Genomic Data Has a Diversity Problem, But Global Efforts Are Underway to Fix It
Genomics has begun its golden age. Just 20 years ago, sequencing a single genome cost nearly $3 billion and took over a decade. Today, the same feat can be achieved for a few hundred dollars and the better part of a day . Suddenly, the prospect of sequencing not just individuals, but whole populations, has become feasible.
The genetic differences between humans may seem meager, only around 0.1 percent of the genome on average, but this variation can have profound effects on an individual's risk of disease, responsiveness to medication, and even the dosage level that would work best.
Already, initiatives like the U.K.'s 100,000 Genomes Project - now expanding to 1 million genomes - and other similarly massive sequencing projects in Iceland and the U.S., have begun collecting population-scale data in order to capture and study this variation.
The resulting data sets are immensely valuable to researchers and drug developers working to design new 'precision' medicines and diagnostics, and to gain insights that may benefit patients. Yet, because the majority of this data comes from developed countries with well-established scientific and medical infrastructure, the data collected so far is heavily biased towards Western populations with largely European ancestry.
This presents a startling and fast-emerging problem: groups that are under-represented in these datasets are likely to benefit less from the new wave of therapeutics, diagnostics, and insights, simply because they were tailored for the genetic profiles of people with European ancestry.
We may indeed be approaching a golden age of genomics-enabled precision medicine. But if the data bias persists then there is a risk, as with most golden ages throughout history, that the benefits will not be equally accessible to all, and existing inequalities will only be exacerbated.
To remedy the situation, a number of initiatives have sprung up to sequence genomes of under-represented groups, adding them to the datasets and ensuring that they too will benefit from the rapidly unfolding genomic revolution.
Global Gene Corp
The idea behind Global Gene Corp was born eight years ago in Harvard when Sumit Jamuar, co-founder and CEO, met up with his two other co-founders, both experienced geneticists, for a coffee.
"They were discussing the limitless applications of understanding your genetic code," said Jamuar, a business executive from New Delhi.
"And so, being a technology enthusiast type, I was excited and I turned to them and said hey, this is incredible! Could you sequence me and give me some insights? And they actually just turned around and said no, because it's not going to be useful for you - there's not enough reference for what a good Sumit looks like."
What started as a curiosity-driven conversation on the power of genomics ended with a commitment to tackle one of the field's biggest roadblocks - its lack of global representation.
Jamuar set out to begin with India, which has about 20 percent of the world's population, including over 4000 different ethnicities, but contributes less than 2 percent of genomic data, he told Leaps.org.
Eight years later, Global Gene Corp's sequencing initiative is well underway, and is the largest in the history of the Indian subcontinent. The program is being carried out in collaboration with biotech giant Regeneron, with support from the Indian government, local communities, and the Indian healthcare ecosystem. In August 2020, Global Gene Corp's work was recognized through the $1 million 2020 Roddenberry award for organizations that advance the vision of 'Star Trek' creator Gene Roddenberry to better humanity.
This problem has already begun to manifest itself in, for example, much higher levels of genetic misdiagnosis among non-Europeans tested for their risk of certain diseases, such as hypertrophic cardiomyopathy - an inherited disease of the heart muscle.
Global Gene Corp also focuses on developing and implementing AI and machine learning tools to make sense of the deluge of genomic data. These tools are increasingly used by both industry and academia to guide future research by identifying particularly promising or clinically interesting genetic variants. But if the underlying data is skewed European, then the effectiveness of the computational analysis - along with the future advances and avenues of research that emerge from it - will be skewed towards Europeans too.
This problem has already begun to manifest itself in, for example, much higher levels of genetic misdiagnosis among non-Europeans tested for their risk of certain diseases, such as hypertrophic cardiomyopathy - an inherited disease of the heart muscle. Most of the genetic variants used in these tests were identified as being causal for the disease from studies of European genomes. However, many of these variants differ both in their distribution and clinical significance across populations, leading to many patients of non-European ancestry receiving false-positive test results - as their benign genetic variants were misclassified as pathogenic. Had even a small number of genomes from other ethnicities been included in the initial studies, these misdiagnoses could have been avoided.
"Unless we have a data set which is unbiased and representative, we're never going to achieve the success that we want," Jamuar says.
"When Siri was first launched, she could hardly recognize an accent which was not of a certain type, so if I was trying to speak to Siri, I would have to repeat myself multiple times and try to mimic an accent which wasn't my accent so that she could understand it.
"But over time the voice recognition technology improved tremendously because the training data was expanded to include people of very diverse backgrounds and their accents, so the algorithms were trained to be able to pick that up and it dramatically improved the technology. That's the way we have to think about it - without that good-quality diverse data, we will never be able to achieve the full potential of the computational tools."
While mapping India's rich genetic diversity has been the organization's primary focus so far, they plan, in time, to expand their work to other under-represented groups in Asia, the Middle East, Africa, and Latin America.
"As other like-minded people and partners join the mission, it just accelerates the achievement of what we have set out to do, which is to map out and organize the world's genomic diversity so that we can enable high-quality life and longevity benefits for everyone, everywhere," Jamuar says.
Empowering African Genomics
Africa is the birthplace of our species, and today still retains an inordinate amount of total human genetic diversity. Groups that left Africa and went on to populate the rest of the world, some 50 to 100,000 years ago, were likely small in number and only took a fraction of the total genetic diversity with them. This ancient bottleneck means that no other group in the world can match the level of genetic diversity seen in modern African populations.
Despite Africa's central importance in understanding the history and extent of human genetic diversity, the genomics of African populations remains wildly understudied. Addressing this disparity has become a central focus of the H3Africa Consortium, an initiative formally launched in 2012 with support from the African Academy of Sciences, the U.S. National Institutes of Health, and the UK's Wellcome Trust. Today, H3Africa supports over 50 projects across the continent, on an array of different research areas in genetics relevant to the health and heredity of Africans.
"Africa is the cradle of Humankind. So what that really means is that the populations that are currently living in Africa are among some of the oldest populations on the globe, and we know that the longer populations have had to go through evolutionary phases, the more variation there is in the genomes of people who live presently," says Zane Lombard, a principal investigator at H3Africa and Associate Professor of Human Genetics at the University of the Witwatersrand in Johannesburg, South Africa.
"So for that reason, African populations carry a huge amount of genetic variation and diversity, which is pretty much uncaptured. There's still a lot to learn as far as novel variation is concerned by looking at and studying African genomes."
A recent landmark H3Africa study, led by Lombard and published in Nature in October, sequenced the genomes of over 400 African individuals from 50 ethno-linguistic groups - many of which had never been sampled before.
Despite the relatively modest number of individuals sequenced in the study, over three million previously undescribed genetic variants were found, and complex patterns of ancestral migration were uncovered.
"In some of these ethno-linguistic groups they don't have a word for DNA, so we've had to really think about how to make sure that we communicate the purposes of different studies to participants so that you have true informed consent," says Lombard.
"The objective," she explained, "was to try and fill some of the gaps for many of these populations for which we didn't have any whole genome sequences or any genetic variation data...because if we're thinking about the future of precision medicine, if the patient is a member of a specific group where we don't know a lot about the genomic variation that exists in that group, it makes it really difficult to start thinking about clinical interpretation of their data."
From H3Africa's conception, the consortium's goal has not only been to better represent Africa's staggering genetic diversity in genomic data sets, but also to build Africa's domestic genomics capabilities and empower a new generation of African researchers. By doing so, the hope is that Africans will be able to set their own genomics agenda, and leapfrog to new and better ways of doing the work.
"The training that has happened on the continent and the number of new scientists, new students, and fellows that have come through the process and are now enabled to start their own research groups, to grow their own research in their countries, to be a spokesperson for genomics research in their countries, and to build that political will to do these larger types of sequencing initiatives - that is really a significant outcome from H3Africa as well. Over and above all the science that's coming out," Lombard says.
"What has been created through H3Africa is just this locus of researchers and scientists and bioethicists who have the same goal at heart - to work towards adjusting the data bias and making sure that all global populations are represented in genomics."
DNA- and RNA-based electronic implants may revolutionize healthcare
Implantable electronic devices can significantly improve patients’ quality of life. A pacemaker can encourage the heart to beat more regularly. A neural implant, usually placed at the back of the skull, can help brain function and encourage higher neural activity. Current research on neural implants finds them helpful to patients with Parkinson’s disease, vision loss, hearing loss, and other nerve damage problems. Several of these implants, such as Elon Musk’s Neuralink, have already been approved by the FDA for human use.
Yet, pacemakers, neural implants, and other such electronic devices are not without problems. They require constant electricity, limited through batteries that need replacements. They also cause scarring. “The problem with doing this with electronics is that scar tissue forms,” explains Kate Adamala, an assistant professor of cell biology at the University of Minnesota Twin Cities. “Anytime you have something hard interacting with something soft [like muscle, skin, or tissue], the soft thing will scar. That's why there are no long-term neural implants right now.” To overcome these challenges, scientists are turning to biocomputing processes that use organic materials like DNA and RNA. Other promised benefits include “diagnostics and possibly therapeutic action, operating as nanorobots in living organisms,” writes Evgeny Katz, a professor of bioelectronics at Clarkson University, in his book DNA- And RNA-Based Computing Systems.
While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output.
Adamala’s research focuses on developing such biocomputing systems using DNA, RNA, proteins, and lipids. Using these molecules in the biocomputing systems allows the latter to be biocompatible with the human body, resulting in a natural healing process. In a recent Nature Communications study, Adamala and her team created a new biocomputing platform called TRUMPET (Transcriptional RNA Universal Multi-Purpose GatE PlaTform) which acts like a DNA-powered computer chip. “These biological systems can heal if you design them correctly,” adds Adamala. “So you can imagine a computer that will eventually heal itself.”
The basics of biocomputing
Biocomputing and regular computing have many similarities. Like regular computing, biocomputing works by running information through a series of gates, usually logic gates. A logic gate works as a fork in the road for an electronic circuit. The input will travel one way or another, giving two different outputs. An example logic gate is the AND gate, which has two inputs (A and B) and two different results. If both A and B are 1, the AND gate output will be 1. If only A is 1 and B is 0, the output will be 0 and vice versa. If both A and B are 0, the result will be 0. While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output. In this case, the DNA enters the logic gate as a single or double strand.
If the DNA is double-stranded, the system “digests” the DNA or destroys it, which results in non-fluorescence or “0” output. Conversely, if the DNA is single-stranded, it won’t be digested and instead will be copied by several enzymes in the biocomputing system, resulting in fluorescent RNA or a “1” output. And the output for this type of binary system can be expanded beyond fluorescence or not. For example, a “1” output might be the production of the enzyme insulin, while a “0” may be that no insulin is produced. “This kind of synergy between biology and computation is the essence of biocomputing,” says Stephanie Forrest, a professor and the director of the Biodesign Center for Biocomputing, Security and Society at Arizona State University.
Biocomputing circles are made of DNA, RNA, proteins and even bacteria.
Evgeny Katz
The TRUMPET’s promise
Depending on whether the biocomputing system is placed directly inside a cell within the human body, or run in a test-tube, different environmental factors play a role. When an output is produced inside a cell, the cell's natural processes can amplify this output (for example, a specific protein or DNA strand), creating a solid signal. However, these cells can also be very leaky. “You want the cells to do the thing you ask them to do before they finish whatever their businesses, which is to grow, replicate, metabolize,” Adamala explains. “However, often the gate may be triggered without the right inputs, creating a false positive signal. So that's why natural logic gates are often leaky." While biocomputing outside a cell in a test tube can allow for tighter control over the logic gates, the outputs or signals cannot be amplified by a cell and are less potent.
TRUMPET, which is smaller than a cell, taps into both cellular and non-cellular biocomputing benefits. “At its core, it is a nonliving logic gate system,” Adamala states, “It's a DNA-based logic gate system. But because we use enzymes, and the readout is enzymatic [where an enzyme replicates the fluorescent RNA], we end up with signal amplification." This readout means that the output from the TRUMPET system, a fluorescent RNA strand, can be replicated by nearby enzymes in the platform, making the light signal stronger. "So it combines the best of both worlds,” Adamala adds.
These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body.
The TRUMPET biocomputing process is relatively straightforward. “If the DNA [input] shows up as single-stranded, it will not be digested [by the logic gate], and you get this nice fluorescent output as the RNA is made from the single-stranded DNA, and that's a 1,” Adamala explains. "And if the DNA input is double-stranded, it gets digested by the enzymes in the logic gate, and there is no RNA created from the DNA, so there is no fluorescence, and the output is 0." On the story's leading image above, if the tube is "lit" with a purple color, that is a binary 1 signal for computing. If it's "off" it is a 0.
While still in research, TRUMPET and other biocomputing systems promise significant benefits to personalized healthcare and medicine. These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body. The study’s lead author and graduate student Judee Sharon is already beginning to research TRUMPET's ability for earlier cancer diagnoses. Because the inputs for TRUMPET are single or double-stranded DNA, any mutated or cancerous DNA could theoretically be detected from the platform through the biocomputing process. Theoretically, devices like TRUMPET could be used to detect cancer and other diseases earlier.
Adamala sees TRUMPET not only as a detection system but also as a potential cancer drug delivery system. “Ideally, you would like the drug only to turn on when it senses the presence of a cancer cell. And that's how we use the logic gates, which work in response to inputs like cancerous DNA. Then the output can be the production of a small molecule or the release of a small molecule that can then go and kill what needs killing, in this case, a cancer cell. So we would like to develop applications that use this technology to control the logic gate response of a drug’s delivery to a cell.”
Although platforms like TRUMPET are making progress, a lot more work must be done before they can be used commercially. “The process of translating mechanisms and architecture from biology to computing and vice versa is still an art rather than a science,” says Forrest. “It requires deep computer science and biology knowledge,” she adds. “Some people have compared interdisciplinary science to fusion restaurants—not all combinations are successful, but when they are, the results are remarkable.”
In today’s podcast episode, Leaps.org Deputy Editor Lina Zeldovich speaks about the health and ecological benefits of farming crickets for human consumption with Bicky Nguyen, who joins Lina from Vietnam. Bicky and her business partner Nam Dang operate an insect farm named CricketOne. Motivated by the idea of sustainable and healthy protein production, they started their unconventional endeavor a few years ago, despite numerous naysayers who didn’t believe that humans would ever consider munching on bugs.
Yet, making creepy crawlers part of our diet offers many health and planetary advantages. Food production needs to match the rise in global population, estimated to reach 10 billion by 2050. One challenge is that some of our current practices are inefficient, polluting and wasteful. According to nonprofit EarthSave.org, it takes 2,500 gallons of water, 12 pounds of grain, 35 pounds of topsoil and the energy equivalent of one gallon of gasoline to produce one pound of feedlot beef, although exact statistics vary between sources.
Meanwhile, insects are easy to grow, high on protein and low on fat. When roasted with salt, they make crunchy snacks. When chopped up, they transform into delicious pâtes, says Bicky, who invents her own cricket recipes and serves them at industry and public events. Maybe that’s why some research predicts that edible insects market may grow to almost $10 billion by 2030. Tune in for a delectable chat on this alternative and sustainable protein.
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Further reading:
More info on Bicky Nguyen
https://yseali.fulbright.edu.vn/en/faculty/bicky-n...
The environmental footprint of beef production
https://www.earthsave.org/environment.htm
https://www.watercalculator.org/news/articles/beef-king-big-water-footprints/
https://www.frontiersin.org/articles/10.3389/fsufs.2019.00005/full
https://ourworldindata.org/carbon-footprint-food-methane
Insect farming as a source of sustainable protein
https://www.insectgourmet.com/insect-farming-growing-bugs-for-protein/
https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/insect-farming
Cricket flour is taking the world by storm
https://www.cricketflours.com/
https://talk-commerce.com/blog/what-brands-use-cricket-flour-and-why/
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.