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Neue Biomarker und Gene in der Prädiktion des Typ-2-Diabetes

New biomarkers and genes for prediction of type 2 diabetes

  • Leitthema
  • Published:
Der Diabetologe Aims and scope

Zusammenfassung

Hintergrund

Typ-2-Diabetes stellt eine multifaktorielle Erkrankung dar, die auf nichtgenetischen und genetischen Risikofaktoren beruht. Für Prädiktionsmodelle werden derzeit im Wesentlichen nichtgenetische Faktoren wie Patientenalter, Übergewicht/Adipositas oder Lebensstilfaktoren verwendet, was zu einer moderaten bis guten Vorhersage des persönlichen Diabetesrisikos führt.

Ziel der Arbeit

Es soll ein Update zu der Frage geliefert werden, inwiefern Genvarianten und Metaboliten als bislang am besten messbare Biomarker im Rahmen der neuen „omiks“-Technologien zur Verbesserung der Risikoprädiktion dienen können.

Ergebnisse

Seit 2008 hat sich aufgrund „Microarray“-basierter genomweiter Assoziationsstudien ein enormer Zuwachs an Informationen zur genetischen Architektur des Typ-2-Diabetes ergeben. Bislang erlauben diese neuen Erkenntnisse jedoch eher ein besseres Verständnis der Pathophysiologie, die zum Typ-2-Diabetes führt, während der prädiktive Wert der neuen genetischen Biomarker noch gering ist. In Metabolomikstudien werden hauptsächlich im Blut zirkulierende Metaboliten wie Aminosäuren und Lipide untersucht. Ihr prädiktiver Wert scheint höher zu sein als der von Genvarianten.

Schlussfolgerung

Weitere Studien, die die komplette Sequenzierung des menschlichen Genoms umfassen, werden in Zukunft helfen, die genetische Prädisposition für Typ-2-Diabetes besser zu erklären als bisher. Der nächste Schritt muss dann in der Integration der Daten aus omik-Studien (Genomik, Epigenomik, Transkriptomik, Proteomik, Metabolomik) bestehen, um neue pathogenetische Mechanismen zu charakterisieren und um Biomarkermuster zu identifizieren, die einen höheren prädiktiven Wert besitzen als die derzeit verfügbaren Genvarianten und Metaboliten.

Abstract

Background

Type 2 diabetes is a multifactorial disease caused by non-genetic and genetic risk factors. Current prediction models use mostly non-genetic factors, such as age, overweight, obesity and lifestyle factors, which result in a moderate or good prediction of the individual diabetes risk.

Aim

This review provides an update on the question to what extent gene variants and metabolites, which are currently the best measurable biomarkers under the new “omics” technologies, can be used to improve risk prediction.

Results

Since 2008 microarray-based genome-wide association studies have led to substantially deeper insights into the genetic architecture of type 2 diabetes. This knowledge has improved the understanding of the pathophysiology leading to type 2 diabetes, whereas the predictive value of the novel genetic biomarkers remains fairly low. Metabolomic studies analyze circulating metabolites, such as amino acids and lipids in blood. The predictive value of these metabolites seems to be higher than that of genetic variants.

Conclusion

Further large scale studies including whole-genome sequencing will help to obtain a better understanding of the genetic susceptibility for type 2 diabetes. Subsequently, data from different “omics” studies (i.e. genomics, epigenomics, transcriptomics, proteomics and metabolomics) need to be integrated to characterize novel pathogenetic mechanisms and to identify patterns of biomarkers which predict type 2 diabetes better than currently available gene variants and metabolites.

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Einhaltung ethischer Richtlinien

Interessenkonflikt. C. Herder und T. Illig geben an, dass kein Interessenkonflikt besteht. Dieser Beitrag beinhaltet keine Studien an Menschen oder Tieren.

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Authors and Affiliations

  1. Institut für Klinische Diabetologie, Deutsches Diabetes-Zentrum, Leibniz-Zentrum für Diabetesforschung an der Heinrich-Heine-Universität, Auf’m Hennekamp 65, 40225, Düsseldorf, Deutschland

    C. Herder

  2. Deutsches Zentrum für Diabetesforschung (DZD e. V.), Partner Düsseldorf, Düsseldorf, Deutschland

    C. Herder

  3. Hannover Unified Biobank, Medizinische Hochschule Hannover, Hannover, Deutschland

    T. Illig

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  1. C. Herder
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  2. T. Illig
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Correspondence to C. Herder.

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Herder, C., Illig, T. Neue Biomarker und Gene in der Prädiktion des Typ-2-Diabetes. Diabetologe 10, 566–571 (2014). https://doi.org/10.1007/s11428-014-1211-y

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  • DOI: https://doi.org/10.1007/s11428-014-1211-y

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