NOVEL COMPUTATIONAL AND EXPERIMENTAL METHODS FOR <EM>GRIN</EM> VARIANTS STRATIFICATION AND DRUG SCREENING FOR GRIN-RELATED DISORDERS

Mutations affecting GRIN genes encoding NMDAR subunits cause GRIN-related disorders (GRD), a group of developmental encephalopathies resulting in a clinical spectrum including intellectual disability, epilepsy, motor impairment and autonomic distress, among others. GRIN variants functional stratification is crucial to understand GRD pathophysiology, and to evaluate GRIN variant personalised therapeutic approaches. Although GRIN variants have traditionally been dichotomously classified as gain- or loss-of-function (GoF and LoF), a definitive annotation remains elusive for the subset of GRIN variants affecting the C-terminal domain (CTD) or resulting in complex electrophysiological phenotypes. To address this molecular diagnosis unmet need, we have implemented computational approaches integrating genetic and functional data. Further, we have developed a comprehensive functional analysis pipeline of GRIN variants, expanding in vitro approaches to annotate “GRIN orphan variants” (“complex” and CTD-affecting variants). More recently, beyond routine methods established in cell lines (surface trafficking, protein stability, and electrophysiology), the impact of orphan GRIN variants has been assessed in primary neurons transfected with GRIN variants. Using neuronal readouts (spontaneous NMDAR-mediated EPSCs recordings, synaptic spines density and morphology), we have characterised GRIN orphan variants effects, both under basal conditions and measuring their differential responsiveness to NMDAR potentiators and inhibitors. Our preliminary data indicate that this integrative novel approach (combined computational and neuronal studies) provides a more accurate functional stratification of GRIN variants together with a pharmacological-responsiveness evaluation that will guide therapeutic decision-making.