Archive for January, 2011

An interesting story by Osagie K. Obasogie of the Huffington Post discusses proposals to lower the bar for collecting and keeping the DNA samples of individuals arrested (but, as we shall see, not necessarily convicted) of crimes. For example, David Paterson, the Govenor of New York, has suggested a law whereby the state DNA database would include not only individuals arrested for felonies but also some individuals that were convicted of misdemeanors. Another example:

[T]he United States House of Representatives recently passed legislation that creates millions of dollars in incentives to encourage states to mandate taking DNA samples from individuals arrested for (but not necessarily charged with or convicted of) certain crimes. This provision (H.R. 4614) is part of the Katie Sepich Enhanced DNA Collection Act of 2010, named after the tragic rape and murder of a young New Mexico woman. The bill provides a 5% bonus in federal money granted to states under a justice assistance program for “minimum DNA collection,” which includes taking DNA samples from felony arrestees of specified major crimes. A 10% bonus would be given to states that partake in “enhanced” collection, which includes the extra step of taking DNA from those arrested for specified lesser crimes. 

As Obasogie points out, this may lead to a situation where the DNA of innocent people is stored along with that of the guilty. For more information on this and other bioethical issues, visit the Center for Genetics and Society

What do you think of the government holding on to the private and sensitive information that is potentially held in an individual’s DNA profile? Does this impinge on civil liberties? 

UPDATE 2.1.2011. A law that will expand the collection of DNA in North Carolina will go into effect on Feb. 2, 2011. Read more at WUNC.


Robert Rowthorn, a professor emeritus of economics at Cambridge University, published a study that models population genetics scenarios based on the observation that religious individuals have, on average, higher fertility than non-religious individuals. In an extreme example, Rowthorn cites studies that show Amish and ultra-orthodox Jews have fertility rates 3 to 4 times higher than the secular average. Rowthorn goes on to build mathematical models that show how religiosity can spread throughout the population. From the paper’s abstract:

The paper considers the effect of religious defections [i.e., abandoning one’s religion] and exogamy [i.e., marrying outside one’s religious denomination or marrying a non-religious individual] on the religious and genetic composition of society. Defections reduce the ultimate share of the population with religious allegiance and slow down the spread of the religiosity gene. However, provided the fertility differential persists, and people with a religious allegiance mate mainly with people like themselves, the religiosity gene will eventually predominate despite a high rate of defection. This is an example of ‘cultural hitch-hiking’, whereby a gene spreads because it is able to hitch a ride with a high-fitness cultural practice.    

This models assumes, of course, that there is some sort of genetic underpinning for religious belief or, as Rowthorn puts it “[b]elief in the supernatural, obedience to authority, and affinity for ceremony and ritual depend on genetically based features of the human brain.” Naturally, there is a lot of debate on the biological foundation of religious belief. A great place to start is Carl Zimmer’s review of Dean H. Hamer’s “The God Gene.”

What do you think? What are some of the problems inherent in this debate?


Rowthorn, R. (2011). Religion, fertility, and genes: a dual inheritance model. Proceedings of the Royal Society B

Hamer, D.H. (2005). The God Gene: How Faith is Hardwired into Our Genes. Doubleday: New York.

What would you do if a genetic screening indicated that you had a 70% chance of developing Alzheimer’s? Well, a recent study published in the New England Journal of Medicine suggests that people really don’t seem to care. From a summary in the New York Times:

…the Scripps Translational Science Institute followed more than 2,000 people who had a genomewide scan by the Navigenics company. After providing saliva, they were given estimates of their genetic risk for more than 20 different conditions, including obesity, diabetes, rheumatoid arthritis, several forms of cancer, multiple sclerosis and Alzheimer’s. About six months after getting the test results, delivered in a 90-page report, the typical person’s level of psychological anxiety was no higher than it had been before taking the test.

Although they were offered sessions, at no cost, with genetic counselors who could interpret the results and allay their anxieties, only 10 percent of the people bothered to take advantage of the opportunity. They apparently didn’t feel overwhelmed by the information, and it didn’t seem to cause much rash behavior, either.

Would you want to be screened for diseases? What would you do with the information once you had it?


Bloss, C.S., Schorck, N.J., Topol, E.J. (2011). Effect of direct-to-consumer genomewide profiling to assess disease risk. New England Journal of Medicine

Gene doping

Doping among elite athletes may have reached a new level…

As laid out by Discovery News, some athletes are trying to “turn on molecular switches inside the body’s own DNA to produce more oxygen-carrying blood or creating bigger muscle cells.” In essence, people are trying to make the genes that code for oxygen carrying capacity or muscle cell development work harder and faster. Scientists are in the process of developing a test for this sort of thing that may be in use before the 2012 Olympic Games in London.

One of the more interesting aspects of this story is the potential side effects. For example, mice that were genetically modified to produce more red blood cells (whose major job is to carry oxygen throughout the body) actually died of stroke because too many cells were being created. In another example, experts suspect that modifying the genes that code for muscle cell creation may only work on part of the body–you could have a super buff right arm and a normal left arm, for instance.

A team of researchers have scanned genes that are known to impact hair color and found that analyzing an individual’s DNA can predict their hair color with a high degree of accuracy. There are upwards of a dozen or so genes that may contribute to hair color in some way, and mutations that change a single nucleotide (Single Nucleotide Polymorphisms, or SNPs) in a gene are largely responsible for color and shade differences. From a summary in Wired Science:

To see if hair color could be predicted using 45 SNPs from 13 genes, Kayser and his team sampled DNA from 385 Polish volunteers and had dermatologists record their hair color. Their testing singled out 13 SNPs on 11 genes that could predict red and black hair colors with about 90 percent accuracy, as well as blond and brown colors with better than 80 percent accuracy.

As if you needed another excuse not to leave your DNA at a crime scene…

One of the genes examined in this study was MC1R, mutations in which have been linked specifically to red hair. Interestingly, the red hair genotype has been identified in some Neandertal individuals (although the specific mutation is different from that seen among modern humans). 


Branicki, W., Liu, F., van Duijn, K., Draus-Barini, J., Pośpiech, E., Walsh, S., Kupiec, T., Wojas-Pelc, A., Kayser, M. (2011). Model-based prediction of human hair color using DNA variants. Human Genetics.

Lalueza-Fox, C., Römpler, H., Caramelli, D., Stäubert, C., Catalano, G., Hughes, D., Rohland, N., Pilli, E., Longo, L., Condemi, S., de la Rasilla, M., Fortea, J., Rosas, A., Stoneking, M., Schöneberg, T., Bertranpetit, J., Hofreiter, M. (2007). A melanocortin 1 receptor allele suggests varying pigmentation among Neanderthals. Science 318: 1453-1455. 

Please use the following form to submit your questions for our Harriet-Elliott participants. We will collect these before the event, present them to our participants, and select a group of questions that our participants will answer during the event.

Irish giants and DNA

As reported in the New York Times and published in the New England Journal of Medicine, researchers have successfully extracted DNA from the skeleton of Charles Byrne, who was known during his lifetime (1761-1783) as the “Irish Giant.” Measuring in at a towering 7’7″, he apparently died of the combined effects of tuberculosis and “an excessive love of gin.” His body was purchased soon after his death, after which it was boiled in acid and put on display at a museum in London. Some years later, after the removal of the top of his skull, it was determined that he suffered from a pituitary tumor. The pituitary gland sits at the base of the brain and regulates, among other things, the release of growth hormone. So, Byrne essentially suffered from growth hormone gone haywire.

The skeleton of Charles Byrne (Photo credit: Ronan McCloskey)

What’s interesting (at least for our purposes here) is that DNA analysis discovered that Byrne had a genetic mutation in his AIP gene.  These sorts of mutations are rare: only about 5% of people with pituitary tumors inherited them via a mutated gene. This particular mutation is so rare that when researchers found the same mutation among four families from Northern Ireland, they determined that these families are in fact related to Byrne (they shared a common ancestor 55 to 67 generations ago, or about 1,500 years ago).

The mutation probably occurs in other populations, either through shared ancestry or spontaneous mutation. Cool stuff.


Chahal, H.S., Stals, K., Unterländer, M., Balding, D.J., Thomas, M.G., Kumar, A.V., Besser, M.G., Atkinson, B.A., Morrison, P.J., M.D.; Howlett, Trevor A. M.D.; Levy, Miles J. M.D.; Orme, Steve M. M.D.; Akker, Scott A. M.B., B.S., Ph.D.; Abel, Richard L. Ph.D.; Grossman, A.B., Burger, J., Ellard, S., Korbonits, M. (2011). AIP mutation in pituitary adenomas in the 18th Century and today. New England Journal of Medicine 364: 43-50.