Painting a new picture of personalised medicine for diabetes.
The current focus on delivery of personalised (or precision) medicine reflects the expectation that developments in genomics, imaging and other domains will extend our diagnostic and prognostic capabilities, and enable more effective targeting of current and future preventative and therapeutic options. The clinical benefits of this approach are already being realised in rare diseases and cancer but the impact on management of complex diseases, such as type 2 diabetes, remains limited. This may reflect reliance on inappropriate models of disease architecture, based around rare, high-impact genetic and environmental exposures that are poorly suited to our emerging understanding of type 2 diabetes. This review proposes an alternative 'palette' model, centred on a molecular taxonomy that focuses on positioning an individual with respect to the major pathophysiological processes that contribute to diabetes risk and progression. This model anticipates that many individuals with diabetes will have multiple parallel defects that affect several of these processes. One corollary of this model is that research efforts should, at least initially, be targeted towards identifying and characterising individuals whose adverse metabolic trajectory is dominated by perturbation in a restricted set of processes.
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford, OX3 7LJ, UK. mark.mccarthy@drl.ox.ac.uk.|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. mark.mccarthy@drl.ox.ac.uk.|Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK. mark.mccarthy@drl.ox.ac.uk.
Mark I
MI
McCarthy
D015415:Biomarkers / Q000097:blood / Q000378:metabolism; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics / Q000378:metabolism* / Q000473:pathology; D023281:Genomics / Q000379:methods; D006801:Humans; D057285:Precision Medicine / Q000379:methods*
D015415:Biomarkers
Biomarkers; Complex disease; Diabetes; Environment; Genetics; Pathogenesis; Review; Risk; Taxonomy