MSACL 2019 EU Abstract

Ultrahigh Resolution MS Profiling of Plasma N-Glycans in Large Type 2 Diabetes Cohorts

Elham Memarian(1,2)Emma Schoep(3)Roosmarijn Lemmers(4)Marco Bladergroen(1)Jan Nouta(1)Gerda Vreeker(1)Aloysius Lieverse(5)Femke Rutters(6)Amber van der Heijden(7)Petra Elders(7)Joline Beulens(6)Roderick Slieker(3)Eric Sijbrands(4)Leen `t Hart(3,6,8)Manfred Wuhrer(1)Mandy van Hoek(4)Viktoria Dotz(1)
(1)Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands (2)Genos Glycoscience Research Laboratory, Zagreb, Croatia(3)Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands (4)Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands(5)Department of Internal Medicine, Maxima Medical Center, Eindhoven, the Netherlands (6)Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, location VUmc University Medical Center, Amsterdam, the Netherlands(7)Department of General Practice and Elderly Care, Amsterdam University Medical Center, location VUmc University Medical Center, Amsterdam, the Netherlands (8)Department of Biomedical data Sciences, section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands

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Elham Memarian (Presenter) Leiden University Medical Center

Presenter Bio: Elham Memarian graduated in analytical chemistry from the faculty of chemistry at Shahid Beheshti University(Tehran,Iran).For her Master’s thesis she was working on the “Optimization of solid phase microextraction and electromembrane extraction techniques to measure certain pollutants and drugs”.During her studies,she was also awarded medals and honorary diplomas from international and national competitions and expositions because of her inventions.In June 2017,she started her Glysign PhD project,conducting research at Genos Ltd.,Zagreb,Croatia,and the Leiden University Medical Centre in Leiden,the Netherlands. Elham’s research is geared towards the quantification of serum protein glycosylation for patient stratification in early-onset and other diabetes types.

Relevant Financial Disclosures (within past 24 months) Grant/Research Support European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

Introduction
Type 2 diabetes mellitus(T2D)represents a major public health challenge. The total plasma N-glycome(TPNG)reflects the levels and glycosylation of major plasma glycoproteins, among which are immunoglobulins, acute-phase proteins and apolipoproteins. Our group and others recently reported on associations between TPNG and T2D, using MALDI-TOF-MS or UPLC. However, little is known on possible links between TPNG and vascular complications of T2D which are the major cause for T2D morbidity and mortality. Here, we applied our new ultrahigh-resolution MS method to assess associations of TPNG with T2D and T2D complications.
Methods
We determined the TPNG in a subsample of the Hoorn Diabetes Care System(DCS) cohort(n = 1519 T2D cases and 192 nondiabetic controls from the new Hoorn study) using our ultrahigh-resolution Fourier-transform ion cyclotron resonance mass spectrometry(MALDI-FTICR-MS) method. Blood plasma samples were randomized over 21 96-well plates, together with technical replicates. Prior to MS analysis, N-glycans were released using PNGase F. For stabilization and linkage differentiation, sialic acids were derivatized. Released glycans were purified and spotted using an automated liquid handling platform. In total, 68 individual glycan compositions were quantified after total-area normalization and summarized into derived traits representing structural features. By applying logistic regression models, we tested for associations of glycan features with case-control status and micro- or macrovascular complications, with adjustment for age, sex, and T2D risk factors.
Results
The recently developed method using MALDI-FTICR-MS improved resolution, mass accuracy, dynamic range and the signal-to-noise ratio, especially for larger glycans, in comparison to our previous MALDI-TOF workflow. The relative standard deviation over the 68 detected glycan species was on average 6.6 %, based on the relative intensities from 93 technical replicates of pooled plasma, representing total method repeatability.
Applying the new method on the DCS cohort, we were able to replicate previously reported associations of TPNG with T2D, such a decreased alpha2,3-sialylation of triantennary glycans(odds ratio(OR) = 0.47 and p = 1.12E-17) or increased alpha2,3-sialylation of various di- and tetraantennary structures(e.g. per-galactose 2,6-sialylation in diantennaries: OR = 2.36 and p = 2.54E-26), after adjustment for age and sex. Moreover, we found additional associations, e.g. for antennary fucosylation of triantennaries(OR = 1.62, p= 2.85E-07), likely a consequence of improved method sensitivity. Statistical analyses of associations between TPNG and T2D complications are ongoing.
Conclusions
Our new method improved the detection of several glycan species, thus providing possible new insights into the association between TPNG and T2D. Our results will be taken forward to improve personalized approaches in T2D and related complications in the future.