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. 2020 Jun;10(6):285.
doi: 10.1007/s13205-020-02273-7. Epub 2020 Jun 1.

The rs1991517 polymorphism is a genetic risk factor for congenital hypothyroidism

Affiliations

The rs1991517 polymorphism is a genetic risk factor for congenital hypothyroidism

Yedukondalu Kollati et al. 3 Biotech. 2020 Jun.

Abstract

The objective of the current study is to explore the association of thyroid-stimulating hormone receptor (TSHR) rs1991517 polymorphism (c.2337 C > G, p.D727E) with congenital hypothyroidism (CH) through a case-control study followed by a meta-analysis. The case-control study was based on 45 CH subjects and 700 healthy controls. Meta-analysis comprised of seven published studies and our current findings (1044 CH cases and 1649 healthy controls). The allele contrast model showed that the presence of G- allele increased CH risk by 45% (OR: 1.45, 95% CI 1.20-1.76) and 41% (OR: 1.41, 95% CI 1.03-1.93) in fixed effect and random effect models, respectively. The GG- genotype is associated with 2.3-fold (95% CI 1.32-3.99) increased risk for CH in the fixed-effect model. I 2 (0.58) and Cochran's Q test (Q: 16.72, p = 0.02) revealed evidence of heterogeneity in the association. No publication bias was observed by Egger's test (p = 0.70). Sensitivity analysis revealed that even after excluding any study this polymorphism is associated with risk for CH. The rs1991517 mutation alters the binding affinity to cAMP (ΔG of 727D vs.727E: - 7.27 vs. - 7.34 kcal/mol). In conclusion, rs1991517 is a genetic risk factor for CH and exerts its impact by altering cAMP-mediated signal transduction.

Keywords: Congenital hypothyroidism; D727E; Meta-analysis; Thyroid-stimulating hormone receptor.

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Conflict of interest statement

Conflict of interestThe authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
The representative sequence chromatograms for the analysis of TSHR rs1991517 polymorphism. This figure illustrates the presence of ‘C’ or ‘G’-alleles (as pointed by a red arrow) in the analyzed samples thus facilitating the genotyping as shown: a homozygous mutant (GG). b heterozygous (CG). c wild (CC)
Fig. 2
Fig. 2
Prisma Flow Chart showing the stages in data extraction for meta-analysis. The flow chart depicts that a total of 11 citations were extracted and screened from the pubmed. Two articles were excluded after screening the title and abstract. One article was excluded after full-text screen and one more excluded after data extraction. Finally, a total of seven articles included
Fig. 3
Fig. 3
Meta-analysis for the association between rs1991517 and Congenital Hypothyroidism. Seven articles and the current study representing 2088 cases and 3298 controls were used for the meta-analysis. a Forest plot of allele contrast model. In each study, the data segregation in cases (Experimental) and controls based on the number of variant alleles (Events) per Total alleles. The odds ratios and 95% confidence intervals were depicted both graphically and numerically. Both fixed effect and random effect models were employed to calculate the cumulative effect. b Funnel diagram showing heterogeneity in the association. In the Funnel diagram, odds ratio vs. standard error were plotted for each study. Two studies (the current study and Singh et al.) deviated from the rest. c Sensitivity analysis. One study at a time was excluded to assess the robustness of meta-analysis. Overall results were not affected by the exclusion of any study
Fig. 4
Fig. 4
Model of wild-type and mutant TSHR protein. Using Phyre 2 module, PDB structures of wild and mutant TSHR proteins were generated. Using the swissdock module, docking was performed for these proteins with cyclic AMP. The figure illustrates a docking of wild TSHR with cAMP (ΔG: − 7.27 kcal/mol; and b docking of mutant TSHR with cAMP (ΔG: − 7.34 kcal/mol). These models are corroborating with the experimental data of Gabriel et al.

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