Unraveling Glycosylation Alterations in Alzheimer’s Disease through Multi-Omics Analysis
- Tang, Xinyu
- Advisor(s): Zivkovic, Angela M
Abstract
Alzheimer’s Disease (AD) is the most common cause of dementia, characterized by the extracellular deposition of β-amyloid plaques and intracellular neurofibrillary tangles resulting from hyperphosphorylated tau protein. AD has emerged as a looming concern in the U.S., with an estimated 6.7 million Americans projected to live with AD by 2023, and about 1 in 9 people aged 65 and older affected by Alzheimer’s dementia. Unfortunately, there is still no effective treatment to reverse or stop AD progression. Glycosylation is a post-translational modification where glycans are attached to peptide chains or lipids. Emerging studies have demonstrated a close link between aberrant protein glycosylation and AD pathology. Given its complexity and diversity, glycosylation holds promise to understand the precise pathogenesis of AD from a novel perspective. Meanwhile, nutritional interventions hold potential to modify glycosylation patterns, as evidenced by the widespread use of oral monosaccharide administration in managing certain congenital disorders of glycosylation. Hence, it is pivotal to investigate the involvement of glycosylation in AD pathology and explore the possibility of nutritional management in modulating glycosylation patterns. This dissertation includes four chapters that highlight work focusing on glycosylation alterations in AD and dietary impacts on glycosylation.The first chapter delved into profiling glycosylation alterations in the postmortem brains of AD individuals, focusing on alterations in glycosyltransferases and N-linked glycans. Leveraging publicly available RNA-seq datasets encompassing seven brain regions and incorporating 1724 samples, we identified differentially expressed glycosyltransferases, including MGAT1, B4GALT1, GALNTs, subsequently confirmed by qPCR in an independent set of human medial temporal cortex (MTC) samples. N-glycan-related changes predicted by differential expression of these glycosyltransferases were confirmed by liquid chromatography-mass spectrometry (LC-MS)-based N-glycan analysis in the MTC (n=9 AD vs. 6 controls). Our findings indicated that MGAT1 and B4GALT1, which are involved in the formation of complex N-linked glycans and galactosylation, were upregulated in multiple brain regions. This upregulation was reflected in an increased abundance of corresponding N-glycans. Additionally, we identified transcription factors (TFs), including nutrient-stimulated TFs, regulating glycosyltransferases, indicating the potential of dietary components to impact glycosylation. Furthermore, heterogeneous differential expression of glycosylation isoenzymes underscored the necessity to investigate the cell-specific functions of these isoenzymes. The second chapter focused on glycosylation alterations in microglia, innate immune cells in the central nervous system. AD pathology has highlighted the importance of microglia due to their role in orchestrating neuroinflammation and phagocytosis. We characterized glycosylation changes in human microglia following (Amyloid-β Oligomer) AβO and (lipopolysaccharide) LPS stimulation. Both treatments had distinct impacts on the N-glycan profile of human microglia, as evidenced by distinct clustering of AβO- and LPS-activated human microglia glycan signatures on the PCA plot. AβO treatment increased sialylated N-glycan abundance, coupled with the upregulation of genes encoding for sialyltransferases, ST3GAL2, ST3GAL4, and ST3GAL6 in AβO-activated microglia. In contrast, LPS stimulation increased fucosylation in N-glycans, alongside the upregulation of genes encoding for fucosyltransferases, including FUT4, and the downregulation of fucosidase, FUCA1. Additionally, LPS stimulation decreased the abundance of complex-type N-glycans, aligned with downregulation of mannosidase genes (MAN1A1, MAN2A2, MAN1C1). However, the glycosphingolipid (GSL) profile did not exhibit significant changes in either AβO- or LPS-activated microglia. While protein glycosylation alterations observed in the brain and in microglia reveal potential mechanisms by which glycosylation is involved in AD, brain tissue samples are not useful for diagnosis. In the third chapter we explored the potential utility of serum glycoproteins as biomarkers for AD diagnosis. Utilizing serum samples from around 100 AD patients and 100 age- and gender-matched controls, we quantified glycopeptides of the most abundant serum proteins. The results indicate that among the differentially expressed glycopeptides, the majority belonged to proteins involved in immune function, including immunoglobulins and acute-phase proteins such as alpha-1-antitrypsin (A1AT), alpha-2-macroglobulin (A2MG), and complement C3 (CO3). Non-fucosylated and mono-fucosylated immunoglobulins G1 and G2 were key discriminators between control and AD individuals. Partial Least Square-Discriminant Analysis demonstrated the potential of these glycopeptides in distinguishing AD from normal controls, albeit with some overlap. Confounding factors, such as age, sex, BMI, and ethnicity, had impacts on glycopeptide abundances. Given the pivotal role of glycosylation in AD, the final chapter investigated the impacts of dietary supplements on glycosylation patterns. We developed a targeted glycoproteomic method to monitor site-specific glycoprofiles and quantities of the most abundant HDL-associated proteins using Orbitrap LC-MS for (glyco)peptide target discovery and QqQ LC-MS for quantitative analysis. Using this glycopeptide quantification workflow, we conducted a pilot study to determine whether HDL protein glycoprofiles are altered in healthy human participants in response to dietary glycan supplementation. Twenty-two healthy adult men/women (age 18-45) with a Body Mass Index (BMI) range of 18.5-25 were randomized to four treatment groups: placebo (n=4), N-acetylglucosamine (n=6), Spirulina (n=6), and galactose (n=6). Blood samples were collected at baseline and after four weeks of supplementation. Peptides and glycopeptides on HDL were quantified using the new workflow. The results demonstrated the potential of dietary intervention in modifying the HDL glycoprofile even within a short-term period. Further studies with larger sample sizes are required to validate diet-induced HDL glycoprofile alterations.