Insights

Blog: Shedding light on genes of uncertain significance

Julie Hathaway · 27.11.2018 · Miika Fadjukov

Recently, I wrote about genes of uncertain significance and how increasing a panel’s size can sometimes be counter-productive when trying to improve the clinical utility of genetic testing. Fortunately, there is a growing, collective effort underway to shed light on genes of uncertain significance by systematically evaluating the evidence behind reported gene-disease associations.

The following are some resources that outline some of the work that is being done in this area:

1) The NIH-funded Clinical Genome Resource has developed a  standard, evidence-based assessment to define clinically relevant genes and variants (Strande NT et al. 2017). The BabySeq project evaluated over 1,500 genes using this ClinGen validity classification framework to create a curated list of genes that would meet criteria for return of results from genomic sequencing for newborns (Ceyhan-Birsoy et al. 2017).

2) Development Disorder Genotype – Phenotype Database (DDG2P) is an effort to create a list of genes reported to be associated with developmental disorders, compiled by clinicians to facilitate feedback of likely causal variants. This database categorizes genes based on the certainty that they would cause disease, the consequence of the variants identified in the gene and the allelic status associated with disease.

In my recent post, I mentioned that genes of uncertain significance continue to be included on cardiovascular genetics testing panels despite the lack of evidence supporting their gene-disease association. Here are a few studies and examples that have been raising some much-needed discussion around these genes:

  • Though not yet curated by ClinGen, a recent review of Long QT syndrome associated genes suggests SNTA1, AKAP9, ANK2, SCN4B will receive a limited evidence classification based on the available data. KCNE2 and KCNJ5 may be classified as disputed (See Giudicessi et al., 2018).
  • In a meta-analysis of 7,855 cardiomyopathy cases, and over 60,000 reference patients, rare ANKRD1 variants were not found to be enriched in DCM or HCM patients (Walsh et al., 2017). TNNC1, MYOZ2, and ACTN2 are other genes where no significant excess of rare variants were seen in cases versus controls in this study.
  • Twenty-one genes with a published association to Brugada syndrome were curated using the above mentioned ClinGen framework; only one gene (SCN5A) was determined to have definite disease causality while the evidence behind all others was disputed. The authors suggest that only SCN5A should be routinely evaluated as part of the clinical care of patients with Brugada syndrome (Hosseini et al., 2018).

Our principles in gene curation

Blueprint Genetics’ cardiology panels are routinely updated to ensure that they remain clinically relevant. Genes such as SNTA1, MYOZ2, SCN4B and ANKRD1 have been long removed from our testing offering, as have some others with limited or disputed evidence.

Our Brugada syndrome panel is currently under review; though several genes, such as ABCC9, CACNA2D1, GPD1L, KCND3, KCNE3, KCNJ8, PKP2, RANGRF, SCN10A, SLMAP,  for which the gene-disease association has been reported as limited or disputed (Hosseini et al., 2018) do not appear on our panel, despite these being routinely analyzed elsewhere.

Interestingly, recent evidence suggests that non-coding deep intronic variants in core cardiovascular genes may in fact be the explanation for disease in some families. For example,  whole genome sequencing identified non-coding deep intronic variants in the MYBPC3 gene in 8% of the studied HCM families (Bagnall et al., 2018). We include known disease causing deep intronic variants on all our cardiomyopathy and arrhythmia panels with new variants being added as evidence arises. For example, the Comprehensive Cardiology panel includes over 125 likely disease-causing deep intronic variants.

Even though rapid advances in technology will continue to broaden available testing options, careful, ongoing evaluation of the clinical relevance is necessary to ensure the delivery of accurate and meaningful results for patients and families.

 

Julie Hathaway
Clinical Liaison

Julie Hathaway is a Clinical Liaison at Blueprint Genetics. She has over six years’ experience working in cardiac genetics; her past roles include both program coordinator and genetic counselor in a provincial multidisciplinary inherited arrhythmia program. Julie is an American and Canadian Board Certified Genetic counselor.

 

References:  
  1. Strande NT et al. 2017. Evaluating the Clinical Validity of the Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource.
  2. Ceyhan-Birsoy et al. 2017. A curated gene list for reporting results of newborn genomic sequencing.
  3. Giudicessi et al., 2018. The genetic architecture of long QT syndrome: A critical reappraisal.
  4. Walsh et al., 2017. Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples.
  5. Hosseini et al. 2018. Reappraisal of Reported Genes for Sudden Arrhythmic Death.
  6. Bagnall et al., 2018. Whole Genome Sequencing Improves Outcomes of Genetic Testing in Patients With Hypertrophic Cardiomyopathy.

 

Last modified: 12.11.2018