| Title: | A study in scarlet: MC1R as the main predictor of red hair and exemplar of the flip-flop effect |
| Journal: | Human Molecular Genetics |
| Published: | 16 Jan 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/30657907/ |
| DOI: | https://doi.org/10.1093/hmg/ddz018 |
| URL: | https://europepmc.org/articles/pmc6548228?pdf=render |
Publication 7443
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Abstract
Genetic variation in melanocortin-1 receptor (MC1R) is a known contributor to disease-free red hair in humans. Three loss-of-function single-nucleotide variants (rs1805007, rs1805008 and rs1805009) have been established as strongly correlated with red hair. The contribution of other loss-of-function MC1R variants (in particular rs1805005, rs2228479 and rs885479) and the extent to which other genetic loci are involved in red hair colour is less well understood. Here, we used the UK Biobank cohort to capture a comprehensive list of MC1R variants contributing to red hair colour. We report a correlation with red hair for both strong-effect variants (rs1805007, rs1805008 and rs1805009) and weak-effect variants (rs1805005, rs2228479 and rs885479) and show that their coefficients differ by two orders of magnitude. On the haplotype level, both strong- and weak-effect variants contribute to the red hair phenotype, but when considered individually, weak-effect variants show a reverse, negative association with red hair. The reversal of association direction in the single-variant analysis is facilitated by a distinguishing structure of MC1R, in which loss-of-function variants are never found to co-occur on the same haplotype. The other previously reported hair colour genes' variants do not substantially improve the MC1R red hair colour predictive model. Our best model for predicting red versus other hair colours yields an unparalleled area under the receiver operating characteristic of 0.96 using only MC1R variants. In summary, we present a comprehensive statistically derived characterization of the role of MC1R variants in red hair colour and offer a powerful, economical and parsimonious model that achieves unsurpassed performance.7 Authors
- Katerina Zorina-Lichtenwalter
- Ryan N Lichtenwalter
- Dima D Zaykin
- Marc Parisien
- Simon Gravel
- Andrey Bortsov
- Luda Diatchenko
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