Schizophrenia and Autism – Genetic Overlaps

Study provides strongest clues to date for causes of schizophrenia

http://www.med.unc.edu/

CHAPEL HILL, N.C. – A new genome-wide association study (GWAS) estimates the number of different places in the human genome that are involved in schizophrenia.

In particular, the study identifies 22 locations, including 13 that are newly discovered, that are believed to play a role in causing schizophrenia.

“If finding the causes of schizophrenia is like solving a jigsaw puzzle, then these new results give us the corners and some of the pieces on the edges,” said study lead author Patrick F. Sullivan, MD. “We’ve debated this for a century, and we are now zeroing in on answers.”

“This study gives us the clearest picture to date of two different pathways that might be going wrong in people with schizophrenia,” Sullivan said. “Now we need to concentrate our research very urgently on these two pathways in our quest to understand what causes this disabling mental illness.”

Sullivan is a professor in the departments of Genetics and Psychiatry and director of the Center for Psychiatric Genomics at the University of North Carolina School of Medicine. The new study was published online Sunday, Aug. 25, 2013 by the journal Nature Genetics.

The results are based on a multi-stage analysis that began with a Swedish national sample of 5,001 schizophrenia cases and 6,243 controls, followed by a meta analysis of previous GWAS studies, and finally by replication of single nucleotide polymorphisms (SNPs) in 168 genomic regions in independent samples. The total number of people in the study was more than 59,000.

One of the two pathways identified by the study, Sullivan said, is a calcium channel pathway. This pathway includes the genes CACNA1C and CACNB2, whose proteins touch each other as part of an important process in nerve cells. The other is the “micro-RNA 137” pathway. This pathway includes its namesake gene, MIR137 – which is a known regulator of neuronal development – and at least a dozen other genes regulated by MIR137.

“What’s really exciting about this is that now we can use standard, off-the-shelf genomic technologies to help us fill in the missing pieces,” Sullivan said. “We now have a clear and obvious path to getting a fairly complete understanding of the genetic part of schizophrenia. That wouldn’t have been possible five years ago.”

The results are based on a multi-stage analysis that began with a Swedish national sample of 5,001 schizophrenia cases and 6,243 controls, followed by a meta analysis of previous GWAS studies, and finally by replication of single nucleotide polymorphisms (SNPs) in 168 genomic regions in independent samples. The total number of people in the study was more than 59,000.

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Further Readings of Interest

Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis.

http://www.ncbi.nlm.nih.gov/pubmed/23453885

BACKGROUND:

Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia.

METHODS:

We analysed genome-wide single-nucleotide polymorphism (SNP) data for the five disorders in 33,332 cases and 27,888 controls of European ancestory. To characterise allelic effects on each disorder, we applied a multinomial logistic regression procedure with model selection to identify the best-fitting model of relations between genotype and phenotype. We examined cross-disorder effects of genome-wide significant loci previously identified for bipolar disorder and schizophrenia, and used polygenic risk-score analysis to examine such effects from a broader set of common variants. We undertook pathway analyses to establish the biological associations underlying genetic overlap for the five disorders. We used enrichment analysis of expression quantitative trait loci (eQTL) data to assess whether SNPs with cross-disorder association were enriched for regulatory SNPs in post-mortem brain-tissue samples.

FINDINGS:

SNPs at four loci surpassed the cutoff for genome-wide significance (p<5×10(-8)) in the primary analysis: regions on chromosomes 3p21 and 10q24, and SNPs within two L-type voltage-gated calcium channel subunits, CACNA1C and CACNB2. Model selection analysis supported effects of these loci for several disorders. Loci previously associated with bipolar disorder or schizophrenia had variable diagnostic specificity. Polygenic risk scores showed cross-disorder associations, notably between adult-onset disorders. Pathway analysis supported a role for calcium channel signalling genes for all five disorders. Finally, SNPs with evidence of cross-disorder association were enriched for brain eQTL markers.

INTERPRETATION:

Our findings show that specific SNPs are associated with a range of psychiatric disorders of childhood onset or adult onset. In particular, variation in calcium-channel activity genes seems to have pleiotropic effects on psychopathology. These results provide evidence relevant to the goal of moving beyond descriptive syndromes in psychiatry, and towards a nosology informed by disease cause.

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This entry was posted in Autism, Genetics, Neurology, Physiology, Schizophrenia. Bookmark the permalink.

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