Title |
Lifestyle and precision diabetes medicine: will genomics help optimise the prediction, prevention and treatment of type 2 diabetes through lifestyle therapy?
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Published in |
Diabetologia, January 2017
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DOI | 10.1007/s00125-017-4207-5 |
Pubmed ID | |
Authors |
Paul W Franks, Alaitz Poveda |
Abstract |
Precision diabetes medicine, the optimisation of therapy using patient-level biomarker data, has stimulated enormous interest throughout society as it provides hope of more effective, less costly and safer ways of preventing, treating, and perhaps even curing the disease. While precision diabetes medicine is often framed in the context of pharmacotherapy, using biomarkers to personalise lifestyle recommendations, intended to lower type 2 diabetes risk or to slow progression, is also conceivable. There are at least four ways in which this might work: (1) by helping to predict a person's susceptibility to adverse lifestyle exposures; (2) by facilitating the stratification of type 2 diabetes into subclasses, some of which may be prevented or treated optimally with specific lifestyle interventions; (3) by aiding the discovery of prognostic biomarkers that help guide timing and intensity of lifestyle interventions; (4) by predicting treatment response. In this review we overview the rationale for precision diabetes medicine, specifically as it relates to lifestyle; we also scrutinise existing evidence, discuss the barriers germane to research in this field and consider how this work is likely to proceed. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 18% |
Spain | 8 | 14% |
United Kingdom | 7 | 13% |
Denmark | 4 | 7% |
Sweden | 3 | 5% |
India | 2 | 4% |
France | 2 | 4% |
Brazil | 2 | 4% |
Montenegro | 1 | 2% |
Other | 7 | 13% |
Unknown | 10 | 18% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 30 | 54% |
Scientists | 19 | 34% |
Practitioners (doctors, other healthcare professionals) | 7 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | <1% |
Switzerland | 1 | <1% |
Unknown | 103 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 18 | 17% |
Researcher | 16 | 15% |
Student > Bachelor | 11 | 10% |
Student > Master | 10 | 10% |
Other | 7 | 7% |
Other | 16 | 15% |
Unknown | 27 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 21 | 20% |
Nursing and Health Professions | 11 | 10% |
Biochemistry, Genetics and Molecular Biology | 10 | 10% |
Agricultural and Biological Sciences | 7 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 5 | 5% |
Other | 14 | 13% |
Unknown | 37 | 35% |