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Neurology: Genetics logoLink to Neurology: Genetics
. 2021 Nov 12;7(6):e641. doi: 10.1212/NXG.0000000000000641

Progressive Myoclonus Epilepsies

Diagnostic Yield With Next-Generation Sequencing in Previously Unsolved Cases

Laura Canafoglia 1, Silvana Franceschetti 1,, Antonio Gambardella 1, Pasquale Striano 1, Anna Teresa Giallonardo 1, Paolo Tinuper 1, Carlo Di Bonaventura 1, Roberto Michelucci 1, Edoardo Ferlazzo 1, Tiziana Granata 1, Adriana Magaudda 1, Laura Licchetta 1, Alessandro Filla 1, Angela La Neve 1, Patrizia Riguzzi 1, Teresa Anna Cantisani 1, Martina Fanella 1, BARBARA CASTELLOTTI 1, Cinzia Gellera 1, Melanie Bahlo 1, Federico Zara 1, Carolina Courage 1, Anna-Elina Lehesjoki 1, Karen L Oliver 1, Samuel F Berkovic 1
PMCID: PMC8589262  PMID: 34786481

Abstract

Background and Objectives

To assess the current diagnostic yield of genetic testing for the progressive myoclonus epilepsies (PMEs) of an Italian series described in 2014 where Unverricht-Lundborg and Lafora diseases accounted for ∼50% of the cohort.

Methods

Of 47/165 unrelated patients with PME of indeterminate genetic origin, 38 underwent new molecular evaluations. Various next-generation sequencing (NGS) techniques were applied including gene panel analysis (n = 7) and/or whole-exome sequencing (WES) (WES singleton n = 29, WES trio n = 7, and WES sibling n = 4). In 1 family, homozygosity mapping was followed by targeted NGS. Clinically, the patients were grouped in 4 phenotypic categories: “Unverricht-Lundborg disease-like PME,” “late-onset PME,” “PME plus developmental delay,” and “PME plus dementia.”

Results

Sixteen of 38 (42%) unrelated patients reached a positive diagnosis, increasing the overall proportion of solved families in the total series from 72% to 82%. Likely pathogenic variants were identified in NEU1 (2 families), CERS1 (1 family), and in 13 nonfamilial patients in KCNC1 (3), DHDDS (3), SACS, CACNA2D2, STUB1, AFG3L2, CLN6, NAXE, and CHD2. Across the different phenotypic categories, the diagnostic rate was similar, and the same gene could be found in different phenotypic categories.

Discussion

The application of NGS technology to unsolved patients with PME has revealed a collection of very rare genetic causes. Pathogenic variants were detected in both established PME genes and in genes not previously associated with PME, but with progressive ataxia or with developmental encephalopathies. With a diagnostic yield >80%, PME is one of the best genetically defined epilepsy syndromes.


Progressive myoclonus epilepsies (PMEs) are caused by heterogeneous genetic disorders and present with cortical myoclonus, generalized tonic-clonic seizures, and variable ataxia or cognitive impairment. In a multicenter Italian collaborative study, we reported the etiologies in a cohort of 204 PME patients from 165 unrelated families studied by classical pathologic, biochemical, and targeted genetic testing.1 The cohort included “classical” PMEs, such as Unverricht-Lundborg (progressive myoclonic epilepsy type 1 [EPM1], 33%) and Lafora body (EPM2, 20%) diseases, and other PMEs resulting from more rare genetic diseases (19%). In 47 unrelated patients (28%), the etiology remained unidentified (Figure 1).

Figure 1. Classification of 165 Families With PME From 2014 to 2021.

Figure 1

NGS = next-generation sequencing; PME = progressive myoclonus epilepsy; ULD = Unverricht-Lundborg disease.

Since 2014, novel genetic causes and pathogenetic mechanisms for PME have been identified. These include pathogenic variants in CERS1,2 involved in ceramide metabolism, KCNC1,3 with a dominant-negative effect on the voltage-gated KV3 channel,4 and the NUS1, DHDDS, and ALG10 genes, involved in dolichol-dependent protein glycosylation.5

We reanalyze the unsolved cases in the 2014 series1 to assess the impact of newer diagnostic procedures, especially next-generation sequencing (NGS). Most of the newly solved cases have been reported elsewhere2-6; we herein provide an overall perspective of the current diagnostic yield in PME.

Methods

We studied 38 unsolved unrelated PME patients who did not reach a positive causal diagnosis in our previously reported PME series; DNA was no longer available from the remaining 9 patients (Figure 2). We obtained informed consent from all patients (or their guardians), in line with local institutional review board requirements for genetic analyses. Seven unrelated patients were initially investigated using a NGS panel containing 240 genes known to cause epilepsies or PME. Subsequently, 29 unrelated patients including 3 unsolved by the panel had singleton whole-exome sequencing (WES).3 A trio-design WES approach was performed in 7 patients, including 2 unsolved by NGS panel and 5 unsolved by singleton WES. In 4 families with 2 or 3 affected siblings, WES was performed on all patients.5 In 1 family with 4 affected siblings, homozygosity mapping was followed by targeted NGS.2

Figure 2. Diagram Flow of the Genetic Investigations Performed Between 2014 and 2020.

Figure 2

NGS = next-generation sequencing; PME = progressive myoclonus epilepsy; WES = whole-exome sequencing.

All patients presented with cortical myoclonus and a progressive course, consistent with PME. The clinical presentation of each patient was reviewed by Istituto Neurologico Besta clinicians (L.C. and S.F.) and researchers at the University of Melbourne (K.L.O. and S.F.B.). Taking into account the clinical classification applied by Courage et al.,5 patients were categorized as (1) “Unverricht-Lundborg disease-like (ULD-like) PME” in case of late childhood/adolescent onset of cortical myoclonus and minimal cognitive impairment similar to EPM1, (2) “late-onset PME” in case of clinical presentation similar to EPM1, but onset after 20 years of age, (3) “PME plus developmental delay” when progressive cortical myoclonus appeared after other symptoms suggesting a developmental encephalopathy (early psychomotor delay, ataxia or seizures), and (4) “PME plus dementia” when patients showed a severe and progressive cognitive impairment as part of the phenotype.

Data Availability

Anonymized data can be made available to qualified investigators upon request to the corresponding author.

Results

We found genetic causes in 16 of the 38 unrelated patients (42%). As shown in Figure 2, 2 patients were solved by NGS panel, 7 by WES singleton, 4 by WES trio, 2 by WES sibling, and 1 by homozygosity mapping.2-6 Table 1 reports the newly identified genetic variants.

Table 1.

Pathogenic Variants Detected in 16/38 Unsolved PME Families Since 2014

graphic file with name NG2021017194T1.jpg

Among “ULD-like” (16 cases), 3 had pathogenic variants in KCNC1 and 3 in CHD2, DHDDS, or AFG3L2. The genetic defect remained undetermined in the remaining 10. Among “late-PME” (6 patients), the WES of siblings revealed different NEU1 pathogenic variants in 2 families, mutation of DHDDS in 1 patient, and mutation of CLN6 in 1 other. In 2, the genetic cause remained unidentified.

In “PME plus developmental delay,” we included 11 patients. Homozygosity mapping revealed a pathogenic missense variant in CERS1 (EPM8; #616230) in 4 siblings, belonging to an Algerian family.2 Four sporadic cases had pathogenic variants in NAXE, DHDDS, SACS, and CACNA2D2. In the remaining 6 patients, the genetic cause remained unidentified.

Among the 5 patients with “PME plus dementia,” 1 had a pathogenic variant in STUB1.

In the 2014 article,1 a cluster analysis based on clinical features associated with PME allowed grouping the 38 unsolved patients evenly into Cluster 1 (n = 20) and Cluster 2 (n = 18). Cluster 1 accounted for all patients now classified as “PME plus developmental delay” with a smaller subset of “ULD-like” and “PME plus dementia” patients. Cluster 2 was predominantly made up of “ULD-like” patients, all “late-onset PME” patients, and 1 patient classified as “PME plus dementia” (eFigure 1, links.lww.com/NXG/A490). Diagnostic success was achieved in 9/20 Cluster 1 cases and 7/18 for Cluster 2.

Overall, concerning the 165 PME unrelated patients reported in 2014, the genetically identified causes increased from 72% to 82%. Figure 1 compares the diagnostic yield and breakdown for the entire Italian series from 2014 to 2021 and (eTable 1, links.lww.com/NXG/A490) lists all genes with pathogenic variants.

Discussion

This reanalysis with next-generation sequencing resulted in a positive diagnosis in 42% of PME unrelated patients who were unsolved at the time of our previous study.1 One clinically relevant observation relates to the atypical presentation of known PME disorders, which can hinder the diagnosis, as occurred with the diagnosis of sialidosis (#256550) in 2 families. Patients presented as “late-onset PME” and escaped diagnosis because of nonindicative biochemical findings and an unapparent cherry-red spot.6

Since 2014, NGS facilitated the discovery of many pathogenic variants in genes not previously identified as a causative for PME.5 Some, such as KCNC1,3,4 can be considered “specific” PME genes, giving rise in a typical age-range to a classical picture of worsening cortical myoclonus. Other findings, however, suggest that in some patients, in whom the syndromic picture is still that of a PME, the disorder results as a “variant” phenotype of genetic disorders typically presenting with other symptoms. In fact, until the studies published by Muona et al.,3 and Courage et al.,5 AFG3L2 (#614487), SACS (#270550), and STUB1 (#615768) were known to be associated with autosomal recessive ataxia and CACNA2D2 (#618501) with ataxia or epileptic encephalopathy. The spectrum of NAXE is phenotypically broad, giving rise to lethal neurometabolic disorder with acute-onset ataxia or epilepsy and movement disorders, occasionally including myoclonus.7 CHD2 is a well-established epileptic encephalopathy gene and was only recently associated with PME.5

The “new” genetic diagnoses were similarly distributed between “Cluster 1 and 2” that we identified in our original 2014 report,1 and the same occurred for the 4 phenotypic categories applied in this study. Moreover, mutations of the same gene, for instance DHDDS, may result either in “PME plus developmental delay,” “ULD-like PME,” or “late-onset PME” phenotypes. Conversely, we did not observe different phenotype categories within families.

Previous retrospective series from referral centers have reported high diagnostic yields in PME,8-10 but these studies likely suffer from referral and recall biases. Although the Italian series is not strictly epidemiologic, it was multicenter and had a prospective component, so it approximates the real-world representation of PME in a Caucasian population without major founder effects.

A methodological limit of this study resides on heterogeneous diagnostic procedures preceding WES. Our observation may indicate that, following an early screening of the most classical causes of PME (e.g., EPM1, resulting from CSTB dodecamer repeat expansion), and in the absence of typical signs revealing well-known disorders causing PME (e.g., cherry-red spot in sialidoses), WES represents the most suitable diagnostic procedure for achieving the causal diagnosis in the unsolved patients. When possible, affected family members and unaffected parents should be sequenced to maximize diagnostic yield and the chances for novel discovery.

The extensive re-evaluation by means of WES in our unclassified cases suggests that in PME it is possible to achieve a high genetic diagnostic yield (>80%), thus making PMEs 1 of the most genetically well-defined groups of all epilepsies.

Acknowledgment

The authors would like to thank the Italian League Against Epilepsy (LICE), which helped to support this study and continues to support many other epilepsy research studies.

Glossary

NGS

next-generation sequencing

PME

progressive myoclonus epilepsy

ULD

Unverricht-Lundborg disease

WES

whole-exome sequencing

Appendix. Authors

Appendix.

Contributor Information

Laura Canafoglia, Email: laura.canafoglia@istituto-besta.it.

Antonio Gambardella, Email: a.gambardella@unicz.it.

Pasquale Striano, Email: strianop@gmail.com.

Anna Teresa Giallonardo, Email: annateresa.giallonardo@uniroma1.it.

Paolo Tinuper, Email: paolo.tinuper@unibo.it.

Carlo Di Bonaventura, Email: c_dibonaventura@yahoo.it.

Roberto Michelucci, Email: roberto.michelucci@isnb.it.

Edoardo Ferlazzo, Email: ferlazzo@unicz.it.

Tiziana Granata, Email: tiziana.granata@istituto-besta.it.

Adriana Magaudda, Email: amagaudda@unime.it.

Laura Licchetta, Email: licchetta@gmail.com.

Alessandro Filla, Email: afilla@unina.it.

Angela La Neve, Email: angelalaneve58@gmail.com.

Patrizia Riguzzi, Email: patrizia.riguzzi@isnb.it.

Teresa Anna Cantisani, Email: cantisani@yahoo.com.

Martina Fanella, Email: fanella.martina@gmail.com.

BARBARA CASTELLOTTI, Email: barbara.castellotti@istituto-besta.it.

Cinzia Gellera, Email: cinzia.gellera@istituto-besta.it.

Melanie Bahlo, Email: bahlo@wehi.edu.au.

Federico Zara, Email: federicozara@gaslini.org.

Carolina Courage, Email: carolina.courage@helsinki.fi.

Anna-Elina Lehesjoki, Email: anna-elina.lehesjoki@helsinki.fi.

Karen L. Oliver, Email: oliverkl@unimelb.edu.au.

Samuel F. Berkovic, Email: s.berkovic@unimelb.edu.au.

Study Funding

No targeted funding reported.

Disclosure

The authors have no disclosure to make in relation to this manuscript. Go to Neurology.org/NG for full disclosure.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Anonymized data can be made available to qualified investigators upon request to the corresponding author.


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