Elevated serum complement levels and higher gene copy number of complement <i>C4B</i> are associated with hypertension and effective response to statin therapy in childhood-onset systemic lupus erythematosus (SLE)
Bibliographic record
Abstract
Objective Systemic lupus erythematosus (SLE) features high frequency of cardiovascular disease (CVD) and fluctuating complement levels. The clinical trial Atherosclerosis Prevention in Pediatric Lupus Erythematosus (APPLE) aimed to evaluate whether atorvastatin treatment reduced the progression of atherosclerosis in 221 patients with childhood-onset SLE (cSLE), using carotid intima media thickness (CIMT) as surrogates. We leveraged APPLE biorepository and trial data to investigate the relationship between complement and CVD in cSLE. Methods Gene copy numbers (GCNs) for total C4 , C4A and C4B were measured by TaqMan-based real-time PCR and Southern blotting, and analysed with laboratory and clinical parameters through Student’s t-test and χ 2 analyses. Effects of total C4 , C4A and C4B GCNs on the response to placebo or atorvastatin treatment and progression of CIMT were examined by regression analyses. Results At baseline, C4 protein levels strongly correlated with GCNs of total C4 (p=1.8×10 −6 ). Each copy of C4 gene increased mean serum C4 by 3.28 mg/dL. Compared with those without hypertension (N=142), individuals with hypertension demonstrated significantly elevated serum levels for C4 and C3 at baseline and serially (C4: P=5.0×10 −25 ; C3: P=5.84×10 −20 ). Individuals with ≥2 C4B genes had 2.5 times the odds of having hypertension (p=0.016) and higher diastolic blood pressure (p=0.015) compared with those with C4B deficiency. At the study end, subjects with ≥2 C4B and atorvastatin treatment had significantly slower increase in CIMT compared with those treated with placebo (p=0.018). Conclusions cSLE with hypertension had elevated serum levels of C4 and C3 and higher GCN of C4B ; cSLE with ≥2 C4B genes would benefit from statins therapy to prevent atherosclerosis.
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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".