Literature DB >> 26392352

Application of targeted multi-gene panel testing for the diagnosis of inherited peripheral neuropathy provides a high diagnostic yield with unexpected phenotype-genotype variability.

Thalia Antoniadi1, Chris Buxton2, Gemma Dennis3, Natalie Forrester4, Debbie Smith5, Peter Lunt6, Sarah Burton-Jones7.   

Abstract

BACKGROUND: Inherited peripheral neuropathy (IPN) is a clinically and genetically heterogeneous group of disorders with more than 90 genes associated with the different subtypes. Sequential gene screening is gradually being replaced by next generation sequencing (NGS) applications.
METHODS: We designed and validated a targeted NGS panel assay including 56 genes associated with known causes of IPN. We report our findings following NGS panel testing of 448 patients with different types of clinically-suspected IPN.
RESULTS: Genetic diagnosis was achieved in 137 patients (31%) and involved 195 pathogenic variants in 31 genes. 93 patients had pathogenic variants in genes where a resulting phenotype follows dominant inheritance, 32 in genes where this would follow recessive inheritance, and 12 presented with X-linked disease. Almost half of the diagnosed patients (64) had a pathogenic variant either in genes not previously available for routine diagnostic testing in a UK laboratory (50 patients) or in genes whose primary clinical association was not IPN (14). Seven patients had a pathogenic variant in a gene not hitherto indicated from their phenotype and three patients had more than one pathogenic variant, explaining their complex phenotype and providing information essential for accurate prediction of recurrence risks.
CONCLUSIONS: Our results demonstrate that targeted gene panel testing is an unbiased approach which overcomes the limitations imposed by limited existing knowledge for rare genes, reveals high heterogeneity, and provides high diagnostic yield. It is therefore a highly efficient and cost effective tool for achieving a genetic diagnosis for IPN.

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Year:  2015        PMID: 26392352      PMCID: PMC4578331          DOI: 10.1186/s12881-015-0224-8

Source DB:  PubMed          Journal:  BMC Med Genet        ISSN: 1471-2350            Impact factor:   2.103


Background

Inherited peripheral neuropathy (IPN) is the most common group of inherited neurological disorders with an estimated prevalence of 1 in 2500 individuals [1]. It is clinically and genetically heterogeneous; with over 90 genes and loci implicated in the normal function of the myelinated axons of the peripheral nervous system. Onset is typically in the first or second decade, but there are congenital and infantile onset forms of the disease, as well as late onset adult forms. The classical clinical phenotype may manifest as distal limb muscle wasting and weakness, mild to moderate sensory loss, abnormalities of deep tendon reflexes and foot deformities (pes cavus and hammer toes). Hearing loss, or respiratory impairment resulting from phrenic nerve involvement, may also be characteristic in some forms. IPN classification is based on clinical phenotype, mode of inheritance, age of onset, electrophysiological studies and causal mutation. The main subtypes include hereditary motor and sensory neuropathy (HMSN), typically known as Charcot-Marie-Tooth disease (CMT); hereditary sensory and autonomic neuropathy (HSAN) also known as hereditary sensory neuropathy; hereditary motor neuropathy (HMN), also known as distal hereditary motor neuropathy, and hereditary neuropathy with liability to pressure palsy (HNPP). CMT is the phenotype with the widest genetic heterogeneity. Nerve conduction velocity studies (NCV) subdivide CMT into type 1 (CMT1), a demyelinating form with median or ulnar motor NCV <38 m/s; type 2 (CMT2), an axonal form with NCV >38 m/s, and an intermediate form with both demyelinating and axonal features. Inheritance modes include autosomal dominant (AD), autosomal recessive (AR) and X-linked (XL). A single gene may be implicated in different phenotypes and present with different modes of inheritance, presenting a challenge to diagnose patients with specific types of IPN [2, 3]. Following the exclusion of a 1.5 Mb duplication at 17p11.2 including the PMP22 gene as the most common cause of CMT1, the traditional strategy for genetic testing consisted of sequential sequencing of individual genes, selected according to the patient’s clinical presentation and family history. This strategy, alongside the cost of serial testing and the limited breadth of genes available for testing, resulted in a low diagnostic yield. Since the cost of next generation sequencing (NGS) has been decreasing dramatically over the last few years, this technology has found numerous applications in the diagnosis of heterogeneous disorders, including IPN. Whole genome sequencing (WGS) and whole exome sequencing (WES) have identified new genetic causes for many conditions, as demonstrated for IPN by the identification of SH3TC2 as a cause of autosomal recessive CMT1 [4] and DYNC1H1 as a new genetic cause for autosomal dominant CMT2 [5]. The targeted panel approach, which restricts analysis to genes known to be implicated in a particular phenotype has also been also successfully applied to IPN. Choi et al. applied WES to a series of unrelated individuals with CMT and restricted analysis to genes already known to be causes of IPN [6]. WGS and WES, however, generate a huge amount of data. Management and storage of this data can present a challenge in a clinical diagnostic environment. We designed and validated a targeted NGS panel assay including 56 genes associated with known causes of inherited neuropathy and evaluated this approach for the diagnosis of IPN. The results of the pilot project were submitted as a gene dossier to the UK Genetic Testing Network (UKGTN) [7]. This received approval in January 2013 and the diagnostic service was launched in July 2013. We present and summarise the results of 448 patients reported in the first 18 months of this diagnostic service.

Methods

Patients

Blood or DNA samples from patients referred by neurologists and clinical geneticists were accepted for testing when the UKGTN approval criteria were met. These criteria are listed below: ‘Idiopathic’ peripheral neuropathy diagnosed by clinical presentation with progressive weakness in hands/wrists and/or feet/ankles and/or associated pes cavus or finger flexion contractures and/or peripheral sensory loss Supportive nerve conduction test result (defining type I or II according to NCV) Absence of other non-genetic causes (alcohol, B12 deficiency, diabetes, trauma) No associated CNS involvement The referring clinicians were also asked to indicated the suspected mode of inheritance and provide a recent clinical letter with further details of the clinical phenotype. A small number of samples were accepted for testing from patients not strictly meeting these criteria, after discussion with the individual requesting clinician. From July 2013 to December 2014, DNA samples from 448 unrelated probands with suspected IPN were tested and reported; a significant proportion of these patients had previously tested negative for the common causes of IPN. Two hundred ninety nine patients were referred by neurologists (67 %) and 149 patients (33 %) by clinical geneticists. Approximately one third of the patients were under 18 years of age at referral (135 patients, 30 %). Informed consent for IPN multi-gene panel testing was obtained from patients or their parents/legal guardians by the requesting clinician. The decision to request this test was made by each clinician according to their local ethical guidelines. This diagnostic test has been assessed for validity, utility and socio-legal/ethical implications in the process of ratification by the UKGTN and UK NHS commissioners, and was undertaken in an accredited UK NHS Laboratory. Data presented pertains only to results of routine diagnostic testing; therefore this study was not subject to ethical approval.

Targeted capture

Genes were selected following extensive searches of the literature and locus specific databases [8, 9] to ensure their clinical validity and utility. Two additional genes flanking PMP22 that are commonly involved in the 1.5 Mb reciprocal deletion/duplication event occurring at 17p11.2 [10] were included, to assist in the copy number assessment of this region (COX10, TEKT3). All the genes had a disease OMIM (Online Mendelian Inheritance in Man) entry related to a subtype of peripheral neuropathy. Table 1 details the 56 genes included in the assay.
Table 1

Genes included in IPN NGS panel, with associated phenotype and inheritance pattern

GENEOMIMLocusCMT1CMT2HMNHS(A)NOMIMInheritance
AARS 60106516q22CMT 2N613287AD
ARHGEF10 6081368p23Slowed NCV; hypomyelination608236AD
ATL1 60643914q11-q21HSN 1D613708AD
ATP7A 300011Xq12-q13dSMAX3300489XL
BAG3 60388310q26.11Myopathy; myofibrillar, BAG-3 related612954AD
BSCL2 60615811q12.3HMN 5600794AD
CCT5 6101505p15.2HSN with spastic paraplegia256840AR
CTDP1 60492718q23CCFDN: Congenital cataracts, facial dysmorphism, neuropathy604168AR
DCTN1 6011432p13.1HMN 7B607641AD
DNM2 60237819p13.2CMT DI B606482AD
CMT 2 M
DYNC1H1 60011214q32.31CMT 2OSMA-LED614228/158600AD
EGR2 12901010q21.1-q22.1CMT 1D607678AD
CMT 4E CHN605253AD
DSS145900AR
FAM134B 6131145p15.1HSAN 2B613115AR
FGD4 61110412p11.21CMT 4H609311AR
FIG4 6093906q21CMT 4J611228AR
GAN 60537916q23.2Giant Axonal Neuropathy 1256850AR
GARS 60028721q22.11CMT 2DHMN 5601472/600794AD
GDAP1 6065988q21CMTA RI608340AR
CMT 4A214400AR
CMT 2H607706AR
CMT 2K607831AD
GJB1 304040Xq13.1CMT X1302800XL
HOXD10 1429842q31.1HMSN with Congenital vertical talus192950AD
HSPB1 6021957q11CMT 2FHMN 2B606595/608634AD
HSPB3 6046245q11.2HMN 2C613376AD
HSPB8 60801412q24CMT 2LHMN 2A608673/158590AD
IGHMBP2 60050211q13.3HMN 6604320AR
IKBKAP 6037229q31.3HSAN 3223900AR
KARS 60142116q23.1CMT RI B613641AR
KIF1B 6059951p36.22CMT 2A1118210AD
LITAF 60379516p13.3-p12CMT 1C601098AD
LMNA 1503301q22CMT 2B1605588AR
LRSAM1 6109339q33.3CMT 2P614436AD/AR
MED25 61019719q33.13CMT 2B2605589AR
MFN2 6085071p35-36CMT 2A2609260AD
HMSN6601152
MPZ 1594401q22CMT 1B118220AD
CHN605253
CMT DI D607791
CMT 2I607677
CMT 2J607736
MTMR2 60355711q21CMT 4B1601382AR
NDRG1 6052628q24.22CMT 4D601455AR
NEFL 1622808p21CMT 1FCMT 2E607734/607684AD
NGFB 1620301q13.2HSAN 5, absence of pain608654AR
NTRK1 1913151q23.1HSAN 4; anhidrosis, insensitivity to pain256800AR
PLEKHG5 6111011p36.31CMT RICdSMA 4615376/611067AR
PMP22 60109717p11.2CMT 1A118220AD
HNPP162500AD
CMT 1E118300AD
DSS145900AR
PRPS1 311850Xq22.3CMT X5311070XL D/R
PRX 60572519q13.1-q13.2CMT 4F/DSS145900AR
RAB7A 6022983q21.3CMT 2BHSN600882AD
REEP1 6091392p11.2HMN5B614751AD
SBF2 60769711p15.4CMT 4B2604563AR
SCN9A 6034152q24.3Absence of pain243000AR
Small fibre neuropathy133020AD
SEPT9 60406117q25.2-q25.3Hereditary neuralgic amyotrophy, HNS, HNA & dysmorphic features162100AD
SH3TC2 6082065q32CMT 4C601596AR
SLC12A6 60487815q14PN with agenesis of the corpus callosum218000AR
SOX10 60222922q13.1PCWH syndrome609136AD
SPTLC1 6057129q22.1-q22.3HSAN 1162400AD
SPTLC2 60571314q24.3HSAN 1C613640AD
TDP1 60719814q32.11Spinocerebellar ataxia, with axonal neuropathy607250AR
TRPV4 60542712q24.1CMT 2C606071AD
WNK1 60523212p13.33HSAN 2A201300AR
YARS 6036231p13.1CMT DI C608323AD
Genes included in IPN NGS panel, with associated phenotype and inheritance pattern A custom SureSelect (Agilent Technologies) solution-based oligonucleotide target capture assay was designed using the web-based tool eArray (version 7.7). Regions of interest (ROI) were designed to encompass coding regions of all alternate transcripts for each gene. 5’ and 3’ untranslated regions and non-coding exons were also included. Promoter sites were included for GJB1 and PMP22, and also part of MPZ intron 1 [11]. Each ROI included 20 base pairs (bp) upstream and 10 bp downstream of the coding exon to capture canonical splicing donor and acceptor sites.

Library preparation and sequencing

Genomic DNA was extracted from whole blood using the Puregene protocol (Gentra Systems Incorporated), EZ1 DNA Blood kit (Qiagen) or a standard phenol-chloroform extraction. We also received DNA samples extracted in other laboratories. A Qubit 2.0 Fluorometer (Life Technologies) was used to quantify double stranded DNA concentration in genomic DNA samples. Sequencing libraries were prepared according to the manufacturer’s standard protocol; SureSelectXT Target Enrichment System for Illumina Paired-End Sequencing Library Illumina HiSeq and MiSeq Multiplexed Sequencing Platforms Version 1.5, November 2012. Genomic DNA was sheared to a median size of 200 bp using the Bioruptor NGS sonicator (Diagenode). Fragment size was assessed using the Tapestation 2100 Bioanalyzer (Agilent Technologies). Sequencing was performed on a MiSeq instrument (Illumina) using Version 2 reagents, 2x150 paired-end reads in batches of 16 patients’ samples. Data analysis was performed using an open source in-house pipeline (alignment: BWA; alignment modification and variant calling: GATKv2; variant annotation: Annovar) with hg19 human genome as a reference, and followed the Association of Clinical Genetics Science (ACGS) Practice Guidelines [12]. Viewing of variants and recording of classification evidence was facilitated using Geneticist Assistant software (Soft Genetics). Copy number enumeration was performed for the 17p11.2 region using the CONTRA tool as a component of the analysis pipeline [13]. This was necessary to ensure that the most frequent cause of CMT1/HNPP (and therefore a positive genetic diagnosis) would not be missed if a patient had not been pre-screened for PMP22 dosage, for reasons of clinical oversight, or an atypical clinical presentation. The assay was validated using genomic DNA samples from nine patients previously tested in our laboratory; six of these had single nucleotide variants (SNVs) in six different genes (a total of 26 SNVs),previously identified by Sanger sequencing. A further three had the classical deletion or duplication of PMP22, identified previously by MLPA dosage analysis. All 26 SNV occurrences and the PMP22 copy number variants (CNVs) were confirmed using this assay. Using 95 % confidence intervals for the binomial distribution, the sensitivity of this assay was determined to be between 87 and 100 % [14]. To date, all of the (410) variants detected by NGS and followed up by subsequent Sanger sequencing have been confirmed as true positives. Due to lack of CNV positive controls for genes other than PMP22, the analysis pipeline has not been validated as capable of CNV detection automatically. Visual checking of CONTRA data is undertaken when one pathogenic variant is detected in a recessive gene. Small insertions and deletions have been detected and confirmed, ranging from 2 bp to whole gene deletions; however this does not exclude the possibility that there are other CNVs present that were not detected. The report of results states clearly that the test has not excluded copy number variation in the genes examined.

Variant filtering and classification

Variants were managed using Genetic Assistant (SoftGenetics). Classification followed the Association of Clinical Genetics Science Practice Guidelines [15], and all variants were classified into five pathogenicity groups. Table 2 details the criteria applied to classify variants (Class 1: clearly not pathogenic; Class 2: unlikely to be pathogenic; Class 3: unknown significance; Class 4: likely to be pathogenic; Class 5; clearly pathogenic). Variants were filtered according to their frequency; assessment included comparison of frequency data from the database dbSNP (version 142) [16] and the Exome Variant Server (version 6500) [17]. All variants with frequency above 3 % were considered as clearly not pathogenic (Class 1). The remaining variants were further investigated for their clinical significance. Literature searches, the IPNMDB database [8] and our local laboratory database were interrogated. In silico analysis was assisted by AlamutVisual (Interactive Biosoftware), which incorporates multiple amino acid substitution and splice-prediction tools.
Table 2

Criteria applied in the classification of variants

ClassPathogenicityCriteria
5Clearly pathogenic1. Reported in the literature as pathogenic with supporting evidence; multiple independent cases, pedigree segregation studies and/or functional analysis AND
2. Phenotype and inheritance pattern in patient correlates with the gene
4Likely to be pathogenic1. Not described in the literature, or weak evidence for pathogenicity in published literature; no segregation or functional analysis available AND
2. Phenotype and inheritance pattern in patient correlates with the gene AND
3. Location of variant in gene and pathogenic mechanism are compatible with previously described pathogenic variants in the gene AND
4. Minor allele frequency (MAF) is <1 % in dbSNP (v142) and <1 % in Exome Variant Server (EVS, v6500) AND
5. a) Missense variant; conserved amino acid, Polyphen 2 (HumVar) and SIFT concur in predicting deleterious effect or three or more of five splice prediction toolsa return >10 % difference in splice site prediction value between wild type and variant OR
b) Frameshift or nonsense variant; where expected mechanism is loss of function OR
c) Synonymous or intronic change; nucleotide highly conserved across multiple species and three or more splice prediction tools return >10 % difference in splice site prediction value between wild type and variant
3Unknown significance (VoUS)1. Minor allele frequency <1 % in dbSNP (v142) and EVS (v6500) AND
2. Phenotype and inheritance pattern in patient correlates with the gene AND
3. Not described in the literature, or described in literature with inconclusive or no evidence AND
a) In silico predictions score variants as Class 4 but phenotype does not correlate with the gene OR
b) In silico predictions are conflicting (for example; conserved amino acid, very low MAF but Polyphen 2 and SIFT predict benign)
2Unlikely to be pathogenic1. a) Minor allele frequency is between 1 % and 3 % in dbSNP (v142) and/or between 1 % and 3 % in EVS (v6500) but phenotype and/or inheritance pattern in patient correlates with the gene OR
 b) Minor allele frequency is <1 % in dbSNP and EVS but phenotype and/or inheritance pattern in patient does not correlate with gene AND
2. a) Missense variant; amino acid is weakly conserved across multiple species and/or Polyphen 2 (HumVar) and SIFT concur in predicting benign OR
 b) Synonymous or intronic change; nucleotide weakly conserved across multiple species and splice prediction toolsa show no significant difference between wild type and variant, even if MAF is <1 % on dbSNP and EVS AND
3. a) Some evidence for benign status in literature but weak or inconclusive AND/OR b) Some evidence that variant does not segregate with disease in pedigree of patient(s) tested in this cohort
1Clearly not pathogenicFrequency >3 % in dbSNP (v142) or >3 % in Exome Variant Server (v6500) OR
Frequency <3 % but described and proven as not pathogenic in published literature

aFive splice prediction tools queried via Alamut software interface: SpliceSite Finder Like, MaxEntScan, NNSplice, GeneSplicer, Human Splicing Finder

Criteria applied in the classification of variants aFive splice prediction tools queried via Alamut software interface: SpliceSite Finder Like, MaxEntScan, NNSplice, GeneSplicer, Human Splicing Finder Variants classified as pathogenic, likely pathogenic or of uncertain clinical significance were confirmed by Sanger sequencing and were detailed within the report of results. Candidate pathogenic CNVs were confirmed by MLPA analysis either using a commercially available probe mix (MRC Holland), or alternatively by designing bespoke MLPA probes to target the gene of interest, combining these with the MRC Holland P300-A2 reference probe mix. Bespoke MLPA probes were designed using the online tool MAPD [18]. For patients without candidate pathogenic variants, one unique variant was selected and confirmed by Sanger sequencing to ensure the correct identification of all samples in the batch.

Results and discussion

Analysis of the data demonstrated high read depth and target coverage. On average, 99.81 % of the targeted region was covered to a minimum of 30x reads, and 99.86 % to a minimum of 15x. The mean depth of coverage was 537x reads. A total of 56,000 variants were detected in the 448 patients. Of those, 1830 variants had prevalence less than 3 % in dbSNP (version 142) or in Exome Variant Server (version 6500). These variants were individually assessed and classified according to the ACGS guidelines [14].

Gene spectrum in the diagnosis

A total of 195 variants in 31 genes provided a genetic diagnosis for 137 patients (diagnostic yield 31 %). Of these, 107 variants were previously reported in the literature as pathogenic with supporting evidence (Additional file 1: Table S1). The remaining 88 variants were novel and were classified as likely pathogenic (class 4) based on conservation, in silico predictions, phenotype compatibility and in several cases family studies (Additional file 2: Table S2). 215 variants were classified as of uncertain clinical significance (Additional file 3: Table S3) and the remaining 1420 variants were assessed as unlikely pathogenic (class 2) or clearly not pathogenic (class 1). Fifty patients had pathogenic variants in genes not previously available for genetic testing in a diagnostic setting in the UK, including six with variants in regions of the DYNC1H1 gene not previously screened due to its large size; another 14 had pathogenic variants in genes where testing was previously available but did not feature in the regular IPN diagnostic strategy (Table 3).
Table 3

Diagnostic yield for each phenotypic group, mode of inheritance and gene

PhenotypeInheritanceGenePatients
CMT1 AD MPZ 5
NEFL 3
LITAF 3
GDAP1 3
MFN2 2
AARS 1
PMP22 1
X-L GJB1 3
ATP7A 1
AR SH3TC2 10
IGHMBP2 a 4
SBF2 2
FIG4 2
FGD4 1
Tested 101 Diagnosed 41
CMT2 AD MFN2 8
BSCL2 5
DYNC1H1 b 4
GDAP1 3
HSPB1 3
PMP22 3
SPTLC2 2
NEFL 2
SCN9A a 2
GARS 2
RAB7A 2
TRPV4 1
SH3TC2 1
DNM2 1
MPZ 1
X-L GJB1 6
AR IGHMBP2 a 4
GDAP1 2
FIG4 1
SLC12A6 1
Tested 152 Diagnosed 54
HMN AD DYNC1H1 b 5
GARS 4
HSPB1 3
REEP1 2
MFN2 2
SPTLC1 1
DNM2 1
PMP22 1
DCTN1 1
NEFL 1
LMNA a 1
AR IGHMBP2 a 2
tested 91 Diagnosed 24
HSN AD SPTLC2 1
AARS 1
PMP22 1
RAB7A 1
AR MED25 1
Tested 25 Diagnosed 5
Mixed AD AARS 5
MPZ 1
X-L GJB1 2
Tested 22 Diagnosed 8
Complex AD DYNC1H1 b 1
SEPT9 1
SH3TC2 1
AR SCN9A a 1
GAN 1
Tested 57 Diagnosed 5
Overall total 448 Diagnosed 137

Highlighted bold: gene not previously available for routine diagnostic testing in UK

aGene not previously requested for IPN

bOnly part of the gene was previously available for testing

Diagnostic yield for each phenotypic group, mode of inheritance and gene Highlighted bold: gene not previously available for routine diagnostic testing in UK aGene not previously requested for IPN bOnly part of the gene was previously available for testing

Diagnostic yield in the different IPN subtypes

The patients were grouped into a phenotypic subtype according to the information on the clinical proforma provided. Table 3 presents the positive diagnostic yield achieved in detail. The diagnostic yield was highest for patients with demyelinating neuropathy (41/101, 41 %). This cohort included CMT1 patients in whom a 17 p11.2 PMP22 copy number variant had previously been excluded. The group of the patients with axonal neuropathy had a diagnostic yield of 35.5 % (54/152), similar to the group of patients with mixed neuropathy (36 %, 8/22). The diagnostic yield in patients with HMN was 26 % (24/91) and for HSN 20 % (5/25). Only 5/57 patients received a genetic diagnosis (9 %) in the group with the complex phenotypes. This group included patients with multisystem disorders, where neuropathy was not the primary cause of disease, and UKGTN criteria were not strictly met; however testing was performed as the clinical teams felt it would be beneficial. The majority (93/137, 68 %) of the genetically diagnosed patients had an autosomal dominant form of neuropathy, while 12 patients presented with X-linked disease (9 %). It has been previously estimated that in Northern Europe and North American populations, approximately 90 % of cases of CMT are either autosomal dominant or X-linked [3, 19]. Autosomal recessive disease is estimated to account for significantly less, although in populations with a high rate of consanguineous marriages, autosomal recessive forms can account for up to 40 % [20]. We identified 32 patients with recessive aetiology, representing almost one quarter of our positive cases (23 %). The age of the patients with recessive neuropathy ranged from 3 to 68 years at the time of diagnosis. Fifteen patients were under 18 years of age (47 %) while 17 were adults (53 %). Evidently autosomal recessive peripheral neuropathy is not exclusively associated with very early onset, severe progressive disease. Two genes, SH3TC2 and IGHMBP2, accounted for 62 % of all recessive diagnoses (20/32 patients). There was no significant difference in the overall diagnostic yield achieved between patients under 18 years of age and those aged 18 and over (36/135 vs 102/313; Fisher’s exact test value 0.222, p < 0.05). The clinical and genetic heterogeneity of IPN has always presented a challenge for the clinical classification. Specialist clinics have played a significant role in guiding the genetic testing. A positive diagnostic yield of 62.6 % in CMT patients attending specialist clinics was reported by Murphy et al. [21] and 67 % by Saporta et al. [22]. This proportion is reported to be significantly lower at 37.7 % in patients that have not been assessed in specialist clinics [21]. These figures include patients positive for the PMP22 duplication. Our overall diagnostic yield of 31 % does not include PMP22 duplication positive patients, as the majority of our patients are referred to us for gene panel testing following a normal result for PMP22 copy number in their local laboratories. For our local patients, the pick-up rate was estimated to be approximately 28 % (125/443) for the PMP22 duplication and 27 % (90/332) for the PMP22 deletion (patients tested in a three year period 2007–2010, unpublished data). This figure is slightly higher than the 20.9 % PMP22 CNVs identified by Murphy et al. [21] in those not attending a specialist inherited neuropathy clinic, and almost twice the level seen in the cohort of DiVincenzo et al., at 14.5 % [23]. DiVincenzo et al. have reported the positive rate of mutations in 14 genes (PMP22, GJB1, MPZ, MFN2, SH3TC2, GDAP1, NEFL, LITAF, GARS, HSPB1, FIG4, EGR2, PRX and RAB7A) in a very large cohort of 17,789 individuals [23]. Among these patients, 4 genes accounted for 94.9 % of positive results: PMP22, GJB1, MFN2, MPZ. Murphy et al. also reported a 94 % pick up rate of those four genes, including point mutations and rearrangements [21]. The equivalent positive pick up rate in our patients, excluding the rearrangements is 43.4 % (we have 36 positive patients in the four genes versus 83 positive in the 14 genes). This possibly reflects the fact that in this first year that the gene panel was available, a significant proportion of the patients referred for testing had already undergone testing for these common genes, and only those without a mutation were referred to us for further testing on the NGS panel.

Copy number variation

Copy number variation (CNV) is considered rare except for the common 17p11.2 PMP22 copy number variants, and accounts for about 1 % of diagnoses [24]. We detected two patients with whole PMP22 gene duplication, and three patients with a whole gene deletion (PMP22, GJB1, SLC12A6). We also detected one patient homozygous for GAN exon 1 deletion and one compound heterozygous for a partial deletion of the SBF2 gene encompassing exons 14 to 27. Our existing pipeline is set up to detect whole gene deletions and duplications; for smaller CNVs we currently manually check the data. However, it has been proven particularly useful to have this ability to check for CNVs in the cases where one pathogenic variant was detected in a gene associated with recessive inheritance.

The PMP22 c.353C > T, p.(Thr118Met) variant

We detected the PMP22 c.353C > T, p.(Thr118Met) variant in five patients (patients 1–5, Table 4). This variant has been widely documented; however its pathogenicity has been controversial in the literature [25-27]. The latest evidence suggested that it is associated with neuropathy, albeit with reduced penetrance [28]. This variant is present in dbSNP (rs104894619) with a minor allele frequency (MAF) of 0.08 %, in the Exome Variant Server with a MAF of 0.53 % (European-American cohort) and in the ExAC browser with MAF 0.73 % (European non-Finnish, including one homozygote). Four out of five of our patients had another class 4 or 5 variant and only one patient had no other variants.
Table 4

Interesting patients; examples to highlight the added value of gene panel testing

PatientPhenotypeGene and RefSeq TranscriptVariantPathogenicity classReference
1CMT2 PMP22 NM_000304.2c.353C > Tp.(Thr118Met)C5[2528]
GJB1 NM_000166.5c.-17G > Ap.?C5[35]
2CMT2 PMP22 NM_000304.2c.353C > Tp.(Thr118Met)C5[2528]
PMP22 NM_000304.2c.281delGp.(Gly94Alafs*17)C5[3638]
3HMN PMP22 NM_000304.2c.353C > Tp.(Thr118Met)C5[2528]
REEP1 NM_001164730.1c.*50G > Ap.?C5[39]
DYNC1H1 NM_001376.4c.3500 T > Ap.(Val1167Glu)C4This study
4HMN PMP22 NM_000304.2c.353C > Tp.(Thr118Met)C5[2528]
GARS NM_002047.2c.485A > Gp.(His162Arg)C4This study
5HSN PMP22 NM_000304.2c.353C > Tp.(Thr118Met)C5[2528]
6CMT2 MFN2 NM_014874.3c.1403G > Ap.(Arg468His)C5[2931]
MFN2 NM_014874.3c.809 T > Cp.(Met270Thr)C3This study
MFN2 NM_014874.3c.1029_1032delGAGp.(Arg344del)C3This study
7HMN MFN2 NM_014874.3c.1403G > Ap.(Arg468His)C5[2931]
8CMT1 MFN2 NM_014874.3c.1403G > Ap.(Arg468His)C5[2931]
9CMT1 MFN2 NM_014874.3c.2119A > Gp.(Arg707Trp)C5[31]
10CMT2 PMP22 NM_000304.2c.448G > Cp.(Gly150Arg)C4This study
11CMT2 PMP22 NM_000304.2c.(?_-1)_(*1_?) delp.0C5[40]
12CMT1 AARS NM_001605.2c.986G > Ap.(Arg329His)C5[41]
13HMN PMP22 NM_000304.2c.185 T > Gp.(Leu62Arg)C4This study
MED25 NM_030973.3c.1004C > Tp.(Ala335Val)C5[42]
14CMT2 PMP22 NM_000304.2c.(?_-1)_(*1_?) dupp.(=) dupC5[43]
SCN9A NM_002977.3c.3369G > Tp.(Leu1123Phe)C4This study
15CMT complex PMP22 NM_000304.2c.(?_-1)_(*1_?) dupp.(=) dupC5[43]
SH3TC2 NM_024577.3c.505 T > Cp.(Tyr169His)C5[4]
MFN2 NM_014874.3c.1936G > Ap.(Val646Ile)C3This study
16CMT2 SH3TC2 NM_024577.3c.505 T > Cp.(Tyr169His)C5[4]
GDAP1 NM_018972.2c.501dupAp.(Glu168Argfs*3)C4This study
17HSN RAB7 NM_004637.5c.484G > Ap.(Val162Met)C5[32]
SPTLC2 NM_004863.3c.1142 T > Cp.(Phe381Ser)C4This study
Interesting patients; examples to highlight the added value of gene panel testing The diversity of the phenotypes in our patients with the c.353C > T, p.(Thr118Met) PMP22 variant, the variant’s co-existence with pathogenic mutations in other genes and its high MAF in the general population, challenge it being a causative variant, although its contribution to a phenotype cannot be excluded.

The MFN2 c.1403G > A, p.(Arg468His) variant

This variant was detected in three patients (patients 6–8, Table 4). The c.1403G > A, p.(Arg468His) variant is recorded on dbSNP (rs138382758) with MAF 0.20 %, on the Exome Variant Server with MAF 0.24 % (European-American cohort) and in the ExAC with MAF 0.32 % (European, non-Finnish cohort) including two homozygotes. It was originally reported by Engelfried K et al. in a patient with distal weakness and atrophy of the legs and also her symptomatic father, but as it was also detected on one allele in the population study (260 chromosomes), it was considered to be a benign polymorphism [29]. In a later study by Casasnovas et al. the variant c.1403G > A, p.(Arg468His) was identified in six of 14 unrelated Spanish families presenting mild or moderate CMT2, with dominant inheritance and onset of disease in the third to fifth decade [30]. Functional studies were conducted on fibroblasts from a skin biopsy and it was demonstrated that this variant decreased efficiency of ATP synthesis leading to decreased ATP production; this supported the pathogenicity of this variant. The authors suggested that the anonymous control subject identified by Engelfried et al. could be a CMT2 patient who had not yet reached the age of onset of symptoms. Braathen et al. described a patient with CMT1 (reduced NCVs) presenting at age 2, who had the MFN2 c.1403G > A variant, suggesting that it may also associate with demyelinating CMT [31]. The presence of this variant was consistent with axonal phenotype in two of our patients while the third presented with early onset CMT1, matching the patient described by Braathen et al.

Broadening the phenotypic spectrum associated with specific genes

A total of six patients were found to have pathogenic variants in genes that would not have been traditionally tested for their phenotype (patients 8–14, Table 4). Two patients referred as having CMT1 were found to have pathogenic variants in MFN2. Two patients referred with axonal neuropathy were found to have a PMP22 variant; one of them the classical PMP22 deletion and the other the PMP22 duplication. A patient referred with HMN was also found to have a likely pathogenic variant in PMP22, and was carrier of a recessive pathogenic variant in MED25. A patient with CMT1 was found to have the recurrent pathogenic variant in AARS. Our IPN multigene testing is an unbiased approach; these patients would have not received a diagnosis based on the phenotypically - led genetic testing, either by the traditional sequential testing or by CMT phenotype-specific panels. A few of these patients might have been misclassified in the local clinic, without the benefit of specialist expertise at a regional or national centre; however the NGS panel approach for genetic diagnosis can help to compensate for limited access to specialist diagnostic expertise.

Identification of multiple genetic causes

Four adult patients were found to have potentially more than one causative variant in different genes (patients 15–17, Table 4). One patient with atypical CMT and known to have the PMP22 duplication was found to have the known pathogenic variant in SH3TC2, c.505 T > C p.(Tyr169His). This patient had also one variant of unknown clinical significance in MFN2, c.1936G > A, p.(Val646Ile). Another adult patient with axonal neuropathy was found to have the SH3TC2 c.505 T > C, p.(Tyr169His) variant alongside a likely pathogenic (predicted truncating) variant in GDAP1, c.501dupA, p.(Glu168Argfs*3). While homozygous or compound heterozygous pathogenic variants in SH3TC2 are associated with autosomal recessive CMT4C, there is growing evidence that heterozygosity for some SH3TC2 variants can cause axonal neuropathy. Lupski et al. identified the p.(Tyr169His) variant in the heterozygous state in a parent and a grandparent of the proband [4]. The p.(Tyr169His) heterozygotes did not have CMT1, but were found to have patchy axonal polyneuropathy with definite median-nerve mononeuropathy at the wrist on neurophysiology. A patient referred with CMT2 was found to have the PMP22 duplication and a SCN9A likely pathogenic variant c.3369G > T, p.(Leu1123Phe). Another patient presenting with HSN was found to have the known RAB7A pathogenic variant c.484G > A, p.(Val162Met) [32], and a likely pathogenic variant in SPTLC2, c.1142 T > C, p.(Phe381Ser). These results support the effectiveness of multi-gene testing, since traditional or phenotype-led testing would not have picked up these variants, and have implications for recurrence risk and genetic counselling. Focused genetic testing has been supported as an approach to provide diagnosis either in the form of small panels or as a tiered approach, by exclusion of variants in common genes before proceeding to NGS testing. The review and recommendations set out by Murphy et al. and Saporta et al. provided essential guidance for clinicians navigating a sea of individual genes in pursuit of a genetic diagnosis [21, 22]. Elsewhere the approach of CMT phenotype-specific panel testing has been proposed for CMT diagnosis as a means to avoid high cost and difficulty in result interpretation [33]. In our experience NGS is efficient and removes the need for serial gene sequencing in most cases. Testing specific genes according to phenotype association may be beneficial if the patients have a very definite neuropathy subtype and are referred from expert neurology clinics; for example GJB1 in a clearly X-linked pedigree, or PMP22 in HNPP. The cost of design and validation for one large panel is significantly lower than the sum costs of multiple smaller panels. The challenge of variant interpretation should not be underestimated; however prioritisation of variants according to phenotypic compatibility, and the use of in silico tools and public databases has proven to be an efficient approach. By incorporating all 56 genes in one assay, we revealed mutations in genes that would have not emerged had we been limited to a phenotype-derived subset of genes. Other authors have also recently been advocating the benefits of expanded multi-gene testing. Hoyer et al. have reported findings similar to ours, including detection of dual pathology and CMT1 patients with MFN2 mutations [34].

Conclusions

We developed a 56-gene IPN NGS targeted panel assay as a specialist UK Genetic Testing Network service. This is a frontline diagnostic tool and has largely replaced single-gene Sanger sequencing. Testing was completed for 448 patients in the first 18 months post launch. Genetic diagnosis was achieved in 137 patients (31 %). Testing revealed high heterogeneity, dual pathology and less-tight phenotype-genotype associations. Assessment and classification of variants is currently a time consuming process, however this task becomes easier as the tools improve and the databases expand. Detailed clinical information is advantageous for variant interpretation, nonetheless we have highlighted cases that would not have achieved a diagnosis had the phenotype been used to guide gene selection. Clinical-exome or whole-exome sequencing may be appropriate for patients in whom no pathogenic variant is detected on the NGS panel. However, the diagnostic yield achieved at this stage does not support sequencing the exome immediately, despite comparable cost, due to the complexity of analysis of larger data sets. This targeted panel approach has the advantage of producing smaller data sets than exome or genome sequencing, but simultaneously it overcomes the limitation imposed by basing testing decisions on the limited genotype-phenotype data available for the rare genes. It facilitates the testing of category-equivocal cases where the patients do not fit in a particular phenotypic subgroup. It is an efficient approach from the perspective of an accredited diagnostic laboratory, as only one assay needs to be validated. Redesign of the panel is relatively straightforward, allowing inclusion of genes newly identified in IPN pedigrees. Genes with very recently established clinical associations tend not to feature on commercial clinical exome panels which are updated infrequently. The clinical and genetic heterogeneity of IPN makes both diagnosis and genetic counselling quite challenging [21]. The benefits of obtaining a genetic diagnosis include provision of a definite clinical classification (including clarification of equivocal cases) and guidance on prognosis. Furthermore, accurate genetic risk assessment and cascade testing is beneficial not only for the patient but also for their family. As clinical trials progress for some types of CMT, genotyping will be essential. Advances in sequencing technology have made it time and cost effective to screen large numbers of causative genes simultaneously.
  36 in total

1.  PMP22 Thr(118)Met: recessive CMT1 mutation or polymorphism?

Authors:  E Nelis; B Holmberg; R Adolfsson; G Holmgren; C van Broeckhoven
Journal:  Nat Genet       Date:  1997-01       Impact factor: 38.330

Review 2.  Autosomal-recessive forms of demyelinating Charcot-Marie-Tooth disease.

Authors:  O Dubourg; H Azzedine; C Verny; G Durosier; N Birouk; R Gouider; M Salih; A Bouhouche; A Thiam; D Grid; M Mayer; M Ruberg; M Tazir; A Brice; E LeGuern
Journal:  Neuromolecular Med       Date:  2006       Impact factor: 3.843

3.  Variable phenotypes are associated with PMP22 missense mutations.

Authors:  M Russo; M Laurá; J M Polke; M B Davis; J Blake; S Brandner; R A C Hughes; H Houlden; D L H Bennett; M P T Lunn; M M Reilly
Journal:  Neuromuscul Disord       Date:  2010-12-30       Impact factor: 4.296

4.  A novel mutation in the nerve-specific 5'UTR of the GJB1 gene causes X-linked Charcot-Marie-Tooth disease.

Authors:  Sinéad M Murphy; James Polke; Hadi Manji; Julian Blake; Lilla Reiniger; Mary Sweeney; Henry Houlden; Sebastian Brandner; Mary M Reilly
Journal:  J Peripher Nerv Syst       Date:  2011-03       Impact factor: 3.494

5.  PMP22 Thr118Met is not a clinically relevant CMT1 marker.

Authors:  P Young; F Stögbauer; B Eller; P de Jonghe; A Löfgren; V Timmerman; B Rautenstrauss; K Oexle; H Grehl; G Kuhlenbäumer; C Van Broeckhoven; E B Ringelstein; H Funke
Journal:  J Neurol       Date:  2000-09       Impact factor: 4.849

6.  Mechanisms for nonrecurrent genomic rearrangements associated with CMT1A or HNPP: rare CNVs as a cause for missing heritability.

Authors:  Feng Zhang; Pavel Seeman; Pengfei Liu; Marian A J Weterman; Claudia Gonzaga-Jauregui; Charles F Towne; Sat Dev Batish; Els De Vriendt; Peter De Jonghe; Bernd Rautenstrauss; Klaus-Henning Krause; Mehrdad Khajavi; Jan Posadka; Antoon Vandenberghe; Francesc Palau; Lionel Van Maldergem; Frank Baas; Vincent Timmerman; James R Lupski
Journal:  Am J Hum Genet       Date:  2010-05-20       Impact factor: 11.025

7.  MFN2 point mutations occur in 3.4% of Charcot-Marie-Tooth families. An investigation of 232 Norwegian CMT families.

Authors:  Geir J Braathen; Jette C Sand; Ana Lobato; Helle Høyer; Michael B Russell
Journal:  BMC Med Genet       Date:  2010-03-29       Impact factor: 2.103

8.  A major determinant for binding and aminoacylation of tRNA(Ala) in cytoplasmic Alanyl-tRNA synthetase is mutated in dominant axonal Charcot-Marie-Tooth disease.

Authors:  Philippe Latour; Christel Thauvin-Robinet; Chantal Baudelet-Méry; Pierre Soichot; Veronica Cusin; Laurence Faivre; Marie-Claire Locatelli; Martine Mayençon; Annie Sarcey; Emmanuel Broussolle; William Camu; Albert David; Robert Rousson
Journal:  Am J Hum Genet       Date:  2009-12-31       Impact factor: 11.025

9.  A rare myelin protein zero (MPZ) variant alters enhancer activity in vitro and in vivo.

Authors:  Anthony Antonellis; Megan Y Dennis; Grzegorz Burzynski; Jimmy Huynh; Valerie Maduro; Chani J Hodonsky; Mehrdad Khajavi; Kinga Szigeti; Sandeep Mukkamala; Seneca L Bessling; William J Pavan; Andrew S McCallion; James R Lupski; Eric D Green
Journal:  PLoS One       Date:  2010-12-16       Impact factor: 3.240

10.  Next-generation sequencing and genetic diagnosis of Charcot-Marie-Tooth disease.

Authors:  Ashok Verma
Journal:  Ann Indian Acad Neurol       Date:  2014-10       Impact factor: 1.383

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  25 in total

1.  Congenital chloride diarrhea needs to be distinguished from Bartter and Gitelman syndrome.

Authors:  Natsuki Matsunoshita; Kandai Nozu; Masahide Yoshikane; Azusa Kawaguchi; Naoya Fujita; Naoya Morisada; Shingo Ishimori; Tomohiko Yamamura; Shogo Minamikawa; Tomoko Horinouchi; Keita Nakanishi; Junya Fujimura; Takeshi Ninchoji; Ichiro Morioka; Hiroaki Nagase; Mariko Taniguchi-Ikeda; Hiroshi Kaito; Kazumoto Iijima
Journal:  J Hum Genet       Date:  2018-05-30       Impact factor: 3.172

2.  Comprehensive genetic testing approach for major inherited kidney diseases, using next-generation sequencing with a custom panel.

Authors:  Takayasu Mori; Kazuyoshi Hosomichi; Motoko Chiga; Shintaro Mandai; Hirofumi Nakaoka; Eisei Sohara; Tomokazu Okado; Tatemitsu Rai; Sei Sasaki; Ituro Inoue; Shinichi Uchida
Journal:  Clin Exp Nephrol       Date:  2016-02-26       Impact factor: 2.801

3.  Transcriptomic analyses of genes and tissues in inherited sensory neuropathies.

Authors:  Matthew R Sapio; Samridhi C Goswami; Jacklyn R Gross; Andrew J Mannes; Michael J Iadarola
Journal:  Exp Neurol       Date:  2016-06-23       Impact factor: 5.330

4.  Wide phenotypic spectrum in axonal Charcot-Marie-Tooth neuropathy type 2 patients with KIF5A mutations.

Authors:  Da Eun Nam; Da Hye Yoo; Sun Seong Choi; Byung-Ok Choi; Ki Wha Chung
Journal:  Genes Genomics       Date:  2017-10-10       Impact factor: 1.839

Review 5.  Hereditary Neuropathies.

Authors:  Katja Eggermann; Burkhard Gess; Martin Häusler; Joachim Weis; Andreas Hahn; Ingo Kurth
Journal:  Dtsch Arztebl Int       Date:  2018-02-09       Impact factor: 5.594

6.  The Impact of Next-Generation Sequencing on the Diagnosis, Treatment, and Prevention of Hereditary Neuromuscular Disorders.

Authors:  Sarah J Beecroft; Phillipa J Lamont; Samantha Edwards; Hayley Goullée; Mark R Davis; Nigel G Laing; Gianina Ravenscroft
Journal:  Mol Diagn Ther       Date:  2020-09-30       Impact factor: 4.074

Review 7.  Next-generation sequencing in Charcot-Marie-Tooth disease: opportunities and challenges.

Authors:  Menelaos Pipis; Alexander M Rossor; Matilde Laura; Mary M Reilly
Journal:  Nat Rev Neurol       Date:  2019-10-03       Impact factor: 42.937

8.  DYNC1H1 mutations associated with neurological diseases compromise processivity of dynein-dynactin-cargo adaptor complexes.

Authors:  Ha Thi Hoang; Max A Schlager; Andrew P Carter; Simon L Bullock
Journal:  Proc Natl Acad Sci U S A       Date:  2017-02-14       Impact factor: 11.205

9.  Identification of Genetic Causes of Inherited Peripheral Neuropathies by Targeted Gene Panel Sequencing.

Authors:  Soo Hyun Nam; Young Bin Hong; Young Se Hyun; Da Eun Nam; Geon Kwak; Sun Hee Hwang; Byung-Ok Choi; Ki Wha Chung
Journal:  Mol Cells       Date:  2016-03-30       Impact factor: 5.034

10.  Improving molecular diagnosis of Chinese patients with Charcot-Marie-Tooth by targeted next-generation sequencing and functional analysis.

Authors:  Li-Xi Li; Shao-Yun Zhao; Zhi-Jun Liu; Wang Ni; Hong-Fu Li; Bao-Guo Xiao; Zhi-Ying Wu
Journal:  Oncotarget       Date:  2016-05-10
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