The genetic architecture of obsessive-compulsive disorder: alleles across the frequency spectrum contribute liability to OCD
Bibliographic record
Abstract
Abstract Objective Obsessive-compulsive disorder (OCD) is known to be substantially heritable; however, the contribution of common genetic variation across the allele frequency spectrum to this heritability remains uncertain. We use two new, homogenous cohorts to estimate heritability of OCD from common genetic variation and contrast results with prior studies. Methods The sample consisted of 2096 Swedish-born individuals diagnosed with OCD and 4609 controls, all genotyped for common genetic variants, specifically >400,000 single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥ 0.01. Using genotypes of these SNPs to estimate distant familial relationships among individuals, we estimated heritability of OCD, both overall and partitioned according to MAF bins. Results We estimated narrow-sense heritability of 28% (SE=4%). The estimate was robust, varying only modestly under different models. Contrary to an earlier study, however, SNPs with MAF between 0.01 and 0.05 accounted for 8% of heritability and estimated heritability per bin roughly follows expectations based on a simple model for SNP-based heritability. Conclusions These results indicate that common inherited risk variation (MAF ≥ 0.01) accounts for most of the heritable variation in OCD. SNPs with low MAF contribute meaningfully to the heritability of OCD and the results are consistent with expectation under the “infinitesimal model,” where risk is influenced by a large number of loci across the genome and across MAF bins.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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 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".