Technological advances in molecular biology could help fix the planet.
- Genomics is the study of genes and their functions. The branch of molecular biology presents the idea that the genome can be manipulated for added resilience against harm.
- Yale professor and editor Daniel C. Esty argues that genetic modification in nature as a way to improve sustainability should be seriously considered.
- In the book A Better Planet: Forty Big Ideas for a Sustainable Future, Esty and several authors offer actionable solutions for dealing with greenhouse gases, including genomic intervention in nature.
Granted, genetic manipulation has been a dream for decades. Here’s what is different now.
Would you pay to give your child a genetic advantage, to make them smarter than their peers, taller, or more beautiful? This is a question that will become relevant within a few decades — if not sooner.
Gene sequencing will cost only a couple of dollars per human. A new generation of genetic editing tools, most notably CRISPR, have made it ridiculously easy to edit the human genome. Rapid advances in computing power will make it easier to understand the minute interplays between the dozens — if not hundreds — of genes that impact complex but valuable characteristics such as intelligence and patience. And, frankly, as artificial intelligence lets machines take on more and more complicated human tasks, we humans may need a genetic boost.
Unfortunately, the rich will likely be able to buy access to better genetics sooner than the rest of us — unless society intervenes. Do we really want a world where money can buy genetic superiority?
Granted, genetic manipulation has been a dream for decades. Here’s what is different now.
To start with, the cost of sequencing and mapping genes has plummeted. The initial Human Genome Project cost over $1 billion. It is presently below $1,000 for a human genome to be sequenced and should fall below $100 over the next few years. That cost will continue to drop rapidly. Within five years, having your genes sequenced will cost less than a fancy cup of coffee.
Also importantly, the available computing power to analyze these sequences has never been greater. The rise of cloud computing, pioneered by Amazon’s Elastic Compute Cloud, and increases in processing power have made it possible to build on-demand analytics systems that researchers can use to unravel the minute interactions of genes. In other words, they have access to supercomputing power but at a fraction of the cost of building a supercomputer — and without all the wires, cables, real estate, and technicians required.
The real breakthrough and missing piece, however, is CRISPR. The acronym is short for Clustered Regularly Interspaced Short Palindromic Repeats. CRISPR is actually an ancient self-defense mechanism of bacteria that modern scientists repurposed for laser-targeted gene editing. It is not a huge overstatement to say that CRISPR has made genetic manipulation a backyard hobby. In fact, DIY geneticists are using CRISPR to modify the genes of pure-bred dogs to try to improve their health. And a DIY CRISPR kit called the Odin is on sale online. In the very near future, CRISPR editing will be akin to cutting and pasting characters in a Microsoft Word document.
Combined, these three changes have ushered in an entirely new era of genomics, one where we move from traditional empiricism — informed guesswork, really — to engineered systems where design is intentional and the workings of genes are understood and known.
The initial stage of this will be ability to handicap the likelihood of which embryo will have which traits. Called pre-implantation genetic diagnosis (PGD), this technique is practiced today to help couples identify embryos that might have high risks of major genetic diseases such as Tay-Sachs disease. In the next few years, parents with access to cash will also be to use this technique to more accurately analyze the pluses and minuses of multiple embryos and select the one that has the best combination of probabilities for in vitro fertilization (IVF). PGD remains expensive and inaccurate, but it will become a more attractive option as it improves. Insurance companies at present don’t cover PGD or genetic improvement, only for disease prevention. That doesn’t mean it can’t be done.
In addition, ongoing improvements in computing power should help scientists better understand the complex interplay of genes. Determining the relationship of genetic makeup to traits like intelligence is a math problem that will probably never have an exact answer, but can be improved to provide more accurate probabilities. The impending arrival of powerful Quantum Computers could turbocharge this process by giving scientists new ways to analyze and simulate complex biological systems. That might make actual gene editing of humans or embryos viable and perhaps more economical than PGD.
CRISPR remains an experimental technique with many questions about the long-term safety of its editing process. Scientists and doctors fear that CRISPR may inadvertently impact non-target genes with unintended consequences. That said, scientists are growing more and more comfortable using CRISPR. Initially, a consensus of scientists advocated banning CRISPR editing on human embryos, even if they were not viable and would never become babies. Today, a growing number of research teams are testing how to use CRISPR more effectively on human embryos.
The initial goal is to modify single genes that cause serious illnesses. In these cases, fixing the mutant form of the gene will cure or reduce the impact of the illness. However, single-gene modification is just the start; many diseases result from the interplay of multiple genes.
For today, PGD carries no obvious risk because no modification of genetic matter occurs. Rather, the parents will be able to pick an embryo with a higher probability, based on the best research, of exhibiting desirable traits. This is less precise than CRISPR but could significantly increase chances of babies having desired traits. But PGD costs a lot of money. So will early stage gene editing of human embryos with CRISPR, albeit not for the tech as for the expertise and the service.
This all prompts challenging ethical questions. To date, many national governments have banned gene editing of live human embryos. Governments have also outlawed editing genes of the human germline — the genes we pass on to our children -— to carry advantageous traits such as height or intelligence.
IVF combined with PGD, or well-tuned CRISPR interventions, could become a highly-sought pre-birth treatment for wealthy folks seeking a leg up for their unborn offspring. This might further exacerbate the already documented trend of increased assortative mating — where people of like backgrounds and positions tend to marry each other. Assortative mating further concentrates wealth or other benefits further in a society, augmenting inequality. Genetics are not destiny but they do help; every extra point of IQ is associated with X dollars more in salary.
Individual rights advocates argue that the government should not possess the right to legislate how parents handle their children’s DNA. In their view, as long as these enhancements are safe and parents understand the risks, then the government should not regulate CRISPR editing on embryos any more than it should regulate whether the rich pay for pricey personal trainers to improve their physiques or expensive science and math tutors to improve chances that their children are accepted into Ivy League schools.
There is one key distinction in those analogies. Unlike personal trainers or tutors, genetic enhancements to embryos will confer benefits transferred from generation to generation. Over time, allowing subsequent generations to choose to gift their offspring with valuable traits via either CRISPR or PGD might generate even more inequality — driven by biology. Given the high current level of global inequality, selective biology generating more inequality will have strong political implications on fairness and the very foundational concept of modern democracy — that all humans are created equal.
While genetic manipulation to save lives makes perfect sense, the process shouldn’t be used to merely improve the chances of success of those already born with inherited socio-economic advantages. Designer babies must only be available if all in society can share the benefits. Equality of opportunity must extend to the realm of genetics and biology.
Vivek Wadhwa is a distinguished fellow at Carnegie Mellon University’s College of Engineering. He is a globally syndicated columnist for the Washington Post and the co-author of The Driver in the Driverless Car. You can follow him on Twitter @wadhwa.
Alex Salkever is the co-author of The Driver In The Driverless Car: How Our Technology Choices Can Change the Future. You can follow him on Twitter @.
Despite doubts from the healthcare industry, Watson recently identified a surprisingly high number of potential cancer treatments for real-life patients.
IBM's Watson is helping doctors identify treatment options for cancer patients — and it's even suggesting solutions that humans failed to see.
Researchers at the University of North Carolina (UNC) Lineberger Comprehensive Cancer Center had the supercomputer Watson analyze “large volumes of data," including past studies, databases, and genetic information, in an attempt to identify treatment options for 1,018 patients with “tumors with specific genetic abnormalities." The researchers then compared Watson's treatment choices with those made by a board of cancer experts.
The results were surprising. Not only did Watson confirm the 703 cases in which the expert panel identified “actionable genetic alterations," its cognitive computing discovered “potential therapeutic options" for 323 additional patients. Human doctors had not identified “recognized actionable mutations" in 96 of these patients.
"To be clear, the additional 323 cases of Watson-identified actionable alterations consisted of only eight genes that had not been considered actionable by the molecular tumor board," the report's corresponding author, William Kim, MD, an associate professor at UNC's medical school, said to the university.
Although the doctors hadn't considered those eight genes, Watson identified clinical trials for most of those patients — including one that began within a week of the computer analysis.
“Our findings, while preliminary, demonstrate that cognitive computing might have a role in identifying more therapeutic options for cancer patients," Kim said. “I can tell you that as a practicing oncologist, it's very reassuring for patients to know that we're able to explore all possible options for them in a very systematic manner."
The results are promising for the future of precision cancer care, which treats the disease by developing an individualized plan based on each patient's genetic information.
“To my knowledge, this is the first published examination of the utility of cognitive computing in precision cancer care," Kim said. “I'm optimistic that as we get more sequencing data, well-annotated treatment information, as well as therapy response, tools like Watson for Genomics will begin to show their true promise. But, of course, we still need to formally answer these questions."
Researchers at Human Longevity have developed technology that can generate images of individuals face using only their genetic information. But not all are convinced.
What if a computer could generate a realistic image of your face using only your genetic information?
That's precisely the technology researchers at Human Longevity, a San-Diego based company with the world's largest genomic database, claim to have developed. The team, led by genome-sequencing pioneer Craig Venter, reported their findings in a controversial paper published in the journal Proceedings of the National Academy of Sciences.
To train the A.I. to generate facial images, the team first sequenced the genomes of 1,061 people of various ages and ethnicity. They also took high-definition 3D photos of each participant. Finally, they fed the photos and genetic information to an algorithm that taught itself how small differences in DNA relate to facial features, like cheekbone height or protrusion of the brow. The algorithm was then given genomes it hadn't seen before, and it used them to generate images of the individual's face that could be reliably matched to real photos.
Well... sort of.
The team successfully matched eight out of ten images to the real photos. However, this rate fell to just five out of ten when researchers analyzed participants of only one race, considering facial features differ slightly by race. Judge for yourself how well the algorithm did:
The potential applications of this technology are especially intriguing for fields like forensic science — what if investigators were able to use genetic information left at a crime scene to “see” the perpetrator?
Interesting as the applications may be, Human Longevity is more concerned with the implications its findings has on privacy in genomics research, namely that technologies like this could be used to match people's thought-to-be anonymous genetic information to their online photos.
“A core belief from the HLI researchers is that there is now no such thing as true deidentification and full privacy in publicly accessible databases,” HLI said in a statement.
Privacy concerns seem to be widely shared in the community. But some scientists say that the paper is misleading. One reason is that the Human Longevity researchers already knew the age, sex and race of the participants — demographic information that could have been used to achieve the same matching rate without using the computer-generated photos at all.
“I don't think this paper raises those risks, because they haven’t demonstrated any ability to individuate this person from DNA,” said Mark Shriver, an anthropologist at Pennsylvania State University in University Park, in an interview with Nature.
Jason Piper, a former employee of Human Longevity, took issue with what he considered a lack of accuracy in the images, writing on Twitter that:
“everyone looks close to the average of their race, everyone looks like their prediction.”
But perhaps the most exhaustive criticism came from computational biologist Yaniv Erlich, who published a paper entitled Major flaws in "Identification of individuals by trait prediction using whole-genome sequencing data, part of which reads:
“The results of the authors are unremarkable. I achieved a similar re-identification accuracy with the Venter cohort in 10 minutes of work without fancy face morphology...”
Just days later, the team behind the original paper issued a rebuttal, titled simply No major flaws in "Identification of individuals by trait prediction using whole-genome sequencing data.
(It may seem mundane to those outside the field, but it's a pretty vicious beef in the scientific community at the moment, as seen by the "shots fired!" and "I'm gonna grab my popcorn..." comments under both papers.)
Access to genomics data
Underlying this whole debate is a question of access. Genomic data is used across various fields of study, but perhaps most importantly in research that seeks to combat diseases. In an interview with Nature, Piper said that Human Longevity has a vested interest in restricting access to DNA databases because it's a for-profit company that's trying to build the largest genome database in the world.
“I think genetic privacy is very important, but the approach being taken is the wrong one,” Piper said. “In order to get more information out of the genome, people have to share.”
Rather than privatizing and restricting access to genomic data, Piper said that a better solution would be to make data public while using techniques that still allow individuals to remain anonymous.
No pep talks here, just a prediction by innovation expert Alec Ross that gene code and precision medicine is set revolutionize life the same way that computer code has.
Modern medicine is pretty fantastic, right? Wrong. Wow, you walked right into that honey trap. Pharmaceuticals are incredibly impressive and most of us wouldn’t be alive without them, but this industry is set to skyrocket in innovation over the next few decades, making our current practices seem as primitive as the 130-pound mobile phone that seemed really futuristic in '90s.
Alec Ross is one of America’s leading experts on innovation (in fact he served for four years as Senior Advisor for Innovation to the Secretary of State Hillary Clinton, a role that earned him a Distinguished Honor Award from the State Department). The world’s last trillion dollar industry was created out of computer code. What’s the world’s next trillion dollar industry? Turns out it’s been inside us all along – genomes. Procedures like genome mapping that cost $2.7 billion dollars a mere 15 years ago are now available for just a few thousand dollars, and if that still sounds like a lot to you, don’t worry, it will get a lot cheaper still.
With genomic mapping as part of our everyday medical arsenal, doctors and technicians will be able to diagnose illnesses much earlier, which has everything to do with survival rates and quality of life, and will be able to develop precision medicines that are specific to your genetic make-up and to the genomic make-up of each disease. Ross says this is "kind of a big deal" as it will add years onto our life expectancies.
Currently on the cusp of exploding, this industry will be able to detect cancers that are usually only recognized at stages 4 and 5, in stage 1 where cure rates are far, far higher. The times are exiting and hopefully many of us will be able to experience them a little longer thanks to genomic innovation.
Alec Ross' most recent book is The Industries of the Future.