Schizophrenia Risk Mediated by microRNA Target Genes Overlapped by Genome-Wide Rare Copy Number Variation in 22q11.2 Deletion Syndrome
Bibliographic record
Abstract
The 22q11.2 deletion is associated with >20-fold increased risk for schizophrenia. The presence of gene DGCR8 in the 22q11.2 deletion region has suggested microRNA (miRNA) dysregulation as possibly contributing to this risk. We therefore investigated the role of miRNA target genes in the context of previously identified genome-wide risk for schizophrenia conveyed by additional copy number variation (CNV) in 22q11.2 deletion syndrome (22q11.2DS). Using a cohort of individuals with 22q11.2DS and documented additional rare CNVs overlapping protein coding genes, we compared those with schizophrenia ( n = 100) to those with no psychotic illness ( n = 118), assessing for rare CNVs that overlapped experimentally supported miRNA target genes. We further characterized the contributing miRNA target genes using gene set enrichment analyses and identified the miRNAs most implicated. Consistent with our hypothesis, we found a significantly higher proportion of individuals in the schizophrenia than in the non-psychotic group to have an additional rare CNV that overlapped one or more miRNA target genes (odds ratio = 2.12, p = 0.0138). Gene set analyses identified an enrichment of FMRP targets and genes involved in nervous system development and postsynaptic density amongst these miRNA target genes in the schizophrenia group. The miRNAs most implicated included miR-17-5p, miR-34a-5p and miR-124-3p. These results provide initial correlational evidence in support of a possible role for miRNA perturbation involving genes affected by rare genome-wide CNVs in the elevated risk for schizophrenia in 22q11.2DS, consistent with the multi-hit and multi-layered genetic mechanisms implicated in this and other forms of schizophrenia.
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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 | 0.000 | 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".