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Insufficient vitamin D levels in the bloodstream, together with the presence of specific genetic variations known as single nucleotide polymorphisms (SNPs) within the VDR gene, have consistently been linked to a higher likelihood of contracting and experiencing more severe forms of various diseases such as the ongoing COVID-19 pandemic. We aimed to explore the potential relationship between vitamin D levels, Bsml and FOKI polymorphisms, and COVID-19 infection outcomes. A case-control study was conducted with COVID-19 patients and a control group of non-COVID-19 patients (n = 107 each). The associations between vitamin D status, polymorphisms, and COVID susceptibility were investigated. Participants diagnosed with COVID-19 exhibited an average age of 48.84 ± 12.18, while non-COVID-19 patients had an average age of 46.82 ± 9.903. Disease severity, assessed by the CT severity score, showed a negative correlation with the Vitamin D levels. Among participants with COVID-19, the mean level of vitamin D was 35.25 ± 9.40 ng/mL while non-COVID-19 patients showed 38.85 ± 9.40 ng/mL with a significant difference (p = 0.004**) although among COVID-19 cases, 87 (81.3%) individuals had sufficient vitamin D levels and non-severity of disease was more common i.e. 54 (50.5%) among the COVID patients who had sufficient level of Vitamin D. The study found no significant association between Vitamin D levels and rs1544410 Bsml polymorphism (p = 0.429). However, it is important to highlight a weak significant association observed between with Fok1 polymorphism (p = 0.049). These findings underscore the weak influence of genetic factors, particularly VDR Fok1 gene variants, in shaping an individual’s susceptibility to COVID-19. A significant difference in vitamin D status was observed between the COVID-19 and non-COVID-19 groups and lower level was observed in the COVID-19 infected patients. Furthermore, a weak significant association was observed between Fok1 rs2228570 genotype and COVID-19 susceptibility. Larger sample sizes are required to comprehensively understand the association between different genotypes and COVID-19 outcomes.

Abstract Background Coronavirus Disease 2019 (COVID-19) is a worldwide pandemic challenge spreading enormously within a few months. COVID-19 is characterized by the over-activation of the immune system causing cytokine storm. Insulin-like growth factor-1 (IGF-1) pathway can regulate the immune response via interaction with various implicated cytokines. Heart-type fatty acid-binding protein (H-FABP) has been shown to promote inflammation. Given the fact that coronavirus infections induce cytokines secretion leading to inflammatory lung injury, it has been suggested that H-FABP levels are affected by COVID-19 severity. Moreover, endotrophin (ETP), the cleavage product of collagen VI, may be an indicator of an overactive repair process and fibrosis, considering that viral infection may predispose or exacerbate existing respiratory conditions, including pulmonary fibrosis. This study aims to assess the prognostic capacity of circulating IGF-1, HFABP, and ETP, levels for COVID-19 severity progression in Egyptian patients. Methods The study cohort included 107 viral RNA-positive patients and an equivalent number of control individuals with no clinical signs of infection. Clinical assessments included profiling of CBC; serum iron; liver and kidney functions; inflammatory markers. Circulating levels of IGF-1; H-FABP, and ETP were estimated using the corresponding ELISA kits. Results No statistical difference in the body mass index was detected between the healthy and control groups, while the mean age of infected patients was significantly higher (P = 0.0162) than the control. Patients generally showed elevated levels of inflammatory markers including CRP and ESR concomitant with elevated serum ferritin; D dimer and procalcitonin levels, besides the COVID-19 characteristic lymphopenia and hypoxemia were also frequent. Logistic regression analysis revealed that oxygen saturation; serum IGF-1, and H-FABP can significantly predict the infection progression (P