Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study
Year: 2021
Type: article
Study design: Observational Study
Abstract: ABSTRACT Aims/hypothesis Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes (T2D). In the current study we replicate and cross-validate these T2D clusters in three large cohorts using readily measured variables in the clinic. Methods In this cross-sectional study, 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide and HDL in three independent cohorts. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort’s cluster centres. Results Five distinct T2D clusters were identified and mapped back to the original four ANDIS clusters. Using C-peptide and HDL instead of HOMA-B and HOMA-S three of the clusters mapped with high sensitivity (80.6 – 90.7%) to the previously identified Severe Insulin Deficient (SIDD), Severe insulin resistant (SIRD) and Obese (MOD) clusters. The previously described ANDIS MARD cluster could be mapped to the two milder groups in our study – one characterised by high HDL, and the other having not any extreme characteristic (MDH cluster). When these two milder groups were combined they mapped well to the previously labelled MARD cluster (sensitivity 79.4%). In the cross-validation between cohorts, particularly the SIDD and MDH cluster cross-validated well with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity ranging from 36.1% to 92.3% where individuals shifted from SIRD to MD and vice versa. Conclusions/interpretation Clusters based on C-peptide instead of HOMA measures result in clusters that resemble those based on HOMA measures, especially for SIDD, SIRD and MOD. By adding HDL, the MARD cluster based upon HOMA measures resulted in the current clustering in two clusters with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts.
Source: Diabetologia
Authors: Roderick C. Slieker, Louise A. Donnelly, Hugo Fitipaldi, Gerard A. Bouland, Giuseppe N. Giordano, Mikael Åkerlund, Mathias J. Gerl, Emma Ahlqvist, Ashfaq Ali, Iulian Dragan, Andreas Festa, Michael K. Hansen, Dina Mansour Aly, Min Kim, Dmitry Kuznetsov, Florence Mehl, Christian Klose, Kai Simons, Imre Pavo, Timothy J. Pullen, Tommi Suvitaival, Asger Wretlind, Peter Rossing, Valeriya Lyssenko, Cristina Legido-Quigley, Leif Groop, Bernard Thorens, Paul W. Franks, Mark Ibberson, Guy A. Rutter, Joline W. J. Beulens, Leen M. ‘t Hart, Ewan R. Pearson
Institutions: Leiden University Medical Center, Amsterdam Public Health, Amsterdam UMC Location Vrije Universiteit Amsterdam, University of Dundee, Lund University, Lipotype (Germany), Steno Diabetes Center Copenhagen, SIB Swiss Institute of Bioinformatics, Eli Lilly (United States), Janssen Research & Development (United States), King's College London, Imperial College London, Skåne University Hospital, University of Bergen, University of Helsinki, Institute for Molecular Medicine Finland, University of Lausanne, Harvard University, Nanyang Technological University, University Medical Center Utrecht
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,480
Awards: G1296115328, G130968091, G1335979935, G1485100654, G1635243398, Genetic and nutritional control of pancreatic beta cell identity., G1891855903, G1937207371, G2040450235, Control of glucagon secretion by AMPK and related kinases., G3555667338, G434337789, Assessing risk and progression of prediabetes and type 2 diabetes to enable disease modification - Sofia ref.: 115881, G4426574518, G4781795914, G5485930741, G5673545276, G609589047, The impact of long non-coding RNA at the Pax6 locus on beta cell identity and function, Defining the molecular and physiological mechanisms of pancreatic islet dysfunction which lead to type 2 diabetes, G6433152044, G6492936739, Coordination and Advancement of sub-Saharan Africa-EU Science & Technology Cooperation Network, Understanding pancreatic beta cell connectivity, Molecular mechanisms linking Sorcin to pancreatic beta cell lipotoxicity and ER Ca2+ stores., G7328074751, Stratified medicine in Type 2 diabetes: Insights from the study of drug response., G7571465722, G8041914798, Stratified medicine in Type 2 diabetes: Insights from the study of drug response., G8823668904, G9000168923, G9000255760, G9000284059
OpenAlex ID: W3168683031