Unravelling inulin molecules in food sources using a matrix-assisted laser desorption/ionization magnetic resonance mass spectrometry (MALDI-MRMS) pipeline.

Inulin, a polysaccharide characterized by a ß-2,1 fructosyl-fructose structure terminating in a glucosyl moiety, is naturally present in plant roots and tubers. Current methods provide average degrees of polymerization (DP) but lack information on the distribution and absolute concentration of each DP. To address this limitation, a reproducible (CV < 10 %) high throughput (<2 min/sample) MALDI-MRMS approach capable of characterizing and quantifying inulin molecules in plants using matched-matrix consisting of α-cyano-4-hydroxycinnamic acid butylamine salt (CHCA-BA), chicory inulin-12C and inulin-13C was developed. The method identified variation in chain lengths and concentration of inulin across various plant species. Globe artichoke hearts, yacón and elephant garlic yielded similar concentrations at 15.6 g/100 g dry weight (DW), 16.8 g/100 g DW and 17.7 g/100 g DW, respectively, for DP range between 9 and 22. In contrast, Jerusalem artichoke demonstrated the highest concentration (53.4 g/100 g DW) within the same DP ranges. Jerusalem artichoke (DPs 9-32) and globe artichoke (DPs 9-36) showed similar DP distributions, while yacón and elephant garlic displayed the narrowest and broadest DP ranges (DPs 9-19 and DPs 9-45, respectively). Additionally, qualitative measurement for all inulin across all plant samples was feasible using the peak intensities normalized to Inulin-13C, and showed that the ratio of yacón, elephant garlic and Jerusalem was approximately one, two and three times that of globe artichoke. This MALDI-MRMS approach provides comprehensive insights into the structure of inulin molecules, opening avenues for in-depth investigations into how DP and concentration of inulin influence gut health and the modulation of noncommunicable diseases, as well as shedding light on refining cultivation practices to elevate the beneficial health properties associated with specific DPs.

Increased central adiposity is associated with pro-inflammatory immunoglobulin G N-glycans.

BACKGROUND: Increased body fat may be associated with an increased risk of developing an underlying pro-inflammatory state, thus leading to greater risk of developing certain chronic conditions. Immunoglobulin G has the ability to exert both anti- and pro-inflammatory effects, and the N-glycosylation of the fragment crystallisable portion is involved in mediating this process. Body mass index, a rudimentary yet gold standard indication for body fat, has been shown to be associated with agalactosylated immunoglobulin G N-glycans. AIM: We aimed to determine the association between increased body fat and the immunoglobulin G glycosylation features, comparing body mass index to other measures of body fat distribution. METHODS: We investigated a sample of 637 community-based 45-69 year olds, with mixed phenotypes, residing in Busselton, Western Australia. Body mass index and the waist-to-hip and waist-to-height ratios were calculated using anthropometry, while dual-energy x-ray absorptiometry was performed to gain an accurate measure of total and area specific body fat. Serum immunoglobulin GN-glycans were analysed by ultra-performance liquid chromatography. RESULTS: Twenty-two N-glycan peaks were found to be associated with at least one of the fat measures. While the previous association of body mass index to agalactosylated immunoglobulin G was replicated, measures of central adiposity explained the most variation in the immunoglobulin G glycome. CONCLUSION: Central adiposity is associated with an increased pro-inflammatory fraction of immunoglobulin G, suggesting that the android/gynoid ratio or waist-to-height ratio instead be considered when controlling for adiposity in immunoglobulin G glycome biomarker studies.

The N-glycosylation of immunoglobulin G as a novel biomarker of Parkinson's disease.

The use of the emerging "omics" technologies for large scale population screening is promising in terms of predictive, preventive and personalized medicine. For Parkinson's disease, it is essential that an accurate diagnosis is obtained and disease progression can be monitored. Immunoglobulin G (IgG) has the ability to exert both anti-inflammatory and pro-inflammatory effects, and the N-glycosylation of the fragment crystallizable portion of IgG is involved in this process. This study aimed to determine whether the IgG glycome could be a candidate biomarker for Parkinson's disease. Ninety-four community-based individuals with Parkinson's disease and a sex-, age- and ethnically-matched cohort of 102 individuals with mixed phenotypes, representative of a "normally" aged Caucasian controls, were investigated. Plasma IgG glycans were analyzed by ultra-performance liquid chromatography. Overall, seven glycan peaks and 11 derived traits had statistically significant differences (P < 8.06 × 10-4) between Parkinson's disease cases and healthy controls. Out of the seven significantly different glycan peaks, four were selected by Akaike's Information Criterion to be included in the logistic regression model, with a sensitivity of 87.2% and a specificity of 92.2%. The study suggested that there may be a reduced capacity for the IgG to inhibit Fcγ-RIIIa binding, which would allow an increased ability for the IgG to cause antibody-dependent cell cytotoxicity and a possible state of low-grade inflammation in individuals with Parkinson's disease.