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Metabolic syndrome and the plasma proteome: from association to causation

BACKGROUND: The metabolic syndrome (MetS), defined by the simultaneous clustering of cardio-metabolic risk factors, is a significant worldwide public health burden with an estimated 25% prevalence worldwide. The pathogenesis of MetS is not entirely clear and the use of molecular level data could hel...

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Autores principales: Elhadad, Mohamed A., Wilson, Rory, Zaghlool, Shaza B., Huth, Cornelia, Gieger, Christian, Grallert, Harald, Graumann, Johannes, Rathmann, Wolfgang, Koenig, Wolfgang, Sinner, Moritz F., Hveem, Kristian, Suhre, Karsten, Thorand, Barbara, Jonasson, Christian, Waldenberger, Melanie, Peters, Annette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138979/
https://www.ncbi.nlm.nih.gov/pubmed/34016094
http://dx.doi.org/10.1186/s12933-021-01299-2
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author Elhadad, Mohamed A.
Wilson, Rory
Zaghlool, Shaza B.
Huth, Cornelia
Gieger, Christian
Grallert, Harald
Graumann, Johannes
Rathmann, Wolfgang
Koenig, Wolfgang
Sinner, Moritz F.
Hveem, Kristian
Suhre, Karsten
Thorand, Barbara
Jonasson, Christian
Waldenberger, Melanie
Peters, Annette
author_facet Elhadad, Mohamed A.
Wilson, Rory
Zaghlool, Shaza B.
Huth, Cornelia
Gieger, Christian
Grallert, Harald
Graumann, Johannes
Rathmann, Wolfgang
Koenig, Wolfgang
Sinner, Moritz F.
Hveem, Kristian
Suhre, Karsten
Thorand, Barbara
Jonasson, Christian
Waldenberger, Melanie
Peters, Annette
author_sort Elhadad, Mohamed A.
collection PubMed
description BACKGROUND: The metabolic syndrome (MetS), defined by the simultaneous clustering of cardio-metabolic risk factors, is a significant worldwide public health burden with an estimated 25% prevalence worldwide. The pathogenesis of MetS is not entirely clear and the use of molecular level data could help uncover common pathogenic pathways behind the observed clustering. METHODS: Using a highly multiplexed aptamer-based affinity proteomics platform, we examined associations between plasma proteins and prevalent and incident MetS in the KORA cohort (n = 998) and replicated our results for prevalent MetS in the HUNT3 study (n = 923). We applied logistic regression models adjusted for age, sex, smoking status, and physical activity. We used the bootstrap ranking algorithm of least absolute shrinkage and selection operator (LASSO) to select a predictive model from the incident MetS associated proteins and used area under the curve (AUC) to assess its performance. Finally, we investigated the causal effect of the replicated proteins on MetS using two-sample Mendelian randomization. RESULTS: Prevalent MetS was associated with 116 proteins, of which 53 replicated in HUNT. These included previously reported proteins like leptin, and new proteins like NTR domain-containing protein 2 and endoplasmic reticulum protein 29. Incident MetS was associated with 14 proteins in KORA, of which 13 overlap the prevalent MetS associated proteins with soluble advanced glycosylation end product-specific receptor (sRAGE) being unique to incident MetS. The LASSO selected an eight-protein predictive model with an (AUC = 0.75; 95% CI = 0.71–0.79) in KORA. Mendelian randomization suggested causal effects of three proteins on MetS, namely apolipoprotein E2 (APOE2) (Wald-Ratio = − 0.12, Wald-p = 3.63e−13), apolipoprotein B (APOB) (Wald-Ratio = − 0.09, Wald-p = 2.54e−04) and proto-oncogene tyrosine-protein kinase receptor (RET) (Wald-Ratio = 0.10, Wald-p = 5.40e−04). CONCLUSIONS: Our findings offer new insights into the plasma proteome underlying MetS and identify new protein associations. We reveal possible casual effects of APOE2, APOB and RET on MetS. Our results highlight protein candidates that could potentially serve as targets for prevention and therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-021-01299-2.
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spelling pubmed-81389792021-05-21 Metabolic syndrome and the plasma proteome: from association to causation Elhadad, Mohamed A. Wilson, Rory Zaghlool, Shaza B. Huth, Cornelia Gieger, Christian Grallert, Harald Graumann, Johannes Rathmann, Wolfgang Koenig, Wolfgang Sinner, Moritz F. Hveem, Kristian Suhre, Karsten Thorand, Barbara Jonasson, Christian Waldenberger, Melanie Peters, Annette Cardiovasc Diabetol Original Investigation BACKGROUND: The metabolic syndrome (MetS), defined by the simultaneous clustering of cardio-metabolic risk factors, is a significant worldwide public health burden with an estimated 25% prevalence worldwide. The pathogenesis of MetS is not entirely clear and the use of molecular level data could help uncover common pathogenic pathways behind the observed clustering. METHODS: Using a highly multiplexed aptamer-based affinity proteomics platform, we examined associations between plasma proteins and prevalent and incident MetS in the KORA cohort (n = 998) and replicated our results for prevalent MetS in the HUNT3 study (n = 923). We applied logistic regression models adjusted for age, sex, smoking status, and physical activity. We used the bootstrap ranking algorithm of least absolute shrinkage and selection operator (LASSO) to select a predictive model from the incident MetS associated proteins and used area under the curve (AUC) to assess its performance. Finally, we investigated the causal effect of the replicated proteins on MetS using two-sample Mendelian randomization. RESULTS: Prevalent MetS was associated with 116 proteins, of which 53 replicated in HUNT. These included previously reported proteins like leptin, and new proteins like NTR domain-containing protein 2 and endoplasmic reticulum protein 29. Incident MetS was associated with 14 proteins in KORA, of which 13 overlap the prevalent MetS associated proteins with soluble advanced glycosylation end product-specific receptor (sRAGE) being unique to incident MetS. The LASSO selected an eight-protein predictive model with an (AUC = 0.75; 95% CI = 0.71–0.79) in KORA. Mendelian randomization suggested causal effects of three proteins on MetS, namely apolipoprotein E2 (APOE2) (Wald-Ratio = − 0.12, Wald-p = 3.63e−13), apolipoprotein B (APOB) (Wald-Ratio = − 0.09, Wald-p = 2.54e−04) and proto-oncogene tyrosine-protein kinase receptor (RET) (Wald-Ratio = 0.10, Wald-p = 5.40e−04). CONCLUSIONS: Our findings offer new insights into the plasma proteome underlying MetS and identify new protein associations. We reveal possible casual effects of APOE2, APOB and RET on MetS. Our results highlight protein candidates that could potentially serve as targets for prevention and therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12933-021-01299-2. BioMed Central 2021-05-20 /pmc/articles/PMC8138979/ /pubmed/34016094 http://dx.doi.org/10.1186/s12933-021-01299-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Original Investigation
Elhadad, Mohamed A.
Wilson, Rory
Zaghlool, Shaza B.
Huth, Cornelia
Gieger, Christian
Grallert, Harald
Graumann, Johannes
Rathmann, Wolfgang
Koenig, Wolfgang
Sinner, Moritz F.
Hveem, Kristian
Suhre, Karsten
Thorand, Barbara
Jonasson, Christian
Waldenberger, Melanie
Peters, Annette
Metabolic syndrome and the plasma proteome: from association to causation
title Metabolic syndrome and the plasma proteome: from association to causation
title_full Metabolic syndrome and the plasma proteome: from association to causation
title_fullStr Metabolic syndrome and the plasma proteome: from association to causation
title_full_unstemmed Metabolic syndrome and the plasma proteome: from association to causation
title_short Metabolic syndrome and the plasma proteome: from association to causation
title_sort metabolic syndrome and the plasma proteome: from association to causation
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138979/
https://www.ncbi.nlm.nih.gov/pubmed/34016094
http://dx.doi.org/10.1186/s12933-021-01299-2
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