GRID – Genomics of Rare Immune Disorders: a highly sensitive and specific diagnostic gene panel for patients with primary immunodeficiencies
Bibliographic record
Abstract
Abstract Primary Immune disorders affect 15,000 new patients every year in Europe. Genetic tests are usually performed on a single or very limited number of genes leaving the majority of patients without a genetic diagnosis. We designed, optimised and validated a new clinical diagnostic platform called GRID, Genomics of Rare Immune Disorders, to screen in parallel 279 genes, including 2015 IUIS genes, known to be causative of Primary Immune disorders (PID). Validation to clinical standard using more than 58,000 variants in 176 PID patients shows an excellent sensitivity, specificity. The customised and automated bioinformatics pipeline prioritises and reports pertinent Single Nucleotide Variants (SNVs), INsertions and DELetions (INDELs) as well as Copy Number Variants (CNVs). An example of the clinical utility of the GRID panel, is represented by a patient initially diagnosed with X-linked agammaglobulinemia due to a missense variant in the BTK gene with severe inflammatory bowel disease. GRID results identified two additional compound heterozygous variants in IL17RC , potentially driving the altered phenotype.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".