Combining evidence from Mendelian randomization and colocalization: Review and comparison of approaches

The effect of histo-blood group ABO system transferase (BGAT) on pregnancy related outcomes：A Mendelian randomization study

Protein level of Histo-Blood Group ABO System Transferase (BGAT) has been reported to be associated with cardiometabolic diseases. But its effect on pregnancy related outcomes still remains unclear. Here we conducted a two-sample Mendelian randomization (MR) study to ascertain the putative causal roles of protein levels of BGAT in pregnancy related outcomes. Cis-acting protein quantitative trait loci (pQTLs) robustly associated with protein level of BGAT (P < 5 ×10-8) were used as instruments to proxy the BGAT protein level (N = 35,559, data from deCODE), with two additional pQTL datasets from Fenland (N = 10,708) and INTERVAL (N = 3301) used as validation exposures. Ten pregnancy related diseases and complications were selected as outcomes. We observed that a higher protein level of BGAT showed a putative causal effect on venous complications and haemorrhoids in pregnancy (VH) (odds ratio [OR]=1.19, 95% confidence interval [95% CI]=1.12-1.27, colocalization probability=91%), which was validated by using pQTLs from Fenland and INTERVAL. The Mendelian randomization results further showed effects of the BGAT protein on gestational hypertension (GH) (OR=0.97, 95% CI=0.96-0.99), despite little colocalization evidence to support it. Sensitivity analyses, including proteome-wide Mendelian randomization of the cis-acting BGAT pQTLs, showed little evidence of horizontal pleiotropy. Correctively, our study prioritised BGAT as a putative causal protein for venous complications and haemorrhoids in pregnancy. Future epidemiology and clinical studies are needed to investigate whether BGAT can be considered as a drug target to prevent adverse pregnancy outcomes.

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

BACKGROUND

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 .

METHODS AND RESULTS

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.

CONCLUSIONS

The present study revealed 4 candidate therapeutic targets for improving functional outcome after ischemic stroke, while the underlying mechanisms need further investigation.

Mendelian Randomization and Bayesian Colocalization Analysis Implicate Glycoprotein VI as a Potential Drug Target for Cardioembolic Stroke in South Asian Populations

BACKGROUND

Circulating plasma proteins are clinically useful biomarkers for stroke risk. We examined the causal links between plasma proteins and stroke risk in individuals of South Asian ancestry.

METHODS AND RESULTS

We applied proteome-wide Mendelian randomization and colocalization approaches to understand causality of 2922 plasma proteins on stroke risk in individuals of South Asian ancestry. We obtained genetic instruments (proxies) for plasma proteins from the UK Biobank (N=920). Genome-wide association studies summary data for strokes (N≤11 312) were sourced from GIGASTROKE consortium. Our primary approach involved the Wald ratio or inverse-variance-weighted methods, with statistical significance set at false discovery rate <0.1. Additionally, a Bayesian colocalization approach assessed shared causal variants among proteome, transcriptome, and stroke phenotypes to minimize bias from linkage disequilibrium. We found evidence of a potential causal effect of plasma GP6 (glycoprotein VI) levels on cardioembolic stroke (odds ratio [OR]Wald ratio=2.53 [95% CI, 1.59-4.03]; P=9.2×10-5, false discovery rate=0.059). Generalized Mendelian randomization accounting for correlated single nucleotide polymorphisms (SNPs), with the P value threshold at P<5×10-8 and clumped at r2=0.3, showed consistent direction of effect of GP6 on cardioembolic stroke (ORgeneralized inverse-variance-weighted=2.21 [95% CI, 1.46-3.33]; P=1.6×10-4). Colocalization analysis indicated that plasma GP6 levels colocalize with cardioembolic stroke (posterior probability=91.4%). Multitrait colocalization combining transcriptome, proteome, and cardioembolic stroke showed moderate to strong evidence that these 2 traits colocalize with GP6 expression in the coronary artery and brain tissues (multitrait posterior probability>50%). The potential causal effect of GP6 on cardioembolic stroke was not significant in European populations (ORinverse-variance-weighted=1.08 [95% CI, 0.93-1.26]; P=0.29).

CONCLUSIONS

Our joint Mendelian randomization and colocalization analyses suggest that genetically predicted GP6 is potentially causally associated with cardioembolic stroke risk in individuals of South Asian ancestry. As genetic data on individuals of South Asian ancestry increase, future Mendelian randomization studies with larger sample size for plasma GP6 levels should be implemented to further validate our findings. Additionally, clinical studies will be necessary to verify GP6 as a therapeutic target for cardioembolic stroke in South Asians.

The Causal Effect of Serum Lipid Levels Mediated by Neuregulin 4 on the Risk of Four Atherosclerosis Subtypes: Evidence from Mendelian Randomization Analysis

Background

Neuregulin 4 (NRG4) was known to be associated with serum lipid levels and atherosclerosis. However, it is unknown whether the role of NRG4 in lipid homeostasis is causal to atherosclerosis and whether the effect is beneficial across different atherosclerosis subtypes.

Methods

We investigated the causal role of the levels of serum low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides regulated by NRG4 in subtypes of atherosclerosis through two sample Mendelian randomization. Aggregated genome-wide association study (GWAS) summary data for serum lipid level of 1.32 million individuals with European ancestry were obtained from the Global Lipids Genetics Consortium. GWAS summary data for four atherosclerosis subtypes (peripheral, coronary, cerebral and the other atherosclerosis) were obtained from FinnGen Consortium. Generalized inverse-variance-weighted Mendelian randomization and several sensitivity analyses were used to obtain the causal estimates.

Results

A 1-SD genetically elevated LDL-C level mediated by NRG4 was validated to be nominally associated with the risk of peripheral atherosclerosis (log (odds ratio)= 4.14, 95% confidence interval 0.11 to 8.17, P = 0.04), and the other associations were not significant or could not be validated by sensitivity analyses.

Conclusion

LDL-C lowering mediated by NRG4 is likely to prevent peripheral atherosclerosis.

Comprehensive analysis of single-cell transcriptomics and genetic factors reveals the mechanisms and preventive strategies for the progression from pulmonary fibrosis to lung cancer

BACKGROUND

Pulmonary fibrosis (PF) leads to excessive deposition of fibrous connective tissue in the lungs, increasing the risk of lung cancer due to the enhanced activity of fibroblasts (FBs). Fibroblast-mediated collagen fiber deposition creates a tumor-like microenvironment, laying the foundation for tumorigenesis. Clinically, numerous cases of lung cancer induced by pulmonary fibrosis have been observed. In recent years, the study of nucleotide point mutations, which provide more detailed insights than gene expression, has made significant advancements, offering new perspectives for clinical research.

METHODS

We initially employed Mendelian randomization to ascertain that the initial stage of lung cancer induced by PF belongs to small cell lung cancer (SCLC). Subsequently, pulmonary neuroendocrine cells (PNECs) were identified by using pseudo-time series analysis as cell clusters with carcinogenic potential. We categorized FBs into four groups according to their cellular metabolism, and then analyzed the cellular communication between FBs and PNECs, as well as changes in intracellular pathways of PNECs. Additionally, we examined the characteristic genome of FBs which is significantly associated with PF and investigated the impact of FBs on immune cells in the PF microenvironment. Finally, we explored strategies for preventing the progression from PF to lung cancer.

RESULTS

The genetic features of cells with carcinogenic potential in PF tissues were revealed, characterized by upregulation of Achaete-Scute Family BHLH Transcription Factor 1 (ASCL1), Homeobox B2 (HOXB2), Teashirt Zinc Finger Homeobox 2 (TSHZ2), Insulinoma-associated 1 (INSM1), and reduced activity of RE1 Silencing Transcription Factor (REST). FBs characterized by high glycolysis and low tricarboxylic acid (TCA) cycling played a key role in the progression of PF. The microenvironment of PF resembles the tumor microenvironment, providing a conducive immunosuppressive environment for the occurrence of cancer cells. In dendritic cells, rs9265808 is a susceptibility locus for progression from pulmonary fibrosis to lung cancer, mutations at this locus increase the expression of Complement Factor B (CFB), and excessive activation of the complement pathway is a crucial factor leading to lung cancer development in patients with pulmonary fibrosis. Ensuring adequate nutritional supply and physical function is one of the effective measures to prevent progression from pulmonary fibrosis to lung cancer.

CONCLUSION

CFB promotes lung cancer occurrence by inducing the accumulation and polarization of a large number of monocytes/macrophages in the lungs, driving disease progression by reducing the physical fitness of patients with pulmonary fibrosis.

SGLT2 inhibition, blood lipids, and cardiovascular disease: A Mendelian randomization study

AIMS

We aim to investigate the causal effect of blood lipids mediating sodium-glucose cotransporter 2 (SGLT2) inhibition in cardiovascular disease (CVD) using Mendelian randomization (MR).

METHODS AND RESULTS

A two-sample two-step MR study was conducted to evaluate the association of SGLT2 inhibition with CVDs and the mediation effects of blood lipids linking SGLT2 inhibition with CVDs. Genetic instruments for SGLT2 inhibition were identified as genetic variants, which were associated with the expression of the SLC5A2 gene and glycated haemoglobin level (HbA1c). SGLT2 inhibition was associated with reduced risk of heart failure (HF) (OR 0.44 [95% CI 0.32-0.61]; P = 6.0 × 10-7), atrial fibrillation (AF) (0.47 [0.37-0.61]; P = 1.81 × 10-8), coronary artery disease (CAD) (0.47 [0.30-0.73]; P = 7.46 × 10-4), myocardial infarction (MI) (0.30 [0.15-0.61]; P = 7.44 × 10-4), any stroke (AS) (0.28 [0.18-0.42]; P = 1.14 × 10-9), and ischaemic stroke (IS) (0.27 [0.17-0.44]; P = 1.97 × 10-7). Our results indicated that the proportion mediated of the mediating effect of total cholesterol was 1.7% (OR 0.99 [95% CI 0.98, 0.99], P = 0.004), 4.7% (0.96 [0.95, 0.98], P = 0.002), and 2.7% (0.97 [0.95, 0.98], P = 0.002) in the association between SGLT2 inhibition and the risk of HF, CAD, and MI, respectively. For low-density lipoprotein cholesterol, the proportion mediated of the mediating effect was 2.2% for HF (OR 0.98 [95% CI 0.98, 0.99], P = 0.003), 8.6% for CAD (0.93 [0.91, 0.95], P = 5.74 × 10-4), and 5.0% for MI (0.95 [0.94, 0.96], P = 6.97 × 10-4). For non-high-density lipoprotein cholesterol, the proportion mediated of the mediating effect was 3.4% for HF (OR 0.98 [95% CI 0.97, 0.98], P = 4.42 × 10-6), 11.8% for CAD (0.92 [0.90, 0.93], P = 7.23 × 10-8), 5.7% for MI (0.94 [0.92, 0.95], P = 8.17 × 10-7), 1.5% for AS (0.98 [0.98, 0.99], P = 0.001), and 1.4% for IS (0.98 [0.98, 0.99], P = 0.004).

CONCLUSIONS

Our study showed the association of SGLT2 inhibition with the reduced risk of CVDs and blood lipids might mediate this association.

Instrumental variable and colocalization analyses identify endotrophin and HTRA1 as potential therapeutic targets for coronary artery disease

Coronary artery disease (CAD) remains a leading cause of disease burden globally, and there is a persistent need for new therapeutic targets. Instrumental variable (IV) and genetic colocalization analyses can help identify novel therapeutic targets for human disease by nominating causal genes in genome-wide association study (GWAS) loci. We conducted cis-IV analyses for 20,125 genes and 1,746 plasma proteins with CAD using molecular trait quantitative trait loci variant (QTLs) data from three different studies. 19 proteins and 119 genes were significantly associated with CAD risk by IV analyses and demonstrated evidence of genetic colocalization. Notably, our analyses validated well-established targets such as PCSK9 and ANGPTL4 while also identifying HTRA1 and endotrophin (a cleavage product of COL6A3) as proteins whose levels are causally associated with CAD risk. Further experimental studies are needed to confirm the causal role of the genes and proteins identified through our multiomic cis-IV analyses on human disease.

A robust cis-Mendelian randomization method with application to drug target discovery

Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on a single genomic region using only cis-SNPs. For example, using cis-pQTLs for a protein as exposure for a disease opens a cost-effective path for drug target discovery. However, few methods effectively handle pleiotropy and linkage disequilibrium (LD) of cis-SNPs. Here, we propose cisMR-cML, a method based on constrained maximum likelihood, robust to IV assumption violations with strong theoretical support. We further clarify the severe but largely neglected consequences of the current practice of modeling marginal, instead of conditional genetic effects, and only using exposure-associated SNPs in cis-MR analysis. Numerical studies demonstrated our method's superiority over other existing methods. In a drug-target analysis for coronary artery disease (CAD), including a proteome-wide application, we identified three potential drug targets, PCSK9, COLEC11 and FGFR1 for CAD.

The effect of gut microbiome and plasma metabolome on systemic sclerosis: a bidirectional two-sample Mendelian randomization study

Background

Cellular and molecular biology, combined with research on the human microbiome and metabolome, have provided new insights into the pathogenesis of systemic sclerosis (SSc). However, most studies on gut microbiota (GM) and metabolome in SSc are observational studies. The impact of confounding factors and reverse causation leads to different insights. To shed light on this matter, we utilized Mendelian randomization (MR) to determine the causal effect of GM/metabolites on SSc.

Methods

Based on summary-level data from genome-wide association studies, bidirectional Two-sample MR was conducted involving 196 GM, 1400 plasma metabolism, and 9,095 SSc. Inverse Variance Weighting (IVW) was mainly used for effect estimation.

Results

Forward MR analysis found that three GM and two plasma metabolites are causally related to SSc. IVW results showed Victivallaceae (family) (OR, 1.469; 95%CI, 1.099-1.963; p = 0.009) and LachnospiraceaeUCG004 (genus) (OR, 1.548; 95%CI, 1.020-2.349; p = 0.04) were risk factor of SSc. Conversely, Prevotella7 (genus) (OR, 0.759; 95%CI, 0.578-0.997; p = 0.048)was a protective factor of SSc. The results on plasma metabolites indicated that Pregnenediol disulfate (C21H34O8S2) levels (OR, 1.164; 95%CI, 1.006-1.347; p = 0.041)was a risk factor of SSc, while Sphingomyelin (d18:1/19:0, d19:1/18:0) levels (OR, 0.821; 95%CI, 0.677-0.996; p = 0.045)was a protective factor of SSc. Reverse MR analysis did not find causally relationship between SSc and the above GM/plasma metabolites.

Conclusion

Our results revealed the causally effect between GM/plasma metabolites and SSc. These findings provided new insights into the mechanism of SSc. In particular, we demonstrated Prevotella7 was a protective factor of SSc despite its controversial role in SSc in previous researches.

Multi-biobank Mendelian randomization analyses identify opposing pathways in plasma low-density lipoprotein-cholesterol lowering and gallstone disease

Plasma low-density lipoprotein (LDL)-cholesterol is positively associated with coronary artery disease risk while biliary cholesterol promotes gallstone formation. Different plasma LDL-cholesterol lowering pathways may have distinct effects on biliary cholesterol and thereby gallstone disease risk. We conducted a Mendelian randomization (MR) study using data from the UK Biobank (30,547 gallstone disease cases/336,742 controls), FinnGen (34,461 cases/301,383 controls) and Biobank Japan (9,305 cases/168,253 controls). We first performed drug-target MR analyses substantiated by colocalization to investigate the effects of plasma LDL-cholesterol lowering therapies on gallstone disease risk. We then performed clustered MR analyses and pathway analyses to identify distinct mechanisms underlying the association of plasma LDL-cholesterol with gallstone disease risk. For a 1-standard deviation reduction in plasma LDL-cholesterol, genetic mimics of statins were associated with lower gallstone disease risk (odds ratio 0.72 [95% confidence interval 0.62, 0.83]), but genetic mimics of PCSK9 inhibitors and targeting apolipoprotein B were associated with higher risk (1.11 [1.03, 1.19] and 1.23 [1.13, 1.35]). The association for statins was supported by colocalization (posterior probability 98.7%). Clustered MR analyses identified variant clusters showing opposing associations of plasma LDL-cholesterol with gallstone disease risk, with some evidence for ancestry-and sex-specific associations. Among variants lowering plasma LDL-cholesterol, those associated with lower gallstone disease risk were mapped to glycosphingolipid biosynthesis pathway, while those associated with higher risk were mapped to pathways relating to plasma lipoprotein assembly, remodelling, and clearance and ATP-binding cassette transporters. This MR study provides genetic evidence that different plasma LDL-cholesterol lowering pathways have opposing effects on gallstone disease risk.

Integrating plasma proteomics with genome-wide association data to identify novel drug targets for inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic disease that includes Crohn's disease (CD) and ulcerative colitis (UC). Although genome-wide association studies (GWASs) have identified many relevant genetic risk loci, the impact of these loci on protein abundance and their potential utility as clinical therapeutic targets remain uncertain. Therefore, this study aimed to investigate the pathogenesis of IBD and identify effective therapeutic targets through a comprehensive and integrated analysis. We systematically integrated GWAS data related to IBD, UC and CD (N = 25,305) by the study of de Lange KM with the human blood proteome (N = 7213) by the Atherosclerosis Risk in Communities (ARIC) study. Proteome-wide association study (PWAS), mendelian randomisation (MR) and Bayesian colocalisation analysis were used to identify proteins contributing to the risk of IBD. Integrative analysis revealed that genetic variations in IBD, UC and CD affected the abundance of five (ERAP2, RIPK2, TALDO1, CADM2 and RHOC), three (VSIR, HGFAC and CADM2) and two (MST1 and FLRT3) cis-regulated plasma proteins, respectively (P < 0.05). Among the proteins identified via Bayesian colocalisation analysis, CADM2 was found to be an important common protein between IBD and UC. A drug and five druggable target genes were identified from DGIdb after Bayesian colocalisation analysis. Our study's findings from genetic and proteomic approaches have identified compelling proteins that may serve as important leads for future functional studies and potential drug targets for IBD (UC and CD).

CoPheScan: phenome-wide association studies accounting for linkage disequilibrium

Phenome-wide association studies (PheWAS) facilitate the discovery of associations between a single genetic variant with multiple phenotypes. For variants which impact a specific protein, this can help identify additional therapeutic indications or on-target side effects of intervening on that protein. However, PheWAS is restricted by an inability to distinguish confounding due to linkage disequilibrium (LD) from true pleiotropy. Here we describe CoPheScan (Coloc adapted Phenome-wide Scan), a Bayesian approach that enables an intuitive and systematic exploration of causal associations while simultaneously addressing LD confounding. We demonstrate its performance through simulation, showing considerably better control of false positive rates than a conventional approach not accounting for LD. We used CoPheScan to perform PheWAS of protein-truncating variants and fine-mapped variants from disease and pQTL studies, in 2275 disease phenotypes from the UK Biobank. Our results identify the complexity of known pleiotropic genes such as APOE, and suggest a new causal role for TGM3 in skin cancer.

Mechanisms of Hypercoagulability Driving Stroke Risk in Obesity: A Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Obesity is hypothesized to induce a hypercoagulable state that increases stroke risk. The molecular mechanisms underlying this association are largely uncharacterized. We aimed to apply mendelian randomization to identify whether the association of genetically proxied body mass index (BMI) with cardioembolic stroke risk is mediated by changes in levels of circulating coagulation factors.

METHODS

Genetic proxies for BMI and levels of circulating coagulation factors were obtained, respectively, from the Genetic Investigation of ANthropometric Traits consortium (n = 694,649) and deCODE cohort (n = 35,559). Genetic associations with cardioembolic stroke risk were obtained from the GIGASTROKE consortium (10,804 cases and 1,234,804 controls). We performed a two-sample mendelian randomization analysis testing the association of genetically proxied BMI with cardioembolic stroke risk, genetically proxied BMI with levels of coagulation factors, and genetically proxied levels of coagulation factors with cardioembolic stroke risk. These estimates were carried forward to mediation and sensitivity analyses.

RESULTS

A 1-SD increase in genetically proxied BMI associated with increased cardioembolic stroke risk (OR of cardioembolic stroke per 1-SD of BMI 1.20, 95% CI 1.08-1.33, p = 8.65 × 10-4) with similar findings in statistical sensitivity analyses more robust to the inclusion of pleiotropic variants. Genetically proxied BMI was further associated with increased levels of Factor VII, Factor Xa, Factor XI, and Protein S (all p < 5.9 × 10-6). Of these factors, genetically proxied levels of Factor XI were associated with cardioembolic stroke risk (OR of cardioembolic stroke per 1-SD increase in Factor XI levels 1.32, 1.19-1.46, p = 6.18 × 10-8). The mediated effect of genetically proxied BMI through Factor XI accounted for 26% (6%-49%) of the total effect of BMI on cardioembolic stroke.

DISCUSSION

Human genetic data support increased levels of Factor XI as a mechanistic explanation for how obesity increases cardioembolic stroke risk. The clinical relevance of this association warrants further investigation within ongoing clinical trials of Factor XI inhibition.

Lipoprotein(a) and Lung Function Are Associated in Older Adults: Longitudinal and Cross-Sectional Analyses

While numerous studies have confirmed a causal association between lipoprotein(a) [Lp(a)] and cardiovascular diseases, only a few studies have assessed the relationship between Lp(a) and pulmonary health, with inconsistent findings regarding this topic. This study's aim was to examine whether levels of serum Lp(a) are associated with lung function in a dataset of relatively healthy older adults. We used longitudinal data collected at two time points 7.4 ± 1.5 years apart from 679 participants (52% women, 68 [65-71] years old) from the Berlin Aging Study II (BASE-II). Multiple linear regression models adjusting for covariates were applied to examine the association between Lp(a) and lung function. The forced expiratory volume in one second (FEV1) and the forced vital capacity (FVC) were higher in both men and women with higher Lp(a) levels. However, since this association between lung function parameters and Lp(a) was not supported by Mendelian randomization analyses using recent genome-wide association study data, these relationships should be investigated in future work, as the observed differences are, in part, considerable and potentially clinically relevant.

Causal associations between chronic heart failure and the cerebral cortex: results from Mendelian randomization study and integrated bioinformatics analysis

Background

Chronic heart failure (CHF) patients exhibit alterations in cerebral cortical structure and cognitive function. However, the mechanisms by which CHF affects cortical structure and functional regions remain unknown. This study aims to investigate potential causal relationship between CHF and cerebral cortical structure through Mendelian randomization (MR).

Methods

The research utilized genome-wide association studies (GWAS) to explore the causal association between CHF and cerebral cortical structure. The results were primarily analyzed using the inverse-variance weighted (IVW). The reliability of the data was verified through horizontal pleiotropy and heterogeneity analysis by MR-Egger intercept test and Cochran's Q-test, respectively. Replication analysis was conducted in the Integrative Epidemiology Unit (IEU) OpenGWAS project for further validation. In addition, we collected mediator genes that mediate causality to reveal potential mechanisms. Integrated bioinformatics analysis was conducted using the Open Target Genetics platform, the STRING database, and Cytoscape software.

Results

The IVW results did not reveal any significant causal association between genetically predicted CHF and the overall structure of the cerebral cortex or the surface area (SA) of the 34 functional regions of the cerebral cortex (P > 0.05). However, the results revealed that CHF increased the thickness (TH) of pars opercularis (IVW: β = 0.015, 95% CI: 0.005-0.025, P = 3.16E-03). Replication analysis supported the causal association between CHF and pars opercularis TH (IVW: β = 0.02, 95% CI: 0.010-0.033, P = 1.84E-04). We examined the degree centrality values of the top 10 mediator genes, namely CDKN1A, CELSR2, NME5, SURF4, PSMA5, TSC1, RPL7A, SURF6, PRDX3, and FTO.

Conclusion

Genetic evidence indicates a positive correlation between CHF and pars opercularis TH.

Gene associations of lipid traits, lipid-lowering drug-target genes and endometriosis

RESEARCH QUESTION

Does the observed correlation between dyslipidaemia and endometriosis indicate a bidirectional causal association?

DESIGN

Bidirectional Mendelian randomization was used to investigate the causal association between lipid traits and endometriosis. Drug-target Mendelian randomization was used to explore potential drug-target genes for managing endometriosis. In cases where lipid-mediated effects via specific drug targets were significant, aggregate analyses, such as summary-data-based Mendelian randomization and colocalization methods, were introduced to validate the outcomes. Mediation analyses supplemented these evaluations.

RESULTS

The bidirectional Mendelian randomization results suggested that genetically predicted triglyceride (OR 1.15, 95% CI 1.08-1.23), high-density lipoprotein cholesterol (OR 0.87, 95% CI 0.81-0.94), low-density lipoprotein cholesterol (OR 1.20, 95% CI 1.06-1.34) and apolipoprotein A (OR 0.90, 95% CI 0.83-0.96) concentrations were causally associated with endometriosis. Reverse Mendelian randomization results revealed that genetically proxied endometriosis was causally associated with triglyceride concentration (OR 1.02, 95% CI 1.01-1.02). In drug-target Mendelian randomization, genetic mimicry in proprotein convertase subtilisin/kexin type 9 (PCSK9) (OR 1.40, 95% CI 1.13-1.72), apolipoprotein B (APOB) (OR 1.49, 95% CI 1.21-1.86) and angiopoietin-related protein 3 (ANGPTL3) (OR 1.57, 95% CI 1.14-2.16) was significantly associated with the risk of endometriosis stages 1-2.

CONCLUSION

There is a potential bidirectional causal association between endometriosis and dyslipidaemia. Genetic mimicry of PCSK9, APOB and ANGPTL3 is associated with the risk of early-stage endometriosis. The development of lipid-lowering drugs to treat endometriosis is of potential clinical interest.

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.

Impaired GK-GKRP interaction rather than direct GK activation worsens lipid profiles and contributes to long-term complications: a Mendelian randomization study

BACKGROUND

Glucokinase (GK) plays a key role in glucose metabolism. In the liver, GK is regulated by GK regulatory protein (GKRP) with nuclear sequestration at low plasma glucose level. Some GK activators (GKAs) disrupt GK-GKRP interaction which increases hepatic cytoplasmic GK level. Excess hepatic GK activity may exceed the capacity of glycogen synthesis with excess triglyceride formation. It remains uncertain whether hypertriglyceridemia associated with some GKAs in previous clinical trials was due to direct GK activation or impaired GK-GKRP interaction.

METHODS

Using publicly available genome-wide association study summary statistics, we selected independent genetic variants of GCKR and GCK associated with fasting plasma glucose (FPG) as instrumental variables, to mimic the effects of impaired GK-GKRP interaction and direct GK activation, respectively. We applied two-sample Mendelian Randomization (MR) framework to assess their causal associations with lipid-related traits, risks of metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular diseases. We verified these findings in one-sample MR analysis using individual-level statistics from the Hong Kong Diabetes Register (HKDR).

RESULTS

Genetically-proxied impaired GK-GKRP interaction increased plasma triglycerides, low-density lipoprotein cholesterol and apolipoprotein B levels with increased odds ratio (OR) of 14.6 (95% CI 4.57-46.4) per 1 mmol/L lower FPG for MASLD and OR of 2.92 (95% CI 1.78-4.81) for coronary artery disease (CAD). Genetically-proxied GK activation was associated with decreased risk of CAD (OR 0.69, 95% CI 0.54-0.88) and not with dyslipidemia. One-sample MR validation in HKDR showed consistent results.

CONCLUSIONS

Impaired GK-GKRP interaction, rather than direct GK activation, may worsen lipid profiles and increase risks of MASLD and CAD. Development of future GKAs should avoid interfering with GK-GKRP interaction.

Genetics of causal relationships between circulating inflammatory proteins and postherpetic neuralgia: a bidirectional Mendelian randomization study

Objective

According to data from several observational studies, there is a strong association between circulating inflammatory cytokines and postherpetic neuralgia (PHN), but it is not clear whether this association is causal or confounding; therefore, the main aim of the present study was to analyze whether circulating inflammatory proteins have a bidirectional relationship with PHN at the genetic inheritance level using a Mendelian randomization (MR) study.

Methods

The Genome-Wide Association Study (GWAS) database was used for our analysis. We gathered data on inflammation-related genetic variation from three GWASs of human cytokines. These proteins included 91 circulating inflammatory proteins, tumor necrosis factor-alpha (TNF-α), macrophage inflammatory protein 1b (MIP-1b), and CXC chemokine 13 (CXCL13). The PHN dataset was obtained from the FinnGen biobank analysis round 5, and consisted of 1,413 cases and 275,212 controls. We conducted a two-sample bidirectional MR study using the TwoSampleMR and MRPRESSO R packages (version R.4.3.1). Our main analytical method was inverse variance weighting (IVW), and we performed sensitivity analyses to assess heterogeneity and pleiotropy, as well as the potential influence of individual SNPs, to validate our findings.

Results

According to our forward analysis, five circulating inflammatory proteins were causally associated with the development of PHN: interleukin (IL)-18 was positively associated with PHN, and IL-13, fibroblast growth factor 19 (FGF-19), MIP-1b, and stem cell growth factor (SCF) showed reverse causality with PHN. Conversely, we found that PHN was closely associated with 12 inflammatory cytokines, but no significant correlation was found among the other inflammatory factors. Among them, only IL-18 had a bidirectional causal relationship with PHN.

Conclusion

Our research advances the current understanding of the role of certain inflammatory biomarker pathways in the development of PHN. Additional verification is required to evaluate the viability of these proteins as targeted inflammatory factors for PHN-based treatments.

Genetic-informed proteome-wide scan reveals potential causal plasma proteins for idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a lethal lung disease for which there are no reliable biomarkers or disease-modifying drugs. Here, we integrated human genomics and proteomics to investigate the causal associations between 2769 plasma proteins and IPF. Our Mendelian randomisation analysis identified nine proteins associated with IPF, of which three (FUT3, ADAM15 and USP28) were colocalised. ADAM15 emerged as the top candidate, supported by expression quantitative trait locus analysis in both blood and lung tissue. These findings provide novel insights into the aetiology of IPF and offer translational opportunities in response to the clinical challenges of this devastating disease.

Integrating plasma protein-centric multi-omics to identify potential therapeutic targets for pancreatic cancer

BACKGROUND

Deciphering the role of plasma proteins in pancreatic cancer (PC) susceptibility can aid in identifying novel targets for diagnosis and treatment.

METHODS

We examined the relationship between genetically determined levels of plasma proteins and PC through a systemic proteome-wide Mendelian randomization (MR) analysis utilizing cis-pQTLs from multiple centers. Rigorous sensitivity analyses, colocalization, reverse MR, replications with varying instrumental variable selections and additional datasets, as well as subsequent meta-analysis, were utilized to confirm the robustness of significant findings. The causative effect of corresponding protein-coding genes' expression and their expression pattern in single-cell types were then investigated. Enrichment analysis, between-protein interaction and causation, knock-out mice models, and mediation analysis with established PC risk factors were applied to indicate the pathogenetic pathways. These candidate targets were ultimately prioritized upon druggability and potential side effects predicted by a phenome-wide MR.

RESULTS

Twenty-one PC-related circulating proteins were identified in the exploratory phase with no evidence for horizontal pleiotropy or reverse causation. Of these, 11 were confirmed in a meta-analysis integrating external validations. The causality at a transcription level was repeated for neutrophil elastase, hydroxyacylglutathione hydrolase, lipase member N, protein disulfide-isomerase A5, xyloside xylosyltransferase 1. The carbohydrate sulfotransferase 11 and histo-blood group ABO system transferase exhibited high-support genetic colocalization evidence and were found to affect PC carcinogenesis partially through modulating body mass index and type 2 diabetes, respectively. Approved drugs have been established for eight candidate targets, which could potentially be repurposed for PC therapies. The phenome-wide investigation revealed 12 proteins associated with 51 non-PC traits, and interference on protein disulfide-isomerase A5 and cystatin-D would increase the risk of other malignancies.

CONCLUSIONS

By employing comprehensive methodologies, this study demonstrated a genetic predisposition linking 21 circulating proteins to PC risk. Our findings shed new light on the PC etiology and highlighted potential targets as priorities for future efforts in early diagnosis and therapeutic strategies of PC.

C-reactive protein and cognitive impairment: A bidirectional Mendelian randomization study

OBJECTIVES

While C-reactive protein (CRP) has been solidly linked as a risk factor for cognitive impairment, observational research alone cannot definitively demonstrate a causal relationship. This study therefore sought to determine whether there was an association between CRP and the development of cognitive impairment.

METHODS

This study employed bidirectional Mendelian randomization (MR) to investigate the genetic association between CRP and cognitive impairment. genome-wide association studies (GWAS) summary statistics for both were sourced from IEU Open GWAS or prior reports. Cognitive GWAS's used were on tests designed to assess cognitive performance, fluid intelligence, prospective memory, and reaction time. The MR analysis applied several methods, including inverse variance-weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode approaches, then use of MR sensitivity analyses to interrogate findings.

RESULTS

Forward MR analysis showed that genetically proxied CRP was associated with prospective memory (P = 0.009), whereas there is little evidence to support an association between CRP and other cognitive tests. Reverse MR analysis indicated a potential association between genetic proxy cognitive performance (P = 0.002) and fluid intelligence score (P = 0.019) with CRP levels. For genetically proxied CRP on prospective memory, the level of pleiotropy (P > 0.05) and no genetic variant heterogeneity (P > 0.05) made bias unlikely, and leave-one-out tests also confirmed robust associations.

CONCLUSIONS

The effect of genetically proxied CRP on prospective memory, with little evidence on other cognitive tests. The reverse MR shows some evidence of genetically proxied cognition (cognitive performance and fluid intelligence) on CRP levels.

Multiple myeloma, IL6, and risk of schizophrenia: A Mendelian randomization, transcriptome, and Bayesian colocalization study

Numerous clinical studies speculated the association between multiple myeloma (MM) and inflammatory diseases; however, there is limited validation of these claims via establishing a causal relationship and revealing the underlying mechanism. This exploratory study employed bidirectional Mendelian randomization (MR) analysis to investigate the causal relationships between MM and inflammatory diseases, including atherosclerosis, asthma, ankylosing spondylitis, Alzheimer's disease (AD), Parkinson's disease (PD), sarcoidosis, inflammatory bowel disease, nonalcoholic fatty liver disease, type II diabetes, and schizophrenia (SZ). Transcriptomic and genome-wide Bayesian colocalization analyses were further applied to reveal the underlying mechanism. A significant and previously unrecognized positive association was identified between genetic predisposition to MM and the risk of SZ. Two independent case reports showed that treatment-resistant psychosis is due to underlying MM and is resolved by treating MM. From our MR analyses, various statistical methods confirmed this association without detecting heterogeneity or pleiotropy effects. Transcriptomic analysis revealed shared inflammation-relevant pathways in MM and SZ patients, suggesting inflammation as a potential pathophysiological mediator of MM's causal effect on SZ. Bayesian colocalization analysis identified rs9273086, which maps to the protein-coding region of HLA-DRB1, as a common risk variant for both MM and SZ. Polymorphism of the HLA-DRB1 allele has been implicated in AD and PD, further highlighting the impact of our results. Additionally, we confirmed that interleukin-6 (IL-6) is a risk factor for SZ through secondary MR, reinforcing the role of neuroinflammation in SZ etiology. Overall, our findings showed that genetic predisposition to MM, HLA-DRB1 polymorphism, and enhanced IL-6 signaling are associated with the increased risk of SZ, providing evidence for a causal role for neuroinflammation in SZ etiology.

Mendelian randomization: causal inference leveraging genetic data

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

From GWASs toward Mechanistic Understanding with Case Studies in Dermatogenetics

Many human skin diseases result from the complex interplay of genetic and environmental mechanisms that are largely unknown. GWASs have yielded insight into the genetic aspect of complex disease by highlighting regions of the genome or specific genetic variants associated with disease. Leveraging this information to identify causal genes and cell types will provide insight into fundamental biology, inform diagnostics, and aid drug discovery. However, the etiological mechanisms from genetic variant to disease are still unestablished in most cases. There now exists an unprecedented wealth of data and computational methods for variant interpretation in a functional context. It can be challenging to decide where to start owing to a lack of consensus on the best way to identify causal genetic mechanisms. This article highlights 3 key aspects of genetic variant interpretation: prioritizing causal genes, cell types, and pathways. We provide a practical overview of the main methods and datasets, giving examples from recent atopic dermatitis studies to provide a blueprint for variant interpretation. A collection of resources, including brief description and links to the packages and web tools, is provided for researchers looking to start in silico follow-up genetic analysis of associated genetic variants.

Identifying novel proteins for migraine by integrating proteomes from blood and CSF with genome-wide association data

BACKGROUND

Proteome-wide Mendelian randomization studies have been increasingly utilized to identify potential drug targets for diseases. We aimed to identify potential therapeutic targets for migraine and its subtypes through the application of Mendelian randomization and co-localization analysis methods.

METHODS

We utilized cis-protein quantitative trait loci data for 1378 plasma proteins available from two studies with 7213 individuals and 35,559 individuals, respectively. Summary data for migraine and its subtypes were obtained from a genetic study involving up to 1,339,303 individuals. Proteins that passed both the discovery and validation Mendelian randomization analysis, sensitivity analysis, heterogeneity test, and pleiotropy test, were associated with ≥2 outcomes, and received strong support from co-localization analysis (PP.H4.abf ≥0.80) and were classified as tier 1 proteins.

RESULTS

We identified three tier 1 proteins (LRP11, ITIH1, and ADGRF5), whose genes have not been previously identified as causal genes for migraine in genetic studies. LRP11 was significantly associated with the risk of any migraine (OR [odds ratio] = 0.968, 95% CI [confidence interval] = 0.955-0.981, p = 1.27 × 10-6) and significantly/suggestively associated with three migraine subtypes. ITIH1 was significantly associated with the risk of any migraine (OR = 1.044, 95% CI = 1.024-1.065, p = 1.08 × 10-5) and migraine with visual disturbances. ADGRF5 was significantly associated with the risk of any migraine (OR = 0.964, 95% CI = 0.946-0.982, p = 8.74 × 10-5) and suggestively associated with migraine with aura. The effects of LRP11 and ADGRF5 were further replicated using cerebrospinal fluid protein data. Apart from ADGRF5, there was no evidence of potential adverse consequences when modulating the plasma levels. We also identified another four proteins (PLCG1, ARHGAP25, CHGA, and MANBA) with no potential adverse consequences when modulating the plasma levels, and their genes were not reported by previous genetic studies.

CONCLUSIONS

We found compelling evidence for two proteins and suggestive evidence for four proteins that could be promising targets for migraine treatment without significant adverse consequences. The corresponding genes were not reported in previous genetic studies. Future studies are needed to confirm the causal role of these proteins and explore the underlying mechanisms.

Effects of antidiabetic agents on platelet characteristics with implications in Alzheimer's disease: Mendelian randomization and colocalization study

Background

Observational studies have found a potential link between the use of thiazolidinediones (TZDs) and a lower risk of Alzheimer's disease (AD) development. Platelets were the great source of amyloid-β (Aβ) and involved in the development of AD. This study aimed to assess the correlation between antidiabetic agents and platelet characteristics, hoping to provide a potential mechanism of TZDs neuroprotection in AD.

Method

Drug-targeted Mendelian randomization (MR) was performed to systematically illustrate the long-term effects of antidiabetic agents on platelet characteristics. Four antidiabetic agent targets were considered. Positive control analysis for type 2 diabetes (T2D) was conducted to validate the selection of instrumental variables (IVs). Colocalization analysis was used to further strengthen the robustness of the results.

Result

Positive control analysis showed an association of four antidiabetic agents with lower risk of T2D, which was consistent with their mechanisms of action and previous evidence from clinical trials. Genetically proxied TZDs were associated with lower platelet count (β[IRNT] = -0.410 [95 % CI -0.533 to -0.288], P = 5.32E-11) and a lower plateletcrit (β[IRNT] = -0.344 [95 % CI -0.481 to -0.206], P = 1.04E-6). Colocalization suggested the posterior probability of hypothesis 4 (PPH4) > 0.8, which further strengthened the MR results.

Conclusion

Genetically proxied TZDs were causally associated with lower platelet characteristics, particularly platelet count and plateletcrit, providing insight into the involvement of platelet-related pathways in the neuroprotection of TZDs against AD. Future studies are warranted to reveal the underlying molecular mechanism of TZDs' neuroprotective effects through platelet pathways.

HMG-CoA reductase is a potential therapeutic target for migraine: a mendelian randomization study

Statins are thought to have positive effects on migraine but existing data are inconclusive. We aimed to evaluate the causal effect of such drugs on migraines using Mendelian randomization. We used four types of genetic instruments as proxies for HMG-CoA reductase inhibition. We included the expression quantitative trait loci of the HMG-CoA reductase gene and genetic variation within or near the HMG-CoA reductase gene region. Variants were associated with low-density lipoprotein cholesterol, apolipoprotein B, and total cholesterol. Genome-wide association study summary data for the three lipids were obtained from the UK Biobank. Comparable data for migraine were obtained from the International Headache Genetic Consortium and the FinnGen Consortium. Inverse variance weighting method was used for the primary analysis. Additional analyses included pleiotropic robust methods, colocalization, and meta-analysis. Genetically determined high expression of HMG-CoA reductase was associated with an increased risk of migraines (OR = 1.55, 95% CI 1.30-1.84, P = 6.87 × 10-7). Similarly, three genetically determined HMG-CoA reductase-mediated lipids were associated with an increased risk of migraine. These conclusions were consistent across meta-analyses. We found no evidence of bias caused by pleiotropy or genetic confounding factors. These findings support the hypothesis that statins can be used to treat migraine.

Role of Ubiquitin-conjugating enzyme E2 (UBE2) in two immune-mediated inflammatory skin diseases: a mendelian randomization analysis

Psoriasis vulgaris (PV) and Atopic dermatitis (AD) are the two major types of immune-mediated inflammatory skin disease (IMISD). Limited studies reported the association between Ubiquitin-conjugating enzyme E2 (UBE2) and IMISD. We employed a two-sample Mendelian randomization (MR) study to assess the causality between UBE2 and PV & AD. UBE2 association genome-wide association study (GWAS) data were collected. The inverse variance weighted (IVW) method was utilized as the principal method in our Mendelian randomization (MR) study, with additional using the MR-Egger, weighted median, simple mode, and weighted mode methods. The MR-Egger intercept test, Cochran's Q test, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and leave-one-out analysis were conducted to identify heterogeneity and pleiotropy, colocalization analysis was also performed. The results showed that Ubiquitin-conjugating enzyme E2 variant 1 (UBE2V1) was causally associated with PV (OR = 0.909, 95% CI: 0.830-0.996, P = 0.040), Ubiquitin-conjugating enzyme E2 L3 (UBE2L3) was causally associated with AD (OR = 0.799, 95% CI: 0.709-0.990, P < 0.001). Both UBE2V1 and UBE2L3 may play protective roles in patients with PV or AD, respectively. No other significant result has been investigated. No heterogeneity or pleiotropy was observed. This study provided new evidence of the relationship between UBE2V1 and PV, UBE2L3 and AD. Our MR suggested that UBE2V1 plays an inhibitory role in PV progression, UBE2L3 plays an inhibitory role in AD. These could be novel and effective ways to treat PV and AD.

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.

Deciphering the causal relationship between plasma and cerebrospinal fluid metabolites and glioblastoma multiforme: a Mendelian Randomization study

BACKGROUND

Glioblastoma Multiforme (GBM) is one of the most aggressive and fatal brain cancers. The study of metabolites could be crucial for understanding GBM's biology and reveal new treatment strategies.

METHODS

The GWAS data for GBM were sourced from the FinnGen database. A total of 1400 plasma metabolites were collected from the GWAS Catalog dataset. The cerebrospinal fluid (CSF) metabolites data were collected from subsets of participants in the WADRC and WRAP studies. We utilized the inverse variance weighting (IVW) method as the primary tool to explore the causal relationship between metabolites in plasma and CSF and glioblastoma, ensuring the exclusion of instances with horizontal pleiotropy. Additionally, four supplementary analytical methods were applied to reinforce our findings. Aberrant results were identified and omitted based on the outcomes of the leave-one-out sensitivity analysis. Conclusively, a reverse Mendelian Randomization analysis was also conducted to further substantiate our results.

RESULTS

The study identified 69 plasma metabolites associated with GBM. Of these, 40 metabolites demonstrated a significant positive causal relationship with GBM, while 29 exhibited a significant negative causal association. Notably, Trimethylamine N-oxide (TMAO) levels in plasma, not CSF, were found to be a significant exposure factor for GBM (OR = 3.1627, 95% CI = (1.6347, 6.1189), P = 0.0006). The study did not find a reverse causal relationship between GBM and plasma TMAO levels.

CONCLUSIONS

This research has identified 69 plasma metabolites potentially associated with the incidence of GBM, among which TMAO stands out as a promising candidate for an early detectable biomarker for GBM.

SharePro: an accurate and efficient genetic colocalization method accounting for multiple causal signals

MOTIVATION

Colocalization analysis is commonly used to assess whether two or more traits share the same genetic signals identified in genome-wide association studies (GWAS), and is important for prioritizing targets for functional follow-up of GWAS results. Existing colocalization methods can have suboptimal performance when there are multiple causal variants in one genomic locus.

RESULTS

We propose SharePro to extend the COLOC framework for colocalization analysis. SharePro integrates linkage disequilibrium (LD) modeling and colocalization assessment by grouping correlated variants into effect groups. With an efficient variational inference algorithm, posterior colocalization probabilities can be accurately estimated. In simulation studies, SharePro demonstrated increased power with a well-controlled false positive rate at a low computational cost. Compared to existing methods, SharePro provided stronger and more consistent colocalization evidence for known lipid-lowering drug target proteins and their corresponding lipid traits. Through an additional challenging case of the colocalization analysis of the circulating abundance of R-spondin 3 GWAS and estimated bone mineral density GWAS, we demonstrated the utility of SharePro in identifying biologically plausible colocalized signals.

AVAILABILITY AND IMPLEMENTATION

SharePro for colocalization analysis is written in Python and openly available at https://github.com/zhwm/SharePro_coloc.

Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.

Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease

BACKGROUND

Hundreds of biomarkers for peripheral artery disease (PAD) have been reported in the literature; however, the observational nature of these studies limits causal inference due to the potential of reverse causality and residual confounding. We sought to evaluate the potential causal impact of putative PAD biomarkers identified in human observational studies through genetic causal inference methods.

METHODS

Putative circulating PAD biomarkers were identified from human observational studies through a comprehensive literature search based on terms related to PAD using PubMed, Cochrane, and Embase. Genetic instruments were generated from publicly available genome-wide association studies of circulating biomarkers. Two-sample Mendelian randomization was used to test the association of genetically determined biomarker levels with PAD using summary statistics from a genome-wide association study of 31 307 individuals with and 211 753 individuals without PAD in the Veterans Affairs Million Veteran Program and replicated in data from FinnGen comprised of 11 924 individuals with and 288 638 individuals without PAD.

RESULTS

We identified 204 unique circulating biomarkers for PAD from the observational literature, of which 173 were genetically instrumented using genome-wide association study results. After accounting for multiple testing (false discovery rate, <0.05), 10 of 173 (5.8%) biomarkers had significant associations with PAD. These 10 biomarkers represented categories including plasma lipoprotein regulation, lipid homeostasis, and protein-lipid complex remodeling. Observational literature highlighted different pathways including inflammatory response, negative regulation of multicellular organismal processes, and regulation of response to external stimuli.

CONCLUSIONS

Integrating human observational studies and genetic causal inference highlights several key pathways in PAD pathophysiology. This work demonstrates that a substantial portion of biomarkers identified in observational studies are not well supported by human genetic evidence and emphasizes the importance of triangulating evidence to understand PAD pathophysiology. Although the identified biomarkers offer insights into atherosclerotic development in the lower limb, their specificity to PAD compared with more widespread atherosclerosis requires further study.

Drug-target Mendelian randomization analysis supports lowering plasma ANGPTL3, ANGPTL4, and APOC3 levels as strategies for reducing cardiovascular disease risk

Aims

APOC3, ANGPTL3, and ANGPTL4 are circulating proteins that are actively pursued as pharmacological targets to treat dyslipidaemia and reduce the risk of atherosclerotic cardiovascular disease. Here, we used human genetic data to compare the predicted therapeutic and adverse effects of APOC3, ANGPTL3, and ANGPTL4 inactivation.

Methods and results

We conducted drug-target Mendelian randomization analyses using variants in proximity to the genes associated with circulating protein levels to compare APOC3, ANGPTL3, and ANGPTL4 as drug targets. We obtained exposure and outcome data from large-scale genome-wide association studies and used generalized least squares to correct for linkage disequilibrium-related correlation. We evaluated five primary cardiometabolic endpoints and screened for potential side effects across 694 disease-related endpoints, 43 clinical laboratory tests, and 11 internal organ MRI measurements. Genetically lowering circulating ANGPTL4 levels reduced the odds of coronary artery disease (CAD) [odds ratio, 0.57 per s.d. protein (95% CI 0.47-0.70)] and Type 2 diabetes (T2D) [odds ratio, 0.73 per s.d. protein (95% CI 0.57-0.94)]. Genetically lowering circulating APOC3 levels also reduced the odds of CAD [odds ratio, 0.90 per s.d. protein (95% CI 0.82-0.99)]. Genetically lowered ANGPTL3 levels via common variants were not associated with CAD. However, meta-analysis of protein-truncating variants revealed that ANGPTL3 inactivation protected against CAD (odds ratio, 0.71 per allele [95%CI, 0.58-0.85]). Analysis of lowered ANGPTL3, ANGPTL4, and APOC3 levels did not identify important safety concerns.

Conclusion

Human genetic evidence suggests that therapies aimed at reducing circulating levels of ANGPTL3, ANGPTL4, and APOC3 reduce the risk of CAD. ANGPTL4 lowering may also reduce the risk of T2D.

Assessing the Role of Cortisol in Anxiety, Major Depression, and Neuroticism: A Mendelian Randomization Study Using SERPINA6/SERPINA1 Variants

Background

Previous evidence informed by the toxic stress model suggests that higher cortisol causes anxiety and major depression, but clinical success is lacking. To clarify the role of cortisol, we used Mendelian randomization to estimate its associations with anxiety, major depression, and neuroticism, leveraging the largest available genome-wide association studies including from the Psychiatric Genomics Consortium, the UK Biobank, and FinnGen.

Methods

After meta-analyzing 2 genome-wide association studies on morning plasma cortisol (n = 32,981), we selected single nucleotide polymorphisms (SNPs) at p < 5 × 10-8 and r2 < 0.3 in the SERPINA6/SERPINA1 gene region encoding proteins that influence cortisol bioavailability. We applied these SNPs to summary genetic associations with the outcomes considered (n = 17,310-449,484), and systolic blood pressure as a positive outcome, using inverse-variance weighted meta-analysis accounting for correlation. Sensitivity analyses addressing SNP correlation and confounding by childhood maltreatment and follow-up analyses using only SNPs that colocalized with SERPINA6 expression were conducted.

Results

Cortisol was associated with anxiety (pooled odds ratio [OR] 1.16 per cortisol z score; 95% CI, 1.04 to 1.31), but not major depression (pooled OR 1.02, 95% CI, 0.95 to 1.10) or neuroticism (β -0.025; 95% CI, -0.071 to 0.022). Sensitivity analyses yielded similar estimates. Cortisol was positively associated with systolic blood pressure, as expected. Using rs9989237 and rs2736898, selected using colocalization, cortisol was associated with anxiety in the UK Biobank (OR 1.32; 95% CI, 1.01 to 1.74) but not with major depression in FinnGen (OR 1.14; 95% CI, 0.95 to 1.37).

Conclusions

Cortisol was associated with anxiety and may be a potential target for prevention. Other targets may be more relevant to major depression and neuroticism.

Large-scale genome-wide association studies reveal the genetic causal etiology between air pollutants and autoimmune diseases

BACKGROUND

Epidemiological evidence links a close correlation between long-term exposure to air pollutants and autoimmune diseases, while the causality remained unknown.

METHODS

Two-sample Mendelian randomization (TSMR) was used to investigate the role of PM10, PM2.5, NO2, and NOX (N = 423,796-456,380) in 15 autoimmune diseases (N = 14,890-314,995) using data from large European GWASs including UKB, FINNGEN, IMSGC, and IPSCSG. Multivariable Mendelian randomization (MVMR) was conducted to investigate the direct effect of each air pollutant and the mediating role of common factors, including body mass index (BMI), alcohol consumption, smoking status, and household income. Transcriptome-wide association studies (TWAS), two-step MR, and colocalization analyses were performed to explore underlying mechanisms between air pollution and autoimmune diseases.

RESULTS

In TSMR, after correction of multiple testing, hypothyroidism was causally associated with higher exposure to NO2 [odds ratio (OR): 1.37, p = 9.08 × 10-4] and NOX [OR: 1.34, p = 2.86 × 10-3], ulcerative colitis (UC) was causally associated with higher exposure to NOX [OR: 2.24, p = 1.23 × 10-2] and PM2.5 [OR: 2.60, p = 5.96 × 10-3], rheumatoid arthritis was causally associated with higher exposure to NOX [OR: 1.72, p = 1.50 × 10-2], systemic lupus erythematosus was causally associated with higher exposure to NOX [OR: 4.92, p = 6.89 × 10-3], celiac disease was causally associated with lower exposure to NOX [OR: 0.14, p = 6.74 × 10-4] and PM2.5 [OR: 0.17, p = 3.18 × 10-3]. The risky effects of PM2.5 on UC remained significant in MVMR analyses after adjusting for other air pollutants. MVMR revealed several common mediators between air pollutants and autoimmune diseases. Transcriptional analysis identified specific gene transcripts and pathways interconnecting air pollutants and autoimmune diseases. Two-step MR revealed that POR, HSPA1B, and BRD2 might mediate from air pollutants to autoimmune diseases. POR pQTL (rs59882870, PPH4=1.00) strongly colocalized with autoimmune diseases.

CONCLUSION

This research underscores the necessity of rigorous air pollutant surveillance within public health studies to curb the prevalence of autoimmune diseases.

New insights from bidirectional Mendelian randomization: causal relationships between telomere length and mitochondrial DNA copy number in aging biomarkers

Mitochondrial DNA (mtDNA) copy number and telomere length (TL) are dynamic factors that have been linked to the aging process in organisms. However, the causal relationship between these variables remains uncertain. In this research, instrumental variables (IVs) related to mtDNA copy number and TL were obtained from publicly available genome-wide association studies (GWAS). Through bidirectional Mendelian randomization (MR) analysis, we examined the potential causal relationship between these factors. The forward analysis, with mtDNA copy number as the exposure and TL as the outcome, did not reveal a significant effect (B=-0.004, P>0.05). On the contrary, upon conducting a reverse analysis, it was found that there exists a positive causal relationship (B=0.054, P<0.05). Sensitivity analyses further confirmed the reliability of these results. The outcomes of this study indicate a one-way positive causal relationship, indicating that telomere shortening in the aging process may lead to a decrease in mtDNA copy number, providing new perspectives on their biological mechanisms.

Potential therapeutic targets for membranous nephropathy: proteome-wide Mendelian randomization and colocalization analysis

Background

The currently available medications for treating membranous nephropathy (MN) still have unsatisfactory efficacy in inhibiting disease recurrence, slowing down its progression, and even halting the development of end-stage renal disease. There is still a need to develop novel drugs targeting MN.

Methods

We utilized summary statistics of MN from the Kiryluk Lab and obtained plasma protein data from Zheng et al. We performed a Bidirectional Mendelian randomization analysis, HEIDI test, mediation analysis, Bayesian colocalization, phenotype scanning, drug bank analysis, and protein-protein interaction network.

Results

The Mendelian randomization analysis uncovered 8 distinct proteins associated with MN after multiple false discovery rate corrections. Proteins related to an increased risk of MN in plasma include ABO [(Histo-Blood Group Abo System Transferase) (WR OR = 1.12, 95%CI:1.05-1.19, FDR=0.09, PPH4 = 0.79)], VWF [(Von Willebrand Factor) (WR OR = 1.41, 95%CI:1.16-1.72, FDR=0.02, PPH4 = 0.81)] and CD209 [(Cd209 Antigen) (WR OR = 1.19, 95%CI:1.07-1.31, FDR=0.09, PPH4 = 0.78)], and proteins that have a protective effect on MN: HRG [(Histidine-Rich Glycoprotein) (WR OR = 0.84, 95%CI:0.76-0.93, FDR=0.02, PPH4 = 0.80)], CD27 [(Cd27 Antigen) (WR OR = 0.78, 95%CI:0.68-0.90, FDR=0.02, PPH4 = 0.80)], LRPPRC [(Leucine-Rich Ppr Motif-Containing Protein, Mitochondrial) (WR OR = 0.79, 95%CI:0.69-0.91, FDR=0.09, PPH4 = 0.80)], TIMP4 [(Metalloproteinase Inhibitor 4) (WR OR = 0.67, 95%CI:0.53-0.84, FDR=0.09, PPH4 = 0.79)] and MAP2K4 [(Dual Specificity Mitogen-Activated Protein Kinase Kinase 4) (WR OR = 0.82, 95%CI:0.72-0.92, FDR=0.09, PPH4 = 0.80)]. ABO, HRG, and TIMP4 successfully passed the HEIDI test. None of these proteins exhibited a reverse causal relationship. Bayesian colocalization analysis provided evidence that all of them share variants with MN. We identified type 1 diabetes, trunk fat, and asthma as having intermediate effects in these pathways.

Conclusions

Our comprehensive analysis indicates a causal effect of ABO, CD27, VWF, HRG, CD209, LRPPRC, MAP2K4, and TIMP4 at the genetically determined circulating levels on the risk of MN. These proteins can potentially be a promising therapeutic target for the treatment of MN.

Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia

BACKGROUND

Numerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies.

METHODS

We utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein-protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets.

RESULTS

We found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data.

CONCLUSIONS

Our study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.

Genetic determinants of plasma protein levels in the Estonian population

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes

Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10-7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

Association between rheumatoid arthritis and autoimmune thyroid disease: evidence from complementary genetic methods

OBJECTIVES

To assess the causal association of Rheumatoid Arthritis (RA) with Autoimmune thyroid disease (AITD).

METHOD

Complementary genetic approaches, including genetic correlation, Mendelian randomization (MR) and colocalization analysis, were conducted to assess the potential causal association between RA and AITD using summary statistics from large-scale genome-wide association studies (GWASs). Various sensitivity analyses had been conducted to assess the robustness and the consistency of the findings.

RESULTS

The linkage disequilibrium score regression revealed a shared genetic structure between RA and AITD, with the significant genetic correlation between RA and autoimmune hyperthyroidism and autoimmune hypothyroidism estimated to be 0.3945 (P = 2.83 × 10-6) and 0.2771 (P = 1.04 × 10-6) respectively. The results of MR analysis showed that RA had a positive causal relationship with autoimmune hypothyroidism and autoimmune hyperthyroidism. The odds ratio (OR) were 1.29 (95% CI, 1.17-1.42; P = 1.08 × 10-7) and 1.47 (95% CI, 1.25-1.72; P = 1.85 × 10-6), respectively. In reverse MR analysis, autoimmune hypothyroidism had a positive causal relationship with RA, OR was 1.51 (95% CI, 1.37-1.66; P = 1.10 × 10-16); autoimmune hyperthyroidism had no causal relationship with RA relationship (P = 0.22). Similar results were found using different MR methods. In addition, colocalization analysis suggested that shared causal variants existed between RA and AITD.

CONCLUSIONS

Our study suggested a potentially causal effect of genetically predicted RA on autoimmune hyperthyroidism and a bidirectional causal relationship between RA and autoimmune hypothyroidism was also observed with complementary genetic approaches, which supports the importance and necessity of thyroid function screening and monitoring in RA patient management in clinical practice.

Examining intergenerational risk factors for conduct problems using polygenic scores in the Norwegian Mother, Father and Child Cohort Study

The aetiology of conduct problems involves a combination of genetic and environmental factors, many of which are inherently linked to parental characteristics given parents' central role in children's lives across development. It is important to disentangle to what extent links between parental heritable characteristics and children's behaviour are due to transmission of genetic risk or due to parental indirect genetic influences via the environment (i.e., genetic nurture). We used 31,290 genotyped mother-father-child trios from the Norwegian Mother, Father and Child Cohort Study (MoBa), testing genetic transmission and genetic nurture effects on conduct problems using 13 polygenic scores (PGS) spanning psychiatric conditions, substance use, education-related factors, and other risk factors. Maternal or self-reports of conduct problems at ages 8 and 14 years were available for up to 15,477 children. We found significant genetic transmission effects on conduct problems for 12 out of 13 PGS at age 8 years (strongest association: PGS for smoking, β = 0.07, 95% confidence interval = [0.05, 0.08]) and for 4 out of 13 PGS at age 14 years (strongest association: PGS for externalising problems, β = 0.08, 95% confidence interval = [0.05, 0.11]). Conversely, we did not find genetic nurture effects for conduct problems using our selection of PGS. Our findings provide evidence for genetic transmission in the association between parental characteristics and child conduct problems. Our results may also indicate that genetic nurture via traits indexed by our polygenic scores is of limited aetiological importance for conduct problems-though effects of small magnitude or effects via parental traits not captured by the included PGS remain a possibility.

Association of lipid-modifying therapy with risk of obstructive sleep apnea: A drug-target mendelian randomization study

BACKGROUND

Obstructive sleep apnea (OSA) is considered to be an important contributor of dyslipidemia. However, there lacks observational studies focusing on the potential effect of lipid management on OSA risk. Thus, we aimed to investigate the genetic association of lipid-modifying therapy with risk of OSA.

METHODS

A drug-target mendelian randomization (MR) study using both cis-variants and cis-expression quantitative trait loci (eQTLs) of lipid-modifying drug targets was performed. The MR analyses used summary-level data of genome wide association studies (GWAS). Primary MR analysis was conducted using inverse-variance-weighted (IVW) method. Sensitivity analysis was performed using weighted median (WM) and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods.

RESULTS

Genetically proxied low-density lipoprotein cholesterol (LDL-C)-lowering effect of cholesteryl ester transfer protein (CETP) was associated with reduced risk of OSA (odds ratio [OR] =0.75, 95% confidence interval [CI]: 0.60-0.94, false discovery rate [FDR] q value = 0.046). A significant MR association with risk of OSA was observed for CETP expression in subcutaneous adipose tissue (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049), lung (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049) and small intestine (OR = 0.96, 95%CI: 0.93-1.00, FDR q value = 0.049). No significant effects of high-density lipoprotein cholesterol (HDL-C)-raising effect of CETP inhibition, LDL-C-lowering and triglycerides-lowering effect of other drug targets on OSA risk were observed.

CONCLUSIONS

The present study presented genetic evidence supporting the association of LDL-C-lowering therapy by CETP inhibition with reduced risk of OSA. These findings provided novel insights into the role of lipid management in patients with OSA and encouraged further clinical validations and mechanistic investigations.

Association between inflammatory bowel disease and cancer risk: evidence triangulation from genetic correlation, Mendelian randomization, and colocalization analyses across East Asian and European populations

BACKGROUND

Inflammatory bowel disease (IBD), which includes Crohn's disease (CD) and ulcerative colitis (UC), has been associated with several cancer risks in observational studies, but the observed associations have been inconsistent and may face the bias of confounding and reverse causality. The potential causal relationships between IBD and the risk of cancers remain largely unclear.

METHODS

We performed genome-wide linkage disequilibrium score regression (LDSC), standard two-sample Mendelian randomization (MR), and colocalization analyses using summary genome-wide association study (GWAS) data across East Asian and European populations to evaluate the causal relationships between IBD and cancers. Sensitivity analyses for the MR approach were additionally performed to explore the stability of the results.

RESULTS

There were no significant genetic correlations between IBD, CD, or UC and cancers (all P values > 0.05) in East Asian or European populations. According to the main MR analysis, no significant causal relationship was observed between IBD and cancers in the East Asian population. There were significant associations between CD and ovarian cancer (odds ratio [OR] = 0.898, 95% CI = 0.844-0.955) and between UC and nonmelanoma skin cancer (OR = 1.002, 95% CI = 1.000-1.004, P = 0.019) in the European population. The multivariable MR analysis did not find any of the above significant associations. There was no shared causal variant to prove the associations of IBD, CD, or UC with cancers in East Asian or European populations using colocalization analysis.

CONCLUSIONS

We did not provide robust genetic evidence of causal associations between IBD and cancer risk. Exposure to IBD might not independently contribute to the risk of cancers, and the increased risk of cancers observed in observational studies might be attributed to factors accompanying the diagnosis of IBD.

Identification of bidirectional causal links between gut microbiota and narcolepsy type 1 using Mendelian randomization

STUDY OBJECTIVES

Narcolepsy type 1 (NT1), characterized by cataplexy and orexin deficiency, is a rare and frequently debilitating neurological disorder. It has been noted to have connections with the gut microbiota, yet the exact causal relationships remain unclear.

METHODS

We conducted a comprehensive bidirectional Mendelian randomization (MR) study to rigorously investigate the causal links between the gut microbiota and NT1, utilizing genetic datasets from the MiBioGen consortium and FinnGen consortium, respectively. The inverse-variance weighted (IVW) method was employed to obtain the primary MR estimates, supplemented by several alternative methods as well as sensitivity analyses including Cochran's Q, MR-Egger, MR pleiotropy residual sum and outlier, leave-one-out, and genetic colocalization.

RESULTS

Our findings indicated that an increased relative abundance of five genera including Blautia (p = 4.47E-5), Collinsella (p = 0.036), Gordonibacter (p = 0.047), Hungatella (p = 0.015), and Lachnospiraceae UCG010 (p = 0.027) may be associated with a decreased risk of NT1. Conversely, an increased relative abundance of class Betaproteobacteria (p = 0.032), genus Alloprevotella (p = 0.009), and genus Ruminiclostridium6 (p = 0.029) may potentially heighten the risk of NT1. The onset of NT1 may lead to a decrease in the relative abundance of genus Eubacterium eligens group (p = 0.022), while a increase in the family Family XI (p = 0.009), genus Hungatella (p = 0.005), genus Prevotella (p = 0.013), and unknown genus id.2001 (p = 0.019). These findings remained robust under all sensitivity analyses.

CONCLUSIONS

Our results offer robust evidence for the bidirectional causal links between particular gut microbial taxa and NT1, underscoring the significance of the microbiota-gut-brain axis in the pathological process of NT1.

TBK1, a prioritized drug repurposing target for amyotrophic lateral sclerosis: evidence from druggable genome Mendelian randomization and pharmacological verification in vitro

BACKGROUND

There is a lack of effective therapeutic strategies for amyotrophic lateral sclerosis (ALS); therefore, drug repurposing might provide a rapid approach to meet the urgent need for treatment.

METHODS

To identify therapeutic targets associated with ALS, we conducted Mendelian randomization (MR) analysis and colocalization analysis using cis-eQTL of druggable gene and ALS GWAS data collections to determine annotated druggable gene targets that exhibited significant associations with ALS. By subsequent repurposing drug discovery coupled with inclusion criteria selection, we identified several drug candidates corresponding to their druggable gene targets that have been genetically validated. The pharmacological assays were then conducted to further assess the efficacy of genetics-supported repurposed drugs for potential ALS therapy in various cellular models.

RESULTS

Through MR analysis, we identified potential ALS druggable genes in the blood, including TBK1 [OR 1.30, 95%CI (1.19, 1.42)], TNFSF12 [OR 1.36, 95%CI (1.19, 1.56)], GPX3 [OR 1.28, 95%CI (1.15, 1.43)], TNFSF13 [OR 0.45, 95%CI (0.32, 0.64)], and CD68 [OR 0.38, 95%CI (0.24, 0.58)]. Additionally, we identified potential ALS druggable genes in the brain, including RESP18 [OR 1.11, 95%CI (1.07, 1.16)], GPX3 [OR 0.57, 95%CI (0.48, 0.68)], GDF9 [OR 0.77, 95%CI (0.67, 0.88)], and PTPRN [OR 0.17, 95%CI (0.08, 0.34)]. Among them, TBK1, TNFSF12, RESP18, and GPX3 were confirmed in further colocalization analysis. We identified five drugs with repurposing opportunities targeting TBK1, TNFSF12, and GPX3, namely fostamatinib (R788), amlexanox (AMX), BIIB-023, RG-7212, and glutathione as potential repurposing drugs. R788 and AMX were prioritized due to their genetic supports, safety profiles, and cost-effectiveness evaluation. Further pharmacological analysis revealed that R788 and AMX mitigated neuroinflammation in ALS cell models characterized by overly active cGAS/STING signaling that was induced by MSA-2 or ALS-related toxic proteins (TDP-43 and SOD1), through the inhibition of TBK1 phosphorylation.

CONCLUSIONS

Our MR analyses provided genetic evidence supporting TBK1, TNFSF12, RESP18, and GPX3 as druggable genes for ALS treatment. Among the drug candidates targeting the above genes with repurposing opportunities, FDA-approved drug-R788 and AMX served as effective TBK1 inhibitors. The subsequent pharmacological studies validated the potential of R788 and AMX for treating specific ALS subtypes through the inhibition of TBK1 phosphorylation.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.