Early metabolomics revealed the sensitivity of sacubitril/valsartan to person with end-stage renal disease accompanied by heart failure.

Heart failure (HF) is a major complication in patients with end-stage renal disease (ESRD) and is the leading cause of death in this high-risk population. Sacubitril/Valsartan is an angiotensin receptor-neprilysin inhibitor (ARNI) that has been shown to improve treatment outcomes in patients with ESRD accompanied by HF. Unfortunately, in clinical practice, some patients who received sacubitril/valsartan treatment not only did not show a good therapeutic effect, but also got worse with the passage of time. To explore potential biomarkers for predicting the clinical efficacy of sacubitril/valsartan, serum samples were prospectively collected upon admission and again collected after sacubitril/valsartan treatment was completed. Patients were divided into good response group (GR) and poor response group (PR). At the same time, samples before treatment were divided into GR group and PR group by sample tracing and matching, and metabolomics analysis was conducted. In the end, a total of 9 different metabolites were identified between patients in the early GR and PR groups. In order to find more effective biomarkers, two algorithms, random forest (RF) and support vector machine (SVM), were used for metabolite selection and performance evaluation, and three kinds of Lysophosphatidylcholine (LysoPC) metabolites showed good predictive effect, and the expression of the enzyme phospholipase A2 group IVA (PLA2G4A), associated with this metabolite was significantly elevated in the PR group. The disordered metabolism may reduce the sensitivity of patients to sacubitril/valsartan treatment, and PLA2G4A targeted inhibitors may be a promising therapeutic strategy to improve the sensitivity of patients with ESRD and HF to sacubitril/valsartan treatment.