Gender-Specific Plasma Proteomic Biomarkers in Patients with Anderson–Fabry disease
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Bibliographic record
Abstract
AIMS: Anderson-Fabry disease (AFD) is an important X-linked metabolic disease resulting in progressive end-organ involvement, with cardiac disease being the dominant determinant of survival in a gender-dependent manner. Recent epidemiological screening for AFD suggests the prevalence is much higher than previously recognized, with estimates of 1:3000. Our aim was to discover novel plasma biomarker signatures in adult patients with AFD. METHODS AND RESULTS: We used an unbiased proteomic screening approach to discover novel plasma biomarker signatures. In the discovery cohort of 46 subjects, 14 healthy controls and 32 patients with AFD, we used a mass spectrometry iTRAQ proteomic approach followed by multiple reaction monitoring (MRM) assays to identify biomarkers. Of the 38 protein groups discovered by iTRAQ, 18 already had existing MRM assays. Based on MRM, we identified an eight-protein biomarker panel (22 kDa protein, afamin, α1 antichymotrypsin, apolipoprotein E, β-Ala His dipeptidase, haemoglobin α-2, isoform 1 of sex hormone-binding globulin, and peroxiredoxin 2) that was very specific and sensitive for male AFD patients. In female AFD patients, we identified a nine-marker panel of proteins with only three proteins, apolipoprotein E, haemoglobin α-2, and peroxiredoxin 2, common to both genders, suggesting a gender-specific alteration in plasma biomarkers in patients with AFD. The biomarkers were validated in plasma samples from 48 subjects using MRM, and they performed inferiorly in patients with heart failure. CONCLUSIONS: We have identified gender-specific plasma protein biomarker panels that are specific and sensitive for the AFD phenotype. The gender-specific panels offer important insight into potential differences in pathophysiology and prognosis between males and females with AFD.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it