Association of C4 Null Alleles and Persistently Low C4 in Asian Indian Patients With Systemic Lupus Erythematosus
Bibliographic record
Abstract
The association between heterozygous C4 deficiency and systemic lupus erythematosus (SLE) is unclear. There is a lack of data in South Asian Indians on any possible association of C4A and C4B null alleles with lupus. We aimed to study the prevalence of C4A and C4B null alleles in a cohort of SLE patients with persistently low C4 levels compared to healthy controls (HC). Patients with SLE and HC were recruited for this prospective observational study. C4 (C4AQ and C4BQ) polymorphisms were tested using a touch-down polymerase chain reaction protocol. One hundred and three SLE patients and 103 HC were included in the study. Persistently low C4 levels were observed in 25 (23.6%) of SLE. The frequency of C4A and C4B null alleles was similarly distributed across SLE and HC (4% and 3.8%, respectively). Univariate analysis showed a low age, higher proportion of elevated dsDNA, and higher positive anti-SSA (Sjogren's syndrome-related antigen A) antibodies at presentation were associated in SLE patients with the null allele group on comparison without the null allele group. However, these associations did not persist in the multivariate analysis. In conclusion, C4 null allele frequency was similar in SLE and HC. No characteristic associations were observed in SLE with C4 null alleles was observed. Therefore, C4 null allele is an unlikely explanation for persistently low C4 in South Indian Asian patients with lupus.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".