Genetic and structural interpretation of NLRP1 FIIND domain variants in glioma in an Indian cohort: a pilot study

Abstract

Gliomas, particularly glioblastoma (GBM), are aggressive primary brain tumors associated with dysregulated NLR signaling, a pathway central to innate immunity and inflammation. NLRP1 triggers proinflammatory cytokine release and pyroptotic cell death via autoproteolytic cleavage. The FIIND missense variant rs11651270 (M1184V) may modulate this cleavage process. While NLRP1 polymorphisms are associated with various diseases and cancers, their specific impact on glioma remains to be investigated. In our study, five FIIND-domain single-nucleotide polymorphisms (SNPs) of NLRP1 rs371579423, rs58604457, rs57636751, rs11651270, and rs2301583, were investigated by Sanger sequencing in a clinical cohort of glioma patients and compared against population-matched controls from the GenomeIndia dataset (Rajasthan cohort) using genetic association models. Molecular dynamics simulations were performed to evaluate the structural effects of the missense variant rs11651270 (M1184V) in NLRP1 during pre- and post-cleavage states. The linked variants rs58604457 (G>A) and rs57636751 (C>T) exhibited complete linkage disequilibrium (r2=1.00) and were significantly associated with lower odds of glioma (odds ratio ~0.5). The missense variant rs11651270 (T>C) showed no association with glioma risk. Notably, the SNP rs2301583 had a higher allelic frequency in glioma cases despite being absent in the GenomeIndia population-based control catalogue. Molecular dynamics simulations revealed that the M1184V substitution stabilizes local FIIND architecture by preserving {beta}-strand organization through persistent interactions with neighboring residues. This study provides the first combined genetic and structural analysis of NLRP1 FIIND-domain variants in an Indian glioma cohort. These findings illustrate the potential value of integrating population-based genetic association with structural modelling to generate hypotheses and uncover potential functional mechanisms of inflammasome-gene variants in neuro-oncology.