Elevated circulating HHIP levels in patients with metabolic syndrome

Abstract

Abnormal fat accumulation can lead to metabolic syndrome (MetS), increasing the risk of diabetes and cardiovascular disease in MetS patients. Early identification of MetS risk is essential for effective disease prevention. Using bioinformatics methods, we sought biomarkers for MetS. After analyzing the GSE9624 and GSE15524 datasets, we identified three commonly differentially expressed genes: COX7A1, PRR12, and HHIP. Subsequently, we validated the expression of these DEGs using the GSE65540 dataset. Quantitative PCR and immunoblotting confirmed significantly elevated HHIP expression in the adipose tissue of HFD-fed and ob/ob mice. Furthermore, a population-based cohort study demonstrated that serum HHIP levels were significantly greater in MetS patients than in healthy controls and were correlated with all MetS components. Receiver operating characteristic (ROC) curve analysis confirmed the robust predictive capacity of HHIP levels for metabolic syndrome, with an area under the curve (AUC) of 0.72 (95 % confidence interval: 0.68–0.78, P < 0.001). Binary logistic regression showed that the serum HHIP concentration was significantly associated with MetS even after adjusting for anthropometric and lipid profile variables. In conclusion, our findings demonstrate that changes in HHIP expression are significantly associated with adverse MetS indicators, indicating that HHIP can serve as a new biomarker for the diagnosis of MetS.