Schizophrenia (SCZ) is thought to be caused by the complex interaction of genetic predisposition and environmental exposure that may be mediated by epigenetic mechanisms, such as deoxyribonucleic acid (DNA) methylation. The current case-control study examined whether there is a combined contribution of methylation differences (i.e., polymethylation score [PMS]) associated with SCZ, similar to a polygenic risk score (PRS). It also tested whether this PMS is relevant to the established SCZ intermediate phenotype, dorsolateral prefrontal cortex (DLPFC) – hippocampus (HC) functional connectivity during working memory performance. Whole-blood samples from patients with SCZ (i.e., cases) and healthy controls were used to identify a PMS using machine learning, yielding a cross-validation accuracy of an area under the curve (AUC) of 0.78 (N=675 [322 controls; 353 cases]), and validate the PMS with two separate samples (AUC=0.69, N=847 [433 controls; 414 cases]; AUC=0.74, N=367 [331 controls; 36 cases]), indicating biological reproducibility of the PMS. The increased PMS compared to controls was specific to SCZ, as comparisons between bipolar disorder (n=39), major depressive disorder (n=35) and autism (n=27) did not differ from controls but were significantly decreased compared to SCZ. The 10 biological pathways contributing most to the SCZ PMS were immune-associated, synaptic and neural, and apoptotic pathways. The SCZ PMS predicted data from controls that was negatively associated with DLPFC-HC functional connectivity during two separate working memory tasks; this negative association was not observed during a face-matching task, indicating specificity for the SCZ intermediate phenotype. Notably, DLPFC-HC connectivity was not associated with the SCZ PRS, nor was there a significant interaction between PMS and PRS on DLPFC-HC connectivity, in two separate validation samples; these findings suggest that epigenetic analysis provides pathophysiologically relevant information not captured by PRS, and that PMS effects were not primarily driven by underlying genetics. Finally, the predicted PMS validated in post-mortem DLPFC brain tissue was significantly higher in SCZ than controls (AUC=0.63), supporting the relevance of the identified blood-derived epigenetic signature for brain-associated phenotypes of SCZ. See Figure 1 for summary of primary findings. Together, these findings help characterize the association between genetic, epigenetic, and environmental risk for SCZ.
Reference:
Chen J et al. JAMA Psychiatry 2020;77(6):628-36. Abstract
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