Gene mutations responsible for primary immunodeficiency disorders: A report from the first primary immunodeficiency biobank in Iran
Bibliographic record
Abstract
BACKGROUND: Primary immunodeficiency (PID) is a heterogeneous group of inheritable genetic disorders with increased susceptibility to infections, autoimmunity, uncontrolled inflammation and malignancy. Timely precise diagnosis of these patients is very essential since they may not be able to live with their congenital immunity defects; otherwise, they could survive with appropriate treatment. DNA biobanks of such patients could be used for molecular and genetic testing, facilitating the detection of underlying mutations in known genes as well as the discovery of novel genes and pathways. METHODS: According to the last update of the International Union of Immunological Societies (IUIS) classification, patients are registered in our biobank during a period of 15 years. All patients' data were collected via questionnaire and their blood samples were taken in order to extract and protect their DNA content. RESULTS: Our study comprised 197 patients diagnosed with PID. Antibody deficiency in 50 patients (25.4%), phagocytic defect in 47 patients (23.8%) and combined immunodeficiency with associated/syndromic feature in 19 patients (9.6%) were the most common PID diagnoses, respectively. The most common variant of PID in our study is common variable immunodeficiency, which accounted for 20 cases (10.1%), followed by chronic mucocutaneous candidiasis in 15 patients (7.9%) and congenital neutropenia in 13 patients (7%). Mean age at onset of disease was 4 years and mean age of diagnosis was 9.6 years. The average diagnostic delay was 5.5 years, with a range of 6 months to 46 years. Parental consanguinity and history of PID in family were observed in 70.2 and 48.9% of the patients, respectively. The majority of PID patients (93.3%) were from families with low socioeconomic status. CONCLUSION: This prospective study was designed to establish a PID Biobank in order to have a high quality DNA reservoir of these patients, shareable for international diagnostic and therapeutic collaborations. This article emphasizes the need to raise the awareness of society and general practitioners to achieve timely diagnosis of these patients and prevent current mismanagements.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".