State-specific GluCEST alterations in insular subregions are associated with depression and plasma inflammatory biomarker levels in patients with inflammatory bowel disease

IF 3.4 2区医学 Q2 NEUROIMAGING

Neuroimage-Clinical Pub Date : 2024-11-23 DOI:10.1016/j.nicl.2024.103713

Lixue Xu , Jun Lu , Minsi Zhou , Haiyun Shi , Jing Zheng , Tianxin Cheng , Hui Xu , Dawei Yang , Xingwang Yong , Fang Xu , Chenyue Xu , Yan Dang , Zhan Wang , Siying Zhu , Chunsaier Wang , Peng Li , Zhenchang Wang , Jing Wu , Yi Zhang , Zhenghan Yang

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引用次数: 0

Abstract

Background

Depression commonly co-occurs with inflammatory bowel disease (IBD). Abnormal glutamate levels in the insula and altered plasma inflammatory biomarkers are observed in IBD and depression. However, the changes in glutamate concentrations in insular subregions in IBD and their relationship with depression and inflammatory markers remain unclear. This study aimed to investigate differences in glutamate concentrations in insular subregions between IBD patients and healthy controls (HCs) and their correlation with depression scores and inflammatory markers.

Methods

Forty-two IBD patients (19 active, IBD-A; 23 in remission, IBD-R) and 46 HCs underwent glutamate chemical exchange saturation transfer (GluCEST) magnetic resonance imaging. Blood samples from 37 IBD patients were collected for plasma inflammatory biomarker analysis. GluCEST indices in insular subregions were measured. The Hospital Anxiety and Depression Scale (HADS-D) was used to estimate depression symptoms. Whole-brain voxel-based analysis using one-way ANOVA explored between-group differences in GluCEST indices within the insula. FDR-corrected partial correlation analysis evaluated the relationships between GluCEST, depression symptoms, and inflammatory factors.

Results

GluCEST indices decreased in IBD patients in the left dorsal dysgranular subregion of the insula (dId) (uncorrected p < 0.001, cluster-level FWE-corrected p < 0.05). GluCEST indices in the left dId showed a significant positive correlation with HADS-D in IBD-R (FDR corrected q < 0.05). Additionally, GluCEST indices in the left dId were negatively correlated with CXCL9 (FDR corrected q < 0.05).

Conclusion

State-specific GluCEST alterations in the left dId are a cerebral metabolic feature of IBD. These changes are associated with depression and inflammatory biomarkers, suggesting that the brain-immune-gut axis might underlie depression in IBD patients.

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炎症性肠病患者脑岛亚区特异性 GluCEST 改变与抑郁和血浆炎症生物标志物水平有关

背景抑郁症通常与炎症性肠病（IBD）并发。在 IBD 和抑郁症患者中观察到岛叶谷氨酸水平异常和血浆炎症生物标志物改变。然而，IBD患者脑岛亚区谷氨酸浓度的变化及其与抑郁和炎症标志物的关系仍不清楚。本研究旨在调查 IBD 患者和健康对照组（HCs）岛叶亚区谷氨酸浓度的差异及其与抑郁评分和炎症标志物的相关性。方法 42 名 IBD 患者（19 名活动期，IBD-A；23 名缓解期，IBD-R）和 46 名健康对照组接受谷氨酸化学交换饱和转移（GluCEST）磁共振成像检查。采集了 37 名 IBD 患者的血样，用于血浆炎症生物标记物分析。测量了脑岛亚区的 GluCEST 指数。医院焦虑抑郁量表（HADS-D）用于评估抑郁症状。使用单向方差分析进行基于体素的全脑分析，探讨了岛叶内 GluCEST 指数的组间差异。结果IBD患者脑岛左侧背侧发育不良亚区（dId）的GluCEST指数下降（未校正p< 0.001，簇水平FWE校正p< 0.05）。左侧 dId 的 GluCEST 指数与 IBD-R 中的 HADS-D 呈显著正相关（FDR 校正 q < 0.05）。此外，左侧 dId 的 GluCEST 指数与 CXCL9 呈负相关（FDR 校正 q < 0.05）。这些变化与抑郁和炎症生物标志物有关，表明脑-免疫-肠轴可能是 IBD 患者抑郁的基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Neuroimage-Clinical NEUROIMAGING-

CiteScore

7.50

自引率

4.80%

发文量

368

审稿时长

52 days

期刊介绍： NeuroImage: Clinical, a journal of diseases, disorders and syndromes involving the Nervous System, provides a vehicle for communicating important advances in the study of abnormal structure-function relationships of the human nervous system based on imaging. The focus of NeuroImage: Clinical is on defining changes to the brain associated with primary neurologic and psychiatric diseases and disorders of the nervous system as well as behavioral syndromes and developmental conditions. The main criterion for judging papers is the extent of scientific advancement in the understanding of the pathophysiologic mechanisms of diseases and disorders, in identification of functional models that link clinical signs and symptoms with brain function and in the creation of image based tools applicable to a broad range of clinical needs including diagnosis, monitoring and tracking of illness, predicting therapeutic response and development of new treatments. Papers dealing with structure and function in animal models will also be considered if they reveal mechanisms that can be readily translated to human conditions.