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More Diverse Genomic Databases Can Tackle Healthcare Inequalities

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More Diverse Genomic Databases Can Tackle Healthcare Inequalities

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When the first complete sequence of the human genome was published in 2003, the Human Genome Project leader, Francis Collins, noted that it marked “the start of an exciting new era."

The opportunities for medicine and healthcare seemed endless, and many of the exciting prospects of human genomics are starting to be realized. Genetic analysis is now a common part of diagnosis or treatment for many conditions ranging from cancer to rare diseases, and targeted treatments based on specific genetic variants have made personalized medicine a reality.

Modern genomic medicine: an unequal playing field

Not everyone has been able to benefit equally from these advances, however. Research has shown that most of the genetic knowledge we have is based on the genomes of a select group of individuals.  According to a recent analysis, an estimated 78 % of genomes in genome-wide association studies (GWAS) are from people of European descent (see figure 1).1 Another recent study puts this number as high as 88 %2 – barely an improvement from a decade ago when 96 % of genomes were European.

This data bias has created healthcare disparities that have left a large part of the global population behind.4

Figure 1: Distribution of ancestry in the overall catalogue of GWAS studies (left) and individuals within studies (right), adapted from Sirugo et al. 2019.1 

All other non-European ethnicities are underrepresented, meaning that the majority of genetic information we have is only accurate for a small portion of the global population.

The source of underrepresentation

There are a number of reasons for this uneven representation of genetic data, ranging from the fact that the first genomic sequencing projects took place in majority white countries, to cultural concerns and privacy issues.

Regardless of how it has occurred, the resulting lack of basic genetic data on people of non-European ethnicities means that individuals are at risk of being misdiagnosed, left undiagnosed, or receiving the wrong medication for their conditions.

Misdiagnoses and side effects

In their recent commentary in Cell, Sarah Tishkoff and colleagues at the University of Pennsylvania highlight some of the specific issues caused by a lack of diversity in genomic information.

One of their examples is the diagnosis and treatment of cystic fibrosis (CF). In people of European background, roughly 70 % of CF cases are caused by a genetic mutation that deletes amino acid phenylalanine-508 (F508) in the CF transmembrane conductance regulator (CFTR) channel. This particular mutation is well-studied, and several precision medicine treatments are tailored to this seemingly common version of the disease.

However, in people of African descent, the F508 deletion in CFTR accounts for only 29 % of CF cases, and a wide variety of other genetic variants seems to be linked to development of the disease.5 Many of these variants haven’t been as extensively studied as the F508 deletion. As a result, CF is underdiagnosed in this population, disenfranchising them from access to speciality care and targeted treatments.

A similar problem occurs with another common disease: asthma. In the United States, this disease is most common among people of Puerto Rican or African descent, yet these groups don’t respond as well to the common asthma drug Albuterol as patients of European descent.

A recent study of over 1400 children with asthma revealed gene variants linked to a lower drug response, but there wasn’t enough data from other groups of patients with similar ethnic backgrounds to be able to replicate the study and verify the finding.6

Besides underdiagnosis or insufficient data on drug side effects, another risk of these imbalanced databases is incorrectly assuming a genetic variant is disease-causing. Many alleles labelled as pathogenic based on European genomes have been shown by research to be harmless regional variations in the context of a more diverse genetic database.7

These types of health inequalities have been emerging for several years now. How can we prevent them?

Increasing diversity in genomics – a growing solution for a growing problem

One of the key steps in tackling this problem is to make sure that genetic databases include a broad diversity of genomes.

Having background genetic information on different populations makes it easier to diagnose genetic conditions within the context of that population and develop more targeted care. 

Even a seemingly small improvement can already make a difference. When researchers discovered that several patients with hypertrophic cardiomyopathy had received a wrong genetic diagnosis, they noted that the problem could have been avoided even if only 10 % of the control cohort had been of African descent.8 

Several projects are currently underway to invite more participants from underrepresented groups to take part in genetic studies. African genomes are extremely diverse and can provide a lot of information regarding global human genetic history, making these populations particularly interesting to study. 

One initiative — the Human Heredity & Health in Africa (H3Africa) programme—  is funded by Wellcome and the NIH, supporting local scientists in carrying out genetic research within different countries across the continent.9

Another example comes from Namibia, sitting within the region of Africa that is widely believed to be the home of the world’s most ancient human race. Its population consists of more than 10 different tribes and ethnic groups, all of which are likely to have their own genetic variations that influence health, disease and response to treatment. 

In November 2018, Global Gene Corp teamed up with the University of Namibia and the Namibian Ministry of Higher Education, Training and Innovation to announce the establishment of a new national genomic initiative for the country, aiming to build a framework for genomic research and improve precision medicine in this area. Future plans also include setting up a Centre of Excellence in Genomics in Namibia, providing training programmes to build local capacity and expertise in this fast-growing field.

For Global Gene Corp’s founder and CEO, Sumit Jamuar, this is a vital part of his mission to realize the promises of genetic medicine for everyone, wherever they live. “People with European ancestries are able to benefit from precision healthcare in a way that isn’t currently available for many other people,” he says. “This is what we want to change for the future.” 

The company is now building a database from the Indian subcontinent, generating insights from the data to build an evolving personalised pharmacogenomics app (ggcMETM) that is tailored to the population. Even though 20 % of the world’s population, and much of its diversity, comes from this part of the world, people with Indian ancestry make up only a fraction of the current genetic databases.

This represents a significant data gap when it comes to the diagnosis and treatment of many common conditions that are increasingly affecting people living in the region, such as diabetes and heart disease.2

By increasing genomic data and insights from underrepresented populations, efforts such as these will allow more people to take advantage of the promises of precision medicine, wherever they come from and wherever they live.

About the authors

Jonathan Picker MD PhD is co-founder and co-Chief Scientific Officer of Global Gene Corp. He is Assistant Professor of Paediatrics at Harvard Medical School and a clinical geneticist at Boston's Children's Hospital.

Dr. Saumya Jamuar, MBBS, MRCPCH, is co-founder and co-Chief Scientific Officer of Global Gene Corp; Head, SingHealth Duke-NUS Genomic Medicine Center, Singapore; Attending, Genetics Service, KK Women’s and Children’s Hospital, Singapore; Assistant Professor, Paediatrics, Duke-NUS Medical School, Singapore; Clinical Director, SingHealth Duke-NUS Institute of Precision Medicine, Singapore; PI, Singapore Undiagnosed Disease Programme.


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2. Mills, M. C., & Rahal, C. (2019). A scientometric review of genome-wide association studies. Communications Biology, 2(1), 9. https://doi.org/10.1038/s42003-018-0261-x 

3. Need, A. C., & Goldstein, D. B. (2009). Next generation disparities in human genomics: concerns and remedies. Trends in Genetics, 25(11), 489–494. https://doi.org/10.1016/j.tig.2009.09.012 

4. Landry, L. G., Ali, N., Williams, D. R., Rehm, H. L., & Bonham, V. L. (2018). Lack of diversity in genomic databases is a barrier to translating precision medicine research into practice. Health Affairs, 37(5), 780–785. https://doi.org/10.1377/hlthaff.2017.1595

5. Stewart, C., & Pepper, M. S. (2016). Cystic fibrosis in the African diaspora. Annals of the American Thoracic Society, 14(1), 1–7. https://doi.org/10.1513/AnnalsATS.201606-481FR 

6. Mak, A. C. Y., White, M. J., Eckalbar, W. L., Szpiech, Z. A., Oh, S. S., Pino-Yanes, M., … Burchard, E. G. (2018). Whole-genome sequencing of pharmacogenetic drug response in racially diverse children with asthma. American Journal of Respiratory and Critical Care Medicine, 197(12), 1552–1564. https://doi.org/10.1164/rccm.201712-2529OC 

7. Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., … Exome Aggregation Consortium. (2016). Analysis of protein-coding genetic variation in 60,706 humans. Nature, 536(7616), 285–291. https://doi.org/10.1038/nature19057 

8. Manrai, A. K., Funke, B. H., Rehm, H. L., Olesen, M. S., Maron, B. A., Szolovits, P., … Kohane, I. S. (2016). Genetic misdiagnoses and the potential for health disparities. New England Journal of Medicine, 375(7), 655–665. https://doi.org/10.1056/NEJMsa1507092 

9. Mulder, N., Abimiku, A., Adebamowo, S. N., Vries, J. de, Matimba, A., Olowoyo, P., … Stein, D. J. (2018, April 10). H3Africa: current perspectives. https://doi.org/10.2147/PGPM.S141546