Protein network analysis links the NSL complex to Parkinson's disease via mitochondrial and nuclear biology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Whilst the majority of Parkinson's Disease (PD) cases are sporadic, much of our understanding of the pathophysiological basis of the disease can be traced back to the study of rare, monogenic forms of PD. In the past decade, the availability of genome-wide association studies (GWAS) has facilitated a shift in focus, toward identifying common risk variants conferring increased risk of developing PD across the population. A recent mitophagy screening assay of GWAS candidates has functionally implicated the non-specific lethal (NSL) complex in the regulation of PINK1-mitophagy. Here, a bioinformatics approach has been taken to investigate the proteome of the NSL complex, to unpick its relevance to PD pathogenesis. The NSL interactome has been built, using 3 online tools: PINOT, HIPPIE and MIST, to mine curated, literature-derived protein-protein interaction (PPI) data. We built (i) the 'mitochondrial' NSL interactome exploring its relevance to PD genetics and (ii) the PD-oriented NSL interactome to uncover biological pathways underpinning the NSL/PD association. In this study, we find the mitochondrial NSL interactome to be significantly enriched for the protein products of PD-associated genes, including the Mendelian PD genes LRRK2 and VPS35. In addition, we find nuclear processes to be amongst those most significantly enriched within the PD-associated NSL interactome. These findings strengthen the role of the NSL complex in sporadic and familial PD, mediated by both its mitochondrial and nuclear functions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it