Precision diabetes: learning from monogenic diabetes
dc.contributor.author | Hattersley, AT | |
dc.contributor.author | Patel, KA | |
dc.date.accessioned | 2017-06-09T07:28:01Z | |
dc.date.issued | 2017-03-17 | |
dc.description.abstract | The precision medicine approach of tailoring treatment to the individual characteristics of each patient or subgroup has been a great success in monogenic diabetes subtypes, MODY and neonatal diabetes. This review examines what has led to the success of a precision medicine approach in monogenic diabetes (precision diabetes) and outlines possible implications for type 2 diabetes. For monogenic diabetes, the molecular genetics can define discrete aetiological subtypes that have profound implications on diabetes treatment and can predict future development of associated clinical features, allowing early preventative or supportive treatment. In contrast, type 2 diabetes has overlapping polygenic susceptibility and underlying aetiologies, making it difficult to define discrete clinical subtypes with a dramatic implication for treatment. The implementation of precision medicine in neonatal diabetes was simple and rapid as it was based on single clinical criteria (diagnosed <6 months of age). In contrast, in MODY it was more complex and slow because of the lack of single criteria to identify patients, but it was greatly assisted by the development of a diagnostic probability calculator and associated smartphone app. Experience in monogenic diabetes suggests that successful adoption of a precision diabetes approach in type 2 diabetes will require simple, quick, easily accessible stratification that is based on a combination of routine clinical data, rather than relying on newer technologies. Analysing existing clinical data from routine clinical practice and trials may provide early success for precision medicine in type 2 diabetes. | en_GB |
dc.description.sponsorship | This work is supported by the MASTERMIND Consortium sponsored by the Medical Research Council (MRC; MR-K005707-1) and by a Wellcome Trust Senior Investigator award given to ATH (and S. Ellard, University of Exeter Medical School, Exeter, UK [WT098395/Z/12/Z]). The work is also supported by the National Institute for Health Research (NIHR) Clinical Research Facility. | en_GB |
dc.identifier.citation | Vol. 60 (5), pp. 769 - 777 | en_GB |
dc.identifier.doi | 10.1007/s00125-017-4226-2 | |
dc.identifier.uri | http://hdl.handle.net/10871/27897 | |
dc.language.iso | en | en_GB |
dc.publisher | Springer Verlag | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/28314945 | en_GB |
dc.rights | © The Author(s) 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | en_GB |
dc.subject | GCK | en_GB |
dc.subject | HNF1A | en_GB |
dc.subject | HNF4A | en_GB |
dc.subject | KCNJ11 | en_GB |
dc.subject | MODY | en_GB |
dc.subject | Maturity onset diabetes of the young | en_GB |
dc.subject | Monogenic diabetes | en_GB |
dc.subject | Neonatal diabetes | en_GB |
dc.subject | Precision diabetes | en_GB |
dc.subject | Precision medicine | en_GB |
dc.subject | Review | en_GB |
dc.subject | Type 2 diabetes | en_GB |
dc.title | Precision diabetes: learning from monogenic diabetes | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2017-06-09T07:28:01Z | |
exeter.place-of-publication | Germany | en_GB |
dc.description | This is the final version of the article. Available from Springer Verlag via the DOI in this record. | en_GB |
dc.identifier.journal | Diabetologia | en_GB |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ |
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Except where otherwise noted, this item's licence is described as © The Author(s) 2017. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.