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dc.contributor.authorSlieker, Roderick C.
dc.contributor.authorDonnelly, Louise A.
dc.contributor.authorFitipaldi, Hugo
dc.contributor.authorBouland, Gerard A.
dc.contributor.authorGiordano, Giuseppe N.
dc.contributor.authorÅkerlund, Mikael
dc.contributor.authorGerl, Mathias J.
dc.contributor.authorAhlqvist, Emma
dc.contributor.authorAli, Ashfaq
dc.contributor.authorDragan, Iulian
dc.contributor.authorFesta, Andreas
dc.contributor.authorHansen, Michael K.
dc.contributor.authorMansour Aly, Dina
dc.contributor.authorKim, Min
dc.contributor.authorKuznetsov, Dmitry
dc.contributor.authorMehl, Florence
dc.contributor.authorKlose, Christian
dc.contributor.authorSimons, Kai
dc.contributor.authorPavo, Imre
dc.contributor.authorPullen, Timothy J.
dc.contributor.authorSuvitaival, Tommi
dc.contributor.authorWretlind, Asger
dc.contributor.authorRossing, Peter
dc.contributor.authorLyssenko, Valeriya
dc.contributor.authorLegido-Quigley, Cristina
dc.contributor.authorGroop, L
dc.contributor.authorThorens, Bernard
dc.contributor.authorFranks, Paul W
dc.contributor.authorIbberson, Mark
dc.contributor.authorRutter, Guy A.
dc.contributor.authorBeulens, Joline W.J.
dc.contributor.author‘t Hart, Leen M.
dc.contributor.authorPearson, Ewan R.
dc.date.accessioned2022-03-23T10:03:27Z
dc.date.available2022-03-23T10:03:27Z
dc.date.created2022-01-25T14:40:50Z
dc.date.issued2021
dc.identifier.issn0012-186X
dc.identifier.urihttps://hdl.handle.net/11250/2987040
dc.description.abstractAims/hypothesis: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. Methods: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide, and HDL-cholesterol. 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. Finally, we compared the time to insulin requirement for each cluster. Results: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6–90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters 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. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression. Conclusions/interpretation: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into 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-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleReplication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY studyen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2021 the authorsen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doi10.1007/s00125-021-05490-8
dc.identifier.cristin1989627
dc.source.journalDiabetologiaen_US
dc.source.pagenumber1982-1989en_US
dc.identifier.citationDiabetologia. 2021, 64 (9), 1982-1989.en_US
dc.source.volume64en_US
dc.source.issue9en_US


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