# Genotype–Phenotype Correlation of TNF-α (−238, rs361525) and Cystatin C for Early Detection of Sepsis-Associated AKI and Its Severity in Critically Ill Neonates

## TL;DR

This study explores how genetic variations and a protein marker can help detect kidney injury in critically ill newborns caused by sepsis.

## Contribution

The study identifies a novel combination of TNF-α genotype and cystatin C as a diagnostic and prognostic biomarker for sepsis-associated acute kidney injury in neonates.

## Key findings

- GA + AA genotypes of TNF-α (−238, rs361525) are strong predictors of sepsis-associated AKI risk.
- Elevated cystatin C levels are a sensitive biomarker for adverse outcomes in these patients.
- Combining genotype and cystatin C improves early detection and severity prediction of S-AKI.

## Abstract

Sepsis-associated acute kidney injury (S-AKI) represents a significant health problem associated with adverse outcomes. Our study aimed to assess the value of serum cystatin-C (sCysC) and TNF-α (rs361525) in combination for diagnosing S-AKI patients and predicting their adverse outcomes. The study included 100 critically ill neonates and 100 controls. Patients were categorized into an S-AKI group and a non-AKI group. TNF-α (−238, rs361525) genotyping was performed using RT-PCR, and sCysC was assessed using ELISA. Our study showed a fundamental difference in the genotype frequencies of TNF-α (−238, rs361525) and SNP between S-AKI and non-AKI patients. Furthermore, there was a significant relationship between cystatin C and TNF-α (−238, rs361525), where cystatin C was higher in patients with AA alleles than in patients with GA and GG alleles. Combining GA + AA genotypes with elevated serum cystatin-C levels can serve as a potential diagnostic and prognostic biomarker for AKI development in this population. The GA/AA genotypes independently predicted S-AKI risk (OR = 6.64, p < 0.001). At the same time, elevated sCysC (>9.4 mg/L) emerged as a sensitive biomarker (AUC = 0.848) and independent predictor of adverse outcomes. Collectively, these findings contribute to the growing field of personalized medicine and represent a strategic advantage, enabling prevention-focused care rather than the treatment of established disease.