Schizophrenia, variability, and the Anna Karenina principle
In neuroimaging studies of people with schizophrenia there is often higher within group variancein the patient group compared to the control group. This is counterintuitive - why would asubset of people selected because they all have the same disease be more varied than the generalpopulation? We used simulated data and real neuroimaging data to identify a potential cause ofelevated variance in populations of patients with schizophrenia. We demonstrated that elevatedvariance can arise within variables that are unrelated to disease status simply because peoplewith a set of neurological perturbations that cause schizophrenia are more likely to have highernumbers of perturbations overall. Additionally, we showed that observed elevated variances inpeople with schizophrenia can be reproduced by models that only rely on perturbation count.These results highlight an important barrier in our attempts to understand the pathophysiology ofschizophrenia. Standard statistical practices in schizophrenia research do not account for the factthat schizophrenia is, at every level of analysis that has been studied, highly heterogeneous. Thisheterogeneity by itself is sufficient to produce elevated variances. Our work suggests that themost effective way to prevent schizophrenia may not be to identify and mitigate specificpathologies but rather to reduce the impact of broadly damaging factors such as those associatedwith poverty.