The ONDRISeq panel: custom-designed next-generation sequencing of genes related to neurodegeneration
Bibliographic record
Abstract
Abstract The Ontario Neurodegenerative Disease Research Initiative (ONDRI) is a multimodal, multi-year, prospective observational cohort study to characterise five diseases: (1) Alzheimer’s disease (AD) or amnestic single or multidomain mild cognitive impairment (aMCI) (AD/MCI); (2) amyotrophic lateral sclerosis (ALS); (3) frontotemporal dementia (FTD); (4) Parkinson’s disease (PD); and (5) vascular cognitive impairment (VCI). The ONDRI Genomics subgroup is investigating the genetic basis of neurodegeneration. We have developed a custom next-generation-sequencing-based panel, ONDRISeq that targets 80 genes known to be associated with neurodegeneration. We processed DNA collected from 216 individuals diagnosed with one of the five diseases, on ONDRISeq. All runs were executed on a MiSeq instrument and subjected to rigorous quality control assessments. We also independently validated a subset of the variant calls using NeuroX (a genome-wide array for neurodegenerative disorders), TaqMan allelic discrimination assay, or Sanger sequencing. ONDRISeq consistently generated high-quality genotyping calls and on average, 92% of targeted bases are covered by at least 30 reads. We also observed 100% concordance for the variants identified via ONDRISeq and validated by other genomic technologies. We were successful in detecting known as well as novel rare variants in 72.2% of cases although not all variants are disease-causing. Using ONDRISeq, we also found that the APOE E4 allele had a frequency of 0.167 in these samples. Our optimised workflow highlights next-generation sequencing as a robust tool in elucidating the genetic basis of neurodegenerative diseases by screening multiple candidate genes simultaneously.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".