Integrative Transcriptomics and Machine Learning Nominate IL15– and PPP2R1A-Centered Programs in PTSD Using Pathway-Informed Autonomic-Cardiac Gene Prioritization

Int J Mol Sci. 2026 Sep 29;27(19):8710. doi: 10.3390/ijms27198710.

ABSTRACT

Post-traumatic stress disorder (PTSD) is associated with immune and autonomic disturbances, but molecular programs linking PTSD-related blood transcriptional signals with autonomic-cardiac biology remain incompletely characterized. The public Gene Expression Omnibus (GEO) cohorts analyzed here did not directly measure palpitations or autonomic dysfunction. Peripheral-blood transcriptomes from GSE81761 and GSE63878 were integrated with a prespecified pathway-derived autonomic-cardiac gene set constructed from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Genes overlapping the curated pathway set were assessed using functional enrichment and protein-protein interaction (PPI) analyses. Multi-algorithm comparison and a separate random-forest/SHapley Additive exPlanations (SHAP) analysis were performed for internal model assessment and biological prioritization. GSE64813 and GSE97356 were analyzed using targeted single-gene analyses and cohort-specific multivariable logistic models. Model performance was examined using repeated nested cross-validation, a fully nested sensitivity analysis, and locked-transfer testing to GSE64813 and GSE97356. Interleukin 15 (IL15) and protein phosphatase 2 scaffold subunit Aalpha (PPP2R1A) were evaluated using external-cohort analyses, immune-cell deconvolution, and descriptive postmortem hippocampal single-nucleus data. Among 1679 nominally significant PTSD-associated candidate genes, 92 overlapped the curated pathway set and were enriched for cytokine signaling, chemotaxis, apoptosis, calcium transport, and PP2A-related functions. PPI analysis yielded 37 recurrent candidate hub genes. The original model comparison ranked support-vector machine (SVM) the highest across the merged and source-cohort summaries [mean area under the receiver-operating-characteristic curve (AUC) 0.853], but these estimates represent internal discovery-stage performance. IL15 was recurrently prioritized by network-based analyses, whereas PPP2R1A was a component of an enriched phosphatase-related module. IL15 and PPP2R1A showed modest single-gene effects in GSE64813 (AUC 0.566 and 0.612) and GSE97356 (AUC 0.558 and 0.593). Cohort-specific refitted models showed apparent AUC values of 0.834 and 0.749, respectively. Repeated nested cross-validation conditional on the preselected 29-gene feature set identified L2-regularized logistic regression as the best-performing algorithm (mean AUC = 0.690). Importantly, a more stringent fully nested sensitivity analysis, in which differential-expression screening and pathway intersection were repeated within each outer training fold, yielded a mean repeated outer-cross-validated AUC of 0.593 [standard deviation (SD) = 0.033; range, 0.541-0.625], indicating limited predictive performance. Locked-transfer AUCs were 0.664 in GSE64813 and 0.534 in GSE97356. Single-nucleus summaries suggested donor- and nucleus-type-dependent expression patterns for IL15 and PPP2R1A. These findings identify IL15-related cytokine signaling and PPP2R1A-related phosphatase regulation as candidate molecular programs linking PTSD-associated transcriptional variation with pathway-derived autonomic-cardiac biology. The results should therefore be interpreted as hypothesis-generating rather than direct molecular evidence for unmeasured palpitation symptoms. Prospective validation in independent, clinically well-characterized cohorts with standardized autonomic and cardiac phenotyping is warranted.

PMID:42883953 | DOI:10.3390/ijms27198710