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Zhang Y, Xia Z, Cai X, Su X, Jin A, Mei L, Jing J, Wang S, Meng X, Li S, Wang M, Wei T, Wang Y, He Y, Pan Y. Association of metabolic dysfunction-associated fatty liver disease with systemic atherosclerosis: a community-based cross-sectional study. Cardiovasc Diabetol 2023; 22:342. [PMID: 38093371 PMCID: PMC10720122 DOI: 10.1186/s12933-023-02083-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Data are limited on the association of metabolic dysfunction-associated fatty liver disease (MAFLD) with systemic atherosclerosis. This study aimed to examine the relationship between MAFLD and the extent of atherosclerotic plaques and stenosis, and presence of polyvascular disease (PolyVD). METHODS In this cross-sectional study, MAFLD was diagnosed based on the presence of metabolic dysfunction (MD) and fatty liver disease (FLD). MAFLD was divided into three subtypes: MAFLD with diabetes mellitus (DM), MAFLD with overweight or obesity (OW), as well as MAFLD with lean/normal weight and at least two metabolic abnormalities. Atherosclerosis was evaluated, with vascular magnetic resonance imaging for intracranial and extracranial arteries, thoracoabdominal computed tomography angiography for coronary, subclavian, aorta, renal, iliofemoral arteries, and ankle-brachial index for peripheral arteries. The extent of plaques and stenosis was defined according to the number of these eight vascular sites affected. PolyVD was defined as the presence of stenosis in at least two vascular sites. RESULTS This study included 3047 participants, with the mean age of 61.2 ± 6.7 years and 46.6% of male (n = 1420). After adjusting for potential confounders, MAFLD was associated with higher extent of plaques (cOR, 2.14, 95% CI 1.85-2.48) and stenosis (cOR, 1.47, 95% CI 1.26-1.71), and higher odds of presence of PolyVD (OR, 1.55, 95% CI 1.24-1.94) as compared with Non-MAFLD. In addition, DM-MAFLD and OW-MAFLD were associated with the extent of atherosclerotic plaques and stenosis, and presence of PolyVD (All P < 0.05). However, lean-MAFLD was only associated with the extent of atherosclerotic plaques (cOR, 1.63, 95% CI 1.14-2.34). As one component of MAFLD, FLD per se was associated with the extent of plaques and stenosis in participants with MAFLD. Furthermore, FLD interacted with MD to increase the odds of presence of systemic atherosclerosis (P for interaction ≤ 0.055). CONCLUSIONS MAFLD and its subtypes of DM-MAFLD and OW-MAFLD were associated with the extent of atherosclerotic plaques and stenosis, and presence of PolyVD. This study implicated that FLD might be a potential target of intervention for reducing the deleterious effects of MAFLD on systemic atherosclerosis.
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Affiliation(s)
- Yanli Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhang Xia
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xueli Cai
- Department of Neurology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Xin Su
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Aoming Jin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Lerong Mei
- Cerebrovascular Research Lab, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Suying Wang
- Department of Neurology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
- Cerebrovascular Research Lab, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Xia Meng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shan Li
- Cerebrovascular Research Lab, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Mengxing Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tiemin Wei
- Department of Cardiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
- Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, China.
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
| | - Yan He
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119, South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, China.
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Shan D, Xu D, Hu S, Qi P, Lu J, Wang D. LC-MS/MS based metabolomic analysis of serum from patients with cerebrovascular stenosis. J Pharm Biomed Anal 2023; 235:115608. [PMID: 37527609 DOI: 10.1016/j.jpba.2023.115608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/26/2023] [Accepted: 07/26/2023] [Indexed: 08/03/2023]
Abstract
Cerebrovascular stenosis (CVS) is the main cause of ischemic stroke, which greatly threatens human life. Hence, it's important to perform early screenings for CVS. Metabolomics is an emerging omics approach that has great advantages in disease screening and diagnosis. Therefore, we aim to elucidate the correlation between CVS and metabolomics, which can aid in conducting CVS screening at an early stage. Patients with CVS in Beijing Hospital were included in the study. A total of 36 participants, including 18 patients diagnosed with CVS and 18 healthy individuals, were recruited at Beijing Hospital between May 2022 and October 2021. The serum samples were analyzed for liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, multivariate statistical methods, including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed. Differential metabolites were obtained and demonstrated by volcano plot and heatmap. The study recruited 36 participants, including 18 patients with CVS and 18 healthy participants. A total of 150 metabolites were identified. Multivariate statistical analysis revealed significant differences between patients and healthy participants. Furthermore, 30 serum metabolites levels differed significantly between two groups. Differential metabolites were enriched in phenylalanine, tyrosine, and tryptophan biosynthesis; primary bile acid biosynthesis, and other pathways. This study identified differential metabolites in patients with CVS and elucidated the relevant metabolic pathways. Thus, these findings aid in the study of the pathogenesis of CVS and its early diagnosis. DATA AVAILABILITY STATEMENT: The datasets generated for this study are available on request to the corresponding author.
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Affiliation(s)
- Dezhi Shan
- Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China
| | - Dingkang Xu
- Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China
| | - Shen Hu
- Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Peng Qi
- Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Jun Lu
- Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Daming Wang
- Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China.
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Lei F, Wang XM, Wang C, Huang X, Liu YM, Qin JJ, Zhang P, Ji YX, She ZG, Cai J, Li HP, Zhang XJ, Li H. Metabolic dysfunction-associated fatty liver disease increased the risk of subclinical carotid atherosclerosis in China. Front Endocrinol (Lausanne) 2023; 14:1109673. [PMID: 37082131 PMCID: PMC10110917 DOI: 10.3389/fendo.2023.1109673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 03/21/2023] [Indexed: 04/07/2023] Open
Abstract
Background and aimsMetabolic dysfunction-associated fatty liver disease (MAFLD) was proposed to substitute NAFLD in 2020. This new term highlights the systematic metabolic disturbances that accompany fatty liver. We evaluated the correlations between MAFLD and subclinical carotid atherosclerosis (SCA) based on a nationwide health examination population in China.MethodsWe performed a nationwide cross-sectional population and a Beijing retrospective cohort from 2009 to 2017. SCA was defined as elevated carotid intima-media thickness. The multivariable logistic and Cox models were used to analyze the association between MAFLD and SCA.Results153,482 participants were included in the cross-sectional study. MAFLD was significantly associated with SCA in fully adjusted models, with an odds ratio of 1.66; 95% confidence interval (CI): 1.62-1.70. This association was consistent in the cohort, with a hazard ratio (HR) of 1.31. The association between baseline MAFLD and incident SCA increased with hepatic steatosis severity. Subgroup analysis showed an interaction between age and MAFLD, with a higher risk in younger groups (HR:1.67, 95% CI: 1.17-2.40).ConclusionIn this large cross-section and cohort study, MAFLD was significantly associated with the presence and development of SCA. Further, the risk was higher among MAFLD individuals with high hepatic steatosis index and young adults.
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Affiliation(s)
- Fang Lei
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Xiao-Ming Wang
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Changquan Wang
- Department of Neurology, Huanggang Central Hospital of Yangtze University, Huanggang, China
- Huanggang Institute of Translational Medicine, Huanggang Central Hospital of Yangtze University, Huanggang, China
| | - Xuewei Huang
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Ye-Mao Liu
- Institute of Model Animal, Wuhan University, Wuhan, China
- Huanggang Institute of Translational Medicine, Huanggang Central Hospital of Yangtze University, Huanggang, China
- Department of Cardiology, Huanggang Central Hospital of Yangtze University, Huanggang, China
| | - Juan-Juan Qin
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Peng Zhang
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Yan-Xiao Ji
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Zhi-Gang She
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Jingjing Cai
- Institute of Model Animal, Wuhan University, Wuhan, China
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Huo-ping Li
- Huanggang Institute of Translational Medicine, Huanggang Central Hospital of Yangtze University, Huanggang, China
- Department of Cardiology, Huanggang Central Hospital of Yangtze University, Huanggang, China
- *Correspondence: Hongliang Li, ; Xiao-Jing Zhang, ; Huo-ping Li,
| | - Xiao-Jing Zhang
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
- *Correspondence: Hongliang Li, ; Xiao-Jing Zhang, ; Huo-ping Li,
| | - Hongliang Li
- Department of Cardiology, Renmin Hospital, School of Basic Medical Science, Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
- Huanggang Institute of Translational Medicine, Huanggang Central Hospital of Yangtze University, Huanggang, China
- Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Hongliang Li, ; Xiao-Jing Zhang, ; Huo-ping Li,
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