Associations of schizophrenia with arrhythmic disorders and electrocardiogram traits: an in-depth genetic exploration of population samples

Figures

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  Figure 1.. Overview of the genetics-based methods that were applied to investigate the mechanisms of schizophrenia with arrhythmic disorders and ECG traits. First, we examined whether there are shared genetic risk factors that overlap between schizophrenia and arrhythmic disorders and ECG traits, by estimating global and local genetic correlations. For regions of the genome that show a correlation between schizophrenia and cardiac functioning, we ran a range of functional annotation analyses to better understand the biological mechanisms involved. Subsequently, we applied bidirectional MR to investigate causal associations between schizophrenia and cardiac function.

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  Figure 2.. Results of global and local genetic correlation analyses between schizophrenia and two arrhythmic disorders and seven ECG traits. The global genetic correlations, computed with Linkage Disequilibrium score regression analyses including all Single Nucleotide Polymorphisms in the respective genome-wide association studies, are shown as diamonds in the middle. Local significant genetic correlations for genomic regions computed with LAVA (Local Analysis of [co]Variant Association) are shown as dots, with each dot representing a region comprising a couple of thousands Single Nucleotide Polymorphisms.

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  Figure 3.. Functional significance of genes in regions that correlate positively between schizophrenia and an arrhythmic disorder or ECG trait. Panel A shows significant enrichment (after FDR-correction) in biological process GO terms for all genes in regions with a positive genetic correlation between schizophrenia and Brugada. GO terms that are primarily related to viral response and immune processes are highlighted in purple. Panel B shows differential tissue expression (downregulation, upregulation, and combined, at marginal p<.05) for genes in regions that showed a positive genetic correlation between a schizophrenia and a cardiac function trait pair. The x-axes in both panels show the log-transformed p-value after FDR-correction, with the dashed lines indicating the significance threshold (pFDR<.05).

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  Figure 4.. Bidirectional Mendelian randomization analyses from liability to schizophrenia onto arrhythmic disorders and ECG traits and vice versa, from arrhythmic disorders and ECG traits to schizophrenia risk. Note that the Inverse Variance Weighted (IVW) analysis is the main analytical method and all other analyses should be seen as sensitivity methods to check whether any potential causal effect indicated by IVW holds (i.e., if there is a significant result for one of the sensitivity methods but not for the IVW, we would not consider that evidence for causality). MR-egger slope indicates the estimated causal effect, while the MR-Egger intercept reflects horizontal pleiotropy (if the p-value for the intercept is significant this indicates that there is horizontal pleiotropy present). The I-squared statistic, which assesses whether the NOME assumption was satisfied and an MR-Egger analysis can be considered reliable, ranged between acceptable to very good values (0.60 and 0·98), if I-squared was <0·90, Egger SIMEX (simulation extrapolation) was applied to correct for any potential bias.