ABSTRACT
Introduction: Increased reporting of menstrual disturbances post-vaccination and inadequate inclusion of questions about menstruation in vaccine trials and disease progression studies have been the baseline for conducting this study. We aim to assess the influence of vaccines and COVID-19 infection on menstruation and identify patterns, if any, in cycles post-disease/vaccination. Methods: A multicenter observational study was performed using a questionnaire-based survey via an online link. The participants who filled the survey were predominantly in the age group of 21–25 years (80%). Participants with prior menstrual irregularities were eliminated from the study. Results: The prevalence of unusual menstrual cycles post-infection/vaccination was 21.7%. A total of 17.11% experienced changes post-vaccination and 22.8% of the infected individuals reported abnormalities post-COVID-19 disease. A substantial increase in dysmenorrhea was reported (p <0.001) post-infection/vaccination. An increase in menstrual flow was observed in 14.9% post-vaccination and 23.9% post-infection. Conclusion: Menstrual changes post-vaccination were insignificant;however, significant differences in menstruation were reported post-infection. The study strengthens the association between COVID-19 and menstruation and urges the inclusion of menstrual health in disease intervention studies.
ABSTRACT
Understanding the pathogenesis of SARS-CoV-2 is essential for developing effective treatment strategies. Viruses hijack the host metabolism to redirect the resources for their replication and survival. The influence of SARS-CoV-2 on host metabolism is yet to be fully understood. In this study, we analyzed the transcriptomic data obtained from different human respiratory cell lines and patient samples (nasopharyngeal swab, peripheral blood mononuclear cells, lung biopsy, bronchoalveolar lavage fluid) to understand metabolic alterations in response to SARS-CoV-2 infection. We explored the expression pattern of metabolic genes in the comprehensive genome-scale network model of human metabolism, Recon3D, to extract key metabolic genes, pathways, and reporter metabolites under each SARS-CoV-2-infected condition. A SARS-CoV-2 core metabolic interactome was constructed for network-based drug repurposing. Our analysis revealed the host-dependent dysregulation of glycolysis, mitochondrial metabolism, amino acid metabolism, nucleotide metabolism, glutathione metabolism, polyamine synthesis, and lipid metabolism. We observed different pro- and antiviral metabolic changes and generated hypotheses on how the host metabolism can be targeted for reducing viral titers and immunomodulation. These findings warrant further exploration with more samples and in vitro studies to test predictions.