Common variants in<i>DRD2</i>are associated with sleep duration: the CARe consortium
Bibliographic record
Abstract
Sleep duration is implicated in the etiologies of chronic diseases and premature mortality. However, the genetic basis for sleep duration is poorly defined. We sought to identify novel genetic components influencing sleep duration in a multi-ethnic sample. Meta-analyses were conducted of genetic associations with self-reported, habitual sleep duration from seven Candidate Gene Association Resource (CARe) cohorts of over 25 000 individuals of African, Asian, European and Hispanic American ancestry. All individuals were genotyped for ∼50 000 SNPs from 2000 candidate heart, lung, blood and sleep genes. African-Americans had additional genome-wide genotypes. Four cohorts provided replication. A SNP (rs17601612) in the dopamine D2 receptor gene (DRD2) was significantly associated with sleep duration (P = 9.8 × 10(-7)). Conditional analysis identified a second DRD2 signal with opposite effects on sleep duration. In exploratory analysis, suggestive association was observed for rs17601612 with polysomnographically determined sleep latency (P = 0.002). The lead DRD2 signal was recently identified in a schizophrenia GWAS, and a genetic risk score of 11 additional schizophrenia GWAS loci genotyped on the IBC array was also associated with longer sleep duration (P = 0.03). These findings support a role for DRD2 in influencing sleep duration. Our work motivates future pharmocogenetics research on alerting agents such as caffeine and modafinil that interact with the dopaminergic pathway and further investigation of genetic overlap between sleep and neuro-psychiatric traits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".