A method to identify trace sulfated IgG N-glycans as biomarkers for rheumatoid arthritis.
Jing-Rong WangWei-Na GaoRudolf GrimmShibo JiangYong LiangHua YeZhan-Guo LiLee-Fong YauHao HuangJu LiuMin JiangQiong MengTian-Tian TongHai-Hui HuangStephanie LeeXing ZengLiang LiuZhi-Hong JiangPublished in: Nature communications (2017)
N-linked glycans on immunoglobulin G (IgG) have been associated with pathogenesis of diseases and the therapeutic functions of antibody-based drugs; however, low-abundance species are difficult to detect. Here we show a glycomic approach to detect these species on human IgGs using a specialized microfluidic chip. We discover 20 sulfated and 4 acetylated N-glycans on IgGs. Using multiple reaction monitoring method, we precisely quantify these previously undetected low-abundance, trace and even ultra-trace N-glycans. From 277 patients with rheumatoid arthritis (RA) and 141 healthy individuals, we also identify N-glycan biomarkers for the classification of both rheumatoid factor (RF)-positive and negative RA patients, as well as anti-citrullinated protein antibodies (ACPA)-positive and negative RA patients. This approach may identify N-glycosylation-associated biomarkers for other autoimmune and infectious diseases and lead to the exploration of promising glycoforms for antibody therapeutics.Post-translational modifications can affect antibody function in health and disease, but identification of all variants is difficult using existing technologies. Here the authors develop a microfluidic method to identify and quantify low-abundance IgG N-glycans and show some of these IgGs can be used as biomarkers for rheumatoid arthritis.
Keyphrases
- rheumatoid arthritis
- end stage renal disease
- disease activity
- newly diagnosed
- ejection fraction
- cell surface
- high throughput
- chronic kidney disease
- infectious diseases
- ankylosing spondylitis
- heavy metals
- public health
- prognostic factors
- multiple sclerosis
- interstitial lung disease
- circulating tumor cells
- deep learning
- patient reported outcomes
- high resolution
- mental health
- gene expression
- binding protein
- microbial community
- drug induced
- copy number
- health information