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In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study
AIMS/HYPOTHESIS: The pathogenesis of type 2 diabetes is not fully understood. We investigated whether circulating levels of preselected proteins were associated with the outcome ‘diabetes’ and whether these associations were causal. METHODS: In 2467 individuals of the population-based, cross-section...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805963/ https://www.ncbi.nlm.nih.gov/pubmed/31446444 http://dx.doi.org/10.1007/s00125-019-4960-8 |
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author | Beijer, Kristina Nowak, Christoph Sundström, Johan Ärnlöv, Johan Fall, Tove Lind, Lars |
author_facet | Beijer, Kristina Nowak, Christoph Sundström, Johan Ärnlöv, Johan Fall, Tove Lind, Lars |
author_sort | Beijer, Kristina |
collection | PubMed |
description | AIMS/HYPOTHESIS: The pathogenesis of type 2 diabetes is not fully understood. We investigated whether circulating levels of preselected proteins were associated with the outcome ‘diabetes’ and whether these associations were causal. METHODS: In 2467 individuals of the population-based, cross-sectional EpiHealth study (45–75 years, 50% women), 249 plasma proteins were analysed by the proximity extension assay technique. DNA was genotyped using the Illumina HumanCoreExome-12 v1.0 BeadChip. Diabetes was defined as taking glucose-lowering treatment or having a fasting plasma glucose of ≥7.0 mmol/l. The associations between proteins and diabetes were assessed using logistic regression. To investigate causal relationships between proteins and diabetes, a bidirectional two-sample Mendelian randomisation was performed based on large, genome-wide association studies belonging to the DIAGRAM and MAGIC consortia, and a genome-wide association study in the EpiHealth study. RESULTS: Twenty-six proteins were positively associated with diabetes, including cathepsin D, retinal dehydrogenase 1, α-l-iduronidase, hydroxyacid oxidase 1 and galectin-4 (top five findings). Three proteins, lipoprotein lipase, IGF-binding protein 2 and paraoxonase 3 (PON-3), were inversely associated with diabetes. Fourteen of the proteins are novel discoveries. The Mendelian randomisation study did not disclose any significant causal effects between the proteins and diabetes in either direction that were consistent with the relationships found between the protein levels and diabetes. CONCLUSIONS/INTERPRETATION: The 29 proteins associated with diabetes are involved in several physiological pathways, but given the power of the study no causal link was identified for those proteins tested in Mendelian randomisation. Therefore, the identified proteins are likely to be biomarkers for type 2 diabetes, rather than representing causal pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-019-4960-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users. |
format | Online Article Text |
id | pubmed-6805963 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-68059632019-11-05 In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study Beijer, Kristina Nowak, Christoph Sundström, Johan Ärnlöv, Johan Fall, Tove Lind, Lars Diabetologia Article AIMS/HYPOTHESIS: The pathogenesis of type 2 diabetes is not fully understood. We investigated whether circulating levels of preselected proteins were associated with the outcome ‘diabetes’ and whether these associations were causal. METHODS: In 2467 individuals of the population-based, cross-sectional EpiHealth study (45–75 years, 50% women), 249 plasma proteins were analysed by the proximity extension assay technique. DNA was genotyped using the Illumina HumanCoreExome-12 v1.0 BeadChip. Diabetes was defined as taking glucose-lowering treatment or having a fasting plasma glucose of ≥7.0 mmol/l. The associations between proteins and diabetes were assessed using logistic regression. To investigate causal relationships between proteins and diabetes, a bidirectional two-sample Mendelian randomisation was performed based on large, genome-wide association studies belonging to the DIAGRAM and MAGIC consortia, and a genome-wide association study in the EpiHealth study. RESULTS: Twenty-six proteins were positively associated with diabetes, including cathepsin D, retinal dehydrogenase 1, α-l-iduronidase, hydroxyacid oxidase 1 and galectin-4 (top five findings). Three proteins, lipoprotein lipase, IGF-binding protein 2 and paraoxonase 3 (PON-3), were inversely associated with diabetes. Fourteen of the proteins are novel discoveries. The Mendelian randomisation study did not disclose any significant causal effects between the proteins and diabetes in either direction that were consistent with the relationships found between the protein levels and diabetes. CONCLUSIONS/INTERPRETATION: The 29 proteins associated with diabetes are involved in several physiological pathways, but given the power of the study no causal link was identified for those proteins tested in Mendelian randomisation. Therefore, the identified proteins are likely to be biomarkers for type 2 diabetes, rather than representing causal pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-019-4960-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users. Springer Berlin Heidelberg 2019-08-24 2019 /pmc/articles/PMC6805963/ /pubmed/31446444 http://dx.doi.org/10.1007/s00125-019-4960-8 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Beijer, Kristina Nowak, Christoph Sundström, Johan Ärnlöv, Johan Fall, Tove Lind, Lars In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
title | In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
title_full | In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
title_fullStr | In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
title_full_unstemmed | In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
title_short | In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
title_sort | in search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805963/ https://www.ncbi.nlm.nih.gov/pubmed/31446444 http://dx.doi.org/10.1007/s00125-019-4960-8 |
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