Periodic Reporting for period 1 - iNtoPoreAge (Assessing transcriptional and nuclear pore aging in age-equivalent and rejuvenated induced neurons from Alzheimer patients )
Okres sprawozdawczy: 2019-08-01 do 2021-07-31
Recently, we used iNs to model sporadic age-dependent AD. These AD patient-derived iNs exhibit strong neuronal transcriptome signatures characterized by down-regulation of mature neuronal properties and up-regulation of immature and progenitor-like signaling pathways. Mapping iNs to longitudinal neuronal differentiation trajectory data demonstrated that AD iNs reflect a hypo-mature neuronal identity characterized by markers of stress, cell cycle, and de-differentiation. Epigenetic landscape profiling revealed an underlying aberrant neuronal state that shares similarities with malignant transformation and age-dependent epigenetic erosion. To probe for the involvement of aging, we generated rejuvenated iPSC-derived neurons that showed no significant disease-related transcriptome signatures, a feature that is consistent with epigenetic clock and brain ontogenesis mapping, which indicate that fibroblast-derived iNs more closely reflect old adult brain stages. These data, which mark a major step in the entire field, were published in 2021 in Cell Stem Cell, as we identify AD-related neuronal changes as age-dependent cellular programs that impair neuronal identity. Similar to the earlier study on aging iNs, also this study attracted major expert and public attention, including major leaders in the European research landscape and neurodegeneration field and led to several conference invitations.
In this project, we published articles in Disease Models and Mechanisms and FEBS letters in which we review and discuss human cell reprogramming models and strategy to advance our understanding of age -related neurological disorders, and we focus on some of the known and new concept and research directions of the interface between metabolism and cell identity, and new disease-related concepts that were suggested by the emerging data of our most recent studies. We published a new method to generate electrophilically functional neurons from murine neural precursor cells in the journal Cells. In the project, we identified a metabolic switch to aerobic glycolysis in AD iNs. Pathological isoform switching of the glycolytic enzyme pyruvate kinase M (PKM) toward the cancer-associated PKM2 isoform conferred metabolic and transcriptional changes in AD iNs. These alterations occurred via PKM2's lack of metabolic activity and via nuclear translocation and associatio
We found that AD brains have significantly higher proportions of neurons that express senescence markers, and their distribution indicates bystander effects. AD patient-derived directly induced neurons (iNs) exhibit strong transcriptomic, epigenetic, and molecular biomarker signatures, indicating a specific human neuronal senescence-like state. AD iN single-cell transcriptomics revealed that senescent-like neurons face oncogenic challenges and metabolic dysfunction as well as display a pro-inflammatory signature. Integrative profiling of the inflammatory secretome of AD iNs and patient cerebral spinal fluid revealed a neuronal senescence-associated secretory phenotype that could trigger astrogliosis in human astrocytes. Finally, we show that targeting senescence-like neurons with senotherapeutics could be a strategy for preventing or treating AD.
The socio-economic impact and wider societal implications of this project are significant. The research addresses the growing global challenge of an aging population and the increasing prevalence of neurodegenerative diseases, such as AD, which is a tremendous source of human suffering. The economic value of targeting aging has been highlighted, with a slowdown in aging that increases life expectancy by 1 year being worth trillions of Euros. The project's focus on understanding the biological mechanisms of aging and neurodegenerative diseases has the potential to lead to the development of novel therapeutic interventions and preventive strategies, which could have substantial economic and societal benefits. Additionally, the project's emphasis on big data quantitative biology and multi-omic approaches contributes to the advancement of scientific knowledge and technological innovation, with potential implications for precision medicine and personalized healthcare. Furthermore, the research may lead to a better understanding of healthy aging and the promotion of healthy lifestyles, ultimately contributing to improved quality of life for aging populations.