Delineating the genetic heterogeneity of ALS using targeted high-throughput sequencing
Bibliographic record
Abstract
BACKGROUND: Over 100 genes have been implicated in the aetiology of amyotrophic lateral sclerosis (ALS). A detailed understanding of their independent and cumulative contributions to disease burden may help guide various clinical and research efforts. METHODS: Using targeted high-throughput sequencing, we characterised the variation of 10 Mendelian and 23 low penetrance/tentative ALS genes within a population-based cohort of 444 Irish ALS cases (50 fALS, 394 sALS) and 311 age-matched and geographically matched controls. RESULTS: Known or potential high-penetrance ALS variants were identified within 17.1% of patients (38% of fALS, 14.5% of sALS). 12.8% carried variants of Mendelian disease genes (C9orf72 8.78%; SETX 2.48%; ALS2 1.58%; FUS 0.45%; TARDBP 0.45%; OPTN 0.23%; VCP 0.23%. ANG, SOD1, VAPB 0%), 4.7% carried variants of low penetrance/tentative ALS genes and 9.7% (30% of fALS, 7.1% of sALS) carried previously described ALS variants (C9orf72 8.78%; FUS 0.45%; TARDBP 0.45%). 1.6% of patients carried multiple known/potential disease variants, including all identified carriers of an established ALS variant (p<0.01); TARDBP:c.859G>A(p.[G287S]) (n=2/2 sALS). Comparison of our results with those from studies of other European populations revealed significant differences in the spectrum of disease variation (p=1.7×10(-4)). CONCLUSIONS: Up to 17% of Irish ALS cases may carry high-penetrance variants within the investigated genes. However, the precise nature of genetic susceptibility differs significantly from that reported within other European populations. Certain variants may not cause disease in isolation and concomitant analysis of disease genes may prove highly important.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".