Genome-Wide Association Study in Craniosynostosis Condition Using Innovative Systematic Bioinformatic Analysis Tools...

Craniosynostosis (CS) conditions are included with the premature fusion of one or more multiple cranial sutures. As the second leading and most common craniofacial anomaly and orofacial clefts globally. Syndromic and nonsyndromic CS (NSCS) occur as a part of a genetic syndrome unlike Apert, Crouzon, Pfeiffer, Muenke, and Saethre-Chotzen syndromes. Approximately, 90% of the cases of CS arises from NSCS group and it is now a great challenge for the researcher and neurosurgeon for Indian-origin children, a great burden worldwide.

Study design: Prospective study of analysis sequence pattern on CS and NSCS from January 2007 to 2018 was carried out.Inclusion criteria: Diagnosed cases in syndromic and NSCS patients between 3 months and 14 years of age either preoperative or postoperative were included in the study of both groups (syndromic and NSCS).Exclusion criteria: Patients with primary microcephaly (secondary CS), postural plagiocephaly, incomplete data, no visual perception, and who were lost to follow-up, and who had no interest to participate the study were excluded from the study.Bioinformatic analysis: We have performed systematic bioinformatic analysis for all responsible genes by combining with using through the GeneDecks, Gene Runner, DAVID, and STRING databases.Genes testing: FGF family genes, MSX genes, such as Irf6, TP63, Dlx2, Dlx5, Pax3, Pax9, Bmp4, Tgf-beta2, and Tgf-beta3 were found to be involved in Cleft lip and cleft palate (CL/P), and Fgfr2, Fgfr1, Fgfr3, and TWIST, MSX, MSX1, 2 were found to be involved in both the groups of CS (SCS + NSCS).

FGFR, MSX, Irf6, TP63, Dlx2, Dlx5, Pax3, Pax9, Bmp4, Tgf-beta2, and Tgf-beta3 demonstrated and find out that in CL/P, and Fgfr2, Fgfr1, Fgfr3, and Twist1 had accurate sequence data with more than accuracy of 95% reported with proper order with additional anomalies CS through newly developed tools.

Newly developed techniques of GeneDecks, Gene Runner, DAVID, and STRING databases gave better picture to analyze the larger population, patients (SCS + NSCS) with complex genetic, maternal, parental age, environmental, and stochastic factors contributing to NSCS networking, signaling, and pathways involvement. This bioinformatic tools analyzed better prediction of CS and NSCS sequences guiding us the newer invention modalities of pattern of screening and further development of recent future application.