August 2, 2013. A new crop of rare genetic mutations in people with schizophrenia implicates genes involved in the early stages of brain development, reports a study published August 1 in Cell. Using exome sequencing, Mary-Claire King of the University of Washington in Seattle and colleagues identified spontaneously arising, or “de novo,” mutations likely to damage protein function in 54 genes in the schizophrenia group. Network analyses of the transcription patterns of these genes in healthy brains, and of the interactions between their protein products, suggest that these diverse genes work together in the prenatal stages of building a brain, particularly in dorsolateral and ventrolateral prefrontal cortex.
The findings support the long-standing notion that schizophrenia’s roots lie in early brain development and add to evidence of the vulnerability of prefrontal cortex, a region important for complex mental processes, in the disorder.
“These investigators are trying to take the next step by asking if there is anything that ties their genetic findings together,” said Daniel Geschwind of the University of California in Los Angeles, who was not involved in the study. “Given that they start with only 54 genes, it’s kind of remarkable there’s any coherence.”
Network analyses of all human genes have detected groups of genes that seem to work together in the brain. For example, Geschwind and colleagues have tracked transcription patterns in the brain to find genes that turn on and off together, with the idea that those that co-vary are likely engaged in the same function. With this approach, Geschwind’s team has identified groups of genes that work together, called modules, that are specific to humans (Oldham et al., 2006) and perturbed in autism (see SRF related news story). Last year, a similar approach by Vahram Haroutunian's group at New York’s Mount Sinai School of Medicine identified anomalous gene modules in schizophrenia (see SRF related news story). Another network analysis published last year by Dennis Vitkup and colleagues of Columbia University in New York grouped genes based on similarities in their likely phenotypic outcomes and found these groupings were enriched for schizophrenia suspects (see SRF related news story).
The new study combines transcriptional data with protein-protein interaction data to build a final network based only on genes fingered by the exome sequencing. As researchers use more and different kinds of data to decipher the functions of their genes, debate will ensue about how best to integrate the different kinds of information. “It would be nice to integrate the protein networks more formally with the transcriptional networks,” Geschwind said, noting that the protein database was relatively permissive in judging two proteins as interacting and not specific to conditions within neurons.
Round up the suspects
First authors Suleyman Gulsuner, Tom Walsh, and Amanda Watts and colleagues sequenced the exomes of 105 people with schizophrenia, 84 of their unaffected siblings, and 210 of their unaffected parents. The researchers were looking for de novo variants—those mutations that spontaneously occur in the sperm or egg cell prior to conception, rather than being inherited from parents. De novo mutations are prime suspects because they are more likely to be nasty, as natural selection hasn’t had a chance to weed them out. Though previous studies have found de novo mutations in schizophrenia (Xu et al., 2011, and see SRF related news story), they don’t necessarily constitute smoking guns because the background levels of de novo mutations are unclear. The unaffected siblings sequenced in the new study provide hard data on this.
The researchers report finding 103 de novo mutations in people with schizophrenia—meaning that these mutations were not found in a person’s parents or siblings. In comparison, 67 were found in unaffected siblings. The mutations consisted mainly of point mutations, in which a single base change is made in the DNA sequence, but included a few small insertions or deletions of DNA. Among the point mutations, slightly more were found in schizophrenia than in controls. Mutations likely to be damaging were also enriched in the schizophrenia group, which had 57 compared to 35 in sibling controls (that’s an average of 0.54 damaging mutations per person with schizophrenia compared to 0.42 per sibling controls). The researchers also noted that chances of carrying a de novo mutation increased with the father’s age at conception, consistent with previous studies (see SRF related news story and SRF Current Hypothesis). When all was counted and sorted, the researchers had 54 different genes that had been hit by potentially damaging mutations in schizophrenia.
Map them out
Many genetic studies would stop there, rounding out their discussion with a laundry list of speculations about how each gene might relate to a disorder. But the new study goes further, using network analyses to try to uncover what the diverse lot might have in common. To find evidence of genes working together, the researchers used transcription patterns available in the BrainSpan Atlas that were obtained by RNA sequencing of postmortem brain tissue from healthy subjects. The researchers asked whether transcription of their 54 genes co-varied more than those genes fingered by de novo mutations in unaffected siblings. The researchers calculated the correlation between the transcript levels of each pair of genes across different brain samples and judged those with correlation coefficients of 0.8 or above as “connected.” The resulting network of connections was compared to a control network, which was also built from pairwise comparisons of 54 different genes randomly selected from a pool of 264 genes hit by de novo mutations in the unaffected siblings from this and other studies (see SRF related news story).
The transcription data came from different brain regions at different stages of development, ranging from prenatal to adult tissue. Thus, the resulting networks were region and time specific. The researchers found that the schizophrenia network based on data from frontal cortex in fetal tissue had more connections than the control network, suggesting that these genes worked together on something there during early stages of development. Further analysis narrowed this to dorsolateral and ventrolateral prefrontal cortex—regions important for cognitive control, working memory, reward learning, and decision making. In contrast, genes hit by non-damaging variants in schizophrenia resulted in a network that was not different from the control networks.
Another way to gauge whether genes are working together is to see if their protein products physically interact. Using the GeneMANIA database of protein-protein interactions, the researchers found that the genes hit by de novo mutations in schizophrenia had a significantly greater degree of interaction than those found in healthy siblings. In contrast, for the genes hit by benign de novo mutations there was no difference between the schizophrenia gene and control networks.
Add them up
The researchers then combined this protein-based network with the transcription network for the fetal dorsolateral and ventrolateral prefrontal cortex, designating genes as connected by protein-protein interaction data and/or transcription data. This yielded a 50-gene network with 126 connections. These genes were associated with processes like neural proliferation, migration, cell signaling, and axon guidance—all crucial to laying down a brain’s foundations. The researchers noted that some of these genes influenced neurotransmitter signaling (ADCY9, SLC18A2, and GLS) and also highlighted CACNA1I, a gene encoding a subunit of a type of calcium channel, which was hit multiple times in their schizophrenia samples.
The findings support the neurodevelopmental hypothesis of schizophrenia and provide some causal evidence for these genes’ involvement in the disorder. Although opinions may differ on which is more persuasive, this study heralds the integrative nature of research to come.—Michele Solis.
Gulsuner S, Walsh T, Watts AC, Lee MK, Thornton AM, Casadei S, Rippey C, Shahin H, Nimgaonkar VL, Go RC, Savage RM, Swerdlow NR, Gur RE, Braff DL, King MC, McClellan JM. Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network. Cell . 2013 Aug 1 ; 154(3):518-29. Abstract