Genetic Misdiagnoses and the Potential for Health Disparities.

BACKGROUND: For more than a decade, risk stratification for hypertrophic cardiomyopathy has been enhanced by targeted genetic testing. Using sequencing results, clinicians routinely assess the risk of hypertrophic cardiomyopathy in a patient's relatives and diagnose the condition in patients who have ambiguous clinical presentations. However, the benefits of genetic testing come with the risk that variants may be misclassified. METHODS: Using publicly accessible exome data, we identified variants that have previously been considered causal in hypertrophic cardiomyopathy and that are overrepresented in the general population. We studied these variants in diverse populations and reevaluated their initial ascertainments in the medical literature. We reviewed patient records at a leading genetic-testing laboratory for occurrences of these variants during the near-decade-long history of the laboratory. RESULTS: Multiple patients, all of whom were of African or unspecified ancestry, received positive reports, with variants misclassified as pathogenic on the basis of the understanding at the time of testing. Subsequently, all reported variants were recategorized as benign. The mutations that were most common in the general population were significantly more common among black Americans than among white Americans (P<0.001). Simulations showed that the inclusion of even small numbers of black Americans in control cohorts probably would have prevented these misclassifications. We identified methodologic shortcomings that contributed to these errors in the medical literature. CONCLUSIONS: The misclassification of benign variants as pathogenic that we found in our study shows the need for sequencing the genomes of diverse populations, both in asymptomatic controls and the tested patient population. These results expand on current guidelines, which recommend the use of ancestry-matched controls to interpret variants. As additional populations of different ancestry backgrounds are sequenced, we expect variant reclassifications to increase, particularly for ancestry groups that have historically been less well studied. (Funded by the National Institutes of Health.).

Development of Clinical Domain Working Groups for the Clinical Genome Resource (ClinGen): lessons learned and plans for the future.

The Clinical Genome Resource (ClinGen) is supported by the National Institutes of Health (NIH) to develop expertly curated and freely accessible resources defining the clinical relevance of genes and variants for use in precision medicine and research. To facilitate expert input, ClinGen has formed Clinical Domain Working Groups (CDWGs) to leverage the collective knowledge of clinicians, laboratory diagnosticians, and researchers. In the initial phase of ClinGen, CDWGs were launched in the cardiovascular, hereditary cancer, and inborn errors of metabolism clinical fields. These early CDWGs established the infrastructure necessary to implement standardized processes developed or adopted by ClinGen working groups for the interpretation of gene-disease associations and variant pathogenicity, and provided a sustainable model for the formation of future disease-focused curation groups. The establishment of CDWGs requires recruitment of international experts to broadly represent the interests of their field and ensure that assertions made are reliable and widely accepted. Building on the successes, challenges, and trade-offs made in establishing the original CDWGs, ClinGen has developed standard operating procedures for the development of CDWGs in new clinical domains, while maximizing efforts to scale up curation and facilitate involvement of external groups who wish to utilize ClinGen methods and infrastructure for expert curation.

NGS testing for cardiomyopathy: Utility of adding RASopathy-associated genes.

RASopathies include a group of syndromes caused by pathogenic germline variants in RAS-MAPK pathway genes and typically present with facial dysmorphology, cardiovascular disease, and musculoskeletal anomalies. Recently, variants in RASopathy-associated genes have been reported in individuals with apparently nonsyndromic cardiomyopathy, suggesting that subtle features may be overlooked. To determine the utility and burden of adding RASopathy-associated genes to cardiomyopathy panels, we tested 11 RASopathy-associated genes by next-generation sequencing (NGS), including NGS-based copy number variant assessment, in 1,111 individuals referred for genetic testing for hypertrophic cardiomyopathy (HCM) or dilated cardiomyopathy (DCM). Disease-causing variants were identified in 0.6% (four of 692) of individuals with HCM, including three missense variants in the PTPN11, SOS1, and BRAF genes. Overall, 36 variants of uncertain significance (VUSs) were identified, averaging ∼3VUSs/100 cases. This study demonstrates that adding a subset of the RASopathy-associated genes to cardiomyopathy panels will increase clinical diagnoses without significantly increasing the number of VUSs/case.

Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples.

PURPOSE: The accurate interpretation of variation in Mendelian disease genes has lagged behind data generation as sequencing has become increasingly accessible. Ongoing large sequencing efforts present huge interpretive challenges, but they also provide an invaluable opportunity to characterize the spectrum and importance of rare variation. METHODS: We analyzed sequence data from 7,855 clinical cardiomyopathy cases and 60,706 Exome Aggregation Consortium (ExAC) reference samples to obtain a better understanding of genetic variation in a representative autosomal dominant disorder. RESULTS: We found that in some genes previously reported as important causes of a given cardiomyopathy, rare variation is not clinically informative because there is an unacceptably high likelihood of false-positive interpretation. By contrast, in other genes, we find that diagnostic laboratories may be overly conservative when assessing variant pathogenicity. CONCLUSIONS: We outline improved analytical approaches that evaluate which genes and variant classes are interpretable and propose that these will increase the clinical utility of testing across a range of Mendelian diseases.Genet Med 19 2, 192-203.

Improving hearing loss gene testing: a systematic review of gene evidence toward more efficient next-generation sequencing-based diagnostic testing and interpretation.

PURPOSE: With next generation sequencing technology improvement and cost reductions, it has become technically feasible to sequence a large number of genes in one diagnostic test. This is especially relevant for diseases with large genetic and/or phenotypic heterogeneity, such as hearing loss. However, variant interpretation remains the major bottleneck. This is further exacerbated by the lack in the clinical genetics community of consensus criteria for defining the evidence necessary to include genes on targeted disease panels or in genomic reports, and the consequent risk of reporting variants in genes with no relevance to disease. METHODS: We describe a systematic evidence-based approach for assessing gene-disease associations and for curating relevant genes for different disease aspects, including mode of inheritance, phenotypic severity, and mutation spectrum. RESULTS: By applying this approach to clinically available hearing loss gene panels with a total of 163 genes, we show that a significant number (45%) of genes lack sufficient evidence of association with disease and thus are expected to increase uncertainty and patient anxiety, in addition to intensifying the interpretation burden. Information about all curated genes is summarized. Our retrospective analysis of 539 hearing loss cases tested by our previous OtoGenomeV2 panel demonstrates the impact of including genes with weak disease association in laboratory wet-bench and interpretation processes. CONCLUSION: Our study is, to our knowledge, the first to highlight the urgent need for defining the clinical validity of gene-disease relationships for more efficient and accurate clinical testing and reporting.Genet Med 18 6, 545-553.

Burden of rare sarcomere gene variants in the Framingham and Jackson Heart Study cohorts.

Rare sarcomere protein variants cause dominant hypertrophic and dilated cardiomyopathies. To evaluate whether allelic variants in eight sarcomere genes are associated with cardiac morphology and function in the community, we sequenced 3,600 individuals from the Framingham Heart Study (FHS) and Jackson Heart Study (JHS) cohorts. Out of the total, 11.2% of individuals had one or more rare nonsynonymous sarcomere variants. The prevalence of likely pathogenic sarcomere variants was 0.6%, twice the previous estimates; however, only four of the 22 individuals had clinical manifestations of hypertrophic cardiomyopathy. Rare sarcomere variants were associated with an increased risk for adverse cardiovascular events (hazard ratio: 2.3) in the FHS cohort, suggesting that cardiovascular risk assessment in the general population can benefit from rare variant analysis.

CORRIGENDUM: Results of clinical genetic testing of 2,912 probands with hypertrophic cardiomyopathy: expanded panels offer limited additional sensitivity.

Genet Med advance online publication, January 22, 2015; doi:10.1038/gim.2014.205. In the Advance Online Publication version, of this article, there is a mistake on page 2 in the first paragraph of the Materials and Methods section. The sentence beginning "Among 3,459 probands initially referred for HCM genetic testing …" the correct number of probands is 3,473 not 3,459. The authors regret the error.

Results of clinical genetic testing of 2,912 probands with hypertrophic cardiomyopathy: expanded panels offer limited additional sensitivity.

PURPOSE: Hypertrophic cardiomyopathy (HCM) is caused primarily by pathogenic variants in genes encoding sarcomere proteins. We report genetic testing results for HCM in 2,912 unrelated individuals with nonsyndromic presentations from a broad referral population over 10 years. METHODS: Genetic testing was performed by Sanger sequencing for 10 genes from 2004 to 2007, by HCM CardioChip for 11 genes from 2007 to 2011 and by next-generation sequencing for 18, 46, or 51 genes from 2011 onward. RESULTS: The detection rate is ~32% among unselected probands, with inconclusive results in an additional 15%. Detection rates were not significantly different between adult and pediatric probands but were higher in females compared with males. An expanded gene panel encompassing more than 50 genes identified only a very small number of additional pathogenic variants beyond those identifiable in our original panels, which examined 11 genes. Familial genetic testing in at-risk family members eliminated the need for longitudinal cardiac evaluations in 691 individuals. Based on the projected costs derived from Medicare fee schedules for the recommended clinical evaluations of HCM family members by the American College of Cardiology Foundation/American Heart Association, our data indicate that genetic testing resulted in a minimum cost savings of about $0.7 million. CONCLUSION: Clinical HCM genetic testing provides a definitive molecular diagnosis for many patients and provides cost savings to families. Expanded gene panels have not substantively increased the clinical sensitivity of HCM testing, suggesting major additional causes of HCM still remain to be identified.

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 predictor's 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.

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.

Slice Testing-Considerations from Ordering to Reporting: A Joint Report of the Association for Molecular Pathology, College of American Pathologists, and National Society of Genetic Counselors.

As the number of genes associated with various germline disorders continues to grow, it is becoming more difficult for clinical laboratories to maintain separate assays for interrogating disease-focused gene panels. One solution to this challenge is termed slice testing, where capture backbone is used to analyze data specific to a set of genes, and for this article, we will focus on exome. A key advantage to this strategy is greater flexibility by adding genes as they become associated with disease or the ability to accommodate specific provider requests. Here, we provide expert consensus recommendations and results from an Association for Molecular Pathology-sponsored survey of clinical laboratories performing exome sequencing to compare a slice testing approach with traditional static gene panels and comprehensive exome analysis. We explore specific considerations for slices, including gene selection, analytic performance, coverage, quality, and interpretation. Our goal is to provide comprehensive guidance for clinical laboratories interested in designing and using slice tests as a diagnostic.

ACMG clinical laboratory standards for next-generation sequencing.

Next-generation sequencing technologies have been and continue to be deployed in clinical laboratories, enabling rapid transformations in genomic medicine. These technologies have reduced the cost of large-scale sequencing by several orders of magnitude, and continuous advances are being made. It is now feasible to analyze an individual's near-complete exome or genome to assist in the diagnosis of a wide array of clinical scenarios. Next-generation sequencing technologies are also facilitating further advances in therapeutic decision making and disease prediction for at-risk patients. However, with rapid advances come additional challenges involving the clinical validation and use of these constantly evolving technologies and platforms in clinical laboratories. To assist clinical laboratories with the validation of next-generation sequencing methods and platforms, the ongoing monitoring of next-generation sequencing testing to ensure quality results, and the interpretation and reporting of variants found using these technologies, the American College of Medical Genetics and Genomics has developed the following professional standards and guidelines.

Familial ebstein anomaly, left ventricular hypertrabeculation, and ventricular septal defect associated with a MYH7 mutation.

Ebstein anomaly is a rare congenital heart defect that most often occurs sporadically within a kindred. Familial cases, although reported, are uncommon. At this time, the genetic etiology of Ebstein anomaly is not fully elucidated. Here, we describe clinical and molecular investigations of a rare case of familial Ebstein anomaly in association with a likely pathogenic mutation of the MYH7 gene. The severity of presentation varies, and Ebstein anomaly can be observed in association with such other heart defects as ventricular septal defect and left ventricular (LV) hypertrabeculation, as seen in our family of study. In our family of study, the 31-year-old father and four of his children have been diagnosed with Ebstein anomaly. Genetic testing revealed that the father was heterozygous for the Glu1220del variant detected in exon 27 of the MYH7 gene. The MYH7 gene encodes the ß-myosin heavy chain and is expressed in cardiac muscle. DNA sequencing of three of his affected children confirmed that they carried the same variant while the fourth affected child was not available for testing. This is the first report of familial Ebstein anomaly associated with the Glu1220del mutation of the MYH7 gene. The mutation segregates with disease in a family with autosomal dominant transmission of congenital heart defects including Ebstein anomaly and other associated cardiovascular defects including LV hypertrabeculation and ventricular septal defect.

Genetic testing for dilated cardiomyopathy in clinical practice.

BACKGROUND: Familial involvement is common in dilated cardiomyopathy (DCM) and >40 genes have been implicated in causing disease. However, the role of genetic testing in clinical practice is not well defined. We examined the experience of clinical genetic testing in a diverse DCM population to characterize the prevalence and predictors of gene mutations. METHODS AND RESULTS: We studied 264 unrelated adult and pediatric DCM index patients referred to 1 reference lab for clinical genetic testing. Up to 10 genes were analyzed (MYH7, TNNT2, TNNI3, TPM1, MYBPC3, ACTC, LMNA, PLN, TAZ, and LDB3), and 70% of patients were tested for all genes. The mean age was 26.6 ± 21.3 years, and 52% had a family history of DCM. Rigorous criteria were used to classify DNA variants as clinically relevant (mutations), variants of unknown clinical significance (VUS), or presumed benign. Mutations were found in 17.4% of patients, commonly involving MYH7, LMNA, or TNNT2 (78%). An additional 10.6% of patients had VUS. Genetic testing was rarely positive in older patients without a family history of DCM. Conversely in pediatric patients, family history did not increase the sensitivity of genetic testing. CONCLUSIONS: Using rigorous criteria for classifying DNA variants, mutations were identified in 17% of a diverse group of DCM index patients referred for clinical genetic testing. The low sensitivity of genetic testing in DCM reflects limitations in both current methodology and knowledge of DCM-associated genes. However, if mutations are identified, genetic testing can help guide family management.

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 GeneInsight(SM) 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.

Harmonizing the Collection of Clinical Data on Genetic Testing Requisition Forms to Enhance Variant Interpretation in Hypertrophic Cardiomyopathy (HCM): A Study from the ClinGen Cardiomyopathy Variant Curation Expert Panel.

Diagnostic laboratories gather phenotypic data through requisition forms, but there is no consensus as to which data are essential for variant interpretation. The ClinGen Cardiomyopathy Variant Curation Expert Panel defined a phenotypic data set for hypertrophic cardiomyopathy (HCM) variant interpretation, with the goal of standardizing requisition forms. Phenotypic data elements listed on requisition forms from nine leading cardiomyopathy testing laboratories were compiled to assess divergence in data collection. A pilot of 50 HCM cases was implemented to determine the feasibility of harmonizing data collection. Laboratory directors were surveyed to gauge potential for adoption of a minimal data set. Wide divergence was observed in the phenotypic data fields in requisition forms. The 50-case pilot showed that although demographics and assertion of a clinical diagnosis of HCM had 86% to 98% completion, specific phenotypic features, such as degree of left ventricular hypertrophy, ejection fraction, and suspected syndromic disease, were completed only 24% to 44% of the time. Nine data elements were deemed essential for variant classification by the expert panel. Participating laboratories unanimously expressed a willingness to adopt these data elements in their requisition forms. This study demonstrates the value of comparing and sharing best practices through an expert group, such as the ClinGen Program, to enhance variant interpretation, providing a foundation for leveraging cumulative case-level data in public databases and ultimately improving patient care.

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 chip's 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 approximately 50%. CONCLUSIONS: The DCM CardioChip is a highly efficient screening test with a projected clinical sensitivity of 26-29%.

A novel, single nucleotide polymorphism-based assay to detect 22q11 deletions.

Velocardiofacial syndrome, DiGeorge syndrome, and conotruncal anomaly face syndrome, now collectively referred to as 22q11deletion syndrome (22q11DS) are caused by microdeletions on chromosome 22q11. The great majority ( approximately 90%) of these deletions are 3 Mb in size. The remaining deleted patients have nested break-points resulting in overlapping regions of hemizygosity. Diagnostic testing for the disorder is traditionally done by fluorescent in situ hybridization (FISH) using probes located in the proximal half of the region common to all deletions. We developed a novel, high-resolution single-nucleotide polymorphism (SNP) genotyping assay to detect 22q11 deletions. We validated this assay using DNA from 110 nondeleted controls and 77 patients with 22q11DS that had previously been tested by FISH. The assay was 100% sensitive (all deletions were correctly identified). Our assay was also able to detect a case of segmental uniparental disomy at 22q11 that was not detected by the FISH assay. We used Bayesian networks to identify a set of 17 SNPs that are sufficient to ascertain unambiguously the deletion status of 22q11DS patients. Our SNP based assay is a highly accurate, sensitive, and specific method for the diagnosis of 22q11 deletion syndrome.

The Case for Laboratory Developed Procedures: Quality and Positive Impact on Patient Care.

An explosion of knowledge and technology is revolutionizing medicine and patient care. Novel testing must be brought to the clinic with safety and accuracy, but also in a timely and cost-effective manner, so that patients can benefit and laboratories can offer testing consistent with current guidelines. Under the oversight provided by the Clinical Laboratory Improvement Amendments, laboratories have been able to develop and optimize laboratory procedures for use in-house. Quality improvement programs, interlaboratory comparisons, and the ability of laboratories to adjust assays as needed to improve results, utilize new sample types, or incorporate new mutations, information, or technologies are positive aspects of Clinical Laboratory Improvement Amendments oversight of laboratory-developed procedures. Laboratories have a long history of successful service to patients operating under Clinical Laboratory Improvement Amendments. A series of detailed clinical examples illustrating the quality and positive impact of laboratory-developed procedures on patient care is provided. These examples also demonstrate how Clinical Laboratory Improvement Amendments oversight ensures accurate, reliable, and reproducible testing in clinical laboratories.