Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort

Abstract

Background:The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology.Methods: For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusionweighted and structural MRI from healthy adults (n=195). Individuals with schizophrenia (n=322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile).Repeating this classification for each tract and region yielded a deviation map for each individual.Results: Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions.Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region, whereas 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59±2%, p<0.001). Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r=-0.17, p=0.006). Conclusions: Anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.

Mental health explains individual deviations from normative range in cognition-associated brain states

“…Whereas recent neuroimaging studies have mainly applied normative modeling to clinical cohorts and studied extreme deviations in estimated brain traits in relation to symptom levels 20,34,35 , our study extended the application of normative modeling to a large population cohort and demonstrated a continuum in the relationship between individual abnormality in brain traits and their overall mental health state. Our findings align well with prior evidence that cognition can be compromised as a function of mental health and highlights potential mechanisms in the brain.…”

Morphometric Analysis of Structural MRI Using Schizophrenia Meta-analytic Priors Distinguish Patients from Controls in Two Independent Samples and in a Sample of Individuals With High Polygenic Risk

“…Our approach has potential utility for cross-modal MRI applications, for any psychiatric condition with well-established brain changes 1 and helps to parse patient heterogeneity not reflected in large meta-analytical SCZ case/control neuroimaging studies. 6,38,[49][50][51] We expect it can also aid future efforts to improve diagnostic classification or prediction based on a combination of biological (e.g. MRS in addition to PRS), psychometric and clinical metrics.…”

Reconsidering brain tissue changes as a mechanistic focus for early intervention in psychiatry

“…[22][23][24] This phenomenon is clearly demonstrated in a recent cross-sectional study of individual deviations from normative models of cortical thickness and white matter integrity in schizophrenia. 25 Whereas 79% of patients show infra-normal deviations (i.e., < 5th percentile value of age-and sex-matched healthy individuals), 46% show supra-normal deviations (i.e., > 95th percentile value) for at least one brain region. Infranormal deviations in thickness are more common in medial prefrontal, insula and lateral temporal regions (but in only 15%-20% of patients), whereas supra-normal changes are more common in occipital and paracentral regions (affecting 3% of patients), indicating distributed changes that lack regional specificity.…”

“…Infranormal deviations in thickness are more common in medial prefrontal, insula and lateral temporal regions (but in only 15%-20% of patients), whereas supra-normal changes are more common in occipital and paracentral regions (affecting 3% of patients), indicating distributed changes that lack regional specificity. 25 Furthermore, in a recent detailed appraisal of this issue of grey matter increase using a meta-analytical network mapping approach, Mancuso and colleagues 26 concluded that whenever grey matter reduction occurs in one brain region, concurrent grey matter increase occurs in other brain regions J Psychiatry Neurosci 2020;45(6) across various psychiatric disorders. Interestingly, such grey matter changes of opposite polarity occurred in distinct functional networks.…”

“…69 Many brain regions are altered by the majority of brain diseases, albeit to a variable extent. 70,71 Third, most patients with psychosis display a pattern of cortical thickness that is indistinguishable from that of healthy controls, 25,72,73 indicating that neuroprogression is an unlikely mechanistic process operating in a large majority of functionally disabled patients who need active interventions. If this is the case, reversing or arresting these brain changes may not bring the desired effects of early intervention.…”