Brain structural networks and connectomes: the brain-obesity interface and its impact on mental health
Brain structural networks and connectomes: the brain-obesity interface and its impact on mental health
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DOI：
10.2147/ndt.s180569
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发表时间：
2018-01-01
影响因子：
3.2
通讯作者：
Weng, Jun-Cheng
中科院分区：
文献类型：
--
作者：
Chen, Vincent Chin-Hung;Liu, Yi-Chun;Weng, Jun-Cheng
目的：肥胖是一种复杂的多因素疾病，被认定为一种全球性的流行病。越来越多的证据表明，肥胖对神经精神疾病患者有不同的影响，这为假设肥胖会改变与大脑情绪和认知紊乱倾向相关的大脑结构和功能提供了依据。在此，我们描述了肥胖受试者（即体重指数[BMI]≥30 kg/m²）与非肥胖对照组相比大脑结构和网络的变化。
患者和方法：我们对20名肥胖受试者（BMI = 37.9 ± 5.2标准差）和30名非肥胖对照组（BMI = 22.6 ± 3.4标准差）进行了无创弥散张量成像和广义q采样成像扫描。进行了图论分析和基于网络的统计分析以评估组间的结构和功能差异。我们还评估了弥散指数、BMI以及焦虑和抑郁症状严重程度（即医院焦虑和抑郁量表总分）之间的相关性。
结果：与对照组相比，肥胖受试者内囊后肢、放射冠和上纵束的弥散指数显著较低。此外，肥胖受试者更有可能报告焦虑和抑郁症状。与非肥胖对照组相比，在肥胖受试者中观察到的结构网络连接较少。肥胖受试者的聚类系数（C）、局部效率（E - 局部）、全局效率（E - 全局）和传递性等拓扑度量显著较低。同样，与非肥胖对照组相比，在肥胖受试者中确定了三个额叶 - 颞叶区域之间结构连接性降低的子网络。
结论：我们通过描绘肥胖个体中受不良影响的大脑区域内和区域间的结构互连性改变，进一步拓展了知识。
Purpose: Obesity is a complex and multi factorial disease identified as a global epidemic. Convergent evidence indicates that obesity differentially influences patients with neuropsychiatric disorders providing a basis for hypothesizing that obesity alters brain structure and function associated with the brain's propensity toward disturbances in mood and cognition. Herein, we characterize alterations in brain structures and networks among obese subjects (ie, body mass index [HMI] >= 30 kg/m(2)) when compared with non-obese controls.Patients and methods: We obtained noninvasive diffusion tensor imaging and generalized q-sampling imaging scans of 20 obese subjects (BMI=37.9 +/- 5.2 SD) and 30 non-obese controls (BMI=22.6 +/- 3.4 SD). Graph theoretical analysis and network-based statistical analysis were performed to assess structural and functional differences between groups. We additionally assessed for correlations between diffusion indices, BMI, and anxiety and depressive symptom severity (ie, Hospital Anxiety and Depression Scale total score).Results: The diffusion indices of the posterior limb of the internal capsule, corona radiata, and superior longitudinal fasciculus were significantly lower among obese subjects when compared with controls. Moreover, obese subjects were more likely to report anxiety and depressive symptoms. There were fewer structural network connections observed in obese subjects compared with non-obese controls. Topological measures of clustering coefficient (C), local efficiency (E-local), global efficiency (E-local), and transitivity were significantly lower among obese subjects. Similarly, three sub-networks were identified to have decreased structural connectivity among frontal-temporal regions in obese subjects compared with non-obese controls.Conclusion: We extend knowledge further by delineating structural interconnectivity alterations within and across brain regions that are adversely affected in individuals who are obese.