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Methylation Marks Sites of Schizophrenia Risk

13 Dec 2015

December 14, 2015. Two studies published November 30 in Nature Neuroscience point to prenatal brain development as the vulnerable period for schizophrenia risk. The studies tracked methylation of DNA, a regulator of gene expression, across the genome in an unprecedented number of postmortem brain samples. Both found evidence of overlap between DNA methylation sites and genetic variants associated with schizophrenia, suggesting DNA methylation as a molecular mechanism of risk.

One paper, led by Andrew Jaffe of the Lieber Institute for Brain Development in Baltimore, Maryland, surveyed DNA methylation sites in 526 brains across the lifespan and found that methylation changes were most pronounced between pre- and postnatal periods. The other paper, led by Jonathan Mill of University of Exeter, UK, pinpointed sites of DNA methylation changes in 166 prenatal brain samples.

"These are both outstanding papers. With the large numbers of samples, they've explored the idea of DNA methylation in psychiatric diseases on a new level," said Dennis Grayson of the University of Illinois in Chicago, who was not involved in the study. Grayson has long studied DNA methylation as a potential risk factor for psychiatric illnesses, but previous studies looked at far fewer sites (see SRF related news report) than the new studies, which used a microarray designed to track 450,000 sites across the genome.

Comparison of the two studies shows a refreshing consistency of results, Grayson said. "Reproducibility between studies has been one of the bigger problems with across-genome methylation studies," he added.

The addition of a methyl group to DNA is but one of several epigenetic mechanisms that influence gene expression both near and far. Mostly thought of as a repressive factor, a methyl group on top of DNA can also spur gene expression and alternate forms of the gene, depending on how it affects access of transcription factors to the gene's control panel.

While methylation helps determine how the DNA sequence is read out in a particular cell, studying methylation patterns in brain samples narrows in on the methylation sites more relevant to disorders such as schizophrenia. This illuminates some of the control panel for early brain development, which is thought to be disrupted in schizophrenia.

The studies also start to help make sense of the windfall of mostly non-coding genetic variants associated with schizophrenia in the landmark genomewide association study (GWAS) published last year by the Psychiatric Genomics Consortium (PGC) (see SRF related news report). To this end, the collaborative PsychENCODE project outlined, in the same issue of the journal, its plans to comprehensively assay gene regulation in a tissue and cell-specific manner.

"These methylation patterns and other epigenetic factors can give good entry points into studying different GWAS loci," Jaffe told SRF. "These associations can be taken advantage of by biologists in the lab to better understand how they work."

Though exactly how methyl groups are laid down remains unclear, this is likely to involve both genetic and environmental factors. "It's possible that epigenetic variation provides a substrate for the gene-environment interactions that we know play a role in complex diseases such as schizophrenia," Mill said.

Methylation across the ages

Jaffe's group focused on methylation patterns in the dorsal lateral prefrontal cortex, with a sample size that surpassed that in their earlier study of DNA methylation (Numata et al., 2012). They've made their data available on the Gene Expression Omnibus website.

The team found that DNA methylation levels changed the most between the prenatal and postnatal periods. After birth, and well into adulthood, these patterns stabilized. This points to the prenatal period as an especially busy time for gene expression changes engineered by DNA methylation, which fits with the group's earlier findings of gene expression changes over the lifetime (see SRF related news report).

Because methylation is probed on DNA from a mixture of brain cell types, it's initially unclear whether methylation changes reflect true changes in methylation levels on DNA or changes in the relative proportions of cell types, each of which has its own methylation profile. Using known cell-specific methylation profiles, the researchers inferred a change in cell composition; namely, they detected a loss of neural progenitor-like cell types as well as increases in mature neural and non-neural cells.

The methylation sites that changed between prenatal and postnatal life were slightly enriched within the 108 regions implicated by the PGC's schizophrenia GWAS (OR = 1.10). The effect seemed specific to schizophrenia, as no enhancement was found between the differentially methylated sites and GWAS loci for Alzheimer's disease, Parkinson's disease, and type 2 diabetes.

The researchers also identified over four million methylation quantitative trait loci (mQTLs), which are genetic variants associated with methylation levels, in adult control tissue. For example, one allele at an mQTL would be associated with more methylation at a site, usually nearby, than the other allele. A majority of schizophrenia GWAS loci (59.6 percent) contained an mQTL derived from the adult cortical data, which suggests that some genetic variants may exert their influence on risk through methylation.

Methylation varied with disease status, though the thousands of differences between samples from people with schizophrenia and healthy controls were much smaller than those detected between prenatal and postnatal time periods. The sites that differentiated ill from healthy brains were slightly enriched in GWAS-supported loci and significantly overlapped with sites regulated during early brain development.

"Whatever risk factors are occurring in the fetal environment in utero, they appear to leave a lasting mark on sites that are different later in life in brains of patients with schizophrenia," Jaffe said.

Because these overlaps were limited, however, the bulk of differentially methylated sites in schizophrenia brains may be consequences of illness rather than causes.

Consistent with a decreased role for DNA methylation on risk later in life, the researchers found no strong evidence for methylation influences around the age of onset of schizophrenia. This suggests that risk factors that coincide with onset may not leave an epigenetic trail, or at least not a methylated one.

Fetal foundation

The paper from Mill's group worked from a precious collection of fetal brains in which his group had already detailed widespread DNA methylation changes during brain development (Spiers et al., 2015).

First author Ellis Hannon and colleagues found that genotype affected methylation levels, as captured by over 16,000 identified mQTLs. Imputting more single nucleotide polymorphisms brought the number over 250,000. The lower number of mQTLs compared to the Jaffe paper likely reflects the smaller number of brains and a more mixed bag of cell types.

The mQTLs were enriched in regions of the genome related to gene transcription, such as DNase1 hypersensitivity sites and transcription factor binding sites. The variants also exerted their effects predominantly nearby.

The mQTLs were mostly stable developmentally: For example, if an allele was associated with high levels of methylation prenatally, this also tended to be true in adults. But a small subset of mQTLs had strong effects in fetal brain but no modulation in adult brain.

"It's the exception rather than the rule, but when it happens, I think it's pretty interesting because that means there's a potential for genetic variation to have development-specific or tissue-specific effects," Mill said.

The full catalogue of mQTLs overlapped with risk loci identified by the PGC's schizophrenia GWAS: Genomewide significant risk variants were found among the mQTLs four times more often than expected by chance. This enrichment was also specific for schizophrenia GWAS loci, as it was not found for GWAS loci for other brain disorders and phenotypes.

The mQTLs could also help pinpoint risk variants within the 108 regions implicated by GWAS. Because of linkage disequilibrium, genomewide significant SNPs usually implicate a stretch of DNA containing several genes rather than a precise base. The researchers reported instances in which mQTLs concentrated near a variant within a region, thus more clearly implicating a single gene.

The group has made their data freely available on their website.

"We're hoping this is a resource that other people in the field can use and take forward to generate hypotheses about the genetic data," Mill said.—Michele Solis.

References:

Jaffe AE, Gao Y, Deep-Soboslay A, Tao R, Hyde TM, Weinberger DR, Kleinman JE.

Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat Neurosci. 2015 Nov 30. Abstract

Hannon E, Spiers H, Viana J, Pidsley R, Burrage J, Murphy TM, Troakes C, Turecki G, O'Donovan MC, Schalkwyk LC, Bray NJ, Mill J. Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci. Nat Neurosci. 2015 Nov 30. Abstract

Akbarian S, Liu C, Knowles JA, Vaccarino FM, Farnham PJ, Crawford GE, Jaffe AE, Pinto D, Dracheva S, Geschwind DH, Mill J, Nairn AC, Abyzov A, Pochareddy S, Prabhakar S, Weissman S, Sullivan PF, State MW, Weng Z, Peters MA, White KP, Gerstein MB, Amiri A, Armoskus C, Ashley-Koch AE, Bae T, Beckel-Mitchener A, Berman BP, Coetzee GA, Coppola G, Francoeur N, Fromer M, Gao R, Grennan K, Herstein J, Kavanagh DH, Ivanov NA, Jiang Y, Kitchen RR, Kozlenkov A, Kundakovic M, Li M, Li Z, Liu S, Mangravite LM, Mattei E, Markenscoff-Papadimitriou E, Navarro FC, North N, Omberg L, Panchision D, Parikshak N, Poschmann J, Price AJ, Purcaro M, Reddy TE, Roussos P, Schreiner S, Scuderi S, Sebra R, Shibata M, Shieh AW, Skarica M, Sun W, Swarup V, Thomas A, Tsuji J, van Bakel H, Wang D, Wang Y, Wang K, Werling DM, Willsey AJ, Witt H, Won H, Wong CC, Wray GA, Wu EY, Xu X, Yao L, Senthil G, Lehner T, Sklar P, Sestan N. The PsychENCODE project. Nat Neurosci. 2015 Nov 25;18(12):1707-12. Abstract