Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study
(2022) In Cell Reports Medicine 3(1).- Abstract
- The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and... (More)
- The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments. © 2021 The Authors (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/6d8173bc-594b-406f-bf8e-71426b4ca8e4
- author
- Wesolowska-Andersen, A. ; Kurbasic, Azra LU ; Franks, Paul LU and Brunak, Soren
- author collaboration
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- archetypes, disease progression, glycaemic deterioration, multi-omics, patient clustering, patient stratification, precision medicine, soft-clustering, type 2 diabetes
- in
- Cell Reports Medicine
- volume
- 3
- issue
- 1
- article number
- 100477
- publisher
- Elsevier
- external identifiers
-
- pmid:35106505
- scopus:85122950661
- ISSN
- 2666-3791
- DOI
- 10.1016/j.xcrm.2021.100477
- language
- English
- LU publication?
- yes
- id
- 6d8173bc-594b-406f-bf8e-71426b4ca8e4
- date added to LUP
- 2022-02-28 12:21:22
- date last changed
- 2022-04-24 18:04:54
@article{6d8173bc-594b-406f-bf8e-71426b4ca8e4,
abstract = {{The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments. © 2021 The Authors}},
author = {{Wesolowska-Andersen, A. and Kurbasic, Azra and Franks, Paul and Brunak, Soren}},
issn = {{2666-3791}},
keywords = {{archetypes; disease progression; glycaemic deterioration; multi-omics; patient clustering; patient stratification; precision medicine; soft-clustering; type 2 diabetes}},
language = {{eng}},
number = {{1}},
publisher = {{Elsevier}},
series = {{Cell Reports Medicine}},
title = {{Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study}},
url = {{http://dx.doi.org/10.1016/j.xcrm.2021.100477}},
doi = {{10.1016/j.xcrm.2021.100477}},
volume = {{3}},
year = {{2022}},
}