Hemandhar-Kumar Nisha, Kluever Verena, Kaufmann Svenja V, Bergmann Cornelius, Mousaei Kanaan, Tomas Miguel, Marrero Miguel Correa, Chopra Avika, Hirose Misa, Pallas Mercè, Sanfeliu Coral, Ibrahim Saleh M, Fischer Andre, Outeiro Tiago F, Urlaub Henning, Tchumatchenko Tatjana, Otín Carlos López, Fornasiero Eugenio F
bioRxiv. 2025 Aug 19:2025.08.14.669896. doi: 10.1101/2025.08.14.669896.
Brain aging is a major risk for neurodegeneration, yet the underlying molecular mechanisms remain poorly understood. Here we performed an integrative proteo-transcriptomic analysis of the aging mouse brain, uncovering molecular signatures of aging through the assessment of protein aggregation, mRNA relocalization, and comparative proteomics across eight models of premature aging and neurodegeneration. We identified dynamic changes in physiological aging highlighting differences in synaptic maintenance and energy-allocation. These were linked to changes associated with fundamental protein biochemical properties such as size and net charge. Network analysis highlighted a decrease in mitochondrial complex I proteins not compensated at the mRNA level. Aggregation of 60S ribosome subunits indicated deteriorating translation efficiency and was accompanied by mitochondrial and proteasomal imbalance. The analysis of the nine models revealed key similarities and differences between physiological aging and pathology. Overall, our study provides an extensive resource on molecular aging, and offers insights into mechanisms predisposing to neurodegeneration, easily accessible at our Brain Aging and Molecular Atlas Project (BrainAging-MAP) website.
脑衰老 是神经退行性变的主要风险因素，但其潜在的分子机制仍知之甚少。在此，我们对衰老小鼠大脑进行了蛋白质组学与转录组学的整合分析，通过评估蛋白质聚集、mRNA重新定位以及对八种早衰和神经退行性变模型进行比较蛋白质组学分析，揭示了衰老的分子特征。我们确定了生理衰老过程中的动态变化，突出了突触维持和能量分配方面的差异。这些变化与蛋白质基本生化特性（如大小和净电荷）相关的变化有关。网络分析突出显示线粒体复合体I蛋白减少，且在mRNA水平未得到补偿。60S核糖体亚基的聚集表明翻译效率下降，并伴有线粒体和蛋白酶体失衡。对这九个模型的分析揭示了生理衰老与病理之间的关键异同。总体而言，我们的研究提供了关于分子衰老的丰富资源，并深入探讨了易患神经退行性变的机制，可在我们的脑衰老与分子图谱项目（BrainAging-MAP）网站上轻松获取。
