Circulating Levels of Dickkopf-Related Protein 1 Decrease as Measured GFR Declines and Are Associated with PTH Levels
Bibliographic record
Abstract
BACKGROUND: The Wnt/β-catenin pathway has been implicated in the development of adynamic bone disease in early-stage chronic kidney disease (CKD). Dickkopf-related protein 1 (DKK1) and sclerostin are antagonists of the Wnt/β-catenin pathway yet have not been widely used as clinical indicators of bone disease. This study characterized levels of DKK1, sclerostin, and other biomarkers of mineral metabolism in participants across a spectrum of inulin-measured glomerular filtration rate (GFR). METHODS: GFR was measured by urinary inulin clearance (mGFR) in 90 participants. Blood samples were obtained for measurement of circulating DKK1, sclerostin, fibroblast growth factor 23 (FGF-23), parathyroid hormone (PTH), calcium, phosphate, α-klotho, and vitamin D metabolites including 25-hydroxyvitamin D3 and 1,25-dihydroxyvitamin D3. Spearman correlations and linear regressions were used where appropriate to examine the associations between measured values. RESULTS: The median [IQR] age was 64 years [53.0-71.0], and the median [IQR] mGFR was 32.6 [21.7-60.6] mL/min. DKK1 decreased (r = 0.6, p < 0.001) and sclerostin increased (r = -0.4, p < 0.001) as kidney function declined, and both were associated with phosphate, PTH, FGF-23, and 1,25-dihydroxyvitamin D3 in the unadjusted analysis. After adjustment for age and mGFR, DKK1 remained significantly associated with PTH. CONCLUSION: The results of this study demonstrate opposing trends in Wnt/β-catenin pathway inhibitors, DKK1 and sclerostin, as mGFR declines. Unlike sclerostin, DKK1 levels decreased significantly as mGFR declined and was independently associated with PTH. Future studies should determine whether measurement of Wnt signaling inhibitors may be useful in predicting bone histomorphometric findings and important clinical outcomes in patients with CKD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".