4.6 Review

Metabolomics applied to diabetes - lessons from human population studies

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.biocel.2017.10.011

关键词

Cohort studies; Large-case studies; Metabonomics; Mass spectrometry; NMR spectroscopy

资金

  1. Medical Research Council [MR/PO11705/1, MC_UP_A090_1006]
  2. Agilent Thought Leader Award
  3. BBSRC [BB/L024152/1] Funding Source: UKRI
  4. MRC [MC_UP_A090_1006, MR/P011705/1, MR/P024416/1, MC_PC_13030, MR/P01836X/1] Funding Source: UKRI
  5. Biotechnology and Biological Sciences Research Council [BB/L024152/1] Funding Source: researchfish
  6. Medical Research Council [MR/P01836X/1, MC_PC_13030, MR/P024416/1, MC_UP_A090_1006, MR/P011705/1] Funding Source: researchfish

向作者/读者索取更多资源

The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism.

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