Paralogue annotation identifies novel pathogenic variants in patients with Brugada syndrome and catecholaminergic polymorphic ventricular tachycardia

Genetic constraint at single amino acid resolution in protein domains improves missense variant prioritisation and gene discovery

BACKGROUND

One of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as "genetic constraint". Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes.

METHODS

We aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues.

RESULTS

We identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism.

CONCLUSIONS

Grouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.

In silico analysis of TRPM4 variants of unknown clinical significance

BACKGROUND

TRPM4 is a calcium-activated channel that selectively permeates monovalent cations. Genetic variants of the channel in cardiomyocytes are associated with various heart disorders, such as progressive familial heart block and Brugada syndrome. About97% of all known TRPM4 missense variants are classified as variants of unknown clinical significance (VUSs). The very large number of VUSs is a serious problem in diagnostics and treatment of inherited heart diseases.

METHODS AND RESULTS

We collected 233 benign or pathogenic missense variants in the superfamily of TRP channels from databases ClinVar, Humsavar and Ensembl Variation to compare performance of 22 algorithms that predict damaging variants. We found that ClinPred is the best-performing tool for TRP channels. We also used the paralogue annotation method to identify disease variants across the TRP family. In the set of 565 VUSs of hTRPM4, ClinPred predicted pathogenicity of 299 variants. Among these, 12 variants are also categorized as LP/P variants in at least one paralogue of hTRPM4. We further used the cryo-EM structure of hTRPM4 to find scores of contact pairs between parental (wild type) residues of VUSs for which ClinPred predicts a high probability of pathogenicity of variants for both contact partners. We propose that 68 respective missense VUSs are also likely pathogenic variants.

CONCLUSIONS

ClinPred outperformed other in-silico tools in predicting damaging variants of TRP channels. ClinPred, the paralogue annotation method, and analysis of residue contacts the hTRPM4 cryo-EM structure collectively suggest pathogenicity of 80 TRPM4 VUSs.

Deep computational phenotyping of genomic variants impacting the SET domain of KMT2C reveal molecular mechanisms for their dysfunction

Introduction: Kleefstra Syndrome type 2 (KLEFS-2) is a genetic, neurodevelopmental disorder characterized by intellectual disability, infantile hypotonia, severe expressive language delay, and characteristic facial appearance, with a spectrum of other distinct clinical manifestations. Pathogenic mutations in the epigenetic modifier type 2 lysine methyltransferase KMT2C have been identified to be causative in KLEFS-2 individuals. Methods: This work reports a translational genomic study that applies a multidimensional computational approach for deep variant phenotyping, combining conventional genomic analyses, advanced protein bioinformatics, computational biophysics, biochemistry, and biostatistics-based modeling. We use standard variant annotation, paralog annotation analyses, molecular mechanics, and molecular dynamics simulations to evaluate damaging scores and provide potential mechanisms underlying KMT2C variant dysfunction. Results: We integrated data derived from the structure and dynamics of KMT2C to classify variants into SV (Structural Variant), DV (Dynamic Variant), SDV (Structural and Dynamic Variant), and VUS (Variant of Uncertain Significance). When compared with controls, these variants show values reflecting alterations in molecular fitness in both structure and dynamics. Discussion: We demonstrate that our 3D models for KMT2C variants suggest distinct mechanisms that lead to their imbalance and are not predictable from sequence alone. Thus, the missense variants studied here cause destabilizing effects on KMT2C function by different biophysical and biochemical mechanisms which we adeptly describe. This new knowledge extends our understanding of how variations in the KMT2C gene cause the dysfunction of its methyltransferase enzyme product, thereby bearing significant biomedical relevance for carriers of KLEFS2-associated genomic mutations.

Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K+ channels: Validation with hERG

Loss of function (LOF) mutations of voltage sensitive K+ channel proteins hERG (Kv11.1) and KCNQ1 (Kv7.1) account for the majority of instances of congenital Long QT Syndrome (cLQTS) with the dominant molecular phenotype being a mistrafficking one resulting from protein misfolding. We explored the use of Evolutionary Coupling (EC) analysis, which identifies evolutionarily conserved pairwise amino acid interactions that may contribute to protein structural stability, to identify regions of the channels susceptible to misfolding mutations. Comparison with published experimental trafficking data for hERG and KCNQ1 showed that the method strongly predicts "scaffolding" regions of the channel membrane domains and has useful predictive power for trafficking phenotypes of individual variants. We identified a region in and around the cytoplasmic S2-S3 loop of the hERG Voltage Sensor Domain (VSD) as susceptible to destabilising mutation, and this was confirmed using a quantitative LI-COR ® based trafficking assay that showed severely attenuated trafficking in eight out of 10 natural hERG VSD variants selected using EC analysis. Our analysis highlights an equivalence in the scaffolding structures of the hERG and KCNQ1 membrane domains. Pathogenic variants of ion channels with an underlying mistrafficking phenotype are likely to be located within similar scaffolding structures that are identifiable by EC analysis.

How Functional Genomics Can Keep Pace With VUS Identification

Over the last two decades, an exponentially expanding number of genetic variants have been identified associated with inherited cardiac conditions. These tremendous gains also present challenges in deciphering the clinical relevance of unclassified variants or variants of uncertain significance (VUS). This review provides an overview of the advancements (and challenges) in functional and computational approaches to characterize variants and help keep pace with VUS identification related to inherited heart diseases.

Genome-wide association analyses identify new Brugada syndrome risk loci and highlight a new mechanism of sodium channel regulation in disease susceptibility

Brugada syndrome (BrS) is a cardiac arrhythmia disorder associated with sudden death in young adults. With the exception of SCN5A, encoding the cardiac sodium channel Na_V1.5, susceptibility genes remain largely unknown. Here we performed a genome-wide association meta-analysis comprising 2,820 unrelated cases with BrS and 10,001 controls, and identified 21 association signals at 12 loci (10 new). Single nucleotide polymorphism (SNP)-heritability estimates indicate a strong polygenic influence. Polygenic risk score analyses based on the 21 susceptibility variants demonstrate varying cumulative contribution of common risk alleles among different patient subgroups, as well as genetic associations with cardiac electrical traits and disorders in the general population. The predominance of cardiac transcription factor loci indicates that transcriptional regulation is a key feature of BrS pathogenesis. Furthermore, functional studies conducted on MAPRE2, encoding the microtubule plus-end binding protein EB2, point to microtubule-related trafficking effects on Na_V1.5 expression as a new underlying molecular mechanism. Taken together, these findings broaden our understanding of the genetic architecture of BrS and provide new insights into its molecular underpinnings.

Intersegment Contacts of Potentially Damaging Variants of Cardiac Sodium Channel

Over 1,500 missense variants of sodium channel hNav1.5, which are reported in the ClinVar database, are associated with cardiac diseases. For most of the variants, the clinical significance is uncertain (VUS), not provided (NP), or has conflicting interpretations of pathogenicity (CIP). Reclassifying these variants as pathogenic/likely pathogenic (P/LP) variants is important for diagnosing genotyped patients. In our earlier work, several bioinformatics tools and paralogue annotation method consensually predicted that 74 VUS/NP/CIP variants of 54 wild type residues (set w54) are potentially damaging variants (PDVs). Atomic mechanisms underlying dysfunction of the PDVs are unknown. Here we employed a recent cryo-EM structure of the hNav1.5 channel with likely inactivated pore domain (PD) and activated voltage-sensing domains (VSDs), and ad hoc models of the closed and open PD and resting VSDs to explore intersegment contacts of w54 residues. We found that 44 residues from set w54 contact 84 residues with 118 disease missense variants. These include 104 VUS/NP/CIP variants, most of which are associated with the loss-of-function Brugada syndrome (BrS1) or gain-of-function long QT syndrome (LQT3). Matrix representation of the PDVs and their contact variants facilitated recognition of coupled mutations associated with the same disease. In particular, BrS1-associated coupled mutations, which disturb the P-loops region with the selectivity filter slow inactivation gate, would cause the channel dysfunction. Other likely causes of the channel dysfunction include coupled BrS1-associated variants within VSDs that would destabilize their activated states and coupled LQT3-associated variants, which would stabilize the open PD or activated VSDs. Our study proposes mechanisms of channel dysfunction for scores of BrS1- and LQT3-associated variants, confirms status for 82% of PDVs, and suggests damaging status for their contact variants, which are currently categorized as VUS/NP/CIP variants.

PIC-Me: paralogs and isoforms classifier based on machine-learning approaches

Background

Paralogs formed through gene duplication and isoforms formed through alternative splicing have been important processes for increasing protein diversity and maintaining cellular homeostasis. Despite their recognized importance and the advent of large-scale genomic and transcriptomic analyses, paradoxically, accurate annotations of all gene loci to allow the identification of paralogs and isoforms remain surprisingly incomplete. In particular, the global analysis of the transcriptome of a non-model organism for which there is no reference genome is especially challenging.

Results

To reliably discriminate between the paralogs and isoforms in RNA-seq data, we redefined the pre-existing sequence features (sequence similarity, inverse count of consecutive identical or non-identical blocks, and match-mismatch fraction) previously derived from full-length cDNAs and EST sequences and described newly discovered genomic and transcriptomic features (twilight zone of protein sequence alignment and expression level difference). In addition, the effectiveness and relevance of the proposed features were verified with two widely used support vector machine (SVM) and random forest (RF) models. From nine RNA-seq datasets, all AUC (area under the curve) scores of ROC (receiver operating characteristic) curves were over 0.9 in the RF model and significantly higher than those in the SVM model.

Conclusions

In this study, using an RF model with five proposed RNA-seq features, we implemented our method called Paralogs and Isoforms Classifier based on Machine-learning approaches (PIC-Me) and showed that it outperformed an existing method. Finally, we envision that our tool will be a valuable computational resource for the genomics community to help with gene annotation and will aid in comparative transcriptomics and evolutionary genomics studies, especially those on non-model organisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04229-x.

L-Type Calcium Channel: Predicting Pathogenic/Likely Pathogenic Status for Variants of Uncertain Clinical Significance

(1) Background: Defects in gene CACNA1C, which encodes the pore-forming subunit of the human Cav1.2 channel (hCav1.2), are associated with cardiac disorders such as atrial fibrillation, long QT syndrome, conduction disorders, cardiomyopathies, and congenital heart defects. Clinical manifestations are known only for 12% of CACNA1C missense variants, which are listed in public databases. Bioinformatics approaches can be used to predict the pathogenic/likely pathogenic status for variants of uncertain clinical significance. Choosing a bioinformatics tool and pathogenicity threshold that are optimal for specific protein families increases the reliability of such predictions. (2) Methods and Results: We used databases ClinVar, Humsavar, gnomAD, and Ensembl to compose a dataset of pathogenic/likely pathogenic and benign variants of hCav1.2 and its 20 paralogues: voltage-gated sodium and calcium channels. We further tested the performance of sixteen in silico tools in predicting pathogenic variants. ClinPred demonstrated the best performance, followed by REVEL and MCap. In the subset of 309 uncharacterized variants of hCav1.2, ClinPred predicted the pathogenicity for 188 variants. Among these, 36 variants were also categorized as pathogenic/likely pathogenic in at least one paralogue of hCav1.2. (3) Conclusions: The bioinformatics tool ClinPred and the paralogue annotation method consensually predicted the pathogenic/likely pathogenic status for 36 uncharacterized variants of hCav1.2. An analogous approach can be used to classify missense variants of other calcium channels and novel variants of hCav1.2.

P2T2: Protein Panoramic annoTation Tool for the interpretation of protein coding genetic variants

MOTIVATION

Genomic data are prevalent, leading to frequent encounters with uninterpreted variants or mutations with unknown mechanisms of effect. Researchers must manually aggregate data from multiple sources and across related proteins, mentally translating effects between the genome and proteome, to attempt to understand mechanisms.

MATERIALS AND METHODS

P2T2 presents diverse data and annotation types in a unified protein-centric view, facilitating the interpretation of coding variants and hypothesis generation. Information from primary sequence, domain, motif, and structural levels are presented and also organized into the first Paralog Annotation Analysis across the human proteome.

RESULTS

Our tool assists research efforts to interpret genomic variation by aggregating diverse, relevant, and proteome-wide information into a unified interactive web-based interface. Additionally, we provide a REST API enabling automated data queries, or repurposing data for other studies.

CONCLUSION

The unified protein-centric interface presented in P2T2 will help researchers interpret novel variants identified through next-generation sequencing. Code and server link available at github.com/GenomicInterpretation/p2t2.

SLC35A2-CDG: Novel variant and review

SLC35A2 encodes the X-linked transporter that carries uridine diphosphate (UDP)-galactose from the cytosol to the lumen of the Golgi apparatus and the endoplasmic reticulum. Pathogenic variants have been associated to a congenital disorder of glycosylation (CDG) with epileptic encephalopathy as a predominant feature. Among the sixty five patients described so far, a strong gender bias is observed as only seven patients are males. This work is a review and reports a SLC35A2-CDG in a male without epilepsy and with growth deficiency associated with decreased serum IGF1, minor neurological involvement, minor facial dysmorphism, and camptodactyly of fingers and toes. Sequence analysis revealed a hemizygosity for a novel de novo variant: c.233A > G (p.Lys78Arg) in SLC35A2. Further analysis of SLC35A2 sequence by comparing both orthologous and paralogous positions, revealed that not only the variant found in this study, but also most of the reported mutated positions are conserved in SLC35A2 orthologous, and many even in the paralogous SLC35A1 and SLC35A3. This is strong evidence that replacements at these positions will have a critical pathological effect and may also explain the gender bias observed among SLC35A2-CDG patients.

The central domain of cardiac ryanodine receptor governs channel activation, regulation, and stability

Structural analyses identified the central domain of ryanodine receptor (RyR) as a transducer converting conformational changes in the cytoplasmic platform to the RyR gate. The central domain is also a regulatory hub encompassing the Ca²⁺-, ATP-, and caffeine-binding sites. However, the role of the central domain in RyR activation and regulation has yet to be defined. Here, we mutated five residues that form the Ca²⁺ activation site and 10 residues with negatively charged or oxygen-containing side chains near the Ca²⁺ activation site. We also generated eight disease-associated mutations within the central domain of RyR2. We determined the effect of these mutations on Ca²⁺, ATP, and caffeine activation and Mg²⁺ inhibition of RyR2. Mutating the Ca²⁺ activation site markedly reduced the sensitivity of RyR2 to Ca²⁺ and caffeine activation. Unexpectedly, Ca²⁺ activation site mutation E3848A substantially enhanced the Ca²⁺-independent basal activity of RyR2, suggesting that E3848A may also affect the stability of the closed state of RyR2. Mutations in the Ca²⁺ activation site also abolished the effect of ATP/caffeine on the Ca²⁺-independent basal activity, suggesting that the Ca²⁺ activation site is also a critical determinant of ATP/caffeine action. Mutating residues with negatively charged or oxygen-containing side chains near the Ca²⁺ activation site significantly altered Ca²⁺ and caffeine activation and reduced Mg²⁺ inhibition. Furthermore, disease-associated RyR2 mutations within the central domain significantly enhanced Ca²⁺ and caffeine activation and reduced Mg²⁺ inhibition. Our data demonstrate that the central domain plays an important role in channel activation, channel regulation, and closed state stability.

Predicting functional effects of missense variants in voltage-gated sodium and calcium channels

Malfunctions of voltage-gated sodium and calcium channels (encoded by SCNxA and CACNA1x family genes, respectively) have been associated with severe neurologic, psychiatric, cardiac, and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) that often corresponds not only to clinical disease manifestations but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. On the basis of known gene-disease mechanisms of 19 different diseases, we inferred LOF (n = 518) and GOF (n = 309) likely pathogenic variants from the disease phenotypes of variant carriers. By training a machine learning model on sequence- and structure-based features, we predicted LOF or GOF effects [area under the receiver operating characteristics curve (ROC) = 0.85] of likely pathogenic missense variants. Our LOF versus GOF prediction corresponded to molecular LOF versus GOF effects for 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and was validated in exome-wide data from 21,703 cases and 128,957 controls. We showed respective regional clustering of inferred LOF and GOF nucleotide variants across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCNxA/CACNA1x family genes.

Role of the voltage sensor module in Nav domain IV on fast inactivation in sodium channelopathies: The implication of closed-state inactivation

The segment 4 (S4) voltage sensor in voltage-gated sodium channels (Na_vs) have domain-specific functions, and the S4 segment in domain DIV (DIVS4) plays a key role in the activation and fast inactivation processes through the coupling of arginine residues in DIVS4 with residues of putative gating charge transfer center (pGCTC) in DIVS1-3. In addition, the first four arginine residues (R1-R4) in Na_v DIVS4 have position-specific functions in the fast inactivation process, and mutations in these residues are associated with diverse phenotypes of Na_v-related diseases (sodium channelopathies). R1 and R2 mutations commonly display a delayed fast inactivation, causing a gain-of-function, whereas R3 and R4 mutations commonly display a delayed recovery from inactivation and profound use-dependent current attenuation, causing a severe loss-of-function. In contrast, mutations of residues of pGCTC in Na_v DIVS1-3 can also alter fast inactivation. Such alterations in fast inactivation may be caused by disrupted interactions of DIVS4 with DIVS1-3. Despite fast inactivation of Na_vs occurs from both the open-state (open-state inactivation; OSI) and closed state (closed-state inactivation; CSI), changes in CSI have received considerably less attention than those in OSI in the pathophysiology of sodium channelopathies. CSI can be altered by mutations of arginine residues in DIVS4 and residues of pGCTC in Na_vs, and altered CSI can be an underlying primary biophysical defect of sodium channelopathies. Therefore, CSI should receive focus in order to clarify the pathophysiology of sodium channelopathies.

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

BACKGROUND

Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs.

METHODS

Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families.

RESULTS

We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint.

CONCLUSION

This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes.

Variant filtering, digenic variants, and other challenges in clinical sequencing: a lesson from fibrillinopathies

Genome-scale high-throughput sequencing enables the detection of unprecedented numbers of sequence variants. Variant filtering and interpretation are facilitated by mutation databases, in silico tools, and population-based reference datasets such as ExAC/gnomAD, while variants are classified using the ACMG/AMP guidelines. These methods, however, pose clinically relevant challenges. We queried the gnomAD dataset for (likely) pathogenic variants in genes causing autosomal-dominant disorders. Furthermore, focusing on the fibrillinopathies Marfan syndrome (MFS) and congenital contractural arachnodactyly (CCA), we screened 500 genomes of our patients for co-occurring variants in FBN1 and FBN2. In gnomAD, we detected 2653 (likely) pathogenic variants in 253 genes associated with autosomal-dominant disorders, enabling the estimation of variant-filtering thresholds and disease predisposition/prevalence rates. In our database, we discovered two families with hitherto unreported co-occurrence of FBN1/FBN2 variants causing phenotypes with mixed or modified MFS/CCA clinical features. We show that (likely) pathogenic gnomAD variants may be more frequent than expected and are challenging to classify according to the ACMG/AMP guidelines as well as that fibrillinopathies are likely underdiagnosed and may co-occur. Consequently, selection of appropriate frequency cutoffs, recognition of digenic variants, and variant classification represent considerable challenges in variant interpretation. Neglecting these challenges may lead to incomplete or missed diagnoses.

Identification of pathogenic variant enriched regions across genes and gene families

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene-family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2871 gene-family protein sequence alignments involving 9990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 76,153 missense variants from patients. With this gene-family approach, we identified 465 regions enriched for patient variants spanning 41,463 amino acids in 1252 genes. As a comparison, by testing the same genes individually, we identified fewer patient variant enriched regions, involving only 2639 amino acids and 215 genes. Next, we selected de novo variants from 6753 patients with neurodevelopmental disorders and 1911 unaffected siblings and observed an 8.33-fold enrichment of patient variants in our identified regions (95% C.I. = 3.90-Inf, P-value = 2.72 × 10-11). By using the complete ClinVar variant set, we found that missense variants inside the identified regions are 106-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 106.15, 95% C.I = 70.66-Inf, P-value < 2.2 × 10-16). All pathogenic variant enriched regions (PERs) identified are available online through "PER viewer," a user-friendly online platform for interactive data mining, visualization, and download. In summary, our gene-family burden analysis approach identified novel PERs in protein sequences. This annotation can empower variant interpretation.

Sequence analysis of 37 candidate genes for male infertility: challenges in variant assessment and validating genes

BACKGROUND

The routine genetic analysis for diagnosing male infertility has not changed over the last twenty years, and currently available tests can only determine the etiology of 4% of unselected infertile patients. Thus, to create new diagnostic assays, we must better understand the molecular and genetic mechanisms of male infertility. Although next-generation sequencing allows for simultaneous analysis of hundreds of genes and the discovery of novel candidates related to male infertility, so far only a few gene candidates have enough sound evidence to support the gene-disease relationship.

OBJECTIVE

Since complementary studies are required to validate genes, we aimed to analyze the presence of potentially pathogenic rare variants in a set of candidate genes related to azoospermia in a hitherto understudied South American population.

SUBJECTS AND METHODS

We performed whole exome sequencing in a group of 16 patients with non-obstructive azoospermia from Ribeirão Preto, Brazil. Based on a recent systematic review of monogenic causes of male infertility, we selected a set of 37 genes related to azoospermia, Sertoli-Cell-Only histology, and spermatogenic arrest to analyze. The identified variants were confirmed by Sanger sequencing, and their functional consequence was predicted by in silico programs.

RESULTS

We identified potential pathogenic variants in seven genes in six patients. Two variants, c.671A>G (p.(Asn224Ser)) in DMRT1 and c.91C>T (p.(Arg31Cys)) in REC8, have already been described in association with azoospermia. We also found new variants in genes that already have moderate evidence of being linked to spermatogenic failure (TEX15, KLHL10), in genes with limited evidence (DNMT3B, TEX14) and in one novel promising candidate gene that has no evidence so far (SYCE1L).

DISCUSSION

Although this study included a small number of patients, the process of rationally selecting genes allowed us to detect rare potentially pathogenic variants, providing supporting evidence for validating candidate genes associated with azoospermia.

Yield of the RYR2 Genetic Test in Suspected Catecholaminergic Polymorphic Ventricular Tachycardia and Implications for Test Interpretation

BACKGROUND

Pathogenic RYR2 variants account for ≈60% of clinically definite cases of catecholaminergic polymorphic ventricular tachycardia. However, the rate of rare benign RYR2 variants identified in the general population remains a challenge for genetic test interpretation. Therefore, we examined the results of the RYR2 genetic test among patients referred for commercial genetic testing and examined factors impacting variant interpretability.

METHODS

Frequency and location comparisons were made for RYR2 variants identified among 1355 total patients of varying clinical certainty and 60 706 Exome Aggregation Consortium controls. The impact of the clinical phenotype on the yield of RYR2 variants was examined. Six in silico tools were assessed using patient- and control-derived variants.

RESULTS

A total of 18.2% (218/1200) of patients referred for commercial testing hosted rare RYR2 variants, statistically less than the 59% (46/78) yield among clinically definite cases, resulting in a much higher potential genetic false discovery rate among referrals considering the 3.2% background rate of rare, benign RYR2 variants. Exclusion of clearly putative pathogenic variants further complicates the interpretation of the next novel RYR2 variant. Exonic/topologic analyses revealed overrepresentation of patient variants in exons covering only one third of the protein. In silico tools largely failed to show evidence toward enhancement of variant interpretation.

CONCLUSIONS

Current expert recommendations have resulted in increased use of RYR2 genetic testing in patients with questionable clinical phenotypes. Using the largest to date catecholaminergic polymorphic ventricular tachycardia patient versus control comparison, this study highlights important variables in the interpretation of variants to overcome the 3.2% background rate that confounds RYR2 variant interpretation.

Multifactorial Origin of Exertional Rhabdomyolysis, Recurrent Hematuria, and Episodic Pain in a Service Member with Sickle Cell Trait

Individuals with Sickle Cell Trait (SCT), generally considered a benign carrier state of hemoglobin S (HbAS), are thought to be at risk for exertional rhabdomyolysis and hematuria, conditions that can also be caused by various other acquired and inherited factors. We report an SCT positive service member with an exertional rhabdomyolysis event, recurrent hematuria with transient proteinuria, and episodic burning pain in the lower extremities. Clinical and genetic studies revealed the multifactorial nature of his complex phenotype. The service member was taking prescription medications known to be associated with exertional rhabdomyolysis. He carried a pathogenic mutation, NPHS2 p.V260E, reported in nephropathy and a new variant p.R838Q in SCN11A, a gene involved in familial episodic pain syndrome. Results suggest that drug-to-drug interactions coupled with the stress of exercise, coinheritance of HbAS and NPHS2 p.V260E, and p. R838Q in SCN11A contributed to exertional rhabdomyolysis, recurrent hematuria with proteinuria, and episodic pain, respectively. This case underscores the importance of comprehensive clinical and genetic evaluations to identify underlying causes of health complications reported in SCT individuals.

Predicting changes to INa from missense mutations in human SCN5A

Mutations in SCN5A can alter the cardiac sodium current I_Na and increase the risk of potentially lethal conditions such as Brugada and long-QT syndromes. The relation between mutations and their clinical phenotypes is complex, and systems to predict clinical severity of unclassified SCN5A variants perform poorly. We investigated if instead we could predict changes to I_Na, leaving the link from I_Na to clinical phenotype for mechanistic simulation studies. An exhaustive list of nonsynonymous missense mutations and resulting changes to I_Na was compiled. We then applied machine-learning methods to this dataset, and found that changes to I_Na could be predicted with higher sensitivity and specificity than most existing predictors of clinical significance. The substituted residues’ location on the protein correlated with channel function and strongly contributed to predictions, while conservedness and physico-chemical properties did not. However, predictions were not sufficiently accurate to form a basis for mechanistic studies. These results show that changes to I_Na, the mechanism through which SCN5A mutations create cardiac risk, are already difficult to predict using purely in-silico methods. This partly explains the limited success of systems to predict clinical significance of SCN5A variants, and underscores the need for functional studies of I_Na in risk assessment.

A homozygous SCN5A mutation associated with atrial standstill and sudden death

BACKGROUND

Atrial standstill is an arrhythmogenic condition characterized by the absence of spontaneous electrical and mechanical atrial activity or in response to stimulation. There are few reported familial cases which have been associated with SCN5A mutations cosegregating with GJA5 or RYR2; however, isolated SCN5A mutations are rare.

OBJECTIVE

The purpose of this study was to determine the clinical and biophysical consequence of a novel SCN5A mutation identified in a family with progressive atrial standstill and sudden death.

METHODS

The family of a sporadic case of congenital atrial standstill underwent genetic screening. Human Embryonic Kidney 293 cells were transfected with wild-type (WT) or mutant SCN5A cDNAs. Biophysical properties were studied using whole-cell using patch clamp methods.

RESULTS

A novel homozygous SCN5A mutation, p.V1340L, was identified in the proband and her sister. The proband had complete atrial standstill whereas the sister had partial atrial standstill. Heterozygous mutations were identified in the mother, father, and brother. All three had normal sinus rhythm and were asymptomatic. The mutant Nav1.5(V1340L) reduced Nav1.5 current density as well as showed a depolarizing shift in the voltage-dependent steady-state activation (WT: -35.3 ± 1.62 mV; V1340L: -22.4 ± 2.59 mV; P  =  0.001).

CONCLUSIONS

A homozygous loss-of-function SCN5A mutation likely results in atrial standstill and sudden death due to suppression of initiation of action potential.

Genetic analysis of sick sinus syndrome in a family harboring compound CACNA1C and TTN mutations

Sick sinus syndrome (SSS) is a sinus node dysfunction characterized by severe sinus bradycardia. SSS results in insufficient blood supply to the brain, heart, kidneys, and other organs and is associated with the increased risk of sudden cardiac death. Bradyarrhythmia appears in the absence of any associated cardiac pathology and displays a genetic legacy. The present study identified a family with primary manifestation of sinus bradycardia (five individuals) along with early repolarization (four individuals) and atrial fibrillation (one individual). Targeted exome sequencing was used to screen exons and adjacent splice sites of 61 inherited arrhythmia‑associated genes, to detect pathogenic genes and variant sites in the proband. Family members were sequenced by Sanger sequencing and protein functions predicted by Polyphen‑2 software. A total of three rare variants were identified in the family, including two missense variants in calcium voltage‑gated channel subunit alpha1 C (CACNA1C) (gi:193788541, NM_001129843), c.1786G>A (p.V596M) and c.5344G>A (p.A1782T), and one missense variant in titin (TTN) c.49415G>A (p.R16472H) (gi:291045222, NM_003319). The variants p.V596M and p.R16472H were predicted to be deleterious and resulted in alterations in the amino acid type and sequence of the polypeptide chain, which may partially or completely inactivate the encoded protein. The comparison of literature, gene database, and pedigree phenotype analysis suggests that p.V596M or p.R16472H variants are pathogenic. The complex overlapping variants at three loci lead to a more severe phenotype in the proband, and may increase the susceptibility of individuals to atrial fibrillation. The simultaneous occurrence of V596M and R16472H may increase the severity of early repolarization. Various family members may have carried heterozygous mutants of p.A1782T and p.R16472H due to genetic heterogeneity, however did not exhibit clinical signs of cardiac electrophysiological alterations, potentially attributable to the low vagal tone. To the best of the author's knowledge, this is the first study to suggest the involvement of the novel missense CACNA1C c.1786G>A and TTN c.49415G>A variants in the inheritance of symptomatic bradycardia and development of SSS.

CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation

PURPOSE

Internationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier ( http://www.cardioclassifier.org ), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).

METHODS

CardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.

RESULTS

We benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher's P = 1.1  ×  10^-18), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.

CONCLUSION

CardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.

Functional characterization of a GFAP variant of uncertain significance in an Alexander disease case within the setting of an individualized medicine clinic

A de novo GFAP variant, p.R376W, was identified in a child presenting with hypotonia, developmental delay, and abnormal brain MRI. Following the 2015 ACMG variant classification guidelines and the functional studies showing protein aggregate formation in vitro, p.R376W should be classified as a pathogenic variant, causative for Alexander disease.

Physiological and Pathophysiological Insights of Nav1.4 and Nav1.5 Comparison

Mutations in Nav1.4 and Nav1.5 α-subunits have been associated with muscular and cardiac channelopathies, respectively. Despite intense research on the structure and function of these channels, a lot of information is still missing to delineate the various physiological and pathophysiological processes underlying their activity at the molecular level. Nav1.4 and Nav1.5 sequences are similar, suggesting structural and functional homologies between the two orthologous channels. This also suggests that any characteristics described for one channel subunit may shed light on the properties of the counterpart channel subunit. In this review article, after a brief clinical description of the muscular and cardiac channelopathies related to Nav1.4 and Nav1.5 mutations, respectively, we compare the knowledge accumulated in different aspects of the expression and function of Nav1.4 and Nav1.5 α-subunits: the regulation of the two encoding genes (SCN4A and SCN5A), the associated/regulatory proteins and at last, the functional effect of the same missense mutations detected in Nav1.4 and Nav1.5. First, it appears that more is known on Nav1.5 expression and accessory proteins. Because of the high homologies of Nav1.5 binding sites and equivalent Nav1.4 sites, Nav1.5-related results may guide future investigations on Nav1.4. Second, the analysis of the same missense mutations in Nav1.4 and Nav1.5 revealed intriguing similarities regarding their effects on membrane excitability and alteration in channel biophysics. We believe that such comparison may bring new cues to the physiopathology of cardiac and muscular diseases.

SCN4A pore mutation pathogenetically contributes to autosomal dominant essential tremor and may increase susceptibility to epilepsy

Essential tremor (ET) is the most prevalent movement disorder, affecting millions of people in the USA. Although a positive family history is one of the most important risk factors for ET, the genetic causes of ET remain unknown. In an attempt to identify genetic causes for ET, we performed whole-exome sequencing analyses in a large Spanish family with ET, in which two patients also developed epilepsy. To further assess pathogenicity, site-directed mutagenesis, mouse and human brain expression analyses, and patch clamp techniques were performed. A disease-segregating mutation (p.Gly1537Ser) in the SCN4A gene was identified. Posterior functional analyses demonstrated that more rapid kinetics at near-threshold potentials altered ion selectivity and facilitated the conductance of both potassium and ammonium ions, which could contribute to tremor and increase susceptibility to epilepsy, respectively. In this report, for the first time, we associated the genetic variability of SCN4A with the development of essential tremor, which adds ET to the growing list of neurological channelopathies.

Massive parallel sequencing applied to the molecular autopsy in sudden cardiac death in the young

Sudden cardiac death in the young is a very traumatic event that occurs often in apparently healthy individuals without an explainable cause of death after a comprehensive medico-legal investigation. Knowledge about the pathologies with a risk of sudden death is increasingly showing a greater underlying genetic heterogeneity, which provides one of the main handicaps for molecular autopsy. On the other hand the enormous technological advances in sequencing technologies, allow us to analyse as many genes as we want at a cost increasingly reduced. The sum of these two factors (increased knowledge of genetics and available technologies) allow us to make an individualized study of the causes of sudden cardiac death in young adults, through massive sequencing of all potential genes involved in the process. We define this approach as massive genomic autopsy, and with this review we will try to explain the possible scenarios and methods available for its implementation.

Enhanced Classification of Brugada Syndrome-Associated and Long-QT Syndrome-Associated Genetic Variants in the SCN5A-Encoded Na(v)1.5 Cardiac Sodium Channel

BACKGROUND

A 2% to 5% background rate of rare SCN5A nonsynonymous single nucleotide variants (nsSNVs) among healthy individuals confounds clinical genetic testing. Therefore, the purpose of this study was to enhance interpretation of SCN5A nsSNVs for clinical genetic testing using estimated predictive values derived from protein-topology and 7 in silico tools.

METHODS AND RESULTS

Seven in silico tools were used to assign pathogenic/benign status to nsSNVs from 2888 long-QT syndrome cases, 2111 Brugada syndrome cases, and 8975 controls. Estimated predictive values were determined for each tool across the entire SCN5A-encoded Na(v)1.5 channel as well as for specific topographical regions. In addition, the in silico tools were assessed for their ability to correlate with cellular electrophysiology studies. In long-QT syndrome, transmembrane segments S3-S5+S6 and the DIII/DIV linker region were associated with high probability of pathogenicity. For Brugada syndrome, only the transmembrane spanning domains had a high probability of pathogenicity. Although individual tools distinguished case- and control-derived SCN5A nsSNVs, the composite use of multiple tools resulted in the greatest enhancement of interpretation. The use of the composite score allowed for enhanced interpretation for nsSNVs outside of the topological regions that intrinsically had a high probability of pathogenicity, as well as within the transmembrane spanning domains for Brugada syndrome nsSNVs.

CONCLUSIONS

We have used a large case/control study to identify regions of Na(v)1.5 associated with a high probability of pathogenicity. Although topology alone would leave the variants outside these identified regions in genetic purgatory, the synergistic use of multiple in silico tools may help promote or demote a variant's pathogenic status.