DNA Methylation Differences in Monozygotic Twin Pairs Discordant for Schizophrenia Identifies Psychosis Related Genes and Networks

Background Despite their singular origin, monozygotic twin pairs often display discordance for complex disorders including schizophrenia. It is a common (1%) and often familial disease with a discordance rate of ~50% in monozygotic twins. This high discordance is often explained by the role of yet unknown environmental, random, and epigenetic factors. The involvement of DNA methylation in this disease appears logical, but remains to be established. Methods We have used blood DNA from two pairs of monozygotic twins discordant for schizophrenia and their parents in order to assess genome-wide methylation using a NimbleGen Methylation Promoter Microarray. Results The genome-wide results show that differentially methylated regions (DMRs) exist between members representing discordant monozygotic twins. Some DMRs are shared with parent(s) and others appear to be de novo. We found twenty-seven genes affected by DMR changes that were shared in the affected member of two discordant monozygotic pairs from unrelated families. Interestingly, the genes affected by pair specific DMRs share specific networks. Specifically, this study has identified two networks; “cell death and survival” and a “cellular movement and immune cell trafficking”. These two networks and the genes affected have been previously implicated in the aetiology of schizophrenia. Conclusions The results are compatible with the suggestion that DNA methylation may contribute to the discordance of monozygotic twins for schizophrenia. Also, this may be accomplished by the direct effect of gene specific methylation changes on specific biological networks rather than individual genes. It supports the extensive genetic, epigenetic and phenotypic heterogeneity implicated in schizophrenia

A clinical evaluation of the performance of five commercial artificial intelligence contouring systems for radiotherapy

Purpose/objective(s)Auto-segmentation with artificial intelligence (AI) offers an opportunity to reduce inter- and intra-observer variability in contouring, to improve the quality of contours, as well as to reduce the time taken to conduct this manual task. In this work we benchmark the AI auto-segmentation contours produced by five commercial vendors against a common dataset.Methods and materialsThe organ at risk (OAR) contours generated by five commercial AI auto-segmentation solutions (Mirada (Mir), MVision (MV), Radformation (Rad), RayStation (Ray) and TheraPanacea (Ther)) were compared to manually-drawn expert contours from 20 breast, 20 head and neck, 20 lung and 20 prostate patients. Comparisons were made using geometric similarity metrics including volumetric and surface Dice similarity coefficient (vDSC and sDSC), Hausdorff distance (HD) and Added Path Length (APL). To assess the time saved, the time taken to manually draw the expert contours, as well as the time to correct the AI contours, were recorded.ResultsThere are differences in the number of CT contours offered by each AI auto-segmentation solution at the time of the study (Mir 99; MV 143; Rad 83; Ray 67; Ther 86), with all offering contours of some lymph node levels as well as OARs. Averaged across all structures, the median vDSCs were good for all systems and compared favorably with existing literature: Mir 0.82; MV 0.88; Rad 0.86; Ray 0.87; Ther 0.88. All systems offer substantial time savings, ranging between: breast 14-20 mins; head and neck 74-93 mins; lung 20-26 mins; prostate 35-42 mins. The time saved, averaged across all structures, was similar for all systems: Mir 39.8 mins; MV 43.6 mins; Rad 36.6 min; Ray 43.2 mins; Ther 45.2 mins.ConclusionsAll five commercial AI auto-segmentation solutions evaluated in this work offer high quality contours in significantly reduced time compared to manual contouring, and could be used to render the radiotherapy workflow more efficient and standardized

The effects of olanzapine on genome-wide DNA methylation in the hippocampus and cerebellum

Background: The mechanism of action of olanzapine in treating schizophrenia is not clear. This research reports the effects of a therapeutic equivalent treatment of olanzapine on DNA methylation in a rat model in vivo. Genome-wide DNA methylation was assessed using a MeDIP-chip analysis. All methylated DNA immunoprecipitation (MeDIP), sample labelling, hybridization and processing were performed by Arraystar Inc (Rockville, MD, USA). The identified gene promoters showing significant alterations to DNA methylation were then subjected to Ingenuity Pathway Analysis (Ingenuity System Inc, CA, USA). Results: The results show that olanzapine causes an increase in methylation in 1,140, 1,294 and 1,313 genes and a decrease in methylation in 633, 565 and 532 genes in the hippocampus, cerebellum and liver, respectively. Most genes affected are tissue specific. Only 41 affected genes (approximately 3%) showed an increase and no gene showed a decrease in methylation in all three tissues. Further, the two brain regions shared 123 affected genes (approximately 10%). The affected genes are enriched in pathways affecting dopamine signalling, molecular transport, nervous system development and functions in the hippocampus; ephrin receptor signalling and synaptic long-term potentiation in the cerebellum; and tissue morphology, cellular assembly and organization in the liver. Also, the affected genes included those previously implicated in psychosis. Conclusions: The known functions of affected genes suggest that the observed epigenetic changes may underlie the amelioration of symptoms as well as accounting for certain adverse effects including the metabolic syndrome. The results give insights into the mechanism of action of olanzapine, therapeutic effects and the side effects of antipsychotics. © 2014 Melka et al.; licensee BioMed Central Ltd

The effects of olanzapine on genome-wide DNA methylation in the hippocampus and cerebellum

Background: The mechanism of action of olanzapine in treating schizophrenia is not clear. This research reports the effects of a therapeutic equivalent treatment of olanzapine on DNA methylation in a rat model in vivo. Genome-wide DNA methylation was assessed using a MeDIP-chip analysis. All methylated DNA immunoprecipitation (MeDIP), sample labelling, hybridization and processing were performed by Arraystar Inc (Rockville, MD, USA). The identified gene promoters showing significant alterations to DNA methylation were then subjected to Ingenuity Pathway Analysis (Ingenuity System Inc, CA, USA). Results: The results show that olanzapine causes an increase in methylation in 1,140, 1,294 and 1,313 genes and a decrease in methylation in 633, 565 and 532 genes in the hippocampus, cerebellum and liver, respectively. Most genes affected are tissue specific. Only 41 affected genes (approximately 3%) showed an increase and no gene showed a decrease in methylation in all three tissues. Further, the two brain regions shared 123 affected genes (approximately 10%). The affected genes are enriched in pathways affecting dopamine signalling, molecular transport, nervous system development and functions in the hippocampus; ephrin receptor signalling and synaptic long-term potentiation in the cerebellum; and tissue morphology, cellular assembly and organization in the liver. Also, the affected genes included those previously implicated in psychosis. Conclusions: The known functions of affected genes suggest that the observed epigenetic changes may underlie the amelioration of symptoms as well as accounting for certain adverse effects including the metabolic syndrome. The results give insights into the mechanism of action of olanzapine, therapeutic effects and the side effects of antipsychotics. © 2014 Melka et al.; licensee BioMed Central Ltd