Laroche Valentin T, Cavill Rachel, Kouhsar Morteza, Müller Joshua, Reijnders Rick A, Harvey Joshua, Smith Adam R, Imm Jennifer, Koetsier Jarno, Weymouth Luke, MacBean Lachlan, Pegoraro Giulia, Eijssen Lars, Creese Byron, Kenis Gunter, Tijms Betty M, van den Hove Daniel, Lunnon Katie, Pishva Ehsan
Maastricht University.
University of Exeter, Royal Devon & Exeter Hospital.
Res Sq. 2025 Aug 4:rs.3.rs-7232080. doi: 10.21203/rs.3.rs-7232080/v1.
Growing evidence suggests that clinical, pathological, and genetic heterogeneity in late onset Alzheimer's disease (LOAD) contributes to variable therapeutic outcomes, potentially explaining many trial failures. Advances in molecular subtyping through proteomic and transcriptomic profiling reveal distinct patient subgroups, highlighting disease complexity beyond amyloid-beta plaques and tau tangles. This underscores the need to expand subtyping across new molecular layers, to identify novel drug targets for different patient subgroups. In this study, we analyzed genome-wide DNA methylation (DNAm) data from three independent postmortem brain cohorts (N = 831) to identify epigenetic subtypes of LOAD. Unsupervised clustering approaches were employed to identify distinct DNAm patterns, with subsequent cross-cohort validation. We assessed how subtype-specific methylation signatures map onto individual brain cell types by comparing them with DNAm profiles from purified cells. Next, we integrated bulk and single-cell RNA-seq data to determine each subtype's functional impact on gene expression. Finally, we explored clinical and neuropathological correlates of the identified subtypes to elucidate biological and clinical significance. We identified two distinct epigenomic subtypes of LOAD, consistently observed across three cohorts. Both subtypes exhibit significant yet distinct microglial methylation enrichment. Bulk transcriptomic analyses further highlighted distinct biological mechanisms underlying these subtypes: subtype 1 was enriched for immune-related processes, while subtype 2 was characterized by neuronal and synaptic pathways. Single-cell transcriptional profiling of microglia revealed subtype-specific inflammatory states: subtype 1 displayed chronic innate immune hyperactivation with impaired resolution, whereas subtype 2 exhibited a more dynamic inflammatory profile, balancing pro-inflammatory signaling with reparative and regulatory mechanisms. These findings reveal distinct epigenetic and functional microglial states underlying LOAD subtypes, advancing our understanding of disease heterogeneity. This work lays the groundwork for targeted therapeutic strategies tailored to specific molecular and cellular disease profiles.
越来越多的证据表明，晚发性阿尔茨海默病（LOAD）的临床、病理和基因异质性导致了不同的治疗结果，这可能是许多试验失败的原因。通过蛋白质组学和转录组学分析进行分子亚型分类的进展揭示了不同的患者亚组，凸显了除淀粉样β斑块和tau缠结之外的疾病复杂性。这强调了需要在新的分子层面扩展亚型分类，以识别不同患者亚组的新型药物靶点。在本研究中，我们分析了来自三个独立的死后大脑队列（N = 831）的全基因组DNA甲基化（DNAm）数据，以识别LOAD的表观遗传亚型。采用无监督聚类方法识别不同的DNAm模式，并进行后续的跨队列验证。我们通过将亚型特异性甲基化特征与来自纯化细胞的DNAm谱进行比较，评估其如何映射到个体脑细胞类型上。接下来，我们整合了大量和单细胞RNA测序数据，以确定每个亚型对基因表达的功能影响。最后，我们探索了所识别亚型的临床和神经病理学相关性，以阐明其生物学和临床意义。我们识别出了LOAD的两种不同的表观基因组亚型，在三个队列中均一致观察到。两种亚型均表现出显著但不同的小胶质细胞甲基化富集。大量转录组分析进一步突出了这些亚型背后不同的生物学机制：亚型1富含免疫相关过程，而亚型2以神经元和突触途径为特征。小胶质细胞的单细胞转录分析揭示了亚型特异性炎症状态：亚型1表现出慢性先天性免疫过度激活且消退受损，而亚型2表现出更动态的炎症特征，在促炎信号与修复和调节机制之间取得平衡。这些发现揭示了LOAD亚型背后不同的表观遗传和功能性小胶质细胞状态，加深了我们对疾病异质性的理解。这项工作为针对特定分子和细胞疾病特征的靶向治疗策略奠定了基础。
