Hints of genomic dark matter: rare variants contribute to schizophrenia risk

Written by: Stephen Hsu

Primary Source: Information Processing

The study below is sensitive to rare variants which are implicated in schizophrenia risk. These rare variants add to the heritability already associated with common variants, estimated to be at least 32%. In related work, mutations affecting schizophrenia risk were shown to depress IQ in individuals who did not present for schizophrenia.

These results suggest a model for individual variation in brain function and cognitive ability driven by the number of disruptive mutations (“nicks” affecting key functions such as those listed below). Some of these variants are relatively common in the population (e.g., have frequency of at least a few percent), others are very rare (e.g., 1 in 10,000 in the population). See also Deleterious variants affecting traits that have been under selection are rare and of small effect.

A polygenic burden of rare disruptive mutations in schizophrenia

Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease.

Figure from related paper: De novo mutations in schizophrenia implicate synaptic networks (doi:10.1038/nature12929)

Caption: Overlap of genes bearing nonsynonymous (NS) de novo mutations in schizophrenia (refs 12–14), autism spectrum disorder (refs 6–9) and intellectual disability (refs 10, 11). Overlaps of six or fewer genes are listed by name. See Extended Data Table 5 for statistical significance of these overlaps, and see Table 2 and text for disease sets.

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Stephen Hsu
Stephen Hsu is vice president for Research and Graduate Studies at Michigan State University. He also serves as scientific adviser to BGI (formerly Beijing Genomics Institute) and as a member of its Cognitive Genomics Lab. Hsu’s primary work has been in applications of quantum field theory, particularly to problems in quantum chromodynamics, dark energy, black holes, entropy bounds, and particle physics beyond the standard model. He has also made contributions to genomics and bioinformatics, the theory of modern finance, and in encryption and information security. Founder of two Silicon Valley companies—SafeWeb, a pioneer in SSL VPN (Secure Sockets Layer Virtual Private Networks) appliances, which was acquired by Symantec in 2003, and Robot Genius Inc., which developed anti-malware technologies—Hsu has given invited research seminars and colloquia at leading research universities and laboratories around the world.
Stephen Hsu

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