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

Evaluating the relationship between glycemic control and bone fragility within the UK Biobank: observational and one-sample Mendelian randomization analyses

We aimed to: (1) examine the relationship between glycemic control, BMD estimated from heel ultrasound (eBMD) and fracture risk in individuals with type 1 (T1D) and type 2 diabetes (T2D) and (2) perform a one-sample Mendelian randomization (MR) study to explore potential causal associations between glycemic control, eBMD, and fractures. This study comprised 452 131 individuals from the UK Biobank with glycated hemoglobin A1C (HbA1c) and eBMD levels. At baseline, 4078 participants were diagnosed with T1D and 23 682 with T2D. HbA1c was used to classify patients into "adequately-" (ACD; n = 17 078; HbA1c < 7.0%/53 mmol/mol) and "inadequately-" (ICD; n = 10 682; HbA1c ≥ 7.0%/53 mmol/mol) controlled diabetes. In individuals with T1D, a 1% unit (11 mmol/mol) increase in HbA1c levels was associated with a 12% increase in fracture risk (HR: 1.12, 95% CI [1.05-1.19]). Fracture risk was highest in individuals with T1D and ICD (HR 2.84, 95%CI [2.53, 3.19]), followed by those with ACD (HR 2.26, 95%CI [1.91, 2.69]), as compared to subjects without diabetes. Evidence for a non-linear association between HbA1c and fracture risk was observed (F-test ANOVA p-value = 0.002) in individuals with T2D, with risk being increased at both low and high levels of HbA1c. Fracture risk between the T2D ACD and ICD groups was not significantly different (HR: 0.97, 95%CI [0.91-1.16]), despite increased BMD. In MR analyses genetically predicted higher HbA1c levels were not significantly associated with fracture risk (causal risk ratio: 1.04, 95%CI [0.95-1.14]). We did observe evidence of a non-linear causal association with eBMD (quadratic test p-value = 0.0002), indicating U-shaped relationship between HbA1c and eBMD. We obtained evidence that lower HbA1c levels will reduce fracture risk in patients with T1D. In individuals with T2D, lowering HbA1c levels can mitigate the risk of fractures up to a threshold, beyond which the risk may begin to rise again.

Association between alcohol consumption and incidence of dementia in current drinkers: linear and non-linear mendelian randomization analysis

Background

Previous conventional epidemiological studies found a J-shape relationship between alcohol consumption and dementia, but this result was subject to confounding biases and reverse causation. Therefore, we aimed to investigate the potential linear or non-linear causal association between alcohol consumption and the incident risk of dementia in current drinkers.

Methods

This study used data from the UK Biobank to investigate the relationship between alcohol consumption and dementia risk. 313,958 White British current drinkers, who were free of dementia during 2006-2010, were followed up until 2021. Alcohol consumption was self-reported and calculated according to the National Health Service guideline. The primary outcome was all-cause dementia identified through hospital and mortality records. We used multivariable Cox models with restricted cubic splines for conventional analysis and both non-linear and linear Mendelian Randomization (MR) analyses to assess causal relationships, employing a genetic score based on 95 SNPs identified from a meta-genome-wide association study of 941,280 people from Europe.

Findings

313,958 current drinkers consumed an average of 13.6 [IQR: 7.1-25.2] units/week alcohol (men averaged 20.2 [11.1-33.9] units/week and women 9.5 [5.3-16.7] units/week). During a mean follow-up of 13.2 years, 5394 (1.7%) developed dementia. Multivariable Cox model with restricted cubic spline functions identified a J-shaped relationship between alcohol consumption and dementia risk, with the lowest risk at 12.2 units/week. The non-linear MR failed to identify a significant non-linear causal relationship (p = 0.45). Both individual-level (HR: 2.22 95%CI [1.06-4.66]) and summary-level (1.89 [1.53-2.32]) linear MR analyses indicated that higher genetically predicted alcohol consumption increased dementia risk.

Interpretation

This study identified a positive linear causal relationship between alcohol consumption and dementia among current drinkers. The J-shaped association found in conventional epidemiological analysis was not supported by non-linear MR analyses. Our findings suggested that there was no safe level of alcohol consumption for dementia.

Funding

The Shenzhen Science and Technology Program and the Strategic Priority Research Program of Chinese Academy of Sciences.

Addressing the credibility crisis in Mendelian randomization

BACKGROUND

Genome-wide association studies have enabled Mendelian randomization analyses to be performed at an industrial scale. Two-sample summary data Mendelian randomization analyses can be performed using publicly available data by anyone who has access to the internet. While this has led to many insightful papers, it has also fuelled an explosion of poor-quality Mendelian randomization publications, which threatens to undermine the credibility of the whole approach.

FINDINGS

We detail five pitfalls in conducting a reliable Mendelian randomization investigation: (1) inappropriate research question, (2) inappropriate choice of variants as instruments, (3) insufficient interrogation of findings, (4) inappropriate interpretation of findings, and (5) lack of engagement with previous work. We have provided a brief checklist of key points to consider when performing a Mendelian randomization investigation; this does not replace previous guidance, but highlights critical analysis choices. Journal editors should be able to identify many low-quality submissions and reject papers without requiring peer review. Peer reviewers should focus initially on key indicators of validity; if a paper does not satisfy these, then the paper may be meaningless even if it is technically flawless.

CONCLUSIONS

Performing an informative Mendelian randomization investigation requires critical thought and collaboration between different specialties and fields of research.

Associations between blood glucose and early- and late-onset colorectal cancer: evidence from two prospective cohorts and Mendelian randomization analyses

Background

The incidence of early-onset colorectal cancer (EOCRC), which exhibits differential clinical, pathological, and molecular features compared to late-onset CRC (LOCRC), is rising globally. The potential differential effects of blood glucose on EOCRC compared to LOCRC have not been investigated.

Methods

This study analyzed 374,568 participants from the UK Biobank cohort and 172,809 participants from the Kailuan cohort. The linear associations between blood glucose and EOCRC/LOCRC were estimated using Cox regression models. Restricted cubic spline (RCS) analysis and non-linear Mendelian randomization (MR) analysis using a 70-SNPs genetic instrument for fasting glucose were used to explore the potential non-linear associations.

Results

Participants in the highest quintile of blood glucose had higher overall CRC risk compared to the lowest quintile (HR = 1.10 in the UK Biobank cohort, 95% CI: 1.01-1.21, P-trend = 0.012; HR = 1.23 in the Kailuan cohort, 95% CI: 1.01-1.51, P-trend = 0.036). Elevated glucose (>7.0 mmol/L) was more strongly associated with increased risk of EOCRC (HR = 1.61, 95% CI: 1.07-2.44) than with LOCRC (HR = 1.14, 95% CI: 1.02-1.27) in the UK Biobank cohort (P-heterogeneity = 0.014). Elevated glucose (>7.0 mmol/L) was associated with increased risk of LOCRC (HR = 1.25, 95% CI: 1.04-1.65) in the Kailuan cohort as well. There was no evidence for non-linear associations between blood glucose and risks of EOCRC/LOCRC.

Conclusions

This study showed a positive association between blood glucose and CRC risk in a dose-response manner, particularly for EOCRC, suggesting that tighter glucose control should be a priority for younger age groups.

Conventional and genetic associations of BMI with major vascular and non-vascular disease incidence and mortality in a relatively lean Chinese population: U-shaped relationship revisited

BACKGROUND

Higher body mass index (BMI) is associated with higher incidence of cardiovascular and some non-cardiovascular diseases (CVDs/non-CVDs). However, uncertainty remains about its associations with mortality, particularly at lower BMI levels.

METHODS

The prospective China Kadoorie Biobank recruited >512 000 adults aged 30-79 years in 2004-08 and genotyped a random subset of 76 000 participants. In conventional and Mendelian randomization (MR) analyses, Cox regression yielded adjusted hazard ratios (HRs) associating measured and genetically predicted BMI levels with incident risks of major vascular events (MVEs; conventional/MR 68 431/23 621), ischaemic heart disease (IHD; 50 698/12 177), ischaemic stroke (IS; 42 427/11 897) and intracerebral haemorrhage (ICH; 7644/4712), and with mortality risks of CVD (15 427/6781), non-CVD (26 915/4355) and all causes (42 342/6784), recorded during ∼12 years of follow-up.

RESULTS

Overall, the mean BMI was 23.8 (standard deviation: 3.2) kg/m2 and 13% had BMIs of <20 kg/m2. Measured and genetically predicted BMI showed positive log-linear associations with MVE, IHD and IS, but a shallower positive association with ICH in conventional analyses. Adjusted HRs per 5 kg/m2 higher genetically predicted BMI were 1.50 (95% CI 1.41-1.58), 1.49 (1.38-1.61), 1.42 (1.31-1.54) and 1.64 (1.58-1.69) for MVE, IHD, IS and ICH, respectively. These were stronger than associations in conventional analyses [1.21 (1.20-1.23), 1.28 (1.26-1.29), 1.31 (1.29-1.33) and 1.14 (1.10-1.18), respectively]. At BMIs of ≥20 kg/m2, there were stronger positive log-linear associations of BMI with CVD, non-CVD and all-cause mortality in MR than in conventional analyses.

CONCLUSIONS

Among relatively lean Chinese adults, higher genetically predicted BMI was associated with higher risks of incident CVDs. Excess mortality risks at lower BMI in conventional analyses are likely not causal and may reflect residual reverse causality.

Vitamin D, chronic pain, and depression: linear and non-linear Mendelian randomization analyses

Vitamin D deficiency has been linked to various chronic pain conditions. However, randomized trials of vitamin D supplementation have had mixed results. In contrast, systematic reviews of randomized trials indicate a protective effect of vitamin D supplementation on depression. We undertake a Mendelian randomization investigation in UK Biobank, a study of UK residents aged 40-65 at recruitment. We perform linear and non-linear Mendelian randomization analyses for four outcomes: fibromyalgia, clinical fatigue, chronic widespread pain, and probable lifetime major depression. We use genetic variants from four gene regions with known links to vitamin D biology as instruments. In linear analyses, genetically-predicted levels of 25-hydroxyvitamin D [25(OH)D], a clinical marker of vitamin D status, were not associated with fibromyalgia (odds ratio [OR] per 10 nmol/L higher 25(OH)D 1.02, 95% confidence interval [CI] 0.93, 1.12), clinical fatigue (OR 0.99, 95% CI 0.94, 1.05), chronic widespread pain (OR 0.95, 95% CI 0.89, 1.02), or probable lifetime major depression (OR 0.97, 95% CI 0.93, 1.01). In non-linear analyses, an association was observed between genetically-predicted 25(OH)D levels and depression in the quintile of the population with the lowest 25(OH)D levels (OR 0.75, 95% CI 0.59, 0.94); associations were null in other strata. Our findings suggest that population-wide vitamin D supplementation will not substantially reduce pain or depression; however, targeted supplementation of deficient individuals may reduce risk of depression.

Independent Effects of Blood Pressure on Intraocular Pressure and Retinal Ganglion Cell Degeneration: A Mendelian Randomization Study

Purpose

To investigate the causal effect of elevated blood pressure on primary open-angle glaucoma (POAG) and POAG endophenotypes.

Methods

Two-sample Mendelian randomization (MR) was performed to investigate the causal effect of elevated systolic blood pressure (SBP) (N = 757,601) and diastolic blood pressure (DBP) (N = 757,601) on intraocular pressure (IOP) (N = 139,555), macular retinal nerve fiber layer (mRNFL) thickness (N = 33,129), ganglion cell complex (GCC) thickness (N = 33,129), vertical cup-to-disc ratio (VCDR) (N = 111,724), and POAG liability (Ncases = 16,677, Ncontrols = 199,580). The primary analysis was conducted using the inverse-variance weighted approach. Sensitivity analyses were performed to investigate robustness to horizontal pleiotropy, winner's curse, and collider bias. Multivariable MR was performed to investigate whether any effect of blood pressure on retinal ganglion cell degeneration was mediated through increased IOP.

Results

Increased genetically predicted SBP and DBP associated with an increase in IOP (0.17 mm Hg [95% CI = 0.11 to 0.24] per 10 mm Hg higher SBP, P = 5.18 × 10-7, and 0.17 mm Hg [95% CI = 0.05 to 0.28 mm Hg] per 10 mm Hg higher DBP, P = 0.004). Increased genetically predicted SBP associated with a thinner GCC (0.04 µm [95% CI = -0.07 to -0.01 µm], P = 0.018) and a thinner mRNFL (0.04 µm [95% CI = -0.07 to -0.01 µm], P = 0.004), an effect that arises independently of IOP according to our mediation analysis. Neither SBP nor DBP associated with VCDR or POAG liability.

Conclusions

These findings support a causal effect of elevated blood pressure on retinal ganglion cell degeneration that does not require intermediary changes in IOP. Targeted blood pressure control may help preserve vision by lowering IOP and, independently, by preventing retinal ganglion cell degeneration, including in individuals with a normal IOP.

Associations of genetically predicted vitamin D status and deficiency with the risk of carotid artery plaque: a Mendelian randomization study

Low concentrations of circulating 25-hydroxy-vitamin D are observationally associated with an increased risk of subclinical atherosclerosis and cardiovascular disease. However, randomized controlled trials have not reported the beneficial effects of vitamin D supplementation on atherosclerotic cardiovascular disease (ASCVD) outcomes. Whether genetically predicted vitamin D status confers protection against the development of carotid artery plaque, a powerful predictor of subclinical atherosclerosis, remains unknown. We conducted a two-sample Mendelian randomization (MR) study to explore the association of genetically predicted vitamin D status and deficiency with the risk of developing carotid artery plaque. We leveraged three genome-wide association studies (GWAS) of vitamin D status and one GWAS of vitamin D deficiency. We used the inverse-variance weighted (IVW) approach as our main method, and MR-Egger, weighted-median, and radialMR as MR sensitivity analyses. We also conducted sensitivity analyses using biologically plausible genetic instruments located within genes encoding for vitamin D metabolism (GC, CYP2R1, DHCR7, CYP24A1). We did not find significant associations between genetically predicted vitamin D status (Odds ratio (OR) = 0.99, P = 0.91) and deficiency (OR = 1.00, P = 0.97) with the risk of carotid artery plaque. We additionally explored the potential causal effect of vitamin D status on coronary artery calcification (CAC) and carotid intima-media thickness (cIMT), two additional markers of subclinical atherosclerosis, and we did not find any significant association (βCAC = - 0.14, P = 0.23; βcIMT = 0.005, P = 0.19). These findings did not support the causal effects of vitamin D status and deficiency on the risk of developing subclinical atherosclerosis.

Vitamin D and major chronic diseases

Numerous observational studies have demonstrated a significant inverse association between vitamin D status and the risk of major chronic disease, including type 2 diabetes (T2D), cardiovascular disease (CVD), and cancer. However, findings from Mendelian randomization (MR) studies and randomized controlled trials (RCTs) suggest minimal or no benefit of increased vitamin D levels. We provide an overview of recent literature linking vitamin D to major chronic diseases. Because emerging evidence indicates a potential threshold effect of vitamin D, future well-designed studies focused on diverse populations with vitamin D deficiency or insufficiency are warranted for a more comprehensive understanding of the effect of maintaining sufficient vitamin D status on the prevention of major chronic diseases.

Body mass index and all-cause mortality in HUNT and UK biobank studies: revised non-linear Mendelian randomisation analyses

OBJECTIVES

To estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomisation framework.

DESIGN

Mendelian randomisation analyses of two prospective population-based cohorts.

SETTING

Individuals of European ancestries living in Norway or the UK.

PARTICIPANTS

56 150 participants from the Trøndelag Health Study (HUNT) in Norway and 366 385 participants from UK Biobank recruited by postal invitation.

OUTCOMES

All-cause mortality and cause-specific mortality (cardiovascular, cancer, non-cardiovascular non-cancer).

RESULTS

A previously published non-linear Mendelian randomisation analysis of these data using the residual stratification method suggested a J-shaped association between genetically predicted BMI and mortality outcomes with the lowest mortality risk at a BMI of around 25 kg/m2. However, the 'constant genetic effect' assumption required by this method is violated. The reanalysis of these data using the more reliable doubly-ranked stratification method provided some indication of a J-shaped relationship, but with much less certainty as there was less precision in estimates at the lower end of the BMI distribution. Evidence for a harmful effect of reducing BMI at low BMI levels was only present in some analyses, and where present, only below 20 kg/m2. A harmful effect of increasing BMI for all-cause mortality was evident above 25 kg/m2, for cardiovascular mortality above 24 kg/m2, for cancer mortality above 30 kg/m2 and for non-cardiovascular non-cancer mortality above 26 kg/m2. In UK Biobank, the association between genetically predicted BMI and mortality at high BMI levels was stronger in women than in men.

CONCLUSION

This research challenges findings from previous conventional observational epidemiology and Mendelian randomisation investigations that the lowest level of mortality risk is at a BMI level of around 25 kg/m2. Our results provide some evidence that reductions in BMI will increase mortality risk for a small proportion of the population, and clear evidence that increases in BMI will increase mortality risk for those with BMI above 25 kg/m2.

A burden of proof study on alcohol consumption and ischemic heart disease

Cohort and case-control data have suggested an association between low to moderate alcohol consumption and decreased risk of ischemic heart disease (IHD), yet results from Mendelian randomization (MR) studies designed to reduce bias have shown either no or a harmful association. Here we conducted an updated systematic review and re-evaluated existing cohort, case-control, and MR data using the burden of proof meta-analytical framework. Cohort and case-control data show low to moderate alcohol consumption is associated with decreased IHD risk - specifically, intake is inversely related to IHD and myocardial infarction morbidity in both sexes and IHD mortality in males - while pooled MR data show no association, confirming that self-reported versus genetically predicted alcohol use data yield conflicting findings about the alcohol-IHD relationship. Our results highlight the need to advance MR methodologies and emulate randomized trials using large observational databases to obtain more definitive answers to this critical public health question.

Non-linear Mendelian randomization: detection of biases using negative controls with a focus on BMI, Vitamin D and LDL cholesterol

Mendelian randomisation (MR) is an established technique in epidemiological investigation, using the principle of random allocation of genetic variants at conception to estimate the causal linear effect of an exposure on an outcome. Extensions to this technique include non-linear approaches that allow for differential effects of the exposure on the outcome depending on the level of the exposure. A widely used non-linear method is the residual approach, which estimates the causal effect within different strata of the non-genetically predicted exposure (i.e. the "residual" exposure). These "local" causal estimates are then used to make inferences about non-linear effects. Recent work has identified that this method can lead to estimates that are seriously biased, and a new method-the doubly-ranked method-has been introduced as a possibly more robust approach. In this paper, we perform negative control outcome analyses in the MR context. These are analyses with outcomes onto which the exposure should have no predicted causal effect. Using both methods we find clearly biased estimates in certain situations. We additionally examined a situation for which there are robust randomised controlled trial estimates of effects-that of low-density lipoprotein cholesterol (LDL-C) reduction onto myocardial infarction, where randomised trials have provided strong evidence of the shape of the relationship. The doubly-ranked method did not identify the same shape as the trial data, and for LDL-C and other lipids they generated some highly implausible findings. Therefore, we suggest there should be extensive simulation and empirical methodological examination of performance of both methods for NLMR under different conditions before further use of these methods. In the interim, use of NLMR methods needs justification, and a number of sanity checks (such as analysis of negative and positive control outcomes, sensitivity analyses excluding removal of strata at the extremes of the distribution, examination of biological plausibility and triangulation of results) should be performed.

Assessing the Role of Cortisol in Anxiety, Major Depression, and Neuroticism: A Mendelian Randomization Study Using SERPINA6/SERPINA1 Variants

Background

Previous evidence informed by the toxic stress model suggests that higher cortisol causes anxiety and major depression, but clinical success is lacking. To clarify the role of cortisol, we used Mendelian randomization to estimate its associations with anxiety, major depression, and neuroticism, leveraging the largest available genome-wide association studies including from the Psychiatric Genomics Consortium, the UK Biobank, and FinnGen.

Methods

After meta-analyzing 2 genome-wide association studies on morning plasma cortisol (n = 32,981), we selected single nucleotide polymorphisms (SNPs) at p < 5 × 10-8 and r2 < 0.3 in the SERPINA6/SERPINA1 gene region encoding proteins that influence cortisol bioavailability. We applied these SNPs to summary genetic associations with the outcomes considered (n = 17,310-449,484), and systolic blood pressure as a positive outcome, using inverse-variance weighted meta-analysis accounting for correlation. Sensitivity analyses addressing SNP correlation and confounding by childhood maltreatment and follow-up analyses using only SNPs that colocalized with SERPINA6 expression were conducted.

Results

Cortisol was associated with anxiety (pooled odds ratio [OR] 1.16 per cortisol z score; 95% CI, 1.04 to 1.31), but not major depression (pooled OR 1.02, 95% CI, 0.95 to 1.10) or neuroticism (β -0.025; 95% CI, -0.071 to 0.022). Sensitivity analyses yielded similar estimates. Cortisol was positively associated with systolic blood pressure, as expected. Using rs9989237 and rs2736898, selected using colocalization, cortisol was associated with anxiety in the UK Biobank (OR 1.32; 95% CI, 1.01 to 1.74) but not with major depression in FinnGen (OR 1.14; 95% CI, 0.95 to 1.37).

Conclusions

Cortisol was associated with anxiety and may be a potential target for prevention. Other targets may be more relevant to major depression and neuroticism.

Vitamin D and human health: evidence from Mendelian randomization studies

We summarized the current evidence on vitamin D and major health outcomes from Mendelian randomization (MR) studies. PubMed and Embase were searched for original MR studies on vitamin D in relation to any health outcome from inception to September 1, 2022. Nonlinear MR findings were excluded due to concerns about the validity of the statistical methods used. A meta-analysis was preformed to synthesize study-specific estimates after excluding overlapping samples, where applicable. The methodological quality of the included studies was evaluated according to the STROBE-MR checklist. A total of 133 MR publications were eligible for inclusion in the analyses. The causal association between vitamin D status and 275 individual outcomes was examined. Linear MR analyses showed genetically high 25-hydroxyvitamin D (25(OH)D) concentrations were associated with reduced risk of multiple sclerosis incidence and relapse, non-infectious uveitis and scleritis, psoriasis, femur fracture, leg fracture, amyotrophic lateral sclerosis, anorexia nervosa, delirium, heart failure, ovarian cancer, non-alcoholic fatty liver disease, dyslipidemia, and bacterial pneumonia, but increased risk of Behçet's disease, Graves' disease, kidney stone disease, fracture of radium/ulna, basal cell carcinoma, and overall cataracts. Stratified analyses showed that the inverse association between genetically predisposed 25(OH)D concentrations and multiple sclerosis risk was significant and consistent regardless of the genetic instruments GIs selected. However, the associations with most of the other outcomes were only pronounced when using genetic variants not limited to those in the vitamin D pathway as GIs. The methodological quality of the included MR studies was substantially heterogeneous. Current evidence from linear MR studies strongly supports a causal role of vitamin D in the development of multiple sclerosis. Suggestive support for a number of other health conditions could help prioritize conditions where vitamin D may be beneficial or harmful.

Plasma adiponectin levels and risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction: large-scale observational and Mendelian randomization evidence

AIMS

Adiponectin may play an important protective role in heart failure and associated cardiovascular diseases. We hypothesized that plasma adiponectin is associated observationally and causally, genetically with risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction.

METHODS AND RESULTS

In the Copenhagen General Population Study, we examined 30 045 individuals with plasma adiponectin measurements observationally and 96 903 individuals genetically in one-sample Mendelian randomization analyses using five genetic variants explaining 3% of the variation in plasma adiponectin. In the HERMES, UK Biobank, The Nord-Trøndelag Health Study (HUNT), deCODE, the Michigan Genomics Initiative (MGI), DiscovEHR, and the AFGen consortia, we performed two-sample Mendelian randomization analyses in up to 1 030 836 individuals using 12 genetic variants explaining 14% of the variation in plasma adiponectin.In observational analyses modelled linearly, a 1 unit log-transformed higher plasma adiponectin was associated with a hazard ratio of 1.51 (95% confidence interval: 1.37-1.66) for heart failure, 1.63 (1.50-1.78) for atrial fibrillation, 1.21 (1.03-1.41) for aortic valve stenosis, and 1.03 (0.93-1.14) for myocardial infarction; levels above the median were also associated with an increased risk of myocardial infarction, and non-linear U-shaped associations were more apparent for heart failure, aortic valve stenosis, and myocardial infarction in less-adjusted models. Corresponding genetic, causal risk ratios were 0.92 (0.65-1.29), 0.87 (0.68-1.12), 1.55 (0.87-2.76), and 0.93 (0.67-1.30) in one-sample Mendelian randomization analyses, and no significant associations were seen for non-linear one-sample Mendelian randomization analyses; corresponding causal risk ratios were 0.99 (0.89-1.09), 1.00 (0.92-1.08), 1.01 (0.79-1.28), and 0.99 (0.86-1.13) in two-sample Mendelian randomization analyses, respectively.

CONCLUSION

Observationally, elevated plasma adiponectin was associated with an increased risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction. However, genetic evidence did not support causality for these associations.

Alcohol consumption and the risk of all-cause and cause-specific mortality-a linear and nonlinear Mendelian randomization study

BACKGROUND

Many observational studies support light-to-moderate alcohol intake as potentially protective against premature death. We used a genetic approach to evaluate the linear and nonlinear relationships between alcohol consumption and mortality from different underlying causes.

METHODS

We used data from 278 093 white-British UK Biobank participants, aged 37-73 years at recruitment and with data on alcohol intake, genetic variants, and mortality. Habitual alcohol consumption was instrumented by 94 variants. Linear Mendelian randomization (MR) analyses were conducted using five complementary approaches, and nonlinear MR analyses by the doubly-ranked method.

RESULTS

There were 20 834 deaths during the follow-up (median 12.6 years). In conventional analysis, the association between alcohol consumption and mortality outcomes was 'J-shaped'. In contrast, MR analyses supported a positive linear association with premature mortality, with no evidence for curvature (Pnonlinearity ≥ 0.21 for all outcomes). The odds ratio [OR] for each standard unit increase in alcohol intake was 1.27 (95% confidence interval [CI] 1.16-1.39) for all-cause mortality, 1.30 (95% CI 1.10-1.53) for cardiovascular disease, 1.20 (95% CI 1.08-1.33) for cancer, and 2.06 (95% CI 1.36-3.12) for digestive disease mortality. These results were consistent across pleiotropy-robust methods. There was no clear evidence for an association between alcohol consumption and mortality from respiratory diseases or COVID-19 (1.32, 95% CI 0.96-1.83 and 1.46, 95% CI 0.99-2.16, respectively; Pnonlinearity ≥ 0.21).

CONCLUSION

Higher levels of genetically predicted alcohol consumption had a strong linear association with an increased risk of premature mortality with no evidence for any protective benefit at modest intake levels.

A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomization

BACKGROUND

Mendelian randomization is a popular method for causal inference with observational data that uses genetic variants as instrumental variables. Similarly to a randomized trial, a standard Mendelian randomization analysis estimates the population-averaged effect of an exposure on an outcome. Dividing the population into subgroups can reveal effect heterogeneity to inform who would most benefit from intervention on the exposure. However, as covariates are measured post-"randomization", naive stratification typically induces collider bias in stratum-specific estimates.

METHOD

We extend a previously proposed stratification method (the "doubly-ranked method") to form strata based on a single covariate, and introduce a data-adaptive random forest method to calculate stratum-specific estimates that are robust to collider bias based on a high-dimensional covariate set. We also propose measures based on the Q statistic to assess heterogeneity between stratum-specific estimates (to understand whether estimates are more variable than expected due to chance alone) and variable importance (to identify the key drivers of effect heterogeneity).

RESULT

We show that the effect of body mass index (BMI) on lung function is heterogeneous, depending most strongly on hip circumference and weight. While for most individuals, the predicted effect of increasing BMI on lung function is negative, it is positive for some individuals and strongly negative for others.

CONCLUSION

Our data-adaptive approach allows for the exploration of effect heterogeneity in the relationship between an exposure and an outcome within a Mendelian randomization framework. This can yield valuable insights into disease aetiology and help identify specific groups of individuals who would derive the greatest benefit from targeted interventions on the exposure.

Effects of uric acid on ischemic diseases, stratified by lipid levels: a drug-target, nonlinear Mendelian randomization study

Although uric acid-lowering agents such as xanthine oxidase inhibitors have potential cardioprotective effects, studies on their use in preventing cardiovascular diseases are lacking. We investigated the genetically proxied effects of reducing uric acid on ischemic cardiovascular diseases in a lipid-level-stratified population. We performed drug-target Mendelian randomization (MR) analyses using UK Biobank data to select genetic instruments within a uric acid-lowering gene, xanthine dehydrogenase (XDH), and construct genetic scores. For nonlinear MR analyses, individuals were stratified by lipid level. Outcomes included acute myocardial infarction (AMI), ischemic heart disease, cerebral infarction, transient cerebral ischemic attack, overall ischemic disease, and gout. We included 474,983 non-gout individuals with XDH-associated single-nucleotide polymorphisms. The XDH-variant-induced uric acid reduction was associated with reduced risk of gout (odds ratio [OR], 0.85; 95% confidence interval [CI], 0.78-0.93; P < 0.001), cerebral infarction (OR, 0.86; 95% CI, 0.75-0.98; P = 0.023), AMI (OR, 0.79; 95% CI, 0.66-0.94; P = 0.010) in individuals with triglycerides ≥ 188.00 mg/dL, and cerebral infarction in individuals with low-density lipoprotein cholesterol (LDL-C) ≤ 112.30 mg/dL (OR, 0.76; 95% CI, 0.61-0.96; P = 0.020) or LDL-C of 136.90-157.40 mg/dL (OR, 0.67; 95% CI, 0.49-0.92; P = 0.012). XDH-variant-induced uric acid reduction lowers the risk of gout, AMI for individuals with high triglycerides, and cerebral infarction except for individuals with high LDL-C, highlighting the potential heterogeneity in the protective effects of xanthine oxidase inhibitors for treating AMI and cerebral infarction depending on the lipid profiles.

Dose-Response Associations of Lipid Traits With Coronary Artery Disease and Mortality

Importance

Apolipoprotein B (apoB), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) are associated with coronary artery disease (CAD). However, trial evidence for the association of intensive LDL-C lowering and TG lowering with mortality is less definitive.

Objectives

To investigate the associations of apoB, LDL-C, and TG with CAD and mortality, both overall and by sex and age, and to characterize the shapes of these associations.

Design, Setting, and Participants

This genetic association study used linear and nonlinear mendelian randomization (MR) to analyze a population-based cohort of individuals of European ancestry from the UK Biobank, which recruited participants from 2006 to 2010 with follow-up information updated until September 2021. Data analysis occurred from December 2022 to November 2023.

Exposures

Genetically predicted apoB, LDL-C, and TG.

Main Outcomes and Measures

The primary outcomes were CAD, all-cause mortality, and cause-specific mortality. Genetic associations with CAD were calculated using logistic regression, associations with all-cause mortality using Cox proportional hazards regression, and associations with cause-specific mortality using cause-specific Cox proportional hazards regression with censoring for other causes of mortality.

Results

This study included 347 797 participants (mean [SD] age, 57.2 [8.0] years; 188 330 female [54.1%]). There were 23 818 people who developed CAD and 23 848 people who died. Genetically predicted apoB was positively associated with risk of CAD (odds ratio [OR], 1.65 per SD increase; 95% CI 1.57-1.73), all-cause mortality (hazard ratio [HR], 1.11; 95% CI, 1.06-1.16), and cardiovascular mortality (HR, 1.36; 95% CI, 1.24-1.50), with some evidence for larger associations in male participants than female participants. Findings were similar for LDL-C. Genetically predicted TG was positively associated with CAD (OR, 1.60; 95% CI 1.52-1.69), all-cause mortality (HR, 1.08; 95% CI, 1.03-1.13), and cardiovascular mortality (HR, 1.21; 95% CI, 1.09-1.34); however, sensitivity analyses suggested evidence of pleiotropy. The association of genetically predicted TG with CAD persisted but it was no longer associated with mortality outcomes after controlling for apoB. Nonlinear MR suggested that all these associations were monotonically increasing across the whole observed distribution of each lipid trait, with no diminution at low lipid levels. Such patterns were observed irrespective of sex or age.

Conclusions and relevance

In this genetic association study, apoB (or, equivalently, LDL-C) was associated with increased CAD risk, all-cause mortality, and cardiovascular mortality, all in a dose-dependent way. TG may increase CAD risk independent of apoB, although the possible presence of pleiotropy is a limitation. These insights highlight the importance of apoB (or, equivalently, LDL-C) lowering for reducing cardiovascular morbidity and mortality across its whole distribution.

Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality: observational and Mendelian randomisation analyses

BACKGROUND

Randomised trials of vitamin D supplementation for cardiovascular disease and all-cause mortality have generally reported null findings. However, generalisability of results to individuals with low vitamin D status is unclear. We aimed to characterise dose-response relationships between 25-hydroxyvitamin D (25[OH]D) concentrations and risk of coronary heart disease, stroke, and all-cause mortality in observational and Mendelian randomisation frameworks.

METHODS

Observational analyses were undertaken using data from 33 prospective studies comprising 500 962 individuals with no known history of coronary heart disease or stroke at baseline. Mendelian randomisation analyses were performed in four population-based cohort studies (UK Biobank, EPIC-CVD, and two Copenhagen population-based studies) comprising 386 406 middle-aged individuals of European ancestries, including 33 546 people who developed coronary heart disease, 18 166 people who had a stroke, and 27 885 people who died. Primary outcomes were coronary heart disease, defined as fatal ischaemic heart disease (International Classification of Diseases 10th revision code I20-I25) or non-fatal myocardial infarction (I21-I23); stroke, defined as any cerebrovascular disease (I60-I69); and all-cause mortality.

FINDINGS

Observational analyses suggested inverse associations between incident coronary heart disease, stroke, and all-cause mortality outcomes with 25(OH)D concentration at low 25(OH)D concentrations. In population-wide genetic analyses, there were no associations of genetically predicted 25(OH)D with coronary heart disease (odds ratio [OR] per 10 nmol/L higher genetically-predicted 25(OH)D concentration 0·98, 95% CI 0·95-1·01), stroke (1·01, [0·97-1·05]), or all-cause mortality (0·99, 0·95-1·02). Null findings were also observed in genetic analyses for cause-specific mortality outcomes, and in stratified genetic analyses for all outcomes at all observed levels of 25(OH)D concentrations.

INTERPRETATION

Stratified Mendelian randomisation analyses suggest a lack of causal relationship for 25(OH)D concentrations with both cardiovascular and mortality outcomes for individuals at all levels of 25(OH)D. Our findings suggest that substantial reductions in mortality and cardiovascular morbidity due to long-term low-dose vitamin D supplementation are unlikely even if targeted at individuals with low vitamin D status.

FUNDING

British Heart Foundation, Medical Research Council, National Institute for Health Research, Health Data Research UK, Cancer Research UK, and International Agency for Research on Cancer.

Mendelian Randomization as a Tool for Cardiovascular Research: A Review

Importance

Mendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease.

Observations

MR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed.

Conclusions and Relevance

This review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

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.

Guidelines for performing Mendelian randomization investigations: update for summer 2023

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.