3billion CEO Keum Chang-won
What would it be if we had to pick one piece of information most important for the genetic diagnosis of rare disease patients?
The information required for genetic diagnosis is very diverse, such as the correlation between genes and diseases, the function of genes, important location information that determines gene function, and the frequency of finding genetic mutations.
However, if there is only one important piece of information, it would be the pathogenic genetic mutation information that determined a patient's diagnosis in the past.
Suppose a genome decoding of a patient waiting for diagnosis shows the same genetic mutation as the previously confirmed patient. In that case, this becomes a strong basis for diagnosis as it means that the patient waiting for diagnosis has the same disease as the previously diagnosed patient.
The increase in pathogenic mutation information means that we can secure the basis for interpreting more genetic mutations, which, in turn, means that more rare disease patients can receive an accurate diagnosis.
With the recent innovation of genome decoding technology, we can decode genome information of many patients, which helped us rapidly accumulate pathogenic mutation information.
However, it cannot be said that there is enough information on pathogenic genetic mutations to be able to diagnose rare diseases at a sufficient level.
Then how much more mutation information do we require?
The human genome is composed of three billion DNA. If we count the number of single-nucleotide variants (SNVs) where DNA at each location is converted into a different type of DNA, the number reaches nine billion.
Considering all the various types of genetic mutations, such as DNA disappearing, overlapping, and multiple DNA changes simultaneously, the number of mutations in the human genome is virtually infinite.
However, only about 1.54 million mutations are registered in ClinVar, the largest database of genetic mutations worldwide.
When compared with the nine billion SNV types, we can infer that the pathogenic information of genetic mutations currently known to mankind is insufficient.
To overcome this situation, the global clinical genetics community has established a public database with ClinVar. It collects information on the pathogenicity of genetic mutations of patients obtained through genetic testing.
If we share the genetic mutation information of the patient we have diagnosed, we can diagnose rare patients with the same mutation worldwide.
If we share the diagnosis of patients with rare diseases, everyone benefits together, and the diagnosis rate of patients with rare diseases increases.
Hospitals and major global genetic diagnosis companies are actively sharing this genetic mutation information.
In terms of numbers, companies share the most genetic mutation information. The top 8 companies, including Invitae, a U.S. company, have shared 1 million cases, GeneDx 310,000 cases, and Color Health with 70,000 cases, accounting for 72 percent of ClinVar’s genetic mutations database.
In Korea, 23 institutions shared 3,533 mutation data to ClinVar, with 3billion accounting for 87 percent of all reported mutations from Korea with 3,074 cases.
There are many reasons why diagnostic companies actively share pathogenic genetic mutation information, which is an asset to the company.
However, after recognizing the limitation that a single institution cannot secure the necessary and sufficient number of genetic mutation information for the diagnosis of genetic diseases, companies are voluntarily sharing data to fulfill their mission and responsibility as a diagnosis company if it means they can accurately diagnose even a single patient.
Governments worldwide invest huge amounts of money to secure patient genetic mutation information through large-scale genome research projects and disclose them for public use.
Korea has currently secured the data of 15,000 patients with rare diseases through a national bio big data pilot project. In addition, the government is planning to disclose pathogenic genetic mutation information so it can be used for public purposes.
The genetic mutation information accumulated on a large scale by the government, business, and academia is not only used as evidence data for direct patient diagnosis. Still, it is also used as learning and test data for artificial intelligence models for pathogenicity prediction.
In addition, it can be utilized in interpreting genetic mutations for which there is no basis and as a resource to improve rare genetic disease diagnosis technology in various forms.
When everyone makes some sacrifices and helps each other, the entire ecosystem can prosper to a greater extent.
The cooperation of global governments, companies, and academia to disclose genetic variation information was possible because they prioritized the public good of diagnosing and treating patients with rare genetic diseases.
Companies that disclose genetic mutations that have sacrificed their potential profit-making data for the public good are rewarded with improved market credibility and growth.
In the future, I look forward to the active data sharing between the government, academia, and companies for diagnosing and treating rare genetic diseases and using this virtuous cycle to establish a growing ecosystem.