Cognitive Development and Brain Gray Matter Susceptibility to Prenatal Adversities: Moderation by the Prefrontal Cortex Brain-Derived Neurotrophic Factor Gene Co-expression Network
Bibliographic record
Abstract
Background: Previous studies focused on the relationship between prenatal conditions and neurodevelopmental outcomes later in life, but few have explored the interplay between gene co-expression networks and prenatal adversity conditions on cognitive development trajectories and gray matter density. Methods: We analyzed the moderation effects of an expression polygenic score (ePRS) for the Brain-derived Neurotrophic Factor gene network (BDNF ePRS) on the association between prenatal adversity and child cognitive development. A score based on genes co-expressed with the prefrontal cortex (PFC) BDNF was created, using the effect size of the association between the individual single nucleotide polymorphisms (SNP) and the BDNF expression in the PFC. Cognitive development trajectories of 157 young children from the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort were assessed longitudinally in 4-time points (6, 12, 18, and 36 months) using the Bayley-II mental scales. Results: Linear mixed-effects modeling indicated that BDNF ePRS moderates the effects of prenatal adversity on cognitive growth. In children with high BDNF ePRS, higher prenatal adversity was associated with slower cognitive development in comparison with those exposed to lower prenatal adversity. Parallel-Independent Component Analysis (pICA) suggested that associations of expression-based SNPs and gray matter density significantly differed between low and high prenatal adversity groups. The brain IC included areas involved in visual association processes (Brodmann area 19 and 18), reallocation of attention, and integration of information across the supramodal cortex (Brodmann area 10). Conclusion: Cognitive development trajectories and brain gray matter seem to be influenced by the interplay of prenatal environmental conditions and the expression of an important BDNF gene network that guides the growth and plasticity of neurons and synapses.
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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 | 0.001 |
| 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".