Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

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Background: One of the many debated topics in inflammation research is whether this scenario is really an accelerated form of human wound healing and immunityboosting or a push towards autoimmune diseases. The answer requires a better understanding of the normal inflammatory process, including the molecular pathology underlying the possible outcomes. Exciting recent investigations regarding severe human inflammatory disorders and autoimmune conditions have implicated molecular changes that are also linked to normal immunity, such as triggering factors, switching on and off, the influence of other diseases and faulty stem cell homeostasis, in disease progression and development. Methods: We gathered around and collected recent online researches on immunity, inflammation, inflammatory disorders and AMPK. We basically searched PubMed, Scopus and Google Scholar to assemble the studies which were published since 2010. Results: Our findings suggested that inflammation and related disorders are on the verge and interfere in the treatment of other diseases. AMPK serves as a key component that prevents various kinds of inflammatory signaling. In addition, our table and hypothetical figures may open a new door in inflammation research, which could be a greater therapeutic target for controlling diabetes, obesity, insulin resistance and preventing autoimmune diseases. Conclusion: The relationship between immunity and inflammation becomes easily apparent. Yet, the essence of inflammation turns out to be so startling that the theory may not be instantly established and many possible arguments are raised for its clearance. However, this study might be able to reveal some possible approaches where AMPK can reduce or prevent inflammatory disorders.

Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.

Background: Identification of prognostic biomarkers in cancers is a crucial step to improve overall survival (OS). Although mutations in tumour protein 53 (TP53) is prevalent in astrocytoma, the prognostic effects of TP53 mutation are unclear. Methods: In this retrospective study, we sequenced TP53 exons 1 to 10 in a cohort of 102 lower-grade glioma (LGG) subtypes and determined the prognostic effects of TP53 mutation in astrocytoma and oligodendroglioma. Publicly available datasets were analysed to confirm the findings. Results: In astrocytoma, mutations in TP53 codon 273 were associated with a significantly increased OS compared to the TP53 wild-type (HR (95% CI): 0.169 (0.036–0.766), p = 0.021). Public datasets confirmed these findings. TP53 codon 273 mutant astrocytomas were significantly more chemosensitive than TP53 wild-type astrocytomas (HR (95% CI): 0.344 (0.13–0.88), p = 0.0148). Post-chemotherapy, a significant correlation between TP53 and YAP1 mRNA was found (p = 0.01). In O (6)-methylguanine methyltransferase (MGMT) unmethylated chemotherapy-treated astrocytoma, both TP53 codon 273 and YAP1 mRNA were significant prognostic markers. In oligodendroglioma, TP53 mutations were associated with significantly decreased OS. Conclusions: Based on these findings, we propose that certain TP53 mutant astrocytomas are chemosensitive through the involvement of YAP1, and we outline a potential mechanism. Thus, TP53 mutations may be key drivers of astrocytoma therapeutic efficacy and influence survival outcomes.