Developing a molecular clock for evaluation of senotherapeutics

在SENISCA，我们发现了一种细胞衰老的新方式;选择性剪接的丧失，一种基因表达的微调形式。我们可以恢复这一过程，在老年（衰老）人体细胞中“逆转衰老时钟”。这为我们老龄化社会面临的许多医疗保健挑战提供了一种可能的解决方案，为常见的老年疾病提供了恢复性和潜在的预防性治疗。实现我们的技术的全部潜力需要一套强大而准确的结果措施来衡量？返老还童？我们的干预措施在体外和体内的效果。其中一个测量方法是一个多组织的“选择性剪接时钟”，它与细胞年龄有关。在这个项目中，我们将通过培养细胞来衰老，为2种不同的疾病相关细胞类型（与心血管和肺功能相关）创建多组织衰老特征。结果还将与来自血液的数据相结合，以提供来自可访问组织的组织相关时钟。将在多个时间点收集样品，用于一组完整的细胞老化测量，同时收集包含受试细胞中每个剪接事件的“RNA条形码”。这个数据集将使我们能够准确地了解细胞衰老过程中发生的基因表达变化。我们将进行各种探索性分析，包括差异表达和基因集富集，以建立细胞衰老的网络模型，从而确定具有足够能力预测生物学年龄的最小可行基因集。然后，我们将相关的表达，这一子集的基因的细胞表型数据，其次是评估其预测能力在人类队列。据我们所知，这将是全球首次将多组织转录组生物钟专门映射到人类样本的细胞衰老和实足年龄。这项工作将产生一些特定于衰老的细胞类型特异性分子钟。这些将成为SENISCA新兴疗法评估措施工具包的组成部分，但将具有其自身的内在和商业价值。目前缺乏衰老的特异性生物标志物，并且一系列组织特异性衰老特异性时钟的生产将对其他公司产生极大的兴趣，这些公司正在努力通过以下方式减轻与年龄相关的疾病：性感疗法以及希望监测其生物年龄的消费者。

At SENISCA we have discovered a new way by which cells age; loss of alternative splicing, a form of fine-tuning of gene expression. We can restore this process to 'turn back the ageing clock' in old (senescent) human cells. This presents a possible solution to many of the healthcare challenges faced by our ageing society, offering restorative, as well as potentially preventative treatments for common diseases of ageing.?Realisation of the full potential of our technology requires a set of robust and accurate outcome measures with which to measure the?rejuvenative?effect of our interventions in vitro and in vivo. One such measure will be a multi-tissue 'alternative splicing clock' specific to senescence which can be linked to cellular age.?With this project, we will create a multi-tissue senescence signature for 2 different disease relevant cell types (relevant to cardiovascular and lung function) by growing cells to senescence in culture. Results will also be integrated with data from blood to provide a tissue-relevant clock from an accessible tissue. Samples will be collected at multiple time-points for a full battery of cell ageing measurements alongside the collection of an 'RNA barcode' comprising every splicing event in the cells under test. This dataset will allow us to develop an accurate picture of the gene expression changes that occur during cellular ageing. We will perform a variety of exploratory analyses including differential expression and gene set enrichment to build a network model of cellular ageing, leading to the identification of a minimal-viable set of genes with sufficient power to predict biological age. We will then correlate expression of this subset of genes to the cellular phenotype data, followed by evaluation of their predictive power in a human cohort.?To our knowledge, this will be the first time globally that a multi-tissue transcriptomic biological clock has been mapped specifically to both cellular senescence and chronological age in human samples. This work will produce a number of cell type specific molecular clocks that are specific to senescence.These will be an integral part of SENISCA's toolkit of evaluation measures for our emerging therapeutics, but will have inherent and commercial value of their own. Specific biomarkers for senescence are currently lacking, and the production of a series of tissue specific senescence-specific clocks would be of great interest to other companies striving to attenuate age-related disease by?senotherapies?and to consumers looking to monitor their biological age.