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Principal Investigator  
Principal Investigator's Name: Joan Maria Arenas Gomez
Institution: Neurobiology Research Unit
Department: Data Analysis
Country:
Proposed Analysis: Dear all, My name is Joan M. Arenas Gomez and I am currently employed as a research assistant at the Neurobiology Research Unit (NRU) at Copenhagen University Hospital Rigshospitalet in Denmark (https://www.nru.dk/). I am currently involved in a project investigating BrainAGE, and we believe your data can be of great usefulness for us. Below the reasoning why: Neurodegenerative disorders (e.g., Parkinson’s Disorder and Alzheimer Dementia) are common and debilitating conditions in the aged individual. Research attempting to identify the mechanisms underlying these disorders have mainly focused on pathologies observable after diagnosis, e.g., the accumulation of amyloid plaques in Alzheimer’s disorder. Despite large resources being invested, no disease modifying treatments exists for this group of brain disorders, underlining the need for a shift in research focus. Biological aging in humans can be defined as the gradual loss of function, both on a cellular and on an organismal level, and is the single largest risk factor for most major chronic diseases, including cardiovascular conditions, cancer, and neurodegenerative disorders. The field of geoscience have identified a set of “hallmarks of aging”, biological processes which are considered fundamental mechanisms underlying aging. Several of these hallmarks have been connected to neurodegenerative disorders, such as an accumulation of senescent cells and mitochondrial dysfunction. An increased understanding of the normal aging of the human brain could be a fruitful way to unlock the pathophysiological mechanisms behind neurodegenerative disorders. Moreover, interventions slowing the overall rate of biological aging in humans could have a broad effect on many pathologies, including neurodegenerative disorders. Despite several drug candidates with proven geroprotective effects in model organisms, there are currently no ongoing clinical trials in humans using lifespan extension, or a proxy thereof, as an endpoint. Clinical trials spanning decades, testing interventions in healthy individuals, are practically and ethically impossible. Instead, an efficient biomarker for aging that can function as a surrogate endpoint for life or health-span extension is needed. PET is an ideal technique for discovering biomarkers, and could be employed in the search for an aging biomarker, which has the potential of making in-human trials of longevity enhancing therapies feasible. Optimally, new radioligands, with the aim of imaging key processes in the “hallmarks of aging”, should be developed. However, before doing so, it is of high interest to characterize how the aging process in healthy individual affects the binding pattern of already existing radioligands. Such an investigation could help guide, or even substitute, development of new radioligands targeting key aging processes. Several PET studies show a strong inverse correlation between neuronal proteins and chronological age, including the serotonin 2A receptor (Frokjaer et al., 2008), for example. There is however a lack of studies attempting to maximize the prediction of age using 1) advanced modeling of PET data, and 2) the combination of PET data and data from other sources, such as morphological information from T1 weighted MR images. Further, there has, to our knowledge, been no attempts made to examine whether radioligand binding is predictive of later onset of age-related health outcomes, such as neurodegenerative disorders. If such a link can be established, it would be a crucial step in the assessment of how suitable such a radioligand is as a marker for biological age. The main objective of our work is to assess existing radioligands as biomarkers for chronological and biological age. In this way, we want to also evaluate the suitability of alternative regions of interest to maximize the prediction of chronological age from PET data. We will also perform a voxel-based analysis to identify tissues within the brain that best predicts age. We are currently identifying and implementing software developed for age prediction from structural MRIs, we will run this on the T1 images of subjects to receive an age estimate. This estimate will be incorporated in the model. Later, we aim to validate the prediction of chronological age through utilizing scans on subjects diagnosed with Alzheimer’s or mild cognitive impairment. A valid prediction model should classify these individuals as “older” compared with healthy controls of the same age. In an initial analysis we are utilizing the 5-HT2A binding radioligands [18F]Altanserin and [11C]Cimbi-36, for which we have our own data at NRU. However, it is becoming interesting to start working as well with other types of data, such as yours. The final model for each radioligand will be applied to the test data set. We will test whether the combined PET and MR model outperforms the prediction from only the structural MRI. For all the aforementioned reasons, we hope to receive an approval and be able to use your dataset, for which we would be very grateful. We look forward to hearing from you. Best regards, Joan
Additional Investigators  
Investigator's Name: Pontus Plavén-Sigray
Proposed Analysis: Same as stated before for the principal investigator.
Investigator's Name: Jonas Svensson
Proposed Analysis: Same as stated before for the principal investigator.
Investigator's Name: Ruben Dörfel
Proposed Analysis: Same as stated before for the principal investigator.