Department of Computer Architecture and Automation, Computer Science Faculty, Complutense University of Madrid, 28040, Madrid, Spain.
Department of Neurology, San Carlos Research Institute (IdSSC), Hospital Clínico San Carlos, 28040, Madrid, Spain.
Sci Rep. 2024 Apr 30;14(1):9970. doi: 10.1038/s41598-024-60707-1.
Alzheimer's disease (AD) shows a high pathological and symptomatological heterogeneity. To study this heterogeneity, we have developed a patient stratification technique based on one of the most significant risk factors for the development of AD: genetics. We addressed this challenge by including network biology concepts, mapping genetic variants data into a brain-specific protein-protein interaction (PPI) network, and obtaining individualized PPI scores that we then used as input for a clustering technique. We then phenotyped each obtained cluster regarding genetics, sociodemographics, biomarkers, fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging, and neurocognitive assessments. We found three clusters defined mainly by genetic variants found in MAPT, APP, and APOE, considering known variants associated with AD and other neurodegenerative disease genetic architectures. Profiling of these clusters revealed minimal variation in AD symptoms and pathology, suggesting different biological mechanisms may activate the neurodegeneration and pathobiological patterns behind AD and result in similar clinical and pathological presentations, even a shared disease diagnosis. Lastly, our research highlighted MAPT, APP, and APOE as key genes where these genetic distinctions manifest, suggesting them as potential targets for personalized drug development strategies to address each AD subgroup individually.
阿尔茨海默病（AD）表现出高度的病理和症状学异质性。为了研究这种异质性，我们开发了一种基于 AD 发展的最重要风险因素之一的患者分层技术：遗传学。我们通过包含网络生物学概念、将遗传变异数据映射到大脑特异性蛋白质-蛋白质相互作用（PPI）网络中，并获得个性化的 PPI 得分，将其作为聚类技术的输入来解决这一挑战。然后，我们根据遗传学、社会人口统计学、生物标志物、氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）成像和神经认知评估对每个获得的簇进行表型分析。我们发现，根据与 AD 和其他神经退行性疾病遗传结构相关的已知变体，主要通过 MAPT、APP 和 APOE 中的遗传变异来定义三个簇。对这些簇的分析揭示了 AD 症状和病理学的最小变化，表明不同的生物学机制可能激活 AD 背后的神经退行性变和病理生物学模式，并导致相似的临床和病理表现，即使是共享的疾病诊断。最后，我们的研究强调了 MAPT、APP 和 APOE 作为这些遗传差异表现的关键基因，这表明它们可能成为针对每个 AD 亚组个体化药物开发策略的潜在靶点。
