The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young

Abstract

Background: Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing.

Methods: The SDY Case Registry is a National Institutes of Health/Centers for Disease Control and Prevention surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases < 20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015 to 2019. The cohort included 211 children (median age 0.33 year; range 0-20 years), determined to have died suddenly and unexpectedly and from whom DNA biospecimens for DNA extractions and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex- and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy, and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, pathogenic and likely pathogenic genetic variation was identified using a Bayesian-based artificial intelligence (AI) tool.

Results: The SDY cohort was 43% European, 29% African, 3% Asian, 16% Hispanic, and 9% with mixed ancestries and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy, or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, potentially damaging variants in epilepsy, cardiomyopathy, and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death.

Conclusions: While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.

Keywords: Arrhythmia; Cardiomyopathy; Epilepsy; Gene burden; Genome sequencing; Sudden death in the young.

Fig. 1

CONSORT diagram of decedents selected for genome sequencing. Phenotype data were made available by the SDY Case Registry after cause of death was determined. * Indicates the following: DUA constraints limited the sharing of detailed phenotypic data from some cases; all cases were reviewed locally and centrally by the SDY Case Registry and met inclusion criteria. These cases were considered as “Phenotype not available to include”. GS, genome sequencing

Fig. 2

Relative enrichment of GEM-damaging variants in epilepsy and Cardiomyopathy/Arrhythmia (CMAR) genes. The SDY cohort has enriched GEM-damaging (A) epilepsy and (B) cardiac gene burden compared to a sex- and ancestry-matched control cohort. Histograms (gray bars) represent distributions of GEM-damaged genes (GEM Score ≥ 0.69) sampled randomly from RefSeq genes using a root phenotype from the SDY cohort (n = 211) (bottom panels) and 1000 Genomes Project Cohort (control) matched for sex and ancestry (n = 211) (top panels). GEM-damaged genes identified in the Epilepsy (n = 191 genes, green) (A) and CMAR1 (n = 118 genes, orange) (B) gene lists were significantly different between the SDY and control cohorts (dark arrows, epilepsy, p = 0.027; cardiac p < 0.001). Light arrows represent the number of GEM-damaged genes identified in a control housekeeping gene set. (C) The results in Fig. 2A and B and Additional File 1: Figure S2 were Z-score transformed to make the gene list findings comparable. The plot reveals a considerable enrichment in both cardiac and epilepsy gene lists (+ 8.0 to + 13.0 SDs). Black line represents the expected normal distribution

Fig. 3

Number of rare, nonsynonymous, epilepsy gene variants correlated with younger age at death. The age at death was plotted against the number of rare variants (gnomAD allele frequency < 0.001) in either the A Epilepsy or B CMAR1 gene list. Number of variants in the epilepsy gene list significantly correlated with age at death, (p = 0.0053, adjusted for the first 6 principal components of ancestry). A similar analysis of rare, predicted damaging variation in the CMAR1 genes did not show association with age at death (p = 0.85, p value adjusted for ancestry). Inset is a histogram showing number of decedents < 1 year old by variant burden, box plots (black) represent decedent age distribution for each variant burden. Dark gray line = regression line of unadjusted model; dark gray shading represents 95% confidence intervals

Fig. 4

Rare VUS in Epilepsy and CMAR genes. The number of rare (< 0.001 gnomAD allele frequency) variants not classified as pathogenic or benign in ClinVar are reported for genes from either the A Epilepsy or B CMAR1 gene list (light gray bars). Variants were scored using the in silico tool M-CAP. The number of suspicious VUS for each gene (> 0.025 M-CAP score) is shown by the dark gray bars. The gold line indicates the expected number of variants based on gnomAD allele frequency data. Gene lists are ranked by the difference between the observed and expected number of variants, when ratios are approximately the same, ranking is determined by number of suspicious gene variants