Unexpected Risks Found in Editing Genes to Prevent Inherited Disorders
npr.org
npr.org
Genetic engineering has exactly the same problems that modifying binary-only code. After some very complex observation of the system you may spot the point that is responsible for a certain problem, but you will never be sure (as in provably sure) that the "fix" you put in place:
1. is going to stop all the occurrences of the behavior you want to fix;
2. will only affect the behavior you want to fix;
3. will have no effect on other systems that you did not modify.
(The article is mostly about 1 and a bit about 2 and 3.)
Modifying legacy code is hard enough when the uncommented source code is around. Changing directly the binary is both a great engineering feat and something to be scared of.
As an example, Some bacterial genomes are circular, code in both directions and have overlapping coding regions, and occasionally trade genetic material between species because why wouldn't they?
I've worked applying machine learning and statistics to genetics and I generally think it's pretty hilarious that many self declared rationalists think we need to worry about AI safety but declare scepticism of genetic engineering anti-scientific.
Now imagine the code arose originally by random chance
Unlike other experiments, genetic engineering can be incredibly disastrous to humanity. There's very real risks of destroying our food supply, the environment, and our health. And so far, we're taking these risks in the name of GMO crops, which are either resistant to toxic chemicals like glyphosate (Round-Up ready soybeans), or worse, plants that produce toxic chemicals to ward off pests (bt corn).
It is because we've already done genetic engineering. Certainly there are tractability problems with the scope of a change and predicting it's full success, but the fact that changes can be made seems undeniable, even if all we do is stick to direct engineering and exclude the engineering we've been doing for thousands of years.
Protein folding is a computationally hard problem, so fully predicting a change's effect will remain imprecise, unless we find some new shortcuts, which is entirely possible.
I'd argue that this goes beyond computational tractability and is still an issue of statistical power. There are millions of common variants in the human genome and we've only sequenced thousands of people so it's not exactly controversial to say genetics is poorly understood.
Which as the AI-safety people say, isn't to say we should be researching it just that we should be devoting more energy to doing it safely as the potential consequences are so high even if the chances of things going wrong is low.
Are the potential consequences really so high? It's not like we're going to be genetically engineering all of humanity in the same way at once, whereas AI safety effects all of humanity at once.
So i mean the consequences may be orders of magnitude smaller but I'd also argue the chance of something happening is orders of magnitude larger. (We're talking about small chances for either event, that's my point).
We've had genetic engineering as long as we've had farming. The difference is that we've applied industrial practice to everything. The result will be destructive in the long term, but profitable for now.
It's profitable because everything is fungible. There is no incentive to maintain the land. Ancient Rome literally had the same problem.
Our butts are at least partly covered that we do anything particularly awful on the genetic engineering front because genomes have been scrambling around in all kinds of different configurations for billions of years now and nothing too awful has happened. Except, arguably, us. Although I like to think we're the best result so far rather than the worst.
The first thing is that with natural selection of cross breeding new strains start small and ramp up providing a natural provisional test period.
With genetic engineering the goal is often something like a blockbuster new type of corn which sees global adoption quickly. So if something unexpected happens there is a non zero risk of lots of people's food supplies not working out.
Further if we're making analogies to nature, it's important to note that terrible things happen in nature. The key part of natural selection is that only some organisms get to reproduce and the rest often live miserable short lives.
I mean, to be flippant, our butts are covered in the sense we probably won't see anything worse than zinka, sickle cell anemia or ebola?
I argue that outside of engineered diseases it's difficult to imagine existential risks that could be posed by genetic engineering. Except, of course, making a better human which would almost certainly and immediately pose an existential risk to old Homo sapiens sapiens.
There is still a difference between "created" and "deployed at large scale".
Depends on perspective. Millions of species are extinct. Which is to say some mutation actually don't work out so well.
Your DNA was meticulously constructed by billions of years of evolution and that is not by chance since there are processes that construct DNA which are not based on "random mutation", you can take in foreign DNA, activate and deactivate genes put in spacers move base pairs from coding and non-coding DNA, modify gene expression and repetition and tons of other tricks and this all happens through a process not by chance.
If you think about evolution only in terms of random mutations which are filtered out through natural selection you throw away most of what we've learned about biology in the past 50 or so years, in fact random mutation is likely not have been workhorse of evolution especially in rapidly reproducing organisms.
Microorganisms edit their DNA and they do it at a very fast pace, this is why you can have bacteria developing resistance to drugs without even reproducing since they start seeking out resistive genes in their non-coding DNA and in their environment (plasmids and phages) as soon as they are exposed to antibiotics, they can integrate them into their coding DNA activate those genes and begin making the needed proteins and even rebuild their cell membranes if needed.
If you said this in any other context, it would sound laughably ludicrous. Imagine billions of lines of code for an incredibly advanced, complex and self-replicating system appearing out of the thin air (over 2 bil. yrs) by mere chance. Even with the long time period, it sounds facetious, prima facie. For some reason people decide to switch off their common sense and rationality when it comes to this.
Frankly I'm surprised to see that kind of sentiment coming out of such a CS-heavy audience, since genetic algorithms demonstrably work, and function on the same mathematical principles minus the biological substrate.
And haven't biologists, in recent years, emphasized the degree to which evolution relies on mutations and genetic drift? That was my understanding of the way the field has been going, anyway.
Saying that evolution as a whole is just "random chance" seems reductionist, but randomness does appear to be involved.
The problem arises because when biologists, statisticians etc say "random process," they mean something very specific that can actually contain many different kinds of mathematical structure, but your average layman hears that term to mean "¯\_(ツ)_/¯"
But if you start throwing the dice and you keep all the sixes you get along the way, Yahtzee-style, we expect you'll have 20 sixes in about 25-30 throws.
In the latter case, external selection has turned an incredibly implausible result into a certainty.
To put it in terms of genetic algorithms, we could run through N generations M different times and get different results each time.
To me that makes it seem like saying "randomness is an important aspect of evolution" isn't so far from the mark.
Again, randomness is an important part of evolution, but there are also necessary deterministic aspects of it that make the "blind watchmaker" type arguments that started this discussion irrelevant.
Complexity argument is not valid. It's debatable at least. AFAIK it's part of the bigger discussion whether evolution has direction.
But this scenario has the implicit assumption of a deterministic outcome (all 6s), and also that after each throw, the outcome of chance is being analyzed according to a set of rules, which are being applied such that keeping/discarding dice is done to produce a deterministic outcome.
Even if you deny that there is traditional "intelligence" in the process such as a dice thrower, the scenario still fails to answer why there is even a set of rules for evaluating these independent dice throws in the first place, where these rules came from, and why those rules seemingly guide events of completely random chance in a pre-determined direction at all (all 6s).
"Evolution works like a Yahtzee dice game minus all the Yahtzee rules"... How does that make sense?
"Chess works like checkers except you remove all the checkers rules and just play chess"
1) the process is iterative, not a single "roll" that has to turn out right
2) each generation is a modification of the previous one, not a completely new "roll"
3) some states more likely to progress to the next generation than others
We occur in an environment where these conditions are satisfied. Why that is the case is a question well beyond the scope of evolutionary theory.
automatic static and dynamic analysis and simulation
[...] in genetic modification
And, of course, these simulations would have to equivalent to real humans, otherwise it'd be pointless.
From technical point of view its just a computational complexity issue, but how about ethical point of view? How about human rights of simulated consious person?
Is this common? An uncommon detrimental variant that is slightly-mitigated by another uncommon detrimental variant, such that the removal of one makes the other worse isn't the type of thing I would expect to come about through natural selection.
https://sites.google.com/site/xxcantorxdustxx/home https://www.youtube.com/watch?v=C8--cXwuuFQ
Something very similar seems to be developed here:
https://github.com/letoram/senseye/wiki
Happy New Cyber!
edit: spelling
It's not always fully apparent what's going on.
Like trying to make a pretty patch on modular synth with access to only one module. This may be a bad idea.
I think you can be sure of the opposite, without even testing.
As the article notes the procedure isn't effectively clearing out all of the old mitochondria, and dynamics can favor them in the future.
It is known that variations in mitochondrial DNA produce radical differences in competition between mitochondrial strains in the cell. That is how deletions affecting OXPHOS machinery cause one mutant to take over the whole population very quickly - some differences produce mitochondria that either replicate better or resist quality control more effectively. That one is one of the causes of aging, but the same principle exists for other differences between mitochondrial genomes. If you put two or more in a cell and let them fight it out, hard to say in advance what the outcome will be given present knowledge.
So, basically, the people working on mitochondrial replacement need to make their tools for cleaning out the old mitochondria more efficient. If 100% success is achieved, that genome isn't coming back.
Alternatively, actual gene therapy might be a better approach - though challenging if you want to edit mitochondrial genomes, as you have the same problem of coverage and competition. There is allotopic expression, moving mitochondrial genes to the cell nucleus, which is feasible via today's gene therapy. Given the amount of work needed to copy mitochondrial genes into the nucleus, however, the challenge being how to alter them so as to get the proteins produced back to the mitochondria, something that has been achieved for three genes so far, it might be more cost-effective to work on better clearance and replacement technologies for the near term of assisted reproduction needs.
Normally, eggs provide all mitochondria. The sperm's mitochondrion gets left outside during fertilization. So in most zygotes, there's a new pairing between the father's nuclear genes and the mother's mitochondrial haplotype.
I wonder what that entails. I do understand that most zygotes fail to implant, or get terminated very early in development. Maybe this is one of the causes. Anyone know?
Some days I feel like people should just go back and study Barbara Mcclintock until they "get it".
It's not a risk of editing the genes so much as a risk of the treatment failing.
So it might happen that even if 100% of 'old mitochondria' is cleared the new symbiosis will also be defective as some of the 40 genes required by the hosting cell might be missing with new mito lineage replacing the original one.