Genome-wide methylation analysis of early-onset schizophrenia
Bibliographic record
Abstract
OBJECTIVE: Schizophrenia (SCZ) is a debilitating disease with a complex genetic cause in which age at onset may reflect genetic vulnerability. Though there has been some association between genetic polymorphisms and age of onset, there has been little exploration of the role of epigenetic processes. We sought to explore the influence of DNA methylation, a key epigenetic mechanism, and its association with the age of onset of illness. METHODS: One hundred thirty-eight participants aged 18-75 years and previously diagnosed with SCZ spectrum disorders by the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (SCID DSM-5) were recruited. Venous blood was collected and genome-wide DNA methylation was quantified using the Illumina Infinium HumanMethylation450 BeadChip array. Individual CpG sites and regions of differential methylation were explored by the age of onset; covariates included age, sex, as well as white blood cell composition. RESULTS: Binary grouping (early vs. late onset) revealed four intergenic CpG sites on chromosome 2 that were above the expected P-value threshold, with hypermethylation of the CpG site cg10392614 most strongly associated with early-onset SCZ. The four most strongly associated CpG sites, including cg 10392614, were intergenic. Continuous analysis revealed the top CpG site to be cg11723066 , which is linked to the JAM3 gene, with hypomethylation associated with earlier onset; however, results were below the expected P-value threshold. CONCLUSION: Studies on DNA methylation in the first-episode psychosis population may help further our understanding of the role of epigenetics in the age of onset of SCZ.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".