Mineral absorption is an enriched pathway in a brain region of restless legs syndrome patients with reduced MEIS1 expression
Bibliographic record
Abstract
Restless legs syndrome is a common complex disorder with different genetic and environmental risk factors. Here we used human cell lines to conduct an RNA-Seq study and observed how the gene showing the most significant association with RLS, MEIS1, acts as a regulator of the expression of many other genes. Some of the genes affected by its expression level are linked to pathways previously reported to be associated with RLS. We found that in cells where MEIS1 expression was either increased or prevented, mineral absorption is the principal dysregulated pathway. The mineral absorption pathway genes, HMOX1 and VDR are involved in iron metabolism and response to vitamin D, respectively. This shows a strong functional link to the known RLS pathways. We observed the same enrichment of the mineral absorption pathway in postmortem brain tissues of RLS patients showing a reduced expression of MEIS1. The expression of genes encoding metallothioneins (MTs) was observed to be dysregulated across the RNA-Seq datasets generated from both human cells and tissues. MTs are highly relevant to RLS as they bind intracellular metals, protect against oxidative stress and interact with ferritins which manage iron level in the central nervous system. Overall, our study suggests that in a subset of RLS patients, the contribution of MEIS1 appears to be associated to its downstream regulation of genes that are more directly involved in pathways that are relevant to RLS. While MTs have been implicated in the pathogenesis of neurodegenerative diseases such as Parkinson's diseases, this is a first report to propose that they have a role in 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 | 0.001 | 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".