29 May 2012. Three new schizophrenia genes—ITIH3/4, CACNA1C, and SDCCAG8—emerge from the latest genomewide association study (GWAS) published online May 22 in Molecular Psychiatry. Led by Michael O’Donovan and Michael Owen at Cardiff University, United Kingdom, the study also replicates previous genomewide significant signals in a new cohort of schizophrenia subjects diagnosed clinically, rather than with the usual, rigorous research criteria. This suggests that clinically defined cohorts could ease the process of collecting the large sample sizes needed for future GWAS.
The study picks up where the Schizophrenia Psychiatric GWAS Consortium (PGC) left off by exploring genotypes at 78 single-nucleotide polymorphisms (SNPs) found by the recent PGC analysis (see SRF related news story) to have “moderate” association with schizophrenia (p <2 x 10-5). As genotyping gets easier and cheaper, rounding up the sample sizes needed to adequately test these SNPs has presented a bottleneck. Concerns over heterogeneous symptoms in schizophrenia have driven researchers to use only those subjects with a standardized research diagnosis, which involves extensive interviews, medical record summaries, and review and consensus among multiple psychiatrists. The new study tries a shortcut by working with a clinically defined schizophrenia cohort, which is not subject to the same level of standardization.
Against this backdrop of GWAS replication, two other studies in Molecular Psychiatry offer alternate views: one, published online May 18, fails to replicate associations found between SNPs and schizophrenia in a Chinese sample, and another, published online May 15, highlights points of genomic convergence by integrating clues from multiple domains of schizophrenia research, including genetic and functional studies of molecules in humans and animal models.
Replicate, then incorporate
In the new GWAS, first author Marian Hamshere and colleagues focused on a cohort of clinically diagnosed people with schizophrenia who were attending a clozapine clinic for regular checks for dangerous declines in white blood cell counts. This side effect, known as agranulocytosis, occurs in about 1 percent of people taking the antipsychotic clozapine.
Naming their cohort CLOZUK, the researchers extracted DNA from blood samples of 2,640 people with schizophrenia, as well as 2,878 controls. Analyzing the 78 SNPs reaching, or just missing, genomewide significance in the PGC study, the researchers found a reassuring pattern of replication in the CLOZUK sample: 47 percent of markers were associated with schizophrenia (one-tailed p <0.05). Of the 57 SNPs not located in the variable major histocompatibility complex (MHC) region, 35 percent reached significance, and the frequency of these associations was greater than expected by chance, suggesting that these reflect true associations with schizophrenia.
Genewise, of the genomewide significant hits in the PGC, the CLOZUK sample had significant associations in SNPs marking CCDC68, CNNM2, and NT5C2, whereas MIR137, a microRNA surprise that came to light in the PGC study, came close in the CLOZUK group (p = 0.074). All five of the genomewide significant hits found by the PGC study within the MHC locus were also replicated in the CLOZUK group. Because genes within the MHC region are tightly linked, it is hard to distinguish the genes being flagged by the SNPs, and the researchers note that a paper focused on the region is in press.
Noting higher effect sizes for these significant SNPs in CLOZUK than in the PGC study, the researchers compared them to a similarly ethnically homogeneous and similarly ascertained Irish sample within the PGC sample. This revealed no differences in non-MHC loci, suggesting the larger effect sizes reflect something about the homogeneity of the population. Alternatively, the CLOZUK sample could comprise people with a more severe form of the disorder, as clozapine is prescribed when other antipsychotic treatments fail.
When the researchers combined their CLOZUK sample with the PGC data, variants in new loci reached genomewide significance for the first time: ITIH3/4 (a region containing many genes, 3.62 x 10-10), CACNA1C (encodes a subunit of a calcium channel, p = 1.23 x 10-8), and SDCCAG8 (serologically defined colon cancer antigen 8, p = 4.22 x 10-8), with effect sizes ranging from 1.09 to 1.11. The first two, ITIH3/4 and CACNA1C, only reached genomewide significance in the PGC study when schizophrenia and bipolar cases were combined. SDCCAG8 encodes a protein involved in cell division, consistent with other schizophrenia-related genes with roles in neurodevelopment.
This theme of replication did not emerge in a brief report from China. Last year, two GWAS in Han Chinese populations reported genomewide significant hits for schizophrenia, but none of these signals was the same between the two studies (Shi et al., 2011; Yue et al., 2011). In the new report, led by Yong-Gang Yao, of the Chinese Academy of Sciences in Yunan, China, and Xiaogang Chen, of Central South University in Hunan, China, researchers genotyped the nine SNPs fingered by these GWAS in an independent Han Chinese population consisting of 976 cases of schizophrenia and 1,043 controls. First authors Ma and Jinsong Tang found that none turned out to be significantly associated with schizophrenia. Minor allele frequencies differed between their population and the ones used in the GWAS, leading the authors to suggest that regional differences might account for the lack of replication.
Convergent functional genomics
As the genetic evidence streams in, a third study steps back to see the big picture. Led by Alexander Niculescu at Indiana University in Indianapolis, the study uses his approach called “convergent functional genomics” (CFG) to weigh and integrate the different pieces of evidence implicating certain genes in schizophrenia, including data from the International Schizophrenia Consortium GWAS (ISC, 2009), data from structural variants like copy number variants (CNVs), gene expression data from human blood and postmortem brain samples, stem cell data, and data from animal model equivalents.
First authors Mikias Ayalew and Helen Le-Niculescu analyzed these huge and diverse datasets by creating a polyevidence CFG score for each gene. This score is similar to the Google PageRank algorithm in that the more times a gene is implicated in schizophrenia in some way by some data, the higher its rank. This scoring method winnowed down the 3,194 genes they started with to 42 genes with the highest rank. The top-scoring genes were DISC1, HSPA1B, MBP, and TCF4. Pathway analysis of these genes highlighted functional categories like brain development, myelination, cell adhesion, and glutamate receptor signaling—all consistent with schizophrenia as a disorder of disrupted connectivity.
If these genes are the top culprits in schizophrenia, could they be used to create a genetic test for risk of developing the disorder? The researchers developed a genetic risk prediction score (GRPS) based on the presence or absence of risk-conferring alleles at 542 SNPs (deemed nominally significant by the ISC GWAS) in the 42 top-scoring genes. This score was significantly different between schizophrenia and control groups in four independent cohorts, and the researchers explored the abilities of a panel comprising these 542 SNPs for distinguishing risk in individuals. Even if the comprehensive look taken by this approach does not lead to a decisive blood test, it could still help distill schizophrenia’s complexities into some solid understanding.—Michele Solis.
Hamshere ML, Walters JT, Smith R, Richards AL, Green E, Grozeva D, Jones I, Forty L, Jones L, Gordon-Smith K, Riley B, O'Neill T, Kendler KS, Sklar P, Purcell S, Kranz J; The Schizophrenia Psychiatric Genome-wide Association Study Consortium (PGC), Wellcome Trust Case Control Consortium+ (WTCCC+), Wellcome Trust Case Control Consortium 2 (WTCCC2), Morris D, Gill M, Holmans P, Craddock N, Corvin A, Owen MJ, O'Donovan MC. Genome-wide significant associations in schizophrenia to ITIH3/4, CACNA1C and SDCCAG8, and extensive replication of associations reported by the Schizophrenia PGC. Mol Psychiatry. 2012 May 22. Abstract
Ma L, Tang J, Wang D, Zhang W, Liu W, Wang D, Liu XH, Gong W, Yao YG, Chen X. Evaluating risk loci for schizophrenia distilled from genome-wide association studies in Han Chinese from central China. Mol Psychiatry. 2012 May 15. Abstract
Ayalew M, Le-Niculescu H, Levey DF, Jain N, Changala B, Patel SD, Winiger E, Breier A, Shekhar A, Amdur R, Koller D, Nurnberger JI, Corvin A, Geyer M, Tsuang MT, Salomon D, Schork NJ, Fanous AH, O'Donovan MC, Niculescu AB. Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. Mol Psychiatry. 2012 May 15. Abstract