Genome-wide association study identifies risk variants for sporadic Creutzfeldt-Jakob disease in <i>STX6</i> and <i>GAL3ST1</i>
Bibliographic record
Abstract
Abstract Mammalian prions are lethal pathogens composed of fibrillar assemblies of misfolded prion protein. Human prion diseases are rare and usually rapidly fatal neurodegenerative disorders, the most common being sporadic Creutzfeldt-Jakob disease (sCJD). Variants in the gene that encodes prion protein ( PRNP ) are strong risk factors for sCJD, but although the condition has heritability similar to other neurodegenerative disorders, no other risk loci have yet been confirmed. By genome-wide association in European ancestry populations, we found three replicated loci (cases n=5208, within PRNP, STX6 , and GAL3ST1 ) and two further unreplicated loci were significant in gene-wide tests (within PDIA4, BMERB1 ). Exome sequencing in 407 sCJD cases, conditional and transcription analyses suggest that associations at PRNP and GAL3ST1 are likely to be caused by common variants that alter the protein sequence, whereas risk variants in STX6 and PDIA4 associate with increased expression of the major transcripts in disease-relevant brain regions. Alteration of STX6 expression does not modify prion propagation in a neuroblastoma cell model of mouse prion infection. We went on to analyse the proteins histologically in diseased tissue and examine the effects of risk variants on clinical phenotypes using deep longitudinal clinical cohort data. Risk SNPs in STX6 , a protein involved in the intracellular trafficking of proteins and vesicles, are shared with progressive supranuclear palsy, a neurodegenerative disease associated with the misfolded protein tau. We present the first evidence of statistically robust associations in sporadic human prion disease that implicate intracellular trafficking and sphingolipid metabolism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".