Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

Identifying potential therapeutic targets in lung adenocarcinoma: a multi-omics approach integrating bulk and single-cell RNA sequencing with Mendelian randomization

Our research aimed to identify new therapeutic targets for Lung adenocarcinoma (LUAD), a major subtype of non-small cell lung cancer known for its low 5-year survival rate of 22%. By employing a comprehensive methodological approach, we analyzed bulk RNA sequencing data from 513 LUAD and 59 non-tumorous tissues, identifying 2,688 differentially expressed genes. Using Mendelian randomization (MR), we identified 74 genes with strong evidence for a causal effect on risk of LUAD. Survival analysis on these genes revealed significant differences in survival rates for 13 of them. Our pathway enrichment analysis highlighted their roles in immune response and cell communication, deepening our understanding. We also utilized single-cell RNA sequencing (scRNA-seq) to uncover cell type-specific gene expression patterns within LUAD, emphasizing the tumor microenvironment's heterogeneity. Pseudotime analysis further assisted in assessing the heterogeneity of tumor cell populations. Additionally, protein-protein interaction (PPI) network analysis was conducted to evaluate the potential druggability of these identified genes. The culmination of our efforts led to the identification of five genes (tier 1) with the most compelling evidence, including SECISBP2L, PRCD, SMAD9, C2orf91, and HSD17B13, and eight genes (tier 2) with convincing evidence for their potential as therapeutic targets.

Ursodeoxycholic acid and COVID-19 outcomes: a cohort study and data synthesis of state-of-art evidence

BACKGROUND

The potential of ursodeoxycholic acid (UDCA) in inhibiting angiotensin-converting enzyme 2 was demonstrated. However, conflicting evidence emerged regarding the association between UDCA and COVID-19 outcomes, prompting the need for a comprehensive investigation.

RESEARCH DESIGN AND METHODS

Patients diagnosed with COVID-19 infection were retrospectively analyzed and divided into two groups: the UDCA-treated group and the control group. Kaplan-Meier recovery analysis and Cox proportional hazards models were used to evaluate the recovery time and hazard ratios. Additionally, study-level pooled analyses for multiple clinical outcomes were performed.

RESULTS

In the 115-patient cohort, UDCA treatment was significantly associated with a reduced recovery time. The subgroup analysis suggests that the 300 mg subgroup had a significant (adjusted hazard ratio: 1.63 [95% CI, 1.01 to 2.60]) benefit with a shorter duration of fever. The results of pooled analyses also show that UDCA treatment can significantly reduce the incidence of severe/critical diseases in COVID-19 (adjusted odds ratio: 0.68 [95% CI, 0.50 to 0.94]).

CONCLUSIONS

UDCA treatment notably improves the recovery time following an Omicron strain infection without observed safety concerns. These promising results advocate for UDCA as a viable treatment for COVID-19, paving the way for further large-scale and prospective research to explore the full potential of UDCA.

Pathway-Based Mendelian Randomization for Pre-Infection IL-6 Levels Highlights Its Role in Coronavirus Disease

OBJECTIVES

Interleukin 6 (IL-6) levels at hospital admission have been suggested for disease prognosis, and IL-6 antagonists have been suggested for the treatment of patients with severe COVID-19. However, less is known about the relationship between pre-COVID-19 IL-6 levels and the risk of severe COVID-19. To fill in this gap, here we extensively investigated the association of genetically instrumented IL-6 pathway components with the risk of severe COVID-19.

METHODS

We used a two-sample Mendelian randomization study design and retrieved genetic instruments for blood biomarkers of IL-6 activation, including IL-6, soluble IL-6 receptor, IL-6 signal transducer, and CRP, from respective large available GWASs. To establish associations of these instruments with COVID-19 outcomes, we used data from the Host Genetics Initiative and GenOMICC studies.

RESULTS

Our analyses revealed inverse associations of genetically instrumented levels of IL-6 and its soluble receptor with the risk of developing severe disease (OR = 0.60 and 0.94, respectively). They also demonstrated a positive association of severe disease with the soluble signal transducer level (OR = 1.13). Only IL-6 associations with severe COVID-19 outcomes reached the significance threshold corrected for multiple testing (p < 0.003; with COVID-19 hospitalization and critical illness).

CONCLUSIONS

These potential causal relationships for pre-COVID-19 IL-6 levels with the risk of developing severe symptoms provide opportunities for further evaluation of these factors as prognostic/preventive markers of severe COVID-19. Further studies will need to clarify whether the higher risk for a severe disease course with lower baseline IL-6 levels may also extend to other infectious diseases.

SCARF2 is a target for chronic obstructive pulmonary disease: Evidence from multi-omics research and cohort validation

Age-related chronic inflammatory lung diseases impose a threat on public health, including idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD). However, their etiology and potential targets have not been clarified. We performed genome-wide meta-analysis for IPF with the largest sample size (2883 cases and 741,929 controls) and leveraged the summary statistics of COPD (17,547 cases and 617,598 controls). Transcriptome-wide and proteome-wide Mendelian randomization (MR) designs, together with genetic colocalization, were implemented to find robust targets. The mediation effect was assessed using leukocyte telomere length (LTL). The single-cell transcriptome analysis was performed to link targets with cell types. Individual-level data from UK Biobank (UKB) were used to validate our findings. Sixteen genetically predicted plasma proteins were causally associated with the risk of IPF and 6 proteins were causally associated with COPD. Therein, genetically-elevated plasma level of SCARF2 protein should reduce the risk of both IPF (odds ratio, OR = 0.9974 [0.9970, 0.9978]) and COPD (OR = 0.7431 [0.6253, 0.8831]) and such effects were not mediated by LTL. Genetic colocalization further corroborated these MR results of SCARF2. The transcriptome-wide MR confirmed that higher expression level of SCARF2 was associated with a reduced risk of both. However, the single-cell RNA analysis indicated that SCARF2 expression level was only relatively lower in epithelial cells of COPD lung tissue compared to normal lung tissue. UKB data implicated an inverse association of serum SCARF2 protein with COPD (hazard ratio, HR = 1.215 [1.106, 1.335]). The SCARF2 gene should be a novel target for COP.

Critically-ill COVID-19 susceptibility gene CCR3 shows natural selection in sub-Saharan Africans

The prevalence of COVID-19 critical illness varies across ethnicities, with recent studies suggesting that genetic factors may contribute to this variation. The aim of this study was to investigate natural selection signals of genes associated with critically-ill COVID-19 in sub-Saharan Africans. Severe COVID-19 SNPs were obtained from the HGI website. Selection signals were assessed in 661 sub-Sahara Africans from 1000 Genomes Project using integrated haplotype score (iHS), cross-population extended haplotype homozygosity (XP-EHH), and fixation index (Fst). Allele frequency trajectory analysis of ancient DNA samples were used to validate the existing of selection in sub-Sahara Africans. We also used Mendelian randomization to decipher the correlation between natural selection and critically-ill COVID-19. We identified that CCR3 exhibited significant natural selection signals in sub-Sahara Africans. Within the CCR3 gene, rs17217831-A showed both high iHS (Standardized iHS = 2) and high XP-EHH (Standardized XP-EHH = 2.5) in sub-Sahara Africans. Allele frequency trajectory of CCR3 rs17217831-A revealed natural selection occurring in the recent 1,500 years. Natural selection resulted in increased CCR3 expression in sub-Sahara Africans. Mendelian Randomization provided evidence that increased blood CCR3 expression and eosinophil counts lowered the risk of critically ill COVID-19. Our findings suggest that sub-Saharan Africans are resistant to critically ill COVID-19 due to natural selection and identify CCR3 as a potential novel therapeutic target.

Mendelian Randomization Identifies Genetically Supported Drug Targets for Amyotrophic Lateral Sclerosis and Frontotemporal Dementia

Currently, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) have no effective treatments. Drug repurposing offers a rapid method to meet therapeutic need for ALS and FTD. To identify therapeutic targets associated with ALS and FTD, Mendelian randomization (MR) analysis and colocalization were performed. Genetic instruments were based on transcriptomic and proteomic data for 422 actionable proteins targeted by approved drugs or clinical drug candidates. The publicly available ALS GWAS summary data (including a total of 20,806 ALS cases and 59,804 controls) and FTD GWAS summary data (including a total of 2154 patients with FTD and 4308 controls) were used. Using cis-expression quantitative trait loci and cis-protein quantitative trait loci genetic instruments, we identified several drug targets for repurposing (ALS: MARK3, false-discovery rate (FDR) = 0.043; LTBR, FDR = 0.068) (FTD: HLA-DRB1, FDR = 0.083; ADH5, FDR = 0.056). Our MR study analyzed the actionable druggable proteins and provided potential therapeutic targets for ALS and FTD. Future studies should further elucidate the underlying mechanism of corresponding drug targets in the pathogenesis of ALS and FTD.

Unraveling genetic threads: Identifying novel therapeutic targets for allergic rhinitis through Mendelian randomization

Background

Allergic rhinitis (AR) is a pervasive global health issue, and currently, there is a scarcity of targeted drug therapies available. This study aims to identify potential druggable target genes for AR using Mendelian randomization (MR) analysis.

Methods

MR analysis was conducted to assess the causal effect of expression quantitative trait loci (eQTL) in the blood on AR. Data on AR were collected from 2 datasets: FinnGen(R9) (11,009 cases and 359,149 controls) and UK Biobank (25,486 cases and 87,097 controls). Colocalization analysis was utilized to assess the common causal genetic variations between the identified drug target genes and AR. We also employed available genome-wide association studies (GWAS) data to gauge the impact of druggable genes on AR biomarkers and other allergic diseases.

Results

This study employs MR to analyze the relationship between 3410 druggable genes and AR. After Bonferroni correction, 10 genes were found to be significantly associated with AR risk (P < 0.05/3410). Colocalization analysis revealed a significant causal relationship between the expression variation of CFL1 and EFEMP2 genes and AR, sharing direct causal variants (colocalization probability PP.H3 + PP.H4 > 0.8), highlighting their importance as potential therapeutic targets for AR. The CFL1 gene showed a causal link with levels of thymic stromal lymphopoietin (TSLP), eosinophil count, and interleukin-13 (IL-13) (P = 0.016, 7.45E-16, 0.00091, respectively). EFEMP2 was also causally related to eosinophil count, IL-13, and interleukin-17 (IL-17) (P = 0.00012, 0.00091, 0.032, respectively). PheWAS analysis revealed significant associations of CFL1 with asthma, whereas EFEMP2 showed associations with both asthma and eczema. Protein-Protein Interaction (PPI) network analysis further unveiled the direct interactions of EFEMP2 and CFL1 with proteins related to immune regulation and inflammatory responses, with 77.64% of the network consisting of direct bindings, indicating their key roles in modulating AR-related immune and inflammatory responses. Notably, there was an 8.01% significant correlation between immune-related pathways and genes involved in inflammatory responses.

Conclusion

These genes present notable associations with AR biomarkers and other autoimmune diseases, offering valuable targets for developing new AR therapies.

Drug repurposing opportunities for chronic kidney disease

The development of targeted drugs for the early prevention and management of chronic kidney disease (CKD) is of great importance. However, the success rates and cost-effectiveness of traditional drug development approaches are extremely low. Utilizing large sample genome-wide association study data for drug repurposing has shown promise in many diseases but has not yet been explored in CKD. Herein, we investigated actionable druggable targets to improve renal function using large-scale Mendelian randomization and colocalization analyses. We combined two population-scale independent genetic datasets and validated findings with cell-type-dependent eQTL data of kidney tubular and glomerular samples. We ultimately prioritized two drug targets, opioid receptor-like 1 and F12, with potential genetic support for restoring renal function and subsequent treatment of CKD. Our findings explore the potential pathological mechanisms of CKD, bridge the gap between the molecular mechanisms of pathogenesis and clinical intervention, and provide new strategies in future clinical trials of CKD.

Exploring the protective association between COVID-19 infection and laryngeal cancer: insights from a Mendelian randomization study

Introduction

Viral infections have been implicated as a risk factor for laryngeal cancer. Given the possible effects of Corona virus disease 2019 (COVID-19) on the laryngeal tissue, we investigated the causal link between COVID-19 and laryngeal cancer using a two-sample Mendelian randomization (MR) approach.

Methods

We utilized genetic data from the 5th Genome-wide association studies (GWAS) edition of the COVID-19 Host Genetics Initiative (published on January 18, 2021) and a large-scale laryngeal cancer GWAS comprising 180 cases and 218,612 controls of European ancestry. We applied inverse variance weighting, MR Egger, and weighted median methods to infer causality. We performed sensitivity analysis using the "leave-one-out" method to verify robustness.

Results

We found no evidence of a causal association between gene-predicted COVID-19 and laryngeal cancer [Odds ratio (OR)=0.24 (95% Confidence intervals (CI), 0.05-1.26), P=0.09]. However, we observed significant inverse associations between gene-predicted COVID-19 hospitalization [OR=0.51 (95% CI, 0.28-0.95), P=0.03] and severe patients [OR=0.62 (95% CI, 0.43-0.90), P=0.01] and laryngeal cancer. Notably, the study detected important genetic variants, such as rs13050728, that modulate the expression of interferon alpha receptor 2 (IFNAR2), indicating possible roles for immune response pathways in both COVID-19 and cancer.

Discussion

This study reveals a potential interaction between COVID-19 severity, genetic factors, and laryngeal cancer, underscoring the importance of investigating the immune response mechanisms in both conditions. These findings contribute to the understanding of the complex interactions between COVID-19 and laryngeal cancer and may guide future research on the role of immune response, particularly involving IFNAR2.

Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for lung cancer

BACKGROUND

Drug repurposing provides a cost-effective approach to address the need for lung cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR).

METHODS

Summary-level data of gene expression quantitative trait loci (eQTLs) were sourced from the eQTLGen resource. We procured genetic associations with lung cancer and its subtypes from the TRICL, ILCCO studies (discovery) and the FinnGen study (replication). We implemented Summary-data-based Mendelian Randomization analysis to identify potential therapeutic targets for lung cancer. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant.

FINDINGS

In the main analysis dataset, we identified 55 genes that demonstrate a causal relationship with lung cancer and its subtypes. However, in the replication cohort, only three genes were found to have such a causal association with lung cancer and its subtypes, and of these, HYKK (also known as AGPHD1) was consistently present in both the primary analysis dataset and the replication cohort. Following HEIDI tests and colocalization analyses, it was revealed that HYKK (AGPHD1) is associated with an increased risk of squamous cell carcinoma of the lung, with an odds ratio and confidence interval of OR = 1.28,95%CI = 1.24 to 1.33.

INTERPRETATION

We have found that the HYKK (AGPHD1) gene is associated with an increased risk of squamous cell carcinoma of the lung, suggesting that this gene may represent a potential therapeutic target for both the prevention and treatment of lung squamous cell carcinoma.

Identifying therapeutic targets for breast cancer: insights from systematic Mendelian randomization analysis

Background

Breast cancer (BC) exhibits a high incidence rate, imposing a substantial burden on healthcare systems. Novel drug targets are urgently needed for BC. Mendelian randomization (MR) has gained widespread application for identifying fresh therapeutic targets. Our endeavor was to pinpoint circulatory proteins causally linked to BC risk and proffer potential treatment targets for BC.

Methods

Through amalgamating protein quantitative trait loci from 2,004 circulating proteins and comprehensive genome-wide association study data from the Breast Cancer Association Consortium, we conducted MR analyses. Employing Steiger filtering, bidirectional MR, Bayesian colocalization, phenotype scanning, and replication analyses, we further solidified MR study outcomes. Additionally, protein-protein interaction (PPI) network was harnessed to unveil latent associations between proteins and prevailing breast cancer medications. The phenome-wide MR (Phe-MR) was employed to assess potential side effects and indications for the druggable proteins of BC. Finally, we further affirmed the drugability of potential drug targets through mRNA expression analysis and molecular docking.

Results

Through comprehensive analysis, we identified five potential drug targets, comprising four (TLR1, A4GALT, SNUPN, and CTSF) for BC and one (TLR1) for BC_estrogen receptor positive. None of these five potential drug targets displayed reverse causation. Bayesian colocalization suggested that these five latent drug targets shared variability with breast cancer. All drug targets were replicated within the deCODE cohort. TLR1 exhibited PPI with current breast cancer therapeutic targets. Furthermore, Phe-MR unveiled certain adverse effects solely for TLR1 and SNUPN.

Conclusion

Our study uncovers five prospective drug targets for BC and its subtypes, warranting further clinical exploration.

Multi-Omic Analysis Reveals Genetic Determinants and Therapeutic Targets of Chronic Kidney Disease and Kidney Function

Chronic kidney disease (CKD) presents a significant global health challenge, characterized by complex pathophysiology. This study utilized a multi-omic approach, integrating genomic data from the CKDGen consortium alongside transcriptomic, metabolomic, and proteomic data to elucidate the genetic underpinnings and identify therapeutic targets for CKD and kidney function. We employed a range of analytical methods including cross-tissue transcriptome-wide association studies (TWASs), Mendelian randomization (MR), summary-based MR (SMR), and molecular docking. These analyses collectively identified 146 cross-tissue genetic associations with CKD and kidney function. Key Golgi apparatus-related genes (GARGs) and 41 potential drug targets were highlighted, with MAP3K11 emerging as a significant gene from the TWAS and MR data, underscoring its potential as a therapeutic target. Capsaicin displayed promising drug-target interactions in molecular docking analyses. Additionally, metabolome- and proteome-wide MR (PWMR) analyses revealed 33 unique metabolites and critical inflammatory proteins such as FGF5 that are significantly linked to and colocalized with CKD and kidney function. These insights deepen our understanding of CKD pathogenesis and highlight novel targets for treatment and prevention.

Systematic characterization of multi-omics landscape between gut microbial metabolites and GPCRome in Alzheimer's disease

Shifts in the magnitude and nature of gut microbial metabolites have been implicated in Alzheimer's disease (AD), but the host receptors that sense and respond to these metabolites are largely unknown. Here, we develop a systems biology framework that integrates machine learning and multi-omics to identify molecular relationships of gut microbial metabolites with non-olfactory G-protein-coupled receptors (termed the "GPCRome"). We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs and 335 gut microbial metabolites. Using genetics-derived Mendelian randomization and integrative analyses of human brain transcriptomic and proteomic profiles, we identify orphan GPCRs (i.e., GPR84) as potential drug targets in AD and that triacanthine experimentally activates GPR84. We demonstrate that phenethylamine and agmatine significantly reduce tau hyperphosphorylation (p-tau181 and p-tau205) in AD patient induced pluripotent stem cell-derived neurons. This study demonstrates a systems biology framework to uncover the GPCR targets of human gut microbiota in AD and other complex diseases if broadly applied.

Leveraging pQTL-based Mendelian randomization to identify new treatment prospects for primary biliary cholangitis and primary sclerosing cholangitis

Primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) are autoimmune disorders characterized by progressive and chronic damage to the bile ducts, presenting clinicians with significant challenges. The objective of this study is to identify potential druggable targets to offer new avenues for treatment. A Mendelian randomization analysis was performed to identify druggable targets for PBC and PSC. This involved obtaining Cis-protein quantitative trait loci (Cis-pQTL) data from the deCODE database to serve as exposure. Outcome data for PBC (557 cases and 281,127 controls) and PSC (1,715 cases and 330,903 controls) were obtained from the FINNGEN database. Colocalization analysis was conducted to determine whether these features share the same associated SNPs. Validation of the expression level of druggable targets was done using the GSE119600 dataset and immunohistochemistry for clinical samples. Lastly, the DRUGBANK database was used to predict potential drugs. The MR analysis identified eight druggable targets each for PBC and PSC. Subsequent summary-data-based MR and colocalization analyses showed that LEFTY2 had strong evidence as a therapeutic candidate for PBC, while HSPB1 had moderate evidence. For PSC, only FCGR3B showed strong evidence as a therapeutic candidate. Additionally, upregulated expression of these genes was validated in PBC and PSC groups by GEO dataset and clinical samples. This study identifies two novel druggable targets with strong evidence for therapeutic candidates for PBC (LEFTY2 and HSPB1) and one for PSC (FCGR3B). These targets offer new therapeutic opportunities to address the challenging nature of PBC and PSC treatment.

Unveiling promising drug targets for autism spectrum disorder: insights from genetics, transcriptomics, and proteomics

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder for which current treatments are limited and drug development costs are prohibitive. Identifying drug targets for ASD is crucial for the development of targeted therapies. Summary-level data of expression quantitative trait loci obtained from GTEx, protein quantitative trait loci data from the ROSMAP project, and two ASD genome-wide association studies datasets were utilized for discovery and replication. We conducted a combined analysis using Mendelian randomization (MR), transcriptome-wide association studies, Bayesian colocalization, and summary-data-based MR to identify potential therapeutic targets associated with ASD and examine whether there are shared causal variants among them. Furthermore, pathway and drug enrichment analyses were performed to further explore the underlying mechanisms and summarize the current status of pharmacological targets for developing drugs to treat ASD. The protein-protein interaction (PPI) network and mouse knockout models were performed to estimate the effect of therapeutic targets. A total of 17 genes revealed causal associations with ASD and were identified as potential targets for ASD patients. Cathepsin B (CTSB) [odd ratio (OR) = 2.66 95, confidence interval (CI): 1.28-5.52, P = 8.84 × 10-3], gamma-aminobutyric acid type B receptor subunit 1 (GABBR1) (OR = 1.99, 95CI: 1.06-3.75, P = 3.24 × 10-2), and formin like 1 (FMNL1) (OR = 0.15, 95CI: 0.04-0.58, P = 5.59 × 10-3) were replicated in the proteome-wide MR analyses. In Drugbank, two potential therapeutic drugs, Acamprosate (GABBR1 inhibitor) and Bryostatin 1 (CASP8 inhibitor), were inferred as potential influencers of autism. Knockout mouse models suggested the involvement of the CASP8, GABBR1, and PLEKHM1 genes in neurological processes. Our findings suggest 17 candidate therapeutic targets for ASD and provide novel drug targets for therapy development and critical drug repurposing opportunities.

Identifying potential drug targets for idiopathic pulmonary fibrosis: a mendelian randomization study based on the druggable genes

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic interstitial lung disease characterized by progressive dyspnea and decreased lung function, yet its exact etiology remains unclear. It is of great significance to discover new drug targets for IPF.

METHODS

We obtained the cis-expression quantitative trait locus (cis-eQTL) of druggable genes from eQTLGen Consortium as exposure and the genome wide association study (GWAS) of IPF from the International IPF Genetics Consortium as outcomes to simulate the effects of drugs on IPF by employing mendelian randomization analysis. Then colocalization analysis was performed to calculate the probability of both cis-eQTL of druggable genes and IPF sharing a causal variant. For further validation, we conducted protein quantitative trait locus (pQTL) analysis to reaffirm our findings.

RESULTS

The expression of 45 druggable genes was significantly associated with IPF susceptibility at FDR < 0.05. The expression of 23 and 15 druggable genes was significantly associated with decreased forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLco) in IPF patients, respectively. IPF susceptibility and two significant genes (IL-7 and ABCB2) were likely to share a causal variant. The results of the pQTL analysis demonstrated that high levels of IL-7 in plasma are associated with a reduced risk of IPF (OR = 0.67, 95%CI: 0.47-0.97).

CONCLUSION

IL-7 stands out as the most promising potential drug target to mitigate the risk of IPF. Our study not only sheds light on potential drug targets but also provides a direction for future drug development in IPF.

Proteogenomic analyses identify coagulation factor XI as a thromboinflammatory mediator of long COVID

SARS-CoV-2 infection can result in long COVID, characterized by post-acute symptoms from multiple organ systems. Current hypotheses on mechanisms underlying long COVID include persistent inflammation and dysregulated coagulation; however, precise mechanisms and causal mediators remain unclear. Here, we tested the associations of genetic instruments for 49 complement and coagulation factors from the UK Biobank ( N =34,557) with long COVID in the Long COVID Host Genetics Initiative ( N =997,600). Primary analyses revealed that genetically predicted higher factor XI increased long COVID risk (odds ratio, 1.17 [95% confidence interval, 1.08-1.27] per standard deviation; P =1.7×10 -4 ). This association was robust to sensitivity analyses using pleiotropy-robust methods and different genetic instruments and was replicated using proteogenomic data from an Icelandic cohort. Genetically predicted factor XI was also associated with venous thromboembolism, but not with acute COVID-19 or long COVID-resembling conditions. Collectively, these findings provide genetic evidence implicating factor XI in the biology of long COVID.

The TRAF3-DYRK1A-RAD54L2 complex maintains ACE2 expression to promote SARS-CoV-2 infection

Angiotensin converting enzyme 2 (ACE2), the host receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, is differentially expressed in a wide variety of tissues and cell types. The expression of ACE2 is under tight regulation, but the mechanisms regulating ACE2 expression have not yet been well defined. Through a genome-wide CRISPR knockout screen, we discovered that host factors TRAF3, DYRK1A, and RAD54L2 (TDR) form a complex to regulate the expression of ACE2. Knockout of TRAF3, DYRK1A, or RAD54L2 reduces the mRNA levels of ACE2 and inhibits the cellular entry of SARS-CoV-2. On the other hand, SARS-CoV-2 continuously evolves by genetic mutations for the adaption to the host. We have identified mutations in spike (S) (P1079T) and nucleocapsid (N) (S194L) that enhance the replication of SARS-CoV-2 in cells that express ACE2 at a low level. Our results have revealed the mechanisms for the transcriptional regulation of ACE2 and the adaption of SARS-CoV-2.

IMPORTANCE

The expression of ACE2 is essential for the entry of SARS-CoV-2 into host cells. We identify a new complex-the TDR complex-that acts to maintain the abundance of ACE2 in host cells. The identification and characterization of the TDR complex provide new targets for the development of therapeutics against SARS-CoV-2 infection. By analysis of SARS-CoV-2 virus replicating in cells expressing low levels of ACE2, we identified mutations in spike (P1079T) and nucleocapsid (S194L) that overcome the restriction of limited ACE2. Functional analysis of these key amino acids in S and N extends our knowledge of the impact of SARS-CoV-2 variants on virus infection and transmission.

From genetic associations to genes: methods, applications, and challenges

Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.

Prioritization of therapeutic targets for cancers using integrative multi-omics analysis

BACKGROUND

The integration of transcriptomic, proteomic, druggable genetic and metabolomic association studies facilitated a comprehensive investigation of molecular features and shared pathways for cancers' development and progression.

METHODS

Comprehensive approaches consisting of transcriptome-wide association studies (TWAS), proteome-wide association studies (PWAS), summary-data-based Mendelian randomization (SMR) and MR were performed to identify genes significantly associated with cancers. The results identified in above analyzes were subsequently involved in phenotype scanning and enrichment analyzes to explore the possible health effects and shared pathways. Additionally, we also conducted MR analysis   to investigate metabolic pathways related to cancers.

RESULTS

Totally 24 genes (18 transcriptomic, 1 proteomic and 5 druggable genetic) showed significant associations with cancers risk. All genes identified in multiple methods were mainly enriched in nuclear factor erythroid 2-related factor 2 (NRF2) pathway. Additionally, biosynthesis of ubiquinol and urate were found to play an important role in gastrointestinal tumors.

CONCLUSIONS

A set of putatively causal genes and pathways relevant to cancers were identified in this study, shedding light on the shared biological processes for tumorigenesis and providing compelling genetic evidence to prioritize anti-cancer drugs development.

Mendelian randomization and colocalization analysis reveal novel drug targets for myasthenia gravis

OBJECTIVE

Myasthenia gravis (MG) is a complex autoimmune disease affecting the neuromuscular junction with limited drug options, but the field of MG treatment recently benefits from novel biological agents. We performed a drug-targeted Mendelian randomization (MR) study to identify novel therapeutic targets of MG.

METHODS

Cis-expression quantitative loci (cis-eQTL), which proxy expression levels for 2176 druggable genes, were used for MR analysis. Causal relationships between genes and disease, identified by eQTL MR analysis, were verified by comprehensive sensitivity, colocalization, and protein quantitative loci (pQTL) MR analyses. The protein-protein interaction (PPI) analysis was also performed to extend targets, followed by enzyme-linked immunosorbent assay (ELISA) to explore the serum level of drug targets in MG patients. A phenome-wide MR analysis was then performed to assess side effects with a clinical trial review assessing druggability.

RESULTS

The eQTL MR analysis has identified eight potential targets for MG, one for early-onset MG and seven for late-onset MG. Further colocalization analyses indicated that CD226, CDC42BPB, PRSS36, and TNFSF12 possess evidence for colocalization with MG or late-onset MG. pQTL MR analyses identified the causal relations of TNFSF12 and CD226 with MG and late-onset MG. Furthermore, PPI analysis has revealed the protein interaction between TNFSF12-TNFSF13(APRIL) and TNFSF12-TNFSF13B(BLyS). Elevated TNFSF13 serum level of MG patients was also identified by ELISA experiments. This study has ultimately proposed three promising therapeutic targets (TNFSF12, TNFSF13, TNFSF13B) of MG.

CONCLUSIONS

Three drug targets associated with the BLyS/APRIL pathway have been identified. Multiple biological agents, including telitacicept and belimumab, are promising for MG therapy.

Bioinformatics and system biology approaches to determine the connection of SARS-CoV-2 infection and intrahepatic cholangiocarcinoma

INTRODUCTION

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide, which poses a severe threat to human health. COVID-19 is a systemic ailment affecting various tissues and organs, including the lungs and liver. Intrahepatic cholangiocarcinoma (ICC) is one of the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. Nonetheless, few studies have investigated the impact of COVID-19 on ICC patients.

METHODS

With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC, and searched for potential therapeutic drugs.

RESULTS

This study identified a total of 70 common differentially expressed genes (DEGs) shared by both diseases, shedding light on their shared functionalities. Enrichment analysis pinpointed metabolism and immunity as the primary areas influenced by these common genes. Subsequently, through protein-protein interaction (PPI) network analysis, we identified SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1 as hub genes. Additionally, 44 transcription factors (TFs) and 112 microRNAs (miRNAs) were forecasted to regulate the hub genes. Most importantly, several drug candidates (Periodate-oxidized adenosine, Desipramine, Quercetin, Perfluoroheptanoic acid, Tetrandrine, Pentadecafluorooctanoic acid, Benzo[a]pyrene, SARIN, Dorzolamide, 8-Bromo-cAMP) may prove effective in treating ICC and COVID-19.

CONCLUSION

This study is expected to provide valuable references and potential drugs for future research and treatment of COVID-19 and ICC.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.

Methods

Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.

Results

A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.

Conclusions

Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Using genetics and proteomics data to identify proteins causally related to COVID-19, healthspan and lifespan: a Mendelian randomization study

BACKGROUND

COVID-19 pandemic poses a heavy burden on public health and accounts for substantial mortality and morbidity. Proteins are building blocks of life, but specific proteins causally related to COVID-19, healthspan and lifespan have not been systematically examined.

METHODS

We conducted a Mendelian randomization study to assess the effects of 1,361 plasma proteins on COVID-19, healthspan and lifespan, using large GWAS of severe COVID-19 (up to 13,769 cases and 1,072,442 controls), COVID-19 hospitalization (32,519 cases and 2,062,805 controls) and SARS-COV2 infection (122,616 cases and 2,475,240 controls), healthspan (n = 300,477) and parental lifespan (~0.8 million of European ancestry).

RESULTS

We identified 35, 43, and 63 proteins for severe COVID, COVID-19 hospitalization, and SARS-COV2 infection, and 4, 32, and 19 proteins for healthspan, father's attained age, and mother's attained age. In addition to some proteins reported previously, such as SFTPD related to severe COVID-19, we identified novel proteins involved in inflammation and immunity (such as ICAM-2 and ICAM-5 which affect COVID-19 risk, CXCL9, HLA-DRA and LILRB4 for healthspan and lifespan), apoptosis (such as FGFR2 and ERBB4 which affect COVID-19 risk and FOXO3 which affect lifespan) and metabolism (such as PCSK9 which lowers lifespan). We found 2, 2 and 3 proteins shared between COVID-19 and healthspan/lifespan, such as CXADR and LEFTY2, shared between severe COVID-19 and healthspan/lifespan. Three proteins affecting COVID-19 and seven proteins affecting healthspan/lifespan are targeted by existing drugs.

CONCLUSIONS

Our study provided novel insights into protein targets affecting COVID-19, healthspan and lifespan, with implications for developing new treatment and drug repurposing.

ASSESSING THE CAUSAL RELATIONSHIP BETWEEN SEPSIS AND AUTOIMMUNE: A MENDELIAN RANDOMIZATION STUDY

ABSTRACT

Objective : Numerous epidemiological studies have identified a potential link between sepsis and a variety of autoimmune disorders. The primary objective of this study is to delve deeper into this connection, investigating the potential causal relationship between sepsis and autoimmune disorders through the application of Mendelian randomization (MR). Methods : To assess the potential genetic impact on sepsis risk relating to susceptibility toward immune-related outcomes, we used summary data from the largest European genome-wide association studies (GWAS) on these conditions using a two-sample MR framework. Single nucleotide polymorphisms-which had strong associations with the nine traits-were extracted from the GWAS and examined their effects in an extensive European sepsis GWAS (486,484 cases and 474,841 controls). We used inverse-variance weighted MR, weighted median, and MR Egger for analyses, supplementing these with sensitivity analyses and assessing level pleiotropy using MR methodologies. We also executed a reverse MR analysis to test sepsis' causal effects on the designated autoimmune traits. Results : With primary sclerosing cholangitis being the exception, our MR analysis suggests that susceptibility toward most autoimmune diseases does not affect sepsis risks. The reverse MR analysis did not validate any influence of sepsis susceptibility over other autoimmune diseases. Our primary inverse-variance weighted MR analysis outcomes found general confirmation through our sensitivity MR examinations. Variance in the exposures, as dictated by the single nucleotide polymorphism sets used as MR instruments, ranged between 4.88 × 10 -5 to 0.005. Conclusion : Our MR research, centered on a European population, does not validate a correlation between susceptibility to the majority of autoimmune disorders and sepsis risk. Associations discerned in epidemiological studies may owe partly to shared biological or environmental confounders. The risk susceptibility for primary sclerosing cholangitis does relate to sepsis risk, opening doors for personalized precision treatments in the future.

Ursodeoxycholic acid may protect from severe acute respiratory syndrome coronavirus 2 Omicron variant by reducing angiotensin-converting enzyme 2

The SARS-CoV-2 caused COVID-19 pandemic has posed a global health hazard. While some vaccines have been developed, protection against viral infection is not perfect because of the urgent approval process and the emergence of mutant SARS-CoV-2 variants. Here, we employed UDCA as an FXR antagonist to regulate ACE2 expression, which is one of the key pathways activated by SARS-CoV-2 Delta variant infection. UDCA is a well-known reagent of liver health supplements and the only clinically approved bile acid. In this paper, we investigated the protective efficacy of UDCA on Omicron variation, since it has previously been verified for protection against Delta variant. When co-housing with an Omicron variant-infected hamster group resulted in spontaneous airborne transmission, the UDCA pre-supplied group was protected from weight loss relative to the non-treated group at 4 days post-infection by more than 5%-10%. Furthermore, UDCA-treated groups had a 3-fold decrease in ACE2 expression in nasal cavities, as well as reduced viral expressing genes in the respiratory tract. Here, the data show that the UDCA serves an alternative option for preventive drug, providing SARS-CoV-2 protection against not only Delta but also Omicron variant. Our results of this study will help to propose drug-repositioning of UDCA from liver health supplement to preventive drug of SARS-CoV-2 infection.

Unveiling potential drug targets for hyperparathyroidism through genetic insights via Mendelian randomization and colocalization analyses

Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions and non-surgical pharmacotherapy for the management of hyperparathyroidism, radical options to halt underlying disease progression remain lacking. Identifying putative genetic drivers and exploring novel drug targets that can impede HPT progression remain critical unmet needs. A Mendelian randomization (MR) analysis was performed to uncover putative therapeutic targets implicated in hyperparathyroidism pathology. Cis-expression quantitative trait loci (cis-eQTL) data serving as genetic instrumental variables were obtained from the eQTLGen Consortium and Genotype-Tissue Expression (GTEx) portal. Hyperparathyroidism summary statistics for single nucleotide polymorphism (SNP) associations were sourced from the FinnGen study (5590 cases; 361,988 controls). Colocalization analysis was performed to determine the probability of shared causal variants underlying SNP-hyperparathyroidism and SNP-eQTL links. Five drug targets (CMKLR1, FSTL1, IGSF11, PIK3C3 and SLC40A1) showed significant causation with hyperparathyroidism in both eQTLGen and GTEx cohorts by MR analysis. Specifically, phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) and solute carrier family 40 member 1 (SLC40A1) showed strong evidence of colocalization with HPT. Multivariable MR and Phenome-Wide Association Study analyses indicated these two targets were not associated with other traits. Additionally, drug prediction analysis implies the potential of these two targets for future clinical applications. This study identifies PIK3C3 and SLC40A1 as potential genetically proxied druggable genes and promising therapeutic targets for hyperparathyroidism. Targeting PIK3C3 and SLC40A1 may offer effective novel pharmacotherapies for impeding hyperparathyroidism progression and reducing disease risk. These findings provide preliminary genetic insight into underlying drivers amenable to therapeutic manipulation, though further investigation is imperative to validate translational potential from preclinical models through clinical applications.

Diagnosis of cystic lung diseases: a position statement from the UK Cystic Lung Disease Rare Disease Collaborative Network

BACKGROUND

Rare cystic lung diseases are increasingly recognised due the wider application of CT scanning making cystic lung disease management a growing part of respiratory care. Cystic lung diseases tend to have extrapulmonary features that can both be diagnostic but also require surveillance and treatment in their own right. As some of these diseases now have specific treatments, making a precise diagnosis is crucial. While Langerhans cell histiocytosis, Birt-Hogg-Dubé syndrome, lymphoid interstitial pneumonia and lymphangioleiomyomatosis are becoming relatively well-known diseases to respiratory physicians, a targeted and thorough workup improves diagnostic accuracy and may suggest other ultrarare diseases such as light chain deposition disease, cystic pulmonary amyloidosis, low-grade metastatic neoplasms or infections. In many cases, diagnostic information is overlooked leaving uncertainty over the disease course and treatments.

AIMS

This position statement from the Rare Disease Collaborative Network for cystic lung diseases will review how clinical, radiological and physiological features can be used to differentiate between these diseases.

NARRATIVE

We highlight that in many cases a multidisciplinary diagnosis can be made without the need for lung biopsy and discuss where tissue sampling is necessary when non-invasive methods leave diagnostic doubt. We suggest an initial workup focusing on points in the history which identify key disease features, underlying systemic and familial diseases and a clinical examination to search for connective tissue disease and features of genetic causes of lung cysts. All patients should have a CT of the thorax and abdomen to characterise the pattern and burden of lung cysts and extrapulmonary features and also spirometry, gas transfer and a 6 min walk test. Discussion with a rare cystic lung disease centre is suggested before a surgical biopsy is undertaken.

CONCLUSIONS

We suggest that this focused workup should be performed in all people with multiple lung cysts and would streamline referral pathways, help guide early treatment, management decisions, improve patient experience and reduce overall care costs. It could also potentially catalyse a national research database to describe these less well-understood and unidentified diseases, categorise disease phenotypes and outcomes, potentially leading to better prognostic data and generating a stronger platform to understand specific disease biology.

Host genetic variants associated with COVID-19 reconsidered in a Slovak cohort

We present the results of an association study involving hospitalized coronavirus disease 2019 (COVID-19) patients with a clinical background during the 3rd pandemic wave of COVID-19 in Slovakia. Seventeen single nucleotide variants (SNVs) in the eleven most relevant genes, according to the COVID-19 Host Genetics Initiative, were investigated. Our study confirms the validity of the influence of LZTFL1 and 2'-5'-oligoadenylate synthetase (OAS)1/OAS3 genetic variants on the severity of COVID-19. For two LZTFL1 SNVs in complete linkage disequilibrium, rs17713054 and rs73064425, the odds ratios of baseline allelic associations and logistic regressions (LR) adjusted for age and sex ranged in the four tested designs from 2.04 to 2.41 and from 2.05 to 3.98, respectively. The OAS1/OAS3 haplotype 'gttg' carrying a functional allele G of splice-acceptor variant rs10774671 manifested its protective function in the Delta pandemic wave. Significant baseline allelic associations of two DPP9 variants in all tested designs and two IFNAR2 variants in the Omicron pandemic wave were not confirmed by adjusted LR. Nevertheless, adjusted LR showed significant associations of NOTCH4 rs3131294 and TYK2 rs2304256 variants with severity of COVID-19. Hospitalized patients' reported comorbidities were not correlated with genetic variants, except for obesity, smoking (IFNAR2), and hypertension (NOTCH4). The results of our study suggest that host genetic variations have an impact on the severity and duration of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Considering the differences in allelic associations between pandemic waves, they support the hypothesis that every new SARS-CoV-2 variant may modify the host immune response by reconfiguring involved pathways.

Integration of human organoids single-cell transcriptomic profiles and human genetics repurposes critical cell type-specific drug targets for severe COVID-19

Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of trait-relevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular-specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications.

Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis

INTRODUCTION

Compared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the treatment of certain breast, colorectal, head and neck, lung and melanoma cancers. These drugs target immune checkpoint proteins to reduce the suppression of T cell activation by cancer cells. As T cell suppression is a hallmark of cancer common across anatomical sites, we hypothesise that immune checkpoint inhibitors could be repurposed for the treatment of additional cancers beyond the ones already indicated.

METHODS AND ANALYSIS

We will use two-sample Mendelian randomisation to investigate the effect of genetically proxied levels of protein targets of two immune checkpoint inhibitors-programmed cell death protein 1 and programmed death ligand 1-on survival of seven cancer types (breast, colorectal, head and neck, lung, melanoma, ovarian and prostate). Summary genetic association data will be obtained from prior genome-wide association studies of circulating protein levels and cancer survival in populations of European ancestry. Various sensitivity analyses will be performed to examine the robustness of findings to potential violations of Mendelian randomisation assumptions, collider bias and the impact of alternative genetic instrument construction strategies. The impact of treatment history and tumour stage on the findings will also be investigated using summary-level and individual-level genetic data where available.

ETHICS AND DISSEMINATION

No separate ethics approval will be required for these analyses as we will be using data from previously published genome-wide association studies which individually gained ethical approval and participant consent. Results from analyses will be submitted as an open-access peer-reviewed publication and statistical code will be made freely available on the completion of the analysis.

Causal association between tea consumption and head and neck cancer: a Mendelian randomization study

Although evidence supports an observational association between tea consumption and susceptibility to head and neck cancer, the causal nature of this association remains unclear. We performed a two-sample Mendelian randomization (MR) analysis to determine the causal effects of tea consumption on head and neck cancer. We employed a fixed-effects inverse variance-weighted model for the MR analysis. Genome-wide association study (GWAS) summary data for tea consumption were obtained from the UK Biobank Consortium, and GWAS data for head and neck cancer were derived from two data sources and were used as the outcomes. Our MR analysis revealed limited evidence for a causal relationship between various types of tea intake and head and neck cancer. After adjustment for smoking and alcohol consumption, there was no causal relationship between tea consumption and head and neck cancer. Further experimental studies are required to confirm its potential role in these malignancies.

Integrative single-cell analysis: dissecting CD8 + memory cell roles in LUAD and COVID-19 via eQTLs and Mendelian Randomization

Lung adenocarcinoma exhibits high incidence and mortality rates, presenting a significant health concern. Concurrently, the COVID-19 pandemic has emerged as a grave global public health challenge. Existing literature suggests that T cells, pivotal components of cellular immunity, are integral to both antiviral and antitumor responses. Yet, the nuanced alterations and consequent functions of T cells across diverse disease states have not been comprehensively elucidated. We gathered transcriptomic data of peripheral blood mononuclear cells from lung adenocarcinoma patients, COVID-19 patients, and healthy controls. We followed a standardized analytical approach for quality assurance, batch effect adjustments, and preliminary data processing. We discerned distinct T cell subsets and conducted differential gene expression analysis. Potential key genes and pathways were inferred from GO and Pathway enrichment analyses. Additionally, we implemented Mendelian randomization to probe the potential links between pivotal genes and lung adenocarcinoma susceptibility. Our findings underscored a notable reduction in mature CD8 + central memory T cells in both lung adenocarcinoma and COVID-19 cohorts relative to the control group. Notably, the downregulation of specific genes, such as TRGV9, could impede the immunological efficacy of CD8 + T cells. Comprehensive multi-omics assessment highlighted genetic aberrations in genes, including TRGV9, correlating with heightened lung adenocarcinoma risk. Through rigorous single-cell transcriptomic analyses, this investigation meticulously delineated variations in T cell subsets across different pathological states and extrapolated key regulatory genes via an integrated multi-omics approach, establishing a robust groundwork for future functional inquiries. This study furnishes valuable perspectives into the etiology of multifaceted diseases and augments the progression of precision medicine.

The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods

ChEMBL (https://www.ebi.ac.uk/chembl/) is a manually curated, high-quality, large-scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like properties, previously described in the 2012, 2014, 2017 and 2019 Nucleic Acids Research Database Issues. Since its introduction in 2009, ChEMBL's content has changed dramatically in size and diversity of data types. Through incorporation of multiple new datasets from depositors since the 2019 update, ChEMBL now contains slightly more bioactivity data from deposited data vs data extracted from literature. In collaboration with the EUbOPEN consortium, chemical probe data is now regularly deposited into ChEMBL. Release 27 made curated data available for compounds screened for potential anti-SARS-CoV-2 activity from several large-scale drug repurposing screens. In addition, new patent bioactivity data have been added to the latest ChEMBL releases, and various new features have been incorporated, including a Natural Product likeness score, updated flags for Natural Products, a new flag for Chemical Probes, and the initial annotation of the action type for ∼270 000 bioactivity measurements.

Therapeutic Challenges in COVID-19

SARS-CoV2 is a novel respiratory coronavirus and, understanding its molecular mechanism is a prerequisite to developing effective treatment for COVID-19. This RNA genome-carrying virus has a protein coat with spikes (S) that attaches to the ACE2 receptor at the cell surface of human cells. Several repurposed drugs are used to treat COVID-19 patients that are proven to be largely unsuccessful or have limited success in reducing mortalities. Several vaccines are in use to reduce the viral load to prevent developing symptoms. Major challenges to their efficacy include the inability of antibody molecules to enter cells but remain effective in the bloodstream to kill the virus. The efficacy of vaccines also depends on their neutralizing ability to constantly evolve new virus strains due to novel mutations and evolutionary survival dynamics. Taken together, SARS-CoV2 antibody vaccines may not be very effective and other approaches based on genetic, genomic, and protein interactome could be fruitful to identify therapeutic targets to reduce disease-related mortalities.

IUPHAR review - Data-driven computational drug repurposing approaches for opioid use disorder

Opioid Use Disorder (OUD) is a chronic and relapsing condition characterized by the misuse of opioid drugs, causing significant morbidity and mortality in the United States. Existing medications for OUD are limited, and there is an immediate need to discover treatments with enhanced safety and efficacy. Drug repurposing aims to find new indications for existing medications, offering a time-saving and cost-efficient alternative strategy to traditional drug discovery. Computational approaches have been developed to further facilitate the drug repurposing process. In this paper, we reviewed state-of-the-art data-driven computational drug repurposing approaches for OUD and discussed their advantages and potential challenges. We also highlighted promising repurposed candidate drugs for OUD that were identified by computational drug repurposing techniques and reviewed studies supporting their potential mechanisms of action in treating OUD.

Mendelian Randomization as a Tool for Cardiovascular Research: A Review

Importance

Mendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease.

Observations

MR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed.

Conclusions and Relevance

This review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

Association of antihypertensive drugs with COVID-19 outcomes: a drug-target Mendelian randomization study

Background: Observational investigations have provided conflicting results regarding the effect of antihypertensive drugs on the risk of COVID-19 outcomes. We intended to assess the causal effect of antihypertensive drugs on COVID-19 outcomes using drug-target Mendelian randomization (MR), mainly including angiotensin-converting enzyme inhibitors (ACEIs), β-blockers (BBs) and calcium channel blockers (CCBs). Methods: We used the genetic variants (minor allele frequency >1%, r 2 < 0.30) located within 100 k bases of each drug target gene and associated with lower systolic blood pressure (p < 5 × 10-8) as genetic proxies for antihypertensive drugs. COVID-19 outcomes included COVID-19 susceptibility (122,616 cases and 2,475,240 controls), hospitalization (32,519 cases and 206,2805 controls), and severe illness (13,769 cases and 1,072,442 controls). All studies were conducted on populations of European ancestry. MR estimates were generated using an inverse variance weighted (IVW) model. Results: IVW-MR analysis observed a weak causality between CCBs and COVID-19 susceptibility (OR: 0.993, 95% CI: 0.988-0.999, p = 0.012). Sensitivity analysis suggested that this result was robust. No evidence was found for a link between other antihypertensive drugs and COVID-19 outcomes. Conclusion: The present study suggests that CCBs may reduce COVID-19 susceptibility in European populations.

Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses

BACKGROUND

Drug repurposing provides a cost-effective approach to address the need for breast cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR) and then validate the candidate drugs using population-based analyses.

METHODS

We identified genetic instruments for 1406 actionable targets of approved non-oncological drugs based on gene expression, DNA methylation, and protein expression quantitative trait loci (eQTL, mQTL, and pQTL, respectively). Genome-wide association study (GWAS) summary statistics were obtained from the Breast Cancer Association Consortium (122,977 cases, 105,974 controls). We further conducted a nested case-control study using data retrieved from Swedish registers to validate the candidate drugs that were identified from MR analyses.

FINDINGS

We identified six significant MR associations with gene expression levels (TUBB, MDM2, CSK, ULK3, MC1R and KCNN4) and two significant associations with gene methylation levels across 21 CpG islands (RPS23 and MAPT). Results from the nested case-control study showed that the use of raloxifene (targeting MAPT) was associated with 35% reduced breast cancer risk (odds ratio, OR, 0.65; 95% confidence interval, CI, 0.51-0.83). However, usage of estradiol, tolterodine, and nitrofurantoin (also targeting MAPT) was associated with increased breast cancer risk, with adjusted ORs and 95% CI of 1.10 (1.07-1.13), 1.16 (1.09-1.24), and 1.09 (1.05-1.13), respectively. The effect of raloxifene and nitrofurantoin lost significance in further validation analyses using active-comparator and new-user design.

INTERPRETATION

This large-scale MR analysis, combined with population-based validation, identified eight druggable target genes for breast cancer and suggested that raloxifene is an effective chemoprevention against breast cancer.

FUNDING

Swedish Research Council, Cancerfonden, Crafoordska Stiftelsen, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, 111 Project and MAS cancer.

Participation of Single-Nucleotide Variants in IFNAR1 and IFNAR2 in the Immune Response against SARS-CoV-2 Infection: A Systematic Review

Host genetic factors significantly influence susceptibility to SARS-CoV-2 infection and COVID-19 severity. Among these genetic factors are single-nucleotide variants (SNVs). IFNAR2 and IFNAR1 genes have been associated with severe COVID-19 in populations from the United Kingdom, Africa, and Latin America. IFNAR1 and IFNAR2 are subunits forming the type I interferon receptor (IFNAR). SNVs in the IFNAR genes impact protein function, affecting antiviral response and disease phenotypes. This systematic review aimed to describe IFNAR1 and IFNAR2 variants associated with COVID-19 susceptibility and severity. Accordingly, the current review focused on IFNAR1 and IFNAR2 studies published between January 2021 and February 2023, utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol. The electronic search was conducted in PubMed databases using Boolean operators and inclusion and exclusion criteria. Of the 170 literature pieces, 11 studies were included. We include case reports of rare SNVs, defined by minor allele frequency (MAF) < 1%, and genome-wide associated studies (GWAS). Variants in IFNAR1 and IFNAR2 could potentially be new targets for therapies that limit the infection and the resulting inflammation by SARS-CoV-2 infection.

Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.

METHODS

A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.

RESULTS

Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.

Molecular PET/CT mapping of rhACE2 distribution and quantification in organs to aid in SARS-CoV-2 targeted therapy

Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, poses a significant threat to public health. Angiotensin-converting enzyme 2 (ACE2) is a key receptor for SARS-CoV-2 infection. Recombinant human ACE2 (RhACE2), as a soluble supplement for human ACE2, can competitively block SARS-CoV-2 infection. In this study, a mouse organ in situ rhACE2 high aggregation model was constructed for the first time, and in vivo real-time positron emission tomography (PET) imaging of rhACE2 in the mouse model was performed using an ACE2-specific agent 68 Ga-HZ20. This radiotracer exhibits reliable radiochemical properties in vitro and maintains a high affinity for rhACE2 in vivo. In terms of probe uptake, 68 Ga-HZ20 showed a good target-to-nontarget ratio and was rapidly cleared from the circulatory system and excreted by the kidneys and urinary system. PET imaging with this radiotracer can noninvasively and accurately monitor the content and distribution of rhACE2 in the body, which clarifies that rhACE2 can aggregate in multiple organs, suggesting the preventive and therapeutic potential of rhACE2 for SARS-CoV-2 and COVID-19.

Leveraging the Million Veteran Program Infrastructure and Data for a Rapid Research Response to COVID-19

Background

The Veterans Health Administration Office of Research and Development (ORD) played a key role in the federal government's response to the COVID-19 pandemic. The ORD effectively leveraged existing resources to answer questions related to the SARS-CoV-2 virus and COVID-19.

Observations

When the COVID-19 pandemic hit in 2020, the Million Veteran Program (MVP), one of the largest genomic cohorts in the world, extended the centralized recruitment and enrollment infrastructure to develop a COVID-19 research volunteer registry to assist enrollment in the vaccine and treatment trials in which the US Department of Veterans Affairs (VA) participated. In addition, the MVP allowed for new data collection and a large genomic cohort to understand host contributions to COVID-19. This article describes ways the MVP contributed to the VA's rapid research response to COVID-19. Several host genetic factors believed to play a role in the development and severity of COVID-19 were identified. Furthermore, existing MVP partnerships with other federal agencies, particularly with the Department of Energy, were leveraged to improve understanding and management of COVID-19.

Conclusions

A previously established enterprise approach and research infrastructure were essential to the VA's successful and timely COVID-19 research response. This infrastructure not only supported rapid recruitment in vaccine and treatment trials, but also leveraged the unique MVP and VA electronic health record data to drive rapid scientific discovery and inform clinical operations. Extending the models that VA research applied to the federal government at large and establishing centralized resources for shared or federated data analyses across federal agencies will better equip the nation to respond to future public health crises.

Integrated Analyses of Single-Cell Transcriptome and Mendelian Randomization Reveal the Protective Role of Resistin in Sepsis Survival in Intensive Care Unit

The high morbidity and mortality rates associated with sepsis highlight the challenges of finding specific remedies for this condition in the intensive care unit (ICU). This study aimed to explore the differentially expressed genes (DEGs) specific to cell types in sepsis and investigate the role of resistin in the survival of sepsis patients through Mendelian randomization (MR) analyses. We used single-cell and bulk transcriptome data to identify cell type-specific DEGs between sepsis and healthy controls. MR analyses were then conducted to investigate the causal relationships between resistin (one of the identified DEGs) levels and the survival of sepsis patients. Additionally, we utilized meQTL (methylation quantitative trait loci) to identify cytosine-phosphate-guanine (CpG) sites that may directly affect sepsis. We identified 560 cell type-specific DEGs between sepsis and healthy controls. Notably, we observed the upregulation of resistin levels in macrophages during sepsis. In bulk transcriptome, RETN is also upregulated in sepsis samples compared with healthy controls. MR analyses revealed a negative association existed between the expression of resistin, at both gene and protein levels, and the mortality or severity of sepsis patients in ICU. Moreover, there were no associations observed between resistin levels and death or organ failure due to other causes. We also identified three methylation CpG sites, located in RETN or its promoter region-cg06633066, cg22322184, and cg02346997-that directly affected both resistin protein levels and sepsis death in the ICU. Our findings suggest that resistin may provide feasible protection for sepsis patients, particularly those with severe cases, without serious side effects. Therefore, resistin could be a potential drug candidate for sepsis treatment. Additionally, we identified two CpG sites, cg06633066 and cg22322184, that were associated with RETN protein levels and sepsis death, providing novel insights into the underlying mechanisms of sepsis.

Colocalization of expression transcripts with COVID-19 outcomes is rare across cell states, cell types and organs

Identifying causal genes at GWAS loci can help pinpoint targets for therapeutic interventions. Expression studies can disentangle such loci but signals from expression quantitative trait loci (eQTLs) often fail to colocalize-which means that the genetic control of measured expression is not shared with the genetic control of disease risk. This may be because gene expression is measured in the wrong cell type, physiological state, or organ. We tested whether Mendelian randomization (MR) could identify genes at loci influencing COVID-19 outcomes and whether the colocalization of genetic control of expression and COVID-19 outcomes was influenced by cell type, cell stimulation, and organ. We conducted MR of cis-eQTLs from single cell (scRNA-seq) and bulk RNA sequencing. We then tested variables that could influence colocalization, including cell type, cell stimulation, RNA sequencing modality, organ, symptoms of COVID-19, and SARS-CoV-2 status among individuals with symptoms of COVID-19. The outcomes used to test colocalization were COVID-19 severity and susceptibility as assessed in the Host Genetics Initiative release 7. Most transcripts identified using MR did not colocalize when tested across cell types, cell state and in different organs. Most that did colocalize likely represented false positives due to linkage disequilibrium. In general, colocalization was highly variable and at times inconsistent for the same transcript across cell type, cell stimulation and organ. While we identified factors that influenced colocalization for select transcripts, identifying 33 that mediate COVID-19 outcomes, our study suggests that colocalization of expression with COVID-19 outcomes is partially due to noisy signals even after following quality control and sensitivity testing. These findings illustrate the present difficulty of linking expression transcripts to disease outcomes and the need for skepticism when observing eQTL MR results, even accounting for cell types, stimulation state and different organs.

Prioritization of therapeutic targets for dyslipidemia using integrative multi-omics and multi-trait analysis

Drug targets with genetic support are several-fold more likely to succeed in clinical trials. We introduce a genetic-driven approach based on causal inferences that can inform drug target prioritization, repurposing, and adverse effects of using lipid-lowering agents. Given that a multi-trait approach increases the power to detect meaningful variants/genes, we conduct multi-omics and multi-trait analyses, followed by network connectivity investigations, and prioritize 30 potential therapeutic targets for dyslipidemia, including SORT1, PSRC1, CELSR2, PCSK9, HMGCR, APOB, GRN, HFE2, FJX1, C1QTNF1, and SLC5A8. 20% (6/30) of prioritized targets from our hypothesis-free drug target search are either approved or under investigation for dyslipidemia. The prioritized targets are 22-fold higher in likelihood of being approved or under investigation in clinical trials than genome-wide association study (GWAS)-curated targets. Our results demonstrate that the genetic-driven approach used in this study is a promising strategy for prioritizing targets while informing about the potential adverse effects and repurposing opportunities.

Association of IFNAR2 rs2236757 and OAS3 rs10735079 Polymorphisms with Susceptibility to COVID-19 Infection and Severity in Palestine

The clinical course and severity of COVID-19 vary among patients. This study aimed to investigate the potential correlation between the gene polymorphisms of the interferon receptor (IFNAR2) rs2236757 and oligoadenylate synthetase 3 (OAS3) rs10735079 with the risk of COVID-19 infection and its severity among Palestinian patients. The study was conducted between April and May 2021 on 154 participants who were divided into three groups: the control group (RT-PCR-negative, n = 52), the community cases group (RT-PCR-positive, n = 70), and the critically ill cases (ICU group; n = 32). The genotyping of the investigated polymorphisms was performed using amplicon-based next-generation sequencing. The genotypes distribution for the IFNAR2 rs2236757 was significantly different among the study groups (P = 0.001), while no statistically significant differences were found in the distribution of genotypes for the OAS3 rs10735079 (P = 0.091). Logistic regression analysis adjusted for possible confounding factors revealed a significant association between the risk allele rs2236757A and critical COVID-19 illness (P  <  0.025). Among all patients, those who carried the rs2236757GA were more likely to have a sore throat (OR, 2.52 (95% CI 1.02-6.24); P = 0.011); the presence of the risk allele rs2236757A was associated with an increased risk to dyspnea (OR, 4.70 (95% CI 1.80-12.27); P  <  0.001), while the rs10735079A carriers were less likely to develop muscle aches (OR, 0.34 (95% CI 0.13-0.88); P = 0.0248) and sore throat (OR, 0.17 (95% CI 0.05-0.55); P  <  0.001). In conclusion, our results revealed that the rs2236757A variant was associated with critical COVID-19 illness and dyspnea, whereas the rs10735079A variant was protective for muscle aches and sore throat.

Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders

BACKGROUND AND HYPOTHESIS

Psychiatric disorders impose a huge health and economic burden on modern society. However, there is currently no proven completely effective treatment available, partly owing to the inefficiency of drug target identification and validation. We aim to identify therapeutic targets relevant to psychiatric disorders by conducting Mendelian randomization (MR) analysis.

STUDY DESIGN

We performed genome-wide MR analysis by integrating expression quantitative trait loci (eQTL) of 4479 actionable genes that encode druggable proteins and genetic summary statistics from genome-wide association studies of psychiatric disorders. After conducting colocalization analysis on the brain MR findings, we employed protein quantitative trait loci (pQTL) data as genetic proposed instruments for intersecting the colocalized genes to provide further genetic evidence.

STUDY RESULTS

By performing MR and colocalization analysis with eQTL genetic instruments, we obtained 31 promising drug targets for psychiatric disorders, including 21 significant genes for schizophrenia, 7 for bipolar disorder, 2 for depression, 1 for attention deficit and hyperactivity (ADHD) and none for autism spectrum disorder. Combining MR results using pQTL genetic instruments, we finally proposed 8 drug-targeting genes supported by the strongest MR evidence, including gene ACE, BTN3A3, HAPLN4, MAPK3 and NEK4 for schizophrenia, gene NEK4 and HAPLN4 for bipolar disorder, and gene TIE1 for ADHD.

CONCLUSIONS

Our findings with genetic support were more likely to be to succeed in clinical trials. In addition, our study prioritizes approved drug targets for the development of new therapies and provides critical drug reuse opportunities for psychiatric disorders.

Ursodeoxycholic acid administration did not reduce susceptibility to SARS-CoV-2 infection in children

BACKGROUND AND AIMS

A recent study suggested that administration of ursodeoxycholic acid (UDCA) at dosages usually employed clinically may reduce rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. A recent surge of SARS-CoV-2 omicron infection in China allowed study of whether UDCA administration reduced susceptibility to SARS-CoV-2 infection in children with liver disease.

METHODS

Through WeChat groups, a questionnaire was distributed to families (n = 300) in which a child had been admitted to our liver service in the past 5 years. Among the families/households in which someone was infected with SARS-CoV-2, the proportion in which a child taking UDCA was infected was compared with the proportion in which a child not taking UDCA was infected.

RESULTS

Of the 300 questionnaire answers, 280 (93.3%) were valid. SARS-CoV-2 infection was confirmed in 226 families (80.7%): 146 children were taking UDCA (10-20 mg/kg/day) and 80 children were not taking UDCA. SARS-CoV-2 infection was confirmed in 95 children taking UDCA (65.1%) and in 51 children not taking UDCA (63.8%) (p = 0.843); SARS-CoV-2 infection was suspected in 23 children taking UDCA (15.8%) and in 11 children not taking UDCA (13.8%) (p = 0.687).

CONCLUSIONS

These results indicate that UDCA administration does not reduce susceptibility to SARS-CoV-2 infection in children with liver disease.

Expression of the readthrough transcript CiDRE in alveolar macrophages boosts SARS-CoV-2 susceptibility and promotes COVID-19 severity

Lung infection during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via the angiotensin-I-converting enzyme 2 (ACE2) receptor induces a cytokine storm. However, the precise mechanisms involved in severe COVID-19 pneumonia are unknown. Here, we showed that interleukin-10 (IL-10) induced the expression of ACE2 in normal alveolar macrophages, causing them to become vectors for SARS-CoV-2. The inhibition of this system in hamster models attenuated SARS-CoV-2 pathogenicity. Genome-wide association and quantitative trait locus analyses identified a IFNAR2-IL10RB readthrough transcript, COVID-19 infectivity-enhancing dual receptor (CiDRE), which was highly expressed in patients harboring COVID-19 risk variants at the IFNAR2 locus. We showed that CiDRE exerted synergistic effects via the IL-10-ACE2 axis in alveolar macrophages and functioned as a decoy receptor for type I interferons. Collectively, our data show that high IL-10 and CiDRE expression are potential risk factors for severe COVID-19. Thus, IL-10R and CiDRE inhibitors might be useful COVID-19 therapies.