Ion Mobility QTOF-MS Untargeted Lipidomics of Human Serum Reveals a Metabolic Fingerprint for GNE Myopathy
Bibliographic record
Abstract
GNE myopathy, also known as hereditary inclusion body myopathy (HIBM), is a rare genetic muscle disorder marked by a gradual onset of muscle weakness in young adults. GNE myopathy (GNEM) is caused by bi-allelic variants in the UDP-N-acetylglucosamine 2-epimerase (UDP-GlcNAc 2-epimerase)/N-acetylmannosamine kinase (ManNAc kinase) gene (GNE), clinically resulting in the loss of ambulation within 10–20 years from the onset of the initial symptoms. The disease’s mechanism is poorly understood and non-invasive biomarkers are lacking, hindering effective therapy development. Based on the available evidence, we employed a lipidomic approach to study the serum lipid profile of GNE patients. The multivariate statistical analysis revealed a downregulation of carnitines, as well as of lysophosphatidylcholines, in sera samples derived from GNEM patients. Furthermore, we identified lower levels of sphingomyelins and, concomitantly, high levels of ceramides in serum samples from GNEM patients when compared to control samples derived from healthy donors. Moreover, the GNEM serum samples showed the upregulation of Krebs cycle intermediates, in addition to a decrease in oxaloacetic acid. The correlated data gathered in this study can offer a promising diagnostic panel of complex lipids and polar metabolites that can be used in clinic for GNEM in terms of a metabolic fingerprint measurable in a minimally invasive manner.
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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 | 0.000 |
| 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) | 0.000 | 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".