Infantile neuroaxonal dystrophy 1 (INAD) (OMIM #256600) is a rare infantile onset neurodegenerative disease characterised by neuroregression and hypotonia, evolving into generalized spasticity, blindness and dementia. We report our diagnostic approach of a pair of siblings with psychomotor regression, hypotonia, optic atrophy and auditory neuropathy. The brain magnetic resonance imaging (MRI) showed progressive cerebellar atrophy. Genetic testing of the PLA2G6 confirmed presence of compound heterozygous novel mutations. As the variant c. 196C>T (p.Gln66X) was a truncating variant, it was considered as pathogenic while the variant c. 2249G>A (p. Cys750Tyr) was considered as "likely pathogenic" by bioinformatics analyses. Our patient expands the clinical phenotype of INAD as it described the first South-East Asian patient with INAD-associated auditory neuropathy. Our report highlights the importance of increased awareness of this condition amongst clinicians, the use of deep phenotyping using neuroimaging and the clinical utility of gene sequencing test in the delineation of syndromes associated with infantile neurodegenerative disease.
We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.