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静息态大脑与FTO肥胖风险等位基因:不同基因型间体感整合和奖赏处理背后的默认模式、感觉运动及突显网络连接性

Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes.

作者信息

Olivo Gaia, Wiemerslage Lyle, Nilsson Emil K, Solstrand Dahlberg Linda, Larsen Anna L, Olaya Búcaro Marcela, Gustafsson Veronica P, Titova Olga E, Bandstein Marcus, Larsson Elna-Marie, Benedict Christian, Brooks Samantha J, Schiöth Helgi B

机构信息

Functional Pharmacology, Department of Neuroscience, Uppsala University Uppsala, Sweden.

Section of Neuroradiology, Department of Radiology, Uppsala University Uppsala, Sweden.

出版信息

Front Hum Neurosci. 2016 Feb 17;10:52. doi: 10.3389/fnhum.2016.00052. eCollection 2016.

Abstract

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention.

摘要

脂肪量与肥胖相关基因(FTO)的单核苷酸多态性(SNP)与肥胖有关,但这些SNP如何影响静息态神经激活尚不清楚。很少有脑成像研究调查与肥胖相关的SNP对神经活动的影响,也没有研究调查静息态连接模式。我们在30名男性参与者中测试了三个主要静息态网络内的连接性:默认模式网络(DMN)、感觉运动网络(SMN)和突显网络(SN),这些参与者根据rs9939609 FTO SNP的基因型进行分组,并通过行为抑制(BIS)和行为激活系统(BAS)问卷测量惩罚和奖励敏感性。由于肥胖与这两个系统的异常有关,我们计算了一个BIS/BAS比率(BBr),该比率考虑了两个分数的特征。BIS高于BAS(较高的BBr)导致额叶和边缘旁区域的连接性增加。这些改变在与肥胖相关的AA基因型中更为明显,在该基因型中,高BBr也与多巴胺能回路中的SN连接性增加以及涉及食物体感整合的一个子网络中的连接性增加有关。与TT基因型的相应参与者相比,AA基因型且BBr高的参与者在涉及食物线索处理的区域以及在内脏感知和基于奖励学习的区域的SMN中也表现出更大的DMN连接性。这些发现表明,神经连接模式在AA携带者中对惩罚和奖励的敏感性影响更密切,使他们更容易患肥胖症。我们的工作解释了在确定肥胖风险时遗传、神经模式和行为测量之间的复杂相互作用,并可能有助于制定针对肥胖预防的个性化策略。

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