Analysis of variants in Chinese individuals with primary open-angle glaucoma using molecular inversion probe (MIP)-based panel sequencing.

Purpose Family-based genetic linkage analysis and genome-wide association studies (GWASs) have identified many genomic loci associated with primary open-angle glaucoma (POAG). Several causative genes of POAG have been intensively analyzed by sequencing in different populations. However, few investigations have been conducted on the identification of variants of coding region in the genes identified in GWASs. Therefore, further research is needed to investigate whether they harbor pathogenically relevant rare coding variants and account for the observed association. Methods To identify the potentially disease-relevant variants (PDVs) in POAG-associated genes in Chinese patients, we applied molecular inversion probe (MIP)-based panel sequencing to analyze 26 candidate genes in 235 patients with POAG and 241 control subjects. Results The analysis identified 82 PDVs in 66 individuals across 235 patients with POAG. By comparison, only 18 PDVs in 19 control subjects were found, indicating an enrichment of PDVs in the POAG cohort (28.1% versus 7.9%, p = 8.629e-09). Among 26 candidate genes, the prevalence rate of PDVs in five genes showed a statistically significant difference between patients and controls (33 out of 235 versus 1 out of 241, p = 4.533e-10), including ATXN2 (p = 0.0033), TXNRD2 (p = 0.0190), MYOC (p = 0.0140), FOXC1 (p = 0.0140), and CDKN2B (p = 0.0287). Furthermore, two sisters harboring a stop-loss mutation EFEMP1 p.Ter494Glu were found in the POAG cohort, and further analysis of the family strongly suggested that EFEMP1 p.Ter494Glu was a potentially disease-causing mutation for POAG. A statistically significant difference in age at diagnosis between patients with PDVs and those without PDVs was found, implying that some of the identified PDVs may have a role in promoting the early onset of POAG disease. Conclusions The results suggest that some of the associations identified in POAG risk loci can be ascribed to rare coding variants with likely functional effects that modify POAG risk.