To investigate the effects of central corneal thickness (CCT)-associated variants on primary open-angle glaucoma (POAG) risk using single nucleotide polymorphisms (SNP) data from the Glaucoma Genes and Environment (GLAUGEN) and National Eye Institute (NEI) Glaucoma Human Genetics Collaboration (NEIGHBOR) consortia.A replication analysis of previously reported CCT SNPs was performed in a CCT dataset (n = 1117) and these SNPs were then tested for association with POAG using a larger POAG dataset (n = 6470). Then a CCT genome-wide association study (GWAS) was performed. Top SNPs from this analysis were selected and tested for association with POAG. cDNA libraries from fetal and adult brain and ocular tissue samples were generated and used for candidate gene expression analysis.Association with one of 20 previously published CCT SNPs was replicated: rs12447690, near the ZNF469 gene (P = 0.001; β = -5.08 μm/allele). None of these SNPs were significantly associated with POAG. In the CCT GWAS, no SNPs reached genome-wide significance. After testing 50 candidate SNPs for association with POAG, one SNP was identified, rs7481514 within the neurotrimin (NTM) gene, that was significantly associated with POAG in a low-tension subset (P = 0.00099; Odds Ratio [OR] = 1.28). Additionally, SNPs in the CNTNAP4 gene showed suggestive association with POAG (top SNP = rs1428758; P = 0.018; OR = 0.84). NTM and CNTNAP4 were shown to be expressed in ocular tissues.The results suggest previously reported CCT loci are not significantly associated with POAG susceptibility. By performing a quantitative analysis of CCT and a subsequent analysis of POAG, SNPs in two cell adhesion molecules, NTM and CNTNAP4, were identified and may increase POAG susceptibility in a subset of cases.
We report four allelic variants (three novel) in three genes previously established as causal for hypopituitarism or related disorders. A novel homozygous variant in the growth hormone gene, GH1 c.171delT (p.Phe 57Leufs*43), was found in a male patient with severe isolated growth hormone deficiency (IGHD) born to consanguineous parents. A hemizygous SOX3 allelic variant (p.Met304Ile) was found in a male patient with IGHD and hypoplastic anterior pituitary. YASARA, a tool to evaluate protein stability, suggests that p.Met304Ile destabilizes the SOX3 protein (ΔΔG = 2.49 kcal/mol). A rare, heterozygous missense variant in the TALE homeobox protein gene, TGIF1 (c.268C>T:p.Arg90Cys) was found in a patient with combined pituitary hormone deficiency (CPHD), diabetes insipidus, and syndromic features of holoprosencephaly (HPE). This variant was previously reported in a patient with severe holoprosencephaly and shown to affect TGIF1 function. A novel heterozygous TGIF1 variant (c.82T>C:p.Ser28Pro) was identified in a patient with CPHD, pituitary aplasia and ectopic posterior lobe. Both TGIF1 variants have an autosomal dominant pattern of inheritance with incomplete penetrance. In conclusion, we have found allelic variants in three genes in hypopituitarism patients. We discuss these variants and associated patient phenotypes in relation to previously reported variants in these genes, expanding our knowledge of the phenotypic spectrum in patient populations.
Abstract Whole Exome Sequencing (WES) has been a useful tool to improve molecular diagnosis in hypopituitarism, leading to the discovery of at least 8 new genes in the last 7 years. However, some genes associated with hypopituitarism show low coverage in this methodology, limiting its use for molecular diagnosis. Our objective is to compare three library prepping kits, NimbleGen (Roche), SureSelect (Agilent) and Nextera (Illumina) examining the best performance related to sequencing quality, exon extension coverage (≥98%) and base depth read (≥20x) of 44 genes associated with hypopituitarism and 32 involved in pituitary development. Three different groups composed of 2 HapMap samples (Group 1), 2 Brazilian patients with hypopituitarism and their respective mothers (Group 2) and 109 random Brazilian samples (Group 3) were sequenced in Illumina platform. Group 1 and 3 were performed using all three library prepping kits, while group 2 was performed with NimbleGen and SureSelect. Although all technologies covered the selected genes with similar efficiency regarding poor (less than 20%) and rich (more than 80%) GC areas, SureSelect has shown to reach the most uniform coverage in the selected region with a lower level of duplicate reads, as well as a higher number of identified pathogenic variants.
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