Host genetic variants can determine their susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS). Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we compute genetic risk scores in diverse Indian sub-populations that may predict differences in the severity of COVID-19 outcomes. We utilized the top 100 most significantly associated single-nucleotide polymorphisms (SNPs) from a GWAS by Pairo-Castineira et al. determining the genetic susceptibility to severe COVID-19 infection, to compute population-wise polygenic risk scores (PRS) for populations represented in the Indian Genome Variation Consortium (IGVC) database. Using a generalized linear model accounting for confounding variables, we found that median PRS was significantly associated (p < 2 x 10−16) with COVID-19 mortality in each district corresponding to the population studied and had the largest effect on mortality (regression coefficient = 10.25). As a control we repeated our analysis on randomly selected 100 non-associated SNPs several times and did not find significant association. Therefore, we conclude that genetic susceptibility may play a major role in determining the differences in COVID-19 outcomes and mortality across the Indian sub-continent. We suggest that combining PRS with other observed risk-factors in a Bayesian framework may provide a better prediction model for ascertaining high COVID-19 risk groups and to design more effective public health resource allocation and vaccine distribution schemes.
Deteriorating weight loss in patients with Huntington’s disease (HD) is a complicated peripheral manifestation and the cause remains poorly understood. Studies suggest that body weight strongly influences the clinical progression rate of HD and thereby offers a valuable target for therapeutic interventions. Mutant huntingtin (mHTT) is ubiquitously expressed and could induce toxicity by directly acting in the peripheral tissues. We investigated the effects of selective expression of mHTT exon1 in fat body (FB; functionally equivalent to human adipose tissue and liver) using transgenic Drosophila . We find that FB-autonomous expression of mHTT exon1 is intrinsically toxic and causes chronic weight loss in the flies despite progressive hyperphagia, and early adult death. Moreover, flies exhibit loss of intracellular lipid stores, and decline in the systemic levels of lipids and carbohydrates which aggravates over time, representing metabolic defects. At the cellular level, besides impairment, cell death also occurs with the formation of mHTT aggregates in the FB. These findings indicate that FB-autonomous expression of mHTT alone is sufficient to cause metabolic abnormalities and emaciation in vivo without any neurodegenerative cues.
Deinococcus species are widely studied due to their utility in bioremediation of sites contaminated with radioactive elements. In the present study, we re-evaluated the taxonomic placement of two species of the genus Deinococcus namely D. swuensis DY59T and D. radiopugnans ATCC 19172T based on whole genome analyses. The 16S rRNA gene analysis revealed a 99.58% sequence similarity between this species pair that is above the recommended threshold value for species delineation. These two species also clustered together in both the 16S rRNA gene and core genome based phylogenies depicting their close relatedness. Furthermore, more than 98% of genes were shared between D. swuensi s DY59T and D. radiopugnans ATCC 19172T. Interestingly, D. swuensis DY59T and D. radiopugnans ATCC 19172T shared high genome similarity in different genomic indices. They displayed an average nucleotide identity value of 97.63%, an average amino acid identity value of 97% and a digital DNA–DNA hybridization value equal to 79.50%, all of which are well above the cut-off for species delineation. Altogether, based on these evidences, D. swuensis DY59T and D. radiopugnans ATCC 19172T constitute a single species. Hence, as per the priority of publication, we propose that Deinococcus swuensis Lee et al. 2015 should be reclassified as a later heterotypic synonym of Deinococcus radiopugnans .
Host genetic variants can determine the susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS) by Pairo-Castineira et al.1. Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we deploy the previous study and compute genetic risk scores in different Indian sub-populations that may predict the severity of COVID-19 outcomes in them. We computed polygenic risk scores (PRSs) in different Indian sub-populations with the top 100 single-nucleotide polymorphisms (SNPs) with a p-value cutoff of 10-6 derived from the previous GWAS summary statistics1. We selected SNPs overlapping with the Indian Genome Variation Consortium (IGVC) and with similar frequencies in the Indian population. For each population, median PRS was calculated, and a correlation analysis was performed to test the association of these genetic risk scores with COVID-19 mortality. We found a varying distribution of PRS in Indian sub-populations. Correlation analysis indicates a positive linear association between PRS and COVID-19 deaths. This was not observed with non-risk alleles in Indian sub-populations. Our analyses suggest that Indian sub-populations differ with respect to the genetic risk for developing COVID-19 mediated critical illness. Combining PRSs with other observed risk-factors in a Bayesian framework can provide a better prediction model for ascertaining high COVID-19 risk groups. This has a potential utility in the design of more effective vaccine disbursal schemes.
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