Systematic Review: Immunoglobulin G N-Glycans as Next-Generation Diagnostic Biomarkers for Common Chronic Diseases

Abstract

Glycomics is a new subspecialty in omics systems sciences that offers significant promise for next-generation biomarkers on disease susceptibility, drug target discovery, and precision medicine. In this context, alternative immunoglobulin G (IgG) N-glycosylation has been reportedly implicated in several common chronic diseases, although systematic assessment is currently lacking in the literature. We conducted a systematic review of observational studies on IgG N-glycan variability and susceptibility to common chronic diseases. Observational studies reporting an association between diseases (such as colorectal cancer, dyslipidemia, ischemic stroke, rheumatoid arthritis, and systemic lupus erythematosus) and IgG N-glycans quantified by ultraperformance liquid chromatography were included. The glycans were categorized into 24 initial IgG glycan peaks (GPs). Notably, aging positively correlated with GP1, GP2, GP4-7, GP10, GP11, GP19, and GP24, while negatively correlated with GP8, GP12-15, GP17, GP18, GP20, GP21, and GP23 (p < 0.05). The absolute value of significant correlation coefficients of age and IgG glycans ranged from 0.043 to 0.645. We found that the high levels of GP1-4, GP6, GP7, and GP24 and low levels of GP9, GP13-15, GP18, and GP23 could potentially increase the risk of disease. In conclusion, the present systematic review suggests that the field of glycomics, and GP1-4, GP6, GP7, GP9, GP13-15, GP18, GP23, and GP24 in particular, holds promise for further candidate biomarker research on susceptibility to common chronic diseases.

Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell

“…The question also relates well to efforts for deploying and integrating multiomics biomarker research across genomics, proteomics, and glycomics, and to account for not only genomic and proteomic contributions to drug response but also those from individual differences in glycan structure and function. In support of this much needed multiomics integrative vision of personalized medicine, Liu et al (2019) have hinted that genomics, alone, will not suffice to solve the puzzle on biological determinants of type 2 diabetes mellitus (T2DM):…”

“…By the end of 2018, >143 genetic variants had been identified as associated with T2DM, blood glucose, or insulin levels, though these only explain <15% of the disease risk (Skyler et al, 2017;Xue et al, 2018), suggesting that epigenetic regulation and post-translational modification play important roles in the etiology of T2DM (Liu et al, 2019).…”

“…The reasons for variability in response to medicines are many and include technical, biological, and social dimensions. A previously overlooked source of variability in personalized medicine research is the ''sugar code'' (i.e., the information stored in glycans and their conjugated forms such as glycoproteins and glycolipids) (Kaltner et al, 2019;Liu et al, 2019;Wang, 2019;.…”

Knowledge Domain and Emerging Trends of IgG Glycosylation: A Bibliometric Study Based on CiteSpace

“…At the same time, glycosylation also plays an important role in the human immune system, and these roles help us to speci cally recognize these reactions [56] . Because IgG is the most abundant glycoprotein in immunoglobulin and its N-glycan participates in many physiological case processes, it was often considered an effective biomarker for us to recognize a certain disease [9,11,57] . It can also be seen from the cutting-edge trends of this research that since 2018, IgG glycosylation as a diagnostic biomarker for chronic diseases has gradually become a major research hotspot in the eld.…”

“…People's interest in the research of immunoglobulin G (Ig G) glycosylation has increased dramatically, and many magazines have published a large number of articles on IgG glycosylation. Many studies have shown that changes in Ig G glycosylation level and sugar chain structure are often accompanied by the occurrence and development of various chronic disease [6][7][8] ,Because Ig G glycosylation is highly heterogeneous and can be regarded as a disease phenotype, it may be used as a dynamic disease biomarker from the perspective of predictive, preventive and personalized medicine Thing [9][10][11][12][13][14] . With the rapid increase in the number of articles published, it becomes very di cult to identify new developments and new trends in IgG glycosylation research.…”