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动态功能连接与颞叶癫痫的基因表达相关性:隐马尔可夫模型的启示。

Dynamic functional connectivity and gene expression correlates in temporal lobe epilepsy: insights from hidden markov models.

机构信息

Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, China.

出版信息

J Transl Med. 2024 Aug 14;22(1):763. doi: 10.1186/s12967-024-05580-2.

Abstract

BACKGROUD

Temporal lobe epilepsy (TLE) is associated with abnormal dynamic functional connectivity patterns, but the dynamic changes in brain activity at each time point remain unclear, as does the potential molecular mechanisms associated with the dynamic temporal characteristics of TLE.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 84 TLE patients and 35 healthy controls (HCs). The data was then used to conduct HMM analysis on rs-fMRI data from TLE patients and an HC group in order to explore the intricate temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI). Additionally, we aim to examine the gene expression profiles associated with the dynamic modular characteristics in TLE patients using the Allen Human Brain Atlas (AHBA) database.

RESULTS

Five HMM states were identified in this study. Compared with HCs, TLE and TLE-CI patients exhibited distinct changes in dynamics, including fractional occupancy, lifetimes, mean dwell time and switch rate. Furthermore, transition probability across HMM states were significantly different between TLE and TLE-CI patients (p < 0.05). The temporal reconfiguration of states in TLE and TLE-CI patients was associated with several brain networks (including the high-order default mode network (DMN), subcortical network (SCN), and cerebellum network (CN). Furthermore, a total of 1580 genes were revealed to be significantly associated with dynamic brain states of TLE, mainly enriched in neuronal signaling and synaptic function.

CONCLUSIONS

This study provides new insights into characterizing dynamic neural activity in TLE. The brain network dynamics defined by HMM analysis may deepen our understanding of the neurobiological underpinnings of TLE and TLE-CI, indicating a linkage between neural configuration and gene expression in TLE.

摘要

背景

颞叶癫痫(TLE)与异常的动态功能连接模式有关,但每个时间点的脑活动动态变化尚不清楚,与 TLE 的动态时间特征相关的潜在分子机制也不清楚。

方法

对 84 例 TLE 患者和 35 例健康对照者(HCs)进行静息态功能磁共振成像(rs-fMRI)。然后,我们使用 HMM 分析 TLE 患者和 HCs 的 rs-fMRI 数据,以探讨认知障碍性 TLE 患者(TLE-CI)脑活动的复杂时间动态。此外,我们还使用 Allen 人类大脑图谱(AHBA)数据库,检测与 TLE 患者动态模块特征相关的基因表达谱。

结果

本研究共识别出 5 种 HMM 状态。与 HCs 相比,TLE 和 TLE-CI 患者的动力学表现出明显的变化,包括分数占据、寿命、平均停留时间和转换率。此外,TLE 和 TLE-CI 患者在 HMM 状态之间的跃迁概率有显著差异(p<0.05)。TLE 和 TLE-CI 患者状态的时间重配置与几个脑网络有关(包括高级默认模式网络(DMN)、皮质下网络(SCN)和小脑网络(CN))。此外,共发现 1580 个基因与 TLE 的动态脑状态显著相关,主要富集于神经元信号和突触功能。

结论

本研究为 TLE 患者的动态神经活动特征提供了新的见解。HMM 分析定义的脑网络动力学可能加深我们对 TLE 和 TLE-CI 的神经生物学基础的理解,表明 TLE 中神经结构与基因表达之间存在联系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dfb/11323657/0d3838d8259a/12967_2024_5580_Fig1_HTML.jpg

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