A scientist devotes her career to tackling inequity in genomics
Genetic datasets do not reflect the diversity of the world’s population. Alicia Martin is working to correct this through data-driven social justice.
The small prairie town of Cottonwood, Idaho might be the last place in the world where you'd expect someone who studies global human genetic variation to grow up. But that is where Alicia Martin began her journey that would lead to a career highlighting the importance of diversity in genomics.
Named for the trees that used to flank its creek, Cottonwood has two churches, a small hotel shaped like a beagle, and a restaurant where visitors stop for burgers before getting back on route 95. For decades, its population has hovered around 1,000; there are still no stoplights.
While many Cottonwood kids grow up interested in farming and raising large families, Martin from a young age was curious about the world outside Idaho. She loved reading and math problems and threw herself into school. As a teenager, she moved with her mother to Spokane, a mid-sized city in eastern Washington, and later to Seattle, where she became the first in her family to attend a university. Martin went on to earn a PhD in human genetics from Stanford University.
Arriving in the Bay Area after a childhood in increasingly diverse surroundings, Martin became acutely aware of health disparities and the profound differences in disease prevalence among different populations. “Seeing that massive gap, I was just really drawn to understanding the basis of those health disparities,” Martin said. “I wanted to know how I could have any impact on studying genetic diversity.”
Now an associate member at the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, assistant investigator in the Analytic and Translational Genetics Unit at Massachusetts General Hospital, and assistant professor at Harvard Medical School, Martin uses population genetics and statistics to study the influence of genes on disease across different populations. She’s been a leader in showing how the lack of diversity in genetic datasets may exacerbate health disparities, and how studies that include people with diverse ancestries can yield insights into genetic factors underlying disease, such as asthma.
Thanks in part to her research, more geneticists are now studying a wider diversity of people and accounting for genetic ancestry in their analyses. Through this work, Martin is showing how a methodical, data-driven kind of social justice can help improve equity in scientific research and lead to better science. The process, conceptually, is simple: identify a problem, quantify it, and show the world how to change it.
“There's been this explosion of genetic data, but it hasn't been equitable. It doesn’t reflect the world's diversity,” Martin said. “I think our work is helping move a lot of researchers to study underrepresented populations, and I’m really proud of that.”
At the Broad, Martin is also helping lead data analysis in two large international studies that are sequencing the DNA of people from Africa and Latin America to learn about the genetics of severe mental illness. And Martin is helping train scientists abroad to run these kinds of analyses in their home countries. In her own lab, she’s building a diverse team of researchers who are developing and distributing genetic resources equitably.
Other researchers are following in her wake, said Ben Neale, director of genetics at the Stanley Center for Psychiatric Research at the Broad, who is a close colleague of Martin. “You can be an activist while still being a scientist. It's just a question of how you focus your attention,” he said. “And that's what Alicia's gotten right, all the way through.”
Martin is particularly excited by the two studies on mental illness — they include tens or hundreds of thousands of individuals who have been historically underrepresented in genetics research, and promise to reveal new genetic factors underlying psychiatric disorders. She knows what the potential impact of this research could be, because she learned earlier than most how genetics can shape a life.
Early influences
When Martin was two years old, her little brother was born blue with a swollen abdomen. Her parents were terrified, and the family spent the next few years in and out of the hospital. Martin’s brother had cystic fibrosis, a genetic disease characterized by thickened mucus that affects the airways and digestive tract. He passed away at the age of three.
With early experience of biology at its most personal, Martin watched with intense interest as genetics began appearing more frequently in the news while she was in high school. She thought about becoming a doctor when she moved to Seattle for college, but wanted to go beyond treating symptoms to make a longer-term impact on human health. And she was most interested in helping patients like her brother, for whom there had been no cure.
After graduating, Martin enrolled in a PhD program at Stanford. Under the guidance of Carlos Bustamante, she began using genetics to understand how humans migrated and adapted over the course of evolution, particularly in African populations underrepresented in traditional genetics research. When she defended her PhD in December 2014, Martin hoped to use what she’d learned about population genetics to address the health disparities she’d seen as she moved across the country. She wanted to develop genetic tools for the average person.
Quantifying inequity
In early 2015, the snowiest recorded winter in New England history, Martin moved to Boston, Massachusetts to work as a postdoctoral fellow in the lab of Mark Daly. Daly, who investigates the connection between genetic variation and disease, is an institute member at the Broad, founding chief of the Analytic and Translational Genetics Unit at Massachusetts General Hospital, associate professor at Harvard Medical School, and the director of the Institute of Molecular Medicine Finland (FIMM) at the University of Helsinki. Martin felt at home in his lab right away.
“It was clear from Alicia's early work that she was committed to understanding important questions relevant to groups of people that don't participate in research very often,” said Neale, a colleague of Daly’s who helped interview Martin when she joined Broad. “Being able to see things as they are, not as we wish them to be, is part of what makes Alicia a wonderful person, but also a tremendous scientist.”
Towards the end of her time at Stanford, Martin had studied how populations with ancestries from different continents mixed in the Americas. When she joined Daly’s lab, she knew she wanted to use similarly diverse populations to study the performance of a genetic test called polygenic scores.
Researchers first developed polygenic scores nearly two decades ago to quantify how much genetics contributes to a disease or trait. These scores are largely a research tool but are used in a few instances in the clinic to assess a patient’s genetic risk of disease. Scientists calculate these scores for a population by comparing millions of single-letter changes in the DNA of large groups of people with and without a disease or trait. This allows them to pinpoint genetic variation associated with the disease or trait, and create a formula that can be used to evaluate whether an individual’s genetic risk is unusually high or low compared to the general population.
When Martin was starting her postdoc at Broad in 2015, scientists generating polygenic scores relied on a simplifying assumption: that populations are genetically homogenous.
That didn’t sit well with Martin, who knew that humans were more genetically diverse than the people of European ancestry who are overrepresented in most genetic studies. She and Daly began analyzing the performance of polygenic risk scores across different populations.
Over the next few years, Martin published a series of papers that have changed how scientists think about polygenic scores.
In 2017, she and others showed that polygenic scores derived from single-ancestry studies did not consistently generalize across other groups. In 2019, they compared the scores’ performance across a wider range of populations, and showed how the scores were about half as likely to reliably predict disease among Hispanic/Latino Americans populations, South Asians, and East Asians as Europeans, and only one-fifth as likely to accurately predict them among African populations. If doctors used the scores without considering ancestry, European descendants would benefit more from more accurate tests, while populations of African ancestry would receive predictions that were only slightly better than random chance. If the scores were integrated into clinical practice without careful framing, they could potentially exacerbate health disparities.
“That paper changed hearts and minds,” Neale, a co-author, said of the 2019 paper in Nature Genetics. Four years after its publication, the paper has been cited almost 1,000 times. Researchers in both genetics companies and academic labs began to include a wider range of ancestries when developing polygenic scores, he added.
This paper underscored that the most important factor for improving the accuracy of the scores was including participants with a greater diversity of ancestries in genetic studies. And this has been the goal of her work ever since.
Alicia Martin and attendees of the KEMRI-Wellcome Trust/GINGER Bioinformatics training in Kilifi, Kenya in September 2018.
Alicia Martin, Allan Kalungi (Makerere University), and Lerato Majara (University of Cape Town) work together on a research project at the 2018 GINGER workshop held in London, UK.
Addressing inequity
Africans are the most genetically diverse populations on the planet, but account for only a small fraction of genetic studies. In 2021, 86 percent of participants in genome-wide association studies — which look for associations between genetic variation and traits or disease — were of European descent, even though Europeans make up only 16 percent of the global population.
“Africa is the cradle of humanity,” Martin said. “If we were trying to design a genomic study in a vacuum, we’d start in Africa. But for infrastructural reasons, that hasn’t been so feasible to date.”
To help address these issues, she and others at the Stanley Center for Psychiatric Research help run the largest psychiatric genetics study ever conducted in Africa, with more than 40,000 participants recruited. The Neuropsychiatric Genetics of African Populations-Psychosis project (NeuroGAP-Psychosis) aims to uncover the genetic underpinnings of schizophrenia and bipolar disorder across African populations.
For NeuroGAP, Martin is helping oversee data analysis and has guided the collection of demographic information to inform a study on genetics and linguistic variation.
In studies like these, scientists usually use arrays, which look for specific variations in the human genome that tend to be common in people of European ancestry. Together with the NeuroGAP team, Martin helped show in 2021 that sequencing the entire genome can more accurately reveal genetic variation in underrepresented populations than arrays. And sequencing even at just “low coverage,” or less detail, can still reveal this variation while keeping costs the same as those for arrays.
Now, Martin is coordinating data analysis as a leader on the Populations Underrepresented in Mental illness Association Studies (PUMAS) project, the largest genetic study of severe mental illness in underrepresented populations across African and Latin American countries. The project, which is led by the Stanley Center, aims to recruit 17,000 new participants to assemble a dataset of genomic data from 183,000 individuals.
The PUMAS team will use a new approach Martin helped develop in collaboration with colleagues at the Broad’s Genomics Platform and the Stanley Center called the Blended Genome Exome. This technique, which is based in part on Martin’s 2021 paper, involves sequencing the exome — the 2 percent of the genome that encodes proteins — in high detail, and the rest of the genome in less detail, which allows researchers to find genes linked to disease in a cost-effective way.
“With really massive efforts, it’s actually becoming feasible to do large-scale studies in continental African populations,” Martin said.
Sustainable change
NeuroGAP and PUMAS would not be possible without systematic efforts to build up resources and expertise in the countries that are participating in the research, to help ensure the work continues to happen in those countries and to benefit them, Martin said. Toward that goal, she has developed training materials and helped mentor scientists through the Global Initiative for Neuropsychiatric Genetics Education in Research (GINGER), a program run by the Stanley Center and the Harvard T.H. Chan School of Public Health that trains scientists to conduct analyses within their home communities in East and South Africa. The program collaborates with academic and research institutions and has been training fellows in bioinformatics, statistics, clinical science, and genetics for the last six years.
“Human capacity is not what’s limiting in these countries,” Martin said. “A lot of times what’s lacking is just having someone down the hallway who’s already done this kind of work before, and who can easily share that know-how.”
GINGER fellows have already begun collecting phenotypic and genetic data, and physicians working in the program are validating comparisons of psychiatric evaluations to deliver diagnoses to more patients in countries such as Kenya, where there aren’t enough psychiatrists to serve everyone. This year, a team of fellows Martin mentored found that the accuracy of polygenic scores varies among African populations as well.
“I really think we’re going to look at this program in the future and find that it’s helped train a lot of the folks who made a lot of the discoveries the project was set up to find,” Martin said. “I’m really excited about what comes next.”
This work with GINGER, NeuroGAP, and PUMAS has taught Martin and her collaborators how to work equitably with scientific partners in countries with different resource levels — lessons that she and others published in 2022.
Mind of a mentor
For the last two and a half years, Martin has been cultivating her own team of population geneticists. Her lab of seven students, postdoctoral fellows, and staff comes from a range of backgrounds, some having grown up as close as New Jersey, but others from farther-flung cities in South Africa and Ethiopia.
Martin says she tries to support each of her trainees’ professional ambitions, which are as wide-reaching as their backgrounds. “My goal is to make sure that my mentees can achieve whatever their career goals are,” she said. “That doesn’t necessarily look the same for a Harvard grad student as it does for someone intending to go back to their home country.”
What unites her team, Martin says, is a deep respect for people of different backgrounds, and a drive for ensuring that the work they do is as representative of the global population as possible.
For her part, Martin hopes that work like her lab’s will lead to genomic resources on every continent. She imagines a world in which clinics use polygenic scores that are accurate for more populations, so that patients can receive their baseline risk of a disease regardless of their race, ethnicity, or ancestry. She hopes, too, that the tools her group develops will be so ingrained into analyses that, one day, it will be routine to run a genetic study in any population, and straightforward to find drivers of disease.
“We've come so far in the last decade — from the time my little brother had cystic fibrosis to now, scientists have developed a treatment for the fundamental cause of the disease,” Martin said. “It’s a fantastic time to be a human geneticist.”
