Age- and Disease-Dependent HERV-W Envelope Allelic Variation in Brain: Association with Neuroimmune Gene Expression
Bibliographic record
Abstract
BACKGROUND: The glycoprotein, Syncytin-1, is encoded by a human endogenous retrovirus (HERV)-W env gene and is capable of inducing neuroinflammation. The specific allele(s) responsible for Syncytin-1 expression in the brain is uncertain. Herein, HERV-W env diversity together with Syncytin-1 abundance and host immune gene profiles were examined in the nervous system using a multiplatform approach. RESULTS: HERV-W env sequences were encoded by multiple chromosomal encoding loci in primary human neurons compared with less chromosomal diversity in astrocytes and microglia (p<0.05). HERV-W env RNA sequences cloned from brains of patients with systemic or neurologic diseases were principally derived from chromosomal locus 7q21.2. Within the same specimens, HERV-W env transcript levels were correlated with the expression of multiple proinflammatory genes (p<0.05). Deep sequencing of brain transcriptomes disclosed the env transcripts to be the most abundant HERV-W transcripts, showing greater expression in fetal compared with healthy adult brain specimens. Syncytin-1's expression in healthy brain specimens was derived from multiple encoding loci and linked to distinct immune and developmental gene profiles. CONCLUSIONS: Syncytin-1 expression in the brain during disease was associated with neuroinflammation and was principally encoded by a full length provirus. The present studies also highlighted the diversity in HERV gene expression within the brain and reinforce the potential contributions of HERV expression to neuroinflammatory diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".