Factor VIII (FVIII) mutations cause haemophilia A (HA), an X-linked recessive coagulation disorder. Over 1000 missense mutations in FVIII are known and they lead to variable clinical phenotypes (severe, moderate and mild). The exact molecular basis of this phenotypic heterogeneity by FVIII missense mutations is elusive to date. In this study, we aimed to identify the severity determinants that cause phenotypic heterogeneity of HA. We compiled and curated a data set of 766 missense mutations from the repertoire of missense mutations in FVIII. We analysed these mutations by computational programs (e.g. Swiss-PdbViewer) and different mutation analysis servers (e.g. SIFT, PROVEAN, CUPSAT, PolyPhen2, MutPred); and various sequence- and structure-based parameters were assessed for any significant distribution bias among different HA phenotypes. Our analyses suggest that 'mutations in evolutionary conserved residues', 'mutations in buried residues', mutation-induced 'steric clash' and 'surface electrostatic potential alteration' act as risk factors towards severe HA. We have developed a grading system for FVIII mutations combining the severity determinants, and the grading pattern correlates with HA phenotype. This study will help to correctly associate the HA phenotype with a mutation and aid early characterization of novel variants.
Wilson disease (WD) is an autosomal-recessive disorder caused by mutations in the ATP7B gene leading to abnormal copper deposition in liver and brain. WD manifests diverse neurological and hepatic phenotypes and different age of onset, even among the siblings, with same mutational background suggesting complex nature of the disease and involvement of other candidate genes. In that context, Apolipoprotein E (APOE) and Prion Protein (PRNP) have been proposed to be potential candidates for modifying the WD phenotype and age of onset. This study aims to identify the contribution of APOE and PRNP polymorphisms on the variable phenotypic expression of Indian WD patients. A total of 171 WD patients and 291 controls from Indian population were included in this study. Two APOE cSNPs (rs429358 and rs7412) resulting in three isoforms and M129V (rs1799990) polymorphism of PRNP were examined for their association with WD and its clinical phenotypes. The APOE ԑ4 allele was found to be significantly overrepresented in WD patients compared to controls. However, the frequency of the APOE ԑ3 allele and ԑ3/ԑ3 genotype was significantly higher in WD patients without cognitive behavior impairment compared to the ones with the impairment. On the contrary, the PRNP allele representing Val129 was found to be present in higher proportion in WD patients with cognitive behavioral decline. Our data suggest that the APOE ԑ4 allele could act as a potential risk for the pathogenesis of WD. Also, APOE and PRNP might contribute toward the cognitive behavioral decline in a section of WD patients.
Vitiligo is a prevalent depigmentation disorder affecting around 1% of the general population. So far, various Genome Wide Association Studies (GWAS) and Candidate Gene Association Studies (CGAS) have identified several single nucleotide variants (SNVs) as a risk factor for vitiligo. Nonetheless, little has been discerned regarding their direct functional significance to the disease pathogenesis. In this study, we did extensive data mining and downstream analysis using several experimentally validated datasets like GTEx Portal and web tools like rSNPBase, RegulomeDB, HaploReg and STRING to prioritize 13 SNVs from a set of 291SNVs that have been previously reported to be associated with vitiligo. We also prioritized their underlying/target genes and tried annotating their functional contribution to vitiligo pathogenesis. Our analysis revealed genes like FGFR10P, SUOX, CDK5RAP1 and RERE that have never been implicated in vitiligo previously to have strong potentials to contribute to the disease pathogenesis. The study is the first of its kind to prioritize and functionally annotate vitiligo-associated GWAS and CGAS SNVs and their underlying/target genes, based on functional data available in the public domain database.
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