Neuroimaging profiling identifies distinct brain maturational subtypes of youth with mood and anxiety disorders

Abstract

Mood and anxiety disorders typically begin in adolescence and have overlapping clinical features but marked inter-individual variation in clinical presentation. The use of multimodal neuroimaging data may offer novel insights into the underlying brain mechanisms. We applied Heterogeneity Through Discriminative Analysis (HYDRA) to measures of regional brain morphometry, neurite density, and intracortical myelination to identify subtypes of youth, aged 9–10 years, with mood and anxiety disorders (N = 1931) compared to typically developing youth (N = 2823). We identified three subtypes that were robust to permutation testing and sample composition. Subtype 1 evidenced a pattern of imbalanced cortical-subcortical maturation compared to the typically developing group, with subcortical regions lagging behind prefrontal cortical thinning and myelination and greater cortical surface expansion globally. Subtype 2 displayed a pattern of delayed cortical maturation indicated by higher cortical thickness and lower cortical surface area expansion and myelination compared to the typically developing group. Subtype 3 showed evidence of atypical brain maturation involving globally lower cortical thickness and surface coupled with higher myelination and neural density. Subtype 1 had superior cognitive function in contrast to the other two subtypes that underperformed compared to the typically developing group. Higher levels of parental psychopathology, family conflict, and social adversity were common to all subtypes, with subtype 3 having the highest burden of adverse exposures. These analyses comprehensively characterize pre-adolescent mood and anxiety disorders, the biopsychosocial context in which they arise, and lay the foundation for the examination of the longitudinal evolution of the subtypes identified as the study sample transitions through adolescence.

Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders

“…In contrast, subtype 2 showed evidence of infra-normal development pattern involving almost globally lower GMV deviations. Our findings can be considered as potential evidence of developmental abnormalities in packing density and cell size which resonates with anomalies in cerebral maturation observed in neurodevelopmental disorders (Ge et al, 2022). In addition, the PLS1-subtype 2 genes were enriched in biological processes such as trans-synaptic signaling and regulation of cellular response to stress, and the genes from the virtual histology analyses of this subtype significantly enriched in microglia and inhibitory neurons, the most abundant neurons in GABAergic system.…”

“…Subtyping studies have been advocated as a vital progression toward a more neurologically grounded understanding of heterogeneity in mood disorders (Drysdale et al, 2017;Sun et al, 2023). Numerous investigations have employed various clustering methods to detect neuroimaging-based biotypes in transdiagnostic or diagnosis-specific groups (Chang et al, 2021;Ge, Sassi, Yatham, & Frangou, 2022;Sun et al, 2023). Recent depression studying studies mainly characterizing the distinct emotional symptoms between subgroups (Drysdale et al, 2017;Han et al, 2022).…”

“…Recent depression studying studies mainly characterizing the distinct emotional symptoms between subgroups (Drysdale et al, 2017;Han et al, 2022). Ge et al, also identified brain maturational subtypes using neuroimaging profiling and characterized the differences in psychopathology and cognition behaviors among youth with mood and anxiety disorders (Ge et al, 2022). Remarkably, they also delineated the biopsychosocial context in which subgroup patients arise (Ge et al, 2022).…”

“…Ge et al, also identified brain maturational subtypes using neuroimaging profiling and characterized the differences in psychopathology and cognition behaviors among youth with mood and anxiety disorders (Ge et al, 2022). Remarkably, they also delineated the biopsychosocial context in which subgroup patients arise (Ge et al, 2022). Distinct neuropathological mechanisms may underlie heterogeneity in the presentation and progression of the clinical phenotype.…”

Identification of shared and distinct patterns of brain network abnormality across mental disorders through individualized structural covariance network analysis

“…Through modern neuroimaging methods, researchers have gradually established the hypothesis that the common etiology of mental disorders is the damage to balanced large-scale interconnected brain networks during development (Fornito, Zalesky, & Breakspear, 2015). This hypothesis has been verified by a series of neuroimaging studies that elaborate on shared and distinct patterns of aberrance brain networks across mental disorders (Ge, Sassi, Yatham, & Frangou, 2022;Itahashi et al, 2020;Koshiyama et al, 2020;Li et al, 2021;Nakamura et al, 2020;Xia et al, 2019). However, the shared and distinct patterns of brain network abnormalities across mental disorders remain largely unclear, owing to high interindividual heterogeneity.…”