ArticleTranslational psychiatry2026
Spatial alignment of chemoarchitecture and resting-state functional connectivity predicts short term weight restoration in anorexia nervosa.
Article in Translational psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Resting-state functional connectivity (rsFC) studies have revealed altered regional homogeneity (ReHo) and degree centrality (DC) in individuals with anorexia nervosa (AN) compared to healthy controls (HC), but the underlying mechanisms remain unclear. Here we explored the spatial alignment with neurotransmitter receptor and transporter densities (i.e., "chemoarchitecture", based on "reference" PET studies) as a potential explanatory factor. We investigated rsFC alterations in acutely underweight patients with AN (n = 87) and age-matched HC (n = 87) cross-sectionally at admission and then again after successful weight-restoration treatment. Global ReHo and DC maps were associated with the spatial distribution of neurotransmitter receptors, transporters and/or metabolic glucose uptake. First, the correlation between rsFC alterations in AN and chemoarchitecture was evaluated at the group/timepoint-level. Second, individual-level correlations of neuroreceptor maps with rsFC alterations were calculated to test for possible associations with early weight restoration. The acute state of AN was characterized by higher DC (but not ReHo) in brain regions with a higher cortical density of vesicular acetylcholine transporter (VAChT), dopamine transporter (DAT) and serotonin transporter (SERT). Conversely, weight restoration was associated with normalization of DC, especially in areas with a higher DAT density. Importantly, individual-level spatial correlations between VAChT, DAT and SERT densities and DC alterations at admission significantly predicted early weight gain over first 90 days of treatment. These results suggest that neurochemical context may underlie functional brain alterations, providing a preliminary step toward identifying biological risk signatures. Replication with individualized PET data will be crucial to validate their potential utility for treatment stratification and personalization.
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