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Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P ≤ 2.40E-09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P ≤ 3.83E-23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P ≤ 4.16E-04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions.

Objective: Up to 40% of patients with epilepsy become drug resistant (DRE). Genetic factors are likely to play a role. While efforts have focused on the transporter and target hypotheses, neither of them fully explains the pan‐pharmacoresistance seen in DRE. Materials and methods: In this study, we developed and used a phenotyping algorithm for the identification of DRE, responders, and epilepsy‐free controls that were sequenced using a gene panel developed by the Pharmacogenomics Research Network (PGRN), which includes 82 genes involved in drug response. We tested the transporter hypothesis of DRE, the association between drug resistance and variants in the ATP‐binding cassette family of genes previously associated with DRE, and also investigated potential new genetic factors. Results: In the analysis of DRE vs controls, NTRK2 was significantly associated with DRE (rs76950094; P = 1.19 × 10−7 and gene‐based P‐value = 1.67 × 10−4). NTRK2 encodes TrkB, which is involved in the development and maturation of the central nervous system, and increased activation of TrkB signaling is suggested to promote epilepsy. Conclusion: Although the role of NTRK2 in DRE needs to be elucidated, these results support alternative mechanisms underlying DRE, complementary to the existing hypotheses, that should be evaluated. [ABSTRACT FROM AUTHOR]

Background: Leber congenital amaurosis (LCA) is a severe form of retinal dystrophy with marked underlying genetic heterogeneity. Until recently, allele-specific assays and Sanger sequencing of targeted segments were the only available approaches for attempted genetic diagnosis in this condition. A broader next-generation sequencing (NGS) strategy, such as whole exome sequencing, provides an improved molecular genetic diagnostic capacity for patients with these conditions., Materials and Methods: In a child with LCA, an allele-specific assay analyzing 135 known LCA-causing variations, followed by targeted segment sequencing of 61 regions in 14 causative genes was performed. Subsequently, exome sequencing was undertaken in the proband, unaffected consanguineous parents and two unaffected siblings. Bioinformatic analysis used two independent pipelines, BWA-GATK and SOAP, followed by Annovar and SnpEff to annotate the variants., Results: No disease-causing variants were found using the allele-specific or targeted segment Sanger sequencing assays. Analysis of variants in the exome sequence data revealed a novel homozygous nonsense mutation (c.1081C > T, p.Arg361*) in TULP1, a gene with roles in photoreceptor function where mutations were previously shown to cause LCA and retinitis pigmentosa. The identified homozygous variant was the top candidate using both bioinformatic pipelines., Conclusions: This study highlights the value of the broad sequencing strategy of exome sequencing for disease gene identification in LCA, over other existing methods. NGS is particularly beneficial in LCA where there are a large number of causative disease genes, few distinguishing clinical features for precise candidate disease gene selection, and few mutation hotspots in any of the known disease genes.