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The Angiotensin-Converting Enzyme-2 (ACE2) gene, located on Xp22.2, attracts a great deal of attention because the protein it encodes is believed to be the functional cellular receptor for the new coronavirus (SARS-CoV-2). However, recent studies are controversial, especially concerning the intrinsic link between ACE2 diversity and COVID-19 susceptibility. Here, we conduct a population genetic study on ACE2 in 6354 individuals representing 210 present-day populations and 5329 individuals of ancient or archaic groups. We dissected the genetic architecture of ACE2 and identified two major haplogroups (hg) in East Asians, i.e. ACE2-hg1 (43%) and ACE2-hg2 (53%), while other populations harbor more diverse ACE2-hgs. Accordingly, there was a significant loss of ACE2 common variations in East Asians in contrast to the X-chromosome-wide and genome-wide patterns. Notably, association analysis between ACE2-hgs and COVID-19 severity in 1229 Han Chinese individuals with various levels of COVID-19 severity showed a higher risk of ACE2-hg1 (odds ratio = 1.56, P

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal carcinoma. It is particularly important to accurately judge the prognosis of patients. Since most tumor prediction models depend on the specific expression level of related genes, a better model therefore needs to be constructed. To provide an immune-related lncRNA (irlncRNAs) tumor prognosis model that is independent of the specific gene expression levels, we first downloaded and sorted out the data on ccRCC in the TCGA database and screened irlncRNAs using co-expression analysis and then obtained the differently expressed irlncRNA (DEirlncRNA) pairs by means of univariate analysis. In addition, we modified LASSO penalized regression. Subsequently, the ROC curve was drawn, and we compared the area under the curve, calculated the Akaike information standard value of the 5-year receiver operating characteristic curve, and determined the cut-off point to establish the best model to distinguish the high- or low-disease-risk group of ccRCC. Subsequently, we reassessed the model from the perspectives of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutics efficacy, and immunosuppressed biomarkers. A total of 17 DEirlncRNAs pairs (AL031710.1|AC104984.5, AC020907.4|AC127-24.4,AC091185.1|AC005104.1, AL513218.1|AC079015.1, AC104564.3|HOXB-AS3, AC003070.1|LINC01355, SEMA6A-AS1|CR936218.1, AL513327.1|AS005785.1, AC084876.1|AC009704.2, IGFL2-AS1|PRDM16-DT, AC011462.4|MMP25-AS1, AL662844.3I|TGB2-AS1, ARHGAP27P1|AC116914.2, AC093788.1|AC007098.1, MCF2L-AS1|AC093001.1, SMIM25|AC008870.2, and AC027796.4|LINC00893) were identified, all of which were included in the Cox regression model. Using the cut-off point, we can better distinguish patients according to different factors, such as survival status, invasive clinic-pathological features, tumor immune infiltration, whether they are sensitive to chemotherapy or not, and expression of immunosuppressive biomarkers. We constructed the irlncRNA model by means of pairing, which can better eliminate the dependence on the expression level of the target genes. In other words, the signature established by pairing irlncRNA regardless of expression levels showed promising clinical prediction value.

RhoGDIα is an inhibitor of RhoGDP dissociation that involves in Aβ metabolism and NFTs production in Alzheimer's disease (AD) by regulating of RhoGTP enzyme activity. Our previous research revealed that RhoGDIα, as the target of Polygala saponin (Sen), might alleviate apoptosis of the nerve cells caused by hypoxia/reoxygenation (H/R). To further clarify the role of RhoGDIα in the generation of NFTs, we explored the relationship between RhoGDIα and Tau. We found out that RhoGDIα and Tau can bind with each other and interact by using coimmunoprecipitation (Co-IP) and GST pulldown methods in vitro. This RhoGDIα-Tau partnership was further verified by using immunofluorescence colocalization and fluorescence resonance energy transfer (FRET) approaches in PC12 cells. Using the RNA interference (RNAi) technique, we found that the RhoGDIα may be involved in an upstream signaling pathway for Tau. Subsequently, in Aβ

Myocardial dysfunction accompanied by severe sepsis could significantly increase the mortality rate of septic patients. This study investigated the effects and the potential mechanisms of sevoflurane preconditioning on septic myocardial dysfunction, which was induced by lipopolysaccharide (LPS; from Escherichia coli O55:B5; 18 mg/kg) in mice. Results indicated that 1 hour after the administration, LPS induced a significant increase in cell-surface Toll-like receptor 4 (TLR4), cytoplasmic IKKα protein expression, and nuclear translocation of nuclear factor kappa-B (NF-κB) protein (P0.05), which was attenuated by preconditioning with sevoflurane. Two hours after the administration, inhalation of sevoflurane significantly reduced the serum levels of tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1β, and IL-10 (P0.05). Twelve hours after administration, LPS caused pathological damage to the heart and elevated the serum levels of lactate dehydrogenase (LDH) and creatine kinase-MB (P0.05). Echocardiography indicated that sevoflurane preconditioning significantly improved systolic and diastolic function. The inhalation of sevoflurane inhibited increases in myeloperoxidase (MPO), macrophage inflammatory protein-2 (MIP-2), TNF-α, and IL-1β levels (P0.05) induced by endotoxemia, whereas IL-6 release was facilitated. Sevoflurane attenuated the myocardial levels of nitric oxide (P0.05) without an apparent influence on malondialdehyde (MDA) or superoxide dismutase (P0.05). In conclusion, our study indicates that exposure to 2% sevoflurane before LPS challenge is protective against myocardial dysfunction. Sevoflurane preconditioning may attenuate neutrophil infiltration and the release of inflammatory mediators during endotoxemia.

As of early May 2021, the ongoing pandemic COVID-19 has caused over 160 million of infections and over 3 million deaths worldwide. Many risk factors, such as age, gender, and comorbidities, have been studied to explain the variable symptoms of infected patients. However, these effects may not fully account for the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients’ laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory features. Based on these findings, we performed Mendelian randomization (MR) analysis to investigate the causality of laboratory traits on disease severity. From the MR study, we identified two causal traits, cholesterol levels and WBC counts. The functional gene related to cholesterol levels is ApoE and people with particular ApoE genotype are more likely to have higher cholesterol levels, facilitating the process that SARS-CoV-2 binds on its receptor ACE2 and aggravating COVID-19 disease. The functional gene related to WBC counts is MHC system that plays a central role in the immune system. The host immune response to the SARS-CoV-2 infection greatly affects the patients’ severity status and clinical outcome. Additionally, our gene-based and GSEA analysis revealed interferon pathways, including type I interferon receptor binding, regulation of IFNA signaling, and SARS coronavirus and innate immunity. We hope that our work will make a contribution in studying the genetic mechanisms of disease illness and serve as useful reference for the clinical diagnosis and treatment of COVID-19.

The COVID-19 pandemic has accounted for millions of infections and hundreds of thousand deaths worldwide in a short-time period. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed interindividual phenotypic variability. Here, we report the first host genetic study in the Chinese population by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third People’s Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe, and critical ill patients after the correction of potential confounding factors. Pedigree analysis suggested a potential monogenic effect of loss of function variants in GOLGA3 and DPP7 for critically ill and asymptomatic disease demonstration. Genome-wide association study suggests the most significant gene locus associated with severity were located in TMEM189–UBE2V1 that involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We identified that the HLA-A*11:01, B*51:01, and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial genomic study of Chinese patients provides genetic insights into the phenotypic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host–pathogen interaction for COVID-19 and other infectious and complex diseases.

SummarySystem-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.

The COVID-19 pandemic has accounted for more than five million infections and hundreds of thousand deaths worldwide in the past six months. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed inter-individual phenotypic variability. Here, we report the first host genetic study in China by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third People’s Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe and critical ill patients after the correction of potential confounding factors. The most significant gene locus associated with severity is located in TMEM189-UBE2V1 involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We also identified that the HLA-A*11:01, B*51:01 and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial study of Chinese patients provides a comprehensive view of the genetic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.

The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further investigate the causality of traits on disease severity. Two causal traits, WBC counts and cholesterol levels, were identified based on MR study, and their functional genes are located at genes MHC complex and ApoE, respectively. Our gene-based analysis and GSEA revealed four interferon pathways, including type I interferon receptor binding and SARS coronavirus and innate immunity. We hope that our work will contribute to studying the genetic mechanisms of disease and serve as a useful reference for COVID-19 diagnosis and treatment., Graphical abstract, Virology; Biological sciences; Genetics

The goal of this work was to investigate the molecular profiles and metastasis markers in Chinese patients with gastric carcinoma (GC). In total, we performed whole exome sequencing (WES) on 74 GC patients with tumor and adjacent normal formalin-fixed, paraffin-embedded (FFPE) tissue samples. The mutation spectrum of these samples showed a high concordance with TCGA and other studies on GC. PTPRT is significantly associated with metastasis of GC, suggesting its predictive role in metastasis of GC. Patients carrying BRCA2 mutations tend not to metastasize, which may be related to their sensitivity to chemotherapy. Mutations in MACF1, CDC27, HMCN1, CDH1 and PDZD2 were moderately enriched in peritoneal metastasis (PM) samples. Furthermore, we found two genomic regions (1p36.21 and Xq26.3) were associated with PM of GC, and patients with amplification of 1p36.21 and Xq26.3 have a worse prognosis (P = 0.002, 0.01, respectively). Our analysis provides GC patients with potential markers for single and combination therapies.

The goal of this work was to investigate the molecular profiles and mutation burden in Chinese patients with gastric carcinoma (GC). In total, we performed whole exome sequencing (WES) on 74 GC patients with tumor and adjacent normal formalin-fixed, paraffin-embedded (FFPE) tissue samples. The mutation spectrum of these samples showed a high concordance with TCGA and other studies on GC. We found the alterations of 17 DNA repair genes (including BRCA2, POLE and MSH3, etc.) were strongly correlated with the tumor mutation burden (TMB) and tumor neoantigen burden (TNB) of GC patients. Patients with mutations of these genes tend to have high TMB (median of TMB = 12.77, p=2.3e-6) and TNB (median of TNB = 5.97, p= 2.8e-3). In addition, younger GC patients (age < 60) have lower TMB (p = 0.0021) and TNB (p = 0.034) than older patients (age >= 60). Furthermore, we found a list of 18 genes and two genomic regions (1p36.21 and Xq26.3) were associated with peritoneal metastasis (PM) of GC, and patients with amplification of 1p36.21 and Xq26.3 have a worse prognosis (p=0.002, 0.01, respectively). Our analysis provides GC patients with potential markers for single and combination therapies.

Neuronal apoptosis is an important event in hypoxia/reoxygenation (H/R)-induced neuronal injury. Senegenin (Sen), the predominant and most active component in Radix Polygalae root extracts, displays anti-apoptotic and anti-oxidative properties. Sen protects against H/R-induced neuronal apoptosis of highly differentiated PC12 cells and primary cortical neurons. Sen has also been investigated as a source of potential therapeutic targets. In this study, a proteomic approach was used to identify Sen-regulated proteins in PC12 cells. We found that Sen protected against H/R-induced neuronal apoptosis by upregulating RhoGDIα protein expression. The regulatory functions of RhoGDIα were investigated by knocking down RhoGDIα expression in PC12 cells using small interfering RNA (siRNA), followed by quantification of apoptosis and then altering the expression levels of apoptosis-related proteins. Our data show that after silencing RhoGDIα, the neuroprotective effects of Sen on H/R-induced PC12 cell apoptosis were absent. Furthermore, RhoGDIα silencing alleviated the Sen-mediated inhibition of the JNK pathway. Therefore, these findings indicated that Sen attenuates H/R-induced neuronal apoptosis by upregulating RhoGDIα expression and inhibiting the JNK pathway. In addition to the mechanism underlying neuroprotective effects of Sen, RhoGDIα was identified as a putative target of Sen based on a primary rat cortical neuron model of H/R-induced injury.