Dysregulated gene expression associated with inflammatory and translation pathways in activated monocytes from children with autism spectrum disorder
Bibliographic record
Abstract
Autism spectrum disorder (ASD) is a complex developmental disorder characterized by deficits in social interactions, communication, and stereotypical behaviors. Immune dysfunction is a common co-morbidity seen in ASD, with innate immune activation seen both in the brain and periphery. We previously identified significant differences in peripheral monocyte cytokine responses after stimulation with lipoteichoic acid (LTA) and lipopolysaccharide (LPS), which activate toll-like receptors (TLR)-2 and 4 respectively. However, an unbiased examination of monocyte gene expression in response to these stimulants had not yet been performed. To identify how TLR activation impacts gene expression in ASD monocytes, we isolated peripheral blood monocytes from 26 children diagnosed with autistic disorder (AD) or pervasive developmental disorder-not otherwise specified (PDDNOS) and 22 typically developing (TD) children and cultured them with LTA or LPS for 24 h, then performed RNA sequencing. Activation of both TLR2 and TLR4 induced expression of immune genes, with a subset that were differentially regulated in AD compared to TD samples. In response to LPS, monocytes from AD children showed a unique increase in KEGG pathways and GO terms that include key immune regulator genes. In contrast, monocytes from TD children showed a consistent decrease in expression of genes associated with translation in response to TLR stimulation. This decrease was not observed in AD or PDDNOS monocytes, suggesting a failure to properly downregulate a prolonged immune response in monocytes from children with ASD. As monocytes are involved in early orchestration of the immune response, our findings will help elucidate the mechanisms regulating immune dysfunction in ASD.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".