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Taking Genomic Data Global

Startups focused on Asia are among those aiming to bring precision medicine to far more people.

Colon cancer is less common in India than in the U.S., but it tends to affect younger people and to be more aggressive when it does occur. Indians with colon cancer also have different genetic mutations from the ones affecting patients who have been studied in Western countries, and whose information is the basis of most published data on the disease. A vegetarian diet may help explain the overall statistics, but why do some Indians develop a more serious form of the disease at a younger age?

Doctors suspect that differences in the genome may help explain how colon cancer expresses itself in the two groups. A startup called Global Gene Corp plans to study Indian patients’ genomes to find out what those links may be and whether they yield clues to better treatment.

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The company will analyze patients’ DNA as well as the genomics of their cancer cells, using algorithms to identify treatment options for individuals—as well as broader trends. Aggregate data could be relevant for pharmaceutical companies looking to develop new medicines, and for policy makers, too.

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Global Gene Corp thinks that by examining genetic patterns, it can help uncover important insights into a number of ailments that affect Indians, among them diabetes, a type of liver disease called Wilson’s disease, and multiple cancers. It offers tests to make diagnoses, to predict whether a person is a carrier for or has an inherited disposition to a disease, and to determine the best type or dose of medicine for an individual.

Examining genetic patterns, Global Gene Corp hopes to gain insight into cancers and other ailments that affect Indians.

Among the genetic mysteries the company hopes to solve is why Indians are predisposed to diabetes and other obesity-­related diseases at a lower body mass index than Westerners.

The firm, which is based in Singapore, got its start in Boston in 2013, when two Harvard Medical School physicians joined two executives to explore how to use genomics to improve health care in the developing world. The quest took them to India, which despite its huge population and rich diversity has largely been left out of the explosion of genomic information that followed the first sequencing of a human genome in 2003. According to the company, just 0.2 percent of genomic data comes from India, even though it has 20 percent of the world’s population.

The situation is similar across much of the world. Though countries outside the U.S., Europe, and Japan make up 60 percent of the world’s population, they contribute less than 1 percent of sequenced genomic data globally, the company says.

This is largely because poor countries historically focused their health resources on managing and eradicating communicable diseases and did not establish programs like the Human Genome Project in the U.S. and Genomics England in the U.K.

Global Gene sees a business opportunity in this omission. Taking into account population predictions, cancer statistics, and pharmaceutical research spending, company executives think the Indian market for genomic information that could be used in drug development and cancer treatment may reach $1.9 billion. Adding in China, Southeast Asia, and the Middle East—areas where Global Gene hopes to expand—would increase the total addressable market to $8.1 billion, with a 14 percent annual growth rate, according to the company.

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The closely held company won’t disclose its revenue, but it has raised private investor funding and forged partnerships with 48 business, government, and scientific organizations across Asia and Europe. The Wellcome Trust Sanger Institute, which played an important role in the original sequencing of the human genome, now houses Global Gene’s R&D center on its campus in Cambridge, England.

The company has also already gathered more than 10,000 DNA samples with patient consent, resulting in what it says is India’s largest genomics biobank, and established the core for a reference genome (a digital “average” genome) for Indians. It says a reference genome will help it derive insights about the many diseases in India.

Global Gene isn’t the only player with its eye on Asia. A nonprofit consortium of academics and companies, called ­GenomeAsia 100K, wants to sequence 100,000 people in South, North, and East Asia and create perhaps 50 to 100 reference genomes, representing all major Asian ethnic groups, within the next four years. Japan, for example, is believed to have three major ethnic groups, with some degree of genome variation, according to project leader Stephan Schuster, a biology professor who is research director of the Singapore Centre on Environmental Life Sciences Engineering at Singapore’s Nanyang Technological University.

Previous attempts to document human genetic variation failed to shed much light in South Asia. The 1000 Genomes Project, which ran between 2008 and 2015 and was designed to capture population diversity, sequenced genomes from only a few South Asian ethnic groups, among them Gujarati Indians and Pakistani Punjabis. An earlier, smaller effort called the International HapMap Project, which was supposed to be a catalogue of common human genetic variants, gathered DNA from just one South Asian population (Gujarati Indians).

Government-funded genome projects may yield more information. Genomics England’s 100,000 Genomes Project, which is sequencing patients who have rare diseases and cancer, records participants’ ethnicities and considers how that information may be relevant to the patient’s condition. In the United States, President Obama’s Precision Medicine Initiative Cohort Program, which is set to launch later this year, will collect participants’ ethnicity, amongst other data. Its goal is for this data to help researchers study individual differences in health and disease.

Such large-scale genetic mapping projects have often struggled to acquire enough samples to draw meaningful conclusions. Global Gene is trying to sidestep the problem by obtaining samples through multiple sources, including partner hospitals, research projects, and voluntary donations from individuals who arrange for testing on their own.

Payment may be an issue, says ­Lawton R. Burns, a professor of health-care management at the University of Pennsylvania’s Wharton School who has written books about China and India. He estimates that only 25 percent of Indians have medical insurance, and most of those plans wouldn’t cover genetic testing. “To make this work, you need people who not only want to know their genetic makeup but are engaged in their health care, have the money to pay for the test, and are willing to spend that money,” Burns says.

Global Gene’s clinical tests range in cost from $75 to $538. India’s median income was $616 in 2013, according to a Gallup survey.

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And there is another big problem, Burns says: “Even if patients buy the tests, what will they be able to do with the information?”

Global Gene is trying to make it useful. Many of the startup’s genetic tests incorporate a proprietary technology that recognizes mutations commonly seen in Indians. Insights from this multi-gene assay provide a baseline that helps the company differentiate clinically insignificant genetic variations present in the Indian population from potentially pathogenic ones.

Using this, plus its software, it can gauge whether a person is likely to suffer potentially life-threatening complications from taking cholesterol-lowering medications known as statins. It can also screen for mutations in genes that are known to increase cancer risk, such as BRCA1 and BRCA2, which are linked to a much higher chance of developing breast and ovarian cancer. (Indians and Western populations have different groupings of BRCA mutations.)

Data from the tests can be used to identify people with particular genetic characteristics, whom pharmaceutical companies could recruit to expedite drug trials.

“To change health, we have to represent the world,” says Jonathan Picker, a Global Gene cofounder who is also a geneticist at Harvard Medical School. “It doesn’t make sense to take a couple of subsets and assume that now we understand everybody.”

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