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Characterization of...
Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes
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- Mendez, D. Y. (författare)
- Karolinska Institutet
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Zhou, M. H. (författare)
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- Lagerros, Y. T. (författare)
- Karolinska Institutet
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Velasco, D. V. G. (författare)
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- Tynelius, P. (författare)
- Karolinska Institutet
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- Gudjonsdottir, H. (författare)
- Karolinska Institutet
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de Leon, A. P. (författare)
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- Eeg-Olofsson, Katarina, 1968 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för molekylär och klinisk medicin,Institute of Medicine, Department of Molecular and Clinical Medicine
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Ostenson, C. G. (författare)
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- Brynedal, B. (författare)
- Karolinska Institutet
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Salinas, C. A. A. (författare)
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- Ebbevi, D. (författare)
- Karolinska Institutet
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- Lager, A. (författare)
- Karolinska Institutet
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(creator_code:org_t)
- 2022-10-18
- 2022
- Engelska.
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Ingår i: Bmc Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 20:1
- Relaterad länk:
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https://gup.ub.gu.se...
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https://doi.org/10.1...
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http://kipublication...
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Abstract
Ämnesord
Stäng
- Background The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. Methods Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and beta-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. Results Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low beta-cell function (LRLB), low-risk high beta-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk beta-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. Conclusions Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)
Nyckelord
- Precision medicine
- Data-driven analysis
- Type 2 diabetes
- Prevention
- Public health
- Epidemiology
- General & Internal Medicine
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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Till lärosätets databas
- Av författaren/redakt...
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Mendez, D. Y.
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Zhou, M. H.
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Lagerros, Y. T.
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Velasco, D. V. G ...
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Tynelius, P.
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Gudjonsdottir, H ...
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visa fler...
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de Leon, A. P.
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Eeg-Olofsson, Ka ...
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Ostenson, C. G.
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Brynedal, B.
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Salinas, C. A. A ...
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Ebbevi, D.
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Lager, A.
-
visa färre...
- Om ämnet
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Klinisk medicin
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och Endokrinologi oc ...
- Artiklar i publikationen
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Bmc Medicine
- Av lärosätet
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Göteborgs universitet
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Karolinska Institutet