Establishing individual metabolic health from clinical biochemistry, metabolomics and genome data for precision health
Approved Research ID: 71521
Approval date: September 21st 2021
The health impact of aging demographics within the EU and the UK leads to a dramatic increase in chronic diseases in the last decade. This is only accelerated by the current pandemic, leading to an increased burden on those of healthy and working-age to provide for the health and social care expenditures for a range of related services for the entire population. This catalyzes an important change, potentially a transition towards stratified prevention and digital care in the healthcare market.
The understanding of human health and disease is evolving from a symptom-based definition of independent diseases perspective towards defining personal health via quantifiable biomarkers and definition of development of (chronic) diseases on a continuum. The availability of medical health technologies, coupled with personal genomes has the potential to support Data-Driven Physicians in healthcare practice making timely and tailored decisions. In this project we aim to use data from UK Biobank as a reference dataset to complement our in-house I Am Frontier cohort data, for developing algorithms and methodologies that can recognize individuals before the onset of symptoms in chronic diseases, identify key risk factors and offer customized therapy options that are best matching their personal situation. The results of our study (after study completion in 36 months) will benefit clinicians in assisting them in their decision-making as well as citizens in understanding stratified risks and managing their health. It will also empower public health officials to review, stratified preventive health measures to be included within the coverage of national healthcare systems