Download PDF
CC BY 4.0 · Glob Med Genet 2022; 09(03): 200-207
DOI: 10.1055/s-0042-1745873
Original Article

Investigating the Genetic Etiology of Pediatric Patients with Peripheral Hypotonia Using the Next-Generation Sequencing Method

Damla Eker 
1   Department of Medical Genetics, Faculty of Medicine, Trakya University, Edirne, Turkey
,
Hakan Gurkan
1   Department of Medical Genetics, Faculty of Medicine, Trakya University, Edirne, Turkey
,
Yasemin Karal
2   Department of Pediatric Neurology, Faculty of Medicine, Trakya University, Edirne, Turkey
,
Sinem Yalcintepe
1   Department of Medical Genetics, Faculty of Medicine, Trakya University, Edirne, Turkey
,
Selma Demir
1   Department of Medical Genetics, Faculty of Medicine, Trakya University, Edirne, Turkey
,
Engin Atli
1   Department of Medical Genetics, Faculty of Medicine, Trakya University, Edirne, Turkey
,
Serap T. Karasalihoglu
2   Department of Pediatric Neurology, Faculty of Medicine, Trakya University, Edirne, Turkey
› Author Affiliations Funding This study was funded by the Scientific Research Projects Unit of Trakya University with the project number 2018/268.
› Further Information
   Permissions and Reprints

Abstract

Background Hypotonia occurs as a result of neurological dysfunction in the brain, brainstem, spinal cord, motor neurons, anterior horn cells, peripheral nerves, and muscles. Although the genotype–phenotype correlation can be established in 15 to 30% of patients, it is difficult to obtain a correlation in most cases.

Aims This study was aimed to investigate the genetic etiology in cases of peripheral hypotonia that could not be diagnosed using conventional methods.

Methods A total of 18 pediatric patients with peripheral hypotonia were included. They were referred to our genetic disorders diagnosis center from the Pediatric Neurology Department with a prediagnosis of hypotonia. A custom designed multigene panel, including ACTA1, CCDC78, DYNC1H1, GARS, RYR1, COL6A1, COL6A2, COL6A3, FKRP, FKTN, IGHMBP2, LMNA, LAMA2, LARGE1, MTM1, NEM, POMGnT1, POMT1, POMT2, and SEPN1, was used for genetic analysis using next-generation sequencing (NGS).

Results In our study, we found 13 variants including pathogenic (two variants in LAMA2) and likely pathogenic variants (three variants in RYR1 and POMGnT1) and variants of uncertain clinical significance (eight variants in RYR1, COL6A3, COL6A2, POMGnT1 and POMT1) in 11 (61%) out of 18 patients. In one of our patients, a homozygous, likely pathogenic c.1649G > A, p.(Ser550Asn) variant was defined in the POMGnT1 gene which was associated with a muscle–eye–brain disease phenotype.

Conclusion The contribution of an in-house designed gene panel in the etiology of peripheral hypotonia with a clinical diagnosis was 5.5%. An important contribution with the clinical diagnosis can be made using the targeted multigene panels in larger samples.

Keywords

hypotonia - peripheral hypotonia - next-generation sequencing - genetic etiology - multigene panel

Authors' Contributions

D.E. devised the project, the main conceptual ideas, and worked the technical details. D.E. and H.G. conceived the study and were in charge of overall direction and planning. Y.K., H.G., S.T.K., and S.Y. followed-up the patients. D.E., H.G., S.D., and E.A. contributed to the analysis and interpretation of the study. All authors approved and contributed to the final version of the manuscript.




Publication History

Article published online:
15 July 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Stuttgart · New York

 

  • References

  • 1 Bayram E, Yiş U, Kurul S. Hypotonic infant: clinical and etiological evaluation. DAE 2012; 26 (03) 219-228
    Google Scholar
  • 2 Lisi EC, Cohn RD. Genetic evaluation of the pediatric patient with hypotonia: perspective from a hypotonia specialty clinic and review of the literature. Dev Med Child Neurol 2011; 53 (07) 586-599
    CrossrefPubMedGoogle Scholar
  • 3 Peredo DE, Hannibal MC. The floppy infant: evaluation of hypotonia. Pediatr Rev 2009; 30 (09) e66-e76
    CrossrefPubMedGoogle Scholar
  • 4 Sparks SE. Neonatal hypotonia. Clin Perinatol 2015; 42 (02) 363-371 , ix
    CrossrefPubMedGoogle Scholar
  • 5 Prasad AN, Prasad C. Genetic evaluation of the floppy infant. Semin Fetal Neonatal Med 2011; 16 (02) 99-108
    CrossrefPubMedGoogle Scholar
  • 6 D'Amico A, Mercuri E, Tiziano FD, Bertini E. Spinal muscular atrophy. Orphanet J Rare Dis 2011; 6: 71
    CrossrefPubMedGoogle Scholar
  • 7 Wang Y, Peng W, Guo HY. et al. Next-generation sequencing-based molecular diagnosis of neonatal hypotonia in Chinese Population. Sci Rep 2016; 6: 29088
    CrossrefPubMedGoogle Scholar
  • 8 Chae JH, Vasta V, Cho A. et al. Utility of next generation sequencing in genetic diagnosis of early onset neuromuscular disorders. J Med Genet 2015; 52 (03) 208-216
    CrossrefPubMedGoogle Scholar
  • 9 Vasli N, Böhm J, Le Gras S. et al. Next generation sequencing for molecular diagnosis of neuromuscular diseases. Acta Neuropathol 2012; 124 (02) 273-283
    CrossrefPubMedGoogle Scholar
  • 10 Kitamura Y, Kondo E, Urano M, Aoki R, Saito K. Target resequencing of neuromuscular disease-related genes using next-generation sequencing for patients with undiagnosed early-onset neuromuscular disorders. J Hum Genet 2016; 61 (11) 931-942
    CrossrefPubMedGoogle Scholar
  • 11 Gonzalez-Quereda L, Rodriguez MJ, Diaz-Manera J. et al. Targeted next-generation sequencing in a large cohort of genetically undiagnosed patients with neuromuscular disorders in Spain. Genes (Basel) 2020; 11 (05) 539
    CrossrefPubMedGoogle Scholar
  • 12 Karczewski KJ, Francioli LC, Tiao G. et al; Genome Aggregation Database Consortium. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 2020; 581 (7809): 434-443
    CrossrefPubMedGoogle Scholar
  • 13 Schwarz JM, Rödelsperger C, Schuelke M, Seelow D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat Methods 2010; 7 (08) 575-576
    CrossrefPubMedGoogle Scholar
  • 14 Adzhubei IA, Schmidt S, Peshkin L. et al. A method and server for predicting damaging missense mutations. Nat Methods 2010; 7 (04) 248-249
    CrossrefPubMedGoogle Scholar
  • 15 Sim NL, Kumar P, Hu J, Henikoff S, Schneider G, Ng PC. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res 2012; 40 (Web Server issue): W452-7
    PubMedGoogle Scholar
  • 16 Quang D, Chen Y, Xie X. DANN: a deep learning approach for annotating the pathogenicity of genetic variants. Bioinformatics 2015; 31 (05) 761-763
    CrossrefPubMedGoogle Scholar
  • 17 Rentzsch P, Witten D, Cooper GM, Shendure J, Kircher M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res 2019; 47 (D1) D886-D894
    CrossrefPubMedGoogle Scholar
  • 18 Davydov EV, Goode DL, Sirota M, Cooper GM, Sidow A, Batzoglou S. Identifying a high fraction of the human genome to be under selective constraint using GERP++. PLOS Comput Biol 2010; 6 (12) e1001025
    CrossrefPubMedGoogle Scholar
  • 19 Richards S, Aziz N, Bale S. et al; ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015; 17 (05) 405-424
    Google Scholar
  • 20 Paro-Panjan D, Neubauer D. Congenital hypotonia: is there an algorithm?. J Child Neurol 2004; 19 (06) 439-442
    CrossrefPubMedGoogle Scholar
  • 21 Laugel V, Cossée M, Matis J. et al. Diagnostic approach to neonatal hypotonia: retrospective study on 144 neonates. Eur J Pediatr 2008; 167 (05) 517-523
    CrossrefPubMedGoogle Scholar
  • 22 Birdi K, Prasad AN, Prasad C, Chodirker B, Chudley AE. The floppy infant: retrospective analysis of clinical experience (1990-2000) in a tertiary care facility. J Child Neurol 2005; 20 (10) 803-808
    CrossrefPubMedGoogle Scholar
  • 23 Richer LP, Shevell MI, Miller SP. Diagnostic profile of neonatal hypotonia: an 11-year study. Pediatr Neurol 2001; 25 (01) 32-37
    CrossrefPubMedGoogle Scholar
  • 24 Warman Chardon J, Beaulieu C, Hartley T, Boycott KM, Dyment DA. Axons to exons: the molecular diagnosis of rare neurological diseases by next-generation sequencing. Curr Neurol Neurosci Rep 2015; 15 (09) 64
    CrossrefPubMedGoogle Scholar
  • 25 Özaydın E, Ürey T, Gündüz M, Güven A, Köse G. Hipotonik infantların ayırıcı tanısında algoritma faydalı mıdır? 53 Olgunun Değerlendirilmesi. Turkish J Pediatr Dis. 2013; 3: 128-133
    Google Scholar
  • 26 Davis MR, Haan E, Jungbluth H. et al. Principal mutation hotspot for central core disease and related myopathies in the C-terminal transmembrane region of the RYR1 gene. Neuromuscul Disord 2003; 13 (02) 151-157
    CrossrefPubMedGoogle Scholar
  • 27 Amburgey K, Bailey A, Hwang JH. et al. Genotype-phenotype correlations in recessive RYR1-related myopathies. Orphanet J Rare Dis 2013; 8: 117
    CrossrefPubMedGoogle Scholar
  • 28 Uribe ML, Haro C, Ventero MP, Campello L, Cruces J, Martín-Nieto J. Expression pattern in retinal photoreceptors of POMGnT1, a protein involved in muscle-eye-brain disease. Mol Vis 2016; 22: 658-673
    PubMedGoogle Scholar
  • 29 Yiş U, Uyanik G, Rosendahl DM. et al. Clinical, radiological, and genetic survey of patients with muscle-eye-brain disease caused by mutations in POMGNT1. Pediatr Neurol 2014; 50 (05) 491-497
    CrossrefPubMedGoogle Scholar
  • 30 Demir E, Gucuyener K, Akturk A. et al. An unusual presentation of muscle-eye-brain disease: severe eye abnormalities with mild muscle and brain involvement. Neuromuscul Disord 2009; 19 (10) 692-695
    CrossrefPubMedGoogle Scholar
  • 31 Endo T, Manya H, Seta N, Guicheney P. POMGnT1, POMT1, and POMT2 mutations in congenital muscular dystrophies. Methods Enzymol 2010; 479: 343-352
    CrossrefPubMedGoogle Scholar
  • 32 Yoshida A, Kobayashi K, Manya H. et al. Muscular dystrophy and neuronal migration disorder caused by mutations in a glycosyltransferase, POMGnT1. Dev Cell 2001; 1 (05) 717-724
    CrossrefPubMedGoogle Scholar
  • 33 Taniguchi K, Kobayashi K, Saito K. et al. Worldwide distribution and broader clinical spectrum of muscle-eye-brain disease. Hum Mol Genet 2003; 12 (05) 527-534
    CrossrefPubMedGoogle Scholar
  • 34 Bönnemann CG. The collagen VI-related myopathies Ullrich congenital muscular dystrophy and Bethlem myopathy. Handb Clin Neurol 2011; 101: 81-96
    CrossrefPubMedGoogle Scholar
  • 35 Lee JH, Shin HY, Park HJ, Kim SH, Kim SM, Choi YC. Clinical, pathologic, and genetic features of collagen VI-related myopathy in Korea. J Clin Neurol 2017; 13 (04) 331-339
    CrossrefPubMedGoogle Scholar
  • 36 Briñas L, Richard P, Quijano-Roy S. et al. Early onset collagen VI myopathies: genetic and clinical correlations. Ann Neurol 2010; 68 (04) 511-520
    CrossrefPubMedGoogle Scholar
  • 37 Fan Y, Liu A, Wei C. et al. Genetic and clinical findings in a Chinese cohort of patients with collagen VI-related myopathies. Clin Genet 2018; 93 (06) 1159-1171
    CrossrefPubMedGoogle Scholar
  • 38 Peat RA, Baker NL, Jones KJ, North KN, Lamandé SR. Variable penetrance of COL6A1 null mutations: implications for prenatal diagnosis and genetic counselling in Ullrich congenital muscular dystrophy families. Neuromuscul Disord 2007; 17 (07) 547-557
    CrossrefPubMedGoogle Scholar