Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Long nighttime sleep duration and risk of renal tubular damage: evidence from rural China and a Mendelian randomization analysis

OBJECTIVE

Renal tubular damage, a pivotal pathological feature of chronic kidney disease (CKD), predicts disease progression. While extreme nighttime sleep duration is linked to glomerular injury by prior studies, its impact on tubular damage remains unclear. Given that 7-9 h of sleep per night is widely recommended for maintaining overall health, this study aimed to assess whether long nighttime sleep duration is associated with renal tubular damage using both observational and genetic evidence.

METHODS

We analyzed 2,683 adults in rural China to assess the link between nighttime sleep duration and renal tubular damage (measured by retinol-binding protein and β2-microglobulin). Mendelian randomization (MR) analysis was performed to assess the causal relationship between prolonged nighttime sleep duration and elevated kidney injury molecule-1 (KIM-1) levels.

RESULTS

Multivariate logistic regression indicated that sleeping more than 9 h per night was associated with a 1.38-fold increased risk of renal tubular damage (95% CI: 1.11-1.71) compared to 7-9 h of sleep, with particularly pronounced effects observed in elderly individuals and women. MR analysis further supported a causal relationship between genetically predicted long nighttime sleep duration and elevated KIM-1 levels (β: 0.994, 95% CI: 0.282-1.707), suggesting a genetic predisposition linking prolonged sleep duration with renal tubular damage.

CONCLUSIONS

Our findings provide observational and genetic evidence linking prolonged nighttime sleep to increased renal tubular damage risk. Given that 7-9 h of sleep per night is the widely accepted recommendation for maintaining overall health, our results emphasize the potential risks of excessive sleep duration exceeding 9 h.

Proximity extension assay reveals serum inflammatory biomarkers in two amyotrophic lateral sclerosis cohorts

Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease with both clinical and hereditary heterogeneity. Inflammation has been suggested to play an important role in ALS pathophysiology. In this study, we aimed to identify serum inflammatory alterations and develop effective inflammatory biomarkers to assist in the diagnosis of ALS. Through proximity extension assay (PEA), we investigated serum inflammatory alterations in two ALS cohorts compared with healthy controls (HCs), including sporadic ALS patients and genetic ALS patients. We found that CHIT1, OSM, SIRT2, CDCP1 and 5 other factors were significantly increased in sporadic ALS patients in both cohorts and that SIRT2, CDCP1 and 6 other factors were different between genetic ALS patients and HCs. Using XGBoost and binary logistic regression analysis, we developed a two-serum protein diagnostic panel (CHIT1 and CDCP1), and the area under the curve (AUC) was 0.904 in the original cohort and 0.907 in the replication cohort. Based on Mendelian Randomization (MR), OSM and SIRT2 are significantly associated with the risk of ALS. In conclusion, our study revealed a consistent and replicable serum inflammatory profile and developed a biomarker panel that can differentiate ALS patients from HCs in two cohorts, which may play an important role in advancing our current understanding of the inflammatory process and identifying novel therapeutic strategies for ALS patients.

Identification of potential drug targets for four site-specific cancers by integrating human plasma proteome with genome

Drug targets supported by genetic evidence with a several-fold higher probability of success in clinical trials. We performed a comprehensive proteome-wide Mendelian randomization (MR) analysis to identify causal proteins and potential therapeutic targets for four site-specific cancers. A total of 13,248 protein quantitative trait loci for 4853 plasma proteins were utilized for proteome-wide MR analysis. Identification of cancer causal proteins in the discovery cohort and further validation in the replication cohort. Colocalization, summary-data-based MR (SMR) analysis, and transcriptome‑wide association studies (TWAS) were performed to check the accuracy of the candidate proteins. Two-step MR analysis was used to explore the effects of plasma protein-mediated 248 modifiable factors on cancer. Phenome-wide MR (Phe-MR) analysis, druggability evaluation, and single-cell type expression analysis further assessed the potential of causal proteins. Combining the results of the meta-analysis of MR estimates from the two cohorts, 21, 2, 24 and 1 causal proteins were identified in breast, lung, prostate and stomach cancers, respectively. Evidence from colocalization, SMR analysis, and TWAS highlighted CD36, DNPH1, and PLXND1 as the most promising drug targets for breast cancer, and ZNF175 for prostate cancer. 1 new potential biomarker (PLXND1) for breast cancer, 2 new promising targets (RELL1, DEFB119) for lung cancer, and 8 new circulating biomarkers (ARFIP2, CCN6, CTRB2, HTR7, MRPL33, TNFRSF6B, VAMP5, ZNF175) for prostate cancer were firstly reported. Some plasma proteins may mediate the association of these cancers with other systemic diseases. Additionally, genetically predicted higher BMI and overweight may reduce breast cancer risk by altering CASP8, ADM, PLXND1, TNFRSF9, ULK3 and VSIG4 protein levels. Causal proteins of breast and prostate cancer were expressed predominantly on macrophages in cancerous tissues. This study genetically identified several cancer causal proteins which provided new perspectives for the understanding of the etiology and development of novel targeted drugs for cancer.

Plasma proteins and herpes simplex virus infection: a proteome-wide Mendelian randomization study

Proteomics plays a pivotal role in clinical diagnostics and monitoring. We conducted proteome-wide Mendelian randomization (MR) study to estimate the causal association between plasma proteins and Herpes simplex virus (HSV) infection. Data for 2,923 plasma protein levels were obtained from a large-scale protein quantitative trait loci study involving 54,219 individuals, conducted by the UK Biobank Pharma Proteomics Project. HSV-associated SNPs were derived from the FinnGen study, which included a total of 400,098 subjects infected with HSV. MR analysis was performed to assess the links between protein levels and the risk of HSV infection. Furthermore, a Phenome-wide MR analysis was utilized to explore potential alternative indications or predict adverse drug events. Finally, we evaluated the impact of 1,949 plasma proteins on HSV infection, identifying 48 proteins that were negatively associated with HSV infection and 54 proteins that were positively associated. Genetically higher HLA-E levels were significantly associated with increased HSV infection risk (OR = 1.39, 95% CI: 1.17-1.65, P = 2.13 × 10-4, while ULBP2 showed a significant negative association with HSV infection risk (OR = 0.81, 95% CI: 0.73-0.90, P = 6.25 × 10-5) in the primary analysis. No significant heterogeneity or pleiotropy was observed in any of the results. Additionally, we found a suggestive association of Lymphotoxin-beta, SMOC1, MICB_MICA, ASGR1, and ANXA10 with HSV infection risk (P < 0.003). In Phenome-wide MR analysis, HLA-E was associated with 214 phenotypes (PFDR < 0.10) while ULBP2 did not show significant associations with any diseases after FDR adjustment. The comprehensive MR analysis established a causal link between multiple plasma proteins and HSV infection, emphasizing the roles of HLA-E and ULBP2. These results provide new insights into the biological mechanisms of HSV and support the potential for early intervention and treatment strategies, although further research is needed to validate these plasma protein biomarkers.

The causal association between cardiovascular proteins and diabetic nephropathy: a Mendelian randomization study

PURPOSE

To clarify the causal association between cardiovascular proteins and diabetic nephropathy (DN) in Europeans.

METHODS

The large genome-wide association study data of cardiovascular proteins and DN were used for this two-sample Mendelian randomization (MR) analysis. We took the Inverse variance weighted (IVW) as the primary method. Moreover, MR-Egger, weighted median, weighted mode, and simple mode were also performed as supplementary methods. Further, Cochrane's Q test, MR-Egger, and MR-PRESSO were conducted for sensitivity analysis.

RESULTS

According to the IVW method, the results indicated that Galanin peptide was a protective factor for DN (OR: 0.835, 95% CI 0.700, 0.996, P = 0.045) and seven cardiovascular proteins were identified as the risk factors for DN, including CX3CL1 (OR: 1.288, 95% CI 1.012, 1.639, P = 0.039), stem cell factor (OR: 1.228, 95%CI: 1.013, 1.489, P = 0.036), tumor necrosis factor receptor 2 (OR: 1.633, 95% CI 1.141, 2.338, P = 0.007), myeloperoxidase (OR: 1.412, 95% CI 1.103, 1.808, P = 0.006), galectin-3 (OR: 1.297, 95% CI 1.095, 1.537, P = 0.003), platelet-derived growth factor subunit B (OR: 1.338, 95% CI 1.020, 1.756, P = 0.035), and interleukin-27 (OR: 1.248, 95% CI 1.033, 1.509, P = 0.022). Moreover, the reverse MR study did not observe the causal effect of DN on cardiovascular proteins. The results of sensitivity analysis suggested no significant pleiotropy and heterogeneity.

CONCLUSION

This MR analysis first evaluated the causal relationship between cardiovascular protein and DN at the genetic level, which could be of great significance for the prevention and treatment of DN.

Prospective Investigation Unravels Plasma Proteomic Links to Dementia

Investigating plasma proteomic signatures of dementia offers insights into its pathology, aids biomarker discovery, supports disease monitoring, and informs drug development. Here, we analyzed data from 48,367 UK Biobank participants with proteomic profiling. Using Cox and generalized linear models, we examined the longitudinal associations between proteomic signatures and dementia-related phenotypes. Mendelian randomization analysis was employed to identify causal associations, and machine learning algorithms were applied to develop protein-based models for dementia prediction. We identified 74 proteins significantly associated with the risk of various types of dementia and cognitive functions after Bonferroni correction. Among these, strong associations were observed for growth/differentiation factor 15 (GDF15), glial fibrillary acidic protein (GFAP), and neurofilament light polypeptide (NEFL), across all types of dementia. Additionally, 15 proteins demonstrated significant associations with neuroimaging-defined dementia endophenotypes. Two-sample Mendelian randomization analyses further substantiated causal relationships between dementia-associated proteins and Alzheimer's disease, particularly involving GDF15, proto-oncogene tyrosine-protein kinase receptor Ret (RET), and GFAP. Moreover, we identified three protein modules associated with dementia, primarily linked to immune system processes, angiogenesis, and energy metabolism, providing insights into potential biological pathways underlying the disease. Furthermore, we proposed a ten-protein panel capable of forecasting dementia over a median follow-up period of 8.6 years, achieving an area under the curve (AUC) of 0.857 (95% confidence interval (CI), 0.837-0.876). Our results revealed dementia-associated plasma proteomic signatures, and their causal relationships, notably GDF15-RET signaling with Alzheimer's disease, and proposed a promising protein panel for high-risk dementia screening.

Mendelian randomization analysis for identifying circulating inflammatory cytokines and risk of pancreatic cancers

OBJECTIVES

Inflammation is intricately linked to the emergence and advancement of most cancers, playing a pivotal role in their malignant transformation. Observational evidence revealed the role of cytokines in pancreatic cancer (PC) carcinogenesis. However, observational studies may be limited by small sample sizes, confounding factors, and reverse causality when establishing a correlation between inflammatory cytokines and PC risk.

DESIGN

Conducting a two-sample Mendelian randomization analysis, we investigated the potential relationship between inflammatory cytokines in circulation and pancreatic cancer. Data from the most extensive genome-wide association studies (GWAS) on cytokines were utilized, involving 31 112 individuals of European descent. Additionally, the PC GWAS from the Integrative Epidemiology Unit (IEU) analysis of Finnish Biobank data was included, consisting of 605 PC cases and 218 187 controls of European ancestry.

RESULTS

Around 47 cytokines were systematically screened, which revealed that circulating levels of IL-1ra (OR: 0.63; 95% CIs: 0.46-0.87; P-value: 4.9 × 10-4), IP-10 (OR: 0.33; 95% CIs: 0.18-0.59; P-value: 1.8 × 10-4) and macrophage inflammatory protein (MIP)-1a (OR: 1.37; 95% CIs: 1.08-1.75; P-value: 1 × 10-2) predicted by genetic criteria were prominently linked to an elevated risk of overall PC.

CONCLUSION

Further evidence indicates that certain inflammatory cytokines play critical roles in PC carcinogenesis and that specific inflammatory cytokines can be targeted to prevent PC. Nevertheless, additional research is necessary to assess the potential of these cytokines in detecting PC at an early stage.

Age-Associated Increase in Growth Differentiation Factor 15 Levels Correlates With Central Arterial Stiffness and Predicts All-Cause Mortality in a Sardinian Population Cohort

BACKGROUND

Growth differentiation factor 15 (GDF-15) levels are emerging as a candidate biomarker of aging. The present study aimed to: (1) characterize the association of GDF-15 with the continuum of arterial stiffening, assessed as carotid-femoral pulse wave velocity, as age increases; (2) determine the predictive role of serum GDF-15 levels on mortality; and (3) identify genetic determinants of serum GDF-15 levels.

METHODS AND RESULTS

Serum levels of GDF-15 and established cardiovascular risk factors, including pulse wave velocity, were assessed in a large (4736 individual) Sardinian population. Serum levels of GDF-15, which can be reliably measured repeatedly over time, increase with age; are associated with a stiffer aorta; "mediate" a large proportion of the age-associated increase in arterial stiffness; pose risks because of their association with greater mortality; and are significantly associated with the variant rs11549407, which causes thalassemia major in homozygosity.

CONCLUSIONS

Because of its consistent ability to predict functional and clinical outcomes, including all-cause mortality, we conclude that GDF-15 serum levels serve as a robust biomarker for the continuum from health to the emergence of clinical disease during aging and, subsequently, to the likelihood of mortality.

Multi-Omics Analysis Identifies Genetic Mechanisms and Therapeutic Targets for Acne Vulgaris

Acne vulgaris is a chronic inflammatory disorder with complex pathophysiology. However, challenges such as antibiotic resistance, side effects, and recurrence highlight the need for precision therapies. This study employed a multi-omics approach, integrating summary-data-based Mendelian randomization (SMR), colocalization, two-sample MR (TSMR), transcriptome-wide (TWAS) and proteome-wide (PWAS) association studies, and functional analyses to identify acne-associated genes and proteins. We analyzed acne GWAS data (n_cases = 34,422; n_controls = 364,991), eQTL datasets from blood, skin-related tissues, and fibroblasts, along with six pQTL databases and a blood mQTL dataset. SMR and sensitivity analyses identified 16 candidate genes, refined to 9 by TWAS. Protein-level SMR and PWAS further recognized two plasma proteins (CRELD2 and TIMP4), with CRELD2 also supported by gene-level associations. A total of 10 non-redundant targets were functionally analyzed, revealing pathways beyond molecular transport, such as carnitine metabolism. Moreover, methylation regulated key genes, and immune cell-specific loci overlapped with acne risk. Transcriptomic data confirmed differential expression of several targets in acne lesions. Finally, we prioritized acne drug targets based on our results and their druggability, highlighting SLC22A5 activators and CRELD2 inhibitors as promising tier 1 candidates. These findings advance the molecular understanding of acne pathogenesis and suggest potential therapeutic targets.

Variant-to-function approaches for adipose tissue: Insights into cardiometabolic disorders

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic disorders. However, the functional interpretation of these loci remains a daunting challenge. This is particularly true for adipose tissue, a critical organ in systemic metabolism and the pathogenesis of various cardiometabolic diseases. We discuss how variant-to-function (V2F) approaches are used to elucidate the mechanisms by which GWAS loci increase the risk of cardiometabolic disorders by directly influencing adipose tissue. We outline GWAS traits most likely to harbor adipose-related variants and summarize tools to pinpoint the putative causal variants, genes, and cell types for the associated loci. We explain how large-scale perturbation experiments, coupled with imaging and multi-omics, can be used to screen variants' effects on cellular phenotypes and how these phenotypes can be tied to physiological mechanisms. Lastly, we discuss the challenges and opportunities that lie ahead for V2F research and propose a roadmap for future studies.

Causal relationship between molecular markers of biological aging and orthopedic diseases: A two-sample bidirectional Mendelian randomization study

BACKGROUND

Studies indicate an association between biological aging and orthopedic diseases, but the causality remains unclear.

AIMS

This study aims to investigate the bidirectional causal relationship between molecular markers of biological aging age and orthopedic conditions.

METHODS

A two-sample Mendelian randomization (MR) analysis based on a genome-wide association study (GWAS) was conducted to explore these causal relationships. Analysis methods included inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode. Sensitivity analyses involved Cochran's Q, MR-Egger, leave-one-out, and MR pleiotropy residual sum and outlier (MR-PRESSO) tests.

RESULTS

The forward MR analysis identified several causal relationships: granulocyte proportions influenced intervertebral disc degeneration (IVDD) (OR 0.2316, P = 0.0101) and low back pain (LBP) (OR 0.2624, P = 0.007); telomere length (TL) affected cervical spondylosis (C/S) (OR 0.8759, P = 0.0167) and IVDD (OR 0.9184, P = 0.023); fibroblast growth factor-23 (FGF-23) impacted frozen shoulder (FS) (OR 1.2424, P = 0.0316); and HannumAge influenced C/S (OR 0.9518, P = 0.0233). The reverse MR analysis found that FS influenced TL (OR 0.9582, P = 0.0002) and α-Klotho (OR 0.7592, P = 0.0256), while sciatica affected TL (OR 0.9344, P = 0.0055) and C/S impacted PhenoAge (OR 1.6583, P = 0.0131) after outlier exclusion. Cochran's Q indicated heterogeneity in certain analyses, and MR-Egger showed no horizontal pleiotropy in significant causal associations.

CONCLUSIONS

This study suggests a potential causal associations between molecular markers of biological aging and orthopedic diseases, suggesting avenues for future research into the underlying mechanisms.

Research Advance of Causal Inference in Clinical Medicine: A Bibliometrics Analysis via Citespace

Objective

Causal inference in clinical medicine provides scientific evidence for precision medicine and individualized treatment by revealing the true associations between interventions and health outcomes. This study aims to conduct a comprehensive bibliometric analysis to identify current research trends, primary themes, and future directions for the application of causal inference in clinical medicine.

Methods

We conducted a literature search in the Web of Science database using causal inference and medical terminology as subject keywords, covering the period from January 1986 to December 2024. After screening, we obtained 4,316 documents for analysis. Utilizing CiteSpace to generate network diagrams, we analyzed data related to the number of publications, citation analysis, collaboration relationships, keyword co-occurrence, and highlighted terms to illustrate the knowledge map and collaboration network in this field.

Results

Publications on medical causal inference shows a fluctuating growth trend over time. The United States was the top contributors to this field. Harvard University is the leading research institution. George David Smith is the most prolific author, Robbins JM is the most cited scholar. The major research hotspots concentrated in fields such as epidemiology, coronary heart disease and health. Notably, marginal structural models, counterfactual forecasting, and Mendelian randomization have consistently been key methodologies in research. The burstness of keywords reveals that big data, DNA methylation, and robust estimation are emerging research directions.

Conclusion

In clinical research, counterfactual forecasting provides prospective guidance for optimizing clinical strategies; Mendelian randomization helps uncover potential therapeutic targets; and marginal structural models enhance the accuracy of causal effect estimation in clinical studies. The future integration of various data sources to improve causal inference methods is anticipated to enhance the sensitivity and specificity of trials, ultimately elucidating the complex mechanisms of diseases and drug effects. The literature retrieve strategy and the metrics of the tools adopted may have a certain impact on the results of this study.

The Genetic Polymorphisms of NPPA:rs5065 and NPPB:rs198389 and Intermediate Phenotypes of Heart Failure in Polish Patients

Heart failure (HF) is a complex disease and a major cause of morbidity and mortality worldwide. Natriuretic peptides (NPs) are involved in the pathogenesis of HF, but their activity may be modified by polymorphisms in the genes encoding them. Aim: To examine the associations of NPPA:rs5065 and NPPB:rs198389 polymorphisms with the risk of HF and cardiovascular phenotypes in Polish patients with HF. The study group comprised 330 HF patients, and the control group comprised 206 healthy newborns. Genomic DNA was extracted from blood, and genotyping of both polymorphisms was performed using polymerase chain reaction-restriction fragment length polymorphism. There were no significant differences in the distributions of NPPA and NPPB genotypes between HF patients and controls. Within the HF group, there were no significant associations between the frequencies of type 2 diabetes, hypertension, left ventricular hypertrophy, or categories of left ventricular ejection fraction (LVEF) and the NPPA or NPPB variants. However, LVEF was significantly higher in NPPA CC homozygotes than in carriers of at least one T allele. The results of our study did not confirm an association between the NPPA:rs5065 or NPPB:rs198389 polymorphisms and predisposition to HF or HF intermediate phenotypes, except for LVEF.

Two-sample bi-directional causality between two traits with some invalid IVs in both directions using GWAS summary statistics

Mendelian randomization (MR) is a widely used method for assessing causal relationships between risk factors and outcomes using genetic variants as instrumental variables (IVs). While traditional MR assumes uni-directional causality, bi-directional MR aims to identify the true causal direction. In uni-directional MR, invalid IVs due to pleiotropy can violate assumptions and introduce biases. In bi-directional MR, traditional MR can be performed separately for each direction, but the presence of invalid IVs poses even greater challenges. We introduce a new bi-directional MR method incorporating stepwise selection (Bidir-SW) designed to address these challenges. Our approach leverages public genome-wide association study (GWAS) datasets for two traits and uses model selection criteria to identify invalid IVs iteratively by stepwise selection. This method accounts for potential bi-directional causality in the presence of common invalid IVs for both directions, even if only GWAS summary statistics are provided. Through simulation studies, we demonstrate that our method outperforms traditional MR techniques, such as MR-Egger and inverse-variance weighted (IVW), with uncorrelated SNPs. We also provide simulations to compare our approach with existing transcriptome-wide association study (TWAS) to show its effectiveness. Finally, we apply the proposed method to genetic traits such as CRP levels and BMI to explore possible bi-directional relationships among these traits. We also used the proposed method to discover causal protein biomarkers. Our findings suggest that the Bidir-SW approach is a powerful tool for bi-directional MR or TWAS, which can provide a valuable framework for future genetic epidemiology studies.

Causal associations between epigenetic age and thromboembolism: a bi-directional two-sample Mendelian randomization study

BACKGROUND

Thromboembolism is one of the most prevalent cardiovascular conditions affecting the elder population. The associations between epigenetic aging and thromboembolism risks remain incompletely elucidated. Through Mendelian randomization (MR), this research seeks to assess the causal links between genetically determined epigenetic aging factors and thromboembolism.

RESULTS

Genetic variants were extracted from genome-wide association studies (GWAS) under stringent threshold as instrumental variables (IVs). Bi-directional two-sample MR analyses were conducted to determine the direction of causal associations. We employed the inverse variance weighted (IVW), weighted median, weighted mode and MR Egger to estimate the causal effect, with sensitivity analyses such as Cochran's Q tests, MR-PRESSO and leave-one-out performed to avoid potential heterogeneity and pleiotropy. Our MR analysis revealed a causal association between intrinsic epigenetic age acceleration and deep vein thrombosis of lower extremities (IVW: OR 0.963, 95% CI 0.934-0.992, P = 0.014), and between the genetically determined levels of plasminogen activator inhibitor-1 and other arterial embolism and thrombosis (IVW: OR 1.000, 95% CI 1.000-1.0005, P = 0.029). Causality was also identified between the genetically predicted levels of FGF23 and other arterial embolism and thrombosis (IVW: OR: 1.661, 95% CI 1.051-2.624, P = 0.029) and arterial embolism and thrombosis of lower extremity artery (IVW: OR 1.68, 95% CI 1.031-2.725, P = 0.037). Moreover, bi-directional MR showed reverse effects between portal vein thrombosis and PhenoAge (IVW: OR 0.871, 95% CI 0.765-0.992, P = 0.037) and between venous thromboembolism and GrimAge (IVW: OR 1.186, 95% CI 1.048-1.341, P = 0.007). Sensitivity analysis using Cochran's Q tests, MR-PRESSO and leave-one-out excluded the influence of heterogeneity, horizontal pleiotropy, and outliers.

CONCLUSION

Our results identified a causal association between genetically predicted epigenetic aging factors and thromboembolism. The findings highlight the necessity for further exploration into the underlying etiology of thromboembolism.

The role of VEGF in Cancer angiogenesis and tumorigenesis: Insights for anti-VEGF therapy

Vascular endothelial growth factor (VEGF) is a critical regulator of angiogenesis, playing a pivotal role in both physiological and pathological processes. It promotes the formation of new blood vessels and activates downstream signaling pathways that regulate endothelial cell function. This review highlights recent advancements in the understanding of VEGF's molecular structure and its isoforms, as well as their implications in disease progression. It also explores the mechanisms of VEGF inhibitors. While VEGF inhibitors show promise in the treatment of cancer and other diseases, their clinical use faces significant challenges, including drug resistance, side effects, and complex interactions with other signaling pathways. To address these challenges, future research should focus on: (i) enhancing the understanding of VEGF subtypes and their distinct roles in various diseases, supporting the development of personalized treatment strategies; (ii) developing combination therapies that integrate VEGF inhibitors with other targeted treatments to overcome resistance and improve efficacy; (iii) optimizing drug delivery systems to reduce off-target effects and enhance therapeutic outcomes. These approaches aim to improve the effectiveness and safety of VEGF-targeted therapies, offering new possibilities for the treatment of VEGF-related diseases.

Causal relationship between serum metalloproteinase 12 levels and aortic dissection and aortic aneurysm: a bidirectional Mendelian randomization study

Background

Elevated matrix metalloproteinase-12 (MMP-12) levels have been shown to be elevated in patients with aortic dissection (AD) and aortic aneurysm (AA). However, whether MMP-12 is associated with AD and AA has not been conclusively examined. The aim of this study was to clarify the role of MMP-12 in AD and AA formation and to verify the correlation between MMP-12 and AD and AA development at the gene level via Mendelian randomization (MR) analysis.

Methods

The data for analyzing MMP-12 gene mutations were obtained from the Integrative Epidemiology Unit (IEU) OpenGWAS database, which includes data from 21,758 European residents. Data on the genetic variation of AD and AA were retrieved from the FinnGen database. In the forward MR analysis, we evaluated the causal effect of MMP-12 on AD and AA. Subsequently, the causal association of AD and AA with MMP-12 was investigated in the reverse MR study. The inverse-variance weighting (IVW) method was the principal statistical technique used in this study.

Results

In the forward MR analysis, the IVW results showed that serum MMP-12 levels were positively related to an increased risk of AD [odds ratio (OR) =1.301; 95% confidence interval (CI): 1.002-1.697; P=0.048] and AA (OR =1.121; 95% CI: 1.007-1.248; P=0.04). For the reverse MR studies, no genetic relationships were observed between AD or AA and MMP-12 levels, nor was any heterogeneity or pleiotropy.

Conclusions

There was a correlation between serum MMP-12 and the risk of AD and AA. MMP-12 may be a potential therapeutic target for AD and AA.

Genetic evidence from Mendelian randomization links CD40 levels to increased risk of estrogen receptor-positive breast cancer

This study uses Mendelian randomization (MR) to investigate the causal roles of CD40 and CD40L in BC.Data from genome-wide association studies (GWAS) on BC (overall, ER-positive, and ER-negative subtypes) and CD40/CD40L levels were obtained from the IEU database. Causal associations were assessed using the inverse-variance weighted (IVW) method, with additional robustness checks performed via MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran's Q test and MR-PRESSO, were conducted to assess heterogeneity and pleiotropy. Reverse MR analyses were also performed to examine if BC influences CD40/CD40L levels.A borderline significant association was found between CD40 levels and overall BC risk (IVW OR 1.027, 95% CI 1.000-1.054, p = 0.049), with a more robust association observed for ER-positive BC (OR 1.048, 95% CI 1.016-1.082, p = 0.003). No significant associations were found between CD40 levels and ER-negative BC. CD40L did not show any significant associations with BC. Reverse MR analysis indicated no causal effect of BC on CD40/CD40L levels. CD40 is causally associated with a borderline increase in overall BC risk and a more significant increase in ER-positive BC risk. These findings suggest a potential role for CD40 in BC, particularly in ER-positive cases.

Widespread recessive effects on common diseases in a cohort of 44,000 British Pakistanis and Bangladeshis with high autozygosity

Genetic association studies have focused on testing additive models in cohorts with European ancestry. Little is known about recessive effects on common diseases, specifically for non-European ancestry. Genes & Health is a cohort of British Pakistani and Bangladeshi individuals with elevated rates of consanguinity and endogamy, making it suitable to study recessive effects. We imputed variants into a genotyped dataset (n = 44,190) by using two reference panels: a set of 4,982 whole-exome sequences from within the cohort and the Trans-Omics for Precision Medicine (TOPMed-r2) panel. We performed association testing with 898 diseases from electronic health records. 185 independent loci reached genome-wide significance (p < 5 × 10-8) under the recessive model, with p values lower than under the additive model, and >40% of these were novel. 140 loci demonstrated nominally significant (p < 0.05) dominance deviation p values, confirming a recessive association pattern. Sixteen loci in three clusters were significant at a Bonferroni threshold, accounting for multiple phenotypes tested (p < 5.4 × 10-12). In FinnGen, we replicated 44% of the expected number of Bonferroni-significant loci we were powered to replicate, at least one from each cluster, including an intronic variant in patatin-like phospholipase domain-containing protein 3 (PNPLA3; rs66812091) and non-alcoholic fatty liver disease, a previously reported additive association. We present evidence suggesting that the association is recessive instead (odds ratio [OR] = 1.3, recessive p = 2 × 10-12, additive p = 2 × 10-11, dominance deviation p = 3 × 10-2, and FinnGen recessive OR = 1.3 and p = 6 × 10-12). We identified a novel protective recessive association between a missense variant in SGLT4 (rs61746559), a sodium-glucose transporter with a possible role in the renin-angiotensin-aldosterone system, and hypertension (OR = 0.2, p = 3 × 10-8, dominance deviation p = 7 × 10-6). These results motivate interrogating recessive effects on common diseases more widely.

Identification of novel plasma proteins as promising noninvasive biomarker for early diagnosis and surveillance of pancreatic ductal adenocarcinoma

BACKGROUND

Although cancer antigen 19-9 (CA 19-9) is the only FDA-approved biomarker for pancreatic ductal adenocarcinoma (PDAC), its diagnostic effectiveness is limited, as it may not be elevated in 15-25% of patients. This study aims to explore novel plasma proteins associated with PDAC as potential biomarkers for early diagnosis and clinical surveillance.

METHODS

Novel plasma protein biomarkers potentially causally associated with PDAC were identified using Mendelian randomization (MR). These biomarkers were validated in a multicenter study encompassing 230 tissue and 1,011 plasma samples to establish a diagnostic model for PDAC. Furthermore, their pre- and post-operative levels were compared to evaluate their potential as clinical surveillance biomarkers.

RESULTS

Genetically predicted expression of seven proteins potentially causally associated with an increased risk of PDAC. In a multicenter, large-scale study, Keratin 5 (KRT5) and Versican (VCAN) were identified as promising biomarkers for PDAC, with an area under the curve (AUC) of 0.90, and a combined panel including CA 19-9 achieved an AUC of 0.95. Additionally, plasma KRT5 and VCAN demonstrated superior diagnostic performance for early-stage PDAC with CA 19-9 levels below 37 U/mL (Stage I, AUC 0.85; Stage II, AUC 0.85). The specificity of plasma KRT5 and VCAN for PDAC was further validated by comparing their expression levels across various digestive cancers. Moreover, a significant decrease in plasma KRT5 and VCAN levels was observed post-surgery (P < 0.05), supporting their potential as biomarkers for clinical surveillance of PDAC.

CONCLUSIONS

Plasma KRT5 and VCAN proteins may serve as promising valuable biomarkers for the early diagnosis and clinical surveillance of PDAC.

Epigenomic and proteomic analyses provide insights into early-life immune regulation and asthma development in infants

Infants with severe bronchiolitis (i.e., bronchiolitis requiring hospitalization) face increased risks of respiratory diseases in childhood. We conduct epigenome-wide association studies in a multi-ethnic cohort of these infants. We identify 61 differentially methylated regions in infant blood (<1 year of age) associated with recurrent wheezing by age 3 (170 cases, 318 non-cases) and/or asthma by age 6 (112 cases, 394 non-cases). These differentially methylated regions are enriched in the enhancers of peripheral blood neutrophils. Several differentially methylated regions exhibit interaction with rhinovirus infection and/or specific blood cell types. In the same blood samples, circulating levels of 104 proteins correlate with the differentially methylated regions, and many proteins show phenotypic association with asthma. Through Mendelian randomization, we find causal evidence supporting a protective role of higher plasma ST2 (also known as IL1RL1) protein against asthma. DNA methylation is also associated with ST2 protein level in infant blood. Taken together, our findings suggest the contribution of DNA methylation to asthma development through regulating early-life systemic immune responses.

Genetic associations of plasma proteins and breast cancer identify potential therapeutic drug candidates

To address the pressing need to improve breast cancer outcomes, we identify 9 plasma proteins with significant associations to breast cancer, namely ULK3, CSK, ASIP, TLR1 in breast cancer, ADH5, SARS2, ULK3, UBE2N in Luminal A subtype, PEX14 in Luminal B subtype. Tumor immune cell infiltration analysis and mutation phenotypes in mice further demonstrate a complex pattern of interaction between these genes and immune responses. Compared to normal tissues, tumor tissues exhibit reduced expression of ULK3 and CSK. Notably, elevated ULK3 expression in both breast cancer and the Luminal A subtype is significantly associated with prolonged recurrence-free survival. Overexpression of CSK and ULK3 is confirmed to significantly inhibit the proliferation and migratory ability of MCF-7 cells. Additionally, three drug candidates-TG100801, Hydrochlorothiazide, and Imatinib-show promise in targeting these proteins, contributing valuable insights for prioritizing drug development in realm of breast cancer.

T Cells Promote Distinct Transcriptional Programs of Cutaneous Inflammatory Disease in Keratinocytes and Dermal Fibroblasts

T cells and structural cells coordinate appropriate inflammatory responses and restoration of barrier integrity following insult. Dysfunctional T cells precipitate skin pathology occurring alongside altered structural cell frequencies and transcriptional states, but to what extent different T cells promote disease-associated changes remains unclear. We show that functionally diverse circulating and skin-resident CD4+CLA+ T-cell populations promote distinct transcriptional outcomes in human keratinocytes and fibroblasts associated with inflamed or healthy tissue. We identify T helper 17 cell-induced genes in keratinocytes that are enriched in psoriasis patient skin and normalized by anti-IL-17 therapy. We also describe a CD103+ skin-resident T-cell-induced transcriptional module enriched in healthy controls that is diminished during psoriasis and scleroderma and show that CD103+ T-cell frequencies are altered during disease. Interrogating clinical data using immune-dependent transcriptional signatures defines the T-cell subsets and genes distinguishing inflamed from healthy skin and allows investigation of heterogeneous patient responses to biologic therapy.

Applications of Artificial Intelligence in Drug Repurposing

Drug repurposing identifies new therapeutic uses for the existing drugs originally developed for different indications, aiming at capitalizing on the established safety and efficacy profiles of known drugs. Thus, it is beneficial to bypass of early stages of drug development, and to reduction of the time and cost associated with bringing new therapies to market. Traditional experimental methods are often time-consuming and expensive, making artificial intelligence (AI) a promising alternative due to its lower cost, computational advantages, and ability to uncover hidden patterns. This review focuses on the availability of AI algorithms in drug development, and their positive and specific roles in revealing repurposing of the existing drugs, especially being integrated with virtual screening. It is shown that the existing AI algorithms excel at analyzing large-scale datasets, identifying the complicated patterns of drug responses from these datasets, and making predictions for potential drug repurposing. Building on these insights, challenges remain in developing efficient AI algorithms and future research, including integrating drug-related data across databases for better repurposing, enhancing AI computational efficiency, and advancing personalized medicine.

Genetic effects of circulating hormone and proteome on amyotrophic lateral sclerosis identified by Mendelian randomization

Altered circulating hormones in ALS patients have been widely reported by previous observational studies, but whether these relationships are causal is unclear. Moreover, the potential therapeutic targets for ALS and the effects of plasma protein fluctuation on ALS progression are not fully understood. Therefore, we conducted a Mendelian randomization (MR) study to evaluate the causal role of 5 hormonal risk factors (insulin-like growth factor-1, IGF-1; sex hormone-binding globulin, SHBG; free testosterone, FT; total testosterone, TT; and estradiol) in ALS risk. Furthermore, we screened up to 90 circulating proteins including cytokines, chemokines, growth factors, and interferons, to identify potential therapeutic targets for ALS. Our MR analysis found genetically predicted higher level of FT was associated with a 23% lowered risk of ALS. Further screening of proteomic traits found that 12 plasma proteins were causally associated with ALS. These findings suggest that higher FT potentially exerts a protective effect on ALS risk. Several proteins may act as potential circulating biomarkers and therapeutic targets for ALS. In the future, high-throughput proteomic analyses and experimental explorations are likely needed to clarify the regulated role and mechanistic pathways.

Mendelian randomization-based observational cohort study on drug targets: Impact of antihypertensive and lipid-lowering therapies on inflammatory cytokines

This study assesses the causal effects of antihypertensive and lipid-lowering drugs on inflammatory cytokines using a Mendelian randomization (MR) approach. We conducted a drug-targeted MR analysis using data from large-scale genome-wide association studies and eQTL datasets. SNPs near drug target genes served as instrumental variables to investigate the impact of antihypertensive (angiotensin-converting enzyme inhibitors [ACEIs], ARBs) and lipid-lowering drugs (HMGCR inhibitors, proprotein convertase subtilisin/Kexin type 9 [PCSK9] inhibitors, Niemann-Pick C1-like 1 inhibitors) on inflammatory cytokines. Sensitivity analyses, including leave-one-out and MR-Egger tests, were performed to confirm the robustness of the findings. ACEIs were associated with decreased levels of IL-1β, TNF-α, and CRP. ARBs did not show significant effects on inflammatory cytokines. HMGCR inhibitors significantly reduced MCP-1, MIP-1β, TNF-α, and IFN-γ, while PCSK9 inhibitors were linked to reductions in IL-1β and IL-6. Sensitivity analyses supported the reliability of these findings. The study demonstrated distinct anti-inflammatory effects of ACEIs, HMGCR inhibitors, and PCSK9 inhibitors. These findings support the potential use of these drugs to mitigate inflammation-related complications in patients with chronic conditions.

Mendelian randomization of plasma proteomics identifies novel ALS-associated proteins and their GO enrichment and KEGG pathway analyses

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurological disorder with an increasing incidence rate. Despite advances in ALS research over the years, the precise etiology and pathogenic mechanisms remain largely elusive.

OBJECTIVE

To identify novel plasma proteins associated with ALS through Mendelian randomization methods in large-scale plasma proteomics and to provide potential biomarkers and therapeutic targets for ALS treatment.

METHODS

This study employed a large-scale plasma proteomic Mendelian randomization approach using genetic data from 80,610 individuals of European ancestry (including 20,806 ALS patients and 59,804 controls) derived from a genome-wide association study (GWAS). Protein quantitative trait loci (pQTLs) data were obtained from Ferkingstad et al. (2021), which measured 4,907 proteins in 35,559 Icelandic individuals. Multiple Mendelian randomization (MR) techniques were utilized, including weighted median, MR-Egger, Wald ratio, inverse-variance weighting (IVW), basic model, and weighted model. Heterogeneity was evaluated using Cochran's Q test. Horizontal pleiotropy was assessed through the MR-Egger intercept test and MR-PRESSO outlier detection. Sensitivity analysis was performed via leave-one-out analysis.

RESULTS

MR analysis revealed potential causal associations between 491 plasma proteins and ALS, identifying 19 novel plasma proteins significantly linked to the disease. Proteins such as C1QC, UMOD, SLITRK5, ASAP2, TREML2, DAPK2, ARHGEF10, POLM, SST, and SIGLEC1 showed positive correlations with ALS risk, whereas ADPGK, BTNL9, COLEC12, ADGRF5, FAIM, CRTAM, PRSS3, BAG5, and PSMD11 exhibited negative correlations. Reverse MR analyses confirmed that ALS negatively correlates with ADPGK and ADGRF5 expression. Enrichment analyses, including Gene Ontology (GO) functional analysis, indicated involvement in critical biological processes such as external encapsulating structure organization, extracellular matrix organization, chemotaxis, and taxis. KEGG pathway analysis highlighted significant enrichment in the PI3K-Akt signaling pathway, cytokine-cytokine receptor interactions, and axon guidance.

CONCLUSION

This study enhances the understanding of ALS pathophysiology and proposes potential biomarkers and mechanistic insights for therapeutic development. Future research should explore the clinical translation of these findings to improve ALS patient outcomes and quality of life.

Plasma proteome variation and its genetic determinants in children and adolescents

Our current understanding of the determinants of plasma proteome variation during pediatric development remains incomplete. Here, we show that genetic variants, age, sex and body mass index significantly influence this variation. Using a streamlined and highly quantitative mass spectrometry-based proteomics workflow, we analyzed plasma from 2,147 children and adolescents, identifying 1,216 proteins after quality control. Notably, the levels of 70% of these were associated with at least one of the aforementioned factors, with protein levels also being predictive. Quantitative trait loci (QTLs) regulated at least one-third of the proteins; between a few percent and up to 30-fold. Together with excellent replication in an additional 1,000 children and 558 adults, this reveals substantial genetic effects on plasma protein levels, persisting from childhood into adulthood. Through Mendelian randomization and colocalization analyses, we identified 41 causal genes for 33 cardiometabolic traits, emphasizing the value of protein QTLs in drug target identification and disease understanding.

An in-depth review of AI-powered advancements in cancer drug discovery

The convergence of artificial intelligence (AI) and genomics is redefining cancer drug discovery by facilitating the development of personalized and effective therapies. This review examines the transformative role of AI technologies, including deep learning and advanced data analytics, in accelerating key stages of the drug discovery process: target identification, drug design, clinical trial optimization, and drug response prediction. Cutting-edge tools such as DrugnomeAI and PandaOmics have made substantial contributions to therapeutic target identification, while AI's predictive capabilities are driving personalized treatment strategies. Additionally, advancements like AlphaFold highlight AI's capacity to address intricate challenges in drug development. However, the field faces significant challenges, including the management of large-scale genomic datasets and ethical concerns surrounding AI deployment in healthcare. This review underscores the promise of data-centric AI approaches and emphasizes the necessity of continued innovation and interdisciplinary collaboration. Together, AI and genomics are charting a path toward more precise, efficient, and transformative cancer therapeutics.

Exploring the Causal Relationship Between the Plasma Levels of MMP1 (Matrix Metalloproteinase-1), MMP3, MMP7, MMP10, and MMP12 and Intervertebral Disc Degeneration: Mendelian Randomization

Background

Several matrix metalloproteinases (MMPs) have been reported to be associated with intervertebral disc degeneration (IDD) in several previous studies. However, the causal relationship between MMPs and IDD remains unclear. In this study, Mendelian randomization (MR) was used to analyze the causal relationship between the plasma levels of multiple MMPs and the risk of IDD.

Methods

The GWAS data of the plasma levels of MMP1, MMP3, MMP7, MMP10, and MMP12 were derived from the genome-wide variation associations of 21 758 European individuals. The genetic associations of the variants with IDD were investigated in the largest genome-wide association study from GWAS pipeline using Phesant derived variables from UKBiobank (1045 cases; 461 965 controls). We used a two-sample MR method to evaluate the causal relationship between these five MMPs and IDD. The causal effects were examined by inverse variance weighted (IVW) test. And sensitivity analysis was performed using Q test of IVW and MR-Egger, MR-Egger-intercept and MR-PRESSO.

Results

We found a significant correlation between increased the plasma level of MMP3 and an increased risk of IDD (IVW: OR 1.000564, 95% CI 1.0000304-1.00110; p = 0.0383). The heterogeneity test (MR-Egger Q test: p = 0.346 and IVW Q test: p = 0.460) indicated that there was no heterogeneity in this instrumental variable on the surface. Also, no directional horizontal pleiotropy was observed in the MR analysis (MR-Egger, p = 0.708 and MR-PRESSO, p = 0.609). There was no significant correlation between the plasma levels of MMP1, MMP7, MMP10, and MMP12 and an increased risk of IDD.

Conclusion

Our MR analysis found that there is a potential causal relationship between increased the plasma level of MMP3 and the risk of IDD in the European population. There is no potential causal relationship between the plasma levels of MMP1, MMP7, MMP10, and MMP12 and an increased risk of IDD.

Causal Association Between Major Depressive Disorder and Cortical Structure: A Bidirectional Mendelian Randomization Study and Mediation Analysis

BACKGROUND

Previous observational studies have reported a possible association between major depressive disorder (MDD) and abnormal cortical structure. However, it is unclear whether MDD causes reductions in global cortical thickness (CT) and global area (SA).

OBJECTIVE

We aimed to test the bidirectional causal relationship between MDD and CT and SA using a Mendelian randomization (MR) design and performed exploratory analyses of MDD on CT and SA in different brain regions.

METHODS

Summary-level data were obtained from two GWAS meta-analysis studies: one screening for single nucleotide polymorphisms (SNPs) predicting the development of MDD (n = 135,458) and the other identifying SNPs predicting the magnitude of cortical thickness (CT) and surface area (SA) (n = 51,665).

RESULTS

The results showed that MDD caused a decrease in CT in the medial orbitofrontal region, a decrease in SA in the paracentral region, and an increase in SA in the lateral occipital region. C-reactive protein, tumor necrosis factor alpha (TNF-α), interleukin-1β, and interleukin-6 did not mediate the reduction. We also found that a reduction in CT in the precentral region and a reduction in SA in the orbitofrontal regions might be associated with a higher risk of MDD.

CONCLUSION

Our study did not suggest an association between MDD and cortical CT and SA.

Cardio-metabolic-related plasma proteins reveal biological links between cardiovascular diseases and fragility fractures: a cohort and Mendelian randomisation investigation

BACKGROUND

How cardiovascular diseases (CVD) predispose to a higher risk of fragility fractures is not well understood. Both contribute to significant components of disease burden and health expenditure. Poor bone quality, central obesity, sarcopenia, falls, and low grip strength are independent risk factors for hip and other fragility fractures and also for CVD and early death.

METHODS

We used proteomics and a cohort design combined with Mendelian randomisation analysis to understand shared mechanisms for developing CVD and fragility fractures, two significant sources of disease burden and health expenditure. We primarily aimed to discover and replicate the association of 274 cardio-metabolic-related proteins with future rates of hip and any fracture in two separate population-based cohorts, with a total of 12,314 women and men.

FINDINGS

The average age at baseline was 68 years in the discovery cohort of women and 74 years in the mixed-sex replication cohort. During 100,619 person-years of follow-up, 2168 had any fracture, and 538 had a hip fracture. Our analysis resulted in 24 cardiometabolic proteins associated with fracture risk: 20 with hip fracture, 9 with any fracture, and 5 with both. The associations remained even if protein concentrations were measured from specimens taken during preclinical stages of cardio-metabolic diseases, and 19 associations remained after adjustment for bone mineral density. Twenty-two of the proteins were associated with total body fat mass or lean body mass. Mendelian randomisation (MR) analysis supported causality since genetically predicted levels of SOST (Sclerostin), CCDC80 (Coiled-coil domain-containing protein 80), NT-proBNP (N-terminal prohormone brain natriuretic peptide), and BNP (Brain natriuretic peptide) were associated with risk of hip fracture. MR analysis also revealed a possible negative impact on bone mineral density (BMD) by genetically predicted higher levels of SOST, CCDC80, and TIMP4 (Metalloproteinase inhibitor 4). The MR association with BMD was positive for PTX3 (Pentraxin-related protein) and SPP1 (Osteopontin). Genetically predicted higher concentrations of SOST and lower concentrations of SPP1 also conferred a higher risk of falls and lowered grip strength. The genetically determined concentration of nine proteins influenced fat mass, and one influenced lean body mass.

INTERPRETATION

These data reveal biological links between cardiovascular diseases and fragility fractures. The proteins should be further evaluated as shared targets for developing pharmacological interventions to prevent fractures and cardiovascular disease.

FUNDING

The study was supported by funding from the Swedish Research Council (https://www.vr.se; grants No. 2015-03257, 2017-00644, 2017-06100, and 2019-01291 to Karl Michaëlsson) and funding from Olle Engkvist Byggmästares stiftelse (SOEB).

Causal inference of inflammatory proteins in infertility: a Mendelian randomization study

Background

Infertility affects 8-12% of couples globally, manifesting as a complex reproductive disorder with varied causes, negatively impacting emotional, physical, and social well-being. Inflammation is implicated in many diseases, including male and female infertility.

Methods

This study employed Mendelian randomization (MR) with two-sample, bidirectional, and mediation approaches to explore the relationship between circulating inflammatory proteins and infertility. Causal analysis was conducted using inverse variance-weighted (IVW) and MR-Egger regression, supplemented by enrichment analysis, protein-protein interaction (PPI) network exploration, and drug signature analysis.

Results

Our findings identified a significant positive correlation between C-X-C motif chemokine 6 (CXCL6) and male infertility, positioning CXCL6 as a potential therapeutic target or biomarker. No causal links were detected between circulating inflammatory proteins and female infertility post-FDR adjustment. Minor mediation effects were observed for metabolites such as androstenediol monosulfate, arachidonoylcholine, and serum phosphate to glycerol ratio. Cytokine-related pathways emerged as significant in both male and female infertility. Gene-drug interaction analysis highlighted the need for further investigation of pioglitazone in treating female infertility.

Conclusion

This study establishes a potentially causal relationship between CXCL6 and male infertility, suggesting its potential as a drug target or molecular biomarker. The integrative approach combining causal inference with molecular pathway and drug interaction analysis opens new avenues for understanding and treating infertility.

PSMB4: a potential biomarker and therapeutic target for depression, perspective from integration analysis of depression GWAS data and human plasma proteome

Depression is a common and severe mental disorder that affects more than 300 million people worldwide. While it is known to have a moderate genetic component, identifying specific genes that contribute to the disorder has been challenging. Previous Genome-wide association studies (GWASs) have identified over 100 genomic loci that are significantly associated with depression. But finding useful therapeutic targets and diagnostic biomarkers from this information has proven difficult. To address this challenge, I conducted a plasma protein proteome-wide association study (PWAS) for depression, using human plasma protein QTL (pQTL) and depression GWAS data. I identified four proteins that were significantly associated with depression: BTN3A3 (P value = 6.41 × 10-06), PSMB4 (P value = 1.42 × 10-05), TIMP4 (P value = 3.77 × 10-05), and ITIH1 (P value = 7.86 × 10-05). Specifically, I found that BTN3A3 and PSMB4 play a causal role in depression, as confirmed by colocalization and Mendelian Randomization (MR) analysis. Interestingly, I also discovered that PSMB4 was significantly associated with depression in both the brain proteome studies and the plasma PWAS results, which suggests that it may be a particularly promising candidate for further study. Overall, this work has identified 4 new risk proteins for depression and highlights the potential of plasma proteome data for uncovering novel therapeutic targets and diagnostic biomarkers.

Genetic and Epigenetic Intersections in COVID-19-Associated Cardiovascular Disease: Emerging Insights and Future Directions

The intersection of COVID-19 and cardiovascular disease (CVD) has emerged as a significant area of research, particularly in understanding the impact of antiplatelet therapies like ticagrelor and clopidogrel. COVID-19 has been associated with acute cardiovascular complications, including myocardial infarction, thrombosis, and heart failure, exacerbated by the virus's ability to trigger widespread inflammation and endothelial dysfunction. MicroRNAs (miRNAs) play a critical role in regulating these processes by modulating the gene expressions involved in platelet function, inflammation, and vascular homeostasis. This study explores the potential of miRNAs such as miR-223 and miR-126 as biomarkers for predicting resistance or responsiveness to antiplatelet therapies in COVID-19 patients with cardiovascular disease. Identifying miRNA signatures linked to drug efficacy could optimize treatment strategies for patients at high risk of thrombotic events during COVID-19 infection. Moreover, understanding miRNA-mediated pathways offers new insights into how SARS-CoV-2 exacerbates CVD, particularly through mechanisms like cytokine storms and endothelial damage. The findings of this research could lead to personalized therapeutic approaches, improving patient outcomes and reducing mortality in COVID-19-associated cardiovascular events. With global implications, this study addresses the urgent need for effective management of CVD in the context of COVID-19, focusing on the integration of molecular biomarkers to enhance the precision of antiplatelet therapy.

Genetic association between inflammatory factors and abdominal aortic aneurysm: Insights from a genome-wide association study

BACKGROUND

Abdominal aortic aneurysm (AAA) is a fatal vascular disorder. The current primary treatment for AAA remains restricted to surgical intervention during advanced stages of the disease, with no efficacious pharmaceutical options available for early-stage AAA patients. Inflammation is known to play a substantial role in the development of AAA, with various inflammatory factors implicated in its pathogenesis. However, conflicting findings have been reported in studies investigating the roles of these inflammatory factors in AAA, making it challenging to establish definitive causal relationships between inflammatory factors and AAA.

METHODS

The research conducted a bidirectional Mendelian randomization (MR) study using genetic variants. Inflammatory factors were obtained from a genome-wide association study (GWAS), while AAA were sourced from the FinnGen consortium. The primary method employed was inverse-variance weighted (IVW), with MR-Egger, weighted median, and MR-PRESSO approaches used as supplementary analyses.

RESULTS

According to the IVW method, hepatocyte growth factor (HGF), matrix metalloproteinase-7 (MMP-7), MMP-12, and NF-kappa-B essential modulator (NEMO/ IKKγ) were associated with a potential increased risk of AAA, while platelet-derived growth factor BB (PDGFbb), interleukin-4 (IL-4), IL-12p70, IL-10, IL-6Rα, and myeloperoxidase (MPO) were associated with a potential decreased risk of AAA. In the reverse MR analysis, no causal relationship was observed between AAA and any of the inflammatory factors.

CONCLUSIONS

This study provides evidence supporting a causal relationship between inflammatory factors and AAA. It suggests that targeting and modulating these specific inflammatory factors may serve as a potential approach for the prevention and noninvasive treatment of AAA.

An integrated multi-omics analysis identifies protein biomarkers and potential drug targets for psoriatic arthritis

Psoriatic arthritis (PsA) is a complex, chronic immune-mediated inflammatory arthropathy that currently lacks definitive biomarkers and treatment targets. Identifying biomarkers and treatment targets is urgently needed for effectively managing PsA. Here, we conducted a multi-omics approach to identify protein biomarkers and potential drug targets for psoriatic arthritis. Proteome-wide Mendelian randomization (MR) analysis revealed seven plasma protein biomarkers significantly associated with PsA. Specifically, genetically predicted lower levels of NEO1 were linked to an increased PsA risk, whereas the remaining six proteins (IL23R, ERAP2, IFNLR1, KIR2DL3, CLSTN3, and POLR2F) exhibited a positive association with PsA risk. PPI analysis further supported these findings. Notably, druggability assessment revealed that scopoletin and esculetin were the two most significant drugs associated with ERAP2. Single-cell RNA-seq analysis revealed expression of IL23R, ERAP2, CLSTN3, and POLR2F in distinct T-cell subgroups of PBMCs derived from PsA patients. Furthermore, phenome-wide association studies (PheWAS) analysis assessed the potential side effects and safety as potential drug targets. Interestingly, experimental evidence showed that IFNLR1 expression is significantly upregulated under simulated inflammatory conditions. This study employed proteome-wide mendelian randomization to identify seven plasma proteins associated with PsA, including IL23R, ERAP2 and IFNLR1, offering potential insights for personalized PsA treatment strategies.

Cross-Ancestry Comparison of Aptamer and Antibody Proteomics Measures

Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants (pQTL) and phenotypes. Here, we examined 2,157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1,930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2,157 proteins followed a bimodal distribution (median r=0.30). Protein measures from each platform were associated with genetic variants (pQTLs), and one-third of the pQTL signals were driven by protein-altering variants (PAVs). We highlight 80 proteins that correlate differently across ancestry groups likely due to differing PAV frequencies by ancestry. Furthermore, adjustment for PAVs with opposite directions of effect by platform improved inter-platform protein measure correlation and resulted in more concordant genetic and phenotypic associations. Hence, PAVs need to be accounted for across ancestries to facilitate platform-concordant and accurate protein measurement.

Causal links between obesity, lipids, adipokines, and cognition: a bidirectional Mendelian-randomization analysis

Background

The aim of this study was to explore the genetic level association between obesity, lipids, adipokines, and cognitive ability using bidirectional Mendelian randomization (MR) strategies.

Methods

Summary data for three obesity indicators [body mass index (BMI), body fat percentage (BFP) and waist-hip ratio (WHR)], three lipid indicators [HDL cholesterol (HDL), LDL cholesterol (LDL) and triglycerides (TG)], three adipokines [circulating leptin (LEP), Agouti-related protein (AgRP) and Adiponectin (APDN)], and four cognitive ability indicators [cognitive function (CF), cognitive performance (CP), simple reaction time (SRT) and fluid intelligence score (FIS)] were collected. Bidirectional inverse-variance weighted Mendelian randomization (MR) was employed to evaluate the relationship between adiposity and cognitive function. We employed genetic instruments for adiposity indicators as exposures in one direction, and repeated the analysis in the opposite direction using instruments for cognitive function. Sensitivity analyses were conducted to explore heterogeneity and potential horizontal pleiotropy.

Results

Genetically predicted adiposity showed robust associations with markers of cognitive ability. Higher genetically predicted obesity indicators (such as BMI, BFP and WHR), and lipid and adipokineslevels (such as HDL and AgRP) with reduced cognitive ability indicators (such as CF and CP). In the opposite direction, FIS and SRT may influence BMI and HDL respectively. MR estimates for the effects of cognition ability on all obesity, lipids and adipokines measures indicated worse FIS and SRT were associated with higher BMI and lower HDL.

Conclusions

Our MR reveals that high BMI, BFP, WHR and AgRP have negative causal direct effects with cognitive ability, while high HDL and ADPN have positive causal direct effects with cognitive ability. For the reverse causal direction, our consistent findings that worse cognitive function such as SRT and FIS may influence serum HDL level and BMI.

Causal association of inflammation with ischemic stroke and its subtypes: a bidirectional Mendelian randomization study

BACKGROUND

Emerging evidence underscores a bidirectional relationship between ischemic stroke (IS) and inflammation, yet the causality of this association remains uncertain. We conducted a two-sample bidirectional Mendelian randomization (MR) study aimed at investigating the causal links between inflammation and IS.

METHODS

Single nucleotide polymorphism from genome-wide association studies of 112 inflammatory cytokines and IS were chosen as instrumental variables. We evaluated the causal effects of inflammatory factors on IS outcomes and examined the mediating effects of risk factors for IS. Additionally, reverse MR analysis was conducted to determine whether the occurrence of IS influenced levels of inflammatory cytokines. Causal associations were assessed using inverse variance weighting, complemented by sensitivity analyses incorporating weighted median and MR-Egger methods.

RESULTS

We found associations between genetically predicted plasma levels of 25 inflammatory factors and IS along with its subtypes. MR supports smoking, body mass index, atrial fibrillation, coronary artery disease, heart failure, systolic blood pressure, diastolic blood pressure and type 2 diabetes as risk factors for IS. Notably, coronary artery disease and heart failure seemed to mediate the RANTES, HGF, IL-5 associations with IS. In addition, reverse MR analysis suggested a causal relationship between IS and its subtypes and 19 inflammatory factors.

CONCLUSION

In summary, inflammation was suggestively causally associated with the risk of IS, and inflammatory cytokines had downstream effect on IS. Future studies should explore whether inflammatory factors found to have significant associations with IS risk could be manipulated to reduce IS risk, and the neuroinflammatory mechanisms after IS.

Human Genetic Evidence to Inform Clinical Development of IL-6 Signaling Inhibition for Abdominal Aortic Aneurysm

BACKGROUND

Abdominal aortic aneurysm (AAA) represents a significant cause of mortality, yet no medical therapies have proven efficacious. The aim of the current study was to leverage human genetic evidence to inform clinical development of IL-6 (interleukin-6) signaling inhibition for the treatment of AAA.

METHODS

Associations of rs2228145, a missense variant in the IL6R gene region, are expressed per additional copy of the C allele, corresponding to the genetically predicted effect of IL-6 signaling inhibition. We consider genetic associations with AAA risk in the AAAgen consortium (39 221 cases and 1 086 107 controls) and UK Biobank (1963 cases and 365 680 controls). To validate against known effects of IL-6 signaling inhibition, we present associations with rheumatoid arthritis, polymyalgia rheumatica, and severe COVID-19. To explore mechanism specificity, we present associations with thoracic aortic aneurysm, intracranial aneurysm, and coronary artery disease. We further explored genetic associations in clinically relevant subgroups of the population.

RESULTS

We observed strong genetic associations with AAA risk in the AAAgen consortium, UK Biobank, and FinnGen (odds ratios: 0.91 [95% CI, 0.90-0.92], P=4×10-30; 0.90 [95% CI, 0.84-0.96], P=0.001; and 0.86 [95% CI, 0.82-0.91], P=7×10-9, respectively). The association was similar for fatal AAA but with greater uncertainty due to the lower number of events. The association with AAA was of greater magnitude than associations with coronary artery disease and even rheumatological disorders for which IL-6 inhibitors have been approved. No strong associations were observed with thoracic aortic aneurysm or intracranial aneurysm. Associations attenuated toward the null in populations with concomitant rheumatological or connective tissue disease.

CONCLUSIONS

Inhibition of IL-6 signaling is a promising strategy for treating AAA but not other types of aneurysmal disease. These findings serve to help inform clinical development of IL-6 signaling inhibition for AAA treatment.

Genetic factors shaping the plasma lipidome and the relations to cardiometabolic risk in children and adolescents

BACKGROUND

Lipid species are emerging as biomarkers for cardiometabolic risk in both adults and children. The genetic regulation of lipid species and their impact on cardiometabolic risk during early life remain unexplored.

METHODS

Using mass spectrometry-based lipidomics, we measured 227 plasma lipid species in 1149 children and adolescents (44.8% boys) with a median age of 11.2 years. We performed genome-wide association analyses to identify genetic variants influencing lipid species. Colocalisation and Mendelian randomisation (MR) analyses were performed to infer causality between lipid species and cardiometabolic outcomes.

FINDINGS

We identified 37 genome-wide significant loci for 52 lipid species, nine of which are previously unreported. Colocalisation analyses revealed that seven lipid loci shared genetic variants associated with adult cardiometabolic outcomes. One-sample MR analysis identified positive causal associations between ceramides and liver enzymes, sphingomyelins and hemoglobin A1c (HbA1c), and phosphatidylethanolamines and high-sensitivity C-reactive protein in children and adolescents. Two-sample MR using adult-based summary statistics showed consistent direction of associations and indicated additional causal links, specifically between ceramides and elevated HbA1c levels, and phosphatidylinositols with elevated liver enzymes.

INTERPRETATION

These findings highlight the potential long-term implications of plasma lipid genetic determinants on cardiometabolic risk.

FUNDING

Novo Nordisk Foundation, The Innovation Fund Denmark, The Danish Heart Foundation, EU Horizon, and LundbeckFonden.

Genetically Predicted Vascular Proteins and Risk of Intracranial Aneurysms: A Mendelian Randomization Study

The relationship between vascular proteins (VPs) and intracranial aneurysms (IAs) has not been fully elucidated. We used Mendelian randomization (MR) analysis to explore the effect of VPs on IAs. Dataset of aneurysmal subarachnoid hemorrhage (aSAH) [5140 cases and 71,934 controls] and unruptured intracranial aneurysm (uIA) [2070 cases and 71,934 controls] were obtained from individuals of European ancestry. Univariate MR was used to explore the associations between 90 VPs and IAs. Then, we performed multivariate MR (MVMR) to further investigate the identified VP-to-IA estimates. Two-sample MR showed that TNFSF14 was inversely associated with aSAH (odds ratio [OR] = 0.831, 95% CI: 0.713-0.969, p = 0.018). IL-16 (OR = 1.218, 95% CI: 1.032-1.438, p = 0.020) and AgRP (OR = 1.394, 95% CI: 1.048-1.855, p = 0.023) were positively associated with aSAH. HBEGF (OR = 0.642, 95% CI: 0.461-0.894, p = 0.009), MCP-1 (OR = 1.537, 95% CI: 1.007-2.344, p = 0.046), and CX3CL1 (OR = 0.762, 95% CI: 0.581-0.999, 0.049 < p < 0.050) were associated with uIA risk. The MVMR showed that the TNFSF14-to-aSAH estimate remained statistically significant after adjustment for past tobacco smoking, alcohol consumption, systolic blood pressure and body mass index. Our study indicated that low serum TNFSF14 levels might be a potential risk factor for IA rupture. Five VPs (HBEGF, MCP-1, IL-6, CX3CL1, and AgRP) are associated with the risk of IAs (both uIA and aSAH).

The causal effect of matrix metalloproteinase-3 on ankylosing spondylitis: Evidence from Mendelian randomization

Previous investigations through observation have found that matrix metalloproteinase-3 (MMP-3) has benefits for ankylosing spondylitis (AS) but it is uncertain whether there is a true positive causal connection. Our goal was to demonstrate the relationship between AS and MMP-3. We executed Mendelian randomization (MR) research utilizing genome-wide association studies genetic data (n = 21,758) for MMP-3 publicly available from IEU Open and genome-wide association studies data for AS (n = 297,932) from FinnGen Biobank. The specific MR protocols were weighted median, weighted mode, MR-Egger, and inverse-variance weighted (IVW). Subsequently, the Cochran Q evaluate, MR pleiotropy residual sum and outlier, and MR-Egger intercept were used to evaluate the heterogeneity and multiplicative effects of instrumental variables. The IVW method demonstrated that MMP-3 had a causal effect on AS (odds ratio, 0.9047 [95% confidence interval, 0.8080-1.0129]; P = .0823). Certainly, other MR techniques were in accordance with the tendency of the IVW method (P < .05), and sensitivity testing verified the reliability of this MR result. This MR study substantiates the causal role of MMP-3 in the development of AS, offering valuable insights into the disease mechanism and potential therapeutic targets.

Fibroblast growth factor 23 and outcomes of atrial fibrillation: from clinical association to genetic evidence

AIMS

Fibroblast growth factor 23 (FGF23) has been implicated in the occurrence of atrial fibrillation (AF), but its prognostic value in AF patients remains unclear.

METHODS AND RESULTS

A total of 35 197 AF patients with available follow-up data (3.56, 0.47-8.92 years) from the UK Biobank were included. Clinical association between serum FGF23 and AF-related outcomes including mortality, heart failure (HF), ischaemic stroke, and dementia were analysed using multivariable Cox regression. In those passed quality control for array sequencing, polygenic score for FGF23 (PGSFGF23) was calculated as genetic instrument, and the association between PGSFGF23 and the occurrence of endpoints after first AF diagnosis were further explored. In 886 patients who diagnosed AF at or prior to the enrolment, elevated serum FGF23 levels were significantly associated with an increased risk of all-cause (37% increase per standard deviation) and cardiovascular (40% increase per standard deviation) mortality and HF (43% increase per standard deviation). A total of 35 197 patients were available for genetic array sequencing data. Using polygenic score including seven independent SNPs reaching genome-wide significance threshold, genetic association analysis indicated that increased PGSFGF23 is associated with reduced risk of HF but increased risk of all-cause mortality and ischaemic stroke.

CONCLUSION

Our findings suggest that FGF23 is a potential biomarker for accessing AF-related outcomes. The paradoxical association between genetic FGF23 and serum FGF23 level highlights the need for further investigation to elucidate the underlying mechanisms.

Mendelian Randomization Study Reveals Causal Pathways for Hypertrophic Cardiomyopathy, Cardiovascular Proteins, and Atrial Fibrillation

Aims/Background Research evidence has demonstrated a significant association between hypertrophic cardiomyopathy (HCM) and atrial fibrillation (AF), but the causality and pattern of this link remain unexplored. Therefore, this study investigated the causal relationship between HCM and AF using a two-sample and bidirectional Mendelian randomization (MR) approach. Additionally, this assessed the role of cardiovascular proteins (CPs) associated with cardiovascular diseases between HCM and AF by applying a two-step MR analysis. Methods Data for HCM, AF, and 90 CPs were obtained from the Finn Gen and IEU Open GWAS Project databases. MR-Egger, inverse variance weighting (IVW), weighted median estimator (WME), weighted mode, and simple mode were used to estimate causal inferences. Furthermore, Cochran's Q test, MR-Egger's intercept terms, and Leave-one-out methods determined the heterogeneity, horizontal pleiotropy, and sensitivity. Additionally, mediation effects were used to assess the role of CPs in the relationship between HCM and AF. Results Two-sample and bidirectional MR analysis revealed HCM as a risk factor for AF (odds ratio (OR) = 1.008, 95% confidence interval (CI): 1.001-1.016, p = 0.029) and AF was found to increase the risk of developing HCM (OR = 1.145, 95% CI: 0.963-1.361, p = 0.126). Moreover, Two-step MR analyses indicated that 5 CPs were causally associated with HCM; 12 CPs with AF and 1 CP (Melusin) with both HCM and AF. Additionally, Melusin was observed as a protective factor for both HCM and AF and may serve as a mediator variable for these two conditions (mediation effect 0.0004, mediation ratio 5.5178%, 95% CI: 5.4624-5.5731). Conclusion HCM may increase the risk of developing AF, with Melusin serving as a mediator for this risk.

Joint analysis of genome-wide cross-trait and multi-omics reveals molecular mechanisms of inflammatory bowel disease and nominates its novel therapeutic genes

Inflammatory bowel disease (IBD) with the two predominant endophenotypes-Crohn's disease (CD) and ulcerative colitis (UC)-represents a group of chronic gastrointestinal inflammatory conditions. Since most genetic associations with IBD are often limited to independent subtypes, we reported a genome-wide association study (GWAS) cross-trait analysis combined with CD and UC to enhance statistical power. Initially, we detected 256 association signals at 54 genomic susceptibility loci and further characterized the functionality of variants within these regions. Subsequently, we revealed tissue and cell-specific heritability enrichment, particularly in whole blood, small intestine terminal ileum, spleen, lung, and colon transverse. Leveraging multi-omics datasets, we adopted a two-pronged approach comprising summary data-based Mendelian randomization (SMR) and transcriptome-wide association study (TWAS) to pinpoint likely causal genes and variants. Further, RNA-seq analysis facilitated the evaluation of differential expression and co-expression in intestinal tissues. Through a multi-stage prioritization strategy, compelling evidence for putative targets was nominated; notably highlighting several potential susceptibility genes such as IL27 and SBNO2. Finally, we utilized Mendelian randomization (MR) analysis with diverse datasets to verify the convergence of these two endophenotype-driven genes. Our investigation yields valuable insights to inform genetic mechanisms in IBD and reveal potential causal gene targets.

The genomic architecture of circulating cytokine levels points to drug targets for immune-related diseases

Circulating cytokines orchestrate immune reactions and are promising drug targets for immune-mediated and inflammatory diseases. Exploring the genetic architecture of circulating cytokine levels could yield key insights into causal mediators of human disease. Here, we performed genome-wide association studies (GWAS) for 40 circulating cytokines in meta-analyses of 74,783 individuals. We detected 359 significant associations between cytokine levels and variants in 169 independent loci, including 150 trans- and 19 cis-acting loci. Integration with transcriptomic data point to key regulatory mechanisms, such as the buffering function of the Atypical Chemokine Receptor 1 (ACKR1) acting as scavenger for multiple chemokines and the role of tumor necrosis factor receptor-associated factor 1 (TRAFD1) in modulating the cytokine storm triggered by TNF signaling. Applying Mendelian randomization (MR), we detected a network of complex cytokine interconnections with TNF-b, VEGF, and IL-1ra exhibiting pleiotropic downstream effects on multiple cytokines. Drug target cis-MR using 2 independent proteomics datasets paired with colocalization revealed G-CSF/CSF-3 and CXCL9/MIG as potential causal mediators of asthma and Crohn's disease, respectively, but also a potentially protective role of TNF-b in multiple sclerosis. Our results provide an overview of the genetic architecture of circulating cytokines and could guide the development of targeted immunotherapies.

A genetic exploration of the relationship between posttraumatic stress disorder and cardiovascular diseases

Experiencing a traumatic event may lead to Posttraumatic Stress Disorder (PTSD), including symptoms such as flashbacks and hyperarousal. Individuals suffering from PTSD are at increased risk of cardiovascular disease (CVD), but it is unclear why. This study assesses shared genetic liability and potential causal pathways between PTSD and CVD. We leveraged summary-level data of genome-wide association studies (PTSD: N = 1,222,882; atrial fibrillation (AF): N = 482,409; coronary artery disease (CAD): N = 1,165,690; hypertension (HT): N = 458,554; heart failure (HF): N = 977,323). First, we estimated genetic correlations and utilized genomic structural equation modeling to identify a common genetic factor for PTSD and CVD. Next, we assessed biological, behavioural, and psychosocial factors as potential mediators. Finally, we employed multivariable Mendelian randomization to examine causal pathways between PTSD and CVD, incorporating the same potential mediators. Significant genetic correlations were found between PTSD and CAD, HT, and HF (rg = 0.21-0.32, p ≤ 3.08 · 10-16), but not between PTSD and AF. Insomnia, smoking, alcohol dependence, waist-to-hip ratio, and inflammation (IL6, C-reactive protein) partly mediated these associations. Mendelian randomization indicated that PTSD causally increases CAD (IVW OR = 1.53, 95% CIs = 1.19-1.96, p = 0.001), HF (OR = 1.44, CIs = 1.08-1.92, p = 0.012), and to a lesser degree HT (OR = 1.25, CIs = 1.05-1.49, p = 0.012). While insomnia, smoking, alcohol, and inflammation were important mediators, independent causal effects also remained. In addition to shared genetic liability between PTSD and CVD, we present strong evidence for causal effects of PTSD on CVD. Crucially, we implicate specific lifestyle and biological mediators (insomnia, substance use, inflammation) which has important implications for interventions to prevent CVD in PTSD patients.