Lipidomic analysis of human TANGO2-deficient cells suggests a lipid imbalance as a cause of TANGO2 deficiency disease
Bibliographic record
Abstract
ABSTRACT TANGO2 deficiency disease (TDD) is a multisystem disease caused by variants in the TANGO2 gene. Symptoms include neurodevelopmental delays, seizures and potentially lethal metabolic crises and cardiac arrhythmias. While the function of TANGO2 remains elusive, vitamin B5/pantothenic acid supplementation has been shown to alleviate symptoms in a fruit fly model and has also been used to treat individuals suffering from TDD with success. Since vitamin B5 is the precursor to the lipid activator coenzyme A (CoA), we hypothesized that TANGO2-deficient cells would display changes in the lipid profile compared to control and that these changes would be rescued by vitamin B5 supplementation. In addition, the specific changes seen might point to a pathway in which TANGO2 functions. Indeed, we found profound changes in the lipid profile of human TANGO2-deficient cells as well as an increased pool of free fatty acids in both human cells devoid of TANGO2 and Drosophila harboring a previously described TANGO2 loss of function allele. All these changes were reversed upon vitamin B5 supplementation. Pathway analysis showed significant increases in triglyceride as well as in lysophospholipid levels as the top enriched pathways in the absence of TANGO2. Consistent with a defect in triglyceride metabolism, we found changes in lipid droplet numbers and sizes in the absence of TANGO2 compared to control. Our data will allow for comparison between other model systems of TDD and the homing in on critical lipid imbalances that lead to the disease state.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".