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Kijpaisalratana N, Ament Z, Patki A, Bhave VM, Jones AC, Couch CA, Guarniz ALG, Cushman M, Long DL, Judd SE, Irvin MR, Kimberly WT. Plasma Metabolites and Life's Simple 7 in REGARDS. Stroke 2024; 55:1191-1199. [PMID: 38482689 PMCID: PMC11039367 DOI: 10.1161/strokeaha.123.044714] [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: 08/02/2023] [Accepted: 01/31/2024] [Indexed: 04/24/2024]
Abstract
BACKGROUND The American Heart Association's Life's Simple 7 (LS7) is a health metric that captures important factors associated with cardiovascular and cerebrovascular health. Previous studies highlight the potential of plasma metabolites to serve as a marker for lifestyle and health behavior that could be a target for stroke prevention. The objectives of this study were to identify metabolites that were associated with LS7 and incident ischemic stroke and mediate the relationship between the two. METHODS Targeted metabolomic profiling of 162 metabolites by liquid chromatography-tandem mass spectrometry was used to identify candidate metabolites in a stroke case-cohort nested within the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Weighted linear regression and weighted Cox proportional hazard models were used to identify metabolites that were associated with LS7 and incident ischemic stroke, respectively. Effect measures were based on a 1-SD change in metabolite level. Metabolite mediators were examined using inverse odds ratio weighting mediation analysis. RESULTS The study comprised 1075 ischemic stroke cases and 968 participants in the random cohort sample. Three out of 162 metabolites were associated with the overall LS7 score including guanosine (β, -0.46 [95% CI, -0.65 to -0.27]; P=2.87×10-6), cotinine (β, -0.49 [95% CI, -0.70 to -0.28]; P=7.74×10-6), and acetylneuraminic acid (β, -0.59 [95% CI, -0.77 to -0.42]; P=4.29×10-11). Guanosine (hazard ratio, 1.47 [95% CI, 1.31-1.65]; P=6.97×10-11), cotinine (hazard ratio, 1.30 [95% CI, 1.16-1.44]; P=2.09×10-6), and acetylneuraminic acid (hazard ratio, 1.29 [95% CI, 1.15-1.45]; P=9.24×10-6) were associated with incident ischemic stroke. The mediation analysis identified guanosine (27% mediation, indirect effect; P=0.002), cotinine (30% mediation, indirect effect; P=0.004), and acetylneurminic acid (22% mediation, indirect effect; P=0.041) partially mediated the relationship between LS7 and ischemic stroke. CONCLUSIONS We identified guanosine, cotinine, and acetylneuraminic acid that were associated with LS7, incident ischemic stroke, and mediated the relationship between LS7 and ischemic stroke.
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Affiliation(s)
- Naruchorn Kijpaisalratana
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Amit Patki
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | | | - Alana C Jones
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Catharine A. Couch
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | | | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - D. Leann Long
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Suzanne E. Judd
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - M. Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - W. Taylor Kimberly
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA
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Kijpaisalratana N, Ament Z, Patki A, Bhave VM, Jones AC, Garcia Guarniz AL, Couch CA, Cushman M, Long DL, Irvin MR, Kimberly WT. Acetylglutamine Differentially Associated with First-Time Versus Recurrent Stroke. Transl Stroke Res 2023:10.1007/s12975-023-01181-1. [PMID: 37531033 PMCID: PMC10834852 DOI: 10.1007/s12975-023-01181-1] [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: 05/09/2023] [Revised: 07/10/2023] [Accepted: 07/24/2023] [Indexed: 08/03/2023]
Abstract
Approximately one-quarter of strokes occur in individuals with prior stroke. Despite the advancement in secondary stroke prevention, the long-term risk of recurrent stroke has remained unchanged. The objective of this study was to identify metabolite risk markers that are associated with recurrent stroke. We performed targeted metabolomic profiling of 162 metabolites by liquid chromatography-tandem mass spectrometry in baseline plasma in a stroke case-cohort study nested within the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, an observational cohort study of 30,239 individuals aged 45 and older enrolled in 2003-2007. Weighted Cox proportional hazard models were used to identify metabolites that had a differential effect on first-time versus recurrent stroke using an interaction term between metabolite and prior stroke at baseline (yes or no). The study included 1391 incident stroke cases identified during 7.1 ± 4.5 years of follow-up and 1050 participants in the random cohort sample. Among 162 metabolites, 13 candidates had a metabolite-by-prior stroke interaction at a p-value <0.05, with one metabolite, acetylglutamine, surpassing the Bonferroni adjusted p-value threshold (p for interaction = 5.78 × 10-5). In an adjusted model that included traditional stroke risk factors, acetylglutamine was associated with recurrent stroke (HR = 2.27 per SD increment, 95% CI = 1.60-3.20, p = 3.52 × 10-6) but not with first-time stroke (HR = 0.96 per SD increment, 95% CI = 0.87-1.06, p = 0.44). Acetylglutamine was associated with recurrent stroke but not first-time stroke, independent of traditional stroke risk factors. Future studies are warranted to elucidate the pathogenesis of acetylglutamine and recurrent stroke risk.
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Affiliation(s)
- Naruchorn Kijpaisalratana
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Amit Patki
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Alana C Jones
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Catharine A Couch
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
| | - D Leann Long
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - M Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - W Taylor Kimberly
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Neurology, Massachusetts General Hospital, Boston, MA, 02114, USA.
- Harvard Medical School, Boston, MA, USA.
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Kijpaisalratana N, Ament Z, Bevers MB, Bhave VM, Garcia Guarniz AL, Couch CA, Irvin MR, Kimberly WT. Trimethylamine N-Oxide and White Matter Hyperintensity Volume Among Patients With Acute Ischemic Stroke. JAMA Netw Open 2023; 6:e2330446. [PMID: 37610752 PMCID: PMC10448304 DOI: 10.1001/jamanetworkopen.2023.30446] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 07/15/2023] [Indexed: 08/24/2023] Open
Abstract
Importance Although increasing evidence suggests that trimethylamine N-oxide (TMAO) is associated with atherosclerosis, little is known about whether TMAO and its related metabolites (ie, choline, betaine, and carnitine) are associated with small vessel disease. Objective To evaluate the association between TMAO and its related metabolites with features of cerebral small vessel disease, including white matter hyperintensity volume (WMHV) and acute lacunar infarction. Design, Setting, and Participants This cross-sectional study included patients enrolled in the Specialized Programs of Translational Research in Acute Stroke biorepository. The registry included 522 patients with acute ischemic stroke who were 18 years or older who presented at the Massachusetts General Hospital or Brigham and Women's Hospital within 9 hours after onset between January 2007 and April 2010. The analyses in this study were conducted between November 2022 and April 2023. Exposures Plasma TMAO, choline, betaine, and carnitine were measured by liquid chromatography-tandem mass spectrometry. Main Outcomes and Measures WMHV was quantified by a semiautomated approach using signal intensity threshold with subsequent manual editing. Ischemic stroke subtype was classified using the Causative Classification System. Results Among 351 patients included in this study, the mean (SD) age was 69 (15) years; 209 patients (59.5%) were male and had a median (IQR) admission National Institute of Health Stroke Scale of 6 (3-13). The magnetic resonance imaging subgroup consisted of 291 patients with a mean (SD) age of 67 (15) years. Among these, the median (IQR) WMHV was 3.2 (1.31-8.4) cm3. TMAO was associated with WMHV after adjustment for age and sex (β, 0.15; 95% CI, 0.01-0.29; P < .001). TMAO remained significant in a multivariate analysis adjusted for age, sex, hypertension, diabetes, and smoking (β, 0.14; 95% CI, 0-0.29; P = .05). TMAO was associated with lacunar stroke but not other ischemic stroke subtypes in a model adjusted for age, sex, hypertension, diabetes, and smoking (OR, 1.67; 95% CI, 1.05-2.66; P = .03). Conclusions and Relevance In this observational study, TMAO was associated with cerebral small vessel disease determined by WMHV and acute lacunar infarction. The association was independent of traditional vascular risk factors.
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Affiliation(s)
- Naruchorn Kijpaisalratana
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- Department of Neurology, Massachusetts General Hospital, Boston
- Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- Department of Neurology, Massachusetts General Hospital, Boston
| | - Matthew B. Bevers
- Divisions of Stroke, Cerebrovascular and Critical Care Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | | | - Catharine A. Couch
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham
| | - M. Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham
| | - W. Taylor Kimberly
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- Department of Neurology, Massachusetts General Hospital, Boston
- Harvard Medical School, Boston, Massachusetts
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Ament Z, Patki A, Bhave VM, Chaudhary NS, Garcia Guarniz AL, Kijpaisalratana N, Judd SE, Cushman M, Long DL, Irvin MR, Kimberly WT. Gut microbiota-associated metabolites and risk of ischemic stroke in REGARDS. J Cereb Blood Flow Metab 2023; 43:1089-1098. [PMID: 36883380 PMCID: PMC10291458 DOI: 10.1177/0271678x231162648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 01/30/2023] [Accepted: 02/08/2023] [Indexed: 03/09/2023]
Abstract
Several metabolite markers are independently associated with incident ischemic stroke. However, prior studies have not accounted for intercorrelated metabolite networks. We used exploratory factor analysis (EFA) to determine if metabolite factors were associated with incident ischemic stroke. Metabolites (n = 162) were measured in a case-control cohort nested in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, which included 1,075 ischemic stroke cases and 968 random cohort participants. Cox models were adjusted for age, gender, race, and age-race interaction (base model) and further adjusted for the Framingham stroke risk factors (fully adjusted model). EFA identified fifteen metabolite factors, each representing a well-defined metabolic pathway. Of these, factor 3, a gut microbiome metabolism factor, was associated with an increased risk of stroke in the base (hazard ratio per one-unit standard deviation, HR = 1.23; 95%CI = 1.15-1.31; P = 1.98 × 10-10) and fully adjusted models (HR = 1.13; 95%CI = 1.06-1.21; P = 4.49 × 10-4). The highest tertile had a 45% increased risk relative to the lowest (HR = 1.45; 95%CI = 1.25-1.70; P = 2.24 × 10-6). Factor 3 was also associated with the Southern diet pattern, a dietary pattern previously linked to increased stroke risk in REGARDS (β = 0.11; 95%CI = 0.03-0.18; P = 8.75 × 10-3). These findings highlight the role of diet and gut microbial metabolism in relation to incident ischemic stroke.
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Affiliation(s)
- Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Amit Patki
- Department of Epidemiology, School of Public Health at the University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Ninad S Chaudhary
- Department of Epidemiology, School of Public Health at the University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Naruchorn Kijpaisalratana
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Suzanne E Judd
- Department of Biostatistics, School of Public Health at the University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
| | - D Leann Long
- Department of Biostatistics, School of Public Health at the University of Alabama at Birmingham, Birmingham, AL, USA
| | - M Ryan Irvin
- Department of Epidemiology, School of Public Health at the University of Alabama at Birmingham, Birmingham, AL, USA
| | - W Taylor Kimberly
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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Kijpaisalratana N, Ament Z, Patki A, Bhave VM, Garcia-Guarniz AL, Judd SE, Cushman M, Long DL, Irvin MR, Kimberly WT. Association of Circulating Metabolites With Racial Disparities in Hypertension and Stroke in the REGARDS Study. Neurology 2023; 100:e2312-e2320. [PMID: 37068957 PMCID: PMC10259286 DOI: 10.1212/wnl.0000000000207264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 02/21/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES In the United States, the risk of stroke is greater among Black compared with that among White individuals. However, the reasons for the difference in stroke incidence are not fully elucidated. We aimed to identify metabolites that account for higher prevalent hypertension and incident ischemic stroke among Black adults. METHODS We used a stroke case cohort nested within the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Targeted metabolomic profiling of 162 plasma metabolites was performed by liquid chromatography-tandem mass spectrometry. We identified metabolites that were associated with prevalent hypertension and incident ischemic stroke and mediated the relationship between hypertension and ischemic stroke by weighted logistic regression, Cox proportional hazard model, and inverse odds ratio weighting mediation analysis. RESULTS Incident ischemic stroke cases adjudicated through April 1, 2019 (n = 1,075) were included in the study. The random cohort sample was derived from the full cohort using stratified sampling (n = 968). Among 162 metabolites, gluconic acid was associated with prevalent hypertension in Black adults (odds ratio [OR] 1.86, 95% CI 1.39-2.47, p = 2.58 × 10-5) but not in White adults (OR 1.00, 95% CI 0.80-1.24, p = 0.97; p for interaction = 4.57 × 10-4). Gluconic acid also demonstrated an association with incident ischemic stroke among Black participants (hazard ratio [HR] 1.53, 95% CI 1.28-1.81, p = 1.76 × 10-6) but not White participants (HR 1.16, 95% CI 1.00-1.34, p = 0.057; p for interaction = 0.019). In mediation analysis, gluconic acid mediated 25.4% (95% CI 4.1%-46.8%, p = 0.02) of the association between prevalent hypertension and incident ischemic stroke among Black individuals. Specific socioeconomic factors were linked to elevated gluconic acid level among Black adults in multivariable analysis, including a Southern dietary pattern (β = 0.18, 95% CI 0.08-0.28, p < 0.001), lower educational attainment (β = 0.45, 95% CI 0.19-0.72, p = 0.001), and a lack of exercise (β = 0.26, 95% CI 0.01-0.51, p = 0.045). DISCUSSION Gluconic acid is associated with prevalent hypertension and incident ischemic stroke and mediates the relationship between hypertension and ischemic stroke in Black but not White adults. Gluconic acid is a biomarker that is associated with social determinants of health including a Southern diet, low educational attainment, and low physical activity.
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Affiliation(s)
- Naruchorn Kijpaisalratana
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Zsuzsanna Ament
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Amit Patki
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Varun M Bhave
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Ana-Lucia Garcia-Guarniz
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Suzanne E Judd
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Mary Cushman
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - D Leann Long
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - M Ryan Irvin
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - W Taylor Kimberly
- From the Center for Genomic Medicine (N.K., Z.A., W.T.K.), Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurology (N.K.), Department of Medicine, and Division of Academic Affairs (N.K.), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Neurology (Z.A., A.-L.G.-G., W.T.K.), Massachusetts General Hospital, Boston; Department of Epidemiology (A.P., M.R.I.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B., W.T.K.), Boston, MA; Department of Biostatistics (S.E.J., D.L.L.), School of Public Health, University of Alabama at Birmingham; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington.
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Santos JL, Ruiz-Canela M, Razquin C, Clish CB, Guasch-Ferré M, Babio N, Corella D, Gómez-Gracia E, Fiol M, Estruch R, Lapetra J, Fitó M, Aros F, Serra-Majem L, Liang L, Martínez MÁ, Toledo E, Salas-Salvadó J, Hu FB, Martínez-González MA. Circulating citric acid cycle metabolites and risk of cardiovascular disease in the PREDIMED study. Nutr Metab Cardiovasc Dis 2023; 33:835-843. [PMID: 36739229 DOI: 10.1016/j.numecd.2023.01.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 11/03/2022] [Accepted: 01/03/2023] [Indexed: 01/13/2023]
Abstract
BACKGROUND AND AIM Plasma citric acid cycle (CAC) metabolites might be likely related to cardiovascular disease (CVD). However, studies assessing the longitudinal associations between circulating CAC-related metabolites and CVD risk are lacking. The aim of this study was to evaluate the association of baseline and 1-year levels of plasma CAC-related metabolites with CVD incidence (a composite of myocardial infarction, stroke or cardiovascular death), and their interaction with Mediterranean diet interventions. METHODS AND RESULTS Case-cohort study from the PREDIMED trial involving participants aged 55-80 years at high cardiovascular risk, allocated to MedDiets or control diet. A subcohort of 791 participants was selected at baseline, and a total of 231 cases were identified after a median follow-up of 4.8 years. Nine plasma CAC-related metabolites (pyruvate, lactate, citrate, aconitate, isocitrate, 2-hydroxyglutarate, fumarate, malate and succinate) were measured using liquid chromatography-tandem mass spectrometry. Weighted Cox multiple regression was used to calculate hazard ratios (HRs). Baseline fasting plasma levels of 3 metabolites were associated with higher CVD risk, with HRs (for each standard deviation, 1-SD) of 1.46 (95%CI:1.20-1.78) for 2-hydroxyglutarate, 1.33 (95%CI:1.12-1.58) for fumarate and 1.47 (95%CI:1.21-1.78) for malate (p of linear trend <0.001 for all). A higher risk of CVD was also found for a 1-SD increment of a combined score of these 3 metabolites (HR = 1.60; 95%CI: 1.32-1.94, p trend <0.001). This result was replicated using plasma measurements after one-year. No interactions were detected with the nutritional intervention. CONCLUSION Plasma 2-hydroxyglutarate, fumarate and malate levels were prospectively associated with increased cardiovascular risk. CLINICAL TRIAL NUMBER ISRCTN35739639.
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Affiliation(s)
- José L Santos
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA (Health Research Institute of Navarra), Pamplona, Spain; Department of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Miguel Ruiz-Canela
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA (Health Research Institute of Navarra), Pamplona, Spain.
| | - Cristina Razquin
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA (Health Research Institute of Navarra), Pamplona, Spain
| | - Clary B Clish
- Broad Institute of MIT and Harvard University, Cambridge, MA, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Nancy Babio
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnología, Unitat de Nutrició, Reus, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | | | - Miquel Fiol
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - Ramón Estruch
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Department of Internal Medicine, Biomedical Research Institute August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - José Lapetra
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Centro de Salud San Pablo, Servicios de Atención Primaria, Servicio Andaluz de Salud, Sevilla, Spain
| | - Montserrat Fitó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Cardiovascular and Nutrition Research Group, Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | | | - Lluis Serra-Majem
- Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria and Service of Preventive Medicine, Complejo Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canary Health Service, Las Palmas de Gran Canaria Spain
| | - Liming Liang
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - María Ángeles Martínez
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnología, Unitat de Nutrició, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Estefanía Toledo
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA (Health Research Institute of Navarra), Pamplona, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
| | - Jordi Salas-Salvadó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnología, Unitat de Nutrició, Reus, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Miguel A Martínez-González
- University of Navarra, Department of Preventive Medicine and Public Health, IdiSNA (Health Research Institute of Navarra), Pamplona, Spain; Broad Institute of MIT and Harvard University, Cambridge, MA, USA; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
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7
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Bhave VM, Ament Z, Patki A, Gao Y, Kijpaisalratana N, Guo B, Chaudhary NS, Garcia Guarniz AL, Gerszten R, Correa A, Cushman M, Judd S, Irvin MR, Kimberly WT. Plasma Metabolites Link Dietary Patterns to Stroke Risk. Ann Neurol 2023; 93:500-510. [PMID: 36373825 PMCID: PMC9974740 DOI: 10.1002/ana.26552] [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: 06/09/2022] [Revised: 11/04/2022] [Accepted: 11/12/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE While dietary intake is linked to stroke risk, surrogate markers that could inform personalized dietary interventions are lacking. We identified metabolites associated with diet patterns and incident stroke in a nested cohort from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. METHODS Levels of 162 metabolites were measured in baseline plasma from stroke cases (n = 1,198) and random controls (n = 904). We examined associations between metabolites and a plant-based diet pattern previously linked to reduced stroke risk in REGARDS. Secondary analyses included 3 additional stroke-associated diet patterns: a Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Southern diet. Metabolites were tested using Cox proportional hazards models with incident stroke as the outcome. Replication was performed in the Jackson Heart Study (JHS). Inverse odds ratio-weighted mediation was used to determine whether metabolites mediated the association between a plant-based diet and stroke risk. RESULTS Metabolites associated with a plant-based diet included the gut metabolite indole-3-propionic acid (β = 0.23, 95% confidence interval [CI] [0.14, 0.33], p = 1.14 × 10-6 ), guanosine (β = -0.13, 95% CI [-0.19, -0.07], p = 6.48 × 10-5 ), gluconic acid (β = -0.11, 95% CI [-0.18, -0.04], p = 2.06 × 10-3 ), and C7 carnitine (β = -0.16, 95% CI [-0.24, -0.09], p = 4.14 × 10-5 ). All of these metabolites were associated with both additional diet patterns and altered stroke risk. Mediation analyses identified guanosine (32.6% mediation, p = 1.51 × 10-3 ), gluconic acid (35.7%, p = 2.28 × 10-3 ), and C7 carnitine (26.2%, p = 1.88 × 10-2 ) as mediators linking a plant-based diet to reduced stroke risk. INTERPRETATION A subset of diet-related metabolites are associated with risk of stroke. These metabolites could serve as surrogate markers that inform dietary interventions. ANN NEUROL 2023;93:500-510.
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Affiliation(s)
| | - Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Amit Patki
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - Naruchorn Kijpaisalratana
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Boyi Guo
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Ninad S. Chaudhary
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
- The University of Texas Health Science Center at Houston, Houston, TX
| | | | - Robert Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Adolfo Correa
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - Suzanne Judd
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - M. Ryan Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - W. Taylor Kimberly
- Harvard Medical School, Boston, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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8
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Li W, Shao C, Zhou H, Du H, Chen H, Wan H, He Y. Multi-omics research strategies in ischemic stroke: A multidimensional perspective. Ageing Res Rev 2022; 81:101730. [PMID: 36087702 DOI: 10.1016/j.arr.2022.101730] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 08/23/2022] [Accepted: 09/03/2022] [Indexed: 01/31/2023]
Abstract
Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high rate of death and long-term impairment. Despite years of studies, there are still no stroke biomarkers for clinical practice, and the molecular mechanisms of stroke remain largely unclear. The high-throughput omics approach provides new avenues for discovering biomarkers of IS and explaining its pathological mechanisms. However, single-omics approaches only provide a limited understanding of the biological pathways of diseases. The integration of multiple omics data means the simultaneous analysis of thousands of genes, RNAs, proteins and metabolites, revealing networks of interactions between multiple molecular levels. Integrated analysis of multi-omics approaches will provide helpful insights into stroke pathogenesis, therapeutic target identification and biomarker discovery. Here, we consider advances in genomics, transcriptomics, proteomics and metabolomics and outline their use in discovering the biomarkers and pathological mechanisms of IS. We then delineate strategies for achieving integration at the multi-omics level and discuss how integrative omics and systems biology can contribute to our understanding and management of IS.
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Affiliation(s)
- Wentao Li
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
| | - Chongyu Shao
- School of Life Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
| | - Huifen Zhou
- School of Life Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
| | - Haixia Du
- School of Life Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
| | - Haiyang Chen
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
| | - Haitong Wan
- School of Life Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
| | - Yu He
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
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9
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Lu C, Liu C, Mei D, Yu M, Bai J, Bao X, Wang M, Fu K, Yi X, Ge W, Shen J, Peng Y, Xu W. Comprehensive metabolomic characterization of atrial fibrillation. Front Cardiovasc Med 2022; 9:911845. [PMID: 36003904 PMCID: PMC9393302 DOI: 10.3389/fcvm.2022.911845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 07/12/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundUsing human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.ObjectivesBy investigating disturbed metabolic pathways, we could evaluate the diagnostic value of biomarkers based on metabolomics for different types of AF.MethodsA cohort of 363 patients was enrolled and divided into a discovery and validation set. Patients underwent an electrocardiogram (ECG) for suspected AF. Groups were divided as follows: healthy individuals (Control), suspected AF (Sus-AF), first diagnosed AF (Fir-AF), paroxysmal AF (Par-AF), persistent AF (Per-AF), and AF causing a cardiogenic ischemic stroke (Car-AF). Serum metabolomic profiles were determined by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Metabolomic variables were analyzed with clinical information to identify relevant diagnostic biomarkers.ResultsThe metabolic disorders were characterized by 16 cross-comparisons. We focused on comparing all of the types of AF (All-AFs) plus Car-AF vs. Control, All-AFs vs. Car-AF, Par-AF vs. Control, and Par-AF vs. Per-AF. Then, 117 and 94 metabolites were identified by GC/MS and LC-QTOF-MS, respectively. The essential altered metabolic pathways during AF progression included D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, etc. For differential diagnosis, the area under the curve (AUC) of specific metabolomic biomarkers ranged from 0.8237 to 0.9890 during the discovery phase, and the predictive values in the validation cohort were 78.8–90.2%.ConclusionsSerum metabolomics is a powerful way to identify metabolic disturbances. Differences in small–molecule metabolites may serve as biomarkers for AF onset, progression, and differential diagnosis.
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10
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Irvine HJ, Acharjee A, Wolcott Z, Ament Z, Hinson HE, Molyneaux BJ, Simard JM, Sheth KN, Kimberly WT. Hypoxanthine is a pharmacodynamic marker of ischemic brain edema modified by glibenclamide. Cell Rep Med 2022; 3:100654. [PMID: 35700741 PMCID: PMC9244997 DOI: 10.1016/j.xcrm.2022.100654] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 03/16/2022] [Accepted: 05/17/2022] [Indexed: 11/13/2022]
Abstract
Brain edema after a large stroke causes significant morbidity and mortality. Here, we seek to identify pharmacodynamic markers of edema that are modified by intravenous (i.v.) glibenclamide (glyburide; BIIB093) treatment. Using metabolomic profiling of 399 plasma samples from patients enrolled in the phase 2 Glyburide Advantage in Malignant Edema and Stroke (GAMES)-RP trial, 152 analytes are measured using liquid chromatography-tandem mass spectrometry. Associations with midline shift (MLS) and the matrix metalloproteinase-9 (MMP-9) level that are further modified by glibenclamide treatment are compared with placebo. Hypoxanthine is the only measured metabolite that associates with MLS and MMP-9. In sensitivity analyses, greater hypoxanthine levels also associate with increased net water uptake (NWU), as measured on serial head computed tomography (CT) scans. Finally, we find that treatment with i.v. glibenclamide reduces plasma hypoxanthine levels across all post-treatment time points. Hypoxanthine, which has been previously linked to inflammation, is a biomarker of brain edema and a treatment response marker of i.v. glibenclamide treatment.
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Affiliation(s)
- Hannah J Irvine
- Division of Neurocritical Care and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Department of Neurology, NYU Langone Health, New York, NY 10016, USA
| | - Animesh Acharjee
- College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham B15 2TT, UK; Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham B15 2TT, UK; NIHR Surgical Reconstruction and Microbiology Research Centre, Birmingham B15 2TT, UK
| | - Zoe Wolcott
- Division of Neurocritical Care and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Zsuzsanna Ament
- Division of Neurocritical Care and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - H E Hinson
- Department of Neurology, Oregon Health Sciences University, Portland, OR 97239, USA
| | - Bradley J Molyneaux
- Division of Neurocritical Care, Department of Neurology, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - J Marc Simard
- Department of Neurosurgery, University of Maryland, Baltimore, MD 21201, USA
| | - Kevin N Sheth
- Division of Neurocritical Care, Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - W Taylor Kimberly
- Division of Neurocritical Care and Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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11
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Edlow BL, Bodien YG, Baxter T, Belanger H, Cali R, Deary K, Fischl B, Foulkes AS, Gilmore N, Greve DN, Hooker JM, Huang SY, Kelemen JN, Kimberly WT, Maffei C, Masood M, Perl D, Polimeni JR, Rosen BR, Tromly S, Tseng CEJ, Yao EF, Zurcher NR, Mac Donald CL, Dams-O'Connor K. Long-Term Effects of Repeated Blast Exposure in United States Special Operations Forces Personnel: A Pilot Study Protocol. J Neurotrauma 2022; 39:1391-1407. [PMID: 35620901 PMCID: PMC9529318 DOI: 10.1089/neu.2022.0030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Emerging evidence suggests that repeated blast exposure (RBE) is associated with brain injury in military personnel. United States (U.S.) Special Operations Forces (SOF) personnel experience high rates of blast exposure during training and combat, but the effects of low-level RBE on brain structure and function in SOF have not been comprehensively characterized. Further, the pathophysiological link between RBE-related brain injuries and cognitive, behavioral, and physical symptoms has not been fully elucidated. We present a protocol for an observational pilot study, Long-Term Effects of Repeated Blast Exposure in U.S. SOF Personnel (ReBlast). In this exploratory study, 30 active-duty SOF personnel with RBE will participate in a comprehensive evaluation of: 1) brain network structure and function using Connectome magnetic resonance imaging (MRI) and 7 Tesla MRI; 2) neuroinflammation and tau deposition using positron emission tomography; 3) blood proteomics and metabolomics; 4) behavioral and physical symptoms using self-report measures; and 5) cognition using a battery of conventional and digitized assessments designed to detect subtle deficits in otherwise high-performing individuals. We will identify clinical, neuroimaging, and blood-based phenotypes that are associated with level of RBE, as measured by the Generalized Blast Exposure Value. Candidate biomarkers of RBE-related brain injury will inform the design of a subsequent study that will test a diagnostic assessment battery for detecting RBE-related brain injury. Ultimately, we anticipate that the ReBlast study will facilitate the development of interventions to optimize the brain health, quality of life, and battle readiness of U.S. SOF personnel.
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Affiliation(s)
- Brian L Edlow
- Harvard Medical School, 1811, 175 Cambridge Street - Suite 300, Boston, Massachusetts, United States, 02115.,Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Yelena G Bodien
- Massachusetts General Hospital, 2348, Department of Neurology, 101 Merrimac, Boston, Massachusetts, United States, 02114;
| | - Timothy Baxter
- University of South Florida, 7831, Institute for Applied Engineering, Tampa, Florida, United States;
| | - Heather Belanger
- University of South Florida, 7831, Department of Psychiatry and Behavioral Neurosciences, Tampa, Florida, United States;
| | - Ryan Cali
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Katryna Deary
- Navy SEAL Foundation, Virginia Beach, Virginia, United States;
| | - Bruce Fischl
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Room 2301, 149 13th Street, Charlestown, Massachusetts, United States, 02129-2020.,Massachusetts General Hospital;
| | - Andrea S Foulkes
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Natalie Gilmore
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Douglas N Greve
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Jacob M Hooker
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Susie Y Huang
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Jessica N Kelemen
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - W Taylor Kimberly
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Chiara Maffei
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Maryam Masood
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Daniel Perl
- Uniformed Services University of the Health Sciences, 1685, Pathology, 4301 Jones Bridge Road, Room B3138, Bethesda, Maryland, United States, 20814;
| | - Jonathan R Polimeni
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Bruce R Rosen
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States;
| | - Samantha Tromly
- University of South Florida, 7831, Institute for Applied Engineering, Tampa, Florida, United States;
| | - Chieh-En J Tseng
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Eveline F Yao
- United States Special Operations Command, Office of the Surgeon General, MacDill Air Force Base, United States;
| | - Nicole R Zurcher
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Christine L Mac Donald
- University of Washington, 7284, Department of Neurological Surgery, Seattle, Washington, United States;
| | - Kristen Dams-O'Connor
- Icahn School of Medicine at Mount Sinai, 5925, Rehabilitation Medicine, One Gustave Levy Place, Box 1163, New York, New York, United States, 10029; kristen.dams-o'
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12
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Ament Z, Patki A, Chaudhary N, Bhave VM, Garcia Guarniz AL, Gao Y, Gerszten RE, Correa A, Judd SE, Cushman M, Long DL, Irvin MR, Kimberly WT. Nucleosides Associated With Incident Ischemic Stroke in the REGARDS and JHS Cohorts. Neurology 2022; 98:e2097-e2107. [PMID: 35264422 DOI: 10.1212/wnl.0000000000200262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 02/04/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Both genetic and environmental factors contribute to stroke risk. We sought to identify novel metabolites associated with incident stroke in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort and determine whether they reflected genetic or environmental variation. METHODS This was a stroke case-cohort observational study nested in REGARDS. Cases were defined as incident stroke and metabolomic profiles were compared to a randomly selected control cohort. In baseline plasma samples, 162 metabolites were measured using liquid chromatography-tandem mass spectrometry. Cox proportional hazards models were adjusted for age, sex, race, and age by race in the base model. Fully adjusted models included traditional stroke risk factors. Mediation analyses conducted for these stroke risk factors used the metabolite as mediator. Genome-wide associations with the leading candidate metabolites were calculated using array data. Replication analyses in the Jackson Heart Study (JHS) were conducted using random effects meta-analysis. RESULTS There were 2,043 participants who were followed over an average period of 7.1 years, including 1,075 stroke cases and 968 random controls. Nine metabolites were associated with stroke in the base model, 8 of which were measured and remained significant in meta-analysis with JHS. In the fully adjusted model in REGARDS, guanosine (hazard ratio [HR] 1.34, 95% CI 1.18-1.53; p = 7.26 × 10-6) and pseudouridine (HR 1.28, 95% CI 1.13-1.45; p = 1.03 × 10-4) were associated with incident ischemic stroke following Bonferroni adjustment. Guanosine also partially mediated the relationship between hypertension and stroke (17.6%) and pseudouridine did not mediate any risk factor. Genome-wide association analysis identified loci rs34631560 and rs34631560 associated with pseudouridine, but these did not explain the association of pseudouridine with stroke. DISCUSSION Guanosine and pseudouridine are nucleosides associated with incident ischemic stroke independently of other risk factors. Genetic and mediation analyses suggest that environmental exposures rather than genetic variation link nucleoside levels to stroke risk. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that guanosine and pseudouridine are associated with incident stroke.
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Affiliation(s)
- Zsuzsanna Ament
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Amit Patki
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Ninad Chaudhary
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Varun M Bhave
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Ana-Lucia Garcia Guarniz
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Yan Gao
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Robert E Gerszten
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Adolfo Correa
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Suzanne E Judd
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - Mary Cushman
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - D Leann Long
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - M Ryan Irvin
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
| | - W Taylor Kimberly
- From the Center for Genomic Medicine, Harvard Medical School (Z.A., W.T.K.), and Department of Neurology (Z.A., A.-L.G.G., W.T.K.), Massachusetts General Hospital, Boston; Departments of Epidemiology (A.P., N.C., R.M.I.) and Biostatistics (S.E.J., L.L.), School of Public Health, University of Alabama at Birmingham; Harvard Medical School (V.M.B.), Boston, MA; The Jackson Heart Study (Y.G., A.C.), University of Mississippi Medical Center, Jackson; Department of Medicine (R.E.G.), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Medicine (M.C.), Larner College of Medicine at the University of Vermont, Burlington
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13
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Bulló M, Papandreou C, García-Gavilán J, Ruiz-Canela M, Li J, Guasch-Ferré M, Toledo E, Clish C, Corella D, Estruch R, Ros E, Fitó M, Lee CH, Pierce K, Razquin C, Arós F, Serra-Majem L, Liang L, Martínez-González MA, Hu FB, Salas-Salvadó J. Tricarboxylic acid cycle related-metabolites and risk of atrial fibrillation and heart failure. Metabolism 2021; 125:154915. [PMID: 34678258 PMCID: PMC9206868 DOI: 10.1016/j.metabol.2021.154915] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/28/2021] [Accepted: 10/14/2021] [Indexed: 01/01/2023]
Abstract
BACKGROUND Tricarboxylic acid (TCA) cycle deregulation may predispose to cardiovascular diseases, but the role of TCA cycle-related metabolites in the development of atrial fibrillation (AF) and heart failure (HF) remains unexplored. This study sought to investigate the association of TCA cycle-related metabolites with risk of AF and HF. METHODS We used two nested case-control studies within the PREDIMED study. During a mean follow-up for about 10 years, 512 AF and 334 HF incident cases matched by age (±5 years), sex and recruitment center to 616 controls and 433 controls, respectively, were included in this study. Baseline plasma levels of citrate, aconitate, isocitrate, succinate, malate and d/l-2-hydroxyglutarate were measured with liquid chromatography-tandem mass spectrometry. Multivariable conditional logistic regression models were fitted to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for metabolites and the risk of AF or HF. Potential confounders included smoking, family history of premature coronary heart disease, physical activity, alcohol intake, body mass index, intervention groups, dyslipidemia, hypertension, type 2 diabetes and medication use. RESULTS Comparing extreme quartiles of metabolites, elevated levels of succinate, malate, citrate and d/l-2-hydroxyglutarate were associated with a higher risk of AF [ORQ4 vs. Q1 (95% CI): 1.80 (1.21-2.67), 2.13 (1.45-3.13), 1.87 (1.25-2.81) and 1.95 (1.31-2.90), respectively]. One SD increase in aconitate was directly associated with AF risk [OR (95% CI): 1.16 (1.01-1.34)]. The corresponding ORs (95% CI) for HF comparing extreme quartiles of malate, aconitate, isocitrate and d/l-2-hydroxyglutarate were 2.15 (1.29-3.56), 2.16 (1.25-3.72), 2.63 (1.56-4.44) and 1.82 (1.10-3.04), respectively. These associations were confirmed in an internal validation, except for aconitate and AF. CONCLUSION These findings underscore the potential role of the TCA cycle in the pathogenesis of cardiac outcomes.
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Affiliation(s)
- Mònica Bulló
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Reus, Spain
| | - Christopher Papandreou
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Reus, Spain
| | - Jesus García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Reus, Spain
| | - Miguel Ruiz-Canela
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA
| | - Estefanía Toledo
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Clary Clish
- Broad Institute of MIT and Harvard University, Cambridge, MA, USA
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramon Estruch
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Department of Endocrinology and Nutrition Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Emilio Ros
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Lipid Clinic, Department of Endocrinology and Nutrition Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular and Nutrition Research Group, Institut de Recerca Hospital del Mar, Barcelona, Spain
| | - Chih-Hao Lee
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Molecular Metabolism (C.-H.L.), Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kerry Pierce
- Broad Institute of MIT and Harvard University, Cambridge, MA, USA
| | - Cristina Razquin
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain
| | - Fernando Arós
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Cardiology, University Hospital of Alava, Vitoria, Spain
| | - Lluís Serra-Majem
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Institute of Health Sciences IUNICS, University of Balearic Islands and Hospital Son Espases, Palma de Mallorca, Spain
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Statistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Miguel A Martínez-González
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Navarra, Spain; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division for Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Statistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; University Hospital of Sant Joan de Reus, Nutrition Unit, Reus, Spain.
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14
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Chen J, Gong J, Chen H, Li X, Wang L, Qian X, Zhou K, Wang T, Jiang S, Li L, Li S. Ischemic stroke induces cardiac dysfunction and alters transcriptome profile in mice. BMC Genomics 2021; 22:641. [PMID: 34481466 PMCID: PMC8418010 DOI: 10.1186/s12864-021-07938-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 08/14/2021] [Indexed: 11/21/2022] Open
Abstract
Background Stroke can induce cardiac dysfunction in the absence of primary cardiac disease; however, the mechanisms underlying the interaction between the neurological deficits and the heart are poorly understood. The objective of this study was to investigate the effects of stroke on cardiac function and to identify the transcriptome characteristics of the heart. Results Stroke significantly decreased heart weight/tibia length ratio and cardiomyocyte cross-sectional areas and increased atrogin-1 and the E3 ubiquitin ligase MuRF-1, indicating myocardial atrophy in MCAO-induced mouse hearts. RNA sequencing of mRNA revealed 383 differentially expressed genes (DEGs) in MCAO myocardium, of which 221 were downregulated and 162 upregulated. Grouping of DEGs based on biological function and quantitative PCR validation indicated that suppressed immune response and collagen synthesis and altered activity of oxidoreductase, peptidase, and endopeptidase may be involved in MCAO-induced cardiomyopathy. The DEGs were mainly distributed in the membrane or extracellular region of cardiomyocytes and acted as potential mediators of stroke-induced cardiac dysregulation involved in cardiac atrophy. Conclusion Stroke induced a unique transcriptome response in the myocardium and resulted in immediate cardiac atrophy and dysfunction. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07938-y.
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Affiliation(s)
- Jie Chen
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Jiahong Gong
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Haili Chen
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Xuqing Li
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Li Wang
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Xiaoli Qian
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Kecheng Zhou
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Ting Wang
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Songhe Jiang
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China.,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Lei Li
- Institute of Cardiovascular Development and Translational Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shengcun Li
- Rehabilitation Medicine Center, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China. .,Integrative & Optimized Medicine Research center, China-USA Institute for Acupuncture and Rehabilitation, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China. .,Institute of Cardiovascular Development and Translational Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
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15
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EphA4 is highly expressed in the atria of heart and its deletion leads to atrial hypertrophy and electrocardiographic abnormalities in rats. Life Sci 2021; 278:119595. [PMID: 33974931 DOI: 10.1016/j.lfs.2021.119595] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 04/25/2021] [Accepted: 05/03/2021] [Indexed: 01/12/2023]
Abstract
AIMS EphA4 is a member of the Eph receptor family, and expressed mainly in central nervous system (CNS), which is involved in CNS development and multiple diseases. Due to the variability in EphA4 expression, we wondered if EphA4 is expressed in other tissues, and what role does EphA4 play? MATERIALS AND METHODS We generated an EphA4 knockout (KO) rat line with red fluorescent marker protein encoded by the mCherry cassette inserted downstream of the EphA4 promoter as a reporter. Using this system, we observed high expression of EphA4 in the heart atria and in the brain. KEY FINDINGS EphaA4 KO rats (EphA4-/-) developed obvious atrial hypertrophy with an increased atria-to-heart weight ratio and atrial cardiomyocyte cross-sectional area at six months of age. EphA4-/- rats had reduced atrial end diastolic volume (EDV), atrial ejection fraction (EF) and left ventricular EF. They also exhibited increased amplitude of QRS complexes and QT intervals, with invisible p waves. RNA sequencing revealed that EphA4 KO altered the transcription of multiple genes involved in regulation of transcription and translation, ion binding, metabolism and cell adhesion. Deletion of EphA4 reduced IGF1 mRNA and protein expression, which is involved in cardiac remodeling. SIGNIFICANCE Our data demonstrated that EphA4 was highly expressed in the atria and its deletion caused atrial dysfunction. Our findings also suggested that the EphA4 KO rat could be a potential model for studies on atrial remodeling.
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16
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Ament Z, Bevers MB, Wolcott Z, Kimberly WT, Acharjee A. Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke. Transl Stroke Res 2021; 12:293-302. [PMID: 33067777 PMCID: PMC7933067 DOI: 10.1007/s12975-020-00862-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 08/31/2020] [Accepted: 10/04/2020] [Indexed: 02/06/2023]
Abstract
Hyperglycemia is a feature of worse brain injury after acute ischemic stroke, but the underlying metabolic changes and the link to cytotoxic brain injury are not fully understood. In this observational study, we applied regression and machine learning classification analyses to identify metabolites associated with hyperglycemia and a neuroimaging proxy for cytotoxic brain injury. Metabolomics and lipidomics were carried out using liquid chromatography-tandem mass spectrometry in admission plasma samples from 381 patients presenting with an acute stroke. Glucose was measured by a central clinical laboratory, and a subgroup of patients (n = 201) had apparent diffusion coefficient (ADC) imaging quantified on magnetic resonance imaging (MRI) to estimate cytotoxic injury. Uric acid was the leading metabolite in univariate analysis of both hyperglycemia (OR 19.6, 95% CI 8.6-44.7, P = 1.44 × 10-12) and ADC (OR 5.3, 95% CI 2.2-13.0, P = 2.42 × 10-4). To further prioritize model features and account for non-linear correlation structure, a random forest machine learning algorithm was applied to separately model hyperglycemia and ADC. The statistical techniques used have identified uric acid and gluconic acids as leading candidate markers common to all models (R2 = 68%, P = 2.2 × 10-10 for uric acid; R2 = 15%, P = 8.09 × 10-10 for gluconic acid). Both uric acid and gluconic acid were associated with hyperglycemia and cytotoxic brain injury. Both metabolites are linked to oxidative stress, which highlights two candidate targets for limiting brain injury after stroke.
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Affiliation(s)
- Zsuzsanna Ament
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street, Boston, MA, 02114, USA
- Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, 55 Fruit Street, Lunder 644, Boston, MA, 02114, USA
| | - Matthew B Bevers
- Division of Stroke, Cerebrovascular and Crital Care Neurology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA
| | - Zoe Wolcott
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street, Boston, MA, 02114, USA
- Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, 55 Fruit Street, Lunder 644, Boston, MA, 02114, USA
| | - W Taylor Kimberly
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, 185 Cambridge Street, Boston, MA, 02114, USA.
- Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, 55 Fruit Street, Lunder 644, Boston, MA, 02114, USA.
| | - Animesh Acharjee
- College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, UK.
- Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
- NIHR Surgical Reconstruction and Microbiology Research Centre, Birmingham, UK.
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Markus A, Valerie S, Mira K. Promising Biomarker Candidates for Cardioembolic Stroke Etiology. A Brief Narrative Review and Current Opinion. Front Neurol 2021; 12:624930. [PMID: 33716927 PMCID: PMC7947187 DOI: 10.3389/fneur.2021.624930] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 01/11/2021] [Indexed: 01/09/2023] Open
Abstract
Determining the cause of stroke is considered one of the main objectives in evaluating a stroke patient in clinical practice. However, ischemic stroke is a heterogeneous disorder and numerous underlying disorders are implicated in its pathogenesis. Although progress has been made in identifying individual stroke etiology, in many cases underlying mechanisms still remain elusive. Since secondary prevention strategies are tailored toward individual stroke mechanisms, patients whose stroke etiology is unknown may not receive optimal preventive treatment. Cardioembolic stroke is commonly defined as cerebral vessel occlusion by distant embolization arising from thrombus formation in the heart. It accounts for the main proportion of ischemic strokes, and its share to stroke etiology is likely to rise even further in future decades. However, it can be challenging to distinguish cardioembolism from other possible etiologies. As personalized medicine advances, stroke researchers' focus is increasingly drawn to etiology-associated biomarkers. They can provide deeper insight regarding specific stroke mechanisms and can help to unravel previously undetected pathologies. Furthermore, etiology-associated biomarkers could play an important role in guiding future stroke prevention strategies. To achieve this, broad validation of promising candidate biomarkers as well as their implementation in well-designed randomized clinical trials is necessary. This review focuses on the most-promising candidates for diagnosis of cardioembolic stroke. It discusses existing evidence for possible clinical applications of these biomarkers, addresses current challenges, and outlines future perspectives.
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Affiliation(s)
- Arnold Markus
- Department of Neurology, University Hospital of Zurich, Zurich, Switzerland
| | - Schütz Valerie
- Department of Neurology, University Hospital of Zurich, Zurich, Switzerland
| | - Katan Mira
- Department of Neurology, University Hospital of Zurich, Zurich, Switzerland
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18
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Liu J, Zhong L, Guo R. The Role of Posttranslational Modification and Mitochondrial Quality Control in Cardiovascular Diseases. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2021; 2021:6635836. [PMID: 33680284 PMCID: PMC7910068 DOI: 10.1155/2021/6635836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 01/26/2021] [Accepted: 02/05/2021] [Indexed: 12/31/2022]
Abstract
Cardiovascular disease (CVD) is the leading cause of death in the world. The mechanism behind CVDs has been studied for decades; however, the pathogenesis is still controversial. Mitochondrial homeostasis plays an essential role in maintaining the normal function of the cardiovascular system. The alterations of any protein function in mitochondria may induce abnormal mitochondrial quality control and unexpected mitochondrial dysfunction, leading to CVDs. Posttranslational modifications (PTMs) affect protein function by reversibly changing their conformation. This review summarizes how common and novel PTMs influence the development of CVDs by regulating mitochondrial quality control. It provides not only ideas for future research on the mechanism of some types of CVDs but also ideas for CVD treatments with therapeutic potential.
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Affiliation(s)
- Jinlin Liu
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
| | - Li Zhong
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, California, USA
| | - Rui Guo
- College of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
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Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke. Nat Rev Neurol 2020; 16:247-264. [PMID: 32322099 DOI: 10.1038/s41582-020-0350-6] [Citation(s) in RCA: 147] [Impact Index Per Article: 36.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2020] [Indexed: 02/07/2023]
Abstract
Despite many years of research, no biomarkers for stroke are available to use in clinical practice. Progress in high-throughput technologies has provided new opportunities to understand the pathophysiology of this complex disease, and these studies have generated large amounts of data and information at different molecular levels. The integration of these multi-omics data means that thousands of proteins (proteomics), genes (genomics), RNAs (transcriptomics) and metabolites (metabolomics) can be studied simultaneously, revealing interaction networks between the molecular levels. Integrated analysis of multi-omics data will provide useful insight into stroke pathogenesis, identification of therapeutic targets and biomarker discovery. In this Review, we detail current knowledge on the pathology of stroke and the current status of biomarker research in stroke. We summarize how proteomics, metabolomics, transcriptomics and genomics are all contributing to the identification of new candidate biomarkers that could be developed and used in clinical stroke management.
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Gao J, Shao K, Chen X, Li Z, Liu Z, Yu Z, Aung LHH, Wang Y, Li P. The involvement of post-translational modifications in cardiovascular pathologies: Focus on SUMOylation, neddylation, succinylation, and prenylation. J Mol Cell Cardiol 2020; 138:49-58. [DOI: 10.1016/j.yjmcc.2019.11.146] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 11/01/2019] [Accepted: 11/13/2019] [Indexed: 12/12/2022]
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