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."
Lori Tipton's life was a cascade of trauma that even a soap opera would not dare inflict upon a character: a mentally unstable family; a brother who died of a drug overdose; the shocking discovery of the bodies of two persons her mother had killed before turning the gun on herself; the devastation of Hurricane Katrina that savaged her hometown of New Orleans; being raped by someone she trusted; and having an abortion. She suffered from severe PTSD.
“My life was filled with anxiety and hypervigilance,” she says. “I was constantly afraid and had mood swings, panic attacks, insomnia, intrusive thoughts and suicidal ideation. I tried to take my life more than once.” She was fortunate to be able to access multiple mental health services, “And while at times some of these modalities would relieve the symptoms, nothing really lasted and nothing really address the core trauma.”
Then in 2018 Tipton enrolled in a clinical trial that combined intense sessions of psychotherapy with limited use of Methylenedioxymethamphetamine, or MDMA, a drug classified as a psychedelic and commonly known as ecstasy or Molly. The regimen was arduous; 1-2 hour preparation sessions, three sessions where MDMA was used, which lasted 6-8 hours, and lengthy sessions afterward to process and integrate the experiences. Two therapists were with her every moment of the three-month program that totaled more than 40 hours.
“It was clear to me that [the therapists] weren't going to heal me, that I was going to have to do the work for myself, but that they were there to completely support my process,” she says. “But the effects of MDMA were really undeniable for me. I felt embodied in a way that I hadn't in years. PTSD had robbed me of the ability to feel safe in my own body.”
Tipton doesn’t think the therapy completely cured her PTSD. “But when I completed the trial in 2018, I no longer qualified for the diagnosis, and I still don't qualify for the diagnosis today,” she told an April workshop on psychedelics as mental health treatment by the National Academies of Sciences, Engineering and Medicine, or NASEM.
Rick Doblin has been a catalyst behind much of the contemporary research into psychedelics. Prior to the DEA clamp down, the Boston psychotherapist had seen that MDMA and other psychedelics could benefit some of his patients where other measures had failed. He immediately organized efforts to question the drug rescheduling but to little avail. In 1986, he created the nonprofit Multidisciplinary Association for Psychedelic Studies (MAPS), which slowly laid the scientific foundation for clinical trials, including the one that Tipton joined, using psychedelics to treat mental health conditions.
Now, only slowly, have researchers been able to explore the power of these drugs to treat a broad spectrum of severely debilitating mental health conditions, including trauma, depression, and PTSD, where other available treatments proved inadequate.
“Psychedelic psychotherapy is an attempt to go after the root causes of the problems with just a relatively few administrations, as contrasted to most of the psychiatric drugs used today that are mostly just reducing symptoms and are meant to be taken on a daily basis,” Doblin said in a 2019 TED Talk. Most of these drugs can have broad effect but “some are probably more effective than others for certain conditions,” he added in a recent interview with Leaps.org. Comparative head-to-head studies of psychedelic therapies simply have not been conducted.
Their mechanisms of action are poorly understood and can vary between drugs, but it is generally believed that psychedelics change the activity of neurons so that the brain processes information differently, says Katrin Preller, a neuropsychologist at the University of Zurich. A recent important study in Nature Medicine by Richard Daws and colleagues used functional magnetic resonance imaging (fMRI) of the brain and found that “functional networks became more functionally interconnected and flexible after psilocybin treatment…implying that psilocybin's antidepressant action may depend on a global increase in brain network integration.”
Rosalind Watts, a clinical investigator at the Imperial College in London, believes there is “an overestimation of the importance of the drug and an underestimation of the importance of the [therapeutic] context” in psychedelic research. “It is unethical to provide the drug without the other,” she says. Doblin notes that “psychotherapy outcomes research demonstrates that the therapeutic alliance between the therapist and the patients is the single most predictive factor of outcomes. [It is] trust and the sense of safety, the willingness to go into difficult spaces” that makes clinical breakthroughs possible with the drug.
Excitement and Challenges
Recurrent themes expressed at the NASEM workshop were exciting glimpses of the potential for psychedelics to treat mental health conditions combined with the challenges of realizing those potentials. A recent review paper found evidence that using psychedelics can help with treating a variety of common mental illnesses, but the paper could identify only 14 clinical trials of classic psychedelics published since 1991. Much of the reason is that the drugs are not patentable and so the pharmaceutical industry has no interest in investing in expensive clinical trials to bring them to market. MAPS has raised about $135 million over its 36-year history to conduct such research, says Doblin, the vast majority of it from individual donors and none from foundations.
The workshop participants’ views also were colored by the history of drug crackdowns and a fear that research might easily be shut down in the future. There was great concern that use of psychedelics should be confined to clinical trials with high safety and ethical standards, instead of doctors and patients experimenting on their own. “We need to get it right this time,” says Charles Grob, a psychiatrist at the UCLA School of Medicine. But restricting access to psychedelics will become even more difficult now that Oregon and several cities have acted to decriminalize possession and use of many of these drugs.
The experience with ketamine also troubled Grob. He is hoping to “mitigate the rush of rapid commercialization” that occurred with that drug. Ketamine technically is not a psychedelic though it does share some of their potentially euphoric properties. In 2019, soon after the FDA approved a form of ketamine with a limited label indication to treat depression, for profit clinics sprang up promoting off label use of the drug for psychiatric conditions where there was little clinical evidence of efficacy. He fears the same thing will happen when true psychedelics are made available.
If these therapies are approved, access to them is likely to be a problem. The drugs themselves are cheap but the accompanying therapy is not, and there is a shortage of trained psychotherapists. Mental health services often are not adequately covered by health insurance, while the poor and people of color suffer additional burdens of inadequate access. Doblin is committed to health care equity by training additional providers and by investigating whether some of the preparatory and integration sessions might be handled in a group setting. He says it is important that the legal aspects of psychedelics also be addressed so that patients “don't have to go underground” in order to receive this care.
As a type 2 diabetic, Michael Snyder has long been interested in how blood sugar levels vary from one person to another in response to the same food, and whether a more personalized approach to nutrition could help tackle the rapidly cascading levels of diabetes and obesity in much of the western world.
Eight years ago, Snyder, who directs the Center for Genomics and Personalized Medicine at Stanford University, decided to put his theories to the test. In the 2000s continuous glucose monitoring, or CGM, had begun to revolutionize the lives of diabetics, both type 1 and type 2. Using spherical sensors which sit on the upper arm or abdomen – with tiny wires that pierce the skin – the technology allowed patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
It gave Snyder an idea for his research at Stanford. Applying the same technology to a group of apparently healthy people, and looking for ‘spikes’ or sudden surges in blood sugar known as hyperglycemia, could provide a means of observing how their bodies reacted to an array of foods.
“We discovered that different foods spike people differently,” he says. “Some people spike to pasta, others to bread, others to bananas, and so on. It’s very personalized and our feeling was that building programs around these devices could be extremely powerful for better managing people’s glucose.”
Unbeknown to Snyder at the time, thousands of miles away, a group of Israeli scientists at the Weizmann Institute of Science were doing exactly the same experiments. In 2015, they published a landmark paper which used CGM to track the blood sugar levels of 800 people over several days, showing that the biological response to identical foods can vary wildly. Like Snyder, they theorized that giving people a greater understanding of their own glucose responses, so they spend more time in the normal range, may reduce the prevalence of type 2 diabetes.
The commercial potential of such apps is clear, but the underlying science continues to generate intriguing findings.
“At the moment 33 percent of the U.S. population is pre-diabetic, and 70 percent of those pre-diabetics will become diabetic,” says Snyder. “Those numbers are going up, so it’s pretty clear we need to do something about it.”
Fast forward to 2022,and both teams have converted their ideas into subscription-based dietary apps which use artificial intelligence to offer data-informed nutritional and lifestyle recommendations. Snyder’s spinoff, January AI, combines CGM information with heart rate, sleep, and activity data to advise on foods to avoid and the best times to exercise. DayTwo–a start-up which utilizes the findings of Weizmann Institute of Science–obtains microbiome information by sequencing stool samples, and combines this with blood glucose data to rate ‘good’ and ‘bad’ foods for a particular person.
“CGMs can be used to devise personalized diets,” says Eran Elinav, an immunology professor and microbiota researcher at the Weizmann Institute of Science in addition to serving as a scientific consultant for DayTwo. “However, this process can be cumbersome. Therefore, in our lab we created an algorithm, based on data acquired from a big cohort of people, which can accurately predict post-meal glucose responses on a personal basis.”
The commercial potential of such apps is clear. DayTwo, who market their product to corporate employers and health insurers rather than individual consumers, recently raised $37 million in funding. But the underlying science continues to generate intriguing findings.
Last year, Elinav and colleagues published a study on 225 individuals with pre-diabetes which found that they achieved better blood sugar control when they followed a personalized diet based on DayTwo’s recommendations, compared to a Mediterranean diet. The journal Cell just released a new paper from Snyder’s group which shows that different types of fibre benefit people in different ways.
“The idea is you hear different fibres are good for you,” says Snyder. “But if you look at fibres they’re all over the map—it’s like saying all animals are the same. The responses are very individual. For a lot of people [a type of fibre called] arabinoxylan clearly reduced cholesterol while the fibre inulin had no effect. But in some people, it was the complete opposite.”
Eight years ago, Stanford's Michael Snyder began studying how continuous glucose monitors could be used by patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.
The Snyder Lab, Stanford Medicine
Because of studies like these, interest in precision nutrition approaches has exploded in recent years. In January, the National Institutes of Health announced that they are spending $170 million on a five year, multi-center initiative which aims to develop algorithms based on a whole range of data sources from blood sugar to sleep, exercise, stress, microbiome and even genomic information which can help predict which diets are most suitable for a particular individual.
“There's so many different factors which influence what you put into your mouth but also what happens to different types of nutrients and how that ultimately affects your health, which means you can’t have a one-size-fits-all set of nutritional guidelines for everyone,” says Bruce Y. Lee, professor of health policy and management at the City University of New York Graduate School of Public Health.
With the falling costs of genomic sequencing, other precision nutrition clinical trials are choosing to look at whether our genomes alone can yield key information about what our diets should look like, an emerging field of research known as nutrigenomics.
The ASPIRE-DNA clinical trial at Imperial College London is aiming to see whether particular genetic variants can be used to classify individuals into two groups, those who are more glucose sensitive to fat and those who are more sensitive to carbohydrates. By following a tailored diet based on these sensitivities, the trial aims to see whether it can prevent people with pre-diabetes from developing the disease.
But while much hope is riding on these trials, even precision nutrition advocates caution that the field remains in the very earliest of stages. Lars-Oliver Klotz, professor of nutrigenomics at Friedrich-Schiller-University in Jena, Germany, says that while the overall goal is to identify means of avoiding nutrition-related diseases, genomic data alone is unlikely to be sufficient to prevent obesity and type 2 diabetes.
“Genome data is rather simple to acquire these days as sequencing techniques have dramatically advanced in recent years,” he says. “However, the predictive value of just genome sequencing is too low in the case of obesity and prediabetes.”
Others say that while genomic data can yield useful information in terms of how different people metabolize different types of fat and specific nutrients such as B vitamins, there is a need for more research before it can be utilized in an algorithm for making dietary recommendations.
“I think it’s a little early,” says Eileen Gibney, a professor at University College Dublin. “We’ve identified a limited number of gene-nutrient interactions so far, but we need more randomized control trials of people with different genetic profiles on the same diet, to see whether they respond differently, and if that can be explained by their genetic differences.”
Some start-ups have already come unstuck for promising too much, or pushing recommendations which are not based on scientifically rigorous trials. The world of precision nutrition apps was dubbed a ‘Wild West’ by some commentators after the founders of uBiome – a start-up which offered nutritional recommendations based on information obtained from sequencing stool samples –were charged with fraud last year. The weight-loss app Noom, which was valued at $3.7 billion in May 2021, has been criticized on Twitter by a number of users who claimed that its recommendations have led to them developed eating disorders.
With precision nutrition apps marketing their technology at healthy individuals, question marks have also been raised about the value which can be gained through non-diabetics monitoring their blood sugar through CGM. While some small studies have found that wearing a CGM can make overweight or obese individuals more motivated to exercise, there is still a lack of conclusive evidence showing that this translates to improved health.
However, independent researchers remain intrigued by the technology, and say that the wealth of data generated through such apps could be used to help further stratify the different types of people who become at risk of developing type 2 diabetes.
“CGM not only enables a longer sampling time for capturing glucose levels, but will also capture lifestyle factors,” says Robert Wagner, a diabetes researcher at University Hospital Düsseldorf. “It is probable that it can be used to identify many clusters of prediabetic metabolism and predict the risk of diabetes and its complications, but maybe also specific cardiometabolic risk constellations. However, we still don’t know which forms of diabetes can be prevented by such approaches and how feasible and long-lasting such self-feedback dietary modifications are.”
Snyder himself has now been wearing a CGM for eight years, and he credits the insights it provides with helping him to manage his own diabetes. “My CGM still gives me novel insights into what foods and behaviors affect my glucose levels,” he says.
He is now looking to run clinical trials with his group at Stanford to see whether following a precision nutrition approach based on CGM and microbiome data, combined with other health information, can be used to reverse signs of pre-diabetes. If it proves successful, January AI may look to incorporate microbiome data in future.
“Ultimately, what I want to do is be able take people’s poop samples, maybe a blood draw, and say, ‘Alright, based on these parameters, this is what I think is going to spike you,’ and then have a CGM to test that out,” he says. “Getting very predictive about this, so right from the get go, you can have people better manage their health and then use the glucose monitor to help follow that.”