Molecular and micro-architectural mapping of gray matter alterations in psychosis

Author:

García-San-Martín NataliaORCID,Bethlehem Richard A. I.ORCID,Mihalik Agoston,Seidlitz JakobORCID,Sebenius Isaac,Alemán-Morillo Claudio,Dorfschmidt Lena,Shafiei GoliaORCID,Ortiz-García de la Foz VíctorORCID,Merritt KateORCID,David AnthonyORCID,Morgan Sarah E.ORCID,Ruiz-Veguilla Miguel,Ayesa-Arriola RosaORCID,Vázquez-Bourgon JavierORCID,Alexander-Bloch AaronORCID,Misic BratislavORCID,Bullmore Edward T.ORCID,Suckling JohnORCID,Crespo-Facorro Benedicto, ,Romero-García RafaelORCID

Abstract

AbstractThe psychosis spectrum encompasses a heterogeneous range of clinical conditions associated with abnormal brain development. Detecting patterns of atypical neuroanatomical maturation across psychiatric disorders requires an interpretable metric standardized by age-, sex- and site-effect. The molecular and micro-architectural attributes that account for these deviations in brain structure from typical neurodevelopment are still unknown. Here, we aggregate structural magnetic resonance imaging data from 38,696 healthy controls (HC) and 1256 psychosis-related conditions, including first-degree relatives of schizophrenia (SCZ) and schizoaffective disorder (SAD) patients (n = 160), individuals who had psychotic experiences (n = 157), patients who experienced a first episode of psychosis (FEP, n = 352), and individuals with chronic SCZ or SAD (n = 587). Using a normative modeling approach, we generated centile scores for cortical gray matter (GM) phenotypes, identifying deviations in regional volumes below the expected trajectory for all conditions, with a greater impact on the clinically diagnosed ones, FEP and chronic. Additionally, we mapped 46 neurobiological features from healthy individuals (including neurotransmitters, cell types, layer thickness, microstructure, cortical expansion, and metabolism) to these abnormal centiles using a multivariate approach. Results revealed that neurobiological features were highly co-localized with centile deviations, where metabolism (e.g., cerebral metabolic rate of oxygen (CMRGlu) and cerebral blood flow (CBF)) and neurotransmitter concentrations (e.g., serotonin (5-HT) and acetylcholine (α4β2) receptors) showed the most consistent spatial overlap with abnormal GM trajectories. Taken together these findings shed light on the vulnerability factors that may underlie atypical brain maturation during different stages of psychosis.

Publisher

Springer Science and Business Media LLC

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