A Novel Human Heterozygous <i>SCP2</i> Mutation Leads to Alterations in Lipid Metabolism
Bibliographic record
Abstract
Peroxisomal β‐oxidation plays a critical role in the detoxification of fatty acids and in cholesterol metabolism to form bile acids. The sterol carrier protein‐x (SCPx) is a lipid transfer protein with thiolase activity catalyzing the final step of the peroxisomal β‐oxidation process. SCPx deficiency has been previously reported in only two patients. Here, we report the third patient with SCPx deficiency and the first resulting from a heterozygous mutation in the SCP2 gene encoding SCPx. The patient presented with azoospermia, cardiac dysrhythmia, muscle wasting, and progressive brainstem neurodegeneration. The objective of this work was to investigate the link between the patient’s SCP2 mutation and his clinical presentations. We hypothesized that, because SCPx plays a critical role in the transport and metabolism of many lipids, the patient’s SCP2 mutation could lead to widespread alterations in lipid‐related genes and their target pathways. Patient fibroblasts (WESP) and normal human dermal fibroblasts (NHDF) were used to investigate the effects of the SCP2 mutation. RNA sequencing was used to identify lipid‐related differentially expressed genes, which led to the identification of metabolic pathways affected by the patient’s SCP2 mutation including cholesterol metabolism, peroxisome proliferator‐activated receptor (PPAR) signaling, and serotonergic synapse signaling. Lipidomic analyses were used to identify changes in the levels of various lipids including several sterols, free fatty acids, phospholipids, and acylcarnitines. This led to the identification of other affected metabolic pathways including steroid biosynthesis, bile acid metabolism, and fatty acid degradation. Collectively, these findings show that the patient’s heterozygous mutation in SCP2 led to alterations in several lipid metabolic pathways, which may explain certain clinical consequences of SCPx deficiency.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".