A Role of Amphiregulin in PDE3A-Mediated Renoprotection
Bibliographic record
Abstract
Background: A primary risk factor for chronic kidney disease (CKD) is hypertension. Autosomal-dominant hypertension with brachydactyly type E (HTNB) resembles essential hypertension, but the patients show almost no signs of end-organ damage such as CKD. HTNB is caused by mutations in the phosphodiesterase 3A (PDE3A) gene. Therefore, we hypothesize that HTNB-causing PDE3A-mutations are renoprotective and aim to gain insight into the underlying mechanisms. Methods: Using CRISPR/Cas9 technology, rats expressing PDE3A with a 3 amino acid deletion (PDE3A-Δ3aa) were generated. These animals recapitulate the HTNB phenotype. Rats with a functional PDE3A knockout (Functional Del) were used as an additional control. Inner medulla (IM) and residual kidney (RK) were investigated using biochemical, molecular biological, histological, and physiological approaches. Vasa recta contractility was measured. Results: The overall kidney morphology of the wild-type (WT), PDE3A-Δ3aa, and functional Del rats was similar. As in second-order mesenteric arteries, the media to lumen ratio of renal arteries was significantly increased in PDE3A-Δ3aa rats compared to wild-type. The relaxation of Vasa recta to forskolin was not affected in PDE3A-Δ3aa rats and appeared stronger in functional Del (both vs. WT). The mRNA and protein expression levels of proinflammatory cytokines and fibrosis markers remained at similar levels as in wild-type rats in both IM and RK. However, compared to wild-type animals, collagen levels in IM and RK of PDE3A-Δ3aa and in IM of functional Del rats were significantly increased. Amphiregulin (AREG) is a fibrosis- and thus kidney damage-inducing epidermal growth factor receptor (EGFR) agonist. The mRNA and protein expression levels of AREG were significantly decreased in IM of PDE3A-Δ3aa animals compared to wild-type, while its serum level remained unchanged. Conclusions: Our data reveal that PDE3A mutations protect the kidneys from hypertension-induced damage and suggested that AREG plays a role in the underlying mechanisms. Funding: Government Support - Non-U.S.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".