The DEXLIFE study methods: identifying novel candidate biomarkers that predict progression to type 2 diabetes in high risk individualsShow others and affiliations
2014 (English)In: Diabetes Research and Clinical Practice, ISSN 0168-8227, E-ISSN 1872-8227, Vol. 106, no 2, p. 383-389, article id S0168-8227(14)00319-2Article in journal (Refereed) Published
Abstract [en]
The incidence of type 2 diabetes (T2D) is rapidly increasing worldwide and T2D is likely to affect 592 million people in 2035 if the current rate of progression is continued. Today, patients are diagnosed with T2D based on elevated blood glucose, either directly or indirectly (HbA1c). However, the information on disease progression is limited. Therefore, there is a need to identify novel early markers of glucose intolerance that reflect the underlying biology and the overall physiological, metabolic and clinical characteristics of progression towards diabetes. In the DEXLIFE study, several clinical cohorts provide the basis for a series of clinical, physiological and mechanistic investigations in combination with a range of--omic technologies to construct a detailed metabolic profile of high-risk individuals across multiple cohorts. In addition, an exercise and dietary intervention study is conducted, that will assess the impact on both plasma biomarkers and specific functional tissue-based markers. The DEXLIFE study will provide novel diagnostic and predictive biomarkers which may not only effectively detect the progression towards diabetes in high risk individuals but also predict responsiveness to lifestyle interventions known to be effective in the prevention of diabetes.
Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 106, no 2, p. 383-389, article id S0168-8227(14)00319-2
Keywords [en]
Biomarkers, Lifestyle intervention, Prevention, Type 2 diabetes
National Category
Endocrinology and Diabetes
Identifiers
URN: urn:nbn:se:oru:diva-63697DOI: 10.1016/j.diabres.2014.07.025ISI: 000346060500039PubMedID: 25125339Scopus ID: 2-s2.0-84920662680OAI: oai:DiVA.org:oru-63697DiVA, id: diva2:1169262
Funder
EU, FP7, Seventh Framework Programme, 2792282017-12-222017-12-222018-08-29Bibliographically approved