Immunometabolic Stratification of Autism Spectrum Disorder by CD4+ T-Cell Phenotype Reveals Subtype-Specific Energetic Deficit and Coordinated Suppression of Micronutrient Acquisition Pathways

Background: Autism spectrum disorder (ASD) is associated with immune dysregulation in a subset of individuals, though findings remain heterogeneous and poorly defined, particularly regarding immune subtypes and metabolic context. Methods: We analyzed whole-blood microarray data from GSE18123 (GPL570: ASD n = 46, controls n = 19; GPL6244: ASD n = 68, controls n = 21) using an integrated immunometabolic framework. CD4+ T-cell transcriptional programs were used to assign dominant immune phenotypes (TH1, TH2, TH17, Tfh, FOXP3+ Treg, Tr1-like). Metabolic demand was quantified via the τ-axis; execution capacity was assessed using cytosolic and mitochondrial energy compensation ratios (CECR, MECR). Induction–execution mismatch was captured by three Gap metrics (Cytosolic, Warburg, Global). Functional validation correlated these metrics with transcriptional signatures of folate transport, one-carbon metabolism, receptor-mediated micronutrient uptake (LRP2–CUBN–AMN), cobalamin processing, and vitamin D activation across both platforms. Results: Six immunometabolic CD4+ subtypes were identified within ASD. τ-axis discrimination was strongest for Tr1-like (AUC = 0.811) and Tfh (AUC = 0.825) states, while TH17 profiles were indistinguishable from controls. Despite variation in metabolic demand, CECR and MECR remained relatively preserved, indicating decoupling between induction and execution capacity. Global Gap values were most negative in Tfh and TH1 states and positive in TH17 and controls. Negative Gap states showed coordinated suppression of ATP-intensive micronutrient acquisition pathways, including folate transport (FOLR1/2, SLC19A1), megalin–cubilin-mediated uptake (r ≈ 0.77–0.79), and vitamin D activation (CYP27B1). Intracellular cobalamin processing was upregulated in proportion to metabolic demand (r > 0.9). Findings were directionally replicated across both datasets. Conclusions: These data demonstrate that ASD exhibits structured immunometabolic heterogeneity characterized by subtype-specific demand–capacity imbalance. The Global Gap framework provides transcriptomic evidence of energetic deficit in Tfh- and Tr1-like-dominant states. Future clinical studies should incorporate subtype-stratified assessment of micronutrient status and metabolic execution capacity.