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Liang H, Li F, Zhang L, Li L, Guo B. Ceramides and pro-inflammatory cytokines for the prediction of acute coronary syndrome: a multi-marker approach. BMC Cardiovasc Disord 2024; 24:47. [PMID: 38218768 PMCID: PMC10788003 DOI: 10.1186/s12872-023-03690-1] [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: 11/23/2023] [Accepted: 12/24/2023] [Indexed: 01/15/2024] Open
Abstract
BACKGROUND There is a growing body of evidence supporting the significant involvement of both ceramides and pro-inflammatory cytokines in the occurrence and progression of acute coronary syndrome (ACS). METHODS This study encompassed 216 participants whose laboratory variables were analysed using standardised procedures. Parameters included baseline serum lipid markers, comprising total cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, triglycerides (TGs), lipoprotein(a) (LPa), fasting blood glucose, B-natriuretic peptide and hypersensitive C-reactive protein. Liquid chromatography-tandem mass spectrometry measured the concentrations of plasma ceramides. Enzyme-linked immunosorbent assay quantified tumour necrosis factor-α (TNF-α), interleukin 6 (IL6) and IL8. The correlation between ceramides and inflammatory factors was determined through Pearson's correlation coefficient. Receiver operating characteristic (ROC) curve analysis and multivariate logistic regression evaluated the diagnostic potential of models incorporating traditional risk factors, ceramides and pro-inflammatory cytokines in ACS detection. RESULTS Among the 216 participants, 138 (63.89%) were diagnosed with ACS. Univariate logistic regression analysis identified significant independent predictors of ACS, including age, gender, history of diabetes, smoking history, TGs, TNF-α, IL-6, ceramide (d18:1/16:0), ceramide (d18:1/18:0), ceramide (d18:1/24:0), ceramide (d18:1/20:0) and ceramide (d18:1/22:0). Multivariate logistic regression analysis revealed significant associations between gender, diabetes mellitus history, smoking history, LPa, IL-6, ceramide (d18:1/16:0) and ACS. Receiver operating characteristic analysis indicated that model 4, which integrated traditional risk factors, IL-6 and ceramide (d18:1/16:0), achieved the highest area under the curve (AUC) of 0.827 (95% CI 0.770-0.884), compared with model 3 (traditional risk factors and ceramide [d18:1/16:0]) with an AUC of 0.782 (95% CI 0.720-0.845) and model 2 (traditional risk factors and IL-6), with an AUC of 0.785 (95% CI 0.723-0.846) in ACS detection. CONCLUSIONS In summary, incorporating the simultaneous measurement of traditional risk factors, pro-inflammatory cytokine IL-6 and ceramide (d18:1/16:0) can improve the diagnostic accuracy of ACS.
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Affiliation(s)
- Huiqing Liang
- Department of Internal Medicine, Hebei Medical University, Shijiazhuang, 050000, China
- Department of Cardiology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, China
| | - Fangjiang Li
- Department of Cardiology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, China
| | - Liang Zhang
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, 100020, China
| | - Lin Li
- Beijing Health Biotech Co. Ltd, Beijing, 102200, China
| | - Bingyan Guo
- Department of Internal Medicine, Hebei Medical University, No 361 Zhongshan East Road, Changan District, Shijiazhuang, 050000, China.
- Department of Cardiovascular Medicine, The Second Hospital of Hebei Medical University, Heping West Road No. 215, Shijiazhuang, 050000, China.
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Yu B, Hu M, Jiang W, Ma Y, Ye J, Wu Q, Guo W, Sun Y, Zhou M, Xu Y, Wu Z, Wang Y, Lam SM, Shui G, Gu J, Li JZ, Fu Z, Gong Y, Zhou H. Ceramide d18:1/24:1 as a potential biomarker to differentiate obesity subtypes with unfavorable health outcomes. Lipids Health Dis 2023; 22:166. [PMID: 37794463 PMCID: PMC10548646 DOI: 10.1186/s12944-023-01921-0] [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: 05/08/2023] [Accepted: 09/11/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND The criteria for metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) remain controversial. This research aimed to identify a potential biomarker to differentiate the subtypes of obesity. METHODS The study conducted a lipidomic evaluation of ceramide in the serum of 77 Chinese adults who had undergone hyperinsulinemic-euglycemic clamps. These adults were divided into three groups according to the clinical data: normal weight control group (N = 21), MHO (N = 20), and MUO (N = 36). RESULTS The serum Cer d18:1/24:1 level in the MHO group was lower than that in the MUO group. As the Cer d18:1/24:1 level increased, insulin sensitivity decreased, and the unfavorable parameters increased in parallel. Multivariate logistic regression analysis revealed that serum Cer d18:1/24:1 levels were independently correlated with MUO in obesity. Individuals with higher levels of Cer d18:1/24:1 also had an elevated risk of cardiovascular disease. Most ceramide subtype levels increased in obesity compared to normal-weight individuals, but the levels of serum Cer d18:0/18:0 and Cer d18:1/16:0 decreased in obesity. CONCLUSIONS The relationships between ceramide subtypes and metabolic profiles might be heterogeneous in populations with different body weights. Cer d18:1/24:1 could be a biomarker that can be used to differentiate MUO from MHO, and to better predict who will develop unfavorable health outcomes among obese individuals. TRIAL REGISTRATION The First Affiliated Hospital of Nanjing Medical University's Institutional Review Board authorized this study protocol, and all participants provided written informed consent (2014-SR-003) prior to study entry.
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Affiliation(s)
- Baowen Yu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Moran Hu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wanzi Jiang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yizhe Ma
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jingya Ye
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qinyi Wu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wen Guo
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yan Sun
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Min Zhou
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yiwen Xu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhoulu Wu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yiwen Wang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Sin Man Lam
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Guanghou Shui
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Jingyu Gu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - John Zhong Li
- Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhenzhen Fu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Yingyun Gong
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Hongwen Zhou
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, China.
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