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Abstract Purposes Gastric cancer (GC) is one of the most common malignant tumors threatening human beings and has a poor prognosis. Therefore, exploring unveiled biomarkers or therapeutic targets for the diagnosis and treatment of GC is crucial. Methods A total of 5772 protein quantitative trait loci (pQTL) were aggregated from four latest large-scale proteomics cohorts. Two-sample Mendelian randomization (two-sample MR) was utilized to identify the causal effect of blood plasma proteins on GC. Heterogeneity, pleiotropy, and directionality analyses were employed to evaluate proteins identified via two-sample MR. The robustness of results was further validated via colocalization. The drug targets of proteins were evaluated to reveal the compounds that can interfere with these proteins. Results Ten proteins with potential causations in relation to GC were identified: LY6D, SLURP1, MLN, PSCA, THSD1, CFTR, PPM1B, KDM3A, TSC1, and HCG22. Among these proteins, LY6D, SLURP1, and THSD1 were considered as the most reliable biomarkers of GC due to their significant H4 posterior probabilities in colocalization analysis and absence of pleiotropy. Compound 35, nitrosamide, and 0175029-0000 were potential drugs or small molecules targeting LY6D, SLURP1, and THSD1, respectively. Conclusion This study identified several plasma proteins as potential biomarkers of GC and provided data support and new insights into the early diagnosis, intervention, and therapeutic targets of GC.

Purposes: Gastric cancer (GC) is one of the most common malignant tumors threatening human beings and has a poor prognosis. Therefore, exploring unveiled biomarkers or therapeutic targets for the diagnosis and treatment of GC is crucial. Methods: A total of 5772 protein quantitative trait loci (pQTL) were aggregated from four latest large-scale proteomics cohorts. Two-sample Mendelian randomization (two-sample MR) was utilized to identify the causal effect of blood plasma proteins on GC. Heterogeneity, pleiotropy, and directionality analyses were employed to evaluate proteins identified via two-sample MR. The robustness of results was further validated via colocalization. The drug targets of proteins were evaluated to reveal the compounds that can interfere with these proteins. Results: Ten proteins with potential causations in relation to GC were identified: LY6D, SLURP1, MLN, PSCA, THSD1, CFTR, PPM1B, KDM3A, TSC1, and HCG22. Among these proteins, LY6D, SLURP1, and THSD1 were considered as the most reliable biomarkers of GC due to their significant H4 posterior probabilities in colocalization analysis and absence of pleiotropy. Compound 35, nitrosamide, and 0175029-0000 were potential drugs or small molecules targeting LY6D, SLURP1, and THSD1, respectively. Conclusion: This study identified several plasma proteins as potential biomarkers of GC and provided data support and new insights into the early diagnosis, intervention, and therapeutic targets of GC. [ABSTRACT FROM AUTHOR]

Background: Sepsis is an inflammatory disease that leads to severe mortality, highlighting the urgent need to identify new therapeutic strategies for sepsis. Proteomic research serves as a primary source for drug target identification. We employed proteome-wide Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to identify potential targets for sepsis and sepsis-related death. Methods: Genetic data for plasma proteomics were obtained from 35,559 Icelandic individuals and an initial MR analysis was conducted using 13,531 sepsis cases from the FinnGen R10 cohort to identify associations between plasma proteins and sepsis. Subsequently, significant proteins underwent genetic correlation analysis, followed by replication in 54,306 participants from the UK Biobank Pharma Proteomics Project and validation in 11,643 sepsis cases from the UK Biobank. The identified proteins were then subjected to colocalization analysis, enrichment analysis, and protein-protein interaction network analysis. Additionally, we also investigated a MR analysis using plasma proteins on 1,896 sepsis cases with 28-day mortality from the UK Biobank. Results: After FDR correction, MR analysis results showed a significant causal relationship between 113 plasma proteins and sepsis. Genetic correlation analysis revealed that only 8 proteins had genetic correlations with sepsis. In the UKB-PPP replication analysis, only 4 proteins were found to be closely associated with sepsis, while validation in the UK Biobank sepsis cases found overlaps for 21 proteins. In total, 30 proteins were identified in the aforementioned analyses, and colocalization analysis revealed that only 2 of these proteins were closely associated with sepsis. Additionally, in the 28-day mortality MR analysis of sepsis, we also found that only 2 proteins were significant. Conclusions: The identified plasma proteins and their associated metabolic pathways have enhanced our understanding of the complex relationship between proteins and sepsis. This provides new avenues for the development of drug targets and paves the way for further research in this field. [ABSTRACT FROM AUTHOR]

It remains challenging to translate the findings from genome-wide association studies (GWAS) of autoimmune diseases (AIDs) into interventional targets, presumably due to the lack of knowledge on how the GWAS risk variants contribute to AIDs. In addition, current immunomodulatory drugs for AIDs are broad in action rather than disease-specific. We performed a comprehensive protein-centric omics integration analysis to identify AIDs-associated plasma proteins through integrating protein quantitative trait loci datasets of plasma protein (1348 proteins and 7213 individuals) and totally ten large-scale GWAS summary statistics of AIDs under a cutting-edge systematic analytic framework. Specifically, we initially screened out the protein-AID associations using proteome-wide association study (PWAS), followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we performed both Mendelian randomization (MR) and colocalization analyses to further identify protein-AID pairs with putatively causal relationships. We finally prioritized the potential drug targets for AIDs. A total of 174 protein-AID associations were identified by PWAS. AIDs-associated plasma proteins were significantly enriched in immune-related biological process and pathways, such as inflammatory response (P = 3.96 × 10–10). MR analysis further identified 97 protein-AID pairs with potential causal relationships, among which 21 pairs were highly supported by colocalization analysis (PP.H4 > 0.75), 10 of 21 were the newly discovered pairs and not reported in previous GWAS analyses. Further explorations showed that four proteins (TLR3, FCGR2A, IL23R, TCN1) have corresponding drugs, and 17 proteins have druggability. These findings will help us to further understand the biological mechanism of AIDs and highlight the potential of these proteins to develop as therapeutic targets for AIDs. [ABSTRACT FROM AUTHOR]

Background: Peripheral neuropathy (PN) is a common neurological disorder, and circulating plasma proteins with causal genetic evidence are a major source of therapeutic targets. This study identifies several potential plasma proteins that are causally related to PN risk, providing new insights into protein-mediated pathogenesis of PN and potential targets for novel therapies. Methods: To identify potential therapeutic targets for PN, we employed twosample Mendelian randomization (MR) to identify plasma proteins associated with six common PN. First, we screened for proteins related to PN using genomewide association studies (GWAS), obtaining genetic data on plasma proteomes from 35,559 Icelanders. Summary data for six common PN, including Carpal Tunnel Syndrome (CTS), Trigeminal Neuralgia (TN), Alcoholic Neuropathy (AIP), Drug-induced Neuropathy (DIP), Diabetic Neuropathy (DP), and Guillain-Barré syndrome (GBS), were obtained from the FinnGen database. Two-sample MR and colocalization analyses were then conducted to further identify proteinPN pairs with presumed causal relationships. Enrichment analysis of positive proteins revealed potential biological processes and pathways. Based on druggene interaction analysis, we ultimately identified causal proteins associated with PN that could serve as potential drug targets for treating PN. Results: Through MR analysis, we identified eight proteins (UBC12, SEM4C, IL23R, Prothrombin, CBS, Microglobulin, MATN4, COLEC12) with causal relationships to PN. We found that UBC12 is a protective factor for DP and CTS, while the remaining proteins are risk factors. Further colocalization analysis showed a posterior probability of hypothesis 4 (PPH4) less than 0.75, indicating no positive colocalization results were found. From the pathway enrichment analysis, we discovered that the proteins were mainly concentrated in pathways related to defense response to bacterium, receptor signaling pathway via STAT, cell killing, negative regulation of cytokine production, and leukocyte mediated immunity. Finally, in Drug-Gene Interaction database (DGIdb), we identified three protein-coding genes (IL23R, F2, CBS) as potential drug targets for PN. Conclusion: Mendelian randomization studies confirm the causal relationship between genetically predicted PN-related risk and genetically predicted plasma protein abundance. Plasma proteins, as biomarkers associated with PN, can provide potential drug targets for etiological intervention research in PN. [ABSTRACT FROM AUTHOR]

Background: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the spine and sacroiliac joints. Recent genetic studies suggest certain plasma proteins may play a causal role in AS development. This study aims to identify and characterize these proteins using Mendelian randomization (MR) and colocalization analyses. Methods: Plasma protein data were obtained from recent publications in Nature Genetics, integrating data from five previous GWAS datasets, including 738 cispQTLs for 734 plasma proteins. GWAS summary data for AS were sourced from IGAS and other European cohorts. MR analyses were conducted using "TwoSampleMR" to assess causal links between plasma protein levels and AS. Colocalization analysis was performed with the coloc R package to identify shared genetic variants. Sensitivity analyses and protein-protein interaction (PPI) network analyses were conducted to validate findings and explore therapeutic targets. We performed Phenome-wide association study (PheWAS) to examine the potential side effects of drug protein on AS treatment. Results: After FDR correction, eight significant proteins were identified: IL7R, TYMP, IL12B, CCL8, TNFAIP6, IL18R1, IL23R, and ERAP1. Elevated levels of IL7R, IL12B, CCL8, IL18R1, IL23R, and ERAP1 increased AS risk, whereas elevated TYMP and TNFAIP6 levels decreased AS risk. Colocalization analysis indicated that IL23R, IL7R, and TYMP likely share causal variants with AS. PPI network analysis identified IL23R and IL7R as potential new therapeutic targets. Conclusions: This study identified eight plasma proteins with significant associations with AS risk, suggesting IL23R, IL7R, and TYMP as promising therapeutic targets. Further research is needed to explore underlying mechanisms and potential for drug repurposing. [ABSTRACT FROM AUTHOR]

Abstract According to the latest cancer research data, there are a significant number of new cancer cases and a substantial mortality rate each year. Although a substantial number of clinical patients are treated with existing cancer drugs each year, the efficacy is unsatisfactory. The incidence is still high and the effectiveness of most cancer drugs remains unsatisfactory. Therefore, we evaluated the human proteins for their causal relationship to for cancer risk and therefore also their potential as drug targets. We used summary tumors data from the FinnGen and cis protein quantitative trait loci (cis-pQTL) data from a genome-wide association study, and employed Mendelian randomization (MR) to explore the association between potential drug targets and nine tumors, including breast, colorectal, lung, liver, bladder, prostate, kidney, head and neck, pancreatic caners. Furthermore, we conducted MR analysis on external cohort. Moreover, Bidirectional MR, Steiger filtering, and colocalization were employed to validate the main results. The DrugBank database was used to discover potential drugs of tumors. Under the threshold of False discovery rate (FDR)

Abstract Background While numerous allergy-related biomarkers and targeted treatment strategies have been developed and employed, there are still signifcant limitations and challenges in the early diagnosis and targeted treatment for allegic diseases. Our study aims to identify circulating proteins causally associated with allergic disease-related traits through Mendelian randomization (MR)-based analytical framework. Methods Large-scale cis-MR was employed to estimate the effects of thousands of plasma proteins on five main allergic diseases. Additional analyses including MR Steiger analyzing and Bayesian colocalisation, were performed to test the robustness of the associations; These findings were further validated utilizing meta-analytical methods in the replication analysis. Both proteome- and transcriptome-wide association studies approach was applied, and then, a protein-protein interaction was conducted to examine the interplay between the identified proteins and the targets of existing medications. Results Eleven plasma proteins were identified with links to atopic asthma (AA), atopic dermatitis (AD), and allergic rhinitis (AR). Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. MR analysis and extra validation revealed STAT6 and TNFRSF6B to be Tier 1 and IL1RL2 and IL6R to be Tier 2 proteins with the potential for AA treatment. Two Tier 1 proteins, CRAT and TNFRSF6B, and five Tier 2 proteins, ERBB3, IL6R, MMP12, ICAM1, and IL1RL2, were linked to AD, and three Tier 2 proteins, MANF, STAT6, and TNFSF8, to AR. Conclusion Eleven Tier 1 and 2 protein targets that are promising drug target candidates were identified for AA, AD, and AR, which influence the development of allergic diseases and expose new diagnostic and therapeutic targets.

Background: Previous epidemiological studies have identified a correlation between serum protein levels and Psoriatic Arthritis (PsA). However, the precise nature of this relationship remains uncertain. Therefore, our objective was to assess whether circulating levels of 2,923 plasma proteins are associated with the risk of PsA, utilizing the Mendelian randomization (MR) approach. Methods: Two-sample MR analysis was performed to assess the causal impact of proteins on PsA risk. Exposure data for plasma proteins were sourced from a genome-wide association study (GWAS) conducted within the UK Biobank Pharma Proteomics Project, which encompassed 2,923 unique plasma proteins. The outcome data for PsA were sourced from the FinnGen study, a large-scale genomics initiative, comprising 3,537 cases and 262,844 controls. Additionally, colocalization analysis, Phenome-wide MR analysis, and candidate drug prediction were employed to identify potential causal circulating proteins and novel drug targets. Results: We thoroughly assessed the association between 1,837 plasma proteins and PsA risk, identifying seven proteins associated with PsA risk. An inverse association of Interleukin-10 (IL-10) with PsA risk was observed [odds ratio (OR)=0.45, 95% confidence interval (CI), 0.28 to 0.70, PFDR=0.072]. Additionally, Apolipoprotein F (APOF) has a positive effect on PsA risk (OR=2.08, 95% CI, 1.51 to 2.86, PFDR=0.005). Subsequently, we found strong evidence indicating that IL-10 and APOF were colocalized with PsA associations (PP.H4 = 0.834 for IL-10 and PP.H4 = 0.900 for APOF). Phenome-wide association analysis suggested that these two proteins may have dual effects on other clinical traits (PFDR<0.1). Conclusion: This study identified 7 plasma proteins associated with PsA risk, particularly IL-10 and APOF, which offer new insights into its etiology. Further studies are needed to assess the utility and effectiveness of these candidate proteins. [ABSTRACT FROM AUTHOR]

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) initially emerged as oral antidiabetic medication but were subsequently discovered to exhibit pleiotropic actions. Insomnia is a prevalent and debilitating sleep disorder. To date, the causality between SGLT2 inhibitors and insomnia remains unclear. This study aims to evaluate the causality between SGLT2 inhibitors and insomnia and identify potential plasma protein mediators. Using a two-sample Mendelian Randomization (MR) analysis, we estimated the causality of SGLT2 inhibition on insomnia and sleep duration. Additionally, employing a two-step and proteome-wide MR analysis, we evaluated the causal link of SGLT2 inhibition on 4907 circulating proteins and the causality of SGLT2 inhibition-driven plasma proteins on insomnia. We applied a false discovery rate (FDR) correction for multiple comparisons. Furthermore, mediation analyses were used to identify plasma proteins that mediate the effects of SGLT2 inhibition on insomnia. SGLT2 inhibition was negatively correlated with insomnia (odds ratio [OR] = 0.791, 95 % confidence interval [CI] [0.715, 0.876], P = 5.579*10^-6) and positively correlated with sleep duration (β = 0.186, 95 % CI [0.059, 0.314], P = 0.004). Among the 4907 circulating proteins, diadenosine tetraphosphatase (Ap4A) was identified as being linked to both SGLT2 inhibition and insomnia. Mediation analysis indicated that the effect of SGLT2 inhibition on insomnia partially operates through Ap4A (β = −0.018, 95 % CI [−0.036, −0.005], P = 0.023), with a mediation proportion of 7.7 %. The study indicated a causality between SGLT2 inhibition and insomnia, with plasma Ap4A potentially serving as a mediator. • Few previous studies have explored the relationship between SGLT2 inhibition and insomnia. • Mendelian randomization made us able to evaluate the causality of SGLT2 inhibition on insomnia. • Genetically-predicted SGLT2 inhibition negatively correlated to insomnia. • Plasma AP4A level mediates the inhibitory effect of SGLT2 inhibition on insomnia. [ABSTRACT FROM AUTHOR]

Background: Proteome‐wide Mendelian randomization studies have been increasingly utilized to identify potential drug targets for diseases. We aimed to identify potential therapeutic targets for migraine and its subtypes through the application of Mendelian randomization and co‐localization analysis methods. Methods: We utilized cis‐protein quantitative trait loci data for 1378 plasma proteins available from two studies with 7213 individuals and 35,559 individuals, respectively. Summary data for migraine and its subtypes were obtained from a genetic study involving up to 1,339,303 individuals. Proteins that passed both the discovery and validation Mendelian randomization analysis, sensitivity analysis, heterogeneity test, and pleiotropy test, were associated with ≥2 outcomes, and received strong support from co‐localization analysis (PP.H4.abf ≥0.80) and were classified as tier 1 proteins. Results: We identified three tier 1 proteins (LRP11, ITIH1, and ADGRF5), whose genes have not been previously identified as causal genes for migraine in genetic studies. LRP11 was significantly associated with the risk of any migraine (OR [odds ratio] = 0.968, 95% CI [confidence interval] = 0.955–0.981, p = 1.27 × 10−6) and significantly/suggestively associated with three migraine subtypes. ITIH1 was significantly associated with the risk of any migraine (OR = 1.044, 95% CI = 1.024–1.065, p = 1.08 × 10−5) and migraine with visual disturbances. ADGRF5 was significantly associated with the risk of any migraine (OR = 0.964, 95% CI = 0.946–0.982, p = 8.74 × 10−5) and suggestively associated with migraine with aura. The effects of LRP11 and ADGRF5 were further replicated using cerebrospinal fluid protein data. Apart from ADGRF5, there was no evidence of potential adverse consequences when modulating the plasma levels. We also identified another four proteins (PLCG1, ARHGAP25, CHGA, and MANBA) with no potential adverse consequences when modulating the plasma levels, and their genes were not reported by previous genetic studies. Conclusions: We found compelling evidence for two proteins and suggestive evidence for four proteins that could be promising targets for migraine treatment without significant adverse consequences. The corresponding genes were not reported in previous genetic studies. Future studies are needed to confirm the causal role of these proteins and explore the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Background: While numerous allergy-related biomarkers and targeted treatment strategies have been developed and employed, there are still signifcant limitations and challenges in the early diagnosis and targeted treatment for allegic diseases. Our study aims to identify circulating proteins causally associated with allergic disease-related traits through Mendelian randomization (MR)-based analytical framework. Methods: Large-scale cis-MR was employed to estimate the effects of thousands of plasma proteins on five main allergic diseases. Additional analyses including MR Steiger analyzing and Bayesian colocalisation, were performed to test the robustness of the associations; These findings were further validated utilizing meta-analytical methods in the replication analysis. Both proteome- and transcriptome-wide association studies approach was applied, and then, a protein-protein interaction was conducted to examine the interplay between the identified proteins and the targets of existing medications. Results: Eleven plasma proteins were identified with links to atopic asthma (AA), atopic dermatitis (AD), and allergic rhinitis (AR). Subsequently, these proteins were classified into four distinct target groups, with a focus on tier 1 and 2 targets due to their higher potential to become drug targets. MR analysis and extra validation revealed STAT6 and TNFRSF6B to be Tier 1 and IL1RL2 and IL6R to be Tier 2 proteins with the potential for AA treatment. Two Tier 1 proteins, CRAT and TNFRSF6B, and five Tier 2 proteins, ERBB3, IL6R, MMP12, ICAM1, and IL1RL2, were linked to AD, and three Tier 2 proteins, MANF, STAT6, and TNFSF8, to AR. Conclusion: Eleven Tier 1 and 2 protein targets that are promising drug target candidates were identified for AA, AD, and AR, which influence the development of allergic diseases and expose new diagnostic and therapeutic targets. [ABSTRACT FROM AUTHOR]

According to the latest cancer research data, there are a significant number of new cancer cases and a substantial mortality rate each year. Although a substantial number of clinical patients are treated with existing cancer drugs each year, the efficacy is unsatisfactory. The incidence is still high and the effectiveness of most cancer drugs remains unsatisfactory. Therefore, we evaluated the human proteins for their causal relationship to for cancer risk and therefore also their potential as drug targets. We used summary tumors data from the FinnGen and cis protein quantitative trait loci (cis-pQTL) data from a genome-wide association study, and employed Mendelian randomization (MR) to explore the association between potential drug targets and nine tumors, including breast, colorectal, lung, liver, bladder, prostate, kidney, head and neck, pancreatic caners. Furthermore, we conducted MR analysis on external cohort. Moreover, Bidirectional MR, Steiger filtering, and colocalization were employed to validate the main results. The DrugBank database was used to discover potential drugs of tumors. Under the threshold of False discovery rate (FDR) < 0.05, results showed that S100A16 was protective protein and S100A14 was risk protein for human epidermal growth factor receptor 2-positive (HER-positive) breast cancer, phosphodiesterase 5A (PDE5A) was risk protein for colorectal cancer, and melanoma inhibitory activity (MIA) was protective protein for non-small cell lung carcinoma (NSCLC). And there was no reverse causal association between them. Colocalization analysis showed that S100A14 (PP.H4.abf = 0.920) and S100A16 (PP.H4.abf = 0.932) shared causal variation with HER-positive breast cancer, and PDE5A (PP.H4.abf = 0.857) shared causal variation with colorectal cancer (CRC). The MR results of all pQTL of PDE5A and MIA were consistent with main results. In addition, the MR results of MIA and external outcome cohort were consistent with main results. In this study, genetic predictions indicate that circulating S100 calcium binding protein A14 (S100A14) and S100 calcium binding protein A16 (S100A16) are associated with increase and decrease in the risk of HER-positive breast cancer, respectively. Circulating PDE5A is associated with increased risk of CRC, while circulating MIA is associated with decreased risk of NSCLC. These findings suggest that four proteins may serve as biomarkers for cancer prevention and as potential drug targets that could be expected for approval. [ABSTRACT FROM AUTHOR]

Background: The currently available medications for treating membranous nephropathy (MN) still have unsatisfactory efficacy in inhibiting disease recurrence, slowing down its progression, and even halting the development of end-stage renal disease. There is still a need to develop novel drugs targeting MN. Methods: We utilized summary statistics of MN from the Kiryluk Lab and obtained plasma protein data from Zheng et al. We performed a Bidirectional Mendelian randomization analysis, HEIDI test, mediation analysis, Bayesian colocalization, phenotype scanning, drug bank analysis, and protein-protein interaction network. Results: The Mendelian randomization analysis uncovered 8 distinct proteins associated with MN after multiple false discovery rate corrections. Proteins related to an increased risk of MN in plasma include ABO [(Histo-Blood Group Abo System Transferase) (WR OR = 1.12, 95%CI:1.05-1.19, FDR=0.09, PPH4 = 0.79)], VWF [(Von Willebrand Factor) (WR OR = 1.41, 95%CI:1.16-1.72, FDR=0.02, PPH4 = 0.81)] and CD209 [(Cd209 Antigen) (WR OR = 1.19, 95%CI:1.07-1.31, FDR=0.09, PPH4 = 0.78)], and proteins that have a protective effect on MN: HRG [(Histidine-Rich Glycoprotein) (WR OR = 0.84, 95%CI:0.76-0.93, FDR=0.02, PPH4 = 0.80)], CD27 [(Cd27 Antigen) (WR OR = 0.78, 95%CI:0.68-0.90, FDR=0.02, PPH4 = 0.80)], LRPPRC [(Leucine-Rich Ppr Motif-Containing Protein, Mitochondrial) (WR OR = 0.79, 95%CI:0.69-0.91, FDR=0.09, PPH4 = 0.80)], TIMP4 [(Metalloproteinase Inhibitor 4) (WR OR = 0.67, 95%CI:0.53-0.84, FDR=0.09, PPH4 = 0.79)] and MAP2K4 [(Dual Specificity Mitogen-Activated Protein Kinase Kinase 4) (WR OR = 0.82, 95%CI:0.72-0.92, FDR=0.09, PPH4 = 0.80)]. ABO, HRG, and TIMP4 successfully passed the HEIDI test. None of these proteins exhibited a reverse causal relationship. Bayesian colocalization analysis provided evidence that all of them share variants with MN. We identified type 1 diabetes, trunk fat, and asthma as having intermediate effects in these pathways. Conclusions: Our comprehensive analysis indicates a causal effect of ABO, CD27, VWF, HRG, CD209, LRPPRC, MAP2K4, and TIMP4 at the genetically determined circulating levels on the risk of MN. These proteins can potentially be a promising therapeutic target for the treatment of MN. [ABSTRACT FROM AUTHOR]

Psychiatric disorders are emerging as a serious public health hazard, influencing an increasing number of individuals worldwide. However, the effect of modifiable lifestyle factors on psychiatric disorders remains unclear. Genome-wide association studies (GWAS) summary statistics were obtained mainly from Psychiatric Genomics Consortium and UK Biobank, with sample sizes varying between 10,000 and 1,200,000. The two-sample Mendelian randomization (MR) method was applied to investigate the causal associations between 45 lifestyle factors and 13 psychiatric disorders, and screen potential mediator proteins from 2992 candidate plasma proteins. We implemented a four-step framework with step-by-step screening incorporating two-step, univariable, and multivariable MR. We found causal effects of strenuous sports or other exercise on Tourette's syndrome (OR [95%CI]: 0.0047 [5.24E-04–0.042]); lifelong smoking index on attention-deficit hyperactivity disorder (10.53 [6.96–15.93]), anxiety disorders (3.44 [1.95–6.05]), bipolar disorder (BD) (2.25 [1.64–3.09]), BD II (2.89 [1.81–4.62]), and major depressive disorder (MDD) (2.47 [1.90–3.20]); and educational years on anorexia nervosa (AN) (1.47 [1.22–1.76]), and MDD (0.74 [0.66–0.83]). Five proteins were found to have causal associations with psychiatric disorders, namely ADH1B, GHDC, STOM, CD226, and TP63. STOM, a membrane protein deficient in the erythrocytes of hereditary stomatocytosis patients, may mediate the effect of educational attainment on AN. The mechanisms underlying the effects of lifestyle factors on psychiatric disorders require further investigation. These findings could help assess the risk of psychiatric disorders based on lifestyle factors and also support lifestyle interventions as a prevention strategy for mental illness. • Individuals who engaged in strenuous sports or other exercises causally associated with a lower risk of Tourette's syndrome. • Higher lifelong smoking index was causally linked to a higher risk of ADHD, ANX, BD, and MDD. • Longer educational attainment causally associated with a higher risk of AN and lower risk of MDD. • STOM may mediate the effect of educational attainment on anorexia nervosa. [ABSTRACT FROM AUTHOR]

Background Finding effective and safe therapeutic drugs for atrial fibrillation (AF) is an important concern for clinicians. Proteome‐wide Mendelian randomization analysis provides new ideas for finding potential drug targets. Methods and Results Using a proteome‐wide Mendelian randomization approach, we assessed the genetic predictive causality between thousands of proteins and AF risk and found that genetically predicted plasma levels of phosphomevalonate kinase, tumor necrosis factor ligand superfamily member 12, sulfhydryl oxidase 2, interleukin‐6 receptor subunit alpha, and low‐affinity immunoglobulin gamma Fc region receptor II‐b might decrease AF risk, while genetically predicted plasma levels of beta‐mannosidase, collagen alpha‐1(XV) chain, ANXA4 (annexin A4), COF2 (cofilin‐2), and RAB1A (Ras‐related protein Rab‐1A) might increase AF risk (P

Context: Although several risk proteins for hypothyroidism have been reported in recent years, many more plasma proteins have not been tested. Objective: To determine potential mechanisms and novel causal plasma proteins for hypothyroidism using Mendelian randomization (MR). Methods: A large-scale plasma proteome MR analysis was conducted using protein quantitative trait loci (pQTLs) for 2297 plasma proteins. We classified pQTLs into 4 different groups. MR analyses were conducted within the 4 groups simultaneously. Significant proteins were discovered and validated in 2 different cohorts. Colocalization analysis and enrichment analysis were conducted using proteins found with MR. Results: Thirty-one proteins were identified in the discovery cohort. Among them, 13 were validated in the validation cohort. Nine of the 13 proteins are risk factors (ISG15, Fc receptor-like protein 2, tumor necrosis factor ligand superfamily member 14, Rab-2A, FcRL3, thrombomodulin, interferon [IFN]-lambda-1, platelet glycoprotein Ib alpha chain, IL-7RA) for hypothyroidism, whereas others are protective proteins (protein O-glucosyltransferase 1 [POGLUT1], tumor necrosis factor ligand superfamily, 3-hydroxyisobutyryl-CoA hydrolase, transferrin receptor protein 1). Among the significant proteins, POGLUT1 strongly colocalized with expression quantitative trait loci from whole blood (posterior probability of colocalization [PP4]=0.978) and the thyroid (PP4=0.978). Two different trans-pQTLs (rs2111485 PP4=0.998; rs35103715 PP4= 0.998) for IFN-lambda-1 strongly colocalized with hypothyroidism in different chromosomes. Conclusion: Thirteen various proteins were identified and validated to be associated with hypothyroidism using univariable MR. We reinforced and expanded the effect of IFN on hypothyroidism. Several proteins identified in this study could explain part of the association between the coagulation system and hypothyroidism. Our study broadens the causal proteins for hypothyroidism and provides the relationships between plasma proteins and hypothyroidism. The proteins identified in this study can be used as early screening biomarkers for hypothyroidism. [ABSTRACT FROM AUTHOR]

• The genetically predicted levels of 18 circulating plasma proteins were associated with ECG traits. • The impact of plasma proteins on the risk of ECG traits was partly mediated through anthropometric measurements. • New insights of cardiac conduction provide a valuable reference for the development of arrhythmia drugs. Cardiac conduction disorders predispose individuals to arrhythmias, currently but the exact mechanisms of cardiac conduction remain elusive. The study sought to identify the causal association between circulating plasma proteins and electrocardiogram (ECG) traits, offer valuable biological insights and clinical guidance into cardiac conduction. Proteome-wide Mendelian randomization (MR) analysis was firstly conducted to assess causal associations between plasma proteins and five ECG traits, including P wave duration (PWD), QRS duration, PR, QT and RR intervals. Multiple sensitivity analyses were implemented. The reverse MR analysis, colocalization analysis and replication analysis were used to consolidate the reliability of our results. Then, we conducted mediation analysis to explore potential mechanism between plasma proteins and ECG traits. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to clarify the biological functions of target proteins. Finally, phenome-wide MR (Phe-MR) and drug databases were searched. We identified 3 proteins (FAM151A, VEGF165, VEGF121) associated with PWD, 12 proteins (ABHD10, ADK, Cathepsin_S, DUSP13, Ephrin_A3, MAPRE2, OMG, PAM, PMM1, SH3BGRL3, TCP4, SYT11) linked to PR interval, 1 protein (PKC_A) related to QRS duration, and 2 proteins (MXRA7, SVEP1) associated with QT interval. A significant causal effects of ECG traits on them was not found in reverse MR. Colocalization and replication analyses strengthened our findings further. The impacts were partly mediated by anthropometric measures. Enrichment analysis of target proteins mainly enriched for multiple key pathways such as regulation of hydrolase activity and fibronectin binding. Through drug databases searching, 5 identified proteins (VEGFA, ADK, PAM, Cathepsin_S, PKC_A) were considered druggable. We discovered significant causal associations between genetically predicted levels of 18 plasma proteins and ECG traits. These results highlight the importance of circulating plasma proteins in cardiac conduction and open up the possibility of novel arrhythmia drug development. [ABSTRACT FROM AUTHOR]

Harsh work environments can include very cold, hot, dusty, and noisy workplaces, as well as exposure in the workplace with chemicals and other fumes, cigarette smoke, and diesel exhaust. Although working in these harsh environments can have a negative effect on health, there are no effective biomarkers for monitoring health conditions until workers develop disease symptoms. Plasma protein concentrations, which reflect metabolism and immune status, have great potential as biomarkers for various health conditions. Using a Mendelian-randomization (MR) design, this study analyzed the effects of these harsh environments on plasma proteins to identify proteins that can be used as biomarkers of health status. Preliminary analysis using inverse variance weighted (IVW) method with a p-value cutoff of 0.05 showed that workplace environments could affect the concentrations of hundreds of plasma proteins. After filtering for sensitivity via MR-Egger, and Weighted Median MR approaches, 28 plasma proteins altered by workplace environments were identified. Further MR analysis showed that 20 of these plasma proteins, including UNC5D, IGFBP1, SCG3, ST3GAL6, and ST3GAL2 are affected by noisy workplace environments; TFF1, RBM39, ACYP2, STAT3, GRB2, CXCL1, EIF1AD, CSNK1G2, and CRKL that are affected by chemical fumes; ADCYAP1, NRSN1, TMEM132A, and CA10 that are affected by passive smoking; LILRB2, and TENM4 that are affected by diesel exhaust, are associated with the risk of at least one disease. These proteins have the potential to serve as biomarkers to monitor the occupational hazards risk of workers working in corresponding environments. These findings also provide clues to study the biological mechanisms of occupational hazards.