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“H” for Heterogeneity in the Algorithm for Type 2 Diabetes Management

  • Genetics (AP Morris, Section Editor)
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A Correction to this article was published on 22 May 2020

This article has been updated

Abstract

Purpose of Review

Genetic, socioeconomic and clinical features vary considerably among individuals with type 2 diabetes (T2D) influencing disease development, progression and response to therapy. Although a patient-centred approach to pharmacologic therapy of T2D is widely recommended, patients are often treated similarly, irrespective of the differences that may affect therapeutic response. Addressing the heterogeneity of T2D is a major task of diabetes research to lower the high rate of treatment failure as well as to reduce the risk of long-term complications.

Recent Findings

A pathophysiology-based clustering system seems the most promising to help in the stratification of diabetes in terms of complication risk and response to treatment. This urges for clinical studies looking at novel biomarkers related to the different metabolic pathways of T2D and able to inform about the therapeutic cluster of each patient.

Summary

Here, we review the main settings of diabetes heterogeneity, to what extent it has been already addressed and the current gaps in knowledge towards a personalized therapeutic approach that considers the distinctive features of each patient.

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Change history

  • 22 May 2020

    The original version of this article unfortunately contained a mistake in the authorgroup section. The authors��� given and family names were inadvertently interchanged.

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  1. Pieralice Silvia and Zampetti Simona contributed equally to this work.

Authors and Affiliations

  1. Department of Medicine, Unit of Endocrinology and Diabetes, Campus Bio-Medico University of Rome, Via Alvaro del Portillo 21, 00128, Rome, Italy

    Pieralice Silvia

  2. Department of Experimental Medicine, Sapienza University, Viale Regina Elena 324, 00161, Rome, Italy

    Zampetti Simona, Maddaloni Ernesto & Buzzetti Raffaella

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  1. Pieralice Silvia
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  2. Zampetti Simona
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  4. Buzzetti Raffaella
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Correspondence to Maddaloni Ernesto.

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Pieralice Silvia, Zampetti Simona, Maddaloni Ernesto, and Buzzetti Raffaella declare that they have conflicts of interest.

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Silvia, P., Simona, Z., Ernesto, M. et al. “H” for Heterogeneity in the Algorithm for Type 2 Diabetes Management. Curr Diab Rep 20, 14 (2020). https://doi.org/10.1007/s11892-020-01297-w

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