Genomic Data Has a Diversity Problem, But Global Efforts Are Underway to Fix It

Genomic Data Has a Diversity Problem, But Global Efforts Are Underway to Fix It

Genetic data sets skew too European, threatening to narrow who will benefit from future advances.

Louis Reed on Unsplash

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.

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Farhan Mitha
Farhan Mitha is a freelance science writer based in London. He regularly writes about biotechnology, synthetic biology, and natural history, and is currently studying for a master's degree in Evolutionary Genomics. Find him on Twitter @FarhanMitha.
Heart model

Elaine Kamil had just returned home after a few days of business meetings in 2013 when she started having chest pains. At first Kamil, then 66, wasn't worried—she had had some chest pain before and recently went to a cardiologist to do a stress test, which was normal.

"I can't be having a heart attack because I just got checked," she thought, attributing the discomfort to stress and high demands of her job. A pediatric nephrologist at Cedars-Sinai Hospital in Los Angeles, she takes care of critically ill children who are on dialysis or are kidney transplant patients. Supporting families through difficult times and answering calls at odd hours is part of her daily routine, and often leaves her exhausted.

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Lina Zeldovich

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.

Did Anton the AI find a new treatment for a deadly cancer?

Researchers used a supercomputer to learn about the subtle movement of a cancer-causing molecule, and then they found the precise drug that can recognize that motion.

Matthew Monteith

Bile duct cancer is a rare and aggressive form of cancer that is often difficult to diagnose. Patients with advanced forms of the disease have an average life expectancy of less than two years.

Many patients who get cancer in their bile ducts – the tubes that carry digestive fluid from the liver to the small intestine – have mutations in the protein FGFR2, which leads cells to grow uncontrollably. One treatment option is chemotherapy, but it’s toxic to both cancer cells and healthy cells, failing to distinguish between the two. Increasingly, cancer researchers are focusing on biomarker directed therapy, or making drugs that target a particular molecule that causes the disease – FGFR2, in the case of bile duct cancer.

A problem is that in targeting FGFR2, these drugs inadvertently inhibit the FGFR1 protein, which looks almost identical. This causes elevated phosphate levels, which is a sign of kidney damage, so doses are often limited to prevent complications.

In recent years, though, a company called Relay has taken a unique approach to picking out FGFR2, using a powerful supercomputer to simulate how proteins move and change shape. The team, leveraging this AI capability, discovered that FGFR2 and FGFR1 move differently, which enabled them to create a more precise drug.

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Sarah Philip
Sarah Philip is a London-based freelance journalist who writes about science, film and TV. You can follow her on Twitter @sarahph1lip.