A four-gene signature for diagnosis of acute kidney injury following kidney transplantation.

Abstract

Acute kidney injury (AKI) is a common and severe complication following renal transplantation, largely driven by ischemia-reperfusion injury (IRI). However, reliable biomarkers for post-transplant AKI remain unavailable. In this study, we analyzed transcriptomic datasets from multiple cohorts to identify robust gene signatures associated with transplant-related AKI. Weighted gene co-expression network and differential expression analyses in the discovery cohort revealed 222 candidate genes altered during early allograft IRI, which were subsequently refined in an integrated training cohort using least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) to a four-gene signature comprising <i>SOCS3</i>, <i>MYC</i>, <i>TGIF1</i>, and <i>LETM2</i>. This signature showed excellent discriminative performance in the training cohort (10-fold cross-validation AUC = 0.969) and was validated in independent external datasets, including a large cohort (AUC = 0.942). Decision curve analyses indicated potential clinical utility for early AKI identification across a broad threshold-probability range, with favorable performance compared with several established biomarkers such as neutrophil gelatinase-associated lipocalin. Single-cell transcriptomics revealed cell type-specific expression of the four genes across renal compartments. Moreover, their protein levels were elevated at 24&#x2009;h after IRI in mouse kidneys, and displayed high expression in human AKI biopsies. Additionally, serum protein levels of SOCS3 and LETM2 were elevated in patients with cardiac surgery-associated AKI, whereas TGIF1 and MYC did not reach statistical significance. Collectively, this study identified a four-gene signature with potential utility as an early diagnostic biomarker panel for post-transplant AKI. Further large-scale clinical trials are needed to validate its diagnostic efficacy. Post-transplant AKI is often driven by ischemia&#x2013;reperfusion injury and is associated with poor graft outcomes, but early molecular biomarkers remain limited.This study adds: We identified and validated a four-gene signature consisting of SOCS3, MYC, TGIF1, and LETM2 for detecting post-transplant AKI.Potential impact: The four-gene signature may serve as a potential early diagnostic biomarker panel for post-transplant AKI, pending validation in larger clinical studies.