Samantha Baxter

The landscape of genetic variation in dilated cardiomyopathy as surveyed by clinical DNA sequencing

Purpose:Dilated cardiomyopathy is characterized by substantial locus, allelic, and clinical heterogeneity that necessitates testing of many genes across clinically overlapping diseases. Few studies have sequenced sufficient individuals; thus, the contributions of individual genes and the pathogenic variant spectrum are still poorly defined. We analyzed 766 dilated cardiomyopathy patients tested over 5 years in our molecular diagnostics laboratory.Methods:Patients were tested using gene panels of increasing size from 5 to 46 genes, including 121 cases tested with a multiple-cardiomyopathy next-generation panel covering 46 genes. All variants were reassessed using our current clinical-grade scoring system to eliminate false-positive disease associations that afflict many older analyses.Results:Up to 37% of dilated cardiomyopathy cases carry a clinically relevant variant in one of 20 genes, titin (TTN) being the largest contributor (up to 14%). Desmoplakin (DSP), an arrhythmogenic right ventricular cardiomyopathy gene, contributed 2.4%, illustrating the utility of multidisease testing. The clinical sensitivity increased from 10 to 37% as gene panel sizes increased. However, the number of inconclusive cases also increased from 4.6 to 51%.Conclusion:Our data illustrate the utility of broad gene panels for genetically and clinically heterogeneous diseases but also highlight challenges as molecular diagnostics moves toward genome-wide testing.Genet Med 16 8, 601–608.Genetics in Medicine (2014); 16 8, 601–608. doi:10.1038/gim.2013.204

A novel custom resequencing array for dilated cardiomyopathy.

Purpose: Genetic tests for the most commonly mutated genes in dilated cardiomyopathy (DCM) can confirm a clinical diagnosis in the proband and inform family management. Presymptomatic family members can be identified, allowing for targeted clinical monitoring to minimize adverse outcomes. However, the marked locus and allelic heterogeneity associated with DCM have made clinical genetic testing challenging. Novel sequencing platforms have now opened up avenues for more comprehensive diagnostic testing while simultaneously decreasing test cost and turn around time.Methods: By using a custom design based on triplicate resequencing and separate genotyping of known disease-causing variants, we developed the DCM CardioChip for efficient analysis of 19 genes previously implicated in causing DCM.Results: The chips analytical sensitivity for known and novel substitution variants is 100% and 98%, respectively. In screening 73 previously tested DCM patients who did not carry clinically significant variants in 10 genes, 7 variants of likely clinical significance were identified in the remaining 9 genes included on the chip. Compared with traditional Sanger-based sequencing, test cost and turn around time were reduced by ∼50%.Conclusions: The DCM CardioChip is a highly efficient screening test with a projected clinical sensitivity of 26–29%.

Communicating new knowledge on previously reported genetic variants

Genetic tests often identify variants whose significance cannot be determined at the time they are reported. In many situations, it is critical that clinicians be informed when new information emerges on these variants. It is already extremely challenging for laboratories to provide these updates. These challenges will grow rapidly as an increasing number of clinical genetic tests are ordered and as the amount of patient DNA assayed per test expands; the challenges will need to be addressed before whole-genome sequencing is used on a widespread basis.Information technology infrastructure can be useful in this context. We have deployed an infrastructure enabling clinicians to receive knowledge updates when a laboratory changes the classification of a variant. We have gathered statistics from this deployment regarding the frequency of both variant classification changes and the effects of these classification changes on patients. We report on the system’s functionality as well as the statistics derived from its use.Genet Med 2012:14(8):713–719

The GeneInsight Suite: A Platform to Support Laboratory and Provider Use of DNA based Genetic Testing

The future of personalized medicine will hinge on effective management of patient genetic profiles. Molecular diagnostic testing laboratories need to track knowledge surrounding an increasingly large number of genetic variants, incorporate this knowledge into interpretative reports, and keep ordering clinicians up to date as this knowledge evolves. Treating clinicians need to track which variants have been identified in each of their patients along with the significance of these variants. The GeneInsightSM Suite assists in these areas. The suite also provides a basis for interconnecting laboratories and clinicians in a manner that increases the scalability of personalized medicine processes. Hum Mutat 32:1–5, 2011.

Development and Validation of a Computational Method for Assessment of Missense Variants in Hypertrophic Cardiomyopathy

Assessing the significance of novel genetic variants revealed by DNA sequencing is a major challenge to the integration of genomic techniques with medical practice. Many variants remain difficult to classify by traditional genetic methods. Computational methods have been developed that could contribute to classifying these variants, but they have not been properly validated and are generally not considered mature enough to be used effectively in a clinical setting. We developed a computational method for predicting the effects of missense variants detected in patients with hypertrophic cardiomyopathy (HCM). We used a curated clinical data set of 74 missense variants in six genes associated with HCM to train and validate an automated predictor. The predictor is based on support vector regression and uses phylogenetic and structural features specific to genes involved in HCM. Ten-fold cross validation estimated our predictors sensitivity at 94% (95% confidence interval: 83%-98%) and specificity at 89% (95% confidence interval: 72%-100%). This corresponds to an odds ratio of 10 for a prediction of pathogenic (95% confidence interval: 4.0-infinity), or an odds ratio of 9.9 for a prediction of benign (95% confidence interval: 4.6-21). Coverage (proportion of variants for which a prediction was made) was 57% (95% confidence interval: 49%-64%). This performance exceeds that of existing methods that are not specifically designed for HCM. The accuracy of this predictor provides support for the clinical use of automated predictions alongside family segregation and population frequency data in the interpretation of new missense variants and suggests future development of similar tools for other diseases.

Use and interpretation of genetic tests in cardiovascular genetics

Our understanding of the genetic basis of many Mendelian forms of cardiovascular disease has advanced significantly in the last 5–10 years. There are now many professional society guidelines that recommend genetic testing for a variety of hereditary cardiovascular diseases including long QT syndrome, hypertrophic cardiomyopathy, and arrhythmogenic right ventricular cardiomyopathy (ARVC).1–3 The number of genes associated with cardiac conditions continues to increase, and the number of clinically available genetic tests for cardiac conditions has expanded rapidly in recent years (table 1). View this table: Table 1 Genetic tests for hereditary cardiac conditions. Genetic tests for hereditary cardiac conditions typically involve sequencing some or all of the various genes associated with a given condition. The number of genes included and the sequencing methodology used may vary by laboratory. Some laboratories also offer analyses to look for duplications or deletions in the associated genes Clinical genetic testing can be highly valuable in the management of families with hereditary disease. Determining which family members inherited the genetic predisposition to cardiac disease allows us to separate those in need of lifelong clinical evaluations from those who need no further evaluations beyond those recommended for the general population. This strategy is particularly valuable in inherited cardiovascular diseases where definitive clinical diagnosis of at-risk relatives is limited by incomplete penetrance, variable age of onset and, in some cases, insensitivity of clinical testing.4–7 Recent guidelines and expert opinions have gone beyond simply recommending genetic testing; they emphasise important points for the judicious use of genetic testing such as performing genetic testing on the most clearly affected person in the family, careful genetic counselling regarding the implications of positive, negative or uncertain results, and consideration of referral to a specialised centre due to the complexity of such genetic evaluations.1 8 9 To further elucidate principles and approaches critical to the …

Usability of a novel clinician interface for genetic results

The complexity and rapid growth of genetic data demand investment in information technology to support effective use of this information. Creating infrastructure to communicate genetic information to healthcare providers and enable them to manage that data can positively affect a patients care in many ways. However, genetic data are complex and present many challenges. We report on the usability of a novel application designed to assist providers in receiving and managing a patients genetic profile, including ongoing updated interpretations of the genetic variants in those patients. Because these interpretations are constantly evolving, managing them represents a challenge. We conducted usability tests with potential users of this application and reported findings to the application development team, many of which were addressed in subsequent versions. Clinicians were excited about the value this tool provides in pushing out variant updates to providers and overall gave the application high usability ratings, but had some difficulty interpreting elements of the interface. Many issues identified required relatively little development effort to fix suggesting that consistently incorporating this type of analysis in the development process can be highly beneficial. For genetic decision support applications, our findings suggest the importance of designing a system that can deliver the most current knowledge and highlight the significance of new genetic information for clinical care. Our results demonstrate that using a development and design process that is user focused helped optimize the value of this application for personalized medicine.

New Molecular Genetic Tests in the Diagnosis of Heart Disease

With the increasing use of next-generation sequencing applications, there has been an increase in identification of genetic causes of cardiac disease. This technology has also enabled the transition of these genes into the clinical setting and the rapid growth of large gene tests for the diagnosis of heart disorders. The ability to combine tests to include similar, but distinct, diseases has shown that many genes can be responsible for a wide variety of both syndromic and nonsyndromic disorders. This article discusses the current state of molecular genetic diagnosis for cardiac disorders, focusing on diseases with mendelian inheritance.