By: David Shifrin, PhD
Science Writer, Filament Life Science Communications
Uncovering the etiologies of mental diseases has been a huge challenge for scientists and clinicians alike. The underlying processes that lead to mental illness are multifactorial, with biological, genetic and environmental/lifestyle contributors all playing a role. Though we are still a long way off from a complete understanding of the genetic side of things, a group out of UCLA has added an intriguing piece to the puzzle of schizophrenia.
The study, published in the open access journal Nature Communications, looked at the occurrence of rare variants in patients with schizophrenia and a control group without the disease.
Schizophrenia is highly heritable, with even third-degree relatives (e.g., first cousins) of individuals with the disease at double the risk relative to the general population. However, as the authors point out first thing, schizophrenia is polygenic, making it that much more difficult to understand the full picture.
For this study, the geneticists looked at the occurrence of rare single nucleotide variants that occurred in either patients with schizophrenia or individuals without the disease. They did not include SNVs that were found in both groups. Additionally, they used a genome-wide approach, reducing selective bias that comes from the alternative method of looking only at previously implicated genes. Finally, they included variants that are “rare but recurrent,” rather than just “extremely rare loss-of-function variants.” This allowed the team to build a more complete picture of the cumulative burden found in individuals with vs. without schizophrenia.
Overall, the study revealed a significant increase in the burden of variants predicted to have a deleterious effect in cases vs. controls. The way the initial analysis was set up left open the possibility that this increase could be due either to more variants in cases or “increased predicted deleteriousness” of any given variant. Using additional tools, the authors were able to suggest (though not statistically confirm) that the increased burden was more due to “a larger number of rare deleterious SNVs […], rather than the SNVs in patients being more deleterious.”
Additionally, in an analysis of the polygencity of the higher burden, the authors found that more genes had deleterious rare variants, splice site variants, and stop-altering variants in cases of schizophrenia than in controls. Thus, almost across the board, individuals with schizophrenia display statistically significant increases in potentially damaging genetic mutations.
Importantly, the authors looked at the functional relevance of a subset of affected genes. In cases of schizophrenia, mutated genes were significantly more likely to be expressed in the fetal brain than controls, pointing to the potential developmental foundation of the disease.
Together, all of this data let the authors to conclude that, “not only does the increased burden of rare variants contribute to schizophrenia, also the specific variants implied by our analysis play a role […]” More total mutations combined with more potentially damaging mutations creates a two-part effect contributing to onset of the disease.
While this work lays the groundwork for understanding the network of genetic contributors to the disease, a full map of the genetic factors remains a long way off. In the future, researchers will need to follow up this work with studies that dig deeper into the functional relevance of genes mutated in schizophrenia. Additionally, though the authors do not address this, it is likely that more studies into the molecular pathways encoded by schizophrenia-associated genes will be needed. If regions across the entire genome combine to increase risk, as indicated by this paper, complex and sometimes indirect molecular effects will contribute to the process. Mapping these networks will be difficult but extraordinarily helpful to understanding such a complex problem.