WeightNameValue
1000 Titel
  • Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease
1000 Autor/in
  1. Birukov, Anna |
  2. Plavša, Branimir |
  3. Eichelman, Fabian |
  4. Kuxhaus, Olga |
  5. Hoshi, Rosangela Akemi |
  6. Rudman, Nadja |
  7. Štambuk, Tamara |
  8. Trbojević-Akmačić, Irena |
  9. Schiborn, Catarina |
  10. Morze, Jakub |
  11. Mihelčić, Matea |
  12. Cindrić, Ana |
  13. Liu, Yanyan |
  14. Demler, Olga |
  15. Perola, Markus |
  16. Mora, Samia |
  17. Schulze, Matthias B. |
  18. Lauc, Gordan |
  19. Wittenbecher, Clemens |
1000 Erscheinungsjahr 2022
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2022-10-25
1000 Erschienen in
1000 Quellenangabe
  • 45(11):2729-2736
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2022
1000 Verlagsversion
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679264/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • OBJECTIVE: N-glycosylation is a functional posttranslational modification of immunoglobulins (Igs). We hypothesized that specific IgG N-glycans are associated with incident type 2 diabetes and cardiovascular disease (CVD). RESEARCH DESIGN AND METHODS: We performed case-cohort studies within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam cohort (2,127 in the type 2 diabetes subcohort [741 incident cases]; 2,175 in the CVD subcohort [417 myocardial infarction and stroke cases]). Relative abundances of 24 IgG N-glycan peaks (IgG-GPs) were measured by ultraperformance liquid chromatography, and eight glycosylation traits were derived based on structural similarity. End point–associated IgG-GPs were preselected with fractional polynomials, and prospective associations were estimated in confounder-adjusted Cox models. Diabetes risk associations were validated in three independent studies. RESULTS: After adjustment for confounders and multiple testing correction, IgG-GP7, IgG-GP8, IgG-GP9, IgG-GP11, and IgG-GP19 were associated with type 2 diabetes risk. A score based on these IgG-GPs was associated with a higher diabetes risk in EPIC-Potsdam and independent validation studies (843 total cases, 3,149 total non-cases, pooled estimate per SD increase 1.50 [95% CI 1.37–1.64]). Associations of IgG-GPs with CVD risk differed between men and women. In women, IgG-GP9 was inversely associated with CVD risk (hazard ratio [HR] per SD 0.80 [95% CI 0.65–0.98]). In men, a weighted score based on IgG-GP19 and IgG-GP23 was associated with higher CVD risk (HR per SD 1.47 [95% CI 1.20–1.80]). In addition, several derived traits were associated with cardiometabolic disease incidence. CONCLUSIONS: Selected IgG N-glycans are associated with cardiometabolic risk beyond classic risk factors, including clinical biomarkers.
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/QmlydWtvdiwgQW5uYQ==|https://frl.publisso.de/adhoc/uri/UGxhdsWhYSwgQnJhbmltaXI=|https://frl.publisso.de/adhoc/uri/RWljaGVsbWFuLCBGYWJpYW4=|https://frl.publisso.de/adhoc/uri/S3V4aGF1cywgT2xnYQ==|https://frl.publisso.de/adhoc/uri/SG9zaGksIFJvc2FuZ2VsYSBBa2VtaQ==|https://frl.publisso.de/adhoc/uri/UnVkbWFuLCBOYWRqYQ==|https://frl.publisso.de/adhoc/uri/xaB0YW1idWssIFRhbWFyYQ==|https://frl.publisso.de/adhoc/uri/VHJib2pldmnEhy1Ba21hxI1pxIcsIElyZW5h|https://frl.publisso.de/adhoc/uri/U2NoaWJvcm4sIENhdGFyaW5h|https://frl.publisso.de/adhoc/uri/TW9yemUsIEpha3Vi|https://frl.publisso.de/adhoc/uri/TWloZWzEjWnEhywgTWF0ZWE=|https://frl.publisso.de/adhoc/uri/Q2luZHJpxIcsIEFuYQ==|https://frl.publisso.de/adhoc/uri/TGl1LCBZYW55YW4=|https://frl.publisso.de/adhoc/uri/RGVtbGVyLCBPbGdh|https://frl.publisso.de/adhoc/uri/UGVyb2xhLCBNYXJrdXM=|https://frl.publisso.de/adhoc/uri/TW9yYSwgU2FtaWE=|https://orcid.org/0000-0002-0830-5277|https://frl.publisso.de/adhoc/uri/TGF1YywgR29yZGFu|https://orcid.org/0000-0001-7792-877X
1000 Label
1000 Förderer
  1. Fundação Lemann |
  2. European Union |
  3. Federal Ministry of Science, Germany |
  4. European Structural and Investment Funds: Research and Development |
  5. Deutsche Forschungsgemeinschaft |
  6. National Institute of Diabetes and Digestive and Kidney Diseases |
  7. National Heart, Lung, and Blood Institute |
  8. Croatian National Centre of Research Excellence |
  9. Centre of Competence |
  10. Bundesministerium für Bildung und Forschung |
  11. State of Brandenburg |
  12. European Community |
  13. Deutsche Krebshilfe |
  14. SciLifeLab & Wallenberg Data Driven Life Science Program |
  15. Horizon 2020 |
1000 Fördernummer
  1. -
  2. 05F02; SOC 95201408
  3. EA 9401
  4. -
  5. WI5132/1-1
  6. DK112940
  7. HL 117861; K24 HL136852; R01 HL134811
  8. KK.01.1.1.01.0010
  9. KK.01.2.2.03.0006
  10. 82DZD00302; 82DZD03D03
  11. 82DZD00302; 82DZD03D03
  12. 05F02; SOC 98200769
  13. 70-2488-Ha
  14. KAW 2020.0239
  15. 721815; 722095
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. -
  5. -
  6. -
  7. -
  8. -
  9. -
  10. -
  11. -
  12. -
  13. -
  14. -
  15. -
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Fundação Lemann |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer European Union |
    1000 Förderprogramm -
    1000 Fördernummer 05F02; SOC 95201408
  3. 1000 joinedFunding-child
    1000 Förderer Federal Ministry of Science, Germany |
    1000 Förderprogramm -
    1000 Fördernummer EA 9401
  4. 1000 joinedFunding-child
    1000 Förderer European Structural and Investment Funds: Research and Development |
    1000 Förderprogramm -
    1000 Fördernummer -
  5. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm -
    1000 Fördernummer WI5132/1-1
  6. 1000 joinedFunding-child
    1000 Förderer National Institute of Diabetes and Digestive and Kidney Diseases |
    1000 Förderprogramm -
    1000 Fördernummer DK112940
  7. 1000 joinedFunding-child
    1000 Förderer National Heart, Lung, and Blood Institute |
    1000 Förderprogramm -
    1000 Fördernummer HL 117861; K24 HL136852; R01 HL134811
  8. 1000 joinedFunding-child
    1000 Förderer Croatian National Centre of Research Excellence |
    1000 Förderprogramm -
    1000 Fördernummer KK.01.1.1.01.0010
  9. 1000 joinedFunding-child
    1000 Förderer Centre of Competence |
    1000 Förderprogramm -
    1000 Fördernummer KK.01.2.2.03.0006
  10. 1000 joinedFunding-child
    1000 Förderer Bundesministerium für Bildung und Forschung |
    1000 Förderprogramm -
    1000 Fördernummer 82DZD00302; 82DZD03D03
  11. 1000 joinedFunding-child
    1000 Förderer State of Brandenburg |
    1000 Förderprogramm -
    1000 Fördernummer 82DZD00302; 82DZD03D03
  12. 1000 joinedFunding-child
    1000 Förderer European Community |
    1000 Förderprogramm -
    1000 Fördernummer 05F02; SOC 98200769
  13. 1000 joinedFunding-child
    1000 Förderer Deutsche Krebshilfe |
    1000 Förderprogramm -
    1000 Fördernummer 70-2488-Ha
  14. 1000 joinedFunding-child
    1000 Förderer SciLifeLab & Wallenberg Data Driven Life Science Program |
    1000 Förderprogramm -
    1000 Fördernummer KAW 2020.0239
  15. 1000 joinedFunding-child
    1000 Förderer Horizon 2020 |
    1000 Förderprogramm -
    1000 Fördernummer 721815; 722095
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6452654.rdf
1000 Erstellt am 2023-05-25T09:41:26.171+0200
1000 Erstellt von 317
1000 beschreibt frl:6452654
1000 Bearbeitet von 317
1000 Zuletzt bearbeitet 2023-05-25T09:41:44.427+0200
1000 Objekt bearb. Thu May 25 09:41:44 CEST 2023
1000 Vgl. frl:6452654
1000 Oai Id
  1. oai:frl.publisso.de:frl:6452654 |
1000 Sichtbarkeit Metadaten public
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