Biomarkers seem to be a major focus currently for the healthcare industry – with old ones continually being evaluated, and new ones being sought. There are two major types of biomarkers: biomarkers of exposure, for use in risk prediction, and biomarkers of disease, which are used in screening, diagnosis and monitoring of disease progression. We have recently published a paper jointly with King’s College London, that describes the discovery of two new potential protein biomarkers for Alzheimer’s disease (PLAUR and ChAt) using a combination of in silico prediction and in vitro validation.
For the in silico prediction, we used a powerful combination of life science vocabularies and our in-house data integration and data harmonisation technologies to pull together assertions linking Alzheimer’s disease pathologies, related proteins and anatomical structures. We could then analyse all the disease-related assertions in the intelligence network against findings for normal tissues, to pull out key proteins that could then be validated against a panel of samples from the European AddNeuroMed cohort.
This approach could be used for any disease state, toxicity or pathology – and shows the value of integrated harmonised access to legacy data – and of course, the benefits gained from good commercial-academic collaboration for the healthcare industry.