SFTPB (rs11130866) and NR3C1 (rs41423247) gene variants as potential clinical biomarkers for personalized treatment strategy selection in patients with severe COVID-19 pneumonia

Causal association and shared genetics between telomere length and COVID-19 outcomes: New evidence from the latest large-scale summary statistics

Background

Observational studies suggested that leukocyte telomere length (LTL) is shortened in COVID-19 patients. However, the genetic association and causality remained unknown.

Methods

Based on the genome-wide association of LTL (N = 472,174) and COVID-19 phenotypes (N = 1086,211-2597,856), LDSC and SUPERGNOVA were used to estimate the genetic correlation. Cross-trait GWAS meta-analysis, colocalization, fine-mapping analysis, and transcriptome-wide association study were conducted to explore the shared genetic etiology. Mendelian randomization (MR) was utilized to infer the causality. Upstream and downstream two-step MR was performed to investigate the potential mediating effects.

Results

LDSC identified a significant genetic association between LTL and all COVID-19 phenotypes (rG < 0, p < 0.05). Six significant regions were observed for LTL and COVID-19 susceptibility and hospitalization, respectively. Colocalization analysis found rs144204502, rs34517439, and rs56255908 were shared causal variants between LTL and COVID-19 phenotypes. Numerous biological pathways associated with LTL and COVID-19 outcomes were identified, mainly involved in -immune-related pathways. MR showed that longer LTL was significantly associated with a lower risk of COVID-19 severity (OR [95% CI] = 0.81 [0.71-0.92], p = 1.24 ×10-3) and suggestively associated with lower risks of COVID-19 susceptibility (OR [95% CI] = 0.96 [0.92-1.00], p = 3.44 ×10-2) and COVID-19 hospitalization (OR [95% CI] = 0.89 [0.80-0.98], p = 1.89 ×10-2). LTL partially mediated the effects of BMI, smoking, and education on COVID-19 outcomes. Furthermore, six proteins partially mediated the causality of LTL on COVID-19 outcomes, including BNDF, QPCT, FAS, MPO, SFTPB, and APOF.

Conclusions

Our findings suggested that shorter LTL was genetically associated with a higher risk of COVID-19 phenotypes, with shared genetic etiology and potential causality.

The surfactant protein B polymorphisms (rs7316 and rs1130866) and their correlation with disease progression of COVID-19

BACKGROUND

It is critical to examine the pathogenic pathways in coronavirus disease 2019 (COVID-19) that resulted in the development of severe lung injury. Surfactant protein B (SFTPB) is a vital component for sustaining life and serves pivotal functions in the host's defensive mechanisms and alveolar surface tension reduction. Our study aimed to determine the effect of SFTPB rs7316 and rs1130866 variants on the course of disease in COVID-19 patients.

METHODS

The study cohort comprised 3,184 individuals diagnosed with COVID-19. We employed the RFLP approach to determine the variations of the SFTPB genes.

RESULTS

SFTPB rs7316 did not exhibit a statistically significant correlation with COVID-19 mortality across different inheritance models. But, after making more changes for SARS-CoV-2 variants, it was found that there was a strong link between the TT and TC genotypes of SFTPB rs7316 and death rates, especially for the Delta variant. Furthermore, our study's findings indicate a significant association between the SFTPB rs1130866 G allele and an elevated risk of mortality in COVID-19 across all variants of SARS-CoV-2.

CONCLUSIONS

The use of the SFTPB rs1130866 marker has the potential to facilitate the prediction of COVID-19 severity. On the other hand, for SFTPB rs7316, this kind of prediction seems to depend on the particular SARS-CoV-2 variants.

Genetic variability in the glucocorticoid pathway and treatment outcomes in hospitalized patients with COVID-19: a pilot study

Introduction: Corticosteroids are widely used for the treatment of coronavirus disease (COVID)-19. Genetic polymorphisms of the glucocorticoid receptor, metabolizing enzymes, or transporters may affect treatment response to dexamethasone. This study aimed to evaluate the association of the glucocorticoid pathway polymorphisms with the treatment response and short-term outcomes in patients with severe COVID-19. Methods: Our pilot study included 107 hospitalized patients with COVID-19 treated with dexamethasone and/or methylprednisolone, genotyped for 14 polymorphisms in the glucocorticoid pathway. Results: In total, 83% of patients had severe disease, 15.1% had critical disease and only 1.9% had moderate disease. CYP3A4 rs35599367 was the major genetic determinant of COVID-19 severity as carriers of this polymorphism had higher risk of critical disease (OR = 6.538; 95% confidence interval = 1.19-35.914: p = 0.031) and needed intensive care unit treatment more frequently (OR = 10; 95% CI = 1.754-57.021: p = 0.01). This polymorphism was also associated with worse disease outcomes, as those patients had to switch from dexamethasone to methylprednisolone more often (OR = 6.609; 95% CI = 1.137-38.424: p = 0.036), had longer hospitalization (p = 0.022) and needed longer oxygen supplementation (p = 0.040). Carriers of NR3C1 rs6198 polymorphic allele required shorter dexamethasone treatment (p = 0.043), but had higher odds for switching therapy with methylprednisolone (OR = 2.711; 95% CI = 1.018-7.22: p = 0.046). Furthermore, rs6198 was also associated with longer duration of hospitalization (p = 0.001) and longer oxygen supplementation (p = 0.001). NR3C1 rs33388 polymorphic allele was associated with shorter hospitalization (p = 0.025) and lower odds for ICU treatment (OR = 0.144; 95% CI = 0.027-0.769: p = 0.023). GSTP1 rs1695 was associated with duration of hospitalization (p = 0.015), oxygen supplementation and (p = 0.047) dexamethasone treatment (p = 0.022). Conclusion: Our pathway-based approach enabled us to identify novel candidate polymorphisms that can be used as predictive biomarkers associated with response to glucocorticoid treatment in COVID-19. This could contribute to the patient's stratification and personalized treatment approach.

Pulmonary and renal long COVID at two-year revisit

This study investigated host responses to long COVID by following up with 89 of the original 144 cohorts for 1-year (N = 73) and 2-year visits (N = 57). Pulmonary long COVID, characterized by fibrous stripes, was observed in 8.7% and 17.8% of patients at the 1-year and 2-year revisits, respectively, while renal long COVID was present in 15.2% and 23.9% of patients, respectively. Pulmonary and renal long COVID at 1-year revisit was predicted using a machine learning model based on clinical and multi-omics data collected during the first month of the disease with an accuracy of 87.5%. Proteomics revealed that lung fibrous stripes were associated with consistent down-regulation of surfactant-associated protein B in the sera, while renal long COVID could be linked to the inhibition of urinary protein expression. This study provides a longitudinal view of the clinical and molecular landscape of COVID-19 and presents a predictive model for pulmonary and renal long COVID.

Novel Advancements in COVID-19 and Neuroscience

From an initial cluster of cases reported in Wuhan, the SARS-Cov-2 infection has since spread globally, causing a pandemic that began on 11 March 2020 [...].

The exploration of glucocorticoid pathway based on disease severity in COVID-19 patients

Systemic inflammation is a hallmark of Coronavirus Disease 2019 (COVID-19) and is the key to the pathophysiology of its severe cases with host cytokine involvement. Glucocorticoids can moderate this inflammatory effect due to receptor binding (NRC31-the gene encoded), influencing the expression of effector genes and pro-inflammatory cytokines. Another important pathway in the processes of the immune and inflammatory responses is nuclear factor-κB (NF-κB) signaling (NFKBIA-the gene encoded). We aimed to explore the expression of genes in the glucocorticoid pathway in mild and severe COVID-19. We performed a cross-sectional, observational study on COVID-19 cases, assessing the expression of RNA in white blood cells. The Illumina® platform was used for RNA sequencing, and FASTQ data were quality-checked with Multiqc. The raw data were analyzed using CLC Genomics Workbench®. Our study included 23 patients with severe COVID-19 and 21 patients with mild COVID-19 with an average age of 49.9 ± 18.2 years old. The NR3C1 and NFKBIA expressions did not show a significantly significant difference between groups (log2 fold change 0.5, p = 0.1; 0.82, p = 0.09). However, the expressions of TSC22D3, DUSP-1, JAK-1 and MAPK-1 were significantly higher in mild cases (log2 fold change 1.3, p < 0.001; 2.6, p < 0.001; 0.9, p < 0.001; 1.48, p-value<0.001; respectively). Furthermore, the TNF, IL-1β, and IL-6 expressions were significantly lower in mild cases (log2 fold change 4.05, p < 0.001; 3.33, p < 0.001; 6.86, p < 0.001; respectively). In conclusion, our results showed that although the NRC31 and NFKBIA expressions did not show a statistically significant difference between groups, the expression of TSC22D3 was higher in mild cases. These results highlight the importance of effector genes, specifically TSC22D3, in combatting systemic inflammation. Our recent findings have the potential to lead to the identification of novel pharmacological targets that could prove to be vital in the fight against diseases associated with inflammation.