Kaitlin H Wade

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

Background Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.

Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies

Mendelian randomization (MR) is an increasingly important tool for appraising causality in observational epidemiology. The technique exploits the principle that genotypes are not generally susceptible to reverse causation bias and confounding, reflecting their fixed nature and Mendel’s first and second laws of inheritance. The approach is, however, subject to important limitations and assumptions that, if unaddressed or compounded by poor study design, can lead to erroneous conclusions. Nevertheless, the advent of 2-sample approaches (in which exposure and outcome are measured in separate samples) and the increasing availability of open-access data from large consortia of genome-wide association studies and population biobanks mean that the approach is likely to become routine practice in evidence synthesis and causal inference research. In this article we provide an overview of the design, analysis, and interpretation of MR studies, with a special emphasis on assumptions and limitations. We also consider different analytic strategies for strengthening causal inference. Although impossible to prove causality with any single approach, MR is a highly cost-effective strategy for prioritizing intervention targets for disease prevention and for strengthening the evidence base for public health policy.

BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian Randomization

This study focused on resolving the relationship between BMI and type 2 diabetes. The availability of multiple variants associated with BMI offers a new chance to resolve the true causal effect of BMI on type 2 diabetes; however, the properties of these associations and their validity as genetic instruments need to be considered alongside established and new methods for undertaking Mendelian randomization (MR). We explore the potential for pleiotropic genetic variants to generate bias, revise existing estimates, and illustrate value in new analysis methods. A two-sample MR approach with 96 genetic variants was used with three different analysis methods, two of which (MR-Egger and the weighted median) have been developed specifically to address problems of invalid instrumental variables. We estimate an odds ratio for type 2 diabetes per unit increase in BMI (kg/m2) of between 1.19 and 1.38, with the most stable estimate using all instruments and a weighted median approach (1.26 [95% CI 1.17, 1.34]). TCF7L2(rs7903146) was identified as a complex effect or pleiotropic instrument, and removal of this variant resulted in convergence of causal effect estimates from different causal analysis methods. This indicated the potential for pleiotropy to affect estimates and differences in performance of alternative analytical methods. In a real type 2 diabetes–focused example, this study demonstrates the potential impact of invalid instruments on causal effect estimates and the potential for new approaches to mitigate the bias caused.

Mendelian randomization: application to cardiovascular disease

In the absence of an ethical, practical, and economical randomized trial, the epidemiologist is left to explore other methods in efforts to assert causality. An approach based on genotypic variation has the potential to mitigate against some of the problems found within conventional observational studies. Genetic variations associated with risk factors of interest at the population level can be used as proxy measures for these risk factors and to generate estimates of causal effect. The potential and the possible limitations of this approach within the cardiovascular field are presented in this review.

The Role of Obesity, Type 2 Diabetes, and Metabolic Factors in Pancreatic Cancer: A Mendelian Randomization Study

Abstract Background Risk factors for pancreatic cancer include a cluster of metabolic conditions such as obesity, hypertension, dyslipidemia, insulin resistance, and type 2 diabetes. Given that these risk factors are correlated, separating out causal from confounded effects is challenging. Mendelian randomization (MR), or the use of genetic instrumental variables, may facilitate the identification of the metabolic drivers of pancreatic cancer. Methods We identified genetic instruments for obesity, body shape, dyslipidemia, insulin resistance, and type 2 diabetes in order to evaluate their causal role in pancreatic cancer etiology. These instruments were analyzed in relation to risk using a likelihood-based MR approach within a series of 7110 pancreatic cancer patients and 7264 control subjects using genome-wide data from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Potential unknown pleiotropic effects were assessed using a weighted median approach and MR-Egger sensitivity analyses. Results Results indicated a robust causal association of increasing body mass index (BMI) with pancreatic cancer risk (odds ratio [OR] = 1.34, 95% confidence interval [CI] = 1.09 to 1.65, for each standard deviation increase in BMI [4.6 kg/m2]). There was also evidence that genetically increased fasting insulin levels were causally associated with an increased risk of pancreatic cancer (OR = 1.66, 95% CI = 1.05 to 2.63, per SD [44.4 pmol/L]). Notably, no evidence of a causal relationship was observed for type 2 diabetes, nor for dyslipidemia. Sensitivity analyses did not indicate that pleiotropy was an important source of bias. Conclusions Our results suggest a causal role of BMI and fasting insulin in pancreatic cancer etiology.

Prospective associations of parental smoking, alcohol use, marital status, maternal satisfaction, and parental and childhood body mass index at 6.5 years with later problematic eating attitudes

Background:Few studies have prospectively investigated whether early-life exposures are associated with pre-adolescent eating attitudes.Objective:The objective of this study is to prospectively investigate associations of parental smoking, alcohol use, marital status, measures of maternal satisfaction, self-reported parental body mass index (BMI) and clinically measured childhood BMI, assessed between birth and 6.5 years, with problematic eating attitudes at 11.5 years.Methods:Observational cohort analysis nested within the Promotion of Breastfeeding Intervention Trial, a cluster-randomised trial conducted in 31 maternity hospitals and affiliated polyclinics in Belarus. Our primary outcome was a Children’s Eating Attitudes Test (ChEAT) score ⩾22.5 (85th percentile), an indicator of problematic eating attitudes. We employed multivariable mixed logistic regression models, which allow inference at the individual level. We also performed instrumental variable (IV) analysis using parents’ BMIs as instruments for the child’s BMI, to assess whether associations could be explained by residual confounding or reverse causation.Subjects:Of the 17 046 infants enrolled between 1996 and 1997 across Belarus, 13 751 (80.7%) completed the ChEAT test at 11.5 years.Results:In fully adjusted models, overweight children at age 6.5 years had a 2.14-fold (95% confidence interval (CI): 1.82, 2.52) increased odds of having ChEAT scores ⩾85th percentile at age 11.5 years, and those who were obese had a 3.89-fold (95% CI: 2.95, 5.14) increased odds compared with normal-weight children. Children of mothers or fathers who were themselves overweight or obese were more likely to score ⩾85th percentile (P for trend ⩽0.001). IV analysis was consistent with a child’s BMI causally affecting future eating attitudes. There was little evidence that parental smoking, alcohol use, or marital status or maternal satisfaction were associated with eating attitudes.Conclusion:In our large, prospective cohort in Belarus, both parental and childhood overweight and obesity at 6.5 years were associated with pre-adolescent problematic eating attitudes 5 years later.

The MR-Base platform supports systematic causal inference across the human phenome

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.

Effects of promoting longer-term and exclusive breastfeeding on childhood eating attitudes: a cluster-randomized trial

BACKGROUND Observational studies suggest that breastfeeding benefits later maternal child-feeding practices, which in turn may contribute to positive eating attitudes. We investigated the effect of a randomized intervention to increase duration and exclusivity of breastfeeding on pre-adolescent eating attitudes. METHODS Long-term follow-up of the Promotion of Breastfeeding Intervention Trial (PROBIT), a cluster-randomized trial in 31 maternity hospitals and affiliated polyclinics in Belarus. Sites were randomly assigned an experimental intervention to promote longer duration and exclusivity of breastfeeding in mothers who initiated breastfeeding (n = 16 sites), or a control intervention of continuing usual care (n = 15 sites); 17 046 healthy infants were enrolled in 1996-7, of whom 13 751 (80.7%) completed the Childrens Eating Attitude Test (ChEAT) at 11.5 years of age. A ChEAT score ≥ 22.5 (85th percentile) was used as an indicator of problematic eating attitudes. Analysis was based on intention-to-treat, accounting for clustering within hospitals/clinics. RESULTS Compared with the control arm, the experimental intervention substantially increased breastfeeding exclusivity (43.3% vs 6.4% exclusively breastfed at 3 months of age) and duration of any breastfeeding throughout infancy. The proportion of children with ChEAT scores ≥ 22.5 was lower in the experimental than control arm (boys 11.4% vs 17.2%; girls 18.5% vs 23.4%) [cluster-adjusted odds ratio (OR), boys: 0.44; 95% confidence interval (CI): 0.21,0.93; girls: 0.51; 95% CI: 0.27,0.99). Results were robust to adjustment for potential confounders and using a ChEAT score ≥ 25.5 (91st percentile) as the outcome (OR: 0.53; 95% CI: 0.28,1.03). CONCLUSIONS An intervention to improve the duration and exclusivity of breastfeeding among term infants in Belarus was associated with a reduction in problematic eating attitudes at 11.5 years of age.

Assessing the causal role of adiposity on disordered eating in childhood, adolescence, and adulthood: a Mendelian randomization analysis

Background: Observational studies have shown that higher body mass index (BMI) is associated with increased risk of developing disordered eating patterns. However, the causal direction of this relation remains ambiguous. Objective: We used Mendelian randomization (MR) to infer the direction of causality between BMI and disordered eating in childhood, adolescence, and adulthood. Design: MR analyses were conducted with a genetic score as an instrumental variable for BMI to assess the causal effect of BMI at age 7 y on disordered eating patterns at age 13 y with the use of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 4473). To examine causality in the reverse direction, MR analyses were used to estimate the effect of the same disordered eating patterns at age 13 y on BMI at age 17 y via a split-sample approach in the ALSPAC. We also investigated the causal direction of the association between BMI and eating disorders (EDs) in adults via a two-sample MR approach and publically available genome-wide association study data. Results: MR results indicated that higher BMI at age 7 y likely causes higher levels of binge eating and overeating, weight and shape concerns, and weight-control behavior patterns in both males and females and food restriction in males at age 13 y. Furthermore, results suggested that higher levels of binge eating and overeating in males at age 13 y likely cause higher BMI at age 17 y. We showed no evidence of causality between BMI and EDs in adulthood in either direction. Conclusions: This study provides evidence to suggest a causal effect of higher BMI in childhood and increased risk of disordered eating at age 13 y. Furthermore, higher levels of binge eating and overeating may cause higher BMI in later life. These results encourage an exploration of the ways to break the causal chain between these complex phenotypes, which could inform and prevent disordered eating problems in adolescence.

Variation in the SLC23A1 gene does not influence cardiometabolic outcomes to the extent expected given its association with l-ascorbic acid

Background: Observational studies showed that circulating l-ascorbic acid (vitamin C) is inversely associated with cardiometabolic traits. However, these studies were susceptible to confounding and reverse causation. Objectives: We assessed the relation between l-ascorbic acid and 10 cardiometabolic traits by using a single nucleotide polymorphism in the solute carrier family 23 member 1 (SLC23A1) gene (rs33972313) associated with circulating l-ascorbic acid concentrations. The observed association between rs33972313 and cardiometabolic outcomes was compared with that expected given the rs33972313-l-ascorbic acid and l-ascorbic acid–outcome associations. Design: A meta-analysis was performed in the following 5 independent studies: the British Womens Heart and Health Study (n = 1833), the MIDSPAN study (n = 1138), the Ten Towns study (n = 1324), the British Regional Heart Study (n = 2521), and the European Prospective Investigation into Cancer (n = 3737). Results: With the use of a meta-analysis of observational estimates, inverse associations were shown between l-ascorbic acid and systolic blood pressure, triglycerides, and the waist-hip ratio [the strongest of which was the waist-hip ratio (−0.13-SD change; 95% CI: −0.20-, −0.07-SD change; P = 0.0001) per SD increase in l-ascorbic acid], and a positive association was shown with high-density lipoprotein (HDL) cholesterol. The variation at rs33972313 was associated with a 0.18-SD (95% CI: 0.10-, 0.25-SD; P = 3.34 × 10−6) increase in l-ascorbic acid per effect allele. There was no evidence of a relation between the variation at rs33972313 and any cardiometabolic outcome. Although observed estimates were not statistically different from expected associations between rs33972313 and cardiometabolic outcomes, estimates for low-density lipoprotein cholesterol, HDL cholesterol, triglycerides, glucose, and body mass index were in the opposite direction to those expected. Conclusions: The nature of the genetic association exploited in this study led to limited statistical application, but despite this, when all cardiometabolic traits were assessed, there was no evidence of any trend supporting a protective role of l-ascorbic acid. In the context of existing work, these results add to the suggestion that observational relations between l-ascorbic acid and cardiometabolic health may be attributable to confounding and reverse causation.