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Moore A, Venkatesh R, Levin MG, Damrauer SM, Reza N, Cappola TP, Ritchie MD. Connecting intermediate phenotypes to disease using multi-omics in heart failure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.06.24311572. [PMID: 39148828 PMCID: PMC11326335 DOI: 10.1101/2024.08.06.24311572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Heart failure (HF) is one of the most common, complex, heterogeneous diseases in the world, with over 1-3% of the global population living with the condition. Progression of HF can be tracked via MRI measures of structural and functional changes to the heart, namely left ventricle (LV), including ejection fraction, mass, end-diastolic volume, and LV end-systolic volume. Moreover, while genome-wide association studies (GWAS) have been a useful tool to identify candidate variants involved in HF risk, they lack crucial tissue-specific and mechanistic information which can be gained from incorporating additional data modalities. This study addresses this gap by incorporating transcriptome-wide and proteome-wide association studies (TWAS and PWAS) to gain insights into genetically-regulated changes in gene expression and protein abundance in precursors to HF measured using MRI-derived cardiac measures as well as full-stage all-cause HF. We identified several gene and protein overlaps between LV ejection fraction and end-systolic volume measures. Many of the overlaps identified in MRI-derived measurements through TWAS and PWAS appear to be shared with all-cause HF. We implicate many putative pathways relevant in HF associated with these genes and proteins via gene-set enrichment and protein-protein interaction network approaches. The results of this study (1) highlight the benefit of using multi-omics to better understand genetics and (2) provide novel insights as to how changes in heart structure and function may relate to HF.
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Affiliation(s)
- Anni Moore
- Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA
| | - Rasika Venkatesh
- Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA
| | - Michael G. Levin
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, 3400 Civic Center Blvd Philadelphia, PA, 19104, USA
| | - Scott M. Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St Philadelphia, PA 19104
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA
- Corporal Michael Crescenz VA Medical Center, 3900 Woodland Ave Philadelphia, PA
| | - Nosheen Reza
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, 3400 Civic Center Blvd Philadelphia, PA, 19104, USA
| | - Thomas P. Cappola
- Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, 3400 Civic Center Blvd Philadelphia, PA, 19104, USA
| | - Marylyn D. Ritchie
- Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk Philadelphia, PA, 19104, USA
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Maushagen J, Addin NS, Schuppert C, Ward-Caviness CK, Nattenmüller J, Adamski J, Peters A, Bamberg F, Schlett CL, Wang-Sattler R, Rospleszcz S. Serum metabolite signatures of cardiac function and morphology in individuals from a population-based cohort. Biomark Res 2024; 12:31. [PMID: 38444025 PMCID: PMC10916302 DOI: 10.1186/s40364-024-00578-w] [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: 12/06/2023] [Accepted: 02/24/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Changes in serum metabolites in individuals with altered cardiac function and morphology may exhibit information about cardiovascular disease (CVD) pathway dysregulations and potential CVD risk factors. We aimed to explore associations of cardiac function and morphology, evaluated using magnetic resonance imaging (MRI) with a large panel of serum metabolites. METHODS Cross-sectional data from CVD-free individuals from the population-based KORA cohort were analyzed. Associations between 3T-MRI-derived left ventricular (LV) function and morphology parameters (e.g., volumes, filling rates, wall thickness) and markers of carotid plaque with metabolite profile clusters and single metabolites as outcomes were assessed by adjusted multinomial logistic regression and linear regression models. RESULTS In 360 individuals (mean age 56.3 years; 41.9% female), 146 serum metabolites clustered into three distinct profiles that reflected high-, intermediate- and low-CVD risk. Higher stroke volume (relative risk ratio (RRR): 0.53, 95%-CI [0.37; 0.76], p-value < 0.001) and early diastolic filling rate (RRR: 0.51, 95%-CI [0.37; 0.71], p-value < 0.001) were most strongly protectively associated against the high-risk profile compared to the low-risk profile after adjusting for traditional CVD risk factors. Moreover, imaging markers were associated with 10 metabolites in linear regression. Notably, negative associations of stroke volume and early diastolic filling rate with acylcarnitine C5, and positive association of function parameters with lysophosphatidylcholines, diacylphosphatidylcholines, and acylalkylphosphatidylcholines were observed. Furthermore, there was a negative association of LV wall thickness with alanine, creatinine, and symmetric dimethylarginine. We found no significant associations with carotid plaque. CONCLUSIONS Serum metabolite signatures are associated with cardiac function and morphology even in individuals without a clinical indication of CVD.
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Affiliation(s)
- Juliane Maushagen
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Nuha Shugaa Addin
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Christopher Schuppert
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, U.S. EPA, Chapel Hill, NC, USA
| | - Johanna Nattenmüller
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, 117597, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany
- German Center for Diabetes Research, DZD, Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Christopher L Schlett
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Rui Wang-Sattler
- German Center for Diabetes Research, DZD, Neuherberg, Germany
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany.
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany.
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany.
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany.
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Sun TH, Wang CC, Wu YL, Hsu KC, Lee TH. Machine learning approaches for biomarker discovery to predict large-artery atherosclerosis. Sci Rep 2023; 13:15139. [PMID: 37704672 PMCID: PMC10499778 DOI: 10.1038/s41598-023-42338-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/08/2023] [Indexed: 09/15/2023] Open
Abstract
Large-artery atherosclerosis (LAA) is a leading cause of cerebrovascular disease. However, LAA diagnosis is costly and needs professional identification. Many metabolites have been identified as biomarkers of specific traits. However, there are inconsistent findings regarding suitable biomarkers for the prediction of LAA. In this study, we propose a new method integrates multiple machine learning algorithms and feature selection method to handle multidimensional data. Among the six machine learning models, logistic regression (LR) model exhibited the best prediction performance. The value of area under the receiver operating characteristic curve (AUC) was 0.92 when 62 features were incorporated in the external validation set for the LR model. In this model, LAA could be well predicted by clinical risk factors including body mass index, smoking, and medications for controlling diabetes, hypertension, and hyperlipidemia as well as metabolites involved in aminoacyl-tRNA biosynthesis and lipid metabolism. In addition, we found that 27 features were present among the five adopted models that could provide good results. If these 27 features were used in the LR model, an AUC value of 0.93 could be achieved. Our study has demonstrated the effectiveness of combining machine learning algorithms with recursive feature elimination and cross-validation methods for biomarker identification. Moreover, we have shown that using shared features can yield more reliable correlations than either model, which can be valuable for future identification of LAA.
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Affiliation(s)
- Ting-Hsuan Sun
- Artificial Intelligence Center, China Medical University Hospital, Taichung, Taiwan
| | - Chia-Chun Wang
- Artificial Intelligence Center, China Medical University Hospital, Taichung, Taiwan
| | - Ya-Lun Wu
- Artificial Intelligence Center, China Medical University Hospital, Taichung, Taiwan
| | - Kai-Cheng Hsu
- Artificial Intelligence Center, China Medical University Hospital, Taichung, Taiwan.
- Department of Neurology, China Medical University Hospital, Taichung, Taiwan.
- Department of Medicine, China Medical University, Taichung, Taiwan.
| | - Tsong-Hai Lee
- Stroke Center and Department of Neurology, Linkou Chang Gung Memorial Hospital, and College of Medicine, Chang Gung University, Taoyuan, Taiwan.
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Giro P, Cunningham JW, Rasmussen-Torvik L, Bielinski SJ, Larson NB, Colangelo LA, Jacobs DR, Gross M, Reiner AP, Lloyd-Jones DM, Guo X, Taylor K, Vaduganathan M, Post WS, Bertoni A, Ballantyne C, Shah A, Claggett B, Boerwinkle E, Yu B, Solomon SD, Shah SJ, Patel RB. Missense Genetic Variation of ICAM1 and Incident Heart Failure. J Card Fail 2023; 29:1163-1172. [PMID: 36882149 PMCID: PMC10477308 DOI: 10.1016/j.cardfail.2023.02.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Intercellular adhesion molecule-1 (ICAM-1) is a cell surface protein that participates in endothelial activation and is hypothesized to play a central role in heart failure (HF). We evaluated associations of ICAM1 missense genetic variants with circulating ICAM-1 levels and with incident HF. METHODS AND RESULTS We identified 3 missense variants within ICAM1 (rs5491, rs5498 and rs1799969) and evaluated their associations with ICAM-1 levels in the Coronary Artery Risk Development in Young Adults Study and the Multi-Ethnic Study of Atherosclerosis (MESA). We determined the association among these 3 variants and incident HF in MESA. We separately evaluated significant associations in the Atherosclerosis Risk in Communities (ARIC) study. Of the 3 missense variants, rs5491 was common in Black participants (minor allele frequency [MAF] > 20%) and rare in other race/ethnic groups (MAF < 5%). In Black participants, the presence of rs5491 was associated with higher levels of circulating ICAM-1 at 2 timepoints separated by 8 years. Among Black participants in MESA (n = 1600), the presence of rs5491 was associated with an increased risk of incident HF with preserved ejection fraction (HFpEF; HR = 2.30; [95% CI 1.25-4.21; P = 0.007]). The other ICAM1 missense variants (rs5498 and rs1799969) were associated with ICAM-1 levels, but there were no associations with HF. In ARIC, rs5491 was significantly associated with incident HF (HR = 1.24 [95% CI 1.02 - 1.51]; P = 0.03), with a similar direction of effect for HFpEF that was not statistically significant. CONCLUSIONS A common ICAM1 missense variant among Black individuals may be associated with increased risk of HF, which may be HFpEF-specific.
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Affiliation(s)
- Pedro Giro
- From the Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Jonathan W Cunningham
- Division of Cardiology, Department of Medicine, Brigham and Woman's Hospital, Boston, MA
| | - Laura Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | | | - Nicholas B Larson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Laura A Colangelo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, MN
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Donald M Lloyd-Jones
- From the Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Kent Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Muthiah Vaduganathan
- Division of Cardiology, Department of Medicine, Brigham and Woman's Hospital, Boston, MA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - Amil Shah
- Division of Cardiology, Department of Medicine, Brigham and Woman's Hospital, Boston, MA
| | - Brian Claggett
- Division of Cardiology, Department of Medicine, Brigham and Woman's Hospital, Boston, MA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Scott D Solomon
- Division of Cardiology, Department of Medicine, Brigham and Woman's Hospital, Boston, MA
| | - Sanjiv J Shah
- From the Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Ravi B Patel
- From the Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
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McFall GP, Bohn L, Gee M, Drouin SM, Fah H, Han W, Li L, Camicioli R, Dixon RA. Identifying key multi-modal predictors of incipient dementia in Parkinson's disease: a machine learning analysis and Tree SHAP interpretation. Front Aging Neurosci 2023; 15:1124232. [PMID: 37455938 PMCID: PMC10347530 DOI: 10.3389/fnagi.2023.1124232] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 06/13/2023] [Indexed: 07/18/2023] Open
Abstract
Background Persons with Parkinson's disease (PD) differentially progress to cognitive impairment and dementia. With a 3-year longitudinal sample of initially non-demented PD patients measured on multiple dementia risk factors, we demonstrate that machine learning classifier algorithms can be combined with explainable artificial intelligence methods to identify and interpret leading predictors that discriminate those who later converted to dementia from those who did not. Method Participants were 48 well-characterized PD patients (Mbaseline age = 71.6; SD = 4.8; 44% female). We tested 38 multi-modal predictors from 10 domains (e.g., motor, cognitive) in a computationally competitive context to identify those that best discriminated two unobserved baseline groups, PD No Dementia (PDND), and PD Incipient Dementia (PDID). We used Random Forest (RF) classifier models for the discrimination goal and Tree SHapley Additive exPlanation (Tree SHAP) values for deep interpretation. Results An excellent RF model discriminated baseline PDID from PDND (AUC = 0.84; normalized Matthews Correlation Coefficient = 0.76). Tree SHAP showed that ten leading predictors of PDID accounted for 62.5% of the model, as well as their relative importance, direction, and magnitude (risk threshold). These predictors represented the motor (e.g., poorer gait), cognitive (e.g., slower Trail A), molecular (up-regulated metabolite panel), demographic (age), imaging (ventricular volume), and lifestyle (activities of daily living) domains. Conclusion Our data-driven protocol integrated RF classifier models and Tree SHAP applications to selectively identify and interpret early dementia risk factors in a well-characterized sample of initially non-demented persons with PD. Results indicate that leading dementia predictors derive from multiple complementary risk domains.
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Affiliation(s)
- G. Peggy McFall
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Linzy Bohn
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Myrlene Gee
- Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
| | - Shannon M. Drouin
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Harrison Fah
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Computing Science, University of Alberta, Edmonton, AB, Canada
| | - Wei Han
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
| | - Roger A. Dixon
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
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Wu Q, Li J, Zhu J, Sun X, He D, Li J, Cheng Z, Zhang X, Xu Y, Chen Q, Zhu Y, Lai M. Gamma-glutamyl-leucine levels are causally associated with elevated cardio-metabolic risks. Front Nutr 2022; 9:936220. [PMID: 36505257 PMCID: PMC9729530 DOI: 10.3389/fnut.2022.936220] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/31/2022] [Indexed: 11/26/2022] Open
Abstract
Objective Gamma-glutamyl dipeptides are bioactive peptides involved in inflammation, oxidative stress, and glucose regulation. Gamma-glutamyl-leucine (Gamma-Glu-Leu) has been extensively reported to be associated with the risk of cardio-metabolic diseases, such as obesity, metabolic syndrome, and type 2 diabetes. However, the causality remains to be uncovered. The aim of this study was to explore the causal-effect relationships between Gamma-Glu-Leu and metabolic risk. Materials and methods In this study, 1,289 subjects were included from a cross-sectional survey on metabolic syndrome (MetS) in eastern China. Serum Gamma-Glu-Leu levels were measured by untargeted metabolomics. Using linear regressions, a two-stage genome-wide association study (GWAS) for Gamma-Glu-Leu was conducted to seek its instrumental single nucleotide polymorphisms (SNPs). One-sample Mendelian randomization (MR) analyses were performed to evaluate the causality between Gamma-Glu-Leu and the metabolic risk. Results Four SNPs are associated with serum Gamma-Glu-Leu levels, including rs12476238, rs56146133, rs2479714, and rs12229654. Out of them, rs12476238 exhibits the strongest association (Beta = -0.38, S.E. = 0.07 in discovery stage, Beta = -0.29, S.E. = 0.14 in validation stage, combined P-value = 1.04 × 10-8). Each of the four SNPs has a nominal association with at least one metabolic risk factor. Both rs12229654 and rs56146133 are associated with body mass index, waist circumference (WC), the ratio of WC to hip circumference, blood pressure, and triglyceride (5 × 10-5 < P < 0.05). rs56146133 also has nominal associations with fasting insulin, glucose, and insulin resistance index (5 × 10-5 < P < 0.05). Using the four SNPs serving as the instrumental SNPs of Gamma-Glu-Leu, the MR analyses revealed that higher Gamma-Glu-Leu levels are causally associated with elevated risks of multiple cardio-metabolic factors except for high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (P > 0.05). Conclusion Four SNPs (rs12476238, rs56146133, rs2479714, and rs12229654) may regulate the levels of serum Gamma-Glu-Leu. Higher Gamma-Glu-Leu levels are causally linked to cardio-metabolic risks. Future prospective studies on Gamma-Glu-Leu are required to explain its role in metabolic disorders.
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Affiliation(s)
- Qiong Wu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Epidemiology and Biostatistics, School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Jiankang Li
- Institute of Medical Research, Northwestern Polytechnical University, Xi’an, China
| | - Jinghan Zhu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Xiaohui Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Di He
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jun Li
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zongxue Cheng
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xuhui Zhang
- Hangzhou Center for Disease Control and Prevention, Hangzhou, China,Affiliated Hangzhou Center of Disease Control and Prevention, School of Public Health, Zhejiang University, Hangzhou, China
| | - Yuying Xu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qing Chen
- Zhejiang Provincial Centers for Disease Control and Prevention, Hangzhou, China,*Correspondence: Qing Chen,
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Department of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China,Cancer Center, Zhejiang University, Hangzhou, China,Yimin Zhu,
| | - Maode Lai
- Key Laboratory of Disease Proteomics of Zhejiang Province, Department of Pathology, School of Medicine, Zhejiang University, Hangzhou, China,State Key Laboratory of Natural Medicines, School of Basic Medical Sciences and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China,Maode Lai,
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7
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Banga R, Banga V, Eltalla A, Shahin L, Parag S, Naim M, Iyer E, Kumrah N, Zacharias B, Nathanson L, Beljanski V. Effects of autophagy modulators tamoxifen and chloroquine on the expression profiles of long non-coding RNAs in MIAMI cells exposed to IFNγ. PLoS One 2022; 17:e0266179. [PMID: 35446871 PMCID: PMC9022845 DOI: 10.1371/journal.pone.0266179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 03/15/2022] [Indexed: 11/18/2022] Open
Abstract
Mesenchymal stromal cells (MSCs) can be utilized clinically for treatment of conditions that result from excessive inflammation. In a pro-inflammatory environment, MSCs adopt an anti-inflammatory phenotype resulting in immunomodulation. A sub-type of MSCs referred to as “marrow-isolated adult multilineage inducible” (MIAMI) cells, which were isolated from bone marrow, were utilized to show that the addition of autophagy modulators, tamoxifen (TX) or chloroquine (CQ), can alter how MIAMI cells respond to IFNγ exposure in vitro resulting in an increased immunoregulatory capacity of the MIAMI cells. Molecularly, it was also shown that TX and CQ each alter both the levels of immunomodulatory genes and microRNAs which target such genes. However, the role of other non-coding RNAs (ncRNAs) such as long non-coding RNAs (lncRNAs) in regulating the response of MSCs to inflammation has been poorly studied. Here, we utilized transcriptomics and data mining to analyze the putative roles of various differentially regulated lncRNAs in MIAMI cells exposed to IFNγ with (or without) TX or CQ. The aim of this study was to investigate how the addition of TX and CQ alters lncRNA levels and evaluate how such changes could alter previously observed TX- and CQ-driven changes to the immunomodulatory properties of MIAMI cells. Data analysis revealed 693 long intergenic non-coding RNAS (lincRNAs), 480 pseudogenes, and 642 antisense RNAs that were differentially regulated with IFNγ, IFNγ+TX and IFNγ+CQ treatments. Further analysis of these RNA species based on the existing literature data revealed 6 antisense RNAs, 2 pseudogenes, and 5 lincRNAs that have the potential to modulate MIAMI cell’s response to IFNγ treatment. Functional analysis of these genomic species based on current literature linking inflammatory response and ncRNAs indicated their potential for regulation of several key pro- and anti-inflammatory responses, including NFκB signaling, cytokine secretion and auto-immune responses. Overall, this work found potential involvement of multiple pro-and anti-inflammatory pathways and molecules in modulating MIAMI cells’ response to inflammation.
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Affiliation(s)
- Rajkaran Banga
- Dr Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Davie, Florida
| | - Veerkaran Banga
- Dr Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Davie, Florida
| | - Amr Eltalla
- Dr Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Davie, Florida
| | - Lauren Shahin
- Dr Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Davie, Florida
| | - Sonam Parag
- Dr Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Davie, Florida
| | - Maha Naim
- Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, Davie, Florida
| | - Easha Iyer
- Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, Davie, Florida
| | - Neha Kumrah
- Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, Davie, Florida
| | - Brian Zacharias
- Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, Davie, Florida
| | - Lubov Nathanson
- Dr Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Davie, Florida
- Institute for Neuroimmune Medicine, Dr Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Davie, Florida
| | - Vladimir Beljanski
- Dr Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Davie, Florida
- Cell Therapy Institute, Dr Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Davie, Florida
- * E-mail:
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Shahian DM, Badhwar V, O'Brien SM, Habib RH, Han J, McDonald DE, Antman MS, Higgins RSD, Preventza O, Estrera AL, Calhoon JH, Grondin SC, Cooke DT. Social Risk Factors in Society of Thoracic Surgeons Risk Models Part 1: Concepts, Indicator Variables, and Controversies. Ann Thorac Surg 2022; 113:1703-1717. [PMID: 34998732 DOI: 10.1016/j.athoracsur.2021.11.067] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/29/2021] [Accepted: 11/02/2021] [Indexed: 11/01/2022]
Affiliation(s)
- David M Shahian
- Division of Cardiac Surgery, Department of Surgery, and Center for Quality and Safety, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
| | - Vinay Badhwar
- Department of Cardiovascular and Thoracic Surgery, West Virginia University, Morgantown WV
| | | | | | - Jane Han
- Society of Thoracic Surgeons, Chicago, IL
| | | | | | - Robert S D Higgins
- Johns Hopkins University School of Medicine and Johns Hopkins Hospital, Baltimore, MD
| | - Ourania Preventza
- Baylor College of Medicine, Texas Heart Institute, Baylor St. Luke's Medical Center, Houston, TX
| | - Anthony L Estrera
- McGovern Medical School at UTHealth; Memorial Hermann Heart and Vascular Institute; Houston, TX
| | - John H Calhoon
- Department of Cardiothoracic Surgery, University of Texas Health Science Center at San Antonio
| | - Sean C Grondin
- Cumming School of Medicine, University of Calgary, and Foothills Medical Centre, Calgary, Alberta, Canada
| | - David T Cooke
- Division of General Thoracic Surgery, UC Davis Health, Sacramento, CA
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9
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Plasma Metabolic Signature of Atherosclerosis Progression and Colchicine Treatment in Rabbits. Sci Rep 2020; 10:7072. [PMID: 32341369 PMCID: PMC7184732 DOI: 10.1038/s41598-020-63306-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 03/30/2020] [Indexed: 01/02/2023] Open
Abstract
Balloon catheter endothelial denudation in New Zealand white rabbits fed high cholesterol diet is a validated atherosclerosis model. Well-characterized in terms of atherosclerosis induction and progression, the metabolic changes associated with the atherosclerosis progression remain indeterminate. Non-targeted metabolomics permits to develop such elucidation and allows to evaluate the metabolic consequences of colchicine treatment, an anti-inflammatory drug that could revert these changes. 16 rabbits underwent 18 weeks of atherosclerosis induction by diet and aortic denudation. Thereafter animals were randomly assigned to colchicine treatment or placebo for 18 weeks while on diet. Plasma samples were obtained before randomization and at 36 weeks. Multiplatform (GC/MS, CE/MS, RP-HPLC/MS) metabolomics was applied. Plasma fingerprints were pre-processed, and the resulting matrixes analyzed to unveil differentially expressed features. Different chemical annotation strategies were accomplished for those significant features. We found metabolites associated with either atherosclerosis progression, or colchicine treatment, or both. Atherosclerosis was profoundly associated with an increase in circulating bile acids. Most of the changes associated with sterol metabolism could not be reverted by colchicine treatment. However, the variations in lysine, tryptophan and cysteine metabolism among others, have shown new potential mechanisms of action of the drug, also related to atherosclerosis progression, but not previously described.
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10
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Chen G, Shriner D, Doumatey AP, Zhou J, Bentley AR, Lei L, Adeyemo A, Rotimi CN. Refining genome-wide associated loci for serum uric acid in individuals with African ancestry. Hum Mol Genet 2020; 29:506-514. [PMID: 31841133 PMCID: PMC7015846 DOI: 10.1093/hmg/ddz272] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 10/31/2019] [Accepted: 11/05/2019] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE Serum uric acid is the end-product of purine metabolism and at high levels is a risk factor for several human diseases including gout and cardiovascular disease. Heritability estimates range from 0.32 to 0.63. Genome-wide association studies (GWAS) provide an unbiased approach to identify loci influencing serum uric acid. Here, we performed the first GWAS for serum uric acid in continental Africans, with replication in African Americans. METHODS Africans (n = 4126) and African Americans (n = 5007) were genotyped on high-density GWAS arrays. Efficient mixed model association, a variance component approach, was used to perform association testing for a total of ~ 18 million autosomal genotyped and imputed variants. CAVIARBF was used to fine map significant regions. RESULTS We identified two genome-wide significant loci: 4p16.1 (SLC2A9) and 11q13.1 (SLC22A12). At SLC2A9, the most strongly associated SNP was rs7683856 (P = 1.60 × 10-44). Conditional analysis revealed a second signal indexed by rs6838021 (P = 5.75 × 10-17). Gene expression and regulatory motif data prioritized a single-candidate causal variant for each signal. At SLC22A12, the most strongly associated SNP was rs147647315 (P = 6.65 × 10-25). Conditional analysis and functional annotation prioritized the missense variant rs147647315 (R (Arg) > H (His)) as the sole causal variant. Functional annotation of these three signals implicated processes in skeletal muscle, subcutaneous adipose tissue and the kidneys, respectively. CONCLUSIONS This first GWAS of serum uric acid in continental Africans identified three associations at two loci, SLC2A9 and SLC22A12. The combination of weak linkage disequilibrium in Africans and functional annotation led to the identification of candidate causal SNPs for all three signals. Each candidate causal variant implicated a different cell type. Collectively, the three associations accounted for 4.3% of the variance of serum uric acid.
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Affiliation(s)
- Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Lin Lei
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
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11
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Genome-wide association study identifies novel risk variants from RPS6KA1, CADPS, VARS, and DHX58 for fasting plasma glucose in Arab population. Sci Rep 2020; 10:152. [PMID: 31932636 PMCID: PMC6957513 DOI: 10.1038/s41598-019-57072-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 12/20/2019] [Indexed: 12/14/2022] Open
Abstract
Consanguineous populations of the Arabian Peninsula, which has seen an uncontrolled rise in type 2 diabetes incidence, are underrepresented in global studies on diabetes genetics. We performed a genome-wide association study on the quantitative trait of fasting plasma glucose (FPG) in unrelated Arab individuals from Kuwait (discovery-cohort:n = 1,353; replication-cohort:n = 1,196). Genome-wide genotyping in discovery phase was performed for 632,375 markers from Illumina HumanOmniExpress Beadchip; and top-associating markers were replicated using candidate genotyping. Genetic models based on additive and recessive transmission modes were used in statistical tests for associations in discovery phase, replication phase, and meta-analysis that combines data from both the phases. A genome-wide significant association with high FPG was found at rs1002487 (RPS6KA1) (p-discovery = 1.64E-08, p-replication = 3.71E-04, p-combined = 5.72E-11; β-discovery = 8.315; β-replication = 3.442; β-combined = 6.551). Further, three suggestive associations (p-values < 8.2E-06) with high FPG were observed at rs487321 (CADPS), rs707927 (VARS and 2Kb upstream of VWA7), and rs12600570 (DHX58); the first two markers reached genome-wide significance in the combined analysis (p-combined = 1.83E-12 and 3.07E-09, respectively). Significant interactions of diabetes traits (serum triglycerides, FPG, and glycated hemoglobin) with homeostatic model assessment of insulin resistance were identified for genotypes heterozygous or homozygous for the risk allele. Literature reports support the involvement of these gene loci in type 2 diabetes etiology.
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12
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Glessner JT, Li J, Desai A, Palmer M, Kim D, Lucas AM, Chang X, Connolly JJ, Almoguera B, Harley JB, Jarvik GP, Ritchie MD, Sleiman PM, Roden DM, Crosslin D, Hakonarson H. CNV Association of Diverse Clinical Phenotypes from eMERGE reveals novel disease biology underlying cardiovascular disease. Int J Cardiol 2020; 298:107-113. [DOI: 10.1016/j.ijcard.2019.07.058] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 06/15/2019] [Accepted: 07/16/2019] [Indexed: 10/26/2022]
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13
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Liu X, Zhou L, Shi X, Xu G. New advances in analytical methods for mass spectrometry-based large-scale metabolomics study. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.115665] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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14
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Liu C, Chen G, Bentley AR, Doumatey A, Zhou J, Adeyemo A, Yang J, Rotimi C. Genome-wide association study for proliferative diabetic retinopathy in Africans. NPJ Genom Med 2019; 4:20. [PMID: 31482010 PMCID: PMC6715701 DOI: 10.1038/s41525-019-0094-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 08/07/2019] [Indexed: 11/08/2022] Open
Abstract
Proliferative diabetic retinopathy (PDR) is a sight-threatening complication of diabetes that is associated with longer duration of diabetes and poor glycemic control under a genetic susceptibility background. Although GWAS of PDR have been conducted in Europeans and Asians, none has been done in continental Africans, a population at increased risk for PDR. Here, we report a GWAS of PDR among Africans. PDR cases (n = 64) were T2D patients with neovascularization in the retina and/or retinal detachment. Controls (n = 227) were T2D patients without listed eye complications despite high risk (T2D duration ≥10 years and fasting blood glucose >169 mg/dl). Replication was assessed in African Americans enrolled in the ARIC study. We identified 4 significant loci: WDR72, HLA-B, GAP43/RP11-326J18.1, and AL713866.1. At WDR72 the most strongly associated SNPs were rs12906891 (MAF = 0.071; p = 9.68 × 10-10; OR = 1.46, 95% CI [1.30,1.64]) and rs11070992 (MAF = 0.14; p = 4.23 × 10-8; OR = 1.28, 95%CI [1.17-1.40]). rs11070992 replicated in African Americans (p = 0.04). Variants in this gene have been associated with diabetic retinopathy, glycemic control, revascularization, and kidney disease.
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Affiliation(s)
- Chang Liu
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 10730 China
- Beijing Diabetes institute, Beijing, 100730 China
| | - Guanjie Chen
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Amy R. Bentley
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Ayo Doumatey
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Jie Zhou
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Adebowale Adeyemo
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - Jinkui Yang
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 10730 China
- Beijing Diabetes institute, Beijing, 100730 China
| | - Charles Rotimi
- The Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
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15
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McCauley MD, Darbar D. Race and Socioeconomic Status Regulate Lifetime Risk of Atrial Fibrillation. Circ Arrhythm Electrophysiol 2019; 11:e006584. [PMID: 30002068 DOI: 10.1161/circep.118.006584] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- Mark D McCauley
- Division of Cardiology, University of Illinois at Chicago. Jesse Brown Veterans Administration, Chicago, IL.
| | - Dawood Darbar
- Division of Cardiology, University of Illinois at Chicago. Jesse Brown Veterans Administration, Chicago, IL.
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16
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Adhikary J, Chakraborty S, Dalal S, Basu S, Dey A, Ghosh A. Circular PVT1: an oncogenic non-coding RNA with emerging clinical importance. J Clin Pathol 2019; 72:513-519. [PMID: 31154423 DOI: 10.1136/jclinpath-2019-205891] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 05/14/2019] [Accepted: 05/15/2019] [Indexed: 12/14/2022]
Abstract
The importance of circular RNAs (circRNAs) in pathological processes like cancer is evident. Among the circRNAs, recent studies have brought circPVT1 under focus as the most potent oncogenic non-coding RNA. Recent studies on various aspects of circPVT1, including its biogenesis, molecular alteration and its probable role in oncogenesis, have been conducted for research and clinical interest. In this review, a first attempt has been made to summarise the available data on circPVT1 from PubMed and other relevant databases with special emphasis on its role in development, progression and prognosis of various malignant conditions. CircPVT1 is derived from the same genetic locus encoding for long non-coding RNA lncPVT1; however, existing literature suggested circPVT1 and lncPVT1 are transcripted independently by different promoters. The interaction between circRNA and microRNA has been highlighted in majority of the few malignancies in which circPVT1 was studied. Besides its importance in diagnostic and prognostic procedures, circPVT1 seemed to have huge therapeutic potential as evident from differential drug response of cancer cell line as well as primary tumors depending on expression level of the candidate. circPVT1 in cancer therapeutics might be promising as a biomarker to make the existing treatment protocol more effective and also as potential target for designing novel therapeutic intervention.
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Affiliation(s)
- Jayashree Adhikary
- Department of Life Sciences, Presidency University Kolkata, Kolkata, India
| | | | - Subhamita Dalal
- Department of Life Sciences, Presidency University Kolkata, Kolkata, India
| | | | - Abhijit Dey
- Department of Life Sciences, Presidency University Kolkata, Kolkata, India
| | - Amlan Ghosh
- Department of Life Sciences, Presidency University Kolkata, Kolkata, India
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17
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Cockrum R, Speidel S, Crawford N, Zeng X, Blackburn H, Holt T, Enns R, Thomas M. Genotypes identified by genome-wide association analyses influence yearling pulmonary arterial pressure and growth traits in Angus heifers from a high-altitude beef production system. Livest Sci 2019. [DOI: 10.1016/j.livsci.2019.04.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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18
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Veenstra J, Kalsbeek A, Koster K, Ryder N, Bos A, Huisman J, VanderBerg L, VanderWoude J, Tintle NL. Epigenome wide association study of SNP-CpG interactions on changes in triglyceride levels after pharmaceutical intervention: a GAW20 analysis. BMC Proc 2018; 12:58. [PMID: 30275900 PMCID: PMC6157099 DOI: 10.1186/s12919-018-0144-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
In the search for an understanding of how genetic variation contributes to the heritability of common human disease, the potential role of epigenetic factors, such as methylation, is being explored with increasing frequency. Although standard analyses test for associations between methylation levels at individual cytosine-phosphate-guanine (CpG) sites and phenotypes of interest, some investigators have begun testing for methylation and how methylation may modulate the effects of genetic polymorphisms on phenotypes. In our analysis, we used both a genome-wide and candidate gene approach to investigate potential single-nucleotide polymorphism (SNP)–CpG interactions on changes in triglyceride levels. Although we were able to identify numerous loci of interest when using an exploratory significance threshold, we did not identify any significant interactions using a strict genome-wide significance threshold. We were also able to identify numerous loci using the candidate gene approach, in which we focused on 18 genes with prior evidence of association of triglyceride levels. In particular, we identified GALNT2 loci as containing potential CpG sites that moderate the impact of genetic polymorphisms on triglyceride levels. Further work is needed to provide clear guidance on analytic strategies for testing SNP–CpG interactions, although leveraging prior biological understanding may be needed to improve statistical power in data sets with smaller sample sizes.
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Affiliation(s)
- Jenna Veenstra
- 1Department of Biology, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA.,2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Anya Kalsbeek
- 1Department of Biology, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA.,2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Karissa Koster
- 2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Nathan Ryder
- 2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Abbey Bos
- 1Department of Biology, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Jordan Huisman
- 2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Lucas VanderBerg
- 2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Jason VanderWoude
- 2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA.,3Department of Computer Science, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
| | - Nathan L Tintle
- 2Department of Mathematics and Statistics, Dordt College, 498 4th Ave. NE, Sioux Center, IA 51250 USA
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Hebebrand J, Peters T, Schijven D, Hebebrand M, Grasemann C, Winkler TW, Heid IM, Antel J, Föcker M, Tegeler L, Brauner L, Adan RAH, Luykx JJ, Correll CU, König IR, Hinney A, Libuda L. The role of genetic variation of human metabolism for BMI, mental traits and mental disorders. Mol Metab 2018; 12:1-11. [PMID: 29673576 PMCID: PMC6001916 DOI: 10.1016/j.molmet.2018.03.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 03/23/2018] [Accepted: 03/29/2018] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE The aim was to assess whether loci associated with metabolic traits also have a significant role in BMI and mental traits/disorders METHODS: We first assessed the number of single nucleotide polymorphisms (SNPs) with genome-wide significance for human metabolism (NHGRI-EBI Catalog). These 516 SNPs (216 independent loci) were looked-up in genome-wide association studies for association with body mass index (BMI) and the mental traits/disorders educational attainment, neuroticism, schizophrenia, well-being, anxiety, depressive symptoms, major depressive disorder, autism-spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer's disease, bipolar disorder, aggressive behavior, and internalizing problems. A strict significance threshold of p < 6.92 × 10-6 was based on the correction for 516 SNPs and all 14 phenotypes, a second less conservative threshold (p < 9.69 × 10-5) on the correction for the 516 SNPs only. RESULTS 19 SNPs located in nine independent loci revealed p-values < 6.92 × 10-6; the less strict criterion was met by 41 SNPs in 24 independent loci. BMI and schizophrenia showed the most pronounced genetic overlap with human metabolism with three loci each meeting the strict significance threshold. Overall, genetic variation associated with estimated glomerular filtration rate showed up frequently; single metabolite SNPs were associated with more than one phenotype. Replications in independent samples were obtained for BMI and educational attainment. CONCLUSIONS Approximately 5-10% of the regions involved in the regulation of blood/urine metabolite levels seem to also play a role in BMI and mental traits/disorders and related phenotypes. If validated in metabolomic studies of the respective phenotypes, the associated blood/urine metabolites may enable novel preventive and therapeutic strategies.
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Affiliation(s)
- Johannes Hebebrand
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Triinu Peters
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Dick Schijven
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Moritz Hebebrand
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Corinna Grasemann
- Pediatric Endocrinology and Diabetology, Klinik für Kinderheilkunde II, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Thomas W Winkler
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Iris M Heid
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Jochen Antel
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Manuel Föcker
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Lisa Tegeler
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Lena Brauner
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Roger A H Adan
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jurjen J Luykx
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, ZNA Hospitals, Antwerp, Belgium
| | - Christoph U Correll
- Division of Psychiatry Research, Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Inke R König
- Institute of Medical Biometry and Statistics, University of Luebeck, Luebeck, Schleswig-Holstein, Germany
| | - Anke Hinney
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Lars Libuda
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
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20
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Circulating Biomarkers in Heart Failure. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1067:89-108. [PMID: 29392578 DOI: 10.1007/5584_2017_140] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Biological markers have served for diagnosis, risk stratification and guided therapy of heart failure (HF). Our knowledge regarding abilities of biomarkers to relate to several pathways of HF pathogenesis and reflect clinical worsening or improvement in the disease is steadily expanding. Although there are numerous clinical guidelines, which clearly diagnosis, prevention and evidence-based treatment of HF, a strategy regarding exclusion of HF, as well as risk stratification of HF, nature evolution of disease is not well established and requires more development. The aim of the chapter is to discuss a role of biomarker-based approaches for more accurate diagnosis, in-depth risk stratification and individual targeting in treatment of patients with HF.
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21
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Nyholt DR, Borsook D, Griffiths LR. Migrainomics — identifying brain and genetic markers of migraine. Nat Rev Neurol 2017; 13:725-741. [DOI: 10.1038/nrneurol.2017.151] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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22
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Cunha MLR, Meijers JCM, Rosendaal FR, Vlieg AVH, Reitsma PH, Middeldorp S. Whole exome sequencing in thrombophilic pedigrees to identify genetic risk factors for venous thromboembolism. PLoS One 2017; 12:e0187699. [PMID: 29117201 PMCID: PMC5695603 DOI: 10.1371/journal.pone.0187699] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 10/24/2017] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Family studies have shown a strong heritability component for venous thromboembolism (VTE), but established genetic risk factors are present in only half of VTE patients. AIM To identify genetic risk factors in two large families with unexplained hereditary VTE. METHODS We performed whole exome sequencing in 10 affected relatives of two unrelated families with an unexplained tendency for VTE. We prioritized variants shared by all affected relatives from both families, and evaluated these in the remaining affected and unaffected individuals. We prioritized variants based on 3 different filter strategies: variants within candidate genes, rare variants across the exome, and SNPs present in patients with familial VTE and with low frequency in the general population. We used whole exome sequencing data available from 96 unrelated VTE cases with a positive family history of VTE from an affected sib study (the GIFT study) to identify additional carriers and compared the risk-allele frequencies with the general population. Variants found in only one individual were also retained for further analysis. Finally, we assessed the association of these variants with VTE in a population-based case-control study (the MEGA study) with 4,291 cases and 4,866 controls. RESULTS Six variants remained as putative disease-risk candidates. These variants are located in 6 genes spread among 3 different loci: 2p21 (PLEKHH2 NM_172069:c.3105T>C, LRPPRC rs372371276, SRBD1 rs34959371), 5q35.2 (UNC5A NM_133369.2:c.1869+23C>A), and 17q25.1 (GPRC5C rs142232982, RAB37 rs556450784). In GIFT, additional carriers were identified only for the variants located in the 2p21 locus. In MEGA, additional carriers for several of these variants were identified in both cases and controls, without a difference in prevalence; no carrier of the UNC5A variant was present. CONCLUSION Despite sequencing of several individuals from two thrombophilic families resulting in 6 candidate variants, we were unable to confirm their relevance as novel thrombophilic defects.
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Affiliation(s)
- Marisa L. R. Cunha
- Department of Experimental Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
- Department of Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Joost C. M. Meijers
- Department of Experimental Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
- Department of Plasma Proteins, Sanquin, Amsterdam, the Netherlands
| | - Frits R. Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Astrid van Hylckama Vlieg
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - Pieter H. Reitsma
- Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Saskia Middeldorp
- Department of Vascular Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
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23
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Chamaria S, Johnson KW, Vengrenyuk Y, Baber U, Shameer K, Divaraniya AA, Glicksberg BS, Li L, Bhatheja S, Moreno P, Maehara A, Mehran R, Dudley JT, Narula J, Sharma SK, Kini AS. Intracoronary Imaging, Cholesterol Efflux, and Transcriptomics after Intensive Statin Treatment in Diabetes. Sci Rep 2017; 7:7001. [PMID: 28765529 PMCID: PMC5539108 DOI: 10.1038/s41598-017-07029-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 06/20/2017] [Indexed: 12/20/2022] Open
Abstract
Residual atherothrombotic risk remains higher in patients with versus without diabetes mellitus (DM) despite statin therapy. The underlying mechanisms are unclear. This is a retrospective post-hoc analysis of the YELLOW II trial, comparing patients with and without DM (non-DM) who received rosuvastatin 40 mg for 8–12 weeks and underwent intracoronary multimodality imaging of an obstructive nonculprit lesion, before and after therapy. In addition, blood samples were drawn to assess cholesterol efflux capacity (CEC) and changes in gene expression in peripheral blood mononuclear cells (PBMC). There was a significant reduction in low density lipoprotein-cholesterol (LDL-C), an increase in CEC and beneficial changes in plaque morphology including increase in fibrous cap thickness and decrease in the prevalence of thin cap fibro-atheroma by optical coherence tomography in DM and non-DM patients. While differential gene expression analysis did not demonstrate differences in PBMC transcriptome between the two groups on the single-gene level, weighted gene coexpression network analysis revealed two modules of coexpressed genes associated with DM, Collagen Module and Platelet Module, related to collagen catabolism and platelet function respectively. Bayesian network analysis revealed key driver genes within these modules. These transcriptomic findings might provide potential mechanisms responsible for the higher cardiovascular risk in DM patients.
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Affiliation(s)
| | - Kipp W Johnson
- Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Genetics and Genomic Sciences, Icahn Institute for Genetics and Genomic Sciences, Icahn School of Medicine, New York, USA
| | | | - Usman Baber
- Mount Sinai Heart, Mount Sinai Hospital, New York, USA
| | - Khader Shameer
- Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Genetics and Genomic Sciences, Icahn Institute for Genetics and Genomic Sciences, Icahn School of Medicine, New York, USA
| | - Aparna A Divaraniya
- Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Genetics and Genomic Sciences, Icahn Institute for Genetics and Genomic Sciences, Icahn School of Medicine, New York, USA
| | - Benjamin S Glicksberg
- Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Genetics and Genomic Sciences, Icahn Institute for Genetics and Genomic Sciences, Icahn School of Medicine, New York, USA
| | - Li Li
- Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Genetics and Genomic Sciences, Icahn Institute for Genetics and Genomic Sciences, Icahn School of Medicine, New York, USA
| | | | - Pedro Moreno
- Mount Sinai Heart, Mount Sinai Hospital, New York, USA
| | | | - Roxana Mehran
- Mount Sinai Heart, Mount Sinai Hospital, New York, USA
| | - Joel T Dudley
- Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, USA.,Department of Genetics and Genomic Sciences, Icahn Institute for Genetics and Genomic Sciences, Icahn School of Medicine, New York, USA.,Department of Population Health and Health Policy, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Jagat Narula
- Mount Sinai Heart, Mount Sinai Hospital, New York, USA
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24
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Warren CR, O'Sullivan JF, Friesen M, Becker CE, Zhang X, Liu P, Wakabayashi Y, Morningstar JE, Shi X, Choi J, Xia F, Peters DT, Florido MHC, Tsankov AM, Duberow E, Comisar L, Shay J, Jiang X, Meissner A, Musunuru K, Kathiresan S, Daheron L, Zhu J, Gerszten RE, Deo RC, Vasan RS, O'Donnell CJ, Cowan CA. Induced Pluripotent Stem Cell Differentiation Enables Functional Validation of GWAS Variants in Metabolic Disease. Cell Stem Cell 2017; 20:547-557.e7. [PMID: 28388431 DOI: 10.1016/j.stem.2017.01.010] [Citation(s) in RCA: 110] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 10/10/2016] [Accepted: 01/27/2017] [Indexed: 12/14/2022]
Abstract
Genome-wide association studies (GWAS) have highlighted a large number of genetic variants with potential disease association, but functional analysis remains a challenge. Here we describe an approach to functionally validate identified variants through differentiation of induced pluripotent stem cells (iPSCs) to study cellular pathophysiology. We collected peripheral blood cells from Framingham Heart Study participants and reprogrammed them to iPSCs. We then differentiated 68 iPSC lines into hepatocytes and adipocytes to investigate the effect of the 1p13 rs12740374 variant on cardiometabolic disease phenotypes via transcriptomics and metabolomic signatures. We observed a clear association between rs12740374 and lipid accumulation and gene expression in differentiated hepatocytes, in particular, expression of SORT1, CELSR2, and PSRC1, consistent with previous analyses of this variant using other approaches. Initial investigation of additional SNPs also highlighted correlations with gene expression. These findings suggest that iPSC-based population studies hold promise as tools for the functional validation of GWAS variants.
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Affiliation(s)
- Curtis R Warren
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - John F O'Sullivan
- Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Max Friesen
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Caroline E Becker
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Xiaoling Zhang
- School of Medicine, Boston University, Boston, MA 02118, USA; The Framingham Heart Study, Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA
| | - Poching Liu
- DNA Sequencing and Genomics Core, National Heart Lung and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Yoshiyuki Wakabayashi
- DNA Sequencing and Genomics Core, National Heart Lung and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Jordan E Morningstar
- Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Xu Shi
- Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Jihoon Choi
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Fang Xia
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Derek T Peters
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Mary H C Florido
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Alexander M Tsankov
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Eilene Duberow
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Lauren Comisar
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Jennifer Shay
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Xin Jiang
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Alexander Meissner
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kiran Musunuru
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Sekar Kathiresan
- Center for Human Genetic Research and Cardiovascular Research Center, Massachusetts General Hospital, 185 Cambridge Street, CPZN 5.252, Boston, MA 02114, USA
| | - Laurence Daheron
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA
| | - Jun Zhu
- DNA Sequencing and Genomics Core, National Heart Lung and Blood Institute, NIH, Bethesda, MD 20892, USA
| | - Robert E Gerszten
- Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Rahul C Deo
- Cardiovascular Research Institute, Department of Medicine and Institute for Human Genetics, University of California, San Francisco, and California Institute for Quantitative Biosciences, San Francisco, CA 94143, USA
| | - Ramachandran S Vasan
- The Framingham Heart Study, Sections of Preventive Medicine and Epidemiology and Cardiology, Framingham, MA 01702, USA; School of Medicine, Boston University, Boston, MA 02118, USA; School of Public Health, Boston University, Boston, MA 02118, USA
| | - Christopher J O'Donnell
- The Framingham Heart Study, Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA 01702, USA; Cardiology Section, Department of Medicine, Boston Veterans Administration Healthcare and Brigham and Women's Hospital, Boston, MA 02114, USA
| | - Chad A Cowan
- Department of Stem Cell and Regenerative Biology and Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
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25
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Park E, Guo J, Shen S, Demirdjian L, Wu YN, Lin L, Xing Y. Population and allelic variation of A-to-I RNA editing in human transcriptomes. Genome Biol 2017; 18:143. [PMID: 28754146 PMCID: PMC5532815 DOI: 10.1186/s13059-017-1270-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2017] [Accepted: 07/05/2017] [Indexed: 11/20/2022] Open
Abstract
Background A-to-I RNA editing is an important step in RNA processing in which specific adenosines in some RNA molecules are post-transcriptionally modified to inosines. RNA editing has emerged as a widespread mechanism for generating transcriptome diversity. However, there remain significant knowledge gaps about the variation and function of RNA editing. Results In order to determine the influence of genetic variation on A-to-I RNA editing, we integrate genomic and transcriptomic data from 445 human lymphoblastoid cell lines by combining an RNA editing QTL (edQTL) analysis with an allele-specific RNA editing (ASED) analysis. We identify 1054 RNA editing events associated with cis genetic polymorphisms. Additionally, we find that a subset of these polymorphisms is linked to genome-wide association study signals of complex traits or diseases. Finally, compared to random cis polymorphisms, polymorphisms associated with RNA editing variation are located closer spatially to their respective editing sites and have a more pronounced impact on RNA secondary structure. Conclusions Our study reveals widespread cis variation in RNA editing among genetically distinct individuals and sheds light on possible phenotypic consequences of such variation on complex traits and diseases. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1270-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Eddie Park
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jiguang Guo
- Department of Microbiology & Parasitology, Medical School of Hebei University, Baoding, Hebei Province, 071002, China
| | - Shihao Shen
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Levon Demirdjian
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Ying Nian Wu
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Lan Lin
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Yi Xing
- Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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26
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Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle. BMC Genomics 2017; 18:386. [PMID: 28521758 PMCID: PMC5437562 DOI: 10.1186/s12864-017-3754-y] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 05/03/2017] [Indexed: 11/13/2022] Open
Abstract
Background Single nucleotide polymorphism (SNP) arrays for domestic cattle have catalyzed the identification of genetic markers associated with complex traits for inclusion in modern breeding and selection programs. Using actual and imputed Illumina 778K genotypes for 3887 U.S. beef cattle from 3 populations (Angus, Hereford, SimAngus), we performed genome-wide association analyses for feed efficiency and growth traits including average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), and residual feed intake (RFI), with marker-based heritability estimates produced for all traits and populations. Results Moderate and/or large-effect QTL were detected for all traits in all populations, as jointly defined by the estimated proportion of variance explained (PVE) by marker effects (PVE ≥ 1.0%) and a nominal P-value threshold (P ≤ 5e-05). Lead SNPs with PVE ≥ 2.0% were considered putative evidence of large-effect QTL (n = 52), whereas those with PVE ≥ 1.0% but < 2.0% were considered putative evidence for moderate-effect QTL (n = 35). Identical or proximal lead SNPs associated with ADG, DMI, MMWT, and RFI collectively supported the potential for either pleiotropic QTL, or independent but proximal causal mutations for multiple traits within and between the analyzed populations. Marker-based heritability estimates for all investigated traits ranged from 0.18 to 0.60 using 778K genotypes, or from 0.17 to 0.57 using 50K genotypes (reduced from Illumina 778K HD to Illumina Bovine SNP50). An investigation to determine if QTL detected by 778K analysis could also be detected using 50K genotypes produced variable results, suggesting that 50K analyses were generally insufficient for QTL detection in these populations, and that relevant breeding or selection programs should be based on higher density analyses (imputed or directly ascertained). Conclusions Fourteen moderate to large-effect QTL regions which ranged from being physically proximal (lead SNPs ≤ 3Mb) to fully overlapping for RFI, DMI, ADG, and MMWT were detected within and between populations, and included evidence for pleiotropy, proximal but independent causal mutations, and multi-breed QTL. Bovine positional candidate genes for these traits were functionally conserved across vertebrate species. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3754-y) contains supplementary material, which is available to authorized users.
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27
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Chen G, Doumatey AP, Zhou J, Lei L, Bentley AR, Tekola-Ayele F, Adebamowo SN, Baker JL, Fasanmade O, Okafor G, Eghan B, Agyenim-Boateng K, Amoah A, Adebamowo C, Acheampong J, Johnson T, Oli J, Shriner D, Adeyemo AA, Rotimi CN. Genome-wide analysis identifies an african-specific variant in SEMA4D associated with body mass index. Obesity (Silver Spring) 2017; 25:794-800. [PMID: 28296344 PMCID: PMC5373947 DOI: 10.1002/oby.21804] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Revised: 01/23/2017] [Accepted: 01/24/2017] [Indexed: 12/23/2022]
Abstract
OBJECTIVE The prevalence of obesity varies between ethnic groups. No genome-wide association study (GWAS) for body mass index (BMI) has been conducted in continental Africans. METHODS We performed a GWAS for BMI in 1,570 West Africans (WA). Replication was conducted in independent samples of WA (n = 1,411) and African Americans (AA) (n = 9,020). RESULTS We identified a novel genome-wide significant African-specific locus for BMI (SEMA4D, rs80068415; minor allele frequency = 0.008, P = 2.10 × 10-8 ). This finding was replicated in independent samples of WA (P = 0.013) and AA (P = 0.017). Individuals with obesity had higher serum SEMA4D levels compared to those without obesity (P < 0.0001), and elevated levels of serum SEMA4D were associated with increased obesity risk (OR = 4.2, P < 1 × 10-4 ). The prevalence of obesity was higher in individuals with the CT versus TT genotypes (55.6% vs. 22.9%). CONCLUSIONS A novel variant in SEMA4D was significantly associated with BMI. Carriers of the C allele were 4.6 BMI units heavier than carriers of the T allele (P = 0.0007). This variant is monomorphic in Europeans and Asians, highlighting the importance of studying diverse populations. While there is evidence for the involvement of SEMA4D in inflammatory processes, this study is the first to implicate SEMA4D in obesity pathophysiology.
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Affiliation(s)
- Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Lin Lei
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Sally N Adebamowo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Jennifer L Baker
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Olufemi Fasanmade
- University of Lagos, College of Medicine, Endocrine and Metabolic Unit, Lagos, Nigeria
| | - Godfrey Okafor
- University of Nigeria Teaching Hospital, Department of Hematology, Enugu, Nigeria
| | - Benjamin Eghan
- University of Science and Technology, Department of Medicine, Kumasi, Ghana
| | | | - Albert Amoah
- University of Ghana Medical School, Department of Medicine and Therapeutics, Accra, Ghana
| | | | - Joseph Acheampong
- University of Science and Technology, Department of Medicine, Kumasi, Ghana
| | - Thomas Johnson
- University of Lagos, College of Medicine, Endocrine and Metabolic Unit, Lagos, Nigeria
| | - Johnnie Oli
- University of Nigeria Teaching Hospital, Department of Hematology, Enugu, Nigeria
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA, 20892
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28
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Chen G, Zhang Z, Adebamowo SN, Liu G, Adeyemo A, Zhou Y, Doumatey AP, Wang C, Zhou J, Yan W, Shriner D, Tekola-Ayele F, Bentley AR, Jiang C, Rotimi CN. Common and rare exonic MUC5B variants associated with type 2 diabetes in Han Chinese. PLoS One 2017; 12:e0173784. [PMID: 28346466 PMCID: PMC5367689 DOI: 10.1371/journal.pone.0173784] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 02/27/2017] [Indexed: 12/17/2022] Open
Abstract
Genome-wide association studies have identified over one hundred common genetic risk variants associated with type 2 diabetes (T2D). However, most of the heritability of T2D has not been accounted for. In this study, we investigated the contribution of rare and common variants to T2D susceptibility by analyzing exome array data in 1,908 Han Chinese genotyped with Affymetrix Axiom® Exome Genotyping Arrays. Based on the joint common and rare variants analysis of 57,704 autosomal SNPs within 12,244 genes using Sequence Kernel Association Tests (SKAT), we identified significant associations between T2D and 25 variants (9 rare and 16 common) in MUC5B, p-value 1.01×10−14. This finding was replicated (p = 0.0463) in an independent sample that included 10,401 unrelated individuals. Sixty-six of 1,553 possible haplotypes based on 25 SNPs within MUC5B showed significant association with T2D (Bonferroni corrected p values < 3.2×10−5). The expression level of MUC5B is significantly higher in pancreatic tissues of persons with T2D compared to those without T2D (p-value = 5×10−5). Our findings suggest that dysregulated MUC5B expression may be involved in the pathogenesis of T2D. As a strong candidate gene for T2D, MUC5B may play an important role in the mechanisms underlying T2D etiology and its complications.
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Affiliation(s)
- Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CNR); (GC)
| | | | - Sally N. Adebamowo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Yanxun Zhou
- Suizhou Central Hospital, Suizhou, Hubei, China
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CNR); (GC)
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29
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Shi J, Zhang B, Choi JY, Gao YT, Li H, Lu W, Long J, Kang D, Xiang YB, Wen W, Park SK, Ye X, Noh DY, Zheng Y, Wang Y, Chung S, Lin X, Cai Q, Shu XO. Age at menarche and age at natural menopause in East Asian women: a genome-wide association study. AGE (DORDRECHT, NETHERLANDS) 2016; 38:513-523. [PMID: 27629107 PMCID: PMC5266214 DOI: 10.1007/s11357-016-9939-5] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2015] [Accepted: 07/14/2016] [Indexed: 06/06/2023]
Abstract
Age at menarche (AM) and age at natural menopause (ANM) are complex traits with a high heritability. Abnormal timing of menarche or menopause is associated with a reduced span of fertility and risk for several age-related diseases including breast, endometrial and ovarian cancer, cardiovascular disease, and osteoporosis. To identify novel genetic loci for AM or ANM in East Asian women and to replicate previously identified loci primarily in women of European ancestry by genome-wide association studies (GWASs), we conducted a two-stage GWAS. Stage I aimed to discover promising novel AM and ANM loci using GWAS data of 8073 women from Shanghai, China. The Stage II replication study used the data from another Chinese GWAS (n = 1230 for AM and n = 1458 for ANM), a Korean GWAS (n = 4215 for AM and n = 1739 for ANM), and de novo genotyping of 2877 additional Chinese women. Previous GWAS-identified loci for AM and ANM were also evaluated. We identified two suggestive menarcheal age loci tagged by rs79195475 at 10q21.3 (beta = -0.118 years, P = 3.4 × 10-6) and rs1023935 at 4p15.1 (beta = -0.145 years, P = 4.9 × 10-6) and one menopausal age locus tagged by rs3818134 at 22q12.2 (beta = -0.276 years, P = 8.8 × 10-6). These suggestive loci warrant a further validation in independent populations. Although limited by low statistical power, we replicated 19 of the 98 menarche loci and 5 of the 20 menopause loci previously identified in women of European ancestry in East Asian women, suggesting a shared genetic architecture for these two traits across populations.
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Affiliation(s)
- Jiajun Shi
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Ben Zhang
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Ji-Yeob Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Huaixing Li
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Wei Lu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jirong Long
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Daehee Kang
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Yong-Bing Xiang
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wanqing Wen
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Sue K Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Xingwang Ye
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Dong-Young Noh
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Ying Zheng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Yiqin Wang
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Seokang Chung
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Xu Lin
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Qiuyin Cai
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Xiao-Ou Shu
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA.
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Snijders AM, Langley SA, Kim YM, Brislawn CJ, Noecker C, Zink EM, Fansler SJ, Casey CP, Miller DR, Huang Y, Karpen GH, Celniker SE, Brown JB, Borenstein E, Jansson JK, Metz TO, Mao JH. Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome. Nat Microbiol 2016; 2:16221. [PMID: 27892936 DOI: 10.1038/nmicrobiol.2016.221] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 10/07/2016] [Indexed: 12/22/2022]
Abstract
Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut. We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts the microbiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes in the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.
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Affiliation(s)
- Antoine M Snijders
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Sasha A Langley
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Young-Mo Kim
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Colin J Brislawn
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Cecilia Noecker
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - Erika M Zink
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Sarah J Fansler
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Cameron P Casey
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Darla R Miller
- Systems Genetics Core Facility, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Yurong Huang
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Gary H Karpen
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
| | - Susan E Celniker
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - James B Brown
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Elhanan Borenstein
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA.,Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, USA.,Santa Fe Institute, Santa Fe, New Mexico 87501, USA
| | - Janet K Jansson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Thomas O Metz
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Jian-Hua Mao
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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31
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Sun YV, Hu YJ. Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases. ADVANCES IN GENETICS 2016; 93:147-90. [PMID: 26915271 DOI: 10.1016/bs.adgen.2015.11.004] [Citation(s) in RCA: 235] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Complex and dynamic networks of molecules are involved in human diseases. High-throughput technologies enable omics studies interrogating thousands to millions of makers with similar biochemical properties (eg, transcriptomics for RNA transcripts). However, a single layer of "omics" can only provide limited insights into the biological mechanisms of a disease. In the case of genome-wide association studies, although thousands of single nucleotide polymorphisms have been identified for complex diseases and traits, the functional implications and mechanisms of the associated loci are largely unknown. Additionally, the genomic variants alone are not able to explain the changing disease risk across the life span. DNA, RNA, protein, and metabolite often have complementary roles to jointly perform a certain biological function. Such complementary effects and synergistic interactions between omic layers in the life course can only be captured by integrative study of multiple molecular layers. Building upon the success in single-omics discovery research, population studies started adopting the multi-omics approach to better understanding the molecular function and disease etiology. Multi-omics approaches integrate data obtained from different omic levels to understand their interrelation and combined influence on the disease processes. Here, we summarize major omics approaches available in population research, and review integrative approaches and methodologies interrogating multiple omic layers, which enhance the gene discovery and functional analysis of human diseases. We seek to provide analytical recommendations for different types of multi-omics data and study designs to guide the emerging multi-omic research, and to suggest improvement of the existing analytical methods.
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Affiliation(s)
- Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Atlanta, GA, United States; Department of Biomedical Informatics, School of Medicine, Atlanta, GA, United States
| | - Yi-Juan Hu
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States
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Abstract
Adhesion G protein-coupled receptors (aGPCRs) have a long evolutionary history dating back to very basal unicellular eukaryotes. Almost every vertebrate is equipped with a set of different aGPCRs. Genomic sequence data of several hundred extinct and extant species allows for reconstruction of aGPCR phylogeny in vertebrates and non-vertebrates in general but also provides a detailed view into the recent evolutionary history of human aGPCRs. Mining these sequence sources with bioinformatic tools can unveil many facets of formerly unappreciated aGPCR functions. In this review, we extracted such information from the literature and open public sources and provide insights into the history of aGPCR in humans. This includes comprehensive analyses of signatures of selection, variability of human aGPCR genes, and quantitative traits at human aGPCR loci. As indicated by a large number of genome-wide genotype-phenotype association studies, variations in aGPCR contribute to specific human phenotypes. Our survey demonstrates that aGPCRs are significantly involved in adaptation processes, phenotype variations, and diseases in humans.
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Affiliation(s)
- Peter Kovacs
- Integrated Research and Treatment Center (IFB) AdiposityDiseases, Medical Faculty, University of Leipzig, Liebigstr. 21, Leipzig, 04103, Germany.
| | - Torsten Schöneberg
- Institute of Biochemistry, Medical Faculty, University of Leipzig, Johannisallee 30, Leipzig, 04103, Germany.
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Abstract
PURPOSE OF REVIEW In contrast to many other human diseases, the use of genome-wide association studies (GWAS) to identify genes for heart failure (HF) has had limited success. We will discuss the underlying challenges as well as potential new approaches to understanding the genetics of common forms of HF. RECENT FINDINGS Recent research using intermediate phenotypes, more detailed and quantitative stratification of HF symptoms, founder populations and novel animal models has begun to allow researchers to make headway toward explaining the genetics underlying HF using GWAS techniques. SUMMARY By expanding analyses of HF to improved clinical traits, additional HF classifications and innovative model systems, the intractability of human HF GWAS should be ameliorated significantly.
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Suhre K, Raffler J, Kastenmüller G. Biochemical insights from population studies with genetics and metabolomics. Arch Biochem Biophys 2015; 589:168-76. [PMID: 26432701 DOI: 10.1016/j.abb.2015.09.023] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 09/28/2015] [Accepted: 09/28/2015] [Indexed: 12/31/2022]
Abstract
Genome-wide association studies with concentrations of hundreds of small molecules in samples collected from thousands of individuals (mGWAS) access otherwise inaccessible natural genetic experiments and their influence on the metabolic capacities of the human body. By sampling the natural metabolic and genetic variability that is present in the general population, mGWAS identified over 150 associations between genetic variants and variation in the metabolic composition of human body fluids. Many of these genetic variants were found to be located in enzyme or transporter coding genes, whose functions match the biochemical nature of the associated metabolites. Associations identified by mGWAS can reveal novel biochemical knowledge, such as the function of uncharacterized genes, the biochemical identity of small molecules, and the structure of entire biochemical pathways. Here we review findings of recent mGWAS and discuss concrete examples of how their results can be interpreted in a biochemical context. We describe online resources that are available for mining mGWAS results. In this context, we present two concepts that also find more general applications in the field of metabolomics: strengthening of associations by looking at ratios between metabolite pairs and reconstruction of metabolic pathways by Gaussian graphical modeling.
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Affiliation(s)
- Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medical College - Qatar, Doha, Qatar; Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Johannes Raffler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
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35
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Plasma metabolomic profiles enhance precision medicine for volunteers of normal health. Proc Natl Acad Sci U S A 2015; 112:E4901-10. [PMID: 26283345 DOI: 10.1073/pnas.1508425112] [Citation(s) in RCA: 127] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.
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36
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Colvin M, Sweitzer NK, Albert NM, Krishnamani R, Rich MW, Stough WG, Walsh MN, Westlake Canary CA, Allen LA, Bonnell MR, Carson PE, Chan MC, Dickinson MG, Dries DL, Ewald GA, Fang JC, Hernandez AF, Hershberger RE, Katz SD, Moore S, Rodgers JE, Rogers JG, Vest AR, Whellan DJ, Givertz MM. Heart Failure in Non-Caucasians, Women, and Older Adults: A White Paper on Special Populations From the Heart Failure Society of America Guideline Committee. J Card Fail 2015; 21:674-93. [DOI: 10.1016/j.cardfail.2015.05.013] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Revised: 05/21/2015] [Accepted: 05/26/2015] [Indexed: 01/11/2023]
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37
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PVT1: a rising star among oncogenic long noncoding RNAs. BIOMED RESEARCH INTERNATIONAL 2015; 2015:304208. [PMID: 25883951 PMCID: PMC4391155 DOI: 10.1155/2015/304208] [Citation(s) in RCA: 168] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 03/12/2015] [Indexed: 12/13/2022]
Abstract
It is becoming increasingly clear that short and long noncoding RNAs critically participate in the regulation of cell growth, differentiation, and (mis)function. However, while the functional characterization of short non-coding RNAs has been reaching maturity, there is still a paucity of well characterized long noncoding RNAs, even though large studies in recent years are rapidly increasing the number of annotated ones. The long noncoding RNA PVT1 is encoded by a gene that has been long known since it resides in the well-known cancer risk region 8q24. However, a couple of accidental concurrent conditions have slowed down the study of this gene, that is, a preconception on the primacy of the protein-coding over noncoding RNAs and the prevalent interest in its neighbor MYC oncogene. Recent studies have brought PVT1 under the spotlight suggesting interesting models of functioning, such as competing endogenous RNA activity and regulation of protein stability of important oncogenes, primarily of the MYC oncogene. Despite some advancements in modelling the PVT1 role in cancer, there are many questions that remain unanswered concerning the precise molecular mechanisms underlying its functioning.
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Vorkas PA, Shalhoub J, Isaac G, Want EJ, Nicholson JK, Holmes E, Davies AH. Metabolic Phenotyping of Atherosclerotic Plaques Reveals Latent Associations between Free Cholesterol and Ceramide Metabolism in Atherogenesis. J Proteome Res 2015; 14:1389-99. [DOI: 10.1021/pr5009898] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Panagiotis A. Vorkas
- Biomolecular
Medicine, Division of Computational and Systems Medicine, Department
of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Joseph Shalhoub
- Academic
Section of Vascular Surgery, Division of Surgery, Department of Surgery
and Cancer, Faculty of Medicine, Imperial College London, London W6 8RF, United Kingdom
| | - Giorgis Isaac
- Pharmaceutical
Discovery and Life Sciences, Waters Corporations, Milford, Massachusetts 01757, United States
| | - Elizabeth J. Want
- Biomolecular
Medicine, Division of Computational and Systems Medicine, Department
of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Jeremy K. Nicholson
- Biomolecular
Medicine, Division of Computational and Systems Medicine, Department
of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Elaine Holmes
- Biomolecular
Medicine, Division of Computational and Systems Medicine, Department
of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Alun H. Davies
- Academic
Section of Vascular Surgery, Division of Surgery, Department of Surgery
and Cancer, Faculty of Medicine, Imperial College London, London W6 8RF, United Kingdom
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39
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Peprah E, Xu H, Tekola-Ayele F, Royal CD. Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease. Public Health Genomics 2014; 18:40-51. [PMID: 25427668 DOI: 10.1159/000367962] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Accepted: 08/29/2014] [Indexed: 01/11/2023] Open
Abstract
Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.
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40
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Go YM, Kim CW, Walker DI, Kang DW, Kumar S, Orr M, Uppal K, Quyyumi AA, Jo H, Jones DP. Disturbed flow induces systemic changes in metabolites in mouse plasma: a metabolomics study using ApoE⁻/⁻ mice with partial carotid ligation. Am J Physiol Regul Integr Comp Physiol 2014; 308:R62-72. [PMID: 25377480 DOI: 10.1152/ajpregu.00278.2014] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Disturbed blood flow (d-flow) occurring in branched and curved arteries promotes endothelial dysfunction and atherosclerosis, in part, by altering gene expression and epigenomic profiles in endothelial cells. While a systemic metabolic change is known to play a role in atherosclerosis, it is unclear whether it can be regulated by local d-flow. Here, we tested this hypothesis by carrying out a metabolomics study using blood plasma samples obtained from ApoE(-/-) mice that underwent a partial carotid ligation surgery to induce d-flow. Mice receiving sham ligation were used as a control. To study early metabolic changes, samples collected from 1 wk after partial ligation when endothelial dysfunction occurs, but before atheroma develops, were analyzed by high-resolution mass spectrometry. A metabolome-wide association study showed that 128 metabolites were significantly altered in the ligated mice compared with the sham group. Of these, sphingomyelin (SM; m/z 703.5747), a common mammalian cell membrane sphingolipid, was most significantly increased in the ligated mice. Of the 128 discriminatory metabolites, 18 and 41 were positively and negatively correlated with SM, respectively. The amino acids methionine and phenylalanine were increased by d-flow, while phosphatidylcholine and phosphatidylethanolamine were decreased by d-flow, and these metabolites were correlated with SM. Other significantly affected metabolites included dietary and environmental agents. Pathway analysis showed that the metabolic changes of d-flow impacted broad functional networks. These results suggest that signaling from d-flow occurring in focal regions induces systemic metabolic changes associated with atherosclerosis.
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Affiliation(s)
- Young-Mi Go
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia
| | - Chan Woo Kim
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, Georgia; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Douglas I Walker
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia; Department of Civil and Environmental Engineering, Tufts University, Medford, Massachusetts; and
| | - Dong Won Kang
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, Georgia; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Sandeep Kumar
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, Georgia; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Michael Orr
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia
| | - Karan Uppal
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia
| | - Arshed A Quyyumi
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, Georgia
| | - Hanjoong Jo
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, Georgia; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Dean P Jones
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Emory University, Atlanta, Georgia;
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