Canadian Journal of Cardiology 30 (2014) 152e154


Sequencing: The Next GenerationdWhat Is the Role of Whole-Exome Sequencing in the Diagnosis of Familial Cardiovascular Diseases? Sali M.K. Farhan, BSc, and Robert A. Hegele, MD, FRCPC Departments of Biochemistry and Medicine, Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada

See article by Greenway et al., pages 181-187 of this issue. Since 2010, we have been living in the era of massively parallel genome sequencing, which generates genetic information from a single individual on a heretofore unimaginable scale. The effect of this technological advance on cardiovascular disease (CVD) is already being felt in the research laboratory, and might be on the cusp of translation into the clinic. In the best case scenario, understanding the genetic architecture underlying CVD might help predict clinical outcomes presymptomatically, and perhaps guide and tailor specific treatments that target pathways, which have become disrupted as the result of variation or mutation in the genome. The decreasing cost of next-generation sequencing (NGS) technologies has allowed human genome sequencing to proceed at unprecedented rates and volumes. The current cost of sequencing a human genome is approximately $7500 and the technical work can be completed within a week. This very cost-effective approach can justify certain research and clinical applications, especially when compared with previous requirements of resources and time to accomplish the same task: $2.7 billion and 13 years of effort resulted in completion of the first human genomic map in 2001, and by 2008 these metrics were down to $1.5 million and 5 months of effort.1-3 However, the overwhelming amount of data gathered from sequencing a complete human genome and the computational power needed to analyze and decipher all genetic variations remain daunting tasks for any biomedical researcher, not to mention a clinician who might entertain the thought of using such data as part of patient care.4 As a compromise, whole-exome sequencing (WES), which reports on only protein-coding regions (< 5% of the genome), is currently the preferred alternative.5 Since its emergence, WES has been successfully applied in the discovery of the

Received for publication December 23, 2013. Accepted December 23, 2013. Corresponding author: Dr Robert A. Hegele, Blackburn Cardiovascular Genetics Laboratory, 4288A-1151 Richmond St North, Robarts Research Institute, Western University, London, Ontario N6A 5B7, Canada. Tel.: þ1519-931-5271; fax: þ1-519-931-5218. E-mail: [email protected] See page 154 for disclosure information.

genetic basis for > 200 disorders, with new ones being reported almost daily.6 Naturally, a single human genome contains numerous rare and common genetic variants and as such, filtering or prioritization criteria are needed to distinguish a potentially causative mutation from merely common benign genetic variations. Being able to ascribe causality to a particular DNA variant with a high degree of likelihood is essential for clinical application of WES results. To date, WES has had its greatest effect in identification of genes and mutations that cause monogenic human diseases, which, although individually rare in the population, cumulatively number > 7000 different conditions and might explain approximately 10% of patient presentations to the health care system.5 Monogenic disorders follow simple Mendelian inheritance patterns, initially determined from a patient’s family history. The causative mutations in monogenic diseases, including CVDs, have a very low carrier frequency in the general population (< 1%) and also have a large phenotypic effect; by definition they are necessary and sufficient on their own to cause disease expression. In contrast, more common or complex forms of CVD tend to result from the integrated effects of multiple common genetic variants, known as single nucleotide polymorphisms, which are observed in > 5% of the population. Furthermore, although common single nucleotide polymorphisms have strong statistical association with the disease phenotype, individually they are neither sufficient nor necessary to cause expression of the disease.7 Instead, they create a fertile background of susceptibility, which, when coupled with environmental factors can eventually lead to clinical expression of common complex CVD.8 WES has not so far been shown to delineate causative genes in common complex diseases, because many individual genetic variants have only small effects, compared with a very high and clean signal-to-noise ratio for a single rare causative mutation in a monogenic disease. Thus, when contemplating the use of WES in a research context to characterize the role of genomic variations in CVD, it is essential to be certain that the disease has a strong monogenic basis. This would include documenting vertical transmission or inheritance of the disease across generations,

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Farhan and Hegele Sequencing: The Next Generation

and demonstrating its mode of inheritance, such as autosomal dominant or recessive. When this is established, DNA from key family members can be fed into WES machines, such as the Illumina MiSeq (recently approved by the US Food and Drug Administration for potential clinical applications).9 The torrent of sequence data is next filtered through a rare variant analysis, which prioritizes potentially disease-causing variants from among thousands that are typically discovered using WES. The following criteria cumulatively increase the likelihood that a mutation found in a patient is disease-causing: (1) the mutation cosegregates with disease status in the family, and especially across generations; (2) the mutation is absent (or virtually absent) from the genomes of a large pool of healthy individuals, ideally from the same ethnic background as the proband; (3) multiple bioinformatic tools (“in silico” analysis) consistently and independently predict that the mutation would result in dysfunction of the protein encoded by the gene; and (4) in vitro and in vivo bench studies clearly demonstrate that the mutant gene product is dysfunctional under controlled experimental conditions.5 In this issue of the Canadian Journal of Cardiology, Greenway and colleagues used WES to study patients very likely to have a single-gene form of atrial septal defect (ASD; Mendelian Inheritance in Man database #612794). In subset of these patients, they identified a novel genetic variant in a well-known CVD gene called ACTC1, encoding the alpha-actin chain in cardiac muscle.10 The authors first identified numerous coding variants in a wide range of genes in the genomes of individuals from certain families with ASD. After applying a series of strict filtering criteria, the authors eventually showed the p.M178L mutation in the ACTC1 gene was the only variant that consistently cosegregated with disease status in an autosomal-dominant disease inheritance model. Furthermore, the mutation was present only in affected family members and was absent from the genomes of unaffected family members. After screening a cohort of 1834 healthy control subjects, they found no additional p.M178L carriers; this importantly demonstrated the rarity of the ACTC1 p.M178L mutation and its strong and nonrandom relationship with ASD. They also applied multiple in silico analyses to gather a consistent biological prediction of the probable dysfunctional effect of the variant. Short of directly testing the mutation on the laboratory bench and in animal model systems, the authors’ package of evidence is reasonably convincing that the ACTC1 p.M178L mutation is necessary and sufficient for ASD to be expressed clinically in these patients. The authors concede the challenges and limitations of these biological prediction programs, which sometimes produce conflicting prediction outputs. Typically, these computer programs have a built-in algorithm that will predict a ‘damaging’ outcome when there is a nonsynonymous mutation that results in a significant change in the chemical structure and property of an amino acid that normally shows strong conservation throughout evolution. But because of inconsistencies of results generated by different in silico prediction programs, analyses should always be interpreted with caution. Perhaps the most compelling evidence for causation derives from a previous report, which is discussed by Greenway et al. in detail. In this 2008 study, Matsson et al. identified a novel genetic variant in ACTC1, p.M123V, as causing ASD in 2 large Swedish families.11 Importantly, those authors validated causation in specific functional studies including in vitro and


in vivo DNA mutagenesis in chick embryos, which seemed to recapitulate aspects of the human disease. In contrast, there is no such direct evidence for the ACTC1 p.M178L found by Greenway et al., because it was not functionally tested. By convention, complete certainty for a causal role would require direct functional analyses of p.M178L. Examples of such functional validation studies include: (1) Western analysis using patients’ cells to measure ACTC1 protein expression; (2) coimmunoprecipitation assays of ACTC1 with 1 of its binding partners, to determine whether protein-protein interaction is compromised in these patients; and finally, (3) in vitro and in vivo ACTC1 knockdown experiments. The discoveries made by Greenway et al. and many others using NGS, have nonetheless been remarkable and collectively, have increased our understanding of the genome and disease. Identifying new or known variants in genes that are already known to cause a monogenic disease is frequently observed in WES experimentsdcomprising approximately one-third of such reports.6 There is even evidence that WES can be used to diagnose a high proportion of monogenic disease cases evaluated in a clinical setting.9 While WES is proving its value for researchers who are hunting for disease genes, what are the implications of this technology for the practicing cardiologist? So far, whole-genome sequencing and WES have been attractive genomic tools for studying diseases considering their speed, accuracy, and affordability. However, most WES studies have been successful so far for monogenic disorders, which represent only a small fraction of known CVDs. For instance, most adults with coronary artery disease or arrhythmias do not have a single-gene problem that fully explains their presentation to the cardiology clinic. Although family history is important in these common garden-variety presentations, we now understand that for the overwhelming majority of patients, many genes of small effect create a background of susceptibility, which then requires exposure to additional nongenetic or lifestyle factors for the disease to manifest. Even though NGS can produce a tidal wave of DNA information, most of it is incidental and has no relevance to a particular patient’s situation. The low genetic signal-to-noise ratio in common garden-variety CVD presentations makes it unlikely that cardiologists would ever find clinical utility of these methods outside of rare patients who a priori likely carry monogenic familial forms of these conditions. Furthermore, only a few high-throughput genomic centres in Canada are currently equipped to meet WES demands, with resulting long turnaround times. Finally, a certain level of expertise and experience is needed to analyze the computational genomic data and to tie them to a clinical diagnosis. Some variations of NGS technology interrogate panels of a limited number of established or known genes of interest, rather than all human genes as evaluated using WES; these more restricted approaches might prove to be more useful for clinical applications. In summary, the work by Greenway et al.10 shows that although WES has hit its stride with respect to utility in CVD research, these methods are still not ready-for-prime-time use in most clinical scenarios. Funding Sources R.A.H. is supported by the Jacob J. Wolfe Distinguished Medical Research Chair at Western University, the Edith


Schulich Vinet Canada Research Chair in Human Genetics (Tier I), the Martha G. Blackburn Chair in Cardiovascular Research, and operating grants from the CIHR (MOP-13430, MOP-79523), and the Heart and Stroke Foundation of Ontario (NA-6059, T-6018). Disclosures The authors have no conflicts of interest to disclose. References 1. Bick D, Dimmock D. Whole exome and whole genome sequencing. Curr Opin Pediatr 2011;23:594-600. 2. Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature 2001;409:860-921. 3. Ng SB, Nickerson DA, Bamshad MJ, et al. Massively parallel sequencing and rare disease. Hum Mol Genet 2010;19:R119-24. 4. El-Metwally S, Hamza T, Zakaria M, et al. Next-generation sequence assembly: four stages of data processing and computational challenges. PLoS Comput Biol 2013;9:e1003345.

Canadian Journal of Cardiology Volume 30 2014 5. Farhan SM, Hegele RA. Genetics 101 for cardiologists: rare genetic variants and monogenic cardiovascular disease. Can J Cardiol 2013;29: 18-22. 6. Boycott KM, Vanstone MR, Bulman DE, et al. Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nat Rev Genet 2013;14:681-91. 7. Dube JB, Hegele RA. Genetics 100 for cardiologists: basics of genomewide association studies. Can J Cardiol 2013;29:10-7. 8. Nolan D, Kraus WE, Hauser E, et al. Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. PLoS One 2013;8:e71779. 9. Collins FS, Hamburg MA. First FDA authorization for next-generation sequencer. N Engl J Med 2013;369:2369-71. 10. Greenway SC, McLeod R, Hume S, et al. Exome sequencing identifies a novel variant in ACTC1 associated with familial artial septal defect. Can J Cardiol 2014;30:181-7. 11. Matsson H, Eason J, Bookwalter CS, et al. Alpha-cardiac actin mutations produce atrial septal defects. Hum Mol Genet 2008;17:256-65.

Sequencing: the next generation--what is the role of whole-exome sequencing in the diagnosis of familial cardiovascular diseases?

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