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Tang Z, Xu B, Wang J, Wang W, Sha S, Sun Y. Novel metabolic biomarkers for the diagnosis of acute ischemic stroke. Biomark Med 2024:1-11. [PMID: 39235047 DOI: 10.1080/17520363.2024.2389033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 07/29/2024] [Indexed: 09/06/2024] Open
Abstract
Aim: To identify novel metabolic biomarkers for patients with acute ischemic stroke (AIS).Methods: The metabolites in the sera of 63 patients with AIS aged 45∼77 years and 60 healthy individuals were analyzed by liquid chromatography (LC)-mass spectrometry (MS)/MS. The efficiency of significantly altered metabolites as biomarkers of AIS was evaluated by ROC curve analysis.Results: Different metabolic profiles were revealed in AIS patients' sera compared with healthy persons. Twelve significantly altered metabolites had an area under the curve (AUC) value >0.80, demonstrating their potential as a biomarker of AIS. Among them, six metabolites are firstly reported to distinguish between AIS patients and healthy individuals.Conclusion: These 12 metabolites can be further researched as potential diagnostic biomarkers of AIS.
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Affiliation(s)
- Zhenzhen Tang
- Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China
| | - Baoli Xu
- Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China
| | - Junjun Wang
- Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China
| | - Wenzhen Wang
- Department of Biochemistry & Molecular Biology, Dalian Medical University, Dalian, 116044, China
| | - Shanshan Sha
- Department of Biochemistry & Molecular Biology, Dalian Medical University, Dalian, 116044, China
| | - Yongjin Sun
- Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, China
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Huang Y, Chen S, Zhang E, Han L. Causal relationship between genetically determined plasma metabolites and stroke: A two sample Mendelian randomization study. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111133. [PMID: 39222903 DOI: 10.1016/j.pnpbp.2024.111133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 08/22/2024] [Accepted: 08/30/2024] [Indexed: 09/04/2024]
Abstract
INTRODUCTION This study investigates the causal relationship between plasma metabolites and stroke. METHOD The primary analytical approach employed was the inverse variance weighted (IVW) method, complemented by the weighted median (WM) and MR Egger methods for Additionally, validation of the identified plasma metabolites was performed using the Steiger test and LD linkage disequilibrium score. Furthermore, the main results were confirmed through data from the UK Biobank. RESULT The IVW analysis revealed the most notable negative association found in X-17335 levels (OR [95 % CI]: 0.82 [0.72, 0.94]). On the other hand, the strongest positive effect was seen in the 5'-homophase (AMP) to phase ratio (OR [95 % CI]: 1.17 [1.03, 1.32]). Moving on to the validation dataset, the most significant positive effect was observed in the 13 HODE+9-HODE levels (OR [95 % CI]: 0.996 [0.993, 0.999]), whereas the most significant negative effect was seen in the Dihydroxide levels (OR [95 % CI]: 1.004 [1.00, 1.007]). Notably, Alpha ketoglutarate levels exhibited strong causal effects in both datasets (OR 0.908 [0.841, 0.981], p = 0.0144). Enrichment analysis highlighted the association of Alpha ketoglutarate levels with five plasma metabolites in metabolic pathways relevant to stroke, specifically Arginine biosynthesis, Butanoate metabolism, Citrate cycle (TCA cycle), Alanine, aspartate, and glutamate metabolism, and Lipid acid metabolism, all linked to oxoglutaric acid. CONCLUSION The discovery dataset showed the most significant positive effect of the 5'-homophase (AMP) to phase ratio, while the validation dataset revealed the most significant positive effect of the 13 HODE+9-HODE levels. Additionally, alpha ketoglutarate may offer a potential protective effect on stroke by influencing five metabolic pathways that intersect with Oxoglutaric acid during the progression of the condition.
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Affiliation(s)
- Yi Huang
- Ningbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang 315010, China; Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province, Ningbo, Zhejiang 315010, China
| | - Siqi Chen
- Ningbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang 315010, China; Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province, Ningbo, Zhejiang 315010, China
| | - Enhao Zhang
- Ningbo Key Laboratory of Nervous System and Brain Function, Department of Neurosurgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang 315010, China; Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province, Ningbo, Zhejiang 315010, China
| | - Liyuan Han
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo 315000, China.
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Karmelić I, Rubić I, Starčević K, Ozretić D, Poljaković Z, Sajko MJ, Kalousek V, Kalanj R, Rešetar Maslov D, Kuleš J, Roje Bedeković M, Sajko T, Rotim K, Mrljak V, Fabris D. Comparative Targeted Metabolomics of Ischemic Stroke: Thrombi and Serum Profiling for the Identification of Stroke-Related Metabolites. Biomedicines 2024; 12:1731. [PMID: 39200198 PMCID: PMC11351249 DOI: 10.3390/biomedicines12081731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 07/23/2024] [Accepted: 07/31/2024] [Indexed: 09/02/2024] Open
Abstract
Ischemic stroke is one of the leading causes of death and permanent disability in the world. Rapid diagnosis and intervention are crucial for reducing its consequences on individuals and societies. Therefore, identifying reliable biomarkers for early detection, prognostics, and therapy can facilitate the early prediction and prevention of stroke. Metabolomics has been shown as a promising tool for biomarker discovery since many post-ischemic metabolites can be found in the plasma or serum of the patient. In this research, we performed a comparative targeted metabolomic analysis of stroke thrombi, stroke patient serums, and healthy control serums in order to determine the alteration in the patients' metabolomes, which might serve as biomarkers for early prediction or stroke prevention. The most statistically altered metabolites characterized in the patient serums compared with the control serums were glutamate and serotonin, followed by phospholipids and triacylglycerols. In stroke thrombi compared with the patients' serums, the most significantly altered metabolites were classified as lipids, with choline-containing phospholipids and sphingomyelins having the highest discriminatory score. The results of this preliminary study could help in understanding the roles of different metabolic changes that occur during thrombosis and cerebral ischemia and possibly suggest new metabolic biomarkers for ischemic stroke.
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Affiliation(s)
- Ivana Karmelić
- Department of Medical Chemistry, Biochemistry and Clinical Chemistry, School of Medicine, University of Zagreb, Šalata 3, 10000 Zagreb, Croatia
| | - Ivana Rubić
- Laboratory of Proteomics, Clinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova 55, 10000 Zagreb, Croatia
| | - Katarina Starčević
- Department of Neurology, University Hospital Centre “Zagreb”, Kišpatićeva 12, 10000 Zagreb, Croatia
| | - David Ozretić
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Centre “Zagreb”, Kišpatićeva 12, 10000 Zagreb, Croatia
| | - Zdravka Poljaković
- Department of Neurology, University Hospital Centre “Zagreb”, Kišpatićeva 12, 10000 Zagreb, Croatia
| | - Mia Jurilj Sajko
- Department of Neurosurgery, University Hospital Centre “Sestre Milosrdnice”, Vinogradska cesta 29, 10000 Zagreb, Croatia
| | - Vladimir Kalousek
- Department of Radiology, University Hospital Centre “Sestre Milosrdnice”, Vinogradska cesta 29, 10000 Zagreb, Croatia
| | - Rafaela Kalanj
- Department of Neurology, University Hospital Centre “Sestre Milosrdnice”, Vinogradska cesta 29, 10000 Zagreb, Croatia
| | - Dina Rešetar Maslov
- Laboratory of Proteomics, Clinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova 55, 10000 Zagreb, Croatia
| | - Josipa Kuleš
- Department of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova 55, 10000 Zagreb, Croatia
| | - Marina Roje Bedeković
- Department of Neurology, University Hospital Centre “Sestre Milosrdnice”, Vinogradska cesta 29, 10000 Zagreb, Croatia
| | - Tomislav Sajko
- Department of Neurosurgery, University Hospital Centre “Sestre Milosrdnice”, Vinogradska cesta 29, 10000 Zagreb, Croatia
| | - Krešimir Rotim
- Department of Neurosurgery, University Hospital Centre “Sestre Milosrdnice”, Vinogradska cesta 29, 10000 Zagreb, Croatia
| | - Vladimir Mrljak
- Laboratory of Proteomics, Clinic for Internal Diseases, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova 55, 10000 Zagreb, Croatia
| | - Dragana Fabris
- Department of Medical Chemistry, Biochemistry and Clinical Chemistry, School of Medicine, University of Zagreb, Šalata 3, 10000 Zagreb, Croatia
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Gusdon AM, Savarraj JPJ, Feng D, Starkman A, Li G, Bodanapally U, Zimmerman W, Ryan AS, Choi HA, Badjatia N. Identification of metabolites associated with preserved muscle volume after aneurysmal subarachnoid hemorrhage due to high protein supplementation and neuromuscular electrical stimulation. Sci Rep 2024; 14:15071. [PMID: 38956192 PMCID: PMC11219968 DOI: 10.1038/s41598-024-64666-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/11/2024] [Indexed: 07/04/2024] Open
Abstract
The INSPIRE randomized clinical trial demonstrated that a high protein diet (HPRO) combined with neuromuscular electrical stimulation (NMES) attenuates muscle atrophy and may improve outcomes after aneurysmal subarachnoid hemorrhage We sought to identify specific metabolites mediating these effects. Blood samples were collected from subjects on admission prior to randomization to either standard of care (SOC; N = 12) or HPRO + NMES (N = 12) and at 7 days. Untargeted metabolomics were performed for each plasma sample. Sparse partial least squared discriminant analysis identified metabolites differentiating each group. Correlation coefficients were calculated between each metabolite and total protein per day and muscle volume. Multivariable models determined associations between metabolites and muscle volume. Unique metabolites (18) were identified differentiating SOC from HPRO + NMES. Of these, 9 had significant positive correlations with protein intake. In multivariable models, N-acetylleucine was significantly associated with preserved temporalis [OR 1.08 (95% CI 1.01, 1.16)] and quadricep [OR 1.08 (95% CI 1.02, 1.15)] muscle volume. Quinolinate was also significantly associated with preserved temporalis [OR 1.05 (95% CI 1.01, 1.09)] and quadricep [OR 1.04 (95% CI 1.00, 1.07)] muscle volume. N-acetylserine and β-hydroxyisovaleroylcarnitine were associated with preserved temporalis or quadricep volume. Metabolites defining HPRO + NMES had strong correlations with protein intake and were associated with preserved muscle volume.
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Affiliation(s)
- Aaron M Gusdon
- Division of Neurocritical Care, Department of Neurosurgery, McGovern School of Medicine, University of Texas Health Science Center, Houston, TX, USA
| | - Jude P J Savarraj
- Division of Neurocritical Care, Department of Neurosurgery, McGovern School of Medicine, University of Texas Health Science Center, Houston, TX, USA
| | - Diana Feng
- Division of Neurocritical Care, Department of Neurosurgery, McGovern School of Medicine, University of Texas Health Science Center, Houston, TX, USA
| | - Adam Starkman
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Guoyan Li
- Division of Gerontology, Geriatric, and Palliative Medicine, Department of Medicine, Geriatric Research, Education, and Clinical Center (GRECC), University of Maryland School of Medicine, Baltimore, MD, USA
| | - Uttam Bodanapally
- Department of Radiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - William Zimmerman
- Program in Trauma, Shock Trauma Neurocritical Care and Department of Neurology, University of Maryland School of Medicine, 22 S. Greene Street, G7K19, Baltimore, MD, 21201, USA
| | - Alice S Ryan
- Division of Gerontology, Geriatric, and Palliative Medicine, Department of Medicine, Geriatric Research, Education, and Clinical Center (GRECC), University of Maryland School of Medicine, Baltimore, MD, USA
| | - Huimahn A Choi
- Division of Neurocritical Care, Department of Neurosurgery, McGovern School of Medicine, University of Texas Health Science Center, Houston, TX, USA
| | - Neeraj Badjatia
- Program in Trauma, Shock Trauma Neurocritical Care and Department of Neurology, University of Maryland School of Medicine, 22 S. Greene Street, G7K19, Baltimore, MD, 21201, USA.
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Niu R, Wang H, Peng R, Wang W, Lin Y, Xiao Y, Zhou L, Xu X, Mu X, Zhang X, He M, Li W, Wu T, Qiu G. Associations of Plasma Metabolites With Risks of Incident Stroke and Its Subtypes in Chinese Adults. J Am Heart Assoc 2024; 13:e033201. [PMID: 38844434 PMCID: PMC11255744 DOI: 10.1161/jaha.123.033201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 05/13/2024] [Indexed: 06/19/2024]
Abstract
BACKGROUND Metabolomics studies have identified various metabolic markers associated with stroke risk, yet much uncertainty persists regarding heterogeneity in these associations between different stroke subtypes. We aimed to examine metabolic profiles associated with incident stroke and its subtypes in Chinese adults. METHODS AND RESULTS We performed a nested case-control study within the Dongfeng-Tongji cohort, including 1029 and 266 incident cases of ischemic stroke (IS) and hemorrhagic stroke (HS), respectively, with a mean follow-up period of 6.1±2.3 years. Fifty-five metabolites in fasting plasma were measured by ultra-high-performance liquid chromatography-mass spectrometry. We examined the associations of metabolites with the risks of total stroke, IS, and HS, with a focus on the comparison of associations of plasma metabolite with IS and HS, using conditional logistic regression. We found that increased levels of asymmetrical/symmetrical dimethylarginine and glutamate were significantly associated with elevated risk of total stroke (odds ratios and 95%, 1.20 [1.08-1.34] and 1.22 [1.09-1.36], respectively; both Benjamini-Hochberg-adjusted P <0.05). When examining stroke subtypes, asymmetrical/symmetrical dimethylarginine was nominally associated with both IS and HS (odds ratios [95% CIs]: 1.16 [1.03-1.31] and 1.39 [1.07-1.81], respectively), while glutamate was associated with only IS (odds ratios [95% CI]: 1.26 [1.11-1.43]). The associations of glutamate with IS risk were significantly stronger among participants with hypertension and diabetes than among those without these diseases (both P for interaction <0.05). CONCLUSIONS This study validated the positive associations of asymmetrical/symmetrical dimethylarginine and glutamate with stroke risk, mainly that of IS, in a Chinese population, and revealed a novel unanimous association of with both IS and HS. Our findings provided potential intervention targets for stroke prevention.
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Affiliation(s)
- Rundong Niu
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Hao Wang
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Rong Peng
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Wei Wang
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yuhui Lin
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yang Xiao
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Lue Zhou
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Xuedan Xu
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Xuanwen Mu
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Xiaomin Zhang
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Meian He
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Wending Li
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Environmental Health SciencesMailman School of Public HealthColumbia UniversityNew YorkNYUSA
| | - Tangchun Wu
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Gaokun Qiu
- Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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Xie Y, Li Y, Zhang J, Chen Y, Ren R, Xiao L, Chen M. Assessing the causal association between human blood metabolites and the risk of gout. Eur J Clin Invest 2024; 54:e14129. [PMID: 37988199 DOI: 10.1111/eci.14129] [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: 07/26/2023] [Revised: 10/25/2023] [Accepted: 11/07/2023] [Indexed: 11/23/2023]
Abstract
BACKGROUND The occurrence of gout is closely related to metabolism, but there is still a lack of evidence on the causal role of metabolites in promoting or preventing gout. METHODS We applied a two-sample Mendelian randomization (MR) analysis to assess the association between 486 serum metabolites and gout using genome-wide association study statistics. The inverse variance weighting method was used to generate the main results, while sensitivity analyses using MR-Egger, weighted median, Cochran's Q test, Egger intercept test, and leave-one-out analysis, were performed to assess the stability and reliability of the results. We also performed a metabolic pathway analysis to identify potential metabolic pathways. RESULTS After screening, 486 metabolites were retained for MR analysis. After screening by IVW and sensitivity analysis, 14 metabolites were identified with causal effect on gout (P < 0.05), among which hexadecanedioate was the most significant candidate metabolite associated with a lower risk of gout (IVW OR = 0.50; 95% CI = 0.38-0.67; P = 1.65 × 10-6 ). Metabolic pathway analysis identified one pathway that may be associated with the disease. CONCLUSION This MR study combining genomics with metabolomics provides a novel insight into the causal role of blood metabolites in the risk of gout, which implies that examination of certain blood metabolites would be a feasible strategy for screening populations with a higher risk of gout.
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Affiliation(s)
- Yufeng Xie
- Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau, China
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Yanfang Li
- The Sixth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Jianmei Zhang
- The Sixth Clinical Medical College, Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Yun Chen
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Rong Ren
- Shenzhen Hospital of Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Lu Xiao
- Zhuhai Campus, Zunyi Medical University, Zhuhai, China
- Key Laboratory of Basic Pharmacology of Ministry of Education and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi Medical University, Zunyi, Guizhou, China
| | - Min Chen
- Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau, China
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He M, Xu C, Yang R, Liu L, Zhou D, Yan S. Causal relationship between human blood metabolites and risk of ischemic stroke: a Mendelian randomization study. Front Genet 2024; 15:1333454. [PMID: 38313676 PMCID: PMC10834680 DOI: 10.3389/fgene.2024.1333454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 01/08/2024] [Indexed: 02/06/2024] Open
Abstract
Background: Ischemic stroke (IS) is a major cause of death and disability worldwide. Previous studies have reported associations between metabolic disorders and IS. However, evidence regarding the causal relationship between blood metabolites and IS lacking. Methods: A two-sample Mendelian randomization analysis (MR) was used to assess the causal relationship between 1,400 serum metabolites and IS. The inverse variance-weighted (IVW) method was employed to estimate the causal effect between exposure and outcome. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode approaches were employed as supplementary comprehensive evaluations of the causal effects between blood metabolites and IS. Tests for pleiotropy and heterogeneity were conducted. Results: After rigorous selection, 23 known and 5 unknown metabolites were identified to be associated with IS. Among the 23 known metabolites, 13 showed significant causal effects with IS based on 2 MR methods, including 5-acetylamino-6-formylamino-3-methyluracil, 1-ribosyl-imidazoleacetate, Behenoylcarnitine (C22), N-acetyltyrosine, and N-acetylputrescine to (N (1) + N (8))-acetate,these five metabolites were positively associated with increased IS risk. Xanthurenate, Glycosyl-N-tricosanoyl-sphingadienine, Orotate, Bilirubin (E,E), Bilirubin degradation product, C17H18N2O, Bilirubin (Z,Z) to androsterone glucuronide, Bilirubin (Z,Z) to etiocholanolone glucuronide, Biliverdin, and Uridine to pseudouridine ratio were associated with decreased IS risk. Conclusion: Among 1,400 blood metabolites, this study identified 23 known metabolites that are significantly associated with IS risk, with 13 being more prominent. The integration of genomics and metabolomics provides important insights for the screening and prevention of IS.
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Affiliation(s)
- Menghao He
- The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
- Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Chun Xu
- Changde College of Science and Technology, Changde, Hunan, China
| | - Renyi Yang
- Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Lijuan Liu
- The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Desheng Zhou
- The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Siyang Yan
- The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
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Zeng J, Zhang R, Zhao T, Wang H, Han L, Pu L, Jiang Y, Xu S, Ren H, Wang C. Plasma lipidomic profiling reveals six candidate biomarkers for the prediction of incident stroke in patients with hypertension. Metabolomics 2024; 20:13. [PMID: 38180633 DOI: 10.1007/s11306-023-02081-z] [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: 07/28/2023] [Accepted: 12/11/2023] [Indexed: 01/06/2024]
Abstract
INTRODUCTION The burden of stroke in patients with hypertension is very high, and its prediction is critical. OBJECTIVES We aimed to use plasma lipidomics profiling to identify lipid biomarkers for predicting incident stroke in patients with hypertension. METHODS This was a nested case-control study. Baseline plasma samples were collected from 30 hypertensive patients with newly developed stroke, 30 matched patients with hypertension, 30 matched patients at high risk of stroke, and 30 matched healthy controls. Lipidomics analysis was performed by ultrahigh-performance liquid chromatography-tandem mass spectrometry, and differential lipid metabolites were screened using multivariate and univariate statistical methods. Machine learning methods (least absolute shrinkage and selection operator, random forest) were used to identify candidate biomarkers for predicting stroke in patients with hypertension. RESULTS Co-expression network analysis revealed that the key molecular alterations of the lipid network in stroke implicate glycerophospholipid metabolism and choline metabolism. Six lipid metabolites were identified as candidate biomarkers by multivariate statistical and machine learning methods, namely phosphatidyl choline(40:3p)(rep), cholesteryl ester(20:5), monoglyceride(29:5), triglyceride(18:0p/18:1/18:1), triglyceride(18:1/18:2/21:0) and coenzyme(q9). The combination of these six lipid biomarkers exhibited good diagnostic and predictive ability, as it could indicate a risk of stroke at an early stage in patients with hypertension (area under the curve = 0.870; 95% confidence interval: 0.783-0.957). CONCLUSIONS We determined lipidomic signatures associated with future stroke development and identified new lipid biomarkers for predicting stroke in patients with hypertension. The biomarkers have translational potential and thus may serve as blood-based biomarkers for predicting hypertensive stroke.
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Affiliation(s)
- Jingjing Zeng
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
- Department of Cardiology, Ningbo No.2 Hospital, Ningbo, 315000, China
| | - Ruijie Zhang
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
| | - Tian Zhao
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
| | - Han Wang
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
| | - Liyuan Han
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
| | - Liyuan Pu
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
| | - Yannan Jiang
- Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Ningbo No.2 Hospital, Ningbo, 315000, China
- Center for Cardiovascular and Cerebrovascular Epidemiology and Translational Medicine, Ningbo Institute of Life and Health Industry, Guoke Ningbo Life Science and Health Industry Research Institute, Ningbo, 315000, China
| | - Shan Xu
- Department of Non-Communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, 518000, China
| | - Huiming Ren
- Department of Rehabilitation Medicine, Ningbo No.2 Hospital, Ningbo, 315000, China.
| | - Changyi Wang
- Department of Non-Communicable Disease Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, 518000, China.
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Chiu HH, Lin SY, Zhang CG, Tsai CC, Tang SC, Kuo CH. A comparative study of plasma and dried blood spot metabolomics and its application to diabetes mellitus. Clin Chim Acta 2024; 552:117655. [PMID: 37977234 DOI: 10.1016/j.cca.2023.117655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 11/03/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023]
Abstract
Metabolomics has become a promising method for understanding pathological mechanisms. Plasma (PLS) is the most common sample type used for metabolomics studies, and dried blood spot (DBS) sampling has been regarded as a good strategy due to its unique characteristics. However, how results obtained from DBS can be correlated to results obtained from PLS remains unclear. To bridge the results and to investigate the feasibility of using DBS to study metabolomics, we performed a comparative study using 64 paired PLS and DBS samples. The number of features extracted from the two different sample types was investigated. The concentration correlations of the identified metabolites between the DBS and PLS were individually studied. Approximately 47 % showed a strong correlation, 19 % showed a moderate correlation, and 34 % showed a low or even negligible correlation. Finally, we applied both PLS- and DBS-based metabolomics to explore the dysregulated metabolites in diabetes mellitus (DM) patients. Thirty-two non-DM subjects and 32 DM patients were enrolled, and 2 significant metabolites were found in both PLS and DBS samples. In summary, detailed correlation information between PLS and DBS metabolites was first explored in this study, and it is anticipated that these results could facilitate future applications in DBS-based metabolomics.
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Affiliation(s)
- Huai-Hsuan Chiu
- Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan; School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Shin-Yi Lin
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Pharmacy, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Guang Zhang
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chuan-Ching Tsai
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Sung-Chun Tang
- Stroke Center and Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Ching-Hua Kuo
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; The Metabolomics Core Laboratory, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
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10
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Li W, Li SG, Li L, Yang LJ, Li ZS, Li X, Ye AY, Xiong Y, Zhang Y, Xiong YY. Soyasaponin I alleviates hypertensive intracerebral hemorrhage by inhibiting the renin-angiotensin-aldosterone system. Clin Exp Hypertens 2023; 45:2177667. [PMID: 36809885 DOI: 10.1080/10641963.2023.2177667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
BACKGROUND Hypertensive intracerebral hemorrhage (HICH) is a life-threatening disease and lacks effective treatments. Previous studies have confirmed that metabolic profiles altered after ischemic stroke, but how brain metabolism changes after HICH was unclear. This study aimed to explore the metabolic profiles after HICH and the therapeutic effects of soyasaponin I on HICH. METHODS HICH model was established first. Hematoxylin and eosin staining was used to estimate the pathological changes after HICH. Western blot and Evans blue extravasation assay were applied to determine the integrity of the blood-brain barrier (BBB). Enzyme-linked immunosorbent assay was used to detect the activation of the renin-angiotensin-aldosterone system (RAAS). Next, liquid chromatography-mass spectrometry-untargeted metabolomics was utilized to analyze the metabolic profiles of brain tissues after HICH. Finally, soyasaponin I was administered to HICH rats, and the severity of HICH and activation of the RAAS were further assessed. RESULTS We successfully constructed HICH model. HICH significantly impaired BBB integrity and activated RAAS. HICH increased PE(14:0/24:1(15Z)), arachidonoyl serinol, PS(18:0/22:6(4Z, 7Z, 10Z, 13Z, 16Z, and 19Z)), PS(20:1(11Z)/20:5(5Z, 8Z, 11Z, 14Z, and 17Z)), glucose 1-phosphate, etc., in the brain, whereas decreased creatine, tripamide, D-N-(carboxyacetyl)alanine, N-acetylaspartate, N-acetylaspartylglutamic acid, and so on in the hemorrhagic hemisphere. Cerebral soyasaponin I was found to be downregulated after HICH and supplementation of soyasaponin I inactivated the RAAS and alleviated HICH. CONCLUSION The metabolic profiles of the brains changed after HICH. Soyasaponin I alleviated HICH via inhibiting the RAAS and may serve as an effective drug for the treatment of HICH in the future.
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Affiliation(s)
- Wei Li
- Department of Neurosurgery, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Shao-Guang Li
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Lan Li
- Department of Neurosurgery, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Li-Jian Yang
- Department of Neurosurgery, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Zeng-Shi Li
- Department of Neurosurgery, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - Xi Li
- Department of Neurosurgery, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China
| | - An-Yuan Ye
- Department of Neurosurgery, People's Hospital of Yiyang, Yiyang, China
| | - Yang Xiong
- Department of Comprehensive Intervention, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yi Zhang
- Department of Neurology, People's Hospital of Wuning County, Wuning, China
| | - Yuan-Yuan Xiong
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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11
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Gusdon AM, Savarraj JP, Feng D, Starkman A, Li G, Bodanapally U, Zimmerman WD, Ryan AS, Choi HA, Badjatia N. High-Protein Supplementation and Neuromuscular Electric Stimulation after Aneurysmal Subarachnoid Hemorrhage Increases Systemic Amino Acid and Oxidative Metabolism: A Plasma Metabolomics Approach. RESEARCH SQUARE 2023:rs.3.rs-3600439. [PMID: 38014126 PMCID: PMC10680941 DOI: 10.21203/rs.3.rs-3600439/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Background The INSPIRE randomized clinical trial demonstrated that a high protein diet (HPRO) combined with neuromuscular electrical stimulation (NMES) attenuates muscle atrophy and may improve functional outcomes after aSAH. Using an untargeted metabolomics approach, we sought to identify specific metabolites mediating these effects. Methods Blood samples were collected from subjects on admission prior to randomization to either standard of care (SOC; N=12) or HPRO+NMES (N=12) and at 7 days as part of the INSPIRE protocol. Untargeted metabolomics were performed for each plasma sample. Paired fold changes were calculated for each metabolite among subjects in the HPRO+NMES group at baseline and 7 days after intervention. Changes in metabolites from baseline to 7 days were compared for the HPRO+NMES and SOC groups. Sparse partial least squared discriminant analysis (sPLS-DA) identified metabolites discriminating each group. Pearson's correlation coefficients were calculated between each metabolite and total protein per day, nitrogen balance, and muscle volume Multivariable models were developed to determine associations between each metabolite and muscle volume. Results A total of 18 unique metabolites were identified including pre and post treatment and differentiating SOC vs HPRO+NMES. Of these, 9 had significant positive correlations with protein intake: N-acetylserine (ρ=0.61, P =1.56x10 -3 ), N-acetylleucine (ρ=0.58, P =2.97x10 -3 ), β-hydroxyisovaleroylcarnitine (ρ=0.53, P =8.35x10 -3 ), tiglyl carnitine (ρ=0.48, P =0.0168), N-acetylisoleucine (ρ=0.48, P =0.0183), N-acetylthreonine (ρ=0.47, P =0.0218), N-acetylkynurenine (ρ=0.45, P =0.0263), N-acetylvaline (ρ=0.44, P =0.0306), and urea (ρ=0.43, P =0.0381). In multivariable regression models, N-acetylleucine was significantly associated with preserved temporalis [OR 1.08 (95%CI 1.01, 1.16)] and quadricep [OR 1.08 (95%CI 1.02, 1.15)] muscle volume. Quinolinate was also significantly associated with preserved temporalis [OR 1.05 (95%CI 1.01, 1.09)] and quadricep [OR 1.04 (95%CI 1.00, 1.07)] muscle volume. N-acetylserine, N-acetylcitrulline, and b-hydroxyisovaleroylcarnitine were also associated with preserved temporalis or quadricep volume. Conclusions Metabolites defining the HPRO+NMES intervention mainly consisted of amino acid derivatives. These metabolites had strong correlations with protein intake and were associated with preserved muscle volume.
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12
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Oliveira N, Sousa A, Amaral AP, Graça G, Verde I. Searching for Metabolic Markers of Stroke in Human Plasma via NMR Analysis. Int J Mol Sci 2023; 24:16173. [PMID: 38003362 PMCID: PMC10671802 DOI: 10.3390/ijms242216173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/31/2023] [Accepted: 11/08/2023] [Indexed: 11/26/2023] Open
Abstract
More than 12 million people around the world suffer a stroke every year, one every 3 s. Stroke has a variety of causes and is often the result of a complex interaction of risk factors related to age, genetics, gender, lifestyle, and some cardiovascular and metabolic diseases. Despite this evidence, it is not possible to prevent the onset of stroke. The use of innovative methods for metabolite analysis has been explored in the last years to detect new stroke biomarkers. We use NMR spectroscopy to identify small molecule variations between different stages of stroke risk. The Framingham Stroke Risk Score was used in people over 63 years of age living in long-term care facilities (LTCF) to calculate the probability of suffering a stroke. Using this parameter, three study groups were formed: low stroke risk (LSR, control), moderate stroke risk (MSR) and high stroke risk (HSR). Univariate statistical analysis showed seven metabolites with increasing plasma levels across different stroke risk groups, from LSR to HSR: isoleucine, asparagine, formate, creatinine, dimethylsulfone and two unidentified molecules, which we termed "unknown-1" and "unknown-3". These metabolic markers can be used for early detection and to detect increasing stages of stroke risk more efficiently.
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Affiliation(s)
- Nádia Oliveira
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
| | - Adriana Sousa
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
| | - Ana Paula Amaral
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
| | - Gonçalo Graça
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Ignacio Verde
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
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13
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Yu X, Luo Y, Yang L, Duan X. Plasma metabonomic study on the effect of Para‑hydroxybenzaldehyde intervention in a rat model of transient focal cerebral ischemia. Mol Med Rep 2023; 28:224. [PMID: 37800608 PMCID: PMC10577806 DOI: 10.3892/mmr.2023.13111] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 06/28/2023] [Indexed: 10/07/2023] Open
Abstract
Gastrodia elata Blume has been widely used to treat various central and peripheral nerve diseases, and Para‑hydroxybenzaldehyde (PHBA) is one of the indicated components suggested to provide a neuroprotective effect. In our previous, it was shown that PHBA protected mitochondria against cerebral ischemia‑reperfusion (I/R) injury in rats. In the present study, how PHBA regulated the metabolic mechanism in blood following cerebral I/R was assessed to identify an effective therapeutic target for the prevention and treatment of ischemic stroke (IS). First, a rat model of cerebral ischemia‑reperfusion injury was established via middle cerebral artery occlusion/reperfusion (MCAO/R). The therapeutic effect of PHBA on brain I/R was evaluated by assessing the neurological function score, triphenyl tetrazolium chloride, hematoxylin and eosin, and Nissl staining. Next, a non‑targeted metabolomic based on high‑performance liquid chromatography quadrupole time‑of‑flight mass spectrometry was established to identify differential metabolites. Finally, a targeted metabolic spectrum was analyzed and the potential therapeutic targets were verified by Western blotting. The results showed that the neurological function score, cerebral infarction area, hippocampal morphology, and the number of neurons in the PHBA group were significantly improved compared with the model group. Metabonomic analysis showed that 13 different metabolites were identified between the model and PHBA group, which may be involved in the 'tricarboxylic acid cycle', 'glutathione metabolism', and 'mutual transformation of pentose and glucuronates', amongst others. Among these, the levels of the most significant differential metabolite, dGMP, decreased significantly following PHBA treatment. Western blotting was used to verify the expression of membrane‑associated guanosine kinase PSD‑95 and the subunit of glutamate AMPA receptor GluA1, which significantly increased after PHBA treatment. In addition, it was also found that PHBA increased the expression of the light chain‑3 protein and autophagy effector protein 1, whilst the expression of sequestosome‑1 decreased, indicating that PHBA promoted autophagy. Similarly, in TUNEL staining and detection of apoptosis‑related proteins, it was found that MCAO/R upregulated the expression of Bax and cleaved‑caspase‑3 whilst downregulating the expression of Bcl‑2 and increasing the apoptosis of hippocampal neurons; PHBA reversed this situation. These results suggest that cerebral I/R causes postsynaptic dysfunction by disrupting the interaction between PSD‑95 and AMPARs, and the inhibition of the autophagy system eventually leads to the apoptosis of hippocampal neurons.
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Affiliation(s)
- Xinglin Yu
- Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, Yunnan 650500, P.R. China
| | - Yuan Luo
- Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, Yunnan 650500, P.R. China
| | - Liping Yang
- Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, Yunnan 650500, P.R. China
| | - Xiaohua Duan
- Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, Yunnan 650500, P.R. China
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14
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Fuller H, Zhu Y, Nicholas J, Chatelaine HA, Drzymalla EM, Sarvestani AK, Julián-Serrano S, Tahir UA, Sinnott-Armstrong N, Raffield LM, Rahnavard A, Hua X, Shutta KH, Darst BF. Metabolomic epidemiology offers insights into disease aetiology. Nat Metab 2023; 5:1656-1672. [PMID: 37872285 PMCID: PMC11164316 DOI: 10.1038/s42255-023-00903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 09/06/2023] [Indexed: 10/25/2023]
Abstract
Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.
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Affiliation(s)
- Harriett Fuller
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yiwen Zhu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jayna Nicholas
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Haley A Chatelaine
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Emily M Drzymalla
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afrand K Sarvestani
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | | | - Usman A Tahir
- Department of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ali Rahnavard
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Xinwei Hua
- Department of Cardiology, Peking University Third Hospital, Beijing, China
| | - Katherine H Shutta
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Burcu F Darst
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
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15
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Bernard L, Chen J, Kim H, Huang Z, Bazzano L, Qi L, He J, Rao VS, Potts KS, Kelly TN, Wong KE, Steffen LM, Yu B, Rhee EP, Rebholz CM. Serum Metabolomic Markers of Dairy Consumption: Results from the Atherosclerosis Risk in Communities Study and the Bogalusa Heart Study. J Nutr 2023; 153:2994-3002. [PMID: 37541543 PMCID: PMC10613758 DOI: 10.1016/j.tjnut.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/14/2023] [Accepted: 08/01/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND Dairy consumption is related to chronic disease risk; however, the measurement of dairy consumption has largely relied upon self-report. Untargeted metabolomics allows for the identification of objective markers of dietary intake. OBJECTIVES We aimed to identify associations between dietary dairy intake (total dairy, low-fat dairy, and high-fat dairy) and serum metabolites in 2 independent study populations of United States adults. METHODS Dietary intake was assessed with food frequency questionnaires. Multivariable linear regression models were used to estimate cross-sectional associations between dietary intake of dairy and 360 serum metabolites analyzed in 2 subgroups of the Atherosclerosis Risk in Communities study (ARIC; n = 3776). Results from the 2 subgroups were meta-analyzed using fixed effects meta-analysis. Significant meta-analyzed associations in the ARIC study were then tested in the Bogalusa Heart Study (BHS; n = 785). RESULTS In the ARIC study and BHS, the mean age was 54 and 48 years, 61% and 29% were Black, and the mean dairy intake was 1.7 and 1.3 servings/day, respectively. Twenty-nine significant associations between dietary intake of dairy and serum metabolites were identified in the ARIC study (total dairy, n = 14; low-fat dairy, n = 10; high-fat dairy, n = 5). Three associations were also significant in BHS: myristate (14:0) was associated with high-fat dairy, and pantothenate was associated with total dairy and low-fat dairy, but 23 of the 27 associations significant in the ARIC study and tested in BHS were not associated with dairy in BHS. CONCLUSIONS We identified metabolomic associations with dietary intake of dairy, including 3 associations found in 2 independent cohort studies. These results suggest that myristate (14:0) and pantothenate (vitamin B5) are candidate biomarkers of dairy consumption.
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Affiliation(s)
- Lauren Bernard
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Hyunju Kim
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Zhijie Huang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Lydia Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Lu Qi
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Varun S Rao
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
| | - Kaitlin S Potts
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States; Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, United States
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States; Division of Nephrology, Department of Medicine, University of Illinois Chicago, Chicago, IL, United States
| | - Kari E Wong
- Metabolon, Research Triangle Park, Morrisville, NC, United States
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, United States
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, United States
| | - Eugene P Rhee
- Division of Nephrology and Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD, United States.
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16
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Wu M, Du Y, Zhang C, Li Z, Li Q, Qi E, Ruan W, Feng S, Zhou H. Mendelian Randomization Study of Lipid Metabolites Reveals Causal Associations with Heel Bone Mineral Density. Nutrients 2023; 15:4160. [PMID: 37836445 PMCID: PMC10574167 DOI: 10.3390/nu15194160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 09/22/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND Osteoporosis, which is a bone disease, is characterized by low bone mineral density and an increased risk of fractures. The heel bone mineral density is often used as a representative measure of overall bone mineral density. Lipid metabolism, which includes processes such as fatty acid metabolism, glycerol metabolism, inositol metabolism, bile acid metabolism, carnitine metabolism, ketone body metabolism, sterol and steroid metabolism, etc., may have an impact on changes in bone mineral density. While some studies have reported correlations between lipid metabolism and heel bone mineral density, the overall causal relationship between metabolites and heel bone mineral density remains unclear. OBJECTIVE to investigate the causal relationship between lipid metabolites and heel bone mineral density using two-sample Mendelian randomization analysis. METHODS Summary-level data from large-scale genome-wide association studies were extracted to identify genetic variants linked to lipid metabolite levels. These genetic variants were subsequently employed as instrumental variables in Mendelian randomization analysis to estimate the causal effects of each lipid metabolite on heel bone mineral density. Furthermore, metabolites that could potentially be influenced by causal relationships with bone mineral density were extracted from the KEGG and WikiPathways databases. The causal associations between these downstream metabolites and heel bone mineral density were then examined. Lastly, a sensitivity analysis was conducted to evaluate the robustness of the results and address potential sources of bias. RESULTS A total of 130 lipid metabolites were analyzed, and it was found that acetylcarnitine, propionylcarnitine, hexadecanedioate, tetradecanedioate, myo-inositol, 1-arachidonoylglycerophosphorine, 1-linoleoylglycerophoethanolamine, and epiandrosterone sulfate had a causal relationship with heel bone mineral density (p < 0.05). Furthermore, our findings also indicate an absence of causal association between the downstream metabolites associated with the aforementioned metabolites identified in the KEGG and WikiPathways databases and heel bone mineral density. CONCLUSION This work supports the hypothesis that lipid metabolites have an impact on bone health through demonstrating a causal relationship between specific lipid metabolites and heel bone mineral density. This study has significant implications for the development of new strategies to osteoporosis prevention and treatment.
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Affiliation(s)
- Mingxin Wu
- National Spinal Cord Injury International Cooperation Base, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin 300070, China
| | - Yufei Du
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin 300070, China
| | - Chi Zhang
- Department of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250013, China
| | - Zhen Li
- National Spinal Cord Injury International Cooperation Base, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin 300070, China
| | - Qingyang Li
- Department of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250013, China
| | - Enlin Qi
- Department of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250013, China
| | - Wendong Ruan
- National Spinal Cord Injury International Cooperation Base, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin 300070, China
| | - Shiqing Feng
- National Spinal Cord Injury International Cooperation Base, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin 300070, China
- Department of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250013, China
| | - Hengxing Zhou
- National Spinal Cord Injury International Cooperation Base, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin 300070, China
- Department of Orthopaedics, Qilu Hospital of Shandong University, Shandong University Centre for Orthopaedics, Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan 250013, China
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17
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Purroy F, Ois A, Jove M, Arque G, Sol J, Mauri-Capdevila G, Rodriguez-Campello A, Pamplona R, Portero M, Roquer J. Lipidomic signature of stroke recurrence after transient ischemic attack. Sci Rep 2023; 13:13706. [PMID: 37607967 PMCID: PMC10444771 DOI: 10.1038/s41598-023-40838-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 08/17/2023] [Indexed: 08/24/2023] Open
Abstract
While TIA patients have transient symptoms, they should not be underestimated, as they could have an underlying pathology that may lead to a subsequent stroke: stroke recurrence (SR). Previously, it has been described the involvement of lipids in different vascular diseases. The aim of the current study was to perform a lipidomic analysis to identify differences in the lipidomic profile between patients with SR and patients without. Untargeted lipidomic analysis was performed in plasma samples of 460 consecutive TIA patients recruited < 24 h after the onset of symptoms. 37 (8%) patients suffered SR at 90 days. Lipidomic profiling disclosed 7 lipid species differentially expressed between groups: 5 triacylglycerides (TG), 1 diacylglyceride (DG), and 1 alkenyl-PE (plasmalogen) [specifically, TG(56:1), TG(63:0), TG(58:2), TG(50:5), TG(53:7, DG(38:5)) and PE(P-18:0/18:2)]. 6 of these 7 lipid species belonged to the glycerolipid family and a plasmalogen, pointing to bioenergetics pathways, as well as oxidative stress response. In this context, it was proposed the PE(P-18:0/18:2) as potential biomarker of SR condition.The observed changes in lipid patterns suggest pathophysiological mechanisms associated with lipid droplets metabolism and antioxidant protection that is translated to plasma level as consequence of a more intensive or high-risk ischemic condition related to SR.
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Affiliation(s)
- F Purroy
- Clinical Neurosciences Group, Institut de Recerca Biomèdica de Lleida, UdL, Lleida, Spain.
- Stroke Unit, Department of Neurology, Universitat de Lleida, Hospital Universitari Arnau de Vilanova, Avda Rovira Roure 80, 25198, Lleida, Spain.
| | - A Ois
- Department of Neurology, Neurology Neurovascular Research Unit Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - M Jove
- Experimental Medicine Department, Lleida University-Lleida Biomedical Research Institute (UdL-IRBLleida), 25198, Lleida, Spain
| | - G Arque
- Clinical Neurosciences Group, Institut de Recerca Biomèdica de Lleida, UdL, Lleida, Spain
| | - J Sol
- Institut Català de la Salut (ICS), Atenció Primària, Lleida, Spain
- Research Support Unit Lleida, Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Lleida, Spain
| | - G Mauri-Capdevila
- Clinical Neurosciences Group, Institut de Recerca Biomèdica de Lleida, UdL, Lleida, Spain
- Stroke Unit, Department of Neurology, Universitat de Lleida, Hospital Universitari Arnau de Vilanova, Avda Rovira Roure 80, 25198, Lleida, Spain
| | - A Rodriguez-Campello
- Department of Neurology, Neurology Neurovascular Research Unit Hospital del Mar Research Institute (IMIM), Barcelona, Spain
| | - R Pamplona
- Experimental Medicine Department, Lleida University-Lleida Biomedical Research Institute (UdL-IRBLleida), 25198, Lleida, Spain
| | - M Portero
- Experimental Medicine Department, Lleida University-Lleida Biomedical Research Institute (UdL-IRBLleida), 25198, Lleida, Spain
| | - J Roquer
- Department of Neurology, Neurology Neurovascular Research Unit Hospital del Mar Research Institute (IMIM), Barcelona, Spain
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18
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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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19
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Ranea-Robles P, Houten SM. The biochemistry and physiology of long-chain dicarboxylic acid metabolism. Biochem J 2023; 480:607-627. [PMID: 37140888 PMCID: PMC10214252 DOI: 10.1042/bcj20230041] [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: 02/15/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/05/2023]
Abstract
Mitochondrial β-oxidation is the most prominent pathway for fatty acid oxidation but alternative oxidative metabolism exists. Fatty acid ω-oxidation is one of these pathways and forms dicarboxylic acids as products. These dicarboxylic acids are metabolized through peroxisomal β-oxidation representing an alternative pathway, which could potentially limit the toxic effects of fatty acid accumulation. Although dicarboxylic acid metabolism is highly active in liver and kidney, its role in physiology has not been explored in depth. In this review, we summarize the biochemical mechanism of the formation and degradation of dicarboxylic acids through ω- and β-oxidation, respectively. We will discuss the role of dicarboxylic acids in different (patho)physiological states with a particular focus on the role of the intermediates and products generated through peroxisomal β-oxidation. This review is expected to increase the understanding of dicarboxylic acid metabolism and spark future research.
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Affiliation(s)
- Pablo Ranea-Robles
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Sander M Houten
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, U.S.A
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20
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Bernard L, Chen J, Kim H, Wong KE, Steffen LM, Yu B, Boerwinkle E, Rebholz CM. Metabolomics of Dietary Intake of Total, Animal, and Plant Protein: Results from the Atherosclerosis Risk in Communities (ARIC) Study. Curr Dev Nutr 2023; 7:100067. [PMID: 37304852 PMCID: PMC10257224 DOI: 10.1016/j.cdnut.2023.100067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 06/13/2023] Open
Abstract
Background Dietary consumption has traditionally been studied through food intake questionnaires. Metabolomics can be used to identify blood markers of dietary protein that may complement existing dietary assessment tools. Objectives We aimed to identify associations between 3 dietary protein sources (total protein, animal protein, and plant protein) and serum metabolites using data from the Atherosclerosis Risk in Communities Study. Methods Participants' dietary protein intake was derived from a food frequency questionnaire administered by an interviewer, and fasting serum samples were collected at study visit 1 (1987-1989). Untargeted metabolomic profiling was performed in 2 subgroups (subgroup 1: n = 1842; subgroup 2: n = 2072). Multivariable linear regression models were used to assess associations between 3 dietary protein sources and 360 metabolites, adjusting for demographic factors and other participant characteristics. Analyses were performed separately within each subgroup and meta-analyzed with fixed-effects models. Results In this study of 3914 middle-aged adults, the mean (SD) age was 54 (6) y, 60% were women, and 61% were Black. We identified 41 metabolites significantly associated with dietary protein intake. Twenty-six metabolite associations overlapped between total protein and animal protein, such as pyroglutamine, creatine, 3-methylhistidine, and 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid. Plant protein was uniquely associated with 11 metabolites, such as tryptophan betaine, 4-vinylphenol sulfate, N-δ-acetylornithine, and pipecolate. Conclusions The results of 17 of the 41 metabolites (41%) were consistent with those of previous nutritional metabolomic studies and specific protein-rich food items. We discovered 24 metabolites that had not been previously associated with dietary protein intake. These results enhance the validity of candidate markers of dietary protein intake and introduce novel metabolomic markers of dietary protein intake.
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Affiliation(s)
- Lauren Bernard
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Hyunju Kim
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Kari E. Wong
- Metabolon, Research Triangle Park, Morrisville, NC, USA
| | - Lyn M. Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
- Human Genome Sequencing Center, Baylor Colleague of Medicine, Houston, TX, USA
| | - Casey M. Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
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21
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Yu Y, Wen X, Lin JG, Liu J, Liang HF, Lin SW, Xu QG, Li JC. Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics. Metabolomics 2023; 19:32. [PMID: 36997715 DOI: 10.1007/s11306-023-01990-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 03/05/2023] [Indexed: 04/01/2023]
Abstract
INTRODUCTION Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial. OBJECTIVES We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach. METHODS Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers. RESULTS Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9. CONCLUSIONS Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.
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Affiliation(s)
- Yi Yu
- Center for Analyses and Measurements, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China
| | - Xue Wen
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China
| | - Jin-Guang Lin
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China
| | - Jun Liu
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China
| | - Hong-Feng Liang
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China
| | - Shan-Wen Lin
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China
| | - Qiu-Gui Xu
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China
| | - Ji-Cheng Li
- The Central Laboratory, Yangjiang People's Hospital, Yangjiang, 529500, Guangdong, China.
- The Central Hospital of Taizhou, Taizhou, 318000, Zhejiang, China.
- Institute of Cell Biology, Zhejiang University, 866 Yuhangtang Rd, Hangzhou, 310058, Zhejiang, China.
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22
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Costamagna G, Bonato S, Corti S, Meneri M. Advancing Stroke Research on Cerebral Thrombi with Omic Technologies. Int J Mol Sci 2023; 24:ijms24043419. [PMID: 36834829 PMCID: PMC9961481 DOI: 10.3390/ijms24043419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/05/2023] [Accepted: 02/07/2023] [Indexed: 02/11/2023] Open
Abstract
Cerebrovascular diseases represent a leading cause of disability, morbidity, and death worldwide. In the last decade, the advances in endovascular procedures have not only improved acute ischemic stroke care but also conceded a thorough analysis of patients' thrombi. Although early anatomopathological and immunohistochemical analyses have provided valuable insights into thrombus composition and its correlation with radiological features, response to reperfusion therapies, and stroke etiology, these results have been inconclusive so far. Recent studies applied single- or multi-omic approaches-such as proteomics, metabolomics, transcriptomics, or a combination of these-to investigate clot composition and stroke mechanisms, showing high predictive power. Particularly, one pilot studies showed that combined deep phenotyping of stroke thrombi may be superior to classic clinical predictors in defining stroke mechanisms. Small sample sizes, varying methodologies, and lack of adjustments for potential confounders still represent roadblocks to generalizing these findings. However, these techniques hold the potential to better investigate stroke-related thrombogenesis and select secondary prevention strategies, and to prompt the discovery of novel biomarkers and therapeutic targets. In this review, we summarize the most recent findings, overview current strengths and limitations, and present future perspectives in the field.
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Affiliation(s)
- Gianluca Costamagna
- Dino Ferrari Centre, Neuroscience Section, Department of Pathophysiology and Transplantation (DEPT), University of Milan, Via Francesco Sforza 35, 20122 Milan, Italy
- Stroke Unit, Neurology Unit, Neuroscience and Mental Health Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
- Correspondence:
| | - Sara Bonato
- Stroke Unit, Neurology Unit, Neuroscience and Mental Health Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Stefania Corti
- Dino Ferrari Centre, Neuroscience Section, Department of Pathophysiology and Transplantation (DEPT), University of Milan, Via Francesco Sforza 35, 20122 Milan, Italy
- Stroke Unit, Neurology Unit, Neuroscience and Mental Health Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Megi Meneri
- Dino Ferrari Centre, Neuroscience Section, Department of Pathophysiology and Transplantation (DEPT), University of Milan, Via Francesco Sforza 35, 20122 Milan, Italy
- Stroke Unit, Neurology Unit, Neuroscience and Mental Health Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
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23
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Lasica N, Raicevic V, Stojanovic NM, Djilvesi D, Horvat I, Jelaca B, Pajicic F, Vulekovic P. Metabolomics as a potential tool for monitoring patients with aneurysmal subarachnoid hemorrhage. Front Neurol 2023; 13:1101524. [PMID: 36698893 PMCID: PMC9868237 DOI: 10.3389/fneur.2022.1101524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 12/21/2022] [Indexed: 01/11/2023] Open
Abstract
Metabolomics has evolved into a particularly useful tool to study interactions between metabolites and serves as an aid in unraveling the complexity of entire metabolomes. Nonetheless, it is increasingly viewed as a methodology with practical applications in the clinical setting, where identifying and quantifying biomarkers of interest could prove useful for diagnostics. Starting from a concise overview of the most prominent analytical techniques employed in metabolomics, herein we present a review of its application in studies of brain metabolism and cerebrovascular diseases, paying most attention to its uses in researching aneurysmal subarachnoid hemorrhage. Both animal models and human studies are considered, and metabolites identified as potential biomarkers are highlighted.
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Affiliation(s)
- Nebojsa Lasica
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia,Clinic of Neurosurgery, University Clinical Center of Vojvodina, Novi Sad, Serbia,*Correspondence: Nebojsa Lasica ✉
| | - Vidak Raicevic
- Department of Chemistry, Biochemistry and Environmental Protection, Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia
| | | | - Djula Djilvesi
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia,Clinic of Neurosurgery, University Clinical Center of Vojvodina, Novi Sad, Serbia
| | - Igor Horvat
- Clinic of Neurosurgery, University Clinical Center of Vojvodina, Novi Sad, Serbia
| | - Bojan Jelaca
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia,Clinic of Neurosurgery, University Clinical Center of Vojvodina, Novi Sad, Serbia
| | - Filip Pajicic
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia,Clinic of Neurosurgery, University Clinical Center of Vojvodina, Novi Sad, Serbia
| | - Petar Vulekovic
- Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia,Clinic of Neurosurgery, University Clinical Center of Vojvodina, Novi Sad, Serbia
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24
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Wang S, Zou X, Wang L, Zhou H, Wu L, Zhang Y, Yao TX, Chen L, Li Y, Zeng Y, Zhang L. Potential preventive markers in the intracerebral hemorrhage process are revealed by serum untargeted metabolomics in mice using hypertensive cerebral microbleeds. Front Endocrinol (Lausanne) 2023; 14:1084858. [PMID: 37152968 PMCID: PMC10159181 DOI: 10.3389/fendo.2023.1084858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 04/03/2023] [Indexed: 05/09/2023] Open
Abstract
Hypertensive cerebral microbleeds (HCMB) may be the early stage of hypertensive intracerebral hemorrhage (HICH), which is a serious threat to health due to its high mortality and disability rates. The early clinical symptoms of HCMB may not be significant. Moreover, it is difficult to achieve early diagnosis and intervention for targeted prevention of HICH. Although hypertension (HTN) is a predisposition for HCMB, it remains unclear whether there is any difference between hypertensive patients with or without HCMB. Therefore, we carried out liquid chromatography-mass spectrometry (LC-MS) to analyze early biomarkers for HCMB in mice with hypertension and to lay the foundation for early prevention of HICH in hypertensive patients. In total, 18 C57 male mice were randomly divided into the HCMB (n = 6), HTN (n = 6), and control groups (CON, n = 6). Hematoxylin-eosin and diaminobenzidine staining were used to assess the reliability of the model. The metabolite expression level and sample category stability were tested using the displacement test of orthogonal partial least squares discriminant analysis (OPLS-DA). Significant differences in metabolites were screened out using variable importance in the projection (VIP > 1), which were determined using the OPLS-DA model and the P-value of the t-test (P < 0.05) combined with the nonparametric rank-sum test. With an area under the curve (AUC) > 0.85 and a P-value of 0.05, the receiver operating characteristic curve (ROC) was used to further screen the distinct metabolites of HCMB. Compared with the HTN and CON groups, the HCMB group had significantly higher blood pressure and lower average body weight (P < 0.05). Through untargeted LC-MS analysis, 93 distinct metabolites were identified in the HCMB (P < 0.05, VIP > 1) group. Among these potential biomarkers, six significantly decreased and eight significantly increased differential metabolites were found. Meanwhile, we found that the HCMB group had statistically distinct arginine and purine metabolism pathways (P < 0.05), and citrulline may be the most significant possible biomarker of HCMB (AUC > 0.85, P < 0.05). All of these potential biomarkers may serve as early biomarkers for HICH in hypertension.
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Affiliation(s)
- Sai Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xuelun Zou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Leiyun Wang
- Department of Pharmacy, Wuhan First Hospital, Wuhan, Hubei, China
| | - Huifang Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Lianxu Wu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yupeng Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Tian-Xing Yao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Lei Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ye Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yi- Zeng
- Department of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Le Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Multi-Modal Monitoring Technology for Severe Cerebrovascular Disease of Human Engineering Research Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
- *Correspondence: Le Zhang,
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25
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Tao S, Xiao X, Li X, Na F, Na G, Wang S, Zhang P, Hao F, Zhao P, Guo D, Liu X, Yang D. Targeted metabolomics reveals serum changes of amino acids in mild to moderate ischemic stroke and stroke mimics. Front Neurol 2023; 14:1153193. [PMID: 37122289 PMCID: PMC10140586 DOI: 10.3389/fneur.2023.1153193] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 03/28/2023] [Indexed: 05/02/2023] Open
Abstract
Background The pathophysiological processes linked to an acute ischemic stroke (IS) can be reflected in the circulating metabolome. Amino acids (AAs) have been demonstrated to be one of the most significant metabolites that can undergo significant alteration after a stroke. Methods We sought to identify the potential biomarkers for the early detection of IS using an extensive targeted technique for reliable quantification of 27 different AAs based on ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). A cohort with 216 participants was enrolled, including 70 mild to moderate ischemic stroke patients (National Institutes of Health Stroke Scale < 15, MB group), 76 stroke mimics (MM group) and 70 healthy controls (NC group). Results It was found that upon comparing MB and MM to control patients, AAs shifts were detected via partial least squares discrimination analysis (PLS-DA) and pathway analysis. Interestingly, MB and MM exhibited similar AAs pattern. Moreover, ornithine, asparagine, valine, citrulline, and cysteine were identified for inclusion in a biomarker panel for early-stage stroke detection based upon an AUC of 0.968 (95% CI 0.924-0.998). Levels of ornithine were positively associated with infract volume, 3 months mRS score, and National Institutes of Health Stroke Scale (NIHSS) score in MB. In addition, a metabolites biomarker panel, including ornithine, taurine, phenylalanine, citrulline, cysteine, yielded an AUC of 0.99 (95% CI 0.966-1) which can be employed to effectively discriminate MM patients from control. Conclusion Overall, alternations in serum AAs are characteristic metabolic features of MB and MM. AAs could serve as promising biomarkers for the early diagnosis of MB patients since mild to moderate IS patients were enrolled in the study. The metabolism of AAs can be considered as a key indicator for both the prevention and treatment of IS.
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Affiliation(s)
- Shuxin Tao
- Department of Neurology, Liaocheng People’s Hospital, Liaocheng, Shandong, China
| | - Xinxing Xiao
- Department of Neurology, Liaocheng People’s Hospital, Liaocheng, Shandong, China
| | - Xin Li
- Department of Clinical Laboratory, Zibo Central Hospital, Zibo, Shandong, China
| | - Fan Na
- Zhong Yuan Academy of Biological Medicine, Liaocheng People’s Hospital, Liaocheng, China
| | - Guo Na
- Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Shuang Wang
- Zhong Yuan Academy of Biological Medicine, Liaocheng People’s Hospital, Liaocheng, China
| | - Pin Zhang
- Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Fang Hao
- Department of Neurology, Liaocheng People’s Hospital, Liaocheng, Shandong, China
| | - Peiran Zhao
- Zhong Yuan Academy of Biological Medicine, Liaocheng People’s Hospital, Liaocheng, China
| | - Dong Guo
- Department of Neurology, Liaocheng People’s Hospital, Liaocheng, Shandong, China
| | - Xuewu Liu
- Department of Neurology, Qilu Hospital of Shandong University, Institute of Epilepsy, Shandong University, Jinan, Shandong, China
- Xuewu Liu,
| | - Dawei Yang
- Zhong Yuan Academy of Biological Medicine, Liaocheng People’s Hospital, Liaocheng, China
- *Correspondence: Dawei Yang,
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Kourtidou C, Ztriva E, Kostourou DT, Polychronopoulos G, Satsoglou S, Chatzopoulos G, Kontana A, Tzavelas M, Valanikas E, Veneti S, Sofogianni A, Milonas D, Papagiannis A, Savopoulos C, Tziomalos K. The Predictive Role of the Triglyceride/Glucose Index in Patients with Hypercholesterolemia and Acute Ischemic Stroke. Rev Cardiovasc Med 2022; 23:399. [PMID: 39076671 PMCID: PMC11270394 DOI: 10.31083/j.rcm2312399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/08/2022] [Accepted: 11/10/2022] [Indexed: 07/31/2024] Open
Abstract
Background The triglyceride/glucose index (TyG) reflects insulin resistance and predicts the risk of acute ischemic stroke (aIS). However, it is uncertain if this index predicts the severity and outcome of aIS because studies that addressed this question are few and all were performed in Asian subjects. Moreover, there are no studies that focused on patients with hypercholesterolemia. Methods We studied 997 Caucasian patients who were hospitalized for aIS and had hypercholesterolemia. aIS severity was assessed at admission with the National Institutes of Health Stroke Scale (NIHSS) and severe aIS was defined as NIHSS ≥ 21. The outcome was assessed with the functional outcome at discharge and with in-hospital mortality. An unfavorable functional outcome was defined as modified Rank in scale (mRs) at discharge between 3 and 6. Results The TyG index did not correlate with the NIHSS at admission (r = 0.032, p = NS) and was similar in patients with severe and non-severe aIS (8.7 ± 0.6 and 8.6 ± 0.6, respectively; p = NS). Risk factors for severe aIS were age, female gender, atrial fibrillation (AF) and diastolic blood pressure (DBP) at admission. The TyG index also did not correlate with the mRs(r = 0.037, p = NS) and was similar in patients who had unfavorable and favorable functional outcome (8.7 ± 0.6 and 8.6 ± 0.5, respectively; p = NS). Risk factors for unfavorable functional outcome were age, previous ischemic stroke, body mass index and the NIHSS at admission. The TyG index was similar in patients who died during hospitalization and patients who were discharged (8.7 ± 0.6 and 8.7 ± 0.6, respectively; p = NS). Risk factors for in-hospital mortality were AF and DBP and NIHSS at admission. Conclusions The TyG index does not appear to be associated with the severity or the outcome of aIS. Nevertheless, since there are few relevant data in Caucasians and the TyG index is an inexpensive and widely available biomarker, more studies in this ethnic group are required to determine the predictive role of this index in patients with aIS.
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Affiliation(s)
- Christodoula Kourtidou
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Eleftheria Ztriva
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Danai-Thomais Kostourou
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Georgios Polychronopoulos
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Sarantis Satsoglou
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Georgios Chatzopoulos
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Anastasia Kontana
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Marios Tzavelas
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Evripidis Valanikas
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Stavroula Veneti
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Areti Sofogianni
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Dimitrios Milonas
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Achilleas Papagiannis
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Christos Savopoulos
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
| | - Konstantinos Tziomalos
- First Propedeutic Department of Internal Medicine, Medical School, Aristotle University of Thessaloniki, AHEPA Hospital, 54636 Thessaloniki, Greece
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Ye X, Zhu B, Chen Y, Wang Y, Wang D, Zhao Z, Li Z. Integrated Metabolomics and Lipidomics Approach for the Study of Metabolic Network and Early Diagnosis in Cerebral Infarction. J Proteome Res 2022; 21:2635-2646. [PMID: 36264770 DOI: 10.1021/acs.jproteome.2c00348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Cerebral infarction (CI) remains a major cause of high mortality and long-term disability worldwide. The exploration of biomarkers and pathogenesis is crucial for the early diagnosis of CI. Although the understanding of metabolic perturbations underlying CI has increased in recent years, the relationship between altered metabolites and disease pathogenesis has only been partially elucidated and requires further investigation. In this study, we performed an integrated metabolomics and lipidomics analysis on 59 healthy subjects and 47 CI patients. Ultimately, 49 metabolite and 68 lipid biomarkers were identified and enriched in 24 disturbed pathways. The metabolic network revealed a significant interaction between altered lipids and other metabolites. Using receiver operating characteristic curve (ROC) analysis, a panel of three polar metabolites and seven lipids was optimized in the training set, which included taurine, oleoylcarnitine, creatinine, PE(22:6/P-18:0), Cer 34:2, GlcCer(d18:0/18:0), DG 44:0, LysoPC(16:0), 22:6-OH/LysoPC, and TAG58:7-FA22:4. Subsequently, a support vector machine (SVM) model was constructed and validated, which showed excellent predictive ability in the validation set. Thereby, the integrated metabolomics and lipidomics approach could contribute to a comprehensive understanding of the metabolic dyshomeostasis associated with the pathogenesis of underlying CI. The present research may promote a deeper understanding and early diagnosis of CI in the clinic. All raw data were deposited in PRIDE (PXD036199).
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Affiliation(s)
- Xinxin Ye
- Department of Chemistry, Capital Normal University, No. 105, West Third Ring Road North, Haidian District, Beijing 100048, P. R. China
| | - Bin Zhu
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring Road West, Fengtai District, Beijing 100070, P. R. China
| | - Yang Chen
- Department of Chemistry, Capital Normal University, No. 105, West Third Ring Road North, Haidian District, Beijing 100048, P. R. China
| | - Yingfeng Wang
- Department of Chemistry, Capital Normal University, No. 105, West Third Ring Road North, Haidian District, Beijing 100048, P. R. China
| | - Dan Wang
- Department of Chemistry, Capital Normal University, No. 105, West Third Ring Road North, Haidian District, Beijing 100048, P. R. China
| | - Zhigang Zhao
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring Road West, Fengtai District, Beijing 100070, P. R. China
| | - Zhongfeng Li
- Department of Chemistry, Capital Normal University, No. 105, West Third Ring Road North, Haidian District, Beijing 100048, P. R. China
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Zhang R, Meng J, Wang X, Pu L, Zhao T, Huang Y, Han L. Metabolomics of ischemic stroke: insights into risk prediction and mechanisms. Metab Brain Dis 2022; 37:2163-2180. [PMID: 35612695 DOI: 10.1007/s11011-022-01011-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/16/2022] [Indexed: 10/18/2022]
Abstract
Ischemic stroke (IS) is the most prevalent type of stroke. The early diagnosis and prognosis of IS are crucial for successful therapy and early intervention. Metabolomics, a tool in systems biology based on several innovative technologies, can be used to identify disease biomarkers and unveil underlying pathophysiological processes. Accordingly, in recent years, an increasing number of studies have identified metabolites from cerebral ischemia patients and animal models that could improve the diagnosis of IS and prediction of its outcome. In this paper, metabolomic research is comprehensively reviewed with a focus on describing the metabolic changes and related pathways associated with IS. Most clinical studies use biofluids (e.g., blood or plasma) because their collection is minimally invasive and they are ideal for analyzing changes in metabolites in patients of IS. We review the application of animal models in metabolomic analyses aimed at investigating potential mechanisms of IS and developing novel therapeutic approaches. In addition, this review presents the strengths and limitations of current metabolomic studies on IS, providing a reference for future related studies.
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Affiliation(s)
- Ruijie Zhang
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
| | - Jiajia Meng
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
- Xihu District Center for Disease Control and Prevention, Hangzhou, 310013, Zhejiang, China
| | - Xiaojie Wang
- Department of Neurology, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, 518067, Guangdong, China
| | - Liyuan Pu
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
| | - Tian Zhao
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China
| | - Yi Huang
- Department of Neurosurgery, Ningbo First Hospital, Ningbo, 315010, Zhejiang, China.
- Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province, Ningbo, 315010, Zhejiang, China.
- Medical Research Center, Ningbo First Hospital, Ningbo, 315010, Zhejiang, China.
| | - Liyuan Han
- Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China.
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, 315010, Zhejiang, China.
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Weinisch P, Fiamoncini J, Schranner D, Raffler J, Skurk T, Rist MJ, Römisch-Margl W, Prehn C, Adamski J, Hauner H, Daniel H, Suhre K, Kastenmüller G. Dynamic patterns of postprandial metabolic responses to three dietary challenges. Front Nutr 2022; 9:933526. [PMID: 36211489 PMCID: PMC9540193 DOI: 10.3389/fnut.2022.933526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake.
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Affiliation(s)
- Patrick Weinisch
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jarlei Fiamoncini
- Food Research Center – FoRC, Department of Food Science and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Daniela Schranner
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Johannes Raffler
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- Digital Medicine, University Hospital of Augsburg, Augsburg, Germany
| | - Thomas Skurk
- Core Facility Human Studies, ZIEL Institute for Food and Health, Technical University of Munich, Freising, Germany
- Else Kröner Fresenius Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Manuela J. Rist
- Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany
| | - Werner Römisch-Margl
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Hans Hauner
- Else Kröner Fresenius Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
| | - Hannelore Daniel
- Department of Food and Nutrition, Technical University of Munich, Freising, Germany
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine—Qatar, Doha, Qatar
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- *Correspondence: Gabi Kastenmüller
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Zhang Y, Zhu D, Li T, Wang X, Zhao L, Yang X, Dang M, Li Y, Wu Y, Lu Z, Lu J, Jian Y, Wang H, Zhang L, Lu X, Shen Z, Fan H, Cai W, Zhang G. Detection of acute ischemic stroke and backtracking stroke onset time via machine learning analysis of metabolomics. Biomed Pharmacother 2022; 155:113641. [PMID: 36088854 DOI: 10.1016/j.biopha.2022.113641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/27/2022] [Accepted: 08/30/2022] [Indexed: 11/30/2022] Open
Abstract
The time window from stroke onset is critical for the treatment decision. However, in unknown onset stroke, it is often difficult to determine the exact onset time because of the lack of assessment methods, which can result in controversial and random treatment decisions. Previous studies have shown that serum biomarkers, in addition to imaging assessment, are useful for determining the stroke onset time. However, as yet there are no specific biomarkers or corresponding methodologies that are accurate and effective for determining the onset time of unknown onset stroke. Herein, we describe our novel advanced metabolites-based machine learning method (termed extreme gradient boost [XGBoost]) combined with recursive feature elimination, which accurately screened five metabolites from 1124 metabolites detected in serum. These metabolites were capable of both detecting acute ischemic stroke and backtracking the acute ischemic stroke onset time. To further investigate the pathological mechanisms of acute ischemic stroke, we also examined characteristic metabolites in different brain regions, and found two metabolites that could distinguish the core infarct area from the ischemic penumbra. Although this study is based on animal experiments, our machine learning framework and selected metabolites may provide a basis for clinical stroke evaluation and treatment.
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Affiliation(s)
- Yiheng Zhang
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Dayu Zhu
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, United States
| | - Tao Li
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Xiaoya Wang
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Lili Zhao
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Meijuan Dang
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Ye Li
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Yulun Wu
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Ziwei Lu
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Jialiang Lu
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Yating Jian
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Heying Wang
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Lei Zhang
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Xiaoyun Lu
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ziyu Shen
- Guangzhou Kingmed Diagnostics Group Co., Ltd., Guangzhou 510030, Guangdong, China
| | - Hong Fan
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Wenshan Cai
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, United States; School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0295, United States.
| | - Guilian Zhang
- Department of Neurology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China.
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Bernard L, Zhou L, Surapaneni A, Chen J, Rebholz CM, Coresh J, Yu B, Boerwinkle E, Schlosser P, Grams ME. Serum Metabolites and Kidney Outcomes: The Atherosclerosis Risk in Communities Study. Kidney Med 2022; 4:100522. [PMID: 36046612 PMCID: PMC9420957 DOI: 10.1016/j.xkme.2022.100522] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Rationale & Objective Novel metabolite biomarkers of kidney failure with replacement therapy (KFRT) may help identify people at high risk for adverse kidney outcomes and implicated pathways may aid in developing targeted therapeutics. Study Design Prospective cohort. Setting & Participants The cohort included 3,799 Atherosclerosis Risk in Communities study participants with serum samples available for measurement at visit 1 (1987-1989). Exposure Baseline serum levels of 318 metabolites. Outcomes Incident KFRT, kidney failure (KFRT, estimated glomerular filtration rate <15 mL/min/1.73 m2, or death from kidney disease). Analytical Approach Because metabolites are often intercorrelated and represent shared pathways, we used a high dimension reduction technique called Netboost to cluster metabolites. Longitudinal associations between clusters of metabolites and KFRT and kidney failure were estimated using a Cox proportional hazards model. Results Mean age of study participants was 53 years, 61% were African American, and 13% had diabetes. There were 160 KFRT cases and 357 kidney failure cases over a mean of 23 years. The 314 metabolites were grouped in 43 clusters. Four clusters were significantly associated with risk of KFRT and 6 were associated with kidney failure (including 3 shared clusters). The 3 shared clusters suggested potential pathways perturbed early in kidney disease: cluster 5 (15 metabolites involved in alanine, aspartate, and glutamate metabolism as well as 5-oxoproline and several gamma-glutamyl amino acids), cluster 26 (6 metabolites involved in sugar and inositol phosphate metabolism), and cluster 34 (21 metabolites involved in glycerophospholipid metabolism). Several individual metabolites were also significantly associated with both KFRT and kidney failure, including glucose and mannose, which were associated with higher risk of both outcomes, and 5-oxoproline, gamma-glutamyl amino acids, linoleoylglycerophosphocholine, 1,5-anhydroglucitol, which were associated with lower risk of both outcomes. Limitations Inability to determine if the metabolites cause or are a consequence of changes in kidney function. Conclusions We identified several clusters of metabolites reproducibly associated with development of KFRT. Future experimental studies are needed to validate our findings as well as continue unraveling metabolic pathways involved in kidney function decline.
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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 PMCID: PMC9169945 DOI: 10.1212/wnl.0000000000200262] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [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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Avery CL, Howard AG, Ballou AF, Buchanan VL, Collins JM, Downie CG, Engel SM, Graff M, Highland HM, Lee MP, Lilly AG, Lu K, Rager JE, Staley BS, North KE, Gordon-Larsen P. Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:55001. [PMID: 35533073 PMCID: PMC9084332 DOI: 10.1289/ehp9098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/08/2022] [Accepted: 04/12/2022] [Indexed: 05/11/2023]
Abstract
Advances in technologies to measure a broad set of exposures have led to a range of exposome research efforts. Yet, these efforts have insufficiently integrated methods that incorporate genetic data to strengthen causal inference, despite evidence that many exposome-associated phenotypes are heritable. Objective: We demonstrate how integration of methods and study designs that incorporate genetic data can strengthen causal inference in exposomics research by helping address six challenges: reverse causation and unmeasured confounding, comprehensive examination of phenotypic effects, low efficiency, replication, multilevel data integration, and characterization of tissue-specific effects. Examples are drawn from studies of biomarkers and health behaviors, exposure domains where the causal inference methods we describe are most often applied. Discussion: Technological, computational, and statistical advances in genotyping, imputation, and analysis, combined with broad data sharing and cross-study collaborations, offer multiple opportunities to strengthen causal inference in exposomics research. Full application of these opportunities will require an expanded understanding of genetic variants that predict exposome phenotypes as well as an appreciation that the utility of genetic variants for causal inference will vary by exposure and may depend on large sample sizes. However, several of these challenges can be addressed through international scientific collaborations that prioritize data sharing. Ultimately, we anticipate that efforts to better integrate methods that incorporate genetic data will extend the reach of exposomics research by helping address the challenges of comprehensively measuring the exposome and its health effects across studies, the life course, and in varied contexts and diverse populations. https://doi.org/10.1289/EHP9098.
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Affiliation(s)
- Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Annie Green Howard
- Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Anna F Ballou
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Victoria L Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jason M Collins
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Carolina G Downie
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Stephanie M Engel
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Heather M Highland
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Moa P Lee
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Adam G Lilly
- Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Sociology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kun Lu
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Julia E Rager
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Brooke S Staley
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Carolina Population Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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Balasubramanian R, Hu J, Guasch-Ferre M, Li J, Sorond F, Zhao Y, Shutta KH, Salas-Salvado J, Hu F, Clish CB, Rexrode KM. Metabolomic Profiles Associated With Incident Ischemic Stroke. Neurology 2022; 98:e483-e492. [PMID: 34853177 PMCID: PMC8826464 DOI: 10.1212/wnl.0000000000013129] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/16/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Women have higher lifetime risk of stroke than men, and metabolic factors seem more strongly associated with stroke for women than men. However, few studies in either men or women have evaluated metabolomic profiles and incident stroke. METHODS We applied liquid chromatography-tandem mass spectrometry to measure 519 plasma metabolites in a discovery set of women in the Nurses' Health Study (NHS; 454 incident ischemic stroke cases, 454 controls) with validation in 2 independent, prospective cohorts: Prevención con Dieta Mediterránea (PREDIMED; 118 stroke cases, 791 controls) and Nurses' Health Study 2 (NHS2; 49 ischemic stroke cases, 49 controls). We applied logistic regression models with stroke as the outcome to adjust for multiple risk factors; the false discovery rate was controlled through the q value method. RESULTS Twenty-three metabolites were significantly associated with incident stroke in NHS after adjustment for traditional risk factors (q < 0.05). Of these, 14 metabolites were available in PREDIMED and 3 were significantly associated with incident stroke: methionine sulfoxide, N6-acetyllysine, and sucrose (q < 0.05). In NHS2, one of the 23 metabolites (glucuronate) was significantly associated with incident stroke (q < 0.05). For all 4 metabolites, higher levels were associated with increased risk. These 4 metabolites were used to create a stroke metabolite score (SMS) in the NHS and tested in PREDIMED. Per unit of standard deviation of SMS, the odds ratio for incident stroke was 4.12 (95% confidence interval [CI] 2.26-7.51) in PREDIMED, after adjustment for risk factors. In PREDIMED, the area under the receiver operating characteristic curve (AUC) for the model including SMS and traditional risk factors was 0.70 (95% CI 0.75-0.79) vs the AUC for the model including the traditional risk factors only of 0.65 (95% CI 0.70-0.75), corresponding to a 5% improvement in risk prediction with SMS (p < 0.005). DISCUSSION Metabolites associated with stroke included 2 amino acids, a carboxylic acid, and sucrose. A composite SMS including these metabolites was associated with ischemic stroke and showed improvement in risk prediction beyond traditional risk factors. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that a SMS accurately predicts incident ischemic stroke risk.
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Affiliation(s)
- Raji Balasubramanian
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge.
| | - Jie Hu
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Marta Guasch-Ferre
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Jun Li
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Farzaneh Sorond
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Yibai Zhao
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Katherine H Shutta
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Jordi Salas-Salvado
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Frank Hu
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Clary B Clish
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
| | - Kathryn M Rexrode
- From the Department of Biostatistics and Epidemiology (R.B., Y.Z., K.H.S.), University of Massachusetts-Amherst; Division of Women's Health (J.H., K.M.R.) and Channing Division of Network Medicine, Department of Medicine (M.G.-F., F.H.), Brigham and Women's Hospital, Harvard Medical School; Departments of Nutrition (M.G.-F., J.L., F.H.) and Epidemiology (J.L., F.H.), Harvard T.H. Chan School of Public Health, Boston, MA; Davee Department of Neurology, Division of Stroke and Neurocritical Care (F.S.), Northwestern Feinberg School of Medicine, Chicago, IL; Departament de Bioquímica i Biotecnologia, Unitat de Nutrició (J.S.S.), Universitat Rovira i Virgili, Reus; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN) (J.S.-S.), Institute of Health Carlos III, Madrid; Nutrition Unit, Pere Virgili Research Institute (IISPV) (J.S.-S.), University Hospital of Sant Joan de Reus, Spain; and Broad Institute of the Massachusetts Institute of Technology and Harvard University (C.B.C.), Cambridge
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Abstract
Although a relationship between traditional cardiovascular risk factors and stroke has long been recognized, these risk factors likely play a role in other aspects of brain health. Clinical stroke is only the tip of the iceberg of vascular brain injury that includes covert infarcts, white matter hyperintensities, and microbleeds. Furthermore, an individual's risk for not only stroke but poor brain health includes not only these traditional vascular risk factors but also lifestyle and genetic factors. The purpose of this narrative review is to summarize the state of the evidence on traditional and nontraditional vascular risk factors and their contributions to brain health. Additionally, we will review important modifiers that interact with these risk factors to increase, or, in some cases, reduce risk of adverse brain health outcomes, with an emphasis on genes and biomarkers associated with Alzheimer disease. Finally, we will consider the importance of social determinants of health in brain health outcomes.
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Affiliation(s)
- Rebecca F Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD (R.F.G.)
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UTHSA, San Antonio, TX (S.S.).,Department of Neurology, Boston University School of Medicine, Boston, MA (S.S.)
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36
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Poupore N, Chosed R, Arce S, Rainer R, Goodwin RL, Nathaniel TI. Metabolomic Profiles of Men and Women Ischemic Stroke Patients. Diagnostics (Basel) 2021; 11:diagnostics11101786. [PMID: 34679483 PMCID: PMC8534835 DOI: 10.3390/diagnostics11101786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 09/20/2021] [Accepted: 09/22/2021] [Indexed: 12/02/2022] Open
Abstract
Background: Stroke is known to affect both men and women; however, incidence and outcomes differ between them. Therefore, the discovery of novel, sex-specific, blood-based biomarkers for acute ischemic stroke (AIS) patients has the potential to enhance the understanding of the etiology of this deadly disease in the content of sex. The objective of this study was to identify serum metabolites associated with male and female AIS patients. Methods: Metabolites were measured with the use of untargeted, reverse-phase ultra-performance liquid chromatography-tandem mass spectrometry quantification from blood specimens collected from AIS patients. Samples were collected from 36 patients comprising each of 18 men and women with matched controls. Metabolic pathway analysis and principal component analysis (PCA) was used to differentiate metabolite profiles for male and female AIS patients from the control, while logistic regression was used to determine differences in metabolites between male and female AIS patients. Results: In female AIS patients, 14 distinct altered metabolic pathways and 49 corresponding metabolites were identified, while 39 metabolites and 5 metabolic pathways were identified in male patients. Metabolites that are predictive of ischemic stroke in female patients were 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC (P-16:0/20:4) (AUC = 0.914, 0.765–1.000), 1-(1-enyl-palmitoyl)-2-palmitoyl-GPC (P-16:0/16:0) (AUC = 0.840, 0.656–1.000), and 5,6-dihydrouracil (P-16:0/20:2) (AUC = 0.815, 0.601–1.000). Significant metabolites that were predictive of stroke in male patients were 5alpha-androstan-3alpha,17beta-diol disulfate (AUC = 0.951, 0.857–1.000), alpha-hydroxyisocaproate (AUC = 0.938, 0.832–1.000), threonate (AUC = 0.877, 0.716–1.000), and bilirubin (AUC = 0.817, 0.746–1.000). Conclusions: In the current study, the untargeted serum metabolomics platform identified multiple pathways and metabolites associated with male and female AIS patients. Further research is necessary to characterize how these metabolites are associated with the pathophysiology in male and female AIS patients.
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Affiliation(s)
- Nicolas Poupore
- School of Medicine Greenville, University of South Carolina, Greenville, SC 29605, USA; (N.P.); (R.C.); (S.A.); (R.L.G.)
| | - Renee Chosed
- School of Medicine Greenville, University of South Carolina, Greenville, SC 29605, USA; (N.P.); (R.C.); (S.A.); (R.L.G.)
| | - Sergio Arce
- School of Medicine Greenville, University of South Carolina, Greenville, SC 29605, USA; (N.P.); (R.C.); (S.A.); (R.L.G.)
| | | | - Richard L. Goodwin
- School of Medicine Greenville, University of South Carolina, Greenville, SC 29605, USA; (N.P.); (R.C.); (S.A.); (R.L.G.)
| | - Thomas I. Nathaniel
- School of Medicine Greenville, University of South Carolina, Greenville, SC 29605, USA; (N.P.); (R.C.); (S.A.); (R.L.G.)
- Correspondence: ; Tel.: +1-8644559846; Fax: +1-8644558404
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Chumachenko MS, Waseem TV, Fedorovich SV. Metabolomics and metabolites in ischemic stroke. Rev Neurosci 2021; 33:181-205. [PMID: 34213842 DOI: 10.1515/revneuro-2021-0048] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 06/09/2021] [Indexed: 12/27/2022]
Abstract
Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.
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Affiliation(s)
- Maria S Chumachenko
- Department of Biochemistry, Faculty of Biology, Belarusian State University, Kurchatova St., 10, Minsk220030, Belarus
| | | | - Sergei V Fedorovich
- Department of Biochemistry, Faculty of Biology, Belarusian State University, Kurchatova St., 10, Minsk220030, Belarus
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Kumar A, Chauhan G, Sharma S, Dabla S, Sylaja PN, Chaudhary N, Gupta S, Agrawal CS, Anand KS, Srivastava AK, Vibha D, Sagar R, Raj R, Maheshwari A, Vivekanandhan S, Kaul B, Raghavan S, Gorthi SP, Mohania D, Kaushik S, Yadav RK, Hazarika A, Sharma P, Prasad K. Association of SUMOylation Pathway Genes With Stroke in a Genome-Wide Association Study in India. Neurology 2021; 97:e345-e356. [PMID: 34031191 DOI: 10.1212/wnl.0000000000012258] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 04/21/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To undertake a genome-wide association study (GWAS) to identify genetic variants for stroke in an Indian population. METHODS In a hospital-based case-control study, 8 teaching hospitals in India recruited 4,088 participants, including 1,609 stroke cases. Imputed genetic variants were tested for association with stroke subtypes using both single-marker and gene-based tests. Association with vascular risk factors was performed with logistic regression. Various databases were searched for replication, functional annotation, and association with related traits. Status of candidate genes previously reported in the Indian population was also checked. RESULTS Associations of vascular risk factors with stroke were similar to previous reports and show modifiable risk factors such as hypertension, smoking, and alcohol consumption as having the highest effect. Single-marker-based association revealed 2 loci for cardioembolic stroke (1p21 and 16q24), 2 for small vessel disease stroke (3p26 and 16p13), and 4 for hemorrhagic stroke (3q24, 5q33, 6q13, and 19q13) at p < 5 × 10-8. The index single nucleotide polymorphism of 1p21 is an expression quantitative trait locus (p lowest = 1.74 × 10-58) for RWDD3 involved in SUMOylation and is associated with platelet distribution width (1.15 × 10-9) and 18-carbon fatty acid metabolism (p = 7.36 × 10-12). In gene-based analysis, we identified 3 genes (SLC17A2, FAM73A, and OR52L1) at p < 2.7 × 10-6. Eleven of 32 candidate gene loci studied in an Indian population replicated (p < 0.05), and 21 of 32 loci identified through previous GWAS replicated according to directionality of effect. CONCLUSIONS This GWAS of stroke in an Indian population identified novel loci and replicated previously known loci. Genetic variants in the SUMOylation pathway, which has been implicated in brain ischemia, were identified for association with stroke.
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Affiliation(s)
- Amit Kumar
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Ganesh Chauhan
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Shriram Sharma
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Surekha Dabla
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - P N Sylaja
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Neera Chaudhary
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Salil Gupta
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Chandra Sekhar Agrawal
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Kuljeet Singh Anand
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Achal Kumar Srivastava
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Deepti Vibha
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Ram Sagar
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Ritesh Raj
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Ankita Maheshwari
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Subbiah Vivekanandhan
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Bhavna Kaul
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Samudrala Raghavan
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Sankar Prasad Gorthi
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Dheeraj Mohania
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Samander Kaushik
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Rohtas Kanwar Yadav
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Anjali Hazarika
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Pankaj Sharma
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India
| | - Kameshwar Prasad
- From the Department of Neurology (A.K., A.K.S., D.V., R.S., R.R., A.M., K.P.), Department of Neurobiochemisty (S.V.), Dr. R. P. Centre for Ophthalmic Sciences (D.M.), and Cardio-Neuro Centre (A.H.), All India Institute of Medical Sciences, New Delhi; Centre for Brain Research (G.C.), Indian Institute of Science, Bangalore; Department of Neurology (S.S.), North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, Meghalaya; Department of Neurology (S.D.), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana; Department of Neurology (P.N.S.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Kerala; Department of Neurology (N.C., B.K., S.R.), Vardhman Mahavir Medical College and Safdarjung Hospital; Department of Neurology (S.G., S.P.G.), Army Research and Referral Hospital; Department of Neurology (C.S.A.), Sir Ganga Ram Hospital; Ram Manohar Lohia Hospital (K.S.A.); Department of Biotechnology (S.K.), Maharshi Dayanand University, Government of India, New Delhi; Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (R.K.Y.), Rohtak, Haryana, India; and Institute of Cardiovascular Research Royal Holloway (P.S.), University of London, Imperial College London, UK. Amit Kumar, Kameshwar Prasad, and Ganesh Chauhan are currently at Rajendra Institute of Medical Sciences, Ranchi, India.
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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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Davis Armstrong NM, Spragley KJ, Chen WM, Hsu FC, Brewer MS, Horn PJ, Williams SR, Sale MM, Worrall BB, Keene KL. Multi-omic analysis of stroke recurrence in African Americans from the Vitamin Intervention for Stroke Prevention (VISP) clinical trial. PLoS One 2021; 16:e0247257. [PMID: 33661917 PMCID: PMC7932724 DOI: 10.1371/journal.pone.0247257] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 02/04/2021] [Indexed: 11/24/2022] Open
Abstract
African Americans endure a nearly two-fold greater risk of suffering a stroke and are 2–3 times more likely to die from stroke compared to those of European ancestry. African Americans also have a greater risk of recurrent stroke and vascular events, which are deadlier and more disabling than incident stroke. Stroke is a multifactorial disease with both heritable and environmental risk factors. We conducted an integrative, multi-omic study on 922 plasma metabolites, 473,864 DNA methylation loci, and 556 variants from 50 African American participants of the Vitamin Intervention for Stroke Prevention clinical trial to help elucidate biomarkers contributing to recurrent stroke rates in this high risk population. Sixteen metabolites, including cotinine, N-delta-acetylornithine, and sphingomyelin (d17:1/24:1) were identified in t-tests of recurrent stroke outcome or baseline smoking status. Serum tricosanoyl sphingomyelin (d18:1/23:0) levels were significantly associated with recurrent stroke after adjusting for covariates in Cox Proportional Hazards models. Weighted Gene Co-expression Network Analysis identified moderate correlations between sphingolipid markers and clinical traits including days to recurrent stroke. Integrative analyses between genetic variants in sphingolipid pathway genes identified 29 nominal associations with metabolite levels in a one-way analysis of variance, while epigenomic analyses identified xenobiotics, predominately smoking-associated metabolites and pharmaceutical drugs, associated with methylation profiles. Taken together, our results suggest that metabolites, specifically those associated with sphingolipid metabolism, are potential plasma biomarkers for stroke recurrence in African Americans. Furthermore, genetic variation and DNA methylation may play a role in the regulation of these metabolites.
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Affiliation(s)
- Nicole M. Davis Armstrong
- Department of Biology, East Carolina University, Greenville, North Carolina, United States of America
| | - Kelsey J. Spragley
- Department of Biology, East Carolina University, Greenville, North Carolina, United States of America
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Fang-Chi Hsu
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Michael S. Brewer
- Department of Biology, East Carolina University, Greenville, North Carolina, United States of America
| | - Patrick J. Horn
- Department of Biology, East Carolina University, Greenville, North Carolina, United States of America
| | - Stephen R. Williams
- Department of Neurology, University of Virginia, Charlottesville, Virginia, United States of America
| | - Michèle M. Sale
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Bradford B. Worrall
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Neurology, University of Virginia, Charlottesville, Virginia, United States of America
| | - Keith L. Keene
- Department of Biology, East Carolina University, Greenville, North Carolina, United States of America
- Center for Health Disparities, Brody School of Medicine, East Carolina University, Greenville, North Carolina, United States of America
- * E-mail:
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Liu J, Yuan J, Zhao J, Zhang L, Wang Q, Wang G. Serum metabolomic patterns in young patients with ischemic stroke: a case study. Metabolomics 2021; 17:24. [PMID: 33554271 DOI: 10.1007/s11306-021-01774-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 01/22/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Ischemic stroke is one of the leading causes of death and adult disability. The incidence of ischemic stroke continues to rise in young adults. This study aimed to provide a comprehensive evaluation of metabolic changes and explore possible mechanisms in young ischemic stroke patients without common risk factors. METHODS This study investigated serum metabolomics in 50 young patients with newly suffered ischemic stroke and 50 age-, sex-, and body mass index-matched healthy controls. Liquid chromatography coupled with a Waters Xevo TQ-S mass spectrometer with an electrospray ionization (ESI) source was used to analyze amino acid or bile acid, and free fatty acid or lipid was analyzed by liquid chromatography coupled with a Qtrap5500 mass spectrometer with an ESI source. The metabolomic data were analyzed by performing a multivariate statistical analysis. RESULTS A total of 197 metabolites, including amino acids, bile acids, free fatty acids, and lipids, were identified in all participants. Multivariate models showed significant differences in serum metabolomic patterns between young patients with ischemic stroke and healthy controls. The stroke patients had increased L-methionine, homocysteine, glutamine, uric acid, GCDCA, and PE (18:0/20:4, 16:0/22:5), and decreased levels of L-citrulline, taurine, PC (16:2/22:6, 16:2/20:5, 15:0/18:2), and SM (d18:1/23:0, d20:0/19:1, d18:1/22:0, d16:0/26:1, d16:0/18:0, d16:0/22:1, d18:1/19:1, d16:0/17:1, d16:1/24:1, d18:1/19:0). Based on the identified metabolites, the metabolic pathways of arginine biosynthesis, glycerophospholipid metabolism, and taurine and hypotaurine metabolism were significantly enriched in the young patients with ischemic stroke. CONCLUSIONS Serum metabolomic patterns were significantly different between young patients with ischemic stroke and healthy controls. Our study is beneficial in providing a further view into the pathophysiology of young patients with ischemic stroke.
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Affiliation(s)
- Jia Liu
- Department of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, NO. 8, Gongti South Road, Chaoyang District, Beijing, 100020, China
| | - Junliang Yuan
- Department of Neurology, Peking University Sixth Hospital, Beijing, 100191, China
| | - Jingwei Zhao
- Department of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, NO. 8, Gongti South Road, Chaoyang District, Beijing, 100020, China
| | - Lin Zhang
- Department of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, NO. 8, Gongti South Road, Chaoyang District, Beijing, 100020, China
| | - Qiu Wang
- Department of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, NO. 8, Gongti South Road, Chaoyang District, Beijing, 100020, China
| | - Guang Wang
- Department of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, NO. 8, Gongti South Road, Chaoyang District, Beijing, 100020, China.
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Hou H, Zhao H. Epigenetic factors in atherosclerosis: DNA methylation, folic acid metabolism, and intestinal microbiota. Clin Chim Acta 2020; 512:7-11. [PMID: 33232735 DOI: 10.1016/j.cca.2020.11.013] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/07/2020] [Accepted: 11/10/2020] [Indexed: 12/11/2022]
Abstract
Atherosclerosis is a complex disease, influenced by both genetic and non-genetic factors. The most important epigenetic mechanism in the pathogenesis of atherosclerosis is DNA methylation, which involves modification of the gene without changes in the gene sequence. Nutrients involved in one-carbon metabolism interact to regulate DNA methylation, especially folic acid and B vitamins. Deficiencies in folic acid and other nutrients, such as vitamins B6 and B12, can increase homocysteine levels, induce endothelial dysfunction, and accelerate atherosclerotic pathological processes. Supplemented nutrients can improve DNA methylation status, reduce levels of inflammatory factors, and delay the process of atherosclerosis. In this review, the influence of intestinal flora on folate metabolism and epigenetics is also considered.
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Affiliation(s)
- Huimin Hou
- Department of Geriatrics, The First Hospital of Jilin University, Changchun 130021, China
| | - Huiying Zhao
- Department of Geriatrics, The First Hospital of Jilin University, Changchun 130021, China.
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Simpkins AN, Janowski M, Oz HS, Roberts J, Bix G, Doré S, Stowe AM. Biomarker Application for Precision Medicine in Stroke. Transl Stroke Res 2020; 11:615-627. [PMID: 31848851 PMCID: PMC7299765 DOI: 10.1007/s12975-019-00762-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 11/22/2019] [Accepted: 11/26/2019] [Indexed: 12/25/2022]
Abstract
Stroke remains one of the leading causes of long-term disability and mortality despite recent advances in acute thrombolytic therapies. In fact, the global lifetime risk of stroke in adults over the age of 25 is approximately 25%, with 24.9 million cases of ischemic stroke and 18.7 million cases of hemorrhagic stroke reported in 2015. One of the main challenges in developing effective new acute therapeutics and enhanced long-term interventions for stroke recovery is the heterogeneity of stroke, including etiology, comorbidities, and lifestyle factors that uniquely affect each individual stroke survivor. In this comprehensive review, we propose that future biomarker studies can be designed to support precision medicine therapeutic interventions after stroke. The current challenges in defining ideal biomarkers for stroke are highlighted, including consideration of disease course, age, lifestyle factors, and subtypes of stroke. This overview of current clinical trials includes biomarker collection, and concludes with an example of biomarker design for aneurysmal subarachnoid hemorrhage. With the advent of "-omics" studies, neuroimaging, big data, and precision medicine, well-designed stroke biomarker trials will greatly advance the treatment of a disease that affects millions globally every year.
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Affiliation(s)
- Alexis N Simpkins
- Department of Anesthesiology, University of Florida, Gainesville, FL, USA
| | - Miroslaw Janowski
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, Baltimore, MD, USA
| | - Helieh S Oz
- Department of Internal Medicine, University of Kentucky, Lexington, KY, USA
| | - Jill Roberts
- Department of Neurosurgery, University of Kentucky, Lexington, KY, USA
- Center for Advanced Translational Stroke Science, Lexington, KY, USA
| | - Gregory Bix
- Clinical Neuroscience Research Center, Tulane University, New Orleans, LA, USA
- Department of Neurosurgery, Neurology, Tulane University, New Orleans, LA, USA
| | - Sylvain Doré
- Department of Anesthesiology, University of Florida, Gainesville, FL, USA
- Department of Neurology, Psychiatry, Pharmaceutics, Neuroscience, University of Florida, Gainesville, FL, USA
| | - Ann M Stowe
- Center for Advanced Translational Stroke Science, Lexington, KY, USA.
- Department of Neurology, University of Kentucky, Lexington, KY, USA.
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44
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Louca P, Menni C, Padmanabhan S. Genomic Determinants of Hypertension With a Focus on Metabolomics and the Gut Microbiome. Am J Hypertens 2020; 33:473-481. [PMID: 32060494 DOI: 10.1093/ajh/hpaa022] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Revised: 02/10/2020] [Accepted: 02/11/2020] [Indexed: 12/28/2022] Open
Abstract
Epidemiologic and genomic studies have progressively improved our understanding of the causation of hypertension and the complex relationship with diet and environment. The majority of Mendelian forms of syndromic hypotension and hypertension (HTN) have all been linked to mutations in genes whose encoded proteins regulate salt-water balance in the kidney, supporting the primacy of the kidneys in blood pressure regulation. There are more than 1,477 single nucleotide polymorphisms associated with blood pressure and hypertension and the challenge is establishing a causal role for these variants. Hypertension is a complex multifactorial phenotype and it is likely to be influenced by multiple factors including interactions between diet and lifestyle factors, microbiome, and epigenetics. Given the finite genetic variability that is possible in humans, it is likely that incremental gains from single marker analyses have now plateaued and a greater leap in our understanding of the genetic basis of disease will come from integration of other omics and the interacting environmental factors. In this review, we focus on emerging results from the microbiome and metabolomics and discuss how leveraging these findings may facilitate a deeper understanding of the interrelationships between genomics, diet, and microbial ecology in humans in the causation of essential hypertension.
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Affiliation(s)
| | - Cristina Menni
- Department of Twin Research, King’s College London, London, UK
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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45
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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: 161] [Impact Index Per Article: 40.3] [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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Castor KJ, Shenoi S, Edminster SP, Tran T, King KS, Chui H, Pogoda JM, Fonteh AN, Harrington MG. Urine dicarboxylic acids change in pre-symptomatic Alzheimer's disease and reflect loss of energy capacity and hippocampal volume. PLoS One 2020; 15:e0231765. [PMID: 32298384 PMCID: PMC7162508 DOI: 10.1371/journal.pone.0231765] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 03/31/2020] [Indexed: 12/13/2022] Open
Abstract
Non-invasive biomarkers will enable widespread screening and early diagnosis of Alzheimer’s disease (AD). We hypothesized that the considerable loss of brain tissue in AD will result in detection of brain lipid components in urine, and that these will change in concert with CSF and brain biomarkers of AD. We examined urine dicarboxylic acids (DCA) of carbon length 3–10 to reflect products of oxidative damage and energy generation or balance that may account for changes in brain function in AD. Mean C4-C5 DCAs were lower and mean C7-C10 DCAs were higher in the urine from AD compared to cognitively healthy (CH) individuals. Moreover, mean C4-C5 DCAs were lower and mean C7-C9 were higher in urine from CH individuals with abnormal compared to normal CSF amyloid and Tau levels; i.e., the apparent urine changes in AD also appeared to be present in CH individuals that have CSF risk factors of early AD pathology. In examining the relationship between urine DCAs and AD biomarkers, we found short chain DCAs positively correlated with CSF Aβ42, while C7-C10 DCAs negatively correlated with CSF Aβ42 and positively correlated with CSF Tau levels. Furthermore, we found a negative correlation of C7-C10 DCAs with hippocampal volume (p < 0.01), which was not found in the occipital volume. Urine measures of DCAs have an 82% ability to predict cognitively healthy participants with normal CSF amyloid/Tau. These data suggest that urine measures of increased lipoxidation and dysfunctional energy balance reflect early AD pathology from brain and CSF biomarkers. Measures of urine DCAs may contribute to personalized healthcare by indicating AD pathology and may be utilized to explore population wellness or monitor the efficacy of therapies in clinical trials.
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Affiliation(s)
- K. J. Castor
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, United States of America
| | - S. Shenoi
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, United States of America
| | - S. P. Edminster
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, United States of America
| | - T. Tran
- Clinical MR Unit, Huntington Medical Research Institutes, Pasadena, CA, United States of America
| | - K. S. King
- Clinical MR Unit, Huntington Medical Research Institutes, Pasadena, CA, United States of America
| | - H. Chui
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - J. M. Pogoda
- Cipher Biostatistics & Reporting, Reno, NV, United States of America
| | - A. N. Fonteh
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, United States of America
- * E-mail: (ANF); (MGH)
| | - M. G. Harrington
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, United States of America
- * E-mail: (ANF); (MGH)
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47
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Zheng F, Zhou YT, Zeng YF, Liu T, Yang ZY, Tang T, Luo JK, Wang Y. Proteomics Analysis of Brain Tissue in a Rat Model of Ischemic Stroke in the Acute Phase. Front Mol Neurosci 2020; 13:27. [PMID: 32174813 PMCID: PMC7057045 DOI: 10.3389/fnmol.2020.00027] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 02/04/2020] [Indexed: 12/11/2022] Open
Abstract
Background: Stroke is a leading health issue, with high morbidity and mortality rates worldwide. Of all strokes, approximately 80% of cases are ischemic stroke (IS). However, the underlying mechanisms of the occurrence of acute IS remain poorly understood because of heterogeneous and multiple factors. More potential biomarkers are urgently needed to reveal the deeper pathogenesis of IS. Methods: We identified potential biomarkers in rat brain tissues of IS using an iTRAQ labeling approach coupled with LC-MS/MS. Furthermore, bioinformatrics analyses including GO, KEGG, DAVID, and Cytoscape were used to present proteomic profiles and to explore the disease mechanisms. Additionally, Western blotting for target proteins was conducted for further verification. Results: We identified 4,578 proteins using the iTRAQ-based proteomics method. Of these proteins, 282 differentiated proteins, comprising 73 upregulated and 209 downregulated proteins, were observed. Further bioinformatics analysis suggested that the candidate proteins were mainly involved in energy liberation, intracellular protein transport, and synaptic plasticity regulation during the acute period. KEGG pathway enrichment analysis indicated a series of representative pathological pathways, including energy metabolite, long-term potentiation (LTP), and neurodegenerative disease-related pathways. Moreover, Western blotting confirmed the associated candidate proteins, which refer to oxidative responses and synaptic plasticity. Conclusions: Our findings highlight the identification of candidate protein biomarkers and provide insight into the biological processes involved in acute IS.
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Affiliation(s)
- Fei Zheng
- College of Electrical and Information Engineering, Hunan University, Changsha, China
| | - Yan-Tao Zhou
- College of Electrical and Information Engineering, Hunan University, Changsha, China
| | - Yi-Fu Zeng
- College of Electrical and Information Engineering, Hunan University, Changsha, China
| | - Tao Liu
- Laboratory of Ethnopharmacology, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Zhao-Yu Yang
- Laboratory of Ethnopharmacology, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Tao Tang
- Laboratory of Ethnopharmacology, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Jie-Kun Luo
- Laboratory of Ethnopharmacology, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Yang Wang
- Laboratory of Ethnopharmacology, Institute of Integrative Medicine, Xiangya Hospital, Central South University, Changsha, China
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Integrated metabolome analysis reveals novel connections between maternal fecal metabolome and the neonatal blood metabolome in women with gestational diabetes mellitus. Sci Rep 2020; 10:3660. [PMID: 32107447 PMCID: PMC7046769 DOI: 10.1038/s41598-020-60540-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 02/13/2020] [Indexed: 12/11/2022] Open
Abstract
Gestational Diabetes Mellitus (GDM), which is correlated with changes in the gut microbiota, is a risk factor for neonatal inborn errors of metabolism (IEMs). Maternal hyperglycemia exerts epigenetic effects on genes that encode IEM-associated enzymes, resulting in changes in the neonatal blood metabolome. However, the relationship between maternal gut microbiota and the neonatal blood metabolome remains poorly understood. This study aimed at understanding the connections between maternal gut microbiota and the neonatal blood metabolome in GDM. 1H-NMR-based untargeted metabolomics was performed on maternal fecal samples and targeted metabolomics on the matched neonatal dry blood spots from a cohort of 40 pregnant women, including 22 with GDM and 18 controls. Multi-omic association methods (including Co-Inertia Analysis and Procrustes Analysis) were applied to investigate the relationship between maternal fecal metabolome and the neonatal blood metabolome. Both maternal fecal metabolome and the matched neonatal blood metabolome could be separated along the vector of maternal hyperglycemia. A close relationship between the maternal and neonatal metabolomes was observed by multi-omic association approaches. Twelve out of thirty-two maternal fecal metabolites with altered abundances from 872 1H- NMR features (Bonferroni-adjusted P < 0.05) in women with GDM and the controls were identified, among which 8 metabolites contribute (P < 0.05 in a 999-step permutation test) to the close connection between maternal and the neonatal metabolomes in GDM. Four of these eight maternal fecal metabolites, including lysine, putrescine, guanidinoacetate, and hexadecanedioate, were negatively associated (Spearman rank correlation, coefficient value < −0.6, P < 0.05) with maternal hyperglycemia. Biotin metabolism was enriched (Bonferroni-adjusted P < 0.05 in the hypergeometric test) with the four-hyperglycemia associated fecal metabolites. The results of this study suggested that maternal fecal metabolites contribute to the connections between maternal fecal metabolome and the neonatal blood metabolome and may further affect the risk of IEMs.
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Recruiting Control Participants into Stroke Biomarker Studies. Transl Stroke Res 2020; 11:861-870. [PMID: 31912324 DOI: 10.1007/s12975-020-00780-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 11/25/2019] [Accepted: 01/02/2020] [Indexed: 10/25/2022]
Abstract
The number of scientists using -omics technologies to investigate biomarkers with the potential to gauge risk and aid in the diagnosis, treatment, and prognosis of stroke continues to rise, yet there are few resources to aid investigators in recruiting control participants. In this review, we describe two major strategies to match control participants to a stroke cohort-propensity score matching and one-to-one matching-including statistical approaches to gauge the balance between groups. We then explore the advantages and disadvantages of traditional recruitment methods including approaching spouses of enrolled stroke participants, direct recruitment from clinics, community outreach events, approaching retirement communities, and buying samples from a 3rd party vendor. Newer methods to identify controls by screening the electronic health record and using an online screening questionnaire are also described. Finally, we cover compensation for control participants and special considerations. The hope is that this review will serve as a roadmap whereby an investigator can successfully tailor their control recruitment strategy to the research question at hand and the local research environment. While this review is focused on blood-based biomarker studies, the principles will apply to investigators studying a broad range of biological materials.
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50
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Ke C, Pan CW, Zhang Y, Zhu X, Zhang Y. Metabolomics facilitates the discovery of metabolic biomarkers and pathways for ischemic stroke: a systematic review. Metabolomics 2019; 15:152. [PMID: 31754808 DOI: 10.1007/s11306-019-1615-1] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2018] [Accepted: 11/11/2019] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Ischemic stroke (IS) is a major contributor to the global disease burden, and effective biomarkers for IS management in clinical practice are urgently needed. Metabolomics can detect metabolites that are small enough to cross the blood-brain barrier in a high-throughput manner, and thus represents a powerful tool for discovering biomarkers of IS. OBJECTIVES In this study, we conducted a systematic review to identify potential metabolic biomarkers and pathways that might facilitate risk predictions, clinical diagnoses, the recognition of complications, predictions of recurrence and an understanding of the pathogenesis of IS. METHODS The PubMed and Web of Science databases were searched for relevant studies published between January 2000 and July 2019. The study objectives, study designs and reported metabolic biomarkers were systematically examined and compared. Pathway analysis was performed using the MetaboAnalyst online software. RESULTS Twenty-eight studies were included in this systematic review. Many consistent metabolites, including isoleucine, leucine, valine, glycine, lysine, glutamate, LysoPC(16:0), LysoPC(18:2), serine, uric acid, citrate and palmitic acid, possess potential as biomarkers of IS. Metabolic pathways and dysregulations that are implicated in excitotoxicity, inflammation, apoptosis, oxidative stress, neuroprotection, energy failure, and elevation of intracellular Ca2+ levels, were indicated as playing important roles in the development and progression of IS. CONCLUSIONS This systematic review summarizes potential metabolic biomarkers and pathways related to IS, which may provide opportunities for the construction of diagnostic or predictive models for IS and the discovery of novel therapeutic targets.
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Affiliation(s)
- Chaofu Ke
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, People's Republic of China
| | - Chen-Wei Pan
- School of Public Health, Medical College of Soochow University, Suzhou, 215123, China
| | - Yuxia Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, People's Republic of China
| | - Xiaohong Zhu
- Suzhou Industrial Park Centers for Disease Control and Prevention (Institute of Health Inspection and Supervision), Suzhou, 215021, Jiangsu, People's Republic of China
| | - Yonghong Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, 199 Renai Road, Suzhou, 215123, People's Republic of China.
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