Congenital Heart Block Maternal Sera Autoantibodies Target an Extracellular Epitope on the α1G T-Type Calcium Channel in Human Fetal Hearts
Bibliographic record
Abstract
BACKGROUND: Congenital heart block (CHB) is a transplacentally acquired autoimmune disease associated with anti-Ro/SSA and anti-La/SSB maternal autoantibodies and is characterized primarily by atrioventricular (AV) block of the fetal heart. This study aims to investigate whether the T-type calcium channel subunit α1G may be a fetal target of maternal sera autoantibodies in CHB. METHODOLOGY/PRINCIPAL FINDINGS: We demonstrate differential mRNA expression of the T-type calcium channel CACNA1G (α1G gene) in the AV junction of human fetal hearts compared to the apex (18-22.6 weeks gestation). Using human fetal hearts (20-22 wks gestation), our immunoprecipitation (IP), Western blot analysis and immunofluorescence (IF) staining results, taken together, demonstrate accessibility of the α1G epitope on the surfaces of cardiomyocytes as well as reactivity of maternal serum from CHB affected pregnancies to the α1G protein. By ELISA we demonstrated maternal sera reactivity to α1G was significantly higher in CHB maternal sera compared to controls, and reactivity was epitope mapped to a peptide designated as p305 (corresponding to aa305-319 of the extracellular loop linking transmembrane segments S5-S6 in α1G repeat I). Maternal sera from CHB affected pregnancies also reacted more weakly to the homologous region (7/15 amino acids conserved) of the α1H channel. Electrophysiology experiments with single-cell patch-clamp also demonstrated effects of CHB maternal sera on T-type current in mouse sinoatrial node (SAN) cells. CONCLUSIONS/SIGNIFICANCE: Taken together, these results indicate that CHB maternal sera antibodies readily target an extracellular epitope of α1G T-type calcium channels in human fetal cardiomyocytes. CHB maternal sera also show reactivity for α1H suggesting that autoantibodies can target multiple fetal targets.
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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 | 0.000 | 0.000 |
| 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".