Weighted burden analysis of exome-sequenced case-control sample implicates synaptic genes in schizophrenia aetiology

Abstract

A previous study of exome-sequenced schizophrenia cases and controls reported an excess of singleton, gene-disruptive variants among cases, concentrated in particular gene sets. The dataset included a number of subjects with a substantial Finnish contribution to ancestry. We have reanalysed the same dataset after removal of these subjects and we have also included non-singleton variants of all types using a weighted burden test which assigns higher weights to variants predicted to have a greater effect on protein function. We investigated the same 31 gene sets as previously and also 1454 GO gene sets. The reduced dataset consisted of 4225 cases and 5834 controls. No individual variants or genes were significantly enriched in cases but 13 out of the 31 gene sets were significant after Bonferroni correction and the "FMRP targets" set produced a signed log p value (SLP) of 7.1. The gene within this set with the highest SLP, equal to 3.4, was FYN, which codes for a tyrosine kinase which phosphorylates glutamate metabotropic receptors and ionotropic NMDA receptors, thus modulating their trafficking, subcellular distribution and function. In the most recent GWAS of schizophrenia it was identified as a "prioritized candidate gene". Two of the subunits of the NMDA receptor which are substrates of FYN are coded for by GRIN1 (SLP=1.7) and GRIN2B (SLP=2.1). Of note, for some sets there was a substantial enrichment of non-singleton variants. Of 1454 GO gene sets, 3 were significant after Bonferroni correction. Identifying specific genes and variants will depend on genotyping them in larger samples and/or demonstrating that they cosegregate with illness within pedigrees.

Weighted burden analysis of exome‐sequenced late‐onset Alzheimer's cases and controls provides further evidence for a role for PSEN1 and suggests involvement of the PI3K/Akt/GSK‐3β and WNT signalling pathways

“…As described previously, ridge regression analysis with was used to test whether the gene‐wise score was associated with caseness (Curtis et al., ). To do this, SCOREASSOC first calculates the likelihood for the phenotypes as predicted by the first 20 principal components and then calculates the likelihood using a model that additionally incorporates the gene‐wise scores.…”

“…Each variant was annotated using VEP, PolyPhen, and SIFT (Adzhubei, Jordan, & Sunyaev, 2013;Kumar, Henikoff, & Ng, 2009;McLaren et al, 2016). The same analytic process has previously been applied to an exome-sequenced sample of schizophrenia cases and controls (Curtis, Coelewij, Liu, Humphrey, & Mott, 2018). The method uses a weighted burden analysis to test whether, in a particular gene or set of genes, variants that are rarer and/or predicted to have more severe functional effects occur more commonly in cases than controls.…”

Weighted burden analysis of exome-sequenced late onset Alzheimer’s cases and controls provides further evidence for a role for PSEN1 and suggests involvement of the PI3K/Akt/GSK-3β and WNT signalling pathways

“…Each variant was annotated using VEP, PolyPhen and SIFT (Adzhubei et al, 2013;Kumar et al, 2009;McLaren et al, 2016). The same analytic process has previously been applied to an exome sequenced sample of schizophrenia cases and controls (Curtis et al, 2018). The method uses a weighted burden analysis to test whether, in a particular gene or set of genes, variants which are rarer and/or predicted to have more severe functional effects occur more commonly in cases than controls.…”

“…Additionally 10 was added to the weight if the PolyPhen annotation was possibly or probably damaging and also if the SIFT annotation was deleterious. The full set of weights is shown in Supplementary Table 1, copied from the previous report (Curtis et al, 2018). Since we reasoned that the effects of any common variants would have been well characterised by previous studies we excluded variants with MAF>0.01 in either cases or controls.…”

“…As described previously, ridge regression analysis with lamda=1 was used to test whether the genewise score was associated with caseness (Curtis et al, 2018). To do this, SCOREASSOC first calculates the likelihood for the phenotypes as predicted by the first 20 principal components and then calculates the likelihood using a model which additionally incorporates the gene-wise scores.…”