Relevance of HLA-DP/DQ and INF-λ4 Polymorphisms to COVID-19 Outcomes.

Background: Single nucleotide polymorphisms provide information on individuals' potential reactions to environmental factors, infections, diseases, as well as various therapies. A study on SNPs that influence SARS-CoV-2 susceptibility and severity may provide a predictive tool for COVID-19 outcomes and improve the customized coronavirus treatment. Aim: To evaluate the role of human leukocyte antigens DP/DQ and IFNλ4 polymorphisms on COVID-19 outcomes among Egyptian patients. Participants and Methods: The study involved 80 patients with severe COVID-19, 80 patients with mild COVID-19, and 80 non-infected healthy volunteers. Genotyping and allelic discrimination of HLA-DPrs3077 (G/A), HLA-DQrs7453920 (A/G), and IFNλ4 rs73555604 (C/T) SNPs were performed using real-time PCR. Results: Ages were 47.9 ± 8, 44.1 ± 12.1, and 45.8 ± 10 years in severe, mild and non-infected persons. There was a statistically significant association between severe COVID-19 and male gender (p = 0.002). A statistically significant increase in the frequency of HLA-DPrs3077G, HLA-DQrs7453920A, and IFNλ4rs73555604C alleles among severe COVID-19 patients when compared with other groups (p < 0.001). Coexistence of these alleles in the same individual increases the susceptibility to severe COVID-19 by many folds (p < 0.001). Univariate and multivariate logistic regression analysis for the studied parameters showed that old age, male gender, non-vaccination, HLA-DQ rs7453920AG+AA, HLA-DPrs3077GA+GG, and IFNλ4rs73555604CT+CC genotypes are independent risk factors for severe COVID-19 among Egyptian patients. Conclusion: HLA-DQ rs7453920A, HLA-DPrs3077G, and IFNλ4rs73555604C alleles could be used as markers of COVID-19 severity.

Impact of ACE and Endoplasmic Reticulum Aminopeptidases Polymorphisms on COVID-19 Outcome.

Background: COVID-19 outcomes display multiple unexpected varieties, ranging from unnoticed symptomless infection to death, without any previous alarm or known aggravating factors. Aim: To appraise the impact of ACErs4291(A/T) and ERAP1rs26618(T/C) human polymorphisms on the outcome of COVID-19. Subjects and methods: In total, 240 individuals were enrolled in the study (80 with severe manifestations, 80 with mild manifestations, and 80 healthy persons). ACErs4291(A/T) and ERAP1rs26618(T/C) genotyping was performed using RT-PCR. Results: The frequency of the ACErs4291AA genotype was higher among the severe COVID-19 group than others (p < 0.001). The ERAP1rs26618TT genotype frequency was higher among the severe COVID-19 group in comparison with the mild group (p < 0.001) and non-infected controls (p = 0.0006). The frequency of the ACErs4291A allele was higher among severe COVID-19 than mild and non-infected groups (64.4% vs. 37.5%, and 34.4%, respectively), and the ERAP1rs26618T allele was also higher in the severe group (67.5% vs. 39.4%, and 49.4%). There was a statistically significant association between severe COVID-19 and ACErs4291A or ERAP1rs26618T alleles. The coexistence of ACErs4291A and ERAP1rs26618T alleles in the same individual increase the severity of the COVID-19 risk by seven times [OR (95%CI) (LL−UL) = 7.058 (3.752−13.277), p < 0.001). A logistic regression analysis revealed that age, male gender, non-vaccination, ACErs4291A, and ERAP1rs26618T alleles are independent risk factors for severe COVID-19. Conclusions: Persons carrying ACErs4291A and/or ERAP1rs26618T alleles are at higher risk of developing severe COVID-19.

Identification of DPP4/CTNNB1/MET as a Theranostic Signature of Thyroid Cancer and Evaluation of the Therapeutic Potential of Sitagliptin.

In recent years, the incidence of thyroid cancer has been increasing globally, with papillary thyroid cancer (PTCa) being the most prevalent pathological type, accounting for approximately 80% of all cases. Although PTCa has been regarded to be slow growing and has a good prognosis, in some cases, PTCa can be aggressive and progress despite surgery and radioactive iodine treatment. In addition, most cancer treatment drugs have been shown to be cytotoxic and nonspecific to cancer cells, as they also affect normal cells and consequently cause harm to the body. Therefore, searching for new targets and therapies is required. Herein, we explored a bioinformatics analysis to identify important theranostic markers for THCA. Interestingly, we identified that the DPP4/CTNNB1/MET gene signature was overexpressed in PTCa, which, according to our analysis, is associated with immuno-invasive phenotypes, cancer progression, metastasis, resistance, and unfavorable clinical outcomes of thyroid cancer cohorts. Since most cancer drugs were shown to exhibit cytotoxicity and to be nonspecific, herein, we evaluated the anticancer effects of the antidiabetic drug sitagliptin, which was recently shown to possess anticancer activities, and is well tolerated and effective. Interestingly, our in silico molecular docking results exhibited putative binding affinities of sitagliptin with DPP4/CTNNB1/MET signatures, even higher than standard inhibitors of these genes. This suggests that sitagliptin is a potential THCA therapeutic, worthy of further investigation both in vitro and in vivo and in clinical settings.