The molecular landscape of osteogenesis imperfecta in a Brazilian tertiary service cohort

Abstract

We have sought the molecular diagnosis of OI in 38 Brazilian cases through targeted sequencing of 15 candidate genes. While 71% had type 1 collagen-related OI, defects in FKBP10, PLOD2 and SERPINF1, and a potential digenic P3H1/WNT1 interaction were prominent causes of OI in this underrepresented population. Introduction Defects in type 1 collagen reportedly account for 85-90% of osteogenesis imperfecta (OI) cases, but most available molecular data has derived from Sanger sequencing-based approaches in developed countries. Massively parallel sequencing (MPS) allows for systematic and comprehensive analysis of OI genes simultaneously. Our objective was to obtain the molecular diagnosis of OI in a single Brazilian tertiary center cohort. Methods Forty-nine individuals (84% adults) with a clinical diagnosis of OI, corresponding to 30 sporadic and 8 familial cases, were studied. Sixty-three percent had moderate to severe OI, and consanguinity was common (26%). Coding regions and 25-bp boundaries of 15 OI genes (COL1A1, COL1A2, IFITM5 [plus 5 ' UTR], SERPINF1, CRTAP, P3H1, PPIB, SERPINH1, FKBP10, PLOD2, BMP1, SP7, TMEM38B, WNT1, CREB3L1) were analyzed by targeted MPS and variants of interest were confirmed by Sanger sequencing or SNP array. Results A molecular diagnosis was obtained in 97% of cases. COL1A1/COL1A2 variants were identified in 71%, whereas 26% had variants in other genes, predominantly FKBP10, PLOD2, and SERPINF1. A potential digenic interaction involving P3H1 and WNT1 was identified in one case. Phenotypic variability with collagen defects could not be explained by evident modifying variants. Four consanguineous cases were associated to heterozygous COL1A1/COL1A2 variants, and two nonconsanguineous cases had compound PLOD2 heterozygosity. Conclusions Novel disease-causing variants were identified in 29%, and a higher proportion of non-collagen defects was seen. Obtaining a precise diagnosis of OI in underrepresented populations allows expanding our understanding of its molecular landscape, potentially leading to improved personalized care in the future.