ASSOCIATION OF RS2435357 AND RS1800858 POLYMORPHISMS IN RET PROTO-ONCOGENE WITH HIRSCHSPRUNG DISEASE: SYSTEMATIC REVIEW AND META-ANALYSIS

Is There Any Mosaicism in REarranged During Transfection Variant in Hirschsprung Disease's Patients?

BACKGROUND

Hirschsprung disease (HSCR) is a heterogeneous genetic disease characterized by the absence of ganglion cells in the intestinal tract. The REarranged during Transfection (RET) is the most responsible gene for its pathogenesis. RET's somatic mosaicisms have been reported for HSCR; however, they are still under-recognized. Therefore, we determined the frequency of somatic mutation of RET rs2435357 in HSCR patients at our institution.

METHODS

We performed RET rs2435357 genotyping from 73 HSCR formalin-fixed and paraffin-embedded (FFPE) rectal and 60 non-HSCR controls using the PCR-RFLP method. Subsequently, we compared those frequencies of genotypes for RET rs2435357 with our previous genotyping data from 93 HSCR blood specimens.

RESULTS

The frequencies of genotypes for RET rs2435357 in HSCR paraffin-embedded rectal were CC 0, CT 11 (15%), and TT 62 (85%), whereas their frequencies in HSCR blood samples were CC 4 (4.3%), CT 22 (23.7%), and TT 67 (72%). Those frequencies differences almost reached a significant level (p = 0.06). Moreover, the frequency of RET rs2435357 risk allele (T) was significantly higher in HSCR patients (135/146, 92.5%) than controls (46/120, 38.3%) (p = 3.4 × 10^-22), with an odds ratio of 19.74 (95% confidence interval = 9.65-40.41).

CONCLUSION

Our study suggests somatic mosaicism in HSCR patients. These findings further imply the complexity of the pathogenesis of HSCR. Moreover, our study confirms the RET rs2435357 as a significant genetic risk factor for HSCR patients.

Association of rs2435357 and rs2506030 polymorphisms in RET with susceptibility to hirschsprung disease: A systematic review and meta-analysis

BACKGROUND

There are numerous published studies on the association between RET polymorphisms and susceptibility to Hirschsprung disease (HSCR). However, some of the results are inconsistent and the studies were conducted with small sample sizes. Therefore, we performed a meta-analysis to clarify the relationship.

METHODS

Relevant data were retrieved from PubMed, Web of Science, Cochrane Library, EMBASE, CNKI, and Google Scholar according to PRISMA guidelines. Odds ratios (OR) were calculated to assess susceptibility to HSCR. Meanwhile, heterogeneity and publication bias were also calculated by R software package (version 4.2.1). The protocol was published in PROSPERO (CRD42022348940).

RESULTS

A total of 12 studies were included in the meta-analysis and comprised 12 studies on the RET polymorphism rs2435357 (1,939 subjects and 3,613 controls) and 7 studies on the RET polymorphism rs2506030 (1,849 patients with HSCR and 3,054 controls). The analysis revealed that rs2435357 [A vs. G: odds ratio (OR) = 3.842, 95% confidence interval (CI) 2.829-5.220; AA vs. GG: OR = 2.597, 95% CI 1.499-4.501; AA + AG vs. GG: OR = 6.789, 95% CI 3.0711-14.9973; AA vs. AG + GG: OR = 8.156, 95%CI 5.429-12.253] and rs2506030 (A vs. G: OR = 0.519, 95% CI 0.469-0.573; AA vs. GG: OR = 0.543, 95% CI 0.474-0.623; AA + AG vs. GG: OR = 0.410, 95% CI 0.360-0.468; AA vs. AG + GG: OR = 0.361, 95%CI 0.292-0.447) were significantly associated with susceptibility to HSCR.

CONCLUSIONS

The polymorphisms rs2435357 and rs2506030 in the RET may be related to susceptibility to HSCR, of which rs2435357 (T > C) is the causal locus and rs2506030 (A > G) is the protective locus.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier:CRD42022348940.

Association of Neuregulin 1 rs7835688 G > C, rs16879552 T > C and rs2439302 G > C Polymorphisms with Susceptibility to Non-Syndromic Hirschsprung's Disease

Hirschsprung's disease (HSCR) is a heterogeneous congenital malformation of the enteric nervous system with a complex genetic etiology. We investigated if there was an association between Neuregulin-1 (NRG1) rs7835688 G > C, rs16879552 T > C and rs2439302 G > C polymorphisms and the risk of HSCR. Methods: We determined and compared the frequency of NRG1 polymorphisms rs7835688 G > C, rs16879552 T > C and rs2439302 G > C in 70 children with HSCR and 90 controls by TaqMan SNPs genotyping assays. Results: No significant differences in allele or genotype frequencies of NRG1 rs7835688 G > C, rs16879552 T > C and rs2439302 G > C polymorphisms were observed between HSCR cases and controls. Analyses showed that the NRG1 rs7835688 G > C, rs16879552 T > C and rs2439302 G > C polymorphisms were not significantly associated with an increased risk of non-syndromic HSCR. Conclusions: Our findings suggested that NRG1 rs7835688 G > C, rs16879552 T > C and rs2439302 G > C polymorphisms are not a risk factor in development of HSCR.

Penalized variance components for association of multiple genes with traits

Variance component models have gained popularity for genetic analyses, driven by their flexibility to simultaneously analyze multiple genetic variants in a gene by kernel statistics, and their ability to account for population stratification via genomic relationship matrices. For exploratory analyses with modest sample sizes and a potentially large number of variance components, it can be challenging to use standard maximum-likelihood or restricted maximum-likelihood methods to estimate variance components, because these iterative methods often fail to converge when likelihood surfaces are fairly flat, and standard-likelihood ratio statistical tests are not adequate. To overcome these limitations, we developed a penalized-likelihood model, whereby the penalty function follows the popular elastic-net approach, applying both L1 and L2 penalties to the variance components. By simulations, we demonstrate the potential gain in power by using both L1 and L2 penalties, and results from our simulations suggest that assigning 80% of the penalty parameter to the L1 penalty and 20% to the L2 penalty provides a reasonable balance between false-positive and false-negative results. Larger sample size improves the properties of our methods, at the cost of longer computation time. Application of our methods to a study of the influence of DNA methylation on levels of cortisol in reaction to stress testing shows how our method can be used to prioritize findings for further functional studies.