An ENIGMA Consortium study of the relationship between white matter microstructure and positive and negative symptom...

Symptom severity in schizophrenia has been repeatedly associated with thinner cortical gray matter. While global and regional white matter microstructure alterations in schizophrenia are well-documented, their association with clinical symptom severity remains unclear. As this is likely due to methodological heterogeneity across studies, we tested whether symptom severity in schizophrenia was associated with regional and global white matter alterations using standardized methods. We hypothesized that positive symptom severity would be associated with temporal white matter changes and that negative symptom severity would be associated with alterations in frontal white matter. Using a standardized fractional anisotropy (FA) analysis pipeline developed by the ENIGMA consortium, we conducted a meta-analysis of the association between white matter microstructure and symptom severity in n = 1025 (ages 16-68 years; 369 women/656 men) across 19 ENIGMA sites. Where significant heterogeneity was detected across sites, we examined whether variation in association strength between white matter microstructure and symptom severity was explained by duration of illness and/or current antipsychotic use. Positive symptom severity was significantly associated with white matter microstructure as measured using temporal lobe FA and global FA. Negative symptom severity showed no significant association with white matter microstructure as measured using frontal lobe FA or global FA. Significant heterogeneity across sites was observed for the negative symptom analysis, explained partly by duration of illness. Post-hoc exploratory analyses identified one site as disproportionately contributing to this heterogeneity, and when removed, negative symptom severity was significantly associated with both global and frontal FA. These findings support the view of schizophrenia as a disorder of brain connectivity, in a manner relevant to understanding variation in clinical symptom severity.