As genetic testing continues to expand in both clinical and research settings, variants of uncertain significance (VUS) present a persistent challenge. For the uninitiated, VUS is one of five classifications assigned to genetic variants under ACMG guidelines which indicate the likelihood that a variant causes disease.
Generally, uncertain significance is the default classification for variants that cannot otherwise be classified as pathogenic/likely pathogenic (i.e. disease causing) or benign/likely benign (not disease causing).
If you’re familiar with genetic testing trends over the last decade, you probably know that VUS are increasingly prevalent on genetic testing reports. In part, that’s due to technological advances, e.g. high-throughput DNA sequencing, that make it possible to interrogate more of the patient’s genome in a timely and cost-effective manner. Gene panels for specific conditions now often encompass thousands of genes, and comprehensive testing — genome or exome sequencing — is increasingly available as a first-tier or second-tier test.
Increasing knowledge — specifically, the number of genes associated with disease — is another important contributor to the VUS explosion. The pace of gene discovery accelerated in the NGS era and continues to grow, as illustrated by the statistics provided by the Online Mendelian Inheritance in Man (OMIM) database:
Long story short, more variants detected in every patient (by comprehensive sequencing) combined with more genes that are possibly reportable (due to association with disease) means more variants on genetic testing reports. And, as I’m about to tell you, for reportable variants, VUS will often be the expected classification.
ACMG Variant Interpretation 101
First, a very brief introduction to the types of evidence that are used when interpreting variants and how they are represented. ACMG evidence codes are letter/number combinations.
- The first letter indicates the type of evidence (Pathogenic or Benign).
- The second 1-2 letters indicate he strength of evidence (Very Strong, Strong, Moderate, or SuPporting).
- The number is a category we use to keep them all straight.
So for example, PS2 is the evidence code applied when a variant occurs de novo in a patient with confirmed maternity/paternity. This is the second (2) type of strong (S) evidence of pathogenicity (P), hence the code PS2. For another example, when a variant’s population allele frequency is greater than expected for the disorder, it gets the code BS1 (the first type of benign strong evidence). The weakest level of evidence, supporting, is given the strength-designation P. For example, BP1 applies when you have a missense variant in a gene in which almost all disease-causing variants are truncating/loss-of-function.
When a variant is assessed, each type of evidence is evaluated to see if it applies. The final set of evidence is combined into a formula to determine the final classification. The rules for combination to get a pathogenic or likely pathogenic variant are shown to the right. So for example, for a variant with very strong (VS) evidence of pathogenicity, only one additional strong evidence code is required to classify it as pathogenic. If that second piece of evidence is moderate strength, the variant would be classified likely pathogenic. There’s a similar formula for benign/likely benign evidence.
How We Get To VUS
What if we have some evidence that a variant is pathogenic, but not enough to meet this threshold? Or worse, what if we have a lot of benign evidence but one pathogenic code? The ACMG guidelines lay it out:
VUS Due to Conflicting Evidence
Under the ACMG framework, every variant is assessed both for pathogenic and benign evidence criteria. It is thus quite possible — and does happen on a regular basis — that a variant has both types of evidence, i.e. conflicting evidence. For example, a variant that does not segregate with disease in a family (BS4) and has no predicted effect on the encoded protein (BP4) might still be rare in the general population (PM2).
Another example we often encounter is a missense variant that is rare (PM2), segregates with disease (PP1), and is computationally predicted to be damaging (PP3), but in a gene in which most known disease-causing variants are null variants (BP1). As written above, under ACMG rules, any variant with both types of evidence, no matter the tipping of the scale, defaults to VUS.
VUS Due to Insufficient Evidence
This is the more common pathway to classifying a variant as VUS: there is not enough evidence of pathogenicity to meet the threshold of likely pathogenic, or there’s benign evidence but not enough for likely benign. For example, a novel missense variant (PM2) in a dominant disease gene which is computationally predicted to damage the encoded protein (PP3), without additional evidence, is a VUS (PM2, PP3). Missense variants in general struggle to garner enough evidence to reach pathogenicity due to the strength of evidence codes that can be applied to them; more on that in the next section.
Variants in new or emerging disease genes are especially prone to the “Insufficient Evidence” VUS classification because the etiology of disease is still being established. If only a handful of disease-causing variants have been reported, it’s often difficult to ascertain:
- Whether null variants or missense variants are the predominant type of causal variants
- The presence of mutation hotspots or critical functional domains in which variants almost always cause disease
- The maximum population frequency of established disease-causing variants
Also, relatively new disease genes rarely have robust functional studies that can be used to enhance variant classification. These problems are all exacerbated for missense variants.
Some Variants Have It Easy: Null Variants and De Novo Mutations
You will note that having Very Strong evidence gets you a long way toward classifying a variant as pathogenic. Unfortunately, there is only one type of evidence that carries the weight Very Strong: PVS1. This is reserved for null variants, i.e. the types of variants (e.g., nonsense, frameshift, canonical ±1 or 2 splice sites, initiation codon, single exon or multiexon deletion) that are “assumed to disrupt gene function by leading to a complete absence of the gene product by lack of transcription or nonsense-mediated decay of an altered transcript.” (Richards et al 2015).
As I mentioned earlier, null variants that qualify for PVS1 only need one more piece of moderate-strength evidence to reach likely pathogenic. That’s great for null variants, but such variants represent a tiny fraction of the variants encountered in most genes in most patients. Missense variants are far more prevalent but face an uphill battle toward pathogenicity.
It’s a similar story for de novo mutations: a variant in a dominant disease gene that occurred de novo is rewarded with the strong evidence code PS2. That’s a long way toward a pathogenic classification. However, applying PS2 requires that you test both parents *and* that the parental relationships, especially paternity, have been confirmed. Again, it’s great when the stars align and you can do this. It’s also one of the reasons most labs prefer having family trios (proband and both parents) whenever possible. Yet we live in the real world where:
- Children are sometimes adopted or in foster care
- Families cannot afford all available testing
- Parents may no longer be alive
- Parents may be incarcerated
- Parents may be unwilling to participate in genetic studies
In these situations, testing both parents is not an option and that usually prevents some of the strongest evidence from being applied.
Consequences of Null and De Novo Variant Bias
The biases that favor null variants and de novo mutations may have scientific underpinnings, but they also exert real-world consequences that often skew the perceptions of emerging disease genes. Let’s be honest: it is far easier to publish a cohort of patients who all have de novo loss-of-function mutations in the same gene. I have been a part of multiple GeneMatcher collaborations in which the study leaders either gave preference to patients with null / de novo variants or were forced to do so to get the work published.
This often means the first few papers linking a gene to a disease describe only de novo / null variants, and that becomes the expected etiology of disease. Even established disease genes can be affected by the null-variant bias: because missense variants are harder to classify as likely pathogenic, they often remain VUS. Anyone who glances at the landscape of disease-causing (P/LP) variants for a gene might (incorrectly) assume that only null variants cause disease. I strongly encourage researchers to push back when they are told that the first paper will only include the “easy button” LOF/de novo variants.
Effects of Changing Variant Interpretation Guidelines
The ACMG 2015 guidelines for interpretation of sequence variants were published 8 years ago this month. It was an important milestone in our field, the members of which increasingly recognized that many variants reported as disease-causing were (in retrospect) probably not. The methods for classifying variants were inconsistent, and there was no universal set of rules that someone could apply. The 2015 guidelines provided such a framework.
However, a lot can change in eight years, and although the ClinGen Sequence Variant Interpretation (SVI) working group has released subsequent recommendations on the use of computational evidence for missense variants and refining classification of splicing variants, these are interim guidance.
The long-awaited revised framework for variant interpretation, which implements a points system to improve accuracy/consistency, is not yet published. In theory, it will help us resolve some VUS. That remains to be seen. Just as some types of evidence can be assigned higher strength (e.g. computational predictions of variant impact), other types of evidence are be blunted (e.g. rareness in the population). We won’t know until the revised guidelines are published, which probably will not be in 2024.
What About Variants in Candidate Genes?
I should take this moment to remind you — as I sometimes have to remind myself — that ACMG variant interpretation should only be applied to sequence variants that affect established disease genes. It should not really be used for variants in unknown genes or candidate genes not yet associated with human disease. That’s because we can’t assess pathogenicity of a variant without a definitive link between the gene and disease.
For clarity, we try to avoid the use of VUS when discussing candidate genes. Occasionally I hear the term GUS — for Gene of Uncertain Significance — and I really like it, but it does not seem to have gained much momentum.
More VUS, More Problems
The increasing number of VUS on genetic testing reports — and our inability to definitively classify them — present significant challenges for clinicians, laboratories, and patient families.
- For the lab, a VUS is a non-diagnostic outcome. They can be reported, but generally in the dreaded “Section 2” of the test report.
- Patients with VUS thus may not qualify for gene therapy or clinical trials if those are available.
- Clinicians must decide whether or not to pursue further testing, either to clarify the VUS or to keep searching.
Which VUS Merit Further Scrutiny?
It’s important to emphasize here that not all VUS are created equal. Because of the conflicting-evidence-means-VUS rules described above, plenty of variants receive this classification but are extremely unlikely to be disease-causing. On the other hand, sometimes VUS offer a promising potential diagnosis in a patient who otherwise has no significant findings. Perhaps the most important question to be answered is the phenotypic overlap, i.e. whether the gene’s associated condition matches the patient clinical presentation. This is why good clinical phenotyping is critical for genetic testing, especially when interpreting uncertain results.
The number, strength, and types of ACMG evidence codes that accompany a VUS classification are also relevant considerations. Some of the proposed revisions of variant classification guidelines allow for tiering of VUS into subsets representing the amount of pathogenic evidence behind them. If these come to pass, they’ll offer a useful communication tool for laboratories to indicate. In the meantime, I tend to refer to them as weak or strong VUS, with the latter category possibly warranting follow-up. Examples of strong VUS include:
- A VUS that is compound-heterozygous with a pathogenic variant in a recessive disease gene.
- A VUS with multiple pathogenic criteria that segregates with disease in a gene that fits the phenotype. For example, VUS (PM2, PP3, PP5) would indicate a rare variant that’s predicted to be deleterious and has been reported as disease-causing by another laboratory.
- A VUS with a predicted effect that could be evaluated by additional testing, such as metabolic/biochemical testing or even RNA-seq for potential splice variants.
This leads to the last section of my post, the million-dollar question.
How Can We Resolve a VUS?
I get asked this question all the time. Honestly, if you’re reading this post and have some ideas, I’d love if you shared them in the comments section below. Note, resolution can go either way: building a case for pathogenicity for a suspicious VUS, or ruling out a VUS that might otherwise be a concern. Here are some strategies we and other groups have tried.
- Segregation testing. Determining the segregation pattern and disease status in family members informs, at the very least, the plausibility of a variant fit and there are ACMG evidence codes for both segregation (PP1) and non-segregation (BS4).
- Clinical evaluations. The clinician can review patient/family medical records, bring them in for another clinical visit, or refer them to a relevant specialty to determine the presence (or absence) of clinical features associated with the disorder.
- Checking the latest population allele frequency databases to determine the variant’s prevalence in presumed-healthy individuals.
- Reaching out to other laboratories who have reported the variant according to ClinVar or the literature can sometimes yield useful information.
- Identifying additional patients with the variant can provide or strengthen certain categories of pathogenicity evidence. This is something we use in my ClinGen Variant Curation Expert Panel to resolve VUS in the RPE65 gene.
- Additional patient testing, such as biochemical/metabolic testing, methylation profiling, etc. that would support or exclude the diagnosis
- Variant functional studies in cells, organoids, or animal models. Obviously we’d love this to clarify any variant, but it can be expensive and time-consuming.
Sometimes strategies like the ones above can push a variant to a more definitive classification, and sometimes not. The hard truth is that some VUS cannot be resolved at the present time. Formal classifications aside, the clinicians can make their own judgements about uncertain findings, and counsel and treat the patients accordingly.
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