A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals

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Deelen , J , Kettunen , J , Fischer , K , van der Spek , A , Trompet , S , Kastenmueller , G , Boyd , A , Zierer , J , van den Akker , E B , Ala-Korpela , M , Amin , N , Demirkan , A , Ghanbari , M , van Heemst , D , Ikram , M A , van Klinken , J B , Mooijaart , S P , Peters , A , Salomaa , V , Sattar , N , Spector , T D , Tiemeier , H , Verhoeven , A , Waldenberger , M , Wuertz , P , Smith , G D , Metspalu , A , Perola , M , Menni , C , Geleijnse , J M , Drenos , F , Beekman , M , Jukema , J W , van Duijn , C M & Slagboom , P E 2019 , ' A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals ' , Nature Communications , vol. 10 , 3346 . https://doi.org/10.1038/s41467-019-11311-9

Title: A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals
Author: Deelen, Joris; Kettunen, Johannes; Fischer, Krista; van der Spek, Ashley; Trompet, Stella; Kastenmueller, Gabi; Boyd, Andy; Zierer, Jonas; van den Akker, Erik B.; Ala-Korpela, Mika; Amin, Najaf; Demirkan, Ayse; Ghanbari, Mohsen; van Heemst, Diana; Ikram, M. Arfan; van Klinken, Jan Bert; Mooijaart, Simon P.; Peters, Annette; Salomaa, Veikko; Sattar, Naveed; Spector, Tim D.; Tiemeier, Henning; Verhoeven, Aswin; Waldenberger, Melanie; Wuertz, Peter; Smith, George Davey; Metspalu, Andres; Perola, Markus; Menni, Cristina; Geleijnse, Johanna M.; Drenos, Fotios; Beekman, Marian; Jukema, J. Wouter; van Duijn, Cornelia M.; Slagboom, P. Eline
Contributor organization: Institute for Molecular Medicine Finland
Research Programs Unit
Date: 2019-08-20
Language: eng
Number of pages: 8
Belongs to series: Nature Communications
ISSN: 2041-1723
DOI: https://doi.org/10.1038/s41467-019-11311-9
URI: http://hdl.handle.net/10138/305241
Abstract: Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18-109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.
3111 Biomedicine
Peer reviewed: Yes
Rights: unspecified
Usage restriction: openAccess
Self-archived version: publishedVersion

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