Lv J, Di Biase M, Cash RFH, et al. - As efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with schizophrenia have failed due to the heterogeneity of the disorder, researchers attempted to map deviations from normative ranges of brain structure for individual patients and examine if the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. Using diffusion-weighted and structural MRI from healthy adults (n = 195), they established normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) for each of 48 white matter tracts and 68 cortical regions. Classification of individuals with schizophrenia (n = 322) was done as either within the normative range for healthy individuals of the same age and gender (5–95% percentiles), infra-normal (< 5% percentile) or supra-normal (> 95% percentile). They obtained a deviation map for each individual via repeating this classification for each tract and region. Widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions, were identified in the schizophrenia group compared with the healthy comparison group. Paradoxically, however, deviation from the normative range for any single tract or region was observed in no more than 15%–20% of patients. Furthermore, infra-normal deviations were observed in 79% of patients for at least one locus (healthy individuals: 59 ± 2%). Thus, while patients had common occurrence of infra-normal deviations, their anatomical loci were highly inconsistent between individuals. A greater number of regions with infra-normal deviations in CT was observed in correlation with higher polygenic risk for schizophrenia. Findings here indicate that heterogeneity in anatomical loci of schizophrenia-related changes is high across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can allow in resolving schizophrenia heterogeneity and guiding personalized interventions.