Immune network dysregulation associated with child neurodevelopmental delay: modulatory role of prenatal alcohol exposure
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that cytokine imbalances may be at the root of deficits that occur in numerous neurodevelopmental disorders, including schizophrenia and autism spectrum disorder. Notably, while clinical studies have demonstrated maternal cytokine imbalances with alcohol consumption during pregnancy-and data from animal models have identified immune disturbances in alcohol-exposed offspring-to date, immune alterations in alcohol-exposed children have not been explored. Thus, here we hypothesized that perturbations in the immune environment as a result of prenatal alcohol exposure will program the developing immune system, and result in immune dysfunction into childhood. Due to the important role of cytokines in brain development/function, we further hypothesized that child immune profiles might be associated with their neurodevelopmental status. METHODS: As part of a longitudinal study in Ukraine, children of mothers reporting low/no alcohol consumption or moderate-to-heavy alcohol consumption during pregnancy were enrolled in the study and received neurodevelopmental assessments. Group stratification was based on maternal alcohol consumption and child neurodevelopmental status resulting in the following groups: A/TD, alcohol-consuming mother, typically developing child; A/ND, alcohol-consuming mother, neurodevelopmental delay in the child; C/TD, control mother (low/no alcohol consumption), typically development child; and C/ND, control mother, neurodevelopmental delay in the child. Forty cytokines/chemokines were measured in plasma and data were analyzed using regression and constrained principle component analysis. RESULTS: Analyses revealed differential cytokine network activity associated with both prenatal alcohol exposure and neurodevelopmental status. Specifically, alcohol-exposed children showed activation of a cytokine network including eotaxin-3, eotaxin, and bFGF, irrespective of neurodevelopmental status. However, another cytokine network was differentially activated based on neurodevelopmental outcome: A/TD showed activation of MIP-1β, MDC, and MCP-4, and inhibition of CRP and PlGF, with opposing pattern of activation/inhibition detected in the A/ND group. By contrast, in the absence of alcohol-exposure, activation of a network including IL-2, TNF-β, IL-10, and IL-15 was associated with neurodevelopmental delay. CONCLUSIONS: Taken together, this comprehensive assessment of immune markers allowed for the identification of unique immune milieus that are associated with alcohol exposure as well as both alcohol-related and alcohol-independent neurodevelopmental delay. These findings are a critical step towards establishing unique immune biomarkers for alcohol-related and alcohol-independent neurodevelopmental delay.
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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 | 0.001 |
| 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".