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The burden of splice-disrupting variants in inherited heart disease and unexplained sudden cardiac death.

ABSTRACT: There is an incomplete understanding of the burden of splice-disrupting variants in definitively associated inherited heart disease genes and whether these genes can amplify from blood RNA to support functional confirmation of splicing outcomes. We performed burden testing of rare splice-disrupting variants in people with inherited heart disease and sudden unexplained death compared to 125,748 population controls. ClinGen definitively disease-associated inherited heart disease genes were amplified using RNA extracted from fresh blood, derived cardiomyocytes, and myectomy tissue. Variants were functionally assessed and classified for pathogenicity. We found 88 in silico-predicted splice-disrupting variants in 128 out of 1242 (10.3%) unrelated participants. There was an excess burden of splice-disrupting variants in PKP2 (5.9%), FLNC (2.7%), TTN (2.8%), MYBPC3 (8.2%) and MYH7 (1.3%), in distinct cardiomyopathy subtypes, and KCNQ1 (3.6%) in long QT syndrome. Blood RNA supported the amplification of 21 out of 31 definitive disease-associated inherited heart disease genes. Our functional studies confirmed altered splicing in six variants. Eleven variants of uncertain significance were reclassified as likely pathogenic based on functional studies and six were used for cascade genetic testing in 12 family members. Our study highlights that splice-disrupting variants are a significant cause of inherited heart disease, and that analysis of blood RNA confirms splicing outcomes and supports variant pathogenicity classification.

SUBMITTER: Singer ES

PROVIDER: S-EPMC10567745 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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The burden of splice-disrupting variants in inherited heart disease and unexplained sudden cardiac death.

Singer Emma S ES Crowe Joshua J Holliday Mira M Isbister Julia C JC Lal Sean S Nowak Natalie N Yeates Laura L Burns Charlotte C Rajagopalan Sulekha S Macciocca Ivan I King Ingrid I Wacker Julie J Ingles Jodie J Weintraub Robert G RG Semsarian Christopher C Bagnall Richard D RD

NPJ genomic medicine 20231011 1

There is an incomplete understanding of the burden of splice-disrupting variants in definitively associated inherited heart disease genes and whether these genes can amplify from blood RNA to support functional confirmation of splicing outcomes. We performed burden testing of rare splice-disrupting variants in people with inherited heart disease and sudden unexplained death compared to 125,748 population controls. ClinGen definitively disease-associated inherited heart disease genes were amplifi ...[more]

PMID: 37821546

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Project description:ImportanceUnexplained sudden cardiac death (SCD) describes SCD with no cause identified. Genetic testing helps to diagnose inherited cardiac diseases in unexplained SCD; however, the associations between pathogenic or likely pathogenic (P/LP) variants of inherited cardiomyopathies (CMs) and arrhythmia syndromes and the risk of unexplained SCD in both White and African American adults living the United States has never been systematically examined.ObjectiveTo investigate cases of unexplained SCD to determine the frequency of P/LP genetic variants of inherited CMs and arrhythmia syndromes.Design, setting, and participantsThis genetic association study included 683 African American and White adults who died of unexplained SCD and were included in an autopsy registry. Overall, 413 individuals had DNA of acceptable quality for genetic sequencing. Data were collected from January 1995 to December 2015. A total of 30 CM genes and 38 arrhythmia genes were sequenced, and variants in these genes, curated as P/LP, were examined to study their frequency. Data analysis was performed from June 2018 to March 2021.Main outcomes and measuresThe frequency of P/LP variants for CM or arrhythmia in individuals with unexplained SCD.ResultsThe median (interquartile range) age at death of the 413 included individuals was 41 (29-48) years, 259 (62.7%) were men, and 208 (50.4%) were African American adults. A total of 76 patients (18.4%) with unexplained SCD carried variants considered P/LP for CM and arrhythmia genes. In total, 52 patients (12.6%) had 49 P/LP variants for CM, 22 (5.3%) carried 23 P/LP variants for arrhythmia, and 2 (0.5%) had P/LP variants for both CM and arrhythmia. Overall, 41 P/LP variants for hypertrophic CM were found in 45 patients (10.9%), 9 P/LP variants for dilated CM were found in 11 patients (2.7%), and 10 P/LP variants for long QT syndrome were found in 11 patients (2.7%). No significant difference was found in clinical and heart characteristics between individuals with or without P/LP variants. African American and White patients were equally likely to harbor P/LP variants.Conclusions and relevanceIn this large genetic association study of community cases of unexplained SCD, nearly 20% of patients carried P/LP variants, suggesting that genetics may contribute to a significant number of cases of unexplained SCD. Our findings regarding both the association of unexplained SCD with CM genes and race-specific genetic variants suggest new avenues of study for this poorly understood entity.

Project description:BackgroundSudden unexplained death (SUD) is a devastating event in the young. Despite efforts to identify causal genetic variants, many cases remain unexplained after genetic screening. This study aimed to investigate an alternative potential contributor to SUD by studying the human methylome using the MethylationEPIC v2.0 BeadChip kit in heart tissue from SUD cases. The genome-wide methylation results of the SUD cases were compared to the results of a control cohort. The SUD cases were divided into three main groups based on their autopsy reports, heart morphology and histopathology (primaryN: macroscopically and histologically normal heart; primaryCM: macroscopically or histologically abnormal heart, suspected cardiomyopathies; and secondary: myocardial damage due to other underlying conditions). The main focus of this study was to identify differentially methylated regions (DMRs) between the case groups and the control cohort.ResultsWe identified DMRs for both the primaryN and primaryCM groups, whereas the secondary group yielded no such results. In the primaryN cases, the corresponding genes for each DMR led to the identification of genes with common biological pathways. Some were associated with heart morphology (e.g. heart outflow tract morphogenesis or trabecular morphogenesis), but the majority belonged to more general cellular regulatory pathways (e.g. transcription coactivator activity, long non-coding RNAs, etc.). Although no common pathways were found for the primaryCM group, some common regulatory molecular functions were identified, such as p53 binding and transcription coactivator activity.ConclusionsOur study is the first to investigate the whole human methylome in heart tissue of SUD cases. We propose that there are observable differences in the methylation patterns of the case groups that may have contributed to SUD. Still, further studies are required to improve our understanding of the impact of methylation levels on SUD risk and to pinpoint methylation-based screening opportunities for SUD relatives.

Project description:BackgroundCongenital heart disease (CHD) is the most common congenital anomaly. Almost 90% of isolated cases have an unexplained genetic etiology after clinical testing. Non-canonical splice variants that disrupt mRNA splicing through the loss or creation of exon boundaries are not routinely captured and/or evaluated by standard clinical genetic tests. Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms.MethodsWe used genome sequencing (GS) (n = 1101 CHD probands) and myocardial RNA-Sequencing (RNA-Seq) (n = 154 CHD and n = 43 cardiomyopathy probands) to identify and validate splice disrupting variants, and to develop a heart-specific model for canonical and non-canonical splice variants that can be applied to patients with CHD and cardiomyopathy. Two thousand five hundred seventy GS samples from the Medical Genome Reference Bank were analyzed as healthy controls.ResultsOf 8583 rare DNA splice-disrupting variants initially identified using SpliceAI, 100 were associated with altered splice junctions in the corresponding patient myocardium affecting 95 genes. Using strength of myocardial gene expression and genome-wide DNA variant features that were confirmed to affect splicing in myocardial RNA, we trained a machine learning model for predicting cardiac-specific splice-disrupting variants (AUC 0.86 on internal validation). In a validation set of 48 CHD probands, the cardiac-specific model outperformed a SpliceAI model alone (AUC 0.94 vs 0.67 respectively). Application of this model to an additional 947 CHD probands with only GS data identified 1% patients with canonical and 11% patients with non-canonical splice-disrupting variants in CHD genes. Forty-nine percent of predicted splice-disrupting variants were intronic and > 10 bp from existing splice junctions. The burden of high-confidence splice-disrupting variants in CHD genes was 1.28-fold higher in CHD cases compared with healthy controls.ConclusionsA new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing.

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The burden of splice-disrupting variants in inherited heart disease and unexplained sudden cardiac death.

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The burden of splice-disrupting variants in inherited heart disease and unexplained sudden cardiac death.

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