MEIS1 intronic risk haplotype associated with restless legs syndrome affects its mRNA and protein expression levels
Bibliographic record
Abstract
Restless legs syndrome (RLS) is a common neurological disorder characterized by an irresistible urge to move the legs at night, which is often accompanied by unpleasant sensations. A recent genomewide association study identified an association between RLS and intronic markers from the MEIS1 gene. Comparative genomic analysis indicates that MEIS1 is the only gene encompassed in this evolutionarily conserved chromosomal segment, i.e. a conservation synteny block, from mammals to fish. We carried out a series of experiments to delineate the role of MEIS1 in RLS pathogenesis and the underlying genetic mechanism. We sequenced all 13 MEIS1 exons and their splice junctions in 285 RLS probands with confirmed clinical diagnosis and did not identify any causative coding or exon-intron junction mutations. We found no evidence of structural variation or disease-associated haplotype differential splicing. However, sequencing of conserved regions of MEIS1 introns 8 and 9 identified a novel single nucleotide polymorphism (C13B_2) significantly associated with RLS (allelic association, P = 1.81E-07). We detected a significant decrease in MEIS1 mRNA expression by quantitative real-time polymerase chain reaction in lymphoblastoid cell lines (LCLs) and brain tissues from RLS patients homozygous for the intronic RLS risk haplotype, compared with those homozygous for the non-risk haplotype. Finally, we found significantly decreased MEIS1 protein levels in the same batch of LCLs and brain tissues from the homozygous carriers of the risk haplotype, compared with the homozygous non-carriers. Therefore, these data suggest that reduced expression of the MEIS1 gene, possibly through intronic cis-regulatory element(s), predisposes to RLS.
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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 | 0.000 |
| 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) | 0.002 | 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".