Sexual dimorphism in metabolomic and phenotypic spectra of UGT deficiency: findings from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: Two of the most frequently deleted genes in the human genome are the UDP-glycosyltransferases UGT2B17 and UGT2B28. They encode metabolic enzymes of the glucuronidation pathway that plays a pivotal role in the maintenance of cellular homeostasis for a variety of small molecule metabolites. These deletions may impact health, yet their effects remain poorly understood. We evaluated the impact of UGT deficiency on the plasma metabolome and examined the association between altered metabolites and health outcomes. METHODS: The metabolomic profiles of 4262 proficient gene carriers were compared with those of 352 UGT2B17-deficient, 97 UGT2B28-deficient, and 20 double-gene-deficient individuals from the Canadian Longitudinal Study on Aging. Significant metabolites found in these comparisons were analyzed for their associations with common diseases. RESULTS: The unexpectedly broad molecular divergence found in UGT-deficient metabolomes, which affected > 10% of metabolites, implies their significant influence across various metabolite classes-particularly lipids and amino acids - extending beyond their known substrates. The metabolic profiles of UGT2B17-deficient men and UGT2B28-deficient women were most impacted, with UGT2B17 deficiency affecting various metabolites linked to metabolic diseases, arthritis, and osteoporosis. Metabolites impacted by a UGT2B28 deficiency such as amino acids, were linked to metabolic disorders in women. CONCLUSION: The findings significantly advance our understanding of the metabolic landscape associated with these frequently deleted genes in the human genome, which may influence susceptibility to various diseases in a sex-specific manner, laying the groundwork for determining their pathological mechanisms and impact on human health.
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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 | 0.001 | 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 | 0.001 |
| 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".