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Reversibility of Impaired Large-Scale Functional Brain Networks in Cushing's Disease After Surgery Treatment: A Longitudinal Study

Overview
Publisher Karger
Specialties Endocrinology
Neurology
Date 2023 Nov 1
PMID 37913760
Authors
Affiliations
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Abstract

Introduction: Chronic exposure to excessive endogenous cortisol leads to brain changes in Cushing's disease (CD). However, it remains unclear how CD affects large-scale functional networks (FNs) and whether these effects are reversible after treatment. This study aimed to investigate functional network changes of CD patients and their reversibility in a longitudinal cohort.

Methods: Active CD patients (N = 37) were treated by transsphenoidal pituitary surgery and reexamined 3 months later. FNs were computed from resting-state fMRI data of the CD patients and matched normal controls (NCs, N = 37). A pattern classifier was built on the FNs to distinguish active CD patients from controls and applied to FNs of the CD patients at the 3-month follow-up. Two subgroups of endocrine-remitted CD patients were identified according to their classification scores, referred to as image-based phenotypically (IBP) recovered and unrecovered CD patients, respectively. The informative FNs identified by the classification model were compared between NCs, active CD patients, and endocrine-remitted patients as well as between IBP recovered and unrecovered CD patients to explore their functional network reversibility.

Results: All 37 CD patients reached endocrine remission after treatment. The classification model identified three informative FNs, including cerebellar network (CerebN), fronto-parietal network (FPN), and default mode network. Among them, CerebN and FPN partially recovered toward normal at 3 months after treatment. Moreover, the informative FNs were correlated with 24-h urinary-free cortisol and emotion scales in CD patients.

Conclusion: These findings suggest that CD patients have aberrant FNs that are partially reversible toward normal after treatment.

Citing Articles

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Ma Y, Li H, Zhou Z, Chen X, Ma L, Guray E bioRxiv. 2024; .

PMID: 38746228 PMC: 11092457. DOI: 10.1101/2024.04.26.591367.

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