The Causal Effects of Inflammation and Coagulation-Related Biomarkers on Sepsis-Related Complications: A Mendelian Randomization Study

Mendelian randomization (MR) study. To examine whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal pain (back or neck pain). Observational studies and a recent MR study have found associations between elevated blood pressure and a greater risk of back pain. Observational studies have found associations between hyperlipidemia and statin use and greater risk of back pain. No prior MR studies have examined the effects of antihypertensives or statins on spinal pain. This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies (GWAS). Sample sizes in exposure GWASs were n=757,601 (systolic blood pressure) and n=173,082 (low-density lipoprotein cholesterol), and n=1,028,947 for the outcome GWAS of spinal pain defined as health care seeking for any spinal pain-related diagnosis. Genes and cis-acting variants were identified as proxies for the drug targets of interest. MR analyses used inverse-variance weighted meta-analysis. The threshold for statistical significance after correction for multiple testing was P <0.0125. No statistically significant associations of these medications with spinal pain were found. However, findings were suggestive of a protective effect of beta-blockers on spinal pain risk (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72-0.98; P =0.03), and calcium channel blockers on greater spinal pain risk (OR 1.12, 95% CI 1.02-1.24; P =0.02). A protective effect of beta-blockers on spinal pain was suggested in the current study, consistent with findings from observational studies of various other pain phenotypes. The detrimental effect of calcium channel blockers on spinal pain suggested in the current study must be interpreted in the context of conflicting directions of effect on nonspinal pain phenotypes in other observational studies.This Mendelian randomization study examined whether antihypertensive medications (beta-blockers, calcium channel blockers, and angiotensin-converting enzyme inhibitors) and statins can be repurposed to prevent or treat spinal.This was a two-sample MR study using publicly available summary statistics from large-scale genome-wide association studies ranging size from 173,082 to 1,028,947 adults.While no statistically significant associations were found, a protective effect of beta-blockers on spinal pain was suggested (odds ratio [OR] 0.84, 95% confidence interval [CI] 0.72 to 0.98; p= 0.03), as was a detrimental effect of calcium channel blockers on spinal pain (OR 1.12, 95% CI 1.02 to 1.24; p= 0.02).

Given the epidemiological evidence suggesting an association between sodium intake and various gastrointestinal (GI) disorders, this study aimed to investigate the causal effect of genetically predicted urinary sodium-to-creatinine ratio (UNaUCr), a proxy for sodium intake, on GI diseases. Employing a Mendelian Randomization (MR) approach, genetic variants closely associated with UNaUCr were identified by extracting data from genome-wide association studies (GWAS). To validate the results, a comprehensive set of statistical methodologies, encompassing inverse-variance weighted (IVW), weighted median, and MR-Egger approaches was employed. Moreover, sensitivity analysis was performed, encompassing examinations of heterogeneity, investigations into horizontal pleiotropy, MR-PRESSO, and leave-one-out analysis. The findings of the IVW method indicated a positive causal association between genetically predicted UNaUCr and 2 GI traits: diseases of the esophagus, stomach, and duodenum (odds ratio = 1.76; 95% confidence interval [CI]: 1.35, 2.30), and irritable bowel syndrome (IBS) (odds ratio = 3.05; 95% CI: 1.64, 5.65). These associations remained significant after false discovery rate (FDR) correction. Other GI outcomes showed no significant associations after multiple testing correction. Results from weighted median and MR-Egger analyses were generally consistent. Although no substantial evidence of horizontal pleiotropy or heterogeneity was detected, residual pleiotropy cannot be completely excluded. This MR study provides evidence supporting a potential causal association between genetically predicted UNaUCr and 2 GI traits after FDR correction. However, as UNaUCr is a proxy for sodium intake and residual pleiotropy cannot be entirely excluded, these findings should be interpreted with caution and require further validation.

Background:To understand a causal role of modifiable lifestyle factors in angiotensin-converting enzyme 2 (ACE2) expression (a putative severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] receptor) across 44 human tissues/organs, and in coronavirus disease 2019 (COVID-19) susceptibility and severity, we conducted a phenome-wide two-sample Mendelian randomization (MR) study.Methods:More than 500 genetic variants were used as instrumental variables to predict smoking and alcohol consumption. Inverse-variance weighted approach was adopted as the primary method to estimate a causal association, while MR-Egger regression, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO) were performed to identify potential horizontal pleiotropy.Results:We found that genetically predicted smoking intensity significantly increased ACE2 expression in thyroid (β=1.468, p=1.8×10−8), and increased ACE2 expression in adipose, brain, colon, and liver with nominal significance. Additionally, genetically predicted smoking initiation significantly increased the risk of COVID-19 onset (odds ratio=1.14, p=8.7×10−5). No statistically significant result was observed for alcohol consumption.Conclusions:Our work demonstrates an important role of smoking, measured by both status and intensity, in the susceptibility to COVID-19.Funding:XJ is supported by research grants from the Swedish Research Council (VR-2018–02247) and Swedish Research Council for Health, Working Life and Welfare (FORTE-2020–00884).

Smoking, measured by both initiation and intensity, are significantly associated with an elevated expression level of ACE2 in multiple human tissues/organs, subsequently increasing the susceptibility and severity of COVID-19.

ObjectiveRecent research suggests a potential link between the gut microbiome (GM) and epilepsy. We undertook a Mendelian randomization (MR) study to determine the possible causal influence of GM on epilepsy and its various subtypes, and explore whether cytokines act as mediators.MethodsWe utilized Genome-Wide Association Study (GWAS) summary statistics to examine the causal relationships between GM, cytokines, and four epilepsy subtypes. Furthermore, we assessed whether cytokines mediate the relationship between GM and epilepsy. Significant GMs were further investigated using transcriptomic MR analysis with genes mapped from the FUMA GWAS. Sensitivity analyses and reverse MR were conducted for validation, and false discovery rate (FDR) correction was applied for multiple comparisons.ResultsWe pinpointed causal relationships between 30 GMs and various epilepsy subtypes. Notably, the Family Veillonellaceae (OR:1.03, 95%CI:1.02–1.05, p = 0.0003) consistently showed a strong positive association with child absence epilepsy, and this causal association endured even after FDR correction (p-FDR &amp;lt; 0.05). Seven cytokines were significantly associated with epilepsy and its subtypes. A mediating role for cytokines has not been demonstrated. Sensitivity tests validated the primary MR analysis outcomes. Additionally, no reverse causality was detected between significant GMs and epilepsy. Of the mapped genes of notable GMs, genes like BLK, FDFT1, DOK2, FAM167A, ZSCAN9, RNGTT, RBM47, DNAJC21, SUMF1, TCF20, GLO1, TMTC1, VAV2, and RNF14 exhibited a profound correlation with the risk factors of epilepsy subtypes.ConclusionOur research validates the causal role of GMs and cytokines in various epilepsy subtypes, and there has been no evidence that cytokines play a mediating role between GM and epilepsy. This could provide fresh perspectives for the prevention and treatment of epilepsy.

Introduction: Both low bone mineral density (BMD) and Alzheimer’s disease (AD) commonly co_occur in the older adult. Until now, the association between AD and BMD has been widely reported by observational studies. However, Mendelian randomization (MR) studies did not support the causal association between BMD and AD. We think that the lack of significant causal association between AD and BMD identified by recent MR studies may be caused by small number of potential instrumental variables.Methods: We conduct a MR study to evaluate the causal effect of heel BMD on the risk of AD using 1,362 genome-wide significant and independent (p &amp;lt; 5.00E-08) heel BMD genetic variants as the potential instrumental variables, which are identified by a large-scale genome wide association study (GWAS) of heel BMD in 394,929 UK Biobank individuals. Using these 1,362 genome-wide significant and independent heel BMD genetic variants, we extracted their corresponding AD GWAS summary results in IGAP AD GWAS dataset (n = 63,926) and FinnGen AD GWAS dataset (n = 377,277). Five methods including inverse-variance weighted meta-analysis (IVW), weighted median, MR-Egger, MR-PRESSO, and MRlap were selected to perform the MR analysis. 951 of these 1,362 genetic variants are available in AD GWAS dataset.Results: We observed statistically significant causal effect of heel BMD on the risk of AD using IVW in IGAP AD GWAS dataset (OR = 1.048, 95%CI: 1.002–1.095, p = 0.04) and FinnGen AD GWAS dataset (OR = 1.053, 95% CI:1.011–1.098, p = 0.011). Importantly, meta-analysis of IVW estimates from IGAP and FinnGen further supported the causal effect of heel BMD on the risk of AD (OR = 1.051, 95% CI: 1.02–1.083, p = 0.0013).Discussion: Collectively, our current MR study supports heel BMD to be a risk factor of AD by analyzing the large-scale heel BMD and AD GWAS datasets. The potential mechanisms underlying the association between heel BMD and AD should be further evaluated in future.

BackgroundPhysical activity and micronutrient intake, including supplementation, have individually and synergistically shown potential benefits against diabetic nephropathy (DN), yet causality remains uncertain.MethodsThis study conducted a Mendelian randomization (MR) study using summary-level data from large-scale genome-wide association studies (GWAS) involving 15 micronutrients grouped into four categories. Moderate-to-vigorous physical activity (MVPA) represented physical activity, whereas leisure screen time (LST) served as an indicator of sedentary behavior. Data for type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) with DN were sourced from the FinnGen consortium. Univariable MR analyses identified causal relationships, linkage disequilibrium score (LDSC) regression evaluated genetic correlations, and multivariable MR adjusted for 18 confounders. Mediation MR analyses explored potential mediating pathways. The primary analytical methods included inverse variance weighted (IVW) and Wald ratio estimation. Statistical rigor included variant pruning, Steiger tests for directional validity, and RadialMR to mitigate pleiotropy.ResultsAfter false discovery rate correction, genetically predicted MVPA significantly reduced T1DM-associated DN risk [odds ratio (OR) = 0.294, 95% CI: 0.120–0.724, Padj = 0.036], independently of renal function markers. Mediation analysis indicated body mass index mediated part of this protective effect (mediation effect: 9.42%). LDSC analysis revealed a significant negative genetic correlation between MVPA and DN risk (genetic correlation = -0.143). Suggestive associations were found between carotene and zinc levels and increased T1DM-related DN risk (OR > 1). For T2DM-related DN, higher vitamin E (γ-tocopherol) levels significantly decreased DN risk (OR = 0.261, 95% CI: 0.111–0.616, Padj = 0.039), with suggestive protective evidence also observed for α-tocopherol (OR = 0.214, 95% CI: 0.058–0.793).ConclusionThis MR analysis confirms physical activity reduces DN risk in T1DM patients, partially through BMI-mediated mechanisms, and highlights vitamin E’s protective potential in managing T2DM-related DN. These findings underline the clinical relevance of lifestyle modifications and dietary supplementation in DN prevention strategies.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12986-025-00980-7.

Bullous pemphigoid (BP) is an autoimmune blistering disease linked to T-lymphocyte dysregulation. Adenosine deaminase (ADA) and adenosine metabolites modulate T-cell function, suggesting a potential role in BP pathogenesis. However, causal evidence from human genetic studies is lacking. This study aimed to investigate the potential causal associations of genetically predicted levels of ADA, ADA protein, and several adenosine metabolites with the risk of BP and its subtypes (mucous membrane pemphigoid [MMP] and other/unspecified pemphigoid [OUP]). We conducted a two-sample Mendelian randomization (MR) study using summary statistics from large-scale genome-wide association studies (GWAS). Genetic instruments for ADA levels, ADA protein levels, 5-methylthioadenosine, N1-methyladenosine, N6-carbamoylthreonyladenosine (t6A), and N6-succinyladenosine were selected. Outcome data for BP, MMP, and OUP were obtained from the FinnGen R12 release. The primary analysis used the inverse-variance weighted (IVW) method. Sensitivity analyses included MR-Egger, weighted median, weighted mode methods, Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. Genetically predicted higher t6A levels were significantly associated with a lower risk of BP (IVW OR: 0.37, 95% Confidence Interval [CI]: 0.21-0.66; P < 0.001; P_FDR < 0.001). This association was supported by the weighted median method (OR: 0.39, 95% CI: 0.18-0.86; P = 0.02). No significant evidence of heterogeneity or horizontal pleiotropy was found for this association. No causal associations were observed for other adenosine metabolites, ADA levels, or ADA protein levels with BP, MMP, or OUP after FDR correction. This MR study suggests a potential causal association between higher t6A levels and reduced risk of bullous pemphigoid. Further research is warranted to elucidate the underlying mechanisms and potential therapeutic implications.

Backgroundα-Klotho may involve in the occurrence and development of venous thromboembolism (VTE). However, the underlying relationship between circulating α-Klotho levels and VTE is still unclear.MethodsThis two-sample Mendelian Randomization (MR) study aims to explore the causal associations of circulating α-Klotho levels with different types of venous thromboembolism. Data of exposure and outcomes were extracted from the genome-wide association study (GWAS) of the MRC Integrative Epidemiology Unit (MRC-IEU). The fixed inverse variance weighted (IVW), MR-Egger, MR-Robust Adjusted Profile Score (RAPS) and the weighted-median methods were utilized to investigate the causal associations of circulating α-Klotho levels with different types of VTE. The effect size was expressed as odds ratios (ORs) and 95% confidence intervals (CIs), and the False Discovery Rate (FDR) test was used for correction. The MR scatter plot and leave-one-out test were used for sensitivity analysis. In addition, reverse causal associations were assessed.ResultsIVW estimates suggested that an elevated circulating α-Klotho level was associated with lower odds of deep vein thrombosis (DVT) of lower extremities (OR = 0.992, 95%CI: 0.986–0.998, P = 0.0074), pulmonary embolism (PE) (OR = 0.474, 95%CI: 0.255–0.881, P = 0.0183), and DVT of lower extremities combined with PE (OR = 0.984, 95%CI: 0.971–0.997, P = 0.0175). However, after the FDR correction, only negatively causal association between circulating α-Klotho level and increased odds of lower-extremity DVT was statistically significant (FDR P = 0.0296). Also, there were no reverse causal associations between the circulating α-Klotho levels and different types of VTE (all P > 0.05). Additionally, both the MR scatter plots and leave-one-out test results showed that these causal associations were relatively robust.ConclusionAn elevated circulating α-Klotho levels was associated with lower risk of DVT of lower extremities, PE, and DVT of lower extremities combined with PE, indicating α-Klotho has the potential to act as a target for early screening or treatment for VTE. However, the specific mechanism that α-Klotho influencing the occurrence of VTE still needed further exploration.Graphical

Assessing causal relationship between non-alcoholic fatty liver disease and risk of atrial fibrillation

Establishing new approaches for the prevention and treatment of stroke relies on identifying modifiable risk factors that contribute to the development of this complex disease. Mendelian randomization (MR) studies, analogous to naturally occurring randomized trials, can assess causality of potentially modifiable biomarkers and offer new insights into biological pathways. Stroke is the second leading cause of death worldwide and the chief determinant of long-term disability. Stroke is a heterogeneous disease arising from several distinct underlying pathologies and is typically classified as ischemic or hemorrhagic, and further subclassified using imaging data. Ischemic stroke (IS), including its 3 main subtypes: small vessel disease, large vessel disease, and cardioembolic stroke, accounts for ≈80% of stroke and is the result of an interrupted blood supply, leading to localized areas of ischemia in the brain. Small vessel disease may be a consequence of nonatherosclerotic, as well as atherosclerotic, mechanisms that result in an occlusion of the small perforating arteries, whereas large vessel disease results from occlusions or emboli from plaque rupture in larger vessels, such as a carotid artery. Cardioembolic stroke arises typically from emboli from the heart. By contrast, hemorrhagic stroke is a consequence of intracerebral hemorrhage (bleeding into the brain) or subarachnoid hemorrhage (bleeding into the subarachnoid space). These diverse stroke subtypes have distinct underlying pathologies reflecting different risk factor distributions. MR studies, using genetic variants as instrumental variables, afford a powerful approach to assessing causality of risk factors and avoid biases inherent in observational studies, including confounding and reverse causation. This review considers the contribution of MR studies to stroke epidemiology and their relevance to understanding risk factors and new therapeutic targets for stroke. Meta-analyses of large prospective studies have enhanced our knowledge of classical and emerging risk factors for stroke.1–4 Classical risk factors for stroke include nonmodifiable characteristics, …

The levels of vitamin D in the human body are primarily measured through serum 25-hydroxyvitamin D (25(OH)D) levels. Observational studies suggest a potential association between the incidence of laryngeal cancer and vitamin D levels, but the causality remains unclear. This study aims to investigate the potential causal relationship between vitamin D levels and laryngeal cancer. This Mendelian Randomization (MR) study is based on large-scale GWAS (Genome-Wide Association Study) summary datasets. We selected two different datasets of 25(OH)D and conducted two two-sample univariable Mendelian Randomization (MR) analyses. Four different MR methods were applied, and a series of sensitivity analyses were performed. In addition, a two-sample Mendelian randomization was conducted to account for the confounding effect of smoking. Furthermore, we performed GO enrichment analyses on the SNPs used as instrumental variables. The combined findings from both univariable MR analyses support a potential causal relationship between serum 25(OH)D levels and laryngeal cancer, suggesting that higher levels of vitamin D may have a protective effect against laryngeal cancer. Multivariable MR analysis showed that even after accounting for smoking as a confounding factor, the impact of 25(OH)D on laryngeal cancer remained significant. Enrichment analysis further indicated that 25(OH)D may inhibit the occurrence and progression of laryngeal cancer by regulating the metabolism of exogenous substances, lipid metabolism, and cellular responses to environmental stimuli. Higher serum 25-hydroxyvitamin D levels serve as a protective factor against laryngeal cancer, suggesting that increasing vitamin D levels may reduce the risk of laryngeal cancer. This was a Mendelian randomized study with a level of evidence second only to clinical randomized trials, and higher than cohort and case-control studies.

Article Figures and data Abstract Editor's evaluation Introduction Methods Results Discussion Data availability References Decision letter Author response Article and author information Metrics Abstract Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the industrialised world and is projected to affect >280 million people worldwide by 2040. Aiming to identify causal factors and potential therapeutic targets for this common condition, we designed and undertook a phenome-wide Mendelian randomisation (MR) study. Methods: We evaluated the effect of 4591 exposure traits on early AMD using univariable MR. Statistically significant results were explored further using: validation in an advanced AMD cohort; MR Bayesian model averaging (MR-BMA); and multivariable MR. Results: Overall, 44 traits were found to be putatively causal for early AMD in univariable analysis. Serum proteins that were found to have significant relationships with AMD included S100-A5 (odds ratio [OR] = 1.07, p-value = 6.80E−06), cathepsin F (OR = 1.10, p-value = 7.16E−05), and serine palmitoyltransferase 2 (OR = 0.86, p-value = 1.00E−03). Univariable MR analysis also supported roles for complement and immune cell traits. Although numerous lipid traits were found to be significantly related to AMD, MR-BMA suggested a driving causal role for serum sphingomyelin (marginal inclusion probability [MIP] = 0.76; model-averaged causal estimate [MACE] = 0.29). Conclusions: The results of this MR study support several putative causal factors for AMD and highlight avenues for future translational research. Funding: This project was funded by the Wellcome Trust (224643/Z/21/Z; 200990/Z/16/Z); the University of Manchester’s Wellcome Institutional Strategic Support Fund (Wellcome ISSF) grant (204796/Z/16/Z); the UK National Institute for Health Research (NIHR) Academic Clinical Fellow and Clinical Lecturer Programmes; Retina UK and Fight for Sight (GR586); the Australian National Health and Medical Research Council (NHMRC) (1150144). Editor's evaluation The findings of this study as well as the strength of the provided evidence are important and have significance beyond a single subfield. This manuscript is of interest to readers in the fields of ophthalmology, epidemiology and public health. The identification of both known and previously unknown risk factors for age-related macular degeneration (AMD) using genetically informed approaches can be combined with traditional epidemiological approaches to develop interventions that reduce the risk of AMD. The key claims of the manuscript are well supported by the data, and the approaches used are thoughtful and rigorous. https://doi.org/10.7554/eLife.82546.sa0 Decision letter eLife's review process Introduction Age-related macular degeneration (AMD) is a common retinal condition that affects individuals who are ≥50 years old. It is caused by the complex interplay of multiple genetic and environmental risk factors, and genome-wide association studies (GWAS) have identified AMD-implicated variants in at least 69 loci. These include important risk alleles in the 1q32 and 10q26 genomic regions (corresponding to the CFH [complement factor H] and ARMS2/HTRA1 locus, respectively) (Fritsche et al., 2016; Winkler et al., 2020). Other key risk factors include age, smoking, alcohol consumption, and low dietary intake of antioxidants (carotenoids, zinc) (Chakravarthy et al., 2010). AMD can be categorised according to severity (early, intermediate, or advanced) or based on the presence of neovascularisation (neovascular or non-neovascular). Advanced AMD results in loss of central vision, often leading to severe visual impairment (Fleckenstein et al., 2021). Notably, AMD is a major cause of blindness in the elderly population and represents a substantial global burden that is expected to continue to grow into the future as an ageing population expands worldwide (Chakravarthy et al., 2010). Mendelian randomisation (MR) is a statistical approach that uses genetic variation to look for causal relationships between exposures (such as smoking) and outcomes (such as risk of a specific disease) (Julian et al., 2021). MR is increasingly being utilised as it can, to a degree, address a major limitation of observational studies: unmeasured confounding (Sanderson et al., 2022). To minimise issues with certain types of confounding and to support causal inference statements, MR uses genetic variation as an instrument (i.e. as a variable that is associated with the exposure but is independent of confounders and is not associated with the outcome, other than through the exposure). The principles of MR are based on Mendel’s laws of segregation and independent assortment, which state that offspring inherit alleles randomly from their parents and randomly with respect to other locations in the genome. A key concept is the use of genetic variants that are related to an exposure of interest to proxy the part of the exposure that is independent of possible confounding influences (e.g. from the environment or from other traits). It is noted that analogies have been drawn between MR and randomised controlled trials with these two approaches considered proximal in terms of hierarchy of evidence (Julian et al., 2021). To date, the use of MR approaches in the context of AMD has been limited although these methods have been successfully implemented to explore the relationship between AMD and a small number of traits including lipids, thyroid function, CRP, and complement factors (Cipriani et al., 2021; Han et al., 2021; Han et al., 2020b; Li et al., 2022; Zuber et al., 2020). In this study, we developed a systematic, broad (‘phenome-wide’) MR-based analytical approach and used it to investigate the relationship between early AMD and several thousand exposure variables. A set of traits that are robustly associated with genetic liability to AMD were identified. Methods Data sources Outcome data Two AMD phenotypes were used as outcome measures in this study. The first one was early AMD. The GWAS summary statistics for this phenotype were taken from a meta-analysis by Winkler et al., 2020. This meta-analysis focussed on populations of European ancestries and used data from the ARIC, AugUR, CHS, GHS, IAMDGC, KORA S4, LIFE-Adult NICOLA, UKBB, and WHI studies (14,034 early AMD cases and 91,214 controls overall). A full description of how these studies classified participants as ‘early AMD’ can be found in the relevant publication Winkler et al., 2020; briefly, a number of approaches considering drusen size/area and the presence or absence of pigmentary abnormalities were utilised including the 3 Continent Consortium (3CC) severity scale (Klein et al., 2014), the Rotterdam Eye Study classification (Korb et al., 2014), the Beckman clinical classification (Ferris et al., 2013), and the AREDS-9 step classification scheme (Davis et al., 2005). All relevant studies used colour fundus photography for grading purposes. The second phenotype that we studied was advanced AMD. For this trait, we drew on GWAS summary statistics from a multiple trait analysis of GWAS (MTAG) study by Han et al., 2020a. This meta-analysis also focussed on individuals with European ancestries and derived data from the IAMDGC 2013 (17,181 cases and 60,074 controls) (Fritsche et al., 2013) and IAMDGC 2016 (16,144 advanced AMD cases and 17,832 controls) (Fritsche et al., 2016) studies as well as the GERA study (4017 cases and 14,984 controls) (Kvale et al., 2015). The relevant summary statistics are primarily reflective of advanced AMD, but the GERA cohort included both advanced and intermediate AMD cases. Advanced AMD was broadly defined by the presence of geographic atrophy or choroidal neovascularisation, although there was a degree of variability in the criteria used in the included studies. Notably, the MTAG approach can leverage the high genetic correlation between the input phenotypes to detect genetic associations relevant only to advanced AMD. Exposure data A phenome-wide screen was performed to make causal inferences on the role of a wide range of traits in early and advanced AMD. To achieve this, both published and unpublished GWAS data from the IEU open GWAS database were used; these were accessible via the TwoSampleMR programme in R (Hemani et al., 2018). All European GWAS within this database were included with the exception of imaging phenotypes and expression quantitative trait locus related data which were removed. The restriction to European datasets limits the generalisability of the results to other populations but is necessary to produce reliable findings. In the early AMD analysis, studies from the ‘ukb’ and ‘met-d’ batches were excluded as data for these studies were entirely from the UK Biobank resource and, as a result, there was extensive population overlap with the early AMD GWAS (Sudlow et al., 2015). In the advanced AMD analysis, the ‘ukb’ and ‘met-d’ batches were included. The early AMD analysis was conducted on 30/12/2021 and a total of 10,979 traits were considered for analysis. The advanced AMD analysis was conducted on 08/01/2022. On 26/01/2022 we added the newly published ‘finn-b’ (n = 2803) traits to the analysis in place of the outdated ‘finn-a’ traits (n = 1489). It was impractical to manually inspect the degree of population overlap for all traits prior to conducting the analysis; instead, the degree of overlap for all significant traits was inspected after the analysis. Instrument selection A statistically driven approach to instrumental variable selection was used. Typically, an arbitrary p-value threshold is set for the identification of appropriate single-nucleotide variants (SNVs); these are subsequently used as instrumental variables (referred to thereafter as instruments). A conventional p-value threshold for the selection of instruments is >5E−08. This approach however can, in some cases, be problematic. For example, when the number of instruments exceeding this threshold is small, the analysis can be underpowered or, in certain cases of unbiased screens, the results can be inflated (Boddy et al., 2022). With this in mind, the p-value for instrument selection for each trait was set to the level where >5 instruments were available for each analysis. More specifically, for each trait, the analysis would first be conducted with a p-value threshold for inclusion of 5E−8 before sequentially increasing the threshold by a factor of 10 each time until >5 eligible instruments are identified. A predefined maximum p-value of 5E−05 was used and the final range of pvalues for inclusion was 5E−06 to 5E−08. Proxies Where an exposure instrument was not present in the outcome dataset, a suitable proxy was identified (Hartwig et al., 2016). In the early AMD analysis, this was achieved by using the TwoSampleMR software with a linkage disequilibrium R2 value of ≥0.9 (Purcell et al., 2007). For the advanced AMD phenotype, data that were not derived from the TwoSampleMR resource were used and therefore the Ensembl server was utilised to identify proxies (Cunningham et al., 2022; Hemani et al., 2018). Clumping SNVs were clumped using a linkage disequilibrium R2 value of 0.001 and a genetic distance cut-off of 10,000 kilo-bases. A European reference panel was used for clumping. Harmonisation The effects of instruments on outcomes and exposures were harmonised to ensure that the beta values (i.e. the regression analysis estimates of effect size) were expressed per additional copy of the same allele (Hartwig et al., 2016). Palindromic alleles (i.e. alleles that are the same on the forward as on the reverse strand) with a minor allele frequency >0.42 were omitted from the analysis in order to reduce the risk of errors. Removal of pleiotropic genetic variants and outliers Pleiotropic instruments and outliers were removed from the analysis by using a statistical approach that removes instruments which are found to be more significant for the outcome than for the exposure (Hemani et al., 2017). Radial MR, a simulation-based approach that detects outlying instruments, was also utilised (Bowden et al., 2018). Causal inference MR relies on three key assumptions with regard to the instrumental variable: (1) the instrumental SNV should be associated with the exposure; (2) the SNV should not be associated with confounders; (3) the SNV should influence the outcome only through the exposure (Julian et al., 2021). MR estimation was primarily performed using a multiplicative random effects (MRE) inverse variance weighted (IVW) method. MRE IVW was selected over a fixed effects (FE) approach as it allows inclusion of heterogeneous instruments (this was certain to occur within the breadth of this screen) (Burgess et al., 2019). A range of ‘robust measures’ were used to increase the accuracy of the results and to account for violations of the above key MR assumptions (Burgess et al., 2019); these measures included weighted median (Bowden et al., 2016a), Egger (Burgess and Thompson, 2017), weighted mode (Hartwig et al., 2017), and radial MR with modified second-order weights (Bowden et al., 2018). Further quality control The instrument strength was determined using the F-statistic (which tests the association between the instruments and the exposure) (Burgess and Thompson, 2011). F-Statistics were calculated against the final set of instruments that were included. A mean F-statistic >10 was considered sufficiently strong. The Cochran’s Q test was performed for each analysis. Cochran’s Q is a measure of heterogeneity among causal estimates and serves as an indicator of the presence of horizontal pleiotropy (which occurs when an instrument exhibits effects on the outcome through pathways other than the exposure) (Bowden and Holmes, 2019). It is noted that a heterogeneous instrument is not necessarily invalid, but rather calls for a primary assessment with an MRE IVW rather than an FE approach; this has been conducted as standard throughout our analysis. The MR-Egger intercept test was used to detect horizontal pleiotropy. When this occurs, the Egger regression is robust to horizontal pleiotropy (under the assumption that that pleiotropy is uncorrelated with the association between the SNV and the exposure) (Burgess and Thompson, 2017). Unless otherwise indicated by the Egger intercept, the assumption that no demonstrable horizontal pleiotropy is present was made and Egger regression was not utilised to determine causal effects (given the low power of this approach in the context of a small number of SNVs) (Bowden et al., 2015). The I2 statistic was calculated as a measure of heterogeneity between variant-specific causal estimates. An I2 < 0.9 indicates that Egger is more likely to be biased towards the null through violation of the ‘NO Measurement Error’ (NOME) assumption (Bowden et al., 2016b). Leave-one-out cross-validation was performed for every analysis to determine if any particular SNV was driving the significance of the causal estimates. Management of duplicate traits As the GWAS database that was used contained multiple different GWAS for certain traits, some exposures were analysed on multiple occasions. Where this occurred, the largest sample size study was considered to be the primary analysis. Where there were duplicate studies in the same population, the study with the largest F-statistic was used. Identification of significant results Before considering an MR result to be significant, the results of a range of causal inference and quality control tests should be taken into account. Notably, it is not necessary for a study to find significance in all measures to determine a true causal relationship. MR is a low power study type and, as such, an overly conservative approach to multiple testing can be excessive (Burgess et al., 2019). However, in the context of the present study the results of the early AMD phenome-wide screen were considered significant only if they remained: significant after false discovery rate (FDR) correction in the MRE IVW; nominally significant in weighted mode and weighted median; and nominally significant throughout the leave-one-out analysis (MRE IVW) (Benjamini and Hochberg, 1995). This conservative approach was selected as a large number of phenotypes was studied and because we wanted to focus on high confidence signals. Where causal traits for early AMD were identified, the relationship between these traits and advanced AMD was studied. These two AMD classifications are phenotypically distinct but are generally part of the same disease spectrum. When traits failed to replicate as causal factors in the advanced AMD dataset, it could not be inferred that these traits are not truly causal for early AMD. However, significance in both AMD phenotypes provided support for the detected causal links and evidence that a factor plays a role across the disease spectrum. Multivariable MR Multivariable MR was performed in circumstances where it was important to estimate the effect of >1 closely related (and/or potentially confounding) exposure trait (Sanderson et al., 2019). P-values for the inclusion of instruments for the exposures of interest were optimised to obtain sufficiently high (>10) conditional F-statistics for reliable analysis (Sanderson et al., 2021). With this in mind, selection for exposures began at a p-value threshold of >5E−08. Where trait’s instruments had a conditional F-statistic <10, the p-value for selection was reduced in an automated manner by factor of 10 until an F-statistic >10 was obtained. The same clumping procedure as in the univariable MR analysis was used. Adjusted Cochran’s Q-statistics were calculated, with a p-value of <0.05 indicating significant heterogeneity. Where the Cochran’s Q-statistic indicated heterogeneity, a Q-statistic minimisation procedure was used to evaluate the causal relationship; testing assumed both high (0.9) and low (0.1) levels of phenotypic correlation (Sanderson et al., 2021). Two-sample multivariable Mendelian randomisation approach based on Bayesian model averaging (MR-BMA) Multivariable MR can be used to obtain effect estimates for a few (potentially related) traits. However, it cannot be directly applied when many traits need to be considered. In contrast, Mendelian randomisation Bayesian model averaging (MR-BMA), a Bayesian approach first described by Zuber et al., 2020, can search over large sets of potential risk factors to determine which are most likely to be causal. Notably, Zuber et al., 2020 previously performed an in-depth analysis which considered the role of lipids against an older AMD GWAS. The relevant study served as proof-of-concept for the MR-BMA method and demonstrated that several lipid traits have causal roles in AMD. However, the analysis had two potential limitations. First, it downweighed fatty acid traits through limiting composite traits for SNV identification to HDL, LDL, and triglycerides. Second, numerous lipid traits with a potential role in AMD were not included in the analysis. For these reasons, we chose to conduct a more comprehensive analysis with a slightly altered approach. The following study design modifications were made compared to the study by Zuber et al., 2020: Fatty acids were included as a composite trait (utilising GWAS data for serum fatty acids derived from the Nightingale Health 2020 resource as listed in TwoSampleMR package [Hemani et al., 2018]). All lipid and fatty acid measures included in a GWAS by Kettunen et al., 2016 were considered as potential causal traits (n = 102 traits). A more recent AMD GWAS was used (Winkler et al., 2020). In general, multivariable MR (of any sort) cannot produce reliable results where the studied traits are ≥0.99 correlated with respect to the included instruments. For this reason, where two traits were highly correlated, one was removed at random rather than by manually selecting traits in a manner which risks selection bias. MR-BMA for immune cell and complement phenotypes was additionally performed. In this analysis, instruments were obtained at genome-wide significance for every included exposure in the model (given that composite traits were not For the immune cell all immune traits that were studied in a GWAS by et al., 2020 and were present in the TwoSampleMR package were used as In the complement analysis, all complement traits available in relevant studies by et al., and et al., were with the exception of complement For the MR-BMA analysis, the prior probability was set to and the prior variance was set to A search with 10,000 was and pvalues with were of effect are to of the of putative risk For the univariable MR analysis, these are as per standard of in the exposure for traits, and as beta values for exposure traits. This approach was selected because are for exposure traits (Burgess and 2018). beta values are not by all MR where an exposure variable is and it is often that these values are only Multivariable MR effect are as beta value estimates of the of the exposure variable (given that the role of multivariable MR within this study was to identify MR-BMA effect are in the of a model-averaged causal estimate The is a conservative estimate of the causal effect of an exposure on an outcome across It is noted that the primary of MR-BMA is to highlight the causal trait among a number of causal risk Although the MR-BMA findings can be used to the of they should not be necessarily as an to et al., 2020). R TwoSampleMR MR-BMA was from 2021; Zuber et al., 2020). Results on early AMD, univariable MR analysis was applied to a broad range of traits. quality significant results were in an advanced AMD and further were conducted using multivariable MR and MR-BMA et al., 2020). Overall, 4591 traits were eligible for analysis. 44 were found to be putatively causal for early AMD data of these causal traits were serum and measures (n = Other significant traits identified included immune cell phenotypes (n = serum proteins (n = and disease phenotypes (n = results detected in a phenome-wide univariable Mendelian randomisation (MR) analysis of early age-related macular degeneration traits the conservative quality control criteria described in the methods are IVW IVW cell cell cell on on in in lipids in of in in in large in large in large lipids in large of large in large in large acid in in in lipids in of in in small lipids in small in small total in large lipids in small of small in small palmitoyltransferase factor false discovery inverse variance multiplicative random as a not exposure traits of not produce beta values can be used to of effect but not necessarily These traits in data had sample overlap with the early AMD dataset, a minor degree of overlap which is to the causal traits had no sample overlap with early AMD. is to AMD risk Univariable MR demonstrated significant causal relationships for serum measures and serum fatty acid in early AMD These relationships were also supported by the results of our advanced AMD analysis data Serum are highly correlated traits, and the instruments for serum and fatty acid measures in the present study were correlated MR-BMA was used in order to which traits were driving the causal In our analysis, two genetic variants and were found to be outliers in terms of Q-statistic and across These SNVs were therefore omitted and the analysis was In no SNVs were identified. The 10 in terms of probability are in the data the 10 risk factors in terms of inclusion probability defined as the of the over all the where the risk factor is are in The of all the traits included this analysis are in The traits with respect to their were serum = = in = = = = and in small = = It is noted that MR-BMA is designed to the likely causal risk factor among a set of causal traits, it is often not possible to achieve this with As such, a of for lipid traits cannot be obtained within the utilised MR causal inference the between the beta values for the considered in our Mendelian randomisation Bayesian model averaging (MR-BMA) analysis for early age-related macular degeneration This represents the correlation between the genetic associations of the exposure variables with respect to their instruments. The traits are according to their further information can be found in the data 2 the with respect to their probability in the first of Mendelian randomisation Bayesian model averaging (MR-BMA) of traits in early age-related macular degeneration and present distance and present Cochran’s instruments are The Cochran’s Q is a measure which serves to identify variants with respect to the of the The Q-statistic is used to identify heterogeneity in a and to specific variants as The of variants to the Q-statistic is as the weighted between the and association with the in order to identify distance on the other is utilised to identify (i.e. variants which have a association with the variants are removed from the analysis because they have an influence over variable leading to which that well but 2 causal traits identified by Mendelian randomisation Bayesian model averaging (MR-BMA) of phenotypes in early age-related macular degeneration (AMD) according to their inclusion probability factor

There has been an increased interest for observational studies or randomized controlled trials exploring the impact of calcium intake on cardiovascular diseases (CVD) including coronary artery disease (CAD) and ischemic stroke (IS). However, a direct relationship between total calcium intake and CVD has not been well established and remains controversial. Mendelian randomization (MR) studies have been performed to evaluate the causal association between serum calcium levels and CAD risk and found that increased serum calcium levels could increase the risk of CAD. However, MR analysis found no significant association between genetically higher serum calcium levels and IS as well as its subtypes. Hence, three MR studies reported inconsistent effects of serum calcium levels on CAD and IS. Here, we performed an updated MR study to investigate the association of serum calcium levels with the risk of IS using large-scale genome-wide association study (GWAS) datasets. We selected 14 independent genetic variants as the potential instrumental variables from a large-scale serum calcium GWAS dataset and extracted summary statistics corresponding to the 14 serum calcium genetic variants from the MEGASTROKE Consortium IS GWAS dataset. Interestingly, we found a significant association between serum calcium levels and IS risk using the robust inverse-variance weighted (IVW) and penalized robust IVW methods, with β = 0.243 and P = 0.002. Importantly, the MR results from the robust MR-Egger and penalized robust MR-Egger methods further supported the causal association between serum calcium levels and IS risk, with β = 0.256 and P = 0.005. Meanwhile, the estimates from other MR methods are also consistent with the above findings.

This research applied a bidirectional Mendelian randomization (MR) framework to investigate potential two-way causal associations between immune cell phenotypes and uterine fibroids (UF). This research drew upon publicly available data from large-scale genome-wide association studies (GWAS), encompassing 731 immune cell phenotypes from 3757 participants and UF data from 21,024 cases and 237,694 controls. Primary causal estimates were derived using the inverse-variance weighted (IVW) approach, with additional validation through MR-Egger, weighted median, and related methods. To ensure the reliability of the results, MR-PRESSO analysis, leave-one-out analysis, and false discovery rate (FDR) correction were also performed. Forward MR analyses initially identified 39 immune phenotypes significantly associated with UF (IVW P < 0.05), comprising 23 risk factors and 16 protective factors. Applying stringent selection criteria-IVW P < 0.001, consistent odds ratio (OR) directions across five analytical methods, and pleiotropy P > 0.05-three phenotypes demonstrated strong causal links with UF: CD39⁺ CD8⁺ T cells, CD25 expression on IgD- CD27- B cells, and HLA-DR expression on CD14⁺ CD16- monocytes (all IVW P < 0.001). The reverse MR analysis indicated a negative causal effect of UF on the proportion of CD39⁺ CD8⁺ T cells (IVW OR = 0.895, P = 0.037). Sensitivity analyses ruled out interference from horizontal pleiotropy and heterogeneity, supporting the reliability of the study's conclusions. However, after FDR correction, none of the causal associations remained statistically significant. Our research offers compelling genetic evidence supporting a forward causal link between CD39⁺ CD8⁺ T cells, CD25 on IgD- CD27- B cells, and HLA-DR on CD14⁺ CD16- monocytes and UF, and a reverse causal link between CD39⁺ CD8⁺ T cells and UF, highlighting immune regulation as a potentially pivotal factor in UF pathogenesis.