Principal Investigator: Dr Peter Fedichev
Department: Research Division
Gero LLC (formerly known as Quantum Pharmaceuticals) Research Division, kosmonavta volkova 6A 1205, Moscow 125171, Russian Federation
Collaborating Lead –
Professor Vadim Gladyshev, Brigham and Womens Hospital, Boston, United StatesTags: 21988, ageing, diagnostics, physical activity, stress response
1a: 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.
1b: UK Biobank is concerned with understanding the determinants of diseases as well as identifying opportunities for prevention. We believe the proposed research addresses these aims by investigating the potential role of physical activity as a source of non-invasive exploration of a biological state. This will provide novel insights into the determinants and markers of common/age related diseases such as neuro-degeneration, adult cancers and cardiovascular diseases and identify novel preventative and diagnostics approaches.
1c: We plan to analyse the raw accelerometer data to derive certain features, such as patterns and power spectrum distribution. We aim to investigate how these features are associated with the diseases of interest. The features that will be found to be most associated with the specific diseases will be nominated for further research as potential biomarkers of corresponding diseases.
1d: Participants that already have physical activity measurements (approx. 30 000 individuals) and all physical activity data as they will be collected and included in UK Biobank database (70 000 individuals more, 100 000 in total).
03/06/2016: APPROVED PROJECT EXTENSION
The goal of our project was to identify signatures of aging and age-related disease. This is why we focused building models of age (aka biological age calculations) and predicting disease-labels, such as diabetes.
We would like to supplement our calculations with extra biological information. It came to our minds that if we were able to access genomic information for a cohort we are working with, we could undertake a GWAS study and, with some luck, find out which genes (SNPs) or, after a proper gene set enrichment analysis, biological processes could be associated with the age- and disease-related signatures in human locomotion we found.
I understand that more than 150k genotypes are now available. We believe that the access to the patients data would help us to make a lot more sense of our findings, strengthen our arguments, and provide an extra appeal to the publication.
APPROVED PROJECT EXTENSION 02/06/2017:
A natural follow-up would be to find out if there are any modifiable genetics-lifestyles interactions of the mortality phenotype. Overall food intake and diet choices are known to be powerful modifiers of lifespan in animals and in humans. If successful, we could use UKBB questionnaire to classify participants according to their food consumption patterns and overlay the information with their genetic makeup.
We believe that the results of the proposed research could be used for personalized diet recommendations based on participants genetics, as well as it could possibly yield novel anti-obesity/diabetes therapeutic targets suggestions.
APPROVED PROJECT EXTENSION 04/09/2017:
To expand our research we would like to understand the influence of the chronic drug administration on all-cause mortality and whether our approach could distinguish people on different therapies. It is known from the published data that long-term administration of some drugs leads to longer survival when compared to general population. A good example is metformin http://onlinelibrary.wiley.com/doi/10.1111/dom.12354/full.
By applying our methods we would like to confirm whether the selected drugs could be associated with longer lifespan and how our approach could assess these effects. We believe that the results of the proposed research could validate the biomarkers of age and frailty we develop for clinical trial and outcome-based recommendations for the administration of the existing drugs.
Last updated Jan 15, 2020