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Identifying blood biomarkers for type 2 diabetes subtyping : a report from the ORIGIN trial

Pigeyre, Marie ; Gerstein, Hertzel ; Ahlqvist, Emma LU ; Hess, Sibylle and Paré, Guillaume (2023) In Diabetologia 66(6). p.1045-1051
Abstract

Aims/hypothesis: Individuals with diabetes can be clustered into five subtypes using up to six routinely measured clinical variables. We hypothesised that circulating protein levels might be used to distinguish between these subtypes. We recently used five of these six variables to categorise 7017 participants from the Outcome Reduction with an Initial Glargine Intervention (ORIGIN) trial into these subtypes: severe autoimmune diabetes (SAID, n=241), severe insulin-deficient diabetes (SIDD, n=1594), severe insulin-resistant diabetes (SIRD, n=914), mild obesity-related diabetes (MOD, n=1595) and mild age-related diabetes (MARD, n=2673). Methods: Forward-selection logistic regression models were used to identify a subset of 233... (More)

Aims/hypothesis: Individuals with diabetes can be clustered into five subtypes using up to six routinely measured clinical variables. We hypothesised that circulating protein levels might be used to distinguish between these subtypes. We recently used five of these six variables to categorise 7017 participants from the Outcome Reduction with an Initial Glargine Intervention (ORIGIN) trial into these subtypes: severe autoimmune diabetes (SAID, n=241), severe insulin-deficient diabetes (SIDD, n=1594), severe insulin-resistant diabetes (SIRD, n=914), mild obesity-related diabetes (MOD, n=1595) and mild age-related diabetes (MARD, n=2673). Methods: Forward-selection logistic regression models were used to identify a subset of 233 cardiometabolic protein biomarkers that were independent determinants of one subtype vs the others. We then assessed the performance of adding identified biomarkers (one after one, from the most discriminant to the least) to predict each subtype vs the others using area under the receiver operating characteristic curve (AUC ROC). Models were adjusted for age, sex, ethnicity, C-peptide level, diabetes duration and glucose-lowering medication usage at blood collection. Results: A total of 25 biomarkers were independent determinants of subtypes, including 13 for SIDD, 2 for SIRD, 7 for MOD and 11 for MARD (all p<4.3 × 10−5). The performance of the biomarker sets (comprising 1 to 25 biomarkers), assessed through the AUC ROC, ranged from 0.611 to 0.734, 0.723 to 0.861, 0.672 to 0.742, and 0.651 to 0.751, for SIDD, SIRD, MOD and MARD, respectively. No biomarkers other than GAD antibodies were determinants of SAID. Conclusions/interpretation: We identified 25 serum biomarkers, as independent determinants of type 2 diabetes subtypes, that could be combined into a diagnostic test for subtyping. Trial registration: ORIGIN trial, ClinicalTrials.gov NCT00069784. Graphical abstract: [Figure not available: see fulltext.].

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Blood biomarkers, Circulating biomarkers, Diabetes clusters, Diabetes subtypes, ORIGIN, Type 2 diabetes
in
Diabetologia
volume
66
issue
6
pages
1045 - 1051
publisher
Springer
external identifiers
  • scopus:85149016947
  • pmid:36854916
ISSN
0012-186X
DOI
10.1007/s00125-023-05887-7
language
English
LU publication?
yes
id
ee900c2b-372d-4b4a-b0d8-11e9845f96fc
date added to LUP
2023-03-16 14:48:54
date last changed
2024-06-13 09:55:29
@article{ee900c2b-372d-4b4a-b0d8-11e9845f96fc,
  abstract     = {{<p>Aims/hypothesis: Individuals with diabetes can be clustered into five subtypes using up to six routinely measured clinical variables. We hypothesised that circulating protein levels might be used to distinguish between these subtypes. We recently used five of these six variables to categorise 7017 participants from the Outcome Reduction with an Initial Glargine Intervention (ORIGIN) trial into these subtypes: severe autoimmune diabetes (SAID, n=241), severe insulin-deficient diabetes (SIDD, n=1594), severe insulin-resistant diabetes (SIRD, n=914), mild obesity-related diabetes (MOD, n=1595) and mild age-related diabetes (MARD, n=2673). Methods: Forward-selection logistic regression models were used to identify a subset of 233 cardiometabolic protein biomarkers that were independent determinants of one subtype vs the others. We then assessed the performance of adding identified biomarkers (one after one, from the most discriminant to the least) to predict each subtype vs the others using area under the receiver operating characteristic curve (AUC ROC). Models were adjusted for age, sex, ethnicity, C-peptide level, diabetes duration and glucose-lowering medication usage at blood collection. Results: A total of 25 biomarkers were independent determinants of subtypes, including 13 for SIDD, 2 for SIRD, 7 for MOD and 11 for MARD (all p&lt;4.3 × 10<sup>−5</sup>). The performance of the biomarker sets (comprising 1 to 25 biomarkers), assessed through the AUC ROC, ranged from 0.611 to 0.734, 0.723 to 0.861, 0.672 to 0.742, and 0.651 to 0.751, for SIDD, SIRD, MOD and MARD, respectively. No biomarkers other than GAD antibodies were determinants of SAID. Conclusions/interpretation: We identified 25 serum biomarkers, as independent determinants of type 2 diabetes subtypes, that could be combined into a diagnostic test for subtyping. Trial registration: ORIGIN trial, ClinicalTrials.gov NCT00069784. Graphical abstract: [Figure not available: see fulltext.].</p>}},
  author       = {{Pigeyre, Marie and Gerstein, Hertzel and Ahlqvist, Emma and Hess, Sibylle and Paré, Guillaume}},
  issn         = {{0012-186X}},
  keywords     = {{Blood biomarkers; Circulating biomarkers; Diabetes clusters; Diabetes subtypes; ORIGIN; Type 2 diabetes}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{1045--1051}},
  publisher    = {{Springer}},
  series       = {{Diabetologia}},
  title        = {{Identifying blood biomarkers for type 2 diabetes subtyping : a report from the ORIGIN trial}},
  url          = {{http://dx.doi.org/10.1007/s00125-023-05887-7}},
  doi          = {{10.1007/s00125-023-05887-7}},
  volume       = {{66}},
  year         = {{2023}},
}