Biomarkers for the prediction of type 2 diabetes and cardiovascular disease.

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  • Author(s): Herder C;Herder C; Karakas M; Koenig W
  • Source:
    Clinical pharmacology and therapeutics [Clin Pharmacol Ther] 2011 Jul; Vol. 90 (1), pp. 52-66. Date of Electronic Publication: 2011 Jun 08.
  • Publication Type:
    Journal Article; Research Support, Non-U.S. Gov't; Review
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Wiley Country of Publication: United States NLM ID: 0372741 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-6535 (Electronic) Linking ISSN: 00099236 NLM ISO Abbreviation: Clin Pharmacol Ther Subsets: MEDLINE
    • Publication Information:
      Publication: 2015- : Hoboken, NJ : Wiley
      Original Publication: St. Louis : C.V. Mosby
    • Subject Terms:
      Biomarkers/*analysis ; Cardiovascular Diseases/*blood ; Diabetes Mellitus, Type 2/*blood; Blood Proteins/analysis ; Blood Proteins/genetics ; Cardiovascular Diseases/epidemiology ; Cardiovascular Diseases/genetics ; Coronary Artery Disease/epidemiology ; Coronary Artery Disease/genetics ; Diabetes Mellitus, Type 2/epidemiology ; Diabetes Mellitus, Type 2/genetics ; Gene Expression Profiling ; Genetic Markers ; Genomics ; Humans ; Metabolomics ; Predictive Value of Tests ; Proteomics ; Risk Factors
    • Abstract:
      Risk prediction for type 2 diabetes (T2D) and cardiovascular disease (CVD) remains suboptimal even after the introduction of global risk assessment by various scores. This has prompted the search for additional biomarkers. A variety of blood biomarkers representing various pathophysiological pathways of insulin resistance and atherosclerosis, as well as markers of subclinical disease and genetic markers, have been investigated. This review provides an overview of studies assessing the clinical utility of various biomarkers on the basis of hypothesis-driven selection as well as hypothesis-free approaches from novel "-omics" technologies. So far, the assessment of genotypes and of several candidate biomarkers from blood has resulted in only small improvements in the accuracy of prediction of CVD and T2D over and above that predicted on the basis of established risk factors. Integrated approaches, combining biomarkers from genomics, transcriptomics, proteomics, and metabolomics, as well as serial measurements of biomarkers, are required to make a complete assessment of the potential clinical usefulness of biomarkers for risk prediction of cardiometabolic disease.
    • Accession Number:
      0 (Biomarkers)
      0 (Blood Proteins)
      0 (Genetic Markers)
    • Publication Date:
      Date Created: 20110610 Date Completed: 20110823 Latest Revision: 20151119
    • Publication Date:
      20221213
    • Accession Number:
      10.1038/clpt.2011.93
    • Accession Number:
      21654741