George Davey Smith

Bio: George Davey Smith is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Mendelian randomization. The author has an hindex of 224, co-authored 2540 publications receiving 248373 citations. Previous affiliations of George Davey Smith include Keele University & Western Infirmary.

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method

Abstract: We identify common genetic variants associated with cognitive performance using a two-stage approach, which we call the proxy-phenotype method. First, we conduct a genome-wide association study of educational attainment in a large sample (n = 106,736), which produces a set of 69 education-associated SNPs. Second, using independent samples (n = 24,189), we measure the association of these education-associated SNPs with cognitive performance. Three SNPs (rs1487441, rs7923609, and rs2721173) are significantly associated with cognitive performance after correction for multiple hypothesis testing. In an independent sample of older Americans (n = 8,652), we also show that a polygenic score derived from the education-associated SNPs is associated with memory and absence of dementia. Convergent evidence from a set of bioinformatics analyses implicates four specific genes (KNCMA1, NRXN1, POU2F3, and SCRT). All of these genes are associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory.

Blood pressure reactions to acute psychological stress and future blood pressure status: a 10-year follow-up of men in the Whitehall II study.

Abstract: Objective The aim of this study was to examine whether blood pressure reactions to mental stress predicted future blood pressure and hypertension. Methods Blood pressure was recorded at an initial medical screening examination after which blood pressure reactions to a mental stress task were determined. A follow-up screening assessment of blood pressure and antihypertensive medication status was undertaken 10 years later. Data were available for 796 male public servants, between 35 and 55 years of age upon entry to the study. Results Systolic blood pressure reactions to mental stress were positively correlated with follow-up screening systolic blood pressure and to a lesser extent, follow-up diastolic pressure. In multivariate tests, by far the strongest predictors of follow-up blood pressures were initial screening blood pressures. In the case of follow-up systolic blood pressure, systolic reactions to stress emerged as an additional predictor of follow-up systolic blood pressure. With regard to follow-up diastolic blood pressure, reactivity did not enter the analogous equations. The same outcomes emerged when the analyses were adjusted for medication status. When hypertension at 10-year follow-up was the focus, both systolic and diastolic reactions to stress were predictive. However, with correction for age and initial screening blood pressure, these associations were no longer statistically significant. Conclusions The results of this study provide modest support for the hypothesis that heightened blood pressure reactions to mental stress contribute to the development of high blood pressure. At the same time, they question the clinical utility of stress testing as a prognostic device.

Differences in smoking associated DNA methylation patterns in South Asians and Europeans

Abstract: DNA methylation is strongly associated with smoking status at multiple sites across the genome. Studies have largely been restricted to European origin individuals yet the greatest increase in smoking is occurring in low income countries, such as the Indian subcontinent. We determined whether there are differences between South Asians and Europeans in smoking related loci, and if a smoking score, combining all smoking related DNA methylation scores, could differentiate smokers from non-smokers. Illumina HM450k BeadChip arrays were performed on 192 samples from the Southall And Brent REvisited (SABRE) cohort. Differential methylation in smokers was identified in 29 individual CpG sites at 18 unique loci. Interaction between smoking status and ethnic group was identified at the AHRR locus. Ethnic differences in DNA methylation were identified in non-smokers at two further loci, 6p21.33 and GNG12. With the exception of GFI1 and MYO1G these differences were largely unaffected by adjustment for cell composition. A smoking score based on methylation profile was constructed. Current smokers were identified with 100% sensitivity and 97% specificity in Europeans and with 80% sensitivity and 95% specificity in South Asians. Differences in ethnic groups were identified in both single CpG sites and combined smoking score. The smoking score is a valuable tool for identification of true current smoking behaviour. Explanations for ethnic differences in DNA methylation in association with smoking may provide valuable clues to disease pathways.

Patterns and distribution of tobacco consumption in India: cross sectional multilevel evidence from the 1998-9 national family health survey

Abstract: Objective To investigate the demographic, socioeconomic, and geographical distribution of tobacco consumption in India. Design Multilevel cross sectional analysis of the 1998-9 Indian national family health survey of 301 984 individuals in 92 447 households in 3215 villages in 440 districts in 26 states. Setting Indian states. Participants 301 984 adults (≥ 18 years). Main outcome measures Dichotomous variable for smoking and chewing tobacco for each respondent (1 if yes, 0 if no) as well as a combined measure of whether an individual smokes, chews tobacco, or both. Results Smoking and chewing tobacco are systematically associated with socioeconomic markers at the individual and household level. Individuals with no education are 2.69 times more likely to smoke and chew tobacco than those with postgraduate education. Households belonging to the lowest fifth of a standard of living index were 2.54 times more likely to consume tobacco than those in the highest fifth. Scheduled tribes (odds ratio 1.23, 95% confidence interval 1.18 to 1.29) and scheduled castes (1.19, 1.16 to 1.23) were more likely to consume tobacco than other caste groups. The socioeconomic differences are more marked for smoking than for chewing tobacco. Socioeconomic markers and demographic characteristics of individuals and households do not account fully for the differences at the level of state, district, and village in smoking and chewing tobacco, with state accounting for the bulk of the variation in tobacco consumption. Conclusion The distribution of tobacco consumption is likely to maintain, and perhaps increase, the current considerable socioeconomic differentials in health in India. Interventions aimed at influencing change in tobacco consumption should consider the socioeconomic and geographical determinants of people9s susceptibility to consume tobacco.

Association of Genetic Variants Related to CETP Inhibitors and Statins With Lipoprotein Levels and Cardiovascular Risk

Abstract: Dr Oliver-Williams is supported by Homerton College, University of Cambridge. Dr Butterworth is supported by the European Research Council. Dr Danesh is supported by the Medical Research Council, British Heart Foundation, and the National Institute for Health Research. Dr Davey Smith works within the Medical Research Council Integrative Epidemiology Unit at the University of Bristol, which is supported by the Medical Research Council (MC_UU_12013/1) and the University of Bristol.

Measuring inconsistency in meta-analyses

Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

Bias in meta-analysis detected by a simple, graphical test

Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

Abstract: Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

Abstract: Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate