Literature DB >> 27900367

Whole-genome sequencing of two probands with hereditary spastic paraplegia reveals novel splice-donor region variant and known pathogenic variant in SPG11.

Allen Chi-Shing Yu1, Anne Yin-Yan Chan2, Wing Chi Au3, Yun Shen4, Ting Fung Chan5, Ho-Yin Edwin Chan6.   

Abstract

Hereditary spastic paraplegias (HSPs) are a group of heterogeneous neurodegenerative disorders, which are often presented with overlapping phenotypes such as progressive paraparesis and spasticity. To assist the diagnosis of HSP subtypes, next-generation sequencing is often used to provide supporting evidence. In this study, we report the case of two probands from the same family with HSP symptoms, including bilateral lower limb weakness, unsteady gait, cognitive decline, dysarthria, and slurring of speech since the age of 14. Subsequent whole-genome sequencing revealed that the patients are compound heterozygous for variants in the SPG11 gene, including the paternally inherited c.6856C>T (p.Arg2286*) variant and the novel maternally inherited c.2316+5G>A splice-donor region variant. Variants in SPG11 are the common cause of autosomal recessive spastic paraplegia type 11. According to the ClinVar database, there are already 101 reported pathogenic variants in SPG11 that are associated with HSPs. To our knowledge, this is the first report of SPG11 variants in our local population. The novel splice variant identified in this study enriches the catalog of SPG11 variants, potentially leading to better genetic diagnosis of HSPs.

Entities:  

Keywords:  gait imbalance; slowed slurred speech; spastic dysarthria; spastic gait; spastic paraparesis; spastic paraplegia

Mesh:

Substances:

Year:  2016        PMID: 27900367      PMCID: PMC5111012          DOI: 10.1101/mcs.a001248

Source DB:  PubMed          Journal:  Cold Spring Harb Mol Case Stud        ISSN: 2373-2873


CASE PRESENTATION

Spastic paraplegia type 11 (SPG11) is a type of autosomal recessive neurological disease characterized by the progression of lower limb muscle stiffness and spasticity and often accompanied with thinning of the corpus callosum, intellectual disability, neuropathy, and a variety of neurological symptoms. Onset time is childhood to early adult (Shibasaki et al. 2000; Casali et al. 2004; Winner et al. 2004; Olmez et al. 2006; Hehr et al. 2007). A majority of SPG11 cases are caused by homozygous recessive or compound heterozygous variants in the SPG11 gene (Stevanin et al. 2007, 2008), which codes for the Spatacsin protein with a role in axonal maintenance, cargo trafficking (Pérez-Brangulí et al. 2014), and autophagy (Chang et al. 2014). Because of overlapping phenotypes in different hereditary spastic paraplegia (HSP) subtypes (Pensato et al. 2014), diagnosis of SPG11 is often supplemented with evidence from molecular genetics testing. In particular, next-generation sequencing is gaining traction as a tool for assisting the diagnosis and treatment of neurological diseases (Tsoi et al. 2014; Petrovski et al. 2015; Yang et al. 2015; Ye et al. 2015). We report the case study of a family with two probands that showed HSP symptoms (Fig. 1A). Both parents were asymptomatic without history of consanguineous marriages. The age of disease onset for the probands was 14, when both of them showed bilateral lower limb weakness and unsteady gait (Table 1). Subsequently, they developed slurring of speech, dysarthria, and cognitive decline. The elder female proband (II:2) presented with slower disease progression, and she is still able to walk with aids. On the other hand, the younger male proband (II:1) suffered from rapid deterioration over a few years after onset and became bedridden. Extensive workup had been done including serum copper, cortisol, cholestanol, campesterol, stigmasterol, and β-sitosterol levels; however, all of these indicators were normal. Further skin biopsy and urine testing for porphyrin also showed negative results. The magnetic resonance imaging (MRI) brain imaging for II:1 showed mild cerebral and cerebellar atrophy at the age of 25, which is compatible with his symptoms of cognitive decline and unsteady gait (Supplemental Fig. 1).
Figure 1.

Compound heterozygous variants in SPG11 in probands. (A) Pedigree of family under study. The two probands inherited compound heterozygous variants (ENST00000261866:c.6856C>T;p.Arg2286* and ENST00000261866:c.2316+5G>A) from unaffected parents. Sanger sequencing validation of (B) the ENST00000261866:c.2316+5G>A variant and (C) the ENST00000261866:c.6856C>T;p.Arg2286* variant. Mutated positions are marked with red arrows. (D) Multiz alignments of vertebrates showed a high degree of conservation at the mutated location.

Table 1.

Clinical parameters of the two probands investigated in this study

II:2II:1
Age3129
GenderFemaleMale
Age of onset14 years old14 years old
Presenting symptomsUnsteady gaitUnsteady gait
Cognitive declineYesYes
PsychosisNoYes
SpasticityYesYes
Compound heterozygous variants in SPG11 in probands. (A) Pedigree of family under study. The two probands inherited compound heterozygous variants (ENST00000261866:c.6856C>T;p.Arg2286* and ENST00000261866:c.2316+5G>A) from unaffected parents. Sanger sequencing validation of (B) the ENST00000261866:c.2316+5G>A variant and (C) the ENST00000261866:c.6856C>T;p.Arg2286* variant. Mutated positions are marked with red arrows. (D) Multiz alignments of vertebrates showed a high degree of conservation at the mutated location. Clinical parameters of the two probands investigated in this study

METHODS

To elucidate the diagnosis of the HSP subtype and potentially inform clinical decisions, whole-genome sequencing was performed using the Illumina HiSeq X Ten platform for all four family members, including the two probands and two unaffected parents. On average, ∼214.8 Gb (∼66.4× depth of coverage) of DNA sequence was generated for each individual (Supplemental Table 1). The short read sequences were aligned to the human genome (version GRCh38) using Burrows–Wheeler alignment (BWA) (version 0.7.12) (Li and Durbin 2009), followed by polymerase chain reaction (PCR) duplicate marking, local realignment around indels, and base quality score recalibration using Picard (version 1.141) tools and the Genome Analysis Toolkit (GATK, version 3.4) (McKenna et al. 2010). Sequence variants and small indels were called according to the best practices for using the GATK HaplotypeCaller (McKenna et al. 2010), resulting in ∼4,790,000 sequence variants and small indels. Because HSP is a rare disease affecting 1–10 in 100,000 individuals depending on the geographical location (Fink 2006), common variants with a minor allele frequency (MAF) >5% were filtered, leaving ∼450,000 variants on average per individual (Supplemental Table 1). Finally, variant annotation was performed using SnpEff (Cingolani et al. 2012) and dbNSFP (Database for Nonsynonymous SNPs’ Functional Predictions; Liu et al. 2013). Published guidelines from the American College of Medical Genetics and Genomics (ACMG) were used for interpretation of the variants (Richards et al. 2015). Copy-number variants and structural variants were called using LUMPY (version 0.2.11) (Layer et al. 2014), yet none of these larger scale variants match the inheritance pattern. Sequence variants focused in this study were validated using conventional Sanger sequencing analysis (Table 2).
Table 2.

List of variants in SPG11

Genomic location (GRCh38)dbSNP/ClinVarHGVS1000G MAFVariant interpretationCADDMutationTasterI:2I:1II:1II:2
Chr15: 44565997rs312262785/41353ENST00000261866:c.6856C>T; p.Arg2286*0.0002Pathogenic (PVS1, PM1, PM2, PP3, PP4)Pathogenic (47)Disease causing (1)N/A0/10/10/1
Chr15: 44622723rs879255274/252959ENST00000261866:c.2316+5G>AENST00000559193:c.2321G>A; p.Gly774AspN/ALikely pathogenic (PM2, PM3, PP1, PP3, PP4)Pathogenic (19.36)Disease causing (1)0/1N/A0/10/1
Chr15: 44651599rs3759873/130364ENST00000261866:c.1348A>G; p.Ile450Val0.0389Benign (BA1, BS1, BS4, BP4)Neutral (0.002)Polymorphism (0.994)N/A0/1N/AN/A

Genotypes for each family member are shown in the right-most columns, in which 0/1 represents heterozygous. Parenthetical codes in the Variant interpretation column denote the pathogenic criteria in the ACMG (American College of Genetics and Genomics) guidelines 2015 (Richards et al. 2015). Predicted functional impact on the transcript and protein was calculated by SnpEff, CADD, and MutationTaster. Numbers in the CADD column denote the degree of pathogenicity in Phred scale. Numbers in the MutationTaster column denote the confidence of pathogenicity classification, in which 1 is the most confident and 0 is the least confident.

dbSNP, Database for Short Genetic Variations; HGVS, Human Genome Variation Society; 1000G, 1000 Genomes; MAF minor allele frequency; CADD, Combined Annotation-Dependent Depletion; N/A, not applicable.

List of variants in SPG11 Genotypes for each family member are shown in the right-most columns, in which 0/1 represents heterozygous. Parenthetical codes in the Variant interpretation column denote the pathogenic criteria in the ACMG (American College of Genetics and Genomics) guidelines 2015 (Richards et al. 2015). Predicted functional impact on the transcript and protein was calculated by SnpEff, CADD, and MutationTaster. Numbers in the CADD column denote the degree of pathogenicity in Phred scale. Numbers in the MutationTaster column denote the confidence of pathogenicity classification, in which 1 is the most confident and 0 is the least confident. dbSNP, Database for Short Genetic Variations; HGVS, Human Genome Variation Society; 1000G, 1000 Genomes; MAF minor allele frequency; CADD, Combined Annotation-Dependent Depletion; N/A, not applicable.

VARIANT INTERPRETATION

After annotation of variants in accordance to the ACMG standards (Richards et al. 2015), one pathogenic nonsense variant was discovered in SPG11 (ENST00000261866:c.6856C>T; p.Arg2286*). The variant is extremely rare, where the global MAF of the variant is 0.0002 (1/5008) in the 1000 Genomes Project Phase III or 1.664 × 10−5 (2/120202) in the Exome Aggregation Consortium (ExAC). The p.Arg2286* variant is known to be associated with autosomal recessive SPG11 (Denora et al. 2009) and recorded as a pathogenic variant in the ClinVar database (Variation ID: 41353). Subsequent Sanger sequencing validation confirmed that all probands are heterozygous carriers of the allele (Fig. 1A,B). However, the heterozygous variant alone cannot fully explain the observed autosomal recessive inheritance pattern, because the unaffected father also carries the p.Arg2286* variant (Fig. 1A,B). This suggests the possibility of compound heterozygosity, in which more than one variant contributes to the autosomal recessive pattern. To explore the possibility of compound heterozygosity, we expanded the search of SPG11 sequence variants and indels to the ACMG “Likely Pathogenic” and “Unknown Significance” tiers. One heterozygous variant in the splice-donor region of SPG11 exon 12 (ENST00000261866:c.2316+5G>A) was found to be shared by two probands and the unaffected mother, which was subsequently validated using Sanger sequencing (Fig. 1C). This novel variant was not described in the 1000 Genomes Project Phase III, the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), nor the ExAC database. Based on multiple sequence alignment of SPG11 sequences from six vertebrates, c.6856C>T and c.2316+5G>A variants were located in a conserved location (Fig. 1D). The variant's impact on splice pattern was further assessed using Human Splicing Finder (HSF) (Desmet et al. 2009) and Alternative Splice Site Predictor (ASSP) (Wang and Marín 2006). HSF showed that the mutant splice site would be 92% weaker than wild type based on the MaxEnt model, whereas ASSP suggested that the variant would lead to the loss of the splice-donor site. Because of alternative splicing, this novel variant can also be found in the coding region of the alternative transcript (ENST00000559193:c.2321G>A; p.Gly774Asp). However, ENST00000559193 is not expressed in brain, whereas ENST00000261866 is the most abundant transcript among those with Transcription Support Level 1 in the Genotype-Tissue Expression (GTEx) project (Lonsdale et al. 2013). This suggests that the variant mainly exerts its impact through ENST00000261866:c.2316+5G>A. The novel maternally inherited c.2316+5G>A variant, in combination with the paternally inherited c.6856C>T (p.Arg2286*) variant, supports the compound heterozygous diagnosis of SPG11.

SUMMARY

The SPG11 gene encodes for the Spatacsin protein, yet the detailed molecular function of Spatacsin is not well understood. It was suggested that axonal defects were observed in patients with nonsense and splice variants in SPG11, which is further supported by a functional study using a mouse model (Pérez-Brangulí et al. 2014). Loss of Spatacsin also causes accumulation of autolysosomes and deprivation of free lysosomes, thereby disrupting the autophagic lysosome reformation pathway, ultimately leading to neurodegeneration (Chang et al. 2014). In this study, we have identified compound heterozygous variants in SPG11 that were predicted to cause truncation of the corresponding protein. The p.Arg2286* nonsense variant was previously reported to be associated with SPG11 (Denora et al. 2009); while in the vicinity of the novel c.2316+5G>A variant identified in this study, a splice variant (c.2316+1G>A) was previously linked to SPG11 (Stevanin et al. 2008). In a recent large-scale investigation of SPG11 cases in London, 79.5% of SPG11 variants were found to be nonsense, frameshift, or splice-site variants that could cause large-scale amino acid sequence changes (Kara et al. 2016). Because both variants identified in this study were predicted to cause the truncation of Spatacsin, findings in this study further supported the major role of loss-of-function variants in SPG11 pathogenesis (Pensato et al. 2014; Pérez-Brangulí et al. 2014). To our knowledge, our study is the first report of SPG11 variants in the Hong Kong population. The novel splice variant identified in this study expands the repertoire of SPG11 variants, facilitating the molecular genetic testing of HSP.

ADDITIONAL INFORMATION

Data Deposition and Access

Raw sequencing data were deposited to the European Genome-phenome Archive (EGA; http://www.ebi.ac.uk/ega) under accession number EGAS00001001849. The variant was deposited in ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) under accession number SCV000292372.

Ethics Statement

Informed and signed consent forms were obtained for all sequenced individuals of this study. The project is approved by The Joint Chinese University of Hong Kong–New Territories East Cluster Clinical Research Ethics Committee (CRE-2012.361).

Author Contributions

Patients were recruited and phenotyped by A.Y.-Y.C. and W.C.A. Data analysis, interpretation, and validation were performed by A.C.-S.Y. and Y.S. The manuscript was prepared by A.C.-S.Y., A.Y.-Y.C., Y.S., H.-Y.E.C., and T.F.C. All authors contributed to the reviewing of the final version.

Funding

This work was partially supported by the Chow Tai Fook Charity Foundation (6903898), Hong Kong Spinocerebellar Ataxia Association (6903291), and Gerald Choa Neuroscience Centre (7105306) grants to H.-Y.E.C. A.C.-S.Y. and T.F.C. are supported by the Research Grants Council (RGC) General Research Fund (GRF14102014) and Collaborative Research Fund (CRF: C4042-14G).

Competing Interest Statement

T.F.C. and H.-Y.E.C. are scientific advisors of Codex Genetics Limited (Codex), and A.C.-S.Y. is the genetic scientist at the same company. However, neither financial relationships nor activities with Codex appear to have influenced the submitted work.
  25 in total

1.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Authors:  Aaron McKenna; Matthew Hanna; Eric Banks; Andrey Sivachenko; Kristian Cibulskis; Andrew Kernytsky; Kiran Garimella; David Altshuler; Stacey Gabriel; Mark Daly; Mark A DePristo
Journal:  Genome Res       Date:  2010-07-19       Impact factor: 9.043

2.  Linkage of autosomal recessive hereditary spastic paraplegia with mental impairment and thin corpus callosum to chromosome 15A13-15.

Authors:  Y Shibasaki; H Tanaka; K Iwabuchi; S Kawasaki; H Kondo; K Uekawa; M Ueda; T Kamiya; Y Katayama; A Nakamura; H Takashima; M Nakagawa; M Masuda; H Utsumi; T Nakamuro; K Tada; K Kurohara; K Inoue; F Koike; T Sakai; S Tsuji; H Kobayashi
Journal:  Ann Neurol       Date:  2000-07       Impact factor: 10.422

3.  Characterization and prediction of alternative splice sites.

Authors:  Magnus Wang; Antonio Marín
Journal:  Gene       Date:  2005-10-13       Impact factor: 3.688

4.  Long-term course and mutational spectrum of spatacsin-linked spastic paraplegia.

Authors:  Ute Hehr; Peter Bauer; Beate Winner; Rebecca Schule; Akguen Olmez; Wolfgang Koehler; Goekhan Uyanik; Anna Engel; Daniela Lenz; Andrea Seibel; Andreas Hehr; Sonja Ploetz; Josep Gamez; Arndt Rolfs; Joachim Weis; Thomas M Ringer; Michael Bonin; Gerhard Schuierer; Joerg Marienhagen; Ulrich Bogdahn; Bernhard H F Weber; Haluk Topaloglu; Ludger Schols; Olaf Riess; Juergen Winkler
Journal:  Ann Neurol       Date:  2007-12       Impact factor: 10.422

5.  dbNSFP v2.0: a database of human non-synonymous SNVs and their functional predictions and annotations.

Authors:  Xiaoming Liu; Xueqiu Jian; Eric Boerwinkle
Journal:  Hum Mutat       Date:  2013-07-10       Impact factor: 4.878

6.  Mutations in SPG11, encoding spatacsin, are a major cause of spastic paraplegia with thin corpus callosum.

Authors:  Giovanni Stevanin; Filippo M Santorelli; Hamid Azzedine; Paula Coutinho; Jacques Chomilier; Paola S Denora; Elodie Martin; Anne-Marie Ouvrard-Hernandez; Alessandra Tessa; Naïma Bouslam; Alexander Lossos; Perrine Charles; José L Loureiro; Nizar Elleuch; Christian Confavreux; Vítor T Cruz; Merle Ruberg; Eric Leguern; Djamel Grid; Meriem Tazir; Bertrand Fontaine; Alessandro Filla; Enrico Bertini; Alexandra Durr; Alexis Brice
Journal:  Nat Genet       Date:  2007-02-18       Impact factor: 38.330

7.  Dysfunction of spatacsin leads to axonal pathology in SPG11-linked hereditary spastic paraplegia.

Authors:  Francesc Pérez-Brangulí; Himanshu K Mishra; Iryna Prots; Steven Havlicek; Zacharias Kohl; Domenica Saul; Christine Rummel; Jonatan Dorca-Arevalo; Martin Regensburger; Daniela Graef; Elisabeth Sock; Juan Blasi; Teja W Groemer; Ursula Schlötzer-Schrehardt; Jürgen Winkler; Beate Winner
Journal:  Hum Mol Genet       Date:  2014-05-02       Impact factor: 6.150

8.  A novel missense mutation in CCDC88C activates the JNK pathway and causes a dominant form of spinocerebellar ataxia.

Authors:  Ho Tsoi; Allen C S Yu; Zhefan S Chen; Nelson K N Ng; Anne Y Y Chan; Liz Y P Yuen; Jill M Abrigo; Suk Ying Tsang; Stephen K W Tsui; Tony M F Tong; Ivan F M Lo; Stephen T S Lam; Vincent C T Mok; Lawrence K S Wong; Jacky C K Ngo; Kwok-Fai Lau; Ting-Fung Chan; H Y Edwin Chan
Journal:  J Med Genet       Date:  2014-07-25       Impact factor: 5.941

9.  Clinical and genetic studies in hereditary spastic paraplegia with thin corpus callosum.

Authors:  C Casali; E M Valente; E Bertini; G Montagna; C Criscuolo; G De Michele; M Villanova; M Damiano; A Pierallini; F Brancati; V Scarano; A Tessa; F Cricchi; G S Grieco; M Muglia; M Carella; B Martini; A Rossi; G A Amabile; G Nappi; A Filla; B Dallapiccola; F M Santorelli
Journal:  Neurology       Date:  2004-01-27       Impact factor: 9.910

10.  De novo truncating variants in the AHDC1 gene encoding the AT-hook DNA-binding motif-containing protein 1 are associated with intellectual disability and developmental delay.

Authors:  Hui Yang; Ganka Douglas; Kristin G Monaghan; Kyle Retterer; Megan T Cho; Luis F Escobar; Megan E Tucker; Joan Stoler; Lance H Rodan; Diane Stein; Warren Marks; Gregory M Enns; Julia Platt; Rachel Cox; Patricia G Wheeler; Carrie Crain; Amy Calhoun; Rebecca Tryon; Gabriele Richard; Patrik Vitazka; Wendy K Chung
Journal:  Cold Spring Harb Mol Case Stud       Date:  2015-10
View more
  5 in total

1.  Three novel mutations in 20 patients with hereditary spastic paraparesis.

Authors:  Mehmet Bugrahan Duz; Selcuk Dasdemir; Aysel Kalayci Yigin; Mehmet Ali Akalin; Mehmet Seven
Journal:  Neurol Sci       Date:  2018-06-16       Impact factor: 3.307

Review 2.  Alternative Splicing of ALS Genes: Misregulation and Potential Therapies.

Authors:  Benedetta Perrone; Valentina La Cognata; Teresa Sprovieri; Carmine Ungaro; Francesca Luisa Conforti; Sebastiano Andò; Sebastiano Cavallaro
Journal:  Cell Mol Neurobiol       Date:  2019-08-05       Impact factor: 5.046

3.  Phen2Gene: rapid phenotype-driven gene prioritization for rare diseases.

Authors:  Mengge Zhao; James M Havrilla; Li Fang; Ying Chen; Jacqueline Peng; Cong Liu; Chao Wu; Mahdi Sarmady; Pablo Botas; Julián Isla; Gholson J Lyon; Chunhua Weng; Kai Wang
Journal:  NAR Genom Bioinform       Date:  2020-05-25

4.  A Targeted Gene Panel That Covers Coding, Non-coding and Short Tandem Repeat Regions Improves the Diagnosis of Patients With Neurodegenerative Diseases.

Authors:  Allen Chi-Shing Yu; Aldrin Kay-Yuen Yim; Anne Yin-Yan Chan; Liz Y P Yuen; Wing Chi Au; Timothy H T Cheng; Xiao Lin; Jing-Woei Li; Larry W L Chan; Vincent C T Mok; Ting-Fung Chan; Ho Yin Edwin Chan
Journal:  Front Neurosci       Date:  2019-12-11       Impact factor: 4.677

5.  PheNominal: an EHR-integrated web application for structured deep phenotyping at the point of care.

Authors:  James M Havrilla; Anbumalar Singaravelu; Dennis M Driscoll; Leonard Minkovsky; Ingo Helbig; Livija Medne; Kai Wang; Ian Krantz; Bimal R Desai
Journal:  BMC Med Inform Decis Mak       Date:  2022-07-28       Impact factor: 3.298

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.