Relapsing-remitting multiple sclerosis: A profile of interleukine-1 gene cluster polymorphisms in Iraqi patients

Meta-analysis of the Selected Genetic Variants in Immune-Related Genes and Multiple Sclerosis Risk

Previous studies have suggested that certain variants in immune-related genes may participate in the pathogenesis of multiple sclerosis (MS), including rs17824933 in the CD6 gene, rs1883832 in the CD40 gene, rs2300747 in the CD58 gene, rs763361 in the CD226 gene, rs16944 in the IL-1β gene, rs2243250 in the IL-4 gene, and rs12722489 and rs2104286 in the IL-2Rα gene. However, the results remained inconclusive and conflicting. In view of this, a comprehensive meta-analysis including all eligible studies was conducted to investigate the association between these 8 selected genetic variants and MS risk. Up to June 2023, 64 related studies were finally included in this meta-analysis. The odds ratios (ORs) and corresponding 95% confidence intervals (CIs) calculated by the random-effects model were used to evaluate the strength of association. Publication bias test, sensitivity analyses, and trial sequential analysis (TSA) were conducted to examine the reliability of statistical results. Our results indicated that rs17824933 in the CD6 gene, rs1883832 in the CD40 gene, rs2300747 in the CD58 gene, rs763361 in the CD226 gene, and rs12722489 and rs2104286 in the IL-2Rα gene may serve as the susceptible factors for MS pathogenesis, while rs16944 in the IL-1β gene and rs2243250 in the IL-4 gene may not be associated with MS risk. However, the present findings need to be confirmed and reinforced in future studies.

Identification of immune-associated gene signature and immune cell infiltration related to overall survival in progressive multiple sclerosis

BACKGROUND

Delayed diagnosis and noneffective treatment contribute to the shorter life expectancy in patients with progressive multiple sclerosis (PMS). Studies demonstrate the key role of autoimmunity in PMS, but the prognostic value of immune-associated factors remains unknown. Thus, this study aimed to develop an immune-associated gene (IAG) signature related to overall survival (OS) and conduct an immune cell infiltration analysis using PMS data.

METHODS

The differentially expressed IAGs were identified based on gene expression profiles (from the Gene Expression Omnibus database) and IAGs (from the ImmPort database). Univariate and least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analyses were used to develop the IAG signature related to OS. Kaplan-Meier analyses were conducted, and receiver operating characteristic (ROC) curves were generated to assess the performance. Additionally, the differential distribution of immune cells was identified by Wilcoxon rank-sum tests and correlations with IAGs were analyzed using Spearman correlation analyses. Moreover, univariate and multivariate Cox regression analyses were used to identify the independent prognostic factors to develop a prognostic nomogram.

RESULTS

The training group, consisting of 57 PMS lesions and 52 control tissues, was obtained through batch normalization to remove the inter-batch difference. A total of 206 differentially expressed IAGs were identified, and 38 of them were associated with OS. Thereafter, a 4-IAG signature was constructed to calculate the risk score and thus classify PMS patients into high- and low-risk groups according to mean risk score. Patients in the high-risk group had a lower survival time than those in the low-risk group. The Kaplan-Meier plots and ROC curves demonstrated a good performance in both the training and internal validation groups. Additionally, five differentially abundant immune cell types were identified and their relationships with IAGs were analyzed. Finally, risk score, cortical region, and naive B cells were identified as independent prognostic factors, and a nomogram incorporating these factors was developed to predict the OS in PMS.

CONCLUSION

The novel IAG signature may be a reliable tool for assisting neurologists in predicting the OS for PMS patients in clinical settings. These findings may facilitate personalized treatment and provide insights into the complex mechanism of PMS.

Detection of association of IL1β, IL4R, and IL6 gene polymorphisms with cervical cancer in the Bangladeshi women by tetra-primer ARMS-PCR method

BACKGROUND

Cervical cancer (CC) is the main cause of cancer-related deaths among women in developing countries. It is the second leading female malignancy in Bangladesh in terms of incidence and mortality. Our present study aimed to investigate the association of IL1β (rs16944), IL4R (rs1801275), and IL6 (rs1800797) gene polymorphisms with the susceptibility of cervical cancer.

MATERIALS AND METHODS

This case-control study was conducted on 252 cervical cancer patients and 228 healthy volunteers, using tetra-primer amplification refractory mutation system-polymerase chain reaction (ARMS-PCR).

RESULTS

In the case of rs16944 polymorphism, GG genotype (OR = 2.10, 95%CI = 1.24-3.56), dominant model (OR = 1.71, 95% CI = 1.11-2.63), recessive model (OR = 1.54, 95% CI = 1.01-2.35), and G allele (OR = 1.30, 95% CI = 1.005-1.68) were significantly associated with increased cervical cancer risk. Among these, GG genotype and dominant model remained significant after the Bonferroni correction (p < 0.017). For rs1801275 polymorphism, GG genotype (OR = 2.66, 95% CI = 1.49-4.75), dominant model (OR = 1.49, 95% CI = 1.04-2.14), recessive model (OR = 2.45, 95% CI = 1.40-4.27), and G allele (OR = 1.59, 95% CI = 1.21-2.10) significantly elevated the risk of cervical cancer but significance did not exist for dominant model after the Bonferroni correction. rs1800797 variant showed significantly increased risk in all genetic models including, AG genotype (OR = 8.13, 95% CI = 5.27-12.55), AA genotype (OR = 9.86, 95% CI = 2.76-35.21), dominant model (OR = 8.25, 95% CI = 5.40-12.60), recessive model (OR = 4.41, 95% CI = 1.25-15.56), and A allele (OR = 4.99, 95% CI = 3.49-7.13) and the significances were consistent with the Bonferroni correction except recessive model. Haplotyping analysis indicates that GAA (p = 5.15x10^-5) and GAG haplotypes (p = 4.72x10^-9) significantly decreased the risk of CC, whereas AAA (p = 3.89x10-9), AAG (p = 0.0003), AGA (p = 3.98x10-5) and AGG haplotypes (p = 0.002) significantly increased the risk of CC. The IL1β mRNA level was up-regulated, which was associated with poor prognosis in silico.

CONCLUSION

Our results conclude that rs16944 (IL1β), rs1801275 (IL4R), and rs1800797 (IL6) polymorphisms are associated with cervical cancer in Bangladeshi women.