Highlighting allelic variations at the interleukin-19 locus in term of preeclampsia predisposing factors and access to an accurate diagnostic/screening option.

BACKGROUND: Preeclampsia is the main cause of preterm parturition and maternal-fetal complications. T helper 1 and T helper 2 cytokines balance is a requirement in normal pregnancy and aberrant in this immunologic balance, play an important role in the pathology of preeclampsia. In previous studies single nucleotide polymorphisms have been associated with the alteration of serum cytokine levels. OBJECTIVE: This study was aimed to discover association between interleukin-13 (rs20541, and rs56035208) and interleukin-19 (rs1028181 (T/C) and rs2243191(T/C)) polymorphisms with susceptibility to preeclampsia. METHODS: In this case-control study 300 women with and without preeclampsia (n = 150/each) who referred to Zeynabieh Hospital- Shiraz, Iran, from February 2021 to April 2022 were enrolled. For genotyping the interleukin-13 and interleukin-19 polymorphisms, the Allele-specific polymerase chain reaction and direct sequencing method was carried out. RESULTS: Our statistical results revealed no significant differences in allele and genotype frequencies for interleukin-13 polymorphisms compared to controls. We found that the interleukin-13 polymorphisms are significantly associated with vulnerability to edema at rs20541 position and maternal drinking at rs56035208 position. But it was interesting to note that the differences of both the allele and genotype frequencies of interleukin-19 polymorphisms and their contribution to the risk of preeclampsia susceptibility were significant. CONCLUSIONS: No risk of preeclampsia was found in all comparisons for interleukin-13 polymorphisms. However, the interleukin-19 polymorphisms were found to confer the risk of preeclampsia in our population.

Spontaneous miscarriage driven by maternal genetic mutation at position of PAI-1-844G/A: shed light on a race-specific genetic polymorphism.

OBJECTIVE: Association between a genetic polymorphism and disease, either positively or negatively, within a population may not necessarily predict association in other race-ethnic populations. The aim of this study was to genotype well recognized thrombophilia associated polymorphisms as common risk factors for miscarriage and investigate their benefit to use as risk factors in southwest region of Iran females (Khuzestan) in the Arabs ethnic minority group with spontaneous miscarriage. We developed a Reverse Dot Blot Assay for the genotyping of four polymorphisms. RESULTS: There were significant differences in the genotype distribution and allelic frequencies of the MTHFR 1298 A > C, MTHFR 677 C > T, Factor V Leiden 1691 G > A, PAI-1-844G > A polymorphisms between the case and control groups. The MTHFR 1298 A > C, MTHFR 677 C > T and Factor V Leiden 1691 G > A polymorphisms were significantly associated with spontaneous miscarriage risk. Unlike some other race-ethnic populations, PAI-1-844G > A polymorphism was associated with risk of developing unplanned miscarriage in Iranian Arabs ethnic minority group females.

Crucial Role of Foxp3 Gene Expression and Mutation in Systemic Lupus Erythematosus, Inferred from Computational and Experimental Approaches.

The impaired suppressive function of regulatory T cells is well-understood in systemic lupus erythematosus. This is likely due to changes in Foxp3 expression that are crucial for regulatory T-cell stability and function. There are a few reports on the correlation between the Foxp3 altered expression level and single-nucleotide polymorphisms within the Foxp3 locus. Moreover, some studies showed the importance of Foxp3 expression in the same diseases. Therefore, to explore the possible effects of single-nucleotide polymorphisms, here, we evaluated the association of IVS9+459/rs2280883 (T>C) and -2383/rs3761549 (C>T) Foxp3 polymorphisms with systemic lupus erythematosus. Moreover, through machine-learning and deep-learning methods, we assessed the connection of the expression level of the gene with the disease. Single-nucleotide polymorphisms of Foxp3 (IVS9+459/rs2280883 (T>C) and -2383/rs3761549 (C>T)) were, respectively, genotyped using allele-specific PCR and direct sequencing and polymerase chain reaction-restriction fragment length polymorphism, in 199 systemic lupus erythematosus patients and 206 healthy age- and sex-matched controls. The Statistical Package for the Social Sciences version 19 and Fisher's exact and chi-square tests were used to analyze the data. Moreover, six machine-learning models and two sequential deep-learning models were designed to classify patients from normal people in the E-MTAB-11191 dataset through the expression level of Foxp3 and its correlated genes. The allele and genotype frequencies of both polymorphisms in question were found to be significantly associated with an increased risk of systemic lupus erythematosus. Furthermore, both of the two single-nucleotide polymorphisms were associated with some systemic-lupus-erythematosus-related risk factors. Three SVM models and the logistic regression model showed an 81% accuracy in classification problems. In addition, the first deep-learning model showed an 83% and 89% accuracy for the training and validation data, respectively, while the second model had an 85% and 79% accuracy for the training and validation datasets. In this study, we are prompted to represent the predisposing loci for systemic lupus erythematosus pathogenesis and strived to provide evidence-based support to the application of machine learning for the identification of systemic lupus erythematosus. It is predicted that the recruiting of machine-learning algorithms with the simultaneous measurement of the applied single nucleotide polymorphisms will increased the diagnostic accuracy of systemic lupus erythematosus, which will be very helpful in providing sufficient predictive value about individual subjects with systemic lupus erythematosus.

Preeclampsia Susceptibility Assessment Based on Deep Learning Modeling and Single Nucleotide Polymorphism Analysis.

The early diagnosis of preeclampsia, a key outlook in improving pregnancy outcomes, still remains elusive. The present study aimed to examine the interleukin-13 and interleukin-4 pathway potential in the early detection of preeclampsia as well as the relationship between interleukin-13 rs2069740(T/A) and rs34255686(C/A) polymorphisms and preeclampsia risk to present a combined model. This study utilized raw data from the GSE149440 microarray dataset, and an expression matrix was constructed using the RMA method and affy package. The genes related to the interleukin-13 and interleukin-4 pathway were extracted from the GSEA, and their expression levels were applied to design multilayer perceptron and PPI graph convolutional neural network models. Moreover, genotyping for the rs2069740(T/A) and rs34255686(C/A) polymorphisms of the interleukin-13 gene were tested using the amplification refractory mutation system PCR method. The outcomes revealed that the expression levels of interleukin-4 and interleukin-13 pathway genes could significantly differentiate early preeclampsia from normal pregnancy. Moreover, the present study's data suggested significant differences in the genotype distribution, the allelic frequencies and some of the risk markers of the study, in the position of rs34255686 and rs2069740 polymorphisms between the case and control groups. A combined test of two single nucleotide polymorphisms and an expression-based deep learning model could be designed for future preeclampsia diagnostic purposes.