The project of Quantum Pharmacutical company (q-pharm.com)
It has long been suggested from the animal data that human locomotion may be related to health. Recently, we identified a generic framework to model and infer critical markers of age-related diseases from biometric signals for example, see our research using genetic networks (http://arxiv.org/abs/1408.0463).
Our plan is to use the same approach to develop and test novel approaches to extract and analyse features from the physical activity data (as measured by accelerometry) and to identify associations between these physical activity features and age-related diseases including neurodegenerative, oncological and cardiovascular diseases. There are numeral suggestions in literature that transposable genetic elements may be the primary cause of aging. We plan to study the role of these structures in human aging using exome sequencing data.
Further, we plan to generate a series of dynamic health indicators (dHIs) associated with aging (biological age), resilience, and chronic disease progression by including a wider set of phenotypic data: physical measures, cognitive functions, blood assays (blood count, biochemistry, NMR metabolomics, and proteomics), or measurements from wearable devices (physical activity and cardiac monitoring).
Once the models are adopted we can utilize a unique combination of genetics and deep phenotyping data to ascribe meaning to the dHIs, and identify molecular and genetic markers as well as, and potential therapeutic targets against major diseases and aging.