2022
DOI: 10.1007/s00125-022-05769-4
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Phenotypic and genetic classification of diabetes

Abstract: The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implement… Show more

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Cited by 46 publications
(24 citation statements)
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“…Some risk factors were assumed as negative when not recorded in the hospital charts, thus potentially underestimating their impact. We used clinical features to label type 2 diabetes, despite the current trend to include genetic and metabolic testing to refine diabetes subtypes classification [ 30 ]. Therefore, women with MODY could had been labelled as having type 2 diabetes, since genetic tests were not available at the two hospitals.…”
Section: Discussionmentioning
confidence: 99%
“…Some risk factors were assumed as negative when not recorded in the hospital charts, thus potentially underestimating their impact. We used clinical features to label type 2 diabetes, despite the current trend to include genetic and metabolic testing to refine diabetes subtypes classification [ 30 ]. Therefore, women with MODY could had been labelled as having type 2 diabetes, since genetic tests were not available at the two hospitals.…”
Section: Discussionmentioning
confidence: 99%
“…A fasting blood glucose level ≥ 126 mg/dL was also an indicator of DM. HS patients with DM were subdivided according to the clusters of the All New Diabetics In Scania (ANDIS) study [ 11 , 36 ]. The cluster classification was based on the presence of antibodies, age at diagnosis of DM, BMI and HbA1c [ 11 ].…”
Section: Methodsmentioning
confidence: 99%
“…10 Further evaluation of the present approaches and novel integrated methods to redefine diabetes subtypes will be required to determine when and how best to introduce these approaches into clinical practice. 11 More recently, a first such effort has been undertaken in persons carrying an increased risk of type 2 diabetes (history of prediabetes [overall 41.2%: IFG 18.7%, IGT 10.9%, IFG + IGT 11.6], family history of diabetes or gestational diabetes, or body mass index (BMI) >27 kg/m 2 ) from the TUEF/TULIP study. Six distinct subphenotypes (clusters) were identified using deep phenotyping, including body fat distribution, liver fat content and genetic risk: (1.)…”
Section: Prediabetes: Classification Epidemiology Impact and Screenin...mentioning
confidence: 99%
“…It remains to be established whether novel subphenotyping approaches are helpful to elucidate the metabolic heterogeneity prior to the development of type 2 diabetes. Their further validation and fine tuning could represent one step forward towards precision medicine in clinical practice 11 . More research is needed to define the exact prevalence of DSPN and CAN in the various categories of prediabetes and to decipher the natural history of these conditions in clearly defined metabolic subpopulations and the corresponding determinants of their development and progression.…”
Section: Conclusion and Future Perspectivesmentioning
confidence: 99%