Genetic Predispositions Between COVID-19 and Three Cardio-Cerebrovascular Diseases

The relationship between COVID-19 and stroke and its risk factors, a Mendelian randomization analysis

BACKGROUND

It remains unclear about the association between stroke and Coronavirus disease 2019 (COVID-19). Therefore, a Mendelian randomization (MR) analysis was conducted to explore the relationship between them.

METHODS

In this study, the most recent large-scale genome-wide association studies (GWASs) were selected from the publicly available COVID-19 GWAS meta-analysis (Round 7) as the exposure. Data from a recent original stroke GWAS were used as the outcome for the experimental group, while the stroke GWAS data from the IEU GWAS database were used as the validation group. In addition, an MR analysis was conducted to explore the causal relationships of susceptibility, hospitalization, and severity of COVID-19 with stroke and its subtypes. In addition, the results of the experimental and validation groups were integrated to perform a meta-analysis.

RESULTS

The MR analysis results corroborated that there was a positively causal relationship between the hospitalization (OR, 1.11; p = 0.015) (ORmeta, 1.11; p < 0.001), and severity (OR, 1.06; p = 0.043) (ORmeta, 1.07; p = 0.002) of COVID-19 and cardioembolic stroke (CES). This result is supported by the validation group and sensitivity analysis.

CONCLUSION

This study demonstrates for the first time that COVID-19 hospitalization and COVID-19 severity are risk factors for CES.

Association between chronic obstructive pulmonary disease and osteoporosis: Mendelian randomization combined with bibliometric analysis

BACKGROUND

Previous observational studies have reported an association between chronic obstructive pulmonary disease (COPD) and osteoporosis (OP). The aim of this study is to investigate the causal relationship between COPD and OP by two-sample Mendelian randomization (MR) analysis. The current status of cross-sectional research between COPD and OP in the past decade was explored through bibliometrics.

METHODS

Single nucleotide polymorphisms (SNPs) that have been found to be strongly associated with COPD were used as instrumental variables (IVs) in MR Analysis. The primary outcome of the study was BMD measurement at five specific anatomical sites, namely the whole body, femoral neck, lumbar spine, forearm, and heel. These BMD measurements were derived primarily from a genome-wide association study (GWAS) and summary statistics from the International Genetic Factors Consortium for Osteoporosis (GEFOS). The main analysis method was inverse variance weighting (IVW). Multiple sensitivity analyses were performed to assess the robustness and reliability of the current MR Results. Further confirmatory MR Analysis between COPD and OP was applied. In bibliometrics. Publications were extracted from the Web of Science core collection publications related to osteoporosis and sarcopenia published between January 2014 and October 2024; Bibliometrics and visualization were performed by Microsoft Office Excel, Citespace, and R (Bibliometrix).

RESULTS

The MR Findings suggest that there is no causal relationship between COPD and BMD at five specific anatomical sites. The results of the primary IVW MR Analysis were generally supported by our sensitivity MR Analysis. We performed MR Analysis for the validation of COPD and OP (IVW OR: 1.019; 95%CI: 0.898-1.564; p = 0.768) also did not support a causal relationship between COPD and BMD. A total of 471 articles written by 1119 organizations from 42 countries/regions by 3331 authors and published in 238 journals were identified in the bibliometric analysis. China is the leading country in terms of the number of publications. China Medical University contributed the most publications. The International Journal of Chronic Obstructive Pulmonary Disease has the highest publication in this field.

CONCLUSIONS

In conclusion, This MR Study found no causal relationship between COPD and OP, suggesting that the observed associations may be due to common genetic effects or environmental confounders. The global research trends in this field in the past decade were summarized through bibliometric analysis, and care became the focus of future research on the relationship between copd and OP.

Effects of gut microbiota and metabolites on pancreatitis: a 2-sample Mendelian randomization study

BACKGROUND

Acute pancreatitis (AP) and chronic pancreatitis (CP) have high incidences and poor prognoses. The early screening of at-risk populations still awaits further study. The limitation was mainly based on observational studies, with limited sample size and the presence of confounding factors. This study used a 2-sample Mendelian randomization (MR) analysis based on publicly available data from genome-wide association studies to reveal the causal effect of gut microbiota and metabolites on pancreatitis.

METHODS

This study collected summary statistics on gut microbiota, metabolites, AP, and CP. A 2-sample MR analysis was performed using MR-Egger, inverse variance-weighted, MR Pleiotropy RESidual Sum and Outlier, maximum likelihood, and weighted median.

RESULTS

The 2-sample MR showed that only Eubacterium coprostanoligenes was an independent protective factor for AP among all gut microbiota, and the other microbiota were not significant for pancreatitis. Unsaturated fatty acids in metabolites are protective factors for both AP (odds ratio [OR], 0.730; 95% CI, 0.593-0.899; P = .003) and CP (OR, 0.660; 95% CI, 0.457-0.916; P = .013). Furthermore, carnitine was a protective factor CP, and glucose was an independent risk factor for CP.

CONCLUSION

This study provides potential evidence of the causal role of gut microbiota and metabolites on pancreatitis, which may be conducive for designing microbiome and metabolite interventions on AP or CP in the future.

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

Purpose

This investigation sought to elucidate the genetic underpinnings that connect obesity indicators, circulating blood lipid levels, adipokines levels and obstructive sleep apnea syndrome (OSAS), employing a bidirectional two-sample Mendelian randomization (MR) analysis that utilizes data derived from extensive genome-wide association studies (GWAS).

Methods

We harnessed genetic datasets of OSAS available from the FinnGen consortium and summary data of four obesity indices (including neck circumference), seven blood lipid (including triglycerides) and eleven adipokines (including leptin) from the IEU OpenGWAS database. We primarily utilized inverse variance weighted (IVW), weighted median, and MR-Egger methods, alongside MR-PRESSO and Cochran's Q tests, to validate and assess the diversity and heterogeneity of our findings.

Results

After applying the Bonferroni correction, we identified significant correlations between OSAS and increased neck circumference (Odds Ratio [OR]: 3.472, 95% Confidence Interval [CI]: 1.954-6.169, P= 2.201E-05) and decreased high-density lipoprotein (HDL) cholesterol levels (OR: 0.904, 95% CI: 0.858-0.952, P= 1.251E-04). Concurrently, OSAS was linked to lower leptin levels (OR: 1.355, 95% CI: 1.069-1.718, P= 0.012) and leptin receptor levels (OR: 0.722, 95% CI: 0.530-0.996, P= 0.047). Sensitivity analyses revealed heterogeneity in HDL cholesterol and leptin indicators, but further multiplicative random effects IVW method analysis confirmed these correlations as significant (P< 0.05) without notable heterogeneity or horizontal pleiotropy in other instrumental variables.

Conclusion

This investigation compellingly supports the hypothesis that OSAS could be a genetic predisposition for elevated neck circumference, dyslipidemia, and adipokine imbalance. These findings unveil potential genetic interactions between OSAS and metabolic syndrome, providing new pathways for research in this domain. Future investigations should aim to delineate the specific biological pathways by which OSAS impacts metabolic syndrome. Understanding these mechanisms is critical for developing targeted prevention and therapeutic strategies.

Exploring the association between COVID-19 and male genital cancer risk in European population: evidence from mendelian randomization analysis

BACKGROUND

Recently accumulated evidence indicates a potential association between COVID-19 and elevated susceptibility to cancer, including male genital cancer. However, the causal nature of this relationship remains unclear.

METHODS

In this Mendelian randomization (MR) study, we investigated the potential causal relationship between COVID-19 and male genital cancer using genetic variants as instrumental variables. We utilized summary statistics from two large-scale genome-wide association studies of COVID-19 hospitalized Vs. controls, as well as data from a population-based male genital cancer database based on European ancestry. We applied stringent quality control measures to select instrumental variables, including checking for linkage disequilibrium, removing low-quality variants, and assessing the strength of the instruments using the F-statistic. We conducted the MR  analysis using the inverse-variance weighted method and several sensitivity analyses (including MR Egger and Weighted Median MR analysis) to test the robustness of our results.

RESULTS

Our MR analysis revealed no causal associations between COVID-19 hospitalization and the incidence of male genital cancer. In the inverse-variance weighted analysis, no causal associations were observed between patients with COVID-19 hospitalization and the incidence of male genital cancer (odds ratio = 1.000 and 95% confidence interval = 0.998-1.001, p = 0.668). The estimated causal effect was consistent across all sensitivity analyses (including the Weighted Median, the MR Egger analysis, and the MR PROSSO analysis). The leave-one-out analysis showed that there was no any sing Single-nucleotide polymorphism significantly influencing our results.

CONCLUSIONS

Our study provides evidence that there is no causal association between COVID-19 hospitalization and male genital cancer.

An inverse causal association between genetically predicted vitamin D and chronic obstructive pulmonary disease risk

Aim

Observational studies have reported that levels of vitamin D were associated with the incidence of chronic obstructive pulmonary disease (COPD), but the relationship between them may have been confounded in previous studies. In this study, we aimed to determine the relationship between the levels of 25-hydroxyvitamin D (25OHD) and the risk of COPD by two-sample Mendelian randomization (MR) analysis.

Methods

Summary statistics for 25OHD and COPD in this study were obtained from the EBI (n = 496,946) consortium and Finn (n = 187,754) consortium. MR was adopted to explore the effect of the genetically predicted levels of 25OHD on the risk of COPD. Based on three assumptions of MR analysis, inverse variance weighting was used as the main analysis. To make our results more robust and reliable, MR Egger’s intercept test, Cochran’s Q test, funnel plot, and “leave-one-out” sensitivity analysis were used to assess the potential pleiotropy and heterogeneity in this study. Then, colocalization analysis and MR Steiger approaches were used to estimate the possible directions of estimates between them. Finally, we analyzed the causal associations between the four core genes (DHCR7, GC, CYP2R1, and CYP24A1) of vitamin D and the levels of 25OHD or the risk of COPD.

Results

Our results showed that each 1 standard deviation (SD) increase in the genetically predicted 25OHD level was associated with a 57.2% lower relative risk of COPD [odds ratio (OR): 0.428, 95% Cl: 0.279–0.657, p = 1.041 × 10−4], and the above association was also verified by maximum likelihood (OR: 0.427, 95% Cl: 0.277–0.657, p = 1.084 × 10−4), MR–Egger (OR: 0.271, 95% CI: 0.176–0.416, p = 2.466 × 10−4), MR-PRESSO (OR: 0.428, 95% Cl: 0.281–0.652, p = 1.421 × 10−4) and MR-RAPS (OR: 0.457, 95% Cl: 0.293–0.712, p = 5.450 × 10−4). Furthermore, colocalization analyses (rs3829251, PP.H4 = 0.99) and MR Steiger (“TRUE”) also showed a reverse association between them. Besides, the core genes of vitamin D also showed similar results except for CYP24A1.

Conclusion

Our findings provide evidence for a reverse association between genetically predicted 25OHD levels and COPD risk. Taking measures to supplement 25OHD may help reduce the incidence of COPD.

Genetically predicted obesity and risk of hip osteoarthritis

OBJECTIVES

To determine the causal association between genetically predicted obesity and the risk of hip osteoarthritis.

METHODS

We performed two-sample Mendelian randomization (MR) analysis to analyze the association between body mass index (BMI) and hip osteoarthritis using pooled-level genome-wide association study (GWAS) data. The inverse variance weighted (IVW), MR‒Egger, and weighted median methods were used to estimate the causal association. In addition, we applied the MR Steiger filtering method, MR robust adjusted profile score (MR.RAPS) methods, and the MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test to examine and address potential horizontal pleiotropy.

RESULTS

We found a causal relationship between genetically predicted BMI and the risk of hip osteoarthritis by the IVW method [OR = 1.45, 95% confidence interval (CI) = 1.04-2.00, P = 0.02]. In the sensitivity analysis, the results of the MR‒Egger and weighted median methods revealed similar estimations but with a wide CI with lower precision. The funnel plot, MR-Egger intercept, and MR-PRESSO all indicated the absence of a directional pleiotropic effect. In addition, no heterogeneity was observed in the present analysis. Therefore, the result of IVW is most suitable and reliable for the present MR analysis.

CONCLUSION

There is a causal relationship between obesity and a higher risk of hip osteoarthritis, suggesting that weight management may be an intervention for the prevention and management of hip osteoarthritis.

LEVEL OF EVIDENCE

Bioinformatics, Basic science.

Causal association of peripheral immune cell counts and atrial fibrillation: A Mendelian randomization study

Background

Atrial fibrillation (AF) is the most common and persistent form of arrhythmia. Recently, increasing evidence has shown a link between immune responses and atrial fibrillation. However, whether the immune response is a cause or consequence of AF remains unknown. We aimed to determine whether genetically predicted peripheral immunity might have a causal effect on AF.

Methods

First, we performed Mendelian randomization (MR) analyses using genetic variants strongly associated with neutrophil, eosinophil, basophil, lymphocyte, and monocyte cell counts as instrumental variables (IVs). Lymphocyte counts were then subjected to further subgroup analysis. The effect of immune cell counts on AF risk was measured using summary statistics from genome-wide association studies (GWAS).

Results

Two-sample MR analysis revealed that a higher neutrophil count, basophil count and lymphocyte count had a causal effect on AF [Odds ratio (OR), 1.06, 95% confidence interval (CI), 1.01-1.10, P = 0.0070; OR, 1.10; 95% CI, 1.04-1.17; P = 0.0015; OR, 0.96; 95% CI, 0.93-0.99; P = 0.0359]. In addition, in our further analysis, genetically predicted increases in CD4 + T-cell counts were also associated with an increased risk of AF (OR, 1.04; 95% CI, 1.0-.09; P = 0.0493).

Conclusion

Our MR analysis provided evidence of a genetically predicted causal relationship between higher peripheral immune cell counts and AF. Subgroup analysis revealed the key role of peripheral lymphocytes in AF, especially the causal relationship between CD4 + T cell count and AF. These findings are beneficial for future exploration of the mechanism of AF.

A phenome-wide investigation of risk factors for severe COVID-19

With the continued spread of COVID-19 globally, it is crucial to identify the potential risk or protective factors associated with COVID-19. Here, we performed genetic correlation analysis and Mendelian randomization analysis to examine genetic relationships between COVID-19 hospitalization and 405 health conditions and lifestyle factors in 456 422 participants from the UK Biobank. The genetic correlation analysis revealed 134 positive and 65 negative correlations, including those with intakes of a variety of dietary components. The MR analysis indicates that a set of body fat-related traits, maternal smoking around birth, basal metabolic rate, lymphocyte count, peripheral enthesopathies and allied syndromes, blood clots in the leg, and arthropathy are causal risk factors for severe COVID-19, while higher education attainment, physical activity, asthma, and never smoking status protect against the illness. Our findings have implications for risk stratification in patients with COVID-19 and the prevention of its severe outcomes.

No evidence of a genetic causal relationship between ankylosing spondylitis and iron homeostasis: A two-sample Mendelian randomization study

Background

Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease that leads to bone hyperplasia and spinal ankylosis. Iron homeostasis plays a very important role in the inflammatory response and is closely related to the pathogenesis of AS. This study aimed to use large-scale genome-wide association study (GWAS) summary data to study the genetic causal relationship between AS and iron homeostasis using Mendelian randomization (MR).

Methods

Genome-wide association study summary data of AS and iron homeostasis-related indicators were obtained from the FinnGen consortium and the DeCODE genetics database, respectively. We used four iron homeostasis-related indicators: ferritin, serum iron, total iron binding capacity (TIBC), and transferrin saturation (TSAT) for two-sample MR analyses to test for genetic causal association with AS using the "TwoSampleMR" package of the R software (version 4.1.2). The random-effects inverse variance weighted (IVW) method was the main analysis method used for MR. We examined the MR analysis results for heterogeneity, horizontal pleiotropy, and possible outliers. In addition, we confirmed the robustness of the MR analysis by testing whether the results were affected by a single SNP and whether they followed a normal distribution.

Results

The random-effects IVW results showed that ferritin [p = 0.225, OR 95% confidence interval (CI) = 0.836 (0.627-1.116)], serum iron [p = 0.714, OR 95% CI = 0.948 (0.714-1.260)], TIBC [p = 0.380, OR 95% CI = 0.917 (0.755-1.113)], and TSAT [p = 0.674, OR 95% CI = 0.942 (0.713-1.244)] have no genetic causal relationship with AS. We detected no heterogeneity，horizontal pleiotropy and possible outliers in our MR analysis (p > 0.05). In addition, our MR analysis results were not affected by a single SNP, and were normally distributed.

Conclusion

Our study did not detect a genetic causal relationship between AS and iron homeostasis. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.

Hyperhomocysteinemia and intracranial aneurysm: A mendelian randomization study

Objective

To investigate the link between genetic variants associated with plasma homocysteine levels and risk of intracranial aneurysm (IA) using two-sample Mendelian randomization.

Methods

We used single-nucleotide polymorphisms associated with human plasma homocysteine levels as instrumental variables for the primary analysis in a genome-wide association study of 44,147 subjects of European ancestry. Summary-level statistics were obtained for 79,429 individuals, including 7,495 IA cases and 71,934 controls. To enhance validity, five different Mendelian randomization methods (MR-Egger, weighted median, inverse variance weighted, simple mode, and weighted mode) were used for the analyses.

Results

The inverse variance weighted analysis method produced P-values of 0.398 for aneurysmal subarachnoid hemorrhage [odds ratio (OR): 1.104; 95% confidence interval (CI): 0.878–1.387], 0.246 for IA (OR: 1.124; 95% CI: 0.923–1.368), and 0.644 for unruptured IA (OR: 1.126; 95% CI: 0.682–1.858). The MR-Egger analysis showed no association between IAs and homocysteine, with all P > 0.05.

Conclusion

Using gene-related instrumental variables, the Mendelian randomization analyses demonstrated a lack of an association between plasma homocysteine levels and IAs or aneurysmal subarachnoid hemorrhage.

Investigating the association of atopic dermatitis with ischemic stroke and coronary heart disease: A mendelian randomization study

Background: Atopic dermatitis (AD) is the most common chronic skin inflammatory disease. Prior observational studies have reported inconsistent results on the association of AD with ischemic stroke and coronary heart disease. In this study, we applied two-sample Mendelian randomization (MR) to evaluate the causal effect of AD on ischemic stroke and coronary heart disease.

Methods: Twelve single-nucleotide polymorphisms robustly associated with AD (p < 5 × 10^–8) were obtained from a genome-wide association study that included 10,788 cases and 30,047 controls by the EArly Genetics and Life course Epidemiology (EAGLE) Consortium (excluding the 23andMe study). The corresponding data for ischemic stroke (34,217 cases and 406,111 controls), large artery stroke (4,373 cases and 406,111 controls), cardioembolic stroke (7,193 cases and 406,111 controls), small vessel stroke (5,386 cases and 192,662 controls), coronary heart disease (122,733 cases and 424,528 controls), and myocardial infarction (43,676 cases and 128,199 controls) were obtained from the MR-Base platform. In the primary MR analyses, we applied the inverse variance weighted method to evaluate the associations. We performed a sensitivity analysis using weighted median, MR-Egger, weighted mode, simple mode, Mendelian Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out methods.

Results: In the primary MR analyses, we found no causal association of genetically predicted AD with ischemic stroke [odds ratio (OR) = 1.00, 95% confidence interval (CI): 0.95–1.06], large artery stroke (OR = 1.02, 95% CI: 0.88–1.17), cardioembolic stroke (OR = 1.06, 95% CI: 0.94–1.18), small vessel stroke (OR = 1.05, 95% CI: 0.94–1.17), coronary heart disease (OR = 1.00, 95% CI: 0.94–1.05), and myocardial infarction (OR = 1.03, 95% CI: 0.98–1.09). The results from the primary MR analyses were supported in sensitivity analyses using the weighted median, weighted mode, simple mode, and MR-Egger methods and multivariable MR analyses adjusting for asthma and several traditional risk factors for ischemic stroke and coronary heart disease. MR-Egger intercepts provided no evidence of directional pleiotropy. The MR-PRESSO and leave-one-out analyses did not indicate any outlier instruments.

Conclusion: Our MR study does not support a causal association of genetically predicted AD with ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke, coronary heart disease, and myocardial infarction.

Genetic Predisposition to Severe COVID-19 Might Increase the Risk of Stroke: A Two-Sample Mendelian Randomization Study

Aims: The causal relationship between COVID-19 infection and stroke has not yet been fully established. This study aimed to explore this causality using two-sample Mendelian randomization (MR).

Materials and Methods: Genetic variants associated with COVID-19 infection and stroke were both obtained from genome-wide association study (GWAS) summary data. The single nucleotide polymorphisms (SNPs) were selected as instrumental variables. The standard inverse variance weighted (IVW) was primarily used to assess this causality. Finally, sensitivity analysis was performed to evaluate the reliability and stability.

Results: The results showed that being hospitalized due to COVID-19 had a positive effect on stroke [OR = 1.05; 95% CI= (1.01, 1.10); p = 2.34 × 10⁻⁵] and ischemic stroke [OR = 1.06; 95% CI= (1.02, 1.11); p = 2.28 × 10⁻⁶] analyzed by inverse variance weighted. Moreover, the results revealed that severe respiratory symptoms due to COVID-19 had a positive effect on stroke [OR = 1.04; 95% CI= (1.00, 1.06); p = 0.04] and that the causal effect of severe respiratory symptoms due to COVID-19 on ischemic stroke estimated by IVW suggested a positive effect [OR = 1.06; 95% CI= (1.02, 1.09); p = 0.0068], too.

Conclusion: In summary, this study showed that severe COVID-19 might increase the risk of stroke, thus much more attention should be paid to patients with severe COVID-19.

Association Between Previous Stroke and Severe COVID-19: A Retrospective Cohort Study and an Overall Review of Meta-Analysis

Objective

The objective of this study was to investigate the association between previous stroke and the risk of severe coronavirus disease 2019 (COVID-19).

Methods

We included 164 (61.8 ± 13.6 years) patients with COVID-19 in a retrospective study. We evaluated the unadjusted and adjusted associations between previous stroke and severe COVID-19, using a Cox regression model. We conducted an overall review of systematic review and meta-analysis to investigate the relationship of previous stroke with the unfavorable COVID-19 outcomes.

Results

The rate of severe COVID-19 in patients with previous stroke was 28.37 per 1,000 patient days (95% confidence interval [CI]: 10.65–75.59), compared to 3.94 per 1,000 patient days (95% CI: 2.66–5.82) in those without previous stroke (p < 0.001). Previous stroke was significantly associated with severe COVID-19 using a Cox regression model (unadjusted [hazard ratio, HR]: 6.98, 95% CI: 2.42–20.16, p < 0.001; adjusted HR [per additional 10 years]: 4.62, 95% CI: 1.52–14.04, p = 0.007). An overall review of systematic review and meta-analysis showed that previous stroke was significantly associated with severe COVID-19, mortality, need for intensive care unit admission, use of mechanical ventilation, and an unfavorable composite outcome.

Conclusion

Previous stroke seems to influence the course of COVID-19 infection; such patients are at high risk of severe COVID-19 and might benefit from early hospital treatment measures and preventive strategies.

Genetically Predicted Obesity Causally Increased the Risk of Hypertension Disorders in Pregnancy

Aims

This study aimed to evaluate the causal association between obesity and hypertension disorders in pregnancy.

Methods

Two-sample Mendelian randomization (MR) study was conducted based on the data obtained from the GIANT (n = 98,697 participants) consortium and FinnGen (n = 96,449 participants) consortium to determine the causal effect of obesity on the risk of hypertension disorders in pregnancy. Based on a genome-wide significance, 14 single-nucleotide polymorphisms (SNPs) associated with obesity-related databases were used as instrumental variables. The random-effects inverse-variance weighted (IVW) method was adopted as the main analysis with a supplemented sensitive analysis of the MR-Egger and weighted median approaches.

Results

All three MR methods showed that genetically predicted obesity causally increased the risk of hypertension disorders in pregnancy. IVW analysis provided obesity as a risk factor for hypertension disorders in pregnancy with an odds ratio (OR) of 1.39 [95% confidence interval (CI) 1.21–1.59; P = 2.46 × 10⁻⁶]. Weighted median and MR Egger regression also showed directionally similar results [weighted median OR = 1.49 (95% CI, 1.24–1.79), P = 2.45 × 10⁻⁵; MR-Egger OR = 1.95 (95% CI, 1.35–2.82), P = 3.84 × 10⁻³]. No directional pleiotropic effects were found between obesity and hypertension disorders in pregnancy with both MR-Egger intercepts and funnel plots.

Conclusions

Our findings provided directed evidence that obesity was causally associated with a higher risk of hypertension disorders in pregnancy. Taking measures to reduce the proportion of obesity may help reduce the incidence of hypertension disorders in pregnancy.