Roger Harbord

Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials.

Funnel plots, and tests for funnel plot asymmetry, have been widely used to examine bias in the results of meta-analyses. Funnel plot asymmetry should not be equated with publication bias, because it has a number of other possible causes. This article describes how to interpret funnel plot asymmetry, recommends appropriate tests, and explains the implications for choice of meta-analysis model

C-reactive protein and its role in metabolic syndrome: mendelian randomisation study.

BACKGROUND Circulating C-reactive protein (CRP) is associated with the metabolic syndrome and might be causally linked to it. Our aim was to generate estimates of the association between plasma CRP and metabolic syndrome phenotypes that were free from confounding and reverse causation, to assess the causal role of this protein. METHODS We examined associations between serum CRP concentration and metabolic syndrome phenotypes in the British Womens Heart and Health Study. We then compared these estimates with those derived from a mendelian randomised framework with common CRP gene haplotypes to generate unconfounded and unbiased estimates of any causal associations. FINDINGS In a sample of British women, body-mass index (BMI), systolic blood pressure, waist-to-hip ratio, serum concentrations of HDL cholesterol and triglycerides, and insulin resistance were all associated with plasma CRP concentration. CRP haplotypes were associated with plasma CRP concentration (p<0.0001). With instrumental variable analyses, there was no association between plasma CRP concentration and any of the metabolic syndrome phenotypes analysed. There was strong evidence that linear regression and mendelian randomisation based estimation gave conflicting results for the CRP-BMI association (p=0.0002), and some evidence of conflicting results for the association of CRP with the score for insulin resistance (p=0.0139), triglycerides (p=0.0313), and HDL cholesterol (p=0.0688). INTERPRETATION Disparity between estimates of the association between plasma CRP and phenotypes comprising the metabolic syndrome derived from conventional analyses and those from a mendelian randomisation approach suggests that there is no causal association between CRP and the metabolic syndrome phenotypes.

Clustered Environments and Randomized Genes: A Fundamental Distinction between Conventional and Genetic Epidemiology

Background In conventional epidemiology confounding of the exposure of interest with lifestyle or socioeconomic factors, and reverse causation whereby disease status influences exposure rather than vice versa, may invalidate causal interpretations of observed associations. Conversely, genetic variants should not be related to the confounding factors that distort associations in conventional observational epidemiological studies. Furthermore, disease onset will not influence genotype. Therefore, it has been suggested that genetic variants that are known to be associated with a modifiable (nongenetic) risk factor can be used to help determine the causal effect of this modifiable risk factor on disease outcomes. This approach, mendelian randomization, is increasingly being applied within epidemiological studies. However, there is debate about the underlying premise that associations between genotypes and disease outcomes are not confounded by other risk factors. We examined the extent to which genetic variants, on the one hand, and nongenetic environmental exposures or phenotypic characteristics on the other, tend to be associated with each other, to assess the degree of confounding that would exist in conventional epidemiological studies compared with mendelian randomization studies. Methods and Findings We estimated pairwise correlations between nongenetic baseline variables and genetic variables in a cross-sectional study comparing the number of correlations that were statistically significant at the 5%, 1%, and 0.01% level (α = 0.05, 0.01, and 0.0001, respectively) with the number expected by chance if all variables were in fact uncorrelated, using a two-sided binomial exact test. We demonstrate that behavioural, socioeconomic, and physiological factors are strongly interrelated, with 45% of all possible pairwise associations between 96 nongenetic characteristics (n = 4,560 correlations) being significant at the p < 0.01 level (the ratio of observed to expected significant associations was 45; p-value for difference between observed and expected < 0.000001). Similar findings were observed for other levels of significance. In contrast, genetic variants showed no greater association with each other, or with the 96 behavioural, socioeconomic, and physiological factors, than would be expected by chance. Conclusions These data illustrate why observational studies have produced misleading claims regarding potentially causal factors for disease. The findings demonstrate the potential power of a methodology that utilizes genetic variants as indicators of exposure level when studying environmentally modifiable risk factors.

Alcohol Intake and Blood Pressure: A Systematic Review Implementing a Mendelian Randomization Approach

Background Alcohol has been reported to be a common and modifiable risk factor for hypertension. However, observational studies are subject to confounding by other behavioural and sociodemographic factors, while clinical trials are difficult to implement and have limited follow-up time. Mendelian randomization can provide robust evidence on the nature of this association by use of a common polymorphism in aldehyde dehydrogenase 2 (ALDH2) as a surrogate for measuring alcohol consumption. ALDH2 encodes a major enzyme involved in alcohol metabolism. Individuals homozygous for the null variant (*2*2) experience adverse symptoms when drinking alcohol and consequently drink considerably less alcohol than wild-type homozygotes (*1*1) or heterozygotes. We hypothesise that this polymorphism may influence the risk of hypertension by affecting alcohol drinking behaviour. Methods and Findings We carried out fixed effect meta-analyses of the ALDH2 genotype with blood pressure (five studies, n = 7,658) and hypertension (three studies, n = 4,219) using studies identified via systematic review. In males, we obtained an overall odds ratio of 2.42 (95% confidence interval [CI] 1.66–3.55, p = 4.8 × 10−6) for hypertension comparing *1*1 with *2*2 homozygotes and an odds ratio of 1.72 (95% CI 1.17–2.52, p = 0.006) comparing heterozygotes (surrogate for moderate drinkers) with *2*2 homozygotes. Systolic blood pressure was 7.44 mmHg (95% CI 5.39–9.49, p = 1.1 × 10−12) greater among *1*1 than among *2*2 homozygotes, and 4.24 mmHg (95% CI 2.18–6.31, p = 0.00005) greater among heterozygotes than among *2*2 homozygotes. Conclusions These findings support the hypothesis that alcohol intake has a marked effect on blood pressure and the risk of hypertension.

Using multiple genetic variants as instrumental variables for modifiable risk factors.

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.

Association of C-Reactive Protein With Blood Pressure and Hypertension Life Course Confounding and Mendelian Randomization Tests of Causality

Background—C-reactive protein (CRP) has repeatedly been associated with blood pressure and prevalent and incident hypertension, but whether a causal link exists is uncertain. Methods and Results—We assessed the cross-sectional relations of CRP to systolic blood pressure, pulse pressure, and prevalent hypertension in a representative sample of >3500 British women aged 60 to 79 years. For both outcomes, substantial associations were observed. However, these associations were greatly attenuated by adjustment for a wide range of confounding factors acting over the life course. We further investigated causality using a Mendelian randomization approach by examining the association of the 1059G/C polymorphism in the human CRP gene with CRP and with blood pressure, pulse pressure, and hypertension. The polymorphism was associated with a robust difference in CRP, and the expectation would be for higher blood pressure and pulse pressure and greater prevalence of hypertension among those carrying the genetic variant associated with higher CRP levels. This was not observed, and the predicted causal effects of CRP on blood pressure, pulse pressure, and hypertension using instrumental variables methods were close to 0, although with wide CIs. Conclusions—CRP levels are associated with blood pressure, pulse pressure, and hypertension, but adjustment for life course confounding and a Mendelian randomization approach suggest the elevated CRP levels do not lead to elevated blood pressure.

Does Greater Adiposity Increase Blood Pressure and Hypertension Risk?: Mendelian Randomization Using the FTO/MC4R Genotype

Elevated blood pressure increases the risk of experiencing cardiovascular events like myocardial infarction and stroke. Current observational data suggest that body mass index may have a causal role in the etiology of hypertension, but this may be influenced by confounding and reverse causation. Through the use of instrumental variable methods, we aim to estimate the strength of the unconfounded and unbiased association between body mass index/adiposity and blood pressure. We explore these issues in the Copenhagen General Population Study. We used instrumental variable methods to obtain estimates of the causal association between body mass index and blood pressure. This was performed using both rs9939609 (FTO) and rs17782313 (MC4R) genotypes as instruments for body mass index. Avoiding the epidemiological problems of confounding, bias, and reverse causation, we confirmed observational associations between body mass index and blood pressure. In analyses including those taking antihypertensive drugs, but for whom appropriate adjustment had been made, systolic blood pressure was seen to increase by 3.85 mm Hg (95% CI: 1.88 to 5.83 mm Hg) for each 10% increase in body mass index (P=0.0002), with diastolic blood pressure showing an increase of 1.79 mm Hg (95% CI: 0.68 to 2.90 mm Hg) for each 10% increase in body mass index (P=0.002). Observed associations are large and illustrate the considerable benefits in terms of reductions in blood pressure–related morbidity that could be achieved through a reduction in body mass index.

Exploring the Developmental Overnutrition Hypothesis Using Parental–Offspring Associations and FTO as an Instrumental Variable

Background The developmental overnutrition hypothesis suggests that greater maternal obesity during pregnancy results in increased offspring adiposity in later life. If true, this would result in the obesity epidemic progressing across generations irrespective of environmental or genetic changes. It is therefore important to robustly test this hypothesis. Methods and Findings We explored this hypothesis by comparing the associations of maternal and paternal pre-pregnancy body mass index (BMI) with offspring dual energy X-ray absorptiometry (DXA)–determined fat mass measured at 9 to 11 y (4,091 parent–offspring trios) and by using maternal FTO genotype, controlling for offspring FTO genotype, as an instrument for maternal adiposity. Both maternal and paternal BMI were positively associated with offspring fat mass, but the maternal association effect size was larger than that in the paternal association in all models: mean difference in offspring sex- and age-standardised fat mass z-score per 1 standard deviation BMI 0.24 (95% confidence interval [CI]: 0.22 to 0.26) for maternal BMI versus 0.13 (95% CI: 0.11, 0.15) for paternal BMI; p-value for difference in effect < 0.001. The stronger maternal association was robust to sensitivity analyses assuming levels of non-paternity up to 20%. When maternal FTO, controlling for offspring FTO, was used as an instrument for the effect of maternal adiposity, the mean difference in offspring fat mass z-score per 1 standard deviation maternal BMI was −0.08 (95% CI: −0.56 to 0.41), with no strong statistical evidence that this differed from the observational ordinary least squares analyses (p = 0.17). Conclusions Neither our parental comparisons nor the use of FTO genotype as an instrumental variable, suggest that greater maternal BMI during offspring development has a marked effect on offspring fat mass at age 9–11 y. Developmental overnutrition related to greater maternal BMI is unlikely to have driven the recent obesity epidemic.

An empirical comparison of methods for meta-analysis of diagnostic accuracy showed hierarchical models are necessary

OBJECTIVE Meta-analysis of studies of the accuracy of diagnostic tests currently uses a variety of methods. Statistically rigorous hierarchical models require expertise and sophisticated software. We assessed whether any of the simpler methods can in practice give adequately accurate and reliable results. STUDY DESIGN AND SETTING We reviewed six methods for meta-analysis of diagnostic accuracy: four simple commonly used methods (simple pooling, separate random-effects meta-analyses of sensitivity and specificity, separate meta-analyses of positive and negative likelihood ratios, and the Littenberg-Moses summary receiver operating characteristic [ROC] curve) and two more statistically rigorous approaches using hierarchical models (bivariate random-effects meta-analysis and hierarchical summary ROC curve analysis). We applied the methods to data from a sample of eight systematic reviews chosen to illustrate a variety of patterns of results. RESULTS In each meta-analysis, there was substantial heterogeneity between the results of different studies. Simple pooling of results gave misleading summary estimates of sensitivity and specificity in some meta-analyses, and the Littenberg-Moses method produced summary ROC curves that diverged from those produced by more rigorous methods in some situations. CONCLUSION The closely related hierarchical summary ROC curve or bivariate models should be used as the standard method for meta-analysis of diagnostic accuracy.

Incidence of severe reproductive tract complications associated with diagnosed genital chlamydial infection: the Uppsala Women's Cohort Study

Objective: To estimate the cumulative incidence of severe complications associated with genital chlamydia infection in the general female population. Methods: The Uppsala Women’s Cohort Study was a retrospective population based cohort study in Sweden, linking laboratory, hospital, and population registers. We estimated the cumulative incidence of hospital diagnosed pelvic inflammatory disease, ectopic pregnancy, and infertility, and used multivariable regression models to estimate hazard ratios according to screening status. Results: We analysed complete data from 43 715 women in Uppsala aged 15–24 years between January 1985 and December 1989. Follow up until the end of 1999 included 709 000 woman years and 3025 events. The cumulative incidence of pelvic inflammatory disease by age 35 years was 3.9% (95% CI 3.7% to 4.0%) overall: 5.6% (4.7% to 6.7%) in women who ever tested positive for chlamydia, 4.0% (3.7% to 4.4%) in those with negative tests, and 2.9% (2.7% to 3.2%) in those who were never screened. The corresponding figures were: for ectopic pregnancy, 2.3% (2.2% to 2.5%) overall, 2.7% (2.1% to 3.5%), 2.0% (1.8% to 2.3%), and 1.9% (1.7% to 2.1%); and for infertility, 4.1% (3.9% to 4.3%) overall, 6.7% (5.7% to 7.9%), 4.7% (4.4% to 5.1%), and 3.1% (2.8% to 3.3%). Low educational attainment was strongly associated with the development of all outcomes. Conclusions: The incidence of severe chlamydia associated complications estimated from ours, and other population based studies, was lower than expected. Studies that incorporate data about pelvic inflammatory disease diagnosed in primary care and behavioural risk factors would further improve our understanding of the natural history of chlamydia. Our results provide reassurance for patients, but mean that the benefits of chlamydia screening programmes might have been overestimated.