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Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5 . Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC. The genetic basis of primary sclerosing cholangitis has only been partially uncovered. Here, the authors perform a multitrait genome-wide association study to provide insight into the genetic etiology of primary sclerosing cholangitis risk and possible therapeutic drug targets.

In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot residue identification and binding free energy calculation, we performed MD simulations followed by MM-PBSA analysis with three different force fields: CHARMM36, AMBER99SB, and GROMOS54a7. We performed MD simulations with 100 ns for 11 protein–ligand complexes. From the series of MD simulations and MM-PBSA calculations, it is identified that the MM-PBSA estimations using different force fields are weakly correlated to each other. From a comparison between the force fields, AMBER99SB and GROMOS54a7 results are fairly correlated while CHARMM36 results show weak or almost no correlations with the others. Our results suggest that MM-PBSA analysis results strongly depend on force fields and should be interpreted carefully. Additionally, we identified the hot spot residues of Mpro, which play critical roles in ligand binding through energy decomposition analysis. It is identified that the residues of the S4 subsite of the binding site, N142, M165, and R188, contribute strongly to ligand binding. In addition, the terminal residues, D295, R298, and Q299 are identified to have attractive interactions with ligands via electrostatic and solvation energy. We believe that our findings will help facilitate developing the novel inhibitors of SARS-CoV-2.

Smoking may be associated with an increased risk of lung metastasis in cancers of non-lung origin. We leverage survey and electronic health record data from the diverse All of Us Research Program (AoURP) database to investigate whether smoking and smoking-related behaviors increase the risk of lung metastasis in non-lung primary cancers. The results suggest that cigarette use, measured by four continuous variables, does not increase the risk of lung metastasis in seven common cancer types but demonstrates a small significant effect in a cohort including all types of cancer in the database in both univariable and multivariable analyses. An increased odds ratio of electronic smoke use in patients with lung metastasis was seen in multivariable analyses of the all cancer (OR = 1.29, 95% CI = 1.04–1.59, P  = 0.02) and liver cancer (OR = 1.57, 95% CI = 1.06–2.28, P  = 0.02) groups. After adjusting for estimated cigarette pack years in the multivariable model, the result remained significant for liver cancer (OR = 1.60, 95% CI = 1.02–2.47, P  = 0.04) but not the all cancer cohort. These results warrant further inquiry and suggest that smoking and e-cigarettes may be associated with lung metastasis risk in patients with non-lung tumors.

The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (r g ) and SNP heritability (h 2 ) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (r g  = − 0.41, h 2  = 0.10, p = 1.33 × 10 –16 ), increased fluid intelligence scores (r g  = − 0.25, h 2  = 0.22, p = 4.54 × 10 –8 ), and the age at which full time education was completed (r g  = − 0.45, h 2  = 0.11, p = 1.24 × 10 –20 ) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (r g  = 0.20, h 2  = 0.25, p = 2.61 × 10 –9 ). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.

The COVID-19 pandemic has produced broad clinical manifestations, from asymptomatic infection to hospitalization and death. Despite progress from genomic and clinical epidemiology research, risk factors for developing severe COVID-19 are incompletely understood and identification of modifiable risk factors is desperately needed. We conducted linkage disequilibrium score regression (LDSR) analysis to estimate cross-trait genetic correlation between COVID-19 severity and various polygenic phenotypes. To attenuate the genetic contribution of smoking and BMI, we further conducted sensitivity analyses by pruning genomic regions associated with smoking/BMI and repeating LDSR analyses. We identified robust positive associations between the genetic architecture of severe COVID-19 and both BMI and smoking. We observed strong positive genetic correlation (rg) with diabetes (rg = 0.25) and shortness of breath walking on level ground (rg = 0.28) and novel protective associations with vitamin E (rg = − 0.53), calcium (rg = − 0.33), retinol (rg = − 0.59), Apolipoprotein A (rg = − 0.13), and HDL (rg = − 0.17), but no association with vitamin D (rg = − 0.02). Removing genomic regions associated with smoking and BMI generally attenuated the associations, but the associations with nutrient biomarkers persisted. This study provides a comprehensive assessment of the shared genetic architecture of COVID-19 severity and numerous clinical/physiologic parameters. Associations with blood and plasma-derived traits identified biomarkers for Mendelian randomization studies to explore causality and nominates therapeutic targets for clinical evaluation.

This study examined individual-level determinants of self-reported changes in healthy (diet and physical activity) and addictive (alcohol use, smoking, and vaping) lifestyle behaviors during the initial COVID-19 lockdown period in the USA. A national online survey was administered between May and June 2020 that targeted a representative U.S. sample and yielded data from 1276 respondents, including 58% male and 50% racial/ethnic minorities. We used univariate and multivariable linear regression models to examine the associations of sociodemographic, mental health, and behavioral determinants with self-reported changes in lifestyle behaviors. Some study participants reported increases in healthy lifestyle behaviors since the pandemic (i.e., 36% increased healthy eating behaviors, and 33% increased physical activity). However, they also reported increases in addictive lifestyle behaviors including alcohol use (40%), tobacco use (41%), and vaping (46%). With regard to individual-level determinants, individuals who reported adhering to social distancing guidelines were also more likely to report increases in healthy lifestyle behaviors (β = 0.12, 95% CI 0.04 to 0.21). Conversely, women (β = −0.37, 95% CI −0.62 to −0.12), and unemployed individuals (β = −0.33, 95% CI −0.64 to −0.02) were less likely to report increases in healthy lifestyle behaviors. In addition, individuals reporting anxiety were more likely to report increases in addictive behaviors (β = 0.26, 95% CI 0.09 to 0.43). Taken together, these findings suggest that women and unemployed individuals may benefit from interventions targeting diet and physical activity, and that individuals reporting anxiety may benefit from interventions targeting smoking and alcohol cessation to address lifestyle changes during the pandemic.

Inflammatory bowel disease (IBD) is an autoimmune disease (AD) characterized by chronic, relapsing intestinal inflammation. Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multisystem involvement and overactivation of both innate and adaptive immunity. The extra intestinal manifestations (EIMs) that commonly occur in IBD include many of the organ sites that are affected by SLE. ADs are often comorbid with one another and may have shared underlying genetic features and architectures contributing to their pathogenesis and disease course. We performed both epidemiological and post-genome wide association study (GWAS) analyses to investigate the shared genetic features between IBD and systemic lupus erythematosus (SLE). Specifically, we performed epidemiological association analysis in the All of Us Research Program (AoURP) and genome-wide/local genetic correlation analysis and cell-type specific SNP heritability enrichment analysis using previously published summary level data. A significant epidemiologic association exists between IBD and SLE with an adjusted odds ratio (aOR) of 2.94 (95% CI: 2.45–3.53; P  < 0.001) in a multivariable model accounting for confounders in the AoURP data. Genome-wide genetic correlation analysis in previously published summary level data demonstrated a significant genetic correlation between IBD, CD, and UC with SLE, and local genetic correlation analysis demonstrated several positive and significant correlations in local genomic regions harboring disease variants in genes common to both SLE and IBD etiology, including variants in ELF1 , CD226 , JAZF1 , WDFY4 , and JAK2 . Cell-type SNP heritability enrichment analysis identified both overlapping and distinct functional categories contributing to SNP heritability across IBD phenotypes. Notably, IBD-related phenotypes demonstrated significant enrichment in T-lymphocyte functional groups while SLE signal appeared in distinct categories, such as B-lymphocytes (along with CD). Gene-level collapsing analysis of rare variants in the United Kingdom BioBank (UKBB) identified overlapping nominally-significant genes between SLE and IBD, CD, and UC. By leveraging several post-GWAS methods, the present study identifies shared genetic features between IBD and SLE, highlighting similarities and differences in the genetic features that contribute to the pathogenesis of each disease.

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis -regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function. Multiple genetic loci are associated with lung cancer risk, but the underlying genetic mechanisms remain poorly understood. Here, the authors perform single-cell RNA-seq and ATAC-seq analyses of lung cells from ever- and never-smokers; they report candidate cis-regulatory elements that colocalise with candidate causal variants in lung cancer risk loci and potential susceptibility genes.

Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits. Lung cancer is the leading cause of cancer mortality, despite declining smoking rates. Gorman et al. report multi-ancestry GWAS meta-analyses of lung cancer providing insights into smoking-independent genetic predisposition to the disease.

Background Acute myeloid leukemia (AML) is a highly aggressive cancer with a 5-year survival rate of less than 35%. It is characterized by significant drug resistance and abnormal energy metabolism. Mitochondrial dynamics and metabolism are crucial for AML cell survival. Mitochondrial fusion protein optic atrophy (OPA)1 is upregulated in AML patients with adverse mutations and correlates with poor prognosis. Method This study investigated targeting OPA1 with TMQ0153, a tetrahydrobenzimidazole derivative, to disrupt mitochondrial metabolism and dynamics as a novel therapeutic approach to overcome treatment resistance. Effects of TMQ0153 treatment on OPA1 and mitofusin (MFN)2 protein levels, mitochondrial morphology, and function in AML cells. In this study, we examined reactive oxygen species (ROS) production, oxidative phosphorylation (OXPHOS) inhibition, mitochondrial membrane potential (MMP) depolarization, and apoptosis. Additionally, metabolic profiling was conducted to analyze changes in metabolic pathways. Results TMQ0153 treatment significantly reduced OPA1 and mitofusin (MFN)2 protein levels and disrupted the mitochondrial morphology and function in AML cells. This increases ROS production and inhibits OXPHOS, MMP depolarization, and caspase-dependent apoptosis. Metabolic reprogramming was observed, shifting from mitochondrial respiration to glycolysis and impaired respiratory chain activity. Profiling revealed reduced overall metabolism along with changes in the glutathione (GSH)/oxidized glutathione (GSSG) and NAD⁺/NADH redox ratios. TMQ0153 treatment reduces tumor volume and weight in MV4-11 xenografts in vivo. Combination therapies with TMQ0153 and other AML drugs significantly reduced the leukemic burden and prolonged survival in NOD scid gamma (NSG) mice xenografted with U937-luc and MOLM-14-luc cells. Conclusion TMQ0153 targets mitochondrial dynamics by inhibiting OPA1, inducing metabolic reprogramming, and triggering apoptosis in AML cells. It enhances the efficacy of existing AML therapies and provides a promising combination treatment approach that exploits mitochondrial vulnerability and metabolic reprogramming to improve treatment outcomes in AML. Graphical Abstract