Causal Inference in Developmental Origins of Health and Disease (DOHaD) Research

Gage, Suzanne H.; Munafò, Marcus R; Smith, George Davey

doi:10.1146/annurev-psych-122414-033352

Cited by 153 publications

(162 citation statements)

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“…They also illustrate the need to triangulate potentially important findings with both mechanistic studies that interrogate putative biological pathways (study 2) and direct replication studies (study 3), where possible using methods that support stronger causal inference 50. Given the growing concerns that many published biomedical research findings may be false 51, and that the reproducibility of much research is consequently lower than is desirable 52, we believe that approaches similar to that we have adopted here will be increasingly important.…”

Section: Discussionmentioning

confidence: 91%

Does coffee consumption impact on heaviness of smoking?

et al. 2017

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Background and AimsCoffee consumption and cigarette smoking are strongly associated, but whether this association is causal remains unclear. We sought to: (1) determine whether coffee consumption influences cigarette smoking causally, (2) estimate the magnitude of any association and (3) explore potential mechanisms.DesignWe used Mendelian randomization (MR) analyses of observational data, using publicly available summarized data from the Tobacco and Genetics (TAG) consortium, individual‐level data from the UK Biobank and in‐vitro experiments of candidate compounds.SettingThe TAG consortium includes data from studies in several countries. The UK Biobank includes data from men and women recruited across England, Wales and Scotland.ParticipantsThe TAG consortium provided data on n ≤ 38 181 participants. The UK Biobank provided data on 8072 participants.MeasurementsIn MR analyses, the exposure was coffee consumption (cups/day) and the outcome was heaviness of smoking (cigarettes/day). In our in‐vitro experiments we assessed the effect of caffeic acid, quercetin and p‐coumaric acid on the rate of nicotine metabolism in human liver microsomes and cDNA‐expressed human CYP2A6.FindingsTwo‐sample MR analyses of TAG consortium data indicated that heavier coffee consumption might lead to reduced heaviness of smoking [beta = −1.49, 95% confidence interval (CI) = −2.88 to −0.09]. However, in‐vitro experiments found that the compounds investigated are unlikely to inhibit significantly the rate of nicotine metabolism following coffee consumption. Further MR analyses in UK Biobank found no evidence of a causal relationship between coffee consumption and heaviness of smoking (beta = 0.20, 95% CI = –1.72 to 2.12).ConclusionsAmount of coffee consumption is unlikely to have a major causal impact upon amount of cigarette smoking. If it does influence smoking, this is not likely to operate via effects of caffeic acid, quercetin or p‐coumaric acid on nicotine metabolism. The observational association between coffee consumption and cigarette smoking may be due to smoking impacting on coffee consumption or confounding.

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Section: Discussionmentioning

confidence: 91%

Does coffee consumption impact on heaviness of smoking?

et al. 2017

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“…Bradykinin is a peptide hormone which is a pro-inflammatory mediator and is involved in vascular permeability and mitogenesis 42 . To our knowledge, variants in this gene and the genome-wide significant SNPs on chromosome 1 have not been identified in previous GWAS of any phenotype 43 , 44 . We have not attempted to replicate the genome-wide hits in independent samples, as we cannot assume that different studies would have the same influences on participation.…”

Section: Discussionmentioning

confidence: 99%

Exploring the association of genetic factors with participation in the Avon Longitudinal Study of Parents and Children

Taylor

Jones

Sallis

et al. 2018

International Journal of Epidemiology

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BackgroundIt is often assumed that selection (including participation and dropout) does not represent an important source of bias in genetic studies. However, there is little evidence to date on the effect of genetic factors on participation.MethodsUsing data on mothers (N = 7486) and children (N = 7508) from the Avon Longitudinal Study of Parents and Children, we: (i) examined the association of polygenic risk scores for a range of sociodemographic and lifestyle characteristics and health conditions related to continued participation; (ii) investigated whether associations of polygenic scores with body mass index (BMI; derived from self-reported weight and height) and self-reported smoking differed in the largest sample with genetic data and a subsample who participated in a recent follow-up; and (iii) determined the proportion of variation in participation explained by common genetic variants, using genome-wide data.ResultsWe found evidence that polygenic scores for higher education, agreeableness and openness were associated with higher participation; and polygenic scores for smoking initiation, higher BMI, neuroticism, schizophrenia, attention-deficit hyperactivity disorder (ADHD) and depression were associated with lower participation. Associations between the polygenic score for education and self-reported smoking differed between the largest sample with genetic data [odds ratio (OR) for ever smoking per standard deviation (SD) increase in polygenic score: 0.85, 95% confidence interval (CI): 0.81, 0.89} and subsample (OR: 0.96, 95% CI: 0.89, 1.03). In genome-wide analysis, single nucleotide polymorphism based heritability explained 18–32% of variability in participation.ConclusionsGenetic association studies, including Mendelian randomization, can be biased by selection, including loss to follow-up. Genetic risk for dropout should be considered in all analyses of studies with selective participation.

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“…However, alternatives to the DOHaD hypothesis suggest that exposure to suboptimal pregnancy conditions (e.g. teratogens) may produce static structural changes in the brain that have lasting effects, or unmeasured genetic and/or postnatal environmental confounding variables can contribute (D'Onofrio, Class, Lahey, & Larsson, 2014;Gage, Munaf o, & Davey Smith, 2016;Lewis, Galbally, Gannon, & Symeonides, 2014).…”

Section: Introductionmentioning

confidence: 99%