Associations of Circulating Biomarkers with Disease Risks: a Two-Sample Mendelian Randomization Study.

Background: Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Methods: Here we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR Egger. We use the MR-base resource (v0.5.6)1 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016)2-4 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). Results: We report novel causal relationships found by 4 or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in 4 or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. Conclusions: This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.

Causal relationship between C-reactive protein and ischemic stroke caused by atherosclerosis: A Mendelian randomization study.

OBJECTIVES: This study investigates the association between C-reactive protein (CRP) and ischemic stroke caused by large artery atherosclerosis (LAA). METHODS: Five Mendelian Randomization (MR) methodologies were used for two-sample analyses: Inverse Variance Weighting (IVW), MR-Egger regression, Weighted Median (WM), Simple Mode, and Weighted Mode. CRP exposure data were obtained from aggregated summary statistics from a meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry (n = 343,524; UK Biobank). Stroke data were used as the outcome, with specific dataset details for relevant subtypes (cases = 40,585, controls = 406,111). RESULTS: In the CRP GWAS dataset, selected single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) showed genome-wide significance and a causal relationship with CRP, particularly in relation to LAA stroke. IVW indicated a robust causal connection between CRP and LAA stroke (Beta = 0.151, SE = 0.055, P = 0.006). The WM approach supported this relationship (Beta = 0.176, SE = 0.082, P = 0.033). However, MR-Egger regression suggested a potential absence of a causal link (Beta = 0.098, SE = 0.077, P = 0.206), with minimal influence from horizontal pleiotropy (Intercept = 0.0029; P = 0.317). The Simple mode found no significant association (Beta = 0.046, SE = 0.217, P = 0.834), while the Weighted mode revealed a significant causal association (Beta = 0.138, SE = 0.059, P = 0.020) between CRP and LAA stroke. CONCLUSIONS: MR analysis provides evidence for a potential causal relationship between CRP and an increased risk of LAA stroke.

PCSK9 inhibitors and osteoporosis: mendelian randomization and meta-analysis.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors represent an effective strategy for reducing cardiovascular disease risk. Yet, PCSK9's impact on osteoporosis remains unclear. Hence, we employed Mendelian randomization (MR) analysis for examining PCSK9 inhibitor effects on osteoporosis. METHODS: Single nucleotide polymorphisms (SNPs) for 3-hydroxy-3-methylglutaryl cofactor A reductase (HMGCR) and PCSK9 were gathered from available online databases for European pedigrees. Four osteoporosis-related genome-wide association studies (GWAS) data served as the main outcomes, and coronary artery disease (CAD) as a positive control for drug-targeted MR analyses. The results of MR analyses examined by sensitivity analyses were incorporated into a meta-analysis for examining causality between PCSK9 and HMGCR inhibitors and osteoporosis. RESULTS: The meta-analysis involving a total of 1,263,102 subjects, showed that PCSK9 inhibitors can increase osteoporosis risk (P < 0.05, I2, 39%). However, HMGCR inhibitors are not associated with osteoporosis risk. Additionally, a replication of the analysis was conducted with another exposure-related GWAS dataset, which led to similar conclusions. CONCLUSION: PCSK9 inhibitors increase osteoporosis risk. However, HMGCR inhibitors are unremarkably linked to osteoporosis.

COPD, PRISm and lung function reduction affect the brain cortical structure: a Mendelian randomization study.

Chronic obstructive pulmonary disease (COPD) has been associated with alterations in the brain cortical structure. Nonetheless, the causality between COPD and brain cortical structure has not been determined. In the present study, we used Mendelian randomization (MR) analysis to explore the causal effects of genetic predicated COPD on brain cortical structure, namely cortical surface area (SA) and cortical thickness (TH). Genetic association summary data for COPD were obtained from the FinnGen consortium (N = 358,369; Ncase = 20,066). PRISm summary genetic data were retrieved from a case-control GWAS conducted in the UK Biobank (N = 296,282). Lung function indices, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC, were extracted from a meta-analysis of the UK Biobank and SpiroMeta consortium (N = 400,102). Brain cortical structure data were obtained from the ENIGMA consortium (N = 51,665). Inverse-variance weighted (IVW) method was used as the primary analysis, and a series of sensitivity tests were exploited to evaluate the heterogeneity and pleiotropy of our results. The results identified potential causal effects of COPD on several brain cortical specifications, including pars orbitalis, cuneus and inferior parietal gyrus. Furthermore, genetic predicated lung function index (FEV1, FVC and FEV1/FVC), as well as PRISm, also has causal effects on brain cortical structure. According to our results, a total of 15 functional specifications were influenced by lung function index and PRISm. These findings contribute to understanding the causal effects of COPD and lung function to brain cortical structure.

Sodium-glucose cotransporter 1/2 inhibition and risk of neurodegenerative disorders: A Mendelian randomization study.

INTRODUCTION: This study aims to evaluate the effects of sodium-glucose cotransporter 1 inhibitors (SGLT1i) and sodium-glucose cotransporter 2 inhibitors (SGLT2i) on neurodegenerative disorders and to investigate the role of hemoglobin A1c (HbA1c) levels. METHODS: Utilizing drug target Mendelian randomization, we employed single nucleotide polymorphisms (SNPs) proximal to the SLC5A1 and SLC5A2 genes to analyze the influence of SGLT1i and SGLT2i on Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), frontotemporal dementia (FTD), Lewy body dementia (LBD), and amyotrophic lateral sclerosis (ALS), with type 2 diabetes (T2D) as a positive control. An additional analysis examined the impact of HbA1c levels on the same disorders. RESULTS: SGLT1i exhibited a significant association with decreased risk for ALS and MS. Conversely, SGLT2i were linked to an increased risk of AD, PD, and MS. Elevated HbA1c levels, independent of SGLT1 and SGLT2 effects, were associated with an increased risk of PD. Sensitivity analyses supported the robustness of these findings. CONCLUSION: Our study suggests that SGLT1i may confer protection against ALS and MS, whereas SGLT2i could elevate the risk of AD, PD, and MS. Additionally, elevated HbA1c levels emerged as a risk factor for PD. These findings underscore the importance of personalized approaches in the utilization of SGLT inhibitors, considering their varying impacts on the risks of neurodegenerative diseases.

Transcriptome-wide association study and Mendelian randomization in pancreatic cancer identifies susceptibility genes and causal relationships with type 2 diabetes and venous thromboembolism.

BACKGROUND: Two important questions regarding the genetics of pancreatic adenocarcinoma (PDAC) are 1. Which germline genetic variants influence the incidence of this cancer; and 2. Whether PDAC causally predisposes to associated non-malignant phenotypes, such as type 2 diabetes (T2D) and venous thromboembolism (VTE). METHODS: In this study of 8803 patients with PDAC and 67,523 controls, we first performed a large-scale transcriptome-wide association study to investigate the association between genetically determined gene expression in normal pancreas tissue and PDAC risk. Secondly, we used Mendelian Randomization (MR) to analyse the causal relationships among PDAC, T2D (74,124 cases and 824,006 controls) and VTE (30,234 cases and 172,122 controls). FINDINGS: Sixteen genes showed an association with PDAC risk (FDR <0.10), including six genes not yet reported for PDAC risk (PPIP5K2, TFR2, HNF4G, LRRC10B, PRC1 and FBXL20) and ten previously reported genes (INHBA, SMC2, ABO, PDX1, MTMR6, ACOT2, PGAP3, STARD3, GSDMB, ADAM33). MR provided support for a causal effect of PDAC on T2D using genetic instruments in the HNF4G and PDX1 loci, and unidirectional causality of VTE on PDAC involving the ABO locus (OR 2.12, P < 1e-7). No evidence of a causal effect of PDAC on VTE was found. INTERPRETATION: These analyses identified candidate susceptibility genes and disease relationships for PDAC that warrant further investigation. HNF4G and PDX1 may induce PDAC-associated diabetes, whereas ABO may induce the causative effect of VTE on PDAC. FUNDING: National Institutes of Health (USA).

Causal association between telomere length and female reproductive endocrine diseases: a univariable and multivariable Mendelian randomization analysis.

BACKGROUND: The relationship between leukocyte telomere length (LTL) and female reproductive endocrine diseases has gained significant attention and research interest in recent years. However, there is still limited understanding of the exact impacts of LTL on these diseases. Therefore, the primary objective of this study was to investigate the genetic causal association between LTL and female reproductive endocrine diseases by employing Mendelian randomization (MR) analysis. METHODS: Instruments for assessing genetic variation associated with exposure and outcome were derived from summary data of published genome-wide association studies (GWAS). Inverse-variance weighted (IVW) was utilized as the main analysis method to investigate the causal relationship between LTL and female reproductive endocrine diseases. The exposure data were obtained from the UK Biobanks GWAS dataset, comprising 472,174 participants of European ancestry. The outcome data were acquired from the FinnGen consortium, including abnormal uterine bleeding (menorrhagia and oligomenorrhea), endometriosis (ovarian endometrioma and adenomyosis), infertility, polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI) and premenstrual syndrome (PMS). Furthermore, to account for potential confounding factors such as smoking, alcohol consumption, insomnia, body mass index (BMI) and a history of pelvic inflammatory disease (PID), multivariable MR (MVMR) analysis was also conducted. Lastly, a series of pleiotropy tests and sensitivity analyses were performed to ensure the reliability and robustness of our findings. P < 0.0063 was considered to indicate statistically significant causality following Bonferroni correction. RESULTS: Our univariable MR analysis demonstrated that longer LTL was causally associated with an increased risk of menorrhagia (IVW: odds ratio [OR]: 1.1803; 95% confidence interval [CI]: 1.0880-1.2804; P = 0.0001) and ovarian endometrioma (IVW: OR: 1.2946; 95%CI: 1.0970-1.5278; P = 0.0022) at the Bonferroni significance level. However, no significant correlation was observed between LTL and oligomenorrhea (IVW: OR: 1.0124; 95%CI: 0.7350-1.3946; P = 0.9398), adenomyosis (IVW: OR: 1.1978; 95%CI: 0.9983-1.4372; P = 0.0522), infertility (IVW: OR: 1.0735; 95%CI: 0.9671-1.1915; P = 0.1828), PCOS (IVW: OR: 1.0633; 95%CI: 0.7919-1.4278; P = 0.6829), POI (IVW: OR: 0.8971; 95%CI: 0.5644-1.4257; P = 0.6459) or PMS (IVW: OR: 0.7749; 95%CI: 0.4137-1.4513; P = 0.4256). Reverse MR analysis indicated that female reproductive endocrine diseases have no causal effect on LTL. MVMR analysis suggested that the causal effect of LTL on menorrhagia and ovarian endometrioma remained significant after accounting for smoking, alcohol consumption, insomnia, BMI and a history of PID. Pleiotropic and sensitivity analyses also showed robustness of our results. CONCLUSION: The results of our bidirectional two-sample MR analysis revealed that genetically predicted longer LTL significantly increased the risk of menorrhagia and ovarian endometrioma, which is consistent with the findings from MVMR studies. However, we did not notice any significant effects of LTL on oligomenorrhea, adenomyosis, infertility, PCOS, POI or PMS. Additionally, reproductive endocrine disorders were found to have no impact on LTL. To enhance our understanding of the effect and underlying mechanism of LTL on female reproductive endocrine diseases, further large-scale studies are warranted in the future.

Associations of modifiable factors with risk of irritable bowel syndrome.

Background: Modifiable factors were found to be associated with the risk of irritable bowel syndrome (IBS) in observational studies, but whether these associations are causal is uncertain. We conducted a Mendelian randomization (MR) study to systematically explore the causal associations of modifiable factors with IBS. Methods: Summary-level statistical data for IBS was obtained from a genome-wide association study (GWAS) meta-analysis of UK Biobank (40,548 cases and 293,220 controls) and the international collaborative Bellygenes initiative (12,852 cases and 139,981 controls). Genetic instruments associated with the exposures at the genome-wide significance (p < 5 × 10-8) level were selected from previous GWASs. Mendelian randomization was performed using inverse-variance weighted (IVW) method, supplemented with several sensitivity analyses to evaluate potentially causal relationships between identified contributing factors and IBS. Furthermore, we applied another database from FinnGen (8,116 IBS cases and 276,683 controls) to testify the reliability of the significant associations. Results: Seven convincing modifiable factors were significantly associated with IBS after correction for multiple testing. Genetically predicted smoking initiation (OR = 1.12, 95% CI = 1.06-1.18, p = 1.03 × 10-4), alcohol consumption (OR = 0.47, 95% CI = 0.34-0.64, p = 3.49 × 10-6), sedentary behavior (OR = 1.17, 95% CI = 1.07-1.28, p = 4.02 × 10-4), chronotype (OR = 0.92, 95% CI = 0.88-0.96, p = 4.42 × 10-4), insomnia (OR = 1.19, 95% CI = 1.15-1.24, p = 7.59 × 10-19), education (OR = 0.80, 95% CI = 0.74-0.88, p = 5.34 × 10-7), and visceral adiposity (OR = 1.15, 95% CI = 1.06-1.24, p = 7.96 × 10-4). We additionally identified several suggestive factors, including serum magnesium, serum phosphorus, physical activity, lifetime smoking, intelligence, lean body mass, and body mass index (BMI). After pooling the effect estimates from FinnGen, the associations remained significant except for chronotype. Conclusion: This MR analysis verified several modifiable risk factors for IBS, thus prevention strategies for IBS should be considered from multiple perspectives on these risk factors.

Causality of immune cells on primary sclerosing cholangitis: a bidirectional two-sample Mendelian randomization study.

Background: Observational studies have indicated that immune dysregulation in primary sclerosing cholangitis (PSC) primarily involves intestinal-derived immune cells. However, the causal relationship between peripheral blood immune cells and PSC remains insufficiently understood. Methods: A bidirectional two-sample Mendelian randomization (MR) analysis was implemented to determine the causal effect between PBC and 731 immune cells. All datasets were extracted from a publicly available genetic database. The standard inverse variance weighted (IVW) method was selected as the main method for the causality analysis. Cochran's Q statistics and MR-Egger intercept were performed to evaluate heterogeneity and pleiotropy. Results: In forward MR analysis, the expression ratios of CD11c on CD62L+ myeloid DC (OR = 1.136, 95% CI = 1.032-1.250, p = 0.009) and CD62L-myeloid DC AC (OR = 1.267, 95% CI = 1.086-1.477, p = 0.003) were correlated with a higher risk of PSC. Each one standard deviation increase of CD28 on resting regulatory T cells (Treg) (OR = 0.724, 95% CI = 0.630-0.833, p < 0.001) and CD3 on secreting Treg (OR = 0.893, 95% CI = 0.823-0.969, p = 0.007) negatively associated with the risk of PSC. In reverse MR analysis, PSC was identified with a genetic causal effect on EM CD8+ T cell AC, CD8+ T cell AC, CD28- CD127- CD25++ CD8+ T cell AC, CD28- CD25++ CD8+ T cell AC, CD28- CD8+ T cell/CD8+ T cell, CD28- CD8+ T cell AC, and CD45 RA- CD28- CD8+ T cell AC. Conclusion: Our study indicated the evidence of causal effects between PSC and immune cells, which may provide a potential foundation for future diagnosis and treatment of PSC.

The levels of circulating cytokines and risk of neuromyelitis optica spectrum disorder: a Mendelian randomization study.

Background: Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory autoimmune disease affecting the central nervous system (CNS). NMOSD pathogenesis involves systemic inflammation. However, a causal relationship between circulating cytokine levels and NMOSD remains unclear. Methods: Mendelian randomization (MR) approaches were used to investigate the potential association between genetically determined circulating 19 inflammatory cytokines and 12 chemokines levels and the risk of developing NMOSD. Results: After Bonferroni correction, the risk of aquaporin 4-antibody (AQP4-ab)-positive NMOSD was suggested to be causally associated with the circulating levels of three cytokines, including interleukin (IL)-4 [odds ratio (OR): 11.01, 95% confidence interval (CI): 1.16-104.56, P = 0.037], IL-24 (OR: 161.37; 95% CI: 2.46-10569.21, P = 0.017), and C-C motif chemokine 19 (CCL19) (OR: 6.87, 95% CI: 1.78-26.93, P = 0.006). Conclusion: These findings suggest that a genetic predisposition to higher levels of IL-4, IL-24, and CCL19 may exert a causal effect on the risk of AQP4-ab-positive NMOSD. Further studies are warranted to clarify how these cytokines affect the development of AQP4-ab-positive NMOSD.

Causal Involvement of Immune Cells in Chronic Obstructive Pulmonary Disease: A Mendelian Randomization Study.

Background: The immune cells play a substantial role in the development and progression of chronic obstructive pulmonary disease (COPD). We aim to investigate the causal involvement of immune cells in COPD via a Mendelian randomization (MR) analysis. Methods: Published genome-wide association studies (GWAS) statistics on immune cells were analyzed, with genetic variants identified as instrumental variables (IVs). Inverse-variance weighting (IVW), weighted median, and MR-Egger regression methods were employed, along with simple mode and weighted mode adopted in the two-sample MR analysis. Sensitivity analysis was conducted to examine the heterogeneity, horizontal pleiotropy, and stability of the causal relationship. Results: IVW results suggested that CCR2 on CD62L+ plasmacytoid dendritic cells (DC), CCR2 on plasmacytoid DC, CD11b on CD66b++ myeloid cells, CD19 on CD20- CD38- CD24+ memory B cell subset, CD25 on transitional B cells, and CD25++CD8br %CD8br T cells were risk factors for the development of COPD. Besides, CD127 on effector memory-like cytotoxic T lymphocytes lacking expression of co-stimulatory molecule 28 (CD28-EM CTLs) and HLA DR+ NK ACs expressing human leukocyte antigen DR molecules while being natural killer cells (%NK ACs) were protective factors for COPD. Conclusion: This study unveiled a causal relationship between immune cell phenotype and COPD. These findings offer new insights for the prevention and treatment of COPD using COPD-associated immune cells.

Causal association between phenylalanine and Parkinson's disease: a two-sample bidirectional mendelian randomization study.

Background: Research findings indicate a putative indirect or latent association between phenylalanine (Phe) and Parkinson's disease (PD). In this study, we aimed to analyze the causal relationship between Phe and PD by two sample Mendelian randomization (MR) analysis. Methods: In this study, the PD-related dataset and Phe-related dataset were downloaded from Integrative Epidemiology U1nit (IEU) Open Genome-Wide Association Study (GWAS) database. Four algorithms (MR Egger, maximum likelihood, inverse variance weighting (IVW) and unweighted regression) were used to perform MR analysis. The sensitivity analysis (heterogeneity test, horizontal pleiotropy test and Leave-One-Out (LOO) analysis) was used to assess the reliability of MR analyses. Results: In the forward MR analysis, Phe was a safety factor for PD (p-value < 0.05 and odds ratios (OR) < 1). The results of reverse MR analysis showed that there was no causal relationship between PD and Phe (p-value > 0.05). In addition, sensitivity analysis showed that MR analysis was reliable. Conclusion: The results of this study revealed that Phe was a safety factor for PD, meaning that Phe reduced the risk of PD.

Causality of genetically determined metabolites on susceptibility to prevalent urological cancers: a two-sample Mendelian randomization study and meta-analysis.

Background: Prevalent urological cancers, including kidney, prostate, bladder, and testicular cancers, contribute significantly to global cancer incidence and mortality. Metabolomics, focusing on small-molecule intermediates, has emerged as a tool to understand cancer etiology. Given the knowledge gap in this field, we employ a two-sample Mendelian randomization (MR) analysis to investigate the causal relationships between genetically determined metabolites (GDMs) and the susceptibility to four common urological cancers. Methods: The study employs genome-wide association studies (GWAS) data from European populations, featuring the most extensive case count available for both blood metabolites and four prevalent urological cancers. Preliminary and secondary MR analyses were separately conducted, employing inverse variance weighted (IVW) as the primary method. Multiple statistical analyses, including the MR-Steiger test, Cochran's Q test, leave-one-out analysis, MR-Egger intercept analysis, and MR-PRESSO analysis, were executed to ensure robustness. Additionally, a meta-analysis was carried out to consolidate findings. The weighted median (WM) method was utilized for a relatively lenient correction (PWM < 0.05). Results: After rigorous genetic variation filtering, 645 out of 1,400 metabolites were included in both preliminary and secondary MR analyses. Preliminary MR analysis identified 96 potential causal associations between 94 distinct metabolites and four urological cancers. Secondary analysis based on Finnish outcome data revealed 93 potential causal associations. Cross-database meta-analysis identified 68 blood metabolites associated with four urological cancers. Notably, 31 metabolites remained significant after using WM for correction, with additional 37 suggestive causal relationships. Reverse MR analysis revealed a significant causal association between genetically predicted prostate cancer and elevated 4-hydroxychlorothalonil levels (IVW, combined OR: 1.039, 95% CI 1.014-1.064, p = 0.002; WM, combined OR: 1.052, 95% CI 1.010-1.095, p = 0.014). Conclusion: This comprehensive MR study provides insights into the causal relationships between blood metabolites and urological cancers, revealing potential biomarkers and therapeutic targets, thereby addressing gaps in understanding and laying the foundation for targeted interventions in urological cancer research and treatment.

Association between serum uric acid and colorectal cancer risk in European population: a two-sample Mendelian randomization study.

Objectives: This study aimed to explore the potential causal associations between serum uric acid (SUA) and the risk of colorectal cancer, colon cancer and rectal cancer. Methods: Twenty-six SUA-related single nucleotide polymorphisms which were identified by a large meta-analysis of genome-wide association studies (GWASs) were used as instrumental variables in the two-sample Mendelian randomization (MR) study. Meta-analyses were used to synthesize the results of multiple GWASs which were extracted from the MRC Integrative Epidemiology Unit GWAS database for each type of cancer. The inverse variance weighted (IVW) method was used as the primary MR method to analyze the association between SUA and colorectal cancer risk. Several sensitivity analyses were performed to test the robustness of results. Results: The IVW method showed that there were no causal relationships between SUA and the risk of colorectal cancer [odds ratio (OR): 1.0015; 95% confidence interval (CI): 0.9975-1.0056] and colon cancer (OR: 1.0015; 95% CI: 0.9974-1.0055). The SUA levels were negative correlated with rectal cancer risk (OR: 0.9984; 95% CI: 0.9971-0.9998). The similar results were observed in both males (OR: 0.9987; 95% CI: 0.9975-0.9998) and females (OR: 0.9985; 95% CI: 0.9971-0.9999). The sensitivity analyses suggested no evidence of heterogeneity or horizontal pleiotropy. The leave-one-out analyses showed that one SNP (rs1471633) significantly drove the causal effect of SUA on rectal cancer risk. The MR-Egger regression and weighted median both showed that there were no causal relationships between SUA and the risk of colorectal cancer and its subtypes. Conclusion: Overall, there was no linear causal association between SUA and the risk of colorectal cancer. However, further research is needed to investigate the role of higher SUA levels such as hyperuricemia or gout in the occurrence of colorectal cancer.

Role of metabolites in mediating the effect of triacylglycerol on aplastic anemia.

BACKGROUND: Observational studies have found a link between lipid metabolism disorders and aplastic anemia (AA). However, due to confounding variables and reverse causation, it is difficult to conclude such a causal link. The precise mechanism and potential implications of lipid metabolism disorder in AA remain unclear, necessitating further studies in this area. METHOD: This study aimed to examine the causal relationship between 38 different subtypes of triacylglycerols and AA using two-sample Mendelian randomization (MR). Additionally, two-step MR analyses were conducted to investigate the mediating effects of vitamin A to oleoyl-linoleoyl-glycerol (18:1-18:2) ratio. RESULTS: MR analysis showed that triacylglycerol (53:3) levels were positively associated with the risk of AA [inverse variance weighting (IVW): odds ratio (OR) = 1.131,95% confidence interval (CI):1.029-1.243, P = 0.011; Bayesian weighted MR (BWMR): OR = 1.137,95% CI:1.031-1.254, P = 0.010]. Triacylglycerol (53:3) level showed no inverse causality with AA (IVW:P = 0.834; BWMR:P = 0.349). Mediation analyses showed that increasing the vitamin A to oleoyl-linoleoyl-glycerol (18:1-18:2) ratio can decrease the risk of AA. CONCLUSION: This study revealed the association between vitamin A to oleoyl-linoleoyl-glycerol (18:1-18:2) ratio, triacylglycerol (53:3) levels and AA, and indicated that lowering triacylglycerol (53:3) levels can reduce the risk of AA.

Integrating plasma proteome with genome reveals novel protein biomarkers in colorectal cancer.

BACKGROUND: Biomarkers for colorectal cancer (CRC) can complement population screening methods, but so far, few plasma proteins have been identified as biomarkers for CRC. This study aims to identify potential protein biomarkers and therapeutic targets for CRC within the proteome range. METHODS: We extracted summary-level data of circulating protein from 7 published genome-wide association studies (GWASs) of plasma proteome for Mendelian randomization (MR), summary-data-based MR (SMR), and co-localization analyses to screen and validate proteins with causal effects in CRC. In addition, we further conducted druggability evaluation, prognosis analysis at the transcriptional level, and enrichment expression at the single-cell level, highlighting the important role of these plasma protein biomarkers in CRC. RESULTS: We identified 117 plasma protein biomarkers associated with CRC risk, with 9 proteins showing stronger genetic correlations in Bayesian co-localization (PP.H4 > 0.70). Further, we found 26 protein-coding genes already used in targeted drug development and may potentially become therapeutic targets for CRC. In prognosis analysis, the encoding genes of plasma proteins exhibited consistent effects with MR analysis and can serve as prognostic biomarkers for CRC. Additionally, we also found that the differentially expressed proteins are mainly expressed in fibroblasts, endothelial cells, macrophages, and T cells. CONCLUSION: Our study has identified plasma protein biomarkers associated with CRC risk, which may complement population screening methods for CRC and achieve more precise treatment for patients.

Causal relationship between multiple sclerosis and primary Sjögren's syndrome: a two-sample mendelian randomization study.

This study aims to investigate the causal relationship between primary Sjögren's syndrome (SS) and multiple sclerosis (MS) using a two-sample Mendelian randomization (MR) analysis to provide insights into their common mechanisms and implications for therapeutic strategies. We utilized data from Genome-Wide Association Studies (GWAS) for primary SS (1,290 cases and 213,145 controls) and MS (4,888 cases and 10,395 controls), restricted to European ancestry. Instrumental variables (IVs) were selected based on genetic variants associated with primary SS. The primary MR method was Inverse Variance Weighted (IVW), supplemented by MR Egger, Weighted Median, Simple Mode, and Weighted Mode algorithms to assess the bidirectional causal relationships between MS and primary SS. Sensitivity analyses, including MR-PRESSO and leave-one-out analysis, were conducted to ensure the robustness of our findings. After excluding SNPs with pleiotropic effects, 42 and 5 SNPs were identified as robust IVs for primary SS and MS, respectively. Our analysis revealed a significant protective effect of MS on primary SS, with IVW showing an OR of 0.896 (95% CI: 0.841-0.954, P = 0.001). No significant heterogeneity or horizontal pleiotropy was detected, supporting the reliability of the results. Our findings suggest a potential protective effect of MS against primary SS, indicating a negative causal association between these two autoimmune diseases. This adds valuable genetic evidence to the understanding of the complex interplay between primary SS and MS, offering new avenues for research and therapeutic interventions.

Innovative approaches for vaccine trials as a key component of pandemic preparedness - a white paper.

BACKGROUND: WHO postulates the application of adaptive design features in the global clinical trial ecosystem. However, the adaptive platform trial (APT) methodology has not been widely adopted in clinical research on vaccines. METHODS: The VACCELERATE Consortium organized a two-day workshop to discuss the applicability of APT methodology in vaccine trials under non-pandemic as well as pandemic conditions. Core aspects of the discussions are summarized in this article. RESULTS: An "ever-warm" APT appears ideally suited to improve efficiency and speed of vaccine research. Continuous learning based on accumulating APT trial data allows for pre-planned adaptations during its course. Given the relative design complexity, alignment of all stakeholders at all stages of an APT is central. Vaccine trial modelling is crucial, both before and in a pandemic emergency. Various inferential paradigms are possible (frequentist, likelihood, or Bayesian). The focus in the interpandemic interval may be on research gaps left by industry trials. For activation in emergency, template Disease X protocols of syndromal design for pathogens yet unknown need to be stockpiled and updated regularly. Governance of a vaccine APT should be fully integrated into supranational pandemic response mechanisms. DISCUSSION: A broad range of adaptive features can be applied in platform trials on vaccines. Faster knowledge generation comes with increased complexity of trial design. Design complexity should not preclude simple execution at trial sites. Continuously generated evidence represents a return on investment that will garner societal support for sustainable funding. Adaptive design features will naturally find their way into platform trials on vaccines.

Association between glioma and neurodegenerative diseases risk: a two-sample bi-directional Mendelian randomization analysis.

Background: Earlier observational studies have demonstrated a correlation between glioma and the risk of neurodegenerative diseases (NDs), but the causality and direction of their associations remain unclear. The objective of this study was to ascertain the causal link between glioma and NDs using Mendelian randomization (MR) methodology. Methods: Genome-wide association study (GWAS) data were used in a two-sample bi-directional MR analysis. From the largest meta-analysis GWAS, encompassing 18,169 controls and 12,488 cases, summary statistics data on gliomas was extracted. Summarized statistics for NDs, including Alzheimer's disease (AD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) were obtained from the GWAS of European ancestry. Inverse variance weighted (IVW) method was elected as the core MR approach with weighted median (WM) method and MR-Egger method as complementary methods. In addition, sensitivity analyses were performed. A Bonferroni correction was used to correct the results. Results: Genetically predicted glioma had been related to decreased risk of AD. Specifically, for all glioma (IVW: OR = 0.93, 95% CI = 0.90-0.96, p = 4.88 × 10-6) and glioblastoma (GBM) (IVW: OR = 0.93, 95% CI = 0.91-0.95, p = 5.11 × 10-9). We also found that genetically predicted all glioma has a suggestive causative association with MS (IVW: OR = 0.90, 95% CI = 0.81-1.00, p = 0.045). There was no evidence of causal association between glioma and ALS or PD. According to the results of reverse MR analysis, no discernible causal connection of NDs was found on glioma. Sensitivity analyses validated the robustness of the above associations. Conclusion: We report evidence in support of potential causal associations of different glioma subtypes with AD and MS. More studies are required to uncover the underlying mechanisms of these findings.

A thorough investigation into the correlation between migraines and the gut microbiome: an in-depth analysis using Mendelian randomization studies.

Objective: A growing body of evidence underscores a significant association between neurological disorders, particularly migraines, and the gut microbiota. However, a research gap persists in understanding the cause-and-effect dynamics between these elements. Therefore, we employed robust methodologies aimed at thoroughly exploring the causal relationship between the gut microbiome and migraines. Methods: Employing bidirectional Two Sample Mendelian Randomization (TSMR) analysis, we investigated the causal association between the composition of the gut microbiota and migraines. Data summarizing the relationship between gut microbiota and migraines were extracted from one or more genome-wide association studies. The TSMR analysis employed five methods to assess the correlation between the gut microbiota and migraines, with the inverse variance-weighted method serving as the primary approach for analyzing causal links. Sensitivity analyses were applied to address horizontal pleiotropy and heterogeneity. Simultaneously, a meta-analysis was performed to strengthen the robustness of the findings. Additionally, a reverse TSMR was carried out to explore potential occurrences of reverse causal relationships. Results: The ongoing TSMR analysis identified a collection of 14 bacterial taxa connected to migraines. Among these, 8 taxa exhibited a protective effect, while 5 taxa had a detrimental impact, and 1 taxon maintained a neutral relationship. The reverse Mendelian randomization analysis highlighted stable outcomes for only one bacterial taxonomic group. Conclusion: The study confirms a causal relationship between the gut microbiota and migraines, offering a new perspective for migraine research. Strategically targeting specific bacterial taxa with dysregulation may be effective in both preventing and treating migraines, thus opening new avenues for therapeutic strategies.