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作为基因和连接组的函数,对阿尔茨海默病tau蛋白病的选择性易损性和恢复力。

Selective vulnerability and resilience to Alzheimer's disease tauopathy as a function of genes and the connectome.

作者信息

Anand Chaitali, Abdelnour Farras, Sipes Benjamin, Ma Daren, Maia Pedro D, Torok Justin, Raj Ashish

机构信息

Institute for Neurodegenerative Diseases, University of California, San Francisco, CA 94158, USA.

Brain Networks Laboratory, Department of Radiology, University of California, San Francisco, CA 94122, USA.

出版信息

Brain. 2025 Jul 9. doi: 10.1093/brain/awaf179.

DOI:10.1093/brain/awaf179
PMID:40631882
Abstract

Brain regions in Alzheimer's disease exhibit distinct vulnerability to its hallmark pathology with the entorhinal cortex and hippocampus succumbing early to tau tangles while others like the primary sensory cortices remain resilient. The quest to understand how local/regional genetic factors, pathogenesis and network-mediated pathology spread, together govern this selective vulnerability (SV) or resilience (SR) is ongoing. Although many Alzheimer's risk genes are known from gene association and transgenic studies, it is still unclear whether and how their baseline expression confers SV/SR to pathology. Prior analyses have yielded conflicting results, pointing to a disconnect between the location of genetic risk factors and downstream tau pathology. The spatial distribution of vulnerability doesn't always align with genetic factors, suggesting a role for non-cell-autonomous mechanisms like transneuronal tau transmission. We hypothesize that a full accounting of the role of genes in mediating SV/SR would require modelling of network-based vulnerability, whereby tau misfolds, aggregates and propagates along fibre projections. We employed an extended network diffusion model (eNDM) and fitted it on tau PET data from 196 patients from the Alzheimer's Disease Neuroimaging Initiative. The fitted eNDM then becomes a reference from which to assess the role of innate genetic factors. Using the residual (observed - model-predicted) tau as a novel target outcome, we obtained its association with 100 Alzheimer's risk genes, whose baseline spatial transcriptional profiles were obtained from the Allen Human Brain Atlas. Our eNDM was successful in capturing tau pathology distribution in patients. After regressing out the model, we found that while many risk genes have spatial expression patterns that correlate with regional tau, many others showed a stronger association with residual tau. This suggests that direct vulnerability aligned with the network, as well as network-independent vulnerability, are conferred by risk genes. We report four classes of risk genes: network-aligned SV (SV-NA), network-independent SV (SV-NI), network-aligned SR (SR-NA) and network-independent SR (SR-NI), each with a distinct spatial signature and associated vulnerability to tau. Remarkably, using gene ontology analysis, we found that the identified gene classes have distinct and sometimes surprising functional enrichment patterns. Network-aligned genes broadly participate in cell death, stress response and metabolic processing; network-independent genes in amyloid-β processing and immune response. These previously unreported segregated roles point to multiple distinct pathways by which risk genes confer vulnerability or resilience in Alzheimer's disease. Our findings offer new insights into vulnerability signatures in Alzheimer's disease and may prove helpful in identifying potential intervention targets.

摘要

阿尔茨海默病中的脑区对其标志性病理表现出不同的易损性,内嗅皮质和海马体较早出现tau缠结,而其他区域如初级感觉皮质则保持相对抗性。目前正在探索局部/区域遗传因素、发病机制和网络介导的病理传播如何共同决定这种选择性易损性(SV)或抗性(SR)。尽管通过基因关联和转基因研究已经发现了许多阿尔茨海默病风险基因,但仍不清楚它们的基线表达是否以及如何赋予对病理的SV/SR。先前的分析得出了相互矛盾的结果,表明遗传风险因素的位置与下游tau病理之间存在脱节。易损性的空间分布并不总是与遗传因素一致,这表明跨神经元tau传播等非细胞自主机制发挥了作用。我们假设,要全面了解基因在介导SV/SR中的作用,需要建立基于网络的易损性模型,即tau错误折叠、聚集并沿纤维投射传播。我们采用了扩展网络扩散模型(eNDM),并将其应用于来自阿尔茨海默病神经影像倡议组织的196名患者的tau PET数据。拟合后的eNDM随后成为评估先天遗传因素作用的参考。以残差(观察值 - 模型预测值)tau作为新的目标结果,我们获得了它与100个阿尔茨海默病风险基因的关联,这些基因的基线空间转录谱来自艾伦人类大脑图谱。我们的eNDM成功地捕捉了患者体内tau病理分布。在去除模型影响后,我们发现虽然许多风险基因具有与区域tau相关的空间表达模式,但其他许多基因与残差tau的关联更强。这表明风险基因赋予了与网络相关的直接易损性以及与网络无关的易损性。我们报告了四类风险基因:网络相关的SV(SV-NA)、网络无关的SV(SV-NI)、网络相关的SR(SR-NA)和网络无关的SR(SR-NI),每一类都有独特的空间特征和对tau的相关易损性。值得注意的是,通过基因本体分析,我们发现所确定的基因类别具有不同的、有时令人惊讶的功能富集模式。网络相关基因广泛参与细胞死亡、应激反应和代谢过程;网络无关基因参与淀粉样β蛋白处理和免疫反应。这些先前未报道的不同作用表明,风险基因通过多种不同途径赋予阿尔茨海默病易损性或抗性。我们的研究结果为阿尔茨海默病的易损性特征提供了新的见解,可能有助于识别潜在的干预靶点。

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