Relationships between C-reactive protein concentration and genotype in healthy volunteers
Bibliographic record
Abstract
BACKGROUND: Polymorphisms of the gene for C-reactive protein (CRP) alter baseline serum CRP concentrations. The impact of polymorphisms of the CRP gene (genotype) on the normal range for CRP concentrations (phenotype) has not been determined. This study evaluated the median serum CRP concentrations in normal subjects stratified for CRP genotype, after adjustment for relevant covariates as well as polymorphisms in tumor necrosis factor-alpha (TNF-alpha) and interleukin 6 (IL-6) genotypes. METHODS: A total of 423 healthy adults without infectious or inflammatory conditions undergoing phlebotomy for laboratory testing were enrolled in the study. Assays for serum high sensitivity CRP (hs-CRP), IL-6, and TNF-alpha genotypes were measured. RESULTS: The median hs-CRP concentration was 0.96 mg/L (range <0.1-40.15 mg/L). The CRP 1444 C/T heterozygote and homozygote genotype was associated with a significantly higher hs-CRP concentration (p<0.05), even after multivariate analysis controlling for age, gender, body mass index, hypertension, dyslipidemia and obstructive sleep apnea. The CRP 286 C/T/A heterozygote genotype was significant (p<0.05) in the multi-variable analysis, univariately was borderline significant (p=0.052). CONCLUSIONS: Selected genetic polymorphisms of the CRP gene are independently associated with higher basal hs-CRP concentrations in healthy adults. Larger studies are needed to perform haplotype analyses and to adequately evaluate the relationship between hs-CRP and genetic polymorphisms with lower allelic frequencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 | 0.000 |
| 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".