Defining the genetic control of human blood plasma N-glycome using genome-wide association study

ST3 beta-galactoside alpha-2,3-sialyltransferase 4 (St3gal4) deficiency reveals correlations among alkaline phosphatase activity, metabolic parameters, and fear-related behavior in mice

ST3 beta-galactoside alpha-2,3-sialyltransferase 4 (ST3GAL4) is a sialyltransferase involved in the biosynthesis of alpha2,3-sialic acid on glycoproteins and glycolipids. In mice, St3gal4 gene expression plays a crucial role in modulating epilepsy and anxiety/depression through its expression in thalamic neurons. Genome-wide association studies (GWAS) have identified several peripheral metabolic traits strongly associated with ST3GAL4 in humans. However, whether the symptoms observed in mice are associated with metabolic changes remains unclear. This study investigated the effects of St3gal4 deficiency on the same metabolic parameters in mice as those in humans. The parameters examined included body weight, plasma biochemistry, specifically alkaline phosphatase (ALP), protein, and cholesterol levels, and free amino acids profiles, resulting in elevated ALP and reduced tryptophan and total cholesterol (T-Cho) levels in St3gal4-knockout (KO) mice. Additionally, clearance of blood glucose was delayed in KO male mice. These findings suggest mouse St3gal4 deficiency correlated with modulated ALP, tryptophan, and T-Cho levels in the plasma. Next, brain ALP activity was compared between St3gal4-KO mice and wild-type (WT) mice, focusing on the thalamus. Fear conditioning tests assessed the relationship between behavior and ALP activity in plasma and brain. In KO mice, the enhanced tone freezing positively correlated with plasma ALP levels. Conversely, thalamic ALP activity was greatly reduced in KO mice, negatively correlating with plasma ALP. These findings suggest that mouse St3gal4 deficiency influences ALP activity in both thalamus and plasma, associating with emotional behaviors and metabolic changes.

The genetic landscape of neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes

In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.

Glycosylation in aging and neurodegenerative diseases

Aging, a complex biological process, involves the progressive decline of physiological functions across various systems, leading to increased susceptibility to neurodegenerative diseases. In society, demographic aging imposes significant economic and social burdens due to these conditions. This review specifically examines the association of protein glycosylation with aging and neurodegenerative diseases. Glycosylation, a critical post-translational modification, influences numerous aspects of protein function that are pivotal in aging and the pathophysiology of diseases such as Alzheimer's disease, Parkinson's disease, and other neurodegenerative conditions. We highlight the alterations in glycosylation patterns observed during aging, their implications in the onset and progression of neurodegenerative diseases, and the potential of glycosylation profiles as biomarkers for early detection, prognosis, and monitoring of these age-associated conditions, and delve into the mechanisms of glycosylation. Furthermore, this review explores their role in regulating protein function and mediating critical biological interactions in these diseases. By examining the changes in glycosylation profiles associated with each part, this review underscores the potential of glycosylation research as a tool to enhance our understanding of aging and its related diseases.

The Human Blood N-Glycome: Unraveling Disease Glycosylation Patterns

Most of the proteins in the circulation are N-glycosylated, shaping together the total blood N-glycome (TBNG). Glycosylation is known to affect protein function, stability, and clearance. The TBNG is influenced by genetic, environmental, and metabolic factors, in part epigenetically imprinted, and responds to a variety of bioactive signals including cytokines and hormones. Accordingly, physiological and pathological events are reflected in distinct TBNG signatures. Here, we assess the specificity of the emerging disease-associated TBNG signatures with respect to a number of key glycosylation motifs including antennarity, linkage-specific sialylation, fucosylation, as well as expression of complex, hybrid-type and oligomannosidic N-glycans, and show perplexing complexity of the glycomic dimension of the studied diseases. Perspectives are given regarding the protein- and site-specific analysis of N-glycosylation, and the dissection of underlying regulatory layers and functional roles of blood protein N-glycosylation.

Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping

Proteogenomics studies generate hypotheses on protein function and provide genetic evidence for drug target prioritization. Most previous work has been conducted using affinity-based proteomics approaches. These technologies face challenges, such as uncertainty regarding target identity, non-specific binding, and handling of variants that affect epitope affinity binding. Mass spectrometry-based proteomics can overcome some of these challenges. Here we report a pQTL study using the Proteograph™ Product Suite workflow (Seer, Inc.) where we quantify over 18,000 unique peptides from nearly 3000 proteins in more than 320 blood samples from a multi-ethnic cohort in a bottom-up, peptide-centric, mass spectrometry-based proteomics approach. We identify 184 protein-altering variants in 137 genes that are significantly associated with their corresponding variant peptides, confirming target specificity of co-associated affinity binders, identifying putatively causal cis-encoded proteins and providing experimental evidence for their presence in blood, including proteins that may be inaccessible to affinity-based proteomics.

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

Genetic control of N-glycosylation of human blood plasma proteins

Glycosylation is an important protein modification, which influences the physical and chemical properties as well as biological function of these proteins. Large-scale population studies have shown that the levels of various plasma protein N-glycans are associated with many multifactorial human diseases. Observed associations between protein glycosylation levels and human diseases have led to the conclusion that N-glycans can be considered a potential source of biomarkers and therapeutic targets. Although biochemical pathways of glycosylation are well studied, the understanding of the mechanisms underlying general and tissue-specific regulation of these biochemical reactions in vivo is limited. This complicates both the interpretation of the observed associations between protein glycosylation levels and human diseases, and the development of glycan-based biomarkers and therapeutics. By the beginning of the 2010s, high-throughput methods of N-glycome profiling had become available, allowing research into the genetic control of N-glycosylation using quantitative genetics methods, including genome-wide association studies (GWAS). Application of these methods has made it possible to find previously unknown regulators of N-glycosylation and expanded the understanding of the role of N-glycans in the control of multifactorial diseases and human complex traits. The present review considers the current knowledge of the genetic control of variability in the levels of N-glycosylation of plasma proteins in human populations. It briefly describes the most popular physical-chemical methods of N-glycome profiling and the databases that contain genes involved in the biosynthesis of N-glycans. It also reviews the results of studies of environmental and genetic factors contributing to the variability of N-glycans as well as the mapping results of the genomic loci of N-glycans by GWAS. The results of functional in vitro and in silico studies are described. The review summarizes the current progress in human glycogenomics and suggests possible directions for further research.

Challenges and opportunities for omics-based precision medicine in chronic low back pain

PURPOSE

Chronic low back pain (cLBP) is a common health condition worldwide and a leading cause of disability with an estimated lifetime prevalence of 80-90% in industrialized countries. However, we have had limited success in treating cLBP likely due to its non-specific heterogeneous nature that goes beyond detectable anatomical changes. We propose that omics technologies as precision medicine tools are well suited to provide insight into its pathophysiology and provide diagnostic markers and therapeutic targets. Therefore, in this review, we explore the current state of omics technologies in the diagnosis and classification of cLBP. We identify factors that may serve as markers to differentiate between acute and chronic cases of low back pain (LBP). Finally, we also discuss some challenges that must be overcome to successfully apply precision medicine to the diagnosis and treatment of cLBP.

METHODS

A literature search for the current applications of omics technologies to chronic low back pain was performed using the following search terms- "back pain," "low back pain," "proteomics," "transcriptomics", "epigenomics," "genomics," "omics." We reviewed molecular markers identified from 35 studies which hold promise in providing information regarding molecular insights into cLBP.

RESULTS

GWAS studies have found evidence for the role of single nucleotide polymorphisms (SNPs) associated with pain pathways in individuals with cLBP. Epigenomic modifications in patients with cLBP have been found to be enriched among genes involved in immune signaling and inflammation. Transcriptomics profiles of patients with cLBP show multiple lines of evidence for the role of inflammation in cLBP. The glycomics profiles of patients with cLBP are similar to those of patients with inflammatory conditions. Proteomics and microbiomics show promise but have limited studies currently.

CONCLUSION

Omics technologies have identified associations between inflammatory and pain pathways in the pathophysiology of cLBP. However, in order to integrate information across the range of studies, it is important for the field to identify and adopt standardized definitions of cLBP and control patients. Additionally, most papers have applied a single omics method to a sampling of cLBP patients which have yielded limited insight into the pathophysiology of cLBP. Therefore, we recommend a multi-omics approach applied to large global consortia for advancing subphenotyping and better management of cLBP, via improved identification of diagnostic markers and therapeutic targets.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Role of Fc Core Fucosylation in the Effector Function of IgG1 Antibodies

The presence of fucose on IgG1 Asn-297 N-linked glycan is the modification of the human IgG1 Fc structure with the most significant impact on FcɣRIII affinity. It also significantly enhances the efficacy of antibody dependent cellular cytotoxicity (ADCC) by natural killer (NK) cells in vitro, induced by IgG1 therapeutic monoclonal antibodies (mAbs). The effect of afucosylation on ADCC or antibody dependent phagocytosis (ADCP) mediated by macrophages or polymorphonuclear neutrophils (PMN) is less clear. Evidence for enhanced efficacy of afucosylated therapeutic mAbs in vivo has also been reported. This has led to the development of several therapeutic antibodies with low Fc core fucose to treat cancer and inflammatory diseases, seven of which have already been approved for clinical use. More recently, the regulation of IgG Fc core fucosylation has been shown to take place naturally during the B-cell immune response: A decrease in α-1,6 fucose has been observed in polyclonal, antigen-specific IgG1 antibodies which are generated during alloimmunization of pregnant women by fetal erythrocyte or platelet antigens and following infection by some enveloped viruses and parasites. Low IgG1 Fc core fucose on antigen-specific polyclonal IgG1 has been linked to disease severity in several cases, such as SARS-CoV 2 and Dengue virus infection and during alloimmunization, highlighting the in vivo significance of this phenomenon. This review aims to summarize the current knowledge about human IgG1 Fc core fucosylation and its regulation and function in vivo, in the context of both therapeutic antibodies and the natural immune response. The parallels in these two areas are informative about the mechanisms and in vivo effects of Fc core fucosylation, and may allow to further exploit the desired properties of this modification in different clinical contexts.

Association Between Human Gut Microbiome and N-Glycan Composition of Total Plasma Proteome

Being one of the most dynamic entities in the human body, glycosylation of proteins fine-tunes the activity of the organismal machinery, including the immune system, and mediates the interaction with the human microbial consortium, typically represented by the gut microbiome. Using data from 194 healthy individuals, we conducted an associational study to uncover potential relations between the gut microbiome and the blood plasma N-glycome, including N-glycome of immunoglobulin G. While lacking strong linkages on the multivariate level, we were able to identify associations between alpha and beta microbiome diversity and the blood plasma N-glycome profile. Moreover, for two bacterial genera, namely, Bilophila and Clostridium innocuum, significant associations with specific glycans were also shown. The study’s results suggest a non-trivial, possibly weak link between the total plasma N-glycome and the gut microbiome, predominantly involving glycans related to the immune system proteins, including immunoglobulin G. Further studies of glycans linked to microbiome-related proteins in well-selected patient groups are required to conclusively establish specific associations.

Genetic regulation of post-translational modification of two distinct proteins

Post-translational modifications diversify protein functions and dynamically coordinate their signalling networks, influencing most aspects of cell physiology. Nevertheless, their genetic regulation or influence on complex traits is not fully understood. Here, we compare the genetic regulation of the same PTM of two proteins - glycosylation of transferrin and immunoglobulin G (IgG). By performing genome-wide association analysis of transferrin glycosylation, we identify 10 significantly associated loci, 9 of which were not reported previously. Comparing these with IgG glycosylation-associated genes, we note protein-specific associations with genes encoding glycosylation enzymes (transferrin - MGAT5, ST3GAL4, B3GAT1; IgG - MGAT3, ST6GAL1), as well as shared associations (FUT6, FUT8). Colocalisation analyses of the latter suggest that different causal variants in the FUT genes regulate fucosylation of the two proteins. Glycosylation of these proteins is thus genetically regulated by both shared and protein-specific mechanisms.

Associations Between Genetically Predicted Plasma N-Glycans and Prostate Cancer Risk: Analysis of Over 140,000 European Descendants

BACKGROUND

Previous studies suggest a potential link between glycosylation and prostate cancer. To better characterize the relationship between the two, we performed a study to comprehensively evaluate the associations between genetically predicted blood plasma N-glycan levels and prostate cancer risk.

METHODS

Using genetic variants associated with N-glycan levels as instruments, we evaluated the associations between levels of 138 plasma N-glycans and prostate cancer risk. We analyzed data of 79,194 cases and 61,112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL.

RESULTS

We identified three N-glycans with genetically predicted levels in plasma to be associated with prostate cancer risk after Bonferroni correction. The estimated odds ratios (95% confidence intervals) were 1.29 (1.20-1.40), 0.80 (0.74-0.88), and 0.79 (0.72-0.87) for PGP18, PGP33, and PGP109, respectively, per every one standard deviation increase in genetically predicted levels of N-glycan. However, the instruments for these N-glycans only involved one to two variants. The proportions of variations that can be explained by the instruments range from 1.58% to 2.95% for these three N-glycans.

CONCLUSION

We observed associations between genetically predicted levels of three N-glycans PGP18, PGP33, and PGP109 and prostate cancer risk. Given the correlated nature of the N-glycans and that many N-glycans share genetic loci, pleiotropy is a major concern. Future work is warranted to better characterize the relationship between N-glycans and prostate cancer.

Correcting for sparsity and interdependence in glycomics by accounting for glycan biosynthesis

Glycans are fundamental cellular building blocks, involved in many organismal functions. Advances in glycomics are elucidating the essential roles of glycans. Still, it remains challenging to properly analyze large glycomics datasets, since the abundance of each glycan is dependent on many other glycans that share many intermediate biosynthetic steps. Furthermore, the overlap of measured glycans can be low across samples. We address these challenges with GlyCompare, a glycomic data analysis approach that accounts for shared biosynthetic steps for all measured glycans to correct for sparsity and non-independence in glycomics, which enables direct comparison of different glycoprofiles and increases statistical power. Using GlyCompare, we study diverse N-glycan profiles from glycoengineered erythropoietin. We obtain biologically meaningful clustering of mutant cell glycoprofiles and identify knockout-specific effects of fucosyltransferase mutants on tetra-antennary structures. We further analyze human milk oligosaccharide profiles and find mother’s fucosyltransferase-dependent secretor-status indirectly impact the sialylation. Finally, we apply our method on mucin-type O-glycans, gangliosides, and site-specific compositional glycosylation data to reveal tissues and disease-specific glycan presentations. Our substructure-oriented approach will enable researchers to take full advantage of the growing power and size of glycomics data.

Glycomics can uncover important molecular changes but measured glycans are highly interconnected and incompatible with common statistical methods, introducing pitfalls during analysis. Here, the authors develop an approach to identify glycan dependencies across samples to facilitate comparative glycomics.

Systems glycobiology for discovering drug targets, biomarkers, and rational designs for glyco-immunotherapy

Cancer immunotherapy has revolutionized treatment and led to an unprecedented wave of immuno-oncology research during the past two decades. In 2018, two pioneer immunotherapy innovators, Tasuku Honjo and James P. Allison, were awarded the Nobel Prize for their landmark cancer immunotherapy work regarding “cancer therapy by inhibition of negative immune regulation” –CTLA4 and PD-1 immune checkpoints. However, the challenge in the coming decade is to develop cancer immunotherapies that can more consistently treat various patients and cancer types. Overcoming this challenge requires a systemic understanding of the underlying interactions between immune cells, tumor cells, and immunotherapeutics. The role of aberrant glycosylation in this process, and how it influences tumor immunity and immunotherapy is beginning to emerge. Herein, we review current knowledge of miRNA-mediated regulatory mechanisms of glycosylation machinery, and how these carbohydrate moieties impact immune cell and tumor cell interactions. We discuss these insights in the context of clinical findings and provide an outlook on modulating the regulation of glycosylation to offer new therapeutic opportunities. Finally, in the coming age of systems glycobiology, we highlight how emerging technologies in systems glycobiology are enabling deeper insights into cancer immuno-oncology, helping identify novel drug targets and key biomarkers of cancer, and facilitating the rational design of glyco-immunotherapies. These hold great promise clinically in the immuno-oncology field.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

BACKGROUND

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

RESULTS

Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

CONCLUSIONS

Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication

Characteristically, cells must sense and respond to environmental cues. Despite the importance of cell-cell communication, our understanding remains limited and often lacks glycans. Glycans decorate proteins and cell membranes at the cell-environment interface, and modulate intercellular communication, from development to pathogenesis. Providing further challenges, glycan biosynthesis and cellular behavior are co-regulating systems. Here, we discuss how glycosylation contributes to extracellular responses and signaling. We further organize approaches for disentangling the roles of glycans in multicellular interactions using newly available datasets and tools, including glycan biosynthesis models, omics datasets, and systems-level analyses. Thus, emerging tools in big data analytics and systems biology are facilitating novel insights on glycans and their relationship with multicellular behavior.

Replication of 15 loci involved in human plasma protein N-glycosylation in 4802 samples from four cohorts

Human protein glycosylation is a complex process, and its in vivo regulation is poorly understood. Changes in glycosylation patterns are associated with many human diseases and conditions. Understanding the biological determinants of protein glycome provides a basis for future diagnostic and therapeutic applications. Genome-wide association studies (GWAS) allow to study biology via a hypothesis-free search of loci and genetic variants associated with a trait of interest. Sixteen loci were identified by three previous GWAS of human plasma proteome N-glycosylation. However, the possibility that some of these loci are false positives needs to be eliminated by replication studies, which have been limited so far. Here, we use the largest set of samples so far (4802 individuals) to replicate the previously identified loci. For all but one locus, the expected replication power exceeded 95%. Of the 16 loci reported previously, 15 were replicated in our study. For the remaining locus (near the KREMEN1 gene), the replication power was low, and hence, replication results were inconclusive. The very high replication rate highlights the general robustness of the GWAS findings as well as the high standards adopted by the community that studies genetic regulation of protein glycosylation. The 15 replicated loci present a good target for further functional studies. Among these, eight loci contain genes encoding glycosyltransferases: MGAT5, B3GAT1, FUT8, FUT6, ST6GAL1, B4GALT1, ST3GAL4 and MGAT3. The remaining seven loci offer starting points for further functional follow-up investigation into molecules and mechanisms that regulate human protein N-glycosylation in vivo.

Lectin and Liquid Chromatography-Based Methods for Immunoglobulin (G) Glycosylation Analysis

Immunoglobulin (Ig) glycosylation has been shown to dramatically affect its structure and effector functions. Ig glycosylation changes have been associated with different diseases and show a promising biomarker potential for diagnosis and prognosis of disease advancement. On the other hand, therapeutic biomolecules based on structural and functional features of Igs demand stringent quality control during the production process to ensure their safety and efficacy. Liquid chromatography (LC) and lectin-based methods are routinely used in Ig glycosylation analysis complementary to other analytical methods, e.g., mass spectrometry and capillary electrophoresis. This chapter covers analytical approaches based on LC and lectins used in low- and high-throughput N- and O-glycosylation analysis of Igs, with the focus on immunoglobulin G (IgG) applications. General principles and practical examples of the most often used LC methods for Ig purification are described, together with typical workflows for N- and O-glycan analysis on the level of free glycans, glycopeptides, subunits, or intact Igs. Lectin chromatography is a historical approach for the analysis of lectin-carbohydrate interactions and glycoprotein purification but is still being used as a valuable tool in Igs purification and glycan analysis. On the other hand, lectin microarrays have found their application in the rapid screening of glycan profiles on intact proteins.

Immunoglobulin G Glycosylation Changes in Aging and Other Inflammatory Conditions

Among the multiple roles played by protein glycosylation, the fine regulation of biological interactions is one of the most important. The asparagine 297 (Asn₂₉₇) of IgG heavy chains is decorated by a diantennary glycan bearing a number of galactose and sialic acid residues on the branches ranging from 0 to 2. In addition, the structure can present core-linked fucose and/or a bisecting GlcNAc. In many inflammatory and autoimmune conditions, as well as in metabolic, cardiovascular, infectious, and neoplastic diseases, the IgG Asn₂₉₇-linked glycan becomes less sialylated and less galactosylated, leading to increased expression of glycans terminating with GlcNAc. These conditions alter also the presence of core-fucose and bisecting GlcNAc. Importantly, similar glycomic alterations are observed in aging. The common condition, shared by the above-mentioned pathological conditions and aging, is a low-grade, chronic, asymptomatic inflammatory state which, in the case of aging, is known as inflammaging. Glycomic alterations associated with inflammatory diseases often precede disease onset and follow remission. The aberrantly glycosylated IgG glycans associated with inflammation and aging can sustain inflammation through different mechanisms, fueling a vicious loop. These include complement activation, Fcγ receptor binding, binding to lectin receptors on antigen-presenting cells, and autoantibody reactivity. The complex molecular bases of the glycomic changes associated with inflammation and aging are still poorly understood.

Genetic Regulation of Immunoglobulin G Glycosylation

Defining the genetic components that control glycosylation of the human immunoglobulin G (IgG) is an ongoing effort, which has so far been addressed by means of heritability, linkage and genome-wide association studies (GWAS). Unlike the synthesis of proteins, N-glycosylation biosynthesis is not a template-driven process, but rather a complex process regulated by both genetic and environmental factors. Current heritability studies have shown that while up to 75% of the variation in levels of some IgG glycan traits can be explained by genetics, some glycan traits are completely defined by environmental influences. Advances in both high-throughput genotyping and glycan quantification methods have enabled genome-wide association studies that are increasingly used to estimate associations of millions of single-nucleotide polymorphisms and glycosylation traits. Using this method, 18 genomic regions have so far been robustly associated with IgG N-glycosylation, discovering associations with genes encoding glycosyltransferases, but also transcription factors, co-factors, membrane transporters and other genes with no apparent role in IgG glycosylation. Further computational analyses have shown that IgG glycosylation is likely to be regulated through the expression of glycosyltransferases, but have also for the first time suggested which transcription factors are involved in the process. Moreover, it was also shown that IgG glycosylation and inflammatory diseases share common underlying causal genetic variants, suggesting that studying genetic regulation of IgG glycosylation helps not only to better understand this complex process but can also contribute to understanding why glycans are changed in disease. However, further studies are needed to unravel whether changes in IgG glycosylation are causing these diseases or the changes in the glycome are caused by the disease.

Glycosylation and Aging

Human lifespan has increased significantly in the last 200 years, emphasizing our need to age healthily. Insights into molecular mechanisms of aging might allow us to slow down its rate or even revert it. Similar to aging, glycosylation is regulated by an intricate interplay of genetic and environmental factors. The dynamics of glycopattern variation during aging has been mostly explored for plasma/serum and immunoglobulin G (IgG) N-glycome, as we describe thoroughly in this chapter. In addition, we discuss the potential functional role of agalactosylated IgG glycans in aging, through modulation of inflammation level, as proposed by the concept of inflammaging. We also comment on the potential to use the plasma/serum and IgG N-glycome as a biomarker of healthy aging and on the interventions that modulate the IgG glycopattern. Finally, we discuss the current knowledge about animal models for human plasma/serum and IgG glycosylation and mention other, less explored, instances of glycopattern changes during organismal aging and cellular senescence.

The GWAS-MAP platform for aggregation of results of genome-wide association studies and the GWAS-MAP|homo database of 70 billion genetic associations of human traits

Hundreds of genome-wide association studies (GWAS) of human traits are performed each year. The results of GWAS are often published in the form of summary statistics. Information from summary statistics can be used for multiple purposes – from fundamental research in biology and genetics to the search for potential biomarkers and therapeutic targets. While the amount of GWAS summary statistics collected by the scientific community is rapidly increasing, the use of this data is limited by the lack of generally accepted standards. In particular, the researchers who would like to use GWAS summary statistics in their studies have to become aware that the data are scattered across multiple websites, are presented in a variety of formats, and, often, were not quality controlled. Moreover, each available summary statistics analysis tools will ask for data to be presented in their own internal format. To address these issues, we developed GWAS-MAP, a high-throughput platform for aggregating, storing, analyzing, visualizing and providing access to a database of big data that result from region- and genome-wide association studies. The database currently contains information on more than 70 billion associations between genetic variants and human diseases, quantitative traits, and “omics” traits. The GWAS-MAP platform and database can be used for studying the etiology of human diseases, building predictive risk models and finding potential biomarkers and therapeutic interventions. In order to demonstrate a typical application of the platform as an approach for extracting new biological knowledge and establishing mechanistic hypotheses, we analyzed varicose veins, a disease affecting on average every third adult in Russia. The results of analysis confirmed known epidemiologic associations for this disease and led us to propose a hypothesis that increased levels of MICB and CD209 proteins in human plasma may increase susceptibility to varicose veins.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.

Pleiotropic ZIP8 A391T implicates abnormal manganese homeostasis in complex human disease

ZIP8 is a metal transporter with a role in manganese (Mn) homeostasis. A common genetic variant in ZIP8 (rs13107325; A391T) ranks in the top 10 of pleiotropic SNPs identified in GWAS; A391T has associations with an increased risk of schizophrenia, obesity, Crohn’s disease, and reduced blood Mn. Here, we used CRISPR/Cas9-mediated knockin (KI) to generate a mouse model of ZIP8 A391T (Zip8 393T-KI mice). Recapitulating the SNP association with blood Mn, blood Mn was reduced in Zip8 393T-KI mice. There was restricted abnormal tissue Mn homeostasis, with decreases in liver and kidney Mn and a reciprocal increase in biliary Mn, providing in vivo evidence of hypomorphic Zip8 function. Upon challenge in a chemically induced colitis model, male Zip8 393T-KI mice exhibited enhanced disease susceptibility. ZIP8 391-Thr associated with reduced triantennary plasma N-glycan species in a population-based cohort to define a genotype-specific glycophenotype hypothesized to be linked to Mn-dependent glycosyltransferase activity. This glycophenotype was maintained in a cohort of patients with Crohn’s disease. These data and the pleiotropic disease associations with ZIP8 391-Thr suggest underappreciated roles of Mn homeostasis in complex human disease.

Abnormal manganese homeostasis is implicated by a GWAS disease-associated SNP, rs13107325 (ZIP8 A391T), studied in a knockin mouse model and human N-glycome analyses.

Genetics meets proteomics: perspectives for large population-based studies

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

The schizophrenia risk locus in SLC39A8 alters brain metal transport and plasma glycosylation

A common missense variant in SLC39A8 is convincingly associated with schizophrenia and several additional phenotypes. Homozygous loss-of-function mutations in SLC39A8 result in undetectable serum manganese (Mn) and a Congenital Disorder of Glycosylation (CDG) due to the exquisite sensitivity of glycosyltransferases to Mn concentration. Here, we identified several Mn-related changes in human carriers of the common SLC39A8 missense allele. Analysis of structural brain MRI scans showed a dose-dependent change in the ratio of T2w to T1w signal in several regions. Comprehensive trace element analysis confirmed a specific reduction of only serum Mn, and plasma protein N-glycome profiling revealed reduced complexity and branching. N-glycome profiling from two individuals with SLC39A8-CDG showed similar but more severe alterations in branching that improved with Mn supplementation, suggesting that the common variant exists on a spectrum of hypofunction with potential for reversibility. Characterizing the functional impact of this variant will enhance our understanding of schizophrenia pathogenesis and identify novel therapeutic targets and biomarkers.

The Human Lung Glycome Reveals Novel Glycan Ligands for Influenza A Virus

Glycans within human lungs are recognized by many pathogens such as influenza A virus (IAV), yet little is known about their structures. Here we present the first analysis of the N- and O- and glycosphingolipid-glycans from total human lungs, along with histological analyses of IAV binding. The N-glycome of human lung contains extremely large complex-type N-glycans with linear poly-N-acetyllactosamine (PL) [-3Galβ1-4GlcNAcβ1-]n extensions, which are predominantly terminated in α2,3-linked sialic acid. By contrast, smaller N-glycans lack PL and are enriched in α2,6-linked sialic acids. In addition, we observed large glycosphingolipid (GSL)-glycans, which also consists of linear PL, terminating in mainly α2,3-linked sialic acid. Histological staining revealed that IAV binds to sialylated and non-sialylated glycans and binding is not concordant with respect to binding by sialic acid-specific lectins. These results extend our understanding of the types of glycans that may serve as binding sites for human lung pathogens.

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.

Glycomic Signatures of Plasma IgG Improve Preoperative Prediction of the Invasiveness of Small Lung Nodules

Preoperative assessment of tumor invasiveness is essential to avoid overtreatment for patients with small-sized ground-glass nodules (GGNs) of 10 mm or less in diameter. However, it is difficult to determine the pathological state by computed tomography (CT) examination alone. Aberrant glycans has emerged as a tool to identify novel potential disease biomarkers. In this study, we used a lectin microarray-based strategy to investigate whether glycosylation changes in plasma immunoglobulin G (IgG) provide additional information about the invasiveness of small GGNs before surgery. Two independent cohorts (discovery set, n = 92; test set, n = 210) of GGN patients were used. Five of 45 lectins (Sambucus nigra agglutinin, SNA; Datura stramonium agglutinin, DSA; Galanthus nivalis agglutinin, GNA; Euonymus europaeus lectin, EEL; and Vicia villosa agglutinin, VVA) were identified as independent factors associated with pathological invasiveness of small GGNs (p < 0.01). Receiver-operating characteristic (ROC) curve analysis indicated the combination of these five lectins could significantly improve the accuracy of CT in diagnosing invasive GGNs, with an area under the curve (AUC) of 0.792 (p < 0.001), a sensitivity of 74.6%, and specificity of 74.4%, which was superior to current clinical biomarkers. These results suggest that the multilectin assay based on plasma IgG glycosylation may be a useful in vitro complementary test to enhance preoperative determination of the invasiveness of GGNs and guide surgeons to select proper clinical management to avoid overtreatment.

Fine-Mapping of the Human Blood Plasma N-Glycome onto Its Proteome

Most human proteins are glycosylated. Attachment of complex oligosaccharides to the polypeptide part of these proteins is an integral part of their structure and function and plays a central role in many complex disorders. One approach towards deciphering this human glycan code is to study natural variation in experimentally well characterized samples and cohorts. High-throughput capable large-scale methods that allow for the comprehensive determination of blood circulating proteins and their glycans have been recently developed, but so far, no study has investigated the link between both traits. Here we map for the first time the blood plasma proteome to its matching N-glycome by correlating the levels of 1116 blood circulating proteins with 113 N-glycan traits, determined in 344 samples from individuals of Arab, South-Asian, and Filipino descent, and then replicate our findings in 46 subjects of European ancestry. We report protein-specific N-glycosylation patterns, including a correlation of core fucosylated structures with immunoglobulin G (IgG) levels, and of trisialylated, trigalactosylated, and triantennary structures with heparin cofactor 2 (SERPIND2). Our study reveals a detailed picture of protein N-glycosylation and suggests new avenues for the investigation of its role and function in the associated complex disorders.