Independent Methylome-Wide Association Studies of Schizophrenia Detect Consistent Case–Control Differences. (5th June 2019)

• Record Type: Journal Article
• Authors: Chan, Robin F; Shabalin, Andrey A; Montano, Carolina; Hannon, Eilis; Hultman, Christina M; Fallin, Margaret D; Feinberg, Andrew P; Mill, Jonathan; van den Oord, Edwin J C G; Aberg, Karolina A
• Is Part Of: Schizophrenia bulletin. Volume 46:Number 2(2020)
• Page Start: 319
• Page End: 327
• Publication Date: 2019-06-05
• Subjects: DNA methylation -- MBD-seq -- methylome-wide association study (MWAS) -- schizophrenia; Schizophrenia -- Periodicals; Schizophrenia -- Research -- Periodicals; 616.898005
• DOI: 10.1093/schbul/sbz056
• Languages: English
• ISSNs: 0586-7614

Abstract

Abstract: Methylome-wide association studies (MWASs) are promising complements to sequence variation studies. We used existing sequencing-based methylation data, which assayed the majority of all 28 million CpGs in the human genome, to perform an MWAS for schizophrenia in blood, while controlling for cell-type heterogeneity with a recently generated platform-specific reference panel. Next, we compared the MWAS results with findings from 3 existing large-scale array-based schizophrenia methylation studies in blood that assayed up to ~450 000 CpGs. Our MWAS identified 22 highly significant loci ( P < 5 × 10 −8 ) and 852 suggestively significant loci ( P < 1 × 10 −5 ). The top finding ( P = 5.62 × 10 −11, q = 0.001) was located in MFN2, which encodes mitofusin-2 that regulates Ca 2+ transfer from the endoplasmic reticulum to mitochondria in cooperation with DISC1 . The second-most significant site ( P = 1.38 × 10 −9, q = 0.013) was located in ALDH1A2, which encodes an enzyme for astrocyte-derived retinoic acid—a key neuronal morphogen with relevance for schizophrenia. Although the most significant MWAS findings were not assayed on the arrays, we observed significant enrichment of overlapping findings with 2 of the 3 array datasets ( P = 0.0315, 0.0045, 0.1946). Overrepresentation analysis of Gene Ontology terms for the genes in the significant overlaps suggested high similarity in the biological functions detected by the different datasets. Top terms were related to immune and/or stress responses, cell adhesion and motility, and a broad range of processes essential for neurodevelopment.