Genetic Testing Companies Are Facing a Racial Bias Problem in Disease Risk Tests
Earlier this year, California-based Ambry Genetics announced that it was discontinuing a test meant to estimate a person's risk of developing prostate or breast cancer. The test looks for variations in a person's DNA that are known to be associated with these cancers.
Known as a polygenic risk score, this type of test adds up the effects of variants in many genes — often in the dozens or hundreds — and calculates a person's risk of developing a particular health condition compared to other people. In this way, polygenic risk scores are different from traditional genetic tests that look for mutations in single genes, such as BRCA1 and BRCA2, which raise the risk of breast cancer.
Traditional genetic tests look for mutations that are relatively rare in the general population but have a large impact on a person's disease risk, like BRCA1 and BRCA2. By contrast, polygenic risk scores scan for more common genetic variants that, on their own, have a small effect on risk. Added together, however, they can raise a person's risk for developing disease.
These scores could become a part of routine healthcare in the next few years. Researchers are developing polygenic risk scores for cancer, heart, disease, diabetes and even depression. Before they can be rolled out widely, they'll have to overcome a key limitation: racial bias.
"The issue with these polygenic risk scores is that the scientific studies which they're based on have primarily been done in individuals of European ancestry," says Sara Riordan, president of the National Society of Genetics Counselors. These scores are calculated by comparing the genetic data of people with and without a particular disease. To make these scores accurate, researchers need genetic data from tens or hundreds of thousands of people.
Myriad's old test would have shown that a Black woman had twice as high of a risk for breast cancer compared to the average woman even if she was at low or average risk.
A 2018 analysis found that 78% of participants included in such large genetic studies, known as genome-wide association studies, were of European descent. That's a problem, because certain disease-associated genetic variants don't appear equally across different racial and ethnic groups. For example, a particular variant in the TTR gene, known as V1221, occurs more frequently in people of African descent. In recent years, the variant has been found in 3 to 4 percent of individuals of African ancestry in the United States. Mutations in this gene can cause protein to build up in the heart, leading to a higher risk of heart failure. A polygenic risk score for heart disease based on genetic data from mostly white people likely wouldn't give accurate risk information to African Americans.
Accuracy in genetic testing matters because such polygenic risk scores could help patients and their doctors make better decisions about their healthcare.
For instance, if a polygenic risk score determines that a woman is at higher-than-average risk of breast cancer, her doctor might recommend more frequent mammograms — X-rays that take a picture of the breast. Or, if a risk score reveals that a patient is more predisposed to heart attack, a doctor might prescribe preventive statins, a type of cholesterol-lowering drug.
"Let's be clear, these are not diagnostic tools," says Alicia Martin, a population and statistical geneticist at the Broad Institute of MIT and Harvard. "We can't use a polygenic score to say you will or will not get breast cancer or have a heart attack."
But combining a patient's polygenic risk score with other factors that affect disease risk — like age, weight, medication use or smoking status — may provide a better sense of how likely they are to develop a specific health condition than considering any one risk factor one its own. The accuracy of polygenic risk scores becomes even more important when considering that these scores may be used to guide medication prescription or help patients make decisions about preventive surgery, such as a mastectomy.
In a study published in September, researchers used results from large genetics studies of people with European ancestry and data from the UK Biobank to calculate polygenic risk scores for breast and prostate cancer for people with African, East Asian, European and South Asian ancestry. They found that they could identify individuals at higher risk of breast and prostate cancer when they scaled the risk scores within each group, but the authors say this is only a temporary solution. Recruiting more diverse participants for genetics studies will lead to better cancer detection and prevent, they conclude.
Recent efforts to do just that are expected to make these scores more accurate in the future. Until then, some genetics companies are struggling to overcome the European bias in their tests.
Acknowledging the limitations of its polygenic risk score, Ambry Genetics said in April that it would stop offering the test until it could be recalibrated. The company launched the test, known as AmbryScore, in 2018.
"After careful consideration, we have decided to discontinue AmbryScore to help reduce disparities in access to genetic testing and to stay aligned with current guidelines," the company said in an email to customers. "Due to limited data across ethnic populations, most polygenic risk scores, including AmbryScore, have not been validated for use in patients of diverse backgrounds." (The company did not make a spokesperson available for an interview for this story.)
In September 2020, the National Comprehensive Cancer Network updated its guidelines to advise against the use of polygenic risk scores in routine patient care because of "significant limitations in interpretation." The nonprofit, which represents 31 major cancer cancers across the United States, said such scores could continue to be used experimentally in clinical trials, however.
Holly Pederson, director of Medical Breast Services at the Cleveland Clinic, says the realization that polygenic risk scores may not be accurate for all races and ethnicities is relatively recent. Pederson worked with Salt Lake City-based Myriad Genetics, a leading provider of genetic tests, to improve the accuracy of its polygenic risk score for breast cancer.
The company announced in August that it had recalibrated the test, called RiskScore, for women of all ancestries. Previously, Myriad did not offer its polygenic risk score to women who self-reported any ancestry other than sole European or Ashkenazi ancestry.
"Black women, while they have a similar rate of breast cancer to white women, if not lower, had twice as high of a polygenic risk score because the development and validation of the model was done in white populations," Pederson said of the old test. In other words, Myriad's old test would have shown that a Black woman had twice as high of a risk for breast cancer compared to the average woman even if she was at low or average risk.
To develop and validate the new score, Pederson and other researchers assessed data from more than 275,000 women, including more than 31,000 African American women and nearly 50,000 women of East Asian descent. They looked at 56 different genetic variants associated with ancestry and 93 associated with breast cancer. Interestingly, they found that at least 95% of the breast cancer variants were similar amongst the different ancestries.
The company says the resulting test is now more accurate for all women across the board, but Pederson cautions that it's still slightly less accurate for Black women.
"It's not only the lack of data from Black women that leads to inaccuracies and a lack of validation in these types of risk models, it's also the pure genomic diversity of Africa," she says, noting that Africa is the most genetically diverse continent on the planet. "We just need more data, not only in American Black women but in African women to really further characterize that continent."
Martin says it's problematic that such scores are most accurate for white people because they could further exacerbate health disparities in traditionally underserved groups, such as Black Americans. "If we were to set up really representative massive genetic studies, we would do a much better job at predicting genetic risk for everybody," she says.
Earlier this year, the National Institutes of Health awarded $38 million to researchers to improve the accuracy of polygenic risk scores in diverse populations. Researchers will create new genome datasets and pool information from existing ones in an effort to diversify the data that polygenic scores rely on. They plan to make these datasets available to other scientists to use.
"By having adequate representation, we can ensure that the results of a genetic test are widely applicable," Riordan says.
In the 1966 movie "Fantastic Voyage," actress Raquel Welch and her submarine were shrunk to the size of a cell in order to eliminate a blood clot in a scientist's brain. Now, 55 years later, the scenario is becoming closer to reality.
California-based startup Bionaut Labs has developed a nanobot about the size of a grain of rice that's designed to transport medication to the exact location in the body where it's needed. If you think about it, the conventional way to deliver medicine makes little sense: A painkiller affects the entire body instead of just the arm that's hurting, and chemotherapy is flushed through all the veins instead of precisely targeting the tumor.
"Chemotherapy is delivered systemically," Bionaut-founder and CEO Michael Shpigelmacher says. "Often only a small percentage arrives at the location where it is actually needed."
But what if it was possible to send a tiny robot through the body to attack a tumor or deliver a drug at exactly the right location?
Several startups and academic institutes worldwide are working to develop such a solution but Bionaut Labs seems the furthest along in advancing its invention. "You can think of the Bionaut as a tiny screw that moves through the veins as if steered by an invisible screwdriver until it arrives at the tumor," Shpigelmacher explains. Via Zoom, he shares the screen of an X-ray machine in his Culver City lab to demonstrate how the half-transparent, yellowish device winds its way along the spine in the body. The nanobot contains a tiny but powerful magnet. The "invisible screwdriver" is an external magnetic field that rotates that magnet inside the device and gets it to move and change directions.
The current model has a diameter of less than a millimeter. Shpigelmacher's engineers could build the miniature vehicle even smaller but the current size has the advantage of being big enough to see with bare eyes. It can also deliver more medicine than a tinier version. In the Zoom demonstration, the micorobot is injected into the spine, not unlike an epidural, and pulled along the spine through an outside magnet until the Bionaut reaches the brainstem. Depending which organ it needs to reach, it could be inserted elsewhere, for instance through a catheter.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu.
Imagine moving a screw through a steak with a magnet — that's essentially how the device works. But of course, the Bionaut is considerably different from an ordinary screw: "At the right location, we give a magnetic signal, and it unloads its medicine package," Shpigelmacher says.
To start, Bionaut Labs wants to use its device to treat Parkinson's disease and brain stem gliomas, a type of cancer that largely affects children and teenagers. About 300 to 400 young people a year are diagnosed with this type of tumor. Radiation and brain surgery risk damaging sensitive brain tissue, and chemotherapy often doesn't work. Most children with these tumors live less than 18 months. A nanobot delivering targeted chemotherapy could be a gamechanger. "These patients really don't have any other hope," Shpigelmacher says.
Of course, the main challenge of the developing such a device is guaranteeing that it's safe. Because tissue is so sensitive, any mistake could risk disastrous results. In recent years, Bionaut has tested its technology in dozens of healthy sheep and pigs with no major adverse effects. Sheep make a good stand-in for humans because their brains and spines are similar to ours.
The Bionaut device is about the size of a grain of rice.
Bionaut Labs
"As the Bionaut moves through brain tissue, it creates a transient track that heals within a few weeks," Shpigelmacher says. The company is hoping to be the first to test a nanobot in humans. In December 2022, it announced that a recent round of funding drew $43.2 million, for a total of 63.2 million, enabling more research and, if all goes smoothly, human clinical trials by early next year.
Once the technique has been perfected, further applications could include addressing other kinds of brain disorders that are considered incurable now, such as Alzheimer's or Huntington's disease. "Microrobots could serve as a bridgehead, opening the gateway to the brain and facilitating precise access of deep brain structure – either to deliver medication, take cell samples or stimulate specific brain regions," Shpigelmacher says.
Robot-assisted hybrid surgery with artificial intelligence is already used in state-of-the-art surgery centers, and many medical experts believe that nanorobotics will be the instrument of the future. In 2016, three scientists were awarded the Nobel Prize in Chemistry for their development of "the world's smallest machines," nano "elevators" and minuscule motors. Since then, the scientific experiments have progressed to the point where applicable devices are moving closer to actually being implemented.
Bionaut's technology was initially developed by a research team lead by Peer Fischer, head of the independent Micro Nano and Molecular Systems Lab at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Fischer is considered a pioneer in the research of nano systems, which he began at Harvard University more than a decade ago. He and his team are advising Bionaut Labs and have licensed their technology to the company.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu, who leads the cooperation with Bionaut Labs. He agrees with Shpigelmacher that the Bionaut's size is perfect for transporting medication loads and is researching potential applications for even smaller nanorobots, especially in the eye, where the tissue is extremely sensitive. "Nanorobots can sneak through very fine tissue without causing damage."
In "Fantastic Voyage," Raquel Welch's adventures inside the body of a dissident scientist let her swim through his veins into his brain, but her shrunken miniature submarine is attacked by antibodies; she has to flee through the nerves into the scientist's eye where she escapes into freedom on a tear drop. In reality, the exit in the lab is much more mundane. The Bionaut simply leaves the body through the same port where it entered. But apart from the dramatization, the "Fantastic Voyage" was almost prophetic, or, as Shpigelmacher says, "Science fiction becomes science reality."
This article was first published by Leaps.org on April 12, 2021.
How the Human Brain Project Built a Mind of its Own
In 2009, neuroscientist Henry Markram gave an ambitious TED talk. “Our mission is to build a detailed, realistic computer model of the human brain,” he said, naming three reasons for this unmatched feat of engineering. One was because understanding the human brain was essential to get along in society. Another was because experimenting on animal brains could only get scientists so far in understanding the human ones. Third, medicines for mental disorders weren’t good enough. “There are two billion people on the planet that are affected by mental disorders, and the drugs that are used today are largely empirical,” Markram said. “I think that we can come up with very concrete solutions on how to treat disorders.”
Markram's arguments were very persuasive. In 2013, the European Commission launched the Human Brain Project, or HBP, as part of its Future and Emerging Technologies program. Viewed as Europe’s chance to try to win the “brain race” between the U.S., China, Japan, and other countries, the project received about a billion euros in funding with the goal to simulate the entire human brain on a supercomputer, or in silico, by 2023.
Now, after 10 years of dedicated neuroscience research, the HBP is coming to an end. As its many critics warned, it did not manage to build an entire human brain in silico. Instead, it achieved a multifaceted array of different goals, some of them unexpected.
Scholars have found that the project did help advance neuroscience more than some detractors initially expected, specifically in the area of brain simulations and virtual models. Using an interdisciplinary approach of combining technology, such as AI and digital simulations, with neuroscience, the HBP worked to gain a deeper understanding of the human brain’s complicated structure and functions, which in some cases led to novel treatments for brain disorders. Lastly, through online platforms, the HBP spearheaded a previously unmatched level of global neuroscience collaborations.
Simulating a human brain stirs up controversy
Right from the start, the project was plagued with controversy and condemnation. One of its prominent critics was Yves Fregnac, a professor in cognitive science at the Polytechnic Institute of Paris and research director at the French National Centre for Scientific Research. Fregnac argued in numerous articles that the HBP was overfunded based on proposals with unrealistic goals. “This new way of over-selling scientific targets, deeply aligned with what modern society expects from mega-sciences in the broad sense (big investment, big return), has been observed on several occasions in different scientific sub-fields,” he wrote in one of his articles, “before invading the field of brain sciences and neuromarketing.”
"A human brain model can simulate an experiment a million times for many different conditions, but the actual human experiment can be performed only once or a few times," said Viktor Jirsa, a professor at Aix-Marseille University.
Responding to such critiques, the HBP worked to restructure the effort in its early days with new leadership, organization, and goals that were more flexible and attainable. “The HBP got a more versatile, pluralistic approach,” said Viktor Jirsa, a professor at Aix-Marseille University and one of the HBP lead scientists. He believes that these changes fixed at least some of HBP’s issues. “The project has been on a very productive and scientifically fruitful course since then.”
After restructuring, the HBP became a European hub on brain research, with hundreds of scientists joining its growing network. The HBP created projects focused on various brain topics, from consciousness to neurodegenerative diseases. HBP scientists worked on complex subjects, such as mapping out the brain, combining neuroscience and robotics, and experimenting with neuromorphic computing, a computational technique inspired by the human brain structure and function—to name just a few.
Simulations advance knowledge and treatment options
In 2013, it seemed that bringing neuroscience into a digital age would be farfetched, but research within the HBP has made this achievable. The virtual maps and simulations various HBP teams create through brain imaging data make it easier for neuroscientists to understand brain developments and functions. The teams publish these models on the HBP’s EBRAINS online platform—one of the first to offer access to such data to neuroscientists worldwide via an open-source online site. “This digital infrastructure is backed by high-performance computers, with large datasets and various computational tools,” said Lucy Xiaolu Wang, an assistant professor in the Resource Economics Department at the University of Massachusetts Amherst, who studies the economics of the HBP. That means it can be used in place of many different types of human experimentation.
Jirsa’s team is one of many within the project that works on virtual brain models and brain simulations. Compiling patient data, Jirsa and his team can create digital simulations of different brain activities—and repeat these experiments many times, which isn’t often possible in surgeries on real brains. “A human brain model can simulate an experiment a million times for many different conditions,” Jirsa explained, “but the actual human experiment can be performed only once or a few times.” Using simulations also saves scientists and doctors time and money when looking at ways to diagnose and treat patients with brain disorders.
Compiling patient data, scientists can create digital simulations of different brain activities—and repeat these experiments many times.
The Human Brain Project
Simulations can help scientists get a full picture that otherwise is unattainable. “Another benefit is data completion,” added Jirsa, “in which incomplete data can be complemented by the model. In clinical settings, we can often measure only certain brain areas, but when linked to the brain model, we can enlarge the range of accessible brain regions and make better diagnostic predictions.”
With time, Jirsa’s team was able to move into patient-specific simulations. “We advanced from generic brain models to the ability to use a specific patient’s brain data, from measurements like MRI and others, to create individualized predictive models and simulations,” Jirsa explained. He and his team are working on this personalization technique to treat patients with epilepsy. According to the World Health Organization, about 50 million people worldwide suffer from epilepsy, a disorder that causes recurring seizures. While some epilepsy causes are known others remain an enigma, and many are hard to treat. For some patients whose epilepsy doesn’t respond to medications, removing part of the brain where seizures occur may be the only option. Understanding where in the patients’ brains seizures arise can give scientists a better idea of how to treat them and whether to use surgery versus medications.
“We apply such personalized models…to precisely identify where in a patient’s brain seizures emerge,” Jirsa explained. “This guides individual surgery decisions for patients for which surgery is the only treatment option.” He credits the HBP for the opportunity to develop this novel approach. “The personalization of our epilepsy models was only made possible by the Human Brain Project, in which all the necessary tools have been developed. Without the HBP, the technology would not be in clinical trials today.”
Personalized simulations can significantly advance treatments, predict the outcome of specific medical procedures and optimize them before actually treating patients. Jirsa is watching this happen firsthand in his ongoing research. “Our technology for creating personalized brain models is now used in a large clinical trial for epilepsy, funded by the French state, where we collaborate with clinicians in hospitals,” he explained. “We have also founded a spinoff company called VB Tech (Virtual Brain Technologies) to commercialize our personalized brain model technology and make it available to all patients.”
The Human Brain Project created a level of interconnectedness within the neuroscience research community that never existed before—a network not unlike the brain’s own.
Other experts believe it’s too soon to tell whether brain simulations could change epilepsy treatments. “The life cycle of developing treatments applicable to patients often runs over a decade,” Wang stated. “It is still too early to draw a clear link between HBP’s various project areas with patient care.” However, she admits that some studies built on the HBP-collected knowledge are already showing promise. “Researchers have used neuroscientific atlases and computational tools to develop activity-specific stimulation programs that enabled paraplegic patients to move again in a small-size clinical trial,” Wang said. Another intriguing study looked at simulations of Alzheimer’s in the brain to understand how it evolves over time.
Some challenges remain hard to overcome even with computer simulations. “The major challenge has always been the parameter explosion, which means that many different model parameters can lead to the same result,” Jirsa explained. An example of this parameter explosion could be two different types of neurodegenerative conditions, such as Parkinson’s and Huntington’s diseases. Both afflict the same area of the brain, the basal ganglia, which can affect movement, but are caused by two different underlying mechanisms. “We face the same situation in the living brain, in which a large range of diverse mechanisms can produce the same behavior,” Jirsa said. The simulations still have to overcome the same challenge.
Understanding where in the patients’ brains seizures arise can give scientists a better idea of how to treat them and whether to use surgery versus medications.
The Human Brain Project
A network not unlike the brain’s own
Though the HBP will be closing this year, its legacy continues in various studies, spin-off companies, and its online platform, EBRAINS. “The HBP is one of the earliest brain initiatives in the world, and the 10-year long-term goal has united many researchers to collaborate on brain sciences with advanced computational tools,” Wang said. “Beyond the many research articles and projects collaborated on during the HBP, the online neuroscience research infrastructure EBRAINS will be left as a legacy even after the project ends.”
Those who worked within the HBP see the end of this project as the next step in neuroscience research. “Neuroscience has come closer to very meaningful applications through the systematic link with new digital technologies and collaborative work,” Jirsa stated. “In that way, the project really had a pioneering role.” It also created a level of interconnectedness within the neuroscience research community that never existed before—a network not unlike the brain’s own. “Interconnectedness is an important advance and prerequisite for progress,” Jirsa said. “The neuroscience community has in the past been rather fragmented and this has dramatically changed in recent years thanks to the Human Brain Project.”
According to its website, by 2023 HBP’s network counted over 500 scientists from over 123 institutions and 16 different countries, creating one of the largest multi-national research groups in the world. Even though the project hasn’t produced the in-silico brain as Markram envisioned it, the HBP created a communal mind with immense potential. “It has challenged us to think beyond the boundaries of our own laboratories,” Jirsa said, “and enabled us to go much further together than we could have ever conceived going by ourselves.”