Summary-level Statistics Research Articles

Exploring the Associations of Obesity and Glycemic Traits with Retinal Vein Occlusion: A Univariate and Multivariable Mendelian Randomization Study

ABSTRACT Purpose To explore the genetic links between obesity, glycemic traits and retinal vein occlusion (RVO). Methods Summary-level statistics for obesity and glycemic traits were extracted from publicly available genome-wide association studies (GWAS) of European participants in the IEU Open GWAS database. Genetic associations with clinically diagnosed RVO were obtained from the FinnGenresearch project (372 cases and 182,573 controls). Two-sample Mendelian randomization (MR) and multivariate MR (MVMR) analysis were performed to determine the total effect and direct effect, respectively. Results After adjustment for the false discovery rate (FDR), the primary inverse-variance-weighted (IVW) methods indicated that the odds ratios of RVO increased with per 1-standard deviation increased in body mass index (BMI) (OR = 1.94, 95% CI: 1.23–3.08,p-FDR = 0.025), waist circumference (OR = 2.4, 95% CI: 1.36–4.24, p-FDR = 0.019), fasting glucose (OR = 5.01, 95% CI: 2–12.55, p-FDR = 0.0067) and two-hour glucose (OR = 3.17, 95% CI: 1.63–6.18,p-FDR = 0.0067). Higher whole-body fat-free mass (OR = 0.45, 95% CI: 0.26–0.8,p-FDR = 0.025) is a potential protective factor for RVO. In addition, the results of MVMR showed that BMI, whole-body fat-free mass, fasting glucose and two-hour glucose were independent factors that had a direct impact on the onset of RVO. Conclusions Our comprehensive MR analysis suggested significant genetic associations between BMI, whole-body fat-free mass, fasting glucose, two-hour glucose and RVO. This study highlighted the importance of weight, blood glucose management and physical activity for primary prevention and control of RVO.

Lipid-Lowering Drugs and Pulmonary Vascular Disease: A Mendelian Randomization Study.

The therapeutic value of lipid-lowering drugs in pulmonary vascular disease remains uncertain due to insufficient studies and evidence. This study aims to investigate the causal effects of lipid-lowering drugs (specifically, inhibitors of APOB, CETP, HMGCR, NPC1L1, and PCSK9) on pulmonary vascular diseases using a Mendelian randomization (MR) approach. We utilized summary-level statistics from genome-wide association studies (GWAS) to simulate the exposure to low-density lipoprotein cholesterol (LDL-C) and its outcomes on pulmonary arterial hypertension (PAH), pulmonary embolism (PE), and pulmonary heart disease (PHD). Single-nucleotide polymorphisms (SNPs) within or near drug target-associated LDL-C loci were selected as proxies for the lipid-lowering drugs. Data from the FinnGen cohort and UK Biobank (UKB) were incorporated to enhance the robustness and generalizability of the findings. The inverse variance weighted (IVW) and MR-Egger methods were employed to estimate MR effects. Our MR analysis indicated that LDL-C mediated by NPC1L1 (odds ratio [OR] = 104.76, 95% confidence interval [CI] = 2.01-5457.01, p = 0.021) and PCSK9 (OR = 10.20, 95% CI = 3.58-29.10, p < 0.001) was associated with an increased risk of PAH. In contrast, LDL-C mediated by APOB was associated with a decreased risk of PE (FinnGen: OR = 0.74, 95% CI = 0.60-0.91, p = 0.005; UKB: OR = 0.998, 95% CI = 0.996-1.000, p = 0.031) and PHD (FinnGen: OR = 0.73, 95% CI = 0.59-0.91, p = 0.004). However, LDL-C mediated by CETP and HMGCR did not show significant associations with the risks of PAH, PE, or PHD. This MR study revealed the causal effects of NPC1L1 and PCSK9 inhibitors on increased PAH risk, while APOB inhibitors appear to reduce the risks of PE and PHD. These findings enhance our understanding of the potential roles of lipid-lowering drugs in pulmonary vascular disease.

Unlocking insights: Clinical associations from the largest 6-minute walk test collection via the my Heart Counts Cardiovascular Health Study, a fully digital smartphone platform.

The six-minute walk test (6MWT) is a prognostic sub-maximal exercise test used clinically as a measure of functional capacity. With the emergence of advanced sensors, 6MWTs are being performed remotely via smartphones and other devices. The My Heart Counts Cardiovascular Health Study is a smartphone application that serves as a digital platform for studies of human cardiovascular health, and has been used to perform 30,475 6MWTs on 8922 unique participants. As our 30,475 6MWTs represent the largest such collection of data available, we sought to identify associations with measured demographic and clinical variables with 6MWT distance at enrollment and separately determine if use of the My Heart Counts smartphone application led to changes in 6MWT distance. We present the public data release of our 30,475 6MWTs and the launch of a webpage-based data viewer of summary-level statistics, to compare the functional capacity of an individual by their age, gender, height, weight, and disease status (https://mhc-6mwts.streamlit.app). Using multivariable regression, we report associations of demographic and clinical variables with baseline 6MWT distance (N = 3606), validating prior associations with age, male gender, height, and baseline physical activity level with 6MWT distance. We also report associations of 6MWT baseline distance with employment status (+12.4 m ±4.9 m, P = 0.011) and feeling depressed (-3.65 m, ±0.79 m, P < 0.001). We separately found that cardiovascular disease status was significantly associated with decreased 6MWT distance for atrial fibrillation (-24.9 m ±7.8 m, P = 0.0013), peripheral artery disease (-41.7 m ±12.5 m, P < 0.001), and pulmonary arterial hypertension (-76.3 m ±24.8 m, P = 0.0022). Heart failure was associated with decreased 6MWT distance but was not statistically significant (-25.5 m ±14.5 m, P = 0.078). In a subset of participants who conducted repeat 6MWTs separated by at least 1 week but no greater than 3 months (N = 1129), we found that use of the My Heart Counts app was associated with a statistically significant increase in 6MWT distance (+17.5 m ±7.85 m, P < 0.001). We validate previously identified associations from clinic-performed 6MWTs, demonstrating the utility of a mobile method in collecting 6MWT data for clinicians and researchers. We also demonstrate that use of the My Heart Counts app is associated with small, but significant increases in 6MWT distance. Given the importance of 6MWTs in assessment of functional capacity, our publicly-available data will serve an important purpose as a health and disease-specific reference for investigators worldwide.

Association between autoimmune diseases and myelodysplastic syndrome:a Mendelian randomization study

ABSTRACT Background: The relationship between different types of autoimmune diseases and myelodysplastic syndrome (MDS) is inconclusive. Therefore, we employed Mendelian randomization (MR) to examine whether genetically predicted susceptibility to ten autoimmune diseases is associated with the risk of MDS. Methods: Single nucleotide polymorphisms (SNPs) significantly associated with 10 autoimmune diseases were extracted from the summary statistics of European genome-wide association studies (GWAS). A two-sample MR analysis was performed using summary-level statistics sourced from GWAS datasets. Inverse-variance weighting (IVW), MR–Egger, and weighted median (WM) were further supported by several sensitivity analyses. Results: Four autoimmune diseases showed genetical predisposition to MDS: rheumatoid arthritis (OR = 1.186,95% CI = 1.028-1.367, P = 0.019), multiple sclerosis (OR = 1.247, 95% CI = 1.013-1.534, P = 0.037), myasthenia gravis (OR = 1.326,95% CI = 1.010-1.742, P = 0.042), and Hashimoto thyroiditis(OR = 1.519,95% CI = 1.008-2.290, P = 0.046). Nevertheless, no similar causal relationship was found between the remaining seven autoimmune diseases and MDS. The accuracy and robustness of these findings were confirmed by sensitivity tests. Conclusions: We are the first to use MR analysis to explore the relationship between autoimmune diseases and MDS. The mechanism needs to be further explored.

Identifying the genetic association between severe autoimmune type 2 diabetes and the risk of focal epilepsy.

Observational studies suggested a bidirectional relationship between severe autoimmune type 2 diabetes and focal epilepsy. However, it remains debated whether and in which direction a causal association exists. This genetics-based study aimed to explore the relationships of severe autoimmune type 2 diabetes (T2DM) and focal epilepsy outcomes with two sample Mendelian randomization (TSMR) method. Genetic instruments were obtained from large-scale genome-wide meta-analysis of severe autoimmune T2DM (Ncase = 452, Ncontrol = 2,744), and focal epilepsy (Ncase = 929, Ncontrol = 212,532) of European ancestry. A series of analyses were performed to select eligible genetic instruments robustly associated with each of the traits using summary-level statistics. Inverse variance weighted was used for primary analysis, with alternative 11 MR methods. A scatter plot was utilized to illustrate the association between single nucleotide polymorphism (SNP) effects on the exposure and SNP effects on the outcome. The Wald ratio for individual SNPs and their cumulative effects was depicted using a forest plot. And diagnostics and sensitivity analyses were used to evaluate if the causal estimates are robust to violations of MR underlying assumptions, including pleiotropy, heterogeneity assessment, and leave-one-out analysis. Then the results were validated using CURATED database of DisGeNET platform. For forward analysis, genetic predisposition to severe autoimmune T2DM was associated with an increased risk of focal epilepsy (Inverse variance weighted (IVW) method: OR = 1.11, 95% CI = 1.03-1.18, p = 0.012). For reverse analysis, there was no enough instrument variables of focal epilepsy on severe autoimmune T2DM. Further, the interrelation between severe autoimmune T2DM and focal epilepsy was demonstrated via variant-disease association network analysis using the instrument SNPs. This MR study supports a causal link between severe autoimmune T2DM and focal epilepsy. More effort should be made to screen seizure in severe autoimmune T2DM, unravel its clinical implications, and explore its role as a putative modifiable risk factor.

Elevated risk for stroke in genetically predisposed bicuspid aortic valve disease: evidences from a mendelian randomization study

Abstract Background Patients with bicuspid aortic valve (BAV) have been recognized to have an elevated risk for stroke. However, the exact causal association between BAV and stroke remains elusive due to stroke-related comorbidities, residual confounding bias and sample size limitations of observational studies. Purpose To identify the causal relationship between genetically predisposed BAV and 15 cardiovascular diseases (CVDs), and whether calcific aortic valve stenosis (CAVS) or atrial fibrillation (AF) could serve as the mediator on the pathway from BAV to stroke by mendelian randomization (MR) approach. Methods Uncorrelated (r² &amp;lt; 0.001) and genome-wide significant (P &amp;lt; 5×10^-8) single nucleotide polymorphisms were extracted from the largest genome-wide association study statistics (2,236 patients and 11,604 controls) of BAV by Gehlen et al. Summary-level statistics for 15 CVDs were obtained from the UK Biobank study, FinnGen study, HERMES consortium, CARDIoGRAMplusC4D consortium and GIGASTROKE consortium. We used 2-sample MR to estimate the causal association between BAV and 15 CVDs, evaluated 12 potential mediators and mediated proportions within 2-step MR framework. Inverse variance weighted was utilized as primary MR analyses method. Results for each outcome from different sources were pooled using the random effect meta-analysis. False discovery rate (FDR) was calculated by Benjamini-Hochberg method to account for multiple comparisons. Results Genetically predicted per log-odds liability increase of BAV was significantly associated with aortic aneurysm (OR, 1.26; 95% CI, 1.13-1.40; FDR-adjusted P = 3.54 × 10^-4), any stroke (OR, 1.06; 95% CI, 1.02-1.09; FDR-adjusted P = 0.004), ischemic stroke (IS) (OR, 1.17; 95% CI, 1.03-1.11; FDR-adjusted P = 0.001) and cardioembolic stroke (CES) (OR, 1.15; 95% CI, 1.06-1.25; FDR-adjusted P = 0.004). No significant association were observed between BAV and another 11 CVD outcomes. Instead of CAVS, genetic liability to AF mediated the total effect of BAV on any stroke (proportion mediated = 13.2% [95% CI, 3.1% - 23.2%]), IS (proportion mediated = 10.8% [95% CI, 2.5% - 19.1%]) and CES (proportion mediated = 21.5% [95% CI, 5.3% - 37.7%]). Conclusions Genetically predisposed BAV is associated with a higher risk of any stroke, IS and CES, which could be mediated by AF. This study implies the pathophysiological processes from BAV towards stroke and highlights the clinical significance of AF intervention in reducing the incidence of stroke for BAV patients.Causal association between BAV and CVDs

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

Extensive observational data suggest a link between celiac disease (CeD) and osteoporosis, but the causality and mediating mechanism remain undetermined. Herein, we performed a Mendelian randomization (MR) study to address these concerns. We obtained the summary-level statistics for CeD from a large genome-wide association study (GWAS) comprising 4,533 cases and 10,750 controls of European ancestry. The GWAS data for osteoporosis-related traits and inflammatory cytokines were derived from the UK Biobank, FinnGen, IEU OpenGWAS database, or GWAS catalog. Two-sample MR with the inverse variance-weighted methods were employed to evaluate the genetic association between CeD and osteoporosis-related traits. The potential inflammatory mediators from CeD to osteoporosis were explored using two-step mediation analyses. The primary MR analyses demonstrated causal associations between genetically predicted CeD and osteoporosis (odds ratio [OR]: 1.110, 95% confidence interval [CI]: 1.043-1.182, p=0.001), total body bone mineral density (β: -0.025, p=0.039), and osteoporotic fracture (OR: 1.124, 95% CI: 1.009-1.253, p=0.034). Extensive sensitivity analyses consolidated these findings. Among the candidate inflammatory cytokines, only interleukin-18 was observed to mediate the effects of CeD on osteoporosis, with an indirect OR of 1.020 (95% CI: 1.000-1.040, p=0.048) and a mediation proportion of 18.9%. The mediation effects of interleukin-18 could be validated in other datasets (OR: 1.015, 95% CI: 1.001-1.029, p=0.041). Bayesian colocalization analysis supported the role of interleukin-18 in osteoporosis. The present MR study reveals that CeD is associated with an increased risk of developing osteoporosis, which may be partly mediated by upregulation of interleukin-18.

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

Parkinson's disease (PD) is a prevalent neurodegenerative disorder with poor prognosis. Observational studies have demonstrated a significant correlation between serum galectin-3 and PD, suggesting a potential role of galectin-3 as a biomarker for PD. However, it is still unclear whether galectin-3 contributes to the risk of the disease. A two-sample Mendelian randomization (MR) approach was used in this study. Genetic instruments for serum galectin-3 level were selected from a genome-wide association study (GWAS), including 30,931 European individuals. Summary-level statistics for PD were derived from another published GWAS, including 33,674 cases and 449,056 controls. Primary analysis was conducted using the inverse-variance weighting (IVW) method. Weighted median, MR-Egger, simple mode, weighted mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were used as complementary analyses. To detect heterogeneity, Cochran's Q statistic and leave-one-out analysis were used. For testing potential horizontal pleiotropy, the MR-Egger intercept test and MR-PRESSO global test were conducted. MR analysis using IVW model (OR 1.112, 95% CI 1.025-1.206, p = 0.010), weighted median (OR 1.135, 95% CI 1.037-1.242, p = 0.006), weighted mode (OR 1.142, 95% CI 1.038-1.257, p = 0.030), and MR-PRESSO (OR 1.112, 95% CI 1.046-1.182, p = 0.012) presented a consistent result, indicating that increased serum galectin-3 was associated with a higher risk of PD. No heterogeneity or horizontal pleiotropy was detected in the analyses. The study shows a suggestive association between galectin-3 and PD. Increasing serum galectin-3 was associated with an increase in PD risk. Galectin-3 may play an important role in the causal pathway to PD.

Genetic liability to higher frailty index may increase the risk of ophthalmic disease.

Frailty and age-related eye diseases are common in older people; however, whether there is a causal link remains unknown. We aimed to explore the causal associations between the frailty index (FI) and ophthalmic traits and identify modifiable mediators. Linkage disequilibrium score regression and two-sample Mendelian randomization were applied to identify genetic correlations and causal associations between FI and ophthalmic traits. Summary data for FI was obtained from a genome-wide association study that included 175,226 individuals of European ancestry. Summary-level statistics for ophthalmic traits were obtained from relative GWASs. Summary-level data for cardiovascular risk factors, inflammatory biomarkers, and the central nervous system were used to identify the possible mediators. FI had a significant genetic correlation with 10 ophthalmic traits. Per SD increment of FI, the odds ratio was 1.329 (95% CI, 1.123, 1.573; P = 9.5 × 10-4) for cataracts, 1.825 (95% CI, 1.115, 2.986; P = 0.016) for keratitis, 1.798 (95% CI, 1.039, 3.11; P = 0.036) for disorders of vitreous body and 1.478 (95% CI, 1.005, 2.173; P = 0.046) for disorders of sclera, cornea, iris and ciliary body. The MR effect estimates of FI on ophthalmic traits were attenuated after adjusting for mental disorders, type 2 diabetes, triglyceride, and interleukin-8 (IL-8) levels. This study reports a genetic correlation and causal association between FI and ophthalmic traits, in which mental disorders, type 2 diabetes, triglycerides, and IL-8 may play a mediating role. These findings highlight a possible method to reduce the risk of FI-related ophthalmic diseases.

Unraveling the genetic association between knee osteoarthritis and hallux deformities

ObjectiveKnee osteoarthritis (KOA), hallux valgus (HV) and hallux rigidus (HR) are common musculoskeletal problems of the lower extremities. However, their underlying causal relationships are unclear. This study attempts to clarify the cause-and-effect relationship between KOA and the two common hallux deformities (HV and HR).DesignThe summary-level statistics for KOA, HV, and HR were collected from genome-wide association studies (GWAS). The causal analysis of KOA on HV or HR was carried out using two-sample Mendelian randomization (MR). In order to assess the robustness of the MR results, sensitivity analyses were performed. In addition, multivariable MR (MVMR) was implemented to assess the influence of KOA in causation as well as calibrate the effect of anthropometric characteristics. Supplementary backward MR analysis was conducted to determine the causal effect of hallux diseases on KOA.ResultsThe univariable analysis indicated that KOA has a causative influence on HR (odds ratio [OR] = 1.29, 95% confidence interval [CI] = 1.18–1.41, P = 2.25E-8) and HV (OR = 1.43, 95% CI = 1.21–1.68, P = 2.76E-5). In the backward MR analyses, hallux deformities did not appear to be the cause of KOA. In the MVMR analysis, after jointly adjusting for the effects of waist-to-hip ratio (WHR), waist circumference (WC), hip circumference (HC) and BMI, the causal impact of KOA on HV and HR remained robust.ConclusionIn this study, the genetic causality between KOA and increased risk of hallux deformities (HV and HR) is established, which can provide evidence-based recommendations for reducing the incidence of hallux deformities in KOA patients. Further high-level studies are warranted to validate the associations and explore its broader implications.

Causal Relationships between Lipid-Lowering Drug Target and Aortic Disease and Calcific Aortic Valve Stenosis: A Two-Sample Mendelian Randomization.

Proprotein convertase subtilisin/kexin type 9 (PCSK9), 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), cholesteryl ester transfer protein (CETP) and apolipoprotein C3 (APOC3) are pivotal regulators of lipid metabolism, with licensed drugs targeting these genes. The use of lipid-lowering therapy via the inhibition of these genes has demonstrated a reduction in the risk of cardiovascular disease. However, concerns persist regarding their potential long-term impact on aortic diseases and calcific aortic valve disease (CAVS). This study aims to investigate causal relationships between genetic variants resembling these genes and aortic disease, as well as calcific aortic valve disease using Mendelian randomization (MR). We conducted drug-target Mendelian randomization employing summary-level statistics of low-density lipoprotein cholesterol (LDL-C) to proxy the loss-of-function of PCSK9, HMGCR, CETP and APOC3. Subsequently, we investigated the association between drug-target genetic variants and calcific aortic valve stenosis and aortic diseases, including thoracic aortic aneurysm (TAA), abdominal aortic aneurysm (AAA), and aortic dissection (AD). The genetically constructed variants mimicking lower LDL-C levels were associated with a decreased risk of coronary artery disease, validating their reliability. Notably, HMGCR inhibition exhibited a robust protective effect against TAA (odds ratio (OR): 0.556, 95% CI: 0.372-0.831, p = 0.004), AAA (OR: 0.202, 95% CI: 0.107-0.315, p = 4.84 10-15), and AD (OR: 0.217, 95% CI: 0.098-0.480, p = 0.0002). Similarly, PCSK9, CETP and APOC3 inhibition proxies reduced the risk of AAA (OR: 0.595, 95% CI: 0.485-0.730, p = 6.75 10-7, OR: 0.127, 95% CI: 0.066-0.243, p = 4.42 10-10, and OR: 0.387, 95% CI: 0.182-0.824, p = 0.014, respectively) while showing a neutral impact on TAA and AD. Inhibition of HMGCR, PCSK9, and APOC3 showed promising potential in preventing CAVS with odds ratios of 0.554 (OR: 0.554, 95% CI: 0.433-0.707, p = 2.27 10-6), 0.717 (95% CI: 0.635-0.810, p = 9.28 10-8), and 0.540 (95% CI: 0.351-0.829, p = 0.005), respectively. However, CETP inhibition did not demonstrate any significant benefits in preventing CAVS (95% CI: 0.704-1.544, p = 0.836). The consistency of these findings across various Mendelian randomization methods, accounting for different assumptions concerning genetic pleiotropy, enhances the causal inference. Our MR analysis reveals that genetic variants resembling statin administration are associated with a reduced risk of AAA, TAA, AD and CAVS. HMGCR, PCSK9 and APOC3 inhibitors but not CETP inhibitors have positive benefits of reduced CAVS. Notably, PCSK9, CETP and APOC3 inhibitors exhibit a protective impact, primarily against AAA, with no discernible benefits extending to TAA or AD.

Bayesian Hierarchical Models for Subgroup Analysis.

In conventional subgroup analyses, subgroup treatment effects are estimated using data from each subgroup separately without considering data from other subgroups in the same study. The subgroup treatment effects estimated this way may be heterogenous with high variability due to small sample sizes in some subgroups and much different from the treatment effect in the overall population. A Bayesian hierarchical model (BHM) can be used to derive more precise, and less heterogenous estimates of subgroup treatment effects that are closer to the treatment effect in the overall population. BHM assumes exchangeability in treatment effect across subgroups after adjusting for effect modifiers and other relevant covariates. In this article, we will discuss the technical details for applying one-way and multi-way BHM using summary-level statistics, and patient-level data for subgroup analysis. Four case studies based on four new drug applications are used to illustrate the application of these models in subgroup analyses for continuous, dichotomous, time-to-event, and count endpoints.

Causal relationship between central corneal thickness and open-angle glaucoma: Evidence from Mendelian randomization

Glaucoma is the leading cause of irreversible blindness worldwide. Previous observational studies have suggested a relationship between central corneal thickness (CCT) and glaucoma; however, the results are inconsistent. This study aimed to investigate whether CCT is associated with a risk for developing open-angle glaucoma (OAG). We employed two-sample Mendelian randomization to assess the relationship between CCT and OAG, namely, primary open-angle glaucoma (POAG) and suspected glaucoma. Genetic instruments composed of variants associated with CCT at genome-wide significance (P < 5 × 10−8) were obtained from published genome-wide association studies from Iglesias et al. for discovery and Bonnemaijer et al. for replication. Summary-level statistics for these instruments for the OAG were obtained from the FinnGen Project (Release 10). Inverse-variance-weighted regression of genetic susceptibility predicted that increased CCT was positively associated with an increased risk for POAG (odds ratio [OR], 1.005; 95% confidence interval [CI], 1.002–1.008; P = 0.001) and suspected glaucoma (OR, 1.006; 95% CI, 1.003–1.009; P < 0.001). In the replication sample of CCT, increased CCT was also positively associated with an increased risk for POAG (OR, 1.004; 95% CI, 1.000–1.008; P = 0.029) and suspected glaucoma (OR, 1.005; 95% CI, 1.001–1.008; P = 0.013).We found genetic evidence supporting a potential causal association between increased CCT and the risk of POAG and suspected glaucoma in the European population. This findings indicates the clinical significance of CCT in the diagnosis and treatment of glaucoma. Further studies are needed to elucidate the underlying mechanisms of this causal relationship.

Syphilis susceptibility factors atlas: A wide-angled Mendelian randomization study

ObjectiveThe pathogenic mechanisms of syphilis and the host defense mechanisms against syphilis remain poorly understood. Exploration of the susceptibility factors of syphilis may provide crucial clues for unraveling its underlying mechanisms. MethodsA two-sample Mendelian Randomization framework was utilized, and the inverse-variance weighted method was used as the main analysis. All data was sourced from Genome-wide association studies datasets from 2015 to 2022 in Europe, and all participants were of European descent. Only summary-level statistics were used. Sensitivity analyses were conducted to evaluate the heterogeneity and pleiotropy of the datasets. ResultsOur study established 18 exposure factors (12 risk factors and 6 protective factors) for syphilis susceptibility. Twelve factors encompassing body mass index, waist circumference, darker natural skin, cooked vegetable intake, processed meat intake, diabetes mellitus, glucose regulation disorders, gout, autoimmune diseases, rheumatoid arthritis, diverticulitis, and longer menstrual cycles were found to increase susceptibility to syphilis. In contrast, 6 factors including easier skin tanning, blonde natural hair color, irritability, higher neuroticism scores, extended sleep duration, and delayed age at first sexual intercourse were connected to a reduced risk of syphilis infection (all P < 0.05). ConclusionsThis study identified 18 influencing factors of syphilis susceptibility. These findings offered novel insights for further probing into the underlying pathogenic mechanisms of syphilis and underscored the importance of multifaceted prevention strategies against syphilis.

Phenome-Wide Investigation of the Causal Associations Between Pre-Pregnancy Obesity Traits and Gestational Diabetes: A Two-Sample Mendelian Randomization Analyses.

Pre-pregnancy obesity was associated with gestational diabetes in observational studies, but whether this relationship is causal remains to be determined. To evaluate whether pre-pregnancy obesity traits causally affect gestational diabetes risk, a two-sample Mendelian randomization (MR) analysis was performed utilizing summary-level statistics from published genome-wide association studies (GWAS). Obesity-related traits included body mass index (BMI), overweight, obesity, obesity class 1, obesity class 2, obesity class 3, childhood obesity, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), percent liver fat, visceral adipose tissue volume, abdominal subcutaneous adipose tissue volume. Effect estimates were evaluated using the inverse-variance weighting method. Weighted median, MR-Egger, simple mode, and weighted mode were performed as sensitivity analyses. Genetically predicted pre-pregnancy BMI [odds ratio (OR) = 1.68; 95% confidence interval (CI): 1.45-1.95; P = 9.13 × 10-12], overweight (OR = 1.49; 95% CI: 1.21-1.85; P = 2.06 × 10-4), obesity (OR = 1.25; 95% CI: 1.18-1.33; P = 8.01 × 10-13), obesity class 1 (OR = 1.31; 95% CI: 1.17-1.46; P = 1.49 × 10-6), obesity class 2 (OR = 1.26; 95% CI: 1.16-1.37; P = 5.23 × 10-8), childhood obesity (OR = 1.33; 95% CI: 1.23-1.44; P = 4.06 × 10-12), and WHR (OR = 2.35; 95% CI: 1.44-3.83; P = 5.89 × 10-4) were associated with increased risk of gestational diabetes. No significant association was observed with obesity class 3, WC, HC, percent liver fat, visceral adipose tissue volume, or abdominal subcutaneous adipose tissue volume. Similar results were observed in sensitivity analyses. Therefore, genetically predicted pre-pregnancy obesity traits may increase the risk of gestational diabetes. Weight control before pregnancy may be beneficial to prevent gestational diabetes.

Total testosterone plays a crucial role in the pathway from hypothyroidism to broad depression in women

BackgroundDepression tends to develop in correlation with hypothyroidism, however it's unclear how testosterone traits contribute to this association. We examined the causal association between depression, testosterone traits, and hypothyroidism using Mendelian randomization (MR). MethodWe conducted univariable and multivariable MR studies using summary-level statistics from genome-wide association studies (GWAS) of Hypothyroidism (n = 213,990), broad depression (n = 322,580), probable major depressive disorder (probable MDD) (n = 174,519), and International Classification of Diseases (ICD)-9 or ICD-10-coded MDD (n = 217,584) from European ancestry. The inverse variance weighted (IVW) method was used as the main MR analysis. ResultsIn univariate MR analysis, there is a positive causal relationship between hypothyroidism and broad depression (P = 0.0074; OR = 1.0066; 95%CI: 1.0018–1.0114) and probable MDD (P = 0.0242; OR = 1.0056; 95%CI: 1.0007–1.0105). In females, there is a causal relationship between hypothyroidism and decreased total testosterone (P < 0.001; OR = 0.9747; 95%CI: 0.9612–0.9885) and sex hormone binding globulin (SHBG) levels (P = 0.0418; OR = 0.9858; 95%CI: 0.9723–0.9995). In females, there is an inverse causal relationship between total testosterone and broad depression (P = 0.0349; OR = 0.9898; 95%CI: 0.9804–0.9993). Furthermore, in multivariate MR analysis, after adjusting for total testosterone in females, hypothyroidism only has a positive causal relationship with probable MDD, and the relationship with broad depression is no longer significant. Most notably, after adjusting for hypothyroidism, the inverse causal effect of female total testosterone levels on broad depression becomes more significant (P = 0.0154; OR = 0.9878; 95%CI: 0.9780–0.9977). ConclusionHypothyroidism increases the risk of broad depression and probable MDD development. Total Testosterone appears to play an important role in the relationship between hypothyroidism and broad depression in female.

Wildfires and climate justice: future wildfire events predicted to disproportionally impact socioeconomically vulnerable communities in North Carolina.

Wildfire events are becoming increasingly common across many areas of the United States, including North Carolina (NC). Wildfires can cause immediate damage to properties, and wildfire smoke conditions can harm the overall health of exposed communities. It is critical to identify communities at increased risk of wildfire events, particularly in areas with that have sociodemographic disparities and low socioeconomic status (SES) that may exacerbate incurred impacts of wildfire events. This study set out to: (1) characterize the distribution of wildfire risk across NC; (2) implement integrative cluster analyses to identify regions that contain communities with increased vulnerability to the impacts of wildfire events due to sociodemographic characteristics; (3) provide summary-level statistics of populations with highest wildfire risk, highlighting SES and housing cost factors; and (4) disseminate wildfire risk information via our online web application, ENVIROSCAN. Wildfire hazard potential (WHP) indices were organized at the census tract-level, and distributions were analyzed for spatial autocorrelation via global and local Moran's tests. Sociodemographic characteristics were analyzed via k-means analysis to identify clusters with distinct SES patterns to characterize regions of similar sociodemographic/socioeconomic disparities. These SES groupings were overlayed with housing and wildfire risk profiles to establish patterns of risk across NC. Resulting geospatial analyses identified areas largely in Southeastern NC with high risk of wildfires that were significantly correlated with neighboring regions with high WHP, highlighting adjacent regions of high risk for future wildfire events. Cluster-based analysis of SES factors resulted in three groups of regions categorized through distinct SES profiling; two of these clusters (Clusters 2 and 3) contained indicators of high SES vulnerability. Cluster 2 contained a higher percentage of younger (<5 years), non-white, Hispanic and/or Latino residents; while Cluster 3 had the highest mean WHP and was characterized by a higher percentage of non-white residents, poverty, and less than a high school education. Counties of particular SES and WHP-combined vulnerability include those with majority non-white residents, tribal communities, and below poverty level households largely located in Southeastern NC. WHP values per census tract were dispersed to the public via the ENVIROSCAN application, alongside other environmentally-relevant data.

Relationship between plasma brain-derived neurotrophic factor levels and neurological disorders: An investigation using Mendelian randomisation

BackgroundAltered brain-derived neurotrophic factor (BDNF) concentrations have been detected in the central nervous system tissues and peripheral blood. These alterations are associated with a series of neurological disorders. ObjectiveTo investigate the potential causal relationships between genetically determined plasma BDNF levels and various neurological diseases using a two-sample Mendelian randomisation study. MethodsWe selected single nucleotide polymorphisms strongly related to plasma BDNF levels as instrumental variables. Within the Mendelian randomisation framework, we used summary-level statistics for exposure (plasma BDNF levels) and outcomes (neurological disorders). ResultsWe observed suggestive evidence of a relation between higher plasma BDNF levels and less risk of nontraumatic intracranial haemorrhage (nITH) (odds ratio [OR] = 0.861, 95 % confidence interval [CI]: 0.774–0.958, P = 0.006, PFDR = 0.078), epilepsy (OR = 0.927, 95 % CI: 0.880–0.976, P = 0.004, PFDR = 0.078), focal epilepsy (OR = 0.928, 95 % CI: 0.874–0.986, P = 0.016, PFDR = 0.139), and non-lesional focal epilepsy (OR = 0.981, 95 % CI: 0.964–0.999, P = 0.041, PFDR = 0.267). Combined with the UK Biobank dataset, the association of plasma BDNF levels with nITH remained significant (OR = 0.88, 95 % CI: 0.81–0.96, P < 0.01). The combined analysis of three consortium datasets demonstrated a considerable impact of plasma BDNF on epilepsy (OR = 0.94, 95 % CI: 0.90–0.98, P < 0.01) and a suggestive impact on focal epilepsy (OR = 0.94, 95 % CI: 0.89–0.99, P = 0.02). However, there was no apparent correlation between plasma BDNF levels and other neurological disorders or related subtypes. ConclusionsOur study supports a possible causal relationship between elevated plasma BDNF levels and a reduced risk of nITH, epilepsy, and focal epilepsy.

Thyroid cancer and cardiovascular diseases: a Mendelian randomization study.

Multiple observational studies have shown associations between thyroid cancer (TC) and cardiovascular diseases (CVDs). However, the results were inconsistent, and the potential causal genetic relationship remains unclear. The genetic instruments of TC and CVDs were derived from data obtained through genome-wide association studies (GWAS). We performed the two-sample Mendelian randomization(MR) methods to investigate the causality of TC on CVDs. Summary-level statistics for CVDs, including heart failure (HF), atrial fibrillation (AF), coronary artery disease (CAD), myocardial infarction (MI), ischemic stroke (IS) and venous thromboembolism (VTE). The primary method employed in this MR analysis was the Inverse Variance Weighted (IVW) approach, and four additional algorithms were used: MR-Egger, weighted median, simple mode, and weighted mode. Additionally, we assessed the reliability of the causal relationship through pleiotropy, heterogeneity and leave-one-out sensitivity analysis. In this MR analysis, we only detected causality of genetically predicted TC on HF (IVW method, odds ratio (OR) = 1.00134, 95% confidence interval (CI): 1.00023-1.00244, p = 0.017). However, There were no causal associations of TC with CAD, MI, AF, IS, and VTE. Our results confirmed the causal association between TC and HF. It is crucial to closely monitor the incidence of HF in TC patients and give comprehensive clinical intervention based on conventional treatment.

Mood disorders influencing endometriosis and adenomyosis: Mendelian randomisation study.

Many studies have found an association between mood-disorder-related traits and endometriosis and adenomyosis. However, the cause-effect relationship remains unclear. We conducted Mendelian randomisation analyses to evaluate any causal relationship between mood disorders and endometriosis as well as different sites of endometriosis. Summary-level statistics for mood-disorder-related traits and endometriosis (8288 cases, 68 969 controls) in European populations were derived from large-scale data-sets of genome-wide association studies. A two-sample Mendelian randomisation was performed using the inverse-variance weighted and weight median methods. Further sensitivity analyses, including heterogeneity, pleiotropy and leave-one-out analyses, were conducted to test the consistency of the results. Genetically determined mood swings (odds ratio = 2.557, 95% CI: 1.192-5.483, P = 0.016) and major depression (odds ratio = 1.233, 95% CI: 1.019-1.493, P = 0.031) were causally associated with an increased risk of endometriosis. Mood swings (odds ratio = 4.238, 95% CI: 1.194-15.048, P = 0.025) and major depression (odds ratio = 1.512, 95% CI: 1.052-2.173, P = 0.025) were also causally associated with the risk of adenomyosis. Sensitivity analyses confirmed the reliability of the results. Our results suggest that mood-disorder-related traits increase the risk of endometriosis and adenomyosis. This study provides new insights into the potential pathogenesis of endometriosis and adenomyosis, and highlights the importance of preventing endometriosis and adenomyosis in patients with mood-disorder-related traits.