I think there's been a lot of research/grants for working on population genetics; specifically, sequencing genomes and genetic expression profiles of patient pool of a particular disease (e.g., schizophrenia) and comparing it to the general population pool and clustering to find particular groups of genes that might be responsible for a particular disease.
Likewise, there are state agencies and startup's alike working on pre-natal genetics screening that basically tries to identify from pre-natal samples particular markers (SNPs) known for Down Syndrome, Tay-Sachs etc. Not to mention people who submit their samples to find interesting markers from 23andme.
I'd love to hear more from folks in the field what they think the next big application of computational biology, clinical genomics will be. Obviously, there has been a lot of mixed opinion regarding both on the consumer side (FDA banning 23andme from making broad statements of users having a higher-probability of cancer due to outdated and controversial data) and research side (has Human Genome Project since its completion in the early 2000's yielded a significant gene to target compound to drug on the market?)
More practically, Illumina (https://www.google.com/finance?q=NASDAQ%3AILMN&ei=af5xVYHoB4...) has more than 10x in the past 6 years, riding the wave of demand and growth of next-gen sequencing technology. If Cloud Computing is hailed as the sequencer's of the next phase in the biotech revolution, what stocks should I buy now to take advantage of it?
A lot of the low-hanging fruit, in terms of statistical significance for heritable disease, has already been picked, in the sense of a naive search for SNP X in gene Y that causes disease Z. The more people continue to look for single SNPs or even single gene causal factors, the more we learn that they are of limited use, due to the complexity and redundancy of biological interaction networks (genes/proteins/epigenetic modifications/environment/etc)
One thing that people are definitely still interested in regarding single genes or SNPS is looking for biomarkers. For instance, it's pretty easy to look at RNA abundance with RNA-seq and make a model with good discriminatory power to predict who does or doesn't have (say) breast cancer. But Those tests can be expensive, and profiling the appropriate tissue can be difficult. On the other hand, if we could find SNPs that correlate well with the RNA expression model that predicts disease, then we could just do a cheaper test/faster/easier test for the SNPs. Even better if we can validate causation independently using the emerging, though incomplete corpus of biological pathways.
Beyond that, some folks are excited about the field of functional genomics, which aims to correlate genome-level data to the structure and function of gene products (eg proteins) to get a more low-level, causal look at things.
Biological network extraction is something I'm excited about. Here, you usually want to extract pairs of features, or better yet, higher order structures from data to learn about what factors are important in disease pathways. This puts you immediately in the regime of way more potential features than data points, even if you sequence everyone in the world. I think this consideration worth thinking about when people try to hype you that big data and machine learning will just "solve" biology or medicine. L1 regularization only gets you so far. But it gets you somewhere, and can be hugely useful in suggesting new experiments.
I also think it's important to think about how it may soon be cheaper to store actual RNA/DNA and sequence it on demand, than it will be to store the data itself. DNA sequences would be a fine thing to sequence once and store, but for stuff, maybe not so much.
DNA databases in the cloud seems like a scary prospect, but it could also help a lot of people.
A family member of mine was recently diagnosed with a MTHFR gene mutation (http://en.wikipedia.org/wiki/Methylenetetrahydrofolate_reduc...), and it's been a life-changer. After years of misdiagnosis as depression, hypothyroid, or adrenal fatigue it's nice to have some answers and see results from getting the right treatment.
GINA does not apply to employers with fewer than 15 employees. GINA's protections in employment do not extend to the US military. Nor does it apply to health insurance through the TRICARE military health system, the Indian Health Service, the Veterans Health Administration, or the Federal Employees Health Benefits Program. Lastly, the law does not cover long term care insurance, life insurance or disability insurance."
While a few states have laws restricting the use of genetic information in the underwriting of these forms of insurance, nothing addresses the use of this information for other forms of discrimination. (Think credit redlining.)
Unfortunately, participating in any form of genetic testing is still a terrible idea for Americans, as it can have real financial consequences. Data are forever. Once this material is "out there," the law only provides recourse in a few specific circumstances (and you have to have the resources to enforce these rights through the legal system.)
The effects of supplements (primarily methylfolate and methylcobalamin) seems to depend on which mutation C677T, A1298, or both, and whether the person is homozygous or heterozygous.
However, the biggest difference is having an answer, instead of doctors guessing and prescribing thyroxine or antidepressants (which can make life so much worse).
Perhaps I'm being naieve but I don't want my DNA in any database without my expressed consent or criminal conviction.
DNA is inherently personal, and while its true you leave your DNA in almost as many places as your fingerprints (skin flakes, stray hairs, et al) DNA can tell you much more about someone's medical conditions than their fingerprint can.
I'm interested in personal medical devices, but not if that means leaking my medical info to the companies selling said devices. That info is personal and private and is nobodies business except mine and my doctors.
Your genetic information can not be used to discriminate against you.
"The President has signed into law the Genetic Information Nondiscrimination Act (GINA) that will protect Americans against discrimination based on their genetic information when it comes to health insurance and employment."
At some point anyone can use it to construct a model of you (face shape reconstruction is now, litter in Hong Kong and your face may show up on a billboard). We have just scratched the surface in regards to what can be known about someone if you have their genetic code. Or what can be done... like make people specific bio-weapons. I wonder how fast individuals will be able edit their own DNA on the fly to moot some of this.
You're right of course, there is a lot more to appearance than genetics, but these approximations do exist now, and will get better. jakeogh's litter example is closer to reality than he probably intended, which just shows how fast this technology is coming along.
> Nonetheless, the police in Columbia, S.C., last month released a sketch of a possible suspect. Rather than an artist’s rendering based on witness descriptions, the face was generated by a computer relying solely on DNA found at the scene of the crime.
I wouldn't even consider that my doctors' business. It's your business, full stop. Your doctor is a contractor whose job it is to help you interpret the results, same as a medical device.
So glad I majored in bioinformatics / comp bio. The future looks bright =)
& FWIW I know of a few postdocs who are either currently employed or are in the process of being poached by Google. It seems they are very serious about this.
This seems interesting. How long until people are sequenced at birth and their ailments predicted from that? (I know they're already doing it on a small scale, but I'm talking of it as a routine procedure).
How long still until our memories are able to be stored, etc ad nauseum.
You should check out Gattaca [http://www.imdb.com/title/tt0119177/]. It's a great movie that explores some of the negatives that crop up from a society that genetically sequences all citizens from birth.
I thought that movie pulled the punch. Turns out, the 'normal' guy actually had some genetic defect that SHOULD have excluded him from service. So it wasn't about discrimination after all.
I thought that was the whole point. The movie wasn't about easy answers.
In many ways they were right and he was the inferior human, but this led to horrible discrimination, relegating "natural" humans to second class status (but horrible discrimination built from a series of perfectly reasonable business decisions). It was also a movie about the power of the human will, but it wasn't about will conquering all, it was an exploration of a possible world where our notions of fairness and someone with sufficient drive surely overcoming all obstacles may be completely upended.
I got something else out of it. I thought the guy was a dirty cheat, risking billions in exploration costs just so he could personally be on the mission. What if he'd had a heart attack during the flight? The main plot of the movie torpedoed the big question of discrimination entirely.
And then there was the matter of wearing business suits on a space mission. Just weird.
It's on my viewing list!
To be honest I don't think that Gattaca at is that much risk of happening. Given the current state of the technology, actual non-vital changes to the embryo (or perhaps even those too) would most likely be banned
(It's already banned in many countries, with good reason: [1])
Not really. It explores some of the negatives that crop up from scientifically illiterate parents crippling their child due to their own misinformed decisions. Vincent was sturggling against his hippie antivaxxer parents who wanted a "natural" child. Unfortunately, naturalist audiences interpret the enemy in the film as society and see his parents' decision as pure and noble.
Don't be so patronizing. The film visualizes a possible society where the line between genetic therapy and genetic enhancement is crossed.
From a bioethical perspective, this isn't "Anti-vaxxing", it deals with misconceptions of genetic predeterminism in humans. Sure you can minimize harm by preventing a child born with tay sachs (genetic therapy) - but you're not minimizing harm by picking a child that will be taller and have blue eyes (enhancement) just because they're statistically likely to be more successful in life.
The main character's roommate provided this contrast as a "failed" olympic athlete, whose life was chosen before he was born.
Exciting but mundane. A lot has been invested but there have been very few useful results. It turns out the genome offers very little more than you already know from living in your body every day.
There's a wealth of knowledge in there, it just turns out it's incredibly complicated and everything is interrelated (exactly as you'd expect from a system that evolved). The problem is that the media has been selling this idea of personalized medicine for decades now on the premise that we'll find a single gene for every malady and physical advantage and be able to then tweak them at will.
Mundane for the most part, but horrifying in other aspects.
Imagine if we were able to identify who was likely to be gay back a few decades ago, say during the AIDs scare? Or imagine what would happen even today in places where homosexuals are put to death?
Thanks eggie for your insight. Was wondering if you can give more specifics as to what you think are the challenges in going from a human genome assembly to drug discovery.
Likewise, there are state agencies and startup's alike working on pre-natal genetics screening that basically tries to identify from pre-natal samples particular markers (SNPs) known for Down Syndrome, Tay-Sachs etc. Not to mention people who submit their samples to find interesting markers from 23andme.
I'd love to hear more from folks in the field what they think the next big application of computational biology, clinical genomics will be. Obviously, there has been a lot of mixed opinion regarding both on the consumer side (FDA banning 23andme from making broad statements of users having a higher-probability of cancer due to outdated and controversial data) and research side (has Human Genome Project since its completion in the early 2000's yielded a significant gene to target compound to drug on the market?)
More practically, Illumina (https://www.google.com/finance?q=NASDAQ%3AILMN&ei=af5xVYHoB4...) has more than 10x in the past 6 years, riding the wave of demand and growth of next-gen sequencing technology. If Cloud Computing is hailed as the sequencer's of the next phase in the biotech revolution, what stocks should I buy now to take advantage of it?