A comprehensive review on technological advances in alternate drug discovery process:Drug repurposing

The traditional de novo drug discovery is time consuming, costly and in some instances the drugs will fail to treat the disease which result in a huge loss to the organization. Drug repurposing is an alternative drug discovery process to overcome the limitations of the De novo drug discovery process. Ithelps for the identification of drugs to the rare diseases as well as in the pandemic situationwithin short span of time in a cost-effective way. The underlying principle of drug repurposing is that most of the drugs identified on a primary purpose have shown to treat other diseases also. One such example is Tocilizumab is primarily used for rheumatoid arthritis and it is repurposed to treat cancer and COVID-19. At present, nearly30% of the FDA approved drugs to treat various diseases are repurposed drugs. The drug repurposing is either drug-centric or disease centric and can be studied by using both experimental and in silico studies. The in silico repurpose drug discovery process is more efficient as it screens thousands of compounds from the diverse libraries within few days by various computational methods like Virtual screening, Docking, MD simulations,Machine Learning, Artificial Intelligence, Genome Wide Association Studies (GWAS), etc. with certain limitations.These limitationscan be addressed by effective integration of advanced technologies to identify a novel multi-purpose drug.Copyright © 2023, Association of Biotechnology and Pharmacy. All rights reserved.

Genetic Determinants of the Acute Respiratory Distress Syndrome.

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition that arises from multiple causes, including sepsis, pneumonia, trauma, and severe coronavirus disease 2019 (COVID-19). Given the heterogeneity of causes and the lack of specific therapeutic options, it is crucial to understand the genetic and molecular mechanisms that underlie this condition. The identification of genetic risks and pharmacogenetic loci, which are involved in determining drug responses, could help enhance early patient diagnosis, assist in risk stratification of patients, and reveal novel targets for pharmacological interventions, including possibilities for drug repositioning. Here, we highlight the basis and importance of the most common genetic approaches to understanding the pathogenesis of ARDS and its critical triggers. We summarize the findings of screening common genetic variation via genome-wide association studies and analyses based on other approaches, such as polygenic risk scores, multi-trait analyses, or Mendelian randomization studies. We also provide an overview of results from rare genetic variation studies using Next-Generation Sequencing techniques and their links with inborn errors of immunity. Lastly, we discuss the genetic overlap between severe COVID-19 and ARDS by other causes.

Host genetic determinants of COVID-19 susceptibility and severity: A systematic review and meta-analysis.

Genome-wide association studies (GWASs) have identified single nucleotide polymorphisms (SNPs) associated with susceptibility and severity of coronavirus disease 2019 (COVID-19). However, identified SNPs are inconsistent across studies, and there is no compelling consensus that COVID-19 status is determined by genetic factors. Here, we conducted a systematic review and meta-analysis to determine the effect of genetic factors on COVID-19. A random-effect meta-analysis was performed to estimate pooled odds ratios (ORs) of SNP effects, and SNP-based heritability (SNP-h2 ) of COVID-19. The analyses were performed using meta-R package, and Stata version 17. The meta-analysis included a total of 96,817 COVID-19 cases and 6,414,916 negative controls. The meta-analysis showed that a cluster of highly correlated 9 SNPs (R2  > 0.9) at 3p21.31 gene locus covering LZTFL1 and SLC6A20 genes was significantly associated with COVID-19 severity, with a pooled OR of 1.8 [1.5-2.0]. Meanwhile, another 3 SNPs (rs2531743-G, rs2271616-T, and rs73062389-A) within the locus was associated with COVID-19 susceptibility, with pooled estimates of 0.95 [0.93-0.96], 1.23 [1.19-1.27] and 1.15 [1.13-1.17], respectively. Interestingly, SNPs associated with susceptibility and SNPs associated with severity in this locus are in linkage equilibrium (R2  < 0.026). The SNP-h2 on the liability scale for severity and susceptibility was estimated at 7.6% (Se = 3.2%) and 4.6% (Se = 1.5%), respectively. Genetic factors contribute to COVID-19 susceptibility and severity. In the 3p21.31 locus, SNPs that are associated with susceptibility are not in linkage disequilibrium (LD) with SNPs that are associated with severity, indicating within-locus heterogeneity.

Genome-wide screening of sex-biased genetic variants potentially associated with COVID-19 hospitalization.

Sex-biased difference in coronavirus disease 2019 (COVID-19) hospitalization has been observed as that male patients tend to be more likely to be hospitalized than female patients. However, due to the insufficient sample size and existed studies that more prioritized to sex-stratified COVID-19 genome-wide association study (GWAS), the searching for sex-biased genetic variants showing differential association signals between sexes with COVID-19 hospitalization was severely hindered. We hypothesized genetic variants would show potentially sex-biased genetic effects on COVID-19 hospitalization if they display significant differential association effect sizes between male and female COVID-19 patients. By integrating two COVID-19 GWASs, including hospitalized COVID-19 patients vs. general population separated into males (case = 1,917 and control = 221,174) and females (case = 1,343 and control = 262,886), we differentiated the association effect sizes of each common single nucleotide polymorphism (SNP) within the two GWASs. Twelve SNPs were suggested to show differential COVID-19 associations between sexes. Further investigation of genes (n = 58) close to these 12 SNPs resulted in the identification of 34 genes demonstrating sex-biased differential expression in at least one GTEx tissue. Finally, 5 SNPs are mapped to 8 genes, including rs1134004 (GADD45G), rs140657166 (TRIM29 and PVRL1), rs148143613 (KNDC1 and STK32C), rs2443615 (PGAP2 and TRIM21), and rs2924725 (CSMD1). The 8 genes display significantly differential gene expression in blood samples derived from COVID-19 patients compared to healthy controls. These genes are potential genetic factors contributing to sex differences in COVID-19 hospitalization and warranted for further functional studies.

Pilot genome-wide association study of antibody response to inactivated SARS-CoV-2 vaccines.

Vaccines are a key weapon against the COVID-19 pandemic caused by SARS-CoV-2. However, there are inter-individual differences in immune response to SARS-CoV-2 vaccines and genetic contributions to these differences have barely been investigated. Here, we performed genome-wide association study (GWAS) of antibody levels in 168 inactivated SARS-CoV-2 vaccine recipients. A total of 177 SNPs, corresponding to 41 independent loci, were identified to be associated with IgG, total antibodies or neutral antibodies. Specifically, the rs4543780, the intronic variant of FAM89A gene, was associated with total antibodies level and was annotated as a potential regulatory variant affecting gene expression of FAM89A, a biomarker differentiating bacterial from viral infections in febrile children. These findings might advance our knowledge of the molecular mechanisms driving immunity to SARS-CoV-2 vaccine.

Host Genetic Factors, Comorbidities and the Risk of Severe COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk. METHODS: A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models' performance. RESULTS: We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36-1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient's progression (AUROC = 82.1%, 95% CI 80.6-83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk. CONCLUSION: In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.

Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity.

BACKGROUND: Epidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity. METHODS: Summary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship. RESULTS: Our results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86-1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54-1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96-1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity. CONCLUSIONS: This indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.

Transcriptome Profiling in Autoimmune Diseases

Autoimmune diseases are a group of different inflammatory disorders characterized by systemic or localized inflammation, affecting approximately 0.1–1% of the general population. Several studies suggest that genetic risk loci are shared between different autoimmune diseases and pathogenic mechanisms may also be shared. The strategy of performing differential gene expression profiles in autoimmune disorders has unveiled new transcripts that may be shared among these disorders. Microarray technology and bioinformatics offer the most comprehensive molecular evaluations and it is widely used to understand the changes in gene expression in specific organs or in peripheral blood cells. The major goal of transcriptome studies is the identification of specific biomarkers for different diseases. It is believed that such knowledge will contribute to the development of new drugs, new strategies for early diagnosis, avoiding tissue autoimmune destruction, or even preventing the development of autoimmune disease. In this review, we primarily focused on the transcription profiles of three typical autoimmune disorders, including type 1 diabetes mellitus (destruction of pancreatic islet beta cells), systemic lupus erythematosus (immune complex systemic disorder affecting several organs and tissues), and multiple sclerosis (inflammatory and demyelinating disease of the nervous system). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.

Causal effects of COVID-19 on cancer risk: A Mendelian randomization study.

In contemporary literature, little attention has been paid to the association between coronavirus disease-2019 (COVID-19) and cancer risk. We performed the Mendelian randomization (MR) to investigate the causal associations between the three types of COVID-19 exposures (critically ill COVID-19, hospitalized COVID-19, and respiratory syndrome coronavirus 2 (SARS-CoV-2) infection) and 33 different types of cancers of the European population. The results of the inverse-variance-weighted model indicated that genetic liabilities to critically ill COVID-19 had suggestive causal associations with the increased risk for HER2-positive breast cancer (odds ratio [OR] = 1.0924; p-value = 0.0116), esophageal cancer (OR = 1.0004; p-value = 0.0226), colorectal cancer (OR = 1.0010; p-value = 0.0242), stomach cancer (OR = 1.2394; p-value = 0.0331), and colon cancer (OR = 1.0006; p-value = 0.0453). The genetic liabilities to hospitalized COVID-19 had suggestive causal associations with the increased risk for HER2-positive breast cancer (OR = 1.1096; p-value = 0.0458), esophageal cancer (OR = 1.0005; p-value = 0.0440) as well as stomach cancer (OR = 1.3043; p-value = 0.0476). The genetic liabilities to SARS-CoV-2 infection had suggestive causal associations with the increased risk for stomach cancer (OR = 2.8563; p-value = 0.0019) but with the decreasing risk for head and neck cancer (OR = 0.9986, p-value = 0.0426). The causal associations of the above combinations were robust through the test of heterogeneity and pleiotropy. Together, our study indicated that COVID-19 had causal effects on cancer risk.

Meta-analysis of age-related cognitive decline reveals a novel locus for the attention domain and implicates a COVID-19-related gene for global cognitive function.

INTRODUCTION: Cognitive abilities have substantial heritability throughout life, as shown by twin- and population-based studies. However, there is limited understanding of the genetic factors related to cognitive decline in aging across neurocognitive domains. METHODS: We conducted a meta-analysis on 3045 individuals aged ≥65, derived from three population-based cohorts, to identify genetic variants associated with the decline of five neurocognitive domains (attention, memory, executive function, language, visuospatial function) and global cognitive decline. We also conducted gene-based and functional bioinformatics analyses. RESULTS: Apolipoprotein E (APOE)4 was significantly associated with decline of memory (p = 5.58E-09) and global cognitive function (p = 1.84E-08). We identified a novel association with attention decline on chromosome 9, rs6559700 (p = 2.69E-08), near RASEF. Gene-based analysis also identified a novel gene, TMPRSS11D, involved in the activation of SARS-CoV-2, to be associated with the decline in global cognitive function (p = 4.28E-07). DISCUSSION: Domain-specific genetic studies can aid in the identification of novel genes and pathways associated with decline across neurocognitive domains. HIGHLIGHTS: rs6559700 was associated with decline of attention. APOE4 was associated with decline of memory and global cognitive decline. TMPRSS11D, a gene involved in the activation of SARS-CoV-2, was implicated in global cognitive decline. Cognitive domain abilities had both unique and shared molecular pathways across the domains.

Associations between brain gene expression perturbations implicated by COVID-19 and psychiatric disorders.

BACKGROUND: Currently, there is increasing evidence from clinic, epidemiology, as well as neuroimaging, demonstrating neuropsychiatric abnormalities in COVID-19, however, whether there were associations between brain changes caused by COVID-19 and genetic susceptibility of psychiatric disorders was still unknown. METHODS: In this study, we performed a meta-analysis to investigate these associations by combing single-cell RNA sequencing datasets of brain tissues of COVID-19 and genome-wide association study summary statistics of psychiatric disorders. RESULTS: The analysis demonstrated that among ten psychiatric disorders, gene expression perturbations implicated by COVID-19 in excitatory neurons of choroid plexus were significantly associated with schizophrenia. CONCLUSIONS: Our analysis might provide insights for the underlying mechanism of the psychiatric consequence of COVID-19.

An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2.

Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.

The Genetics of Primary Biliary Cholangitis: A GWAS and Post-GWAS Update.

Primary biliary cholangitis (PBC) is a chronic, progressive cholestatic liver disease in which the small intrahepatic bile ducts are destroyed by autoimmune reactions. Among autoimmune diseases, which are polygenic complex traits caused by the combined contribution of genetic and environmental factors, PBC exhibits the strongest involvement of genetic heritability in disease development. As at December 2022, genome-wide association studies (GWASs) and associated meta-analyses identified approximately 70 PBC susceptibility gene loci in various populations, including those of European and East Asian descent. However, the molecular mechanisms through which these susceptibility loci affect the pathogenesis of PBC are not fully understood. This study provides an overview of current data regarding the genetic factors of PBC as well as post-GWAS approaches to identifying primary functional variants and effector genes in disease-susceptibility loci. Possible mechanisms of these genetic factors in the development of PBC are also discussed, focusing on four major disease pathways identified by in silico gene set analyses, namely, (1) antigen presentation by human leukocyte antigens, (2) interleukin-12-related pathways, (3) cellular responses to tumor necrosis factor, and (4) B cell activation, maturation, and differentiation pathways.

Computational network analysis of host genetic risk variants of severe COVID-19.

BACKGROUND: Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks. RESULTS: We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein-protein interaction networks. We identified 24 protein-protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction. CONCLUSIONS: This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.

Genome-wide association studies of COVID-19: Connecting the dots.

Genome-wide association studies (GWASs) are a research approach used to identify genetic variants associated with common diseases, like COVID-19. The lead genetic variants (n = 41) reported by the eleven largest COVID-19 GWASs are mapped to 22 different chromosomal regions. The loci 3q21.31 (LZTFL1 and chemokine receptor genes) and 9q34.2 (ABO), associated with disease severity and susceptibility to infection, respectively, were the most replicated findings across studies. Genes involved with mucociliary clearance (CEP97, FOXP4), viral-entry (ACE2, SLC6A20) and mucosal immunity (MIR6891) are associated with the risk of SARS-CoV-2 infection while genes of antiviral immune response (IFNAR2, OAS1), leukocyte trafficking (CCR9, CXCR6) and lung injury (DPP9, NOTCH4) are associated with severe disease. The biological processes underlying the risk of infection occur prominently, but not exclusively, in the upper airways whereas the severe COVID-19-associated processes in alveolar-capillary interface. The COVID-19 GWASs has unraveled key genetic mechanisms of SARS-CoV-2 pathogenesis, although the genetic basis of other COVID-19 related phenotypes (long COVID and neurological impairment) remains to be elucidated.

Disentangling the common genetic architecture and causality of rheumatoid arthritis and systemic lupus erythematosus with COVID-19 outcomes: Genome-wide cross trait analysis and bidirectional Mendelian randomization study.

Coronavirus Disease (COVID-19) may cause a dysregulation of the immune system and has complex relationships with multiple autoimmune diseases, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, little is known about their common genetic architecture. Using the latest data from COVID-19 host genetics consortium and consortia on RA and SLE, we conducted a genome-wide cross-trait analysis to examine the shared genetic etiology between COVID-19 and RA/SLE and evaluated their causal associations using bidirectional Mendelian randomization (MR). The cross-trait meta-analysis identified 23, 28, and 10 shared genetic loci for severe COVID-19, COVID-19 hospitalization, and SARS-CoV-2 infection with RA, and 14, 17, and 7 shared loci with SLE, respectively. Co-localization analysis identified five causal variants in TYK2, IKZF3, PSORS1C1, and COG6 for COVID-19 with RA, and four in CRHR1, FUT2, and NXPE3 for COVID-19 with SLE, involved in immune function, angiogenesis and coagulation. Bidirectional MR analysis suggested RA is associated with a higher risk of COVID-19 hospitalization, and COVID-19 is not related to RA or SLE. Our novel findings improved the understanding of the genetic etiology shared by COVID-19, RA and SLE, and suggested an increased risk of COVID-19 hospitalization in people with higher genetic liability to RA.

Genetic screening for hypertension and COVID-19 reveals functional variation of SPEG potentially associated with severe COVID-19 in women.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to more than 6.4 million deaths worldwide. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-biased prevalence, common genetic factors between the two diseases may display sex-biased differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms (SNPs) derived from more than 1 million European individuals in two sex-stratified severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) showing sex-biased association with severe COVID-19 in women. The risk allele rs12474050*T associates with higher blood pressure. In our study, we found it is significantly correlated with lower SPEG expression in muscle-skeletal but with higher expression in both brain cerebellum and cerebellar hemisphere. Additionally, nominal significances were detected for the association between rs12474050*T and lower SPEG expression in both heart left ventricle and atrial appendage; among these tissues, the SPEG expression is nominally significantly higher in females than in males. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher upregulation of SPEG only observed in female but not in male COVID-19 patients compared to both normal female and male individuals, suggesting upregulation of SPEG is a female-specific protective mechanism against COVID-19 induced heart damage. Taken together, our analyses suggest the involvement of SPEG in both hypertension and severe COVID-19 in women, which provides new insights for sex-biased effect of severe COVID-19 in women.

Genome-Wide Pleiotropy Study Identifies Association of PDGFB with Age-Related Macular Degeneration and COVID-19 Infection Outcomes.

Age-related macular degeneration (AMD) has been implicated as a risk factor for severe consequences from COVID-19. We evaluated the genetic architecture shared between AMD and COVID-19 (critical illness, hospitalization, and infections) using analyses of genetic correlations and pleiotropy (i.e., cross-phenotype meta-analysis) of AMD (n = 33,976) and COVID-19 (n ≥ 1,388,342) and subsequent analyses including expression quantitative trait locus (eQTL), differential gene expression, and Mendelian randomization (MR). We observed a significant genetic correlation between AMD and COVID-19 infection (rG = 0.10, p = 0.02) and identified novel genome-wide significant associations near PDGFB (best SNP: rs130651; p = 2.4 × 10-8) in the pleiotropy analysis of the two diseases. The disease-risk allele of rs130651 was significantly associated with increased gene expression levels of PDGFB in multiple tissues (best eQTL p = 1.8 × 10-11 in whole blood) and immune cells (best eQTL p = 7.1 × 10-20 in T-cells). PDGFB expression was observed to be higher in AMD cases than AMD controls {fold change (FC) = 1.02; p = 0.067}, as well as in the peak COVID-19 symptom stage (11-20 days after the symptom onset) compared to early/progressive stage (0-10 days) among COVID-19 patients over age 40 (FC = 2.17; p = 0.03) and age 50 (FC = 2.15; p = 0.04). Our MR analysis found that the liability of AMD risk derived from complement system dysfunction {OR (95% CI); hospitalization = 1.02 (1.01-1.03), infection = 1.02 (1.01-1.03) and increased levels of serum cytokine PDGF-BB {ß (95% CI); critical illness = 0.07 (0.02-0.11)} are significantly associated with COVID-19 outcomes. Our study demonstrated that the liability of AMD is associated with an increased risk of COVID-19, and PDGFB may be responsible for the severe COVID-19 outcomes among AMD patients.

Report on the 11th international workshop on the CCN family of genes, Nice, October 20-24, 2022.

In celebration of the twentieth anniversary of the inception of the CCN society, and of the first post-Covid-19 live meeting, the executive board of the ICCNS had chosen Nice as the venue for the 11th International workshop on the CCN family of genes. On this occasion participation in the meeting was extended to colleagues from other cell signaling fields who were invited to present both an overview of their work and the future directions of their laboratory. Also, for the first time, the members of the JCCS Editorial Board were invited to participate in a JCCS special session during which all aspects of the journal « life ¼ were addressed and opened to free critical discussion. The scientific presentations and the discussions that followed showed once more that an expansion of the session topics was beneficial to the quality of the meeting and confirmed that the ARBIOCOM project discussed last April in Nice was now on track to be launched in 2023. The participants unanimously welcomed Professor Attramadal's proposition to organize the 2024, 12th International CCN workshop in Oslo, Norway.

Genetic predisposition to blood cell indices in relation to severe COVID-19.

Despite considerable variation in disease manifestations observed among coronavirus disease 2019 (COVID-19) patients infected with severe acute respiratory syndrome coronavirus 2, the risk factors predicting disease severity remain elusive. Recent studies suggest that peripheral blood cells play a pivotal role in COVID-19 pathogenesis. Here, we applied two-sample Mendelian randomization (MR) analyses to evaluate the potential causal contributions of blood cell indices variation to COVID-19 severity, using single-nucleotide polymorphisms (SNPs) as instrumental variables for 17 indices from the UK Biobank and INTERVAL genome-wide association studies (N = 173 480). Data on the associations between the SNPs and very severe respiratory confirmed COVID-19 were obtained from the COVID-19 host genetics initiative (N = 8779/1 001 875). We observed significant negative association between hematocrit (HCT; odds ratio, OR = 0.775, 95% confidence interval, CI = 0.635-0.915, p = 3.48E-04) or red blood cell count (OR = 0.830, 95% CI = 0.728-0.932, p = 2.19E-03) and very severe respiratory confirmed COVID-19, as well as nominal negative association of hemoglobin concentration (OR = 0.808, 95% CI = 0.673-0.943, p = 3.95E-03) with very severe respiratory confirmed COVID-19 (no effect survived multiple correction). In conclusion, the MR study supports a protective effect of high HCT and red blood cell count from very severe respiratory confirmed COVID-19, suggesting potential strategies to ameliorate/treat clinical conditions in very severe respiratory confirmed COVID-19.