Biology subjects

George Davey Smith

Publications and source records attributed to George Davey Smith.

6 recordsLinked to original sources

bioRxiv2016

Collider Scope: How selection bias can induce spurious associations

Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited - either through selection into studies, or by attrition from studies over time. Here we explore the potential impact of this selection bias on results obtained from these studies, from the perspective that this amounts to conditioning on a collider (i.e., a form of collider bias). While it is acknowledged that selection bias will have a strong effect on representativeness and prevalence estimates, it is often assumed that it should not have a strong impact on estimates of associations. We argue that because selection can induce collider bias (which occurs when two variables independently influence a third variable, and that third variable is conditioned upon), selection can lead to substantially biased estimates of associations. In particular, selection related to phenotypes can bias associations with genetic variants associated with those phenotypes. In simulations, we show that even modest influences on selection into, or attrition from, a study can generate biased and potentially misleading estimates of both phenotypic and genotypic associations. Our results highlight the value of knowing which population your study sample is representative of. If the factors influencing selection and attrition are known, they can be adjusted for. For example, having DNA available on most participants in a birth cohort study offers the possibility of investigating the extent to which polygenic scores predict subsequent participation, which in turn would enable sensitivity analyses of the extent to which bias might distort estimates.\n\nKey MessagesSelection bias (including selective attrition) may limit the representativeness of large-scale cross-sectional and cohort studies.\n\nThis selection bias may induce collider bias (which occurs when two variables independently influence a third variable, and that variable is conditioned upon).\n\nThis may lead to substantially biased estimates of associations, including of genetic associations, even when selection / attrition is relatively modest.

Epidemiology↗

bioRxiv2016

The Causal Effects of Education on Health, Mortality, Cognition, Well-being, and Income in the UK Biobank

Educated people are generally healthier, have fewer comorbidities and live longer than people with less education. Previous evidence about the effects of education come from observational studies many of which are affected by residual confounding. Legal changes to the minimum school leave age is a potential natural experiment which provides a potentially more robust source of evidence about the effects of schooling. Previous studies have exploited this natural experiment using population-level administrative data to investigate mortality, and relatively small surveys to investigate the effect on mortality. Here, we add to the evidence using data from a large sample from the UK Biobank. We exploit the raising of the school-leaving age in the UK in September 1972 as a natural experiment and regression discontinuity and instrumental variable estimators to identify the causal effects of staying on in school. Remaining in school was positively associated with 23 of 25 outcomes. After accounting for multiple hypothesis testing, we found evidence of causal effects on twelve outcomes, however, the associations of schooling and intelligence, smoking, and alcohol consumption may be due to genomic and socioeconomic confounding factors. Education affects some, but not all health and socioeconomic outcomes. Differences between educated and less educated people may be partially due to residual genetic and socioeconomic confounding.\n\nSignificance StatementOn average people who choose to stay in education for longer are healthier, wealthier, and live longer. We investigated the causal effects of education on health, income, and well-being later in life. This is the largest study of its kind to date and it has objective clinic measures of morbidity and aging. We found evidence that people who were forced to remain in school had higher wages and lower mortality. However, there was little evidence of an effect on intelligence later in life. Furthermore, estimates of the effects of education using conventionally adjusted regression analysis are likely to suffer from genomic confounding. In conclusion, education affects some, but not all health outcomes later in life.\n\nFundingThe Medical Research Council (MRC) and the University of Bristol fund the MRC Integrative Epidemiology Unit [MC_UU_12013/1, MC_UU_12013/9]. NMD is supported by the Economics and Social Research Council (ESRC) via a Future Research Leaders Fellowship [ES/N000757/1]. The research described in this paper was specifically funded by a grant from the Economics and Social Research Council for Transformative Social Science. No funding body has influenced data collection, analysis or its interpretations. This publication is the work of the authors, who serve as the guarantors for the contents of this paper. This work was carried out using the computational facilities of the Advanced Computing Research Centre -http://www.bris.ac.uk/acrc/ and the Research Data Storage Facility of the University of Bristol -- http://www.bris.ac.uk/acrc/storage/. This research was conducted using the UK Biobank Resource.\n\nData accessThe statistical code used to produce these results can be accessed here: (https://github.com/nmdavies/UKbiobankROSLA). The final analysis dataset used in this study is archived with UK Biobank, which can be accessed by contacting UK Biobank access@biobank.ac.uk.

Epidemiology↗

bioRxiv2016

Metabolic signatures of birth weight in 18288 adolescents and adults

BackgroundLower birth weight is associated with increased susceptibility to cardiometabolic diseases in adulthood, but the underlying molecular pathways are incompletely understood. We examined associations of birth weight with a comprehensive metabolic profile measured in adolescents and adults.\n\nMethodsHigh-throughput nuclear magnetic resonance metabolomics and biochemical assays were used to quantify 87 circulating metabolic measures in seven cohorts from Finland and the United Kingdom comprising altogether 18 288 individuals (mean age 26 years, range 15-75). Metabolic associations with birth weight were assessed by linear regression models adjusted for sex, gestational age, and age at blood sampling. The metabolic associations with birth weight were compared to the corresponding associations with adult body mass index (BMI).\n\nResultsLower birth weight was adversely associated with cardiometabolic biomarkers, including lipoprotein subclasses, fatty acids, amino acids, and markers of inflammation and impaired liver function (P<0.0015 for 46 measures). Associations were consistent across cohorts with different ages at metabolic profiling, but the magnitudes were weak. The pattern of metabolic deviations associated with lower birth weight resembled the metabolic signature of higher adult BMI (R2=0.77). The resemblance indicated that 1-kg lower birth weight is associated with similar metabolic aberrations as caused by 0.92-units higher BMI in adulthood.\n\nConclusionLower birth weight is associated with adverse biomarker aberrations across multiple metabolic pathways. Coherent metabolic signatures between lower birth weight and higher adult adiposity suggest potentially shared underlying molecular mechanisms. However, the magnitudes of metabolic associations with birth weight are modest in comparison to the effects of adiposity, implying that birth weight is only a weak indicator of metabolic risk in adulthood.\n\nKEY POINTSO_LILower birth weight is adversely associated with a wide range of established and emerging circulating cardiometabolic biomarkers in adulthood, including lipoprotein subclasses and their lipids, fatty acid balance, amino acids, and markers of inflammation and liver function.\nC_LIO_LIThe metabolic associations are consistent across a wide age span from adolescence to retirement age, and similar for men and women.\nC_LIO_LIThe magnitudes of metabolic aberrations are weak for the variation in birth weight observed in general population cohorts. Although the metabolic associations with birth weight are statistically significant, they are likely to be of minor public health relevance.\nC_LIO_LIThe overall metabolic association pattern with lower birth weight closely resembles the metabolic signature of higher adult adiposity, suggesting that shared underlying metabolic pathways may be involved.\nC_LIO_LI1-kg lower birth weight ({approx}2 SD) is associated with similar adverse metabolic effects as caused by 0.92 higher BMI ({approx}0.25 SD) in adulthood. These findings indicate that fetal growth, as assessed by birth weight, only has minor effects on the adult metabolic risk profile in general population settings.\nC_LI

Systems Biology↗

bioRxiv2015

Genetic Associations with Subjective Well-Being Also Implicate Depression and Neuroticism

We conducted a genome-wide association study of subjective well-being (SWB) in 298,420 individuals. We also performed auxiliary analyses of depressive symptoms (\"DS\"; N = 161,460) and neuroticism (N = 170,910), both of which have a substantial genetic correlation with SWB [Formula]. We identify three SNPs associated with SWB at genome-wide significance. Two of them are significantly associated with DS in an independent sample. In our auxiliary analyses, we identify 13 additional genome-wide-significant associations: two with DS and eleven with neuroticism, including two inversion polymorphisms. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are enriched. The discovery of genetic loci associated with the three phenotypes we study has proven elusive; our findings illustrate the payoffs from studying them jointly.\n\nOne Sentence Summary: Using both genome-wide association studies and proxy-phenotype studies, we identify genetic variants associated with subjective well-being, depressive symptoms, and neuroticism.

Genetics↗

bioRxiv2015

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of that risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortia and population based resources, we find genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both inherited and de novo variation, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in an ASD or other neuropsychiatric disorder diagnosis. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.

Genetics↗

bioRxiv2015

Mendelian randomization: a premature burial?

Mendelian randomization is a promising approach to help improve causal inference in observational studies, with widespread potential applications, including to prioritization of pharmacotherapeutic targets for evaluation in RCTs. From its initial proposal the limitations of Mendelian randomization approaches have been widely recognised and discussed, and recently Pickrell has reiterated these1. However this critique did not acknowledge recent developments in both methodological and empirical research, nor did it recognise many future opportunities for application of the Mendelian randomization approach. These issues are briefly reviewed here.

Genetics↗