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In the 15 years since the human genome project first unveiled our DNA fingerprint, vast amounts of genetic data have been collected from millions of people in many parts of the world. The work of Carlos D. Bustamante consists of looking into these genetic data for clues ranging from ancient history to human migration patterns to the reasons why people with different ancestors are so different in their response to common diseases.
Bustamante's career lasted about the same time as the human genome project. Professor of Genetics and Biomedical Data Science at Stanford and 2010 winner of the MacArthur Engineering Award, he helped unravel the complex genetic variations between different populations. These variants mean that the causes of diseases can vary considerably between groups. One of the motivations of Bustamante, born in Venezuela and settled in the United States at the age of seven, is to use this information to reduce the medical disparities that still strike us.
While this is an area for improving medicine, it also raises many controversies about how to interpret genetic differences between human populations. At a time still obsessed with race and ethnicity – and marked by the misuse of science to define the characteristics of different groups – Bustamante remains fearless in his search for nuanced genetic differences of these groups.
His optimism may be due to his personality: few sentences pass without "fantastic" or "extraordinarily exciting". But it's also his recognition, as a population geneticist, for the incredible opportunity that understanding of the differences in human genomes offers to improve health and fight disease.
David Rotman, Review of MIT technologyThe publisher as a whole explained to Bustamante why it is so important to include more people in genetic studies and understand the genetics of different populations.
How can we ensure that the genomic data we collect is inclusive?
I am optimistic, but it has not happened yet.
In our 2011 article, the statistic we had was that more than 96% of participants in genome-wide association studies were of European origin. During the follow-up in 2016, this number went from 96% to about 80%. So it's better. Unfortunately, or perhaps fortunately, this is largely due to China's entry into genetics. This is largely due to large-scale studies of Chinese and East Asian populations. Hispanics, for example, account for less than 1% of genome-wide association studies. We must do better. In the end, we want precision medicine to benefit everyone.
Aside from an equity issue, why is the diversity of genomic data important? What is missing without it?
First of all, it has nothing to do with the politically correct. This has everything to do with human biology and the fact that human populations and the large diaspora of human migrations have left their mark on the human genome. The genetic foundations of health and disease have components common to human populations and elements unique to different populations.
How's it going?
Diabetes is a good example. If we look at the genetics of diabetes, it differs from country to country. In early 2010, the Broad [Institute of MIT and Harvard] conducted a study with the National Institute of Genomic Medicine of Mexico to study the genetics of diabetes. Indeed, they found in Mexico a genetic variant whose frequency is 25% and that we do not observe in European, Asian or African populations. It is generally seen only in the Americas, which highlights much of the ethnic disparity in diabetes.
We did research on seemingly innocuous traits like blond hair. There is no more striking phenotype. Some people have blond hair and some do not. And the cause of blond hair in Melanesia is completely different from the cause in Europe – and that blond hair. So, why do you think that diabetes, heart disease, all these other complex traits will have identical causes in all humans? It does not mean anything.
It turns out that the highest prevalence of asthma [in the US] is composed of individuals of Puerto Rican descent, followed by individuals of African-American descent, followed by European descent. The people with the lowest rate of asthma are those of Mexican origin. You have two Hispanic populations at opposite ends of the spectrum.
Why are these genetic differences useful for medicine?
If the genetic etiology of the disease is different, this gives us the opportunity to discover new drug targets. This gives us a new biology that can then be used even for those who do not necessarily suffer from the disease in this way. This is important for drug discovery. If you think it looks like oil, we're just looking for oil in the North Sea. There are many other places to look for, and this benefits everyone.
Second, we find that polygenic risk scores [disease-risk predictions based on genetic tests] of European descent does not easily translate into other populations. If we do not have a broad representation in medicine and population genetics, we risk aggravating health disparities, which will be a terrible result for precision medicine and precision health.
So, are not you disappointed by the lack of progress in including more populations in the genomic data?
I am really excited. We have done an excellent job in extracting drug targets in Europe. Iceland opened the way, Britain preceded it and now Finland. So we are exploiting all these resources – great. But what about Latin America? What about Africa? What about Southeast Asia? All of these places have a lot to contribute to our understanding of health and illness.
It is both a moral obligation and a missed scientific opportunity if we do not go to work in these populations.
Many genetic researchers have long argued that race has no scientific basis. But the debate does not seem to disappear.
In a global context, there is no model for three, five or even ten human races. There is a wide continuum of structured genetic variations and pockets of isolated populations. Three, five, or ten human races are simply not a precise model; it's much more a continuum model.
Humans are a wonderfully diverse species, both phenotypically and genetically. It is a very classical population genetics. If I walk from Cape Horn to the top of Finland, each village looks like the neighboring village, but at extremes, people are different.
But as a population geneticist?
I do not find in race a meaningful way of characterizing people.
You walk in a difficult line, however, is not it? You emphasize the importance of the variance between different populations, but you do not want to reinforce the old breed categories.
We can not use genetics to try to define the stories we tell about ourselves. The social determinants of health are often much more important than genetic determinants of health, but this does not mean that genetic determinants are not important. We must understand the complexity and understand how we translate this to the general public.
I am actually an optimist. I think the world is becoming less racist. If you talk to the next generation of people, millennials down, those abominable ideologies are rejected. This means that it gives us space to reflect now on the role that genetics plays in health, disease and human evolution, in a way that we can understand soberly and address important issues.
We can not let genetics be diverted by the politics of identity. If you start allowing politics and other interests to interfere, you just have to scramble the tracks. You must let the data drive. You must let the results lead. And the rest will follow.
Data bias in dna studies
Precision medicine becomes more accurate for some but leaves many others behind. And those who remain are often people of Latin American, African, Native American descent and other ancestors who are underrepresented in genomic databases.
By far, most data from genome-wide association studies, which have been essential for detecting genetic variants related to common diseases, come from people of European origin. In 2011, Carlos D. Bustamante and his colleagues highlighted the disparities and the resulting threat that genomic medicine "will greatly benefit a few privileged". In the following years, the collection of genomic data exploded, but disparities remain. In 2016, Alice Popejoy, a PhD student at the University of Washington and a postdoctoral fellow at the Bustamante Laboratory, updated the results in the journal. Nature, noting much progress for most population groups.
One of the results of this lack of data is that genetic testing may be less relevant and less accurate for people from underrepresented groups. Increasingly popular genetic testing for consumption can be misleading or simply wrong, and medical genetic testing for some common diseases is often inconclusive. Similarly, says Popejoy, false positives and false negatives in genetic diagnoses are more common among non-European ancestry, as the results are interpreted using incomplete or biased databases. favor of European descent.
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