Reorganization of functional brain network architecture in chronic osteoarthritis pain.
Reorganization of functional brain network architecture in chronic osteoarthritis pain.
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慢性骨关节炎疼痛中功能性脑网络结构的重组。
DOI：
10.1002/hbm.25287
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发表时间：
2021-03
影响因子：
4.8
通讯作者：
Apkarian AV
中科院分区：
文献类型：
--
作者：
Barroso J;Wakaizumi K;Reis AM;Baliki M;Schnitzer TJ;Galhardo V;Apkarian AV
骨关节炎（OA）表现为慢性疼痛、运动障碍和本体感觉改变。然而，大脑在这种疾病中的作用在很大程度上是未知的。在这里，我们使用图的数学性质研究了大样本膝关节和髋关节OA （KOA, n = 91； HOA, n = 23）患者的大脑网络。通过将KOA数据细分为发现组和测试组，我们使用了一种强大的验证策略，并测试了我们的发现在HOA中的普遍性。尽管在OA中大脑的整体拓扑属性是保守的，但我们发现存在一个网络范围的重组模式，可以通过一个单一的测量来捕获，即中枢中断指数。我们定位了重组模式，并揭示了OA中网络枢纽层次结构的变化：初级感觉和运动区域以及海马体旁回充当枢纽，而岛叶皮层失去了中心位置。在网络结构的中间水平，额顶叶和扣眼模块表现出优先重组。我们检查了网络属性与临床相关因素之间的关系：整体破坏指数和孤立度属性不能反映临床参数；然而，通过模拟全脑节点度特性，我们确定了一组分布的区域，可以可靠地预测KOA的疼痛强度，并推广到髋关节OA。总之，我们的研究结果表明，在保留全局拓扑特性的同时，OA中的大脑网络架构在全局和局部尺度上都进行了重组。与OA疼痛强度相关的网络连接与主要中枢中断分离，挑战OA疼痛对伤害性信号的依赖程度。骨关节炎（OA）表现为慢性疼痛、运动障碍和本体感觉改变。然而，大脑在这种疾病中的作用在很大程度上是未知的。在这里，我们使用膝盖和臀部OA图的数学性质来研究大脑网络。研究表明，在保留全局拓扑属性的同时，OA中的大脑网络架构在全局和局部尺度上都进行了重组。与OA疼痛强度相关的网络连接与发现的主要中枢中断分离：岛/M1/S1/副海马体；挑战OA疼痛对伤害性信号的依赖程度。
Osteoarthritis (OA) manifests with chronic pain, motor impairment, and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in a large sample of knee and hip OA (KOA, n = 91; HOA, n = 23) patients. We used a robust validation strategy by subdividing the KOA data into discovery and testing groups and tested the generalizability of our findings in HOA. Despite brain global topological properties being conserved in OA, we show there is a network wide pattern of reorganization that can be captured at the subject‐level by a single measure, the hub disruption index. We localized reorganization patterns and uncovered a shift in the hierarchy of network hubs in OA: primary sensory and motor regions and parahippocampal gyrus behave as hubs and insular cortex loses its central placement. At an intermediate level of network structure, frontoparietal and cingulo‐opercular modules showed preferential reorganization. We examined the association between network properties and clinical correlates: global disruption indices and isolated degree properties did not reflect clinical parameters; however, by modeling whole brain nodal degree properties, we identified a distributed set of regions that reliably predicted pain intensity in KOA and generalized to hip OA. Together, our findings reveal that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions, challenging the extent of dependence of OA pain on nociceptive signaling. Osteoarthritis (OA) manifests with chronic pain, motor impairment and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in knee and hip OA. We show that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions found:insula/M1/S1/parahippocampus; challenging the extent of dependence of OA pain on nociceptive signaling.
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影响因子：
3.7
作者：
Humphries MD;Gurney K
通讯作者：
Gurney K
骨关节炎疼痛中的脑灰质异常：横断面评估。
影响因子：
7.4
作者：
Barroso J;Vigotsky AD;Branco P;Reis AM;Schnitzer TJ;Galhardo V;Apkarian AV
通讯作者：
Apkarian AV
影响因子：
4.3
作者：
Miller RE;Tran PB;Obeidat AM;Raghu P;Ishihara S;Miller RJ;Malfait AM
通讯作者：
Malfait AM
影响因子：
--
作者：
Kulkarni, B.;Bentley, D. E.;Jones, A. K. P.
通讯作者：
Jones, A. K. P.
影响因子：
7.4
作者：
Kaplan, Chelsea M.;Schrepf, Andrew;Harris, Richard E.
通讯作者：
Harris, Richard E.