Diagnostic yield of genetic testing in a multinational heterogeneous cohort of 2088 DCM patients.

Background: Familial dilated cardiomyopathy (DCM) causes heart failure and may lead to heart transplantation. DCM is typically a monogenic disorder with autosomal dominant inheritance. Currently disease-causing variants have been reported in over 60 genes that encode proteins in sarcomeres, nuclear lamina, desmosomes, cytoskeleton, and mitochondria. Over half of the patients undergoing comprehensive genetic testing are left without a molecular diagnosis even when patient selection follows strict DCM criteria. Methods and results: This study was a retrospective review of patients referred for genetic testing at Blueprint Genetics due to suspected inherited DCM. Next generation sequencing panels included 23-316 genes associated with cardiomyopathies and other monogenic cardiac diseases. Variants were considered diagnostic if classified as pathogenic (P) or likely pathogenic (LP). Of the 2,088 patients 514 (24.6%) obtained a molecular diagnosis; 534 LP/P variants were observed across 45 genes, 2.7% (14/514) had two diagnostic variants in dominant genes. Nine copy number variants were identified: two multigene and seven intragenic. Diagnostic variants were observed most often in TTN (45.3%), DSP (6.7%), LMNA (6.7%), and MYH7 (5.2%). Clinical characteristics independently associated with molecular diagnosis were: a lower age at diagnosis, family history of DCM, paroxysmal atrial fibrillation, absence of left bundle branch block, and the presence of an implantable cardioverter-defibrillator. Conclusions: Panel testing provides good diagnostic yield in patients with clinically suspected DCM. Causative variants were identified in 45 genes. In minority, two diagnostic variants were observed in dominant genes. Our results support the use of genetic panels in clinical settings in DCM patients with suspected genetic etiology.

Opt-in for secondary findings as part of diagnostic whole-exome sequencing: Real-life experience from an international diagnostic laboratory.

BACKGROUND: Discussion about the risks and benefits of offering secondary findings as part of genome-wide diagnostics lacks real-life data. We studied the opt-in decisions of patients/families referred to whole exome study (WES) in Blueprint Genetics (BpG), a genetic testing company with customers in over 70 countries to receive secondary findings. Based on the American College of Medical Genetics (ACMG) recommendations for reporting secondary findings, BpG offered testing of specific actionable genes without additional charge for specimens submitted to WES diagnostics. METHODS: Individuals could opt-in for a secondary findings analysis by using a separate electronic consent form. Data from BpG database of electronic consent forms was used for the analysis. RESULTS: During the selected study period there were 3263 WES referrals, from which 2012 were index patients. About half of the individuals (50.4%) opted in to receiving secondary findings. Of patients who opted in, a secondary finding was detected for 2.7%, similar to other studies. We detected huge differences relating to opt-in between individuals from different countries; for instance, 90% of the 41 patients and their family members in Romania opted to receive secondary findings, while none of the 98 patients in Luxembourg chose that option. CONCLUSION: Differences between sexes or between children and adults were small. This data offers one view to the interest of patients and family members to opt in to receiving secondary findings. Research is needed to understand the influence of factors like age, education etc. and possible participation in pre-test counseling to receiving/not receiving secondary findings.

Prevalence of RPGR-Mediated Retinal Dystrophy in an Unselected Cohort of Over 5000 Patients.

Purpose: Comprehensive genetic testing for inherited retinal dystrophy (IRD) is challenged by difficult-to-sequence genomic regions, which are often mutational hotspots, such as RPGR ORF15. The purpose of this study was to evaluate the diagnostic contribution of RPGR variants in an unselected IRD patient cohort referred for testing in a clinical diagnostic laboratory. Methods: A total of 5201 consecutive patients were analyzed with a clinically validated next-generation sequencing (NGS)-based assay, including the difficult-to-sequence RPGR ORF15 region. Copy number variant (CNV) detection from NGS data was included. Variant interpretation was performed per the American College of Medical Genetics and Genomics guidelines. Results: A confirmed molecular diagnosis in RPGR was found in 4.5% of patients, 24.0% of whom were females. Variants in ORF15 accounted for 74% of the diagnoses; 29% of the diagnostic variants were in the most difficult-to-sequence central region of ORF15 (c.2470-3230). Truncating variants made up the majority (91%) of the diagnostic variants. CNVs explained 2% of the diagnostic cases, of which 80% were one- or two-exon deletions outside of ORF15. Conclusions: Our findings indicate that high-throughput, clinically validated NGS-based testing covering the difficult-to-sequence region of ORF15, in combination with high-resolution CNV detection, can help to maximize the diagnostic yield for patients with IRD. Translational Relevance: These results demonstrate an accurate and scalable method for the detection of RPGR-related variants, including the difficult-to-sequence ORF15 hotspot, which is relevant given current and emerging therapeutic opportunities.

GRINL1A Complex Transcription Unit Containing GCOM1, MYZAP, and POLR2M Genes Associates with Fully Penetrant Recessive Dilated Cardiomyopathy.

Background: Familial dilated cardiomyopathy (DCM) is a monogenic disorder typically inherited in an autosomal dominant pattern. We have identified two Finnish families with familial cardiomyopathy that is not explained by a variant in any previously known cardiomyopathy gene. We describe the cardiac phenotype related to homozygous truncating GCOM1 variants. Methods and Results: This study included two probands and their relatives. All the participants are of Finnish ethnicity. Whole-exome sequencing was used to test the probands; bi-directional Sanger sequencing was used to identify the GCOM1 variants in probands' family members. Clinical evaluation was performed, medical records and death certificates were obtained. Immunohistochemical analysis of myocardial samples was conducted. A homozygous GCOM1 variant was identified altogether in six individuals, all considered to be affected. None of the nine heterozygous family members fulfilled any cardiomyopathy criteria. Heart failure was the leading clinical feature, and the patients may have had a tendency for atrial arrhythmias. Conclusions: This study demonstrates the significance of GCOM1 variants as a cause of human cardiomyopathy and highlights the importance of searching for new candidate genes when targeted gene panels do not yield a positive outcome.

Diagnostic utility of next-generation sequencing-based panel testing in 543 patients with suspected skeletal dysplasia.

BACKGROUND: Skeletal dysplasia is typically diagnosed using a combination of radiographic imaging, clinical examinations, and molecular testing. Identifying a molecular diagnosis for an individual with a skeletal dysplasia can lead to improved clinical care, guide future medical management and treatment, and inform assessment of risk for familial recurrence. The molecular diagnostic utility of multi-gene panel testing using next-generation sequencing (NGS) has not yet been characterized for an unselected population of individuals with suspected skeletal dysplasia. In this study, we retrospectively reviewed patient reports to assess the diagnostic yield, reported variant characteristics, impact of copy number variation, and performance in prenatal diagnostics of panel tests for variants in genes associated with skeletal dysplasia and growth disorders. RESULTS: Clinical reports of consecutive patients with a clinical indication of suspected skeletal dysplasia who underwent panel testing were examined. The 543 patients included in the study submitted samples for diagnostic genetic testing with an indication of suspected skeletal dysplasia or growth disorder and received one of three nested panel tests. A molecular diagnosis was established in 42.0% of patients (n = 228/543). Diagnostic variants were identified in 71 genes, nearly half of which (n = 35, 49.3%) contributed uniquely to a molecular diagnosis for a single patient in this cohort. Diagnostic yield was significantly higher among fetal samples (58.0%, n = 51/88) than postnatal samples (38.9%, n = 177/455; z = 3.32, p < 0.0009). Diagnostic variants in fetal cases were identified across 18 genes. Thirteen diagnostic CNVs were reported, representing 5.7% of diagnostic findings and ranging in size from 241-bp to whole chromosome aneuploidy. Additionally, 11.4% (36/315) of non-diagnostic patient reports had suspicious variants of unknown significance (VUS), in which additional family studies that provide segregation data and/or functional characterization may result in reclassification to likely pathogenic. CONCLUSIONS: These findings demonstrate the utility of panel testing for individuals with a suspected skeletal dysplasia or growth disorder, with a particularly high diagnostic yield seen in prenatal cases. Pursuing comprehensive panel testing with high-resolution CNV analysis can provide a diagnostic benefit, given the considerable phenotype overlap amongst skeletal dysplasia conditions.

Next-generation sequencing in childhood-onset epilepsies: Diagnostic yield and impact on neuronal ceroid lipofuscinosis type 2 (CLN2) disease diagnosis.

Epilepsy is one of the most common childhood-onset neurological conditions with a genetic etiology. Genetic diagnosis provides potential for etiologically-based management and treatment. Existing research has focused on early-onset (<24 months) epilepsies; data regarding later-onset epilepsies is limited. The goal of this study was to determine the diagnostic yield of a clinically available epilepsy panel in a selected pediatric epilepsy cohort with epilepsy onset between 24-60 months of life and evaluate whether this approach decreases the age of diagnosis of neuronal ceroid lipofuscinosis type 2 (CLN2). Next-generation sequencing (NGS)-based epilepsy panels, including genes associated with epileptic encephalopathies and inborn errors of metabolism (IEMs) that present with epilepsy, were used. Copy-number variant (CNV) detection from NGS data was included. Variant interpretation was performed per American College of Medical Genetics and Genomics (ACMG) guidelines. Results are reported from 211 consecutive patients with the following inclusion criteria: 24-60 months of age at the time of enrollment, first unprovoked seizure at/after 24 months, and at least one additional finding such as EEG/MRI abnormalities, speech delay, or motor symptoms. Median age was 42 months at testing and 30 months at first seizure onset; the mean delay from first seizure to comprehensive genetic testing was 10.3 months. A genetic diagnosis was established in 43 patients (20.4%). CNVs were reported in 25.6% diagnosed patients; 27.3% of CNVs identified were intragenic. Within the diagnosed cohort, 11 (25.6%) patients were diagnosed with an IEM. The predominant molecular diagnosis was CLN2 (14% of diagnosed patients). For these patients, diagnosis was achieved 12-24 months earlier than reported by natural history of the disease. This study supports comprehensive genetic testing for patients whose first seizure occurs ≥ 24 months of age. It also supports early application of testing in this age group, as the identified diagnoses can have significant impact on patient management and outcome.

Diagnostic yield of genetic testing in a heterogeneous cohort of 1376 HCM patients.

BACKGROUND: Genetic testing in hypertrophic cardiomyopathy (HCM) is a published guideline-based recommendation. The diagnostic yield of genetic testing and corresponding HCM-associated genes have been largely documented by single center studies and carefully selected patient cohorts. Our goal was to evaluate the diagnostic yield of genetic testing in a heterogeneous cohort of patients with a clinical suspicion of HCM, referred for genetic testing from multiple centers around the world. METHODS: A retrospective review of patients with a suspected clinical diagnosis of HCM referred for genetic testing at Blueprint Genetics was undertaken. The analysis included syndromic, myopathic and metabolic etiologies. Genetic test results and variant classifications were extracted from the database. Variants classified as pathogenic (P) or likely pathogenic (LP) were considered diagnostic. RESULTS: A total of 1376 samples were analyzed. Three hundred and sixty-nine tests were diagnostic (26.8%); 373 P or LP variants were identified. Only one copy number variant was identified. The majority of diagnostic variants involved genes encoding the sarcomere (85.0%) followed by 4.3% of diagnostic variants identified in the RASopathy genes. Two percent of diagnostic variants were in genes associated with a cardiomyopathy other than HCM or an inherited arrhythmia. Clinical variables that increased the likelihood of identifying a diagnostic variant included: an earlier age at diagnosis (p < 0.0001), a higher maximum wall thickness (MWT) (p < 0.0001), a positive family history (p < 0.0001), the absence of hypertension (p = 0.0002), and the presence of an implantable cardioverter-defibrillator (ICD) (p = 0.0004). CONCLUSION: The diagnostic yield of genetic testing in this heterogeneous cohort of patients with a clinical suspicion of HCM is lower than what has been reported in well-characterized patient cohorts. We report the highest yield of diagnostic variants in the RASopathy genes identified in a laboratory cohort of HCM patients to date. The spectrum of genes implicated in this unselected cohort highlights the importance of pre-and post-test counseling when offering genetic testing to the broad HCM population.

Biallelic loss-of-function in NRAP is a cause of recessive dilated cardiomyopathy.

BACKGROUND: Familial dilated cardiomyopathy (DCM) is typically a monogenic disorder with dominant inheritance. Although over 40 genes have been linked to DCM, more than half of the patients undergoing comprehensive genetic testing are left without molecular diagnosis. Recently, biallelic protein-truncating variants (PTVs) in the nebulin-related anchoring protein gene (NRAP) were identified in a few patients with sporadic DCM. METHODS AND RESULTS: We determined the frequency of rare NRAP variants in a cohort of DCM patients and control patients to further evaluate role of this gene in cardiomyopathies. A retrospective analysis of our internal variant database consisting of 31,639 individuals who underwent genetic testing (either panel or direct exome sequencing) was performed. The DCM group included 577 patients with either a confirmed or suspected DCM diagnosis. A control cohort of 31,062 individuals, including 25,912 individuals with non-cardiac (control group) and 5,150 with non-DCM cardiac indications (Non-DCM cardiac group). Biallelic (n = 6) or two (n = 5) NRAP variants (two PTVs or PTV+missense) were identified in 11 unrelated probands with DCM (1.9%) but none of the controls. None of the 11 probands had an alternative molecular diagnosis. Family member testing supports co-segregation. Biallelic or potentially biallelic NRAP variants were enriched in DCM vs. controls (OR 1052, p<0.0001). Based on the frequency of NRAP PTVs in the gnomAD reference population, and predicting full penetrance, biallelic NRAP variants could explain 0.25%-2.46% of all DCM cases. CONCLUSION: Loss-of-function in NRAP is a cause for autosomal recessive dilated cardiomyopathy, supporting its inclusion in comprehensive genetic testing.

Sparse group factor analysis for biclustering of multiple data sources.

MOTIVATION: Modelling methods that find structure in data are necessary with the current large volumes of genomic data, and there have been various efforts to find subsets of genes exhibiting consistent patterns over subsets of treatments. These biclustering techniques have focused on one data source, often gene expression data. We present a Bayesian approach for joint biclustering of multiple data sources, extending a recent method Group Factor Analysis to have a biclustering interpretation with additional sparsity assumptions. The resulting method enables data-driven detection of linear structure present in parts of the data sources. RESULTS: Our simulation studies show that the proposed method reliably infers biclusters from heterogeneous data sources. We tested the method on data from the NCI-DREAM drug sensitivity prediction challenge, resulting in an excellent prediction accuracy. Moreover, the predictions are based on several biclusters which provide insight into the data sources, in this case on gene expression, DNA methylation, protein abundance, exome sequence, functional connectivity fingerprints and drug sensitivity. AVAILABILITY AND IMPLEMENTATION: http://research.cs.aalto.fi/pml/software/GFAsparse/ CONTACTS: : kerstin.bunte@googlemail.com or samuel.kaski@aalto.fi.