Genome-wide association study of pigmentary traits (skin and iris color) in individuals of East Asian ancestry
Bibliographic record
Abstract
Background Currently, there is limited knowledge about the genetics underlying pigmentary traits in East Asian populations. Here, we report the results of the first genome-wide association study of pigmentary traits (skin and iris color) in individuals of East Asian ancestry. Methods We obtained quantitative skin pigmentation measures (M-index) in the inner upper arm of the participants using a portable reflectometer ( N = 305). Quantitative measures of iris color (expressed as L*, a* and b* CIELab coordinates) were extracted from high-resolution iris pictures ( N = 342). We also measured the color differences between the pupillary and ciliary regions of the iris (e.g., iris heterochromia). DNA samples were genotyped with Illumina’s Infinium Multi-Ethnic Global Array (MEGA) and imputed using the 1000 Genomes Phase 3 samples as reference haplotypes. Results For skin pigmentation, we did not observe any genome-wide significant signal. We followed-up in three independent Chinese samples the lead SNPs of five regions showing multiple common markers (minor allele frequency ≥ 5%) with good imputation scores and suggestive evidence of association ( p -values < 10 −5 ). One of these markers, rs2373391 , which is located in an intron of the ZNF804B gene on chromosome 7, was replicated in one of the Chinese samples ( p = 0.003). For iris color, we observed genome-wide signals in the OCA2 region on chromosome 15. This signal is driven by the non-synonymous rs1800414 variant, which explains 11.9%, 10.4% and 6% of the variation observed in the b*, a* and L* coordinates in our sample, respectively. However, the OCA2 region was not associated with iris heterochromia. Discussion Additional genome-wide association studies in East Asian samples will be necessary to further disentangle the genetic architecture of pigmentary traits in East Asian populations.
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 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".