Cis-expression Quantitative Trait Loci Research Articles

Circulating RAC1 contributed to steroid-sensitive nephrotic syndrome: Mendelian randomization, single-cell RNA-sequencing, proteomic, and experimental evidence

Objectives The small GTPase Rac1 (RAC1) has been linked to podocyte disorders and steroid-sensitive nephrotic syndrome (SSNS). The aim of this study was to explore and validate the potential causal association between circulating RAC1 and SSNS. Methods The association between circulating RAC1 and SSNS at both gene expression and proteomic levels was investigated using Mendelian randomization analysis, and further validated by single-cell RNA-sequencing, proteomic analysis, and experimental studies. The genetic instruments comprised cis-expression quantitative trait loci (cis-eQTLs) associated with RAC1 gene expression and protein QTLs correlated with plasma RAC1 protein levels. Causal associations were estimated utilizing the inverse variance weighted and MR-PRESSO methods. Validation of RAC1 expression was conducted through single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with SSNS and healthy controls. Proteomic analysis was performed among patients with minimal change nephrotic syndrome. Experimental validation was conducted using a puromycin aminonucleoside (PAN)-induced nephrosis model. Results Increased expression of RAC1 was associated with a higher risk of SSNS (gene expression level: odds ratio [OR], 1.53; 95% confidence interval [CI], 1.02–2.28; protein level: OR, 1.82; 95% CI, 1.05–3.17). The results of MR-PRESSO were consistent (gene expression level: OR, 1.49; 95% CI, 1.17–1.92; protein level: OR, 1.81; 95% CI, 1.16–2.85). Single-cell RNA sequencing and proteomic analysis confirmed elevated RAC1 expression in patients with SSNS compared to healthy controls. Experimental data further supported increased RAC1 expression in PAN-induced nephropathy. Conclusions Increased expression of RAC1 might be causally associated with SSNS, suggesting that targeting RAC1 might represent a potential therapeutic strategy for SSNS.

Identification of candidate genes for endometrial cancer in multi-omics: a Mendelian randomization analysis

Endometrial cancer is the most common malignant tumor of the uterus, but the underlying genetic mechanisms of EC remain unclear. To identify candidate genes and investigate genetic mechanisms for endometrial cancer, we utilized the summary-data-based Mendelian randomization (SMR) method to investigate causal associations between genetic variants, gene expression, DNA methylation, and endometrial cancer. Three main analyses were conducted utilizing cis-expression and methylation quantitative trait loci (eQTLs and mQTLs) as instrumental variables to examine causal relationships with endometrial cancer, and assessing the causal relationship between DNA methylation and gene expression. Data sources included genetic association data from O'Mara et al. eQTL data from the GTEx database, and mQTL data from McRae et al. Analysis involved the HEIDI test to distinguish pleiotropy, SMR analysis with multiple testing correction, and colocalization analysis to assess associations driven by linkage disequilibrium. Functional enrichment analysis was performed by the Metascape tool. Our study showed that three genes, SNX11, LINC00243, and EVI2A, were identified as causally related to endometrial cancer. SNX11 exhibited a positive causal relationship, while LINC00243 and EVI2A showed negative ones. Furthermore, 24 CpG sites were identified as causally related to endometrial cancer, with cg14424631 (CYP19A1) being the most significant. The study revealed common genes implicated in endometrial cancer, gene expression, and methylation sites, with LINC00243 playing a key role. Colocalization analysis confirmed significant causal relationships between LINC00243, SNX11, and endometrial cancer. Enrichment analysis uncovered pathways like interferon gamma signaling enriched in both endometrial cancer GWAS and e/mQTL. These findings shed light on the molecular mechanisms underlying endometrial cancer development. The study identified candidate genes and DNA methylation loci causally associated with endometrial cancer, which are expected to serve as potential targets for treatment.

Validation of TYK2 and exploration of PRSS36 as drug targets for psoriasis using Mendelian randomization

Psoriasis is a chronic inflammatory skin disorder with multiple causes, including genetic and environmental factors. Despite advances in treatment, there remains a need to identify novel therapeutic targets. A Mendelian randomization (MR) analysis was conducted to identify therapeutic targets for psoriasis. Data on cis-expression quantitative trait loci were obtained from the eQTLGen Consortium (n = 31,684). Summary statistics for psoriasis (outcome) were sourced from the GWAS Catalog with a sample size of 484,598, including 5,427 cases and 479,171 controls. Colocalization analysis was used to assess whether psoriasis risk and gene expression were driven by shared single nucleotide polymorphisms. Drug prediction and molecular docking were utilized to validate the pharmacological value of the drug targets. The MR analysis found that 81 drug targets were significantly associated, and two (TYK2 and PRSS36) were supported by colocalization analysis (PP.H4 > 0.80). Phenome-wide association studies did not show any associations with other traits at the gene level. Biologically, these genes were closely related to immune function. Molecular docking revealed strong binding with drugs and proteins, as supported by available structural data. This study validated TYK2 as a drug target for psoriasis, in line with its existing clinical use, including the development of decucravacitinib. PRSS36 is a potential novel target requiring further investigation.

Causal relationship between novel antidiabetic drugs and ischemic stroke: a drug-targeted Mendelian randomization study.

The escalating global economic burden of ischemic stroke poses a significant public health challenge amid global aging trends. The broad therapeutic efficacy of new antidiabetic drugs may offer new options in the prevention and treatment of ischemic stroke. Consistent conclusions regarding the relationship between novel antidiabetic agents and the risk of ischemic stroke remain elusive, and the causal relationship deserves further investigation. Three novel antidiabetic drug targets were selected, and cis-expression quantitative trait loci (cis-eQTL) were screened as instrumental variables. Genetic association data for ischemic stroke were obtained from the Genome-wide Association Study (GWAS) database. Mendelian randomization (MR) analysis, facilitated by R software, calculated MR estimates for each single nucleotide polymorphism (SNP), and meta-analysis was performed using five methods. To ensure robustness, sensitivity analyses, heterogeneity analyses, horizontal pleiotropy analyses, and co-localization analyses were conducted for significant MR associations. Three eQTLs for antidiabetic drug genes served as instrumental variables, utilizing a GWAS dataset comprising 34,217 cases and 406,111 controls for ischemic stroke. Genetic variants in glucagon-like peptide-1 receptor agonists (GLP-1 RA) targets exhibited a positive correlation with ischemic stroke risk (OR 1.06, 95% CI 1.04-1.08, P = 0.000), while genetic variation in dipeptidyl peptidase 4 inhibitors (DPP-4i) targets showed a negative association with ischemic stroke risk (OR 0.93, 95% CI 0.89-0.97, P = 0.003). Sensitivity analyses supported robust conclusions, revealing no heterogeneity or horizontal pleiotropy. This study found that GLP-1 RA and DPP-4i were associated with an increased risk of ischemic stroke by MR analysis. Although sensitivity analyses provide support for this result, it contradicts previous knowledge. Therefore, the results of this study still need to treated with caution. Updated and more in-depth GWAS data and high-quality real-world data are expected to validate the results.

Genetic analysis from multiple cohorts implies causality between 2200 druggable genes, telomere length, and leukemia

BackgroundClinical therapeutic targets for leukemia remain to be identified and the causality between leukemia and telomere length is unclear. MethodsThis work employed cis expression quantitative trait locus (eQTL) for 2,200 druggable genes from the eQTLGen Consortium and genome-wide association studies (GWAS) summary data for telomere length in seven blood cell types from the UK Biobank, Netherlands Cohort as exposures. GWAS data for lymphoid leukemia (LL) and myeloid leukemia (ML) from FinnGen and Lee Lab were used as outcomes for discovery and replication cohorts, respectively. Robust Mendelian randomization (MR) findings were generated from seven MR models and a series of sensitivity analyses. Summary-data-based MR (SMR) analysis and transcriptome-wide association studies (TWAS) were further implemented to verify the association between identified druggable genes and leukemia. Single-cell type expression analysis was employed to identify the specific expression of leukemia casual genes on human bone marrow and peripheral blood immune cells. Multivariable MR analysis, linkage disequilibrium score regression (LDSC), and Bayesian colocalization analysis were performed to further validate the relationship between telomere length and leukemia. Mediation analysis was used to assess the effects of identified druggable genes affecting leukemia via telomere length. Phenome-wide MR (Phe-MR) analysis for assessing the effect of leukemia causal genes and telomere length on 1,403 disease phenotypes. ResultsCombining the results of the meta-analysis for MR estimates from two cohorts, SMR and TWAS analysis, we identified five LL causal genes (TYMP, DSTYK, PPIF, GDF15, FAM20A) and three ML causal genes (LY75, ADA, ABCA2) as promising drug targets for leukemia. Univariable MR analysis showed genetically predicted higher leukocyte telomere length increased the risk of LL (odds ratio [OR] = 2.33, 95 % confidence interval [95 % CI] 1.70–3.18; P = 1.33E-07), and there was no heterogeneity and horizontal pleiotropy. Evidence from the meta-analysis of two cohorts strengthened this finding (OR = 1.88, 95 % CI 1.06–3.05; P = 0.01). Multivariable MR analysis showed the causality between leukocyte telomere length and LL without interference from the other six blood cell telomere length (OR = 2.72, 95 % CI 1.88–3.93; P = 1.23E-07). Evidence from LDSC supported the positive genetic correlation between leukocyte telomere length and LL (rg = 0.309, P = 0.0001). Colocalization analysis revealed that the causality from leukocyte telomere length on LL was driven by the genetic variant rs770526 in the TERT region. The mediation analysis via two-step MR showed that the causal effect from TYMP on LL was partly mediated by leukocyte telomere length, with a mediated proportion of 12 %. ConclusionOur study identified several druggable genes associated with leukemia risk and provided new insights into the etiology and drug development of leukemia. We also found that genetically predicted higher leukocyte telomere length increased LL risk and its potential mechanism of action.

PRCP is a promising drug target for intracranial aneurysm rupture supported via multi-omics analysis

BackgroundCerebral aneurysms are life-threatening cerebrovascular disorders. Currently, there are no effective treatments for preventing disease progression. Mendelian randomisation (MR) is widely used to repurify licensed drugs and identify new therapeutic...

Systematic Druggable Genome-Wide Mendelian Randomization Identifies Therapeutic Targets for Functional Outcome After Ischemic Stroke.

Stroke is a leading cause of death worldwide, with a lack of effective treatments for improving the prognosis. The aim of the present study was to identify novel therapeutic targets for functional outcome after ischemic stroke . Cis-expression quantitative trait loci data for druggable genes were used as instrumental variables. The primary outcome was the modified Rankin Scale score at 3 months after ischemic stroke, evaluated as a dichotomous variable (3-6 versus 0-2) and also as an ordinal variable. Drug target Mendelian randomization, Steiger filtering analysis, and colocalization analysis were performed. Additionally, phenome-wide Mendelian randomization analysis was performed to identify the safety of the drug target genes at the genetic level. Among >2600 druggable genes, genetically predicted expression of 16 genes (ABCC2, ATRAID, BLK, CD93, CHST13, NR1H3, NRBP1, PI3, RIPK4, SEMG1, SLC22A4, SLC22A5, SLCO3A1, TEK, TLR4, and WNT10B) demonstrated the causal associations with ordinal modified Rankin Scale (P<1.892×10-5) or poor functional outcome (modified Rankin Scale 3-6 versus 0-2, P<1.893×10-5). Steiger filtering analysis suggested potential directional stability (P<0.05). Colocalization analysis provided further support for the associations between genetically predicted expression of ABCC2, NRBP1, PI3, and SEMG1 with functional outcome after ischemic stroke. Furthermore, phenome-wide Mendelian randomization revealed additional beneficial indications and few potential safety concerns of therapeutics targeting ABCC2, NRBP1, PI3, and SEMG1, but the robustness of these results was limited by low power. The present study revealed 4 candidate therapeutic targets for improving functional outcome after ischemic stroke, while the underlying mechanisms need further investigation.

Potential drug targets for osteoporosis identified: A Mendelian randomization study

BackgroundOsteoporosis is a prevalent global health condition, primarily affecting the aging population, and several therapies for osteoporosis have been widely used. However, available drugs for osteoporosis are far from satisfactory because they cannot alleviate disease progression. This study aimed to explore potential drug targets for osteoporosis through Mendelian randomization analysis. MethodsUsing cis-expression quantitative trait loci (cis-eQTL) data of druggable genes and two genome-wide association studies (GWAS) datasets related to osteoporosis (UK Biobank and FinnGen cohorts), we employed mendelian randomization (MR) analysis to identify the druggable genes with causal relationships with osteoporosis. Subsequently, a series of follow-up analyses were conducted, such as colocalization analysis, cell-type specificity analysis, and correlation analysis with risk factors. The association between potential drug targets and osteoporosis was validated by qRT-PCR. ResultsSix druggable genes with causal relationships with osteoporosis were identified and successfully replicated, including ACPP, DNASE1L3, IL32, PPOX, ST6GAL1, and TGM3. Cell-type specificity analysis revealed that PPOX and ST6GAL1 were expressed in all cell types in the bone samples, while IL32, ACPP, DNASE1L3, and TGM3 were expressed in specific cell types. The GWAS data showed there were seven risk factors for osteoporosis, including vitamin D deficiency, COPD, physical activity, BMI, MMP-9, ALP and PTH. Furthermore, ACPP was associated with vitamin D deficiency and COPD; DNASE1L3 was linked to physical activity; IL32 correlated with BMI and MMP-9; and ST6GAL1 was related to ALP, physical activity, and MMP-9. Among these risk factors, only MMP-9 had a high genetic correlation with osteoporosis. The results of qRT-PCR demonstrated that IL32 was upregulated while ST6GAL1 was downregulated in peripheral blood of osteoporosis patients. ConclusionOur findings suggested that those six druggable genes offer potential drug targets for osteoporosis and require further clinical investigation, especially IL32 and ST6GAL1.

A phased small interfering RNA-derived pathway mediates lead stress tolerance in maize.

Phased small interfering RNAs (phasiRNAs) are a distinct class of endogenous small interfering RNAs, which regulate plant growth, development and environmental stress response. To determine the effect of phasiRNAs on maize (Zea mays L.) tolerance to lead (Pb) stress, the roots of 305 maize lines under Pb treatment were subjected to generation of individual databases of small RNAs. We identified 55 high-confidence phasiRNAs derived from 13 PHAS genes (genes producing phasiRNAs) in this maize panel, of which 41 derived from nine PHAS loci were negatively correlated with Pb content in the roots. The potential targets of the 41 phasiRNAs were enriched in ion transport and import. Only the expression of PHAS_1 (ZmTAS3j, Trans-Acting Short Interference RNA3) was regulated by its cis-expression quantitative trait locus and thus affected the Pb content in the roots. Using the Nicotiana benthamiana (N. benthamiana) transient expression system, 5'-rapid amplification of cDNA ends, and Arabidopsis heterologously expressed, we verified that ZmTAS3j was cleaved by zma-miR390 and thus generated tasiRNA targeting ARF genes (tasiARFs), and that the 5' and 3' zma-miR390 target sites of ZmTAS3j were both necessary for efficient biosynthesis and functional integrity of tasiARFs. We validated the involvement of the zma-miR390-ZmTAS3j-tasiARF-ZmARF3-ZmHMA3 pathway in Pb accumulation in maize seedlings using genetic, molecular, and cytological methods. Moreover, the increased Pb tolerance in ZmTAS3j-overexpressed lines was likely attributed to the zma-miR390-ZmTAS3j-tasiARF-ZmARF3-SAURs pathway, which elevated indole acetic acid levels and thus reactive oxygen species scavenging capacity in maize roots. Our study reveals the importance of the TAS3-derived tasiRNA pathway in plant adaptation to Pb stress.

Sources of gene expression variation in a globally diverse human cohort.

Genetic variation that influences gene expression and splicing is a key source of phenotypic diversity1-5. Although invaluable, studies investigating these links in humans have been strongly biased towards participants of European ancestries, which constrains generalizability and hinders evolutionary research. Here to address these limitations, we developed MAGE, an open-access RNA sequencing dataset of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project6, spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, which mirrored the variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-expression quantitative trait loci (eQTLs) and cis-splicing QTLs (sQTLs), respectively). We identified more than 15,000 putatively causal eQTLs and more than 16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1,310 eQTLs and 1,657 sQTLs that are largely private to underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations. Moreover, the apparent 'population-specific' effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands our understanding of human gene expression diversity and provides an inclusive resource for studying the evolution and function of human genomes.

Single nucleus RNA-sequencing integrated into risk variant colocalization discovers 17 cell-type-specific abdominal obesity genes for metabolic dysfunction-associated steatotic liver disease

Abdominal obesity increases the risk for non-alcoholic fatty liver disease (NAFLD), now known as metabolic dysfunction-associated steatotic liver disease (MASLD). To elucidate the directional cell-type level biological mechanisms underlying the association between abdominal obesity and MASLD, we integrated adipose and liver single nucleus RNA-sequencing and bulk cis-expression quantitative trait locus (eQTL) data with the UK Biobank genome-wide association study (GWAS) data using colocalization. Then we used colocalized cis-eQTL variants as instrumental variables in Mendelian randomization (MR) analyses, followed by functional validation experiments on the target genes of the cis-eQTL variants. We identified 17 colocalized abdominal obesity GWAS variants, regulating 17 adipose cell-type marker genes. Incorporating these 17 variants into MR discovers a putative tissue-of-origin, cell-type-aware causal effect of abdominal obesity on MASLD consistently with multiple MR methods without significant evidence for pleiotropy or heterogeneity. Single cell data confirm the adipocyte-enriched mean expression of the 17 genes. Our cellular experiments across human adipogenesis identify risk variant -specific epigenetic and transcriptional mechanisms. Knocking down two of the 17 genes, PPP2R5A and SH3PXD2B, shows a marked decrease in adipocyte lipidation and significantly alters adipocyte function and adipogenesis regulator genes, including DGAT2, LPL, ADIPOQ, PPARG, and SREBF1. Furthermore, the 17 genes capture a characteristic MASLD expression signature in subcutaneous adipose tissue. Overall, we discover a significant cell-type level effect of abdominal obesity on MASLD and trace its biological effect to adipogenesis. NIH grants R01HG010505, R01DK132775, and R01HL170604; the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant No. 802825), Academy of Finland (Grants Nos. 333021), the Finnish Foundation for Cardiovascular Research the Sigrid Jusélius Foundation and the Jane and Aatos Erkko Foundation; American Association for the Study of Liver Diseases (AASLD) Advanced Transplant Hepatology award and NIH/NIDDK (P30DK41301) Pilot and Feasibility award; NIH/NIEHS F32 award (F32ES034668); Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2021), the Academy of Finland grant (Contract no. 138006); Academy of Finland (Grant Nos 335443, 314383, 272376 and 266286), Sigrid Jusélius Foundation, Finnish Medical Foundation, Finnish Diabetes Research Foundation, Novo Nordisk Foundation (#NNF20OC0060547, NNF17OC0027232, NNF10OC1013354) and Government Research Funds to Helsinki University Hospital; Orion Research Foundation, Maud Kuistila Foundation, Finish Medical Foundation, and University of Helsinki.

Fine mapping of candidate effector genes for heart rate.

An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.

Genome sequence analyses identify novel risk loci for multiple system atrophy.

Multiple system atrophy (MSA) is an adult-onset, sporadic synucleinopathy characterized by parkinsonism, cerebellar ataxia, and dysautonomia. The genetic architecture of MSA is poorly understood, and treatments are limited to supportive measures. Here, we performed a comprehensive analysis of whole genome sequence data from 888 European-ancestry MSA cases and 7,128 controls to systematically investigate the genetic underpinnings of this understudied neurodegenerative disease. We identified four significantly associated risk loci using a genome-wide association study approach. Transcriptome-wide association analyses prioritized USP38-DT, KCTD7, and lnc-KCTD7-2 as novel susceptibility genes for MSA within these loci, and single-nucleus RNA sequence analysis found that the associated variants acted as cis-expression quantitative trait loci for multiple genes across neuronal and glial cell types. In conclusion, this study highlights the role of genetic determinants in the pathogenesis of MSA, and the publicly available data from this study represent a valuable resource for investigating synucleinopathies.

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

BackgroundIdiopathic 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.MethodsWe 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.ResultsThe 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).ConclusionIL-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.

Identifying potential drug targets for varicose veins through integration of GWAS and eQTL summary data.

Varicose veins (VV) are a common chronic venous disease that is influenced by multiple factors. It affects the quality of life of patients and imposes a huge economic burden on the healthcare system. This study aimed to use integrated analysis methods, including Mendelian randomization analysis, to identify potential pathogenic genes and drug targets for VV treatment. This study conducted Summary-data-based Mendelian Randomization (SMR) analysis and colocalization analysis on data collected from genome-wide association studies and cis-expression quantitative trait loci databases. Only genes with PP.H4 > 0.7 in colocalization were chosen from the significant SMR results. After the above analysis, we screened 12 genes and performed Mendelian Randomization (MR) analysis on them. After sensitivity analysis, we identified four genes with potential causal relationships with VV. Finally, we used transcriptome-wide association studies and The Drug-Gene Interaction Database data to identify and screen the remaining genes and identified four drug targets for the treatment of VV. We identified four genes significantly associated with VV, namely, KRTAP5-AS1 [Odds ratio (OR) = 1.08, 95% Confidence interval (CI): 1.05-1.11, p = 1.42e-10] and PLEKHA5 (OR = 1.13, 95% CI: 1.06-1.20, p = 6.90e-5), CBWD1 (OR = 1.05, 95% CI: 1.01-1.11, p = 1.42e-2) and CRIM1 (OR = 0.87, 95% CI: 0.81-0.95, p = 3.67e-3). Increased expression of three genes, namely, KRTAP5-AS1, PLEKHA5, and CBWD1, was associated with increased risk of the disease, and increased expression of CRIM1 was associated with decreased risk of the disease. These four genes could be targeted for VV therapy. We identified four potential causal proteins for varicose veins with MR. A comprehensive analysis indicated that KRTAP5-AS1, PLEKHA5, CBWD1, and CRIM1 might be potential drug targets for varicose veins.

Effect of smoking cessation medications on intracranial aneurysm risk: A Mendelian randomization study.

We aim to assess the association between smoking behavior and intracranial aneurysms (IAs) and the effect of smoking cessation medications on IAs at the genetic level. Causal effects of four phenotypes: 1) age at initiation of regular smoking, 2) cigarettes smoked per day, 3) smoking cessation, and 4) smoking initiation on IAs, were analyzed using two-sample inverse-variance weighted Mendelian randomization analyses. The effects of genes interacting with the smoking cessation medications were analyzed using cis-expression quantitative trait loci genetic instruments on IAs using summary statistics-based Mendelian randomization analyses. Colocalization analyses were then used to test whether the genes shared causal variants with IAs. The role of confounding phenotypes as potential causative mechanisms of IAs at these gene loci was tested. Cigarettes smoked per day (OR=2.89; 95% CI:1.85-4.51) and smoking initiation on IAs (OR=4.64; 95% CI: 2.64-8.15) were significantly associated with IA risk. However, age at initiation of regular smoking (OR=0.54; 95% CI: 0.10-2.8) and smoking cessation (OR=6.80; 95% CI: 0.01-4812) had no overall effect on IAs. Of 88 genes that interacted with smoking cessation medications, two had a causal effect on IA risk. Genetic variants affecting HYKK levels showed strong evidence of colocalization with IA risk. Higher HYKK levels in the blood were associated with a lower IA risk. Gene target analyses revealed that cigarettes/day could be a main mediator of HYKK's effect on IA risk. This study provides evidence supporting that smoking initiation on IAs and cigarettes/day may increase IA risk. Increased HYKK gene expression may reduce IA risk. This can be explained by the increased number of cigarettes consumed daily. HYKK could also reduce IA risk due to the positive effect of continuous abstinence and varenicline therapy on smoking cessation.

Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions.

Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals.

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

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. 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. 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. 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.

Single-cell multiplex chromatin and RNA interactions in ageing human brain

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1–3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4–7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA–chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an ‘older’ transcriptomic signature and Alzheimer’s disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

Causal effect of gut microbiota on pancreatic cancer: A Mendelian randomization and colocalization study.

The causal relationship between gut microbiota (GM) and pancreatic cancer (PC) remains unclear. This study aimed to investigate the potential genes underlying this mechanism. GM Genome-wide association study (GWAS) summary data were from the MiBioGen consortium. PC GWAS data were from the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalogue. To detect the causal relationship between GM and PC, we implemented three complementary Mendelian randomization (MR) methods: Inverse Variance Weighting (IVW), MR-Egger and Weighted Median, followed by sensitivity analyses. Furthermore, we integrated GM GWAS data with blood cis-expression quantitative trait loci (eQTLs) and blood cis-DNA methylation QTL (mQTLs) using Summary data-based Mendelian Randomization (SMR) methods. This integration aimed to prioritize potential GM-affecting genes through SMR analysis of two molecular traits. PC cis-eQTLs and cis-mQTLs were summarized from The Cancer Genome Atlas (TCGA) data. Through colocalization analysis of GM cis-QTLs and PC cis-QTLs data, we identified common genes that influence both GM and PC. Our study found a causal association between GM and PC, including four protective and five risk-associated GM [Inverse Variance Weighted (IVW), p < 0.05]. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found. The gene SVBP was identified as a GM-affecting gene using SMR analysis of two molecular traits (FDR<0.05, P_HEIDI>0.05). Additionally, two genes, MCM6 and RPS26, were implicated in the interaction between GM and PC based on colocalization analysis (PPH4>0.5). In summary, this study provides evidence for future research aimed at developing suitable therapeutic interventions and disease prevention.