ABSTRACT
Coronavirus disease 2019 (COVID-19), a pandemic that is triggered by a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) or 2019-nCoV, causes primarily respiratory discomfort along with other mild symptoms/no symptoms, leading to severe illness and death, if proper care is not taken. At present, COVID-19 is the resilient reason for a large number of human casualties worldwide as well as a cause of crucial economic loss posturing global threat. There is a necessity of intensive research to elucidate the pathogenic mechanisms of COVID-19, which would assist in understating the susceptibility towards the infection as well as prompt development of effective prevention and treatment strategies. Over the years, clinical studies have indicated the risk of various pathogenic infections prejudiced due to preexisting chronic diseases as well as ABO blood group types to a larger extent. In line of this, current COVID-19 infection-associated clinical studies intensely endorse the relationship of blood group type of individual and risk of COVID-19 infection. In this chapter, various clinical studies from January 2020 to June 2020 have been summarized to highlight the eminence of ABO blood group and COVID-19 infection susceptibility in human population. These reports evidently support the fact that individuals with A histo blood group were found to be more vulnerable to COVID-19 infection whereas individuals with blood group O were less likely to get infected with virus. To get deeper insight in this fact, many more studies are desirable in order to further explicate the promising protective role of the blood group O and it will be supportive for designing and planning several additional countermeasures against COVID-19 infection. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021.
ABSTRACT
Autoimmune diseases are a group of different inflammatory disorders characterized by systemic or localized inflammation, affecting approximately 0.1–1% of the general population. Several studies suggest that genetic risk loci are shared between different autoimmune diseases and pathogenic mechanisms may also be shared. The strategy of performing differential gene expression profiles in autoimmune disorders has unveiled new transcripts that may be shared among these disorders. Microarray technology and bioinformatics offer the most comprehensive molecular evaluations and it is widely used to understand the changes in gene expression in specific organs or in peripheral blood cells. The major goal of transcriptome studies is the identification of specific biomarkers for different diseases. It is believed that such knowledge will contribute to the development of new drugs, new strategies for early diagnosis, avoiding tissue autoimmune destruction, or even preventing the development of autoimmune disease. In this review, we primarily focused on the transcription profiles of three typical autoimmune disorders, including type 1 diabetes mellitus (destruction of pancreatic islet beta cells), systemic lupus erythematosus (immune complex systemic disorder affecting several organs and tissues), and multiple sclerosis (inflammatory and demyelinating disease of the nervous system). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.
ABSTRACT
Coronavirus disease (COVID-19) spreads mainly through close contact of infected persons, but the molecular mechanisms underlying its pathogenesis and transmission remain unknown. Here, we propose a statistical physics model to coalesce all molecular entities into a cohesive network in which the roadmap of how each entity mediates the disease can be characterized. We argue that the process of how a transmitter transforms the virus into a recipient constitutes a triad unit that propagates COVID-19 along reticulate paths. Intrinsically, person-to-person transmissibility may be mediated by how genes interact transversely across transmitter, recipient, and viral genomes. We integrate quantitative genetic theory into hypergraph theory to code the main effects of the three genomes as nodes, pairwise cross-genome epistasis as edges, and high-order cross-genome epistasis as hyperedges in a series of mobile hypergraphs. Charting a genome-wide atlas of horizontally epistatic hypergraphs can facilitate the systematic characterization of the community genetic mechanisms underlying COVID-19 spread. This atlas can typically help design effective containment and mitigation strategies and screen and triage those more susceptible persons and those asymptomatic carriers who are incubation virus transmitters.