Researchers, writing in Schizophrenia Bulletin, found that genetic factors explain about 0.5% of whether a person will meet criteria for the diagnosis of schizophrenia. That means that 99.5% is attributable to other factors. Anne Marsman from Maastricht University in the Netherlands was the lead author of the report, and the study included well-known psychosis researcher Jim van Os.
“Social-environmental circumstances, particularly childhood trauma and perceived status gap, drive most of the attributable variation in population mental health,” the study authors explain.
The researchers were trying to create a predictive model for the diagnosis of schizophrenia. They included everything they could find, including age and sex, social circumstances, pain, environmental risk factors, family history, and a polygenic risk score (PRS; a pattern of tens of thousands of genetic markers). This model enabled the researchers to see the relative contribution of each of these risks.
The researchers found that even with the inclusion of all of these factors, they were only able to predict 17% of whether a person went on to meet the criteria for a diagnosis of schizophrenia. Only 3% of 17% was attributable to genetics. That is, genetics explains about 0.5% of whether a person will receive a diagnosis of schizophrenia.
“In the combined model, familial and environmental factors explained around 17% of the variance in mental health, of which around 5% was explained by age and sex, 30% by social circumstances, 16% by pain, 22% by environmental risk factors, 24% by family history, and 3% by PRS for schizophrenia (PRS-SZ).”
The researchers tested their model for other diagnoses as well and found that genetics predicted even less for depression and bipolar disorder.
The researchers used data from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2), which included 2380 participants.
According to the authors, the contribution of genetic risk is typically “evaluated on the basis of statistical significance-testing in massive samples, in which minute effects can acquire statistical significance.” However, statistical significance should not be confused for clinical relevance.
For instance, in a recent study, researchers looked at 90,595 people (49,588 of which had a history of anxiety/depression) and found “pathogenic” copy number variants (CNVs) in 708 of the participants. Even those with a “pathogenic” CNV, however, did not necessarily have a history of anxiety/depression. Although these CNVs were associated with slightly more risk of experiencing mental health issues, they provided no clinical value, and over 99% of the “depressed/anxious” people in the study did not have a CNV.
This is consistent with previous research, which found that even after sequencing the entire genome, genetic factors explained 2.28% of whether a person received a diagnosis of schizophrenia. In another study of “exome” sequencing, the researchers concluded that their results provided no relevant data regarding the risk of psychiatric diagnosis.
Marsman A, Pries LK, ten Have M, de Graaf R, van Dorsselaer S, Bak M, . . . & van Os J. (2020). Do current measures of polygenic risk for mental disorders contribute to population variance in mental health? Schizophrenia Bulletin, sbaa086. https://doi.org/10.1093/schbul/sbaa086 (Link)