High Prevalence of a Monogenic Cause in Han Chinese Diagnosed With Type 1 Diabetes, Partly Driven by Nonsyndromic Recessive <i>WFS1</i> Mutations
Bibliographic record
Abstract
It is estimated that ∼1% of European ancestry patients clinically diagnosed with type 1 diabetes (T1D) actually have monogenic forms of the disease. Because of the much lower incidence of true T1D in East Asians, we hypothesized that the percentage would be much higher. To test this, we sequenced the exome of 82 Chinese Han patients clinically diagnosed with T1D but negative for three autoantibodies. Analysis focused on established or proposed monogenic diabetes genes. We found credible mutations in 18 of the 82 autoantibody-negative patients (22%). All mutations had consensus pathogenicity support by five algorithms. As in Europeans, the most common gene was HNF1A (MODY3), in 6 of 18 cases. Surprisingly, almost as frequent were diallelic mutations in WFS1, known to cause Wolfram syndrome but also described in nonsyndromic cases. Fasting C-peptide varied widely and was not predictive. Given the 27.4% autoantibody negativity in Chinese and 22% mutation rate, we estimate that ∼6% of Chinese with a clinical T1D diagnosis have monogenic diabetes. Our findings support universal sequencing of autoantibody-negative cases as standard of care in East Asian patients with a clinical T1D diagnosis. Nonsyndromic diabetes with WSF1 mutations is not rare in Chinese. Its response to alternative treatments should be investigated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".