scholarly journals Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank

BMJ ◽  
2018 ◽  
pp. k1767 ◽  
Author(s):  
Robert Carreras-Torres ◽  
Mattias Johansson ◽  
Philip C Haycock ◽  
Caroline L Relton ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Smoking Behaviour ◽  
Mendelian Randomisation ◽  
Uk Biobank

scholarly journals Mendelian randomisation analysis of the effect of educational attainment and cognitive ability on smoking behaviour

2018 ◽  
Author(s):  
Eleanor Sanderson ◽  
George Davey Smith ◽  
Jack Bowden ◽  
Marcus R. Munafò
Keyword(s):  
Educational Attainment ◽  
Health Outcomes ◽  
Cognitive Ability ◽  
Smoking Behaviour ◽  
Mendelian Randomisation ◽  
Individual Data ◽  
General Cognitive Ability ◽  
Uk Biobank ◽  
The Uk ◽  
Summary Data

AbstractRecent analyses have shown educational attainment to be associated with a number of health outcomes. This association may, in part, be due to an effect of educational attainment on smoking behaviour. In this study we apply a multivariable Mendelian randomisation design to determine whether the effect of educational attainment on smoking behaviour could be due to educational attainment or general cognitive ability. We use individual data from the UK Biobank study (N = 120,050) and summary data from large GWAS studies of educational attainment, cognitive ability and smoking behaviour. Our results show that more years of education are associated with a reduced likelihood of smoking which is not due to an effect of general cognitive ability on smoking behaviour. Given the considerable physical harms associated with smoking, the effect of educational attainment on smoking is likely to contribute to the health inequalities associated with differences in educational attainment.

A life course approach to elucidate the role of adiposity in asthma risk: evidence from a Mendelian randomisation study

2020 ◽  
pp. jech-2020-213745
Author(s):  
Shiu Lun Au Yeung ◽  
Albert Martin Li ◽  
C Mary Schooling
Keyword(s):  
Childhood Obesity ◽  
Life Course ◽  
Life Course Perspective ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Asthma Risk ◽  
A Genome ◽  
The Uk ◽  
The Relationship

BackgroundAdiposity is associated with asthma although studies do not usually explore the inter-related role of childhood and adult adiposity in asthma risk using a life course perspective.MethodsWe conducted a Mendelian randomisation (MR) study using genetic instruments for childhood body mass index (BMI) (n=47 541), childhood obesity (n=29 822) and adult BMI (n=681 725) applied to the UK Biobank (n=401 837), with validation in a genome-wide association study of asthma (GABRIEL, n=5616). We used inverse variance weighting and other sensitivity analyses to examine the relationship between adiposity and asthma risk. We assessed mediation using multivariable Mendelian randomisation (MVMR) analysis.ResultsChildhood BMI was related to asthma in the UK Biobank (OR 1.10 per SD increase, 95% CI 0.99 to 1.22). Adult BMI was associated with asthma risk (OR 1.33 per SD increase, 95% CI 1.25 to 1.43). Analyses in GABRIEL gave directionally consistent results but with wide CI. The relationship between childhood obesity and asthma risk was less clear in both data sources. MVMR suggested the relation of childhood BMI with asthma risk was largely mediated via adult BMI.ConclusionAdiposity in childhood likely cause asthma, but the effect is primarily mediated via adult BMI.

scholarly journals 146Mendelian randomisation for mediation analysis: current methods and challenges for implementation

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Alice Carter ◽  
Eleanor Sanderson ◽  
Gemma Hammerton ◽  
Rebecca Richmond ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Measurement Error ◽  
Causal Inference ◽  
Mediation Analysis ◽  
Mendelian Randomization ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Reverse Causality ◽  
Single Model ◽  
Instrument Bias

Abstract Background Mendelian randomisation uses genetic variants randomly allocated at conception as instrumental variables for an exposure. Methodological advances allow for mediation analysis to be carried out using Mendelian randomisation using either multivariable Mendelian randomisation or two-step Mendelian randomisation. Methods We use simulations and an applied example to demonstrate when multivariable Mendelian randomisation and two-step Mendelian randomisation methods are valid and how they relate to traditional phenotypic regression-based approaches to mediation. We demonstrate how Mendelian randomisation methods can relax assumptions required for causal inference in phenotypic mediation, as well as which Mendelian randomisation specific assumptions are required. We illustrate our methods in data from UK Biobank, estimating the role of body mass index mediating the association between education and cardiovascular outcomes. Results Both multivariable Mendelian randomization and two-step Mendelian randomization are unbiased when estimating the total effect, direct effect, indirect effect and proportion mediated when both confounding, and measurement error are present. Multivariable Mendelian Randomization can be used when multiple mediators are to be investigated in a single model. Conclusions Mendelian randomisation provides an opportunity to improve causal inference in mediation analysis. Although Mendelian randomisation specific assumptions apply, such as no weak instrument bias and no pleiotropic pathways, strong phenotypic assumptions of no confounding and no measurement error can be relaxed. Key messages Mendelian randomisation offers an opportunity to address bias by unmeasured confounding, measurement error and reverse causality in mediation analysis.

scholarly journals Assessing the role of cortisol in cancer: a wide-ranged Mendelian randomisation study

2021 ◽  
Author(s):  
Susanna C. Larsson ◽  
Wei-Hsuan Lee ◽  
Siddhartha Kar ◽  
Stephen Burgess ◽  
Elias Allara
Keyword(s):  
Mendelian Randomisation

scholarly journals Socioeconomic Inequalities and Ethnicity Are Associated with a Positive COVID-19 Test among Cancer Patients in the UK Biobank Cohort

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1514
Author(s):  
Shing Fung Lee ◽  
Maja Nikšić ◽  
Bernard Rachet ◽  
Maria-Jose Sanchez ◽  
Miguel Angel Luque-Fernandez
Keyword(s):  
Cancer Patients ◽  
Socioeconomic Inequalities ◽  
Uk Biobank ◽  
Incident Cancer ◽  
Increased Risk ◽  
Exposure Variable ◽  
Independent Risk Factors ◽  
The Uk ◽  
Deprived Areas

We explored the role of socioeconomic inequalities in COVID-19 incidence among cancer patients during the first wave of the pandemic. We conducted a case-control study within the UK Biobank cohort linked to the COVID-19 tests results available from 16 March 2020 until 23 August 2020. The main exposure variable was socioeconomic status, assessed using the Townsend Deprivation Index. Among 18,917 participants with an incident malignancy in the UK Biobank cohort, 89 tested positive for COVID-19. The overall COVID-19 incidence was 4.7 cases per 1000 incident cancer patients (95%CI 3.8–5.8). Compared with the least deprived cancer patients, those living in the most deprived areas had an almost three times higher risk of testing positive (RR 2.6, 95%CI 1.1–5.8). Other independent risk factors were ethnic minority background, obesity, unemployment, smoking, and being diagnosed with a haematological cancer for less than five years. A consistent pattern of socioeconomic inequalities in COVID-19 among incident cancer patients in the UK highlights the need to prioritise the cancer patients living in the most deprived areas in vaccination planning. This socio-demographic profiling of vulnerable cancer patients at increased risk of infection can inform prevention strategies and policy improvements for the coming pandemic waves.

scholarly journals Osteoarthritis: Insights Offered by the Study of Bone Mass Genetics

2021 ◽  
Vol 19 (2) ◽  
pp. 115-122
Author(s):  
A. Hartley ◽  
C. L. Gregson ◽  
L. Paternoster ◽  
J. H. Tobias
Keyword(s):  
Bone Mass ◽  
Causal Effect ◽  
Mendelian Randomisation ◽  
Mineral Density ◽  
High Bone Mass ◽  
Increased Risk ◽  
High Bone ◽  
Genetic Mechanisms ◽  
Additional Support

Abstract Purpose of Review This paper reviews how bone genetics has contributed to our understanding of the pathogenesis of osteoarthritis. As well as identifying specific genetic mechanisms involved in osteoporosis which also contribute to osteoarthritis, we review whether bone mineral density (BMD) plays a causal role in OA development. Recent Findings We examined whether those genetically predisposed to elevated BMD are at increased risk of developing OA, using our high bone mass (HBM) cohort. HBM individuals were found to have a greater prevalence of OA compared with family controls and greater development of radiographic features of OA over 8 years, with predominantly osteophytic OA. Initial Mendelian randomisation analysis provided additional support for a causal effect of increased BMD on increased OA risk. In contrast, more recent investigation estimates this relationship to be bi-directional. However, both these findings could be explained instead by shared biological pathways. Summary Pathways which contribute to BMD appear to play an important role in OA development, likely reflecting shared common mechanisms as opposed to a causal effect of raised BMD on OA. Studies in HBM individuals suggest this reflects an important role of mechanisms involved in bone formation in OA development; however further work is required to establish whether the same applies to more common forms of OA within the general population.

FC 062OBESITY AS A CAUSE OF KIDNEY DISEASE - INSIGHTS FROM MENDELIAN RANDOMISATION STUDIES

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Xiaoguang Xu ◽  
James Eales ◽  
Xiao Jiang ◽  
Eleanor Sanderson ◽  
David Scannali ◽  
...  
Keyword(s):  
Waist Circumference ◽  
Kidney Disease ◽  
Renal Disease ◽  
Kidney Diseases ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Anthropometric Indices ◽  
Health And Disease ◽  
Kidney Health

Abstract Background and Aims Obesity and kidney diseases are common complex disorders with an increasing clinical and economic impact on healthcare around the globe. We aim to examine if modifiable anthropometric indices of obesity exert putatively causal effects on different measures of kidney health and disease. Method We performed conventional observational and Mendelian randomisation (MR) study to examine if modifiable anthropometric indices of obesity exert putatively causal effects on different kidney health and disease-related phenotypes. These analyses were conducted using approximately 300,000 participants of white-British ancestry from UK Biobank and up to 480,000 participants of predominantly European ancestry from genome-wide association studies. Results The Mendelian randomisation analysis indicated that increasing values of genetically predicted BMI and waist circumference were causally linked to changes in renal function indices including reduced estimated glomerular filtration (PeGFRcystatineC=5.96 × 10-59 for BMI and PeGFRcystatineC=1.72 × 10-69 for waist circumference) and increased blood urea nitrogen (PBUN=2.01 × 10-10 for BMI and PBUN=4.54 × 10-12 for waist circumference) in UK Biobank individuals. These associations were replicated using data from CKDGen Consortium individuals (PeGFRcystatineC=1.47 × 10-5 for BMI and PeGFRcystatineC=7.63 × 10-5 for waist circumference; PBUN=1.96 × 10-4 for BMI and PBUN=3.10 × 10-3 for waist circumference). One standard deviation increase in genetically-predicted BMI and waist circumference decreased the relative odds of kidney health index by 14% and 18% (OR=0.86; 95%CI: 0.82-0.92; P=9.18 × 10-6 for BMI and OR=0.82; 95%CI: 0.75-0.90; P=2.12 × 10-5 for waist circumference). Approximately 13-16% of the causal effect of obesity indices on kidney health was mediated by blood pressure. Obesity increased the risk of both acute and chronic kidney disease of several aetiologies including hypertensive renal disease (OR=1.79; 95%CI: 1.14-2.82; P=1.15 × 10-2 for BMI and OR=2.41; 95%CI: 1.30-4.45; P=5.03 × 10-3 for waist circumference), renal failure (OR=1.51; 95%CI: 1.25-1.83; P=2.60 × 10-5 for BMI and OR=1.86; 95%CI: 1.43-2.42; P=4.16 × 10-6 for waist circumference) and CKD (OR=1.50; 95%CI: 1.16-1.96; P=2.44 × 10-3 for BMI and OR=1.83; 95%CI: 1.28-2.63; P=9.49 × 10-4 for waist circumference) and diabetic nephropathy (OR=1.92; 95%CI: 1.44-2.54; P=6.86 × 10-6 for BMI). Conclusion These findings indicate that obesity is causally linked to indices of renal health and the risk of different kidney diseases. This evidence substantiates the value of weight loss as a strategy of preventing and/or counteracting a decline in kidney health as well as decreasing the risk of renal disease.

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