Genomics & Informatics

Korea Genome Organization (한국유전체학회)
권호 표지
DOI QR코드

DOI QR Code

Presentation of potential genes and deleterious variants associated with non-syndromic hearing loss: a computational approach

  • Ray, Manisha (Department of Pathology and Lab Medicine, All India Institute of Medical Sciences) ;
  • Rath, Surya Narayan (Department of Bioinformatics, Odisha University of Agriculture and Technology) ;
  • Sarkar, Saurav (Department of Ear Nose Throat, All India Institute of Medical Sciences) ;
  • Sable, Mukund Namdev (Department of Pathology and Lab Medicine, All India Institute of Medical Sciences)
  • Received : 2021.11.15
  • Accepted : 2022.02.17
  • Published : 2022.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Non-syndromic hearing loss (NSHL) is a common hereditary disorder. Both clinical and genetic heterogeneity has created many obstacles to understanding the causes of NSHL. The present study has attempted to ravel the genetic aetiology in NSHL progression and to screen out potential target genes using computational approaches. The reported NSHL target genes (2009-2020) have been studied by analyzing different biochemical and signaling pathways, interpretation of their functional association network, and discovery of important regulatory interactions with three previously established miRNAs in the human inner ear as well as in NSHL such as miR-183, miR-182, and miR-96. This study has identified SMAD4 and SNAI2 as the most putative target genes of NSHL. But pathogenic and deleterious non-synonymous single nucleotide polymorphisms discovered within SMAD4 is anticipated to have an impact on NSHL progression. Additionally, the identified deleterious variants in the functional domains of SMAD4 added a supportive clue for further study. Thus, the identified deleterious variant i.e., rs377767367 (G491V) in SMAD4 needs further clinical validation. The present outcomes would provide insights into the genetics of NSHL progression.

Keywords

Acknowledgement

We are thankful to Indian Council of Medical Research (ICMR), New Delhi for providing the Senior Research fellowship.

References

  1. Yuan Y, You Y, Huang D, Cui J, Wang Y, Wang Q, et al. Comprehensive molecular etiology analysis of nonsyndromic hearing impairment from typical areas in China. J Transl Med 2009;7:79. https://doi.org/10.1186/1479-5876-7-79
  2. Bitarafan F, Seyedena SY, Mahmoudi M, Garshasbi M. Identification of novel variants in Iranian consanguineous pedigrees with nonsyndromic hearing loss by next-generation sequencing. J Clin Lab Anal 2020;34:e23544. https://doi.org/10.1002/jcla.23544
  3. Cunningham LL, Tucci DL. Hearing loss in adults. N Engl J Med 2017;377:2465-2473. https://doi.org/10.1056/NEJMra1616601
  4. Korver AM, Smith RJ, Van Camp G, Schleiss MR, Bitner-Glindzicz MA, Lustig LR, et al. Congenital hearing loss. Nat Rev Dis Primers 2017;3:16094. https://doi.org/10.1038/nrdp.2016.94
  5. Schrijver I. Hereditary non-syndromic sensorineural hearing loss: transforming silence to sound. J Mol Diagn 2004;6:275-284. https://doi.org/10.1016/S1525-1578(10)60522-3
  6. Sindura KP, Banerjee M. An immunological perspective to non-syndromic sensorineural hearing loss. Front Immunol 2019;10:2848. https://doi.org/10.3389/fimmu.2019.02848
  7. Bozanic Urbancic N, Battelino S, Tesovnik T, Trebusak Podkrajsek K. The importance of early genetic diagnostics of hearing loss in children. Medicina (Kaunas) 2020;56:471. https://doi.org/10.3390/medicina56090471
  8. Cabanillas R, Dineiro M, Cifuentes GA, Castillo D, Pruneda PC, Alvarez R, et al. Comprehensive genomic diagnosis of non-syndromic and syndromic hereditary hearing loss in Spanish patients. BMC Med Genomics 2018;11:58. https://doi.org/10.1186/s12920-018-0375-5
  9. Shaffer JR, Feingold E, Marazita ML. Genome-wide association studies: prospects and challenges for oral health. J Dent Res 2012;91:637-641. https://doi.org/10.1177/0022034512446968
  10. Bush WS, Moore JH. Chapter 11: Genome-wide association studies. PLoS Comput Biol 2012;8:e1002822. https://doi.org/10.1371/journal.pcbi.1002822
  11. Schenone M, Dancik V, Wagner BK, Clemons PA. Target identification and mechanism of action in chemical biology and drug discovery. Nat Chem Biol 2013;9:232-240. https://doi.org/10.1038/nchembio.1199
  12. Rai A, Shinde P, Jalan S. Network spectra for drug-target identification in complex diseases: new guns against old foes. Appl Netw Sci 2018;3:51. https://doi.org/10.1007/s41109-018-0107-y
  13. Udhaya Kumar S, Thirumal Kumar D, Bithia R, Sankar S, Magesh R, Sidenna M, et al. Analysis of differentially expressed genes and molecular pathways in familial hypercholesterolemia involved in atherosclerosis: a systematic and bioinformatics approach. Front Genet 2020;11:734. https://doi.org/10.3389/fgene.2020.00734
  14. Zhu HM, Fei Q, Qian LX, Liu BL, He X, Yin L. Identification of key pathways and genes in nasopharyngeal carcinoma using bioinformatics analysis. Oncol Lett 2019;17:4683-4694.
  15. Chen L, Chu C, Lu J, Kong X, Huang T, Cai YD. Gene ontology and KEGG pathway enrichment analysis of a drug target-based classification system. PLoS One 2015;10:e0126492. https://doi.org/10.1371/journal.pone.0126492
  16. Karimizadeh E, Sharifi-Zarchi A, Nikaein H, Salehi S, Salamatian B, Elmi N, et al. Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis. BMC Med Genomics 2019;12:199. https://doi.org/10.1186/s12920-019-0632-2
  17. Tomkins JE, Manzoni C. Advances in protein-protein interaction network analysis for Parkinson's disease. Neurobiol Dis 2021;155:105395. https://doi.org/10.1016/j.nbd.2021.105395
  18. Fan R, Dong L, Li P, Wang X, Chen X. Integrated bioinformatics analysis and screening of hub genes in papillary thyroid carcinoma. PLoS One 2021;16:e0251962. https://doi.org/10.1371/journal.pone.0251962
  19. Srivastava N, Mishra BN, Srivastava P. Protein network analysis to prioritize key genes and pathway for stress-mediated neurodegeneration. Open Bioinformatics J 2018;11:240-251. https://doi.org/10.2174/1875036201811010240
  20. Thomson DW, Bracken CP, Goodall GJ. Experimental strategies for microRNA target identification. Nucleic Acids Res 2011;39:6845-6853. https://doi.org/10.1093/nar/gkr330
  21. Mahmoodian Sani MR, Hashemzadeh-Chaleshtori M, Saidijam M, Jami MS, Ghasemi-Dehkordi P. MicroRNA-183 family in inner ear: hair cell development and deafness. J Audiol Otol 2016;20:131-138. https://doi.org/10.7874/jao.2016.20.3.131
  22. Chadly DM, Best J, Ran C, Bruska M, Wozniak W, Kempisty B, et al. Developmental profiling of microRNAs in the human embryonic inner ear. PLoS One 2018;13:e0191452. https://doi.org/10.1371/journal.pone.0191452
  23. Solda G, Robusto M, Primignani P, Castorina P, Benzoni E, Cesarani A, et al. A novel mutation within the MIR96 gene causes non-syndromic inherited hearing loss in an Italian family by altering pre-miRNA processing. Hum Mol Genet 2012;21:577-585. https://doi.org/10.1093/hmg/ddr493
  24. Hildebrand MS, Witmer PD, Xu S, Newton SS, Kahrizi K, Najmabadi H, et al. miRNA mutations are not a common cause of deafness. Am J Med Genet A 2010;152:646-652.
  25. Matsuda K. PCR-based detection methods for single-nucleotide polymorphism or mutation: real-time PCR and its substantial contribution toward technological refinement. Adv Clin Chem 2017;80:45-72. https://doi.org/10.1016/bs.acc.2016.11.002
  26. Shastry BS. SNPs in disease gene mapping, medicinal drug development and evolution. J Hum Genet 2007;52:871-880. https://doi.org/10.1007/s10038-007-0200-z
  27. Das SS, Chakravorty N. Identification of deleterious SNPs and their effects on BCL11A, the master regulator of fetal hemoglobin expression. Genomics 2020;112:397-403. https://doi.org/10.1016/j.ygeno.2019.03.002
  28. 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:W452-W457. https://doi.org/10.1093/nar/gks539
  29. Bendl J, Stourac J, Salanda O, Pavelka A, Wieben ED, Zendulka J, et al. PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations. PLoS Comput Biol 2014;10:e1003440. https://doi.org/10.1371/journal.pcbi.1003440
  30. Bendl J, Musil M, Stourac J, Zendulka J, Damborsky J, Brezovsky J. PredictSNP2: a unified platform for accurately evaluating SNP effects by exploiting the different characteristics of variants in distinct genomic regions. PLoS Comput Biol 2016;12:e1004962. https://doi.org/10.1371/journal.pcbi.1004962
  31. Kiernan AE. Notch signaling during cell fate determination in the inner ear. Semin Cell Dev Biol 2013;24:470-479. https://doi.org/10.1016/j.semcdb.2013.04.002
  32. Munnamalai V, Fekete DM. Wnt signaling during cochlear development. Semin Cell Dev Biol 2013;24:480-489. https://doi.org/10.1016/j.semcdb.2013.03.008
  33. Riccomagno MM, Takada S, Epstein DJ. Wnt-dependent regulation of inner ear morphogenesis is balanced by the opposing and supporting roles of Shh. Genes Dev 2005;19:1612-1623. https://doi.org/10.1101/gad.1303905
  34. Zhao HB, Kikuchi T, Ngezahayo A, White TW. Gap junctions and cochlear homeostasis. J Membr Biol 2006;209:177-186. https://doi.org/10.1007/s00232-005-0832-x
  35. Wang B, Hu B, Yang S. Cell junction proteins within the cochlea: a review of recent research. J Otol 2015;10:131-135. https://doi.org/10.1016/j.joto.2016.01.003
  36. Kitajiri S, Katsuno T. Tricellular tight junctions in the inner ear. Biomed Res Int 2016;2016:6137541. https://doi.org/10.1155/2016/6137541
  37. Nayak G, Lee SI, Yousaf R, Edelmann SE, Trincot C, Van Itallie CM, et al. Tricellulin deficiency affects tight junction architecture and cochlear hair cells. J Clin Invest 2013;123:4036-4049. https://doi.org/10.1172/JCI69031
  38. Wilson T, Omelchenko I, Foster S, Zhang Y, Shi X, Nuttall AL. JAK2/STAT3 inhibition attenuates noise-induced hearing loss. PLoS One 2014;9:e108276. https://doi.org/10.1371/journal.pone.0108276
  39. Mittal R, Liu G, Polineni SP, Bencie N, Yan D, Liu XZ. Role of microRNAs in inner ear development and hearing loss. Gene 2019;686:49-55. https://doi.org/10.1016/j.gene.2018.10.075
  40. Trune DR. Ion homeostasis in the ear: mechanisms, maladies, and management. Curr Opin Otolaryngol Head Neck Surg 2010;18:413-419. https://doi.org/10.1097/MOO.0b013e32833d9597
  41. Sohmer H. Pathophysiological mechanisms of hearing loss. J Basic Clin Physiol Pharmacol 1997;8:113-125. https://doi.org/10.1515/JBCPP.1997.8.3.113
  42. Hirata H, Ueno K, Shahryari V, Tanaka Y, Tabatabai ZL, Hinoda Y, et al. Oncogenic miRNA-182-5p targets Smad4 and RECK in human bladder cancer. PLoS One 2012;7:e51056. https://doi.org/10.1371/journal.pone.0051056
  43. Ueno K, Hirata H, Shahryari V, Deng G, Tanaka Y, Tabatabai ZL, et al. microRNA-183 is an oncogene targeting Dkk-3 and SMAD4 in prostate cancer. Br J Cancer 2013;108:1659-1667. https://doi.org/10.1038/bjc.2013.125
  44. Zhou J, Zhang C, Zhou B, Jiang D. miR-183 modulated cell proliferation and apoptosis in ovarian cancer through the TGF-beta/ Smad4 signaling pathway. Int J Mol Med 2019;43:1734-1746.
  45. Lewis MA, Di Domenico F, Ingham NJ, Prosser HM, Steel KP. Hearing impairment due to Mir183/96/182 mutations suggests both loss and gain of function effects. Dis Model Mech 2020;14:dmm047225.
  46. Du X, Li Q, Yang L, Liu L, Cao Q, Li Q. SMAD4 activates Wnt signaling pathway to inhibit granulosa cell apoptosis. Cell Death Dis 2020;11:373. https://doi.org/10.1038/s41419-020-2578-x
  47. Gallione C, Aylsworth AS, Beis J, Berk T, Bernhardt B, Clark RD, et al. Overlapping spectra of SMAD4 mutations in juvenile polyposis (JP) and JP-HHT syndrome. Am J Med Genet A 2010;152A:333-339. https://doi.org/10.1002/ajmg.a.33206
  48. Gallione CJ, Repetto GM, Legius E, Rustgi AK, Schelley SL, Tejpar S, et al. A combined syndrome of juvenile polyposis and hereditary haemorrhagic telangiectasia associated with mutations in MADH4 (SMAD4). Lancet 2004;363:852-859. https://doi.org/10.1016/S0140-6736(04)15732-2
  49. Aretz S, Stienen D, Uhlhaas S, Stolte M, Entius MM, Loff S, et al. High proportion of large genomic deletions and a genotype phenotype update in 80 unrelated families with juvenile polyposis syndrome. J Med Genet 2007;44:702-709. https://doi.org/10.1136/jmg.2007.052506
  50. Howe JR, Sayed MG, Ahmed AF, Ringold J, Larsen-Haidle J, Merg A, et al. The prevalence of MADH4 and BMPR1A mutations in juvenile polyposis and absence of BMPR2, BMPR1B, and ACVR1 mutations. J Med Genet 2004;41:484-491. https://doi.org/10.1136/jmg.2004.018598
  51. Alazzouzi H, Alhopuro P, Salovaara R, Sammalkorpi H, Jarvinen H, Mecklin JP, et al. SMAD4 as a prognostic marker in colorectal cancer. Clin Cancer Res 2005;11:2606-2611. https://doi.org/10.1158/1078-0432.ccr-04-1458
  52. Attisano L, Lee-Hoeflich ST. The Smads. Genome Biol 2001;2:REVIEWS3010.
  53. Kuang C, Chen Y. Tumor-derived C-terminal mutations of Smad4 with decreased DNA binding activity and enhanced intramolecular interaction. Oncogene 2004;23:1021-1029. https://doi.org/10.1038/sj.onc.1207219