The Sweat Metabolome of Screen-Positive Cystic Fibrosis Infants: Revealing Mechanisms beyond Impaired Chloride Transport
Bibliographic record
Abstract
The sweat chloride test remains the gold standard for confirmatory diagnosis of cystic fibrosis (CF) in support of universal newborn screening programs. However, it provides ambiguous results for intermediate sweat chloride cases while not reflecting disease progression when classifying the complex CF disease spectrum given the pleiotropic effects of gene modifiers and environment. Herein we report the first characterization of the sweat metabolome from screen-positive CF infants and identify metabolites associated with disease status that complement sweat chloride testing. Pilocarpine-stimulated sweat specimens were collected independently from two CF clinics, including 50 unaffected infants (e.g., carriers) and 18 confirmed CF cases. Nontargeted metabolite profiling was performed using multisegment injection-capillary electrophoresis-mass spectrometry as a high throughput platform for analysis of polar/ionic metabolites in volume-restricted sweat samples. Amino acids, organic acids, amino acid derivatives, dipeptides, purine derivatives, and unknown exogenous compounds were identified in sweat when using high resolution tandem mass spectrometry, including metabolites associated with affected yet asymptomatic CF infants, such as asparagine and glutamine. Unexpectedly, a metabolite of pilocarpine, used to stimulate sweat secretion, pilocarpic acid, and a plasticizer metabolite from environmental exposure, mono(2-ethylhexyl)phthalic acid, were secreted in the sweat of CF infants at significantly lower concentrations relative to unaffected CF screen-positive controls. These results indicated a deficiency in human paraoxonase, an enzyme unrelated to mutations to the cystic fibrosis transmembrane conductance regulator (CFTR) and impaired chloride transport, which is a nonspecific arylesterase/lactonase known to mediate inflammation, bacterial biofilm formation, and recurrent lung infections in affected CF children later in life. This work sheds new light into the underlying mechanisms of CF pathophysiology as required for new advances in precision medicine of orphan diseases that benefit from early detection and intervention, including new molecular targets for therapeutic intervention.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".