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Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population

Type 2 diabetes (T2D) has a heterogeneous etiology influencing its progression, treatment, and complications. A data driven cluster analysis in European individuals with T2D previously identified four subtypes: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild obesity-related (M...

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Published in:Nature communications 2022-11, Vol.13 (1), p.7121-17, Article 7121
Main Authors: Zaghlool, Shaza B., Halama, Anna, Stephan, Nisha, Gudmundsdottir, Valborg, Gudnason, Vilmundur, Jennings, Lori L., Thangam, Manonanthini, Ahlqvist, Emma, Malik, Rayaz A., Albagha, Omar M. E., Abou‑Samra, Abdul Badi, Suhre, Karsten
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Language:English
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Summary:Type 2 diabetes (T2D) has a heterogeneous etiology influencing its progression, treatment, and complications. A data driven cluster analysis in European individuals with T2D previously identified four subtypes: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) diabetes. Here, the clustering approach was applied to individuals with T2D from the Qatar Biobank and validated in an independent set. Cluster-specific signatures of circulating metabolites and proteins were established, revealing subtype-specific molecular mechanisms, including activation of the complement system with features of autoimmune diabetes and reduced 1,5-anhydroglucitol in SIDD, impaired insulin signaling in SIRD, and elevated leptin and fatty acid binding protein levels in MOD. The MARD cluster was the healthiest with metabolomic and proteomic profiles most similar to the controls. We have translated the T2D subtypes to an Arab population and identified distinct molecular signatures to further our understanding of the etiology of these subtypes. Four T2D subtypes were previously identified: severe insulin deficient, severe insulin resistant, mild obesity-related, and mild age-related diabetes. Here, the authors show that these subtypes can be translated to an Arabic population and identify distinct subtype-specific metabolic and proteomic signatures.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-022-34754-z