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Abstract：
The human brain is complex and interconnected structurally. Brain connectome change is associated with Alzheimer\'s disease (AD) and other neurodegenerative diseases. Genetics and genomics studies have identified molecular changes in AD; however, the results are often limited to isolated brain regions and are difficult to interpret its findings in respect to brain connectome. The mechanisms of how one brain region impacts the molecular pathways in other regions have not been systematically studied. And how the brain regions susceptible to AD pathology interact with each other at the transcriptome level and how these interactions relate to brain connectome change are unclear.
Here, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer\'s Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions.
We observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort. The result suggests that disease associated white matter changes are focal. Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.03). And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.08 × 10-9). Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level. Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (Ppermutation = 1.0 × 10-2 and 4.9 × 10-4 for left and right respectively).
In summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.
Here, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer\'s Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions.
We observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort. The result suggests that disease associated white matter changes are focal. Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.03). And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.08 × 10-9). Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level. Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (Ppermutation = 1.0 × 10-2 and 4.9 × 10-4 for left and right respectively).
In summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.
摘要：
人脑是复杂的，在结构上是相互联系的。脑连接体改变与阿尔茨海默病(AD)和其他神经退行性疾病有关。遗传学和基因组学研究已经确定了AD的分子变化；然而，结果通常仅限于孤立的大脑区域，并且很难解释其关于大脑连接体的发现。尚未系统地研究一个大脑区域如何影响其他区域的分子途径的机制。而且，对AD病理敏感的大脑区域如何在转录组水平上相互作用，以及这些相互作用如何与大脑连接体变化相关，目前尚不清楚。
这里,我们使用阿尔茨海默病神经影像学计划数据库中的弥散磁共振成像数据和覆盖17个脑区的脑转录组数据集,比较了由概率束定义的结构性脑连接组.
我们观察到，与AD诊断状态相关的扩散测量的变化和关联在一个独立的队列中重复。结果表明，疾病相关的白质变化是局灶性的。通过基因组数据分析大脑连接体，17个脑区之间的组织-组织转录同步，表明由AD相关束连接的区域可能在转录组水平上与大量的组织到组织相关（TTC）基因对（P=0.03）连接。白质束连接脑区之间的TTC基因对涉及的基因在信号通路中富集(P=6.08×10-9)。进一步的通路相互作用分析确定了离子型谷氨酸受体通路和Toll受体信号通路对于转录组水平的组织-组织同步是重要的。导致血液中Toll受体信号传导的转录谱与白质束的扩散特性显着相关，各向异性分数与双侧扣带角束之间的显着关联（左右分别为Ppermutation=1.0×10-2和4.9×10-4）。
总之，我们的研究表明,MRI定义的脑连接体和转录组数据相互重叠.
这里,我们使用阿尔茨海默病神经影像学计划数据库中的弥散磁共振成像数据和覆盖17个脑区的脑转录组数据集,比较了由概率束定义的结构性脑连接组.
我们观察到，与AD诊断状态相关的扩散测量的变化和关联在一个独立的队列中重复。结果表明，疾病相关的白质变化是局灶性的。通过基因组数据分析大脑连接体，17个脑区之间的组织-组织转录同步，表明由AD相关束连接的区域可能在转录组水平上与大量的组织到组织相关（TTC）基因对（P=0.03）连接。白质束连接脑区之间的TTC基因对涉及的基因在信号通路中富集(P=6.08×10-9)。进一步的通路相互作用分析确定了离子型谷氨酸受体通路和Toll受体信号通路对于转录组水平的组织-组织同步是重要的。导致血液中Toll受体信号传导的转录谱与白质束的扩散特性显着相关，各向异性分数与双侧扣带角束之间的显着关联（左右分别为Ppermutation=1.0×10-2和4.9×10-4）。
总之，我们的研究表明,MRI定义的脑连接体和转录组数据相互重叠.
