A model to investigate SNPs' interaction in GWAS studies

Selecting variants of unknown significance through network-based gene-association significantly improves risk prediction for disease-control cohorts

Variants of unknown/uncertain significance (VUS) pose a huge dilemma in current genetic variation screening methods and genetic counselling. Driven by methods of next generation sequencing (NGS) such as whole exome sequencing (WES), a plethora of VUS are being detected in research laboratories as well as in the health sector. Motivated by this overabundance of VUS, we propose a novel computational methodology, termed VariantClassifier (VarClass), which utilizes gene-association networks and polygenic risk prediction models to shed light into this grey area of genetic variation in association with disease. VarClass has been evaluated using numerous validation steps and proves to be very successful in assigning significance to VUS in association with specific diseases of interest. Notably, using VUS that are deemed significant by VarClass, we improved risk prediction accuracy in four large case-studies involving disease-control cohorts from GWAS as well as WES, when compared to traditional odds ratio analysis. Biological interpretation of selected high scoring VUS revealed interesting biological themes relevant to the diseases under investigation. VarClass is available as a standalone tool for large-scale data analyses, as well as a web-server with additional functionalities through a user-friendly graphical interface.

Hippocampal Pruning as a New Theory of Schizophrenia Etiopathogenesis

Pruning in neurons has been suggested to be strongly involved in Schizophrenia's (SKZ) etiopathogenesis in recent biological, imaging, and genetic studies. We investigated the impact of protein-coding genes known to be involved in pruning, collected by a systematic literature research, in shaping the risk for SKZ in a case-control sample of 9,490 subjects (Psychiatric Genomics Consortium). Moreover, their modifications through evolution (humans, chimpanzees, and rats) and subcellular localization (as indicative of their biological function) were also investigated. We also performed a biological pathways (Gene Ontology) analysis. Genetics analyses found four genes (DLG1, NOS1, THBS4, and FADS1) and 17 pathways strongly involved in pruning and SKZ in previous literature findings to be significantly associated with the sample under analysis. The analysis of the subcellular localization found that secreted genes, and so regulatory ones, are the least conserved through evolution and also the most associated with SKZ. Their cell line and regional brain expression analysis found that their areas of primary expression are neuropil and the hippocampus, respectively. At the best of our knowledge, for the first time, we were able to describe the SKZ neurodevelopmental hypothesis starting from a single biological process. We can also hypothesize how alterations in pruning fine regulation and orchestration, strongly related with the evolutionary newest (and so more sensitive) secreted proteins, may be of particular relevance in the hippocampus. This early alteration may lead to a mis-structuration of neural connectivity, resulting in the different brain alteration that characterizes SKZ patients.