Changes Due to Ageing in the Glycan Structure of Alpha-2-Macroglobulin and Its Reactivity with Ligands

Effects of age, amyloid, sex, and APOE ε4 on the CSF proteome in normal cognition

Introduction

It is important to understand which biological processes change with aging, and how such changes are associated with increased Alzheimer's disease (AD) risk. We studied how cerebrospinal fluid (CSF) proteomics changed with age and tested if associations depended on amyloid status, sex, and apolipoprotein E Ɛ4 genotype.

Methods

We included 277 cognitively intact individuals aged 46 to 89 years from Alzheimer's Disease Neuroimaging Initiative, European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery, and Metabolic Syndrome in Men. In total, 1149 proteins were measured with liquid chromatography mass spectrometry with multiple reaction monitoring/Rules-Based Medicine, tandem mass tag mass spectrometry, and SOMAscan. We tested associations between age and protein levels in linear models and tested enrichment for Reactome pathways.

Results

Levels of 252 proteins increased with age independently of amyloid status. These proteins were associated with immune and signaling processes. Levels of 21 proteins decreased with older age exclusively in amyloid abnormal participants and these were enriched for extracellular matrix organization.

Discussion

We found amyloid-independent and -dependent CSF proteome changes with older age, perhaps representing physiological aging and early AD pathology.

Lectin-Based Protein Microarray for the Glycan Analysis of Colorectal Cancer Biomarkers: The Insulin-Like Growth Factor System

Lectin-based protein microarrays are used for glycoprofiling of various kinds of biological samples. Here we describe lectin-based microarray assay in the reverse-phase format where glycoprotein samples are spotted onto microarray slide and then are incubated with set of lectins. This configuration allows high-throughput screening of a large cohort of samples by a set of lectins without need of separation of glycans from glycoproteins. We applied the described method for glycan analysis of glycoprotein biomarkers of colorectal cancer associated with the insulin-like growth factor system.

Glycosylation Biomarkers Associated with Age-Related Diseases and Current Methods for Glycan Analysis

Ageing is a complex process which implies the accumulation of molecular, cellular and organ damage, leading to an increased vulnerability to disease. In Western societies, the increase in the elderly population, which is accompanied by ageing-associated pathologies such as cardiovascular and mental diseases, is becoming an increasing economic and social burden for governments. In order to prevent, treat and determine which subjects are more likely to develop these age-related diseases, predictive biomarkers are required. In this sense, some studies suggest that glycans have a potential role as disease biomarkers, as they modify the functions of proteins and take part in intra- and intercellular biological processes. As the glycome reflects the real-time status of these interactions, its characterisation can provide potential diagnostic and prognostic biomarkers for multifactorial diseases. This review gathers the alterations in protein glycosylation profiles that are associated with ageing and age-related diseases, such as cancer, type 2 diabetes mellitus, metabolic syndrome and several chronic inflammatory diseases. Furthermore, the review includes the available techniques for the determination and characterisation of glycans, such as liquid chromatography, electrophoresis, nuclear magnetic resonance and mass spectrometry.

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.

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.

GALNT6 promotes breast cancer metastasis by increasing mucin-type O-glycosylation of α2M

Breast cancer is the most lethal malignancy in women. N-acetylgalactosaminyltransferase 6 (GALNT6) is an enzyme which mediates the initial step of mucin-type O-glycosylation, and has been reported to be involved in mammary carcinogenesis. However, the molecular mechanism of GALNT6 in breast cancer metastasis has not been fully explored. In this study, based on online database analyses and tissue microarrays, the overall survival (OS) of breast cancer patients with high expression of GALNT6 was found to be shorter than those with low expression of GALNT6. Also, high GALNT6 expression was positively correlated with advanced pN stage and pTNM stage. GALNT6 was shown to be able to promote the migration and invasion of breast cancer cells, and enhance the level of mucin-type O-glycosylation of substrates in the supernatants of breast cancer cells. Qualitative mucin-type glycosylomics analysis identified α2M as a novel substrate of GALNT6. Further investigation showed that GALNT6 increased O-glycosylation of α2M, and the following activation of the downstream PI3K/Akt signaling pathway was involved in the promotion of migration and invasion of breast cancer cells. This study identified a new substrate of GALNT6 and provides novel understanding of the role of GALNT6 in promoting metastasis and poor prognosis in breast cancer.