Molecular characterization of a large cohort of mucopolysaccharidosis patients: Iran Mucopolysaccharidosis RE‐diagnosis study (IMPRESsion)
Bibliographic record
Abstract
Mucopolysaccharidoses (MPSs) are rare, heterogeneous inborn errors of metabolism (IEM) diagnosed through a combination of clinical, biochemical, and genetic investigations. The aim of this study was molecular characterization of the largest cohort of Iranian MPS patients (302 patients from 289 unrelated families), along with tracking their ethnicity and geographical origins. 185/289 patients were studied using an IEM-targeted NGS panel followed by complementary Sanger sequencing, which led to the diagnosis of 154 MPS patients and 5 non-MPS IEMs (diagnostic yield: 85.9%). Furthermore, 106/289 patients who were referred with positive findings went through reanalysis and confirmatory tests which confirmed MPS diagnosis in 104. Among the total of 258 MPS patients, 225 were homozygous, 90 harbored novel variants, and 9 had copy number variations. MPS IV was the most common type (34.8%) followed by MPS I (22.7%) and MPS VI (22.5%). Geographical origin analysis unveiled a pattern of distribution for frequent variants in ARSB (c.430G>A, c.962T>C [p.Leu321Pro], c.281C>A [p.Ser94*]), GALNS (c.319G>A [p.Ala107Thr], c.860C>T [p.Ser287Leu], c.1042A>G [p.Thr348Ala]), and IDUA (c.1A>C [p.Met1Leu], c.1598C>G [p.Pro533Arg], c.1562_1563insC [p.Gly522Argfs*50]). Our extensive patient cohort reveals the genetic and geographic landscape of MPS in Iran, which provides insight into genetic epidemiology of MPS and can facilitate a more cost-effective, time-efficient diagnostic approach based on the region-specific variants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".