Precision subclassification of type 2 diabetes: a systematic review

Authors

Shivani Misra, Imperial College London
Shivani Misra, Imperial College London
Robert Wagner, Universitätsklinikum Düsseldorf
Bige Ozkan, Welch Center for Prevention Epidemiology and Clinical Research
Martin Schön, Deutsches Diabetes-Zentrum
Magdalena Sevilla-Gonzalez, Massachusetts General Hospital
Katsiaryna Prystupa, Deutsches Diabetes-Zentrum
Caroline C. Wang, Welch Center for Prevention Epidemiology and Clinical Research
Raymond J. Kreienkamp, Broad Institute
Sara J. Cromer, Broad Institute
Mary R. Rooney, Welch Center for Prevention Epidemiology and Clinical Research
Daisy Duan, Johns Hopkins University School of Medicine
Anne Cathrine Baun Thuesen, Novo Nordisk Foundation Center for Basic Metabolic Research
Amelia S. Wallace, Welch Center for Prevention Epidemiology and Clinical Research
Aaron Leong, Broad Institute
Aaron J. Deutsch, Broad Institute
Mette K. Andersen, Novo Nordisk Foundation Center for Basic Metabolic Research
Liana K. Billings, NorthShore University HealthSystem
Liana K. Billings, NorthShore University HealthSystem
Robert H. Eckel, University of Colorado School of Medicine
Wayne Huey Herng Sheu, National Health Research Institutes Taiwan
Torben Hansen, Novo Nordisk Foundation Center for Basic Metabolic Research
Norbert Stefan, Deutsches Zentrum für Diabetesforschung
Mark O. Goodarzi, Cedars-Sinai Medical Center
Debashree Ray, Johns Hopkins Bloomberg School of Public Health
Elizabeth Selvin, Welch Center for Prevention Epidemiology and Clinical Research
Jose C. Florez, Broad Institute
Paul W. Franks, Harvard T.H. Chan School of Public Health
Stephen S. Rich, University of Virginia School of Medicine
Tina Vilsbøll, Steno Diabetes Center Copenhagen
Kimberly K. Vesco, Kaiser Permanente Center for Health Research
Miriam S. Udler, Harvard Medical School
Tiinamaija Tuomi, Helsinki University Hospital
Arianne Sweeting, Faculty of Medicine and Health

Document Type

Article

Publication Date

12-1-2023

Abstract

Background: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. Methods: We searched PubMed and Embase for publications that used ‘simple subclassification’ approaches using simple categorisation of clinical characteristics, or ‘complex subclassification’ approaches which used machine learning or ‘omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. Results: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. Conclusion: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

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