Multiple rare genetic variants co-segregating with familial IgA nephropathy all act within a single immune-related network

• Autores: S. N. Cox, F. Pesce, J.S. El Sayed Moustafa, F. Sallustio, Giovanni Serino, C. Kkoufou, A. Giampetruzzi, N. Ancona, M. Falchi, F. P. Schena
• Localización: Journal of Internal Medicine, ISSN-e 1365-2796, Vol. 281, Nº. 2, 2017, págs. 189-205
• Idioma: inglés
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• Resumen

  • Background IgA nephropathy (IgAN) is a common complex disease with a strong genetic involvement. We aimed to identify novel, rare, highly penetrant risk variants combining family-based linkage analysis with whole-exome sequencing (WES).

    Methods Linkage analysis of 16 kindreds of South Italian ancestry was performed using an ‘affected-only’ strategy. Eight most informative trios composed of two familial cases and an intrafamilial control were selected for WES. High-priority variants in linked regions were identified and validated using Sanger sequencing. Custom TaqMan assays were designed and carried out in the 16 kindreds and an independent cohort of 240 IgAN patients and 113 control subjects.

    Results We found suggestive linkage signals in 12 loci. After sequential filtering and validation of WES data, we identified 24 private or extremely rare (MAF <0.0003) linked variants segregating with IgAN status. These were present within coding or regulatory regions of 23 genes that merged into a common functional network. The genes were interconnected by AKT, CTNNB1, NFKB, MYC and UBC, key modulators of WNT/β-catenin and PI3K/Akt pathways, which are implicated in IgAN pathogenesis. Overlaying publicly available expression data, genes/proteins with expression notably altered in IgAN were included in this immune-related network. In particular, the network included the glucocorticoid receptor gene, NR3C1, which is the target of corticosteroid therapy routinely used in the treatment of IgAN.

    Conclusion Our findings suggest that disease susceptibility could be influenced by multiple rare variants acting in a common network that could provide the starting point for the identification of potential drug targets for personalized therapy.