Pathogenic EFHC1 mutations are tolerated in healthy individuals dependent on reported ancestry

Abstract

SummaryObjectiveScreening for specific coding mutations in the EFHC1 gene has been proposed as a means of assessing susceptibility to juvenile myoclonic epilepsy (JME). To clarify the role of these mutations, especially those reported to be highly penetrant, we sought to measure the frequency of exonic EFHC1 mutations across multiple population samples.MethodsTo find and test variants of large effect, we sequenced all EFHC1 exons in 23 JME and 23 non-JME idiopathic generalized epilepsy (IGE) Hispanic patients, and 60 matched controls. We also genotyped specific EFHC1 variants in IGE cases and controls from multiple ethnic backgrounds, including 17 African American IGE patients, with 24 matched controls, and 92 Caucasian JME patients with 103 matched controls. These variants are reported to be pathogenic, but are also found among unphenotyped individuals in public databases. All subjects were from the New York City metro area and all controls were required to have no family history of seizures.ResultsWe found the reportedly pathogenic EFHC1 P77T-R221H (rs149055334-rs79761183) JME haplotype in one Hispanic control and in two African American controls. Public databases also show that the EFHC1 P77T-R221H JME haplotype is present in unphenotyped West African ancestry populations, and we show that it can be found at appreciable frequency in healthy individuals with no family history of epilepsy. We also found a novel splice-site mutation in a single Hispanic JME patient, the effect of which is unknown.SignificanceOur findings raise questions about the effect of reportedly pathogenic EFHC1 mutations on JME. One intriguing possibility is that some EFHC1 mutations may be pathogenic only when introduced into specific genetic backgrounds. By focusing on data from multiple populations, including the understudied Hispanic and Black/African American populations, our study highlights that for complex traits like JME, the body of evidence necessary to infer causality is high.

EFHC1 variants in juvenile myoclonic epilepsy: reanalysis according to NHGRI and ACMG guidelines for assigning disease causality

“…Like variants associated with other diseases that have a complex genetic architecture, some EFHC1 variants may not be sufficient by themselves to cause epilepsy; however, they may have an additive effect toward the pathogenesis of JME disease in conjunction with other alleles associated with epilepsy. This would also explain the discovery of JME disease alleles in screened study controls 20,21 as well as in the case of multiple disease alleles in linkage disequilibrium and the autosomal dominant transmission with incomplete penetrance that we see in our large families.…”

“…14), were not available in 2004 when variants of the EF-hand domain (C-terminal) containing 1 gene (EFHC1) were reported as disease-causing mutations in myoclonic and grand mal clonic-tonic-clonic (CTC) convulsions produced by juvenile myoclonic epilepsy (JME). Consequently, all EFHC1 variants discovered in the first decade of this millennium and reported with respect to epilepsy or not [15][16][17][18][19][20][21][22][23][24][25][26][27][28] have not been "vetted" through NHGRI and ACMG guidelines. More importantly, both NHGRI and ACMG guidelines advise that "with evidence on variants evolving" and the "content of sequencing tests expanding, " "rigorous evaluation" and "reanalysis of variants are encouraged" to prevent misannotation of the pathogenicity of variants in public databases.…”

Predictors of incident epilepsy in older adults

“…Emerging data from genetic studies suggest that ethnicity may have a role in genetic causes of epilepsy in specific populations. 30,31 Although genetic epilepsy would be unlikely to begin in older age, other genetic mutations may be associated with increased susceptibility to incident epilepsy in older age among different ethnic groups.…”

Understanding Genotypes and Phenotypes in Epileptic Encephalopathies

“…With the arrival of massive amounts of data, novel paradigms have been established in the field largely reflecting a growing sense of caution of not overinterpreting genomic findings in the absence of confirmatory data or statistical association. In the absence of appropriate guidelines for variant interpretation and gene-disease associations in the genetics community, wrong assertions about genes and variants became very abundant in the literature, posing a major interpretation [Pal and Helbig, 2015;Subaran et al, 2015]. These examples suggest that the current wave of gene discovery is paralleled by a wave of gene retirement , constantly refining the list of possible genetic etiologies based on an evolving catalogue of criteria [Richards et al, 2015].…”