Relationship Between Blood Pressure and Incident Cardiovascular Disease: Linear and Nonlinear Mendelian Randomization Analyses

Does the effect of adolescent health behaviours on adult cardiometabolic health differ by socioeconomic background? Protocol for a population-based cohort study

INTRODUCTION

Adolescence is a sensitive period for cardiometabolic health. Yet, it remains unknown if adolescent health behaviours, such as alcohol use, smoking, diet and physical activity, have differential effects across socioeconomic strata. Adopting a life-course perspective and a causal inference framework, we aim to assess whether the effects of adolescent health behaviours on adult cardiometabolic health differ by levels of neighbourhood deprivation, parental education and occupational class. Gaining a better understanding of these social disparities in susceptibility to health behaviours can inform policy initiatives that aim to improve population health and reduce socioeconomic inequalities in cardiometabolic health.

METHODS AND ANALYSIS

We will conduct a secondary analysis of the Young Finns Study, which is a longitudinal population-based cohort study. We will use measures of health behaviours-smoking, alcohol use, fruit and vegetable consumption, and physical activity-as exposure and parental education, occupational class and neighbourhood deprivation as effect modifiers during adolescence (ages 12-18 years). Eight biomarkers of cardiometabolic health (outcomes)-waist circumference, body mass index, blood pressure, low-density lipoprotein cholesterol, apolipoprotein B, plasma glucose and insulin resistance-will be measured when participants were aged 33-40. A descriptive analysis will investigate the clustering of health behaviours. Informed by this, we will conduct a causal analysis to estimate effects of single or clustered adolescent health behaviours on cardiometabolic health conditional on socioeconomic background. This analysis will be based on a causal model implemented via a directed acyclic graph and inverse probability-weighted marginal structural models to estimate effect modification.

ETHICS AND DISSEMINATION

The Young Finns study was conducted according to the guidelines of the Declaration of Helsinki, and the protocol was approved by ethics committees of University of Helsinki, Kuopio, Oulu, Tampere and Turku. We will disseminate findings at international conferences and a manuscript in an open-access peer-reviewed journal.

Non-linear association and benchmark dose of blood pressure on carotid artery intima-media thickening in a general population of southern China

Background and aims

This study aimed to evaluate whether there is a J-curve association between blood pressure (BP) and carotid artery intima-media thickening (CAIT) and estimate the effect of the turning point of BP on CAIT.

Methods and results

Data from 111,494 regular physical examinations conducted on workers and retirees (aged 18 years or older) between January 2011 and December 2016, exported from the hospital information system, were analyzed. Restricted cubic splines (RCS) logistic regression was employed to access the association of BP with CAIT, and Bayesian benchmark dose methods were used to estimate the benchmark dose as the departure point of BP measurements. All the pnon-linear values of BP measurements were less than 0.05 in the RCS logistic regression models. Both systolic blood pressure (SBP) and diastolic blood pressure (DBP) had J-curve associations with the risk of CAIT at a turning point around 120/70 mmHg in the RCS. The benchmark dose for a 1% change in CAIT risk was estimated to be 120.64 mmHg for SBP and 72.46 mmHg for DBP.

Conclusion

The J-curve associations between SBP and DBP and the risk of CAIT were observed in the general population in southern China, and the turning point of blood pressure for significantly reducing the risk of CAIT was estimated to be 120.64/72.46 mmHg for SBP/DBP.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data

BACKGROUND

Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios.

METHODS

We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning.

RESULTS

Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively.

CONCLUSIONS

By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

Mendelian randomization study of whole blood viscosity and cardiovascular diseases

AIMS

Association between whole blood viscosity (WBV) and an increased risk of cardiovascular disease (CVD) has been reported. However, the causal relationship between WBV and CVD remains not thoroughly investigated. The aim of this study was to investigate the causal relation between WBV and CVD.

METHODS

Two-sample Mendelian randomization (MR) was employed, with inverse variance weighting (IVW) as the primary method, to investigate the casual relationship between WBV and CVD. The calculated WBV and medical records of 378,210 individuals participating in the UK Biobank study were divided into halves and analyzed.

RESULTS

The means of calculated WBVs were 16.9 (standard deviation: 0.8) and 55.1 (standard deviation: 17.2) for high shear rate (HSR) and low shear rate (LSR), respectively. 37,859 (10.0%) major cardiovascular events (MACE) consisted of 23,894 (6.3%) cases of myocardial infarction (MI), 9,245 (2.4%) cases of ischemic stroke, 10,377 (2.7%) cases of revascularization, and 5,703 (1.5%) cases of coronary heart disease-related death. In the MR analysis, no evidence was found indicating a causal effect of WBV on MACE (IVW p-value for HSR = 0.81, IVW p-value for LSR = 0.47), MI (0.92, 0.83), ischemic stroke (0.52, 0.74), revascularization (0.71, 0.54), and coronary heart disease-related death (0.83, 0.70). The lack of sufficient evidence for causality persisted in other MR methods, including weighted median and MR-egger.

CONCLUSIONS

The Mendelian randomization analysis conducted in this study does not support a causal relationship between calculated WBV and CVD.

Hypertensive disorders of pregnancy and cardiovascular disease risk: a Mendelian randomisation study

OBJECTIVE

Observational studies show that hypertensive disorders of pregnancy (HDPs) are related to unfavourable maternal cardiovascular disease (CVD) risk profiles later in life. We investigated whether genetic liability to pre-eclampsia/eclampsia and gestational hypertension is associated with CVD risk factors and occurrence of CVD events.

METHODS

We obtained genetic associations with HDPs from a genome-wide association study and used individual participant data from the UK Biobank to obtain genetic associations with CVD risk factors and CVD events (defined as myocardial infarction or stroke). In our primary analysis, we applied Mendelian randomisation using inverse-variance weighted regression analysis in ever pregnant women. In sensitivity analyses, we studied men and nulligravidae to investigate genetic liability to HDPs and CVD risk without the ability to experience the underlying phenotype.

RESULTS

Our primary analysis included 221 155 ever pregnant women (mean age 56.8 (SD 7.9) years) with available genetic data. ORs for CVD were 1.20 (1.02 to 1.41) and 1.24 (1.12 to 1.38) per unit increase in the log odds of genetic liability to pre-eclampsia/eclampsia and gestational hypertension, respectively. Furthermore, genetic liability to HDPs was associated with higher levels of systolic and diastolic blood pressure and younger age at hypertension diagnosis. Sensitivity analyses revealed no statistically significant differences when comparing the findings with those of nulligravidae and men.

CONCLUSIONS

Genetic liability to HDPs is associated with higher CVD risk, lower blood pressure levels and earlier hypertension diagnosis. Our study suggests similar findings in ever pregnant women, nulligravidae and men, implying biological mechanisms relating to HDPs are causally related to CVD risk.

Association analysis between an epigenetic risk score and blood pressure

Background

Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases.

Results

We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN.

Conclusions

Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

Association analysis between an epigenetic alcohol risk score and blood pressure

Background

Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases.

Results

We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN.

Conclusions

Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

Intensive Blood Pressure Lowering in Individuals With Low Diastolic Blood Pressure and Elevated Troponin Levels in SPRINT

BACKGROUND

Among individuals with hypertension and low diastolic blood pressure (DBP), the optimal BP target remains controversial due to concerns that BP lowering may reduce coronary perfusion. We determined the impact of intensive BP control among individuals with elevated systolic BP who have low DBP and elevated hs-cTnT (high-sensitivity cardiac troponin T) levels.

METHODS AND RESULTS

A total of 8828 participants in SPRINT (Systolic Blood Pressure Intervention Trial) were stratified by baseline DBP. Those with low DBP (<70 mm Hg) were further stratified by elevated hs-cTnT (≥14 ng/L) at baseline. The effects of intensive versus standard BP lowering on a cardiovascular disease composite end point, all-cause death, and 1-year change in hs-cTnT were determined. The combination of low DBP/high hs-cTnT was independently associated with a higher risk for cardiovascular disease and all-cause death, as well as greater 1-year increases in hs-cTnT, compared with DBP ≥70 mm Hg. However, randomization to intensive versus standard BP lowering led to similar reductions in cardiovascular disease risk among individuals with low DBP/high hs-cTnT (hazard ratio [HR], 0.82 [95% CI, 0.57-1.19]), low DBP/low hs-cTnT (HR, 0.48 [95% CI, 0.29-0.79]), and DBP ≥70 mm Hg (HR, 0.73 [95% CI, 0.60-0.89]; P for interaction=0.20). Intensive BP lowering also led to a reduction in all-cause death that was similar across groups (P for interaction=0.57).

CONCLUSIONS

In this nonprespecified subgroup analysis of SPRINT, individuals with low DBP and elevated hs-cTnT, low DBP and nonelevated hs-cTnT, and DBP ≥70 mm Hg derived similar cardiovascular disease and mortality benefits from intensive BP lowering. These findings warrant confirmation in other studies.

Dementia prevention: the Mendelian randomisation perspective

Understanding the causes of Alzheimer's disease and related dementias remains a challenge. Observational studies investigating dementia risk factors are limited by the pervasive issues of confounding, reverse causation and selection biases. Conducting randomised controlled trials for dementia prevention is often impractical due to the long prodromal phase and the inability to randomise many potential risk factors. In this essay, we introduce Mendelian randomisation as an alternative approach to examine factors that may prevent or delay Alzheimer's disease. Mendelian randomisation is a causal inference method that has successfully identified risk factors and treatments in various other fields. However, applying this method to dementia risk factors has yielded unexpected findings. Here, we consider five potential explanations and provide recommendations to enhance causal inference from Mendelian randomisation studies on dementia. By employing these strategies, we can better understand factors affecting dementia risk.

Mendelian randomization studies on coronary artery disease: a systematic review and meta-analysis

BACKGROUND

Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide. We aimed to summarize what is currently known with regard to causal modifiable risk factors associated with CAD in populations of diverse ancestries through conducting a systematic review and meta-analysis of Mendelian randomization (MR) studies on CAD.

METHODS

The databases Embase, Medline, Cochrane Library and Web of Science were searched on the 19th and 20th of December 2022 for MR studies with CAD as a primary outcome; keywords of the search strategy included "coronary artery disease" and "mendelian randomization". Studies were included if they were published in the English language, included only human participants, employed Mendelian randomization as the primary methodology and studied CAD as the outcome of interest. The exclusion criteria resulted in the removal of studies that did not align with the predefined inclusion criteria, as well as studies which were systematic reviews themselves, and used the same exposure and outcome source as another study. An ancestry-specific meta-analysis was subsequently conducted on studies which investigated either body mass index, lipid traits, blood pressure or type 2 diabetes as an exposure variable. Assessment of publication bias and sensitivity analyses was conducted for risk of bias assessment in the included studies.

RESULTS

A total of 1781 studies were identified through the database searches after de-duplication was performed, with 47 studies included in the quantitative synthesis after eligibility screening. Approximately 80% of all included study participants for MR studies on CAD were of European descent irrespective of the exposure of interest, while no study included individuals of African ancestry. We found no evidence of differences in terms of direction of causation between ancestry groups; however, the strength of the respective relationships between each exposure and CAD were different, with this finding most evident when blood pressure was the exposure of interest.

CONCLUSIONS

Findings from this review suggest that patterns regarding the causational relationship between modifiable risk factors and CAD do not differ in terms of direction when compared across diverse ancestry populations. Differences in the observed strengths of the respective relationships however are indicative of the value of increasing representation in non-European populations, as novel genetic pathways or functional SNPs relating to CAD may be uncovered through a more global analysis.

SYSTEMATIC REVIEW REGISTRATION

The protocol for this systematic review was registered to the International Prospective Register of Systematic Reviews (PROSPERO) and is publicly available online (CRD42021272726).

Association between systolic blood pressure and low-density lipoprotein cholesterol with coronary heart disease according to age

BACKGROUND

The impact of elevated systolic blood pressure (SBP) and low-density lipoprotein cholesterol (LDL-C) on the risk of coronary heart disease (CHD) at different stages of life is unclear. We aimed to investigate whether genetically mediated SBP/LDL-C is associated with the risk of CHD throughout life.

METHODS AND FINDINGS

We conducted a three-sample Mendelian randomization analysis using data from the UK Biobank including 136,648 participants for LDL-C, 135,431 participants for SBP, and 24,052 cases for CHD to assess the effect of duration of exposure to the risk factors on risk of CHD. Analyses were stratified by age at enrolment. In univariable analyses, there was a consistent association between exposure to higher LDL-C and SBP with increased odds of incident CHD in individuals aged ≤55 years, ≤60 years, and ≤65 years (p-value for heterogeneity = 1.00 for LDL-C and 0.67 for SBP, respectively). In multivariable Mendelian randomization analyses, exposure to elevated LDL-C/SBP early in life (age ≤55 years) was associated with a higher risk of CHD independent of later life levels (age >55 years) (odds ratio 1.68, 95% CI 1.20-2.34 per 1 mmol/L LDL-C, and odds ratio 1.33, 95% CI 1.18-1.51 per 10 mmHg SBP).

CONCLUSIONS

Genetically predicted SBP and LDL-C increase the risk of CHD independent of age. Elevated SBP and LDL-C in early to middle life is associated with increased CHD risk independent of later-life SBP and LDL-C levels. These findings support the importance of lifelong risk factor control in young individuals, whose risk of CHD accumulates throughout life.

Blood pressure measurement and adverse pregnancy outcomes: A cohort study testing blood pressure variability and alternatives to 140/90 mmHg

OBJECTIVE

To examine the association with adverse pregnancy outcomes of: (1) American College of Cardiology/American Heart Association blood pressure (BP) thresholds, and (2) visit-to-visit BP variability (BPV), adjusted for BP level.

DESIGN

An observational study.

SETTING

Analysis of data from the population-based UK Southampton Women's Survey (SWS).

POPULATION OR SAMPLE

3003 SWS participants.

METHODS

Generalised estimating equations were used to estimate crude and adjusted relative risks (RRs) of adverse pregnancy outcomes by BP thresholds, and by BPV (as standard deviation [SD], average real variability [ARV] and variability independent of the mean [VIM]). Likelihood ratios (LRs) were calculated to evaluate diagnostic test properties, for BP at or above a threshold, compared with those below.

MAIN OUTCOME MEASURES

Gestational hypertension, severe hypertension, pre-eclampsia, preterm birth (PTB), small-for-gestational-age (SGA) infants, neonatal intensive care unit (NICU) admission.

RESULTS

A median of 11 BP measurements were included per participant. For BP at ≥20 weeks' gestation, higher BP was associated with more adverse pregnancy outcomes; however, only BP <140/90 mmHg was a good rule-out test (negative LR <0.20) for pre-eclampsia and BP ≥140/90 mmHg a good rule-in test (positive LR >8.00) for the condition. BP ≥160/110 mmHg could rule-in PTB, SGA infants and NICU admission (positive LR >5.0). Higher BPV (by SD, ARV, or VIM) was associated with gestational hypertension, severe hypertension, pre-eclampsia, PTB, SGA and NICU admission (adjusted RRs 1.05-1.39).

CONCLUSIONS

While our findings do not support lowering the BP threshold for pregnancy hypertension, they suggest BPV could be useful to identify elevated risk of adverse outcomes.

Influence of Baseline Diastolic Blood Pressure on the Effects of Intensive Blood Pressure Lowering: Results From the STEP Randomized Trial

BACKGROUND

The STEP (Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients) trial demonstrated that intensive systolic blood pressure (SBP) lowering has cardiovascular benefits. However, the influence of baseline diastolic blood pressure (DBP) on the effects of intensive blood pressure lowering on cardiovascular outcomes has not been fully elucidated.

METHODS

We performed a post hoc analysis of the STEP trial. Participants were randomly allocated to intensive (110 to <130 mm Hg) or standard (130 to <150 mm Hg) treatment groups. The effects of intensive SBP lowering on the primary composite outcome (stroke, acute coronary syndrome, acute decompensated heart failure, coronary revascularization, atrial fibrillation, and cardiovascular death), major adverse cardiac event (a composite of the individual components of the primary outcome except for stroke), and all-cause mortality were analyzed according to baseline DBP as both a categorical and a continuous variable.

RESULTS

The 8259 participants had a mean age of 66.2±4.8 years, and 46.5% were men. Participants with lower DBP were slightly older and had greater histories of cardiovascular disease, diabetes, and hyperlipidemia. Within each baseline DBP quartile, the mean achieved DBP was lower in the intensive versus standard group. The effects of intensive SBP lowering were not modified by baseline DBP as a continuous variable or as a categorical variable (quartiles, or <70, 70 to <80, and ≥80 mm Hg; all P value for interaction >0.05).

CONCLUSIONS

The beneficial effects of intensive SBP lowering on cardiovascular outcomes were unaffected by baseline DBP. Lower DBP should not be an obstacle to intensive SBP control.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03015311.

Hypertensive disorders of pregnancy and cardiovascular disease risk: A Mendelian Randomisation study

Objective

Observational studies show that hypertensive disorders of pregnancy (HDPs) are related to unfavourable maternal cardiovascular disease (CVD) risk profiles later in life. We investigated whether genetic liability to pre-eclampsia/eclampsia and gestational hypertension is associated with CVD risk factors and occurrence of CVD events.

Methods

We obtained genetic associations with HDPs from a genome-wide association study and used individual-participant-data from the UK Biobank to obtain genetic associations with CVD risk factors and CVD events (defined as myocardial infarction or stroke). In our primary analysis, we applied Mendelian Randomisation using inverse-variance weighted regression analysis in ever pregnant women. In sensitivity analyses, we studied men and nulligravidae to investigate genetic liability to HDPs and CVD risk without the ability to experience the underlying phenotype.

Results

Our primary analysis included 221,155 ever pregnant women (mean age 56.8 [SD 7.9]) with available genetic data. Odds ratios for CVD were 1.20 (1.02-1.41) and 1.24 (1.12-1.38) per unit increase in the log odds of genetic liability to pre-eclampsia/eclampsia and gestational hypertension, respectively. Furthermore, genetic liability to HDPs was associated with higher levels of systolic and diastolic blood pressure and younger age at hypertension diagnosis. Sensitivity analyses revealed no statistically significant differences when comparing the findings to those of nulligravidae and men.

Conclusions

Genetic liability to HDPs is associated with higher CVD risk, lower blood pressure levels, and earlier hypertension diagnosis. Our study suggests similar findings in ever pregnant women, nulligravidae and men, implying biological mechanisms relating to HDPs are causally related to CVD risk.

Poor sleep and shift work associate with increased blood pressure and inflammation in UK Biobank participants

Disrupted circadian rhythms have been linked to an increased risk of hypertension and cardiovascular disease. However, many studies show inconsistent findings and are not sufficiently powered for targeted subgroup analyses. Using the UK Biobank cohort, we evaluate the association between circadian rhythm-disrupting behaviours, blood pressure (SBP, DBP) and inflammatory markers in >350,000 adults with European white British ancestry. The independent U-shaped relationship between sleep length and SBP/DBP is most prominent with a low inflammatory status. Poor sleep quality and permanent night shift work are also positively associated with SBP/DBP. Although fully adjusting for BMI in the linear regression model attenuated effect sizes, these associations remain significant. Two-sample Mendelian Randomisation (MR) analyses support a potential causal effect of long sleep, short sleep, chronotype, daytime napping and sleep duration on SBP/DBP. Thus, in the current study, we present a positive association between circadian rhythm-disrupting behaviours and SBP/DBP regulation in males and females that is largely independent of age.

Elevated blood pressure accelerates white matter brain aging among late middle-aged women: a Mendelian Randomization study in the UK Biobank

BACKGROUND

Elevated blood pressure (BP) is a modifiable risk factor associated with cognitive impairment and cerebrovascular diseases. However, the causal effect of BP on white matter brain aging remains unclear.

METHODS

In this study, we focused on N  = 228 473 individuals of European ancestry who had genotype data and clinical BP measurements available (103 929 men and 124 544 women, mean age = 56.49, including 16 901 participants with neuroimaging data available) collected from UK Biobank (UKB). We first established a machine learning model to compute the outcome variable brain age gap (BAG) based on white matter microstructure integrity measured by fractional anisotropy derived from diffusion tensor imaging data. We then performed a two-sample Mendelian randomization analysis to estimate the causal effect of BP on white matter BAG in the whole population and subgroups stratified by sex and age brackets using two nonoverlapping data sets.

RESULTS

The hypertension group is on average 0.31 years (95% CI = 0.13-0.49; P  < 0.0001) older in white matter brain age than the nonhypertension group. Women are on average 0.81 years (95% CI = 0.68-0.95; P  < 0.0001) younger in white matter brain age than men. The Mendelian randomization analyses showed an overall significant positive causal effect of DBP on white matter BAG (0.37 years/10 mmHg, 95% CI 0.034-0.71, P  = 0.0311). In stratified analysis, the causal effect was found most prominent among women aged 50-59 and aged 60-69.

CONCLUSION

High BP can accelerate white matter brain aging among late middle-aged women, providing insights on planning effective control of BP for women in this age group.

Long-term blood pressure patterns in midlife and dementia in later life: Findings from the Framingham Heart Study

INTRODUCTION

Long-term blood pressure (BP) measures, such as visit-to-visit BP variability (BPV) and cumulative BP, are strong indicators of cardiovascular risks. This study modeled up to 20 years of BP patterns representative of midlife by using BPV and cumulative BP, then examined their associations with development of dementia in later life.

METHODS

For 3201 individuals from the Framingham Heart Study, multivariate logistic regression analyses were performed to examine the association between long-term BP patterns during midlife and the development of dementia (ages ≥ 65).

RESULTS

After adjusting for covariates, every quartile increase in midlife cumulative BP was associated with a sequential increase in the risk of developing dementia (e.g., highest quartile of cumulative systolic blood pressure had approximately 2.5-fold increased risk of all-cause dementia). BPV was not significantly associated with dementia.

DISCUSSION

Findings suggest that cumulative BP over the course of midlife predicts risk of dementia in later life. HIGHLIGHTS Long-term blood pressure (BP) patterns are strong indicators of vascular risks. Cumulative BP and BP variability (BPV) were used to reflect BP patterns across midlife. High cumulative BP in midlife is associated with increased dementia risk. Visit-to-visit BPV was not associated with the onset of dementia.

Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases

OBJECTIVE

To scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the two methods have distinct assumptions that make comparisons between their results invaluable.

METHODS

We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.

RESULTS

We found that only 13% of completed RCTs identified in ClinicalTrials.Gov submitted their results to the database. Similarly low coverage was revealed for Semantic Medline (SemMedDB) semantic triples derived from MR and RCT publications -36% and 12%, respectively. Among intervention types that can be mimicked by MR, only trials of pharmaceutical interventions could be automatically matched to MR results due to insufficient annotation with Medical Subject Headings ontology. A manual survey of the literature highlighted the potential for triangulation across a number of exposure/outcome pairs if these challenges can be addressed.

CONCLUSIONS

We conclude that careful triangulation of MR with RCT evidence should involve consideration of similarity of phenotypes across study designs, intervention intensity and duration, study population demography and health status, comparator group, intervention goal and quality of evidence.

Value of blood lipid in predicting graft dysfunction after organ and tissue transplantation: A study of Mendelian randomization

Background

While immunosuppressive regimens have improved outcomes in solid organ transplantation, non-immune factors have also been identified as contributors to graft prognosis. Age, gender, hormones, heredity, and other diseases have been recognized to affect organ transplantation. However, the causal relationship between blood lipids and graft dysfunction remains unverified in human clinical investigations. In this study, we employed two-sample Mendelian randomization (MR) to examine the causality between different types of blood lipids and graft dysfunction following organ and tissue transplantation.

Methods

We conducted a two-sample MR study using available genome-wide association summary data from the online database MRBASE (http://app.mrbase.org/), which encompasses over 11 billion associations between genetic factors and health-related outcomes, enabling researchers to explore various potential determinants of poor health. The exposure factors included four types of blood lipids: high-density lipoprotein, low-density lipoprotein, cholesterol, and triglycerides. For each exposure factor, three databases were selected for analysis. The outcome factor was the failure and rejection of transplanted organs and tissues. All databases consisted of European population samples, without specific subgroups. The related studies were conducted between 2016 and 2022, and the "TwoSampleMR" R package was employed for variant selection.

Results

A total of 13 sample groups were collected and analyzed. The results revealed a causal association between blood lipids and graft dysfunction following organ and tissue transplantation. Specifically, the two-sample MR analysis confirmed that low-density lipoprotein and cholesterol levels were significant risk factors for increased graft dysfunction risk after transplantation. Moreover, high-density lipoprotein potentially reduced the risk of allograft dysfunction, while triglycerides possibly elevated the risk.

Conclusions

Our recent study provides the initial confirmation that blood lipids may initiate causal pathological processes leading to graft dysfunction after organ and tissue transplantation.

Deciphering the causal relationship between blood pressure and regional white matter integrity: A two-sample Mendelian randomization study

Elevated arterial blood pressure (BP) is a common risk factor for cerebrovascular and cardiovascular diseases, but no causal relationship has been established between BP and cerebral white matter (WM) integrity. In this study, we performed a two-sample Mendelian randomization (MR) analysis with individual-level data by defining two nonoverlapping sets of European ancestry individuals (genetics-exposure set: N = 203,111; mean age = 56.71 years, genetics-outcome set: N = 16,156; mean age = 54.61 years) from UK Biobank to evaluate the causal effects of BP on regional WM integrity, measured by fractional anisotropy of diffusion tensor imaging. Two BP traits: systolic and diastolic blood pressure were used as exposures. Genetic variant was carefully selected as instrumental variable (IV) under the MR analysis assumptions. We existing large-scale genome-wide association study summary data for validation. The main method used was a generalized version of inverse-variance weight method while other MR methods were also applied for consistent findings. Two additional MR analyses were performed to exclude the possibility of reverse causality. We found significantly negative causal effects (FDR-adjusted p < .05; every 10 mmHg increase in BP leads to a decrease in FA value by .4% ~ 2%) of BP traits on a union set of 17 WM tracts, including brain regions related to cognitive function and memory. Our study extended the previous findings of association to causation for regional WM integrity, providing insights into the pathological processes of elevated BP that might chronically alter the brain microstructure in different regions.

Violation of the Constant Genetic Effect Assumption Can Result in Biased Estimates for Non-Linear Mendelian Randomization

INTRODUCTION

Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice.

METHODS

We use the recently developed doubly ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D (25[OH]D) used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality.

RESULTS

The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method but not for the doubly ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures and less reasonable for others. If the doubly ranked method indicates that this assumption is violated, then estimates from both the residual and doubly ranked methods can be biased, although bias was smaller on average in the doubly ranked method.

CONCLUSION

Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly ranked methods, as well as consider transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.

Sex-specific Mendelian randomisation to assess the causality of sex differences in the effects of risk factors and treatment: spotlight on hypertension

Hypertension is a key modifiable risk factor for cardiovascular disease. Several observational studies have found a stronger association of blood pressure and cardiovascular disease risk in women compared to men. Since observational studies can be affected by sex-specific residual confounding and reverse causation, it remains unclear whether these differences reflect actual differential effects. Other study designs are needed to uncover the causality of sex differences in the strength of risk factor and treatment effects. Mendelian randomisation (MR) uses genetic variants as instrumental variables to provide evidence about putative causal relations between risk factors and outcomes. By exploiting the random allocation of genes at gamete forming, MR is unaffected by confounding and results in more reliable causal effect estimates. In this review, we discuss why and how sex-specific MR and cis-MR could be used to study sex differences in risk factor and drug target effects. Sex-specific MR can be helpful to strengthen causal inferences in the field of sex differences, where it is often challenging to distinguish nature from nurture. The challenge of sex-specific (drug target) MR lays in leveraging robust genetic instruments from sex-specific GWAS studies which are not commonly available. Knowledge on sex-specific causal effects of hypertension, or other risk factors, could improve clinical practice and health policies by tailoring interventions based on personalised risk. Drug target MR can help to determine the anticipated on-target effects of a drug compound and to identify targets to pursue in drug development.

Air Pollution, Built Environment, and Early Cardiovascular Disease

As the world's population becomes increasingly urbanized, there is growing concern about the impact of urban environments on cardiovascular health. Urban residents are exposed to a variety of adverse environmental exposures throughout their lives, including air pollution, built environment, and lack of green space, which may contribute to the development of early cardiovascular disease and related risk factors. While epidemiological studies have examined the role of a few environmental factors with early cardiovascular disease, the relationship with the broader environment remains poorly defined. In this article, we provide a brief overview of studies that have examined the impact of the environment including the built physical environment, discuss current challenges in the field, and suggest potential directions for future research. Additionally, we highlight the clinical implications of these findings and propose multilevel interventions to promote cardiovascular health among children and young adults.

Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification method

Non-linear Mendelian randomization is an extension to standard Mendelian randomization to explore the shape of the causal relationship between an exposure and outcome using an instrumental variable. A stratification approach to non-linear Mendelian randomization divides the population into strata and calculates separate instrumental variable estimates in each stratum. However, the standard implementation of stratification, referred to as the residual method, relies on strong parametric assumptions of linearity and homogeneity between the instrument and the exposure to form the strata. If these stratification assumptions are violated, the instrumental variable assumptions may be violated in the strata even if they are satisfied in the population, resulting in misleading estimates. We propose a new stratification method, referred to as the doubly-ranked method, that does not require strict parametric assumptions to create strata with different average levels of the exposure such that the instrumental variable assumptions are satisfied within the strata. Our simulation study indicates that the doubly-ranked method can obtain unbiased stratum-specific estimates and appropriate coverage rates even when the effect of the instrument on the exposure is non-linear or heterogeneous. Moreover, it can also provide unbiased estimates when the exposure is coarsened (that is, rounded, binned into categories, or truncated), a scenario that is common in applied practice and leads to substantial bias in the residual method. We applied the proposed doubly-ranked method to investigate the effect of alcohol intake on systolic blood pressure, and found evidence of a positive effect of alcohol intake, particularly at higher levels of alcohol consumption.

Using genetic association data to guide drug discovery and development: Review of methods and applications

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

A genomic deep field view of hypertension

Blood pressure is regulated by a complex neurohumoral system including the renin-angiotensin-aldosterone system, natriuretic peptides, endothelial pathways, the sympathetic nervous system, and the immune system. This review charts the evolution of our understanding of the genomic basis of hypertension at increasing resolution over the last 5 decades from monogenic causes to polygenic associations, spanning ∼30 monogenic rare variants and >1500 single nucleotide variants. Unexpected early wins from blood pressure genomics include deepening of our understanding of the complex causation of hypertension; refinement of causal estimates bidirectionally between blood pressure, risk factors, and outcomes through Mendelian randomization; risk stratification using polygenic risk scores; and opportunities for precision medicine and drug repurposing.

Answering Clinical Questions Using Machine Learning: Should We Look at Diastolic Blood Pressure When Tailoring Blood Pressure Control?

Background: The guidelines recommend intensive blood pressure control. Randomized trials have focused on the relevance of the systolic blood pressure (SBP) lowering, leaving the safety of the diastolic blood pressure (DBP) reduction unresolved. There are data available which show that low DBP should not stop clinicians from achieving SBP targets; however, registries and analyses of randomized trials present conflicting results. The purpose of the study was to apply machine learning (ML) algorithms to determine, whether DBP is an important risk factor to predict stroke, heart failure (HF), myocardial infarction (MI), and primary outcome in the SPRINT trial database. Methods: ML experiments were performed using decision tree, random forest, k-nearest neighbor, naive Bayesian, multi-layer perceptron, and logistic regression algorithms, including and excluding DBP as the risk factor in an unselected and selected (DBP < 70 mmHg) study population. Results: Including DBP as the risk factor did not change the performance of the machine learning models evaluated using accuracy, AUC, mean, and weighted F-measure, and was not required to make proper predictions of stroke, MI, HF, and primary outcome. Conclusions: Analyses of the SPRINT trial data using ML algorithms imply that DBP should not be treated as an independent risk factor when intensifying blood pressure control.

Association of a Multiancestry Genome-Wide Blood Pressure Polygenic Risk Score With Adverse Cardiovascular Events

BACKGROUND

Traditional cardiovascular risk factors and the underlying genetic risk of elevated blood pressure (BP) determine an individual's composite risk of developing adverse cardiovascular events. We sought to evaluate the relative contributions of the traditional cardiovascular risk factors to the development of adverse cardiovascular events in the context of varying BP genetic risk profiles.

METHODS

Genome-wide polygenic risk score (PRS) was computed using multiancestry genome-wide association estimates among US adults who underwent whole-genome sequencing in the Trans-Omics for Precision program. Individuals were stratified into high, intermediate, and low genetic risk groups (>80th, 20-80th, and <20th centiles of systolic BP [SBP] PRS). Based on the ACC/AHA Pooled Cohort Equations, participants were stratified into low and high (10 year-atherosclerotic cardiovascular disease [CVD] risk: <10% or ≥10%) cardiovascular risk factor profile groups. The primary study outcome was incident cardiovascular event (composite of incident heart failure, incident stroke, and incident coronary heart disease).

RESULTS

Among 21 897 US adults (median age: 56 years; 56.0% women; 35.8% non-White race/ethnicity), 1 SD increase in the SBP PRS, computed using 1.08 million variants, was associated with SBP (β: 4.39 [95% CI, 4.13-4.65]) and hypertension (odds ratio, 1.50 [95% CI, 1.46-1.55]), respectively. This association was robustly seen across racial/ethnic groups. Each SD increase in SBP PRS was associated with a higher risk of the incident CVD (multivariable-adjusted hazards ratio, 1.07 [95% CI, 1.04-1.10]) after controlling for ACC/AHA Pooled Cohort Equations risk scores. Among individuals with a high SBP PRS, low atherosclerotic CVD risk was associated with a 58% lower hazard for incident CVD (multivariable-adjusted hazards ratio, 0.42 [95% CI, 0.36-0.50]) compared to those with high atherosclerotic CVD risk. A similar pattern was noted in intermediate and low genetic risk groups.

CONCLUSIONS

In a multiancestry cohort of >21 000 US adults, genome-wide SBP PRS was associated with BP traits and adverse cardiovascular events. Adequate control of modifiable cardiovascular risk factors may reduce the predisposition to adverse cardiovascular events among those with a high SBP PRS.

The Causal Effect of Systolic Blood Pressure Lowering on Vascular Outcomes in Diabetes: A Mendelian Randomization Study

CONTEXT

The effect of lowering systolic blood pressure (SBP) on clinical outcomes in diabetic patients is controversial.

OBJECTIVE

We used 2-sample mendelian randomization (MR) to study the causal effect of decreasing SBP on the risk of macrovascular and microvascular outcomes in diabetic patients.

METHODS

We used 362 SBP-related genetic variants from a large genome-wide association study (n = 299 024) and UK Biobank (n = 375 256) as exposure. We evaluated 5 macrovascular and microvascular complications up to 60 742 cases as outcomes in diabetes, including coronary artery disease (CAD), peripheral artery disease (PAD), nephropathy, retinopathy, and composite complications. All cases were diagnosed together with diabetes. We performed follow-up analyses by conducting 7 sensitivity analyses and comparing the present MR with results in general population, and clinical trials.

RESULTS

Genetic predisposition of each 10-mm Hg SBP decrease was significantly associated with a 28% decreased risk of CAD (odds ratio [OR]: 0.72; 95% CI, 0.59-0.89; P = .002), a 34% decreased risk of nephropathy (OR: 0.66; 95% CI, 0.54-0.81; P < .001), and a 34% decreased risk of the composite complications (OR: 0.66; 95% CI, 0.58-0.76; P < .001), and was nominally associated with a decreased risk of PAD (OR: 0.69; 95% CI, 0.48-0.99) and retinopathy (OR: 0.90; 95% CI, 0.81-0.99). The MR results in diabetes were similar with that in the general population and clinical trials.

CONCLUSION

SBP lowering was causally associated with an attenuated risk of diabetic CAD and nephropathy. It provides genetic evidence for the beneficial effect of lifelong SBP control in preventing diabetes-related vascular outcomes.

Unravelling the Distinct Effects of Systolic and Diastolic Blood Pressure Using Mendelian Randomisation

A true discrepancy between the effect of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on cardiovascular (CV) outcomes remains unclear. This study performed two-sample Mendelian randomization (MR) using genetic instruments that exclusively predict SBP, DBP or both to dissect the independent effect of SBP and DBP on a range of CV outcomes. Genetic predisposition to higher SBP and DBP was associated with increased risk of coronary artery disease (CAD), myocardial infarction (MI), stroke, heart failure (HF), atrial fibrillation (AF), chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Genetically proxied SBP exclusively was associated with CAD (OR 1.18, 95% CI: 1.03–1.36, per 10 mmHg), stroke (1.44[1.28–1.62]), ischemic stroke (1.49[1.30–1.69]), HF (1.41[1.20–1.65]), AF (1.28[1.15–1.43]), and T2DM (1.2[1.13–1.46]). Genetically proxied DBP exclusively was associated with stroke (1.21[1.06–1.37], per 5 mmHg), ischemic stroke (1.24[1.09–1.41]), stroke small-vessel (1.35[1.10–1.65]) and CAD (1.19[1.00–1.41]). Multivariable MR using exclusive SBP and DBP instruments showed the predominant effect of SBP on CAD (1.23[1.05–1.44], per 10 mmHg), stroke (1.39[1.20–1.60]), ischemic stroke (1.44[1.25–1.67]), HF (1.42[1.18–1.71]), AF (1.26[1.10–1.43]) and T2DM (1.31[1.14–1.52]). The discrepancy between effects of SBP and DBP on outcomes warrants further studies on underpinning mechanisms which may be amenable to therapeutic targeting.

Avoiding collider bias in Mendelian randomization when performing stratified analyses

Mendelian randomization (MR) uses genetic variants as instrumental variables to investigate the causal effect of a risk factor on an outcome. A collider is a variable influenced by two or more other variables. Naive calculation of MR estimates in strata of the population defined by a collider, such as a variable affected by the risk factor, can result in collider bias. We propose an approach that allows MR estimation in strata of the population while avoiding collider bias. This approach constructs a new variable, the residual collider, as the residual from regression of the collider on the genetic instrument, and then calculates causal estimates in strata defined by quantiles of the residual collider. Estimates stratified on the residual collider will typically have an equivalent interpretation to estimates stratified on the collider, but they are not subject to collider bias. We apply the approach in several simulation scenarios considering different characteristics of the collider variable and strengths of the instrument. We then apply the proposed approach to investigate the causal effect of smoking on bladder cancer in strata of the population defined by bodyweight. The new approach generated unbiased estimates in all the simulation settings. In the applied example, we observed a trend in the stratum-specific MR estimates at different bodyweight levels that suggested stronger effects of smoking on bladder cancer among individuals with lower bodyweight. The proposed approach can be used to perform MR studying heterogeneity among subgroups of the population while avoiding collider bias.

Polynomial Mendelian randomization reveals non-linear causal effects for obesity-related traits

Causal inference is a critical step in improving our understanding of biological processes, and Mendelian randomization (MR) has emerged as one of the foremost methods to efficiently interrogate diverse hypotheses using large-scale, observational data from biobanks. Although many extensions have been developed to address the three core assumptions of MR-based causal inference (relevance, exclusion restriction, and exchangeability), most approaches implicitly assume that any putative causal effect is linear. Here, we propose PolyMR, an MR-based method that provides a polynomial approximation of an (arbitrary) causal function between an exposure and an outcome. We show that this method provides accurate inference of the shape and magnitude of causal functions with greater accuracy than existing methods. We applied this method to data from the UK Biobank, testing for effects between anthropometric traits and continuous health-related phenotypes, and found most of these (84%) to have causal effects that deviate significantly from linear. These deviations ranged from slight attenuation at the extremes of the exposure distribution, to large changes in the magnitude of the effect across the range of the exposure (e.g., a 1 kg/m² change in BMI having stronger effects on glucose levels if the initial BMI was higher), to non-monotonic causal relationships (e.g., the effects of BMI on cholesterol forming an inverted U shape). Finally, we show that the linearity assumption of the causal effect may lead to the misinterpretation of health risks at the individual level or heterogeneous effect estimates when using cohorts with differing average exposure levels.

Genome-wide meta-analysis of iron status biomarkers and the effect of iron on all-cause mortality in HUNT

Iron is essential for many biological processes, but iron levels must be tightly regulated to avoid harmful effects of both iron deficiency and overload. Here, we perform genome-wide association studies on four iron-related biomarkers (serum iron, serum ferritin, transferrin saturation, total iron-binding capacity) in the Trøndelag Health Study (HUNT), the Michigan Genomics Initiative (MGI), and the SardiNIA study, followed by their meta-analysis with publicly available summary statistics, analyzing up to 257,953 individuals. We identify 123 genetic loci associated with iron traits. Among 19 novel protein-altering variants, we observe a rare missense variant (rs367731784) in HUNT, which suggests a role for DNAJC13 in transferrin recycling. We further validate recently published results using genetic risk scores for each biomarker in HUNT (6% variance in serum iron explained) and present linear and non-linear Mendelian randomization analyses of the traits on all-cause mortality. We find evidence of a harmful effect of increased serum iron and transferrin saturation in linear analyses that estimate population-averaged effects. However, there was weak evidence of a protective effect of increasing serum iron at the very low end of its distribution. Our findings contribute to our understanding of the genes affecting iron status and its consequences on human health.

A GWAS on the four major iron-related biomarkers is conducted using data from the Trøndelag Health Study (HUNT), Michigan Genomics Initiative (MGI), and SardiNIA study, to identify 123 loci associated with iron homeostasis and effect on all-cause mortality.

Nonlinear causal effects of estimated glomerular filtration rate on myocardial infarction risks: Mendelian randomization study

BACKGROUND

Previous observational studies suggested that a reduction in estimated glomerular filtration rate (eGFR) or a supranormal eGFR value was associated with adverse cardiovascular risks. However, a previous Mendelian randomization (MR) study under the linearity assumption reported null causal effects from eGFR on myocardial infarction (MI) risks. Further investigation of the nonlinear causal effect of kidney function assessed by eGFR on the risk of MI by nonlinear MR analysis is warranted.

METHODS

In this MR study, genetic instruments for log-eGFR based on serum creatinine were developed from European samples included in the CKDGen genome-wide association study (GWAS) meta-analysis (N=567,460). Alternate instruments for log-eGFR based on cystatin C were developed from a GWAS of European individuals that included the CKDGen and UK Biobank data (N=460,826). Nonlinear MR analysis for the risk of MI was performed using the fractional polynomial method and the piecewise linear method on data from individuals of white British ancestry in the UK Biobank (N=321,024, with 12,205 MI cases).

RESULTS

Nonlinear MR analysis demonstrated a U-shaped (quadratic P value < 0.001) association between MI risk and genetically predicted eGFR (creatinine) values, as MI risk increased as eGFR declined in the low eGFR range and the risk increased as eGFR increased in the high eGFR range. The results were similar even after adjustment for clinical covariates, such as blood pressure, diabetes mellitus, dyslipidemia, or urine microalbumin levels, or when genetically predicted eGFR (cystatin C) was included as the exposure.

CONCLUSION

Genetically predicted eGFR is significantly associated with the risk of MI with a parabolic shape, suggesting that kidney function impairment, either by reduced or supranormal eGFR, may be causally linked to a higher MI risk.

Kidney stone disease and cardiovascular events: a study on bidirectional causality based on mendelian randomization

Background

Kidney stone disease (KSD) has been reported to be associated with several cardiovascular diseases. However, the causality between the conditions remains unknown. In the study, we performed a study on bidirectional causality by two-sample Mendelian randomization (MR) to investigate the causality between KSD and cardiovascular diseases including coronary atherosclerosis, hypertension, and cardiomyopathy.

Methods

In the recent study, we performed a bidirectional two-sample MR study using available genome-wide association summary data from the online database MRBASE. We identified genetic variants associated with KSD in one European population from UK Biobank (version 2, n=462,933). Two phenotypes of samples were chosen from the population to define our genetic instrumental variables: (I) samples with the phenotype of kidney stone/ureter stone/bladder stone (ukb-b-8297), and (II) samples with the phenotype of kidney stone surgery/lithotripsy (ukb-b-13537). For cardiovascular diseases, we picked up another independent European population from FinnGen Biobank (n=93,421). We selected the exposure and outcome SNPs and then performed the two-sample MR using R package.

Results

After bidirectional causality by two-sample MR, we verified that genetic predisposition to KSD could increase the risk of coronary atherosclerosis (OR: 4.45×1037; SE=±7.80×10¹⁴, P for MR-Egger =0.024) and cardiomyopathy (OR: 5.35×10¹³; SE=±7.18×10⁶, P for IVW=0.045 for finn-a-I9_CARDMYO, and OR: 3.60×10²⁵; SE=±3.26×10¹², P for IVW=0.041 for finn-a-I9_CARDMYOOTH) when we used ukb-b-13537 as exposure group. Furthermore, hypertension could increase the risk of KSD (OR: 1.001; SE=±1.00, P for IVW=0.003) when we used ukb-b-8297 as exposure group, without detected pleiotropy bias (P>0.05).

Conclusions

We confirmed KSD may trigger causal pathological processes including coronary atherosclerosis and cardiomyopathy. Furthermore, hypertension may causally affect KSD.

No causal effect of tea consumption on cardiovascular diseases: A two-sample Mendelian randomization study

Background

Numerous studies have been conducted to investigate the relationship between tea consumption and the risk of cardiovascular diseases (CVD); however, no conclusive results have been achieved. We conducted a Mendelian randomization (MR) study to elucidate the causal associations between tea consumption and several CVD outcomes, including coronary artery disease (CAD), myocardial infarction (MI), atrial fibrillation (AF), and heart failure (HF).

Methods

Independent single-nucleotide polymorphisms (SNPs) genome-wide significantly associated with tea consumption were used as instrumental variables (IVs). Summary statistics for CVD outcomes were obtained from the corresponding genetic consortia and the FinnGen consortium. The inverse-variance weighted (IVW) method was the primary analytical method, and MR estimates from different data sources were combined using fixed-effects meta-analysis. Supplementary MR analyses, including the weighted median, MR-Egger, and the MR pleiotropy residual sum and outlier methods, were conducted to evaluate the robustness of the results. Further MR analyses were repeated by including more genetic variants at a higher P-value threshold.

Results

We found that genetically predicted tea consumption was not causally associated with any CVD outcomes in the IVW method using data from large genetic consortia [CAD: odds ratio (OR) = 1.00, 95% confidence interval (CI), 0.91, 1.10, P = 0.997; MI: OR = 0.98, 95% CI, 0.90, 1.08, P = 0.751; AF: OR = 0.97, 95% CI, 0.92, 1.03, P = 0.350; HF: OR = 0.96, 95% CI, 0.88, 1.05, P = 0.401] or the FinnGen consortium (CAD: OR = 1.06, 95% CI, 0.96, 1.17, P = 0.225; MI: OR = 1.01, 95% CI, 0.89, 1.15, P = 0.882; AF: OR = 1.00, 95% CI, 0.88, 1.14, P = 0.994; HF: OR = 0.96, 95% CI, 0.88, 1.04, P = 0.362). The results were robust and consistent across meta-analysis, supplementary MR analyses, and analyses with more IVs included.

Conclusion

This MR study revealed no causal association between tea consumption and four CVD outcomes, suggesting that tea consumption may not be beneficial for the primary prevention of CVD.

Systolic blood pressure as the mediator of the effect of early menarche on the risk of coronary artery disease: A Mendelian randomization study

Background

Menarche timing may not be directly associated with the risk of coronary artery disease (CAD). Therefore, we investigated the roles of metabolic factors in explaining the effect of age at menarche on CAD risk.

Methods

We identified women with age at menarche and CAD by using three analytical methods: Mendelian randomization (MR), logistic regression analysis, and Cox proportional hazard regression. The first two analyses were performed in the Taiwan Biobank (N = 71,923) study, and the last analysis was performed in the Chin-Shan Community Cardiovascular Cohort study (N = 1,598). We further investigated the role of metabolic factors in mediating the effect of age at menarche on CAD risk by using three complementary methods with mediation analyses.

Results

One standard deviation of earlier age at menarche was associated with a 2% higher CAD risk [odds ratio = 1.02, 95% confidence interval (CI) = 1.001-1.03] in the MR analysis, an 11% higher risk (odds ratio = 1.11, 95% CI = 1.02-1.21) in the logistic regression analysis, and a 57% higher risk (hazard ratio = 1.57, 95% CI = 1.12-2.19) in the Cox proportional hazard regression. All the analyses consistently supported the role of systolic blood pressure in mediating this effect. The MR results indicated that 29% (95% CI = 26%-32%) of the effect of genetically predicted earlier age at menarche on CAD risk was mediated by genetically predicted systolic blood pressure.

Conclusion

The results obtained using different analytical methods suggest that interventions aimed at lowering systolic blood pressure can reduce the cases of CAD attributable to earlier age at menarche.

Individual and Combined Cardiometabolic Morbidities and the Subsequent Risk of Cardiovascular Events in Chinese Adults

CONTEXT

Diabetes, hypertension and dyslipidemia accelerates the incidence of cardiovascular disease (CVD) events. However, data regarding the association between main cardiometabolic morbidities such as diabetes, hypertension, and dyslipidemia and the subsequent risk of CVD events in Chinese adults are still limited.

OBJECTIVE

To investigate the associations between individual and combined cardiometabolic morbidities and incident cardiovascular events in Chinese adults.

METHODS

Baseline data were obtained from a prospective, nationwide, and population-based cohort study in China during 2011-2012. A total of 133 572 participants aged ≥40 years were included in the study. The main outcome measures were CVD events.

RESULTS

Compared with participants without diabetes, hypertension and dyslipidemia, participants with only diabetes (hazard ratio [HR], 1.58; 95% CI, 1.32-1.90) or only hypertension (2.04; 1.82-2.28) exhibited significantly higher risk for CVD events, while participants with only dyslipidemia (0.97; 0.84-1.12) exhibited no significantly higher risk for CVD events. When analyzed collectively, participants with diabetes plus hypertension (HR, 2.67; 95% CI, 2.33-3.06), diabetes plus dyslipidemia (1.57; 1.32-1.87), and hypertension plus dyslipidemia (2.12; 1.88-2.39) exhibited significantly higher risk for CVD. Moreover, participants with the combination of diabetes, hypertension, and dyslipidemia exhibited the highest risk for CVD events (HR, 3.06; 95% CI, 2.71-3.46). Multivariable-adjusted HRs (95% CIs) for CVD associated with diabetes based on fasting glucose ≥7.0 mmol/L, oral glucose tolerance test 2-hour glucose ≥11.1 mmol/L, and hemoglobin A1c ≥6.5% were 1.64 (1.51-1.78), 1.57 (1.45-1.69), and 1.54 (1.42-1.66), respectively; associated with hypertension based on systolic blood pressure ≥140 mmHg and diastolic blood pressure ≥90 mmHg were 1.89 (1.76-2.03) and 1.74 (1.60-1.88), respectively; associated with dyslipidemia based on total cholesterol ≥6.22 mmol/L, low-density lipoprotein cholesterol ≥4.14 mmol/L, high-density lipoprotein cholesterol <1.04 mmol/L, and triglycerides ≥2.26 mmol/L were 1.18 (1.08-1.30), 1.30 (1.17-1.44), 1.00 (0.92-1.09), and 1.10 (1.01-1.20), respectively.

CONCLUSION

Diabetes, hypertension and dyslipidemia showed additive associations with the risk of CVD events in middle-aged and elderly Chinese adults.

The Diastolic Blood Pressure J-Curve in Hypertension Management: Links and Risk for Cardiovascular Disease

Purpose of Review

The treatment of hypertension has changed dramatically over the last century, with recent trials informing clinical guidelines that recommend aiming for lower blood pressure (BP) targets than ever before. However, a “J”- or “U-shaped curve” in the association between diastolic BP and cardiovascular events has been observed in epidemiological studies, suggesting that both high diastolic BPs and diastolic BPs below a certain nadir are associated with higher risk of cardiovascular disease (CVD) events. Despite the potential for confounding and reverse causation, this association may caution against overly intensive BP lowering in some hypertensive adults who also have a low baseline diastolic BP.

Recent Findings

Recent post-hoc analyses of the landmark Systolic Blood Pressure Intervention Trial (SPRINT) appear to contradict these J-curve concerns, finding that the benefit of more intensive BP treatment did not differ based on baseline blood pressure. Similarly, sensitivity analyses of The Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients (STEP) randomized controlled trial found that patients experienced similar benefits from an intensive BP goal, regardless of whether their diastolic BP was above or below 60 mm Hg. Finally, several Mendelian randomization analyses, which are less susceptible to confounding and reverse causation, demonstrated a clear linear relationship between diastolic BP and cardiovascular events. These studies indicate that a potential reduction in CVD risk is possible, irrespective of baseline diastolic BP values.

Summary

Sufficient recent evidence indicates that low diastolic BP is not causal of worse cardiovascular outcomes but rather represents confounding or reverse causation. Therefore, while low diastolic BP can be considered a marker of CVD risk, this risk is not expected to increase with further BP lowering when necessary to control concomitant elevations of systolic BP. Indeed, BP reduction in this setting appears beneficial.

The "Common Soil Hypothesis" Revisited-Risk Factors for Type 2 Diabetes and Cardiovascular Disease

The prevalence and the incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance, as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic variants in interaction with lifestyle and environmental factors. Cardiovascular disease (CVD) is the major cause of morbidity and mortality. Detailed understanding of molecular mechanisms underlying in CVD events is still largely missing. Several risk factors are shared between T2D and CVD, including obesity, insulin resistance, dyslipidemia, and hyperglycemia. CVD can precede the development of T2D, and T2D is a major risk factor for CVD, suggesting that both conditions have common genetic and environmental antecedents and that they share “common soil”. We analyzed the relationship between the risk factors for T2D and CVD based on genetics and population-based studies with emphasis on Mendelian randomization studies.

Estimating the Population Benefits of Blood Pressure Lowering: A Wide-Angled Mendelian Randomization Study in UK Biobank

Background The causal relevance of elevated blood pressure for several cardiovascular diseases (CVDs) is uncertain, as is the population impact of blood pressure lowering. This study systematically assesses evidence of causality for various CVDs in a 2-sample Mendelian randomization framework, and estimates the potential reduction in the prevalence of these diseases attributable to long-term population shifts in the distribution of systolic blood pressure (SBP). Methods and Results We investigated associations of genetically predicted SBP as predicted by 256 genetic variants with 21 CVDs in UK Biobank, a population-based cohort of UK residents. The sample consisted of 376 703 participants of European ancestry, aged 40 to 69 years at recruitment. Genetically predicted SBP was positively associated with 14 of the outcomes (P<0.002), including dilated cardiomyopathy, endocarditis, peripheral vascular disease, and rheumatic heart disease. Using genetic variation to estimate the long-term impact of blood pressure lowering on disease in a middle-aged to early late-aged UK-based population, population reductions in SBP were predicted to result in an overall 16.9% (95% CI, 12.2%-21.3%) decrease in morbidity for a 5-mm Hg decrease from a population mean of 137.7 mm Hg, 30.8% (95% CI, 22.8%-38.0%) decrease for a 10-mm Hg decrease, and 56.2% (95% CI, 43.7%-65.9%) decrease for a 22.7-mm Hg decrease in SBP (22.7 mm Hg represents a shift from the current mean SBP to 115 mm Hg). Conclusions Risk of many CVDs is influenced by long-term differences in SBP. The burden of a broad range of CVDs could be substantially reduced by long-term population-wide reductions in the distribution of blood pressure.