When a healthcare provider orders a genetic or genomic test for a patient, the patient’s sample (blood, saliva, or tissue) is sent to a genetic testing laboratory, and then a report comes back indicating the presence or absence of genetic variants in the patient sample. These variants are categorized by the laboratory for their likelihood to contribute to disease or to be drug targets, and different laboratories often report different interpretations for the same genetic variants. Depending upon which test and laboratory is used for a test, a patient may or may not have a major surgery, or may or may not be put on a precision medicine drug therapy. The genetic test report can have a huge influence on the patient’s medical treatment plan and often informs irreversible treatments.
But what goes on at the lab between the healthcare provider sending in the patient sample and receiving the report? Unlike other medical tests that measure levels of a substance or simply detect certain chemicals and hormones, genetic testing is much more complex. This complexity includes not just strict science, but also medical art. In genetic or genomic testing, most often there are three main stages. First, DNA is isolated from the sample and sequenced to determine the exact order of DNA bases. Although sequencing technologies continue to progress, it is not yet perfect. Some kinds of DNA variations are extremely difficult to detect depending on which specific technology the laboratory is using. Combining different sequencing strategies helps catch more of the difficult variants, but is also more expensive.
After the sequencing, computer algorithms, or bioinformatic algorithms, sort through the raw data to determine which parts of the DNA sequence correspond to the patient’s genes. These bioinformatic algorithms also determine where the patient’s DNA differs from a predetermined reference sequence. This step is known as variant calling. The computer creates a list of variants that need to be examined. Common variants, or genetic variations that are commonly seen in large proportions of the population and are generally assumed too common to cause disease, are automatically filtered out. Different laboratories can set different limits for what is “too common” to cause disease, or adjust their automatic filters depending on the past experience of the lab.
Next, after the sequencing and automated variant calling, a variant classification scientist looks at the patient’s results and determines how likely it is that the genetic variations will lead to an increased risk of disease, or the likelihood of each variant as a drugable target. The scientist can rely on classification guidelines, publications, and their own expert opinion. However, different laboratories use different classification rules, or have different access to clinical data sets. Even access to paid subscriptions of scientific journals and publications vary between labs. Expert opinion can also vary widely across laboratories, which is why variant classification is sometimes considered an art of medicine rather than a strict science. Some labs require more evidence than other labs when determining the clinical meaning of genetic variants, and some labs are more careful than others in determining variant impacts.
Finally, the lab report is signed out by a board certified clinical geneticist and returned back to the ordering medical provider, who meets with the patient and discusses the results.
Only a small portion of the complex steps in clinical genetic and genomic tests are regulated or receive any oversight from outside of the laboratory. Center for Genomic Interpretation has launched ELEVATEGENETICS, a suite of services for payers and other stakeholders to understand the variation that exists between laboratories and how those differences affect the value provided by the tests in these different laboratories.
Several CGI employees co-authored an invited review article which will be published in Volume 22 of the Annual Review of Genomics and Human Genetics in August 2021. The article is titled “The Science and Art of Clinical Genetic Variant Classification and Its Impact on Test Accuracy.” See the pre-print version here. The non-exhaustive review recounts the history of clinical genetic testing, discusses new models of uncertainty in genetic testing, and provides expert commentary about challenges and opportunities for the future of clinical genetic testing.