Multi-ancestry GWAS reveals excitotoxicity associated with outcome after ischaemic stroke

Abstract

During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6 h of stroke onset and NIHSS at 24 h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24 h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke.

Keywords: NIHSS; genetics; ischaemic stroke; neuroprotection.

Figure 1

Study design. Summarized description of the multi-step approach used to account for the genetic heterogeneity intrinsic to the multi-ancestry nature of the GENISIS study (A). We performed single variant analysis in each of the participating countries separately. Then we meta-analysed all the non-Hispanic whites (blue) and Hispanic (green) ethnicities. Finally, we analysed the non-Hispanic whites, Hispanics, Korea (orange) and US participants of African descent (US AfA, yellow) using a Bayesian model. The variants with genome-wide significant or suggestive results were annotated using sequential steps to elucidate the gene driving the association (B). We performed gene-based and pathway analyses, we collected the information available in publicly available datasets and we performed Mendelian randomization. We also performed genetic architecture overlap tests to examine overlap with known genetic risk factors.

Figure 2

Association and annotation results. (A) Manhattan plot shows the LBF values from the multi-ancestry meta-analysis in each genomic location. The red line indicates the GWAS-significant threshold (LBF > 5) and the blue line the GWAS suggestive threshold (LBF > 4). The genome-wide significant loci are highlighted. Local Manhattan plots are shown for rs16838349 (C) and rs17115057 (F) along with the corresponding forest plots (D and G), showing the contribution of each population to the overall signal. As part of the functional gene mapping, we accessed an in-house single-nuclei dataset (B) to describe the expression patterns in human brain cortical cell populations of the driving genes identified for rs16838349, ADAM23 (E) and rs17115057, GRIA1 (H).

Figure 3

Gene prioritizing summary. Summary showing the seven genome-wide significant loci from the multi-ancestry analysis (first column), the total number of genes identified in each of the locus (second column) and gene name for genes for which we have found some kind of evidence (third column). We have included the results from the gene-based analyses, the presence of any eQTL in GTEx portal or Braineac for any of the genome-wide or suggestive variants, if the gene is differentially expressed in any bran region according to the single-nuclei RNA-seq data and the results from Mendelian randomization using Westra dataset (whole blood) or GTEx portal (all tissues). Black dots indicate that the gene was not found, red is that it was found but was not significant, yellow it was moderately significant (0.05 < P < 1 × 10⁻³) and green shows a significant association (P < 1 × 10⁻³).