News in Exploration of the Biological Causes of Mental Illness: Potential for New Treatments
Reporter: Aviva Lev-Ari, PhD,RN
Broad’s Stanley Center for Psychiatric Genome Research: Ted Stanley Pledges $650M
Initially opened with a gift from Stanley and his late wife in 2007, the Broad’s Stanley Center has already made progress in identifying genetic risk factors for schizophrenia and bipolar disorder and investigating therapeutic efforts based on those discoveries. This week researchers from Broad and other institutes published a GWAS analysis inNature that identified more than 100 regions of DNA associated with schizophrenia.
“Ten years ago, finding the biological causes of psychiatric disorders was like trying to climb a wall with no footholds,” Stanley Center Director Steven Hyman said in a statement. “But in the last few years, we’ve turned this featureless landscape into something we can exploit. If this is a wall, we’ve put toeholds into it. Now, we have to start climbing.”
The Nature paper1 was produced by the Psychiatric Genomics Consortium (PGC) — a collaboration of more than 80 institutions, including the Broad Institute. Hundreds of researchers from the PGC pooled samples from more than 150,000 people, of whom 36,989 had been diagnosed with schizophrenia. This enormous sample size enabled them to spot 108 genetic locations, or loci, where the DNA sequence in people with schizophrenia tends to differ from the sequence in people without the disease. “This paper is in some ways proof that genomics can succeed,” Hyman says.
“This is a pretty exciting moment in the history of this field,” agrees Thomas Insel, director of the National Institute of Mental Health (NIMH) in Bethesda, Maryland, who was not involved in the study.
- 108 independent associated loci•
- Characterization of associated loci•
- The brain and immunity•
- Overlap with rare mutations•
- Polygenic risk score profiling•
- Author information•
- Extended data figures and tables•
- Supplementary information
Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
In the largest (to our knowledge) molecular genetic study of schizophrenia, or indeed of any neuropsychiatric disorder, ever conducted, we demonstrate the power of GWAS to identify large numbers of risk loci. We show that the use of alternative ascertainment and diagnostic schemes designed to rapidly increase sample size does not inevitably introduce a crippling degree of heterogeneity. That this is true for a phenotype like schizophrenia, in which there are no biomarkers or supportive diagnostic tests, provides grounds to be optimistic that this approach can be successfully applied to GWAS of other clinically defined disorders.
We further show that the associations are not randomly distributed across genes of all classes and function; rather they converge upon genes that are expressed in certain tissues and cellular types. The findings include molecules that are the current, or the most promising, targets for therapeutics, and point to systems that align with the predominant aetiological hypotheses of the disorder. This suggests that the many novel findings we report also provide an aetiologically relevant foundation for mechanistic and treatment development studies. We also find overlap between genes affected by rare variants in schizophrenia and those within GWAS loci, and broad convergence in the functions of some of the clusters of genes implicated by both sets of genetic variants, particularly genes related to abnormal glutamatergic synaptic and calcium channel function. How variation in these genes impact function to increase risk for schizophrenia cannot be answered by genetics, but the overlap strongly suggests that common and rare variant studies are complementary rather than antagonistic, and that mechanistic studies driven by rare genetic variation will be informative for schizophrenia.
Manhattan plot showing schizophrenia associations.
Manhattan plot of the discovery genome-wide association meta-analysis of 49 case control samples (34,241 cases and 45,604 controls) and 3 family based association studies (1,235 parent affected-offspring trios). The x axis is chromosomal position and the y axis is the significance (–log10 P; 2-tailed) of association derived by logistic regression. The red line shows the genome-wide significance level (5 × 10−8). SNPs in green are in linkage disequilibrium with the index SNPs (diamonds) which represent independent genome-wide significant associations.