DNA methylation in the human frontal cortex reveals a putative mechanism for age-by-disease interactions
Bibliographic record
Abstract
Abstract A consistent gene set undergoes age-associated expression changes in the human cerebral cortex, and our Age-by-Disease Model posits that these changes contribute to psychiatric diseases by “pushing” the expression of disease-associated genes in disease-promoting directions. DNA methylation (DNAm) is an attractive candidate mechanism for age-associated gene expression changes. We used the Illumina HumanMethylation450 array to characterize genome-wide DNAm in the postmortem orbital frontal cortex from 20 younger (<42 years) and 19 older (>60 years) subjects. DNAm data were integrated with existing normal brain aging expression data and sets of psychiatric disease risk genes to test the hypothesis that age-associated DNAm changes contribute to age-associated gene expression changes and, by extension, susceptibility to psychiatric diseases. We found that age-associated differentially methylated regions (aDMRs) are common, robust, bidirectional, concentrated in CpG island shelves and sea, depleted in CpG islands, and enriched among genes undergoing age-associated expression changes (OR = 2.30, p = 1.69 × 10 −27 ). We found the aDMRs are enriched among genetic association-based risk genes for schizophrenia, Alzheimer’s disease (AD), and major depressive disorder (MDD) (OR = 2.51, p = 0.00015; OR = 2.38, p = 0.036; and OR = 3.08, p = 0.018, respectively) as well as expression-based MDD-associated genes (OR = 1.48, p = 0.00012). Similar patterns of enrichment were found for aDMRs that correlate with local gene expression. These results were replicated in a large publically-available dataset, and confirmed by meta-analysis of the two datasets. Our findings suggest DNAm is a molecular mechanism for age-associated gene expression changes and support a role for DNAm in age-by-disease interactions through preferential targeting of disease-associated genes.
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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".