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Background: Reductions in the volume of brain white matter are a common feature in schizophrenia and bipolar disorder while the association between white matter and polygenic schizophrenia-related risk is unclear. To look at the intermediate state between health and the full-blown disorder, we investigated this aspect in groups of patients before and after the onset of psychosis. Methods: On a 3 Tesla scanner, total and regional white matter volumes were investigated by structural magnetic resonance imaging (MRI) in the following groups: 37 at-risk mental state patients (ARMS), including 30 with no transition to psychosis (ARMS-NT) and 7 with a transition to psychosis (ARMS-T) pooled with 25 first episode psychosis (FEP) patients. These T1-weighted images were automatically processed with the FreeSurfer software and compared with an odds-ratio-weighted polygenic schizophrenia-related risk score (PSRS) based on the publicly available top white matter single-nucleotide polymorphisms. Results: We found no association, only a trend, between PSRS and white matter volume over all groups (β = 0.24, p = 0.07, 95% confidence interval = [-0.02 – 0.49]). However, a higher PSRS was significantly associated with a higher probability of being assigned to the ARMS-T + FEP group rather than to the ARMS-NT group (β = 0.70, p = 0.02, 95% confidence interval = [0.14 – 1.33]); there was no such association with white matter volume. Additionally, a positive association was found between PSRS and the Brief Psychiatric Rating Scale (BPRS) total score for the pooled ARMS-NT/ARMS-T+FEP sample and for the ARMS-T + FEP group also, but none for the ARMS-NT group only. Conclusion: These findings suggest that at-risk mental state patients with a transition and first-episode psychosis patients have a higher genetic risk for schizophrenia than at-risk mental state patients with no transition to psychosis; this risk was associated with psychopathological symptoms. Further analyses may allow polygenic schizophrenia-related risk scores to be used as biomarkers to predict psychosis.