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1.
Cardiovasc Diabetol ; 22(1): 219, 2023 08 24.
Article in English | MEDLINE | ID: mdl-37620823

ABSTRACT

BACKGROUND: Clinical observations suggest a complex relationship between obesity and coronary artery disease (CAD). This study aimed to characterize the intermediate metabolism phenotypes among obese patients with CAD and without CAD. METHODS: Sixty-two participants who consecutively underwent coronary angiography were enrolled in the discovery cohort. Transcriptional and untargeted metabolomics analyses were carried out to screen for key molecular changes between obese patients with CAD (CAD obese), without CAD (Non-CAD obese), and Non-CAD leans. A targeted GC-MS metabolomics approach was used to further identify differentially expressed metabolites in the validation cohorts. Regression and receiver operator curve analysis were performed to validate the risk model. RESULTS: We found common aberrantly expressed pathways both at the transcriptional and metabolomics levels. These pathways included cysteine and methionine metabolism and arginine and proline metabolism. Untargeted metabolomics revealed that S-adenosylhomocysteine (SAH), 3-hydroxybenzoic acid, 2-hydroxyhippuric acid, nicotinuric acid, and 2-arachidonoyl glycerol were significantly elevated in the CAD obese group compared to the other two groups. In the validation study, targeted cysteine and methionine metabolomics analyses showed that homocysteine (Hcy), SAH, and choline were significantly increased in the CAD obese group compared with the Non-CAD obese group, while betaine, 5-methylpropanedioic acid, S-adenosylmethionine, 4-PA, and vitamin B2 (VB2) showed no significant differences. Multivariate analyses showed that Hcy was an independent predictor of obesity with CAD (hazard ratio 1.7; 95%CI 1.2-2.6). The area under the curve based on the Hcy metabolomic (HCY-Mtb) index was 0.819, and up to 0.877 for the HCY-Mtb.index plus clinical variables. CONCLUSION: This is the first study to propose that obesity with hyperhomocysteinemia is a useful intermediate metabolism phenotype that could be used to identify obese patients at high risk for developing CAD.


Subject(s)
Coronary Artery Disease , Hyperhomocysteinemia , Obesity , Humans , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/etiology , Coronary Artery Disease/genetics , Coronary Artery Disease/metabolism , Cross-Sectional Studies , Cysteine , East Asian People , Hyperhomocysteinemia/complications , Hyperhomocysteinemia/genetics , Hyperhomocysteinemia/metabolism , Metabolomics , Obesity/complications , Obesity/genetics , Obesity/metabolism , Prospective Studies , Risk Factors , Transcriptome , Coronary Angiography , Cardiometabolic Risk Factors , Adult , Middle Aged , Aged
2.
Ann Med ; 55(2): 2236640, 2023.
Article in English | MEDLINE | ID: mdl-37851510

ABSTRACT

BACKGROUND: The prognostic value of the Gustave Roussy immune (GRIm) score in cancer patients has been widely reported but remains inconsistent. The aim of this study is to systematically investigate the relationship between the GRIm score and survival outcomes in cancer patients. METHODS: Relevant literature was identified using electronic databases including Web of Science, PubMed, and Embase from the inception to March 2023. The primary endpoints were long-term oncological outcomes. Subgroup analysis and sensitivity analysis were conducted during the meta-analysis. RESULTS: Fifteen studies (20 cohorts) including 4997 cancer patients were enrolled. The combined results revealed that patients in the high GRIm group had a deteriorated overall survival (HR = 2.07 95%CI: 1.73-2.48; p < 0.0001; I2 = 62%) and progression-free survival (HR = 1.42; 95%CI: 1.22-1.66; p < 0.0001; I2 = 36%). The prognostic values of GRIm on overall survival and progression-free survival were observed across various tumour types and tumour stages. Sensitivity analysis supported the stability and reliability of the above results. CONCLUSION: Our evidence suggested that the GRIm score could be a valuable prognostic marker in cancer patients, which can be used by clinicians to stratify patients and formulate individualized treatment plans.


Subject(s)
Neoplasms , Humans , Prognosis , Reproducibility of Results , Neoplasms/diagnosis , Progression-Free Survival
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