scholarly journals Obesity as a cause of kidney disease - insights from Mendelian randomisation studies

2020 ◽  
Author(s):  
Xiaoguang Xu ◽  
James M. Eales ◽  
Xiao Jiang ◽  
Eleanor Sanderson ◽  
David Scannali ◽  
...  
Keyword(s):  
Waist Circumference ◽  
Kidney Disease ◽  
Renal Disease ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Health Index ◽  
Genome Wide ◽  
Kidney Health

Objective: To examine if modifiable anthropometric indices of obesity exert putatively causal effects on different measures of kidney health and disease. Design: Conventional observational and Mendelian randomisation study. Setting: UK Biobank and international genome-wide association studies. Participants: 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. Main outcome measures: Estimated glomerular filtration, blood urea nitrogen, kidney health index, chronic kidney disease, hypertensive renal disease, renal failure, acute renal failure, other disorders of kidney and ureters, IgA nephropathy and diabetic nephropathy. Results: The Mendelian randomisation analysis indicated that increasing values of genetically predicted body mass index (BMI) and waist circumference were causally linked to changes in renal function indices including reduced estimated glomerular filtration and increased blood urea nitrogen in UK Biobank individuals. These associations were replicated using data from CKDGen Consortium individuals. 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, respectively). 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 and diabetic nephropathy. Conclusions: 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.

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.

Body size and composition and site-specific cancers in UK Biobank: a Mendelian randomisation study

2020 ◽  
Author(s):  
Mathew Vithayathil ◽  
Paul Carter ◽  
Siddhartha Kar ◽  
Amy M. Mason ◽  
Stephen Burgess ◽  
...  
Keyword(s):  
Instrumental Variables ◽  
Association Studies ◽  
Genome Wide Association ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Site Specific ◽  
Genome Wide ◽  
Increased Risk ◽  
The Uk

ABSTRACTObjectivesTo investigate the casual role of body mass index, body fat composition and height in cancer.DesignTwo stage mendelian randomisation studySettingPrevious genome wide association studies and the UK BiobankParticipantsGenetic instrumental variables for body mass index (BMI), fat mass index (FMI), fat free mass index (FFMI) and height from previous genome wide association studies and UK Biobank. Cancer outcomes from 367 586 participants of European descent from the UK Biobank.Main outcome measuresOverall cancer risk and 22 site-specific cancers risk for genetic instrumental variables for BMI, FMI, FFMI and height.ResultsGenetically predicted BMI (per 1 kg/m2) was not associated with overall cancer risk (OR 0.99; 95% confidence interval (CI) 0-98-1.00, p=0.105). Elevated BMI was associated with increased risk of stomach cancer (OR 1.15, 95% (CI) 1.05-1.26; p=0.003) and melanoma (OR 0.96, 95% CI 0.92-1.00; p=0.044). For sex-specific cancers, BMI was positively associated with uterine cancer (OR 1.08, 95% CI 1.01-1.14; p=0.015) but inversely associated with breast (OR 0.95, 95% CI 0.92-0.98; p=0.001), prostate (OR 0.95, 95% CI 0.92-0.99; p=0.007) and testicular cancer (OR 0.89, 95% CI 0.81-0.98; p=0.017). Elevated FMI (per 1 kg/m2) was associated with gastrointestinal cancer (stomach cancer OR 4.23, 95% CI 1.18-15.13, p=0.027; colorectal cancer OR 1.94, 95% CI 1.23-3.07; p=0.004). Increased height (per 1 standard deviation, approximately 6.5cm) was associated with increased risk of overall cancer (OR 1.06; 95% 1.04-1.09; p = 2.97×10-8) and most site-specific cancers with the strongest estimates for kidney, non-Hodgkin lymphoma, colorectal, lung, melanoma and breast cancer.ConclusionsThere is little evidence for BMI as a casual risk factor for cancer. BMI may have a causal role for sex-specific cancers, although with inconsistent directions of effect, and FMI for gastrointestinal malignancies. Elevated height is a risk factor for overall cancer and multiple site cancers.

scholarly journals Genetic liability to insomnia in relation to cardiovascular diseases: a Mendelian randomisation study

2021 ◽  
Author(s):  
Shuai Yuan ◽  
Amy M. Mason ◽  
Stephen Burgess ◽  
Susanna C. Larsson
Keyword(s):  
Cardiovascular Diseases ◽  
Association Studies ◽  
European Ancestry ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genetic Liability ◽  
Genome Wide ◽  
Increased Risk ◽  
The Uk

AbstractThe present study aimed to determine the associations between insomnia and cardiovascular diseases (CVDs) using Mendelian randomisation (MR) analysis. As instrumental variables, we used 208 independent single-nucleotide polymorphisms associated with insomnia at the genome-wide significance threshold in a meta-analysis of genome-wide association studies in the UK Biobank and 23andMe including a total of 397 959 self-reported insomnia cases and 933 057 non-cases. Summary-level data for nine CVDs were obtained from the UK Biobank including 367 586 individuals of European ancestry. After correction for multiple testing, genetic liability to insomnia was associated with higher odds of six CVDs, including peripheral arterial disease (odd ratio (OR) 1.22; 95% confidence interval (CI), 1.21, 1.33), heart failure (OR 1.21; 95% CI, 1.13, 1.30), coronary artery disease (OR 1.19; 95% CI, 1.14, 1.25), ischaemic stroke (OR 1.15; 95% CI, 1.06, 1.25), venous thromboembolism (OR 1.13; 95% CI, 1.07, 1.19) and atrial fibrillation (OR 1.10; 95% CI, 1.05, 1.15). There were suggestive associations for aortic valve stenosis (OR, 1.17; 95% CI, 1.04, 1.32) and haemorrhagic stroke (OR 1.14; 95% CI, 1.00, 1.29) but no association for abdominal aortic aneurysm (OR, 1.14, 95% CI, 0.98, 1.33). The patterns of associations remained with mild attenuation in multivariable MR analyses adjusting for genetically correlated phenotypes and potential mediators, including sleep duration, depression, body mass index, type 2 diabetes and smoking. The present MR study suggests potential causal associations of genetic liability to insomnia with increased risk of a broad range of CVDs.

scholarly journals A multivariable Mendelian randomisation study exploring the direct effects of nicotine on health compared with the other constituents of tobacco smoke: Implications for e-cigarette use

2021 ◽  
Author(s):  
Jasmine N Khouja ◽  
Eleanor Sanderson ◽  
Robyn E Wootton ◽  
Amy E Taylor ◽  
Marcus R Munafò
Keyword(s):  
Heart Rate ◽  
Tobacco Smoke ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Direct Effects ◽  
Uk Biobank ◽  
Genome Wide ◽  
Increased Risk ◽  
Summary Data

AbstractObjectivesGiven the popularity of e-cigarettes, and the lack of longitudinal evidence regarding their safety, novel methods are required to explore potential health effects resulting directly from nicotine use. The aim of this study was to explore the direct effects of nicotine compared with the other constituents of tobacco smoke on health outcomes associated with smoking.DesignObservational study, using Mendelian randomisation and multivariable Mendelian randomisation analyses of summary data.SettingSummary data from two previous genome-wide association studies, and summary data generated from UK Biobank, a prospective cohort study.ParticipantsN = 337,010 individuals enrolled in UK Biobank, and a total of N = 341,882 individuals from two previous genome-wide association studies.Main outcome measuresWe explored the effect of cotinine levels (as a proxy for nicotine exposure) and smoking heaviness (to capture cigarette smoke exposure) on body mass index (BMI), chronic obstructive pulmonary disease (COPD), forced vital capacity (FVC), forced expiratory volume (FEV-1), coronary heart disease (CHD), and heart rate.ResultsIn multivariable Mendelian randomisation analyses, there was weak evidence to suggest that increased cotinine levels may cause increased heart rate among current smokers (β = 0.50 bpm, 95% CI −0.06 to 1.05). There was stronger evidence to suggest that increased smoking heaviness causes decreased BMI among current smokers (β = −1.81 kg/m2, 95% CI −2.64 to −0.98), as well as increased risk of COPD, decreased FEV-1 and FVC, and increased heart rate among ever and current smokers. We also found evidence to suggest that increased smoking heaviness causes increased risk of CHD among ever smokers.ConclusionsOur combined findings are consistent with smoking-related health outcomes being caused by exposure to the non-nicotine components of tobacco smoke.

scholarly journals Analysing electrocardiographic traits and predicting cardiac risk in UK biobank

2021 ◽  
Vol 10 ◽  
pp. 204800402110236
Author(s):  
Julia Ramírez ◽  
Stefan van Duijvenboden ◽  
William J Young ◽  
Michele Orini ◽  
Aled R Jones ◽  
...  
Keyword(s):  
Genetic Information ◽  
Association Studies ◽  
Cardiac Risk ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Biological Mechanisms ◽  
Clinical Tool ◽  
Genome Wide ◽  
Response To Exercise ◽  
Electrocardiogram Ecg

The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.

scholarly journals Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jamie W. Robinson ◽  
Richard M. Martin ◽  
Spiridon Tsavachidis ◽  
Amy E. Howell ◽  
Caroline L. Relton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Studies ◽  
Tissue Expression ◽  
Tissue Type ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Causal Pathways ◽  
Genome Wide ◽  
Glioma Risk ◽  
Brain Tissues

AbstractGenome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.

scholarly journals Genome-wide association studies in East Asians identify new loci for waist-hip ratio and waist circumference

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Wanqing Wen ◽  
Norihiro Kato ◽  
Joo-Yeon Hwang ◽  
Xingyi Guo ◽  
Yasuharu Tabara ◽  
...  
Keyword(s):  
Waist Circumference ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
East Asians ◽  
Waist Hip Ratio ◽  
Genome Wide

scholarly journals Cigarette smoking and personality: interrogating causality using Mendelian randomisation

2018 ◽  
Vol 49 (13) ◽  
pp. 2197-2205 ◽  
Author(s):  
Hannah M. Sallis ◽  
George Davey Smith ◽  
Marcus R. Munafò
Keyword(s):  
Personality Traits ◽  
Association Studies ◽  
Smoking Initiation ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Individual Level ◽  
Causal Pathways ◽  
Genome Wide ◽  
Level Data ◽  
Causal Nature

AbstractBackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.MethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.ResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).ConclusionWe found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.

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