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Researchers at the Mount Sinai School of Medicine have recently published a method that may further complicate the way society relates to genetic information and an individual’s right to privacy. Drs. Eric E. Schadt and Ke Hao from Mount Sinai’s Institute for Genomics and Multiscale Biology, have developed a method for identifying an individual’s DNA barcode using only their RNA expression levels. According to Schadt “By observing RNA levels in a given tissue, we can infer a genotypic barcode that uniquely tags an individual in ways that enables matching the individual to an independently derived DNA sample.”
While regulators have established privacy laws related to what can be done with an individual’s genome, very little, (if anything), has been discussed with regards to how personal RNA information can be used. Considering that, until now, it would have been difficult, at best, to identify an individual based on their RNA expression, such laws were considered useless. However, with the development of this new technique all that has changed. Not only will the new technique allow scientists to predict disease risks which were previously done using genomic data information, but it would also enable law enforcement authorities to tie genomic DNA found at a crime scene to individual information stored in a research studies’ RNA database (which are publicly available via a number of databases in the United States and Europe and contain thousands of genomic studies from around the world).
According to the authors, society needs to rethink the way they relate to privacy information. “Rather than developing ways to further protect an individual’s privacy given the ability to collect mountains of information on him or her, we would be better served by a society that accepts the fact that new types of high-dimensional data reflect deeply on who we are,” Dr. Schadt said. “We need to accept the reality that it is difficult—if not impossible—to shield personal information from others. It is akin to trying to protect privacy regarding appearances, for example, in a public place.”
This reminds me of a recent spoof produced by The Onion highlighting the significant paradigm shift social media has created for our right to privacy. What are your thoughts on the matter?
Reference: Schadt, E., Woo, S., & Hao, K. (2012). Bayesian method to predict individual SNP genotypes from gene expression data Nature Genetics DOI: 10.1038/ng.2248
Disclosure: I don’t believe that we are in as bad a shape as some would have us believe. Nonetheless, in a recent survey conducted by Research!America more than half of likely voters doubt that the United States will be the No. 1 world leader in science, technology and health care by the year 2020.
Significant findings include:
57% are upset by cuts in federal spending for medical and health research
54% think that federal spending for medical and health research should be exempt from across-the-board cuts outlined in the Budget Control Act of 2011
58% of Americans do not believe the United States will be a world leader in science and technology in 2020
53% of Americans do not believe the United States will be a world leader in health care in 2020
65% of Americans say it’s important that the U.S. is a leader in medical and health research
85% of likely voters are concerned about the impact of a decreased federal investment in research, including the possibility of scientists leaving their profession or moving abroad to countries with a stronger investment in research
66% of likely voters believe government investment in medical and health research will have an impact on the future of the United States
Nearly 70% of Americans believe science and math education will have an impact on the future of the United States
There is, of course, an upside to all of these negative findings, and that is that more than half of likely voters (64%) say they would be more likely to vote for a presidential candidate who supports increased government funding for medical and health research. We are fortunate to live in a strong democracy. We have the power to change the future!
Proteomics is about to take a big leap forward, that is if the NIH can help it.
Last week, the NIH put out a request for information aimed at determining how best to accelerate research in disruptive proteomics technologies. The organization is hoping that submissions will aim to greatly outperform current mass spec technologies and introduce an all new way of advancing proteomic questions.
According to the proposal:
The Disruptive Proteomics Technologies (DPT) Working Group of the NIH Common Fund wishes to identify gaps and opportunities in current technologies and methodologies related to proteome-wide measurements. For the purposes of this RFI, “disruptive” is defined as very rapid, very significant gains, similar to the “disruptive” technology development that occurred in DNA sequencing technology.
These are exciting times for the field of proteomics. Don’t be left behind! Click here to find out more on how to get involved today!
Several neurodegenerative diseases – including Alzheimer’s and ALS (Lou Gehrig’s disease) – are caused when the body’s own proteins fold incorrectly, recruit and convert healthy proteins to the misfolded form, and aggregate in large clumps that gum up the works of the nervous system. Now scientists have developed an algorithm that can predict which regions of a protein are prone to exposure upon misfolding, and how mutations in the protein and changes in the cellular environment might affect the stability of these vulnerable regions. These predictions help scientists gain a better understanding of protein dynamics, and may one day help in developing treatments to effectively combat currently incurable neurodegenerative diseases.
The algorithm uses the energy equations of thermodynamics to calculate the likelihood that certain stretches of protein will be displayed when the protein misfolds. Since the exposed regions are specific to the misfolded version of the protein, researchers can use these regions as targets for diagnostic and therapeutic treatments. The algorithm can be adapted for different proteins and predicts several potential target regions for each protein. The group has used it to study neurodegenerative disease-causing proteins as well as misfolded proteins that have been implicated in some cancers.
Sit back and relax with some popcorn as you watch this interesting talk by Professor Bonnie Bassler of Princeton University talk about the social world of bacteria. And you thought that only human’s had Facebook!
If you don’t have enough patience (or popcorn) to watch the 50 minute version of her talk, checkout her 20 minute 2009 TED talk on the same subject below.
