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  • Plasma protein N-glycosylation is associated with cardiovascular disease, nephropathy, and retinopathy in type 2 diabetes

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Genetics/Genomes/Proteomics/Metabolomics
Plasma protein N-glycosylation is associated with cardiovascular disease, nephropathy, and retinopathy in type 2 diabetes
  1. Elham Memarian1,2,
  2. Leen M 't Hart3,4,5,
  3. Roderick C Slieker3,4,
  4. Roosmarijn F L Lemmers6,
  5. Amber A van der Heijden7,
  6. Femke Rutters8,
  7. Giel Nijpels7,
  8. Emma Schoep3,
  9. Aloysius G Lieverse9,
  10. Eric J G Sijbrands6,
  11. Manfred Wuhrer1,
  12. Mandy van Hoek6,
  13. Viktoria Dotz1
  1. 1Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands
  2. 2Genos Glycoscience Research Laboratory, Zagreb, Croatia
  3. 3Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands
  4. 4Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, location VUmc, Amsterdam, The Netherlands
  5. 5Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
  6. 6Department of Internal Medicine, Erasmus Medical Center, University Medical Center, Rotterdam, The Netherlands
  7. 7Amsterdam UMC, Vrije Universiteit Amsterdam, Department of General Practice Medicine, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
  8. 8Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
  9. 9Department of Internal Medicine, Maxima Medical Center, Eindhoven, The Netherlands
  1. Correspondence to Dr Mandy van Hoek; m.vanhoek{at}erasmusmc.nl

Abstract

Introduction Although associations of total plasma N-glycome (TPNG) with type 2 diabetes have been reported, little is known on the role of TPNG in type 2 diabetes complications, a major cause of type 2 diabetes-related morbidity and mortality. Here, we assessed TPNG in relation to type 2 diabetes complications in subsamples of two Dutch cohorts using mass spectrometry (n=1815 in DiaGene and n=1518 in Hoorn Diabetes Care System).

Research design and methods Blood plasma samples and technical replicates were pipetted into 96-well plates in a randomized manner. Peptide:N-glycosidase F (PNGase F) was used to release N-glycans, whereafter sialic acids were derivatized for stabilization and linkage differentiation. After total area normalization, 68 individual glycan compositions were quantified in total and were used to calculate 45 derived traits which reflect structural features of glycosylation. Associations of glycan features with prevalent and incident microvascular or macrovascular complications were tested in logistic and Cox regression in both independent cohorts and the results were meta-analyzed.

Results Our results demonstrated similarities between incident and prevalent complications. The strongest association for prevalent cardiovascular disease was a high level of bisection on a group of diantennary glycans (A2FS0B; OR=1.38, p=1.34×10−11), while for prevalent nephropathy the increase in 2,6-sialylation on triantennary glycans was most pronounced (A3E; OR=1.28, p=9.70×10−6). Several other TPNG features, including fucosylation, galactosylation, and sialylation, firmly demonstrated associations with prevalent and incident complications of type 2 diabetes.

Conclusions These findings may provide a glance on how TPNG patterns change before complications emerge, paving the way for future studies on prediction biomarkers and potentially disease mechanisms.

  • biomarkers
  • diabetes complications
  • glycosylation

Data availability statement

Data are available upon reasonable request. The data that support the findings of this study are available on request from the corresponding author, who takes responsibility for the integrity of the data and the accuracy of the data analysis. The data are not publicly available due to them containing information that could compromise research participant privacy/consent.

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi.org/10.1136/bmjdrc-2021-002345

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    Data availability statement

    Data are available upon reasonable request. The data that support the findings of this study are available on request from the corresponding author, who takes responsibility for the integrity of the data and the accuracy of the data analysis. The data are not publicly available due to them containing information that could compromise research participant privacy/consent.

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    Footnotes

    • EM and LM'tH contributed equally.

    • MvH and VD contributed equally.

    • Contributors EM performed glycomic analysis of the Hoorn DCS cohort, processed Hoorn DCS glycomics raw data, developed the R-scripts for data visualization, and wrote the manuscript. LM’tH contributed to the coordination of the Hoorn DCS study, performed statistical analyses, and reviewed/edited the manuscript. ES and RCS performed statistical analyses and reviewed/edited the manuscript. RFLL collected clinical follow-up data and performed statistical analyses in the DiaGene study. AAvdH, FR, and GN contributed to the collection, design, and coordination of the Hoorn DCS study and reviewed/edited the manuscript. AGL contributed to the collection, design, and coordination of the DiaGene study and reviewed/edited the manuscript. EJGS contributed to the design and coordination of the DiaGene study and reviewed/edited the manuscript. MW supervised the glycomics study, contributed to discussion, and reviewed/edited the manuscript. MvH contributed to the conception of research question, collection, and coordination of the DiaGene study, reviewed/edited the manuscript, and contributed to the discussion; she is the guarantor of this work and as such had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. VD supervised the glycomics study, processed the glycomics data, developed the R-script for data visualization, interpreted the results, reviewed/edited the manuscript, and contributed to the discussion. All authors have given approval to the final version of the manuscript.

    • Funding EM was supported by funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant for the project GlySign (contract no. 722095). MvH was supported by the ErasmusMC fellowship.

    • Competing interests MW is inventor on a patent application on sialic acid derivatization by ethyl esterification. EM is employed by Genos. VD currently works at BioTherapeutics Analytical Development, Janssen Biologics BV. No other potential conflicts of interest relevant to this article were reported.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.