An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-Peptide
Accurately measuring circulating proinsulin proteoforms is crucial for clinical investigation of diabetes, but was previously not feasible owing to limited assay specificity/sensitivity. Here we devised a highly sensitive LC-MS-based strategy to quantify intact proinsulin, des-31,32 and des-64,65 proinsulin, and C-peptide in circulation. The method involves: (i) quantitative, robust affinity capture using an optimized antibody cocktail, eliminating the severe quantitative bias across multiple proteoforms typically introduced when using a single antibody; (ii) Lys-C digestion producing unique signature peptides for each proteoform, and (iii) trapping-nano-LC coupled with FAIMS/dCV-MS for an ultrasensitive analysis. The selective trapping/delivery ensured sensitive/selective analysis of the targets while achieving excellent analytical robustness that is critical for clinical assays, and the FAIMS/dCV substantially reduces baseline noise/interferences, further enhancing <i>S</i>/<i>N</i>. The assay achieved exceptional sensitivity, with serum LOQs of 1.7, 2.3, and 3.6 pg/mL respectively for intact-proinsulin, des-31,32 and des-64,65, representing the first assay capable of sensitively quantifying these major circulating proinsulin proteoforms. We applied this assay to 78 subjects, including autoantibody positive (<i>n</i> = 20) and new-onset type 1 diabetes (T1D, <i>n</i> = 19) with respective age/sex/BMI-matched controls, enabling the first accurate profiling of proinsulin proteoforms in clinical groups. The assay results demonstrated a clear separation of control and new-onset T1D groups that a parallel total-proinsulin ELISA assay fails to capture. Furthermore, distinct expression patterns in relative abundance ratios among proteoforms were observed across clinical groups. This assay may provide valuable insights into the β-cell functions and the onset/progression of diabetes and other associated conditions. Moreover, the strategy is broadly applicable to targeted measurement of other biomarker proteoforms.
Authors
- Qingqing Shen (ORCID: https://orcid.org/0000-0002-6251-8564)
- Scott Peterman
- Emily K. Sims (ORCID: https://orcid.org/0000-0002-4393-954X)
- Gabriela S. F. Monaco
- Carmella Evans‐Molina (ORCID: https://orcid.org/0000-0001-7764-8663)
- Jun Qu (ORCID: https://orcid.org/0000-0002-1346-6809)
- Lorenz Nierves (ORCID: https://orcid.org/0000-0001-5545-4323)
- Tujin Shi (ORCID: https://orcid.org/0000-0002-5592-3588)
- Weijun Qian (ORCID: https://orcid.org/0000-0002-5393-2827)
- Cornelia Boeser
- Ming Zhang (ORCID: https://orcid.org/0000-0003-1175-4636)
- Wang Cao (ORCID: https://orcid.org/0000-0001-8023-6096)
- T L Lin (ORCID: https://orcid.org/0000-0001-6544-8170)
Institutions
- Pacific Northwest National Laboratory (US)
- Diabetes Australia (AU)
- New York State College of Agriculture & Life Sciences (US)
- Richard L. Roudebush VA Medical Center (US)
- Thermo Fisher Scientific (United States) (US)
- Herman Miller (United States) (US)
- University School (US)
- Pharmaceutical Biotechnology (Czechia) (CZ)
- Indiana University School of Medicine
- Indiana University – Purdue University Indianapolis (US)
- Indiana University (US)
- University at Buffalo, State University of New York (US)
- Center for Excellence in Education (US)
Publication Details
- Journal
- Analytical Chemistry
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1021/acs.analchem.5c03256
- Primary Topic
- Monoclonal and Polyclonal Antibodies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Diabetes and Digestive and Kidney Diseases