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Shao M, Tian M, Chen K, Jiang H, Zhang S, Li Z, Shen Y, Chen F, Shen B, Cao C, Gu N. Leveraging Random Effects in Cistrome-Wide Association Studies for Decoding the Genetic Determinants of Prostate Cancer. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2400815. [PMID: 39099406 DOI: 10.1002/advs.202400815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 07/09/2024] [Indexed: 08/06/2024]
Abstract
Cistrome-wide association studies (CWAS) are pivotal for identifying genetic determinants of diseases by correlating genetically regulated cistrome states with phenotypes. Traditional CWAS typically develops a model based on cistrome and genotype data to associate predicted cistrome states with phenotypes. The random effect cistrome-wide association study (RECWAS), reevaluates the necessity of cistrome state prediction in CWAS. RECWAS utilizes either a linear model or marginal effect for initial feature selection, followed by kernel-based feature aggregation for association testing is introduced. Through simulations and analysis of prostate cancer data, a thorough evaluation of CWAS and RECWAS is conducted. The results suggest that RECWAS offers improved power compared to traditional CWAS, identifying additional genomic regions associated with prostate cancer. CWAS identified 102 significant regions, while RECWAS found 50 additional significant regions compared to CWAS, many of which are validated. Validation encompassed a range of biological evidence, including risk signals from the GWAS catalog, susceptibility genes from the DisGeNET database, and enhancer-domain scores. RECWAS consistently demonstrated improved performance over traditional CWAS in identifying genomic regions associated with prostate cancer. These findings demonstrate the benefits of incorporating kernel methods into CWAS and provide new insights for genetic discovery in complex diseases.
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Affiliation(s)
- Mengting Shao
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Min Tian
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Kaiyang Chen
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Hangjin Jiang
- Center for Data Science, Zhejiang University, Hangzhou, 310058, P. R. China
| | - Shuting Zhang
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Zhenghui Li
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Yan Shen
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Feng Chen
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
| | - Baixin Shen
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, 210011, P. R. China
| | - Chen Cao
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, 210011, P. R. China
| | - Ning Gu
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, P. R. China
- Nanjing Key Laboratory for Cardiovascular Information and Health Engineering Medicine, Institute of Clinical Medicine, Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing, 210093, P. R. China
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Wang C, Wang T, Kiryluk K, Wei Y, Aschard H, Ionita-Laza I. Genome-wide discovery for biomarkers using quantile regression at biobank scale. Nat Commun 2024; 15:6460. [PMID: 39085219 PMCID: PMC11291931 DOI: 10.1038/s41467-024-50726-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 07/18/2024] [Indexed: 08/02/2024] Open
Abstract
Genome-wide association studies (GWAS) for biomarkers important for clinical phenotypes can lead to clinically relevant discoveries. Conventional GWAS for quantitative traits are based on simplified regression models modeling the conditional mean of a phenotype as a linear function of genotype. We draw attention here to an alternative, lesser known approach, namely quantile regression that naturally extends linear regression to the analysis of the entire conditional distribution of a phenotype of interest. Quantile regression can be applied efficiently at biobank scale, while having some unique advantages such as (1) identifying variants with heterogeneous effects across quantiles of the phenotype distribution; (2) accommodating a wide range of phenotype distributions including non-normal distributions, with invariance of results to trait transformations; and (3) providing more detailed information about genotype-phenotype associations even for those associations identified by conventional GWAS. We show in simulations that quantile regression is powerful across both homogeneous and various heterogeneous models. Applications to 39 quantitative traits in the UK Biobank demonstrate that quantile regression can be a helpful complement to linear regression in GWAS and can identify variants with larger effects on high-risk subgroups of individuals but with lower or no contribution overall.
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Affiliation(s)
- Chen Wang
- Department of Biostatistics, Columbia University, New York, NY, USA
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | | | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Ying Wei
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, France
| | - Iuliana Ionita-Laza
- Department of Biostatistics, Columbia University, New York, NY, USA.
- Department of Statistics, Lund University, Lund, Sweden.
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Jiang D, Shi Z, Wei J, Tran H, Zheng SL, Xu J, Lee CJ. Polygenic risk score informed clinical model for improving abdominal aortic aneurysm screening. Ann Vasc Surg 2024:S0890-5096(24)00473-4. [PMID: 39067852 DOI: 10.1016/j.avsg.2024.06.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 05/24/2024] [Accepted: 06/02/2024] [Indexed: 07/30/2024]
Abstract
INTRODUCTION Abdominal aortic aneurysm (AAA) is a complex disease with environmental and genetic risk factors. Polygenic risk scores (PRS) based on disease-specific risk-associated single nucleotide variants (SNVs) have demonstrated effectiveness in stratifying individual-level disease risk for cardiovascular diseases. This prospective cohort study assessed associations of PRS of AAA (PRSAAA) with risk of incident AAA, analyzed the effectiveness of a combined clinical-genetic risk model, and explored the clinical utility of the model in identifying high-risk individuals for AAA screening. METHODS PRSAAA was calculated using 911,440 SNVs and PRSCAD was calculated using 2,324,683 SNVs derived from mixed ancestry genome wide association studies. The UK Biobank was used as the study cohort. All individuals with complete genetic data available and no diagnosis of AAA at time of recruitment were included in the analysis and followed prospectively to assess for incident AAA. A PRS informed clinical model, Prob-AAA, was developed using clinically significant variables and PRSAAA. RESULTS 481,105 individuals were included in the analysis with 2,668 incident AAA cases. Incident AAA increased from 0.30% to 0.93% between the lowest and highest decile of PRSAAA; similarly, severe AAA, requiring surgery and/or presenting with rupture, increased from 23% to 39% of incident AAA cases across deciles. PRSAAA was a predictor of incident AAA diagnosis (HR 2.06 [1.70 - 2.48]) independent of other clinical risk factors including male sex, older age, and smoking history. Prob-AAA was an independent predictor of incident AAA (HR 1.92 [1.69 - 2.20]), and identified 9.6% of cases of incident AAA compared to only 4.2% by PRSAAA. Current screening guidelines captured 5.7% of the overall cohort, with an incident AAA rate of approximately 3.2%. Amongst males not included by current guidelines, Prob-AAA identified an additional cohort, approximately 2% of the overall cohort, with a similar rate of incident AAA. CONCLUSIONS Prob-AAA, a PRS informed clinical model for AAA, improved upon the predictive power of current, clinical risk factor informed, screening guidelines for AAA.
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Affiliation(s)
- David Jiang
- Department of Surgery, University of Chicago Medicine, Chicago, Illinois, USA.
| | - Zhuqing Shi
- Program for Personalized Cancer Care, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA
| | - Jun Wei
- Program for Personalized Cancer Care, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA
| | - Huy Tran
- Program for Personalized Cancer Care, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA
| | - S Lilly Zheng
- Program for Personalized Cancer Care, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA
| | - Jianfeng Xu
- Department of Surgery, University of Chicago Medicine, Chicago, Illinois, USA; Program for Personalized Cancer Care, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA; Department of Surgery, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA
| | - Cheong J Lee
- Department of Surgery, Endeavor Health (formerly NorthShore University HealthSystem), Evanston, Illinois, USA
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Hartwell EE, Jinwala Z, Milone J, Ramirez S, Gelernter J, Kranzler HR, Kember RL. Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits. Neuropsychopharmacology 2024:10.1038/s41386-024-01922-2. [PMID: 39043921 DOI: 10.1038/s41386-024-01922-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 06/07/2024] [Accepted: 06/28/2024] [Indexed: 07/25/2024]
Abstract
Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.
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Affiliation(s)
- Emily E Hartwell
- Crescenz VA Medical Center, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Zeal Jinwala
- Crescenz VA Medical Center, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Joel Gelernter
- West Haven VA Medical Center, West Haven, CT, USA
- Yale University, New Haven, CT, USA
| | - Henry R Kranzler
- Crescenz VA Medical Center, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Rachel L Kember
- Crescenz VA Medical Center, Philadelphia, PA, USA.
- University of Pennsylvania, Philadelphia, PA, USA.
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Naderian M, Hamed ME, Vaseem AA, Norland K, Dikilitas O, Teymourzadeh A, Bailey KR, Kullo IJ. Effect of disclosing a polygenic risk score for coronary heart disease on adverse cardiovascular events: 10-year follow-up of the MI-GENES randomized clinical trial. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.19.24310709. [PMID: 39072039 PMCID: PMC11275655 DOI: 10.1101/2024.07.19.24310709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Background The MI-GENES clinical trial (NCT01936675), in which participants at intermediate risk of coronary heart disease (CHD) were randomized to receive a Framingham risk score (FRSg, n=103), or an integrated risk score (IRSg, n=104) that additionally included a polygenic risk score (PRS), demonstrated that after 6 months, participants randomized to IRSg had higher statin initiation and lower low-density lipoprotein cholesterol (LDL-C). Objectives In a post hoc 10-year follow-up analysis of the MI-GENES trial, we investigated whether disclosure of a PRS for CHD was associated with a reduction in adverse cardiovascular events. Methods Participants were followed from randomization beginning in October 2013 until September 2023 to ascertain adverse cardiovascular events, testing for CHD, and changes in risk factors, by blinded review of electronic health records. The primary outcome was the time from randomization to the occurrence of the first major adverse cardiovascular event (MACE), defined as cardiovascular death, non-fatal myocardial infarction, coronary revascularization, and non-fatal stroke. Statistical analyses were conducted using Cox proportional hazards regression and linear mixed-effects models. Results We followed all 203 participants who completed the MI-GENES trial, 100 in FRSg and 103 in IRSg (mean age at the end of follow-up: 68.2±5.2, 48% male). During a median follow-up of 9.5 years, 9 MACEs occurred in FRSg and 2 in IRSg (hazard ratio (HR), 0.20; 95% confidence interval (CI), 0.04 to 0.94; P=0.042). In FRSg, 47 (47%) underwent at least one test for CHD, compared to 30 (29%) in IRSg (HR, 0.51; 95% CI, 0.32 to 0.81; P=0.004). IRSg participants had a longer duration of statin therapy during the first four years post-randomization and a greater reduction in LDL-C for up to 3 years post-randomization. No significant differences between the two groups were observed for hemoglobin A1C, systolic and diastolic blood pressures, weight, and smoking cessation rate during follow-up. Conclusions The disclosure of an IRS that included a PRS to individuals at intermediate risk for CHD was associated with a lower incidence of MACE after a decade of follow-up, likely due to a higher rate of initiation and longer duration of statin therapy, leading to lower LDL-C levels.
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Affiliation(s)
| | - Marwan E. Hamed
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ali A. Vaseem
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Kristjan Norland
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ozan Dikilitas
- Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Azin Teymourzadeh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Kent R. Bailey
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
- Gonda Vascular Center, Mayo Clinic, Rochester, MN, USA
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Sun YV, Liu C, Hui Q, Zhou JJ, Gaziano JM, Wilson PWF, Joseph J, Phillips LS. Identification and correction for collider bias in a genome-wide association study of diabetes-related heart failure. Am J Hum Genet 2024; 111:1481-1493. [PMID: 38897203 PMCID: PMC11267521 DOI: 10.1016/j.ajhg.2024.05.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 05/20/2024] [Accepted: 05/21/2024] [Indexed: 06/21/2024] Open
Abstract
Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) and has elevated incidence among individuals with HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted a genome-wide association study (GWAS) of diabetes-related HF with correction for collider bias. We first performed a GWAS of HF to identify genetic instrumental variables (GIVs) for HF and to enable bidirectional Mendelian randomization (MR) analysis between T2D and HF. We identified 61 genomic loci, significantly associated with all-cause HF in 114,275 individuals with HF and over 1.5 million controls of European ancestry. Using a two-sample bidirectional MR approach with 59 and 82 GIVs for HF and T2D, respectively, we estimated that T2D increased HF risk (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to the study design of index cases. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program and replicated the associations in the UK Biobank. Our MR findings provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci.
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Affiliation(s)
- Yan V Sun
- Atlanta VA Healthcare System, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA.
| | - Chang Liu
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Qin Hui
- Atlanta VA Healthcare System, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jin J Zhou
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Division of Aging, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter W F Wilson
- Atlanta VA Healthcare System, Decatur, GA, USA; Emory University School of Medicine, Atlanta, GA, USA
| | - Jacob Joseph
- VA Providence Healthcare System, Providence, RI, USA; The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Lawrence S Phillips
- Atlanta VA Healthcare System, Decatur, GA, USA; Emory University School of Medicine, Atlanta, GA, USA
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Weldy CS, Li Q, Monteiro JP, Guo H, Galls D, Gu W, Cheng PP, Ramste M, Li D, Palmisano BT, Sharma D, Worssam MD, Zhao Q, Bhate A, Kundu RK, Nguyen T, Li JB, Quertermous T. Smooth muscle expression of RNA editing enzyme ADAR1 controls vascular integrity and progression of atherosclerosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.08.602569. [PMID: 39026721 PMCID: PMC11257488 DOI: 10.1101/2024.07.08.602569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 ( IFIH1 ) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing to be an important mechanism of coronary artery disease (CAD) risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque, we implicate the vascular smooth muscle cell (SMC) to have a unique requirement for RNA editing, and that ISG induction occurs in SMC phenotypic modulation, implicating MDA5 activation. Through culture of human coronary artery SMCs, generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background, and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality.
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Trastulla L, Dolgalev G, Moser S, Jiménez-Barrón LT, Andlauer TFM, von Scheidt M, Budde M, Heilbronner U, Papiol S, Teumer A, Homuth G, Völzke H, Dörr M, Falkai P, Schulze TG, Gagneur J, Iorio F, Müller-Myhsok B, Schunkert H, Ziller MJ. Distinct genetic liability profiles define clinically relevant patient strata across common diseases. Nat Commun 2024; 15:5534. [PMID: 38951512 PMCID: PMC11217418 DOI: 10.1038/s41467-024-49338-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/31/2024] [Indexed: 07/03/2024] Open
Abstract
Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.
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Affiliation(s)
- Lucia Trastulla
- Max Planck Institute of Psychiatry, Munich, Germany
- Technische Universität München Medical Graduate Center Experimental Medicine, Munich, Germany
- Human Technopole, Milan, Italy
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Georgii Dolgalev
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Sylvain Moser
- Max Planck Institute of Psychiatry, Munich, Germany
- Technische Universität München Medical Graduate Center Experimental Medicine, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Laura T Jiménez-Barrón
- Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Till F M Andlauer
- Max Planck Institute of Psychiatry, Munich, Germany
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Moritz von Scheidt
- Klinik für Herz-und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
| | - Sergi Papiol
- Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
| | - Alexander Teumer
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Institute of Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Peter Falkai
- Max Planck Institute of Psychiatry, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Julien Gagneur
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Institute of Human Genetics, School of Medicine and Health, Technical University of Munich, Munich, Germany
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
| | | | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Heribert Schunkert
- Klinik für Herz-und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Michael J Ziller
- Max Planck Institute of Psychiatry, Munich, Germany.
- Department of Psychiatry, University of Münster, Münster, Germany.
- Center for Soft Nanoscience, University of Münster, Münster, Germany.
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Shi W, Song J, Weiner JM, Chopra A, Dommisch H, Beule D, Schaefer AS. lncRNA CDKN2B-AS1 regulates collagen expression. Hum Genet 2024; 143:907-919. [PMID: 38833008 PMCID: PMC11294485 DOI: 10.1007/s00439-024-02674-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/27/2024] [Indexed: 06/06/2024]
Abstract
The long noncoding RNA CDKN2B-AS1 harbors a major coronary artery disease risk haplotype, which is also associated with progressive forms of the oral inflammatory disease periodontitis as well as myocardial infarction (MI). Despite extensive research, there is currently no broad consensus on the function of CDKN2B-AS1 that would explain a common molecular role of this lncRNA in these diseases. Our aim was to investigate the role of CDKN2B-AS1 in gingival cells to better understand the molecular mechanisms underlying the increased risk of progressive periodontitis. We downregulated CDKN2B-AS1 transcript levels in primary gingival fibroblasts with LNA GapmeRs. Following RNA-sequencing, we performed differential expression, gene set enrichment analyses and Western Blotting. Putative causal alleles were searched by analyzing associated DNA sequence variants for changes of predicted transcription factor binding sites. We functionally characterized putative functional alleles using luciferase-reporter and antibody electrophoretic mobility shift assays in gingival fibroblasts and HeLa cells. Of all gene sets analysed, collagen biosynthesis was most significantly upregulated (Padj=9.7 × 10- 5 (AUC > 0.65) with the CAD and MI risk gene COL4A1 showing strongest upregulation of the enriched gene sets (Fold change = 12.13, Padj = 4.9 × 10- 25). The inflammatory "TNFA signaling via NFKB" gene set was downregulated the most (Padj=1 × 10- 5 (AUC = 0.60). On the single gene level, CAPNS2, involved in extracellular matrix organization, was the top upregulated protein coding gene (Fold change = 48.5, P < 9 × 10- 24). The risk variant rs10757278 altered a binding site of the pathogen responsive transcription factor STAT1 (P = 5.8 × 10- 6). rs10757278-G allele reduced STAT1 binding 14.4% and rs10757278-A decreased luciferase activity in gingival fibroblasts 41.2% (P = 0.0056), corresponding with GTEx data. CDKN2B-AS1 represses collagen gene expression in gingival fibroblasts. Dysregulated collagen biosynthesis through allele-specific CDKN2B-AS1 expression in response to inflammatory factors may affect collagen synthesis, and in consequence tissue barrier and atherosclerotic plaque stability.
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Affiliation(s)
- Weiwei Shi
- Dept. of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité - University Medicine Berlin, Berlin, Germany
| | - Jiahui Song
- Dept. of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité - University Medicine Berlin, Berlin, Germany
| | - January Mikolaj Weiner
- Dept. of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité - University Medicine Berlin, Berlin, Germany
| | - Avneesh Chopra
- Dept. of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité - University Medicine Berlin, Berlin, Germany
| | - Henrik Dommisch
- Dept. of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité - University Medicine Berlin, Berlin, Germany
| | - Dieter Beule
- Core Unit Bioinformatics, Berlin Institute of Health at Charité, Berlin, Germany
| | - Arne S Schaefer
- Dept. of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité - University Medicine Berlin, Berlin, Germany.
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10
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Petrazzini BO, Forrest IS, Rocheleau G, Vy HMT, Márquez-Luna C, Duffy Á, Chen R, Park JK, Gibson K, Goonewardena SN, Malick WA, Rosenson RS, Jordan DM, Do R. Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease. Nat Genet 2024; 56:1412-1419. [PMID: 38862854 DOI: 10.1038/s41588-024-01791-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 05/08/2024] [Indexed: 06/13/2024]
Abstract
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disease progression, severity and underdiagnosis on this spectrum and could enhance genetic discovery efforts for CAD. Here we tested associations of rare and ultrarare coding variants with the in silico score for CAD in the UK Biobank, All of Us Research Program and BioMe Biobank. We identified associations in 17 genes; of these, 14 show at least moderate levels of prior genetic, biological and/or clinical support for CAD. We also observed an excess of ultrarare coding variants in 321 aggregated CAD genes, suggesting more ultrarare variant associations await discovery. These results expand our understanding of the genetic etiology of CAD and illustrate how digital markers can enhance genetic association investigations for complex diseases.
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Affiliation(s)
- Ben Omega Petrazzini
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Iain S Forrest
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ghislain Rocheleau
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ha My T Vy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carla Márquez-Luna
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Áine Duffy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Chen
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joshua K Park
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kyle Gibson
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sascha N Goonewardena
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Division of Cardiovascular Medicine, VA Ann Arbor Health System, Ann Arbor, MI, USA
| | - Waqas A Malick
- Metabolism and Lipids Program, Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert S Rosenson
- Metabolism and Lipids Program, Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel M Jordan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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11
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Pan H, Ho SE, Xue C, Cui J, Johanson QS, Sachs N, Ross LS, Li F, Solomon RA, Connolly ES, Patel VI, Maegdefessel L, Zhang H, Reilly MP. Atherosclerosis Is a Smooth Muscle Cell-Driven Tumor-Like Disease. Circulation 2024; 149:1885-1898. [PMID: 38686559 PMCID: PMC11164647 DOI: 10.1161/circulationaha.123.067587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/25/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Atherosclerosis, a leading cause of cardiovascular disease, involves the pathological activation of various cell types, including immunocytes (eg, macrophages and T cells), smooth muscle cells (SMCs), and endothelial cells. Accumulating evidence suggests that transition of SMCs to other cell types, known as phenotypic switching, plays a central role in atherosclerosis development and complications. However, the characteristics of SMC-derived cells and the underlying mechanisms of SMC transition in disease pathogenesis remain poorly understood. Our objective is to characterize tumor cell-like behaviors of SMC-derived cells in atherosclerosis, with the ultimate goal of developing interventions targeting SMC transition for the prevention and treatment of atherosclerosis. METHODS We used SMC lineage tracing mice and human tissues and applied a range of methods, including molecular, cellular, histological, computational, human genetics, and pharmacological approaches, to investigate the features of SMC-derived cells in atherosclerosis. RESULTS SMC-derived cells in mouse and human atherosclerosis exhibit multiple tumor cell-like characteristics, including genomic instability, evasion of senescence, hyperproliferation, resistance to cell death, invasiveness, and activation of comprehensive cancer-associated gene regulatory networks. Specific expression of the oncogenic mutant KrasG12D in SMCs accelerates phenotypic switching and exacerbates atherosclerosis. Furthermore, we provide proof of concept that niraparib, an anticancer drug targeting DNA damage repair, attenuates atherosclerosis progression and induces regression of lesions in advanced disease in mouse models. CONCLUSIONS Our findings demonstrate that atherosclerosis is an SMC-driven tumor-like disease, advancing our understanding of its pathogenesis and opening prospects for innovative precision molecular strategies aimed at preventing and treating atherosclerotic cardiovascular disease.
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Affiliation(s)
- Huize Pan
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sebastian E. Ho
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- These authors contributed equally
| | - Chenyi Xue
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- These authors contributed equally
| | - Jian Cui
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Quinian S. Johanson
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Nadja Sachs
- Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University Munich, 81675 Munich, Germany
- German Center for Cardiovascular Research, partner site: Munich Heart Alliance, 10785 Berlin, Germany
| | - Leila S. Ross
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Fang Li
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Robert A. Solomon
- Department of Neurologic Surgery, New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY 10032, USA
| | - E. Sander Connolly
- Department of Neurologic Surgery, New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Virendra I. Patel
- Section of Vascular Surgery and Endovascular Interventions, New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Lars Maegdefessel
- Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University Munich, 81675 Munich, Germany
- German Center for Cardiovascular Research, partner site: Munich Heart Alliance, 10785 Berlin, Germany
- Department of Medicine, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Hanrui Zhang
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Muredach P. Reilly
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, NY 10032, USA
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12
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Cignarella A, Bolego C, Barton M. Sex and sex steroids as determinants of cardiovascular risk. Steroids 2024; 206:109423. [PMID: 38631602 DOI: 10.1016/j.steroids.2024.109423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/08/2024] [Accepted: 04/14/2024] [Indexed: 04/19/2024]
Abstract
There are considerable sex differences regarding the risk of cardiovascular disease (CVD), including arterial hypertension, coronary artery disease (CAD) and stroke, as well as chronic renal disease. Women are largely protected from these conditions prior to menopause, and the risk increases following cessation of endogenous estrogen production or after surgical menopause. Cardiovascular diseases in women generally begin to occur at a later age than in men (on average with a delay of 10 years). Cessation of estrogen production also impacts metabolism, increasing the risk of developing obesity and diabetes. In middle-aged individuals, hypertension develops earlier and faster in women than in men, and smoking increases cardiovascular risk to a greater degree in women than it does in men. It is not only estrogen that affects female cardiovascular health and plays a protective role until menopause: other sex hormones such as progesterone and androgen hormones generate a complex balance that differentiates heart and blood vessel function in women compared to men. Estrogens improve vasodilation of epicardial coronary arteries and the coronary microvasculature by augmenting the release of vasodilating factors such as nitric oxide and prostacyclin, which are mechanisms of coronary vasodilatation that are more pronounced in women compared to men. Estrogens are also powerful inhibitors of inflammation, which in part explains their protective effects on CVD and chronic renal disease. Emerging evidence suggests that sex chromosomes also play a significant role in shaping cardiovascular risk. The cardiovascular protection conferred by endogenous estrogens may be extended by hormone therapy, especially using bioidentical hormones and starting treatment early after menopause.
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Affiliation(s)
| | - Chiara Bolego
- Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy
| | - Matthias Barton
- Molecular Internal Medicine, University of Zürich, Zürich, Switzerland; Andreas Grüntzig Foundation, Zürich, Switzerland.
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13
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Henry J, Lin Y, Bouatia-Naji N. Enhancing the Prediction Power of Polygenic Risk Scores in Genetically Diverse Coronary Heart Disease. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004610. [PMID: 38586952 DOI: 10.1161/circgen.124.004610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Affiliation(s)
- Joséphine Henry
- Université Paris Cité, Paris-Cardiovascular Research Center, Institut National de la Sante et de la Recherche Medicale, France
| | - Yilong Lin
- Université Paris Cité, Paris-Cardiovascular Research Center, Institut National de la Sante et de la Recherche Medicale, France
| | - Nabila Bouatia-Naji
- Université Paris Cité, Paris-Cardiovascular Research Center, Institut National de la Sante et de la Recherche Medicale, France
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14
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Selvarajan I, Kiema M, Huang RT, Li J, Zhu J, Pölönen P, Örd T, Õunap K, Godiwala M, Golebiewski AK, Ravindran A, Mäklin K, Toropainen A, Stolze LK, Arce M, Magnusson PU, White S, Romanoski CE, Heinäniemi M, Laakkonen JP, Fang Y, Kaikkonen MU. Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro. Arterioscler Thromb Vasc Biol 2024; 44:1330-1345. [PMID: 38602103 PMCID: PMC11111333 DOI: 10.1161/atvbaha.123.318964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 03/25/2024] [Indexed: 04/12/2024]
Abstract
BACKGROUND CALCRL (calcitonin receptor-like) protein is an important mediator of the endothelial fluid shear stress response, which is associated with the genetic risk of coronary artery disease. In this study, we functionally characterized the noncoding regulatory elements carrying coronary artery disease that risks single-nucleotide polymorphisms and studied their role in the regulation of CALCRL expression in endothelial cells. METHODS To functionally characterize the coronary artery disease single-nucleotide polymorphisms harbored around the gene CALCRL, we applied an integrative approach encompassing statistical, transcriptional (RNA-seq), and epigenetic (ATAC-seq [transposase-accessible chromatin with sequencing], chromatin immunoprecipitation assay-quantitative polymerase chain reaction, and electromobility shift assay) analyses, alongside luciferase reporter assays, and targeted gene and enhancer perturbations (siRNA and clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) in human aortic endothelial cells. RESULTS We demonstrate that the regulatory element harboring rs880890 exhibits high enhancer activity and shows significant allelic bias. The A allele was favored over the G allele, particularly under shear stress conditions, mediated through alterations in the HSF1 (heat shock factor 1) motif and binding. CRISPR deletion of rs880890 enhancer resulted in downregulation of CALCRL expression, whereas HSF1 knockdown resulted in a significant decrease in rs880890-enhancer activity and CALCRL expression. A significant decrease in HSF1 binding to the enhancer region in endothelial cells was observed under disturbed flow compared with unidirectional flow. CALCRL knockdown and variant perturbation experiments indicated the role of CALCRL in mediating eNOS (endothelial nitric oxide synthase), APLN (apelin), angiopoietin, prostaglandins, and EDN1 (endothelin-1) signaling pathways leading to a decrease in cell proliferation, tube formation, and NO production. CONCLUSIONS Overall, our results demonstrate the existence of an endothelial-specific HSF (heat shock factor)-regulated transcriptional enhancer that mediates CALCRL expression. A better understanding of CALCRL gene regulation and the role of single-nucleotide polymorphisms in the modulation of CALCRL expression could provide important steps toward understanding the genetic regulation of shear stress signaling responses.
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Affiliation(s)
- Ilakya Selvarajan
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Miika Kiema
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Ru-Ting Huang
- Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Jin Li
- Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Jiayu Zhu
- Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Petri Pölönen
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, P.O. Box 1627, FIN-70211, Kuopio, Finland
| | - Tiit Örd
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Kadri Õunap
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Mehvash Godiwala
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Anna Kathryn Golebiewski
- Department of Cellular and Molecular Medicine, The College of Medicine, The University of Arizona; Tucson, AZ 85721, USA
| | - Aarthi Ravindran
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Kiira Mäklin
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Anu Toropainen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Lindsey K. Stolze
- Department of Cellular and Molecular Medicine, The College of Medicine, The University of Arizona; Tucson, AZ 85721, USA
| | - Maximiliano Arce
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Peetra U. Magnusson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Stephen White
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle NE1 3BZ, UK
| | - Casey E. Romanoski
- Department of Cellular and Molecular Medicine, The College of Medicine, The University of Arizona; Tucson, AZ 85721, USA
| | - Merja Heinäniemi
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, P.O. Box 1627, FIN-70211, Kuopio, Finland
| | - Johanna P. Laakkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
| | - Yun Fang
- Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Minna U Kaikkonen
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
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15
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Shah PW, Reinberger T, Hashmi S, Aherrahrou Z, Erdmann J. MRAS in coronary artery disease-Unchartered territory. IUBMB Life 2024; 76:300-312. [PMID: 38251784 DOI: 10.1002/iub.2805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 12/03/2023] [Indexed: 01/23/2024]
Abstract
Genome-wide association studies (GWAS) have identified coronary artery disease (CAD) susceptibility locus on chromosome 3q22.3. This locus contains a cluster of several genes that includes muscle rat sarcoma virus (MRAS). Common MRAS variants are also associated with CAD causing risk factors such as hypertension, dyslipidemia, obesity, and type II diabetes. The MRAS gene is an oncogene that encodes a membrane-bound small GTPase. It is involved in a variety of signaling pathways, regulating cell differentiation and cell survival (mitogen-activated protein kinase [MAPK]/extracellular signal-regulated kinase and phosphatidylinositol 3-kinase) as well as acute phase response signaling (tumor necrosis factor [TNF] and interleukin 6 [IL6] signaling). In this review, we will summarize the role of genetic MRAS variants in the etiology of CAD and its comorbidities with the focus on tissue distribution of MRAS isoforms, cell type/tissue specificity, and mode of action of single nucleotide variants in MRAS associated complex traits. Finally, we postulate that CAD risk variants in the MRAS locus are specific to smooth muscle cells and lead to higher levels of MRAS, particularly in arterial and cardiac tissue, resulting in MAPK-dependent tissue hypertrophy or hyperplasia.
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Affiliation(s)
- Pashmina Wiqar Shah
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Tobias Reinberger
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Satwat Hashmi
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Zouhair Aherrahrou
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
- DZHK (German Research Centre for Cardiovascular Research), Lübeck, Germany
- University Heart Center Lübeck, Lübeck, Germany
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16
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Smith JL, Tcheandjieu C, Dikilitas O, Iyer K, Miyazawa K, Hilliard A, Lynch J, Rotter JI, Chen YDI, Sheu WHH, Chang KM, Kanoni S, Tsao PS, Ito K, Kosel M, Clarke SL, Schaid DJ, Assimes TL, Kullo IJ. Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004272. [PMID: 38380516 DOI: 10.1161/circgen.123.004272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 01/23/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRSCHD) for 5 genetic ancestry groups. METHODS We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSPT) and ancestry-based continuous shrinkage priors (PRSCSx) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRSCHD in 176,988 individuals across 9 diverse cohorts. RESULTS Multi-ancestry PRSPT and PRSCSx outperformed ancestry-specific PRSPT and PRSCSx across a range of tuning values. Two best-performing multi-ancestry PRSCHD (ie, PRSPTmult and PRSCSxmult) and 1 ancestry-specific (PRSCSxEUR) were taken forward for validation. PRSPTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41-3.14], 1.65 [1.59-1.72]), followed by East Asian ancestry (1.56 [1.50-1.61]), Hispanic/Latino ancestry (1.38 [1.24-1.54]), and African ancestry (1.16 [1.11-1.21]). PRSCSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38-3.00]) and European ancestry (1.65 [1.59-1.71]), lower in East Asian ancestry (1.59 [1.54-1.64]), Hispanic/Latino ancestry (1.51 [1.35-1.69]), and the lowest in African ancestry (1.20 [1.15-1.26]). CONCLUSIONS The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRSCHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRSCHD.
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Affiliation(s)
- Johanna L Smith
- Department of Cardiovascular Medicine (J.L.S., O.D., I.J.K.), Mayo Clinic, Rochester, MN
| | - Catherine Tcheandjieu
- Department of Epidemiology and Biostatistics, University of California San Francisco (C.T.)
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institute, San Francisco, CA (C.T.)
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine (J.L.S., O.D., I.J.K.), Mayo Clinic, Rochester, MN
| | - Kruthika Iyer
- Stanford University School of Medicine, Palo Alto, CA (K. Iyer, A.H.)
| | - Kazuo Miyazawa
- Riken Center for Integrative Medical Sciences, Yokohama City, Japan (K.M., K. Ito)
| | - Austin Hilliard
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
- Stanford University School of Medicine, Palo Alto, CA (K. Iyer, A.H.)
| | | | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA (J.I.R., Y.-D.I.C.)
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA (J.I.R., Y.-D.I.C.)
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute (W.H.-H.S.)
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taipei Veterans General Hospital (W.H.-H.S.)
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taiwan (W.H.-H.S.)
| | - Kyong-Mi Chang
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA (K.-M.C.)
| | - Stavroula Kanoni
- Queen Mary University of London, Cambridge, United Kingdom (S.K.)
| | - Philip S Tsao
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
- Stanford University, Stanford, CA (P.S.T., S.L.C., T.L.A.)
| | - Kaoru Ito
- Riken Center for Integrative Medical Sciences, Yokohama City, Japan (K.M., K. Ito)
| | - Matthew Kosel
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN (M.K., D.J.S.)
| | - Shoa L Clarke
- VA Palo Alto Health Care System (C.T., A.H., P.S.T., S.L.C.)
- Stanford University, Stanford, CA (P.S.T., S.L.C., T.L.A.)
| | - Daniel J Schaid
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN (M.K., D.J.S.)
| | | | - Iftikhar J Kullo
- Department of Cardiovascular Medicine (J.L.S., O.D., I.J.K.), Mayo Clinic, Rochester, MN
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17
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Ranjan R, Hasan MK, Adhikary AB. Bangladeshi Atherosclerosis Biobank and Hub: The BANGABANDHU Study. Int J Gen Med 2024; 17:2507-2512. [PMID: 38826511 PMCID: PMC11144007 DOI: 10.2147/ijgm.s466706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 05/24/2024] [Indexed: 06/04/2024] Open
Abstract
Background Genetic factors contribute significantly to the risk of ischaemic heart disease (IHD), which is the leading cause of mortality in Bangladesh. The BANGABANDHU (Bangladeshi Atherosclerosis Biobank AND Hub) study will allow a hypothesis-free genome-wide association study (GWAS) to identify genetic risk factors associated with ischaemic heart disease patients undergoing coronary artery bypass graft (CABG) surgery in Bangladesh. Methods This is a multi-centre population-based case-control study aimed to evaluate 1500 (Fifteen Hundred) adult (≥18 years of age) people divided into 2 study groups: Case/Proband (750 IHD patients undergoing CABG surgery) and Control (750 healthy people). Spouses or family members are preferred as healthy control subjects due to their shared geographic location and similar environmental exposure. Results This will be the first largest DNA repository of CABG patients in Bangladesh, and identifying novel gene loci among CABG patients might help to discover novel therapeutic targets for Bangladeshi IHD patients. Further, identifying and comparing novel gene loci among CABG patients with other ancestry might help devise national guidelines for treating coronary artery disease. Conclusion Promising current study results will encourage Bangladeshi researchers and pharmaceutical companies to conduct further studies into the genetic basis of Bangladeshi complex coronary artery disease, which might identify novel genes for therapeutic targets for Bangladeshi patients and strengthen the healthcare standards in Bangladesh.
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Affiliation(s)
- Redoy Ranjan
- Department of Cardiac Surgery, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh
| | - Md Kamrul Hasan
- Department of Cardiac Surgery, National Institute of Cardiovascular Diseases, Dhaka, Bangladesh
| | - Asit Baran Adhikary
- Department of Cardiac Surgery, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh
- Department of Cardiac Surgery, Impulse Hospital & Research Centre, Dhaka, Bangladesh
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18
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Alireza Z, Maleeha M, Kaikkonen M, Fortino V. Enhancing prediction accuracy of coronary artery disease through machine learning-driven genomic variant selection. J Transl Med 2024; 22:356. [PMID: 38627847 PMCID: PMC11020205 DOI: 10.1186/s12967-024-05090-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/14/2024] [Indexed: 04/19/2024] Open
Abstract
Machine learning (ML) methods are increasingly becoming crucial in genome-wide association studies for identifying key genetic variants or SNPs that statistical methods might overlook. Statistical methods predominantly identify SNPs with notable effect sizes by conducting association tests on individual genetic variants, one at a time, to determine their relationship with the target phenotype. These genetic variants are then used to create polygenic risk scores (PRSs), estimating an individual's genetic risk for complex diseases like cancer or cardiovascular disorders. Unlike traditional methods, ML algorithms can identify groups of low-risk genetic variants that improve prediction accuracy when combined in a mathematical model. However, the application of ML strategies requires addressing the feature selection challenge to prevent overfitting. Moreover, ensuring the ML model depends on a concise set of genomic variants enhances its clinical applicability, where testing is feasible for only a limited number of SNPs. In this study, we introduce a robust pipeline that applies ML algorithms in combination with feature selection (ML-FS algorithms), aimed at identifying the most significant genomic variants associated with the coronary artery disease (CAD) phenotype. The proposed computational approach was tested on individuals from the UK Biobank, differentiating between CAD and non-CAD individuals within this extensive cohort, and benchmarked against standard PRS-based methodologies like LDpred2 and Lassosum. Our strategy incorporates cross-validation to ensure a more robust evaluation of genomic variant-based prediction models. This method is commonly applied in machine learning strategies but has often been neglected in previous studies assessing the predictive performance of polygenic risk scores. Our results demonstrate that the ML-FS algorithm can identify panels with as few as 50 genetic markers that can achieve approximately 80% accuracy when used in combination with known risk factors. The modest increase in accuracy over PRS performances is noteworthy, especially considering that PRS models incorporate a substantially larger number of genetic variants. This extensive variant selection can pose practical challenges in clinical settings. Additionally, the proposed approach revealed novel CAD-genetic variant associations.
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Affiliation(s)
- Z Alireza
- Institute of Biomedicine, University of Eastern Finland, 70210, Kuopio, Finland
| | - M Maleeha
- Institute of Biomedicine, University of Eastern Finland, 70210, Kuopio, Finland
| | - M Kaikkonen
- A.I.Virtanen Institute, University of Eastern Finland, 70210, Kuopio, Finland
| | - V Fortino
- Institute of Biomedicine, University of Eastern Finland, 70210, Kuopio, Finland.
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19
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Adelus ML, Ding J, Tran BT, Conklin AC, Golebiewski AK, Stolze LK, Whalen MB, Cusanovich DA, Romanoski CE. Single-cell 'omic profiles of human aortic endothelial cells in vitro and human atherosclerotic lesions ex vivo reveal heterogeneity of endothelial subtype and response to activating perturbations. eLife 2024; 12:RP91729. [PMID: 38578680 PMCID: PMC10997331 DOI: 10.7554/elife.91729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2024] Open
Abstract
Heterogeneity in endothelial cell (EC) sub-phenotypes is becoming increasingly appreciated in atherosclerosis progression. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs) exposed to activating environments characteristic of the atherosclerotic microenvironment in vitro. Meta-analysis of single-cell transcriptomes across 17 human ex vivo arterial specimens was performed and two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and ex vivo cell profiles. HAEC cultures were reproducibly populated by four major clusters with distinct pathway enrichment profiles and modest heterogeneous responses: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Quantitative comparisons between in vitro and ex vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated single-nucleotide polymorphisms from Genome Wide Association Studies (GWAS), suggesting that these cell phenotypes harbor CAD-modulating mechanisms. Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and ex vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.
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Affiliation(s)
- Maria L Adelus
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
- The Clinical Translational Sciences Graduate Program, The University of ArizonaTucsonUnited States
| | - Jiacheng Ding
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
| | - Binh T Tran
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
| | - Austin C Conklin
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
| | - Anna K Golebiewski
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
| | - Lindsey K Stolze
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
| | - Michael B Whalen
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
| | - Darren A Cusanovich
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
- Asthma and Airway Disease Research Center, The University of ArizonaTucsonUnited States
| | - Casey E Romanoski
- The Department of Cellular and Molecular Medicine, The University of ArizonaTucsonUnited States
- The Clinical Translational Sciences Graduate Program, The University of ArizonaTucsonUnited States
- Asthma and Airway Disease Research Center, The University of ArizonaTucsonUnited States
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20
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Brennan PG, Mota L, Aridi T, Patel N, Liang P, Ferran C. Advancements in Omics and Breakthrough Gene Therapies: A Glimpse into the Future of Peripheral Artery Disease. Ann Vasc Surg 2024:S0890-5096(24)00156-0. [PMID: 38582204 DOI: 10.1016/j.avsg.2024.01.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 01/01/2024] [Indexed: 04/08/2024]
Abstract
Peripheral artery disease (PAD), a highly prevalent global disease, associates with significant morbidity and mortality in affected patients. Despite progress in endovascular and open revascularization techniques for advanced PAD, these interventions grapple with elevated rates of arterial restenosis and vein graft failure attributed to intimal hyperplasia (IH). Novel multiomics technologies, coupled with sophisticated analyses tools recently powered by advances in artificial intelligence, have enabled the study of atherosclerosis and IH with unprecedented single-cell and spatial precision. Numerous studies have pinpointed gene hubs regulating pivotal atherogenic and atheroprotective signaling pathways as potential therapeutic candidates. Leveraging advancements in viral and nonviral gene therapy (GT) platforms, gene editing technologies, and cutting-edge biomaterial reservoirs for delivery uniquely positions us to develop safe, efficient, and targeted GTs for PAD-related diseases. Gene therapies appear particularly fitting for ex vivo genetic engineering of IH-resistant vein grafts. This manuscript highlights currently available state-of-the-art multiomics approaches, explores promising GT-based candidates, and details GT delivery modalities employed by our laboratory and others to thwart mid-term vein graft failure caused by IH, as well as other PAD-related conditions. The potential clinical translation of these targeted GTs holds the promise to revolutionize PAD treatment, thereby enhancing patients' quality of life and life expectancy.
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Affiliation(s)
- Phillip G Brennan
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Lucas Mota
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Tarek Aridi
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Nyah Patel
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Patric Liang
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Christiane Ferran
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Division of Nephrology and the Transplant Institute, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
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21
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Muse ED, Topol EJ. Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management. Cell Metab 2024; 36:670-683. [PMID: 38428435 PMCID: PMC10990799 DOI: 10.1016/j.cmet.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/25/2024] [Accepted: 02/06/2024] [Indexed: 03/03/2024]
Abstract
The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpretation of diagnostic studies such as chest X-rays and electrocardiograms in addition to predicting patient outcomes and future disease onset. However, AI has evolved with the introduction of transformer models, allowing analysis of the diverse, multimodal data sources existing in medicine today. Multimodal AI holds great promise in more accurate disease risk assessment and stratification as well as optimizing the key driving factors in cardiometabolic disease: blood pressure, sleep, stress, glucose control, weight, nutrition, and physical activity. In this article we outline the current state of medical AI in cardiometabolic disease, highlighting the potential of multimodal AI to augment personalized prevention and treatment strategies in cardiometabolic disease.
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Affiliation(s)
- Evan D Muse
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA 92037, USA; Division of Cardiovascular Diseases, Scripps Clinic, La Jolla, CA 92037, USA
| | - Eric J Topol
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA 92037, USA; Division of Cardiovascular Diseases, Scripps Clinic, La Jolla, CA 92037, USA.
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22
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Ben Dhaou C, Scott ML, Orr AW. Advances in Understanding Cardiovascular Disease Pathogenesis through Next-Generation Technologies. THE AMERICAN JOURNAL OF PATHOLOGY 2024; 194:476-481. [PMID: 38519246 PMCID: PMC10988757 DOI: 10.1016/j.ajpath.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 01/19/2024] [Accepted: 01/23/2024] [Indexed: 03/24/2024]
Affiliation(s)
- Cyrine Ben Dhaou
- Department of Pathology and Translational Pathobiology, LSU Health Shreveport, Shreveport, Louisiana
| | - Matthew L Scott
- Department of Pathology and Translational Pathobiology, LSU Health Shreveport, Shreveport, Louisiana
| | - A Wayne Orr
- Department of Pathology and Translational Pathobiology, LSU Health Shreveport, Shreveport, Louisiana; Department of Molecular and Cellular Physiology, LSU Health Shreveport, Shreveport, Louisiana; Department of Cell Biology and Anatomy, LSU Health Shreveport, Shreveport, Louisiana.
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23
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Pepin ME, Gupta RM. The Role of Endothelial Cells in Atherosclerosis: Insights from Genetic Association Studies. THE AMERICAN JOURNAL OF PATHOLOGY 2024; 194:499-509. [PMID: 37827214 PMCID: PMC10988759 DOI: 10.1016/j.ajpath.2023.09.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/21/2023] [Accepted: 09/01/2023] [Indexed: 10/14/2023]
Abstract
Endothelial cells (ECs) mediate several biological functions that are relevant to atherosclerosis and coronary artery disease (CAD), regulating an array of vital processes including vascular tone, wound healing, reactive oxygen species, shear stress response, and inflammation. Although which of these functions is linked causally with CAD development and/or progression is not yet known, genome-wide association studies have implicated more than 400 loci associated with CAD risk, among which several have shown EC-relevant functions. Given the arduous process of mechanistically interrogating single loci to CAD, high-throughput variant characterization methods, including pooled Clustered Regularly Interspaced Short Palindromic Repeats screens, offer exciting potential to rapidly accelerate the discovery of bona fide EC-relevant genetic loci. These discoveries in turn will broaden the therapeutic avenues for CAD beyond lipid lowering and behavioral risk modification to include EC-centric modalities of risk prevention and treatment.
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Affiliation(s)
- Mark E Pepin
- Cardiovascular Disease Initiative, The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts; Divisions of Genetics and Cardiovascular Medicine, Brigham & Women's Hospital, Boston, Massachusetts
| | - Rajat M Gupta
- Cardiovascular Disease Initiative, The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts; Divisions of Genetics and Cardiovascular Medicine, Brigham & Women's Hospital, Boston, Massachusetts.
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24
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Ahmed IA, Liu M, Gomez D. Nuclear Control of Vascular Smooth Muscle Cell Plasticity during Vascular Remodeling. THE AMERICAN JOURNAL OF PATHOLOGY 2024; 194:525-538. [PMID: 37820925 PMCID: PMC10988766 DOI: 10.1016/j.ajpath.2023.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 09/18/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023]
Abstract
Control of vascular smooth muscle cell (SMC) gene expression is an essential process for establishing and maintaining lineage identity, contractility, and plasticity. Most mechanisms (epigenetic, transcriptional, and post-transcriptional) implicated in gene regulation occur in the nucleus. Still, intranuclear pathways are directly impacted by modifications in the extracellular environment in conditions of adaptive or maladaptive remodeling. Integration of extracellular, cellular, and genomic information into the nucleus through epigenetic and transcriptional control of genome organization plays a major role in regulating SMC functions and phenotypic transitions during vascular remodeling and diseases. This review aims to provide a comprehensive update on nuclear mechanisms, their interactions, and their integration in controlling SMC homeostasis and dysfunction. It summarizes and discusses the main nuclear mechanisms preponderant in SMCs in the context of vascular disease, such as atherosclerosis, with an emphasis on studies employing in vivo cell-specific loss-of-function and single-cell omics approaches.
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Affiliation(s)
- Ibrahim A Ahmed
- Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania; Division of Cardiology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Mingjun Liu
- Department of Pathology, New York University, New York, New York
| | - Delphine Gomez
- Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, Pennsylvania; Division of Cardiology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
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25
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Wu X, Zhang H. Omics Approaches Unveiling the Biology of Human Atherosclerotic Plaques. THE AMERICAN JOURNAL OF PATHOLOGY 2024; 194:482-498. [PMID: 38280419 PMCID: PMC10988765 DOI: 10.1016/j.ajpath.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 12/16/2023] [Accepted: 12/20/2023] [Indexed: 01/29/2024]
Abstract
Atherosclerosis is a chronic inflammatory disease of the arterial wall, characterized by the buildup of plaques with the accumulation and transformation of lipids, immune cells, vascular smooth muscle cells, and necrotic cell debris. Plaques with collagen-poor thin fibrous caps infiltrated by macrophages and lymphocytes are considered unstable because they are at the greatest risk of rupture and clinical events. However, the current histologic definition of plaque types may not fully capture the complex molecular nature of atherosclerotic plaque biology and the underlying mechanisms contributing to plaque progression, rupture, and erosion. The advances in omics technologies have changed the understanding of atherosclerosis plaque biology, offering new possibilities to improve risk prediction and discover novel therapeutic targets. Genomic studies have shed light on the genetic predisposition to atherosclerosis, and integrative genomic analyses expedite the translation of genomic discoveries. Transcriptomic, proteomic, metabolomic, and lipidomic studies have refined the understanding of the molecular signature of atherosclerotic plaques, aiding in data-driven hypothesis generation for mechanistic studies and offering new prospects for biomarker discovery. Furthermore, advancements in single-cell technologies and emerging spatial analysis techniques have unveiled the heterogeneity and plasticity of plaque cells. This review discusses key omics-based discoveries that have advanced the understanding of human atherosclerotic plaque biology, focusing on insights derived from omics profiling of human atherosclerotic vascular specimens.
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Affiliation(s)
- Xun Wu
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Hanrui Zhang
- Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, New York.
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26
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Delgado JL, Warren RC. To advance science we need to address 'otherness'. Nat Hum Behav 2024; 8:622-624. [PMID: 38308090 DOI: 10.1038/s41562-024-01821-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2024]
Affiliation(s)
- Jane L Delgado
- National Alliance for Hispanic Health, Washington, DC, USA.
- Healthy Americas Foundation, Washington, DC, USA.
| | - Rueben C Warren
- National Center for Bioethics in Research and Health Care, Tuskegee University, Tuskegee, AL, USA
- School of Dentistry, Meharry Medical College, Nashville, TN, USA
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27
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Zhao K, Shen X, Liu H, Lin Z, Li J, Chen S, Liu F, Huang K, Cao J, Liu X, Shen C, Yu L, Zhao Y, Zhao L, Li Y, Hu D, Huang J, Lu X, Gu D. Somatic and Germline Variants and Coronary Heart Disease in a Chinese Population. JAMA Cardiol 2024; 9:233-242. [PMID: 38198131 PMCID: PMC10782380 DOI: 10.1001/jamacardio.2023.5095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/03/2023] [Indexed: 01/11/2024]
Abstract
Importance The genetic basis of coronary heart disease (CHD) has expanded from a germline to somatic genome, including clonal hematopoiesis of indeterminate potential (CHIP). How CHIP confers CHD risk in East Asian individuals, especially those with small clones (variant allele fraction [VAF] 0.5%-2%) and different genetic backgrounds, was completely unknown. Objective To investigate the CHIP profile in a general Chinese cohort by deep sequencing and further explore the association between CHIP and incident CHD considering germline predisposition. Design, Setting, and Participants This cohort study used data from 3 prospective cohorts in the project Prediction for Atherosclerotic Cardiovascular Disease Risk in China. Participants without cardiovascular disease or cancer at baseline were enrolled in 2001 and 2008 and had a median follow-up of 12.17 years extending into 2021. Exposures CHIP mutations were detected by targeted sequencing (mean depth, 916×). A predefined CHD polygenic risk score (PRS) comprising 531 variants was used to evaluate germline predisposition. Main Outcomes and Measures The main outcome was first incident CHD. Results Among 6181 participants, the median (IQR) age was 53.83 years (45.35-62.39 years); 3082 participants (49.9%) were female, and 3099 (50.1%) were male. A total of 1100 individuals (17.80%) harbored 1372 CHIP mutations at baseline. CHIP was independently associated with incident CHD (hazard ratio [HR], 1.42; 95% CI, 1.18-1.72; P = 2.82 × 10-4) and presented a risk gradient with increasing VAF (P = 3.98 × 10-3 for trend). Notably, individuals with small clones, nearly half of CHIP carriers, also demonstrated a higher CHD risk compared with non-CHIP carriers (HR, 1.33; 95% CI, 1.02-1.74; P = .03) and were 4 years younger than those with VAF of 2% or greater (median age, 58.52 vs 62.70 years). Heightened CHD risk was not observed among CHIP carriers with low PRS (HR, 1.02; 95% CI, 0.64-1.64; P = .92), while high PRS and CHIP jointly contributed a 2.23-fold increase in risk (95% CI, 1.51-3.29; P = 6.29 × 10-5) compared with non-CHIP carriers with low PRS. Interestingly, the diversity in CHIP-related CHD risk within each PRS group was substantially diminished when removing variants in the inflammatory pathway from the PRS. Conclusions This study revealed that elevated CHD risk attributed to CHIP was nonnegligible even for small clones. Inflammation genes involved in CHD could aggravate or abrogate CHIP-related CHD risk.
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Affiliation(s)
- Kun Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuxiang Shen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongwei Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhennan Lin
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Keyong Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People’s Hospital and Cardiovascular Institute, Guangzhou, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, China
| | - Yingxin Zhao
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Liancheng Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, China
| | - Jiangfeng Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- School of Public Health and Emergency Management, School of Medicine, Southern University of Science and Technology, Shenzhen, China
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Gaber MA, Omar OHM, Meki ARMA, Nassar AY, Hassan AKM, Mahmoud MS. The significance of PCSK-9's level and polymorphism in premature coronary artery disease: Relation to risk and severity. Clin Biochem 2024; 125:110729. [PMID: 38342398 DOI: 10.1016/j.clinbiochem.2024.110729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/03/2024] [Accepted: 02/06/2024] [Indexed: 02/13/2024]
Abstract
BACKGROUND Proprotein convertase subtilisin/kexin type 9 (PCSK-9) is a circulating protein that plays an important role in lipid metabolism and is linked to inflammation, which has implications for atherosclerosis and its severe cardiac effects. We studied the potential association of the PCSK-9 gene single nucleotide polymorphism (SNP), Oxidized low-density lipoprotein receptor 1- (OLR-1), and caspase-3 serum levels with the risk and severity of premature coronary artery disease (PCAD). The potential contribution of PCSK-9 serum level to the severity of PCAD patients was also assessed. METHOD This case-control study included 120 PCAD patients (age < 45), and 60 age matched healthy controls. Serum PCSK-9 and caspase-3 levels and clinical characteristics were recorded. SYNTAX score was calculated to estimate the severity of the coronary artery lesions. The SNP rs2483205 of the PCSK-9 gene and the rs11053646 of the OLR-1gene were genotyped in all participants. RESULTS Serum PCSK-9 levels were higher in PCAD patients and were significantly different among the three SYNTAX score groups (SS ≤ 12, 12 < SS ≤ 21.5, and SS > 21.5). The diagnostic cutoff values of PCSK-9 and caspase-3 levels for PCAD were > 3.2 ng/mL for both, yielding an area under the curve (AUC) of 0.98 and 0.92, sensitivity of 85 %, 98 %, and specificity of 99.5 %, 93 % for PCSK-9 and caspase-3, respectively. The genotypes TT + CT vs. CC of PCSK-9's rs2483205 SNP presented a higher risk for PCAD and higher SYNTAX scores. Furthermore, the rs11053646 SNP of OLR-1 presented the CG genotype as more risky and having higher SYNTAX scores. CONCLUSION Circulating PCSK9 and caspase-3 concentrations were higher in PCAD patients and were associated with CAD severity. The SNPs of PCSK-9 (rs2483205) and OLR-1 (rs11053646) were associated with PCAD and its severity.
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Affiliation(s)
- Marwa A Gaber
- Medical Biochemistry Department, Faculty of Medicine, Assiut University, Assiut, Egypt.
| | - Omnia H M Omar
- Assiut International Center of Nanomedicine, Al-rajhy Liver Hospital, Assiut University, Assiut, Egypt
| | - Abdel-Raheim M A Meki
- Medical Biochemistry Department, Faculty of Medicine, Assiut University, Assiut, Egypt; Biochemistry Department, Faculty of Pharmacy, Sphinx University, New Assiut, Egypt
| | - Ahmed Y Nassar
- Medical Biochemistry Department, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Ayman K M Hassan
- Cardiology Department, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Marwan S Mahmoud
- Cardiology Department, Faculty of Medicine, Assiut University, Assiut, Egypt
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Abirami S, Adole PS, Vinod KV. Association of Tenascin-C Gene Polymorphisms with Risk of Acute Coronary Syndrome in South Indian Population: A Case-Control Genetic Association Study. Genet Test Mol Biomarkers 2024; 28:114-122. [PMID: 38471098 PMCID: PMC10979666 DOI: 10.1089/gtmb.2023.0482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024] Open
Abstract
Background: The extracellular matrix (ECM) glycoprotein changes are associated with the pathogenesis and complications of atherosclerosis, leading to acute coronary syndrome (ACS). Tenascin-C (TNC), an ECM protein, has been implemented in the pathogenesis, diagnosis, and prognosis of patients with cardiovascular disease. Aim: The study aimed to compare the genetic variants of the TNC gene (rs13321, rs2104772, and rs12347433) between South Indians with ACS and healthy participants. Materials and Methods: This case-control study recruited 150 ACS patients as cases and 150 healthy participants as controls. TNC genotyping was performed using TaqMan 5'-exonuclease allele discrimination assay. Serum TNC levels were measured by enzyme-linked immunosorbent assay. Results: Serum TNC levels were significantly higher in cases compared with controls. No significant difference was observed in allele and genotype frequencies of rs13321, rs2104772, and rs12347433 between cases and controls, which was confirmed by dominant, recessive, codominant, and homozygotic genetic models. The patients with heterozygous genotypes of rs13321, rs2104772, and rs12347433 had significantly lower serum TNC levels than patients with respective homozygous genotypes. Haplotype analyses revealed that the C-T-A haplotype in the block of rs13321-rs12347433-rs2104772 was associated with lower ACS risk (OR = 0.33, 95% CI: 0.15 - 0.75; p = 0.005). Also, the C-T-T and G-T-A haplotypes of the TNC gene were associated with higher and lower serum TNC levels, respectively. Conclusion: Our study demonstrated no genetic association between single nucleotide polymorphisms of the TNC gene and ACS risk; however, the C-T-A haplotype of the TNC gene might be associated with reduced ACS risk in South Indians.
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Affiliation(s)
- Sankar Abirami
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Prashant Shankarrao Adole
- Department of Biochemistry, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
| | - Kolar Vishwanath Vinod
- Department of Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Pondicherry, India
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Chung A, Chang HK, Pan H, Bashore AC, Shuck K, Matias CV, Gomez J, Yan H, Li M, Bauer RC. ADAMTS7 Promotes Smooth Muscle Cell Foam Cell Expansion in Atherosclerosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582156. [PMID: 38463994 PMCID: PMC10925101 DOI: 10.1101/2024.02.26.582156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Human genetic studies have repeatedly associated SNPs near the gene ADAMTS7 with atherosclerotic cardiovascular disease. Subsequent investigations in mice demonstrated that ADAMTS7 is proatherogenic, induced in response to vascular injury, and alters smooth muscle cell function. However, the mechanisms governing this function and its relationship to atherosclerosis remain unclear. Here, we report the first conditional Adamts7 transgenic mouse in which the gene can be conditionally overexpressed in smooth muscle cells, mimicking its induction in atherosclerosis. We observed that smooth muscle cell Adamts7 overexpression results in a 3.5-fold increase in peripheral atherosclerosis, coinciding with an expansion of smooth muscle foam cells. RNA sequencing of Adamts7 overexpressed primary smooth muscle cells revealed an upregulation in the expression of lipid uptake genes. Subsequent experiments in primary smooth muscle cells demonstrated that increased Spi1 and Cd36 expression leads to increased smooth muscle cell oxLDL uptake. To uncover ADAMTS7 expression in human disease, we have interrogated the largest scRNA-seq dataset of human carotid atherosclerosis. This analysis discovered that endothelial cells had the highest expression level of ADAMTS7 with lesser expression in smooth muscle cells, fibroblasts, and mast cells. Subsequent conditional knockout studies in smooth muscle cells surprisingly showed no change in atherosclerosis, suggesting redundant expression of this secreted factor in the vessel wall. Finally, mice overexpressing Adamts7 in endothelial cells also exhibit increased atherosclerosis, suggesting that multiple vascular cell types can contribute to ADAMTS7-mediated foam cell expansion. In summary, Adamts7 is expressed by multiple vascular cell types in atherosclerosis, and ADAMTS7 promotes oxLDL uptake in smooth muscle cells, increasing smooth muscle foam cell formation and peripheral atherosclerosis in mice.
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Tian Q, Chen JH, Ding Y, Wang XY, Qiu JY, Cao Q, Zhuang LL, Jin R, Zhou GP. EGR1 transcriptionally regulates SVEP1 to promote proliferation and migration in human coronary artery smooth muscle cells. Mol Biol Rep 2024; 51:365. [PMID: 38409611 DOI: 10.1007/s11033-024-09322-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 02/06/2024] [Indexed: 02/28/2024]
Abstract
A low-frequency variant of sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SVEP1) is associated with the risk of coronary artery disease, as determined by a genome-wide association study. SVEP1 induces vascular smooth muscle cell proliferation and an inflammatory phenotype to promote atherosclerosis. In the present study, qRT‒PCR demonstrated that the mRNA expression of SVEP1 was significantly increased in atherosclerotic plaques compared to normal tissues. Bioinformatics revealed that EGR1 was a transcription factor for SVEP1. The results of the luciferase reporter assay, siRNA interference or overexpression assay, mutational analysis and ChIP confirmed that EGR1 positively regulated the transcriptional activity of SVEP1 by directly binding to its promoter. EGR1 promoted human coronary artery smooth muscle cell (HCASMC) proliferation and migration via SVEP1 in response to oxidized low-density lipoprotein (ox-LDL) treatment. Moreover, the expression level of EGR1 was increased in atherosclerotic plaques and showed a strong linear correlation with the expression of SVEP1. Our findings indicated that EGR1 binding to the promoter region drive SVEP1 transcription to promote HCASMC proliferation and migration.
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Affiliation(s)
- Qiang Tian
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jia-He Chen
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yi Ding
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xin-Yu Wang
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jia-Yun Qiu
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qian Cao
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Li-Li Zhuang
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Rui Jin
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Guo-Ping Zhou
- Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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32
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Qin M, Wu Y, Fang X, Pan C, Zhong S. Polygenic risk score predicts all-cause death in East Asian patients with prior coronary artery disease. Front Cardiovasc Med 2024; 11:1296415. [PMID: 38414927 PMCID: PMC10896892 DOI: 10.3389/fcvm.2024.1296415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 01/31/2024] [Indexed: 02/29/2024] Open
Abstract
Introduction Coronary artery disease (CAD) is a highly heritable and multifactorial disease. Numerous genome-wide association studies (GWAS) facilitated the construction of polygenic risk scores (PRS) for predicting future incidence of CAD, however, exclusively in European populations. Furthermore, identifying CAD patients with elevated risks of all-cause death presents a critical challenge in secondary prevention, which will contribute largely to reducing the burden for public healthcare. Methods We recruited a cohort of 1,776 Chinese CAD patients and performed medical follow-up for up to 11 years. A pruning and thresholding method was used to calculate PRS of CAD and its 14 risk factors. Their correlations with all-cause death were computed via Cox regression. Results and discussion We found that the PRS for CAD and its seven risk factors, namely myocardial infarction, ischemic stroke, angina, heart failure, low-density lipoprotein cholesterol, total cholesterol and C-reaction protein, were significantly associated with death (P ≤ 0.05), whereas the PRS of body mass index displayed moderate association (P < 0.1). Elastic-net Cox regression with 5-fold cross-validation was used to integrate these nine PRS models into a meta score, metaPRS, which performed well in stratifying patients at different risks for death (P < 0.0001). Combining metaPRS with clinical risk factors further increased the discerning power and a 4% increase in sensitivity. The metaPRS generated from the genetic susceptibility to CAD and its risk factors can well stratify CAD patients by their risks of death. Integrating metaPRS and clinical risk factors may contribute to identifying patients at higher risk of poor prognosis.
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Affiliation(s)
- Min Qin
- School of Medicine, South China University of Technology, Guangzhou, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yonglin Wu
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Guangzhou, China
| | - Xianhong Fang
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, China
| | - Cuiping Pan
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Guangzhou, China
- Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Shilong Zhong
- School of Medicine, South China University of Technology, Guangzhou, China
- Department of Pharmacy, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Guangzhou, China
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Chappell E, Arbour L, Laksman Z. The Inclusion of Underrepresented Populations in Cardiovascular Genetics and Epidemiology. J Cardiovasc Dev Dis 2024; 11:56. [PMID: 38392270 PMCID: PMC10888590 DOI: 10.3390/jcdd11020056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 01/25/2024] [Accepted: 02/02/2024] [Indexed: 02/24/2024] Open
Abstract
Novel genetic risk markers have helped us to advance the field of cardiovascular epidemiology and refine our current understanding and risk stratification paradigms. The discovery and analysis of variants can help us to tailor prognostication and management. However, populations underrepresented in cardiovascular epidemiology and cardiogenetics research may experience inequities in care if prediction tools are not applicable to them clinically. Therefore, the purpose of this article is to outline the barriers that underrepresented populations can face in participating in genetics research, to describe the current efforts to diversify cardiogenetics research, and to outline strategies that researchers in cardiovascular epidemiology can implement to include underrepresented populations. Mistrust, a lack of diverse research teams, the improper use of sensitive biodata, and the constraints of genetic analyses are all barriers for including diverse populations in genetics studies. The current work is beginning to address the paucity of ethnically diverse genetics research and has already begun to shed light on the potential benefits of including underrepresented and diverse populations. Reducing barriers for individuals, utilizing community-driven research processes, adopting novel recruitment strategies, and pushing for organizational support for diverse genetics research are key steps that clinicians and researchers can take to develop equitable risk stratification tools and improve patient care.
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Affiliation(s)
- Elias Chappell
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Laura Arbour
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada
| | - Zachary Laksman
- Department of Medicine and the School of Biomedical Engineering, Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
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Yan Y, Du X, Dou X, Li J, Zhang W, Yang S, Meng W, Tian G. Effects of Ninjurin 2 polymorphisms on susceptibility to coronary heart disease. Cell Cycle 2024; 23:328-337. [PMID: 38512812 PMCID: PMC11057668 DOI: 10.1080/15384101.2024.2330225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 02/29/2024] [Indexed: 05/01/2024] Open
Abstract
OBJECTIVE The aim of this study was to explore the effects of Ninjurin 2 (NINJ2) polymorphisms on susceptibility to coronary heart disease (CHD). METHODS We conducted a case-control study with 499 CHD cases and 505 age and gender-matched controls. Five single nucleotide polymorphisms (SNPs) in NINJ2 (rs118050317, rs75750647, rs7307242, rs10849390, and rs11610368) were genotyped by the Agena MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression analysis to assess the association of NINJ2 polymorphisms and CHD risk-adjusted for age and gender. What's more, risk genes and molecular functions were screened via protein-protein interaction (PPI) network and functional enrichment analysis. RESULTS Rs118050317 in NINJ2 significantly increased CHD risk in people aged more than 60 years and women. Rs118050317 and rs7307242 had strong relationships with hypertension risk in CHD patients. Additionally, rs75750647 exceedingly raised diabetes risk in cases under multiple models, whereas rs10849390 could protect CHD patients from diabetes in allele, homozygote, and additive models. We also observed two blocks in NINJ2. Further interaction network and enrichment analysis showed that NINJ2 played a greater role in the pathogenesis and progression of CHD. CONCLUSION Our results suggest that NINJ2 polymorphisms are associated with CHD risk.
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Affiliation(s)
- Yuping Yan
- Department of Cardiovascular Medicine, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
- Department of Cardiovascular Medicine, Xi’an Daxing Hospital, Xi’an, Shaanxi, China
| | - Xiaoyan Du
- Department of Cardiovascular Medicine, First Hospital of Yulin City, Yulin, Shaanxi, China
| | - Xia Dou
- Ministry of Education, Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Xi’an, Shaanxi, China
| | - Jingjie Li
- Ministry of Education, Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Xi’an, Shaanxi, China
| | - Wenjie Zhang
- Ministry of Education, Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Xi’an, Shaanxi, China
| | - Shuangyu Yang
- Ministry of Education, Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Xi’an, Shaanxi, China
| | - Wenting Meng
- Ministry of Education, Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), Xi’an, Shaanxi, China
| | - Gang Tian
- Department of Cardiovascular Medicine, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
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Schnitzler GR, Kang H, Fang S, Angom RS, Lee-Kim VS, Ma XR, Zhou R, Zeng T, Guo K, Taylor MS, Vellarikkal SK, Barry AE, Sias-Garcia O, Bloemendal A, Munson G, Guckelberger P, Nguyen TH, Bergman DT, Hinshaw S, Cheng N, Cleary B, Aragam K, Lander ES, Finucane HK, Mukhopadhyay D, Gupta RM, Engreitz JM. Convergence of coronary artery disease genes onto endothelial cell programs. Nature 2024; 626:799-807. [PMID: 38326615 PMCID: PMC10921916 DOI: 10.1038/s41586-024-07022-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 01/03/2024] [Indexed: 02/09/2024]
Abstract
Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge1-3. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway1-6. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes. Here we introduce a method to connect GWAS variants to functions. This method links variants to genes using epigenomics data, links genes to pathways de novo using Perturb-seq and integrates these data to identify convergence of GWAS loci onto pathways. We apply this approach to study the role of endothelial cells in genetic risk for coronary artery disease (CAD), and discover 43 CAD GWAS signals that converge on the cerebral cavernous malformation (CCM) signalling pathway. Two regulators of this pathway, CCM2 and TLNRD1, are each linked to a CAD risk variant, regulate other CAD risk genes and affect atheroprotective processes in endothelial cells. These results suggest a model whereby CAD risk is driven in part by the convergence of causal genes onto a particular transcriptional pathway in endothelial cells. They highlight shared genes between common and rare vascular diseases (CAD and CCM), and identify TLNRD1 as a new, previously uncharacterized member of the CCM signalling pathway. This approach will be widely useful for linking variants to functions for other common polygenic diseases.
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Affiliation(s)
- Gavin R Schnitzler
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Helen Kang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Shi Fang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ramcharan S Angom
- Department of Biochemistry and Molecular Biology, Mayo Clinic College of Medicine and Science, Jacksonville, FL, USA
| | - Vivian S Lee-Kim
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - X Rosa Ma
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Ronghao Zhou
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Tony Zeng
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Katherine Guo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Martin S Taylor
- Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Shamsudheen K Vellarikkal
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Aurelie E Barry
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Oscar Sias-Garcia
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Alex Bloemendal
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA
| | - Glen Munson
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Tung H Nguyen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Drew T Bergman
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Stephen Hinshaw
- Department of Chemical and Systems Biology, ChEM-H, and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nathan Cheng
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Brian Cleary
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Faculty of Computing and Data Sciences, Departments of Biology and Biomedical Engineering, Biological Design Center, and Program in Bioinformatics, Boston University, Boston, MA, USA
| | - Krishna Aragam
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, MIT, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Hilary K Finucane
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Debabrata Mukhopadhyay
- Department of Biochemistry and Molecular Biology, Mayo Clinic College of Medicine and Science, Jacksonville, FL, USA
| | - Rajat M Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA.
- Divisions of Genetics and Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Jesse M Engreitz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA.
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
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Quertermous T, Li DY, Weldy CS, Ramste M, Sharma D, Monteiro JP, Gu W, Worssam MD, Palmisano BT, Park CY, Cheng P. Genome-Wide Genetic Associations Prioritize Evaluation of Causal Mechanisms of Atherosclerotic Disease Risk. Arterioscler Thromb Vasc Biol 2024; 44:323-327. [PMID: 38266112 PMCID: PMC10857784 DOI: 10.1161/atvbaha.123.319480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 11/28/2023] [Indexed: 01/26/2024]
Abstract
OBJECTIVE The goal of this review is to discuss the implementation of genome-wide association studies to identify causal mechanisms of vascular disease risk. APPROACH AND RESULTS The history of genome-wide association studies is described, the use of imputation and the creation of consortia to conduct meta-analyses with sufficient power to arrive at consistent associated loci for vascular disease. Genomic methods are described that allow the identification of causal variants and causal genes and how they impact the disease process. The power of single-cell analyses to promote genome-wide association studies of causal gene function is described. CONCLUSIONS Genome-wide association studies represent a paradigm shift in the study of cardiovascular disease, providing identification of genes, cellular phenotypes, and disease pathways that empower the future of targeted drug development.
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Affiliation(s)
- Thomas Quertermous
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Daniel Yuhang Li
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Chad S Weldy
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Markus Ramste
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Disha Sharma
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - João P Monteiro
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Wenduo Gu
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Matthew D Worssam
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Brian T Palmisano
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Chong Y Park
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Paul Cheng
- Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
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Akyüz K, Cano Abadía M, Goisauf M, Mayrhofer MT. Unlocking the potential of big data and AI in medicine: insights from biobanking. Front Med (Lausanne) 2024; 11:1336588. [PMID: 38357641 PMCID: PMC10864616 DOI: 10.3389/fmed.2024.1336588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 01/19/2024] [Indexed: 02/16/2024] Open
Abstract
Big data and artificial intelligence are key elements in the medical field as they are expected to improve accuracy and efficiency in diagnosis and treatment, particularly in identifying biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. These applications belong to current research practice that is data-intensive. While the combination of imaging, pathological, genomic, and clinical data is needed to train algorithms to realize the full potential of these technologies, biobanks often serve as crucial infrastructures for data-sharing and data flows. In this paper, we argue that the 'data turn' in the life sciences has increasingly re-structured major infrastructures, which often were created for biological samples and associated data, as predominantly data infrastructures. These have evolved and diversified over time in terms of tackling relevant issues such as harmonization and standardization, but also consent practices and risk assessment. In line with the datafication, an increased use of AI-based technologies marks the current developments at the forefront of the big data research in life science and medicine that engender new issues and concerns along with opportunities. At a time when secure health data environments, such as European Health Data Space, are in the making, we argue that such meta-infrastructures can benefit both from the experience and evolution of biobanking, but also the current state of affairs in AI in medicine, regarding good governance, the social aspects and practices, as well as critical thinking about data practices, which can contribute to trustworthiness of such meta-infrastructures.
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Affiliation(s)
- Kaya Akyüz
- Department of ELSI Services and Research, BBMRI-ERIC, Graz, Austria
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Wurst C, Maixner F, Paladin A, Mussauer A, Valverde G, Narula J, Thompson R, Zink A. Genetic Predisposition of Atherosclerotic Cardiovascular Disease in Ancient Human Remains. Ann Glob Health 2024; 90:6. [PMID: 38273870 PMCID: PMC10809863 DOI: 10.5334/aogh.4366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 12/30/2023] [Indexed: 01/27/2024] Open
Abstract
Background Several computed tomographic studies have shown the presence of atherosclerosis in ancient human remains. However, while it is important to understand the development of atherosclerotic cardiovascular disease (ASCVD), genetic data concerning the prevalence of the disease-associated single nucleotide polymorphisms (SNPs) in our ancestors are scarce. Objective For a better understanding of the role of genetics in the evolution of ASCVD, we applied an enrichment capture sequencing approach to mummified human remains from different geographic regions and time periods. Methods Twenty-two mummified individuals were analyzed for their genetic predisposition of ASCVD. Next-generation sequencing methods were applied to ancient DNA (aDNA) samples, including a novel enrichment approach specifically designed to capture SNPs associated with ASCVD in genome-wide association studies of modern humans. Findings Five out of 22 ancient individuals passed all filter steps for calculating a weighted polygenic risk score (PRS) based on 87 SNPs in 56 genes. PRSs were correlated to scores obtained from contemporary people from around the world and cover their complete range. The genetic results of the ancient individuals reflect their phenotypic results, given that the only two mummies showing calcified atherosclerotic arterial plaques on computed tomography scans are the ones exhibiting the highest calculated PRSs. Conclusions These data show that alleles associated with ASCVD have been widespread for at least 5,000 years. Despite some limitations due to the nature of aDNA, our approach has the potential to lead to a better understanding of the interaction between environmental and genetic influences on the development of ASCVD.
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Affiliation(s)
- Christina Wurst
- Eurac Research –Institute for Mummy Studies, Bozen/Bolzano, Italy
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution (iomE), Johannes Gutenberg University of Mainz, Mainz, Germany
| | - Frank Maixner
- Eurac Research –Institute for Mummy Studies, Bozen/Bolzano, Italy
| | - Alice Paladin
- Eurac Research –Institute for Mummy Studies, Bozen/Bolzano, Italy
| | | | - Guido Valverde
- Eurac Research –Institute for Mummy Studies, Bozen/Bolzano, Italy
| | - Jagat Narula
- Medicine & Cardiology, McGovern Medical School, Houston, Texas, USA
| | | | - Albert Zink
- Eurac Research –Institute for Mummy Studies, Bozen/Bolzano, Italy
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Hartwell EE, Jinwala Z, Milone J, Ramirez S, Gelernter J, Kranzler HR, Kember RL. Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and medical traits. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.22.24301615. [PMID: 38343859 PMCID: PMC10854354 DOI: 10.1101/2024.01.22.24301615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and medical traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and medical traits were calculated in European-ancestry (EUR; n=5,691) participants and, when discovery datasets were available, for African-ancestry (AFR; n=4,918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGS MDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGS BMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and medical traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.
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Adelus ML, Ding J, Tran BT, Conklin AC, Golebiewski AK, Stolze LK, Whalen MB, Cusanovich DA, Romanoski CE. Single cell 'omic profiles of human aortic endothelial cells in vitro and human atherosclerotic lesions ex vivo reveals heterogeneity of endothelial subtype and response to activating perturbations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.04.03.535495. [PMID: 37066416 PMCID: PMC10104082 DOI: 10.1101/2023.04.03.535495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Objective Endothelial cells (ECs), macrophages, and vascular smooth muscle cells (VSMCs) are major cell types in atherosclerosis progression, and heterogeneity in EC sub-phenotypes are becoming increasingly appreciated. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Approach and Results To create an in vitro dataset to study human EC heterogeneity, multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs). To model pro-inflammatory and activating environments characteristic of the atherosclerotic microenvironment in vitro, HAECs from at least three donors were exposed to three distinct perturbations with their respective controls: transforming growth factor beta-2 (TGFB2), interleukin-1 beta (IL1B), and siRNA-mediated knock-down of the endothelial transcription factor ERG (siERG). To form a comprehensive in vivo/ex vivo dataset of human atherosclerotic cell types, meta-analysis of single cell transcriptomes across 17 human arterial specimens was performed. Two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and in vivo cell profiles. HAEC cultures were reproducibly populated by 4 major clusters with distinct pathway enrichment profiles: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Exposure to siERG, IL1B or TGFB2 elicited mostly distinct transcriptional and accessible chromatin responses. EC1 and EC2, the most canonically 'healthy' EC populations, were affected predominantly by siERG; the activated cluster EC3 was most responsive to IL1B; and the mesenchymal population EC4 was most affected by TGFB2. Quantitative comparisons between in vitro and in vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated SNPs from GWAS, suggesting these cell phenotypes harbor CAD-modulating mechanisms. Conclusion Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here, which have been reported by others to be involved in the pathogenesis of atherosclerosis as well as induce endothelial-to-mesenchymal transition (EndMT), only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and in vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.
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Affiliation(s)
- Maria L. Adelus
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
- The Clinical Translational Sciences Graduate Program, The University of Arizona, Tucson, AZ, 85721, USA
| | - Jiacheng Ding
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
| | - Binh T. Tran
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
| | - Austin C. Conklin
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
| | - Anna K. Golebiewski
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
| | - Lindsey K. Stolze
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
| | - Michael B. Whalen
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
| | - Darren A. Cusanovich
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
- Asthma and Airway Disease Research Center, The University of Arizona, Tucson, AZ, 85721, USA
| | - Casey E. Romanoski
- The Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85721, USA
- The Clinical Translational Sciences Graduate Program, The University of Arizona, Tucson, AZ, 85721, USA
- Asthma and Airway Disease Research Center, The University of Arizona, Tucson, AZ, 85721, USA
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Hodonsky CJ, Turner AW, Khan MD, Barrientos NB, Methorst R, Ma L, Lopez NG, Mosquera JV, Auguste G, Farber E, Ma WF, Wong D, Onengut-Gumuscu S, Kavousi M, Peyser PA, van der Laan SW, Leeper NJ, Kovacic JC, Björkegren JLM, Miller CL. Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci. CELL GENOMICS 2024; 4:100465. [PMID: 38190101 PMCID: PMC10794848 DOI: 10.1016/j.xgen.2023.100465] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/07/2023] [Accepted: 11/19/2023] [Indexed: 01/09/2024]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.
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Affiliation(s)
- Chani J Hodonsky
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Adam W Turner
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Mohammad Daud Khan
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Nelson B Barrientos
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Ruben Methorst
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nicolas G Lopez
- Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA
| | - Jose Verdezoto Mosquera
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Gaëlle Auguste
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Wei Feng Ma
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Medical Scientist Training Program, Department of Pathology, University of Virginia, Charlottesville, VA 22908, USA
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, 3000 CA Rotterdam, the Netherlands
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48019, USA
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Nicholas J Leeper
- Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA
| | - Jason C Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Victor Chang Cardiac Research Institute, Darlinghurst, NSW 2010, Australia; St. Vincent's Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
| | - Johan L M Björkegren
- Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Huddinge, Karolinska Institutet, 141 52 Huddinge, Sweden
| | - Clint L Miller
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Division of Vascular Surgery, Department of Surgery, Stanford University, Stanford, CA 94305, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
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Mavura Y, Sahin-Hodoglugil N, Hodoglugil U, Kvale M, Martin PM, Van Ziffle J, Devine WP, Ackerman SL, Koenig BA, Kwok PY, Norton ME, Slavotinek A, Risch N. Genetic ancestry and diagnostic yield of exome sequencing in a diverse population. NPJ Genom Med 2024; 9:1. [PMID: 38172272 PMCID: PMC10764913 DOI: 10.1038/s41525-023-00385-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 11/09/2023] [Indexed: 01/05/2024] Open
Abstract
It has been suggested that diagnostic yield (DY) from Exome Sequencing (ES) may be lower among patients with non-European ancestries than those with European ancestry. We examined the association of DY with estimated continental/subcontinental genetic ancestry in a racially/ethnically diverse pediatric and prenatal clinical cohort. Cases (N = 845) with suspected genetic disorders underwent ES for diagnosis. Continental/subcontinental genetic ancestry proportions were estimated from the ES data. We compared the distribution of genetic ancestries in positive, negative, and inconclusive cases by Kolmogorov-Smirnov tests and linear associations of ancestry with DY by Cochran-Armitage trend tests. We observed no reduction in overall DY associated with any genetic ancestry (African, Native American, East Asian, European, Middle Eastern, South Asian). However, we observed a relative increase in proportion of autosomal recessive homozygous inheritance versus other inheritance patterns associated with Middle Eastern and South Asian ancestry, due to consanguinity. In this empirical study of ES for undiagnosed pediatric and prenatal genetic conditions, genetic ancestry was not associated with the likelihood of a positive diagnosis, supporting the equitable use of ES in diagnosis of previously undiagnosed but potentially Mendelian disorders across all ancestral populations.
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Affiliation(s)
- Yusuph Mavura
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA.
| | - Nuriye Sahin-Hodoglugil
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Ugur Hodoglugil
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Mark Kvale
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Pierre-Marie Martin
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Jessica Van Ziffle
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - W Patrick Devine
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - Sara L Ackerman
- Institute for Health & Aging, School of Nursing, University of California San Francisco, San Francisco, CA, USA
- Department of Social & Behavioral Sciences, School of Nursing, University of California San Francisco, San Francisco, CA, USA
| | - Barbara A Koenig
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Program in Bioethics, University of California San Francisco, San Francisco, CA, USA
| | - Pui-Yan Kwok
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Cardiovascular Research Institute and Department of Dermatology, University of California San Francisco, San Francisco, CA, USA
| | - Mary E Norton
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Division of Maternal Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Anne Slavotinek
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Neil Risch
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA.
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Elfaki I, Mir R, Tayeb F, Alalawy AI, Barnawi J, Dabla PK, Moawadh MS. Potential Association of The Pathogenic Kruppel-like Factor 14 (KLF14) and Adiponectin (ADIPOQ) SNVs with Susceptibility to T2DM. Endocr Metab Immune Disord Drug Targets 2024; 24:1090-1100. [PMID: 38031795 DOI: 10.2174/0118715303258744231117064253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/15/2023] [Accepted: 10/10/2023] [Indexed: 12/01/2023]
Abstract
AIM To evaluate the associations of the pathogenic variants in Kruppel-like Factor 14 (KLF 14) and Adiponectin (ADIPOQ) with susceptibility to type 2 diabetes mellitus (T2DM). BACKGROUND Type 2 diabetes mellitus (T2DM) is a pandemic metabolic disease characterized by increased blood sugar and caused by resistance to insulin in peripheral tissues and damage to pancreatic beta cells. Kruppel-like Factor 14 (KLF-14) is proposed to be a regulator of metabolic diseases, such as diabetes mellitus (DM) and obesity. Adiponectin (ADIPOQ) is an adipocytokine produced by the adipocytes and other tissues and was reported to be involved in T2DM. OBJECTIVES To study the possible association of the KLF-14 rs972283 and ADIPOQ-rs266729 with the risk of T2DM in the Saudi population. METHODS We have evaluated the association of KLF-14 rs972283 C>T and ADIPOQ-rs266729 C>G SNV with the risk to T2D in the Saudi population using the Amplification Refractory Mutation System PCR (ARMS-PCR), and blood biochemistry analysis. For the KLF-14 rs972283 C>T SNV we included 115 cases and 116 healthy controls, and ADIPOQ-rs266729 C>G SNV, 103 cases and 104 healthy controls were included. RESULTS Results indicated that the KLF-14 rs972283 GA genotype and A allele were associated with T2D risk with OR=2.14, p-value= 0.014 and OR=1.99, p-value=0.0003, respectively. Results also ADIPOQ-rs266729 CG genotype and C allele were associated with an elevated T2D risk with an OR=2.53, p=0.003 and OR=1.66, p-value =0.012, respectively. CONCLUSION We conclude that SNVs in KLF-14 and ADIPOQ are potential loci for T2D risk. Future large-scale studies to verify these findings are recommended. These results need further verifications in protein functional and large-scale case control studies before being introduced for genetic testing.
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Affiliation(s)
- Imadeldin Elfaki
- Department of Biochemistry, Faculty of Science, University of Tabuk, Tabuk 47713, Saudi Arabia
| | - Rashid Mir
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 47713, Saudi Arabia
| | - Faris Tayeb
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 47713, Saudi Arabia
| | - Adel I Alalawy
- Department of Biochemistry, Faculty of Science, University of Tabuk, Tabuk 47713, Saudi Arabia
| | - Jameel Barnawi
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 47713, Saudi Arabia
| | - Pradeep Kumar Dabla
- Department of Biochemistry, Govind Ballabh Pant Institute of Postgraduate Medical Education & Research (GIPMER), Associated to Maulana Azad Medical College, Delhi 110002, India
| | - Mamdoh Shafig Moawadh
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 47713, Saudi Arabia
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Kachuri L, Chatterjee N, Hirbo J, Schaid DJ, Martin I, Kullo IJ, Kenny EE, Pasaniuc B, Witte JS, Ge T. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet 2024; 25:8-25. [PMID: 37620596 PMCID: PMC10961971 DOI: 10.1038/s41576-023-00637-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2023] [Indexed: 08/26/2023]
Abstract
Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.
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Affiliation(s)
- Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jibril Hirbo
- Department of Medicine Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Iman Martin
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Department of Genetics, Stanford University, Stanford, CA, USA.
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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Cornelissen A, Gadhoke NV, Ryan K, Hodonsky CJ, Mitchell R, Bihlmeyer NA, Duong T, Chen Z, Dikongue A, Sakamoto A, Sato Y, Kawakami R, Mori M, Kawai K, Fernandez R, Ghosh SKB, Braumann R, Abebe B, Kutys R, Kutyna M, Romero ME, Kolodgie FD, Miller CL, Hong CC, Grove ML, Brody JA, Sotoodehnia N, Arking DE, Schunkert H, Mitchell BD, Guo L, Virmani R, Finn AV. Polygenic Risk Score Associates With Atherosclerotic Plaque Characteristics at Autopsy. Arterioscler Thromb Vasc Biol 2024; 44:300-313. [PMID: 37916415 DOI: 10.1161/atvbaha.123.319818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/19/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND Polygenic risk scores (PRSs) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically. METHODS From 4327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner for sudden death between 1994 and 2015, 2455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas, and thrombotic CAD. RESULTS After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age, 48.8±14.7 years; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared with subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% versus 50.4%±38.7%; adjusted P<0.001) and a higher frequency of calcification (69.6% versus 35.8%; adjusted P=0.004) and thin-cap fibroatheroma (26.7% versus 9.5%; adjusted P=0.007). Even after adjustment for traditional CAD risk factors, subjects within the highest PRS quintile had higher odds of severe atherosclerosis (ie, ≥75% stenosis; adjusted odds ratio, 3.77 [95% CI, 2.10-6.78]; P<0.001) and plaque rupture (adjusted odds ratio, 4.05 [95% CI, 2.26-7.24]; P<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged ≤50 years (adjusted odds ratio, 4.08 [95% CI, 2.01-8.30]; P<0.001). No statistically significant associations were observed with plaque erosion after adjusting for covariates. CONCLUSIONS This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.
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Affiliation(s)
- Anne Cornelissen
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
- Department of Cardiology, University Hospital RWTH Aachen, Germany (A.C.)
| | - Neel V Gadhoke
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Kathleen Ryan
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
| | - Chani J Hodonsky
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (C.J.H., C.L.M.)
| | - Rebecca Mitchell
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Nathan A Bihlmeyer
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - ThuyVy Duong
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Zhifen Chen
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (Z.C., H.S.)
- Deutsches Zentrum für Herz-und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Germany (Z.C., H.S.)
| | - Armelle Dikongue
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Atsushi Sakamoto
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Yu Sato
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Rika Kawakami
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Masayuki Mori
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Kenji Kawai
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Raquel Fernandez
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Saikat Kumar B Ghosh
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Ryan Braumann
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Biniyam Abebe
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Robert Kutys
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Matthew Kutyna
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Maria E Romero
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Frank D Kolodgie
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Clint L Miller
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (C.J.H., C.L.M.)
| | - Charles C Hong
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
| | - Megan L Grove
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.A.B.)
| | - Nona Sotoodehnia
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Dan E Arking
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (R.M., N.A.B., T.D., M.L.G., N.S., D.E.A.)
| | - Heribert Schunkert
- Department of Cardiology, Deutsches Herzzentrum München, Technische Universität München, Munich, Germany (Z.C., H.S.)
- Deutsches Zentrum für Herz-und Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Germany (Z.C., H.S.)
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, MD (B.D.M.)
| | - Liang Guo
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Renu Virmani
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
| | - Aloke V Finn
- CVPath Institute, Gaithersburg, MD (A.C., N.V.G., A.D., A.S., Y.S., R. Kawakami, M.M., K.K., R.F., S.K.B.G., R.B., B.A., R. Kutys, M.K., M.E.R., F.D.K., L.G., R.V., A.V.F.)
- Department of Medicine, University of Maryland School of Medicine, Baltimore (K.R., C.C.H., B.D.M., A.V.F.)
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Schuermans A, Pournamdari AB, Lee J, Bhukar R, Ganesh S, Darosa N, Small AM, Yu Z, Hornsby W, Koyama S, Januzzi JL, Honigberg MC, Natarajan P. Integrative proteomic analyses across common cardiac diseases yield new mechanistic insights and enhanced prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.19.23300218. [PMID: 38196601 PMCID: PMC10775327 DOI: 10.1101/2023.12.19.23300218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Cardiac diseases represent common highly morbid conditions for which underlying molecular mechanisms remain incompletely understood. Here, we leveraged 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation, and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P <8.6×10 -6 . Cis -Mendelian randomization suggested causal roles that aligned with epidemiological findings for 6% of proteins identified in primary analyses, prioritizing novel therapeutic targets for different cardiac diseases (e.g., interleukin-4 receptor for heart failure and spondin-1 for atrial fibrillation). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (vs. clinical risk factors alone) improved prediction for coronary artery disease, heart failure, and atrial fibrillation. These results lay a foundation for future investigations to uncover novel disease mechanisms and assess the clinical utility of protein-based prevention strategies for cardiac diseases.
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47
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Kurt Z, Cheng J, Barrere-Cain R, McQuillen CN, Saleem Z, Hsu N, Jiang N, Pan C, Franzén O, Koplev S, Wang S, Björkegren J, Lusis AJ, Blencowe M, Yang X. Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse. eLife 2023; 12:RP88266. [PMID: 38060277 PMCID: PMC10703441 DOI: 10.7554/elife.88266] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023] Open
Abstract
Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.
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Affiliation(s)
- Zeyneb Kurt
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- The Information School at the University of SheffieldSheffieldUnited Kingdom
| | - Jenny Cheng
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Rio Barrere-Cain
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Caden N McQuillen
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Zara Saleem
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Neil Hsu
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Nuoya Jiang
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Calvin Pan
- Department of Medicine, Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
| | - Oscar Franzén
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Simon Koplev
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Susanna Wang
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Johan Björkegren
- Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Medicine, (Huddinge), Karolinska InstitutetHuddingeSweden
| | - Aldons J Lusis
- Department of Medicine, Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
- Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, UCLALos AngelesUnited States
- Cardiovascular Research Laboratory, David Geffen School of Medicine, UCLALos AngelesUnited States
| | - Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los AngelesLos AngelesUnited States
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los AngelesLos AngelesUnited States
- Interdepartmental Program of Bioinformatics, University of California, Los AngelesLos AngelesUnited States
- Department of Molecular and Medical Pharmacology, University of California, Los AngelesLos AngelesUnited States
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48
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Mani A. From mouse to human. eLife 2023; 12:e94382. [PMID: 38060304 PMCID: PMC10703438 DOI: 10.7554/elife.94382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023] Open
Abstract
A deep analysis of multiple genomic datasets reveals which genetic pathways associated with atherosclerosis and coronary artery disease are shared between mice and humans.
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Affiliation(s)
- Arya Mani
- Department of Internal Medicine and Genetics, Yale University School of MedicineNew HavenUnited States
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49
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Qiu W, Chen H, Kaeberlein M, Lee SI. ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age. THE LANCET. HEALTHY LONGEVITY 2023; 4:e711-e723. [PMID: 37944549 DOI: 10.1016/s2666-7568(23)00189-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 08/10/2023] [Accepted: 08/30/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We introduce ExplaiNAble BioLogical Age (ENABL Age), a computational framework that combines machine-learning models with explainable artificial intelligence (XAI) methods to accurately estimate biological age with individualised explanations. METHODS To construct the ENABL Age clock, we first predicted an age-related outcome (eg, all-cause or cause-specific mortality), and then rescaled these predictions to estimate biological age, using UK Biobank and National Health and Nutrition Examination Survey (NHANES) datasets. We adapted existing XAI methods to decompose individual ENABL Ages into contributing risk factors. For broad accessibility, we developed two versions: ENABL Age-L, based on blood tests, and ENABL Age-Q, based on questionnaire characteristics. Finally, we validated diverse ageing mechanisms captured by each ENABL Age clock through genome-wide association studies (GWAS) association analyses. FINDINGS Our ENABL Age clock was significantly correlated with chronological age (r=0·7867, p<0·0001 for UK Biobank; r=0·7126, p<0·0001 for NHANES). These clocks distinguish individuals who are healthy (ie, their ENABL Age is lower than their chronological age) from those who are unhealthy (ie, their ENABL Age is higher than their chronological age), predicting mortality more effectively than existing clocks. Groups of individuals who were unhealthy showed approximately three to 12 times higher log hazard ratio than healthy groups, as per ENABL Age. The clocks achieved high mortality prediction power with an area under the receiver operating characteristic curve of 0·8179 for 5-year mortality and 0·8115 for 10-year mortality on the UK Biobank dataset, and 0·8935 for 5-year mortality and 0·9107 for 10-year mortality on the NHANES dataset. The individualised explanations that revealed the contribution of specific characteristics to ENABL Age provided insights into the important characteristics for ageing. An association analysis with risk factors and ageing-related morbidities and GWAS results on ENABL Age clocks trained on different mortality causes showed that each clock captures distinct ageing mechanisms. INTERPRETATION ENABL Age brings an important leap forward in the application of XAI for interpreting biological age clocks. ENABL Age also carries substantial potential in practical settings, assisting medical professionals in untangling the complexity of ageing mechanisms, and potentially becoming a valuable tool in informed clinical decision-making processes. FUNDING National Science Foundation and National Institutes of Health.
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Affiliation(s)
- Wei Qiu
- Paul G Allen School of Computer Science and Engineering, University of Washington, Washington, DC, USA
| | - Hugh Chen
- Paul G Allen School of Computer Science and Engineering, University of Washington, Washington, DC, USA
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, University of Washington, Washington, DC, USA
| | - Su-In Lee
- Paul G Allen School of Computer Science and Engineering, University of Washington, Washington, DC, USA.
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50
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Hasbani NR, Westerman KE, Kwak SH, Chen H, Li X, Di Corpo D, Wessel J, Bis JC, Sarnowski C, Wu P, Bielak LF, Guo X, Heard-Costa N, Kinney GL, Mahaney MC, Montasser ME, Palmer ND, Raffield LM, Terry JG, Yanek LR, Bon J, Bowden DW, Brody JA, Duggirala R, Jacobs DR, Kalyani RR, Lange LA, Mitchell BD, Smith JA, Taylor KD, Carson AP, Curran JE, Fornage M, Freedman BI, Gabriel S, Gibbs RA, Gupta N, Kardia SLR, Kral BG, Momin Z, Newman AB, Post WS, Viaud-Martinez KA, Young KA, Becker LC, Bertoni AG, Blangero J, Carr JJ, Pratte K, Psaty BM, Rich SS, Wu JC, Malhotra R, Peyser PA, Morrison AC, Vasan RS, Lin X, Rotter JI, Meigs JB, Manning AK, de Vries PS. Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:e004176. [PMID: 38014529 PMCID: PMC10843644 DOI: 10.1161/circgen.123.004176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 09/29/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS Using a Bonferroni-corrected significance threshold of P<1.6×10-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis. CONCLUSIONS These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.
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Affiliation(s)
- Natalie R Hasbani
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
| | - Kenneth E Westerman
- Department of Medicine, Clinical and Translation Epidemiology Unit (K.E.W., A.K.M.), Massachusetts General Hospital, Boston
- Programs in Metabolism and Medical and Population Genetics (K.E.W., J.B.M., A.K.M.), Broad Institute, Cambridge
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, South Korea (S.H.K.)
| | - Han Chen
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
- School of Biomedical Informatics, Center for Precision Health (H.C.), The University of Texas Health Science Center at Houston
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health (X. Li, X. Lin), Boston University School of Public Health, MA
| | - Daniel Di Corpo
- Department of Biostatistics (D.D., P.W.), Boston University School of Public Health, MA
| | - Jennifer Wessel
- Department of Epidemiology, Fairbanks School of Public Health, Indianapolis, IN (J.W.)
| | - Joshua C Bis
- Department of Medicine, Cardiovascular Health Research Unit (J.C.B., J.A.B., B.M.P.), University of Washington, Seattle
| | - Chloè Sarnowski
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
| | - Peitao Wu
- Department of Biostatistics (D.D., P.W.), Boston University School of Public Health, MA
| | - Lawrence F Bielak
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-University of California Los Angeles Medical Center, Torrance (X.G., K.D.T.)
| | | | - Gregory L Kinney
- Department of Epidemiology, University of Colorado School of Public Health, Aurora (G.L.K., K.A.Y.)
| | - Michael C Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville (M.C.M., J.E.C., J. Blangero)
| | - May E Montasser
- Department of Medicine, Division of Endocrinology Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore (M.E.M., B.D.M.)
| | - Nicholette D Palmer
- Department of Biochemistry (N.D.P., D.W.B.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill (L.M.R.)
| | - James G Terry
- Department of Radiology, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN (J.G.T., J.J.C.)
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Jessica Bon
- Department of Medicine, Division of Pulmonary Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, PA (J. Bon)
| | - Donald W Bowden
- Department of Biochemistry (N.D.P., D.W.B.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Jennifer A Brody
- Department of Medicine, Cardiovascular Health Research Unit (J.C.B., J.A.B., B.M.P.), University of Washington, Seattle
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, McAllen (R.D.)
| | | | - Rita R Kalyani
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine University of Colorado, Aurora (L.A.L.)
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore (M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, MD (B.D.M.)
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (L.F.B., J.A.S., S.L.R.K., P.A.P.)
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor (J.A.S.)
| | - Kent D Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-University of California Los Angeles Medical Center, Torrance (X.G., K.D.T.)
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson (A.P.C.)
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville (M.C.M., J.E.C., J. Blangero)
| | - Myriam Fornage
- Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Stacey Gabriel
- Genomics Platform (S.G., N.G.), Broad Institute, Cambridge
| | - Richard A Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX (R.A.G., Z.M.)
| | - Namrata Gupta
- Genomics Platform (S.G., N.G.), Broad Institute, Cambridge
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (L.F.B., J.A.S., S.L.R.K., P.A.P.)
| | - Brian G Kral
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Zeineen Momin
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX (R.A.G., Z.M.)
| | - Anne B Newman
- Department of Epidemiology, University of Pittsburgh School of Public Health, PA (A.B.N.)
| | - Wendy S Post
- Division of Cardiology, Johns Hopkins Medicine, Baltimore, MD (W.S.P.)
| | | | - Kendra A Young
- Department of Epidemiology, University of Colorado School of Public Health, Aurora (G.L.K., K.A.Y.)
| | - Lewis C Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Alain G Bertoni
- Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC (A.G.B.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville (M.C.M., J.E.C., J. Blangero)
| | - John J Carr
- Department of Radiology, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN (J.G.T., J.J.C.)
| | - Katherine Pratte
- Department of Biostatistics, National Jewish Health, Denver, CO (K.P.)
| | - Bruce M Psaty
- Department of Medicine, Cardiovascular Health Research Unit (J.C.B., J.A.B., B.M.P.), University of Washington, Seattle
- Department of Epidemiology (B.M.P.), University of Washington, Seattle
- Department of Health Systems and Population Health (B.M.P.), University of Washington, Seattle
| | | | - Joseph C Wu
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (J.C.W.)
- Department of Medicine, Division of Cardiovascular Medicine, Stanford Cardiovascular Institute, Stanford University School of Medicine (J.C.W.), Stanford University, CA
| | - Rajeev Malhotra
- Division of Cardiology (R.M.), Massachusetts General Hospital, Boston
- Department of Radiology Molecular Imaging Program at Stanford (R.M.), Stanford University, CA
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (L.F.B., J.A.S., S.L.R.K., P.A.P.)
| | - Alanna C Morrison
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
| | - Ramachandran S Vasan
- Framingham Heart Study, MA (N.H.-C., R.S.V.)
- Department of Quantitative and Qualitative Health Sciences, University of Texas Health San Antonio School of Public Health (R.S.V.)
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health (X. Li, X. Lin), Boston University School of Public Health, MA
| | | | - James B Meigs
- Division of General Internal Medicine (J.B.M.), Massachusetts General Hospital, Boston
- Programs in Metabolism and Medical and Population Genetics (K.E.W., J.B.M., A.K.M.), Broad Institute, Cambridge
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Alisa K Manning
- Department of Medicine, Clinical and Translation Epidemiology Unit (K.E.W., A.K.M.), Massachusetts General Hospital, Boston
- Programs in Metabolism and Medical and Population Genetics (K.E.W., J.B.M., A.K.M.), Broad Institute, Cambridge
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Paul S de Vries
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
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