Suppr超能文献

伏隔核的功能连接与抑郁症患者食欲变化的关系。

Functional Connectivity of the Nucleus Accumbens and Changes in Appetite in Patients With Depression.

机构信息

Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany.

Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany.

出版信息

JAMA Psychiatry. 2022 Oct 1;79(10):993-1003. doi: 10.1001/jamapsychiatry.2022.2464.

Abstract

IMPORTANCE

Major depressive disorder (MDD) is characterized by a substantial burden on health, including changes in appetite and body weight. Heterogeneity of depressive symptoms has hampered the identification of biomarkers that robustly generalize to most patients, thus calling for symptom-based mapping.

OBJECTIVE

To define the functional architecture of the reward circuit subserving increases vs decreases in appetite and body weight in patients with MDD by specifying their contributions and influence on disease biomarkers using resting-state functional connectivity (FC).

DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, functional magnetic resonance imaging (fMRI) data were taken from the Marburg-Münster FOR 2107 Affective Disorder Cohort Study (MACS), collected between September 2014 and November 2016. Cross-sectional data of patients with MDD (n = 407) and healthy control participants (n = 400) were analyzed from March 2018 to June 2022.

MAIN OUTCOMES AND MEASURES

Changes in appetite during the depressive episode and their association with FC were examined using fMRI. By taking the nucleus accumbens (NAcc) as seed of the reward circuit, associations with opposing changes in appetite were mapped, and a sparse symptom-specific elastic-net model was built with 10-fold cross-validation.

RESULTS

Among 407 patients with MDD, 249 (61.2%) were women, and the mean (SD) age was 36.79 (13.4) years. Reduced NAcc-based FC to the ventromedial prefrontal cortex (vmPFC) and the hippocampus was associated with reduced appetite (vmPFC: bootstrap r = 0.13; 95% CI, 0.02-0.23; hippocampus: bootstrap r = 0.15; 95% CI, 0.05-0.26). In contrast, reduced NAcc-based FC to the insular ingestive cortex was associated with increased appetite (bootstrap r = -0.14; 95% CI, -0.24 to -0.04). Critically, the cross-validated elastic-net model reflected changes in appetite based on NAcc FC and explained variance increased with increasing symptom severity (all patients: bootstrap r = 0.24; 95% CI, 0.16-0.31; patients with Beck Depression Inventory score of 28 or greater: bootstrap r = 0.42; 95% CI, 0.25-0.58). In contrast, NAcc FC did not classify diagnosis (MDD vs healthy control).

CONCLUSIONS AND RELEVANCE

In this study, NAcc-based FC reflected important individual differences in appetite and body weight in patients with depression that can be leveraged for personalized prediction. However, classification of diagnosis using NAcc-based FC did not exceed chance levels. Such symptom-specific associations emphasize the need to map biomarkers onto more confined facets of psychopathology to improve the classification and treatment of MDD.

摘要

重要性

重度抑郁症(MDD)的特点是对健康造成重大负担,包括食欲和体重的变化。抑郁症状的异质性阻碍了对能够广泛适用于大多数患者的生物标志物的识别,因此需要基于症状进行映射。

目的

通过使用静息态功能连接(FC)指定其对疾病生物标志物的贡献和影响,来定义参与调节食欲和体重增加或减少的奖励回路的功能结构,从而确定 MDD 患者的功能结构。

设计、设置和参与者:在这项病例对照研究中,使用功能性磁共振成像(fMRI)数据来自于 2014 年 9 月至 2016 年 11 月期间进行的马尔堡-明斯特 FOR 2107 情感障碍队列研究(MACS)。2018 年 3 月至 2022 年 6 月分析了 MDD 患者(n=407)和健康对照组参与者(n=400)的横断面数据。

主要结果和措施

使用 fMRI 检查抑郁发作期间食欲的变化及其与 FC 的关系。以伏隔核(NAcc)为奖励回路的种子,映射与食欲变化相反的关联,并使用 10 倍交叉验证构建稀疏症状特异性弹性网模型。

结果

在 407 名 MDD 患者中,有 249 名(61.2%)为女性,平均(SD)年龄为 36.79(13.4)岁。NAcc 与腹内侧前额叶皮质(vmPFC)和海马体的功能连接减少与食欲下降有关(vmPFC:自举 r=0.13;95%CI,0.02-0.23;海马体:自举 r=0.15;95%CI,0.05-0.26)。相比之下,NAcc 与岛叶摄食皮质的功能连接减少与食欲增加有关(自举 r=-0.14;95%CI,-0.24 至 -0.04)。关键的是,经交叉验证的弹性网模型反映了基于 NAcc FC 的食欲变化,并随着症状严重程度的增加,解释方差的增加而增加(所有患者:自举 r=0.24;95%CI,0.16-0.31;贝克抑郁量表评分 28 或更高的患者:自举 r=0.42;95%CI,0.25-0.58)。相比之下,NAcc FC 并不能对诊断(MDD 与健康对照组)进行分类。

结论和相关性

在这项研究中,基于 NAcc 的 FC 反映了抑郁患者在食欲和体重方面的重要个体差异,可用于个性化预测。然而,基于 NAcc 的 FC 对诊断的分类并未超过机会水平。这种特定症状的关联强调需要将生物标志物映射到更受限的精神病理学特征上,以改善 MDD 的分类和治疗。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验