A study published in the American scientific journal GeroScience reveals a significant but little-known problem for the future of preventive genomics: the reference genome currently used internationally to compare genetic data, known as GRCh38, can lead to false alarms during automated analysis. Researchers at Semmelweis University in Budapest compared the complete genomes of twenty healthy Hungarians with the GRCh38 reference sequence. In all twenty cases, the automated analysis identified the same serious genetic variant, but this finding proved incorrect after manual examination by specialists—none of the participants actually carried a medically significant variant.
Whole-genome sequencing could usher in a new era of personalised preventive medicine, says Dr Gyula Richárd Nagy, a clinical geneticist and associate professor in the Department of Obstetrics and Gynaecology at Semmelweis University. With this tool, each person could receive a “personalised guide” to their risk of specific diseases and their predisposition to them, long before symptoms appear, and explore personalised prevention options. According to Nagy, none of this is even in the distant future.
Whole-genome sequencing means reading almost the entire “text” of a person’s genetic information: more than six billion DNA letters, including around 40,000 genes and the regions that regulate their function. “If we put them all side by side, they would fill about 4,000 books of 500 pages each,” Nagy explains. The international Human Genome Project began in 1990, and the first draft of the human genome was completed in 2001, but it was not until 2022 that an essentially complete genome without gaps was assembled for the first time.
The problem lies in what is used as the reference point. GRCh38 is not an “average” human genome that fits every person perfectly. It is based on a single, linear reference coordinate system. Although it contains genetic data from many people, 70% of the data comes from the genome of one man from Buffalo in the United States. “When we analyse the whole genome, we need to examine and compare a huge amount of data. This is done by automated software around the world. However, if the system encounters a healthy genetic variant in a patient that is listed in the reference as an extremely rare gene variant, it can trigger a false alarm,” adds Nagy, a lead author of the study.
In current clinical practice, the problem is not immediately apparent, as discrepancies identified by the software are examined and analysed manually by specialists, who also use other population databases. However, this correction would create an unsustainable bottleneck if preventive screening increased and could become one of the obstacles to the future expansion of mass preventive testing, Nagy warns. In other words, if the map does not provide a comprehensive picture of human genetic diversity, then without specialist oversight—relying solely on certain automated data—we could easily mistake healthy genetic traits for defects. This is exactly what the university researchers’ study showed.
The solution proposed by the researchers is a graph-based pangenome. Instead of comparing each person’s genome with a single reference sequence, a kind of network of genetic maps would be built from the data of many genetically diverse people, providing a much better picture of human genetic diversity. The pangenome graph already exists as a computational reference: it represents the shared and differing sections of many human genomes in a branching structure, rather than describing one person’s DNA sequence as a single sequence. However, its clinical application in everyday practice has yet to happen.
“The key question for the future is how far information technology will be able to keep pace with medical progress. Today’s everyday IT systems simply cannot support the daily use of such enormous databases,” notes Dr Balázs Győrffy, head of the Department of Bioinformatics at Semmelweis University and another lead author of the study. Nagy stresses that it is extremely important to actively explore the limits of the technology so that this branch of preventive medicine can provide the highest level of safety without compromise.
Genetic testing is already used in medicine today. For certain types of cancer, for example, a tumour sample is analysed to identify genetic abnormalities that can help determine which targeted treatment is likely to be effective. Genetic testing plays an important role in diagnosing and treating rare conditions, as well as detecting hereditary diseases. It can be used to assess the risk of hereditary diseases in members of affected families, allowing early detection and preventive interventions, as in cardiogenetics.
However, the fundamental approach of future preventive and predictive medicine, based on whole-genome sequencing, goes beyond these limits. The researchers point out that it rests on the idea that we will not only know how to treat a disease once it develops, but will know the risk before symptoms appear and understand who needs early attention and why. They add that whole-genome sequencing for this purpose is not currently part of publicly funded routine healthcare and is available only through private funding.
Comments