4.7 Article

A Global Overview of Precision Medicine in Type 2 Diabetes

期刊

DIABETES
卷 67, 期 10, 页码 1911-1922

出版社

AMER DIABETES ASSOC
DOI: 10.2337/dbi17-0045

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资金

  1. European Commission [CoG-2015_681742_NASCENT]
  2. Swedish Research Council (Distinguished Young Researchers Award in Medicine)
  3. Swedish Heart-Lung Foundation
  4. Novo Nordisk Foundation
  5. European Foundation for the Study of Diabetes
  6. Swedish Foundation for Strategic Research (Industrial Research Center in Precision Medicine)
  7. Boehringer Ingelheim
  8. Sanofi
  9. Servier
  10. National Institute for Health Research (NIHR)
  11. Wellcome Trust [098381, 203141, 106130]
  12. National Institutes of Health [U01-DK105535]
  13. AbbVie
  14. AstraZeneca
  15. Takeda
  16. National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases [R01 DK072041, U01 DK105554, R01 DK105154, K24 DK110550]
  17. National Institute of General Medical Sciences [R01 GM117163]
  18. Eli Lilly
  19. Janssen
  20. Novo Nordisk
  21. Merck
  22. Pfizer
  23. Roche

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The detailed characterization of human biology and behaviors is now possible at scale owing to innovations in biomarkers, bioimaging, and wearable technologies; big data from electronic medical records, health insurance databases, and other platforms becoming increasingly accessible; and rapidly evolving computational power and bioinformatics methods. Collectively, these advances are creating unprecedented opportunities to better understand diabetes and many other complex traits. Identifying hidden structures within these complex data sets and linking these structures to outcome data may yield unique insights into the risk factors and natural history of diabetes, which in turn may help optimize the prevention and management of the disease. This emerging area is broadly termed precision medicine. In this Perspective, we give an overview of the evidence and barriers to the development and implementation of precision medicine in type 2 diabetes. We also discuss recently presented paradigms through which complex data might enhance our understanding of diabetes and ultimately our ability to tackle the disease more effectively than ever before.

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