Year: 2017
Type: article
Abstract: 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.
Source: Diabetologia
Author: Mark I. McCarthy
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
Awards: Characterising causal alleles for common disease., G3529949959, G4426574518, A systems based approach to integrating genetic and longitudinal omics data to support diagnosis and prediction of common chronic disease, Integrating genome-scale data to reveal causal mechanisms in type 2 diabetes, NIHR Senior Investigator Award, Defining the molecular and physiological mechanisms of pancreatic islet dysfunction which lead to type 2 diabetes, Understanding the genetic basis of common human diseases: core funding for the Wellcome Trust Centre for Human Genetics., G7328074751, A systematic approach to understanding the biology underpinning GWAS hits., A systematic approach to understanding the biology underpinning GWAS hits.
OpenAlex ID: W2586927659