A genetic test provides raw data, but the results often identify genetic variants, which are common changes in our DNA sequence. The task for scientists is to determine if a specific variant has any bearing on health through a process called variant interpretation. This methodical investigation translates raw genetic data into actionable information that can guide healthcare decisions for individuals and their families.
The Evidence Gathering Process
Interpreting a genetic variant begins with a comprehensive evidence-gathering mission. To build a case for or against a variant’s role in disease, scientists draw a conclusion from the collective weight of all data, as no single piece is sufficient. This process helps ensure the final classification is as accurate as possible.
A primary step is consulting large-scale population databases like the Genome Aggregation Database (gnomAD). These resources compile genetic information from thousands of individuals from diverse backgrounds. Scientists check how frequently the variant appears in the general population, as a common variant is less likely to cause a rare genetic disorder.
Researchers also use computational, or in silico, prediction tools like SIFT and PolyPhen-2. These programs analyze the genetic change to forecast its potential impact on the resulting protein’s structure or function. While a useful component of the investigation, these predictions are not definitive and are considered supportive, rather than conclusive, evidence.
Functional studies are laboratory-based experiments designed to test the specific effect of a variant on a protein or cell. For example, a study might insert the variant into cells to observe whether it disrupts normal cellular processes. This evidence provides a direct biological readout of the variant’s consequence, though such studies are not always available.
Another line of evidence is segregation analysis within families. This involves examining a family’s genetic information and health history to see if the variant travels with a disease through generations. If all affected family members carry the variant while unaffected members do not, it provides strong evidence linking the two.
Finally, a review of existing scientific literature is performed. Researchers search databases like PubMed and specialized variant repositories for previous studies on the specific variant. Discovering that a variant has already been documented by other experts can provide substantial information and streamline the interpretation process.
The Classification System
After gathering evidence, scientists use a standardized framework to classify the variant. Guided by recommendations from the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP), this system sorts variants into five distinct categories. This creates a common language for laboratories, clinicians, and patients.
The system sorts variants into the following five categories:
- Pathogenic: A variant is placed in this group when evidence confirms it directly causes a specific disease. This classification is for variants with a well-established link to a health condition and can confirm a diagnosis for a patient.
- Likely Pathogenic: This is used when evidence strongly suggests the variant is disease-causing, but falls just short of the pathogenic criteria. There is a very high confidence (greater than 90%) that the variant is responsible for disease.
- Benign: These are changes that are known not to cause disease. Evidence, such as a high frequency in the general population or functional studies showing no effect, confirms their harmless nature.
- Likely Benign: This category is for variants where there is strong evidence of a benign status, but without the same level of certainty as a definitively benign variant.
- Variant of Uncertain Significance (VUS): This is given when there is not enough evidence to place the variant in either the pathogenic or benign categories. The available information may be limited, conflicting, or absent.
Navigating Variants of Uncertain Significance
Receiving a “Variant of Uncertain Significance” (VUS) result means the scientific community currently lacks enough information to determine if the genetic change is related to a health condition or is a harmless variation. A VUS is not a diagnosis but a statement of the current limits of our knowledge.
A variant receives a VUS classification because it is exceptionally rare and has not been observed enough in population databases to be labeled benign. It may also be that computational predictions are ambiguous, or there are no functional studies or family data available. Sometimes, the existing evidence is contradictory.
For patients, clinical management following a VUS result is based on their personal and family health history, not on the VUS itself. Medical decisions and screening recommendations will continue to follow established guidelines for the individual’s circumstances, independent of the uncertain genetic finding.
Testing other family members can sometimes help clarify the significance of a VUS. If the variant is found in other relatives with the same health condition but not in those who are unaffected, it could provide evidence to reclassify it. Patients are also encouraged to maintain contact with their clinic, as new research may allow the lab to re-evaluate the VUS.
The Evolving Nature of Genetic Knowledge
The interpretation of a genetic variant is not a final conclusion. Genetics is a dynamic field, and our understanding is refined as new data becomes available. A classification assigned today may be updated in the future based on new scientific evidence, a process called reclassification.
This ongoing evolution is relevant for all variants, especially a VUS. As more people undergo genetic testing and researchers conduct more studies, a VUS may be reclassified to either pathogenic or benign. This happens when new evidence, like new population data or functional studies, provides the previously missing clarity.
This process is facilitated by global data-sharing efforts. Public databases like ClinVar serve as central repositories where laboratories and researchers can submit their variant classifications and supporting evidence. This collaborative approach allows for the aggregation of knowledge, enabling the medical community to refine interpretations over time.
Consequently, a genetic test result is a snapshot of our understanding at a specific point. The continuous growth of genetic data ensures that the interpretation of our DNA will become more precise. This highlights the importance of the ongoing relationship between patients, clinicians, and laboratories to apply the most current knowledge to healthcare.