Integrated Bulk and Single-Cell Transcriptomic Analysis Prioritizes Candidate Paraptosis-Related Genes in Painful Diabetic Peripheral Neuropathy.

Painful diabetic peripheral neuropathy (PDPN) is among the most disabling complications of diabetes, but its molecular features and underlying biological mechanisms remain incompletely understood. Paraptosis, a non-canonical form of programmed cell death characterized by endoplasmic reticulum/mitochondrial swelling and cytoplasmic vacuolization, is associated with endoplasmic reticulum and mitochondrial stress, processes that are also implicated in diabetic neuropathy, but its potential involvement in PDPN remains unclear. This study applied an exploratory integrative strategy that combined peripheral blood bulk transcriptomic data from 12 patients with PDPN and 12 healthy controls, together with publicly available single-cell transcriptomic data from human peripheral nerve tissue (GSE266026), comprising samples from patients with DPN and traumatic limb amputation (TLA) comparators. Candidate genes were identified by intersecting differentially expressed genes with a paraptosis-related gene set, and were prioritized using LASSO, SVM-RFE, and random forest. The biological context of the prioritized genes was further explored through immune infiltration analysis, two-sample Mendelian randomization, single-cell characterization, and scTenifoldKnk-based computational virtual knockout analysis. Fifteen paraptosis-related differentially expressed genes were identified, with a significantly elevated paraptosis-related score in PDPN. AKT1, CASP9, and EIF2S1 were prioritized by all three machine-learning methods. Computational immune-cell deconvolution estimated increased the estimated neutrophil abundance and decreased the estimated CD8⁺ T-cell and resting memory CD4⁺ T-cell abundance in PDPN blood, with distinct correlations between the three candidate genes and inferred immune-cell profiles. Mendelian randomization provided evidence consistent with a potential association between genetically proxied higher AKT1 expression and diabetic polyneuropathy risk. Single-cell analysis revealed cell type-specific expression patterns of the three candidate genes, while computational virtual knockout analyses predicted gene-regulatory perturbations involving immune-inflammatory, neuronal structural, and cell-adhesion pathways within the respective network backgrounds. This exploratory integrative analysis prioritizes AKT1, CASP9, and EIF2S1 as candidate paraptosis-related genes associated with PDPN and provides a biological context for further mechanistic and experimental investigation.