Phenylethanolamine N-Methyltransferase Gene Polymorphisms and Adverse Outcomes in Acute Kidney Injury
Bibliographic record
Abstract
BACKGROUND/AIMS: The catecholaminergic pathway is important in the physical stress response; however, its role is not well understood in acute kidney injury (AKI). We studied single nucleotide polymorphisms (SNPs) of phenylethanolamine N-methyltransferase (PNMT), the terminal enzyme of the catecholaminergic pathway, and their association with adverse outcomes in AKI. METHODS: We performed a case-control study of 961 Caucasian subjects (194 with AKI and 767 controls). The PNMT promoter G-161A (rs876493) and coding A+1543G (rs5638) SNPs were genotyped and haplotypes generated. The outcomes of interest were the development of AKI, in-hospital mortality, dialysis requirement, oliguria, and hemodynamic shock. Urine catecholamines were measured in cases to explore genotype-phenotype correlations. RESULTS: The PNMT +1543 G allele was associated with AKI [odds ratio (OR) 2.19, 95% confidence interval (CI): 1.04-4.60]. For AKI cases, each PNMT -161 A allele was associated with lower mortality (OR 0.58, 95% CI: 0.35-0.99) and hemodynamic shock (OR 0.63, 95% CI: 0.40-1.00). The PNMT +1543 G allele was associated with oliguria (OR 3.35, 95% CI: 1.13-9.95). Urine adrenaline was associated with increased hemodynamic shock and mortality, but was lowest in PNMT -161 A/A carriers. CONCLUSION: In Caucasians, PNMT SNPs are associated with the development of AKI, disease severity, and in-hospital mortality. The adrenergic pathway provides another area of focus in the study of AKI.
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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) | 0.000 | 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".