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

Genetic predisposition to high circulating levels of interleukin 6 and risk for Alzheimer's disease. Discovery and replication

IMPORTANCE

Aging is accompanied by immune dysregulation, which has been implicated in Alzheimer's disease (AD) pathogenesis. Individuals who are genetically predisposed to elevated levels of proinflammatory mediators might be at increased risk for AD.

OBJECTIVE

To investigate whether genetic propensity for higher circulating levels of interleukin 6 (IL-6) is associated with AD risk.

DESIGN

We analyzed data from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD). Mean follow-up was 2.9 (SD, 0.8) years. Baseline assessment was from 11/2009 to 11/2016, and cognitive follow-up from 01/2013 to 07/2019. Associations of interest were also examined in the UK Biobank (UKB) for replication purposes (mean follow-up was 12.9 (SD, 2.4) years; baseline assessment was from 12/2006 to 10/2010).

SETTING

Population-based study.

PARTICIPANTS

The HELIAD sample included 622 participants ≥65 years of age without baseline dementia or amnestic mild cognitive impairment (aMCI-the prodromal stage of AD). The UKB sample included 142,637 participants ≥60 years of age without prevalent dementia.

EXPOSURES

Genetic predisposition to elevated circulating levels of IL-6 was estimated using a polygenic risk score (PRS), calculated based on the summary statistics of a current GWAS meta-analysis.

MAIN OUTCOMES AND MEASURES

AD and MCI diagnoses were based on standard clinical criteria [HELIAD], or hospital records and death registry data [UKB]. Associations with AD or aMCI incidence [HELIAD] and AD incidence [UKB] were examined with Cox regression models.

RESULTS

In HELIAD, mean age was 73.4 (SD, 5.0) years; 363 (58%) women. An increase in IL-6 PRS by 1 standard deviation unit (SDU) was associated with up to a 43% increase in the risk for incident AD/aMCI (HRGWAS significance threshold of 0.01, 1.43 [95%CI, 1.14 - 1.80]). In UKBB, mean age was 64.2 (SD, 2.8) years; 73,707 (52%) women. A 1 SDU increase in IL-6 PRS was associated with up to an 8% increase in the risk for incident AD (HRGWAS significance threshold of 0.2, 1.08 [95%CI, 1.04 - 1.12]).

CONCLUSIONS AND RELEVANCE

Genetic predisposition to higher circulating levels of IL-6 was associated with an increased risk for AD, supporting the role of IL-6-related pathways in AD pathogenesis, and suggesting that genetic predisposition to proinflammatory states might trigger or accelerate AD-related neuropathology.

Therapeutic targets for hepatocellular carcinoma identified using proteomics and Mendelian randomization

BACKGROUND AND AIM

Hepatocellular carcinoma (HCC) emerges as a formidable malignancy marked by elevated morbidity and mortality rates, coupled with a dismal prognosis. The revelation of gene-protein associations has presented an avenue for the exploration of novel therapeutic targets.

METHODS

Pooling plasma proteomic data (seven published GWAS) and HCC data (DeCODE cohort), we applied MR to identify potential drug targets, which were further validated in the FinnGen cohort and UK Biobank. Subsequent colocalization and summary-data-based Mendelian randomization analyses were performed for potential associations of this set of proteins. In addition, enrichment information pathways were investigated in depth by KEGG pathway analysis, single-cell sequencing, PPI and DGIdb, ChEMBL, and DrugBank database analyses, specific cell types enriched for expression were identified, interacting proteins were identified, and finally, druggability was assessed.

RESULTS

In summary, the levels of 10 proteins are linked to HCC risk. Elevated levels of TFPI2 as well as decreased levels of ALDH1A1, KRT18, ADAMTS13, TIMD4, SCLY, HRSP12, TNFAIP6, FTCD, and DDC are associated with increased HCC risk. Notably, HRSP12 show the strongest evidence. These genes are primarily expressed in specific cell types within the HCC TME. Moreover, intricate protein-protein interactions, involving key players like ALDH1A1 and RIDA, ALDH1A1 and DDC, and ALDH1A1 and KRT18, contribute significantly to the amino acid metabolism and dopaminergic neurogenesis pathway. Proteins such as ALDH1A1, KRT18, TFPI2, and DDC are promising targets for HCC therapy and broader cancer drug development. Targeting these proteins offers substantial potential in advancing HCC treatment strategies.

CONCLUSIONS

This research delineates 10 protein biomarkers linked to HCC risk and offers novel perspectives on its etiology, as well as promising avenues for the screening of HCC protein markers and therapeutic agents.

Serum Matrix Metalloproteinases and Risk of Urologic Cancers: A Bidirectional Mendelian Randomization Study

Many observational epidemiological studies have reported an association between matrix metalloproteinases (MMPs) and urologic cancers. However, the causal relationship between these two phenotypes remains uncertain. This study aims to examine the bidirectional causal relationship between serum MMPs and three urologic cancers: kidney, prostate, and bladder cancer. Using data from large-scale genome-wide association studies (GWAS), we employed two-sample Mendelian randomization (MR) methods to assess the causal relationship between serum MMPs and urologic cancers. We performed inverse variance-weighted MR as the primary method for calculating the overall effects of multiple instruments, while implementing additional MR methods and sensitivity analyses. Odds ratios (ORs) were employed to evaluate the causal relationship between serum MMPs and urologic cancers risk. Our findings indicated a causal relationship between serum MMP-3 levels and prostate cancer risk (OR = 1.07, 95% confidence interval [CI] = [1.02, 1.11], p = .003). There was a possible causal relationship between serum MMP-1 and prostate cancer (OR = 0.95, 95% CI = [0.92, 0.99], p = .02). Serum MMP-1 may also increase the risk of bladder cancer (OR = 1.24, 95% CI = [1.04, 1.49], p = .016). We did not find significant associations of the remaining MMPs with prostate, bladder, and kidney cancer. In reverse MR, no significant results were observed supporting the effect of urologic cancers on MMPs (p > .05). Our study provides evidence of a potential causal relationship between serum MMPs and both prostate cancer and bladder cancer. However, large-scale studies are necessary to confirm and reveal the underlying mechanisms of this association.

Genetic insights into therapeutic targets for gout: evidence from a multi-omics mendelian randomization study

BACKGROUND

Considering that the treatment of gout is poor, we performed a Mendelian randomization (MR) study to identify candidate biomarkers and therapeutic targets for gout.

METHODS

A drug-targeted MR study was performed for gout by integrating the gout genome-wide association studies (GWAS) summary data and cis expression quantitative trait loci of 2,633 druggable genes from multiple cohorts. Summary data-based Mendelian randomization (SMR) analyses based on transcript and protein levels were further implemented to validate the reliability of the identified potential therapeutic targets for gout. Phenome-wide MR (Phe-MR) analysis was conducted in 1403 diseases to investigate incidental side effects of potential therapeutic targets for gout.

RESULTS

Eight potential therapeutic targets (ALDH3B1, FCGR2B, IL2RB, NRBP1, RCE1, SLC7A7, SUMF1, THBS3) for gout were identified in the discovery cohort using MR analysis. Replication analysis and meta-analysis implemented in the replication cohort validated the robustness of the MR findings (P < 0.05). Evidence from the SMR analysis (P < 0.05) further strengthened the reliability of the 8 potential therapeutic targets for gout also revealed that high levels of ALDH3B1 reduced the gout risk possibly modified by the methylation site cg25402137. SMR analysis (P < 0.05) at the protein level added emphasis on the impact of the risk genes NRBP1 and SUMF1 on gout. Phe-MR analysis indicated significant causality between 7 gout causal genes and 45 diseases.

CONCLUSION

This study identified several biomarkers associated with gout risk, providing new insights into the etiology of gout and promising targets for the development of therapeutic agents.

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 Th17 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.

Causal effects of the RANK-RANKL-OPG system and scoliosis: A bidirectional 2-sample Mendelian randomization study

Epidemiological studies and a recent Mendelian randomization (MR) study have identified an association between low bone mass and an increased risk of scoliosis. Previous research suggests that bone loss in patients with scoliosis may be related to the RANK-RANKL-OPG system. This study is to investigate whether a causal relationship exists between the RANK-RANKL-OPG system and the development of scoliosis. Genome-wide association study (GWAS) data for RANK and RANKL were sourced from the UK Biobank's Pharmaceutical Proteomics Project, while OPG data were derived from 2 independent cohorts, and scoliosis data from the FinnGen R10 database. A bidirectional 2-sample MR framework was applied to investigate causal relationships between OPG, RANK, RANKL, and scoliosis, with inverse variance weighting (IVW) as the main analytical method. Meta-analysis was used to integrate findings across cohorts, and multiple sensitivity analyses were conducted to assess the robustness and reliability of the results. According to the IVW results, there was no significant causal relationship between RANK (OR = 0.973, 95% CI = 0.871-1.087, P = .626) and RANKL (OR = 1.048, 95% CI = 0.938-1.171, P = .411) and scoliosis. OPG is a potential protective factor for scoliosis (Folkersen 2020 OR = 0.739, 95% CI = 0.611-0.893, P = .002; Zhao 2023 OR = 0.833, 95% CI = 0.716-0.968, P = .017).The results of Meta-analysis also showed OPG (P = 1.428e-4) would reduce the risk of scoliosis. Inverse MR analysis showed no statistically significant causal relationship between scoliosis and RANK, RANKL and OPG levels (P > .05). Our study employing MR methodology provides robust evidence supporting a causal relationship between decreased osteoprotegerin (OPG) levels and increased susceptibility to scoliosis. However, no significant relationship was found between scoliosis with the RANK-RANKL-OPG system. This research establishes a basis for further exploration of the pathophysiological mechanisms and potential targeted treatments for scoliosis. Future studies are necessary to understand how OPG influences the development of scoliosis.

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Identification of potential drug targets for diabetic polyneuropathy through Mendelian randomization analysis

BACKGROUND

Diabetic polyneuropathy (DPN) is a common diabetes complication with limited treatment options. We aimed to identify circulating plasma proteins as potential therapeutic targets for DPN using Mendelian Randomization (MR).

METHODS

The protein quantitative trait loci (pQTLs) utilized in this study were derived from seven previously published genome-wide association studies (GWASs) on plasma proteomics. The DPN data were obtained from the IEU OpenGWAS project. This study employed two-sample MR using MR-Egger and inverse-variance weighted methods to evaluate the causal relationship between plasma proteins and DPN risk, with Cochran's Q test, and I2 statistics, among other methods, used to validate the robustness of the results.

RESULTS

Using cis-pQTLs as genetic instruments, we identified 62 proteins associated with DPN, with 33 increasing the risk and 29 decreasing the risk of DPN. Using cis-pQTLs + trans-pQTLs, we identified 116 proteins associated with DPN, with 44 increasing the risk and 72 decreasing the risk of DPN. Steiger directionality tests indicated that the causal relationships between circulating plasma proteins and DPN were consistent with expected directions.

CONCLUSION

This study identified 96 circulating plasma proteins with genetically determined levels that affect the risk of DPN, providing new potential targets for DPN drug development, particularly ITM2B, CREG1, CD14, and PLXNA4.

Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

AIMS/HYPOTHESIS

Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.

METHODS

Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.

RESULTS

We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development.

CONCLUSIONS/INTERPRETATION

Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations.

DATA AVAILABILITY

The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https://github.com/Arthur1021/MESA-1K-PWAS ).

Evaluating the association between immunological proteins and common intestinal diseases using a bidirectional two-sample Mendelian randomization study

Dysregulation of intestinal homeostasis, characterized by imbalanced immunological proteins, contributes to the pathogenesis of common intestinal diseases, e.g., irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and colorectal cancer (CRC). However, the potential causal relationships between specific immunological proteins and these diseases remain to be fully elucidated. In this study, we employed the bidirectional two-sample Mendelian randomization analysis to infer potential causal relationships between representative immunological proteins and these intestinal diseases. Genome-wide association study (GWAS) summary statistics of IBS, IBD, and CRC were obtained from public databases and utilized in MR analysis. Multiple sensitivity analyses were performed to evaluate the robustness, with p-values adjusted using the Benjamini-Hochberg method for multiple comparisons. Our findings revealed a significant association between IL-1β (OR = 0.783, 95 % CI: 0.676 to 0.908, adjusted P = 0.048) and a decreased risk of IBS. Furthermore, genetic predisposition to IBS was related to the reduced levels of IL-25 (β =  - 0.233, 95 % CI: -0.372 to -0.094, adjusted P = 0.047). Additionally, genetic predisposition to IBD was correlated with elevated levels of IL-6 (β = 0.046, 95 % CI: 0.022-0.069, adjusted P = 0.010). The levels of TNF-α (OR = 1.252, 95 % CI: 1.102 to 1.423, adjusted P = 0.047) were associated with an increased risk of CRC. Our study suggests associations between specific immunological proteins and intestinal diseases, which would provide valuable insights for developing targeted immunomodulation therapies for these conditions. Further investigation into underlying mechanisms remains a research priority in the future.

Association between walking pace and heart failure: A Mendelian randomization analysis

BACKGROUND AND AIM

The relationship between walking pace and heart failure (HF) has been recognized, yet the directionality and underlying mediating risk factors remain unclear.

METHODS AND RESULTS

This study utilized bidirectional two-sample Mendelian randomization (MR) with genome-wide association studies (GWAS) summary statistics to assess the causal relationships between walking pace and HF. Additionally, we employed a two-step Multivariable Mendelian Randomization (MVMR) to explore potential mediating factors. We further validated our findings by conducting two-sample MR with another available GWAS summary data on heart failure. Results indicated that genetically predicted increases in walking pace were associated with a reduced risk of HF (odds ratio (OR), 0.589, 95% confidence interval (CI): 0.417-0.832). Among the considered mediators, the waist-to-hip ratio (WHR) accounts for the largest proportion of the effect (45.7%, 95% CI: 13.2%, 78.2%). This is followed by type 2 diabetes at 24.4% (95% CI: 6.7%, 42.0%) and triglycerides at 18.6% (95% CI: 4.5%, 32.7%). Furthermore, our findings reveal that genetically predicted HF risk (OR, 0.975, 95% CI: 0.960-0.991) is associated with a slower walking pace. Validated findings were consistent with the main results.

CONCLUSIONS

In conclusion, MR analysis demonstrates that a slow walking pace is a reliable indicator of an elevated risk of HF, and the causal relationship is bidirectional. Interventions focusing on waist-to-hip ratio, type 2 diabetes, and triglycerides may provide valuable strategies for HF prevention in individuals with a slow walking pace.

Integrative proteomic analyses across common cardiac diseases yield mechanistic insights and enhanced prediction

Cardiac diseases represent common highly morbid conditions for which molecular mechanisms remain incompletely understood. Here we report the analysis of 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P < 8.6 × 10-6. Cis-Mendelian randomization suggested causal roles aligning with epidemiological findings for 4% of proteins identified in primary analyses, prioritizing therapeutic targets across cardiac diseases (for example, spondin-1 for atrial fibrillation and the Kunitz-type protease inhibitor 1 for coronary artery disease). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (versus clinical risk factors alone) improved prediction for coronary artery disease, heart failure and atrial fibrillation. These results lay a foundation for future investigations to uncover disease mechanisms and assess the utility of protein-based prevention strategies for cardiac diseases.

Association Between Neuroinflammation and Parkinson's Disease: A Comprehensive Mendelian Randomization Study

The objective of the study is to determine the causal relationship and potential mechanisms between Parkinson's disease (PD) and neuroinflammatory and neurotoxic mediators. We conducted two-sample Mendelian randomization (2SMR) study and multivariable Mendelian randomization (MVMR) analysis to investigate the causality between PD and neuroinflammatory and neurotoxic mediators. The mediation analysis with MR was also conducted to determine the potential mediating effect of neuroinflammatory and neurotoxic mediators between asthma and PD. Genetically predicted levels of nine neuroinflammation were associated with changes in PD risk. The associations of PD with CCL24, galectin-3 levels, haptoglobin, and Holo-Transcobalamin-2 remained significant in multivariable analyses. The mediation analysis with MR revealed that asthma affects PD through CCL24 and galectin-3. The results showed neuroinflammation could affect the pathogenesis of PD. In the combined analysis of these nine variables, CCL24, galectin-3 levels, HP, and Holo-Transcobalamin-2 alone were found to be significant. Asthma plays an intermediary role through CCL24 and galectin-3 levels.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for juvenile idiopathic arthritis

Background

Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatic disease affecting children. Current medications merely alleviate symptoms rather than curing the disease. Hence, the identification and development of novel drug targets and biomarkers for JIA are imperative for enhancing treatment efficacy.

Methods

We employed two-sample Mendelian randomization (MR) analysis to investigate the causal effects of plasma proteins on JIA. Additionally, colocalization, bulk RNA-seq, and single-cell RNA-seq analyses were conducted to further investigate and validate the potential of candidate proteins as drug targets.

Results

Through MR analysis, we successfully identified five plasma proteins that are causally linked to JIA. Genetically inferred lower levels of AIF1, TNF, and TNFSF11 were associated with an elevated risk of JIA, while higher levels of AGER and GP1BA proteins were positively correlated with JIA risk. Colocalization analysis further supported our findings on GP1BA (OR = 9.26, 95 % CI: 2.30-37.20) and TNFSF11 (OR = 0.18, 95 % CI: 0.07-0.45). Based on this evidence, we classified these five proteins into two tiers. Finally, we conducted a systematic evaluation of the druggability and current drug development progress for these identified candidate proteins.

Conclusions

This study employed MR analysis to reveal causal relationships between plasma proteins and JIA, identifying five potential candidate proteins as promising drug targets for JIA, particularly focusing on GP1BA and TNFSF11.

Circulating interleukin-27 is associated with the risk of chronic periodontitis and allergic rhinitis: A Mendelian randomization analysis

BACKGROUND

Chronic periodontitis (CP) and allergic rhinitis (AR) have attracted wide attention as global public health problems with high incidence. Recent studies have shown that circulating interleukin-27 (IL-27) is associated with the risk of CP and AR. The aim of this study is to analyze the causal effect between them using Mendelian randomization (MR).

METHODS

Bidirectional MR analyses were performed with the use of publicly available genome-wide association study (GWAS) data. Summary data on circulating IL-27, CP, and AR published in genome-wide association studies were collected. Instrumental variables (IV) were extracted using assumptions of correlation, independence and exclusivity as criteria. Inverse variance weighting (IVW) was used as the main method, combined with weighted median method (WM) and MR-Egger and other MR Analysis methods for causal inference of exposure and outcome. Cochran's Q and MR-Egger intercept were used for sensitivity analysis.

RESULTS

The IVW study showed a causal effect between increased circulating IL-27 levels and increased risk of CP (OR = 1.14, 95%CI = 1.02-1.26, p = .020). Similarly, the increase of circulating IL-27 level had a causal effect on the decreased risk of AR (OR = 0.88, 95%CI = 0.80-0.97, p = .012). In addition, IVW study found that there was a causal between the increased risk of CP and circulating IL-27 level (OR = 1.05, 95%CI = 1.01-1.10, p = .016). However, there was no significant causal relationship between the risk of AR and circulating IL-27 levels (OR = 0.97, 95%CI = 0.91-1.02, p = .209). no significant heterogeneity or horizontal pleiotropy was found in sensitivity analysis.

CONCLUSIONS

There is a causal effect between circulating IL-27 level and CP, AR, which will help to find new ideas and methods for the diagnosis and treatment of CP and AR.

Novel Drug Targets for Atrial Fibrillation Identified Through Mendelian Randomization Analysis of the Blood Proteome

PURPOSE

Novel, effective, and safe preventive therapy targets for AF are still needed. Circulating proteins with causal genetic evidence are promising candidates. We aimed to systematically screen circulating proteins for AF drug targets and determine their safety and efficacy using genetic methods.

METHODS

The protein quantitative trait loci (pQTL) of up to 1949 circulating proteins were retrieved from nine large genome-proteome-wide association studies. Two-sample Mendelian Randomization (MR) and colocalization analyses were used to estimate the causal effects of proteins on the risk of AF. Furthermore, phenome-wide MR was conducted to depict side effects and the drug-target databases were searched for drug validation and repurposing.

RESULTS

Systematic MR screen identified 30 proteins as promising AF drug targets. Genetically predicted 12 proteins increased AF risk (TES, CFL2, MTHFD1, RAB1A, DUSP13, SRL, ANXA4, NEO1, FKBP7, SPON1, LPA, MANBA); 18 proteins decreased AF risk (PMVK, UBE2F, SYT11, CHMP3, PFKM, FBP1, TNFSF12, CTSZ, QSOX2, ALAD, EFEMP1, FLRT2, LRIG1, OLA1, SH3BGRL3, IL6R, B3GNT8, FCGR2A). DUSP13 and TNFSF12 possess strong colocalization evidence. For the proteins that were identified, extended phe-MR analysis was conducted to assess their side-effect profiles, while drug-target databases provided information on their approved or investigated indications.

CONCLUSION

We identified 30 circulating proteins as potential preventive targets for AF.

Causal relationships between gut microbiome and aplastic anemia: a Mendelian randomization analysis

BACKGROUND

Previous observational studies have hinted at a potential correlation between aplastic anemia (AA) and the gut microbiome. However, the precise nature of this bidirectional causal relationship remains uncertain.

METHODS

We conducted a bidirectional two-sample Mendelian randomization (MR) study to investigate the potential causal link between the gut microbiome and AA. Statistical analysis of the gut microbiome was based on data from an extensive meta-analysis (genome-wide association study) conducted by the MiBioGen Alliance, involving 18,340 samples. Summary statistical data for AA were obtained from the Integrative Epidemiology Unit database. Single -nucleotide polymorphisms (SNPs) were estimated and summarized using inverse variance weighted (IVW), MR Egger, and weighted median methods in the bidirectional MR analysis. Cochran's Q test, MR Egger intercept test, and sensitivity analysis were employed to assess SNP heterogeneity, horizontal pleiotropy, and stability.

RESULTS

The IVW analysis revealed a significant correlation between AA and 10 bacterial taxa. However, there is currently insufficient evidence to support a causal relationship between AA and the composition of gut microbiome.

CONCLUSION

This study suggests a causal connection between the prevalence of specific gut microbiome and AA. Further investigation into the interaction between particular bacterial communities and AA could enhance efforts in prevention, monitoring, and treatment of the condition.

Unraveling the heart-brain axis: shared genetic mechanisms in cardiovascular diseases and Schizophrenia

The comorbidity between cardiovascular diseases (CVD) and schizophrenia (SCZ) has attracted widespread attention from researchers, with shared genetic causes potentially providing important insights into their association. This study conducted a comprehensive analysis of genetic data from 17 types of CVD and SCZ using genome-wide multi-trait association studies (GWAS), employing statistical methods such as LDSC, MTAG, LAVA, and bidirectional Mendelian randomization to explore global and local genetic correlations and identify pleiotropic single nucleotide variants (SNVs). The analysis revealed a significant genetic correlation between CVD and SCZ, identifying 842 potential pleiotropic single nucleotide variants (SNVs) and multiple associated biological pathways. Notably, genes such as TRIM27, CENPM, and MYH7B played critical roles in the shared genetic variations of both types of diseases. This study reveals the complex genetic relationship between CVD and SCZ, highlighting potential shared biological mechanisms involving immune responses, metabolic factors, and neurodevelopmental processes, thereby providing new directions for future interventions and treatments.

Exploring genetic associations between immune cells and hypertensive disorder of pregnancy using Mendelian randomization

BACKGROUND

Observational epidemiological studies suggested that immunological dysregulation and inflammation play a significant role in the placental and renal dysfunction that leads to maternal hypertension. The immunophenotypes' possible causalities with hypertensive disease of pregnancy remain ambiguous. We performed two-sample Mendelian randomization (MR) analyses to comprehensively investigate the causal effect of immunophenotypes on hypertensive disorder of pregnancy (HDP).

METHODS

The large-scale genome-wide association studies (GWASs) data on immunological traits was taken from public catalog for 731 immunophenotypes. The summarized GWAS data in 4 types of HDP were retrieved from FinnGen database, including 811,605 Finnish individuals. The primary analysis was the inverse variance weighted (IVW) method, supplemented by conducting sensitivity analysis. To confirm whether cardiovascular proteins mediated the causal effect of immune cells on HDP, we additionally executed a mediation MR study.

RESULTS

After looking into genetically predicted immunophenotype biomarkers, we discovered 14 highly correlative immunophenotypes and 104 suggestive possible factors. The IVW analysis indicated that HLA DR on myeloid DC, HLA DR on plasmacytoid DC, and HLA DR on DC had a significant association with pre-eclampsia/eclampsia (PE), whereas CD4+ CD8dim AC and CD4+ CD8dim % leukocyte were protective against gestational hypertension (GH). All of HDP in our study had no statistically significant impact on immune cells, according to reverse MR analysis. The mediating role of LOX-1between HLA DR on plasmacytoid DC and chronic hypertension prior to pregnancy was validated.

CONCLUSION

This study showed that many immunophenotypes are implicated in HDP. Furthermore, the level of LOX-1 mediated the pathophysiology relationship between HLA DR on plasmacytoid dendritic cells and chronic hypertension prior to pregnancy.

Relationship of proteins and subclinical cardiovascular traits in the population-based LIFE-Adult study

BACKGROUND AND AIMS

Understanding molecular processes of the early phase of atherosclerotic cardiovascular disease conditions is of utmost importance for early prediction and intervention measures.

METHODS

We measured 92 cardiovascular-disease-related proteins (Olink, Cardiovascular III) in 2024 elderly participants of the population-based LIFE-Adult study. We analysed the impact of 27 covariables on these proteins including blood counts, cardiovascular risk factors and life-style-related parameters. We also analysed protein associations with 13 subclinical cardiovascular traits comprising carotid intima media thickness, plaque burden, three modes of Vicorder-based pulse-wave velocities, ankle-brachial index and ECLIA-based N-terminal prohormone of brain natriuretic peptide (NT-proBNP).

RESULTS

Estimated glomerular filtration rate, triglycerides and sex where the most relevant covariables explaining more than 1 % variance of 49, 22 and 20 proteins, respectively. A total of 43 proteins were significantly associated with at least one of the analysed subclinical cardiovascular traits. NT-pro-BNP, brachial-ankle pulse-wave velocity (baPWV) and parameters of carotid plaque burden accounted for the largest number of associations. Association overlaps were relatively sparse. Only growth/differentiation factor 15, low density lipoprotein receptor and interleukin-1 receptor type 2 are associated with these three different cardiovascular traits. We confirmed several literature findings and found yet unreported associations for carotid plaque presence (von-Willebrand factor, galectin 4), carotid intima-media thickness (carboxypeptidase A1 andB1), baPWV (cathepsin D) and NT-proBNP (cathepsin Z, low density lipoprotein receptor, neurogenic locus homolog protein 3, trem-like transcript 2). Sex-interaction effects were observed, e.g. for spondin-1 and growth/differentiation factor 15 likely regulated by androgen response elements.

CONCLUSIONS

We extend the catalogue of proteome biomarkers possibly involved in early stages of cardiovascular disease pathologies providing targets for early risk prediction or intervention strategies.

The genetic landscape of neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

Integrating metabolomics and proteomics to identify novel drug targets for heart failure and atrial fibrillation

BACKGROUND

Altered metabolism plays a role in the pathophysiology of cardiac diseases, such as atrial fibrillation (AF) and heart failure (HF). We aimed to identify novel plasma metabolites and proteins associating with cardiac disease.

METHODS

Mendelian randomisation (MR) was used to assess the association of 174 metabolites measured in up to 86,507 participants with AF, HF, dilated cardiomyopathy (DCM), and non-ischemic cardiomyopathy (NICM). Subsequently, we sourced data on 1567 plasma proteins and performed cis MR to identify proteins affecting the identified metabolites as well as the cardiac diseases. Proteins were prioritised on cardiac expression and druggability, and mapped to biological pathways.

RESULTS

We identified 35 metabolites associating with cardiac disease. AF was affected by seventeen metabolites, HF by nineteen, DCM by four, and NCIM by taurine. HF was particularly enriched for phosphatidylcholines (p = 0.029) and DCM for acylcarnitines (p = 0.001). Metabolite involvement with AF was more uniform, spanning for example phosphatidylcholines, amino acids, and acylcarnitines. We identified 38 druggable proteins expressed in cardiac tissue, with a directionally concordant effect on metabolites and cardiac disease. We recapitulated known associations, for example between the drug target of digoxin (AT1B2), taurine and NICM risk. Additionally, we identified numerous novel findings, such as higher RET values associating with phosphatidylcholines and decreasing AF and HF. RET is targeted by drugs such as regorafenib which has known cardiotoxic side-effects. Pathway analysis implicated involvement of GDF15 signalling through RET, and ghrelin regulation of energy homeostasis in cardiac pathogenesis.

CONCLUSIONS

This study identified 35 plasma metabolites involved with cardiac diseases and linked these to 38 druggable proteins, providing actionable leads for drug development.

A comprehensive study of genetic regulation and disease associations of plasma circulatory microRNAs using population-level data

BACKGROUND

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression. Perturbations in plasma miRNA levels are known to impact disease risk and have potential as disease biomarkers. Exploring the genetic regulation of miRNAs may yield new insights into their important role in governing gene expression and disease mechanisms.

RESULTS

We present genome-wide association studies of 2083 plasma circulating miRNAs in 2178 participants of the Rotterdam Study to identify miRNA-expression quantitative trait loci (miR-eQTLs). We identify 3292 associations between 1289 SNPs and 63 miRNAs, of which 65% are replicated in two independent cohorts. We demonstrate that plasma miR-eQTLs co-localise with gene expression, protein, and metabolite-QTLs, which help in identifying miRNA-regulated pathways. We investigate consequences of alteration in circulating miRNA levels on a wide range of clinical conditions in phenome-wide association studies and Mendelian randomisation using the UK Biobank data (N = 423,419), revealing the pleiotropic and causal effects of several miRNAs on various clinical conditions. In the Mendelian randomisation analysis, we find a protective causal effect of miR-1908-5p on the risk of benign colon neoplasm and show that this effect is independent of its host gene (FADS1).

CONCLUSIONS

This study enriches our understanding of the genetic architecture of plasma miRNAs and explores the signatures of miRNAs across a wide range of clinical conditions. The integration of population-based genomics, other omics layers, and clinical data presents opportunities to unravel potential clinical significance of miRNAs and provides tools for novel miRNA-based therapeutic target discovery.

Association of inflammatory cytokines with lung function, chronic lung diseases, and COVID-19

We investigated the effects of 35 inflammatory cytokines on respiratory outcomes, including COVID-19, asthma (atopic and non-atopic), chronic obstructive pulmonary disease (COPD), and pulmonary function indices, using Mendelian randomization and colocalization analyses. The emerging associations were further explored using observational analyses in the UK Biobank. We found an inverse association between genetically predicted macrophage colony stimulating factor (MCSF), soluble intercellular adhesion molecule-1 (sICAM), and soluble vascular cell adhesion molecule-1 with risk of COVID-19 outcomes. sICAM was positively associated with atopic asthma risk, whereas tumor necrosis factor-alfa showed an inverse association. A positive association was shown between interleukin-18 and COPD risk (replicated in observational analysis), whereas an inverse association was shown for interleukin-1 receptor antagonist (IL-1ra). IL-1ra and monocyte chemotactic protein-3 were positively associated with lung function indices, whereas inverse associations were shown for MCSF and interleukin-18 (replicated in observational analysis). Our results point to these cytokines as potential pharmacological targets for respiratory traits.

Causal effect of vascular endothelial growth factor on the risk of atrial fibrillation: a two-sample Mendelian randomization study

Background

Observational studies have found that vascular endothelial growth factor (VEGF) levels are associated with the risk of cardiovascular disease. However, it remains unclear whether VEGF levels have a causal effect on the risk of atrial fibrillation.

Methods

A two-sample Mendelian randomization (MR) study was conducted to explore the causal relationship between VEGF levels and the risk of atrial fibrillation. Genetic variants associated with VEGF [VEGF-A, VEGF-C, VEGF-D, VEGF receptor-2 (VEGFR-2), VEGFR-3] and atrial fibrillation (atrial fibrillation, atrial fibrillation and flutter) were used as instrumental variables. Data on genetic variants were obtained from published genome-wide association studies (GWAS) or the IEU Open GWAS project. Inverse-variance weighted (IVW) analysis was used as the primary basis for the results, and sensitivity analyses were used to reduce bias. Causal relationships were expressed as odds ratio (OR) with 95% confidence interval (CI), and a P-value of <0.1 corrected for False Discovery Rate (FDR) (PFDR  < 0.1) was considered to have a significant causal relationship.

Results

Genetically predicted high levels of VEGF-A [OR = 1.025 (95%CI: 1.004-1.047), PFDR  = 0.060] and VEGF-D [OR = 1.080 (95%CI: 1.039-1.123), PFDR  = 0.001]] were associated with an increased risk of atrial fibrillation, while no causal relationship was observed between VEGF-C (PFDR  = 0.419), VEGFR-2 (PFDR  = 0.784), and VEGFR-3 (PFDR  = 0.899) and atrial fibrillation risk. Moreover, only genetically predicted high levels of VEGF-D [OR = 1.071 (95%CI: 1.014-1.132), PFDR  = 0.087] increased the risk of atrial fibrillation and flutter. Sensitivity analysis demonstrated that the relationship between VEGF-D levels and the risk of atrial fibrillation was robust.

Conclusion

This study supports a causal association between high VEGF-D levels and increased risk of atrial fibrillation.

Identification of novel proteins for coronary artery disease by integrating GWAS data and human plasma proteomes

Background

Most coronary artery disease (CAD) risk loci identified by genome-wide association studies (GWAS) are located in non-coding regions, hampering the interpretation of how they confer CAD risk. It is essential to integrate GWAS with molecular traits data to further explore the genetic basis of CAD.

Methods

We used the probabilistic Mendelian randomization (PMR) method to identify potential proteins involved in CAD by integrating CAD GWAS data (∼76,014 cases and ∼264,785 controls) and human plasma proteomes (N = 35,559). Then, Bayesian co-localization analysis, confirmatory PMR analysis using independent plasma proteome data (N = 7752), and gene expression data (N1 = 213, N2 = 670) were performed to validate candidate proteins. We further investigated the associations between candidate proteins and CAD-related traits and explored the rationality and biological functions of candidate proteins through disease enrichment, cell type-specific, GO, and KEGG enrichment analysis.

Results

This study inferred that the abundance of 30 proteins in the plasma was causally associated with CAD (P < 0.05/4408, Bonferroni correction), such as PLG, IL15RA, and CSNK2A1. PLG, PSCK9, COLEC11, ZNF180, ERP29, TCP1, FN1, CDH5, IL15RA, MGAT4B, TNFRSF6B, DNM2, and TGF1R were replicated in the confirmatory PMR (P < 0.05). PCSK9 (PP.H4 = 0.99), APOB (PP.H4 = 0.89), FN1 (PP.H4 = 0.87), and APOC1 (PP.H4 = 0.78) coding proteins shared one common variant with CAD. MTAP, TCP1, APOC2, ERP29, MORF4L1, C19orf80, PCSK9, APOC1, EPOR, DNM2, TNFRSF6B, CDKN2B, and LDLR were supported by PMR at the transcriptome level in whole blood and/or coronary arteries (P < 0.05). Enrichment analysis identified multiple pathways involved in cholesterol metabolism, regulation of lipoprotein levels and telomerase, such as cholesterol metabolism (hsa04979, P = 2.25E-7), plasma lipoprotein particle clearance (GO:0034381, P = 5.47E-5), and regulation of telomerase activity (GO:0051972, P = 2.34E-3).

Conclusions

Our integration analysis has identified 30 candidate proteins for CAD, which may provide important leads to design future functional studies and potential drug targets for CAD.

Role of interleukin-18 in mediating the impacts of celiac disease on osteoporosis: a Mendelian randomization study

Background

Extensive observational data suggest a link between celiac disease (CeD) and osteoporosis, but the causality and mediating mechanism remain undetermined. Herein, we performed a Mendelian randomization (MR) study to address these concerns.

Methods

We obtained the summary-level statistics for CeD from a large genome-wide association study (GWAS) comprising 4,533 cases and 10,750 controls of European ancestry. The GWAS data for osteoporosis-related traits and inflammatory cytokines were derived from the UK Biobank, FinnGen, IEU OpenGWAS database, or GWAS catalog. Two-sample MR with the inverse variance-weighted methods were employed to evaluate the genetic association between CeD and osteoporosis-related traits. The potential inflammatory mediators from CeD to osteoporosis were explored using two-step mediation analyses.

Results

The primary MR analyses demonstrated causal associations between genetically predicted CeD and osteoporosis (odds ratio [OR]: 1.110, 95% confidence interval [CI]: 1.043-1.182, p=0.001), total body bone mineral density (β: -0.025, p=0.039), and osteoporotic fracture (OR: 1.124, 95% CI: 1.009-1.253, p=0.034). Extensive sensitivity analyses consolidated these findings. Among the candidate inflammatory cytokines, only interleukin-18 was observed to mediate the effects of CeD on osteoporosis, with an indirect OR of 1.020 (95% CI: 1.000-1.040, p=0.048) and a mediation proportion of 18.9%. The mediation effects of interleukin-18 could be validated in other datasets (OR: 1.015, 95% CI: 1.001-1.029, p=0.041). Bayesian colocalization analysis supported the role of interleukin-18 in osteoporosis.

Conclusion

The present MR study reveals that CeD is associated with an increased risk of developing osteoporosis, which may be partly mediated by upregulation of interleukin-18.

Effect of inflammatory factors on myocardial infarction

BACKGROUND

Cohort studies have increasingly shown associations between inflammatory markers and myocardial infarction (MI); however, the specific causal relationships between inflammatory markers and the development of MI remain unclear.

METHODS AND RESULTS

By utilizing publicly accessible genome-wide association studies, we performed a two-sample Mendelian randomization (MR) analysis to explore the causal associations between inflammatory markers and myocardial infarction (MI). A random-effects inverse-variance weighted method was used to calculate effect estimates. The study included a total of 395,795 European participants for MI analysis and various sample sizes for inflammatory factors, ranging from 3,301 to 563,946 participants.Neutrophil count was found to increase the risk of MI (odds ratio [OR] = 1.08; 95% confidence interval [CI], 1.00-1.17; p = 0.04). C-reactive protein levels correlated positively with MI. No associations were observed with IL-1 beta, IL-6, IL-18, procalcitonin, TNF-α, total white cell count, or neutrophil percentage of white cells. Neutrophil count and C-reactive protein were inversely associated with lactate dehydrogenase: neutrophil cell count (OR 0.95; 95% CI, 0.93-0.98; p < 0.01) and C-reactive protein (OR 0.96; 95% CI, 0.92-1.00; p = 0.02). No associations of MI with myoglobin, troponin I, and creatine kinase-MB levels were found.

CONCLUSIONS

This two-sample MR analysis revealed a causal positive association of MI with neutrophil count, C-reactive protein level, and the myocardial injury marker lactate dehydrogenase. These results indicate that monitoring C-reactive protein and neutrophil counts may be useful in management of MI patients.

Cathepsins and neurological diseases: a Mendelian randomization study

Background

The causal relationship between cathepsins and neurological diseases remains uncertain. To address this, we utilized a two-sample Mendelian randomization (MR) approach to assess the potential causal effect of cathepsins on the development of neurological diseases.

Methods

This study conducted a two-sample two-way MR study using pooled data from published genome-wide association studies to evaluate the relationship between 10 cathepsins (B, D, E, F, G, H, L2, O, S, and Z) and 7 neurological diseases, which included ischemic stroke, cerebral hemorrhage, Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, and epilepsy. The analysis employed various methods such as inverse variance weighting (IVW), weighted median, MR Egger regression, MR pleiotropy residual sum and outlier, Cochran Q statistic, and leave-one-out analysis.

Results

We found a causal relationship between cathepsins and neurological diseases, including Cathepsin B and Parkinson's disease (IVW odds ratio (OR): 0.89, 95% confidence interval (CI): 0.83, 0.95, p = 0.001); Cathepsin D and Parkinson's disease (OR: 0.80, 95%CI: 0.68, 0.95, p = 0.012); Cathepsin E and ischemic stroke (OR: 1.05, 95%CI: 1.01, 1.09, p = 0.015); Cathepsin O and ischemic stroke (OR: 1.05, 95%CI: 1.01, 1.10, p = 0.021). Reverse MR analyses revealed that multiple sclerosis and Cathepsin E (OR: 1.05, 95%CI: 1.01, 1.10, p = 0.030). There is currently no significant relationship has been found between other cathepsins and neurological diseases.

Conclusion

Our study reveals a causal relationship between Cathepsins B, D, E, and O and neurological diseases, offering valuable insights for research aimed at improving the diagnosis and treatment of such conditions.

Association Between Serum Galectin-3 and Parkinson's Disease: A Two-Sample Mendelian Randomization Study

BACKGROUND

Parkinson's disease (PD) is a prevalent neurodegenerative disorder with poor prognosis. Observational studies have demonstrated a significant correlation between serum galectin-3 and PD, suggesting a potential role of galectin-3 as a biomarker for PD. However, it is still unclear whether galectin-3 contributes to the risk of the disease.

METHODS

A two-sample Mendelian randomization (MR) approach was used in this study. Genetic instruments for serum galectin-3 level were selected from a genome-wide association study (GWAS), including 30,931 European individuals. Summary-level statistics for PD were derived from another published GWAS, including 33,674 cases and 449,056 controls. Primary analysis was conducted using the inverse-variance weighting (IVW) method. Weighted median, MR-Egger, simple mode, weighted mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were used as complementary analyses. To detect heterogeneity, Cochran's Q statistic and leave-one-out analysis were used. For testing potential horizontal pleiotropy, the MR-Egger intercept test and MR-PRESSO global test were conducted.

RESULTS

MR analysis using IVW model (OR 1.112, 95% CI 1.025-1.206, p = 0.010), weighted median (OR 1.135, 95% CI 1.037-1.242, p = 0.006), weighted mode (OR 1.142, 95% CI 1.038-1.257, p = 0.030), and MR-PRESSO (OR 1.112, 95% CI 1.046-1.182, p = 0.012) presented a consistent result, indicating that increased serum galectin-3 was associated with a higher risk of PD. No heterogeneity or horizontal pleiotropy was detected in the analyses.

CONCLUSIONS

The study shows a suggestive association between galectin-3 and PD. Increasing serum galectin-3 was associated with an increase in PD risk. Galectin-3 may play an important role in the causal pathway to PD.

Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance

Studying the genetic regulation of protein expression (through protein quantitative trait loci (pQTLs)) offers a deeper understanding of regulatory variants uncharacterized by mRNA expression regulation (expression QTLs (eQTLs)) studies. Here we report cis-eQTL and cis-pQTL statistical fine-mapping from 1,405 genotyped samples with blood mRNA and 2,932 plasma samples of protein expression, as part of the Japan COVID-19 Task Force (JCTF). Fine-mapped eQTLs (n = 3,464) were enriched for 932 variants validated with a massively parallel reporter assay. Fine-mapped pQTLs (n = 582) were enriched for missense variations on structured and extracellular domains, although the possibility of epitope-binding artifacts remains. Trans-eQTL and trans-pQTL analysis highlighted associations of class I HLA allele variation with KIR genes. We contrast the multi-tissue origin of plasma protein with blood mRNA, contributing to the limited colocalization level, distinct regulatory mechanisms and trait relevance of eQTLs and pQTLs. We report a negative correlation between ABO mRNA and protein expression because of linkage disequilibrium between distinct nearby eQTLs and pQTLs.

Association of asthma with the risk of cardiovascular disease: A Mendelian randomization study

BACKGROUND

Association of asthma with the risk of cardiovascular disease has not been fully elucidated. So, this study tried to explore the genetic effect of asthma on five cardiovascular diseases and 90 peripheral cardiovascular proteins to answer the above topic.

METHODS

Instrumental variables predicting asthma was extracted from its genome-wide association study data. Two-sample and multivariate MR approaches were used to assess the genetic association of exposure factor (i.e., asthma) with outcome factors (i.e., hypertension, atrial fibrillation, angina pectoris, myocardial infarction, heart failure, and 90 peripheral cardiovascular proteins).

RESULTS

First, asthma nominally increased the risk of hypertension and atrial fibrillation (OR = 1.009, 95%CI = 1.003-1.016, P = 0.004; OR = 1.074, 95%CI = 1.024-1.127, P = 0.003). Second, of the 90 cardiovascular proteins, asthma was associated with the increased levels of tumor necrosis factor ligand superfamily member 14 and CC motif chemokine 4 (β = 0.145, 95%CI = 0.077-0.212, P = 2.936e-05; β = 0.128, 95%CI = 0.063-0.193, P = 1.036e-04). Third, CC motif chemokine 4 increased the risk of hypertension (P = 0.043); and after adjusting for this protein, asthma still increased the risk of hypertension, but the strength of its P-value changed from 0.004 to 0.011.

CONCLUSION

Asthma was a risk factor for hypertension and atrial fibrillation at the genetic level, and CC motif chemokine 4 might play a mediating role in the mechanism by which asthma promoted hypertension. Thus, effective control of asthma may help reduce the risk of some cardiovascular diseases in older adults.

Association between psychiatric admissions in patients with schizophrenia and IL-6 plasma levels polygenic score

Schizophrenia diagnosis and admission history were associated with a polygenic score (PGS) for schizophrenia based on a subset of variants that act by modifying the expression of genes whose expression is also modified by antipsychotics. This gene set was enriched in cytokine production. Interleukin-6 (IL-6) is the only cytokine whose plasma levels were associated both with schizophrenia diagnosis and with acute decompensations in the largest meta-analysis. Therefore, we hypothesized that an IL-6 PGS, but not other cytokines PGSs, would be associated with schizophrenia chronicity/psychiatric admissions. Using the IL-6 PGS model from The PGS Catalog, IL-6 PGS was calculated in 427 patients with schizophrenia and data regarding admission history. Association between IL-6 PGS and chronicity, measured as number and duration of psychiatric admissions, or ever readmission was analyzed by multivariate ordinal and logistic regression, respectively. Specificity of results was assessed by analysis of PGSs from the other cytokines at The PGS Catalog with meta-analytic evidence of association with schizophrenia diagnosis or acute decompensations, IL-1RA, IL-4, IL-8, and IL-12. IL-6 PGS was associated with schizophrenia chronicity, explaining 1.51% of variability (OR = 1.29, 95% CI 1.07-1.55, P = 0.007). There was no association with ever readmission. Other cytokines PGSs were not associated with chronicity. Association with IL-6 PGS was independent of association with schizophrenia PGS. Our results provide evidence that genetically regulated higher levels of IL-6 are involved in schizophrenia chronicity, highlighting the relevance of immunity processes for a subgroup of patients.

Integrating Genome-Wide Polygenic Risk Scores With Nongenetic Models to Predict Surgical Site Infection After Total Knee Arthroplasty Using United Kingdom Biobank Data

BACKGROUND

Prediction of the risk of developing surgical site infection (SSI) in patients following total knee arthroplasty (TKA) is of clinical importance. Genetic susceptibility is involved in developing TKA-related SSI. Previously reported models for predicting SSI were constructed using nongenetic risk factors without incorporating genetic risk factors. To address this issue, we performed a genome-wide association study (GWAS) using the UK Biobank database.

METHODS

Adult patients who underwent primary TKA (n = 19,767) were analyzed and divided into SSI (n = 269) and non-SSI (n = 19,498) cohorts. Nongenetic covariates, including demographic data and preoperative comorbidities, were recorded. Genetic variants associated with SSI were identified by GWAS and included to obtain standardized polygenic risk scores (zPRS, an estimate of genetic risk). Prediction models were established through analyses of multivariable logistic regression and the receiver operating characteristic curve.

RESULTS

There were 4 variants (rs117896641, rs111686424, rs8101598, and rs74648298) achieving genome-wide significance that were identified. The logistic regression analysis revealed 7 significant risk factors: increasing zPRS, decreasing age, men, chronic obstructive pulmonary disease, diabetes mellitus, rheumatoid arthritis, and peripheral vascular disease. The areas under the receiver operating characteristic curve were 0.628 and 0.708 when zPRS (model 1) and nongenetic covariates (model 2) were used as predictors, respectively. The areas under the receiver operating characteristic curve increased to 0.76 when both zPRS and nongenetic covariates (model 3) were used as predictors. A risk-prediction nomogram was constructed based on model 3 to visualize the relative effect of statistically significant covariates on the risk of SSI and predict the probability of developing SSI. Age and zPRS were the top 2 covariates that contributed to the risk, with younger age and higher zPRS associated with higher risks.

CONCLUSIONS

Our GWAS identified 4 novel variants that were significantly associated with susceptibility to SSI following TKA. Integrating genome-wide zPRS with nongenetic risk factors improved the performance of the model in predicting SSI.

Dietary influences on urinary tract infections: unraveling the gut microbiota connection

This study employs Mendelian randomization to investigate the causal relationships between dietary factors, gut microbiota, and urinary tract infections (UTIs). Our analysis revealed statistically significant associations, including high alcohol intake, cheese, and oily fish consumption with UTI risk, as well as links between UTI risk and specific gut microbiota, such as Prevotellaceae, Butyrivibrio, Anaerotruncus, and Dorea. Additionally, we observed associations with inflammatory markers, including C-Reactive Protein and Interleukin-6. Although the observed effects of these dietary factors on UTI risk are minimal and may limit their clinical relevance, these findings can still hold significant implications at the population level in public health. This research offers novel insights into the interplay between diet, gut microbiota, and UTI risk, laying a foundation for future studies. Further research is warranted to validate these associations and to explore the underlying mechanisms and their broader impact on public health.

A Mendelian randomization study on causal relationship between metabolic factors and abnormal spermatozoa

Background

Male infertility is a global health problem. There is an increasing attention on the association of metabolic status with spermatogenesis. However, the impacts of metabolic factors on semen parameters are still unclear. To provide evidence for developing appropriate interventions on disease screening and prevention, we performed a Mendelian randomization (MR) analysis to assess causality between various metabolic factors and abnormal spermatozoa.

Methods

We conducted a two-sample MR study to appraise the causal effects of 16 metabolic factors (including indexes of metabolic traits, glucose metabolism, lipid profile, adipokines, uric acid and metabolic diseases) on abnormal spermatozoa from genome-wide association studies (GWASs). Filtering with strict criteria, eligible genetic instruments closely associated with each of the factors were extracted. We employed inverse variance weighted for major analysis, with supplement MR methods including MR-Egger and weighted median. Heterogeneity and pleiotropy tests were further used to detect the reliability of analysis.

Results

After rigorous quality control in this MR framework, we identified that body fat percentage [odds ratio (OR) =1.49, 95% confidence interval (CI): 1.01-2.20, P=0.046] and resistin (OR =1.55, 95% CI: 1.11-2.19, P=0.01) were causally associated with a higher risk of abnormal spermatozoa. In terms of other indexes of metabolic traits, glucose metabolism, serum lipid profile and uric acid and metabolic diseases including type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD), no causal effects were observed (P>0.05).

Conclusions

Our MR analysis provides robust evidence that body fat percentage and resistin are risk factors for abnormal spermatozoa, suggesting implications of identifying them for potential interventions and clinical therapies in male infertility. Further investigation in larger-scale GWASs on subgroups of abnormal spermatozoa will verify impacts of metabolic factors on spermatogenesis.

Ancestrally diverse genome-wide association analysis highlights ancestry-specific differences in genetic regulation of plasma protein levels

Fully characterizing the genetic architecture of circulating proteins in multi-ancestry populations provides an unprecedented opportunity to gain insights into the etiology of complex diseases. We characterized and contrasted the genetic associations of plasma proteomes in 9,455 participants of European and African (19.8%) ancestry from the Atherosclerosis Risk in Communities Study. Of 4,651 proteins, 1,408 and 2,565 proteins had protein-quantitative trait loci (pQTLs) identified in African and European ancestry respectively, and twelve unreported potentially causal protein-disease relationships were identified. Shared pQTLs across the two ancestries were detected in 1,113 aptamer-region pairs pQTLs, where 53 of them were not previously reported (all trans pQTLs). Sixteen unique protein-cardiovascular trait pairs were colocalized in both European and African ancestry with the same candidate causal variants. Our systematic cross-ancestry comparison provided a reliable set of pQTLs, highlighted the shared and distinct genetic architecture of proteome in two ancestries, and demonstrated possible biological mechanisms underlying complex diseases.

Proteome-wide mendelian randomization identifies novel therapeutic targets for chronic kidney disease

There is an urgent need to pinpoint novel targets for drug discovery in the context of chronic kidney disease (CKD), and the proteome represents a significant pool of potential therapeutic targets. To address this, we performed proteome-wide analyses using Mendelian randomization (MR) and colocalization techniques to uncover potential targets for CKD. We extracted summary-level data from the ARIC study, focusing on 7213 European American (EA) individuals and 4657 plasma proteins. To broaden our analysis, we incorporated genetic association data from Icelandic cohorts, thereby enhancing our investigation into the correlations with chronic kidney disease (CKD), creatinine-based estimated glomerular filtration rate (eGFRcrea), and estimated glomerular filtration rate (eGFR). We utilized genetic association data from the GWAS Catalog, including CKD (765,348, 625,219 European ancestry and 140,129 non-European ancestry), eGFRcrea (1,004,040, European ancestry), and eGFR (567,460, European ancestry). Employing MR analysis, we estimated the associations between proteins and CKD risk. Additionally, we conducted colocalization analysis to evaluate the existence of shared causal variants between the identified proteins and CKD. We detected notable correlations between levels predicted based on genetics of three circulating proteins and CKD, eGFRcrea, and eGFR. Notably, our colocalization analysis provided robust evidence supporting these associations. Specifically, genetically predicted levels of Transcription elongation factor A protein 2 (TCEA2) and Neuregulin-4 (NRG4) exhibited an inverse relationship with CKD risk, while Glucokinase regulatory protein (GCKR) showed an increased risk of CKD. Furthermore, our colocalization analysis also supported the associations of TCEA2, NRG4, and GCKR with the risk of eGFRcrea and eGFR.

The Mediating Roles of Lung Function Traits and Inflammatory Factors on the Associations between Measures of Obesity and Risk of Lower Respiratory Tract Infections: A Mendelian Randomization Study

BACKGROUND

Identifying mediators between obesity-related traits and lower respiratory tract infections (LRTIs) would inform preventive and therapeutic strategies to reduce the burden of LRITs. We aimed to recognize whether lung function and inflammatory factors mediate their associations.

METHODS

We conducted a two-step, two-sample Mendelian randomization (MR) analysis. Two-sample MR was performed on (1) obesity-related traits (i.e., body mass index [BMI], waist circumference [WC], and waist-to-hip ratio [WHR]) and LRTIs (i.e., acute bronchitis, acute bronchiolitis, bronchiectasis, influenza, and pneumonia), (2) obesity-related traits and potential mediators, and (3) potential mediators and LRTIs. Next, two-step MR was applied to infer whether the mediation effects exist.

RESULTS

We found that C-reactive protein (CRP), interleukin-6 (IL-6), and forced expiratory volume in the first second (FEV1) mediated 32.59% (95% CI: 17.90%, 47.27%), 7.96% (95% CI: 1.79%, 14.14%), and 4.04% (95% CI: 0.34%, 7.74%) of the effect of BMI on pneumonia, and they mediated 26.90% (95% CI: 13.98%, 39.83%), 10.23% (95% CI: 2.72%, 17.73%), and 4.67% (95% CI: 0.25%, 9.09%) of the effect of WC on pneumonia, respectively. Additionally, CRP, forced vital capacity (FVC), and FEV1 mediated 18.66% (95% CI: 8.70%, 28.62%), 8.72% (95% CI: 1.86%, 15.58%), and 8.41% (95% CI: 2.77%, 14.06%) of the effect of BMI on acute bronchitis, and they mediated 19.96% (95% CI: 7.44%, 32.48%), 12.19% (95% CI: 2.00%, 22.39%), and 12.61% (95% CI: 2.94%, 22.29%) of the effect of WC on acute bronchitis, respectively.

CONCLUSIONS

Health interventions linked to reducing inflammation and maintaining normal lung function could help mitigate the risk of obesity-related LRTIs.

Plasma proteometabolome in lung cancer: exploring biomarkers through bidirectional Mendelian randomization and colocalization analysis

Unlike other cancers with widespread screening (breast, colorectal, cervical, prostate, and skin), lung nodule biopsies for positive screenings have higher morbidity with clinical complications. Development of non-invasive diagnostic biomarkers could thereby significantly enhance lung cancer management for at-risk patients. Here, we leverage Mendelian Randomization (MR) to investigate the plasma proteome and metabolome for potential biomarkers relevant to lung cancer. Utilizing bidirectional MR and co-localization analyses, we identify novel associations, highlighting inverse relationships between plasma proteins SFTPB and KDELC2 in lung adenocarcinoma (LUAD) and positive associations of TCL1A with lung squamous cell carcinoma (LUSC) and CNTN1 with small cell lung cancer (SCLC). Additionally, our work reveals significant negative correlations between metabolites such as theobromine and paraxanthine, along with paraxanthine-related ratios, in both LUAD and LUSC. Conversely, positive correlations are found in caffeine/paraxanthine and arachidonate (20:4n6)/paraxanthine ratios with these cancer types. Through single-cell sequencing data of normal lung tissue, we further explore the role of lung tissue-specific protein SFTPB in carcinogenesis. These findings offer new insights into lung cancer etiology, potentially guiding the development of diagnostic biomarkers and therapeutic approaches.

Exploring the relationship between the interleukin family and lung adenocarcinoma through Mendelian randomization and RNA sequencing analysis

BACKGROUND

Lung adenocarcinoma (LUAD) is still one of the most prevalent malignancies. Interleukin factors are closely associated with the initiation and progression of cancer. However, the relationship between interleukin factors and LUAD has not been fully elucidated. This study aimed to use Mendelian randomization (MR) and RNA sequencing (RNA-seq) analyses to identify the interleukin factors associated with the onset and progression of LUAD.

METHODS

Exposure-related instrumental variables were selected from interleukin factor summary datasets. The LUAD summary dataset from FINGENE served as the outcome. MR and sensitivity analyses were conducted to screen for interleukin factors associated with LUAD occurrence. Transcriptome analyses revealed the role of interleukin factors in lung tissues. The results were validated through Western blotting and further confirmed with driver gene-negative patients from multiple centers. Potential mechanisms influencing LUAD occurrence and development were explored using bulk RNA-seq and single-cell RNA-seq data.

RESULTS

MR analysis indicated that elevated plasma levels of IL6RB, IL27RA, IL22RA1, and IL16 are causally associated with increased LUAD risk, while IL18R1 and IL11RA exhibit the opposite effect. Transcriptome analyses revealed that IL11RA, IL18R1, and IL16 were downregulated in tumor tissues compared with normal lung tissue, but only higher expression of IL11RA correlated with improved prognosis in patients with LUAD from different centers and persisted even in driver-gene negative patients. The IL11RA protein level was lower in various LUAD cell lines than in human bronchial epithelial cells. The genes co-expressed with IL11RA were enriched in the Ras signaling pathway and glycosylation processes. Fibroblasts were the primary IL11RA-expressing cell population, with IL11RA+fibroblasts exhibiting a more immature state. The genes differentially expressed between IL11RA+and IL11RA- fibroblasts were involved in the PI3K-Akt/TNF signaling pathway.

CONCLUSION

According to the MR and transcriptome analyses, the downregulation of IL11RA was closely related to the occurrence and development of LUAD.

Plasma Proteomics to Identify Drug Targets and Potential Drugs for Retinal Artery Occlusion: An Integrated Analysis in the UK Biobank

Retinal artery occlusion (RAO), which is positively correlated with acute ischemic stroke (IS) and results in severe visual impairment, lacks effective intervention drugs. This study aims to perform integrated analysis using UK Biobank plasma proteome data of RAO and IS to identify potential targets and preventive drugs. A total of 7191 participants (22 RAO patients, 1457 IS patients, 8 individuals with both RAO and IS, and 5704 healthy age-gender-matched controls) were included in this study. Unique 1461 protein expression profiles of RAO, IS, and the combined data set, extracted from UK Biobank Plasma proteomics projects, were analyzed using both differential expression analysis and elastic network regression (Enet) methods to identify shared key proteins. Subsequent analyses, including single cell type expression assessment, pathway enrichment, and druggability analysis, were conducted for verifying shared key proteins and discovery of new drugs. Five proteins were found to be shared among the samples, with all of them showing upregulation. Notably, adhesion G-protein coupled receptor G1 (ADGRG1) exhibited high expression in glial cells of the brain and eye tissues. Gene set enrichment analysis revealed pathways associated with lipid metabolism and vascular regulation and inflammation. Druggability analysis unveiled 15 drug candidates targeting ADGRG1, which demonstrated protective effects against RAO, especially troglitazone (-8.5 kcal/mol). Our study identified novel risk proteins and therapeutic drugs associated with the rare disease RAO, providing valuable insights into potential intervention strategies.

Plasma metabolites and inflammatory proteins profiling predict outcome of Fufang Duzhong Jiangu granules treating Kashin-Beck disease

To investigate predictive biomarkers that could be used to identify patients' response to treatment, plasma metabolomics and proteomics analyses were performed in Kashin-Beck disease (KBD) patients treated with Fufang Duzhong Jiangu Granules (FDJG). Plasma was collected from 12 KBD patients before treatment and 1 month after FDJG treatment. LC-MS and olink proteomics were employed for obtaining plasma metabolomics profiling and inflammatory protein profiles. Patients were classified into responders and non-responders based on drug efficacy. Enrichment analyses of differential metabolites and proteins of the responders at baseline and after treatment were conducted to study the mechanism of drug action. Differential metabolites and proteins between the two groups were screened as biomarkers to predict the drug efficacy. The receiver operating characteristic curve was used to evaluate the prediction accuracy of biomarkers. The changes in metabolites and inflammatory proteins in responders after treatment reflected the mechanism of FDJG treatment for KBD, which may act on glycerophospholipid metabolism, d-glutamine and d-glutamate metabolism, nitrogen metabolism and NF-kappa B signaling pathway. Three metabolites were identified as potential predictors: N-undecanoylglycine, β-aminopropionitrile and PC [18:3(6Z,9Z,12Z)/20:4(8Z,11Z,14Z,17Z)]. For inflammatory protein, interleukin-8 was identified as a predictive biomarker to detect responders. Combined use of these four biomarkers had high predictive ability (area under the curve = 0.972).

Identifying genetically-supported drug repurposing targets for non-small cell lung cancer through mendelian randomization of the druggable genome

Background

Lung cancer is responsible for most cancer-related deaths, and non-small cell lung cancer (NSCLC) accounts for the majority of cases. Targeted therapy has made promising advancements in systemic treatment for NSCLC over the last two decades, but inadequate drug targets with clinically proven survival benefits limit its universal application in clinical practice compared to chemotherapy and immunotherapy. There is an urgent need to explore new drug targets to expand the beneficiary group. This study aims to identify druggable genes and to predict the efficacy and prognostic value of the corresponding targeted drugs in NSCLC.

Methods

Two-sample mendelian randomization (MR) of druggable genes was performed to predict the efficacy of their corresponding targeted therapy for NSCLC. Subsequent sensitivity analyses were performed to assess potential confounders. Accessible RNA sequencing data were incorporated for subsequent verifications, and Kaplan-Meier survival curves of different gene expressions were used to explore the prognostic value of candidate druggable genes.

Results

MR screening encompassing 4,863 expression quantitative trait loci (eQTL) and 1,072 protein quantitative trait loci (pQTL, with 453 proteins overlapping) were performed. Seven candidate druggable genes were identified, including CD33, ENG, ICOSLG and IL18R1 for lung adenocarcinoma, and VSIR, FSTL1 and TIMP2 for lung squamous cell carcinoma. The results were validated by further transcriptomic investigations.

Conclusions

Drugs targeting genetically supported genomes are considerably more likely to yield promising efficacy and succeed in clinical trials. We provide compelling genetic evidence to prioritize drug development for NSCLC.

Potential mechanisms of gut microbiota influence on different types of vertigo: a bidirectional Mendelian randomization and mediation analysis

BACKGROUND

The relationship between gut microbiota and vertigo, specifically Benign Paroxysmal Vertigo (BPV) and Vertigo of Central (VC), remains underexplored.

AIM AND HYPOTHESES

This study aims to investigate the causal relationships between gut microbiota and two types of vertigo, BPV and VC. Additionally, the study seeks to explore the mediation effects of metabolic, inflammatory, and psychological factors on these relationships. We hypothesize that specific taxa of gut microbiota have a causal effect on the risk of developing BPV and VC. The mediation effects of HbA1c, obesity, major depression, and interleukin-18 levels significantly influence the relationships between gut microbiota and vertigo.

METHOD

Utilizing a bidirectional two-sample Mendelian randomization approach, this study investigated causal associations between gut microbiota and the two types of vertigo. A network MR assessed mediation effects of HbA1c, major depression, obesity, and interleukin-18 levels, with data sourced from several consortia, including MiBioGen.

RESULTS

Distinct gut microbiota displayed varying influences on BPV and VC risks. A total of ten taxa affect BPV. Among these, two taxa have an odds ratio (OR) greater than 1, including one class, one order. Conversely, eight taxa have an OR less than 1, encompassing four families, three genera, and one order. The OR for these taxa ranges from 0.693 to 0.930, with p-values between 0.006 and 0.048. For VC, eight taxa were found to have an impact. Five of these taxa exhibit an OR greater than 1, including four genera and one phylum. The OR for these taxa ranges from 1.229 to 2.179, with p-values from 0.000 to 0.046. The remaining three taxa have an OR less than 1, comprising one family and two genera, with an OR range of 0.445 to 0.792 and p-values ranging from 0.013 to 0.050. The mediation analysis for BPV shows that major depression, obesity, and HbA1c are key mediators between specific taxa and BPV. Major depression mediates 28.77% of the effect of family Rhodospirillaceae on BPV. Obesity mediates 13.90% of the effect of class Lentisphaeria/order Victivallales. HbA1c mediates 11.79% of the effect of genus Bifidobacterium, 11.36% of family Bifidobacteriaceae/order Bifidobacteriales. For VC, interleukin-18 levels and major depression are significant mediators. Interleukin-18 levels mediate 6.56% of the effect of phylum Actinobacteria. Major depression mediates 6.51% of the effect of genus Alloprevotella.

CONCLUSION

The study highlights potential causal links between gut microbiota and vertigo, emphasizing metabolic and psychological mediators. These insights underscore the therapeutic potential of targeting gut health in vertigo management.

Is there a causal relationship between resistin levels and bone mineral density, fracture occurrence? A mendelian randomization study

BACKGROUND

In a great many of observational studies, whether there is a relevance of resistin levels on bone mineral density (BMD) and fracture occurrence has been inconsistently reported, and the causality is unclear.

METHODS

We aim to assess the resistin levels on BMD and fracture occurrence within a Mendelian randomization (MR) analysis. Exposure and outcome data were derived from the Integrative Epidemiology Unit (IEU) Open genome wide association studies (GWAS) database. Screening of instrumental variables (IVs) was performed subject to conditions of relevance, exclusivity, and independence. Inverse variance weighting (IVW) was our primary method for MR analysis based on harmonized data. Weighted median and MR-Egger were chosen to evaluate the robustness of the results of IVW. Simultaneously, heterogeneity and horizontal pleiotropy were also assessed and the direction of potential causality was detected by MR Steiger. Multivariable MR (MVMR) analysis was used to identify whether confounding factors affected the reliability of the results.

RESULTS

After Bonferroni correction, the results showed a suggestively positive causality between resistin levels and total body BMD (TB-BMD) in European populations over the age of 60 [β(95%CI): 0.093(0.021, 0.165), P = 0.011]. The weighted median [β(95%CI): 0.111(0.067, 0.213), P = 0.035] and MR-Egger [β(95%CI): 0.162(0.025, 0.2983), P = 0.040] results demonstrate the robustness of the IVW results. No presence of pleiotropy or heterogeneity was detected between them. MR Steiger supports the causal inference result and MVMR suggests its direct effect.

CONCLUSIONS

In European population older than 60 years, genetically predicted higher levels of resistin were associated with higher TB-BMD. A significant causality between resistin levels on BMD at different sites, fracture in certain parts of the body, and BMD in four different age groups between 0-60 years of age was not found in our study.

The role of serum interleukins in Cancer: A Multi-center Mendelian Randomization study

The occurrence of cancer is often accompanied by immune evasion and tumor-promoting inflammation, with interleukins (IL) playing a pivotal role in the immune-inflammatory mechanism. However, the precise contribution of serum interleukins in cancer remains elusive. We obtained GWAS summary data for 35 interleukins from eight independent large-scale serum proteome studies of European ancestry populations and for 23 common cancers from the FinnGen Consortium. We then conducted a multicenter Mendelian Randomization (MR) study to explore the relationship between systemic inflammatory status and cancers. 24 causal associations between interleukins and cancers were supported by multicenter data, 18 of which were reported for the first time. Our results indicated that IL-1α (Hodgkin lymphoma), IL-5 (bladder cancer), IL-7 (prostate cancer), IL-11 (bone malignant tumor), IL-16 (lung cancer), IL-17A (pancreatic cancer), IL-20 (bladder cancer), IL-22 (lymphocytic leukemia), IL-34 (breast cancer), IL-36β (prostate cancer), and IL-36γ (liver cancer) were risk factors for related cancers. Conversely, IL-9 (malignant neoplasms of the corpus uteri), IL-17C (liver cancer), and IL-31 (colorectal cancer, bladder cancer, pancreatic cancer, and cutaneous melanoma) exhibited protective effects against related cancers. Notably, the dual effects of serum interleukins were also observed. IL-18 acted as a risk factor for prostate cancer, however, was a protective factor against laryngeal cancer. Similarly, IL-19 promoted the development of lung cancer and myeloid leukemia, while conferring protection against Breast, cervical, and thyroid cancers. Our study confirmed the genetic association between multiple serum interleukins and cancers. Immune and anti-inflammatory strategies targeting these associations provide opportunities for prevention and treatment.

Therapeutic potential of cis-targeting bispecific antibodies

The growing clinical success of bispecific antibodies (bsAbs) has led to rapid interest in leveraging dual targeting in order to generate novel modes of therapeutic action beyond mono-targeting approaches. While bsAbs that bind targets on two different cells (trans-targeting) are showing promise in the clinic, the co-targeting of two proteins on the same cell surface through cis-targeting bsAbs (cis-bsAbs) is an emerging strategy to elicit new functionalities. This includes the ability to induce proximity, enhance binding to a target, increase target/cell selectivity, and/or co-modulate function on the cell surface with the goal of altering, reversing, or eradicating abnormal cellular activity that contributes to disease. In this review, we focus on the impact of cis-bsAbs in the clinic, their emerging applications, and untangle the intricacies of improving bsAb discovery and development.

Integration of QTL and comprehensive analysis in the circulating inflammatory cytokines for pan-cancer

BACKGROUND

Chemokines and cytokines are components of the tumor microenvironment and also influence tumorigenesis and its composition. However, whether they genetically proxy tumorigenesis is unclear. For causal inferences, eQTL and pQTL were used to determine the role of chemokines and cytokines in pan-cancer. The impact on the tumor immune microenvironment was also explored.

METHODS

This study leveraged summary statistics from respective genome-wide association studies (GWAS) of 109 cytokines and chemokines in 18 types of solid tumors. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines and chemokines, located in or close to their coding gene (cis), were used as instrumental variables. A two-sample MR design was employed, followed by comprehensive sensitivity analyses to validate the robustness of results. The impact on immune infiltration was investigated using the TIMER and TISIDB websites. Survival analysis was conducted using the K-M plotter and TIMER 2.0 websites. The TISCH and GEO databases were used to carry out scRNA cell analysis.Analyzing relevant proteins using the STRING database and conducting enrichment pathways for GO analysis of the identified proteins.

RESULTS

The results of the inverse-variance weighted (IVW) method using cis-protein QTL (cis-pQTL) instruments showed the causal effects of TNF in reducing the risk of squamous cell lung cancer (LUSC) and HGF in reducing the risk of head and neck cancer (HNSC).The results were consistent with the eQTL. HGF was associated with better overall survival (OS) in HNSC, regardless of the types of cells enriched. However, high expression of the ligand MET for HGF leads to a decrease in overall survival in LUSC. TNF was related to poor OS in LUSC with no significant impact. However, in CD8 + T cell-enriched, eosinophil-enriched, macrophage-enriched, and NK cell-deficient types of LUSC, high expression of TNF leads to a poor prognosis, and there is statistical significance. The results showed a significant positive correlation between TNF and most immune cell infiltration, immunomodulator and chemokine in LUSC. HGF is positively correlated with the majority of immune cells except CD56 + cells, as well as some immune regulatory factors and chemotactic factors. According to single-cell sequencing results, HGF is mainly secreted by fibroblasts and myofibroblasts in HNSC, while in LUSC, it is primarily secreted by macrophages and CD8 + T cells secrete TNF. The GO/KEGG analysis suggests that proteins related to HGF are mainly involved in regulating peptidyl-tyrosine phosphorylation and positive regulation of the MAPK cascade. Proteins related to TNF are primarily associated with the regulation of I-kappaB kinase/NF-kappaB signaling and cytokine-mediated signaling pathway.

CONCLUSIONS

HGF is primarily secreted by fibroblasts in HNSC and may have a protective effect on the occurrence and prognosis of HNSC. These effects are independent of immune cell influence, and this role may not necessarily be mediated through the HGF/MET pathway. On the other hand, TNF in LUSC is mainly secreted by immune cells like CD8 + T cell, and it may have a protective effect on the occurrence of LUSC. However, it's impact on the prognosis of LUSC through the immune microenvironment may have a different effect.

Circulating inflammatory cytokines and the risk of sepsis: a bidirectional mendelian randomization analysis

BACKGROUND

Sepsis is a life-threatening condition that is characterized by multiorgan dysfunction and caused by dysregulated cytokine networks, which are closely associated with sepsis progression and outcomes. However, currently available treatment strategies that target cytokines have failed. Thus, this study aimed to investigate the interplay between genetically predicted circulating concentrations of cytokines and the outcomes of sepsis and to identify potential targets for sepsis treatment.

METHODS

Data related to 35 circulating cytokines in 31,112 individuals (including 11,643 patients with sepsis) were included in genome-wide association studies (GWASs) from the UK Biobank and FinnGen consortia. A bidirectional two-sample Mendelian randomization (MR) analysis was performed using single nucleotide polymorphisms (SNPs) to evaluate the causal effects of circulating cytokines on sepsis outcomes and other cytokines.

RESULTS

A total of 35 inflammatory cytokine genes were identified in the GWASs, and 11 cytokines, including Interleukin-1 receptor antagonist (IL-1ra), macrophage inflammatory protein 1 (MIP1α), IL-16, et al., were associated with sepsis outcome pairs according to the selection criteria of the cis-pQTL instrument. Multiple MR methods verified that genetically predicted high circulating levels of IL-1ra or MIP1α were negatively correlated with genetic susceptibility to risk of sepsis, including sepsis (28-day mortality), septicaemia, streptococcal and pneumonia-derived septicaemia (P ≤ 0.01). Furthermore, genetic susceptibility of sepsis outcomes except sepsis (28-day mortality) markedly associated with the circulating levels of five cytokines, including active plasminogen activator inhibitor (PAI), interleukin 7 (IL-7), tumour necrosis factor alpha (TNF-α), beta nerve growth factor (NGF-β), hepatic growth factor (HGF) (P < 0.05). Finally, we observed that the causal interaction network between MIP1α or IL-1ra and other cytokines (P < 0.05).

CONCLUSIONS

This comprehensive MR analysis provides insights into the potential causal mechanisms that link key cytokines, particularly MIP1α, with risk of sepsis, and the findings suggest that targeting MIP1α may be a potential strategy for preventing sepsis.