Genetically predicted iron status and cardiovascular function and structure: a Mendelian randomization study.

Pernicious anaemia (PA) is characterised by vitamin B12 deficiency due to autoimmune-mediated destruction of gastric parietal cells and the consequent loss of intrinsic factor, a specific transporter for the intestinal uptake of vitamin B12. The aetiology of PA remains largely unknown, although genetic and environmental factors have been proposed to underpin the onset of PA(1). A significant proportion of PA patients exhibit iron deficiency, with approximately 50% of PA patients presenting with it before or at diagnosis and 61% subsequently, suggesting an association between the two(2). However, findings from traditional epidemiological studies are subject to confounding and reverse causality. For instance, these associations do not clarify whether iron deficiency contributes to the development of PA or is a consequence of the disease process. Given the profound prevalence of iron deficiency at diagnosis, we hypothesised that reduced iron levels may play a causal role in the onset of PA. We used a Mendelian randomisation (MR) approach to test the causal relationship between iron status and PA.MR leverages the naturally randomised allocation of genetic variants among the population as instrumental variables to gauge the causal effect of an exposure on an outcome of interest(3). We conducted two-sample MR analyses to assess the association between genetically predicted iron levels and PA risk. We obtained genetic association data on iron status from the deCODE study(4). PA genetic association data was sourced from the R10 release of Finngen as our main analysis. The participant data consisted of 3,694 cases of PA and 393,684 controls. Our primary MR analysis method was the inverse-variance weighted approach with additional sensitivity analyses, including leave-one-out, Egger and weighted median analyses.Four single nucleotide polymorphisms (SNPs) were strongly associated with systemic iron status and used as genetic instruments to proxy iron status in two-sample MR analyses. We found that genetically predicted higher iron status was not significantly associated with risk of PA (odds ratio per 1 standard deviation increase in serum iron: 1.12, 95% confidence interval 0.80 to 1.57, P = 0.49). Sensitivity analyses had consistent results, indicating that MR assumptions were not violated and that no single SNP drove the association.This is the first study to test the hypothesis that iron deficiency is causally associated with an increased risk of PA. Our results show that genetically predicted lower iron levels were not associated with an increased risk of PA among individuals of Finnish ancestry. Further investigation is required to understand the manifestation of iron deficiency in PA. Iron deficiency may only be a consequence of PA due to the loss of parietal cells, which produce hydrochloric acid necessary for iron absorption. The frequent presence of iron deficiency before or at diagnosis may also reflect delays in diagnosing PA.

Smoking, alcohol consumption, and age at onset of Huntington's disease: a Mendelian randomization study

ObjectiveLonger QRS duration on the ECG is associated with increased cardiovascular (CV) mortality. To evaluate potential mechanisms, we examined in this study the relationship between QRS duration and left ventricular...

BackgroundObservational studies have shown that central obesity is associated with adverse cardiac structure and function. However, causal association between central obesity and left ventricular (LV) structure and function in preserved ejection fraction (EF) population is still uncertain.MethodsGenome-wide association studies summary data of waist circumference adjusted for body mass index (WCadjBMI) and waist-to-hip ratio adjusted for body mass index (WHRadjBMI) were selected as instrumental variables from the Genetic Investigation of Anthropometric Traits (GIANT) Consortium (n = 224,459). Outcome datasets for LV parameters including LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), LV ejection fraction (LVEF), LV mass (LVM), and LV mass-to-end-diastolic volume ratio (LVMVR) were obtained from the participants without prevalent myocardial infarction or heart failure (LVEF ≥ 50%) in UK Biobank Cardiovascular Magnetic Resonance sub-study (n = 16,923). Two-sample Mendelian randomization (MR) was performed with the inverse-variance weighted (IVW) method as the primary estimate and with the weighted median and MR-Egger as the supplemental estimates. Sensitivity analysis was used to assess the heterogeneity and pleiotropic bias in the MR results.ResultsIn the IVW analysis, every 1-standard deviation (SD) higher WHRadjBMI was significantly associated with higher LVMVR (β = 0.4583; 95% confidence interval [CI]: 0.2921 to 0.6244; P = 6.418 × 10–8) and lower LVEDV (β = –0.2395; 95% CI: –0.3984 to –0.0807; P = 0.0031) after Bonferroni adjustment. No heterogeneity and horizontal pleiotropy were detected in the analysis. No association of WCadjBMI was found with LVEF, LVEDV, LVESV, LVM, or LVMVR.ConclusionOur findings provide evidence of significant causal association between WHRadjBMI and adverse changes in LV structure and function in preserved EF population.

The correlation between obesity and primary open-angle glaucoma (POAG) has not yet been fully established. The aim of this study was to investigate the causal relationship between obesity and POAG by a two-sample Mendelian randomization (MR) study. In this study, body mass index (BMI), an index to evaluate general obesity, and waist and hip circumference, indices to evaluate abdominal obesity, were selected as exposures in MR analysis. Single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables (IVs). Summary data from genome-wide association studies (GWASs) based on a European ancestry by Locke et al., with regard to BMI, and Shungin et al., with regard to waist and hip circumference, were used. Genetic predictors of POAG were obtained from public GWAS summary data. To assess the causal effect of obesity on POAG, the inverse variance-weighted (IVW) method was used as the primary method, and other methods, such as MR–Egger, weighted median, simple mode, and weighted mode, were also used as complementary analyses. Finally, we performed Cochran’s Q statistic to assess heterogeneity, and sensitivity analysis was performed to evaluate the reliability and stability of the MR results. MR analysis showed that BMI has a positive effect on the risk of POAG, with 1 standard deviation (SD) increase in BMI; the risk of POAG increases by approximately 90.9% [OR = 1.909; 95% CI= (1.225, 2.975); p = 0.0042)] (analyzed by IVW); there were no heterogeneity and pleiotropy in the result; and waist circumference also had a positive effect on the risk of POAG [OR = 2.319; 95% CI= (1.071, 5.018); p = 0.033)] analyzed by weighted median. As hip circumference increases, with 1 SD increase in hip circumference, the risk of POAG increases by approximately 119% [OR = 2.199; 95% CI= (1.306, 3.703); p = 0.00305)] estimated by IVW, there were not heterogeneity and pleiotropy as for the result. Our study for the first time confirms that obesity might increase the risk of POAG using two-sample MR analysis. These results might provide guidance on the prevention and treatment of POAG.

BackgroundAs the number of COVID-19 deaths continues to rise worldwide, the identification of risk factors for the disease is an urgent issue, and it remains controversial whether atherogenic lipid-related traits including serum apolipoprotein B, low-density lipoprotein (LDL)-cholesterol, and triglyceride levels, are risk factors. The aim of this study was to estimate causal effects of lipid-related traits on COVID-19 risk in the European population using a two-sample Mendelian randomization (MR) approach.MethodsWe used summary statistics from a genome-wide association study (GWAS) that included 441,016 participants from the UK Biobank as the exposure dataset of lipid-related traits and from COVID-19 Host Genetics Initiative GWAS meta-analyses of European ancestry as the outcome dataset for COVID-19 susceptibility (32,494 cases and 1,316,207 controls), hospitalization (8316 cases and 1,549,095 controls), and severity (4792 cases and 1,054,664 controls). We performed two-sample MR analyses using the inverse variance weighted (IVW) method. As sensitivity analyses, the MR-Egger regression, weighted median, and weighted mode methods were conducted as were leave-one-out sensitivity analysis, the MR-PRESSO global test, PhenoScanner searches, and IVW multivariable MR analyses. A P value below 0.0055 with Bonferroni correction was considered statistically significant.ResultsThis MR study suggested that serum apolipoprotein B or LDL-cholesterol levels were not significantly associated with COVID-19 risk. On the other hand, we inferred that higher serum triglyceride levels were suggestively associated with higher risks of COVID-19 susceptibility (odds ratio [OR] per standard deviation increase in lifelong triglyceride levels, 1.065; 95% confidence interval [CI], 1.001–1.13; P = 0.045) and hospitalization (OR, 1.174; 95% CI, 1.04–1.33; P = 0.012), and were significantly associated with COVID-19 severity (OR, 1.274; 95% CI, 1.08–1.50; P = 0.004). Sensitivity and bidirectional MR analyses suggested that horizontal pleiotropy and reverse causation were unlikely.ConclusionsOur MR study indicates a causal effect of higher serum triglyceride levels on a greater risk of COVID-19 severity in the European population using the latest and largest GWAS datasets to date. However, as the underlying mechanisms remain unclear and our study might be still biased due to possible horizontal pleiotropy, further studies are warranted to validate our findings and investigate underlying mechanisms.

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, …

Background: Previous Mendelian randomization (MR) studies showed an association between hypothyroidism and cataract and between high-normal free thyroxine (FT4) and late age-related macular degeneration (AMD), but not between FT4, thyroid stimulating hormone (TSH), or hyperthyroidism and diabetic retinopathy or cataract. These studies included a limited number of genetic variants for thyroid function and did not investigate autoimmune thyroid disease (AITD) or glaucoma, include bidirectional and multivariable MR (MVMR), and examine sex differences or potential mediation effects of diabetes. We aimed to address this knowledge gap. Methods: We examined the causality and directionality of the associations of AITD, and FT4 and TSH within the reference range with common age-related eye diseases (diabetic retinopathy, cataract, early and late AMD, and primary open-angle glaucoma). We conducted a bidirectional two-sample MR study utilizing publicly available genome-wide association study (GWAS) summary statistics from international consortia (ThyroidOmics, International AMD Genetics Consortium, deCODE, UK Biobank, FinnGen, and DIAGRAM). Bidirectional MR tested directionality, whereas MVMR estimated independent causal effects. Furthermore, we investigated type 1 diabetes (T1D) and type 2 diabetes (T2D) as potential mediators. Results: Genetic predisposition to AITD was associated with increased risk of diabetic retinopathy (p = 3 × 10-4), cataract (p = 3 × 10-3), and T1D (p = 1 × 10-3), but less likely T2D (p = 0.01). MVMR showed attenuated estimates for diabetic retinopathy and cataract when adjusting for T1D, but not T2D. We found pairwise bidirectional associations between AITD, T1D, and diabetic retinopathy. Genetic predisposition to both T1D and T2D increased the risk of diabetic retinopathy and cataract (p < 4 × 10-4). Moreover, genetically predicted higher FT4 within the reference range was associated with an increased risk of late AMD (p = 0.01), particularly in women (p = 7 × 10-3). However, we neither found any association between FT4 and early AMD nor between TSH and early and late AMD. No other associations were observed. Conclusions: Genetic predisposition to AITD is associated with risk of diabetic retinopathy and cataract, mostly mediated through increased T1D risk. Reciprocal associations between AITD, diabetic retinopathy, and T1D imply a shared autoimmune origin. The role of FT4 in AMD and potential sex discrepancies needs further investigation.

PurposeVentricular function is a powerful predictor of survival in patients with heart failure (HF). However, studies characterizing gated F-18 FDG PET for the assessment of the cardiac function are rare. The aim of this study was to prospectively compare gated F-18 FDG PET and cardiac MRI for the assessment of ventricular volume and ejection fraction (EF) in patients with HF.MethodsEighty-nine patients with diagnosed HF who underwent both gated F-18 FDG PET/CT and cardiac MRI within 3 days were included in the analysis. Left ventricular (LV) end-diastolic volume (EDV), end-systolic volume (ESV), and EF were obtained from gated F-18 FDG PET/CT using the Quantitative Gated SPECT (QGS) and 4D-MSPECT software.ResultsLV EDV and LV ESV measured by QGS were significantly lower than those measured by cardiac MRI (both P<0.0001). In contrast, the corresponding values for LV EDV for 4D-MSPECT were comparable, and LV ESV was underestimated with borderline significance compared with cardiac MRI (P = 0.047). LV EF measured by QGS and cardiac MRI showed no significant differences, whereas the corresponding values for 4D-MSPECT were lower than for cardiac MRI (P<0.0001). The correlations of LV EDV, LV ESV, and LV EF between gated F-18 FDG PET/CT and cardiac MRI were excellent for both QGS (r = 0.92, 0.92, and 0.76, respectively) and 4D-MSPECT (r = 0.93, 0.94, and 0.75, respectively). However, Bland-Altman analysis revealed a significant systemic error, where LV EDV (−27.9±37.0 mL) and ESV (−18.6±33.8 mL) were underestimated by QGS.ConclusionDespite the observation that gated F-18 FDG PET/CT were well correlated with cardiac MRI for assessing LV function, variation was observed between the two imaging modalities, and so these imaging techniques should not be used interchangeably.

Observational studies have indicated significant contributions of protein C and protein S to thrombotic diseases, yet the "anticoagulation paradox" in deep venous thrombosis (DVT) remains unresolved. Therefore, we conducted an investigation to discern the causal effects of protein C, protein S and antithrombin-III on DVT risk. We employed a two-sample (one to evaluate the gene-exposure relationship and the other to evaluate the gene-outcome relationship) bidirectional Mendelian randomization (MR) framework to assess the causal associations between protein C, protein S, antithrombin-III and DVT. Genetic associations with DVT were extracted from a comprehensive genome-wide association study involving 484,598 individuals. In the multivariable MR analysis, the odds ratios for DVT per standard deviation (SD) increase were 1.005 (95% CI: 1.002-1.008; p < 0.001) for protein C, 0.997 (95% CI: 0.992-1.001; p = 0.146) for protein S, and 1.001 (95% CI: 0.998-1.005; p = 0.456) for antithrombin-III. A two-step MR mediation analysis revealed that the association between protein C and DVT was partially mediated by body mass index, with a mediated proportion of 11.4% (95% confidence interval, 2.3% to 79.2%). These findings provide insights into the genetic relationship between relative protein C rather than protein S or antithrombin-III levels and DVT, offering potential utility in identifying at-risk patients for DVT development.

Adiposity has been associated with an increased risk of head and neck cancer (HNC). Although body mass index (BMI) has been inversely associated with HNC risk among smokers, this is likely due to confounding. Previous Mendelian randomization (MR) studies could not fully discount causality between adiposity and HNC due to limited statistical power. Hence, we aimed to revisit this using the largest genome-wide association study (GWAS) of HNC available, which has more granular data on HNC subsites.We assessed the genetically predicted effects of BMI (N=806,834), waist-to-hip ratio (WHR; N=697,734) and waist circumference (N=462,166) on the risk of HNC (N=12,264 cases and 19,259 controls) and its subsites (oral, laryngeal, hypopharyngeal and oropharyngeal cancers) using a two-sample MR framework. We used the inverse variance weighted (IVW) MR approach and multiple sensitivity analyses including the weighted median, weighted mode, MR-Egger, MR-PRESSO, and CAUSE approaches. We also used multivariable MR (MVMR) to explore the direct effects of the adiposity measures on HNC, while accounting for smoking behaviour, a well-known HNC risk factor.In univariable MR, higher genetically predicted BMI increased the risk of overall HNC (IVW OR=1.17 per 1 standard deviation [1-SD] higher BMI, 95% CI 1.02–1.34, p=0.03), with no heterogeneity across subsites (Q p=0.78). However, the effect was not consistent in sensitivity analyses. The IVW effect was attenuated when smoking was included in the MVMR model (OR accounting for comprehensive smoking index=0.96 per 1-SD higher BMI, 95% CI 0.80–1.15, p=0.64) and CAUSE indicated the IVW results could be biased by correlated pleiotropy. Furthermore, we did not find a link between genetically predicted WHR (IVW OR=1.05 per 1-SD higher WHR, 95% CI 0.89–1.24, p=0.53) or waist circumference and HNC risk (IVW OR=1.01 per 1-SD higher waist circumference, 95% CI 0.85–1.21, p=0.87).Our findings suggest that adiposity does not play a major role in HNC risk.

There is still some controversy about the relationship between lipids and venous thrombosis (VTE). A bidirectional Mendelian randomization (MR) study was conducted to clarify the causal relationship between three classical lipids (low-density lipoprotein (LDL), high-density lipoprotein (HDL) and triglycerides (TGs)) and venous thromboembolism (VTE) (deep venous thrombosis (DVT) and pulmonary embolism (PE)). Three classical lipids and VTE were analysed by bidirectional Mendelian randomization (MR). We used the random effect inverse variance weighted (IVW) model as the main analysis model and the weighted median method, simple mode method, weighted mode method and MR–Egger methods as supplementary methods. The leave-one-out test was used to determine the influence of outliers. The heterogeneity was calculated by using Cochran Q statistics in the MR–Egger and IVW methods. The intercept term in the MR‒Egger regression was used to indicate whether horizontal pleiotropy affected the results of the MR analysis. In addition, MR-PRESSO identified outlier single-nucleotide polymorphisms (SNPs) and obtained a stable result by removing outlier SNPs and then performing MR analysis. When we used three classical lipids (LDL, HDL and TGs) as exposure variables, no causal relationship between them and VTE (DVT and PE) was found. In addition, we did not find significant causal effects of VTE on the three classical lipids in reverse MR analysis. There is no significant causal relationship between three classical lipids (LDL, HDL and TGs) and VTE (DVT and PE) from a genetic point of view.

Endometriosis (EMs) and depression are both common conditions that have a significant negative impact on quality of life. However, it is still unclear about the relationship between them. The study was designed to investigate the phenotypic and causal association between depression and EMs. For its nationally representative sample, comprehensive health data and publicly accessibility, we chose data from the National Health and Nutrition Examination Survey for our observational study section including 1393 participants in 2005 to 2006 year cycle which contains information both on depression assessed by the Patient Health Questionnaire 9 and self-reported EMs. Initially, we conducted logistic regression analysis to evaluate phenotypic association between depression and EMs utilizing extensive data taken from National Health and Nutrition Examination Survey. Then, using data from the genome-wide association study (female self-reported depression data: N = 194,153 and female medical-recorded depression data: N = 192,680 from UK Biobank where sex-stratified data was provided; EMs data: N = 150,350 from FinnGen consortium database), we assessed the genetically predicted association performing bidirectional two-sample Mendelian randomization (MR) analysis. Inverse-variance weighted method was employed as the main MR analysis. The Weighted median, MR Egger, Simple mode, Weighted mode, and MR pleiotropy residual sum and outlier test were also performed to assess the robustness of our findings. EMs was present in almost 13.64% of the participants in the depression group, which was much greater than the 6.63% in the non-depression group. Depression and EMs were positively correlated in the observational analysis (OR = 2.44, 95%CI = 1.26–4.74). Furthermore, each greater Patient Health Questionnaire 9 score was associated with a 7% increased risk of EMs. EMs did not have a genetically informed influence on depression, while depression clearly had a genetically predicted effect on EMs, according to bidirectional MR analysis. This study shows a genetically predicted association between depression and EMs as well as a favorable phenotypic correlation. It implies that monitoring of diseases of the reproductive system, such as EMs, in female patients with mood disorders and treating them from a multidisciplinary perspective should not be neglected. Further large-scale prospective cohort studies or mechanistic research are warranted to confirm these results and explore the underlying biological mechanisms.

BackgroundObservational studies have illustrated that maternal central obesity is associated with birth size, including of birth weight, birth length and head circumference, but the causal nature of these associations remains unclear. Our study aimed to test the causal effect of maternal central obesity on birth size and puberty height growth using a Mendelian randomization (MR) analysis.MethodsWe performed two-sample MR using summary-level genome-wide public data. Thirty-five single nucleotide polymorphisms (SNPs), 25 SNPs and 41 SNPs were selected as instrumental variables for waist-to-hip ratio adjusted for BMI, waist circumference adjusted for BMI and hip circumference adjusted for BMI, respectively to test the causal effects of maternal central obesity on birth size and puberty height using an inverse-variance-weighted approach.ResultsIn this MR analysis, we found no evidence of a causal association between waist circumference or waist-to-hip ratio and the outcomes. However, we observed that one standard deviation (SD) increase in hip circumference (HIP) was associated with a 0.392 SD increase in birth length (p = 1.1 × 10− 6) and a 0.168 SD increase in birth weight (p = 7.1 × 10− 5), respectively at the Bonferroni-adjusted level of significance. In addition, higher genetically predicted maternal HIP was strongly associated with the puberty heights (0.835 SD, p = 8.4 × 10− 10). However, HIP was not associated with head circumference (p = 0.172).ConclusionsA genetic predisposition to higher maternal HIP was causally associated with larger offspring birth size independent of maternal BMI. However, we found no evidence of a causal association between maternal waist circumference, waist-to-hip ratio and birth size.

Association between blood mitochondrial DNA copy number and mental disorders: A bidirectional two-sample mendelian randomization study