Coordinated cortical thickness alterations across six neurodevelopmental and psychiatric disorders

Abstract

Neuropsychiatric disorders are increasingly conceptualized as overlapping spectra sharing multi-level neurobiological alterations. However, whether transdiagnostic cortical alterations covary in a biologically meaningful way is currently unknown. Here, we studied co-alteration networks across six neurodevelopmental and psychiatric disorders, reflecting pathological structural covariance. In 12,024 patients and 18,969 controls from the ENIGMA consortium, we observed that co-alteration patterns followed normative connectome organization and were anchored to prefrontal and temporal disease epicenters. Manifold learning revealed frontal-to-temporal and sensory/limbic-to-occipitoparietal transdiagnostic gradients, differentiating shared illness effects on cortical thickness along these axes. The principal gradient aligned with a normative cortical thickness covariance gradient and established a transcriptomic link to cortico-cerebello-thalamic circuits. Moreover, transdiagnostic gradients segregated functional networks involved in basic sensory, attentional/perceptual, and domain-general cognitive processes, and distinguished between regional cytoarchitectonic profiles. Together, our findings indicate that shared illness effects occur in a synchronized fashion and along multiple levels of hierarchical cortical organization.

Multimodal neural correlates of childhood psychopathology

“…We found that betweennetwork RSFC loadings related to the p factor followed the sensory-to-transmodal gradient, with the default and control networks yielding higher between-network FC (i.e., greater integration) while sensory systems exhibited lower between-network FC (i.e., greater segregation), suggesting that connectivity between the two anchors of the principal gradient might be affected by the p factor. This finding is in line with recent studies showing that the sensory-to-transmodal axis is impacted across several disorders (Hettwer et al, 2022;Opel et al, 2020;Park et al, 2022a). As the p factor represents a general liability to all common forms of psychopathology, this points towards a disorder-general biomarker of dysconnectivity between lower-order and higher-order systems in the cortical hierarchy (Elliott et al, 2018;Kebets et al, 2019), which might be due to abnormal differentiation between higher-order and lower-order brain networks, possibly due to atypical maturation of higher-order networks.…”

Multimodal, multiscale connectivity blueprints of the cerebral cortex

“…Combining connectivity modes has also been used to better resolve clusters of functional activation in BOLD data [84], and inform the application of deep brain stimulation to psychiatric and neurological diseases [11, 67]. Encouragingly, previous work has found that incorporating multiple perspectives of brain connectivity can result in novel discoveries, including improved generative models of brain connectivity [100], structure-function coupling [56, 105], epicentres of transdiagnostic alterations [57, 60], and the characterization of homophilic wiring principles [16].…”

“…This approach is already widely used on the haemodynamic BOLD signal but also exists for time-series measures from other imaging modalities such as magneto-/electroencephalography (MEG/EEG) and dynamic FDG-fPET (all called “functional connectivity”) [24, 32, 46, 52, 70]. In cases where multiple measures of a feature exist at each brain region, such as gene expression levels across many genes, connectivity can represent the similarity of brain regions with respect to a single local feature [56, 57, 60, 103, 111, 122, 125]. In each case, the ensuing region × region network represents a form of connectivity between brain regions.…”

Shared pattern of impaired social communication and cognitive ability in the youth brain across diagnostic boundaries

“…The MRI data was processed using the same analysis pipeline as described above for HBN. Clinical variables included 129 symptom scores decomposed into 7 components using ICA, as reported previously ( Alnaes et al, 2018 ): Attention/ADHD, anxiety, conduct disorder, depression, psychosis prodrome, mania, and obsessive-compulsive disorder ( Hettwer et al, 2022 ). These clinical symptom components reflect increased presence of symptoms.…”