Neurogenetics Curriculum
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NeuroGenetics Curriculum·advanced·30 min

Variant Interpretation & ACMG Classification

Reading genetic testing reports — the ACMG/AMP classification system worked through a gene panel and a WES trio.

Tags: Neurogenetics · Advanced

Learning Objectives

  1. 1.Explain the five-tier ACMG/AMP classification system and identify which tiers are clinically actionable vs. which are not
  2. 2.Describe the main types of evidence used in variant classification: population frequency, computational predictions, de novo status, and functional studies
  3. 3.Walk through a genetic testing report and identify the ACMG criteria applied to classify a variant
  4. 4.Explain how parental testing can change a VUS classification — particularly through confirming de novo status
  5. 5.Recognize key neurogenetics interpretation pitfalls: gain-of-function vs. loss-of-function genes, repeat expansion blind spots, and splice variant uncertainty
  6. 6.Communicate VUS results to families appropriately and plan follow-up including reanalysis timelines

01How Variants Get Classified

Every genetic test you order — whether it's an epilepsy panel, an exome, or a genome — will come back with variants classified into one of five tiers. The reason this system matters is not bureaucratic: the tier is a compressed statement of probability, and that probability is what determines whether you are allowed to act on the result clinically.

The ACMG/AMP 2015 guidelines (Richards et al. 2015) created a standardized five-tier system: Pathogenic (P), Likely Pathogenic (LP), Variant of Uncertain Significance (VUS), Likely Benign (LB), and Benign (B). The crucial conceptual move is to read these as points on a continuous probability spectrum rather than discrete categories. Richards 2015 set the convention that 'likely' means more than 90% certainty; the Bayesian model of Tavtigian 2018 places pathogenic at ≥99% posterior probability, and VUS is the wide middle band (roughly 10–90%) where the evidence genuinely does not resolve. A variant does not 'become' pathogenic at a magic moment — it accumulates evidence until the probability crosses a threshold we have agreed to call actionable.

Why draw the actionable line at LP rather than only at P? Because a 90% probability of pathogenicity is already high enough that withholding management would do more harm than the residual 10% uncertainty. So both P and LP are actionable — they can inform treatment, guide surveillance, and justify cascade testing of relatives. A VUS is NOT actionable. This is the single most misunderstood point in clinical genetics: a VUS does not mean 'mildly suspicious' or 'probably the answer.' It means the lab weighed everything available and the scale did not tip. Acting on a VUS imports an unresolved probability, anywhere from 10 to 90 percent, into a clinical decision while feeling like you have a molecular diagnosis — which is exactly the trap.

One important caveat that trips up trainees: for autosomal recessive conditions, a single heterozygous P/LP variant does not diagnose the disease — it identifies a carrier. The actionable content there is recurrence-risk counseling, not treatment. A diagnosis requires a second pathogenic variant on the other allele, confirmed in trans (parental or long-read phasing), because two pathogenic variants sitting on the same allele leave the patient with one fully functional copy and no disease.

Behind each tier is a structured evidence tally. The 2015 framework was originally a qualitative rulebook of combining criteria; Tavtigian et al. 2018 showed it behaves like a naive Bayesian classifier, and Tavtigian et al. 2020 re-expressed it as an exponentially scaled point system (benign totals: −1 to −6 likely benign, ≤ −7 benign) — Supporting/Moderate/Strong/Very Strong map to roughly ±1/±2/±4/±8 points. That insight is practically useful to you: it means evidence adds, so you can look at a VUS, see it sitting at 2 or 5 points, and ask concretely 'what single piece of evidence (usually parental testing) would push it over the line?' You don't need to memorize criterion codes to do that — you need to understand that classification is arithmetic on evidence, not a verdict handed down by the lab.

Five-Tier Classification

ClassProbability of PathogenicityClinical Action?
Pathogenic (P)≥99%Yes — actionable
Likely Pathogenic (LP)≥90% and <99%Yes — actionable
VUS10–90% (uncertain)No — do not use for clinical decisions
Likely Benign (LB)≥0.1% and <10%No action needed
Benign (B)<0.1%No action needed

The Point System (Tavtigian 2020)

Strength LevelPoints (Pathogenic)Points (Benign)
Very Strong+8−8
Strong+4−4
Moderate+2−2
Supporting+1−1

Score → Classification

Total ScoreClassification
≥10 pointsPathogenic
6–9 pointsLikely Pathogenic
0–5 pointsVUS
−1 to −6Likely Benign
≤−7Benign

Key Points

  • P and LP are both clinically actionable — they trigger follow-up, cascade testing, and treatment decisions; VUS is NOT actionable
  • VUS means 'we don't know' — not 'it's probably fine' and not 'it's probably bad'; it is genuinely uncertain
  • The Bayesian point system: Very Strong ±8, Strong ±4, Moderate ±2, Supporting ±1; thresholds: ≥10 = P, 6–9 = LP, 0–5 = VUS
  • BA1 (allele frequency >5%) is the only stand-alone criterion — it classifies as Benign by itself, no matter what other evidence exists
  • You don't need to memorize every criterion code — but understanding the point system helps you know when follow-up testing could change a VUS

02The Evidence Behind a Classification

Every criterion the lab applies is really an attempt to answer one of a few orthogonal questions about a variant. Once you see the underlying question, the criterion codes stop being a list to memorize and become a logic you can reconstruct — and, crucially, anticipate which missing evidence would move the classification.

Population Frequency — the asymmetry that surprises people

The first question is simply: how often does this variant appear in people who do not have the disease? gnomAD (v4: about 807,000 individuals, 730,947 exomes and 76,215 genomes) is the reference. The deep point here is an asymmetry. Common is powerful evidence against pathogenicity — a variant present at >5% in any population is benign on that fact alone (BA1), because a rare Mendelian disease cannot be caused by a variant with a 5% allele frequency, which about 1 in 10 people carry. BA1 assumes an adequately sized continental population, and ClinGen keeps a short list of exceptions, high-frequency variants that are nonetheless pathogenic for a recessive or low-penetrance condition (Ghosh et al. 2018). But the converse is weak: rare is only +1 (supporting), because the human genome is full of rare variants that do nothing. Absence from gnomAD is necessary for most Mendelian pathogenic variants but nowhere near sufficient — which is exactly why so many genuinely rare variants languish as VUS. The right intuition: high frequency closes a case; low frequency merely keeps it open.

Computational Predictions — why no single tool is allowed to win

In silico tools estimate damage from conservation, protein structure, and learned features: REVEL (ensemble, 0–1), CADD (Phred-scaled; a score of 20 marks the top 1% of all possible substitutions, which is not the same as 'deleterious'), SpliceAI (splicing; ClinGen applies PP3 at ≥0.2 and BP4 at ≤0.1 outside the ±1,2 positions, Walker et al. 2023). The 2015 framework capped these at supporting strength, and set conflicting predictions aside, because the tools of the time had limited accuracy and similar algorithms are not independent measurements of biology, so stacking three agreeing tools does not triple your confidence. ClinGen's calibration (Pejaver et al. 2022) put real numbers on this: REVEL ≥0.644 reaches PP3_Supporting and only at the much higher ≥0.932 does it earn Strong. That same paper supplied the benign side (BP4: REVEL ≤0.290 supporting, ≤0.183 moderate, ≤0.016 strong), so a low REVEL is genuine evidence against pathogenicity, not merely absence of evidence for it. It also recommends choosing a single calibrated tool before seeing any scores; picking whichever predictor agrees after the fact is the bias calibration was meant to remove. Note that CADD 20, the developers' traditional cut-off, falls in the benign range of the calibration; CADD needs ≥25.3 for PP3_Supporting.

Gene Constraint (pLI, LOEUF) vs. positional conservation — a distinction trainees blur

Constraint asks whether the human population tolerates losing a copy of this gene: compare observed LoF variants in gnomAD to the number expected by chance. pLI ≥0.9 flags a gene highly intolerant to heterozygous LoF; LOEUF <0.35 in gnomAD v2, or <0.6 in v4 (the newer, continuous metric), says the same. This is a gene-level, within-species selection signal, and it is conceptually different from cross-species conservation (PhyloP, GERP++), which asks whether one specific nucleotide has been frozen across vertebrates for millions of years. They answer different questions and can disagree: a constrained gene can contain individually unconserved positions, and a deeply conserved position can sit in a gene that otherwise tolerates LoF. The practical payoff: constraint tells you whether deleting the gene matters (relevant to PVS1 / truncating variants), while positional conservation tells you whether this particular residue matters (relevant to PP3 / missense variants). Reaching for the wrong metric is a common reasoning error.

Why constrained genes look 'empty' — a survivorship-bias trap. It is worth pausing on why a highly constrained gene carries so few variants in gnomAD, because the naive reading is exactly backwards. gnomAD is a catalog of people who are alive and largely healthy — so, like the WWII bombers that returned hit everywhere except the engine, it shows only the damage that was survivable. Loss-of-function variants are scarce in a constrained gene not because the gene rarely mutates, but because LoF hits there are strongly deleterious and are removed from the population every generation by negative selection. The 'missing' variation is absent from the living, reproducing sample, not from reality. Two consequences follow: (1) absence of LoF variation is a signal of importance, not of safety — it is exactly what makes high pLI / low LOEUF meaningful evidence for haploinsufficiency; and (2) because pathogenic LoF in these genes cannot persist in the population, it keeps re-arising as new mutations — which is precisely why de novo variants dominate severe, sporadic neurodevelopmental disease, and why trio testing (which flags a variant as new in the child) is so powerful.

De Novo Status — strong because it is improbable by chance

A variant present in the child and confirmed absent from both biological parents is among the strongest single lines of evidence: PS2, Strong (+4 points) by the generic 2015 default. The logic is purely probabilistic: each person carries only ~1–2 new coding variants, so the chance that the one spontaneous hit happens to land in the one gene that explains the child's phenotype is tiny — and it shrinks further in constrained genes. That is why confirmation matters so much: 'assumed' de novo without confirmed parental relationships is PM6 (Moderate, +2), because non-paternity, sample mix-ups, and low-level parental mosaicism are all real ways an untested 'de novo' can be wrong.

ClinGen's Sequence Variant Interpretation group refined this in its de novo recommendation (ClinGen SVI, PS2/PM6 v1.1): each proband earns points by how specific the phenotype is for the gene. A phenotype highly specific for the gene earns 2 points with confirmed parentage (1 if assumed); consistent but not highly specific, 1 (0.5); consistent but not specific with high genetic heterogeneity, 0.5 (0.25). The summed points set the strength: 0.5 supporting, 1 moderate, 2 strong, 4 very strong. The SVI's own epilepsy example scores one confirmed de novo in an early infantile epileptic encephalopathy at 1 point, PS2_Moderate (+2), because that phenotype fits many genes. A confirmed de novo is therefore worth +4 only when the phenotype is highly specific or several probands share the variant.

Functional Studies — only as good as their controls

A functional assay can be strong evidence, but the framework deliberately sets a high bar: the readout must measure a disease-relevant function and the assay must be calibrated against known pathogenic and benign controls so the lab can quantify how well 'abnormal in the dish' actually predicts 'pathogenic in the patient.' An elegant experiment with no benign comparators tells you the variant changes something, not that the change causes disease — so it may not qualify at full strength.

Segregation and Phasing

Does the variant travel with disease through the family? Each additional informative affected relative who carries the variant adds evidence, scaling with the number of meioses. Phase is not optional in recessive disease: confirming two variants sit on different alleles (in trans) is what distinguishes a true compound heterozygote from a carrier who happens to have two changes on one chromosome.

Null Variants and PVS1 — the strongest criterion, and the most context-dependent

PVS1 (up to +8, Very Strong) applies to 'null' variants predicted to abolish the gene product: nonsense, frameshift, canonical ±1,2 splice variants, start-loss, and whole/multi-exon deletions. Its strength is graded, not fixed: the ClinGen decision tree (Abou Tayoun et al. 2018) downgrades start-loss variants (moderate at most), truncations predicted to escape nonsense-mediated decay or to remove only a small part of the protein, and splice or exon events predicted to preserve the reading frame. Its force also rests on one premise: that loss of function is an established disease mechanism for the gene. That premise is not a property of the variant; it is a property of the gene, established from known pathogenic LoF variants and ClinGen curation of the disease mechanism. Constraint (pLI ≥0.9, LOEUF <0.35 in v2 or <0.6 in v4) supports it but does not establish it on its own. So PVS1 does not apply where disease arises only through gain of function: in KCNT1, for example, the epilepsies are caused by gain-of-function missense variants and loss of function is not an established mechanism, so a truncating KCNT1 variant does not explain the phenotype. Genes such as SCN8A and GRIN2A cause disease by either mechanism, with different phenotypes for each, so the variant type must match the patient's phenotype. The discipline is fixed: confirm the gene's established mechanism before you let PVS1 fire.

Key Points

  • Population frequency is the most powerful benign criterion — >5% in gnomAD = Benign, full stop; rarity alone is only +1 point (supporting)
  • Computational predictions count only at calibrated thresholds (Pejaver 2022: REVEL ≥0.644 supporting, ≥0.773 moderate, ≥0.932 strong); choose one tool before seeing scores
  • Gene constraint (pLI, LOEUF) measures intolerance to LoF within the human population — distinct from cross-species conservation (PhyloP, GERP++); high constraint supports PVS1 for truncating variants
  • De novo weight depends on the phenotype: PS2 is +4 by the generic default, but ClinGen SVI scales it, so one confirmed de novo in a heterogeneous phenotype such as an epileptic encephalopathy is PS2_Moderate (+2); assumed de novo is PM6
  • PVS1 (+8, Very Strong) applies to null variants (nonsense, frameshift, canonical splice ±1,2, gene deletion) in haploinsufficiency genes — does NOT apply to gain-of-function genes
  • For recessive conditions, two variants must be confirmed in trans (different alleles) — phase matters for correct interpretation

03Report Walkthrough: Epilepsy Gene Panel with a VUS

Now we apply the evidence logic to a concrete report — the kind that lands in your inbox on service. This is a representative teaching example built from real clinical patterns.

The patient: An 8-month-old boy with infantile epileptic spasms (West syndrome), developmental plateau, no family history of epilepsy, normal brain MRI, and hypsarrhythmia on EEG. The neurologist orders a comprehensive epilepsy panel (300+ genes) as a singleton — proband only, parents not included.

The report: one variant of interest — an SCN2A missense variant returned as VUS. The criteria walkthrough is below.

Trace the arithmetic, not just the verdict. The lab applied two pieces of positive evidence and nothing else fired: absent from gnomAD (PM2_Supporting, +1) and a computational prediction crossing the calibrated bar (REVEL 0.71 ≥ 0.644 → PP3_Supporting, +1). That is 2 points — solidly VUS, well short of the 6 needed for LP. Notice which criteria are blank and why: PS3 is empty because no one has run a function assay on this specific change, and PS2 is empty for a structural reason — a singleton panel physically cannot evaluate de novo status, because the parents were never sequenced.

That blank PS2 matters most. The variant is not stuck at VUS because the evidence argues against it; it is stuck because the highest-yield evidence was never collected. Order parental testing, and if the variant proves de novo, how much it adds depends on the weighting the laboratory uses. By the generic default PS2 adds +4, for a total of 6, which just reaches Likely Pathogenic. Under the ClinGen SVI de novo scaling, infantile spasms fit many genes, so one confirmed de novo earns PS2_Moderate (+2), for a total of 4, still VUS. Ask the laboratory which it applies. SCN2A also now has ClinGen Epilepsy Sodium Channel VCEP specifications (approved 2024), which take precedence over the generic rules, and a laboratory may weigh PP2 or PM1 for a missense variant in this gene. Parental samples are still the first request, because they supply the evidence the singleton design could not collect. Whenever you see a VUS on a singleton, the reflex should be: what would a trio tell me?

Clinical Genetic Testing Report
Example Genetics Laboratory (teaching example)
Test: Epilepsy Gene Panel (300+ genes)
Strategy: Singleton (proband only)
PATIENT
8-month-old male — infantile epileptic spasms, hypsarrhythmia, developmental plateau, normal MRI
GeneVariant (HGVS)ZygosityClassification
SCN2Ac.1264G>A (p.Gly422Arg)HeterozygousVUS

ACMG Criteria Walkthrough

CriterionEvidenceStrengthPoints
PM2_SupportingAbsent from gnomADSupporting+1
PP3_SupportingREVEL 0.71 (above ClinGen 0.644 supporting threshold, below 0.773 moderate threshold); CADD 28.5Supporting+1
PS2Not assessed — parents not tested (singleton panel)——
PS3No published functional studies for this specific variant——
Total Score2 pts → VUS
What would change this classification?
If parental testing confirms this variant is de novo (absent from both parents), that adds PS2. By the generic default PS2 is +4: 2 + 4 = 6 points → Likely Pathogenic. Under ClinGen SVI de novo scaling, infantile spasms are not specific to SCN2A, so one confirmed de novo is PS2_Moderate (+2): 2 + 2 = 4 points → still VUS. The SCN2A VCEP specifications (2024) should be applied where available.

Key Points

  • A singleton gene panel cannot assess de novo status — this is the most common reason a variant stays VUS when it might otherwise be LP
  • Parental testing is often the single highest-value follow-up step after a VUS result — a confirmed de novo adds +2 to +4 points depending on how specific the phenotype is for the gene, with just two blood draws
  • Per Pejaver et al. 2022 (ClinGen calibration), REVEL ≥0.644 = PP3_Supporting (+1 point), ≥0.773 = PP3_Moderate (+2 points), ≥0.932 = PP3_Strong (+4 points)
  • Absent from gnomAD = PM2_Supporting (+1 point only) — rarity alone is necessary but far from sufficient for pathogenicity
  • Always ask: 'What additional evidence could move this VUS?' In most cases, the answer is parental testing for de novo status

04Report Walkthrough: WES Trio with a VUS

The first walkthrough showed a VUS rescued toward LP by adding evidence. This one shows the more sobering case: a variant that has the strong evidence everyone wants — confirmed de novo — and still does not reach LP. It is the antidote to the reflex of treating 'de novo' as a synonym for 'diagnosis.'

The patient: A 3-year-old girl with global developmental delay, drug-resistant epilepsy (onset 4 months), no distinctive features, neurologically healthy parents, and mild cerebral atrophy on MRI. The team orders trio WES — the right call for a severe early-onset phenotype, precisely because it can detect de novo events a singleton would miss.

The report: a de novo variant in STXBP1 — a thoroughly established developmental and epileptic encephalopathy gene. And yet the lab calls it VUS. Resist the temptation to override the lab; instead, follow the math.

By the generic default the tally is PS2 (+4, confirmed de novo) plus PM2_Supporting (+1, absent from gnomAD) = 5 points; with the ClinGen SVI de novo scaling for a phenotype that fits many genes, PS2 is moderate (+2) and the total is 3. Six is the LP threshold, so it lands one point short. The natural question — why didn't the computational evidence close the gap? — is the instructive part. REVEL here is 0.48, below the 0.644 calibrated bar, so PP3 does not fire; the ensemble model is simply not convinced this particular amino-acid substitution is damaging. Note what is missing: a strong inheritance signal is being held at VUS by the absence of evidence about this particular amino-acid change. A laboratory may also weigh PP2 (a missense variant in a gene with few benign missense variants) or PM1 (a critical, well-studied domain); either would add the missing point.

The lesson is conceptual, not arithmetic. De novo is strong, not decisive. Every healthy person also carries ~1–2 de novo coding variants, most of them inert, so 'arose spontaneously' lowers but does not eliminate the prior that this is an innocent bystander. De novo + rarity buys you 5 points and an honest VUS; crossing into LP needs one more independent line — a controlled functional assay, a second unrelated patient with the same de novo change, hotspot or domain evidence (PM1), or a gene-specific VCEP rule that reweights the evidence. A different computational tool is not one of them: the predictor is chosen before the scores are seen. The discipline is to let the variant sit at VUS until that evidence actually exists, rather than promoting it because the gene name looks familiar.

Clinical Genetic Testing Report
Example Genetics Laboratory (teaching example)
Test: Whole Exome Sequencing
Strategy: Trio (proband + both parents)
PATIENT
3-year-old female — GDD, drug-resistant epilepsy (onset 4 mo), mild cerebral atrophy on MRI
GeneVariant (HGVS)ZygosityInheritanceClassification
STXBP1c.1631C>T (p.Pro544Leu)HeterozygousDe novoVUS

ACMG Criteria Walkthrough

CriterionEvidenceStrengthPoints
PS2Confirmed de novo (absent from both parents by trio WES)Strong+4
PM2_SupportingAbsent from gnomADSupporting+1
PP3REVEL 0.48 (below ClinGen 0.644 threshold) — does not meet PP3—0
PS3No published functional studies for this specific variant——
Total Score5 pts → VUS (1 point short of LP)
Key lesson: de novo alone is not enough
Even with confirmed de novo status (+4) and population rarity (+1), this variant scores only 5 points — one short of LP. The computational evidence didn’t cross the threshold. This variant could be upgraded over time if: (1) functional studies demonstrate disrupted STXBP1 function, (2) additional unrelated patients are found with the same de novo variant, or (3) gene-specific VCEP guidelines provide more nuanced criteria.

Key Points

  • Even confirmed de novo status (+4 by the generic default, often +2 under ClinGen SVI scaling) doesn't always push a variant to LP — you still need additional evidence to reach the 6-point threshold
  • Each person carries ~1–2 de novo coding variants, and most are harmless — de novo alone doesn't equal pathogenic
  • REVEL below 0.644 means computational evidence doesn't support pathogenicity at the ClinGen-calibrated threshold — this is a common reason de novo VUS variants stay as VUS
  • This variant sits at the VUS/LP border (5 points) — functional studies, additional affected individuals, or gene-specific VCEP guidelines could upgrade it over time
  • Trio WES is still the preferred strategy — it provided the de novo information that singleton testing would have missed entirely

05Pitfalls You Need to Know

The pitfalls below are not random trivia — each one is a place where the default ACMG reasoning quietly assumes something that is false in a corner of neurogenetics. Knowing where the standard logic breaks is what separates reading a report from being fooled by one.

Mechanism mismatch — the assumption hidden in PVS1

The entire null-variant rule assumes that losing the protein causes the disease. Where disease arises only from an abnormally active protein, that assumption fails: in KCNT1, the epilepsies are caused by gain-of-function missense variants, and loss of function is not an established mechanism, so a truncating KCNT1 variant does not explain the phenotype however damaging it looks. Genes such as SCN8A, KCNQ3 and GRIN2A cause disease through either mechanism, but with different phenotypes, so a truncating variant there is pathogenic for the loss-of-function phenotype and not for the gain-of-function one. Reflex: before you trust a truncating call, confirm that loss of function causes the phenotype in front of you.

Repeat expansions are invisible to standard short-read sequencing

Exome does NOT reliably detect trinucleotide and other tandem-repeat expansions. Many expanded alleles are longer than a short read and the repetitive sequence cannot be uniquely mapped, and exome capture misses repeats that sit in introns or untranslated regions (the FXN GAA repeat is intronic; the FMR1 CGG repeat is in the 5′ untranslated region). Short-read genome analysis with dedicated callers such as ExpansionHunter detects many expansions, but it does not replace a sizing assay. Friedreich ataxia, most spinocerebellar ataxias, myotonic dystrophy, Huntington disease, Fragile X, and C9orf72 ALS/FTD all live in this blind spot. The dangerous failure mode is a falsely reassuring negative: if the phenotype points to a repeat disorder, a normal exome has not excluded it — order the dedicated repeat-sizing assay (or long-read/optical methods).

Splice variants — certainty falls off just past the canonical sites

The ±1,2 intronic positions are the invariant splice dinucleotides; variants there usually disrupt splicing and may support PVS1, at a strength that depends on whether the predicted mis-splicing disrupts the reading frame (Abou Tayoun et al. 2018). The surrounding splice region, +3 to +6 on the donor side (+5 especially) and −3 on the acceptor side, matters often; beyond it the effect is less predictable (Walker et al. 2023). Deep intronic variants, far from the exon, can create new splice sites and are invisible to most exome designs. SpliceAI can flag likely disruption, but a prediction is not a measurement — RNA studies (RT-PCR from patient tissue, ideally the disease-relevant tissue) show whether the transcript is actually mis-spliced and are far stronger evidence. Beware tissue-specific splicing: a variant silent in blood can be pathogenic in brain.

Mosaicism can fool the variant caller and the pedigree

A post-zygotic variant present in only a fraction of cells carries a variant allele fraction below the ~50% expected for a heterozygote, so it can sink beneath standard bioinformatic filters and be missed entirely — relevant in focal cortical dysplasia and hemimegalencephaly, where the pathogenic variant may exist only in brain. The flip side fools inheritance: low-level gonadal mosaicism in a phenotypically normal parent makes a variant look de novo on a blood-based trio, yet the parent transmits it to more than one child. So when an 'apparently de novo' condition recurs in a sibling, do not conclude the first result was wrong — suspect parental gonadal mosaicism, and counsel recurrence risk accordingly.

Key Points

  • Truncating variants in gain-of-function genes may be benign — always verify whether the gene's disease mechanism is LoF or GoF before interpreting
  • Standard WES does NOT detect repeat expansion disorders (Friedreich, SCA types, DM1, Fragile X, Huntington, C9orf72) — these require dedicated testing
  • Splice variants beyond canonical ±1,2 positions need SpliceAI prediction and ideally RNA studies for definitive evidence
  • Low-level parental mosaicism can mimic de novo inheritance — consider this when recurrence occurs after an apparently de novo event
  • ClinGen VCEP gene-specific guidelines specify and modify the generic ACMG rules for specified genes (e.g., SCN1A, RASopathy genes) — always check for a published VCEP before finalizing interpretation

06What to Tell Families About VUS Results

A VUS generates anxiety precisely because it sounds like information when it is, by definition, the absence of a conclusion. The communication task is to convey genuine uncertainty without making the family feel either dismissed or doomed — and to avoid the two equal-and-opposite errors clinicians fall into.

The key message to families: 'We found a change in a gene that could be related to your child's condition, but right now the scientific evidence isn't strong enough to say for sure. We call this a variant of uncertain significance. It does not confirm a diagnosis, and it does not rule one out. We will keep watching it as new information comes in.' The framing that lands is uncertain, not bad and not fine — because both of the comforting-sounding shortcuts are clinically dangerous.

Why the two opposite errors both cause harm. Telling a family 'it's probably the cause' manufactures a diagnosis out of an unresolved probability: it can anchor the entire workup, stop the search for the real etiology, and invite management changes that a VUS does not justify. Telling a family 'it's nothing' is just as wrong, because a meaningful minority of VUS are later upgraded — and a family told to forget it may never return for the reanalysis that would have made the diagnosis. The honest middle is uncomfortable to deliver and is exactly the correct answer.

What to do next

  • Order parental testing — usually the single highest-yield move, because (as Walkthrough 1 showed) a confirmed de novo adds +2 to +4 points depending on how specific the phenotype is, enough to tip some VUS to LP, and because it can also do the opposite, demonstrating the variant is inherited from an unaffected parent and arguing against it.
  • Document the VUS with explicit uncertainty language so a future clinician skimming the chart does not silently convert 'VUS' into 'has a mutation in gene X.' This downstream misreading is a real and recurring source of harm.
  • Schedule reanalysis in 1–2 years. The stored data does not change; our interpretation of it does, as gnomAD/ClinVar grow and new gene–disease relationships are validated.
  • Refer to genetic counseling for the detailed family conversation and cascade planning.

What NOT to do: never start or change treatment on a VUS alone; never collapse the uncertainty in either direction for the sake of a tidier conversation.

Reanalysis and reclassification — why uncertainty is temporary. Interpretation is a moving target. Reanalyzing previously negative or VUS-only exomes yields new diagnoses in about 10% of cases (6–13% in a 2022 meta-analysis, Dai 2022), making it one of the highest-yield, lowest-cost interventions in clinical genetics. Among VUS that do get reclassified, the majority drift toward benign (the base rate of harmlessness reasserting itself), but a meaningful fraction are upgraded — which is why the door stays open in both directions, including re-counseling families if a prior LP/P call is ever downgraded. Finally, ClinGen Variant Curation Expert Panels (VCEPs) publish gene-specific rules that replace the generic ACMG criteria for that gene, recalibrating thresholds and defining which assays count; always check for a relevant VCEP before finalizing. See the Genetic Epilepsies and Pharmacogenetics modules for how a confirmed classification then drives real treatment decisions.

Key Points

  • Never use a VUS for clinical decisions — manage based on clinical findings alone; explain uncertainty honestly to families
  • Parental testing for de novo status is often the single most valuable follow-up step after a VUS result
  • Document VUS with explicit uncertainty language in the medical record to prevent downstream misinterpretation
  • Schedule reanalysis every 1–2 years — yields new diagnoses in about 10% (6–13%; Dai 2022) of previously unsolved cases as databases and knowledge grow
  • A minority of VUS are reclassified within a few years, most toward benign — but a meaningful fraction are upgraded, so keep the door open
  • When a VUS is reclassified to LP/P, the lab should notify the ordering clinician so management can be updated; re-counsel families when LP/P variants are downgraded

Quiz Questions

1. A 2-year-old with developmental delay has exome sequencing that identifies a variant classified as VUS (Variant of Uncertain Significance) in a gene associated with intellectual disability. The parents ask whether this confirms their child's diagnosis. Which response is most appropriate?

  1. A.Yes — a VUS in a gene that matches the phenotype is treated as likely pathogenic in practice once the laboratory confirms the variant by Sanger sequencing
  2. B.No — a VUS means the variant is likely benign, so the family should be reassured that it is not the cause
  3. C.No — a VUS means insufficient evidence exists to determine pathogenicity; it cannot confirm or exclude a diagnosis✓
  4. D.Yes — the variant was found in a child with the matching phenotype, which is sufficient to treat it as pathogenic

A VUS (Variant of Uncertain Significance) is the middle tier of the five-level ACMG/AMP classification system. It means the laboratory has reviewed all available evidence — population frequency, computational predictions, functional data, published literature — and the evidence is insufficient to classify the variant as either pathogenic or benign. Critically, a VUS is NOT 'probably fine' and NOT 'probably bad' — it is genuinely uncertain. A VUS must never be used to confirm a genetic diagnosis or to guide treatment decisions. The appropriate response is to explain the uncertainty honestly, manage the child based on clinical findings alone, and plan for re-analysis in 1–2 years as new evidence accumulates. Over time, most VUS that get reclassified move toward benign.

2. A missense variant in SCN1A is identified in a child with epilepsy. The variant is present at 8% allele frequency in the gnomAD population database. How does this information affect the variant's classification?

  1. A.The variant should be downgraded one tier, to Likely Benign, since population frequency counts as Strong (BS1) but not stand-alone evidence
  2. B.The variant is classified as Benign, because a variant present at >5% in the general population is far too common to cause a rare Mendelian disease✓
  3. C.The variant remains a VUS, because the gnomAD frequency must be confirmed in an ancestry-matched sub-population before it can be applied
  4. D.The variant is Likely Pathogenic, because SCN1A is a highly constrained gene (pLI = 1) and in-silico tools predict a damaging effect

Population allele frequency is one of the most powerful lines of evidence in variant interpretation. The ACMG/AMP framework includes BA1 — a stand-alone Benign criterion that applies when a variant's allele frequency exceeds 5% in any large population database (such as gnomAD). At 8% allele frequency, this variant is present in roughly 1 in 6 people — far too common to cause a rare Mendelian disorder like Dravet syndrome. BA1 is unique among all ACMG criteria because it classifies a variant as Benign by itself, regardless of any other evidence (BS1, Strong, applies to frequencies higher than expected for the disorder but below the 5% BA1 cutoff). Even if the variant is in a known disease gene, the population frequency overrides: the variant is simply too common in healthy individuals to be disease-causing.

3. A nonsense (stop-gain) variant is identified in a gene known to cause disease exclusively through gain-of-function missense mutations (not loss of function). The variant is predicted to trigger nonsense-mediated mRNA decay. Which interpretation is most accurate?

  1. A.The variant is Pathogenic — nonsense-mediated decay eliminates the transcript, and a 50% reduction in protein is sufficient to cause disease in most dominant genes
  2. B.A truncating variant in a gain-of-function gene may be benign, because disease requires an abnormally active protein✓
  3. C.The variant qualifies for PVS1 at Strong rather than Very Strong, because the truncation is predicted to undergo NMD and the gene has a GoF mechanism
  4. D.This variant should be classified as Likely Pathogenic because triggering nonsense-mediated decay is inherently harmful

This question tests a critical concept in neurogenetics: the distinction between loss-of-function (LoF) and gain-of-function (GoF) disease mechanisms. The strongest single pathogenicity criterion (PVS1) applies to truncating variants — but ONLY in genes where loss of function is the established disease mechanism. In GoF genes, the disease is caused by a protein that works abnormally (e.g., a constitutively active ion channel), not by absence of the protein. A truncating variant that destroys the protein does not explain a disease caused only by gain of function. This is particularly important in neurogenetics: in KCNT1 the epilepsies arise from gain-of-function missense variants, and genes such as SCN8A, KCNQ3 and GRIN2A cause different phenotypes through gain versus loss of function. Always verify whether a gene's disease mechanism is LoF or GoF before interpreting truncating variants.

4. Trio exome sequencing (child + both parents) identifies a missense variant in a neurodevelopmental gene that is present in the child but confirmed absent from both parents (de novo). Why is confirmed de novo status considered strong evidence for pathogenicity?

  1. A.A confirmed de novo variant meets criteria for Pathogenic on its own, because the ACMG rules treat PS2 as stand-alone evidence
  2. B.De novo status counts as Moderate (PM6) evidence, worth +2 points, unless the variant is also absent from gnomAD
  3. C.A confirmed de novo variant provides strong evidence because a new mutation coincidentally hitting the causative gene is very unlikely✓
  4. D.De novo status is most informative in autosomal recessive disease, where it establishes that the second allele arose independently

De novo variants — arising spontaneously in the child and absent from both parents — are among the most powerful evidence for pathogenicity. In the ACMG/AMP framework, a confirmed de novo variant (PS2) receives Strong evidence (+4 points on the Bayesian scale) by the generic default; PM6 (Moderate) applies when parental relationships are assumed rather than confirmed. ClinGen SVI further scales de novo strength by how specific the phenotype is for the gene, so in a phenotype shared by many genes one confirmed de novo may count as moderate. The reasoning: each person carries only ~1–2 de novo coding variants. The probability that a random new mutation would land in the exact gene causing the patient's phenotype is extremely small. This is especially true for 'constrained' genes (those intolerant to new mutations, measured by high pLI scores), where de novo variants are even less likely to occur by chance. In neurogenetics, de novo variants are the primary cause of many severe conditions including Dravet syndrome (SCN1A), KCNQ2 neonatal epilepsy, and many developmental and epileptic encephalopathies. Trio sequencing (proband + both parents) is essential to detect de novo events.

5. A child had exome sequencing 3 years ago that was reported as negative (no pathogenic or likely pathogenic variants found). The family returns asking if anything has changed. Which statement best reflects current practice?

  1. A.A negative exome result is definitive — if no pathogenic variant was found, the genetic workup is complete
  2. B.The original exome data should be reanalyzed — new evidence accumulates continuously and yields new diagnoses in 10–25% of cases✓
  3. C.Exome data older than 2 years is no longer analyzable under current pipelines, so the test should be repeated with genome sequencing
  4. D.Reanalysis is reserved for cases where a new clinical feature has emerged, since the original variant calls were already compared against ClinVar at the time

Variant interpretation is not static — it evolves as scientific knowledge grows. The raw sequencing data from a 3-year-old exome contains the same variants it always did, but our ability to interpret those variants improves continuously. New gene-disease associations are validated, population databases like gnomAD and ClinVar expand, new functional studies are published, and ClinGen expert panels issue new guidance. When existing exome data is reanalyzed with current knowledge, studies consistently show new diagnoses in about 10% (6–13%; Dai 2022) of previously unsolved cases, with some older cohorts showing even higher incremental yields. This makes reanalysis one of the highest-yield, lowest-cost interventions in clinical genetics. Current recommendations suggest reanalysis every 1–2 years, or when new clinical features emerge.

6. A variant has conflicting computational predictions — one tool predicts it is damaging while another predicts it is tolerated. How should this affect the variant's classification?

  1. A.Use the most concerning prediction to be safe — classify the computational evidence as supporting pathogenicity
  2. B.Conflicting predictions cancel out — the evidence is counted as neutral, contributing neither toward pathogenic nor benign✓
  3. C.Computational tools are definitive, so the variant classification must wait until all prediction algorithms agree
  4. D.Whichever tool was published most recently should take priority over older computational methods

Computational (in silico) predictions are used as supporting evidence in variant classification through the PP3 (supporting pathogenic) and BP4 (supporting benign) criteria. However, no single computational tool is diagnostic, and the ACMG/AMP framework requires multiple lines of computational evidence pointing in the same direction. When different tools give conflicting results — one predicting damage and another predicting tolerance — the evidence is treated as neutral. This means no computational evidence points are added in either direction, and the variant classification relies on other evidence types (population frequency, functional studies, segregation, de novo data, etc.). This is an important safeguard: computational tools have known limitations, and overreliance on any single prediction can lead to misclassification. Current ClinGen guidance (Pejaver 2022) largely avoids this situation: a laboratory chooses one calibrated tool before seeing any scores and applies its thresholds, rather than polling several predictors.

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