Scientific evaluation of negative exome sequencing followed by systematic scoring of candidate genes to decipher the genetics of neurodevelopmental disorders

Abstract

BackgroundDeciphering the monogenetic causes of neurodevelopmental disorders (NDD) is an important milestone to offer personalized care. But the plausibility of reported candidate genes in exome studies often remains unclear, which slows down progress in the field.MethodsWe performed exome sequencing (ES) in 198 cases of NDD. Cases that remained unresolved (n=135) were re-investigated in a research setting. We established a candidate scoring system (CaSc) based on 12 different parameters reflecting variant and gene attributes as well as current literature to rank and prioritize candidate genes.ResultsIn this cohort, we identified 158 candidate variants in 148 genes with CaSc ranging from 2 to 11.7. Only considering the top 15% of candidates, 14 genes were already published or funneled into promising validation studies.ConclusionsWe promote that in an approach of case by case re-evaluation of primarily negative ES, systematic and standardized scoring of candidate genes can and should be applied. This simple framework enables better comparison, prioritization, and communication of candidate genes within the scientific community. This would represent an enormous benefit if applied to the tens of thousands of negative ES performed in routine diagnostics worldwide and speed up deciphering the monogenetic causes of NDD.

AutoCaSc: Prioritizing candidate genes for neurodevelopmental disorders

“…This was calculated based on reviewing OMIM and PubMed entries to check if the gene is involved in neurological processes, using MGI (Bult et al, 2019) and PubMed for animal models, STRING (Szklarczyk et al, 2019) for protein interactions, GTEx (Consortium, 2020) for gene expression in central nervous system, as well as a list of resources to find out if variants in the gene have been described in association with autism spectrum disorder or NDD (the resources included the DDD study, the Human Gene Mutation Database (HGMD), ClinVar, cooperation partners, and entries in GeneMatcher). An overview of the manual version of CaSc is provided in Figure S1 and a detailed description in the corresponding preprint (Büttner et al, 2019). Evaluators manually applied these rules to all candidate variants and focused on following up the highest scoring and thus most promising genes through matchmaking.…”

AutoCaSc: Prioritizing candidate genes for neurodevelopmental disorders

“…This was calculated based on reviewing OMIM and PubMed entries to check if the gene is involved in neurological processes, using Mouse Genome Informatics (MGI) (Bult et al, 2019) and PubMed for animal models, search tool for recurring instances of neighbouring genes (STRING) (Szklarczyk et al, 2019) for protein interactions, Genotype-Tissue Expression (GTEx) (Consortium & Gte, 2020) for gene expression in the central nervous system, as well as a list of resources to find out if variants in the gene have been described in association with an autism spectrum disorder or NDD (the resources included the DDD study, the Human Gene Mutation Database, ClinVar, cooperation partners, and entries in GeneMatcher). An overview of the manual version of CaSc is provided in the Supporting Information: Figure S1 and a detailed description in the corresponding preprint (Büttner et al, 2019). Evaluators manually applied these rules to all candidate variants and focused on following up the highest scoring and thus most promising genes through matchmaking.…”