Deviations from normative functioning underlying emotional episodic memory revealed cross-scale neurodiverse alterations linked to affective symptoms in distinct psychiatric disorders

Abstract

BackgroundAffective symptoms are a prevalent psychopathological feature in various psychiatric disorders. However, the underlying neurobiological mechanisms are complex and not yet fully understood. MethodsWe used normative modelling to establish a reference for neurofunctional activation of functional magnetic resonance imaging based on an emotional episodic memory task, which is frequently used to study affective symptoms in psychiatric disorders. This normative reference was derived from a large dataset of healthy individuals (n = 409), and used to evaluate individualized functional alterations by calculating deviations from this reference in a clinical dataset of 328 participants, which included 168 healthy controls and patients with major depressive disorder (MDD, n = 56), bipolar disorder (BD, n = 31), and schizophrenia (SZ, n = 73). The neurofunctional deviations were mapped to emotional networks with specific emotional functions and used to predict affective symptoms in different mental disorders. The microscale cellular signatures underlying macroscale variations were identified using imaging transcriptomic analysis, and associated with affective symptoms. ResultsWe observed distinct patterns of cross-scale neural alterations linked to affective symptoms in three psychiatric disorders. Macroscale neural dysfunctions in distinct disorders were embedded into non-overlapping emotional networks and significantly associated with affective symptoms. The oligodendrocytes may mediate the network-specific impairments, and microglia for MDD, astrocytes for BD, and excitatory neurons for SZ as replicable cell-type correlates of affective symptoms. ConclusionsThese findings have potential implications for the understanding of unique neuropathological patterns of affective symptoms in distinct psychiatric disorders and improving individualized treatment response.