ABSTRACT
Background/Objectives: Corticosteroids are widely used for the treatment of coronavirus disease (COVID)-19 caused by SARS-CoV- 2 as they attenuate the immune response with their antiinflammatory properties. Genetic polymorphisms of glucocorticoid receptor, metabolizing enzymes or transporters may affect treatment response to dexamethasone. The aim of this study was to evaluate the association of polymorphisms in glucocorticoid pathway with disease severity and duration of dexamethasone treatment in COVID-19 patients. Method(s): Our study included 107 hospitalized COVID-19 patients treated with dexamethasone. We isolated DNA from peripheral blood and genotyped all samples for polymorphisms in NR3C1 (rs6198, rs33388), CYP3A4 (rs35599367), CYP3A5 (rs776746), GSTP1 (rs1695, rs1138272), GSTM1/GSTT1 deletions and ABCB1 (1045642, rs1128503, rs2032582 Fisher's and Mann- Whitney tests were used in statistical analysis. Result(s): The median (min-max) age of the included patients was 62 (26-85) years, 69.2 % were male and 30.8 % female and they had moderate (1.9 %), severe (83 %) or critical (15.1 %) disease. NR3C1 rs6198 polymorphism was associated with more severe disease in additive genetic model (P = 0.022). NR3C1 rs6198, ABCB1 rs1045642 and ABCB1 rs1128503 polymorphisms were associated with a shorter duration of dexamethasone treatment in additive (P = 0.048, P = 0.047 and P = 0.024, respectively) and dominant genetic models (P = 0.015, P = 0.048 and P = 0.020, respectively), while carriers of the polymorphic CYP3A4 rs35599367 allele required longer treatment with dexamethasone (P = 0.033). Other polymorphisms were not associated with disease severity or dexamethasone treatment duration. Conclusion(s): Genetic variability of glucocorticoid pathway genes was associated with the duration of dexamethasone treatment of COVID-19 patients.
ABSTRACT
Background: The pathophysiology of viral-infections is highly complex and involves host immunocompetence, host genetics, and gene-environment interactions. We hypothesized that polymorphic variants in host genes, blood group and previous vaccination status against H1N1 may affect the clinical course of covid-19 infection. Method(s): A total of 202 subjects who were RT-PCR negative after Covid-19 infection were recruited. We investigated association between Covid-19 infection (Severity and recovery period) and multiple factors including ABO and Rh blood groups, H1N1 vaccination, polymorphism in Viral susceptibility genes (ACE2 G8790A), and polymorphism in host response genes (ACE I/D rs4646994, IL6- 174G/C, GSTT1/GSTM1 I/D and GSTP1 Ile 105 Val). Result(s): B-ve and O-ve ABO and Rh blood groups had significantly higher Covid-19 recovery period applied on one-vs.-all in a nonparametric t-test (p<0.05). Subjects who had vaccinated themselves against H1N1 presented with a lower recovery-period (p<0.05). Both variables (blood group and H1N1 vaccination) were not however associated with Covid-19 severity. Out of the studied polymorphisms, ACE2 G8790A and GSTT1/GSTM1 were significantly associated with covid-19 infection. Our results indicated that G/G genotype of ACE2 G8790A (OR 3.52, P 0.007) and GSTT1/ GSTM1 null (M1 - / - OR = 3.98, P = 0.0004;T1 - / - OR 3.84, P = 0.004) and double null (M1 - / - /T1 - / - OR = 9.66, P = 0.001) are likely to be associated with an increased risk for severe-critical outcomes in individuals with COVID-19. Other polymorphisms analyzed in this study were found to have no significant association with Covid-19 outcome. Conclusion(s): This study suggests that outcome of Covid-19 infection is affected by both clinical and genetic factors. Thus it seems plausible to utilize these factors as prediction and susceptibility markers in the prognosis of COVID-19, which may help to personalize the treatment.
ABSTRACT
Comprehensive proteomic studies of HSC derived from bone marrow of healthy human subjects (n = 59) in different age groups (range: 20 - 72 years) showed that aging HSCs are characterized not only by myeloid lineage skewing, senescence associated secretory phenotype (SASP), accumulation of reactive oxygen species (ROS), anti-apoptosis, but prominently by elevated glycolysis, glucose uptake, and accumulation of glycogen. This is caused by a subset of HSC that has become more glycolytic than others and not on a per cell basis. Subsequent comparative transcriptome studies of HSCs from human subjects >60 years versus those from <30 years have confirmed this association of elevated glycolysis with aging transcriptome signature. Provided with this background and based on glucose metabolism levels, we have developed a method to isolate human HSCs (CD34+ cells) from bone marrow into three distinct subsets with high, intermediate, and low glucose uptake (GU) capacity (GU high, GU inter, GU low). For human subjects >60 years old (n=9), the proportions of these subsets are: GU high= 5.4+3.5 %, GU inter= 66.4+22.5 %, GU low= 28.2+21.7 %. For subjects <30 years (n=5), the proportions are GU high= 1.7+1.5 %, GU inter= 66.5+36.9 %, GU low= 31.8+36.7. Single-cell RNA-sequencing (scRNA-seq) studies and gene ontology analysis of biological processes revealed that, compared to the GU inter and GU low subsets, the GU high cells showed a significantly higher expression of genes involved in myeloid development, inflammation response (AIF1, CASP2, ANXA1, ZFP36), anti-apoptosis (GSTP1, NME1, BCL2, DMNT1, BAX), cell cycle checkpoint (MCL1, CDK1, CDK4, EIF5A), histone regulation (BCL6, EGR1, KDM1A, MLLT3), b-galactosidase, and significantly lower expressions of genes involved in lymphoid development, and of MDM4, MDM2, FOXP1, SOX4, RB1. Functional studies indicated that the glycolytic enzymes were elevated in elderly HSCs, and the GU low subset corresponded to primitive and more pluripotent HSCs than the GU interand GU high subsets. Pathway analyses have then demonstrated that the GU high subset is associated with up-regulated p53 as well as JAK/STAT signaling pathways, characteristic of senescent HSCs observed in murine models. Applying Gene Set Enrichment Analysis (GSEA) algorithms, we have compared the scRNA-seq data of CD34+ cells derived from young (<30 years) versus older (>60 years) subjects, as well as the scRNA-seq data from GU high subset versus GU inter and GU lowsubsets from each individual subject (n = 6). The results are shown in Figure 1. In analogy to the comparison between old (>60 years) versus young (<30 years) HSCs (CD34+ cells), GSEA of the GU high versus GU inter and GU low subsets shows the same pattern of changes - significant upregulation of gene-set expressions for (a) inflammatory response (b) G2M checkpoint, (c) MTORC1, (d) ROS, (Fig. 1B), (e) allograft rejection;and down-regulation of gene-set expressions for (f) pluripotency, (g) androgen response, (h) UV response (Fig. 1C) as well as (i) interferon-a induction during SARS-CoV2-infection (data not shown in Fig. 1). Thus, our novel findings of elevated glycolysis coupled with significant activation of MTORC1 in the senescent cells of the HSC compartment have provided evidence for the important role of calorie restriction (CR) for healthy aging of HSCs. In numerous animal models, aging has been shown to be driven by the nutrient-sensing MTORC1 network. In animal models of aging, CR has been reported to deactivate the MTOR pathway, thus slowing aging and delaying diseases of aging. Conclusion: In a series of multi-omics studies, we have demonstrated that the GU high subset is identical to the senescent cells (SCs) in human HSC compartment. Studies in animal models have shown that SCs in murine bone marrow are responsible for driving the aging process, and elimination of this subset by inhibitors of anti-apoptotic factors is able to rejuvenate hematopoiesis in mice. Our present results have provided cellular and molecular evidence that SCs in human HSC compartment re also dependent on anti-apoptotic factors, elevated MTORC1 as well as increased glycolysis for survival. Inhibition of MTORC1 or glycolysis, either by specific inhibitors or by CR, may eliminate senescent HSCs and promote rejuvenation of human hematopoiesis. [Formula presented] Disclosures: No relevant conflicts of interest to declare.