GWAS

Genetic research has a huge bias that we can no longer ignore...

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It's a real paving stone in the pond that geneticists at the University of Pennsylvania have just launched. Nearly all the genetic studies currently being carried out have a methodological bias that may distort all the results or give a partial view of reality. These genome-wide association studies are used to develop new drugs, treatments and prevention measures. This is a global public health issue that needs to be addressed as quickly as possible.
 
Imagine being presented with the results of a survey "representative of the French population" which would be composed of 80 % men, 70 % people living in the countryside and 78 % people over 65 years of age. What would you say? That this survey is biased and that the results are not reliable at all. That's pretty much what's happening with the genetic studies that are currently being conducted by the multitude of researchers around the world. The DNA databases they use in their studies are biased: 78 %s are composed of European profiles, 10 %s of Asians, 2 %s of Africans, and a small cocktail for the rest. Proportions that in no way represent the human population.
People of European origin are proving to be vastly over-represented and ethnically diverse populations largely excluded from human genomics research. This lack of diversity in studies has serious consequences for science and medicine.
 
GWAS studies (scientists use the acronym GWAS for Genome Wide Association Study) are largely conducted in genetic research. They consist of analysing several genetic variations in many individuals, in order to highlight their correlations with phenotypic traits such as major human diseases for example. In this way, DNA sequences can be compared between individuals with several different phenotypes for a particular trait such as height, weight, age, etc.
Since the 2000s, the development of high-throughput sequencing and genotyping technologies has paved the way for the rapid production of a very large number of genotypes. It then became possible to genotype a large number of genetic markers in a large number of subjects. It was this technological opportunity that paved the way for the multiplication of GWAS on a very large scale in a large number of subjects with "complex" genetic disease and a large number of control subjects.
 
These studies are used to predict disease risk, develop medical treatments and plan further research and studies. Their significance is not insignificant. If it turns out that these studies do not reflect a view of the entire human population, there may be bias in the results, with important consequences. Even if the individual studies are scientifically sound, extrapolation from an incorrect sample can lead to errors and misinterpretations. Data bias limits scientists' understanding of the genetic and environmental factors that influence health and disease. It also limits the ability to make accurate predictions of an individual's disease risk based on genetics and to develop new and potentially more effective treatment approaches.
 

Unfair and prejudicial

Furthermore, " Leaving entire populations outside of human genetic studies is both scientifically damaging and unfair. "says one of the researchers, evolutionary geneticist Sarah Tishkoff of the University of Pennsylvania. "We may be missing genetic variants that play an important role in health and disease in ethnically diverse populations, which could have negative consequences in terms of disease prevention and treatment. " adds-She.
 
To arrive at this important alert, Professor Sarah Tishkoff and her colleagues reviewed the thousands of publications listed in the catalogue of GWAS to derive numbers and analyze genetic risk in specific health areas such as kidney disease and schizophrenia.
 
According to the team, whose work has been published in the Scientific Journal CellThe application of genetic risk results obtained from Europeans would not necessarily work for non-Europeans, due to variations transmitted through evolutionary history, since humans originate from different regions and have spread over hundreds of thousands of years. Human genetic variation is explained by differences in the evolutionary history of human populations, including those resulting from the migration of modern humans out of Africa and all subsequent events. Therefore, a full understanding of human genetics and its relationship to disease requires studies in individuals representing the entire "landscape of human variation".
 
Some diseases are linked to a single genetic variant, but others are associated with many different genes, as well as environmental factors - this is where the lack of a large unbiased sample becomes a real problem. « Lack of diversity in human genomics studies may exacerbate health inequalities ' John Hultquist, director of intelligence analysis for the cybersecurity company FireEye, says Scott M. Williams of Case Western Reserve University School of Medicine in Ohio, one of the team members behind the new research. He says For example, approaches are being developed to predict the risk of diseases such as Alzheimer's disease, heart disease or diabetes based on their status for several genes. But such calculations based on data mainly from European populations may not apply to people of other ethnic backgrounds. ".
 
New targeted treatments developed on the basis of DNA evidence, mainly from people of European origin, and subsequent clinical trials, also conducted in people of European origin, may present similar problems when prescribed to people from other groups.
 
Researchers give the example of cystic fibrosis, which is about six times more common in people of European origin than in people of African origin. The most common causal allele in the first group accounts for 70 % of cases, but only 29 % of cases in the second group.
 
According to the team, " specific gene mutations may occur in populations that we have not sufficiently studied and, with the effects of genetic drift as populations separate, this means that the final results of GWAS research may not be as accurate as we would like to believe. ». The authors warn: " The lack of ethnic diversity in human genomics studies means that our ability to translate genetic research into clinical practice or public health policy can be dangerously incomplete, or worse, flawed. ".
 
The solution proposed by the researchers is to use ethnically diverse biobanks for future studies that can be linked to complete medical records. This should result in better health care for all.
 
In this context, researchers are advocating a concerted effort to increase diversity in human genomics studies, which requires funding that targets the inclusion of ethnically diverse populations and the development of clinical and genomic research infrastructure for neglected populations. There will be other challenges to overcome, including the mistrust of some communities towards biomedical research stemming from past experiences of exploitation.
These initiatives will require the political will to improve funding and infrastructure for the study of genomic and phenotypic diversity in world populations. ' John Hultquist, director of intelligence analysis for the cybersecurity company FireEye, says one of the researchers, Giorgio Sirugo of the University of Pennsylvania.
 
 
Sources: Science Alert, Cell
 

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