Human pigmentation variation: Evolution, genetic basis, and implications for public health
Bibliographic record
Abstract
Pigmentation, which is primarily determined by the amount, the type, and the distribution of melanin, shows a remarkable diversity in human populations, and in this sense, it is an atypical trait. Numerous genetic studies have indicated that the average proportion of genetic variation due to differences among major continental groups is just 10-15% of the total genetic variation. In contrast, skin pigmentation shows large differences among continental populations. The reasons for this discrepancy can be traced back primarily to the strong influence of natural selection, which has shaped the distribution of pigmentation according to a latitudinal gradient. Research during the last 5 years has substantially increased our understanding of the genes involved in normal pigmentation variation in human populations. At least six genes have been identified using genotype/phenotype association studies and/or direct functional assays, and there is evidence indicating that several additional genes may be playing a role in skin, hair, and iris pigmentation. The information that is emerging from recent studies points to a complex picture where positive selection has been acting at different genomic locations, and for some genes only in certain population groups. There are several reasons why elucidating the genetics and evolutionary history of pigmentation is important. 1) Pigmentation is a trait that should be used as an example of how misleading simplistic interpretations of human variation can be. It is erroneous to extrapolate the patterns of variation observed in superficial traits such as pigmentation to the rest of the genome. It is similarly misleading to suggest, based on the "average" genomic picture, that variation among human populations is irrelevant. The study of the genes underlying human pigmentation diversity brings to the forefront the mosaic nature of human genetic variation: our genome is composed of a myriad of segments with different patterns of variation and evolutionary histories. 2) Pigmentation can be very useful to understand the genetic architecture of complex traits. The pigmentation of unexposed areas of the skin (constitutive pigmentation) is relatively unaffected by environmental influences during an individual's lifetime when compared with other complex traits such as diabetes or blood pressure, and this provides a unique opportunity to study gene-gene interactions without the effect of environmental confounders. 3) Pigmentation is of relevance from a public health perspective, because of its critical role in photoprotection and vitamin D synthesis. Fair-skinned individuals are at higher risk of several types of skin cancer, particularly in regions with high UVR incidence, and dark-skinned individuals living in high latitude regions are at higher risk for diseases caused by deficient or insufficient vitamin D levels.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".