scholarly journals Interpretation of mendelian randomization using one measure of an exposure that varies over time.

2021 ◽  
Author(s):  
Tim T Morris ◽  
Jon Heron ◽  
Eleanor Sanderson ◽  
George Davey Smith ◽  
Kate Tilling
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Observational Data ◽  
Genetic Variant ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Effects ◽  
Time Points ◽  
The Life Course ◽  
Over Time

Background Mendelian randomization (MR) is a powerful tool through which the causal effects of modifiable exposures on outcomes can be estimated from observational data. Most exposures vary throughout the life course, but MR is commonly applied to one measurement of an exposure (e.g., weight measured once between ages 40 and 60). It has been argued that MR provides biased causal effect estimates when applied to one measure of an exposure that varies over time. Methods We propose an approach that emphasises the liability that causes the entire exposure trajectory. We demonstrate this approach using simulations and an applied example. Results We show that rather than estimating the direct or total causal effect of changing the exposure value at a given time, MR estimates the causal effect of changing the liability as induced by a specific genotype that gives rise to the exposure at that time. As such, results from MR conducted at different time points are expected to differ (unless the liability of exposure is constant over time), as we demonstrate by estimating the effect of BMI measured at different ages on systolic blood pressure. Conclusions Practitioners should not interpret MR results as timepoint-specific direct or total causal effects, but as the effect of changing the liability that causes the entire exposure trajectory. Estimates of how the effects of a genetic variant on an exposure vary over time are needed to interpret timepoint-specific causal effects.

Abstract 14652: Systolic Blood Pressure Trajectories and Cardiovascular Outcomes in SPRINT

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Charles A German ◽  
Tali Elfassy ◽  
Matthew J Singleton ◽  
Carlos J Rodriguez ◽  
Walter T Ambrosius ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Latent Class ◽  
Stable Group ◽  
Coronary Syndrome ◽  
Average Blood Pressure ◽  
Increased Risk ◽  
All Cause Mortality ◽  
Over Time

Introduction: Blood pressure trajectories have been associated with cardiovascular disease (CVD) in observational studies. It is unclear whether these associations are independent of average blood pressure over time. Methods: We used data from SPRINT to identify systolic blood pressure (SBP) trajectories among a cohort of 8901 participants by incorporating SBP measures during the first 12 months of the trial post randomization. Trajectories were identified using latent class based modeling. Study outcomes included incident CVD, defined as myocardial infarction, acute coronary syndrome not resulting in myocardial infarction, stroke, acute decompensated heart failure, or death attributable to CVD, and all-cause mortality. Cox proportional hazards models were used to evaluate associations between SBP trajectories and our outcomes of interest. Results: Four distinct SBP trajectories were identified: ‘low decline’ (40%), ‘high decline’ (6%), ‘low stable’ (48%), and ‘high stable’ (5%) (Figure 1). Relative to the low decline group, the low stable group was associated with a 29% increased risk of CVD (HR: 1.29, 95%CI: 1.06-1.57) and the high stable group was associated with a 76% increased risk of all-cause mortality (HR: 1.76, 95%CI: 1.15-2.68) after baseline multivariable adjustment. Relative to the low stable group, the high stable group was associated with a 54% increased risk of all-cause mortality (HR: 1.54, 95%CI: 1.05-2.28). When adjusting for average blood pressure across the 12 month time period, there were no significant differences in outcomes. Conclusion: We identified 4 SBP trajectories using data from SPRINT and found differences in the risk of CVD and all-cause mortality after baseline adjustment. However, there were no differences in the risk of these outcomes after adjusting for average blood pressure over time. These results suggest that the pattern of blood pressure control may not be relevant as long as the target blood pressure is achieved.

Association between ibrutinib treatment and hypertension

Heart ◽  
2021 ◽  
pp. heartjnl-2021-319110
Author(s):  
Dae Hyun Lee ◽  
Fahad Hawk ◽  
Kieun Seok ◽  
Matthew Gliksman ◽  
Josephine Emole ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Repeated Measures ◽  
Treatment Initiation ◽  
Kinase Inhibitor ◽  
Pressure Change ◽  
Exact Test ◽  
N 93 ◽  
Pressure Changes ◽  
Over Time

BackgroundIbrutinib is a tyrosine kinase inhibitor most commonly associated with atrial fibrillation. However, additional cardiotoxicities have been identified, including accelerated hypertension. The incidence and risk factors of new or worsening hypertension following ibrutinib treatment are not as well known.MethodsWe conducted a retrospective study of 144 patients diagnosed with B cell malignancies treated with ibrutinib (n=93) versus conventional chemoimmunotherapy (n=51) and evaluated their effects on blood pressure at 1, 2, 3 and 6 months after treatment initiation. Descriptive statistics were used to compare baseline characteristics for each treatment group. Fisher’s exact test was used to identify covariates significantly associated with the development of hypertension. Repeated measures analyses were conducted to analyse longitudinal blood pressure changes.ResultsBoth treatments had similar prevalence of baseline hypertension at 63.4% and 66.7%, respectively. There were no differences between treatments by age, sex and baseline cardiac comorbidities. Both systolic and diastolic blood pressure significantly increased over time with ibrutinib compared with baseline, whereas conventional chemoimmunotherapy was not associated with significant changes in blood pressure. Baseline hypertensive status did not affect the degree of blood pressure change over time. A significant increase in systolic blood pressure (defined as more than 10 mm Hg) was noted for ibrutinib (36.6%) compared with conventional chemoimmunotherapy (7.9%) at 1 month after treatment initiation. Despite being hypertensive at follow-up, 61.2% of patients who were treated with ibrutinib did not receive adequate blood pressure management (increase or addition of blood pressure medications). Within the ibrutinib group, of patients who developed more than 20 mm Hg increase in systolic blood pressure, only 52.9% had hypertension management changes.ConclusionsIbrutinib is associated with the development of hypertension and worsening of blood pressure. Cardiologists and oncologists must be aware of this cardiotoxicity to allow timely management of blood pressure elevations.

scholarly journals Causal Effect Between Total Cholesterol and HDL Cholesterol as Risk Factors for Chronic Kidney Disease: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Liu Miao ◽  
Yan Min ◽  
Chuan-Meng Zhu ◽  
Jian-Hong Chen ◽  
Bin Qi ◽  
...  
Keyword(s):  
Total Cholesterol ◽  
Serum Lipid ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Hdl Cholesterol ◽  
Causal Effects ◽  
Lipid Levels ◽  
Serum Lipid Levels ◽  
Genome Wide ◽  
Mr Study

Abstract Background/Aims: While observational studies show an association between serum lipid levels and cardiovascular disease (CVD), intervention studies that examine the preventive effects of serum lipid levels on the development of CKD are lacking. Methods: To estimate the role of serum lipid levels in the etiology of CKD, we conducted a two-sample Mendelian randomization (MR) study on serum lipid levels. Single nucleotide polymorphisms (SNPs), which were significantly associated genome-wide with plasma serum lipid levels from the GLGC and CKDGen consortium genome-wide association study (GWAS), including total cholesterol (TC, n = 187365), triglyceride (TG, n = 177861), HDL cholesterol (HDL-C, n = 187167), LDL cholesterol (LDL-C, n = 173082), apolipoprotein A1 (ApoA1, n = 20687), apolipoprotein B (ApoB, n = 20690) and CKD (n = 117165), were used as instrumental variables. None of the lipid-related SNPs was associated with CKD (all P > 0.05). Results: MR analysis genetically predicted the causal effect between TC/HDL-C and CKD. The odds ratio (OR) and 95% confidence interval (CI) of TC within CKD was 0.756 (0.579 to 0.933) (P = 0.002), and HDL-C was 0.85 (0.687 to 1.012) (P = 0.049). No causal effects between TG, LDL-C- ApoA1, ApoB and CKD were observed. Sensitivity analyses confirmed that TC and HDL-C were significantly associated with CKD. Conclusions: The findings from this MR study indicate causal effects between TC, HDL-C and CKD. Decreased TC and elevated HDL-C may reduce the incidence of CKD but need to be further confirmed by using a genetic and environmental approach.

scholarly journals Education, intelligence and Alzheimer’s disease: Evidence from a multivariable two-sample Mendelian randomization study

2018 ◽  
Author(s):  
Emma L Anderson ◽  
Laura D Howe ◽  
Kaitlin H Wade ◽  
Yoav Ben-Shlomo ◽  
W. David Hill ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Univariate Analysis ◽  
Causal Effects ◽  
Training Interventions ◽  
Bidirectional Relationship ◽  
Years Of Schooling

AbstractObjectivesTo examine whether educational attainment and intelligence have causal effects on risk of Alzheimer’s disease (AD), independently of each other.DesignTwo-sample univariable and multivariable Mendelian Randomization (MR) to estimate the causal effects of education on intelligence and vice versa, and the total and independent causal effects of both education and intelligence on risk of AD.Participants17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP) consortiumMain outcome measureOdds ratio of AD per standardised deviation increase in years of schooling and intelligenceResultsThere was strong evidence of a causal, bidirectional relationship between intelligence and educational attainment, with the magnitude of effect being similar in both directions. Similar overall effects were observed for both educational attainment and intelligence on AD risk in the univariable MR analysis; with each SD increase in years of schooling and intelligence, odds of AD were, on average, 37% (95% CI: 23% to 49%) and 35% (95% CI: 25% to 43%) lower, respectively. There was little evidence from the multivariable MR analysis that educational attainment affected AD risk once intelligence was taken into account, but intelligence affected AD risk independently of educational attainment to a similar magnitude observed in the univariate analysis.ConclusionsThere is robust evidence for an independent, causal effect of intelligence in lowering AD risk, potentially supporting a role for cognitive training interventions to improve aspects of intelligence. However, given the observed causal effect of educational attainment on intelligence, there may also be support for policies aimed at increasing length of schooling to lower incidence of AD.

scholarly journals MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging

2018 ◽  
Author(s):  
Louise A C Millard ◽  
Marcus R Munafò ◽  
Kate Tilling ◽  
Robyn E Wootton ◽  
George Davey Smith
Keyword(s):  
Lung Function ◽  
Detrimental Effect ◽  
Genetic Variant ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Causal Effects ◽  
Uk Biobank ◽  
Facial Aging ◽  
Heavy Smoking ◽  
Never Smokers

AbstractMendelian randomization (MR) is an established approach for estimating the causal effect of an environmental exposure on a downstream outcome. The gene x environment (GxE) study design can be used within an MR framework to determine whether MR estimates may be biased if the genetic instrument affects the outcome through pathways other than via the exposure of interest (known as horizontal pleiotropy). MR phenome-wide association studies (MR-pheWAS) search for the effects of an exposure, and a recently published tool (PHESANT) means that it is now possible to do this comprehensively, across thousands of traits in UK Biobank. In this study, we introduce the GxE MR-pheWAS approach, and search for the causal effects of smoking heaviness – stratifying on smoking status (ever versus never) – as an exemplar. If a genetic variant is associated with smoking heaviness (but not smoking initiation), and this variant affects an outcome (at least partially) via tobacco intake, we would expect the effect of the variant on the outcome to differ in ever versus never smokers. If this effect is entirely mediated by tobacco intake, we would expect to see an effect in ever smokers but not never smokers. We used PHESANT to search for the causal effects of smoking heaviness, instrumented by genetic variant rs16969968, among never and ever smokers respectively, in UK Biobank. We ranked results by: 1) strength of effect of rs16969968 among ever smokers, and 2) strength of interaction between ever and never smokers. We replicated previously established causal effects of smoking heaviness, including a detrimental effect on lung function and pulse rate. Novel results included a detrimental effect of heavier smoking on facial aging. We have demonstrated how GxE MR-pheWAS can be used to identify causal effects of an exposure, while simultaneously assessing the extent that results may be biased by horizontal pleiotropy.Author summaryMendelian randomization uses genetic variants associated with an exposure to investigate causality. For instance, a genetic variant that relates to how heavily a person smokes has been used to test whether smoking causally affects health outcomes. Mendelian randomization is biased if the genetic variant also affects the outcome via other pathways. We exploit additional information – that the effect of heavy smoking only occurs in people who actually smoke – to overcome this problem. By testing associations in ever and never smokers separately we can assess whether the genetic variant affects an outcome via smoking or another pathway. If the effect is entirely via smoking heaviness, we would expect to see an effect in ever but not never smokers, and this would suggest that smoking causally influences the outcome. Previous Mendelian randomization studies of smoking heaviness focused on specific outcomes – here we searched for the causal effects of smoking heaviness across over 18,000 traits. We identified previously established effects (e.g. a detrimental effect on lung function) and novel results including a detrimental effect of heavier smoking on facial aging. Our approach can be used to search for the causal effects of other exposures, where the exposure only occurs in known subsets of the population.

Abstract P084: Neighborhood Characteristics and Changes in Systolic Blood Pressure Over Time: The Multi-Ethnic Study of Atherosclerosis

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Paulina Kaiser ◽  
Lynda Lisabeth ◽  
Philippa Clarke ◽  
Sara Adar ◽  
Mahasin Mujahid ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Standard Deviation ◽  
Systolic Blood Pressure ◽  
Social Environment ◽  
Social Environments ◽  
Lower Baseline ◽  
Neighborhood Environments ◽  
Physical Activity Environments ◽  
Over Time

Introduction: Research on the association between neighborhood environments and systolic blood pressure (SBP) is limited, predominantly cross-sectional, and has produced mixed results. Investigating specific aspects of neighborhood environments in relation to changes in SBP may help to identify the most important interventions for reducing the population burden of hypertension. Hypothesis: Better neighborhood food, physical activity, and social environments will be associated with lower baseline levels of SBP and smaller increases in SBP over time. Methods: The Multi-Ethnic Study of Atherosclerosis recruited participants from six sites in the U.S., aged 45-84 (mean 59) and free of clinical cardiovascular disease at baseline. Those with non-missing data for key variables were included (N=5,997); the analytic sample was 52.5% female, 39.1% White, 27.3% Hispanic, 11.9% Black, and 21.7% Chinese, with median follow-up time of 9.2 years (IQR 4.5) and SBP measured at three or more exams for 91.3% of participants. SBP in subjects taking anti-hypertensive medication were replaced with multiply imputed estimates of unmedicated SBP, imputed at each exam. Summary measures of neighborhood food and physical activity environments incorporated survey-based scales (healthy food availability and walking environment) and GIS-based measures (density of favorable food stores and recreational resources). The summary measure of the social environment combined survey-based measures of social cohesion and safety. Neighborhoods were defined by a one-mile buffer around each participant’s home address. Linear mixed models were used to model associations of time-varying cumulative average neighborhood environmental summary measures with SBP over time, adjusting for individual-level covariates (demographics, individual- and neighborhood-level SES); models with and without adjustment for baseline SBP were used to evaluate associations of neighborhood environments with SBP trajectories. Results: In models mutually adjusted for all three neighborhood domains and covariates, living in a better physical activity environment was associated with lower SBP at baseline (-1.34 mmHg [95% CI: -2.24, -0.45] per standard deviation higher cumulative average physical activity summary score), while living in a better social environment was associated with higher SBP at baseline (1.00 mmHg [0.39, 1.63] per standard deviation higher); food environment scores were not associated with baseline SBP. After adjustment for baseline SBP, there was no association between any neighborhood environments and trajectories of SBP. Conclusions: Better food and physical activity environments were associated with lower baseline SBP, while better social environments were associated with higher baseline SBP. Neighborhood environments appear to have minimal direct effect on SBP trajectories.

Circulating adiponectin levels and systemic lupus erythematosus: a two-sample Mendelian randomization study

Rheumatology ◽  
2020 ◽  
Author(s):  
Yi-Lin Dan ◽  
Peng Wang ◽  
Zhongle Cheng ◽  
Qian Wu ◽  
Xue-Rong Wang ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Instrumental Variables ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Effects ◽  
European Ancestry ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Inverse Variance ◽  
Weighted Median

Abstract Objectives Several studies have reported increased serum/plasma adiponectin levels in SLE patients. This study was performed to estimate the causal effects of circulating adiponectin levels on SLE. Methods We selected nine independent single-nucleotide polymorphisms that were associated with circulating adiponectin levels (P < 5 × 10−8) as instrumental variables from a published genome-wide association study (GWAS) meta-analysis. The corresponding effects between instrumental variables and outcome (SLE) were obtained from an SLE GWAS analysis, including 7219 cases with 15 991 controls of European ancestry. Two-sample Mendelian randomization (MR) analyses with inverse-variance weighted, MR-Egger regression, weighted median and weight mode methods were used to evaluate the causal effects. Results The results of inverse-variance weighted methods showed no significantly causal associations of genetically predicted circulating adiponectin levels and the risk for SLE, with an odds ratio (OR) of 1.38 (95% CI 0.91, 1.35; P = 0.130). MR-Egger [OR 1.62 (95% CI 0.85, 1.54), P = 0.195], weighted median [OR 1.37 (95% CI 0.82, 1.35), P = 0.235) and weighted mode methods [OR 1.39 (95% CI 0.86, 1.38), P = 0.219] also supported no significant associations of circulating adiponectin levels and the risk for SLE. Furthermore, MR analyses in using SLE-associated single-nucleotide polymorphisms as an instrumental variable showed no associations of genetically predicted risk of SLE with circulating adiponectin levels. Conclusion Our study did not find evidence for a causal relationship between circulating adiponectin levels and the risk of SLE or of a causal effect of SLE on circulating adiponectin levels.

You Can’t Drive a Car With Only Three Wheels

2019 ◽  
Vol 188 (9) ◽  
pp. 1682-1685 ◽  
Author(s):  
Hailey R Banack
Keyword(s):  
Causal Inference ◽  
Observational Data ◽  
Causal Effect ◽  
Causal Effects ◽  
Measurement Bias ◽  
Exposure Misclassification ◽  
Unmeasured Confounding ◽  
Obstetrical Care ◽  
The Impact ◽  
Fundamental Requirement

Abstract Authors aiming to estimate causal effects from observational data frequently discuss 3 fundamental identifiability assumptions for causal inference: exchangeability, consistency, and positivity. However, too often, studies fail to acknowledge the importance of measurement bias in causal inference. In the presence of measurement bias, the aforementioned identifiability conditions are not sufficient to estimate a causal effect. The most fundamental requirement for estimating a causal effect is knowing who is truly exposed and unexposed. In this issue of the Journal, Caniglia et al. (Am J Epidemiol. 2019;000(00):000–000) present a thorough discussion of methodological challenges when estimating causal effects in the context of research on distance to obstetrical care. Their article highlights empirical strategies for examining nonexchangeability due to unmeasured confounding and selection bias and potential violations of the consistency assumption. In addition to the important considerations outlined by Caniglia et al., authors interested in estimating causal effects from observational data should also consider implementing quantitative strategies to examine the impact of misclassification. The objective of this commentary is to emphasize that you can’t drive a car with only three wheels, and you also cannot estimate a causal effect in the presence of exposure misclassification bias.

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