Immunometabolic synaptopathy: linking metabolic syndrome to epileptogenesis through trained immunity and parvalbumin...

Metabolic syndrome (MetS) and epilepsy are clinically associated, but how chronic peripheral metabolic stress might influence seizure susceptibility remains unclear. The potential links among CNS-interface dysfunction, glial responses, and inhibitory-circuit vulnerability require further clarification.

We propose immunometabolic synaptopathy as a hypothesis-driven framework linking chronic metabolic dysfunction to impaired inhibitory-circuit resilience. MetS-associated metabolic and inflammatory signals may alter blood-brain barrier function, CNS-border immune signaling, and glial homeostasis. Evidence from peripheral myeloid training and CNS immune-memory models supports the plausibility of trained-immunity-like microglial priming, but its occurrence and persistence in MetS-associated epileptogenesis remain unestablished.

We identify the parvalbumin-positive interneuron-perineuronal net (PV-PNN) unit as a candidate convergence point because of its energetic demands and dependence on ionic and extracellular-matrix homeostasis. Altered metabolic and trophic support, oxidative stress, impaired K⁺ and glutamate handling, and PNN remodeling may jointly compromise PV-mediated inhibition. Whether these processes preferentially affect PV-PNN units or precede spontaneous seizures requires direct testing.

Five candidate nodes-NLRP3, mTOR, HIF-1α, MMP-9, and Kir4.1-provide opportunities for mechanistic testing. Their therapeutic relevance to MetS-associated epilepsy remains uncertain, and available compounds differ in selectivity, CNS exposure, and safety. The framework motivates experimental evaluation of intervention timing and target dependence rather than specific clinical treatment recommendations.

Immunometabolic synaptopathy integrates cross-context evidence into a testable hypothesis of metabolically associated seizure susceptibility. The complete pathway to spontaneous epilepsy has not been demonstrated end-to-end and requires longitudinal, cell- and pathway-specific validation.