Introduction Growing evidence documented the critical impacts of vitamin D (VD) in the prognosis of COVID-19 patients. The functions of VD are dependent on the vitamin D receptor (VDR) in the VD/VDR signaling pathway. Therefore, we aimed to assess the association of VDR gene polymorphisms with COVID-19 outcomes. Methods In the present study, eight VDR single nucleotide polymorphisms (SNPs) were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in 500 COVID-19 patients in Iran, including 160 asymptomatic, 250 mild/moderate, and 90 severe/critical cases. The association of these polymorphisms with severity, clinical outcomes, and comorbidities were evaluated through the calculation of the Odds ratio (OR). Results Interestingly, significant associations were disclosed for some of the SNP-related alleles and/or genotypes in one or more genetic models with different clinical data in COVID-19 patients. Significant association of VDR-SNPs with signs, symptoms, and comorbidities was as follows: Apa I with shortness of breath (P ˂ 0.001) and asthma (P = 0.034) in severe/critical patients (group III); Bsm I with chronic renal disease (P = 0.010) in mild/moderate patients (group II); Tru9I with vomiting (P = 0.031), shortness of breath (P = 0.04), and hypertension (P = 0.030); Fok I with fever and hypertension (P = 0.027) in severe/critical patients (group III); CDX2 with shortness of breath (P = 0.022), hypertension (P = 0.036), and diabetes (P = 0.042) in severe/critical patients (group III); Eco RV with diabetes (P ˂ 0.001 and P = 0.045 in mild/moderate patients (group II) and severe/critical patients (group III), respectively). However, the association of VDR TaqI and Bgl I polymorphisms with clinical symptoms and comorbidities in COVID-19 patients was not significant. Conclusion VDR gene polymorphisms might play critical roles in the vulnerability to infection and severity of COVID-19, probably by altering the risk of comorbidities. However, these results require further validation in larger studies with different ethnicities and geographical regions.

Polycystic ovary syndrome is a multifactorial condition associated with reproductive and endocrine organs and might cause infertility and metabolic abnormalities in childbearing age. PCOS seems to be a multifactorial disorder resulting from the combination of several genetic and environmental factors. Little research has been conducted to date on the impact of polymorphisms in infertility. We aim to review the appearance of polymorphisms in females of diverse ethnicities and their effect on infertility in the population with polycystic ovary syndrome. There have been numerous reports of the importance of the steroidogenesis pathway and genetic variants in PCOS pathogenesis. The most important genes that play a role in the aetiology of PCOS are CYP11A1, CYP17A1, and CYP19A1. We evaluated the occurrence of polymorphisms in various ethnicities in the CYP11A1, CYP17A1, and CYP19A1 genes and their efficacy on increasing PCOS risk with infertility. Our findings revealed that polymorphisms in various ethnicities are associated with the risk of PCOS with infertility. Although conflicting results regarding CYP11A1, CYP17A1, and CYP19A1 polymorphisms and their influence on PCOS with infertility have been reported in a small number of papers, the authors feel this may be attributable to the sample size and ethnic composition of the examined populations. In conclusion, our study strongly suggests that the CYP11A1, CYP17A1, and CYP19A1 genes might significantly enhance the probability of developing PCOS with infertility.

Background Coronary artery disease (CAD) is the leading cause of death worldwide and remains a major health problem, providing the rationale for identification of molecular markers for detection of individuals at high risk of developing CAD. Tumor necrosis factor‐α (TNF‐α) plays a crucial role in the pathogenesis of CAD. We have therefore explored the association of TNF‐α 308 (G/A) gene polymorphism in 903 individuals with/without CAD. Methods TNF‐α 308 gene polymorphism was analyzed in 903 subjects of whom 222 were healthy controls. Among the 681 patients who were investigated angiographically, 468 had ≧50% stenosis and 213 patients had <50% stenosis. Biochemical profiles (eg, triglycerides, high‐density lipoprotein cholesterol, low‐density lipoprotein cholesterol, fasting blood glucose, and CRP) were evaluated. Associations between TNF‐α genotypes with biochemical and anthropometric characteristics were determined. Results The frequencies of TNF‐α‐AA or AG genotypes were significantly lower in patients classified as CAD patients with ≥ or <50% obstruction in at least one coronary artery, compared to the control group. We observed that CAD patients with ≥50% stenosis and with AA genotype were associated with higher risk of CAD with OR of 3.56 (95%CI: 1.02‐12.41; P=.046) using multivariate analysis. Moreover, we found that TNF‐α‐308‐AA genotype was associated with blood pressure and CRP level in CAD patients, compared to the wild type‐genotype. Conclusion Our data showed an association of TNF‐α‐308G/A polymorphism with CAD patients with ≥50% obstruction, supporting the need for further investigations on the role of TNF‐α‐308G/A polymorphism with hypertension.

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Parkinson's disease (PD) is categorized as a neurodegenerative disorder. Different studies have focused on the role of microRNAs (miRNAs) on PD progression. Due to its complexity in initiation and progression, a considerable requirement has arisen to identify novel miRNA biomarkers in a noninvasive manner. In silico analysis has been used to select differentially expressed miRNAs (DE‐miRNAs) and key pathways in this disease. In this manner, several data sets of different neurodegenerative diseases have been analyzed to purify the findings of the present study. Totally, 15 DE miRNAs showed significant changes compared to healthy controls and other neurodegenerative diseases. Then, the targets of the miRNAs were predicted through miRTarBase and TargetScan databases. Besides, enrichment analysis was implemented for predicted target genes. Most of the target genes were enriched in the TRAIL signaling pathway, Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism, protein serine/threonine kinase activity, and Cytoplasm. Moreover, a protein−protein interaction network was constructed to find the most key DE miRNAs and targets in this disease. The results of the present study may help researchers shed light on the discovery of novel biomarkers for PD.