Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, United States.
Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, United States; Biomedical Research Imaging Center, University of North Carolina at Chapel Hill School of Medicine, United States.
Neuroimage. 2018 Nov 1;181:55-63. doi: 10.1016/j.neuroimage.2018.06.082. Epub 2018 Jun 30.
Understanding weight-related differences in functional connectivity provides key insight into neurocognitive factors implicated in obesity. Here, we sampled three groups from human connectome project data: 1) 47 pairs of BMI-discordant twins (n = 94; average BMI-discordancy 6.7 ± 3.1 kg/m), 2) 47 pairs of gender and BMI matched BMI-discordant, unrelated individuals, and 3) 47 pairs of BMI-similar twins, to test for body mass dependent differences in between network functional connectivity. Across BMI discordant samples, three networks appeared to be highly sensitive to weight status; specifically, a network comprised of gustatory processing regions, a visual processing network, and the default mode network (DMN). Further, in the BMI-discordant twin sample, twins with lower BMI had stronger connectivity between striatal/thalamic and prefrontal networks (pFWE = 0.04). We also observed that individuals with a higher BMI than their twin had stronger connectivity between cerebellar and insular networks (pFWE = 0.04). Connectivity patterns observed in the BMI-discordant twin sample were not seen in a BMI-similar sample, providing evidence that the results are specific to BMI discordance. Beyond the involvement of gustatory and visual networks and the DMN, little overlap in results were seen between the two BMI-discordant samples. In concordance with previous findings, we hypothesize that stronger cortical-striatal-thalamic connectivity associated with lower body mass in twins may facilitate increased regulation of hedonically motivated behaviors. In twins with higher body mass, increased cerebellar-insula connectivity may be associated with compromised satiation signaling, an interpretation dovetailing prior research. The lack of overlapping results between the two BMI discordant samples may be a function of higher study design sensitivity in the BMI-discordant twin sample, relative to the more generalizable results in the unrelated sample. These findings demonstrate that distinct connectivity patterns can represent weight variability, adding to mounting evidence that implicates atypical brain functioning with the accumulation and/or maintenance of elevated weight.
了解与体重相关的功能连接差异为肥胖相关的神经认知因素提供了关键的见解。在这里，我们从人类连接组计划数据中抽取了三个组：1）47 对 BMI 不一致的双胞胎（n=94；平均 BMI 差异为 6.7±3.1kg/m），2）47 对性别和 BMI 匹配但 BMI 不一致的非相关个体，以及 3）47 对 BMI 相似的双胞胎，以测试网络间功能连接中体重依赖的差异。在 BMI 不一致的样本中，三个网络似乎对体重状态高度敏感；具体而言，一个由味觉处理区域、视觉处理网络和默认模式网络（DMN）组成的网络。此外，在 BMI 不一致的双胞胎样本中，BMI 较低的双胞胎的纹状体/丘脑和前额叶网络之间的连接更强（pFWE=0.04）。我们还观察到，BMI 高于双胞胎的个体的小脑和岛叶网络之间的连接更强（pFWE=0.04）。在 BMI 相似的样本中没有观察到 BMI 不一致的双胞胎样本中观察到的连接模式，这表明结果是特定于 BMI 不一致的。除了味觉和视觉网络以及 DMN 的参与外，两个 BMI 不一致的样本之间的结果很少重叠。与之前的发现一致，我们假设双胞胎中与较低体重相关的更强皮质-纹状体-丘脑连接可能有助于增加对享乐动机行为的调节。在体重较高的双胞胎中，增加的小脑-岛叶连接可能与饱食信号受损有关，这一解释与之前的研究相符。两个 BMI 不一致的样本之间没有重叠的结果可能是 BMI 不一致的双胞胎样本在研究设计上的敏感性更高的结果，相对于更具普遍性的非相关样本结果。这些发现表明，不同的连接模式可以代表体重的变化，越来越多的证据表明，异常的大脑功能与体重升高的积累和/或维持有关。
