Next-Generation Sequencing Gene Panels in Inheritable Cardiomyopathies and Channelopathies: Prevalence of Pathogenic Variants and Variants of Unknown Significance in Uncommon Genes

The diffusion of next-generation sequencing (NGS)-based approaches allows for the identification of pathogenic mutations of cardiomyopathies and channelopathies in more than 200 different genes. Since genes considered uncommon for a clinical phenotype are also now included in molecular testing, the detection rate of disease-causing variants has increased. Here, we report the prevalence of genetic variants detected by using a NGS custom panel in a cohort of 133 patients with inherited cardiomyopathies (n = 77) or channelopathies (n = 56). We identified 82 variants, of which 50 (61%) were identified in genes without a strong or definitive evidence of disease association according to the NIH-funded Clinical Genome Resource (ClinGen; “uncommon genes”). Among these, 35 (70%) were variants of unknown significance (VUSs), 13 (26%) were pathogenic (P) or likely pathogenic (LP) mutations, and 2 (4%) benign (B) or likely benign (LB) variants according to American College of Medical Genetics (ACMG) classifications. These data reinforce the need for the screening of uncommon genes in order to increase the diagnostic sensitivity of the genetic testing of inherited cardiomyopathies and channelopathies by allowing for the identification of mutations in genes that are not usually explored due to a currently poor association with the clinical phenotype.


Introduction
Inheritable cardiomyopathies and channelopathies are disorders with phenotypic and genetic heterogeneous features caused by the presence of structural or electrical heart abnormalities [1]. Variable penetrance and incomplete expression are also common and may be due to the interaction of the causal mutation with modifier genes, epigenetic changes, environmental factors, or individual factors such as age, gender, ethnicity, or physical activity [2]. According to their functional and morphological features, cardiomyopathies are commonly classified as hypertrophic cardiomyopathy (HCM), arrhythmogenic cardiomyopathy (ACM), dilated cardiomyopathy (DCM), or restrictive cardiomyopathy (RCM) [3].
genes" as all limited, disputed, or refuted genes, or those without a reported association with the clinical phenotype of the patients.

Patient Enrolment and DNA Extraction
In total, 133 unrelated patients with a clinical diagnosis or suspicion of an inherited cardiac disease (cardiomyopathy or channelopathy) were enrolled from June 2018 to date and followed up on an average period of 3 years at the Department of Cardiomyopathy and Inherited Heart Disease Clinic, UOC Cardiology, University of Campania 'Luigi Vanvitelli' of Naples, and at the Center for the Study of Hypertrophic Cardiomyopathies of the Cardiology Division of the Federico II University of Naples. Genetic testing was performed at the CEINGE diagnostic laboratory.
The reference clinicians of the patients required the molecular analysis to investigate the presence of a possible genetic disease. A blood sample was collected in EDTA from each study subject. Each patient gave their written informed consent to molecular analysis according to the tenets of the Helsinki Declaration [60] and the internal ethics committee (N. 77/21). Genomic DNA was extracted using a Maxwell 16 instrument (Promega, Madison, WI, USA). DNA quality was assessed with a Nanodrop (Thermo Fisher, Waltham, MA, USA) spectrophotometer and Tape Station (Agilent, Santa Clara, CA, USA) analyzers to verify their concentration, purity, and integrity before proceeding to library preparation.

Molecular Analysis
Molecular testing was carried out by analyzing a panel of target genes through an NGSbased procedure. In particular, 2 custom panels were used: (1) a first-level panel including 60 diagnostic genes associated to the different genetic cardiomyopathies, including HCM, DCM, ACM, and channelopathies, such as LQTS and BrS; and (2) an enlarged panel of 129 genes including rarer genes; this panel was used in cases of complex or unclear phenotypes and in the presence of a positive family history for SCD. In both cases, HaloPlex technology (Agilent, Santa Clara, CA, USA) was used for library preparation. In detail, each genomic DNA sample was fragmented using a pool of restriction enzymes. The obtained fragments were enriched with hybridization with the custom capture probes, and then purified and PCR-amplified to obtain a DNA library or sample. During this procedure, each genomic DNA sample was univocally tagged with a barcode sequence to allow for sample multiplexing during the subsequent sequencing step.
The obtained enriched and indexed libraries were sequenced using the MiSeq (Illumina, San Diego, CA, USA) instrument (2 × 250 PE). Alissa software (Agilent, Santa Clara, CA, USA) was used to perform sequence data analysis. This tool allows for the alignment of the sequences to the reference genome to obtain a list of genomic variants that can be prioritized using a customizable pipeline in order to highlight pathogenic mutations or potentially pathogenic variants. This pipeline allows for variant classification based on their position with regard to the gene structure (exonic or intronic), population frequency, coding effect, ClinVar classification, and functional predictions. In addition, we classified the variants according to American College of Medical Genetics and Genomics (ACMG) guidelines adapted to cardiomyopathy [61]. In detail, all variants were evaluated for their frequency in international population database gnomAD (http://gnomad.broadinstitute.org/, accessed on 26 September 2022): we excluded variants showing minor frequency alleles (MAF) below the calculated maximal tolerated allele frequency for the specific cardiomyopathy [62]. According to these criteria, the maximal credible allele frequency was 0.000084 for DCM, 0.00004 for HCM, 0.000092 for ACM, 0.00001 for BrS, and 0.0000082 for LQTS [62]. However, we kept 10 variants showing an MAF greater than the threshold because they are reported as pathogenetic in the HGMD database. The latter classifies variants on the basis of the interpretation at first reporting; thus, even if it is less valuable with respect to ACMG classification and more prone to subsequent modifications, it may provide additional data supporting the variants' correct classification and subsequent interpretation. Moreover, bioinformatic pathogenicity evaluation for missense variants was performed by using multiple in silico tools, including Grantham distance and an Align-GVGD matrix. The splicing module from Alamut visual v.2.7.0.0 software was used to test the pathogenicity of a possible splicing variant. In some cases, we had informative families, i.e., ones having at least 3 affected relatives in which we analyzed variant cosegregation. In families with one affected member being a noncarrier, the variant is considered to be non-disease-causing. Pathogenic or doubtful variants were confirmed with Sanger sequencing.

Results
In total, 133 independent subjects underwent genetic testing because of a clinical suspicion of inherited cardiomyopathy or channelopathy over a period of enrollment of 3 years (2018-2020). The average sequencing coverage of the target regions was in the range of 150-250X with a 50X minimal acceptable threshold. In detail, 60/133 patients showing a phenotype, and/or laboratory or instrumental data supporting a clinical diagnosis of a specific inherited cardiomyopathy according to international guidelines were analyzed using a first-level panel including 60 main diagnostic genes that had been associated with different cardiomyopathies/channelopathies. The remaining 73/133 subjects, showing unclear cardiological clinical signs and/or a positive family history for SCD, were analyzed using an enlarged 129 gene panel. In our cohort of 133 patients, we detected a total of 82 variants, excluding polymorphisms. The variants, shown in Table 1 Among the 82 detected variants, 27 were novel as they were missing in the reference SNP, ClinVar, and HGMD databases. The ClinVar database reported 39/82 variants. Of these variants, 20 were classified as pathogenic or likely pathogenic (P/LP), 13 as conflicting (CI), and 6 of uncertain or unknown significance (VUS). The remaining 43 variants were not reported (NR) in ClinVar. HGMD reported 38/82 variants as pathogenic or likely pathogenic, while the remaining 44 were not reported. According to ACMG interpretation criteria, 39/82 variants were classified as P/LP (48%), of which 6 were novel (without reference SNP ID number), and 41/82 as VUSs (50%), of which 26 were novel ones. Furthermore, two of the identified variants (2%) were classified by ACMG guideline as benign or likely benign (B/LB). According to ACMG criteria, we globally identified P/LP variants in 53 patients (40% of the analyzed population), VUSs in 38 patients (29%), and B/LB variants in 4 patients (3%). In addition, 11 patients carried multiple variants. We did not identify any pathogenic mutations or VUSs in the remaining 38 patients (29%), who showed only known polymorphisms and/or LB variants in the analyzed genes. If we separately analyzed the two cohorts of patients, among the 60 patients admitted to the first-level test, 24 carried a P/LP variant (41%, 7 channelopathy and 17 cardiomyopathy patients) and 24 carried a VUS (41%, 7 channelopathy and 17 cardiomyopathy patients). Similarly, among the 73 patients analyzed using the enlarged panel, 29 carried a P/LP variant (40%, 4 channelopathy and 25 cardiomyopathy patients) and 14 carried a VUS (19%, 6 channelopathy and 8 cardiomyopathy patients).  Figure 1 shows the distribution of P/LP and VUS variants among channelopathy ( Figure 1A,C) and cardiomyopathy ( Figure 1B,D) patients analyzed via the two genes panels. The percentage of patients with an unknown causal gene included subjects without pathogenic mutations or VUSs, carrying known polymorphisms and/or LB variants in the analyzed genes. In total, 11 patients (8.3%) carried multiple variants: in particular, 3 patients carried two different P/LP mutations, 3 patients carried 1 P/LP mutation and a VUS, and 5 patients carried more than one VUS. We analyzed 5/11 patients with the first-level test, and 6/11 with the enlarged one. Furthermore, 7/11 patients showed double mutations in uncommon genes with respect to their phenotype, 2 patients were doubly mutated in main genes, and 2 patients showed one mutation in an uncommon and the other in a main gene.
Globally, among the 82 variants, 50 (61%) were localized in genes without reported evidence, or classified with limited or disputed evidence for a role in cardiomyopathies or channelopathies in ClinGen (uncommon genes), while 32 (39%) were had a definitive or moderate association with the disease.
Among the 50 identified variants in uncommon genes, 48 were P/LP or VUS (13 as P/LP and 35 as VUSs) and 2 as B/LB according to ACMG classification. In addition, 11/13 P/LP and 14/35 VUSs were identified among patients who had undergone extended molecular analysis.
The detailed distribution of all identified variants divided by clinical phenotype is reported in Table 1.
Overall, in this study group, we detected 39 pathogenic or likely pathogenic mutations, of which 26 were identified in main genes (67%) and 13 (33%) in uncommon genes. Furthermore, we identified 41 VUSs, of which 35 (85%) in uncommon genes and 6 (15%) in main genes. Our findings indicate that P/LP variants are more likely to be identified in main genes, while VUSs are mostly identified in uncommon genes. When considering the two analyzed cohorts separately, we found that the number of variants (both P/LP and VUSs) in the main genes was almost the same within the two different panels; the number of P/LP variants identified in uncommon genes increased when the enlarged panel was used ( Figure 2).
Furthermore, among the 41 identified VUSs, 6 (15%) were detected in ACM, 6 (15%) in DCM, 13 (32%) in HCM, 13 (32%) in BrS, and 3 (7%) in LQTS patients ( Figure 4A). Interestingly, 35/41 VUSs (85%) fell into the uncommon-gene group, with 22 (63%) identified in patients who had undergone the first-level test and 13 (37%) in those who performed the enlarged one. When we analyzed the distribution of the VUSs in uncommon and main genes per each disease, we found a higher percentage of VUSs in common genes in all the diseases with the exception of DCM ( Figure 4B).
In the enrolled patients among 133 analyzed subjects, we detected 53 patients 40%) carrying at least one P or LP variants. In particular, 15 out of 53 patients (28%) carried P or LP variants in uncommon genes and 38 (72%) in main genes ( Figure 5). Table 2 shows the demographic, clinical, and instrumental data of eight patients carrying pathogenic or likely pathogenic variants detected in uncommon genes with respect to the clinical diagnosis or suspicion for the inherited cardiac disease (cardiomyopathy or channelopathy). All except 1 patient (NA04) were analyzed with the enlarged panel of 129 genes, including rarer genes. As shown in Figure 3A, P/LP mutations in both main and uncommon genes (accordingly with association with the reported cardiomyopathy in Clinical Genome Resource) were mainly detected in HCM patients (57% of the P/LP variants), followed by ACM (20%), LQTS, DCM, and BrS patients (12%, 6% and 6%, respectively). Among ACM, (accordingly with association with the reported cardiomyopathy in Clinical Genome Resource) were mainly detected in HCM patients (57% of the P/LP variants), followed by ACM (20%), LQTS, DCM, and BrS patients (12%, 6% and 6%, respectively). Among ACM, HCM, BrS, DCM, and LQTS patients carrying P or LP mutations, 4/10 (40%), 7/29 (24%), 2/3 (67%), 2/3 (67%), 1/6 (17%) were detected in uncommon genes, respectively ( Figure  3B). Only 3 (19%) of these variants were identified in patients who had undergone the first-level test, while the remaining 13 (81%) were identified with the enlarged-gene panel. Furthermore, among the 41 identified VUSs, 6 (15%) were detected in ACM, 6 (15%) in DCM, 13 (32%) in HCM, 13 (32%) in BrS, and 3 (7%) in LQTS patients ( Figure 4A). Interestingly, 35/41 VUSs (85%) fell into the uncommon-gene group, with 22 (63%) identified in patients who had undergone the first-level test and 13 (37%) in those who performed the enlarged one. When we analyzed the distribution of the VUSs in uncommon and main genes per each disease, we found a higher percentage of VUSs in common genes in all the diseases with the exception of DCM ( Figure 4B).  In the enrolled patients among 133 analyzed subjects, we detected 53 patients 40%) carrying at least one P or LP variants. In particular, 15 out of 53 patients (28%) carried P or LP variants in uncommon genes and 38 (72%) in main genes ( Figure 5). Table 2 shows the demographic, clinical, and instrumental data of eight patients carrying pathogenic or likely pathogenic variants detected in uncommon genes with respect to the clinical diagnosis or suspicion for the inherited cardiac disease (cardiomyopathy or channelopathy). All except 1 patient (NA04) were analyzed with the enlarged panel of 129 genes, including rarer genes.  In the enrolled patients among 133 analyzed subjects, we detected 53 patients 40%) carrying at least one P or LP variants. In particular, 15 out of 53 patients (28%) carried P or LP variants in uncommon genes and 38 (72%) in main genes ( Figure 5). Table 2 shows the demographic, clinical, and instrumental data of eight patients carrying pathogenic or likely pathogenic variants detected in uncommon genes with respect to the clinical diagnosis or suspicion for the inherited cardiac disease (cardiomyopathy or channelopathy). All except 1 patient (NA04) were analyzed with the enlarged panel of 129 genes, including rarer genes.  These eight patients were recruited according to the physician's clinical suspicion for an inherited cardiomyopathy or channelopathy. In detail, four HCM patients carried mutations in uncommon genes ABCC9, KCNQ1, PKP2 and RAF1, and two BrS patients in uncommon genes MYBPC3 and POLG. Furthermore, we identified one ACM patient carrying a mutation in uncommon gene KCNE3 and one ACM patient in trans carrying two variants in uncommon gene POLG (c.752C>T and c.1760C>T), classified as LP/P according to the novel ACMG criteria.
Furthermore, VUSs were identified in 38 out of 133 patients (29%), of which 32 (84%) showed VUSs in uncommon genes and 6 (16%) in main genes ( Figure 5). Table 2. Demographic, clinical, and instrumental data of patients carrying pathogenic or likely pathogenic variants in uncommon genes with respect to the clinical diagnosis or suspicion of an inherited cardiac disease (cardiomyopathy or channelopathy). LGE, late gadolinium enhancement. * At first evaluation; ** at last follow-up.

Discussion
In this study, we report the results of a targeted-NGS-based genetic screening carried out on 133 unrelated patients from South Italy diagnosed with cardiomyopathy or channelopathy. We used a large panel of 129 cardiomyopathy-related genes to increase the yield of genetic testing considering the genetic heterogeneity and variable and overlapping phenotypes, which is a characteristic of hereditary structural and electric cardiac diseases. Using the clinical genome resource approach to assess the strength of gene-disease association, we focused on variants in genes without definitive or strong evidence for an association with cardiomyopathies or channelopathies, which we defined as uncommon causal genes.
Globally, our NGS panel test demonstrated a yield of 40% if we considered the genetic test to be positive in the presence of pathogenic or likely pathogenic variants in both main and uncommon genes. When we included the VUSs, the global yield of the test increased up to 69%.
We detected 39 pathogenic or likely pathogenic variants according to the ACMG classification in 53 patients (44 cardiomyopathies and 9 channelopathies), including 13 patients carrying P or LP variants in uncommon genes. The role of these uncommon genes as causal genes should be evaluated in the context of the clinical manifestations and the evidence of the functional effects of the variant on the encoded protein; moreover, when large pedigrees are available, the analysis of the segregation of the genetic variant with the phenotype allows for confirming the phenotype-genotype association. Furthermore, we verified whether similar gene-disease associations to those identified in our study were reported in the literature. For example, in our study cohort, we detected a mutation in sarcomeric gene MYBPC3 (c.906-1G>C; rs587776700) in a BrS patient. Experimental studies showed that this variant disrupts mRNA splicing, leading to a loss of protein function [64]. Some studies reported a MYBPC3 mutation in patients showing the Brugada phenotype [65,66]. In addition, the literature reported cases of Brugada phenocopies in patients carrying a pathogenic mutation in the MYBPC3 gene [67], speculating that Brugada type 1 ECG could be an early sign of an occult structural heart disease. Brugada syndrome is generally considered to be a disease of the ion channels. However, recent studies have also identified structural heart impairment, i.e., epicardial surface and interstitial fibrosis, increased collagen, and reduced contractility in BrS patients. These observations agree with the finding of causal mutations in genes that are molecular causes of cardiomyopathies, such as sarcomeric genes [66]. These data suggest that structural and electrical cardiac alterations may be present in BrS patients, which may develop from the same molecular alteration.
Similarly, although HCM is commonly considered to be a disease of the sarcomere, recent literature data reported an association of the HCM phenotype with mutations in the ABCC9 [48,68], PKP2 [69][70][71], and RAF1 [72] genes, and in other nonsarcomeric genes [73]. The pathogenic mechanisms leading to the development of the HCM phenotype need to be elucidated.
Furthermore, in our study, we identified (L)P variants in the POLG gene in two patients with BrS and ACM, respectively. Our data are in accordance with recently published data in which the POLG gene was associated with the ACM phenotype [74].
Overall, in our cohort, the prevalence of (L)P variants in uncommon genes was about 8% (3% in the first-level and 15% in the enlarged panels). This result supports the need for extended genetic testing including uncommon genes for such heterogeneous diseases as cardiomyopathies and channelopathies. Indeed, by limiting the genetic test to just phenotype-related (main) genes, we would have failed in identifying 13 mutations and the corresponding carrying patients (8% of the screened population). On the other hand, our approach was able to increase the diagnostic sensitivity of the test identifying these additional patients.
Biotechnological research is always looking for new diagnostic strategies [75]. As NGS-based applications are currently widely used in diagnostic laboratories, and their costs are decreasing progressively, their use is desirable to enlarge the spectrum of the genes related to a specific disease. Indeed, accumulating data from different studies may allow for reconsidering the genotype-phenotype associations for some genes now considered to be uncommon.
In addition to pathogenic and likely pathogenic mutations, as expected in this kind of extended molecular screening, we identified many VUSs (41/82; 50% of the total number of identified variants) according to ACMG classification. Of the VUSs, 85% (35/41) were detected in uncommon genes. We detected variant c.764G>C in an HCM patient in the FHL1 gene, which is classifiable as a VUS according to ACMG criteria. However, it is reported as pathogenic by HGMD database, showing strong evidence for a primary pathogenic role in HCM [73,76]. The FHL1 gene was classified without evidence for a HCM association by ClinGen. The ACMG rule for classification is hypothesized to minimize the risk for false positive interpretations; however, it is also well-accepted that these rigorous criteria result in undercalling pathogenic variants in well-established cardiomyopathy genes.
Certainly, VUS interpretation and the consequent clinical management of their carriers is a key challenge following NGS-based molecular testing [77]. The possibility to study a specific VUS in the context of a large pedigree by allowing for the robust analysis of the variant's segregation with the clinical phenotype may be decisive to establish its pathogenic role; however, this is often unfeasible [78]. To definitively assess the molecular consequence of an identified VUS and thus establish its functional effects, the most proper approach should include in vitro functional assays [79][80][81][82]. Nevertheless, these functional evaluations are often difficult to be realized, especially in a routine setting and on a large scale, since different cellular models and different assays need to be used on the basis of the gene involved and on the type of molecular defect. The more that we enlarge the analyzed genomic region, the more the number of VUSs per patient increases. Nevertheless, even if VUS communication may be challenging and frustrating for both patients and clinicians, it offers a great opportunity for the re-evaluation of cases over time. Indeed, monitoring these variants over time may allow for their reclassification, and hence provide novel clues for the management of carriers and their relatives. Moreover, some of the VUSs may act as modifier genes, influencing a patient's clinical phenotype, and may contribute to also explaining the observed clinical heterogeneity within families.

Conclusions
Considering all the above, extensive genetic test approaches are required to unravel the molecular bases of such a complex group of diseases as cardiomyopathies and channelopathies. NGS-based approaches, by allowing for the simultaneous analysis of multiple genes, increase the detection rate of causal mutations in inherited structural and electric hereditary cardiac diseases, and provide epidemiological data regarding the prevalence of causative mutations in uncommon genes. In addition, several uncertain or unknown variants (VUSs) are being identified and require more efforts in the near future to assess their pathogenicity.
The use of an NGS-based approach in diagnostics also increases the yield of mutations carriers' identification in the rarest and uncommon genes, as shown in our study. Indeed, our data are a parameter of the increased diagnostic yield of such extended molecular analyses that also enable screening for rare and uncommon genes in a simple, reliable, and cost-saving manner.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/biom12101417/s1. Table S1: genes reported in the literature associated with cardiomyopathies and channelopathies.  Acknowledgments: The authors thank Serena Conato for the technical support to the experimental work.

Conflicts of Interest:
The authors declare no conflict of interest. Tumor protein P63 SCN10A sodium voltage-gated channel alpha subunit 10 CACNA1C Calcium voltage-gated channel subunit alpha1 c ABCC9