Functional Signature of LRP4 Antibodies in Myasthenia Gravis.

BACKGROUND AND OBJECTIVES: Antibodies (Abs) specific for the low-density lipoprotein receptor-related protein 4 (LRP4) occur in up to 5% of patients with myasthenia gravis (MG). The objective of this study was to profile LRP4-Ab effector actions. METHODS: We evaluated the efficacy of LRP4-specific compared with AChR-specific IgG to induce Ab-dependent cellular phagocytosis (ADCP), Ab-dependent cellular cytotoxicity (ADCC), and Ab-dependent complement deposition (ADCD). Functional features were additionally assessed in an independent AChR-Ab+ MG cohort. Levels of circulating activated complement proteins and frequency of Fc glycovariants were quantified and compared with demographically matched 19 healthy controls. RESULTS: Effector actions that required binding of Fc domains to cellular FcRs such as ADCC and ADCP were detectable for both LRP4-specific and AChR-specific Abs. In contrast to AChR-Abs, LRP4-binding Abs showed poor efficacy in inducing complement deposition. Levels of circulating activated complement proteins were not substantially increased in LRP4-Ab-positive MG. Frequency of IgG glycovariants carrying 2 sialic acid residues, indicative for anti-inflammatory IgG activity, was decreased in patients with LRP4-Ab-positive MG. DISCUSSION: LRP4-Abs are more effective in inducing cellular FcR-mediated effector mechanisms than Ab-dependent complement activation. Their functional signature is different from AChR-specific Abs.

Mapping of the gene network that regulates glycan clock of ageing.

Glycans are an essential structural component of immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation), a trait which was shown to be associated with ageing. We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in the in vitro IgG expression system. Upregulation of three genes, EEF1A1, MANBA and TNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in this in vitro expression system.

Integrated omics approach for the identification of HDL structure-function relationships in PCSK9-related familial hypercholesterolemia.

BACKGROUND: The role of proprotein convertase subtilisin/kexin type 9 (PCSK9) in dyslipidemia may go beyond its immediate effects on low-density lipoprotein receptor (LDL-R) activity. OBJECTIVE: This study aimed to assess PCSK9-derived alterations of high-density lipoprotein (HDL) physiology, which bear a potential to contribute to cardiovascular risk profile. METHODS: HDL was isolated from 33 patients with familial autosomal dominant hypercholesterolemia (FH), including those carrying PCSK9 gain-of-function (GOF) genetic variants (FH-PCSK9, n = 11), together with two groups of dyslipidemic patients employed as controls and carrying genetic variants in the LDL-R not treated (ntFH-LDLR, n = 11) and treated (tFH-LDLR, n = 11) with statins, and 11 normolipidemic controls. Biological evaluations paralleled by proteomic, lipidomic and glycomic analyses were applied to characterize functional and compositional properties of HDL. RESULTS: Multiple deficiencies in the HDL function were identified in the FH-PCSK9 group relative to dyslipidemic FH-LDLR patients and normolipidemic controls, which involved reduced antioxidative, antiapoptotic, anti-thrombotic and anti-inflammatory activities. By contrast, cellular cholesterol efflux capacity of HDL was unchanged. In addition, multiple alterations of the proteomic, lipidomic and glycomic composition of HDL were found in the FH-PCSK9 group. Remarkably, HDLs from FH-PCSK9 patients were systematically enriched in several lysophospholipids as well as in A2G2S2 (GP13) glycan and apolipoprotein A-IV. Based on network analysis of functional and compositional data, a novel mosaic structure-function model of HDL biology involving FH was developed. CONCLUSION: Several metrics of anti-atherogenic HDL functionality are altered in FH-PCSK9 patients paralleled by distinct compositional alterations. These data provide a first-ever overview of the impact of GOF PCSK9 genetic variants on structure-function relationships in HDL.

Dose imbalance of DYRK1A kinase causes systemic progeroid status in Down syndrome by increasing the un-repaired DNA damage and reducing LaminB1 levels.

BACKGROUND: People with Down syndrome (DS) show clinical signs of accelerated ageing. Causative mechanisms remain unknown and hypotheses range from the (essentially untreatable) amplified-chromosomal-instability explanation, to potential actions of individual supernumerary chromosome-21 genes. The latter explanation could open a route to therapeutic amelioration if the specific over-acting genes could be identified and their action toned-down. METHODS: Biological age was estimated through patterns of sugar molecules attached to plasma immunoglobulin-G (IgG-glycans, an established "biological-ageing-clock") in n = 246 individuals with DS from three European populations, clinically characterised for the presence of co-morbidities, and compared to n = 256 age-, sex- and demography-matched healthy controls. Isogenic human induced pluripotent stem cell (hiPSCs) models of full and partial trisomy-21 with CRISPR-Cas9 gene editing and two kinase inhibitors were studied prior and after differentiation to cerebral organoids. FINDINGS: Biological age in adults with DS is (on average) 18.4-19.1 years older than in chronological-age-matched controls independent of co-morbidities, and this shift remains constant throughout lifespan. Changes are detectable from early childhood, and do not require a supernumerary chromosome, but are seen in segmental duplication of only 31 genes, along with increased DNA damage and decreased levels of LaminB1 in nucleated blood cells. We demonstrate that these cell-autonomous phenotypes can be gene-dose-modelled and pharmacologically corrected in hiPSCs and derived cerebral organoids. Using isogenic hiPSC models we show that chromosome-21 gene DYRK1A overdose is sufficient and necessary to cause excess unrepaired DNA damage. INTERPRETATION: Explanation of hitherto observed accelerated ageing in DS as a developmental progeroid syndrome driven by DYRK1A overdose provides a target for early pharmacological preventative intervention strategies. FUNDING: Main funding came from the "Research Cooperability" Program of the Croatian Science Foundation funded by the European Union from the European Social Fund under the Operational Programme Efficient Human Resources 2014-2020, Project PZS-2019-02-4277, and the Wellcome Trust Grants 098330/Z/12/Z and 217199/Z/19/Z (UK). All other funding is described in details in the "Acknowledgements".

Comparative analysis of transferrin and IgG N-glycosylation in two human populations.

Human plasma transferrin (Tf) N-glycosylation has been mostly studied as a marker for congenital disorders of glycosylation, alcohol abuse, and hepatocellular carcinoma. However, inter-individual variability of Tf N-glycosylation is not known, mainly due to technical limitations of Tf isolation in large-scale studies. Here, we present a highly specific robust high-throughput approach for Tf purification from human blood plasma and detailed characterization of Tf N-glycosylation on the level of released glycans by ultra-high-performance liquid chromatography based on hydrophilic interactions and fluorescence detection (HILIC-UHPLC-FLD), exoglycosidase sequencing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We perform a large-scale comparative study of Tf and immunoglobulin G (IgG) N-glycosylation analysis in two human populations and demonstrate that Tf N-glycosylation is associated with age and sex, along with multiple biochemical and physiological traits. Observed association patterns differ compared to the IgG N-glycome corroborating tissue-specific N-glycosylation and specific N-glycans' role in their distinct physiological functions.

Baseline IgG-Fc N-glycosylation profile is associated with long-term outcome in a cohort of early inflammatory arthritis patients.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease for which prediction of long-term prognosis from disease's outset is not clinically feasible. The importance of immunoglobulin G (IgG) and its Fc N-glycosylation in inflammation is well-known and studies described its relevance for several autoimmune diseases, including RA. Herein we assessed the association between IgG N-glycoforms and disease prognosis at 2 years in an early inflammatory arthritis cohort. METHODS: Sera from 118 patients with early inflammatory arthritis naïve to treatment sampled at baseline were used to obtain IgG Fc glycopeptides, which were then analyzed in a subclass-specific manner by liquid chromatography coupled to mass spectrometry (LC-MS). Patients were prospectively followed and a favorable prognosis at 2 years was assessed by a combined index as remission or low disease activity (DAS28 < 3.2) and normal functionality (HAQ ≤ 0.25) while on treatment with conventional synthetic DMARDs and never used biologic DMARDs. RESULTS: We observed a significant association between high levels of IgG2/3 Fc galactosylation (effect 0.627 and adjusted p value 0.036 for the fully galactosylated glycoform H5N4F1; effect -0.551 and adjusted p value 0.04963 for the agalactosylated H3N4F1) and favorable outcome after 2 years of treatment. The inclusion of IgG glycoprofiling in a multivariate analysis to predict the outcome (with HAQ, DAS28, RF, and ACPA included in the model) did not improve the prognostic performance of the model. CONCLUSION: Pending confirmation of these findings in larger cohorts, IgG glycosylation levels could be used as a prognostic marker in early arthritis, to overcome the limitations of the current prognostic tools.

Developments and perspectives in high-throughput protein glycomics: enabling the analysis of thousands of samples.

Glycans expand the structural complexity of proteins by several orders of magnitude, resulting in a tremendous analytical challenge when including them in biomedical research. Recent glycobiological research is painting a picture in which glycans represent a crucial structural and functional component of the majority of proteins, with alternative glycosylation of proteins and lipids being an important regulatory mechanism in many biological and pathological processes. Since interindividual differences in glycosylation are extensive, large studies are needed to map the structures and to understand the role of glycosylation in human (patho)physiology. Driven by these challenges, methods have emerged, which can tackle the complexity of glycosylation in thousands of samples, also known as high-throughput (HT) glycomics. For facile dissemination and implementation of HT glycomics technology, the sample preparation, analysis, as well as data mining, need to be stable over a long period of time (months/years), amenable to automation, and available to non-specialized laboratories. Current HT glycomics methods mainly focus on protein N-glycosylation and allow to extensively characterize this subset of the human glycome in large numbers of various biological samples. The ultimate goal in HT glycomics is to gain better knowledge and understanding of the complete human glycome using methods that are easy to adapt and implement in (basic) biomedical research. Aiming to promote wider use and development of HT glycomics, here, we present currently available, emerging, and prospective methods and some of their applications, revealing a largely unexplored molecular layer of the complexity of life.

Heritability of the glycan clock of biological age.

Immunoglobulin G is posttranslationally modified by the addition of complex N-glycans affecting its function and mediating inflammation at multiple levels. IgG glycome composition changes with age and health in a predictive pattern, presumably due to inflammaging. As a result, a novel biological aging biomarker, glycan clock of age, was developed. Glycan clock of age is the first of biological aging clocks for which multiple studies showed a possibility of clock reversal even with simple lifestyle interventions. However, none of the previous studies determined to which extent the glycan clock can be turned, and how much is fixed by genetic predisposition. To determine the contribution of genetic and environmental factors to phenotypic variation of the glycan clock, we performed heritability analysis on two TwinsUK female cohorts. IgG glycans from monozygotic and dizygotic twin pairs were analyzed by UHPLC and glycan age was calculated using the glycan clock. In order to determine additive genetic, shared, and unique environmental contributions, a classical twin design was applied. Heritability of the glycan clock was calculated for participants of one cross-sectional and one longitudinal cohort with three time points to assess the reliability of measurements. Heritability estimate for the glycan clock was 39% on average, suggesting a moderate contribution of additive genetic factors (A) to glycan clock variation. Remarkably, heritability estimates remained approximately the same in all time points of the longitudinal study, even though IgG glycome composition changed substantially. Most environmental contributions came from shared environmental factors (C), with unique environmental factors (E) having a minor role. Interestingly, heritability estimates nearly doubled, to an average of 71%, when we included age as a covariant. This intervention also inflated the estimates of unique environmental factors contributing to glycan clock variation. A complex interplay between genetic and environmental factors defines alternative IgG glycosylation during aging and, consequently, dictates the glycan clock's ticking. Apparently, environmental factors (including lifestyle choices) have a strong impact on the biological age measured with the glycan clock, which additionally clarifies why this aging clock is one of the most potent biomarkers of biological aging.

A Multi-Factorial Observational Study on Sequential Fecal Microbiota Transplant in Patients with Medically Refractory Clostridioides difficile Infection.

Fecal microbiota transplantation (FMT) is highly effective in recurrent Clostridioides difficile infection (CDI); increasing evidence supports FMT in severe or fulminant Clostridioides difficile infection (SFCDI). However, the multifactorial mechanisms that underpin the efficacy of FMT are not fully understood. Systems biology approaches using high-throughput technologies may help with mechanistic dissection of host-microbial interactions. Here, we have undertaken a deep phenomics study on four adults receiving sequential FMT for SFCDI, in which we performed a longitudinal, integrative analysis of multiple host factors and intestinal microbiome changes. Stool samples were profiled for changes in gut microbiota and metabolites and blood samples for alterations in targeted epigenomic, metabonomic, glycomic, immune proteomic, immunophenotyping, immune functional assays, and T-cell receptor (TCR) repertoires, respectively. We characterised temporal trajectories in gut microbial and host immunometabolic data sets in three responders and one non-responder to sequential FMT. A total of 562 features were used for analysis, of which 78 features were identified, which differed between the responders and the non-responder. The observed dynamic phenotypic changes may potentially suggest immunosenescent signals in the non-responder and may help to underpin the mechanisms accompanying successful FMT, although our study is limited by a small sample size and significant heterogeneity in patient baseline characteristics. Our multi-omics integrative longitudinal analytical approach extends the knowledge regarding mechanisms of efficacy of FMT and highlights preliminary novel signatures, which should be validated in larger studies.

Significant Associations of IgG Glycan Structures With Chronic Graft-Versus-Host Disease Manifestations: Results of the Cross-Sectional NIH Cohort Study.

Chronic graft-versus-host disease (cGvHD) is a systemic alloimmune and autoimmune disorder and a major late complication of allogeneic hematopoietic stem cell transplantation (alloHSCT). The disease is characterized by an altered homeostasis of the humoral immune response. Immunoglobulin G (IgG) glycoprotein is the main effector molecule of the humoral immune response. Changes in IgG glycosylation are associated with a number of autoimmune diseases. IgG glycosylation analysis was done by the means of liquid chromatography in the National Institutes of Health (NIH) cohort of 213 cGvHD patients. The results showed statistically significant differences with regards to cGvHD NIH joint/fascia and skin score, disease activity and intensity of systemic immunosuppression. ROC analysis confirmed that IgG glycosylation increases specificity and sensitivity of models using laboratory parameters and markers of inflammation associated with cGvHD (eosinophil count, complement components C3 and C4 and inflammation markers: albumin, CRP and thrombocyte count). This research shows that IgG glycosylation may play a significant role in cGvHD pathology. Further research could contribute to the understanding of the disease biology and lead to the clinical biomarker development to allow personalized approaches to chronic GvHD therapy.

Multiomics Profiling Reveals Signatures of Dysmetabolism in Urban Populations in Central India.

BACKGROUND: Non-communicable diseases (NCDs) have become a major cause of morbidity and mortality in India. Perturbation of host-microbiome interactions may be a key mechanism by which lifestyle-related risk factors such as tobacco use, alcohol consumption, and physical inactivity may influence metabolic health. There is an urgent need to identify relevant dysmetabolic traits for predicting risk of metabolic disorders, such as diabetes, among susceptible Asian Indians where NCDs are a growing epidemic. METHODS: Here, we report the first in-depth phenotypic study in which we prospectively enrolled 218 adults from urban and rural areas of Central India and used multiomic profiling to identify relationships between microbial taxa and circulating biomarkers of cardiometabolic risk. Assays included fecal microbiota analysis by 16S ribosomal RNA gene amplicon sequencing, quantification of serum short chain fatty acids by gas chromatography-mass spectrometry, and multiplex assaying of serum diabetic proteins, cytokines, chemokines, and multi-isotype antibodies. Sera was also analysed for N-glycans and immunoglobulin G Fc N-glycopeptides. RESULTS: Multiple hallmarks of dysmetabolism were identified in urbanites and young overweight adults, the majority of whom did not have a known diagnosis of diabetes. Association analyses revealed several host-microbe and metabolic associations. CONCLUSIONS: Host-microbe and metabolic interactions are differentially shaped by body weight and geographic status in Central Indians. Further exploration of these links may help create a molecular-level map for estimating risk of developing metabolic disorders and designing early interventions.

Changes in IgA-targeted microbiota following fecal transplantation for recurrent Clostridioides difficile infection.

Secretory immunoglobulin A (IgA) interacts with intestinal microbiota and promotes mucosal homeostasis. IgA-bacteria interactions are altered during inflammatory diseases, but how these interactions are shaped by bacterial, host, and environmental factors remains unclear. In this study, we utilized IgA-SEQ to profile IgA-bound fecal bacteria in 48 recurrent Clostridioides difficile patients before and after successful fecal microbiota transplantation (FMT) to gain further insight. Prior to FMT, Escherichia coli was the most highly IgA-targeted taxon; following restoration of the microbiota by FMT, highly IgA-targeted taxa included multiple Firmicutes species. Post-FMT IgA-targeting was unaffected by the route of FMT delivery (colonoscopy versus capsule), suggesting that both methods lead to the establishment of healthy immune-bacterial interactions in the gut. Interestingly, IgA-targeting in FMT recipients closely resembled the IgA-targeting patterns of the donors, and fecal donor identity was significantly associated with IgA-targeting of the recipient microbiota. These data support the concept that intrinsic bacterial properties drive IgA recognition across genetically distinct human hosts. Together, this study suggests that IgA-bacterial interactions are reestablished in human FMT recipients to resemble that of the healthy fecal donor.

A strategy to incorporate prior knowledge into correlation network cutoff selection.

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization.

Global variability of the human IgG glycome.

Immunoglobulin G (IgG) is the most abundant serum antibody which structural characteristics and effector functions are modulated through the attachment of various sugar moieties called glycans. Composition of the IgG N-glycome changes with age of an individual and in different diseases. Variability of IgG glycosylation within a population is well studied and is known to be affected by both genetic and environmental factors. However, global inter-population differences in IgG glycosylation have never been properly addressed. Here we present population-specific N-glycosylation patterns of IgG, analyzed in 5 different populations totaling 10,482 IgG glycomes, and of IgG's fragment crystallizable region (Fc), analyzed in 2,579 samples from 27 populations sampled across the world. Country of residence associated with many N-glycan features and the strongest association was with monogalactosylation where it explained 38% of variability. IgG monogalactosylation strongly correlated with the development level of a country, defined by United Nations health and socioeconomic development indicators, and with the expected lifespan. Subjects from developing countries had low levels of IgG galactosylation, characteristic for inflammation and ageing. Our results suggest that citizens of developing countries may be exposed to environmental factors that can cause low-grade chronic inflammation and the apparent increase in biological age.

Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference.

Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, here, we quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms: Liquid Chromatography - ElectroSpray Ionization - Mass Spectrometry (LC-ESI-MS), Ultra High Performance Liquid Chromatography with Fluorescence Detection (UHPLC-FLD), and Matrix Assisted Laser Desorption Ionization - Furier Transform Ion Cyclotron Resonance - Mass Spectrometry (MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the 'Probabilistic Quotient' method followed by log-transformation, irrespective of the measurement platform. This recommendation is further supported by an additional analysis, where we ranked normalization methods based on their statistical associations with age, a factor known to associate with glycomics measurements.

Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases.

Effector functions of immunoglobulin G (IgG) are regulated by the composition of a glycan moiety, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the underlying mechanisms. We performed a genome-wide association study of IgG N-glycosylation (N = 8090) and, using a data-driven network approach, suggested how associated loci form a functional network. We confirmed in vitro that knockdown of IKZF1 decreases the expression of fucosyltransferase FUT8, resulting in increased levels of fucosylated glycans, and suggest that RUNX1 and RUNX3, together with SMARCB1, regulate expression of glycosyltransferase MGAT3. We also show that variants affecting the expression of genes involved in the regulation of glycoenzymes colocalize with variants affecting risk for inflammatory diseases. This study provides new evidence that variation in key transcription factors coupled with regulatory variation in glycogenes modifies IgG glycosylation and has influence on inflammatory diseases.

Potential Novel Biomarkers in Chronic Graft-Versus-Host Disease.

Prognostic, diagnostic or predictive biomarkers are urgently needed for assessment of chronic graft-versus-host disease (cGvHD), a major risk for patients undergoing allogeneic hematopoietic stem cell transplantation. The main goal of this review generated within the COST Action EUROGRAFT "Integrated European Network on Chronic Graft Versus Host Disease" was to identify potential novel biomarkers for cGvHD besides the widely accepted molecular and cellular biomarkers. Thus, the focus was on cellular biomarkers, alloantibodies, glycomics, endothelial derived particles, extracellular vesicles, microbiome, epigenetic and neurologic changes in cGvHD patients. Both host-reactive antibodies in general, and particularly alloantibodies have been associated with cGvHD and require further consideration. Glycans attached to IgG modulate its activity and represent a promising predictive and/or stratification biomarker for cGVHD. Furthermore, epigenetic changes such as microRNAs and DNA methylation represent potential biomarkers for monitoring cGvHD patients and novel targets for developing new treatment approaches. Finally, the microbiome likely affects the pathophysiology of cGvHD; bacterial strains as well as microbial metabolites could display potential biomarkers for dysbiosis and risk for the development of cGvHD. In summary, although there are no validated biomarkers currently available for clinical use to better inform on the diagnosis, prognosis or prediction of outcome for cGvHD, many novel sources of potential markers have shown promise and warrant further investigation using well characterized, multi-center patient cohorts.

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods.

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods.

Heritability of Human Plasma N-Glycome.

The N-glycosylation profile of total human plasma proteins could be a useful biomarker for various pathological states. Reliable high-throughput methods for such profiling have been developed. However, studies of relative importance of genetic and environmental factors in regulating plasma N-glycome are scarce. The aim of our study was to determine the role of genetic factors in phenotypic variation of plasma N-glycan profile through the estimates of its heritability. Thirty-nine total plasma N-glycome traits were analyzed in 2816 individuals from the TwinsUK data set. For the majority of the traits, high heritability estimates (>50%) were obtained pointing at a significant contribution of genetic factors in plasma N-glycome variation, especially for glycans mostly attached to immunoglobulins. We have also found several structures with higher environmental contribution to their variation.