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.
|Number of pages||10|
|Publication status||Published - 17 Mar 2017|
- Journal Article