Association of Anti-GAD Antibody Positivity Measured by RIA and ELISA with Clinical Characteristics in Patients with Type 1 Diabetes
Bibliographic record
Abstract
Background: Serum anti-GAD antibody (GADA) is a diagnostic marker of immune-mediated type 1 diabetes mellitus. Discrepancies have been reported between GADA positivity assessed by radioimmunoassay (RIA) and enzyme-linked immunosorbent assay (ELISA). To analyze heterogeneity in type 1 diabetes, this study investigated patients with this discrepancy. Subjects and Method: This study included 65 patients with acute-onset type 1 diabetes (AT1D) and 32 with slowly progressive type 1 diabetes (SPIDDM), all weakly positive (1.5-10 U/mL) for GADA, as measured by RIA in 2013-2015. GADA was measured in the same samples, stored at -80°C, by ELISA in 2016-2017. GADA concentrations ≥ 5 U/mL and < 5 U/mL on ELISA were defined as positive and negative, respectively. Postprandial C-peptide was measured at the time of RIA. Results: Of the patients with A1TD and SPIDDM, 86% and 59%, respectively, were ELISA-positive. Duration of diabetes did not differ significantly between positive and negative patients in each subtype. Postprandial C-peptide index was significantly lower in positive than negative patients with SPIDDM (0.39±0.48 vs. 1.56±1.16, p<0.001), but not with AT1D. HLA was assessed in 15 patients with SPIDDM, nine positive and six negative for GADA. Seven of the nine positive, but none of the five negative, patients had HLA-DR9 (p=0.007). HLA was also assessed in 39 patients with AT1D, 33 positive and six negative for GADA. Eleven of the 33 positive, but none of the six negative, patients had HLA-DR9 (p=0.158). Discussion: In SPIDDM patients weakly positive for GADA by RIA, ELISA positivity was significantly associated with lower insulin secretion, suggesting that more cytotoxic epitopes of GAD are recognized by ELISA than by RIA. ELISA positivity in SPIDDM is associated with HLA-DR9, a haplotype linked to cytotoxicity against pancreatic β-cells. Measuring GADA by RIA and ELISA may predict insulin secretion in patients with SPIDDM. Disclosure S. Takagi: Stock/Shareholder; Self; Astellas Pharma Inc., Mitsubishi Tanabe Pharma Corporation. J. Miura: None. S. Hoshina: None. Y. Uchigata: None. T. Babazono: Research Support; Self; Abbott, Arkray, Inc.. Speaker's Bureau; Self; Asahi Kasei Corporation, AstraZeneca. Research Support; Self; Baxter, Becton, Dickinson and Company, Boehringer Ingelheim Pharmaceuticals, Inc.. Speaker's Bureau; Self; Eli Lilly and Company. Research Support; Self; Kowa Pharmaceuticals America, Inc., Kissei Pharmaceutical Co., Ltd., Kyowa Hakko Kirin Co., Ltd., MSD K.K., Nippon Boehringer Ingelheim Co. Ltd.. Board Member; Self; Japan Diabetes Society. Research Support; Self; Johnson & Johnson Diabetes Institute, LLC., Novartis Pharma K.K., Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd.. Speaker's Bureau; Self; Otsuka Holdings Co., Ltd.. Research Support; Self; Sanofi K.K., Sumitomo Dainippon Pharma Co., Ltd., Takeda Canada Inc., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceuticals U.S.A., Inc., Teijin Pharma Limited, Terumo Medical Corporation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".