Popular press versions of biological research are often ripe with anthropocentrism, and this is no exception. Evolution by natural selection acts on 'copying mistakes' all the time, whether adding, deleting, or mistaking a single letter, word, sentence, or paragraph (to extend the crappy metaphor). The underlying research reports that a gene duplication event, the sort of thing that has been well characterized for many years, has occurred in a gene that modifies the number of projections that a neuron has. The amazing thing is the connection between the gene and the trait, not the mutation arose by a copying mistake. One could argue that all mutations are copying mistakes.
The reason that people are paying attention to hight is, in part, that it's a simply measured complex trait. Every study of human genetics under the sun collects basic anthropometrics, and so it's relatively easy to lump everyone together in an effort to increase the power to detect genetic variation that influences height. I think the real interesting part here is that even after collecting a hundred thousand data points, the obvious data analysis methods can account for a relatively low proportion of the total variance in height. That has consequences for studies of other disease traits with complex genetic architecture like diabetes or schizophrenia, which have often have study sizes one or two orders of magnitude lower than this one. In the not so recent past, influential members of the scientific community have suggested that big studies of complex traits in humans might have a profound impact on bedside medical decisions. It's going to take a bit longer than they anticipated. To our collective dismay, biology is still complicated.
There is almost certainly an epigenetic effect. The latest buzz is that there is no genetics without epigenetics. However, the size of the effect must be less than the 80% that is attributable to genes (and yes, that figure is pretty robust). The real problem is having the data to measure the epigenetic effects from studies that have already been conducted. If the study of epigenetic factors wasn't part of the original study design, it's awfully hard to model these effects as an afterthought in a meta analysis.
Services like those mentioned in TFA may be able to provide information on which genetic variants a person carries, but will not interpret those results. Non-scientists, and even scientists seem to over estimate the ability of modern genetics to assign meaning to common genetic variation. Your average M.D. when confronted with a print out of a patients 'mutations' would be completely unable to make heads or tails of them. There are few instances such as cystic fibrosis, where the etiology is well known, and known mutations WILL cause disease. In other cases such as BRCA in breast cancer, 'mutations' are risk factors for disease. In the vast majority of cases, modern genetics has no idea what a 'mutation' at rs39842093 might actually do.
These services are expensive, ambiguous, and require a certain measure of vanity on the part of the consumer. If you have a family history of disease X, there may be a small number of 'mutations' for which you might be tested that could actually impact your future health, and those services are provided by someone other than 23andMe.
Biology is a bit different than technology in that observing that biology works does not imply that someone knows how it works. (Creationists can bite me.)
Google's business plan is to collect information, and apply that information to generate revenue.
Applied information is knowledge. Knowledge is power. Power corrupts.
There are other agencies that collect information on this scale, think Homeland Security, and though they are 'heavily regulated,' there are still abuses. As much as we would prefer to believe that 'Do No Evil' actually means 'Do Good,' it doesn't. Maximizing shareholder value will necessarily mean leveraging accumulated information right up to the limit of the law.
We have a report of a correlation between cat ownership and some measure of health. Lets examine the possibilities...
a) Perhaps cat ownership causes people to have healthier hearts. Certainly this is the conclusion to which we are 'supposed to believe.'
b) Perhaps healthy hearts cause cat ownership. Counter-intuitive to say the least, but the statement that the two factors are correlated support this causal relationship just as strongly as option a).
c) Perhaps there is a latent factor that contributes to both cat ownership and healthy hearts. Do poor folks who do not have access to health care have fewer cats than wealthy folks? If so, cat ownership and health in general may be confounded.
d) Perhaps this phenomenon is observed completely by chance. Given the number of individuals, one might be doubtful, but I find it quite odd that they have sufficient cat owners to make this inference, but not enough dog owners. TFA: the numbers of dog owners in the study wasn't big enough to count statistically. Over half of the sample owned a cat, but not enough owned a dog to report the numbers... dubious.
I suspect that cats, dogs, healthy eating, frequent sex, and happiness in general are all positively correlated with healthier hearts. This report makes for great 'news', placating innumerate cat lovers, but contributes remarkably little to actually understanding the world.
Based on what I saw in the article, there's nothing this DNA does that hasn't been available in any number of DNA sequence manipulation suites for the last 10 years. 'Reverse translation', constructing a DNA sequence that could be transcribed and translated into actual protein is the sort of thing you might see in an undergraduate genetics homework assignment. Higher throughput versions, akin to what this article is describing, perhaps a masters level bioinformatics project. As to 'protecting' against potential evil-doers ordering proteins of mass destruction, viruses are quite a bit more complicated than proteins. Anyone who needs to order their custom gene from somebody else is not likely to be decades ahead of state of the art infectious disease researchers who, to the best of my knowledge, have been unable to generate a de novo infectious agent. Honestly, these algorithms have been around for quite some time.
Slashdot Mirror
Popular press versions of biological research are often ripe with anthropocentrism, and this is no exception. Evolution by natural selection acts on 'copying mistakes' all the time, whether adding, deleting, or mistaking a single letter, word, sentence, or paragraph (to extend the crappy metaphor). The underlying research reports that a gene duplication event, the sort of thing that has been well characterized for many years, has occurred in a gene that modifies the number of projections that a neuron has. The amazing thing is the connection between the gene and the trait, not the mutation arose by a copying mistake. One could argue that all mutations are copying mistakes.
Appeal to authority, whether the authority is a crowd or a bearded man in a white robe, is a logical fallacy.
The reason that people are paying attention to hight is, in part, that it's a simply measured complex trait. Every study of human genetics under the sun collects basic anthropometrics, and so it's relatively easy to lump everyone together in an effort to increase the power to detect genetic variation that influences height. I think the real interesting part here is that even after collecting a hundred thousand data points, the obvious data analysis methods can account for a relatively low proportion of the total variance in height. That has consequences for studies of other disease traits with complex genetic architecture like diabetes or schizophrenia, which have often have study sizes one or two orders of magnitude lower than this one. In the not so recent past, influential members of the scientific community have suggested that big studies of complex traits in humans might have a profound impact on bedside medical decisions. It's going to take a bit longer than they anticipated. To our collective dismay, biology is still complicated.
There is almost certainly an epigenetic effect. The latest buzz is that there is no genetics without epigenetics. However, the size of the effect must be less than the 80% that is attributable to genes (and yes, that figure is pretty robust). The real problem is having the data to measure the epigenetic effects from studies that have already been conducted. If the study of epigenetic factors wasn't part of the original study design, it's awfully hard to model these effects as an afterthought in a meta analysis.
Services like those mentioned in TFA may be able to provide information on which genetic variants a person carries, but will not interpret those results. Non-scientists, and even scientists seem to over estimate the ability of modern genetics to assign meaning to common genetic variation. Your average M.D. when confronted with a print out of a patients 'mutations' would be completely unable to make heads or tails of them. There are few instances such as cystic fibrosis, where the etiology is well known, and known mutations WILL cause disease. In other cases such as BRCA in breast cancer, 'mutations' are risk factors for disease. In the vast majority of cases, modern genetics has no idea what a 'mutation' at rs39842093 might actually do. These services are expensive, ambiguous, and require a certain measure of vanity on the part of the consumer. If you have a family history of disease X, there may be a small number of 'mutations' for which you might be tested that could actually impact your future health, and those services are provided by someone other than 23andMe. Biology is a bit different than technology in that observing that biology works does not imply that someone knows how it works. (Creationists can bite me.)
Obligatory http://xkcd.com/384/
Google's business plan is to collect information, and apply that information to generate revenue. Applied information is knowledge. Knowledge is power. Power corrupts. There are other agencies that collect information on this scale, think Homeland Security, and though they are 'heavily regulated,' there are still abuses. As much as we would prefer to believe that 'Do No Evil' actually means 'Do Good,' it doesn't. Maximizing shareholder value will necessarily mean leveraging accumulated information right up to the limit of the law.
We have a report of a correlation between cat ownership and some measure of health.
Lets examine the possibilities...
a) Perhaps cat ownership causes people to have healthier hearts. Certainly this is the conclusion to which we are 'supposed to believe.'
b) Perhaps healthy hearts cause cat ownership. Counter-intuitive to say the least, but the statement that the two factors are correlated support this causal relationship just as strongly as option a).
c) Perhaps there is a latent factor that contributes to both cat ownership and healthy hearts. Do poor folks who do not have access to health care have fewer cats than wealthy folks? If so, cat ownership and health in general may be confounded.
d) Perhaps this phenomenon is observed completely by chance. Given the number of individuals, one might be doubtful, but I find it quite odd that they have sufficient cat owners to make this inference, but not enough dog owners. TFA: the numbers of dog owners in the study wasn't big enough to count statistically. Over half of the sample owned a cat, but not enough owned a dog to report the numbers... dubious.
I suspect that cats, dogs, healthy eating, frequent sex, and happiness in general are all positively correlated with healthier hearts. This report makes for great 'news', placating innumerate cat lovers, but contributes remarkably little to actually understanding the world.
Based on what I saw in the article, there's nothing this DNA does that hasn't been available in any number of DNA sequence manipulation suites for the last 10 years. 'Reverse translation', constructing a DNA sequence that could be transcribed and translated into actual protein is the sort of thing you might see in an undergraduate genetics homework assignment. Higher throughput versions, akin to what this article is describing, perhaps a masters level bioinformatics project. As to 'protecting' against potential evil-doers ordering proteins of mass destruction, viruses are quite a bit more complicated than proteins. Anyone who needs to order their custom gene from somebody else is not likely to be decades ahead of state of the art infectious disease researchers who, to the best of my knowledge, have been unable to generate a de novo infectious agent. Honestly, these algorithms have been around for quite some time.
No more perfect way to quash piracy but to report it to the MPAA. http://www.mpaa.org/ReportPiracy.asp