Julian, Julian, Adawiyah, Robiatul, Wahdini, Sri. (1405). Multilayer Immunogenomic Decoding within an In Silico Framework: MBL2 as a Central Susceptibility Factor in Cryptococcal Meningitis. سامانه مدیریت نشریات علمی, (), -. doi: 10.66224/ari.2026.371688.3983
Julian Julian; Robiatul Adawiyah; Sri Wahdini. "Multilayer Immunogenomic Decoding within an In Silico Framework: MBL2 as a Central Susceptibility Factor in Cryptococcal Meningitis". سامانه مدیریت نشریات علمی, , , 1405, -. doi: 10.66224/ari.2026.371688.3983
Julian, Julian, Adawiyah, Robiatul, Wahdini, Sri. (1405). 'Multilayer Immunogenomic Decoding within an In Silico Framework: MBL2 as a Central Susceptibility Factor in Cryptococcal Meningitis', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.66224/ari.2026.371688.3983
Julian, Julian, Adawiyah, Robiatul, Wahdini, Sri. Multilayer Immunogenomic Decoding within an In Silico Framework: MBL2 as a Central Susceptibility Factor in Cryptococcal Meningitis. سامانه مدیریت نشریات علمی, 1405; (): -. doi: 10.66224/ari.2026.371688.3983
Multilayer Immunogenomic Decoding within an In Silico Framework: MBL2 as a Central Susceptibility Factor in Cryptococcal Meningitis
2Department of Parasitology, Faculty of Medicine, Universitas Indonesia Infectious Disease and Immunology Research Centre, Indonesian Medical Education and Research Institute, Faculty of Medicine, Universitas Indonesia
3Department of Parasitology, Faculty of Medicine, Universitas Indonesia, Indonesia
چکیده
Introduction: Cryptococcal meningitis (CM) is a life-threatening opportunistic fungal infection with variable host susceptibility, yet the role of immunogenomic variation remains poorly defined. This study aimed to decode single-nucleotide polymorphism (SNP)-driven susceptibility in key immune-related candidate genes (MBL2, FCGR2A, FCGR2B, FCGR3A, TLR1, TLR2, TLR4, TLR6, TLR9, CLEC6A) using an integrated, multi-layer in silico framework. Methods: The multi-layer analytical framework incorporated pathogenicity predictions, molecular modeling, protein stability assessment, post-translational modification mapping, evolutionary conservation, regulatory evaluations (eQTL/pQTL), and system-level network analyses (GeneMANIA). Results: Three MBL2 missense variants (R52C, G54D, G57E) consistently demonstrated the strongest deleterious signatures, including structural destabilization, disruption of critical collagen-like and lectin-binding residues, and promoter dysfunction. Expression analyses revealed a discordant pattern with reduced circulating protein levels despite upregulated hepatic MBL2 transcripts, indicating post-translational destabilization and defective secretion. In contrast, FcγR variants exhibited largely benign effects due to functional redundancy, while TLR variants preserved signaling capacity. Network integration positioned MBL2 as the central vulnerability node connecting lectin-complement activation, humoral immunity, phagocytic pathways, and apoptotic cell clearance. Conclusion: This multi-layer in silico framework highlights MBL2 as a key determinant of host susceptibility to CM by linking sequence variation to structural and network-level functional disruptions. These findings provide mechanistic insights into individual immune variability, establishing a foundation for biomarker development and risk stratification.