Whole Genome Profiling to Detect Schizophrenia Methylation Markers

Schizophrenia (SCZ) is a devastating psychiatric disorder. The aim of this study was to detect DNA methylation (5meC) profiles in whole blood associated with SCZ. The sample consisted of schizophrenia cases and controls selected from national population registers in Sweden. We employed MBD protein-based enrichment of the methylated DNA fraction, followed by single end sequencing (50 bp reads) on the SOLiD platform. To improve methylome-wide coverage we used an existing protocol variant, which increases the relative number of fragments from CpG poor regions. To analyze the data, we used an analysis pipeline described elsewhere7, that was designed specifically for MBD-seq and included alignment, quality control (QC) of reads and samples, coverage calculations for the 26,752,702 autosomal CpGs in the reference genome using a non-parametric estimate of the fragment size distribution, an in silico experiment to identify CpGs in loci with alignment problems, a 2-stage adaptive algorithm to combine data from correlated adjacent CpG sites in "blocks", principal component analysis (PCA), association testing, bioinformatics annotation and network analysis. After QC, 1459 subjects with on average 32.4 million high quality reads remained. Association testing was performed on 4.3 million high quality blocks after regressing out possible assay related technical artifacts, sex/age, and unmeasured confounders through the PCA components.

• Study Design:
  • Case-Control
• Study Type:
  • Case-Control
• Total number of consented subjects: 1459
• Subject Sample Telemetry Report (SSTR)

• BioProject
• PubMed
• BioSample
• MeSH

• Primary Phenotype: Schizophrenia

• Principal Investigator
  • Edwin van den Oord, PhD. Virginia Commonwealth University, VA, USA.
• Funding Source
  • RC2MH089996. National Institutes of Health, Bethesda, MD, USA.