Multiple Random Effects Research Articles

Causal associations and shared genetic etiology of neurodegenerative diseases with epigenetic aging and human longevity.

The causative mechanisms underlying the genetic relationships of neurodegenerative diseases with epigenetic aging and human longevity remain obscure. We aimed to detect causal associations and shared genetic etiology of neurodegenerative diseases with epigenetic aging and human longevity. We obtained large-scale genome-wide association study summary statistics data for four measures of epigenetic age (GrimAge, PhenoAge, IEAA, and HannumAge) (N = 34,710), multivariate longevity (healthspan, lifespan, and exceptional longevity) (N = 1,349,462), and for multiple neurodegenerative diseases (N = 6618-482,730), including Lewy body dementia, Alzheimer's disease (AD), Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis. Main analyses were conducted using multiplicative random effects inverse-variance weighted Mendelian randomization (MR), and conditional/conjunctional false discovery rate (cond/conjFDR) approach. Shared genomic loci were functionally characterized to gain biological understanding. Evidence showed that AD patients had 0.309 year less in exceptional longevity (IVW beta = -0.309, 95% CI: -0.38 to -0.24, p = 1.51E-19). We also observed suggestively significant causal evidence between AD and GrimAge age acceleration (IVW beta = -0.10, 95% CI: -0.188 to -0.013, p = 0.02). Following the discovery of polygenic overlap, we identified rs78143120 as shared genomic locus between AD and GrimAge age acceleration, and rs12691088 between AD and exceptional longevity. Among these loci, rs78143120 was novel for AD. In conclusion, we observed that only AD had causal effects on epigenetic aging and human longevity, while other neurodegenerative diseases did not. The genetic overlap between them, with mixed effect directions, suggested complex shared genetic etiology and molecular mechanisms.

Variability in Causal Effects and Noncompliance in a Multisite Trial: A Bivariate Hierarchical Generalized Random Coefficients Model for a Binary Outcome.

Within each of 170 physicians, patients were randomized to access e-assist, an online program that aimed to increase colorectal cancer screening (CRCS), or control. Compliance was partial: of the experimental patients accessed e-assist while no controls were provided the access. Of interest are the average causal effect of assignment to treatment and the complier average causal effect as well as the variation of these causal effects across physicians. Each physician generates probabilities of screening for experimental compliers (experimental patients who accessed e-assist), control compliers (controls who would have accessed e-assist had they been assigned to e-assist), and never takers (patients who would have avoided e-assist no matter what). Estimating physician-specific probabilities jointly over physicians poses novel challenges. We address these challenges by maximum likelihood, factoring a "complete-data likelihood" uniquely into the conditional distribution of screening and partially observed compliance given random effects and the distribution of random effects. We marginalize this likelihood using adaptive Gauss-Hermite quadrature. The approach is doubly iterative in that the conditional distribution defies analytic evaluation. Because the small sample size per physician constrains estimability of multiple random effects, we reduce their dimensionality using a shared random effects model having a factor analytic structure. We assess estimators and recommend sample sizes to produce reasonably accurate and precise estimates by simulation, and analyze data from a trial of a CRCS intervention.

Accurate PM2.5 urban air pollution forecasting using multivariate ensemble learning Accounting for evolving target distributions

Over the past decades, air pollution has caused severe environmental and public health problems. According to the World Health Organization (WHO), fine particulate matter (PM2.5), a key component reflecting air quality, is the fourth leading cause of death worldwide after cardiovascular disease, smoking, and diet. Various research efforts have aimed to develop PM2.5 forecasting models that can be integrated into a solution to mitigate the adverse effects of air pollution. However, PM2.5 forecasting is challenging because air pollution data are non-stationary and influenced by multiple random effects. This paper proposes an effective multivariate multi-step ensemble machine learning model for predicting continuous 24-h PM2.5 concentrations, considering meteorological conditions, the rolling mean of PM2.5 time series, and temporal features. PM2.5 is strongly correlated with space and time. Therefore, forecasting results from one location are insufficient to represent the level of air pollution for an entire city. In this study, we established six real-time air quality monitoring sites in different regions, including traffic, residential, and industrial areas in Ho Chi Minh City (HCMC), and generated forecasting results for each station. Various statistical methods are incorporated to evaluate the performance of the model. The experimental results confirm that the model performs well, substantially improving its forecasting accuracy compared to existing PM2.5 forecasting models developed for HCMC. In addition, we analyze to determine the contribution of different feature groups to model performance. The model can serve as a reference for citizens scheduling local travel and for healthcare providers to provide early warnings.

Does metformin really reduce prostate cancer risk: an up-to-date comprehensive genome-wide analysis

BackgroundThe relationship between metformin use and prostate cancer (PCa) risk has yet to be clear despite more than a decade of debate on this topic. Hence, we aimed to investigate the causal role of metformin in reducing PCa risk through an up-to-date comprehensive genome-wide analysis.MethodsWe employed validated instrument variables of metformin use derived from a prior high-quality study, including five potential targets (AMPK, GCG, GDF15, MCI and MG3). Mendelian randomization (MR) analysis was performed to harmonize genetically predicted metformin use and PCa phenotypes. PCa phenotypes were from two large genome-wide association studies (GWAS), the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) and the FinnGen cohort. Seven methods were applied to generate MR results: the inverse variance weighted (IVW), IVW with multiplicative random effects, MR-Egger, MR-Egger (bootstrap), weighted median, simple mode and weighted mode. Strict sensitivity analysis was conducted to satisfy core assumptions of MR design.ResultsWe enrolled 32 significant single nucleotide polymorphisms (SNPs) that involved with metformin use. Nearly all targets yielded insignificant primary results (IVW with multiplicative random effects), except that AMPK target posed a positive effect on PCa risk from FinnGen cohort [odds ratio (OR): 6.09, 95% confidence interval (CI): 1.10-33.53, P value: 0.038]. The general effect of metformin use, comprising all 5 targets, also yielded negative results (random-effect meta-analysis with OR: 1.09, 95% CI: 0.76–1.58, P value: 0.637 for PRACTICAL; OR: 2.55, 95% CI: 0.58–11.16, P value: 0.215 for FinnGen). None of the sensitivity analyses provided support for a causal association between metformin use and PCa risk.ConclusionThis up-to-date study did not support the protective role of metformin in reducing PCa risk, considering each target, overall effect, and sensitivity analysis. It is imperative to reflect on the presumed “almighty medicine” and ongoing phase III trials are anticipated to assess the anti-neoplasm effect of metformin.

Association of circulating vitamin levels with thyroid diseases: a Mendelian randomization study.

Previous observational studies have shown conflicting results of vitamins supplementation for thyroid diseases. The causal relationships between vitamins and thyroid diseases are unclear. Therefore, we conducted a two-sample bidirectional Mendelian randomization (MR) study to explore association of circulating vitamin levels with thyroid diseases. We performed a bidirectional MR analysis using genome-wide association study (GWAS) data. Genetic tool variables for circulating vitamin levels include vitamins A, B9, B12, C, D, and E, Genetic tool variables of thyroid diseases include autoimmune hyperthyroidism, autoimmune hypothyroidism, thyroid nodules (TNs), and Thyroid cancer (TC). Inverse-variance weighted multiplicative random effects (IVW-RE) was mainly used for MR Analysis, weighted median (WM) and MR Egger were used as supplementary methods to evaluate the relationships between circulating vitamin levels and thyroid diseases. Sensitivity and pluripotency were evaluated by Cochran's Q test, MR-PRESSO, Radial MR, MR-Egger regression and leave-one-out analysis. Positive MR evidence suggested that circulating vitamin C level is a protective factor in autoimmune hypothyroidism (ORIVW-RE=0.69, 95%CI: 0.58-0.83, p = 1.05E-04). Reverse MR Evidence showed that genetic susceptibility to autoimmune hyperthyroidism is associated with reduced level of circulating vitamin A(ORIVW-RE = 0.97, 95% CI: 0.95-1.00, p = 4.38E-02), genetic susceptibility of TNs was associated with an increased level of circulating vitamin D (ORIVW-RE = 1.02, 95% CI: 1.00-1.03, p = 6.86E-03). No causal and reverse causal relationship was detected between other circulating vitamin levels and thyroid diseases. Our findings provide genetic evidence supporting a bi-directional causal relationship between circulating vitamin levels and thyroid diseases. These findings provide information for the clinical application of vitamins prevention and treatment of thyroid diseases.

REVEALS—a longitudinal cohort study of multifaceted respiratory assessment in ALS

Objective To systematically assess decline in respiratory measures in amyotrophic lateral sclerosis (ALS) and to examine the impact of sex, disease onset type and baseline morbidity on progression. Methods The REVEALS study (Registry of Endpoints and Validated Experiences in ALS) was conducted between April 2018 and February 2021 in six European ALS centers. Slow and forced vital capacity (S/FVC), sniff nasal inspiratory pressure (SNIP), peak cough flow, amyotrophic lateral sclerosis functional rating scale-revised (ALSFRS-R), and respiratory morbidity were collected. Data were analyzed using a Bayesian multiple outcomes random effects model. Results Two hundred and eighty participants had a median of three assessments (IQR 2.0, 5.0) over a median of 8 months (IQR 2.3, 14.1). There were 974 data collection timepoints. Differences in respiratory measures and rates of decline between disease-onset and sex subgroups were identified. Females had lower scores in all respiratory measures and females with bulbar onset ALS had faster decline compared with other sub-groups. These differences were not detected by the ALSFRS-r respiratory subscale. Dyspnea, orthopnea, and a higher King’s stage at baseline were associated with lower respiratory scores throughout follow-up, while having a regular productive cough at baseline was associated with lower peak cough flow scores. Conclusion Respiratory function declines more quickly in females with ALS compared with males when measured by FVC, SVC, SNIP, or PCF, but not the ALSFRS-R respiratory sub-score. Higher baseline King’s staging and the presence of clinical respiratory symptoms at baseline were associated with worse respiratory function. The ALSFRS-R respiratory sub-score is poorly correlated with objective respiratory measurements.

Omeprazole and risk of osteoarthritis: insights from a mendelian randomization study in the UK Biobank

BackgroundA former cohort study has raised concern regarding the unanticipated hazard of omeprazole in expediting osteoarthritis (OA) advancement. The precise nature of their causal evidence, however, remains undetermined. The present research endeavors to investigate the underlying causal link between omeprazole and OA through the application of mendelian randomization (MR) analysis.MethodsThe study incorporated the ukb-a-106 and ukb-b-14,486 datasets. The investigation of causal effects employed methodologies such as MR-Egger, Weighted median, Inverse variance weighted (IVW) with multiplicative random effects, and IVW (fixed effects). The IVW approach was predominantly considered for result interpretation. Sensitivity analysis was conducted, encompassing assessments for heterogeneity, horizontal pleiotropy, and the Leave-one-out techniques.ResultsThe outcomes of the MR analysis indicated a causal relationship between omeprazole and OA, with omeprazole identified as a contributing risk factor for OA development (IVW model: OR = 1.2473, P < 0.01 in ukb-a-106; OR = 1.1288, P < 0.05 in ukb-b-14,486). The sensitivity analysis underscored the robustness and dependability of the above-mentioned analytical findings.ConclusionThis study, employing MR, reveals that omeprazole, as an exposure factor, elevates the risk of OA. Considering the drug’s efficacy and associated adverse events, clinical practitioners should exercise caution regarding prolonged omeprazole use, particularly in populations with heightened OA risks. Further robust and high-quality research is warranted to validate our findings and guide clinical practice.

Obesity-Related Traits Mediate the Effects of Educational Attainment on the Risk of Varicose Veins, Venous Thromboembolism, and Phlebitis.

The extent to which educational attainment (EA) influences the risk of varicose veins (VVs), venous thromboembolism (VTE), and phlebitis occurrence, whether this pathway is mediated by obesity-related traits, and the proportion of their mediation is unknown. A Mendelian randomization (MR) design was used to genetically investigate the causal effects of EA on the risk of VV, VTE, and phlebitis and to assess the mediating effect of obesity-related traits. Causal effects were estimated using primarily the multiplicative random-effects inverse variance-weighted method. This was supplemented by Cochran's Q-statistic, MR-Egger regression, MR funnel plots, and leave-one-out test to evaluate the reliability of the results. For the individual mediation effect, the coefficient product method was mainly utilized to estimate. An increase in genetically predicted EA was associated with a lower risk of VV, VTE, and phlebitis, as well as lower body mass index, basal metabolic rate, hip circumference, and waist circumference. As genetically predicted body mass index, basal metabolic rate, hip circumference, and waist circumference increased, the risk of developing VV, VTE, and phlebitis increased, respectively. Body mass index, basal metabolic rate, hip circumference, and waist circumference were identified as mediators of the protective effects of EA on VV, VTE, and phlebitis. The findings support a causal relationship between higher EA and lower risk of VV, VTE, and phlebitis. Obesity-related traits play a significant mediating role in these pathways, and there are interactions between them, with hip circumference mediating these pathways relatively independently from the other three.

Ulcerative colitis and nephrotic syndrome: a two-sample Mendelian randomization study.

To investigate the potential causal relationship between ulcerative colitis and nephrotic syndrome. We obtained the whole-genome association study data of ulcerative colitis in the European population from the GWAS database. Relevant single nucleotide polymorphisms (SNPs) were selected for analysis. We employed the inverse variance-weighted meta-analysis of multiplicative random effects models to obtain SNP-specific Wald ratio estimates, which assume horizontal pleiotropy. In addition, we performed sensitivity analyses using MR-Egger, weighted median, and IVW. Our findings suggest a strong association between ulcerative colitis and nephrotic syndrome (P < 0.05). After conducting sensitivity analyses, we found no evidence of horizontal pleiotropy or heterogeneity (P > 0.05). This study provides evidence for an association between ulcerative colitis and nephrotic syndrome, which may help us better understand the conditions of ulcerative colitis and nephropathy.

Obstructive Sleep Apnea Syndrome and Obesity Indicators, Circulating Blood Lipid Levels, and Adipokines Levels: A Bidirectional Two-Sample Mendelian Randomization Study.

This investigation sought to elucidate the genetic underpinnings that connect obesity indicators, circulating blood lipid levels, adipokines levels and obstructive sleep apnea syndrome (OSAS), employing a bidirectional two-sample Mendelian randomization (MR) analysis that utilizes data derived from extensive genome-wide association studies (GWAS). We harnessed genetic datasets of OSAS available from the FinnGen consortium and summary data of four obesity indices (including neck circumference), seven blood lipid (including triglycerides) and eleven adipokines (including leptin) from the IEU OpenGWAS database. We primarily utilized inverse variance weighted (IVW), weighted median, and MR-Egger methods, alongside MR-PRESSO and Cochran's Q tests, to validate and assess the diversity and heterogeneity of our findings. After applying the Bonferroni correction, we identified significant correlations between OSAS and increased neck circumference (Odds Ratio [OR]: 3.472, 95% Confidence Interval [CI]: 1.954-6.169, P= 2.201E-05) and decreased high-density lipoprotein (HDL) cholesterol levels (OR: 0.904, 95% CI: 0.858-0.952, P= 1.251E-04). Concurrently, OSAS was linked to lower leptin levels (OR: 1.355, 95% CI: 1.069-1.718, P= 0.012) and leptin receptor levels (OR: 0.722, 95% CI: 0.530-0.996, P= 0.047). Sensitivity analyses revealed heterogeneity in HDL cholesterol and leptin indicators, but further multiplicative random effects IVW method analysis confirmed these correlations as significant (P< 0.05) without notable heterogeneity or horizontal pleiotropy in other instrumental variables. This investigation compellingly supports the hypothesis that OSAS could be a genetic predisposition for elevated neck circumference, dyslipidemia, and adipokine imbalance. These findings unveil potential genetic interactions between OSAS and metabolic syndrome, providing new pathways for research in this domain. Future investigations should aim to delineate the specific biological pathways by which OSAS impacts metabolic syndrome. Understanding these mechanisms is critical for developing targeted prevention and therapeutic strategies.

Identifying the causal relationship between immune factors and osteonecrosis: a two-sample Mendelian randomization study

A wealth of evidence intimates a profound connection between the immune system and osteonecrosis, albeit the specific immune factors underlying this connection remain largely veiled. A bidirectional Mendelian randomization (MR) study was conducted based on genome-wide association study summary data to identify causal links between 731 immune factors and osteonecrosis including drug-induced osteonecrosis. Preliminary MR analysis was accomplished utilizing the inverse-variance weighted method under a multiplicative random effects model, and heterogeneity and potential horizontal pleiotropy were evaluated through Cochrane's Q-test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis. Upon false discovery rate correction, the gene-predicted level of one immune factor (CD62L − monocyte %monocyte) exhibited a significant positive correlation with osteonecrosis, while eight immune traits associated with monocytes, dendritic cells, and NK cells demonstrated significant causal effects with drug-induced osteonecrosis. Reverse MR revealed no significant correlations. This MR research provides genetic evidence for the causal associations between a broad spectrum of immune factors and osteonecrosis. Such a study aids in unraveling the intricate interaction patterns between the immune and skeletal systems, elucidating the pathogenesis of osteonecrosis, and identifying potential novel therapeutic approaches.

Self-directed Learning Ability and Shadow Education Expenditures: A Comparison of Impact on Student Achievement in Korea During COVID-19

This study examines the impact of students’ self-directed learning (SDL) ability and parental expenditures for shadow education, and other factors, on academic achievement in South Korea during the pandemic. Busan Education Longitudinal Study panel data for 2019 (pre-COVID) and 2020–2021 (COVID) were utilized. National exam scores of middle and high school students in Korean, English, and math subject areas were analyzed using multiple regression, random effects, and two-way random effects models. The analysis revealed that, during the pandemic, parents’ high expenditures to provide shadow education to complement their children’s public education did not significantly influence academic achievement. In contrast, SDL ability was found to have a significant impact on achievement in all three subject areas during the pandemic. The findings underscore the importance of programs, policies, and teaching strategies that develop students’ SDL skills to enable them to learn on their own when a crisis restricts traditional teacher-guided classroom instruction.

Deciphering thyroid function and CIMT: a Mendelian randomization study of the U-shaped influence mediated by apolipoproteins.

Carotid Intima-Media Thickness (CIMT) is a key marker for atherosclerosis, with its modulation being crucial for cardiovascular disease (CVD) risk assessment. While thyroid function's impact on cardiovascular health is recognized, the causal relationship and underlying mechanisms influencing CIMT remain to be elucidated. In this study, Mendelian Randomization (MR) was employed to assess the causal relationship between thyroid function and CIMT. Thyroid hormone data were sourced from the Thyroidomics Consortium, while lipid traits and CIMT measurements were obtained from the UK Biobank. The primary analysis method was a two-sample MR using multiplicative random effects inverse variance weighting (IVW-MRE). Additionally, the study explored the influence of thyroid hormones on lipid profiles and assessed their potential mediating role in the thyroid function-CIMT relationship through multivariate MR analysis. The study revealed that lower levels of Free Thyroxine (FT4) within the normal range are significantly associated with increased CIMT. This association was not observed with free triiodothyronine (FT3), thyroid-stimulating hormone (TSH), or TPOAb. Additionally, mediation analysis suggested that apolipoprotein A-I and B are involved in the relationship between thyroid function and CIMT. The findings indicate a potential U-shaped curve relationship between FT4 levels and CIMT, with thyroid hormone supplementation in hypothyroid patients showing benefits in reducing CIMT. This research establishes a causal link between thyroid function and CIMT using MR methods, underscoring the importance of monitoring thyroid function for early cardiovascular risk assessment. The results advocate for the consideration of thyroid hormone supplementation in hypothyroid patients as a strategy to mitigate the risk of carotid atherosclerosis. These insights pave the way for more targeted approaches in managing patients with thyroid dysfunction to prevent cardiovascular complications.

Causal Effects of COVID-19 on the Risk of Thrombosis: A Two-Sample Mendel Randomization Study.

Coronavirus disease 2019 (COVID-19) and thrombosis are linked, but the biomolecular mechanism is unclear. We aimed to investigate the causal relationship between COVID-19 and thrombotic biomarkers. We used two-sample Mendelian randomization (MR) to assess the effect of COVID-19 on 20 thrombotic biomarkers. We estimated causality using inverse variance weighting with multiplicative random effect, and performed sensitivity analysis using weighted median, MR-Egger regression and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) methods. All the results were examined by false discovery rate (FDR) with the Benjamin and Hochberg method for this correction to minimize false positives. We used R language for the analysis. All COVID-19 classes showed lower levels of tissue factor pathway inhibitor (TFPI) and interleukin-1 receptor type 1 (IL-1R1). COVID-19 significantly reduced TFPI (odds ratio [OR] = 0.639, 95% confidence interval [CI]: 0.435-0.938) and IL-1R1 (OR = 0.603, 95% CI = 0.417-0.872), nearly doubling the odds. We also found that COVID-19 lowered multiple coagulation factor deficiency protein 2 and increased C-C motif chemokine 3. Hospitalized COVID-19 cases had less plasminogen activator, tissue type (tPA) and P-selectin glycoprotein ligand 1 (PSGL-1), while severe cases had higher mean platelet volume (MPV) and lower platelet count. These changes in TFPI, tPA, IL-1R1, MPV, and platelet count suggested a higher risk of thrombosis. Decreased PSGL-1 indicated a lower risk of thrombosis. TFPI, IL-1R, and seven other indicators provide causal clues of the pathogenesis of COVID-19 and thrombosis. This study demonstrated that COVID-19 causally influences thrombosis at the biomolecular level.

An evaluation of common stock assessment diagnostic tools for choosing among state-space models with multiple random effects processes

State-space models have received increasing attention in fisheries stock assessments given their flexibility to incorporate multiple sources of process errors. Identifying which process errors to include is important because incorrectly including some process errors can induce bias in management quantities. Existing model selection tools commonly applied in traditional statistical catch-at-age models may not perform as well for state-space models. We evaluated the efficacy of common diagnostic tools for correctly identifying the presence, absence, and magnitude of three process errors (survival, selectivity, and natural mortality) in a simulation–estimation experiment. No model diagnostic tools could consistently identify the correct process error structure in all situations. Incorrectly attributing the process error from natural mortality to other processes, or vice versa, led to relatively large bias in management quantities. Furthermore, incorrectly including an additional source of process error in the assessment models exhibited similar performance to the correct model and generally showed unbiased estimates of management quantities; incorrectly excluding a source of process error, however, generated large biases. Thus, despite not having generally reliable model diagnostic tools for state-space assessments, practitioners should err on the side of using overly complex models, except for natural mortality unless there is external corroborating evidence of changing natural mortality.

Publisher Correction: Mind, a methodology for multivariate small area estimation with multiple random effects

Publisher Correction: Mind, a methodology for multivariate small area estimation with multiple random effects

Genetic causal association between rheumatoid arthritis and periodontitis: a bidirectional two-sample Mendelian randomization analysis.

A link between rheumatoid arthritis (RA) and periodontitis (PD) has been established. However, their causal relationship remains unclear and the effect of different serotypes of RA on the PD development has not been investigated. This study aims to elucidate the causal association between PD and different serotypes of RA using Mendelian randomization (MR). A bidirectional two-sample MR analysis was performed using available large-scale genome-wide association studies statistics. The inverse-variance weighted (IVW) or multiplicative random-effects IVW was used to determine causality, depending on the heterogeneity of instrumental variables. Additional sensitivity analyses were also performed. The forward MR analysis identified that seropositive RA (odds ratio (OR), 1.26; 95% confidence interval (CI), 1.07-1.44; p = 0.0018), but not seronegative RA (OR, 1.01; 95% CI, 0.95-1.06; p = 0.9098), was associated with an increased risk of PD. The reverse MR analysis did not show any significant causal effect of PD on RA, independent of the serotypes. The sensitivity tests (p > 0.05) confirmed the robustness and accuracy of these findings. This study revealed that there was a genetic causal effect of seropositive RA on PD, suggesting that this subtype of RA patients may require specific clinical attention to prevent the development of PD.

Causal Relationships of Chronic Constipation and Irritable Bowel Syndrome with Digestive Tract Cancers: A Mendelian Randomization Study.

Chronic constipation and irritable bowel syndrome (IBS) manifest as prevalent gastrointestinal disorders, while digestive tract cancers (DTCs) present formidable challenges to global well-being. However, extant observational studies proffer uncertain insights into potential causal relationships of constipation and IBS with susceptibility to DTCs. We executed Mendelian randomization (MR) analysis to establish causal connections between these conditions and seven distinct categories of DTCs, including colorectal carcinoma (CRC), hepatocellular cancer (HCC), esophageal malignancy (ESCA), pancreatic adenocarcinoma (PAAD), biliary tract carcinoma (BTCs), gastric carcinoma (GC), and small intestine neoplasm (SIC). Leveraging instrumental variables (IVs) obtained from GWAS data of the FinnGen database, we employed a range of analytical methodologies, including inverse-variance weighting multiplicative random effects (IVW_MRE), inverse-variance weighting fixed effects (IVW_FE), maximum likelihood (ML), weighted median (WM), MR‒Egger regression, and the MR-PRESSO test. We observed a substantial linkage between genetically predicted constipation and increased vulnerability to PAAD (OR = 2.29, 95% CI: 1.422-3.69, P = 0.001) via the IVW method. Following the removal of outlier SNPs through MR-PRESSO, genetically predicted IBS was affiliated with an increased risk of CRC (OR = 1.17, 95% CI: 1-1.37, P = 0.05). Nonetheless, decisive causal correlations of constipation or IBS with other DTCs remain elusive. In summary, genetically predicted constipation was associated with an augmented PAAD risk, and IBS was associated with an increased CRC susceptibility within European cohorts, in agreement with some observational studies. Nevertheless, the causal associations of constipation and IBS with other DTCs remain inconclusive.

Repurposing antihypertensive drugs for pain disorders: a drug-target mendelian randomization study.

Addressing the rising prevalence of pain disorders and limitations of current analgesics, our study explores repurposing antihypertensive drugs for pain management, inspired by the link between hypertension and pain. We leverage a drug-target Mendelian Randomization (MR) approach to explore their dual benefits and establish causal connections. A comprehensive compilation of antihypertensive drug classes was undertaken through British National Formulary, with their target genes identified using the DrugBank database. Relevant single nucleotide polymorphisms (SNPs) associated with these targets were selected from published genomic studies on systolic blood pressure (SBP) as genetic instruments. These SNPs were validated through MR against acute coronary artery disease (CAD) to ensure genes not linked to CAD were excluded from acting as proxies for antihypertensive drugs. An MR analysis of 29 pain-related outcomes was conducted using the FinnGen R10 database employing the selected and validated genetic instruments. We utilized the Inverse Variance Weighted (IVW) method for primary analysis, applying Bonferroni correction to control type I error. IVW's multiplicative random effects (MRE) addressed heterogeneity, and MR-PRESSO managed pleiotropy, ensuring accurate causal inference. Our analysis differentiates strong and suggestive evidence in linking antihypertensive drugs to pain disorder risks. Strong evidence was found for adrenergic neuron blockers increasing migraine without aura risk, loop diuretics reducing panniculitis, and vasodilator antihypertensives lowering limb pain risk. Suggestive evidence suggests alpha-adrenoceptor blockers might increase migraine risk, while beta-adrenoceptor blockers could lower radiculopathy risk. Adrenergic neuron blockers also show a potential protective effect against coxarthrosis (hip osteoarthritis) and increased femgenpain risk (pain and other conditions related to female genital organs and menstrual cycle). Additionally, suggestive links were found between vasodilator antihypertensives and reduced radiculopathy risk, and both alpha-adrenoceptor blockers and renin inhibitors possibly decreasing dorsalgianas risk (unspecified dorsalgia). These findings highlight the intricate effects of antihypertensive drugs on pain disorders, underlining the need for further research. The findings indicate that antihypertensive medications may exert varied effects on pain management, suggesting a repurposing potential for treating specific pain disorders. The results advocate for further research to confirm these associations and to explore underlying mechanisms, to optimize pain management practices.

The role of coffee and potential mediators in subclinical atherosclerosis: insights from Mendelian randomization study.

Coffee contains many bioactive compounds, and its inconsistent association with subclinical atherosclerosis has been reported in observational studies. In this Mendelian randomization study, we investigated whether genetically predicted coffee consumption is associated with subclinical atherosclerosis, as well as the role of potential mediators. We first conducted a two-sample Mendelian randomization analysis to examine the causal effect of coffee and its subtypes on subclinical atherosclerosis inferred from coronary artery calcification (CAC). Next, the significant results were validated using another independent dataset. Two-step Mendelian randomization analyses were utilized to evaluate the causal pathway from coffee to subclinical atherosclerosis through potential mediators, including blood pressure, blood lipids, body mass index, and glycated hemoglobin. Mendelian randomization analyses were performed using the multiplicative random effects inverse-variance weighted method as the main approach, followed by a series of complementary methods and sensitivity analyses. Coffee, filtered coffee, and instant coffee were associated with the risk of CAC (β = 0.79, 95% CI: 0.12 to 1.47, p = 0.022; β = 0.66, 95% CI: 0.17 to 1.15, p = 0.008; β = 0.66, 95% CI: 0.20 to 1.13, p = 0.005; respectively). While no significant causal relationship was found between decaffeinated coffee and CAC (β = -1.32, 95% CI: -2.67 to 0.04, p = 0.056). The association between coffee and CAC was validated in the replication analysis (β = 0.27, 95% CI: 0.07 to 0.48, p = 0.009). Body mass index mediated 39.98% of the effect of coffee on CAC (95% CI: 9.78 to 70.19%, p = 0.009), and 5.79% of the effect of instant coffee on CAC (95% CI: 0.54 to 11.04%, p = 0.030). Our study suggests that coffee other than decaffeinated coffee increases the risk of subclinical atherosclerosis inferred from CAC. Body mass index mediated 39.98 and 5.79% of the causal effects of coffee and instant coffee on CAC, respectively. Coffee should be consumed with caution, especially in individuals with established cardiovascular risk factors, and decaffeinated coffee appears to be a safer choice.