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Genetic factors contributing to skeletal class III malocclusion: a systematic review and meta-analysis

Abstract

Objectives

The present systematic review aims to report and critically assess the findings of the available scientific evidence from genetic association studies examining the genetic variants underlying skeletal class III malocclusion and its sub-phenotypes.

Material and methods

A pre-piloted protocol was registered and followed. The PubMed, Scopus, WOS, Cochrane Library, Gray Open literature, and CADTH databases were explored for genetic association studies following PICOS-based selection criteria. The research was reported in accordance with PRISMA statement and HuGE guidelines. The Q-genie tool was applied to assess the quality of genetic studies. Meta-analysis of genetic association studies was done by means of Meta-Genyo tool.

Results

A total of 8258 articles were retrieved, of which 22 were selected for in-depth analysis. Most of the studies did not differentiate between sub-phenotypes, and the cohorts were heterogeneous regarding ethnicity. Four to five principal components of class III malocclusion explained the phenotypic variation, and gene variants at MYO1H(rs10850110), BMP3(rs1390319), GHR (rs2973015,rs6184, rs2973015), FGF7(rs372127537), FGF10(rs593307), and SNAI3(rs4287555) (p < .05) explained most of the variation across the studies, associated to vertical, horizontal, or combined skeletal discrepancies. Meta-analysis results identified a statistically significant association between risk of class III malocclusion of A allele of the FBN3 rs7351083 [OR 2.13; 95% CI 1.1–4.1; p 0.02; recessive model].

Conclusion

Skeletal class III is a polygenic trait substantially modulated by ethnicity. A multicentric approach should be considered in future studies to increase sample sizes, applying multivariate analysis such as PCA and cluster analysis to characterize existing sub-phenotypes warranting a deeper analysis of genetic variants contributing to skeletal class III craniofacial disharmony.

Clinical relevance

Grasping the underlying mechanisms of this pathology is critical for a fuller understanding of its etiology, allowing generation of preventive strategies, new individualized therapeutic approaches and more accurate treatment planification strategies.

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Notes

  1. 1.

    http://mesh.med.yale.edu/

  2. 2.

    https://idostatistics.com/cohen-kappa-free-calculator/

  3. 3.

    http://bioinfo.genyo.es/metagenyo/

References

  1. 1.

    Nikopensius T, Saag M, Jagomägi T, Annilo T, Kals M, Kivistik PA, Milani L, Metspalu A (2013) A missense mutation in DUSP6 is associated with Class III malocclusion. J Dent Res 92(10):893–898. https://doi.org/10.1177/0022034513502790

    Article  PubMed  Google Scholar 

  2. 2.

    Doraczynska-Kowalik A, Nelke KH, Pawlak W, Sasiadek MM, Gerber H (2017) Genetic Factors Involved in Mandibular Prognathism. J Craniofac Surg 28(5):e422–e431. https://doi.org/10.1097/scs.0000000000003627

    Article  PubMed  Google Scholar 

  3. 3.

    de Frutos-Valle L, Martin C, Alarcon JA, Palma-Fernandez JC, Iglesias-Linares A (2019) Subclustering in Skeletal Class III Phenotypes of Different Ethnic Origins: A Systematic Review. J Evid Based Dent Pract 19(1):34–52. https://doi.org/10.1016/j.jebdp.2018.09.002

    Article  PubMed  Google Scholar 

  4. 4.

    Kajii TS, Oka A, Saito F, Mitsui J, Iida J (2019) Whole-exome sequencing in a Japanese pedigree implicates a rare non-synonymous single-nucleotide variant in BEST3 as a candidate for mandibular prognathism. Bone 122:193–198. https://doi.org/10.1016/j.bone.2019.03.004

    Article  PubMed  Google Scholar 

  5. 5.

    Liu H, Wu C, Lin J, Shao J, Chen Q, Luo E (2017) Genetic Etiology in Nonsyndromic Mandibular Prognathism. J Craniofac Surg 28(1):161–169. https://doi.org/10.1097/scs.0000000000003287

    Article  PubMed  Google Scholar 

  6. 6.

    Sidlaukas Antanas LK (2009) The prevalence of malocclusion among 7–15-year-old Lithuanian schoolchildren. Medicina (Kaunas) 45(2):147–152

    Article  Google Scholar 

  7. 7.

    Perillo L, Masucci C, Ferro F, Apicella D, Baccetti T (2010) Prevalence of orthodontic treatment need in southern Italian schoolchildren. Eur J Orthod 32(1):49–53. https://doi.org/10.1093/ejo/cjp050

    Article  PubMed  Google Scholar 

  8. 8.

    Nowrin S, Alam M, Basri R (2015) Genetic effect and prevalence of class iii malocclusion in different population: An overview. Int J Pharm Bio Sci 6:910–918

    Google Scholar 

  9. 9.

    Moreno Uribe LM, Miller SF (2015) Genetics of the dentofacial variation in human malocclusion. Orthod Craniofacial Res 18(Suppl 1(0 1)):91–99. https://doi.org/10.1111/ocr.12083

    Article  Google Scholar 

  10. 10.

    da Fontoura CS, Miller SF, Wehby GL, Amendt BA, Holton NE, Southard TE, Allareddy V, Moreno Uribe LM (2015) Candidate Gene Analyses of Skeletal Variation in Malocclusion. J Dent Res 94(7):913–920. https://doi.org/10.1177/0022034515581643

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Moreno Uribe LM, Ray A, Blanchette DR, Dawson DV, Southard TE (2015) Phenotypegenotype correlations of facial width and height proportions in patients with Class II malocclusion. Orthod Craniofacial Res 18(Suppl 1(0 1)):100–108. https://doi.org/10.1111/ocr.12084

    Article  Google Scholar 

  12. 12.

    Moreno Uribe LM, Vela KC, Kummet C, Dawson DV, Southard TE (2013) Phenotypic diversity in white adults with moderate to severe Class III malocclusion. Am J Orthod Dentofac Orthop 144(1):32–42. https://doi.org/10.1016/j.ajodo.2013.02.019

    Article  Google Scholar 

  13. 13.

    Claes P, Roosenboom J, White JD, Swigut T, Sero D, Li J, Lee MK, Zaidi A, Mattern BC, Liebowitz C, Pearson L, Gonzalez T, Leslie EJ, Carlson JC, Orlova E, Suetens P, Vandermeulen D, Feingold E, Marazita ML, Shaffer JR, Wysocka J, Shriver MD, Weinberg SM (2018) Genome-wide mapping of global-to-local genetic effects on human facial shape. Nat Genet 50(3):414–423. https://doi.org/10.1038/s41588-018-0057-4

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Moreno Uribe LM, Ray A, Blanchette DR, Dawson DV, Southard TE (2015) Phenotypegenotype correlations of facial width and height proportions in patients with Class II malocclusion. Orthod Craniofacial Res 18(Suppl 1):100–108. https://doi.org/10.1111/ocr.12084

    Article  Google Scholar 

  15. 15.

    Yamaguchi T, Park SB, Narita A, Maki K, Inoue I (2005) Genome-wide linkage analysis of mandibular prognathism in Korean and Japanese patients. J Dent Res 84(3):255–259. https://doi.org/10.1177/154405910508400309

    Article  PubMed  Google Scholar 

  16. 16.

    Cruz CV, Mattos CT, Maia JC, Granjeiro JM, Reis MF, Mucha JN, Vilella B, Ruellas AC, Luiz RR, Costa MC, Vieira AR (2017) Genetic polymorphisms underlying the skeletal Class III phenotype. Am J Orthod Dentofac Orthop 151(4):700–707. https://doi.org/10.1016/j.ajodo.2016.09.013

    Article  Google Scholar 

  17. 17.

    Cruz RM, Krieger H, Ferreira R, Mah J, Hartsfield J Jr, Oliveira S (2008) Major gene and multifactorial inheritance of mandibular prognathism. Am J Med Genet A 146a(1):71–77. https://doi.org/10.1002/ajmg.a.32062

    Article  PubMed  Google Scholar 

  18. 18.

    Jang JY, Park EK, Ryoo HM, Shin HI, Kim TH, Jang JS, Park HS, Choi JY, Kwon TG (2010) Polymorphisms in the Matrilin-1 gene and risk of mandibular prognathism in Koreans. J Dent Res 89(11):1203–1207. https://doi.org/10.1177/0022034510375962

    Article  PubMed  Google Scholar 

  19. 19.

    Xue F, Wong R, Rabie AB (2010) Identification of SNP markers on 1p36 and association analysis of EPB41 with mandibular prognathism in a Chinese population. Arch Oral Biol 55(11):867–872. https://doi.org/10.1016/j.archoralbio.2010.07.018

    Article  PubMed  Google Scholar 

  20. 20.

    Ikuno K, Kajii TS, Oka A, Inoko H, Ishikawa H, Iida J (2014) Microsatellite genome-wide association study for mandibular prognathism. Am J Orthod Dentofac Orthop 145(6):757–762. https://doi.org/10.1016/j.ajodo.2014.01.022

    Article  Google Scholar 

  21. 21.

    Saito F, Kajii TS, Oka A, Ikuno K, Iida J (2017) Genome-wide association study for mandibular prognathism using microsatellite and pooled DNA method. Am J Orthod Dentofac Orthop 152(3):382–388. https://doi.org/10.1016/j.ajodo.2017.01.021

    Article  Google Scholar 

  22. 22.

    Frazier-Bowers S, Rincon-Rodriguez R, Zhou J, Alexander K, Lange E (2009) Evidence of linkage in a Hispanic cohort with a Class III dentofacial phenotype. J Dent Res 88(1):56–60. https://doi.org/10.1177/0022034508327817

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Cunha A, Nelson-Filho P, Maranon-Vasquez GA, Ramos AGC, Dantas B, Sebastiani AM, Silverio F, Omori MA, Rodrigues AS, Teixeira EC, Levy SC, Araujo MC, Matsumoto MAN, Romano FL, Antunes LAA, Costa DJD, Scariot R, Antunes LS, Vieira AR, Kuchler EC (2019) Genetic variants in ACTN3 and MYO1H are associated with sagittal and vertical craniofacial skeletal patterns. Arch Oral Biol 97:85–90. https://doi.org/10.1016/j.archoralbio.2018.09.018

    Article  PubMed  Google Scholar 

  24. 24.

    Jheon AH, Oberoi S, Solem RC, Kapila S (2017) Moving towards precision orthodontics: An evolving paradigm shift in the planning and delivery of customized orthodontic therapy. Orthod Craniofacial Res 20(Suppl 1):106–113. https://doi.org/10.1111/ocr.12171

    Article  Google Scholar 

  25. 25.

    Moher D, Liberati A, Tetzlaff J, Altman DG, Group P (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6(7):e1000097. https://doi.org/10.1371/journal.pmed.1000097

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Little JHJe (2006) The HuGENetTM HuGE Review Handbook, version 1.0.

  27. 27.

    Saleh AA, Ratajeski MA, Bertolet M (2014) Grey Literature Searching for Health Sciences Systematic Reviews: A Prospective Study of Time Spent and Resources Utilized. Evid Based Libr Inf Pract 9(3):28–50. https://doi.org/10.18438/b8dw3k

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    (EPOC) CEPaOoC (2017) How to develop a search strategy. EPOC Resources for review authors. http://epoc.cochrane.org/resources/epoc-resources-review-authors

  29. 29.

    Sohani ZN, Meyre D, de Souza RJ, Joseph PG, Gandhi M, Dennis BB, Norman G, Anand SS (2015) Assessing the quality of published genetic association studies in meta-analyses: the quality of genetic studies (Q-Genie) tool. BMC Genet 16:50. https://doi.org/10.1186/s12863-015-0211-2

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Martorell-Marugan J, Toro-Dominguez D, Alarcon-Riquelme ME, Carmona-Saez P (2017) MetaGenyo: a web tool for meta-analysis of genetic association studies. BMC Bioinformatics 18(1):563. https://doi.org/10.1186/s12859-017-1990-4

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Nakaoka H, Inoue I (2009) Meta-analysis of genetic association studies: methodologies, between-study heterogeneity and winner's curse. J Hum Genet 54(11):615–623. https://doi.org/10.1038/jhg.2009.95

    Article  PubMed  Google Scholar 

  32. 32.

    Rodrigues AS, Teixeira EC, Antunes LS, Nelson-Filho P, Cunha AS, Levy SC, de Souza Araújo MT, de Carvalho Ramos AG, Cruz GV, Omori MA, Matsumoto MAN, Vieira AR, Küchler EC, Marañón-Vásquez GA, Antunes LAA (2020) Association between craniofacial morphological patterns and tooth agenesis-related genes. Prog Orthod 21(1):9. https://doi.org/10.1186/s40510-020-00309-5

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Marañón-Vásquez GA, Vieira AR, de Carvalho Ramos AG, Dantas B, Romano FL, Palma-Dibb RG, Arid J, Carpio K, Nelson-Filho P, de Rossi A, Scariot R, Levy SC, Antunes LAA, Antunes LS, Küchler EC (2020) GHR and IGF2R genes may contribute to normal variations in craniofacial dimensions: Insights from an admixed population. Am J Orthod Dentofac Orthop 158(5):722–730.e716. https://doi.org/10.1016/j.ajodo.2019.10.020

    Article  Google Scholar 

  34. 34.

    Marañón-Vásquez GA, Dantas B, Kirschneck C, Arid J, Cunha A, Ramos AGC, Omori MA, Rodrigues AS, Teixeira EC, Levy SC, Schroeder A, Matsumoto MAN, Proff P, Antunes LAA, Vieira AR, Antunes LS, Küchler EC (2019) Tooth agenesis-related GLI2 and GLI3 genes may contribute to craniofacial skeletal morphology in humans. Arch Oral Biol 103:12–18. https://doi.org/10.1016/j.archoralbio.2019.05.008

    Article  PubMed  Google Scholar 

  35. 35.

    Guan X, Song Y, Ott J, Zhang Y, Li C, Xin T, Li Z, Gan Y, Li J, Zhou S, Zhou Y (2015) The ADAMTS1 Gene Is Associated with Familial Mandibular Prognathism. J Dent Res 94(9):1196–1201. https://doi.org/10.1177/0022034515589957

    Article  PubMed  Google Scholar 

  36. 36.

    Jiang Q, Zhou X, Cheng L, Li M (2019) The Adhesion and Invasion Mechanisms of Streptococci. Curr Issues Mol Biol 32:521–560. https://doi.org/10.21775/cimb.032.521

    Article  PubMed  Google Scholar 

  37. 37.

    Xue F, Rabie AB, Luo G (2014) Analysis of the association of COL2A1 and IGF-1 with mandibular prognathism in a Chinese population. Orthod Craniofacial Res 17(3):144–149. https://doi.org/10.1111/ocr.12038

    Article  Google Scholar 

  38. 38.

    Xiong X, Li S, Cai Y, Chen F (2017) Targeted sequencing in FGF/FGFR genes and association analysis of variants for mandibular prognathism. Medicine (Baltimore) 96(25):e7240. https://doi.org/10.1097/md.0000000000007240

    Article  Google Scholar 

  39. 39.

    Sun R, Wang Y, Jin M, Chen L, Cao Y, Chen F (2018) Identification and Functional Studies of MYO1H for Mandibular Prognathism. J Dent Res 97(13):1501–1509. https://doi.org/10.1177/0022034518784936

    Article  PubMed  Google Scholar 

  40. 40.

    Tobón-Arroyave SI, Jiménez-Arbeláez GA, Alvarado-Gómez VA, Isaza-Guzmán DM, Flórez-Moreno GA, Pérez-Cano MI (2018) Association analysis between rs6184 and rs6180 polymorphisms of growth hormone receptor gene regarding skeletal-facial profile in a Colombian population. Eur J Orthod 40(4):378–386. https://doi.org/10.1093/ejo/cjx070

    Article  PubMed  Google Scholar 

  41. 41.

    Sasaki Y, Satoh K, Hayasaki H, Fukumoto S, Fujiwara T, Nonaka K (2009) The P561T polymorphism of the growth hormone receptor gene has an inhibitory effect on mandibular growth in young children. Eur J Orthod 31(5):536–541. https://doi.org/10.1093/ejo/cjp017

    Article  PubMed  Google Scholar 

  42. 42.

    Gupta P, Chaturvedi TP, Sharma V (2017) Expressional Analysis of MSX1 (Human) Revealed its Role in Sagittal Jaw Relationship. J Clin Diagn Res 11(8):Zc71–zc77. https://doi.org/10.7860/jcdr/2017/26755.10441

    Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Ghergie M, Feştila D, Lupan I, Popescu O, Kelemen BS (2013) Testing the association between orthodonthic classes I, II, III and SNPs (rs731236, rs8004560, rs731236) in a Romanian clinical sample. Ann Romanian Soc Cell Biol 18:43–51

    Google Scholar 

  44. 44.

    Bayram S, Basciftci FA, Kurar E (2014) Relationship between P561T and C422F polymorphisms in growth hormone receptor gene and mandibular prognathism. Angle Orthod 84(5):803–809. https://doi.org/10.2319/091713-680.1

    Article  PubMed  Google Scholar 

  45. 45.

    Weaver CA, Miller SF, da Fontoura CS, Wehby GL, Amendt BA, Holton NE, Allareddy V, Southard TE, Moreno Uribe LM (2017) Candidate gene analyses of 3-dimensional dentoalveolar phenotypes in subjects with malocclusion. Am J Orthod Dentofac Orthop 151(3):539–558. https://doi.org/10.1016/j.ajodo.2016.08.027

    Article  Google Scholar 

  46. 46.

    Tassopoulou-Fishell M, Deeley K, Harvey EM, Sciote J, Vieira AR (2012) Genetic variation in myosin 1H contributes to mandibular prognathism. Am J Orthod Dentofac Orthop 141(1):51–59. https://doi.org/10.1016/j.ajodo.2011.06.033

    Article  Google Scholar 

  47. 47.

    Klingenberg CP (2016) Size, shape, and form: concepts of allometry in geometric morphometrics. Dev Genes Evol 226(3):113–137. https://doi.org/10.1007/s00427-016-0539-2

    Article  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Signorelli L, Patcas R, Peltomaki T, Schatzle M (2016) Radiation dose of cone-beam computed tomography compared to conventional radiographs in orthodontics. J Orofac Orthop 77(1):9–15. https://doi.org/10.1007/s00056-015-0002-4

    Article  PubMed  Google Scholar 

  49. 49.

    Huang D, Petrykowska HM, Miller BF, Elnitski L, Ovcharenko I (2019) Identification of human silencers by correlating cross-tissue epigenetic profiles and gene expression. Genome Res 29(4):657–667. https://doi.org/10.1101/gr.247007.118

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Sun YV, Hu YJ (2016) Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases. Adv Genet 93:147–190. https://doi.org/10.1016/bs.adgen.2015.11.004

    Article  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Wafi A, Mirnezami R (2018) Translational -omics: Future potential and current challenges in precision medicine. Methods 151:3–11. https://doi.org/10.1016/j.ymeth.2018.05.009

    Article  PubMed  Google Scholar 

  52. 52.

    UniProt C (2019) UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res 47(D1):D506–D515. https://doi.org/10.1093/nar/gky1049

    Article  Google Scholar 

  53. 53.

    Arun RM, Lakkakula BV, Chitharanjan AB (2016) Role of myosin 1H gene polymorphisms in mandibular retrognathism. Am J Orthod Dentofac Orthop 149(5):699–704. https://doi.org/10.1016/j.ajodo.2015.10.028

    Article  Google Scholar 

  54. 54.

    Sella-Tunis T, Pokhojaev A, Sarig R, O'Higgins P, May H (2018) Human mandibular shape is associated with masticatory muscle force. Sci Rep 8(1):6042. https://doi.org/10.1038/s41598-018-24293-3

    Article  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Wieczorek A, Loster J, Loster BW (2013) Relationship between occlusal force distribution and the activity of masseter and anterior temporalis muscles in asymptomatic young adults. Biomed Res Int 2013:354017. https://doi.org/10.1155/2013/354017

    Article  PubMed  Google Scholar 

  56. 56.

    Iodice G, Danzi G, Cimino R, Paduano S, Michelotti A (2016) Association between posterior crossbite, skeletal, and muscle asymmetry: a systematic review. Eur J Orthod 38(6):638–651. https://doi.org/10.1093/ejo/cjw003

    Article  PubMed  Google Scholar 

  57. 57.

    Qi K, Guo SX, Xu Y, Deng Q, Liu L, Li B, Wang MQ (2016) An investigation of the simultaneously recorded occlusal contact and surface electromyographic activity of jawclosing muscles for patients with temporomandibular disorders and a scissors-bite relationship. J Electromyogr Kinesiol 28:114–122. https://doi.org/10.1016/j.jelekin.2016.04.004

    Article  PubMed  Google Scholar 

  58. 58.

    Toro-Ibacache V, Ugarte F, Morales C, Eyquem A, Aguilera J, Astudillo W (2019) Dental malocclusions are not just about small and weak bones: assessing the morphology of the mandible with cross-section analysis and geometric morphometrics. Clin Oral Investig 23(9):3479–3490. https://doi.org/10.1007/s00784-018-2766-6

    Article  PubMed  Google Scholar 

  59. 59.

    Lu Y, Li Y, Cavender AC, Wang S, Mansukhani A, D'Souza RN (2012) Molecular studies on the roles of Runx2 and Twist1 in regulating FGF signaling. Dev Dyn 241(11):1708–1715. https://doi.org/10.1002/dvdy.23858

    Article  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Lee SK, Kim YS, Oh HS, Yang KH, Kim EC, Chi JG (2001) Prenatal development of the human mandible. Anat Rec 263(3):314–325. https://doi.org/10.1002/ar.1110

    Article  PubMed  Google Scholar 

  61. 61.

    Schoenebeck JJ, Hutchinson SA, Byers A, Beale HC, Carrington B, Faden DL, Rimbault M, Decker B, Kidd JM, Sood R, Boyko AR, Fondon JW 3rd, Wayne RK, Bustamante CD, Ciruna B, Ostrander EA (2012) Variation of BMP3 contributes to dog breed skull diversity. PLoS Genet 8(8):e1002849. https://doi.org/10.1371/journal.pgen.1002849

    Article  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Fu X, Xu J, Chaturvedi P, Liu H, Jiang R, Lan Y (2017) Identification of Osr2 Transcriptional Target Genes in Palate Development. J Dent Res 96(12):1451–1458. https://doi.org/10.1177/0022034517719749

    Article  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Perillo L, Monsurro A, Bonci E, Torella A, Mutarelli M, Nigro V (2015) Genetic association of ARHGAP21 gene variant with mandibular prognathism. J Dent Res 94(4):569–576. https://doi.org/10.1177/0022034515572190

    Article  PubMed  Google Scholar 

  64. 64.

    O'Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D, McVeigh R, Rajput B, Robbertse B, Smith-White B, Ako-Adjei D, Astashyn A, Badretdin A, Bao Y, Blinkova O, Brover V, Chetvernin V, Choi J, Cox E, Ermolaeva O, Farrell CM, Goldfarb T, Gupta T, Haft D, Hatcher E, Hlavina W, Joardar VS, Kodali VK, Li W, Maglott D, Masterson P, McGarvey KM, Murphy MR, O'Neill K, Pujar S, Rangwala SH, Rausch D, Riddick LD, Schoch C, Shkeda A, Storz SS, Sun H, Thibaud-Nissen F, Tolstoy I, Tully RE, Vatsan AR, Wallin C, Webb D, Wu W, Landrum MJ, Kimchi A, Tatusova T, DiCuccio M, Kitts P, Murphy TD, Pruitt KD (2016) Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res 44(D1):D733–D745. https://doi.org/10.1093/nar/gkv1189

    Article  PubMed  Google Scholar 

  65. 65.

    Brooks AJ, Waters MJ (2010) The growth hormone receptor: mechanism of activation and clinical implications. Nat Rev Endocrinol 6(9):515–525. https://doi.org/10.1038/nrendo.2010.123

    Article  PubMed  Google Scholar 

  66. 66.

    Chen J, Chin A, Almarza AJ, Taboas JM (2020) Hydrogel to guide chondrogenesis versus osteogenesis of mesenchymal stem cells for fabrication of cartilaginous tissues. Biomed Mater 15(4):045006. https://doi.org/10.1088/1748-605X/ab401f

    Article  PubMed  Google Scholar 

  67. 67.

    Davis MR, Summers KM (2012) Structure and function of the mammalian fibrillin gene family: implications for human connective tissue diseases. Mol Genet Metab 107(4):635–647. https://doi.org/10.1016/j.ymgme.2012.07.023

    Article  PubMed  Google Scholar 

  68. 68.

    Li C, Cai Y, Chen S, Chen F (2016) Classification and characterization of class III malocclusion in Chinese individuals. Head Face Med 12(1):31. https://doi.org/10.1186/s13005-016-0127-8

    Article  PubMed  PubMed Central  Google Scholar 

  69. 69.

    Di Resta C, Ferrari M (2018) Next Generation Sequencing: From Research Area to Clinical Practice. EJIFCC 29(3):215–220

    PubMed  PubMed Central  Google Scholar 

  70. 70.

    Jamuar SS, Tan EC (2015) Clinical application of next-generation sequencing for Mendelian diseases. Hum Genomics 9(1):10. https://doi.org/10.1186/s40246-015-0031-5

    Article  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Hong EP, Park JW (2012) Sample size and statistical power calculation in genetic association studies. Genomics Inform 10(2):117–122. https://doi.org/10.5808/GI.2012.10.2.117

    Article  PubMed  PubMed Central  Google Scholar 

  72. 72.

    Xue F, Wong RW, Rabie AB (2010) Genes, genetics, and Class III malocclusion. Orthod Craniofacial Res 13(2):69–74. https://doi.org/10.1111/j.1601-6343.2010.01485.x

    Article  Google Scholar 

  73. 73.

    El-Gheriani AA, Maher BS, El-Gheriani AS, Sciote JJ, Abu-Shahba FA, Al-Azemi R, Marazita ML (2003) Segregation analysis of mandibular prognathism in Libya. J Dent Res 82(7):523–527. https://doi.org/10.1177/154405910308200707

    Article  PubMed  Google Scholar 

  74. 74.

    Wolff G, Wienker TF, Sander H (1993) On the genetics of mandibular prognathism: analysis of large European noble families. J Med Genet 30(2):112–116. https://doi.org/10.1136/jmg.30.2.112

    Article  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Nievergelt CM, Libiger O, Schork NJ (2007) Generalized analysis of molecular variance. PLoS Genet 3(4):e51. https://doi.org/10.1371/journal.pgen.0030051

    Article  PubMed  PubMed Central  Google Scholar 

  76. 76.

    Zhou W, Nielsen JB, Fritsche LG, Dey R, Gabrielsen ME, Wolford BN, LeFaive J, VandeHaar P, Gagliano SA, Gifford A, Bastarache LA, Wei WQ, Denny JC, Lin M, Hveem K, Kang HM, Abecasis GR, Willer CJ, Lee S (2018) Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nat Genet 50(9):1335–1341. https://doi.org/10.1038/s41588-018-0184-y

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Alexandra Dehesa-Santos contributed to the study conception and design, wrote the paper, and performed the literature search and data analysis of the manuscript.

Paula Iber-Diaz contributed to the literature search and data analysis.

Alejandro Iglesias-Linares contributed to the study conception and design and wrote the paper as well as its critical revision.

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Correspondence to Alejandro Iglesias-Linares.

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Supplementary information

Online Resource 1.

Search strategy. (DOCX 15 kb)

Online Resource 2.

Full text excluded articles and reasons for exclusion. (DOCX 19 kb)

Online Resource 3.

Genetic variants contributing to Class III craniofacial characteristics. (PPTX 44 kb)

Online Resource 4.

Hardy-Weinberg equilibrium test for each genetic variant within eligible studies. (PPTX 700 kb)

Online Resource 5.

Egger's test Funnel Plots, sensitivity-Leave-1-out Forest plots random or fixed effects for each of the genetic variant. (PPTX 4440 kb)

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Dehesa-Santos, A., Iber-Diaz, P. & Iglesias-Linares, A. Genetic factors contributing to skeletal class III malocclusion: a systematic review and meta-analysis. Clin Oral Invest 25, 1587–1612 (2021). https://doi.org/10.1007/s00784-020-03731-5

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Keywords

  • Skeletal class III malocclusion
  • Principal component analysis
  • Genetic factors
  • Malocclusion sub-phenotypes