Pathway studies confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders

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Manuel Mattheisen, Associate Professor, Dept. of Biomedicine, Aarhus University

From genes to biology

Genome-wide association studies (GWAS) have identified large numbers of risk variants and loci that show robust associations with one or even more then one mental disorder. Nevertheless, in most cases it remains unclear how these variants confer risk to the disorders under study. Moreover, the identified susceptibility variants only explain a small fraction of the disease variance. A recent study for example has suggested that several thousand common loci might be involved in the etiology of schizophrenia. Many common risk loci with potentially small effect sizes are therefore still to be detected. In an attempt to learn more about the biological processes behind disorders, such as schizophrenia, bipolar disorder and major depression, two recent studies have performed pathway and gene-set analyses based on genetic information from a total of more then 60,000 individuals.

New analytical frameworks helped to dissect complex disorders

Both studies highlighted in this report developed sophisticated analytical frameworks in order to analyze the data at hand. Juraeva and colleagues choose to focus on all the different levels from pathways to genes to single single-nucleotide polymorphism (SNPs) and developed a framework that allowed them to implicate single genes and SNPs of importance in the analyzed pathways. The Network and Pathway Analysis Subgroup (NPAS-PGC) of the Psychiatric Genomics Consortium (PGC) was faced with the problem to combine information from five different analysis programs (FORGE, INRICH, SET-SCR, MAGENTA, and ALIGATOR) and up to three of the five analyzed disorders. They developed a new rank-based method to combine the results across analysis methods and disorders. As a result they could maximize the informativeness while avoiding the confounding by the biases or shortcomings of the individual methods. Subsequent analyses comprised usage of co-expression and brain topology networks. Both studies used multiple resources (among others KeGG, GO, Reactome and others) to include information about biological processes and pathways in the analyses.

Known mechanisms and several novel insights

Juraeva and colleagues report CTCF, CACNB2 as risk factors for schizophrenia, a finding that was later confirmed by the PGC in their latest GWAS on schizophrenia (see previous newsletter reports). In addition, several biological processes were identified that had previously been implicated in the etiology of schizophrenia (regulation of gene expression, cell adhesion molecules and synapse organization). Gerome Breen, Peter Holmans and colleagues found for schizophrenia, bipolar disorder and major depression that genes relating to histone methylation (molecular changes that alter DNA expression), immune and neuronal signaling pathways are risk factors associated with the development of these disorders. Their results suggest that the integration of gene expression with pathway-level analyses on larger GWAS will help future research and that the polygenic overlap between different psychiatric illnesses is nonrandom at a molecular or pathway level.

Both studies are the result of several years of work by the respective working groups. The “Systematic Investigation of the Molecular Causes of Major Mood Disorders and Schizophrenia” (MooDS) project in Germany was a national multi-institutional collaboration between 2008 and 2013. Both MooDS and its successor IntegraMent (“Integrated Understanding of Causes and Mechanisms in Mental Disorders”) are long standing collaboration partners for iPSYCH research groups. “The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium” (PGC) is an international, multi-institutional collaboration founded to conduct broad-scale pathway analyses of genetic data for psychiatric disease. The group is co-lead by Gerome Breen from King's College London and Peter A. Holmans from Cardiff University.

The article “Integrated pathway-based approach identifies association between genomic regions at CTCF and CACNB2 and schizophrenia”, Juraeva D, Haenisch B, et al., was published in PLoS Genetics, 2014, 10(6):e1004345.

The article “Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways”, The Network and Pathway Analysis Subgroup of the Psychiatric Genomics Consortium, was published in Nature Neuroscience, 2015, 18(2):199-209.

Facts about the studies

  • Together more than 375 authors from 255 research institutes in 19 countries are behind the articles in Nature Neuroscience and PLoS Genetics.
  • Together the studies are based on DNA from a total of approx. 60,000 persons.
  • Five psychiatric disorders have been studied: ADHD, autism, schizophrenia, bipolar disorder, and major depression.
  • Integrated pathway analysis designs allowed for identification of CTCF, CACNB2 as risk factors for schizophrenia. Both genes have since then been confirmed in the latest and largest genome-wide association analysis for schizophrenia.
  • “Histone methylation processes”, multiple “immune and neuronal signaling pathways”, as well as “postsynaptic density” have been identified as important contributors to disease risk in schizophrenia, bipolar disorder and major depression.
  • Danish researchers are members of almost all disease-working groups in the Psychiatric Genomics Consortium (PGC) and are members of the “Network and Pathway Analysis Subgroup of the PGC”.
  • iPSYCH researchers from Aarhus University and Mental Health Centre Sct. Hans and Bispebjerg have been participating in these collaborations as well as Statens Serum Institut (SSI).

Further information:

Manuel Mattheisen, Associate Professor, Department of Biomedicine, Aarhus University. Email: