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Dahal, C. ; Wawro, N. ; Meisinger, C. ; Breuninger, T. ; Thorand, B. ; Rathmann, W.* ; Koenig, W.* ; Hauner, H.* ; Peters, A. ; Linseisen, J.

Optimized metabotype definition based on a limited number of standard clinical parameters in the population-based KORA study.

Life 12:1460 (2022)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The aim of metabotyping is to categorize individuals into metabolically similar groups. Earlier studies that explored metabotyping used numerous parameters, which made it less transferable to apply. Therefore, this study aimed to identify metabotypes based on a set of standard laboratory parameters that are regularly determined in clinical practice. K-means cluster analysis was used to group 3001 adults from the KORA F4 cohort into three clusters. We identified the clustering parameters through variable importance methods, without including any specific disease endpoint. Several unique combinations of selected parameters were used to create different metabotype models. Metabotype models were then described and evaluated, based on various metabolic parameters and on the incidence of cardiometabolic diseases. As a result, two optimal models were identified: a model composed of five parameters, which were fasting glucose, HDLc, non-HDLc, uric acid, and BMI (the metabolic disease model) for clustering; and a model that included four parameters, which were fasting glucose, HDLc, non-HDLc, and triglycerides (the cardiovascular disease model). These identified metabotypes are based on a few common parameters that are measured in everyday clinical practice. These metabotypes are cost-effective, and can be easily applied on a large scale in order to identify specific risk groups that can benefit most from measures to prevent cardiometabolic diseases, such as dietary recommendations and lifestyle interventions.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Cardiovascular Diseases ; Clinical Marker ; Cluster Analysis ; Metabolic Diseases ; Metabotype ; Parameter Selection
ISSN (print) / ISBN 2075-1729
e-ISSN 2075-1729
Zeitschrift Life
Quellenangaben Band: 12, Heft: 10, Seiten: , Artikelnummer: 1460 Supplement: ,
Verlag MDPI
Verlagsort Basel
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology II (EPI2)
Independent Research Group Clinical Epidemiology (KEPI)
Förderungen German Ministry for Education and Research (BMBF)
enable Competence Cluster of Nutrition Research