NPHS2 Revisited Through 208 Cases and Podocin Complex Modeling

通过 208 个病例和足细胞蛋白复合物建模重新审视 NPHS2

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Abstract

INTRODUCTION: Steroid-resistant nephrotic syndrome (SRNS) is the leading cause of chronic glomerular disease in individuals under 25 years of age. Biallelic variants in NPHS2, encoding podocin, are the most common monogenic etiology. Podocin homo-oligomerizes to a critical slit diaphragm complex. NPHS2 genotype-phenotype relationships and podocin's assembly architecture remain incompletely defined. METHODS: Analysis of 208 individuals with pathogenic NPHS2 variants was conducted, which is the largest reported single cohort. Genotype-phenotype correlations were tested using clinical data, in silico pathogenicity tools, rare exome variant ensemble learner (REVEL) evolutionary model of variant effect (EVE), and high-order structural modeling (AlphaFold3) based on published experimental data. RESULTS: A broad allelic spectrum with variable disease onset (median 2.75 years; range 0-30) was identified. Although most cases presented early, later onset was associated with compound heterozygous variants with p.R229Q (including in trans with novel variant p.E281K), the homozygous missense variant p.V180M, or select compound heterozygous variants with p.R138Q (in trans with p.V180M or p.V290M). REVEL and EVE scores reliably distinguished pathogenic from benign missense variants. A novel artificial intelligence -generated architecture of podocin higher-order assemblies, featuring a chalice-like structure with a central hydrophobic core and a single transmembrane plane is proposed, resembling the solved structures of multiple paralogous SPFH family proteins. Pathogenic missense variants in the proposed model cluster at oligomer interfaces, with distinct physicochemical alterations, and variants associated with earlier onset appear to localize closer to the transmembrane plane. CONCLUSION: This study delineates genotype-phenotype relationships in NPHS2-associated SRNS and proposes high-order podocin assemblies. Combined genetic and structural insights enhance variant assessment, though experimental validation remains essential.

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