Painkillers Work Best on Redheads
Gene for Red Hair Makes Redheaded Women More Sensitive to Painkillers
March 28, 2003 -- There's a reason why some women have gorgeous red hair and fair skin -- and it's called a gene. Turns out, that gene for red hair has an interesting twist -- it also makes redheaded women more sensitive to painkillers. It's a new finding from Canada that adds to other research on female-specific pain pathways in the brain.
"While we believe pain is the same in all women of all hair colors, our study shows women with red hair respond better to the pain-killing drug we tested than anyone else -- including men," says lead researcher Jeffrey Mogil, PhD, a psychology professor at McGill University in Montreal. His study is published in the April Proceedings of the National Academy of Sciences.
Analgesics that target receptors on a female-specific pain pathway -- called kappa-opioid receptors -- have been reported to work only in women. In laboratory studies, Mogil and his colleagues have identified a gene that may be responsible for this sex-specific difference in pain response.
The gene, called Mc1r, was first linked with pigmentation -- not with pain response. Variations of this gene cause red hair and fair skin in humans.
In this study, researchers tested the effects of the kappa-specific analgesic on laboratory mice that have an inactive version of Mc1r similar to the "redhead variation" in humans. The normal mice had the sex-specific pain response to these kappa-specific analgesics, but the mutants mice did not show sex-specific responses to the painkiller.
The researchers then tested another analgesic on humans -- both men and women -- all with different variations of the Mc1r gene, with different hair colors and skin types.
The upshot: In men, no differences in response were seen whether the men had the Mr1c or not. In women, only the redheaded, fair-skinned ones showed a greater response.
The study demonstrates not only sex differences in pain and analgesic sensitivity but also shows promise in identifying new areas for drug development.