HLA-DQB1 and HLA-DRB1 Variants Confer Susceptibility to Latent Autoimmune Diabetes in Adults: Relative Predispositional Effects among Allele Groups
Bibliographic record
Abstract
Latent autoimmune diabetes in adults (LADA) was recently demonstrated to be the most frequent form of adult-onset autoimmune diabetes mellitus. Case–control studies have investigated the relationship between human leukocyte antigen (HLA)-DQB1 and HLA-DRB1 polymorphisms and LADA risk, but their conclusions are inconsistent. This study aimed to more precisely explore the correlation between these HLA gene variants and LADA development. Eight databases, including PubMed, Embase, and Medline, were systematically searched for relevant studies up to September 15, 2018. We performed this retrospective study using meta-analysis and relative predispositional effect (RPE) methods. The meta-analysis results indicated that DQB1*02 (odds ratio (OR) = 1.685, pc < 0.005) and DQB1*06 (OR = 0.604, pc = 0.010) have opposite effects on susceptibility to LADA, while a significant decrease in LADA risk caused by DQB1*05 (OR = 0.764, pc = 0.100) disappeared upon Bonferroni correction. The RPE method confirmed the roles of DQB1*02 (χ² = 46.475, p < 0.001) and DQB1*06 (χ² = 17.883, p < 0.001) and further suggested protective effects of DQB1*05 (χ² = 16.496, p < 0.001). Additionally, the meta-analysis results showed that DRB1*03 (OR = 2.685, pc < 0.013), DRB1*04 (OR = 1.954, pc < 0.013), and DRB1*09 (OR = 1.346, pc < 0.013) are associated with increased LADA risk, while DRB1*12 (OR = 0.600, pc < 0.013) and DRB1*13 (OR = 0.583, pc < 0.013) carriers have a decreased risk of developing LADA. Furthermore, the RPE method revealed that DRB1*03 (χ² = 98.754, p < 0.001), DRB1*04 (χ² = 94.685, p < 0.001), DRB1*09 (χ² = 40.489, p < 0.001), DRB1*01 (χ² = 12.181, p < 0.001), DRB1*07 (χ² = 10.882, p = 0.001), and DRB1*08 (χ² = 5.000, p = 0.025) play protective roles against LADA. LADA showed a close relationship with genetic polymorphisms of HLA-DQB1 and WHLA-DRB1, which could contribute to a better understanding of disease pathogenesis and the identification of predisposing loci in the diagnosis and treatment of LADA.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.017 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".