What are the steps involved in exome (genetic testing of all protein-coding regions) treatments?

Exome Sequencing: Clinical Implementation and Workflow

What is Exome Sequencing?

Whole exome sequencing (WES) is a next-generation sequencing method that captures and analyzes all protein-coding regions (exons) of the genome, representing approximately 1-2% of the total genome but containing ~85% of disease-causing mutations. 1, 2 This targeted approach sequences roughly 20,000 genes to identify genetic variants underlying disease phenotypes. 3

Clinical Indications for Ordering WES

When to Order WES

• Suspected genetic disorders where multiple genes could explain the clinical syndrome - WES is more cost-effective than sequential single-gene testing when genetic heterogeneity exists 1, 4, 5
• Patients with complex or atypical phenotypes where single-gene testing has been unrevealing 6
• Mendelian disorders (autosomal dominant, autosomal recessive, X-linked) with unclear genetic etiology 3, 2
• Pediatric patients with neurologic phenotypes - approximately 80% of initial clinical WES cases involved children with neurologic presentations 6
• When clinical phenotype alone cannot identify the specific genetic defect 4, 5

Specific Disease Examples Where WES is Effective

• Limb-girdle muscular dystrophies (sarcoglycanopathy, calpainopathy) 1
• Congenital myasthenia syndromes 5
• Glycogen storage diseases when standard sequencing identifies only one mutation 4
• Cardiomyopathies and channelopathies (though targeted panels may suffice for some) 3
• Inflammatory bowel disease with atypical presentations 3

Pre-Test Considerations

Laboratory Requirements

WES must be performed in a CLIA/CAP-certified laboratory with review by qualified clinical molecular geneticists to ensure accurate interpretation. 1, 5 This certification ensures quality standards for clinical diagnostic testing.

Sample Selection Strategy

• Trio sequencing (proband + both parents) significantly enhances diagnostic yield by enabling phase determination and identification of de novo variants 3
• Confirm maternity and paternity when evaluating de novo variants - egg donation, surrogate motherhood, and embryo transfer errors can contribute to non-maternity 3
• Consider sequencing additional affected family members to assess co-segregation with disease 3

Cost and Insurance Coverage

• Current costs range from $7,000 to $12,000 for clinical WES 3
• Insurance coverage is similar to that for established genetic tests, with approximately 25% diagnostic yield justifying reimbursement 6
• Gene panel testing costs $500-$3,000 and may be appropriate first-line for phenotypes with limited genetic heterogeneity 3

Technical Aspects of WES

Sequencing Methodology

• WES uses DNA enrichment methods (sequence capture) to isolate protein-coding regions, followed by massively parallel next-generation sequencing 3, 7
• The depth of sequencing (number of times each nucleotide is read) and coverage of genes of interest significantly influence diagnostic yield 3, 1
• Higher depth and better coverage provide more reliable findings - inadequate depth can miss true variants 3, 1

What WES Can Detect

• Single-nucleotide variants (SNVs) 1, 5
• Small insertions and deletions (indels) 1, 5
• Copy number variants in some cases 1
• Large multiexon deletions/duplications (with appropriate analysis) 4
• Stop codons and frameshift mutations 3

Technical Limitations

WES routinely misses chromosomal abnormalities - if clinical features suggest chromosomal involvement, array comparative genomic hybridization should be performed first 5

Complex structural variants and mutations in non-coding regions are not detected by WES and may require whole genome sequencing 1

Population data for indels may be poorly called by next-generation sequencing 3

Variant Analysis and Interpretation Pipeline

Step 1: Variant Calling and Quality Control

• Robust bioinformatics pipelines are essential for accurate variant calling 3, 1
• Different laboratories may use different analysis methods that could result in discordant results for the same patient 3, 1
• Use multiple variant calling tools and rigorous filtering to remove false positives 1, 5

Step 2: Variant Annotation

Annotate all detected variants using:

• Population allele frequency from databases (ExAC, gnomAD, 1000 Genomes Project) - variants present at high frequency in control populations are unlikely to be pathogenic 3
• Location in genome (exonic, intronic, splice site, UTR) 3
• Predicted functional impact using computational tools 3
• Gene constraint metrics (intolerance to loss-of-function variants) 3

Step 3: Variant Filtering and Prioritization

Apply systematic filtering based on:

• Inheritance pattern - filter for homozygous/compound heterozygous variants in recessive disorders, heterozygous in dominant disorders 3
• Allele frequency thresholds - for recessive disorders, variants should be absent or extremely rare in population databases 3
• Functional consequence - prioritize loss-of-function variants (nonsense, frameshift, splice site) and missense variants in critical domains 3
• Gene-disease associations - prioritize variants in genes definitively known to cause the patient's phenotype 3

Step 4: Variant Classification Using ACMG/AMP Guidelines

The American College of Medical Genetics and Genomics (ACMG) provides standardized criteria for classifying variants as:

• Pathogenic - sufficient evidence of disease causation 3
• Likely pathogenic - strong but not conclusive evidence 3
• Variant of uncertain significance (VUS) - insufficient evidence to classify 3, 1
• Likely benign - evidence against pathogenicity 3
• Benign - established as non-pathogenic 3

Strong evidence of pathogenicity includes:

• Same amino acid change as previously established pathogenic variant 3
• De novo occurrence with confirmed maternity and paternity in affected patient without family history 3
• Well-established functional studies supporting damaging effect 3
• Significantly increased prevalence in affected individuals versus controls (OR >5.0) 3

Step 5: Utilize Population Databases

Critical databases for variant interpretation:

• ExAC (60,706 exomes) - provides deep catalogue of protein-coding variation for clinical interpretation 3
• gnomAD (123,136 exomes + 15,496 genomes) - successor to ExAC with expanded data 3
• 1000 Genomes Project (2,504 individuals) - genome-wide variant frequencies across 26 populations 3
• ClinVar - open archive of variants with clinical phenotypes and interpreted significance 3

Common pitfall: A variant may have low overall allele frequency but substantially higher frequency in specific subpopulations, making it less likely to be pathogenic 3

Step 6: Assess Gene-Phenotype Relationships

• Review whether loss-of-function is a known disease mechanism for the candidate gene 3
• Evaluate whether missense variants are a common mechanism of disease in the gene 3
• Assess whether patient's phenotype matches established phenotypes for the candidate gene 3
• Use caution with variants at extreme 3' end of genes or those predicted to cause exon skipping while leaving remainder of protein intact 3

Validation and Confirmation

Confirmation of relevant genetic variants identified by WES should be performed using Sanger sequencing to validate findings before clinical decisions are made. 1, 4 This orthogonal method confirms that variants are real and not sequencing artifacts.

Diagnostic Yield and Expected Outcomes

• Clinical WES achieves approximately 25% molecular diagnostic rate in consecutive patients referred for suspected genetic conditions 6
• Among diagnosed patients, 83% of autosomal dominant mutations and 40% of X-linked mutations occur de novo 6
• Standard sequence analysis may miss ~6% of mutations even in confirmed cases, highlighting WES value for comprehensive detection 4

Managing Challenging Results

Variants of Uncertain Significance (VUS)

WES may identify variants for which clinical significance has not been established, creating interpretation challenges. 1, 4 When VUS are identified:

• Segregation analysis in additional family members can provide evidence for or against pathogenicity 3
• Functional studies may help establish variant impact 3
• Periodic re-analysis as databases expand may reclassify VUS 3

Incidental Findings

WES may identify pathogenic variants in genes unrelated to the indication for testing. 3 The ACMG recommends analysis of 56 genes associated with actionable conditions, though this represents purposeful additional analysis beyond the clinical question 3

Multiple Diagnoses

Approximately 4 out of 250 patients (1.6%) may receive two nonoverlapping molecular diagnoses, potentially challenging the clinical diagnosis made on history and physical examination 6

Integration with Clinical Practice

For optimal diagnostic yield, WES should be combined with proper clinical phenotyping and family history to guide interpretation of genetic findings. 1, 4 The technology is most powerful when clinical context informs variant prioritization and when genetic findings inform clinical management.

When analyzing WES data, expert review requiring >20 minutes per variant is often necessary - in one study, review of 239 "disease-causing" variants required >92 hours of expert time, ultimately confirming only 9 as truly pathogenic 3