COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211, and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe, and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data support the notion that the host’s genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708, and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.

The effectiveness of coronavirus disease 2019 (COVID-19) vaccination strategies is affected by several factors, including the genetic background of the host. In our study, we evaluated the contribution of the functional polymorphism rs1883832 affecting the Kozak sequence of the TNFSF5 gene (c.-1C>T), encoding CD40, to humoral immune responses after vaccination with the spike protein of SARS-CoV-2. The rs1883832 polymorphism was analyzed by PCR-RFLP in 476 individuals (male/female: 216/260, median age: 55.0 years, range: 20–105) of whom 342 received the BNT162b2 mRNA vaccine and 134 received the adenovirus-based vector vaccines (67 on ChAdOx1-nCoV-19 vaccine, 67 on Ad.26.COV2.S vaccine). The IgG and IgA responses were evaluated with chemiluminescent microparticle and ELISA assays on days 21, 42, and 90 after the first dose. The T allele of the rs1883832 polymorphism (allele frequency: 32.8%) was significantly associated with lower IgA levels and represented, as revealed by multivariable analysis, an independent risk factor for reduced anti-spike protein IgA levels on days 42 and 90 following BNT162b2 mRNA vaccination. Similar to serum anti-spike IgA levels, a trend of lower anti-spike IgA concentrations in saliva was found in individuals with the T allele of rs1883832. Finally, the intensity of IgA and IgG responses on day 42 significantly affected the prevalence of COVID-19 after vaccination. The rs1883832 polymorphism may be used as a molecular predictor of the intensity of anti-spike IgA responses after BNT162b2 mRNA vaccination.

Herbal medicinal products are increasingly used alongside conventional medicines, raising the risk of potential interactions such as pharmacodynamic drug–herb interactions (PD-DHIs) that can cause serious adverse drug reactions (ADRs). This review aims to present available pharmacological, clinical and pharmacoepidemiological literature regarding potential DHIs associated with serotonin syndrome or cardiac arrhythmias. Furthermore, it assesses the current evidence using the Oxford Centre for Evidence-Based Medicine (CEBM) 2009 framework. Serotonin syndrome most often results from combining serotonergic herbs (e.g., St. John’s wort) with antidepressants like serotonin reuptake inhibitors (SSRIs), as supported by repeated case reports and mechanistic plausibility (CEBM Level 3, Grade C). Other herbs such as black cohosh, ginseng, Syrian rue, turmeric, rhodiola, ashwagandha, and L-tryptophan/5-HTP have been linked to serotonin syndrome when used with SSRIs, serotonin-norepinephrine reuptake inhibitors (SNRIs), or monoamine oxidase inhibitors (MAOIs), but evidence is limited (Levels 4–5, Grade D). For cardiac arrhythmias, PD-DHIs arise when herbs interact with drugs that alter cardiac electrophysiology—such as QT-prolonging agents, psychotropics, antiarrhythmics or digoxin—thereby amplifying arrhythmogenic risk. Ephedra with sympathomimetics is strongly associated with arrhythmias (Level 2–3, Grade B). Licorice may potentiate digoxin and QT-prolonging drugs via hypokalemia (Level 4, Grade C). Other related PD-DHIs include aconite with antiarrhythmics, bitter orange or caffeine with QT-prolonging psychotropics, yohimbine with cardiovascular agents, and aloe or senna with digoxin. Overall, the evidence for PD-DHIs varies from moderate to weak but large-scale pharmacoepidemiological data is scarce. Future approaches, including artificial intelligence with explainable machine learning and network pharmacology, may integrate mechanistic, clinical, and real-world data to improve early detection or prediction of PD-DHIs. However, several specific challenges must be addressed. Therefore, it is crucial for healthcare providers in both clinical and community settings to increase their awareness of these interactions and ADRs to ensure the safe use of herbal remedies alongside conventional therapies.

COVID-19 is characterized by a heterogeneous clinical presentation and prognosis. Risk factors contributing to the development of severe disease include old age and the presence of comorbidities. However, the genetic background of the host has also been recognized as an important determinant of disease prognosis. Considering the pivotal role of innate immunity in the control of SARS-CoV-2 infection, we analyzed the possible contribution of several innate immune gene polymorphisms (including TLR2-rs5743708, TLR4-rs4986790, TLR4-rs4986791, CD14-rs2569190, CARD8-rs1834481, IL18-rs2043211 and CD40-rs1883832) in disease severity and prognosis. A total of 249 individuals were enrolled and further divided into five (5) groups, according to the clinical progression scale provided by the World Health Organization (WHO) (asymptomatic, mild, moderate, severe and critical). We identified that elderly patients with obesity and/or diabetes mellitus were more susceptible to developing pneumonia and respiratory distress syndrome after SARS-CoV-2 infection, while the IL18-rs1834481 polymorphism was an independent risk factor for developing pneumonia. Moreover, individuals carrying either the TLR2-rs5743708 or the TLR4-rs4986791 polymorphisms exhibited a 3.6- and 2.5-fold increased probability for developing pneumonia and a more severe disease, respectively. Our data supports the notion that the host’s genetic background can significantly affect COVID-19 clinical phenotype, also suggesting that the IL18-rs1834481, TLR2-rs5743708 and TLR4-rs4986791 polymorphisms may be used as molecular predictors of COVID-19 clinical phenotype.

Background and Objectives: Severe combined immunodeficiency (SCID) represents a group of rare and potentially fatal monogenic disorders arising from pathogenic variants in a broad spectrum of genes. Diagnostic delays beyond the first few months of life have been associated with poor overall survival and hematopoietic stem cell transplantation (HSCT) outcomes. Therefore, the aim of our study was to apply an NGS assay enabling the rapid and reliable diagnosis of SCID. Materials and Methods: We developed a targeted NGS panel of 30 genes implicated in the pathogenesis of most SCID cases and we applied it to three Greek infants with suspected SCID. Results: Each patient displayed a distinct immunophenotype—T⁻B⁻NK⁻, T⁻B⁻NK⁺ and T⁻B⁺NK⁻, respectively—and was found to harbor pathogenic or likely pathogenic variants in the analyzed SCID-related genes. In particular, patient 1 carried two heterozygous ADA variants (c.58G>A, p.Gly20Arg and c.956_960del, p.Glu319Glyfs); patient 2 harbored two discrete pathogenic variants in the DCLRE1C gene (a large deletion of exons 1–3 and the nonsense mutation c.241C>T, p.Arg81*), causing Artemis deficiency; and patient 3 carried a hemizygous IL2RG missense variant (c.437T>C, p.Leu146Pro), associated with X-linked SCID. All variants were confirmed by Sanger sequencing. Conclusions: Our method successfully identified the underlying genetic defects in all patients, thereby establishing a molecular diagnosis of SCID. These findings highlight the potential of targeted NGS assays for achieving rapid and accurate molecular diagnosis of SCID, which is crucial for the timely treatment of life-threatening conditions in affected children.