Identification of a novel missense mutation in angiogenin in a Chinese amyotrophic lateral sclerosis cohort
Bibliographic record
Abstract
Abstract Angiogenin (ANG) gene mutations have been identified in both familial and sporadic amyotrophic lateral sclerosis (ALS) patients from multiple European and North American populations. However, no ANG mutation has yet been reported in Asian ALS populations. Here, we screened for ANG mutations in a Chinese ALS cohort. The entire coding region of the ANG gene was sequenced in 10 familial ALS pedigrees, 202 sporadic ALS patients, and 151 healthy controls. All patients were negative for SOD1, FUS, and TARDBP mutations. We identified a novel missense mutation, c.379G > A (p.V103I), in one sporadic ALS patient, but not in the controls. No mutations were found in the familial ALS patients. A novel missense variant, c.323A > G (p.H84R), was detected in one healthy individual. We identified the presence of the known single nucleotide polymorphism, rs11701 (T/G), in both ALS cases and controls. However, no significant association of the G allele with ALS susceptibility was demonstrated. In conclusion, ANG mutations accounted for 0.5% of our SOD1-, FUS-, TARDBP- mutation-negative ALS cohort. Our findings highlight that the genetic background of ALS differs between different populations, and suggest that ANG mutation may be involved in the aetiology of ALS in the Han Chinese population.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".