ArticleNeuropsychiatric disease and treatment2026
Morphometric Similarity Loss and Gray Matter Atrophy Align with Neurotransmitter and Mitochondrial Maps in Drug-Resistant Epilepsy.
Article in Neuropsychiatric disease and treatment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Epilepsy imposes a substantial global burden, and drug-resistant epilepsy (DRE) accounts for a disproportionate share of morbidity due to persistent seizures and limited treatment options. Although MRI studies have reported gray-matter (GM) atrophy in DRE, its spatial specificity, accompanying changes in morphometric similarity network (MSN) connectivity strength, and the performance of an MRI-only supportive screening model for identifying DRE remain incompletely understood. We therefore tested whether GM atrophy clusters non-randomly in territories with high neurotransmitter-receptor, cellular, and mitochondrial distributions, whether MSNs are altered, and evaluated the feasibility of an MRI-only model to support DRE identification. Methods: This study first used voxel-based morphometry (VBM) to map group GM atrophy, then constructed MSN from structural MRI features to analyze global, regional, and graph-theoretic metrics; we next tested the spatial correlation of the GM atrophy map with neurotransmitter receptor and cellular/mitochondrial distributions under family-wise FDR control. Finally, we trained classifiers using LASSO-selected MRI features to develop an MRI-based screening/support tool. All analyses were performed separately in two independent cohorts. Results: Both cohorts showed temporo-limbic-anchored GM atrophy, with discovery-cohort stratification indicating broader thalamo-ventral temporal involvement in TLE and more focal cerebellar effects in non-TLE. MSNs showed preserved global indices with focal regional meanMS reductions (isthmus cingulate/medial orbitofrontal/pars triangularis), reproduced in TLE but not other subtype contrasts. The atrophy map co-localized with 5-HT1B and mGluR5 and with mitochondrial Complex I/IV (plus respiratory capacity and a neuronal subtype map) in discovery, while validation showed no FDR-significant correspondences and opposite directions for mGluR5 and respiratory capacity. The MRI-only panel achieved moderate external AUC (~0.75), consistent with a supportive screening application rather than diagnostic replacement. Conclusion: GM atrophy in DRE aligns with neurotransmitter and mitochondrial distributions and coincides with regional meanMS reductions; an MRI-only model aids DRE identification, though causality and clinical utility await validation in larger longitudinal/interventional studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.