Genetic Variation in C-Reactive Protein (CRP) Gene May Be Associated with Risk of Systemic Lupus Erythematosus and CRP Concentrations
Bibliographic record
Abstract
OBJECTIVE: The gene coding for C-reactive protein (CRP) is located on chromosome 1q23.2, which falls within a linkage region thought to harbor a systemic lupus erythematosus (SLE) susceptibility gene. Recently, 2 single-nucleotide polymorphisms (SNP) in the CRP gene (+838, +2043) have been shown to be associated with CRP concentrations and/or SLE risk in a British family-based cohort. Our study was done to confirm the reported association in an independent population-based case-control cohort, and also to investigate the influence of 3 additional CRP tagSNP (-861, -390, +90) on SLE risk and serum CRP concentrations. METHODS: DNA from 337 Caucasian women who met the American College of Rheumatology criteria for definite (n = 324) or probable (n = 13) SLE and 448 Caucasian healthy female controls was genotyped for 5 CRP tagSNP (-861, -390, +90, +838, +2043). Genotyping was performed using restriction fragment length polymorphism-polymerase chain reaction, pyrosequencing, or TaqMan assays. Serum CRP levels were measured using ELISA. Association studies were performed using the chi-squared distribution, Z-test, Fisher's exact test, and analysis of variance. Haplotype analysis was performed using EH software and the haplo.stats package in R 2.1.2. RESULTS: While none of the SNP were found to be associated with SLE risk individually, there was an association with the 5 SNP haplotypes (p < 0.001). Three SNP (-861, -390, +90) were found to significantly influence serum CRP level in SLE cases, both independently and as haplotypes. CONCLUSION: Our data suggest that unique haplotype combinations in the CRP gene may modify the risk of developing SLE and influence circulating CRP levels.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".