The need to assess the pathogeneticity of genetic variants

Genetic sequencing is increasing diagnosis of pre-existing conditions, identifying which diseases a patient is at risk of developing, and which treatments they will best respond to. As the cost of genetic sequencing falls its use in clinical, research and private testing will continue to increase. Whilst we know that variation is a natural feature of the human genome, we are currently unable to accurately predict the effect on health, and the penetrance of this effect, for the majority of reported variants.

The variable pathogenicity of putative Loss-of-Function (pLOF) mutations was the focus of a recent paper by Johnston et al., (2015): genetic sequencing identified 103 individuals (from 951) carrying a pLOF mutation in a gene previously associated with haploinsufficiency pathologies. Of the 79 patients available for in depth clinical follow-up screening 43% had an individual or family history attributable to the variation. This included two undiagnosed BHD patients who can now be monitored for the development of renal cancer. However, 54% of these patients were positive for a pLOF variant but had no clinical indicators. This included a family carrying a mutation in the X-linked DMD gene, the cause of Duchenne muscular dystrophy, but with no evidence of muscle weakness in either male carrier. It is unknown whether these pLOF mutations are non-pathogenic variants or have variable penetrance. Potentially such patients could help identification modifier genes and increase understanding of disease pathology.

Determining whether a variant is non-pathogenic or non-penetrative is important both when a mutation is being sought and for incidental findings resulting from a more general genetic analysis. Patients should be warned in advance that mutations in disease-risk genes could be identified as a result of testing. The ACMG provides recommendations on reporting incidental findings (Green et al., 2013) but the variable penetrance of even well-known cancer-risk genes such as BRCA1 (Petrucelli et al., 2013) can make calculating risk complicated.

This difficulty in assessing the risk factors associated with genetic variants was highlighted in a recent review by ClinGen which reported variation in the interpretation of 17% of variants identified in more than one genetic lab (Rehm et al., 2015). These interpretations, stating either that a variation is non-pathogenic or highly pathogenic, could influence and potentially compromise patient care. Therefore it is essential that more accurate assessments of risk can be conducted.

The NCBI hosts a genetic variation database, ClinVar, which encourages private, clinical and research labs to submit genetic testing data which is then accessible to the wider research community (coded for anonymity). Currently over 300 different labs worldwide contribute data and over 172,000 variants in 23,000 genes have been reported. ClinGen are using this database to assess the clinical relevance of genomic variants – a large project as 71% of known variants are of “uncertain clinical significance” and even the majority of the 29% “likely or known to be pathogenic” have only been reported once (Rehm et al., 2015). The submission of further genetic data, both to general and disease-specific databases such as the LOVD-hosted FLCN mutation database, will enable researchers to make more robust assessments of individual variant pathogenicity.

Large scale sequencing projects such as the WGS500 and 100,000 Genomes Project can discover more about rare disease and cancer patients’ genomes, and potentially increase understanding of pathology (Taylor et al., 2015). However, to be able to accurately assess the risk factor of disease variants similar large sequencing projects in reportedly healthy individuals are required to identify variants that are common in the population and therefore most likely non-pathogenic. For now, even if variant risk cannot be accurately calculated, genetic sequencing enables identification of suspected pathogenic variants, which provides the basis for further clinical evaluation and care of patients and their families.


  • Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, McGuire AL, Nussbaum RL, O’Daniel JM, Ormond KE, Rehm HL, Watson MS, Williams MS, Biesecker LG (2013). American College of Medical Genetics and Genomics. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. Jul;15(7):565-74. PubMed PMID: 23788249.
  • Johnston JJ, Lewis KL, Ng D, Singh LN, Wynter J, Brewer C, Brooks BP, Brownell I, Candotti F, Gonsalves SG, Hart SP, Kong HH, Rother KI, Sokolic R, Solomon BD, Zein WM, Cooper DN, Stenson PD, Mullikin JC, & Biesecker LG (2015). Individualized Iterative Phenotyping for Genome-wide Analysis of Loss-of-Function Mutations. American journal of human genetics, 96 (6), 913-25 PMID: 26046366.
  • Petrucelli N, Daly MB, Feldman GL. BRCA1 and BRCA2 Hereditary Breast and Ovarian Cancer (2013). GeneReviews. Sept 26. NCBI Bookshelf: NBK1247.
  • Rehm HL, Berg JS, Brooks LD, Bustamante CD, Evans JP, Landrum MJ, Ledbetter DH, Maglott DR, Martin CL, Nussbaum RL, Plon SE, Ramos EM, Sherry ST, Watson MS, & ClinGen (2015). ClinGen–the Clinical Genome Resource. The New England journal of medicine, 372 (23), 2235-42 PMID: 26014595.
  • Taylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C, Aricescu AR, Attar M, Babbs C, Becq J, Beeson D, Bento C, Bignell P, Blair E, Buckle VJ, Bull K, Cais O, Cario H, Chapel H, Copley RR, Cornall R, Craft J, Dahan K, Davenport EE, Dendrou C, Devuyst O, Fenwick AL, Flint J, Fugger L, Gilbert RD, Goriely A, Green A, Greger IH, Grocock R, Gruszczyk AV, Hastings R, Hatton E, Higgs D, Hill A, Holmes C, Howard M, Hughes L, Humburg P, Johnson D, Karpe F, Kingsbury Z, Kini U, Knight JC, Krohn J, Lamble S, Langman C, Lonie L, Luck J, McCarthy D, McGowan SJ, McMullin MF, Miller KA, Murray L, Németh AH, Nesbit MA, Nutt D, Ormondroyd E, Oturai AB, Pagnamenta A, Patel SY, Percy M, Petousi N, Piazza P, Piret SE, Polanco-Echeverry G, Popitsch N, Powrie F, Pugh C, Quek L, Robbins PA, Robson K, Russo A, Sahgal N, van Schouwenburg PA, Schuh A, Silverman E, Simmons A, Sørensen PS, Sweeney E, Taylor J, Thakker RV, Tomlinson I, Trebes A, Twigg SR, Uhlig HH, Vyas P, Vyse T, Wall SA, Watkins H, Whyte MP, Witty L, Wright B, Yau C, Buck D, Humphray S, Ratcliffe PJ, Bell JI, Wilkie AO, Bentley D, Donnelly P, McVean G (2015). Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet. May 18. [Epub ahead of print] PubMed PMID: 25985138.

Leave a Reply