfp335 had significantly lower non-HDL cholesterol levels than wild-type C57BL/6J mice in a sex combined model (p = 0.04). Furthermore, male (but not female) mice carrying the Zfp335 R1092W allele had significantly lower total and HDL cholesterol levels than wild-type mice. In a separate experiment, wild-type mice fed a control diet for 4 weeks and a matched simvastatin diet for an additional 4 weeks had significant statin-induced reductions in non-HDLC (−43 ± 18% and −23 ± 19% for males and females, respectively). Wild-type male (but not female) mice experienced significant reductions in plasma LDL particle concentrations, while male mice carrying Zfp335 R1092W allele(s) exhibited a significantly blunted LDL statin response. Conclusions Our in vitro and in vivo studies identified ZNF335 as a novel modulator of plasma cholesterol levels and statin response, suggesting that variation in ZNF335 activity could contribute to inter-individual differences in statin clinical efficacy.

Published
2024
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12. Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations

Author

Jessica I. Lundin, Ulrike Peters, Yao Hu, Farah Ammous, Christy L. Avery, Emelia J. Benjamin, Joshua C. Bis, Jennifer A. Brody, Chris Carlson, Mary Cushman, Chris Gignoux, Xiuqing Guo, Jeff Haessler, Chris Haiman, Roby Joehanes, Silva Kasela, Eimear Kenny, Tuuli Lapalainien, Daniel Levy, Chunyu Liu, Yongmei Liu, Ruth J.F. Loos, Ake Lu, Tara Matise, Kari E. North, Sungshim L. Park, Scott M. Ratliff, Alex Reiner, Stephen S. Rich, Jerome I. Rotter, Jennifer A. Smith, Nona Sotoodehnia, Russell Tracy, David Van den Berg, Huichun Xu, Ting Ye, Wei Zhao, Laura M. Raffield, and Charles Kooperberg

Subjects
Inflammation, C-reactive protein, methylation, epigenetics, EWAS, racial and ethnic diversity, Genetics, QH426-470
Abstract

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p

Published
2024
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13. Metabolites Link Intake of a Healthy Diet to Better Insulin and Glucose Homeostasis in the Microbiome and Insulin Longitudinal Evaluation Study (MILES)

Author

Alexis C Wood, Danielle J Lee, Patricia A Sheridan, Elizabeth T Jensen, Gautam Ramesh, Alain G Bertoni, Stephen S Rich, Yii-Der I Chen, David M Herrington, Jerome I Rotter, and Mark O Goodarzi

Subjects
glucose homeostasis, insulin, glycemia, dysglycemia, oral glucose tolerance test, metabolites, Nutrition. Foods and food supply, TX341-641, Nutritional diseases. Deficiency diseases, RC620-627
Abstract

Background: Dietary quality has been linked to better glycemic control, but the precise molecular mechanisms giving rise to these associations are not fully understood. Objectives: To examine the association of metabolites associated with the intake of a healthy diet with measures of insulin/glucose homeostasis. Methods: Using cross-sectional data from 295 United States adults, the associations between 3 diet pattern scores and metabolome-wide metabolites were estimated via linear regression models, which controlled for demographic factors and health behaviors. Subsequently, the associations between the diet-related metabolites with 6 measures of glucose/insulin homeostasis were examined in similar models. A Bonferroni correction was applied to control the family-wise error rate at 5%. Results: Fifty-five metabolites were significantly associated with ≥1 diet score (all P < 1.7∗10–5). When these were summed into each of the 3 diet-specific metabolite summary scores, all 3 aggregate measures showed strong associations with 5 out of 6 measures of glucose/insulin homeostasis (P = 9.7∗10–5–4.1∗10–13). Conclusions: Adherence to a priori-defined “healthy diet” is associated with the plasma metabolites that, in turn, are associated with better glycemia. If the associations between replicated in future studies and examined using large-scale longitudinal data, the identified molecules could yield insights into mechanisms by which diet may support glucose and insulin homeostasis.

Published
2024
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14. Metagenomic Study of the MESA: Detection of Gemella Morbillorum and Association With Coronary Heart Disease

Author

Kent D. Taylor, Alexis C. Wood, Jerome I. Rotter, Xiuqing Guo, David M. Herrington, W. Craig Johnson, Wendy S. Post, Russell P. Tracy, Stephen S. Rich, and Shaista Malik

Subjects
cardiovascular heart disease, Gemella morbillorum, MESA, metagenomics, Pseudomonas, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Inflammation is a feature of coronary heart disease (CHD), but the role of proinflammatory microbial infection in CHD remains understudied. Methods and Results CHD was defined in the MESA (Multi‐Ethnic Study of Atherosclerosis) as myocardial infarction (251 participants), resuscitated arrest (2 participants), and CHD death (80 participants). We analyzed sequencing reads from 4421 MESA participants in the National Heart, Lung, and Blood Institute Trans‐Omics for Precision Medicine program using the PathSeq workflow of the Genome Analysis Tool Kit and a 65‐gigabase microbial reference. Paired reads aligning to 840 microbes were detected in >1% of participants. The association of the presence of microbe reads with incident CHD (follow‐up, ~18 years) was examined. First, important variables were ascertained using a single regularized Cox proportional hazard model, examining change of risk as a function of presence of microbe with age, sex, education level, Life's Simple 7, and inflammation. For variables of importance, the hazard ratio (HR) was estimated in separate (unregularized) Cox proportional hazard models including the same covariates (significance threshold Bonferroni corrected P

Published
2024
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15. Determinants of mosaic chromosomal alteration fitness

Author

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

Subjects
Science
Abstract

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

Published
2024
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16. Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes

Author

Rebecca Keener, Surya B. Chhetri, Carla J. Connelly, Margaret A. Taub, Matthew P. Conomos, Joshua Weinstock, Bohan Ni, Benjamin Strober, Stella Aslibekyan, Paul L. Auer, Lucas Barwick, Lewis C. Becker, John Blangero, Eugene R. Bleecker, Jennifer A. Brody, Brian E. Cade, Juan C. Celedon, Yi-Cheng Chang, L. Adrienne Cupples, Brian Custer, Barry I. Freedman, Mark T. Gladwin, Susan R. Heckbert, Lifang Hou, Marguerite R. Irvin, Carmen R. Isasi, Jill M. Johnsen, Eimear E. Kenny, Charles Kooperberg, Ryan L. Minster, Take Naseri, Satupa’itea Viali, Sergei Nekhai, Nathan Pankratz, Patricia A. Peyser, Kent D. Taylor, Marilyn J. Telen, Baojun Wu, Lisa R. Yanek, Ivana V. Yang, Christine Albert, Donna K. Arnett, Allison E. Ashley-Koch, Kathleen C. Barnes, Joshua C. Bis, Thomas W. Blackwell, Eric Boerwinkle, Esteban G. Burchard, April P. Carson, Zhanghua Chen, Yii-Der Ida Chen, Dawood Darbar, Mariza de Andrade, Patrick T. Ellinor, Myriam Fornage, Bruce D. Gelb, Frank D. Gilliland, Jiang He, Talat Islam, Stefan Kaab, Sharon L. R. Kardia, Shannon Kelly, Barbara A. Konkle, Rajesh Kumar, Ruth J. F. Loos, Fernando D. Martinez, Stephen T. McGarvey, Deborah A. Meyers, Braxton D. Mitchell, Courtney G. Montgomery, Kari E. North, Nicholette D. Palmer, Juan M. Peralta, Benjamin A. Raby, Susan Redline, Stephen S. Rich, Dan Roden, Jerome I. Rotter, Ingo Ruczinski, David Schwartz, Frank Sciurba, M. Benjamin Shoemaker, Edwin K. Silverman, Moritz F. Sinner, Nicholas L. Smith, Albert V. Smith, Hemant K. Tiwari, Ramachandran S. Vasan, Scott T. Weiss, L. Keoki Williams, Yingze Zhang, Elad Ziv, Laura M. Raffield, Alexander P. Reiner, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group, Marios Arvanitis, Carol W. Greider, Rasika A. Mathias, and Alexis Battle

Subjects
Science
Abstract

Abstract Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Published
2024
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17. Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores

Author

Yana Hrytsenko, Benjamin Shea, Michael Elgart, Nuzulul Kurniansyah, Genevieve Lyons, Alanna C. Morrison, April P. Carson, Bernhard Haring, Braxton D. Mitchell, Bruce M. Psaty, Byron C. Jaeger, C. Charles Gu, Charles Kooperberg, Daniel Levy, Donald Lloyd-Jones, Eunhee Choi, Jennifer A. Brody, Jennifer A. Smith, Jerome I. Rotter, Matthew Moll, Myriam Fornage, Noah Simon, Peter Castaldi, Ramon Casanova, Ren-Hua Chung, Robert Kaplan, Ruth J. F. Loos, Sharon L. R. Kardia, Stephen S. Rich, Susan Redline, Tanika Kelly, Timothy O’Connor, Wei Zhao, Wonji Kim, Xiuqing Guo, Yii-Der Ida Chen, The Trans-Omics in Precision Medicine Consortium, and Tamar Sofer

Subjects
Medicine, Science
Abstract

Abstract We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model’s performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1 to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8 to 5.1% (SBP) and 4.7 to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs. In summary, non-linear ML models improves BP prediction in models incorporating diverse populations.

Published
2024
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18. Polygenic scores and Mendelian randomization identify plasma proteins causally implicated in Alzheimer’s disease

Author

Davis B. Cammann, Yimei Lu, Jerome I. Rotter, Alexis C. Wood, and Jingchun Chen

Subjects
polygenic score, Mendelian randomization, Alzheimer’s disease, plasma proteins, pQTL, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

BackgroundAn increasing body of evidence suggests that neuroinflammation is one of the key drivers of late-onset Alzheimer’s disease (LOAD) pathology. Due to the increased permeability of the blood–brain barrier (BBB) in older adults, peripheral plasma proteins can infiltrate the central nervous system (CNS) and drive neuroinflammation through interactions with neurons and glial cells. Because these inflammatory factors are heritable, a greater understanding of their genetic relationship with LOAD could identify new biomarkers that contribute to LOAD pathology or offer protection against it.MethodsWe used a genome-wide association study (GWAS) of 90 different plasma proteins (n = 17,747) to create polygenic scores (PGSs) in an independent discovery (cases = 1,852 and controls = 1,990) and replication (cases = 799 and controls = 778) cohort. Multivariate logistic regression was used to associate the plasma protein PGSs with LOAD diagnosis while controlling for age, sex, principal components 1–2, and the number of APOE-e4 alleles as covariates. After meta-analyzing the PGS-LOAD associations between the two cohorts, we then performed a two-sample Mendelian randomization (MR) analysis using the summary statistics of significant plasma protein level PGSs in the meta-analysis as an exposure, and a GWAS of clinically diagnosed LOAD (cases = 21,982, controls = 41,944) as an outcome to explore possible causal relationships between the two.ResultsWe identified four plasma protein level PGSs that were significantly associated (FDR-adjusted p

Published
2024
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19. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements

Author

Markus Scholz, Katrin Horn, Janne Pott, Matthias Wuttke, Andreas Kühnapfel, M. Kamal Nasr, Holger Kirsten, Yong Li, Anselm Hoppmann, Mathias Gorski, Sahar Ghasemi, Man Li, Adrienne Tin, Jin-Fang Chai, Massimiliano Cocca, Judy Wang, Teresa Nutile, Masato Akiyama, Bjørn Olav Åsvold, Nisha Bansal, Mary L. Biggs, Thibaud Boutin, Hermann Brenner, Ben Brumpton, Ralph Burkhardt, Jianwen Cai, Archie Campbell, Harry Campbell, John Chalmers, Daniel I. Chasman, Miao Ling Chee, Miao Li Chee, Xu Chen, Ching-Yu Cheng, Renata Cifkova, Martha Daviglus, Graciela Delgado, Katalin Dittrich, Todd L. Edwards, Karlhans Endlich, J. Michael Gaziano, Ayush Giri, Franco Giulianini, Scott D. Gordon, Daniel F. Gudbjartsson, Stein Hallan, Pavel Hamet, Catharina A. Hartman, Caroline Hayward, Iris M. Heid, Jacklyn N. Hellwege, Bernd Holleczek, Hilma Holm, Nina Hutri-Kähönen, Kristian Hveem, Berend Isermann, Jost B. Jonas, Peter K. Joshi, Yoichiro Kamatani, Masahiro Kanai, Mika Kastarinen, Chiea Chuen Khor, Wieland Kiess, Marcus E. Kleber, Antje Körner, Peter Kovacs, Alena Krajcoviechova, Holly Kramer, Bernhard K. Krämer, Mikko Kuokkanen, Mika Kähönen, Leslie A. Lange, James P. Lash, Terho Lehtimäki, Hengtong Li, Bridget M. Lin, Jianjun Liu, Markus Loeffler, Leo-Pekka Lyytikäinen, Patrik K. E. Magnusson, Nicholas G. Martin, Koichi Matsuda, Yuri Milaneschi, Pashupati P. Mishra, Nina Mononen, Grant W. Montgomery, Dennis O. Mook-Kanamori, Josyf C. Mychaleckyj, Winfried März, Matthias Nauck, Kjell Nikus, Ilja M. Nolte, Raymond Noordam, Yukinori Okada, Isleifur Olafsson, Albertine J. Oldehinkel, Brenda W. J. H. Penninx, Markus Perola, Nicola Pirastu, Ozren Polasek, David J. Porteous, Tanja Poulain, Bruce M. Psaty, Ton J. Rabelink, Laura M. Raffield, Olli T. Raitakari, Humaira Rasheed, Dermot F. Reilly, Kenneth M. Rice, Anne Richmond, Paul M. Ridker, Jerome I. Rotter, Igor Rudan, Charumathi Sabanayagam, Veikko Salomaa, Neil Schneiderman, Ben Schöttker, Mario Sims, Harold Snieder, Klaus J. Stark, Kari Stefansson, Hannah Stocker, Michael Stumvoll, Patrick Sulem, Gardar Sveinbjornsson, Per O. Svensson, E-Shyong Tai, Kent D. Taylor, Bamidele O. Tayo, Andrej Teren, Yih-Chung Tham, Joachim Thiery, Chris H. L. Thio, Laurent F. Thomas, Johanne Tremblay, Anke Tönjes, Peter J. van der Most, Veronique Vitart, Uwe Völker, Ya Xing Wang, Chaolong Wang, Wen Bin Wei, John B. Whitfield, Sarah H. Wild, James F. Wilson, Thomas W. Winkler, Tien-Yin Wong, Mark Woodward, Xueling Sim, Audrey Y. Chu, Mary F. Feitosa, Unnur Thorsteinsdottir, Adriana M. Hung, Alexander Teumer, Nora Franceschini, Afshin Parsa, Anna Köttgen, Pascal Schlosser, and Cristian Pattaro

Subjects
Science
Abstract

Abstract X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

Published
2024
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20. Genome-wide association identifies novel ROP risk loci in a multiethnic cohort

Author

Xiaohui Li, Leah A. Owen, Kent D. Taylor, Susan Ostmo, Yii-Der Ida Chen, Aaron S. Coyner, Kemal Sonmez, M. Elizabeth Hartnett, Xiuqing Guo, Eli Ipp, Kathryn Roll, Pauline Genter, R. V. Paul Chan, Margaret M. DeAngelis, Michael F. Chiang, J. Peter Campbell, Jerome I. Rotter, and on behalf of the i-ROP Consortium

Subjects
Biology (General), QH301-705.5
Abstract

Abstract We conducted a genome-wide association study (GWAS) in a multiethnic cohort of 920 at-risk infants for retinopathy of prematurity (ROP), a major cause of childhood blindness, identifying 1 locus at genome-wide significance level (p

Published
2024
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21. Identification of circulating proteins associated with general cognitive function among middle-aged and older adults

Author

Adrienne Tin, Alison E. Fohner, Qiong Yang, Jennifer A. Brody, Gail Davies, Jie Yao, Dan Liu, Ilana Caro, Joni V. Lindbohm, Michael R. Duggan, Osorio Meirelles, Sarah E. Harris, Valborg Gudmundsdottir, Adele M. Taylor, Albert Henry, Alexa S. Beiser, Ali Shojaie, Annabell Coors, Annette L. Fitzpatrick, Claudia Langenberg, Claudia L. Satizabal, Colleen M. Sitlani, Eleanor Wheeler, Elliot M. Tucker-Drob, Jan Bressler, Josef Coresh, Joshua C. Bis, Julián Candia, Lori L. Jennings, Maik Pietzner, Mark Lathrop, Oscar L. Lopez, Paul Redmond, Robert E. Gerszten, Stephen S. Rich, Susan R. Heckbert, Thomas R. Austin, Timothy M. Hughes, Toshiko Tanaka, Valur Emilsson, Ramachandran S. Vasan, Xiuqing Guo, Yineng Zhu, Christophe Tzourio, Jerome I. Rotter, Keenan A. Walker, Luigi Ferrucci, Mika Kivimäki, Monique M. B. Breteler, Simon R. Cox, Stephanie Debette, Thomas H. Mosley, Vilmundur G. Gudnason, Lenore J. Launer, Bruce M. Psaty, Sudha Seshadri, and Myriam Fornage

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p

Published
2023
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22. Circulating metabolites may illustrate relationship of alcohol consumption with cardiovascular disease

Author

Yi Li, Mengyao Wang, Xue Liu, Jian Rong, Patricia Emogene Miller, Roby Joehanes, Tianxiao Huan, Xiuqing Guo, Jerome I. Rotter, Jennifer A. Smith, Bing Yu, Matthew Nayor, Daniel Levy, Chunyu Liu, and Jiantao Ma

Subjects
Alcohol consumption, Metabolites, Cardiovascular disease, Medicine
Abstract

Abstract Background Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD. Methods Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine, and liquor on average of 19 years in 2428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure). Results We identified 60 metabolites associated with cumulative average alcohol consumption (p

Published
2023
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23. Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA

Author

Xiaowei Hu, Jeongok G. Logan, Younghoon Kwon, Joao A. C. Lima, David R. Jacobs, Daniel Duprez, Lyndia Brumback, Kent D. Taylor, Peter Durda, W. Craig Johnson, Elaine Cornell, Xiuqing Guo, Yongmei Liu, Russell P. Tracy, Thomas W. Blackwell, George Papanicolaou, Gary F. Mitchell, Stephen S. Rich, Jerome I. Rotter, David J. Van Den Berg, Julio A. Chirinos, Timothy M. Hughes, Francine E. Garrett-Bakelman, and Ani Manichaikul

Subjects
Medicine, Science
Abstract

Abstract Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

Published
2023
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24. Deleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality

Author

Yun Soo Hong, Stephanie L. Battle, Wen Shi, Daniela Puiu, Vamsee Pillalamarri, Jiaqi Xie, Nathan Pankratz, Nicole J. Lake, Monkol Lek, Jerome I. Rotter, Stephen S. Rich, Charles Kooperberg, Alex P. Reiner, Paul L. Auer, Nancy Heard-Costa, Chunyu Liu, Meng Lai, Joanne M. Murabito, Daniel Levy, Megan L. Grove, Alvaro Alonso, Richard Gibbs, Shannon Dugan-Perez, Lukasz P. Gondek, Eliseo Guallar, and Dan E. Arking

Subjects
Science
Abstract

Abstract Mitochondria carry their own circular genome and disruption of the mitochondrial genome is associated with various aging-related diseases. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1000 s to 10,000 s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbors a particular variant. We quantify mtDNA heteroplasmy in 194,871 participants in the UK Biobank and find that heteroplasmy is associated with a 1.5-fold increased risk of all-cause mortality. Additionally, we functionally characterize mtDNA single nucleotide variants (SNVs) using a constraint-based score, mitochondrial local constraint score sum (MSS) and find it associated with all-cause mortality, and with the prevalence and incidence of cancer and cancer-related mortality, particularly leukemia. These results indicate that mitochondria may have a functional role in certain cancers, and mitochondrial heteroplasmic SNVs may serve as a prognostic marker for cancer, especially for leukemia.

Published
2023
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25. Genetic insights into resting heart rate and its role in cardiovascular disease

Author

Yordi J. van de Vegte, Ruben N. Eppinga, M. Yldau van der Ende, Yanick P. Hagemeijer, Yuvaraj Mahendran, Elias Salfati, Albert V. Smith, Vanessa Y. Tan, Dan E. Arking, Ioanna Ntalla, Emil V. Appel, Claudia Schurmann, Jennifer A. Brody, Rico Rueedi, Ozren Polasek, Gardar Sveinbjornsson, Cecile Lecoeur, Claes Ladenvall, Jing Hua Zhao, Aaron Isaacs, Lihua Wang, Jian’an Luan, Shih-Jen Hwang, Nina Mononen, Kirsi Auro, Anne U. Jackson, Lawrence F. Bielak, Linyao Zeng, Nabi Shah, Maria Nethander, Archie Campbell, Tuomo Rankinen, Sonali Pechlivanis, Lu Qi, Wei Zhao, Federica Rizzi, Toshiko Tanaka, Antonietta Robino, Massimiliano Cocca, Leslie Lange, Martina Müller-Nurasyid, Carolina Roselli, Weihua Zhang, Marcus E. Kleber, Xiuqing Guo, Henry J. Lin, Francesca Pavani, Tessel E. Galesloot, Raymond Noordam, Yuri Milaneschi, Katharina E. Schraut, Marcel den Hoed, Frauke Degenhardt, Stella Trompet, Marten E. van den Berg, Giorgio Pistis, Yih-Chung Tham, Stefan Weiss, Xueling S. Sim, Hengtong L. Li, Peter J. van der Most, Ilja M. Nolte, Leo-Pekka Lyytikäinen, M. Abdullah Said, Daniel R. Witte, Carlos Iribarren, Lenore Launer, Susan M. Ring, Paul S. de Vries, Peter Sever, Allan Linneberg, Erwin P. Bottinger, Sandosh Padmanabhan, Bruce M. Psaty, Nona Sotoodehnia, Ivana Kolcic, The DCCT/EDIC Research Group, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Beverley Balkau, Claudia T. Silva, Christopher H. Newton-Cheh, Kjell Nikus, Perttu Salo, Karen L. Mohlke, Patricia A. Peyser, Heribert Schunkert, Mattias Lorentzon, Jari Lahti, Dabeeru C. Rao, Marilyn C. Cornelis, Jessica D. Faul, Jennifer A. Smith, Katarzyna Stolarz-Skrzypek, Stefania Bandinelli, Maria Pina Concas, Gianfranco Sinagra, Thomas Meitinger, Melanie Waldenberger, Moritz F. Sinner, Konstantin Strauch, Graciela E. Delgado, Kent D. Taylor, Jie Yao, Luisa Foco, Olle Melander, Jacqueline de Graaf, Renée de Mutsert, Eco J. C. de Geus, Åsa Johansson, Peter K. Joshi, Lars Lind, Andre Franke, Peter W. Macfarlane, Kirill V. Tarasov, Nicholas Tan, Stephan B. Felix, E-Shyong Tai, Debra Q. Quek, Harold Snieder, Johan Ormel, Martin Ingelsson, Cecilia Lindgren, Andrew P. Morris, Olli T. Raitakari, Torben Hansen, Themistocles Assimes, Vilmundur Gudnason, Nicholas J. Timpson, Alanna C. Morrison, Patricia B. Munroe, David P. Strachan, Niels Grarup, Ruth J. F. Loos, Susan R. Heckbert, Peter Vollenweider, Caroline Hayward, Kari Stefansson, Philippe Froguel, Leif Groop, Nicholas J. Wareham, Cornelia M. van Duijn, Mary F. Feitosa, Christopher J. O’Donnell, Mika Kähönen, Markus Perola, Michael Boehnke, Sharon L. R. Kardia, Jeanette Erdmann, Colin N. A. Palmer, Claes Ohlsson, David J. Porteous, Johan G. Eriksson, Claude Bouchard, Susanne Moebus, Peter Kraft, David R. Weir, Daniele Cusi, Luigi Ferrucci, Sheila Ulivi, Giorgia Girotto, Adolfo Correa, Stefan Kääb, Annette Peters, John C. Chambers, Jaspal S. Kooner, Winfried März, Jerome I. Rotter, Andrew A. Hicks, J. Gustav Smith, Lambertus A. L. M. Kiemeney, Dennis O. Mook-Kanamori, Brenda W. J. H. Penninx, Ulf Gyllensten, James F. Wilson, Stephen Burgess, Johan Sundström, Wolfgang Lieb, J. Wouter Jukema, Mark Eijgelsheim, Edward L. M. Lakatta, Ching-Yu Cheng, Marcus Dörr, Tien-Yin Wong, Charumathi Sabanayagam, Albertine J. Oldehinkel, Harriette Riese, Terho Lehtimäki, Niek Verweij, and Pim van der Harst

Subjects
Science
Abstract

Abstract Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Published
2023
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26. Genome-wide study investigating effector genes and polygenic prediction for kidney function in persons with ancestry from Africa and the Americas

Author

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

Subjects
kidney function, chronic kidney disease, genome-wide association study, multi-ancestry, admixed populations, eGFR, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract

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

Published
2024
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27. 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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28. Large scale proteomic studies create novel privacy considerations

Author

Andrew C. Hill, Claire Guo, Elizabeth M. Litkowski, Ani W. Manichaikul, Bing Yu, Iain R. Konigsberg, Betty A. Gorbet, Leslie A. Lange, Katherine A. Pratte, Katerina J. Kechris, Matthew DeCamp, Marilyn Coors, Victor E. Ortega, Stephen S. Rich, Jerome I. Rotter, Robert E. Gerzsten, Clary B. Clish, Jeffrey L. Curtis, Xiaowei Hu, Ma-en Obeidat, Melody Morris, Joseph Loureiro, Debby Ngo, Wanda K. O’Neal, Deborah A. Meyers, Eugene R. Bleecker, Brian D. Hobbs, Michael H. Cho, Farnoush Banaei-Kashani, and Russell P. Bowler

Subjects
Medicine, Science
Abstract

Abstract Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90–95% of proteomes to their correct genome and for 95–99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Published
2023
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29. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

Author

William J. Young, Jeffrey Haessler, Jan-Walter Benjamins, Linda Repetto, Jie Yao, Aaron Isaacs, Andrew R. Harper, Julia Ramirez, Sophie Garnier, Stefan van Duijvenboden, Antoine R. Baldassari, Maria Pina Concas, ThuyVy Duong, Luisa Foco, Jonas L. Isaksen, Hao Mei, Raymond Noordam, Casia Nursyifa, Anne Richmond, Meddly L. Santolalla, Colleen M. Sitlani, Negin Soroush, Sébastien Thériault, Stella Trompet, Stefanie Aeschbacher, Fariba Ahmadizar, Alvaro Alonso, Jennifer A. Brody, Archie Campbell, Adolfo Correa, Dawood Darbar, Antonio De Luca, Jean-François Deleuze, Christina Ellervik, Christian Fuchsberger, Anuj Goel, Christopher Grace, Xiuqing Guo, Torben Hansen, Susan R. Heckbert, Rebecca D. Jackson, Jan A. Kors, Maria Fernanda Lima-Costa, Allan Linneberg, Peter W. Macfarlane, Alanna C. Morrison, Pau Navarro, David J. Porteous, Peter P. Pramstaller, Alexander P. Reiner, Lorenz Risch, Ulrich Schotten, Xia Shen, Gianfranco Sinagra, Elsayed Z. Soliman, Monika Stoll, Eduardo Tarazona-Santos, Andrew Tinker, Katerina Trajanoska, Eric Villard, Helen R. Warren, Eric A. Whitsel, Kerri L. Wiggins, Dan E. Arking, Christy L. Avery, David Conen, Giorgia Girotto, Niels Grarup, Caroline Hayward, J.Wouter Jukema, Dennis O. Mook-Kanamori, Morten Salling Olesen, Sandosh Padmanabhan, Bruce M. Psaty, Cristian Pattaro, Antonio Luiz P. Ribeiro, Jerome I. Rotter, Bruno H. Stricker, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, James G. Wilson, Michele Orini, Philippe Charron, Hugh Watkins, Charles Kooperberg, Henry J. Lin, James F. Wilson, Jørgen K. Kanters, Nona Sotoodehnia, Borbala Mifsud, Pier D. Lambiase, Larisa G. Tereshchenko, and Patricia B. Munroe

Subjects
Science
Abstract

The spatial and frontal QRS-T angles are electrocardiographic (ECG) predictors for arrhythmia. This work used genetic analyses to identify associated loci and pathways, and explore their relationships with other ECG traits and cardiovascular disease.

Published
2023
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30. Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis

Author

Kristina L. Buschur, Craig Riley, Aabida Saferali, Peter Castaldi, Grace Zhang, Francois Aguet, Kristin G. Ardlie, Peter Durda, W. Craig Johnson, Silva Kasela, Yongmei Liu, Ani Manichaikul, Stephen S. Rich, Jerome I. Rotter, Josh Smith, Kent D. Taylor, Russell P. Tracy, Tuuli Lappalainen, R. Graham Barr, Frank Sciurba, Craig P. Hersh, and Panayiotis V. Benos

Subjects
COPD, Graphical models, Gene expression, Disease subtypes, Diseases of the respiratory system, RC705-779
Abstract

Abstract Background Chronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment. Methods Blood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples. Results The discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS). Conclusions The identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis.

Published
2023
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31. An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling

Author

Nuzulul Kurniansyah, Danielle A. Wallace, Ying Zhang, Bing Yu, Brian Cade, Heming Wang, Heather M. Ochs-Balcom, Alexander P. Reiner, Alberto R. Ramos, Joshua D. Smith, Jianwen Cai, Martha Daviglus, Phyllis C. Zee, Robert Kaplan, Charles Kooperberg, Stephen S. Rich, Jerome I. Rotter, Sina A. Gharib, Susan Redline, and Tamar Sofer

Subjects
Biology (General), QH301-705.5
Abstract

An integrated multi-omics analysis identifies an association chain among sleep-disordered breathing (SDB) traits, gene expression in circulating leukocytes, and serum metabolites, and supports a mechanistic role for P2XR4 purinergic signaling in SDB.

Published
2023
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32. Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program

Author

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

Subjects
blood pressure, antihypertensive response, whole genome sequencing, TOPMed, treatment resistant hypertension, Genetics, QH426-470
Abstract

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

Published
2023
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33. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci

Author

Lisa de las Fuentes, Karen L. Schwander, Michael R. Brown, Amy R. Bentley, Thomas W. Winkler, Yun Ju Sung, Patricia B. Munroe, Clint L. Miller, Hugo Aschard, Stella Aslibekyan, Traci M. Bartz, Lawrence F. Bielak, Jin Fang Chai, Ching-Yu Cheng, Rajkumar Dorajoo, Mary F. Feitosa, Xiuqing Guo, Fernando P. Hartwig, Andrea Horimoto, Ivana Kolčić, Elise Lim, Yongmei Liu, Alisa K. Manning, Jonathan Marten, Solomon K. Musani, Raymond Noordam, Sandosh Padmanabhan, Tuomo Rankinen, Melissa A. Richard, Paul M. Ridker, Albert V. Smith, Dina Vojinovic, Alan B. Zonderman, Maris Alver, Mathilde Boissel, Kaare Christensen, Barry I. Freedman, Chuan Gao, Franco Giulianini, Sarah E. Harris, Meian He, Fang-Chi Hsu, Brigitte Kühnel, Federica Laguzzi, Xiaoyin Li, Leo-Pekka Lyytikäinen, Ilja M. Nolte, Alaitz Poveda, Rainer Rauramaa, Muhammad Riaz, Antonietta Robino, Tamar Sofer, Fumihiko Takeuchi, Bamidele O. Tayo, Peter J. van der Most, Niek Verweij, Erin B. Ware, Stefan Weiss, Wanqing Wen, Lisa R. Yanek, Yiqiang Zhan, Najaf Amin, Dan E. Arking, Christie Ballantyne, Eric Boerwinkle, Jennifer A. Brody, Ulrich Broeckel, Archie Campbell, Mickaël Canouil, Xiaoran Chai, Yii-Der Ida Chen, Xu Chen, Kumaraswamy Naidu Chitrala, Maria Pina Concas, Ulf de Faire, Renée de Mutsert, H. Janaka de Silva, Paul S. de Vries, Ahn Do, Jessica D. Faul, Virginia Fisher, James S. Floyd, Terrence Forrester, Yechiel Friedlander, Giorgia Girotto, C. Charles Gu, Göran Hallmans, Sami Heikkinen, Chew-Kiat Heng, Georg Homuth, Steven Hunt, M. Arfan Ikram, David R. Jacobs, Maryam Kavousi, Chiea Chuen Khor, Tuomas O. Kilpeläinen, Woon-Puay Koh, Pirjo Komulainen, Carl D. Langefeld, Jingjing Liang, Kiang Liu, Jianjun Liu, Kurt Lohman, Reedik Mägi, Ani W. Manichaikul, Colin A. McKenzie, Thomas Meitinger, Yuri Milaneschi, Matthias Nauck, Christopher P. Nelson, Jeffrey R. O’Connell, Nicholette D. Palmer, Alexandre C. Pereira, Thomas Perls, Annette Peters, Ozren Polašek, Olli T. Raitakari, Kenneth Rice, Treva K. Rice, Stephen S. Rich, Charumathi Sabanayagam, Pamela J. Schreiner, Xiao-Ou Shu, Stephen Sidney, Mario Sims, Jennifer A. Smith, John M. Starr, Konstantin Strauch, E. Shyong Tai, Kent D. Taylor, Michael Y. Tsai, André G. Uitterlinden, Diana van Heemst, Melanie Waldenberger, Ya-Xing Wang, Wen-Bin Wei, Gregory Wilson, Deng Xuan, Jie Yao, Caizheng Yu, Jian-Min Yuan, Wei Zhao, Diane M. Becker, Amélie Bonnefond, Donald W. Bowden, Richard S. Cooper, Ian J. Deary, Jasmin Divers, Tõnu Esko, Paul W. Franks, Philippe Froguel, Christian Gieger, Jost B. Jonas, Norihiro Kato, Timo A. Lakka, Karin Leander, Terho Lehtimäki, Patrik K. E. Magnusson, Kari E. North, Ioanna Ntalla, Brenda Penninx, Nilesh J. Samani, Harold Snieder, Beatrice Spedicati, Pim van der Harst, Henry Völzke, Lynne E. Wagenknecht, David R. Weir, Mary K. Wojczynski, Tangchun Wu, Wei Zheng, Xiaofeng Zhu, Claude Bouchard, Daniel I. Chasman, Michele K. Evans, Ervin R. Fox, Vilmundur Gudnason, Caroline Hayward, Bernardo L. Horta, Sharon L. R. Kardia, Jose Eduardo Krieger, Dennis O. Mook-Kanamori, Patricia A. Peyser, Michael M. Province, Bruce M. Psaty, Igor Rudan, Xueling Sim, Blair H. Smith, Rob M. van Dam, Cornelia M. van Duijn, Tien Yin Wong, Donna K. Arnett, Dabeeru C. Rao, James Gauderman, Ching-Ti Liu, Alanna C. Morrison, Jerome I. Rotter, and Myriam Fornage

Subjects
educational attainment, lipids, cholesterol, triglycerides, genome-wide association study, meta-analysis, Genetics, QH426-470
Abstract

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue.Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Published
2023
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34. Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

Author

Adolfo Correa, Annie Green Howard, Kari E North, Jerome I Rotter, Stephen S Rich, Ulrike Peters, Zhe Wang, Michael Y Tsai, Penny Gordon-Larsen, Christie Ballantyne, Shia T Kent, Ruth J F Loos, Christy L Avery, Xiuqing Guo, Jie Yao, Yao Hu, Mariaelisa Graff, Paul S de Vries, Keri L Monda, Moa P Lee, Sofia F Dimos, Laura M Raffield, Anna F Ballou, Carolina G Downie, Christopher H Arehart, Zhaohui Du, Christopher R Gignoux, Jeffrey Haessler, Helina Kassahun, J Antonio G Lopez, Michael H Preuss, Shannon L Rhodes, Rina Yarosh, and Charles L Kooperberg

Subjects
Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Introduction The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations.Methods Here, we examined how ancestrally diverse studies could clarify Lp(a)’s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations.Results Fourteen genome-wide significant loci with numerous population specific signals of large effect were identified that enabled construction of Lp(a) PRS of moderate (R2=15% in East Asians) to high (R2=50% in Europeans) accuracy. For all populations, PRS showed promise as a ‘rule out’ for elevated Lp(a) because certainty of assignment to the low-risk threshold was high (88.0%–99.9%) across PRS thresholds (80th–99th percentile). Causal effects of increased Lp(a) with increased glycated haemoglobin were estimated for Europeans (p value =1.4×10−6), although inverse effects in Africans and East Asians suggested the potential for heterogeneous causal effects. Finally, Hispanic/Latinos were the only population in which known associations with coronary atherosclerosis and ischaemic heart disease were identified in external testing of Lp(a) PRS phenotypic effects.Conclusions Our results emphasise the merits of prioritising ancestral diversity when addressing Lp(a) evidence gaps.

Published
2023
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35. Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations

Author

Daniel S. Araujo, Chris Nguyen, Xiaowei Hu, Anna V. Mikhaylova, Chris Gignoux, Kristin Ardlie, Kent D. Taylor, Peter Durda, Yongmei Liu, George Papanicolaou, Michael H. Cho, Stephen S. Rich, Jerome I. Rotter, Hae Kyung Im, Ani Manichaikul, and Heather E. Wheeler

Subjects
genetics, genomics, human genetics, transcriptome-wide association studies, transcriptome prediction, multivarite adaptive shrinkage, Genetics, QH426-470
Abstract

Summary: Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized that methods that leverage shared regulatory effects across different conditions, in this case, across different populations, may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWASs) using different methods (elastic net, joint-tissue imputation [JTI], matrix expression quantitative trait loci [Matrix eQTL], multivariate adaptive shrinkage in R [MASHR], and transcriptome-integrated genetic association resource [TIGAR]) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios. Additionally, to evaluate model applicability in TWASs, we integrated publicly available multiethnic genome-wide association study (GWAS) summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study and Pan-ancestry genetic analysis of the UK Biobank (PanUKBB) with our developed transcriptome prediction models. In regard to transcriptome prediction accuracy, MASHR models performed better or the same as other methods in both population-matched and cross-population transcriptome predictions. Furthermore, in multiethnic TWASs, MASHR models yielded more discoveries that replicate in both PAGE and PanUKBB across all methods analyzed, including loci previously mapped in GWASs and loci previously not found in GWASs. Overall, our study demonstrates the importance of using methods that benefit from different populations’ effect size estimates in order to improve TWASs for multiethnic or underrepresented populations.

Published
2023
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36. The functional impact of rare variation across the regulatory cascade

Author

Taibo Li, Nicole Ferraro, Benjamin J. Strober, Francois Aguet, Silva Kasela, Marios Arvanitis, Bohan Ni, Laurens Wiel, Elliot Hershberg, Kristin Ardlie, Dan E. Arking, Rebecca L. Beer, Jennifer Brody, Thomas W. Blackwell, Clary Clish, Stacey Gabriel, Robert Gerszten, Xiuqing Guo, Namrata Gupta, W. Craig Johnson, Tuuli Lappalainen, Henry J. Lin, Yongmei Liu, Deborah A. Nickerson, George Papanicolaou, Jonathan K. Pritchard, Pankaj Qasba, Ali Shojaie, Josh Smith, Nona Sotoodehnia, Kent D. Taylor, Russell P. Tracy, David Van Den Berg, Matthew T. Wheeler, Stephen S. Rich, Jerome I. Rotter, Alexis Battle, and Stephen B. Montgomery

Subjects
rare variants, multi-omics, functional genomics, machine learning, transcriptome, proteome, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract

Summary: Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype’s ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13–27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, “Watershed,” to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer’s disease.

Published
2023
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37. Association Between Whole Blood–Derived Mitochondrial DNA Copy Number, Low‐Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Author

Xue Liu, Xianbang Sun, Yuankai Zhang, Wenqing Jiang, Meng Lai, Kerri L. Wiggins, Laura M. Raffield, Lawrence F. Bielak, Wei Zhao, Achilleas Pitsillides, Jeffrey Haessler, Yinan Zheng, Thomas W. Blackwell, Jie Yao, Xiuqing Guo, Yong Qian, Bharat Thyagarajan, Nathan Pankratz, Stephen S. Rich, Kent D. Taylor, Patricia A. Peyser, Susan R. Heckbert, Sudha Seshadri, Eric Boerwinkle, Megan L. Grove, Nicholas B. Larson, Jennifer A. Smith, Ramachandran S. Vasan, Annette L. Fitzpatrick, Myriam Fornage, Jun Ding, April P. Carson, Goncalo Abecasis, Josée Dupuis, Alexander Reiner, Charles Kooperberg, Lifang Hou, Bruce M. Psaty, James G. Wilson, Daniel Levy, Jerome I. Rotter, Joshua C. Bis, Claudia L. Satizabal, Dan E. Arking, and Chunyu Liu

Subjects
cardiometabolic risk factors, cardiovascular disease, low‐density lipoprotein cholesterol, Mendelian randomization, mitochondrial DNA copy number, vascular atherosclerosis, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross‐sectional and prospective association analyses of blood‐derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole‐genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P

Published
2023
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38. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization [version 1; peer review: 2 approved]

Author

Natasha H. J. Ng, Sara M. Willems, Jian'an Luan, Rebecca S. Fine, Juan Fernandez, Jennifer Wessel, Eleanor Wheeler, Gaelle Marenne, Hidetoshi Kitajima, Hanieh Yaghootkar, Xueling Sim, Ian J. Deary, Sai Chen, Shuai Wang, Yii-Der Ida Chen, Caroline Hayward, Yuning Chen, Jennifer L. Asimit, Claudia Langenberg, Tibor V. Varga, Archie Campbell, Rona J. Strawbridge, Shuang Feng, Tarunveer S. Ahluwalia, Erica L. Kleinbrink, Emil V. Appel, Ping An, Lawrence F. Bielak, Dan E. Arking, Jennifer A. Brody, Nathan A. Bihlmeyer, David Porteous, Ayse Demirkan, Audrey Y. Chu, Franco Giulianini, James S. Floyd, Stefan Gustafsson, Xiuqing Guo, Johanna Jakobsdottir, Anne U. Jackson, Stavroula Kanoni, Richard A. Jensen, Igor Rudan, Man Li, Sirkka Keinanen-Kiukaanniemi, Alisa K. Manning, Yingchang Lu, Karina Meidtner, Jonathan Marten, Giorgio Pistis, Taulant Muka, Kenneth M. Rice, Bram Prins, Albert Vernon Smith, Serena Sanna, Lorraine Southam, Jennifer A. Smith, Vinicius Tragante, Heather M. Stringham, Helen R. Warren, Sander W. van der Laan, Andrianos M. Yiorkas, Jie Yao, Wei Zhao, Weihua Zhang, Heather M. Highland, Mariaelisa Graff, Eirini Marouli, Anne E. Justice, Wesam A. Alhejily, Saima Afaq, Folkert W. Asselbergs, Najaf Amin, Michiel L. Bots, Lori L. Bonnycastle, Ji Chen, Ivan Brandslund, Abbas Dehghan, John Danesh, Tapani Ebeling, Jessica D. Faul, Aliki-Eleni Farmaki, Steve Franks, Paul W. Franks, Anette P. Gjesing, Andreas Fritsche, Göran Hallmans, Mark O. Goodarzi, Karl-Heinz Herzig, Tamara B. Harris, Min A Jhun, Marie-France Hivert, Marit E. Jørgensen, Torben Jørgensen, Eero Kajantie, Pekka Jousilahti, Sharon L.R. Kardia, Maria Karaleftheri, Heikki A. Koistinen, Leena Kinnunen, Peter Kovacs, Pirjo Komulainen, Markku Laakso, Johanna Kuusisto, Aaron Leong, Lenore J. Launer, Jocelyn E. Manning Fox, Jaana Lindström, Nisa M. Maruthur, Satu Männistö, Antonella Mulas, Leena Moilanen, Matthew Neville, Mike A. Nalls, Alison Pattie, James S. Pankow, Hannu Puolijoki, Eva R.B. Petersen, Paul Redmond, Asif Rasheed, Michael Roden, Frida Renström, Juha Saltevo, Danish Saleheen, Sylvain Sebert, Kai Savonen, Alena Stančáková, Kerrin S. Small, Konstantin Strauch, Jakob Stokholm, Betina H. Thuesen, Juha Auvinen, E-Shyong Tai, Emmanouil Tsafantakis, Anke Tönjes, Jaakko Tuomilehto, Tiinamaija Tuomi, Marja Vääräsmäki, Matti Uusitupa, Magdalena Zoledziewska, Ilonca Vaartjes, Beverley Balkau, Goncalo Abecasis, Alexandra I. Blakemore, Hans Bisgaard, Heiner Boeing, Ruth J.F. Loos, Matthias Blüher, Klaus Bønnelykke, Eric Boerwinkle, Mark J. Caulfield, Erwin P. Bottinger, Daniel I. Chasman, John C. Chambers, Francis S. Collins, Ching-Yu Cheng, Francesco Cucca, Josef Coresh, George Dedoussis, Gert J. de Borst, Hester M. den Ruijter, Panos Deloukas, Ele Ferrannini, Michele K. Evans, Harald Grallert, Oscar H. Franco, Arfan Ikram, Joel N. Hirschhorn, Fredrik Karpe, Erik Ingelsson, Wieland Kiess, Carolina Medina-Gomez, Kay-Tee Kaw, Antje Körner, Jaspal S. Kooner, Cecilia M. Lindgren, Timo Lakka, Ching-Ti Liu, Leonard Lipovich, Patrick E. MacDonald, Jun Liu, Andrew D. Morris, Karen L. Mohlke, Alison Murray, Patricia B. Munroe, Gerard Pasterkamp, Colin N. A . Palmer, Patricia A. Peyser, Oluf Pedersen, Paul M. Ridker, Rainer Rauramaa, Patrik Rorsman, Olov Rolandsson, Veikko Salomaa, Frits R. Rosendaal, Robert Sladek, Matthias B. Schulze, Michael Stumvoll, Timothy D. Spector, Mark Walker, Cornelia M. van Duijn, David R. Weir, Nick J. Wareham, Tien Yin Wong, James G. Wilson, Alan B. Zonderman, Eleftheria Zeggini, Andrew P. Morris, Jerome I. Rotter, Jose C. Florez, Michael Boehnke, James B. Meigs, Mark I. McCarthy, Robert A. Scott, Anubha Mahajan, Inês Barroso, Anna L. Gloyn, Michael A. Province, Niels Grarup, Ruifang Li-Gao, Jette Bork-Jensen, Yongmei Liu, Allan Linneberg, Leslie A. Lange, Sandosh Padmanabhan, Gail Davies, Lars Lind, Bruce M. Psaty, Tea Skaaby, Torben Hansen, Ozren Polasek, John M. Starr, Dennis O. Mook-Kanamori, Vilmundur Gudnason, Kent D. Taylor, Marjo-Riitta Järvelin, Renée de Mutsert, Paul Elliott, Josée Dupuis, Blair H. Smith, and Andrew T. Hattersley

Subjects
exome chip, glycaemic traits, genetic discovery, effector genes, summary statistics resources, eng, Medicine, Science
Abstract

Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Published
2023
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39. Development and validation of a metabolite index for obstructive sleep apnea across race/ethnicities

Author

Ying Zhang, Debby Ngo, Bing Yu, Neomi A. Shah, Han Chen, Alberto R. Ramos, Phyllis C. Zee, Russell Tracy, Peter Durda, Robert Kaplan, Martha L. Daviglus, Stephen S. Rich, Jerome I. Rotter, Jianwen Cai, Clary Clish, Robert Gerszten, Bruce S. Kristal, Sina A. Gharib, Susan Redline, and Tamar Sofer

Subjects
Medicine, Science
Abstract

Abstract Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. Studying metabolomic associations with OSA in a diverse community-based cohort may provide insights into the pathophysiology of OSA. We aimed to develop and replicate a metabolite index for OSA and identify individual metabolites associated with OSA. We studied 219 metabolites and their associations with the apnea hypopnea index (AHI) and with moderate-severe OSA (AHI ≥ 15) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n = 3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites jointly associated with OSA, which was used to develop a metabolite index for OSA. Results were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n = 475). When assessing the associations with individual metabolites, we identified seven metabolites significantly positively associated with OSA in HCHS/SOL (FDR p

Published
2022
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40. Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program

Author

Marsha M. Wheeler, Adrienne M. Stilp, Shuquan Rao, Bjarni V. Halldórsson, Doruk Beyter, Jia Wen, Anna V. Mihkaylova, Caitlin P. McHugh, John Lane, Min-Zhi Jiang, Laura M. Raffield, Goo Jun, Fritz J. Sedlazeck, Ginger Metcalf, Yao Yao, Joshua B. Bis, Nathalie Chami, Paul S. de Vries, Pinkal Desai, James S. Floyd, Yan Gao, Kai Kammers, Wonji Kim, Jee-Young Moon, Aakrosh Ratan, Lisa R. Yanek, Laura Almasy, Lewis C. Becker, John Blangero, Michael H. Cho, Joanne E. Curran, Myriam Fornage, Robert C. Kaplan, Joshua P. Lewis, Ruth J. F. Loos, Braxton D. Mitchell, Alanna C. Morrison, Michael Preuss, Bruce M. Psaty, Stephen S. Rich, Jerome I. Rotter, Hua Tang, Russell P. Tracy, Eric Boerwinkle, Goncalo R. Abecasis, Thomas W. Blackwell, Albert V. Smith, Andrew D. Johnson, Rasika A. Mathias, Deborah A. Nickerson, Matthew P. Conomos, Yun Li, Unnur Þorsteinsdóttir, Magnús K. Magnússon, Kari Stefansson, Nathan D. Pankratz, Daniel E. Bauer, Paul L. Auer, and Alex P. Reiner

Subjects
Science
Abstract

Most genetic association studies have been done on single nucleotide polymorphisms and small indels, while other types of variants have been less studied. Here, the authors use whole genome sequencing in a diverse population to identify and provide experimental evidence for associations between structural variants and blood-cell traits.

Published
2022
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41. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Author

Stavroula Kanoni, Sarah E. Graham, Yuxuan Wang, Ida Surakka, Shweta Ramdas, Xiang Zhu, Shoa L. Clarke, Konain Fatima Bhatti, Sailaja Vedantam, Thomas W. Winkler, Adam E. Locke, Eirini Marouli, Greg J. M. Zajac, Kuan-Han H. Wu, Ioanna Ntalla, Qin Hui, Derek Klarin, Austin T. Hilliard, Zeyuan Wang, Chao Xue, Gudmar Thorleifsson, Anna Helgadottir, Daniel F. Gudbjartsson, Hilma Holm, Isleifur Olafsson, Mi Yeong Hwang, Sohee Han, Masato Akiyama, Saori Sakaue, Chikashi Terao, Masahiro Kanai, Wei Zhou, Ben M. Brumpton, Humaira Rasheed, Aki S. Havulinna, Yogasudha Veturi, Jennifer Allen Pacheco, Elisabeth A. Rosenthal, Todd Lingren, QiPing Feng, Iftikhar J. Kullo, Akira Narita, Jun Takayama, Hilary C. Martin, Karen A. Hunt, Bhavi Trivedi, Jeffrey Haessler, Franco Giulianini, Yuki Bradford, Jason E. Miller, Archie Campbell, Kuang Lin, Iona Y. Millwood, Asif Rasheed, George Hindy, Jessica D. Faul, Wei Zhao, David R. Weir, Constance Turman, Hongyan Huang, Mariaelisa Graff, Ananyo Choudhury, Dhriti Sengupta, Anubha Mahajan, Michael R. Brown, Weihua Zhang, Ketian Yu, Ellen M. Schmidt, Anita Pandit, Stefan Gustafsson, Xianyong Yin, Jian’an Luan, Jing-Hua Zhao, Fumihiko Matsuda, Hye-Mi Jang, Kyungheon Yoon, Carolina Medina-Gomez, Achilleas Pitsillides, Jouke Jan Hottenga, Andrew R. Wood, Yingji Ji, Zishan Gao, Simon Haworth, Noha A. Yousri, Ruth E. Mitchell, Jin Fang Chai, Mette Aadahl, Anne A. Bjerregaard, Jie Yao, Ani Manichaikul, Chii-Min Hwu, Yi-Jen Hung, Helen R. Warren, Julia Ramirez, Jette Bork-Jensen, Line L. Kårhus, Anuj Goel, Maria Sabater-Lleal, Raymond Noordam, Pala Mauro, Floris Matteo, Aaron F. McDaid, Pedro Marques-Vidal, Matthias Wielscher, Stella Trompet, Naveed Sattar, Line T. Møllehave, Matthias Munz, Lingyao Zeng, Jianfeng Huang, Bin Yang, Alaitz Poveda, Azra Kurbasic, Claudia Lamina, Lukas Forer, Markus Scholz, Tessel E. Galesloot, Jonathan P. Bradfield, Sanni E. Ruotsalainen, EWarwick Daw, Joseph M. Zmuda, Jonathan S. Mitchell, Christian Fuchsberger, Henry Christensen, Jennifer A. Brody, Miguel Vazquez-Moreno, Mary F. Feitosa, Mary K. Wojczynski, Zhe Wang, Michael H. Preuss, Massimo Mangino, Paraskevi Christofidou, Niek Verweij, Jan W. Benjamins, Jorgen Engmann, Noah L. Tsao, Anurag Verma, Roderick C. Slieker, Ken Sin Lo, Nuno R. Zilhao, Phuong Le, Marcus E. Kleber, Graciela E. Delgado, Shaofeng Huo, Daisuke D. Ikeda, Hiroyuki Iha, Jian Yang, Jun Liu, Ayşe Demirkan, Hampton L. Leonard, Jonathan Marten, Mirjam Frank, Börge Schmidt, Laura J. Smyth, Marisa Cañadas-Garre, Chaolong Wang, Masahiro Nakatochi, Andrew Wong, Nina Hutri-Kähönen, Xueling Sim, Rui Xia, Alicia Huerta-Chagoya, Juan Carlos Fernandez-Lopez, Valeriya Lyssenko, Suraj S. Nongmaithem, Swati Bayyana, Heather M. Stringham, Marguerite R. Irvin, Christopher Oldmeadow, Han-Na Kim, Seungho Ryu, Paul R. H. J. Timmers, Liubov Arbeeva, Rajkumar Dorajoo, Leslie A. Lange, Gauri Prasad, Laura Lorés-Motta, Marc Pauper, Jirong Long, Xiaohui Li, Elizabeth Theusch, Fumihiko Takeuchi, Cassandra N. Spracklen, Anu Loukola, Sailalitha Bollepalli, Sophie C. Warner, Ya Xing Wang, Wen B. Wei, Teresa Nutile, Daniela Ruggiero, Yun Ju Sung, Shufeng Chen, Fangchao Liu, Jingyun Yang, Katherine A. Kentistou, Bernhard Banas, Giuseppe Giovanni Nardone, Karina Meidtner, Lawrence F. Bielak, Jennifer A. Smith, Prashantha Hebbar, Aliki-Eleni Farmaki, Edith Hofer, Maoxuan Lin, Maria Pina Concas, Simona Vaccargiu, Peter J. van der Most, Niina Pitkänen, Brian E. Cade, Sander W. van der Laan, Kumaraswamy Naidu Chitrala, Stefan Weiss, Amy R. Bentley, Ayo P. Doumatey, Adebowale A. Adeyemo, Jong Young Lee, Eva R. B. Petersen, Aneta A. Nielsen, Hyeok Sun Choi, Maria Nethander, Sandra Freitag-Wolf, Lorraine Southam, Nigel W. Rayner, Carol A. Wang, Shih-Yi Lin, Jun-Sing Wang, Christian Couture, Leo-Pekka Lyytikäinen, Kjell Nikus, Gabriel Cuellar-Partida, Henrik Vestergaard, Bertha Hidalgo, Olga Giannakopoulou, Qiuyin Cai, Morgan O. Obura, Jessica van Setten, Xiaoyin Li, Jingjing Liang, Hua Tang, Natalie Terzikhan, Jae Hun Shin, Rebecca D. Jackson, Alexander P. Reiner, Lisa Warsinger Martin, Zhengming Chen, Liming Li, Takahisa Kawaguchi, Joachim Thiery, Joshua C. Bis, Lenore J. Launer, Huaixing Li, Mike A. Nalls, Olli T. Raitakari, Sahoko Ichihara, Sarah H. Wild, Christopher P. Nelson, Harry Campbell, Susanne Jäger, Toru Nabika, Fahd Al-Mulla, Harri Niinikoski, Peter S. Braund, Ivana Kolcic, Peter Kovacs, Tota Giardoglou, Tomohiro Katsuya, Dominique de Kleijn, Gert J. de Borst, Eung Kweon Kim, Hieab H. H. Adams, M. Arfan Ikram, Xiaofeng Zhu, Folkert W. Asselbergs, Adriaan O. Kraaijeveld, Joline W. J. Beulens, Xiao-Ou Shu, Loukianos S. Rallidis, Oluf Pedersen, Torben Hansen, Paul Mitchell, Alex W. Hewitt, Mika Kähönen, Louis Pérusse, Claude Bouchard, Anke Tönjes, Yii-Der Ida Chen, Craig E. Pennell, Trevor A. Mori, Wolfgang Lieb, Andre Franke, Claes Ohlsson, Dan Mellström, Yoon Shin Cho, Hyejin Lee, Jian-Min Yuan, Woon-Puay Koh, Sang Youl Rhee, Jeong-Taek Woo, Iris M. Heid, Klaus J. Stark, Martina E. Zimmermann, Henry Völzke, Georg Homuth, Michele K. Evans, Alan B. Zonderman, Ozren Polasek, Gerard Pasterkamp, Imo E. Hoefer, Susan Redline, Katja Pahkala, Albertine J. Oldehinkel, Harold Snieder, Ginevra Biino, Reinhold Schmidt, Helena Schmidt, Stefania Bandinelli, George Dedoussis, Thangavel Alphonse Thanaraj, Sharon L. R. Kardia, Patricia A. Peyser, Norihiro Kato, Matthias B. Schulze, Giorgia Girotto, Carsten A. Böger, Bettina Jung, Peter K. Joshi, David A. Bennett, Philip L. De Jager, Xiangfeng Lu, Vasiliki Mamakou, Morris Brown, Mark J. Caulfield, Patricia B. Munroe, Xiuqing Guo, Marina Ciullo, Jost B. Jonas, Nilesh J. Samani, Jaakko Kaprio, Päivi Pajukanta, Teresa Tusié-Luna, Carlos A. Aguilar-Salinas, Linda S. Adair, Sonny Augustin Bechayda, H. Janaka de Silva, Ananda R. Wickremasinghe, Ronald M. Krauss, Jer-Yuarn Wu, Wei Zheng, Anneke Iden Hollander, Dwaipayan Bharadwaj, Adolfo Correa, James G. Wilson, Lars Lind, Chew-Kiat Heng, Amanda E. Nelson, Yvonne M. Golightly, James F. Wilson, Brenda Penninx, Hyung-Lae Kim, John Attia, Rodney J. Scott, D. C. Rao, Donna K. Arnett, Steven C. Hunt, Mark Walker, Heikki A. Koistinen, Giriraj R. Chandak, Josep M. Mercader, Maria C. Costanzo, Dongkeun Jang, Noël P. Burtt, Clicerio Gonzalez Villalpando, Lorena Orozco, Myriam Fornage, EShyong Tai, Rob M. van Dam, Terho Lehtimäki, Nish Chaturvedi, Mitsuhiro Yokota, Jianjun Liu, Dermot F. Reilly, Amy Jayne McKnight, Frank Kee, Karl-Heinz Jöckel, Mark I. McCarthy, Colin N. A. Palmer, Veronique Vitart, Caroline Hayward, Eleanor Simonsick, Cornelia M. van Duijn, Zi-Bing Jin, Jia Qu, Haretsugu Hishigaki, Xu Lin, Winfried März, Vilmundur Gudnason, Jean-Claude Tardif, Guillaume Lettre, Leen M.‘t Hart, Petra J. M. Elders, Scott M. Damrauer, Meena Kumari, Mika Kivimaki, Pim van der Harst, Tim D. Spector, Ruth J. F. Loos, Michael A. Province, Esteban J. Parra, Miguel Cruz, Bruce M. Psaty, Ivan Brandslund, Peter P. Pramstaller, Charles N. Rotimi, Kaare Christensen, Samuli Ripatti, Elisabeth Widén, Hakon Hakonarson, Struan F. A. Grant, Lambertus A. L. M. Kiemeney, Jacqueline de Graaf, Markus Loeffler, Florian Kronenberg, Dongfeng Gu, Jeanette Erdmann, Heribert Schunkert, Paul W. Franks, Allan Linneberg, J. Wouter Jukema, Amit V. Khera, Minna Männikkö, Marjo-Riitta Jarvelin, Zoltan Kutalik, Cucca Francesco, Dennis O. Mook-Kanamori, Ko Willems van Dijk, Hugh Watkins, David P. Strachan, Niels Grarup, Peter Sever, Neil Poulter, Lee-Ming Chuang, Jerome I. Rotter, Thomas M. Dantoft, Fredrik Karpe, Matt J. Neville, Nicholas J. Timpson, Ching-Yu Cheng, Tien-Yin Wong, Chiea Chuen Khor, Hengtong Li, Charumathi Sabanayagam, Annette Peters, Christian Gieger, Andrew T. Hattersley, Nancy L. Pedersen, Patrik K. E. Magnusson, Dorret I. Boomsma, Allegonda H. M. Willemsen, LAdrienne Cupples, Joyce B. J. van Meurs, Mohsen Ghanbari, Penny Gordon-Larsen, Wei Huang, Young Jin Kim, Yasuharu Tabara, Nicholas J. Wareham, Claudia Langenberg, Eleftheria Zeggini, Johanna Kuusisto, Markku Laakso, Erik Ingelsson, Goncalo Abecasis, John C. Chambers, Jaspal S. Kooner, Paul S. de Vries, Alanna C. Morrison, Scott Hazelhurst, Michèle Ramsay, Kari E. North, Martha Daviglus, Peter Kraft, Nicholas G. Martin, John B. Whitfield, Shahid Abbas, Danish Saleheen, Robin G. Walters, Michael V. Holmes, Corri Black, Blair H. Smith, Aris Baras, Anne E. Justice, Julie E. Buring, Paul M. Ridker, Daniel I. Chasman, Charles Kooperberg, Gen Tamiya, Masayuki Yamamoto, David A. van Heel, Richard C. Trembath, Wei-Qi Wei, Gail P. Jarvik, Bahram Namjou, M. Geoffrey Hayes, Marylyn D. Ritchie, Pekka Jousilahti, Veikko Salomaa, Kristian Hveem, Bjørn Olav Åsvold, Michiaki Kubo, Yoichiro Kamatani, Yukinori Okada, Yoshinori Murakami, Bong-Jo Kim, Unnur Thorsteinsdottir, Kari Stefansson, Jifeng Zhang, YEugene Chen, Yuk-Lam Ho, Julie A. Lynch, Daniel J. Rader, Philip S. Tsao, Kyong-Mi Chang, Kelly Cho, Christopher J. O’Donnell, John M. Gaziano, Peter W. F. Wilson, Timothy M. Frayling, Joel N. Hirschhorn, Sekar Kathiresan, Karen L. Mohlke, Yan V. Sun, Andrew P. Morris, Michael Boehnke, Christopher D. Brown, Pradeep Natarajan, Panos Deloukas, Cristen J. Willer, Themistocles L. Assimes, and Gina M. Peloso

Subjects
Cholesterol, Lipids, Genetics, Genome-wide association study, GWAS, Biology (General), QH301-705.5, QH426-470
Abstract

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Published
2022
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42. Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Author

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

Subjects
Science
Abstract

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data.

Published
2022
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43. Genetic modification of inflammation- and clonal hematopoiesis–associated cardiovascular risk

Author

Zhi Yu, Trevor P. Fidler, Yunfeng Ruan, Caitlyn Vlasschaert, Tetsushi Nakao, Md Mesbah Uddin, Taralynn Mack, Abhishek Niroula, J. Brett Heimlich, Seyedeh M. Zekavat, Christopher J. Gibson, Gabriel K. Griffin, Yuxuan Wang, Gina M. Peloso, Nancy Heard-Costa, Daniel Levy, Ramachandran S. Vasan, François Aguet, Kristin G. Ardlie, Kent D. Taylor, Stephen S. Rich, Jerome I. Rotter, Peter Libby, Siddhartha Jaiswal, Benjamin L. Ebert, Alexander G. Bick, Alan R. Tall, and Pradeep Natarajan

Subjects
Cardiology, Genetics, Medicine
Abstract

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk.

Published
2023
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44. Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease

Author

M d Mesbah Uddin, Ngoc Quynh H. Nguyen, Bing Yu, Jennifer A. Brody, Akhil Pampana, Tetsushi Nakao, Myriam Fornage, Jan Bressler, Nona Sotoodehnia, Joshua S. Weinstock, Michael C. Honigberg, Daniel Nachun, Romit Bhattacharya, Gabriel K. Griffin, Varuna Chander, Richard A. Gibbs, Jerome I. Rotter, Chunyu Liu, Andrea A. Baccarelli, Daniel I. Chasman, Eric A. Whitsel, Douglas P. Kiel, Joanne M. Murabito, Eric Boerwinkle, Benjamin L. Ebert, Siddhartha Jaiswal, James S. Floyd, Alexander G. Bick, Christie M. Ballantyne, Bruce M. Psaty, Pradeep Natarajan, and Karen N. Conneely

Subjects
Science
Abstract

Clonal hematopoiesis, often caused by mutations in DNMT3A and TET2, is associated with blood cancer and coronary artery disease. Here, the authors conduct an epigenome-wide association study, finding that clonal hematopoiesis caused by DNMT3A vs. TET2 mutations has directionally opposing changes in DNA methylation profiles, with both promoting stem cell self-renewal.

Published
2022
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45. Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

Author

William J. Young, Najim Lahrouchi, Aaron Isaacs, ThuyVy Duong, Luisa Foco, Farah Ahmed, Jennifer A. Brody, Reem Salman, Raymond Noordam, Jan-Walter Benjamins, Jeffrey Haessler, Leo-Pekka Lyytikäinen, Linda Repetto, Maria Pina Concas, Marten E. van den Berg, Stefan Weiss, Antoine R. Baldassari, Traci M. Bartz, James P. Cook, Daniel S. Evans, Rebecca Freudling, Oliver Hines, Jonas L. Isaksen, Honghuang Lin, Hao Mei, Arden Moscati, Martina Müller-Nurasyid, Casia Nursyifa, Yong Qian, Anne Richmond, Carolina Roselli, Kathleen A. Ryan, Eduardo Tarazona-Santos, Sébastien Thériault, Stefan van Duijvenboden, Helen R. Warren, Jie Yao, Dania Raza, Stefanie Aeschbacher, Gustav Ahlberg, Alvaro Alonso, Laura Andreasen, Joshua C. Bis, Eric Boerwinkle, Archie Campbell, Eulalia Catamo, Massimiliano Cocca, Michael J. Cutler, Dawood Darbar, Alessandro De Grandi, Antonio De Luca, Jun Ding, Christina Ellervik, Patrick T. Ellinor, Stephan B. Felix, Philippe Froguel, Christian Fuchsberger, Martin Gögele, Claus Graff, Mariaelisa Graff, Xiuqing Guo, Torben Hansen, Susan R. Heckbert, Paul L. Huang, Heikki V. Huikuri, Nina Hutri-Kähönen, M. Arfan Ikram, Rebecca D. Jackson, Juhani Junttila, Maryam Kavousi, Jan A. Kors, Thiago P. Leal, Rozenn N. Lemaitre, Henry J. Lin, Lars Lind, Allan Linneberg, Simin Liu, Peter W. MacFarlane, Massimo Mangino, Thomas Meitinger, Massimo Mezzavilla, Pashupati P. Mishra, Rebecca N. Mitchell, Nina Mononen, May E. Montasser, Alanna C. Morrison, Matthias Nauck, Victor Nauffal, Pau Navarro, Kjell Nikus, Guillaume Pare, Kristen K. Patton, Giulia Pelliccione, Alan Pittman, David J. Porteous, Peter P. Pramstaller, Michael H. Preuss, Olli T. Raitakari, Alexander P. Reiner, Antonio Luiz P. Ribeiro, Kenneth M. Rice, Lorenz Risch, David Schlessinger, Ulrich Schotten, Claudia Schurmann, Xia Shen, M. Benjamin Shoemaker, Gianfranco Sinagra, Moritz F. Sinner, Elsayed Z. Soliman, Monika Stoll, Konstantin Strauch, Kirill Tarasov, Kent D. Taylor, Andrew Tinker, Stella Trompet, André Uitterlinden, Uwe Völker, Henry Völzke, Melanie Waldenberger, Lu-Chen Weng, Eric A. Whitsel, James G. Wilson, Christy L. Avery, David Conen, Adolfo Correa, Francesco Cucca, Marcus Dörr, Sina A. Gharib, Giorgia Girotto, Niels Grarup, Caroline Hayward, Yalda Jamshidi, Marjo-Riitta Järvelin, J. Wouter Jukema, Stefan Kääb, Mika Kähönen, Jørgen K. Kanters, Charles Kooperberg, Terho Lehtimäki, Maria Fernanda Lima-Costa, Yongmei Liu, Ruth J. F. Loos, Steven A. Lubitz, Dennis O. Mook-Kanamori, Andrew P. Morris, Jeffrey R. O’Connell, Morten Salling Olesen, Michele Orini, Sandosh Padmanabhan, Cristian Pattaro, Annette Peters, Bruce M. Psaty, Jerome I. Rotter, Bruno Stricker, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, James F. Wilson, Dan E. Arking, Julia Ramirez, Pier D. Lambiase, Nona Sotoodehnia, Borbala Mifsud, Christopher Newton-Cheh, and Patricia B. Munroe

Subjects
Science
Abstract

The QT interval is a heritable electrocardiographic measure associated with arrhythmia risk when prolonged. Here, the authors used a series of genetic analyses to identify genetic loci, pathways, therapeutic targets, and relationships with cardiovascular disease.

Published
2022
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46. Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations

Author

Michael Elgart, Genevieve Lyons, Santiago Romero-Brufau, Nuzulul Kurniansyah, Jennifer A. Brody, Xiuqing Guo, Henry J. Lin, Laura Raffield, Yan Gao, Han Chen, Paul de Vries, Donald M. Lloyd-Jones, Leslie A. Lange, Gina M. Peloso, Myriam Fornage, Jerome I. Rotter, Stephen S. Rich, Alanna C. Morrison, Bruce M. Psaty, Daniel Levy, Susan Redline, the NHLBI’s Trans-Omics in Precision Medicine (TOPMed) Consortium, and Tamar Sofer

Subjects
Biology (General), QH301-705.5
Abstract

Combining a standard polygenic risk score (PRS) as a feature in a machine learning model increases the percentage variance explained for those traits, helping to account for non-linearities or interaction effects in genetics-based prediction models.

Published
2022
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47. Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes

Author

Jennifer L. Halford, Valerie N. Morrill, Seung Hoan Choi, Sean J. Jurgens, Giorgio Melloni, Nicholas A. Marston, Lu-Chen Weng, Victor Nauffal, Amelia W. Hall, Sophia Gunn, Christina A. Austin-Tse, James P. Pirruccello, Shaan Khurshid, Heidi L. Rehm, Emelia J. Benjamin, Eric Boerwinkle, Jennifer A. Brody, Adolfo Correa, Brandon K. Fornwalt, Namrata Gupta, Christopher M. Haggerty, Stephanie Harris, Susan R. Heckbert, Charles C. Hong, Charles Kooperberg, Henry J. Lin, Ruth J. F. Loos, Braxton D. Mitchell, Alanna C. Morrison, Wendy Post, Bruce M. Psaty, Susan Redline, Kenneth M. Rice, Stephen S. Rich, Jerome I. Rotter, Peter F. Schnatz, Elsayed Z. Soliman, Nona Sotoodehnia, Eugene K. Wong, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Marc S. Sabatine, Christian T. Ruff, Kathryn L. Lunetta, Patrick T. Ellinor, and Steven A. Lubitz

Subjects
Science
Abstract

Accurate classification of genetic variants is critical for research and patient care. Here, the authors report that population-based associations between rare variants and quantitative endophenotypes for monogenic diseases can provide support for variant pathogenicity.

Published
2022
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48. Whole Genome Association Study of the Plasma Metabolome Identifies Metabolites Linked to Cardiometabolic Disease in Black Individuals

Author

Usman A. Tahir, Daniel H. Katz, Julian Avila-Pachecho, Alexander G. Bick, Akhil Pampana, Jeremy M. Robbins, Zhi Yu, Zsu-Zsu Chen, Mark D. Benson, Daniel E. Cruz, Debby Ngo, Shuliang Deng, Xu Shi, Shuning Zheng, Aaron S. Eisman, Laurie Farrell, Michael E. Hall, Adolfo Correa, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Xiuqing Guo, Jie Yao, Yii-Der Ida Chen, Ani W. Manichaikul, Frederick L. Ruberg, William S. Blaner, Deepti Jain, NHLBI Trans-Omics for Precision Medicine 1 Consortium, Claude Bouchard, Mark A. Sarzynski, Stephen S. Rich, Jerome I. Rotter, Thomas J. Wang, James G. Wilson, Clary B. Clish, Pradeep Natarajan, and Robert E. Gerszten

Subjects
Science
Abstract

Most studies of the genetics of the metabolome have been done in individuals of European descent. Here, the authors integrate genomics and metabolomics in Black individuals, highlighting the value of whole genome sequencing in diverse populations and linking circulating metabolites to human disease.

Published
2022
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49. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

Author

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

Subjects
Biology (General), QH301-705.5
Abstract

This study of 23,000 non-diabetic individuals highlights loci associated with fasting glucose and fasting insulin in diverse cohorts with whole genome sequence data.

Published
2022
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50. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood

Author

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

Subjects
Science
Abstract

Polygenic risk scores have potential to predict an individual’s risk of disease based on genetic markers. Here, the authors develop a polygenic risk score for hypertension and test it in a multi-ethnic cohort, finding that the score is associated with higher likelihood of hypertension development 4-6 years later.

Published
2022
Full Text
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