Publications by authors named "Kaitlin H Wade"

46 Publications

Body muscle gain and markers of cardiovascular disease susceptibility in young adulthood: A cohort study.

PLoS Med 2021 09 9;18(9):e1003751. Epub 2021 Sep 9.

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

Background: The potential benefits of gaining body muscle for cardiovascular disease (CVD) susceptibility, and how these compare with the potential harms of gaining body fat, are unknown. We compared associations of early life changes in body lean mass and handgrip strength versus body fat mass with atherogenic traits measured in young adulthood.

Methods And Findings: Data were from 3,227 offspring of the Avon Longitudinal Study of Parents and Children (39% male; recruited in 1991-1992). Limb lean and total fat mass indices (kg/m2) were measured using dual-energy X-ray absorptiometry scans performed at age 10, 13, 18, and 25 y (across clinics occurring from 2001-2003 to 2015-2017). Handgrip strength was measured at 12 and 25 y, expressed as maximum grip (kg or lb/in2) and relative grip (maximum grip/weight in kilograms). Linear regression models were used to examine associations of change in standardised measures of these exposures across different stages of body development with 228 cardiometabolic traits measured at age 25 y including blood pressure, fasting insulin, and metabolomics-derived apolipoprotein B lipids. SD-unit gain in limb lean mass index from 10 to 25 y was positively associated with atherogenic traits including very-low-density lipoprotein (VLDL) triglycerides. This pattern was limited to lean gain in legs, whereas lean gain in arms was inversely associated with traits including VLDL triglycerides, insulin, and glycoprotein acetyls, and was also positively associated with creatinine (a muscle product and positive control). Furthermore, this pattern for arm lean mass index was specific to SD-unit gains occurring between 13 and 18 y, e.g., -0.13 SD (95% CI -0.22, -0.04) for VLDL triglycerides. Changes in maximum and relative grip from 12 to 25 y were both positively associated with creatinine, but only change in relative grip was also inversely associated with atherogenic traits, e.g., -0.12 SD (95% CI -0.18, -0.06) for VLDL triglycerides per SD-unit gain. Change in fat mass index from 10 to 25 y was more strongly associated with atherogenic traits including VLDL triglycerides, at 0.45 SD (95% CI 0.39, 0.52); these estimates were directionally consistent across sub-periods, with larger effect sizes with more recent gains. Associations of lean, grip, and fat measures with traits were more pronounced among males. Study limitations include potential residual confounding of observational estimates, including by ectopic fat within muscle, and the absence of grip measures in adolescence for estimates of grip change over sub-periods.

Conclusions: In this study, we found that muscle strengthening, as indicated by grip strength gain, was weakly associated with lower atherogenic trait levels in young adulthood, at a smaller magnitude than unfavourable associations of fat mass gain. Associations of muscle mass gain with such traits appear to be smaller and limited to gains occurring in adolescence. These results suggest that body muscle is less robustly associated with markers of CVD susceptibility than body fat and may therefore be a lower-priority intervention target.
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http://dx.doi.org/10.1371/journal.pmed.1003751DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428664PMC
September 2021

Piloting the objective measurement of eating behaviour at a population scale: a nested study within the Avon Longitudinal Study of Parents and Children.

Wellcome Open Res 2020 4;5:185. Epub 2020 Aug 4.

Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.

Effective measurement and adaption of eating behaviours, such as eating speed, may improve weight loss and weight over time. We assessed whether the Mandometer, a portable weighing scale connected to a computer that generates a graph of food removal rate from the plate to which it is connected, together with photo-imaging of food, might prove an effective approach to measuring eating behaviours at large scale. We deployed the Mandometer in the home environment to measure main meals over three days of 95 21-year-old participants of the Avon Longitudinal Study of Parents and Children. We used multi-level models to describe food weight and eating speed and, as exemplar analyses, examined the relationship of eating behaviours with body mass index (BMI), dietary composition (fat content) and genotypic variation (the rs9939609 variant). Using this pilot data, we calculated the sample size required to detect differences in food weight and eating speed between groups of an exposure variable. All participants were able to use the Mandometer effectively after brief training. In exemplar analyses, evidence suggested that obese participants consumed more food than those of "normal" weight (i.e., BMI 19 to <25 kg/m ) and that A/A homozygotes (an indicator of higher weight) ate at a faster rate compared to T/T homozygotes. There was also some evidence that those with a high-fat diet consumed less food than those with a low-fat diet, but no strong evidence that individuals with medium- or high-fat diets ate at a faster rate. We demonstrated the potential for assessing eating behaviour in a short-term home setting and combining this with information in a research setting. This study may offer the opportunity to design interventions tailored for at-risk eating behaviours, offering advantages over the "one size fits all" approach of current failing obesity interventions.
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http://dx.doi.org/10.12688/wellcomeopenres.16091.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215563PMC
August 2020

Loss-of-function mutations in the melanocortin 4 receptor in a UK birth cohort.

Nat Med 2021 06 27;27(6):1088-1096. Epub 2021 May 27.

Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK.

Mutations in the melanocortin 4 receptor gene (MC4R) are associated with obesity but little is known about the prevalence and impact of such mutations throughout human growth and development. We examined the MC4R coding sequence in 5,724 participants from the Avon Longitudinal Study of Parents and Children, functionally characterized all nonsynonymous MC4R variants and examined their association with anthropometric phenotypes from childhood to early adulthood. The frequency of heterozygous loss-of-function (LoF) mutations in MC4R was ~1 in 337 (0.30%), considerably higher than previous estimates. At age 18 years, mean differences in body weight, body mass index and fat mass between carriers and noncarriers of LoF mutations were 17.76 kg (95% CI 9.41, 26.10), 4.84 kg m (95% CI 2.19, 7.49) and 14.78 kg (95% CI 8.56, 20.99), respectively. MC4R LoF mutations may be more common than previously reported and carriers of such variants may enter adult life with a substantial burden of excess adiposity.
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http://dx.doi.org/10.1038/s41591-021-01349-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611835PMC
June 2021

Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses.

BMC Med 2021 03 18;19(1):69. Epub 2021 Mar 18.

Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.

Background: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease.

Methods: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions.

Results: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures.

Conclusions: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.
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http://dx.doi.org/10.1186/s12916-021-01939-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7971964PMC
March 2021

Estimating the causal effect of BMI on mortality risk in people with heart disease, diabetes and cancer using Mendelian randomization.

Int J Cardiol 2021 05 14;330:214-220. Epub 2021 Feb 14.

Division of Endocrinology, Diabetes & Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Rd, Manchester M13 9PL, UK; Diabetes, Endocrinology and Metabolism Centre, Peter Mount Building, Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 0HY, UK.

Background: Observational data have reported that being overweight or obese, compared to being normal weight, is associated with a lower risk for death - the "obesity paradox". We used Mendelian randomization (MR) to estimate causal effects of body mass index (BMI) on mortality risks in people with coronary heart disease (CHD), type 2 diabetes mellitus (T2DM) or malignancy in whom this paradox has been often reported.

Methods: We studied 457,746 White British UK Biobank participants including three subgroups with T2DM (n = 19,737), CHD (n = 21,925) or cancer (n = 42,612) at baseline and used multivariable-adjusted Cox models and MR approaches to describe relationships between BMI and mortality risk.

Results: Observational Cox models showed J-shaped relationships between BMI and mortality risk including within disease subgroups in which the BMI values associated with minimum mortality risk were within overweight/obese ranges (26.5-32.5 kg/m). In all participants, MR analyses showed a positive linear causal effect of BMI on mortality risk (HR for mortality per unit higher BMI: 1.05; 95% CI: 1.03-1.08), also evident in people with CHD (HR: 1.08; 95% CI: 1.01-1.14). Point estimates for hazard ratios across all BMI values in participants with T2DM and cancer were consistent with overall positive linear effects but confidence intervals included the null.

Conclusion: These data support the idea that population efforts to promote intentional weight loss towards the normal BMI range would reduce, not enhance, mortality risk in the general population including, importantly, individuals with CHD.
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http://dx.doi.org/10.1016/j.ijcard.2021.02.027DOI Listing
May 2021

Large-scale association analyses identify host factors influencing human gut microbiome composition.

Nat Genet 2021 02 18;53(2):156-165. Epub 2021 Jan 18.

Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10 < P < 5 × 10) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.
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http://dx.doi.org/10.1038/s41588-020-00763-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515199PMC
February 2021

Common health conditions in childhood and adolescence, school absence, and educational attainment: Mendelian randomization study.

NPJ Sci Learn 2021 Jan 4;6(1). Epub 2021 Jan 4.

Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.

Good health is positively related to children's educational outcomes, but relationships may not be causal. Demonstrating a causal influence would strongly support childhood and adolescent health as important for education policy. We applied genetic causal inference methods to assess the causal relationship of common health conditions at age 10 (primary/elementary school) and 13 (mid-secondary/mid-high school) with educational attainment at 16 and school absence at 14-16. Participants were 6113 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Exposures were symptoms of attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), depression, asthma, migraines and BMI. Genetic liability for these conditions and BMI was indexed by polygenic scores. In non-genetic, multivariate-adjusted models, all health conditions except asthma and migraines were associated with poorer attainment and greater school absence. School absence substantially mediated effects of BMI (39.9% for BMI at 13) and migraines (72.0% at 10), on attainment with more modest mediation for emotional and neurodevelopmental conditions. In genetic models, a unit increase in standardized BMI at 10 predicted a 0.19 S.D. decrease (95% CI: 0.11, 0.28) in attainment at 16, equivalent to around a 1/3 grade lower in all subjects, and 8.7% more school absence (95% CI:1.8%,16.1%). Associations were similar at 13. Genetic liability for ADHD predicted lower attainment but not more absence. Triangulation across multiple approaches supports a causal, negative influence on educational outcomes of BMI and ADHD, but not of ASD, depression, asthma or migraine. Higher BMI in childhood and adolescence may causally impair educational outcomes.
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http://dx.doi.org/10.1038/s41539-020-00080-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782810PMC
January 2021

Enhanced Protection Against Diarrhea Among Breastfed Infants of Nonsecretor Mothers.

Pediatr Infect Dis J 2021 03;40(3):260-263

From the Department of Pediatrics and Child Health, University of Manitoba and Manitoba Interdisciplinary Lactation Centre (MILC), Children's Hospital Research Institute of Manitoba, Winnipeg, Manitoba, Canada.

Diarrhea is a major cause of infant mortality. Being a "nonsecretor" (having an inactive fucosyltransferase-2 gene) protects against diarrhea by inhibiting enteric infections. Breastfeeding also protects against diarrhea; however, the impact of maternal secretor status is unknown. In the ALSPAC cohort (N = 4971), we found that breastfeeding by nonsecretor mothers was especially protective against diarrhea, which could inform new prevention strategies.
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http://dx.doi.org/10.1097/INF.0000000000003014DOI Listing
March 2021

Is disrupted sleep a risk factor for Alzheimer's disease? Evidence from a two-sample Mendelian randomization analysis.

Int J Epidemiol 2021 07;50(3):817-828

MRC Integrative Epidemiology Unit, at the University of Bristol, Bristol, UK.

Background: It is established that Alzheimer's disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.

Methods: We used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk.

Results: Overall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50-0.99). Some other sleep traits (accelerometer-measured 'eveningness' and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated.

Conclusions: Overall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available.
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http://dx.doi.org/10.1093/ije/dyaa183DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271193PMC
July 2021

Genome-wide associations of human gut microbiome variation and implications for causal inference analyses.

Nat Microbiol 2020 09 22;5(9):1079-1087. Epub 2020 Jun 22.

Department of Microbiology and Immunology, Rega Instituut, KU Leuven-University of Leuven, Leuven, Belgium.

Recent population-based and clinical studies have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci, human twin studies and microbiome genome-wide association studies have provided evidence for genetic contributions to microbiome composition. Despite this, there is still poor overlap in genetic association across human studies. Using appropriate taxon-specific models, along with support from independent cohorts, we show an association between human host genotype and gut microbiome variation. We also suggest that interpretation of applied analyses using genetic associations is complicated by the probable overlap between genetic contributions and heritable components of host environment. Using faecal 16S ribosomal RNA gene sequences and host genotype data from the Flemish Gut Flora Project (n = 2,223) and two German cohorts (FoCus, n = 950; PopGen, n = 717), we identify genetic associations involving multiple microbial traits. Two of these associations achieved a study-level threshold of P = 1.57 × 10; an association between Ruminococcus and rs150018970 near RAPGEF1 on chromosome 9, and between Coprococcus and rs561177583 within LINC01787 on chromosome 1. Exploratory analyses were undertaken using 11 other genome-wide associations with strong evidence for association (P < 2.5 × 10) and a previously reported signal of association between rs4988235 (MCM6/LCT) and Bifidobacterium. Across these 14 single-nucleotide polymorphisms there was evidence of signal overlap with other genome-wide association studies, including those for age at menarche and cardiometabolic traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease (including Bifidobacterium and body composition); however, in the absence of clear microbiome-driven effects, caution is needed in interpretation. Overall, this work marks a growing catalogue of genetic associations that will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.
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http://dx.doi.org/10.1038/s41564-020-0743-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610462PMC
September 2020

Improving causality in microbiome research: can human genetic epidemiology help?

Wellcome Open Res 2019 24;4:199. Epub 2020 Apr 24.

Gut Microbes & Health, Quadram Institute Bioscience, Norwich, NR4 7UQ, UK.

Evidence supports associations between human gut microbiome variation and multiple health outcomes and diseases. Despite compelling results from and models, few findings have been translated into an understanding of modifiable causal relationships. Furthermore, epidemiological studies have been unconvincing in their ability to offer causal evidence due to their observational nature, where confounding by lifestyle and behavioural factors, reverse causation and bias are important limitations. Whilst randomized controlled trials have made steps towards understanding the causal role played by the gut microbiome in disease, they are expensive and time-consuming. This evidence that has not been translated between model systems impedes opportunities for harnessing the gut microbiome for improving population health. Therefore, there is a need for alternative approaches to interrogate causality in the context of gut microbiome research. The integration of human genetics within population health sciences have proved successful in facilitating improved causal inference (e.g., with Mendelian randomization [MR] studies) and characterising inherited disease susceptibility. MR is an established method that employs human genetic variation as natural "proxies" for clinically relevant (and ideally modifiable) traits to improve causality in observational associations between those traits and health outcomes. Here, we focus and discuss the utility of MR within the context of human gut microbiome research, review studies that have used this method and consider the strengths, limitations and challenges facing this research. Specifically, we highlight the requirements for careful examination and interpretation of derived causal estimates and host (i.e., human) genetic effects themselves, triangulation across multiple study designs and inter-disciplinary collaborations. Meeting these requirements will help support or challenge causality of the role played by the gut microbiome on human health to develop new, targeted therapies to alleviate disease symptoms to ultimately improve lives and promote good health.
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http://dx.doi.org/10.12688/wellcomeopenres.15628.3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217228PMC
April 2020

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

Mol Psychiatry 2021 06 11;26(6):2056-2069. Epub 2020 May 11.

Department of Endocrinology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (r ≈ 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|r| ≈ 0.1-0.3) and positive genetic correlations with physical activity (r ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (r ≈-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.
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http://dx.doi.org/10.1038/s41380-020-0697-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7767645PMC
June 2021

Common variation at 16p11.2 is associated with glycosuria in pregnancy: findings from a genome-wide association study in European women.

Hum Mol Genet 2020 07;29(12):2098-2106

Medical Research Council Integrative Epidemiology Unit, Avon Longitudinal Study of Parents and Children, Population Health Science, Bristol Medical School, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.

Glycosuria is a condition where glucose is detected in urine at higher concentrations than normal (i.e. not detectable). Glycosuria at some point during pregnancy has an estimated prevalence of 50% and is associated with adverse outcomes in both mothers and offspring. Little is currently known about the genetic contribution to this trait or the extent to which it overlaps with other seemingly related traits, e.g. diabetes. We performed a genome-wide association study (GWAS) for self-reported glycosuria in pregnant mothers from the Avon Longitudinal Study of Parents and Children (cases/controls = 1249/5140). We identified two loci, one of which (lead SNP = rs13337037; chromosome 16; odds ratio of glycosuria per effect allele: 1.42; 95% CI: 1.30, 1.56; P = 1.97 × 10-13) was then validated using an obstetric measure of glycosuria measured in the same cohort (227/6639). We performed a secondary GWAS in the 1986 Northern Finland Birth Cohort (NFBC1986; 747/2991) using midwife-reported glycosuria and offspring genotype as a proxy for maternal genotype. The combined results revealed evidence for a consistent effect on glycosuria at the chromosome 16 locus. In follow-up analyses, we saw little evidence of shared genetic underpinnings with the exception of urinary albumin-to-creatinine ratio (Rg = 0.64; SE = 0.22; P = 0.0042), a biomarker of kidney disease. In conclusion, we identified a genetic association with self-reported glycosuria during pregnancy, with the lead SNP located 15kB upstream of SLC5A2, a target of antidiabetic drugs. The lack of strong genetic correlation with seemingly related traits such as type 2 diabetes suggests different genetic risk factors exist for glycosuria during pregnancy.
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http://dx.doi.org/10.1093/hmg/ddaa054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390941PMC
July 2020

Education, intelligence and Alzheimer's disease: evidence from a multivariable two-sample Mendelian randomization study.

Int J Epidemiol 2020 08;49(4):1163-1172

Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Objectives: To examine whether educational attainment and intelligence have causal effects on risk of Alzheimer's disease (AD), independently of each other.

Design: Two-sample univariable and multivariable Mendelian randomization (MR) to estimate the causal effects of education on intelligence and vice versa, and the total and independent causal effects of both education and intelligence on AD risk.

Participants: 17 008 AD cases and 37 154 controls from the International Genomics of Alzheimer's Project (IGAP) consortium.

Main Outcome Measure: Odds ratio (OR) of AD per standardized deviation increase in years of schooling (SD = 3.6 years) and intelligence (SD = 15 points on intelligence test).

Results: There was strong evidence of a causal, bidirectional relationship between intelligence and educational attainment, with the magnitude of effect being similar in both directions [OR for intelligence on education = 0.51 SD units, 95% confidence interval (CI): 0.49, 0.54; OR for education on intelligence = 0.57 SD units, 95% CI: 0.48, 0.66]. Similar overall effects were observed for both educational attainment and intelligence on AD risk in the univariable MR analysis; with each SD increase in years of schooling and intelligence, odds of AD were, on average, 37% (95% CI: 23-49%) and 35% (95% CI: 25-43%) lower, respectively. There was little evidence from the multivariable MR analysis that educational attainment affected AD risk once intelligence was taken into account (OR = 1.15, 95% CI: 0.68-1.93), but intelligence affected AD risk independently of educational attainment to a similar magnitude observed in the univariate analysis (OR = 0.69, 95% CI: 0.44-0.88).

Conclusions: There is robust evidence for an independent, causal effect of intelligence in lowering AD risk. The causal effect of educational attainment on AD risk is likely to be mediated by intelligence.
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http://dx.doi.org/10.1093/ije/dyz280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660137PMC
August 2020

Mendelian randomisation for nutritional psychiatry.

Lancet Psychiatry 2020 02 20;7(2):208-216. Epub 2019 Nov 20.

Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Medical Research Centre (MRC), Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Nutritional psychiatry is a growing area of research, with several nutritional factors implicated in the cause of psychiatric ill-health. However, nutritional research is highly complex, with multiple potential factors involved, highly confounded exposures and small effect sizes for individual nutrients. This Personal View considers whether Mendelian randomisation provides a solution to these difficulties, by investigating causality in a low-risk and low-cost way. We reviewed studies using Mendelian randomisation in nutritional psychiatry, along with the potential opportunities and challenges of using this approach for investigating the causal effects of nutritional exposures. Several studies have identified nutritional exposures that are potentially causal by using Mendelian randomisation in psychiatry, offering opportunities for further mechanistic research, intervention development, and replication. The use of Mendelian randomisation as a foundation for intervention development facilitates the best use of resources in an emerging discipline in which opportunities are rich, but resources are often poor.
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http://dx.doi.org/10.1016/S2215-0366(19)30293-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983323PMC
February 2020

Determinants of Intima-Media Thickness in the Young: The ALSPAC Study.

JACC Cardiovasc Imaging 2021 02 11;14(2):468-478. Epub 2019 Oct 11.

Vascular Physiology Unit, UCL Institute of Cardiovascular Science, London, United Kingdom. Electronic address:

Objectives: This study characterized the determinants of carotid intima-media thickness (cIMT) in a large (n > 4,000) longitudinal cohort of healthy young people age 9 to 21 years.

Background: Greater cIMT is commonly used in the young as a marker of subclinical atherosclerosis, but its evolution at this age is still poorly understood.

Methods: Associations between cardiovascular risk factors and cIMT were investigated in both longitudinal (ages 9 to 17 years) and cross-sectional (ages 17 and 21 years) analyses, with the latter also related to other measures of carotid structure and stress. Additional use of ultra-high frequency ultrasound in the radial artery at age 21 years allowed investigation of the distinct layers (i.e., intima or media) that may underlie observed differences.

Results: Fat-free mass (FFM) and systolic blood pressure were the only modifiable risk factors positively associated with cIMT (e.g., mean difference in cIMT per 1-SD increase in FFM at age 17: 0.007 mm: 95% confidence interval [CI]: 0.004 to 0.010; p < 0.001), whereas fat mass was negatively associated with cIMT (difference: -0.0032; 95% CI: 0.004 to -0.001; p = 0.001). Similar results were obtained when investigating cumulative exposure to these factors throughout adolescence. An increase in cIMT maintained circumferential wall stress in the face of increased mean arterial pressure when increases in body mass were attributable to increased FFM, but not fat mass. Risk factor-associated differences in the radial artery occurred in the media alone, and there was little evidence of a relationship between intimal thickness and any risk factor.

Conclusions: Subtle changes in cIMT in the young may predominantly involve the media and represent physiological adaptations as opposed to subclinical atherosclerosis. Other vascular measures may be more appropriate for the identification of arterial disease before adulthood.
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http://dx.doi.org/10.1016/j.jcmg.2019.08.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7851110PMC
February 2021

Variation of all-cause and cause-specific mortality with body mass index in one million Swedish parent-son pairs: An instrumental variable analysis.

PLoS Med 2019 08 9;16(8):e1002868. Epub 2019 Aug 9.

Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, United Kingdom.

Background: High body mass index (BMI) is associated with mortality, but the pervasive problem of confounding and reverse causality in observational studies limits inference about the direction and magnitude of causal effects. We aimed to obtain estimates of the causal association of BMI with all-cause and cause-specific mortality.

Methods And Findings: In a record-linked, intergenerational prospective study from the general population of Sweden, we used two-sample instrumental variable (IV) analysis with data from 996,898 fathers (282,407 deaths) and 1,013,083 mothers (153,043 deaths) and their sons followed up from January 1, 1961, until December 31, 2004. Sons' BMI was used as the instrument for parents' BMI to compute hazard ratios (HRs) for risk of mortality per standard deviation (SD) higher parents' BMI. Using offspring exposure as an instrument for parents' exposure is unlikely to be affected by reverse causality (an important source of bias in this context) and reduces confounding. IV analyses supported causal associations between higher BMI and greater risk of all-cause mortality (HR [95% confidence interval (CI)] per SD higher fathers' BMI: 1.29 [1.26-1.31] and mothers' BMI: 1.39 [1.35-1.42]) and overall cancer mortality (HR per SD higher fathers' BMI: 1.20 [1.16-1.24] and mothers' BMI: 1.29 [1.24-1.34]), including 9 site-specific cancers in men (bladder, colorectum, gallbladder, kidney, liver, lung, lymphatic system, pancreas, and stomach) and 11 site-specific cancers in women (gallbladder, kidney, liver, lung, lymphatic system, ovaries, pancreas, stomach, uterus, cervix, and endometrium). There was evidence supporting causal associations between higher BMI in mothers and greater risk of mortality from kidney disease (HR: 2.17 [1.68-2.81]) and lower risk of mortality from suicide (HR: 0.77 [0.65-0.90]). In both sexes, there was evidence supporting causal associations between higher BMI and mortality from cardiovascular diseases (CVDs), stroke, diabetes, and respiratory diseases. We were unable to test the association between sons' and mothers' BMIs (as mothers' data were unavailable) or whether the instrument was independent of unmeasured or residual confounding; however, the associations between parents' mortality and sons' BMI were negligibly influenced by adjustment for available confounders.

Conclusions: Consistent with previous large-scale meta-analyses and reviews, results supported the causal role of higher BMI in increasing the risk of several common causes of death, including cancers with increasing global incidence. We also found positive effects of BMI on mortality from respiratory disease, prostate cancer, and lung cancer, which has been inconsistently reported in the literature, suggesting that the causal role of higher BMI in mortality from these diseases may be underestimated. Furthermore, we expect different patterns of bias in the current observational and IV analyses; therefore, the similarities between our findings from both methods increases confidence in the results. These findings support efforts to understand the mechanisms underpinning these effects to inform targeted interventions and develop population-based strategies to reduce rising obesity levels for disease prevention.
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http://dx.doi.org/10.1371/journal.pmed.1002868DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688790PMC
August 2019

A Phenome-Wide Mendelian Randomization Study of Pancreatic Cancer Using Summary Genetic Data.

Cancer Epidemiol Biomarkers Prev 2019 12 17;28(12):2070-2078. Epub 2019 Jul 17.

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

Background: The 5-year mortality rate for pancreatic cancer is among the highest of all cancers. Greater understanding of underlying causes could inform population-wide intervention strategies for prevention. Summary genetic data from genome-wide association studies (GWAS) have become available for thousands of phenotypes. These data can be exploited in Mendelian randomization (MR) phenome-wide association studies (PheWAS) to efficiently screen the phenome for potential determinants of disease risk.

Methods: We conducted an MR-PheWAS of pancreatic cancer using 486 phenotypes, proxied by 9,124 genetic variants, and summary genetic data from a GWAS of pancreatic cancer (7,110 cancer cases, 7,264 controls). ORs and 95% confidence intervals per 1 SD increase in each phenotype were generated.

Results: We found evidence that previously reported risk factors of body mass index (BMI; 1.46; 1.20-1.78) and hip circumference (1.42; 1.21-1.67) were associated with pancreatic cancer. We also found evidence of novel associations with metabolites that have not previously been implicated in pancreatic cancer: *, a fibrinogen-cleavage peptide (1.60; 1.31-1.95), and O-sulfo-l-tyrosine (0.58; 0.46-0.74). An inverse association was also observed with lung adenocarcinoma (0.63; 0.54-0.74).

Conclusions: Markers of adiposity (BMI and hip circumference) are potential intervention targets for pancreatic cancer prevention. Further clarification of the causal relevance of the fibrinogen-cleavage peptides and O-sulfo-l-tyrosine in pancreatic cancer etiology is required, as is the basis of our observed association with lung adenocarcinoma.

Impact: For pancreatic cancer, MR-PheWAS can augment existing risk factor knowledge and generate novel hypotheses to investigate.
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http://dx.doi.org/10.1158/1055-9965.EPI-19-0036DOI Listing
December 2019

Association between fat mass through adolescence and arterial stiffness: a population-based study from The Avon Longitudinal Study of Parents and Children.

Lancet Child Adolesc Health 2019 07 21;3(7):474-481. Epub 2019 May 21.

Vascular Physiology Unit, Institute of Cardiovascular Science, University College London, London, UK. Electronic address:

Background: The link between adiposity, metabolic abnormalities, and arterial disease progression in children and adolescents remains poorly defined. We aimed to assess whether persistent high adiposity levels are associated with increased arterial stiffness in adolescence and any mediation effects by common metabolic risk factors.

Methods: We included participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) who had detailed adiposity measurements between the ages 9-17 years and arterial stiffness (carotid to femoral pulse wave velocity [PWV]) measured at age 17 years. Body-mass index (BMI) and waist-to-height ratio were calculated from weight, height, and waist circumference measurements whereas fat mass was assessed using repeated dual-energy x-ray absorptiometry (DEXA) scans. We used total and trunk fat mass indices (FMIs) to classify participants as normal (<75th percentile) or high (>75th percentile) FMI. We classified participants as being metabolically unhealthy if they had three or more of the following risk factors: high levels of systolic blood pressure, triglycerides, or glucose (all >75th percentile) or low levels of high-density lipoprotein (<25th percentile). We used multivariable linear regression analysis to assess the relationship between PWV and exposure to adiposity, and tested for linear trend of PVW levels across ordinal groups. We used latent class growth mixture modelling analysis to assess the effect of longitudinal changes in adiposity indices through adolescence on arterial stiffness.

Findings: We studied 3423 participants (1866 [54·5%] female and 1557 [45·5%] male). Total fat mass was positively associated with PWV at age 17 years (0·004 m/s per kg, 95% CI 0·001-0·006; p=0·0081). Persistently high total FMI and trunk FMI between ages 9 and 17 years were related to greater PWV (0·15 m/s per kg/m, 0·05-0·24; p=0·0044 and 0·15 m/s per kg/m, 0·06-0·25; p=0·0021) compared with lower FMI. Metabolic abnormalities amplified the adverse effect of high total FMI on arterial stiffness (PWV 6·0 m/s [95% CI 5·9-6·0] for metabolically healthy participants and 6·2 m/s [5·9-6·4] for metabolically unhealthy participants). Participants who restored normal total FMI in adolescence (PWV 5·8 m/s [5·7-5·9] for metabolically healthy and 5·9 m/s [5·6-6·1] for metabolically unhealthy) had comparable PWV to those who had normal FMI throughout (5·7 m/s [5·7-5·8] for metabolically healthy and 5·9 m/s [5·8-5·9] for metabolically unhealthy).

Interpretation: Persistently high fat mass during adolescence was associated with greater arterial stiffness and was further aggravated by an unfavourable metabolic profile. Reverting to normal FMI in adolescence was associated with normal PWV, suggesting adolescence as an important period for interventions to tackle obesity in the young to maximise long-term vascular health.

Funding: UK Medical Research Council, Wellcome Trust, British Heart Foundation, and AFA Insurances.
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http://dx.doi.org/10.1016/S2352-4642(19)30105-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558973PMC
July 2019

Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood.

Cell 2019 04;177(3):587-596.e9

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment.
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http://dx.doi.org/10.1016/j.cell.2019.03.028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661115PMC
April 2019

Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis.

Nat Commun 2019 01 18;10(1):333. Epub 2019 Jan 18.

Medical Research Council Integrative Epidemiology Unit, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype data in large studies.
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http://dx.doi.org/10.1038/s41467-018-08219-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338768PMC
January 2019

Adiposity and Cardiometabolic Outcomes: What Can Meta-analyses of Mendelian Randomization Studies Contribute?

JAMA Netw Open 2018 11 2;1(7):e183778. Epub 2018 Nov 2.

Medical Research Council, Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

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http://dx.doi.org/10.1001/jamanetworkopen.2018.3778DOI Listing
November 2018

Associations of Body Mass and Fat Indexes With Cardiometabolic Traits.

J Am Coll Cardiol 2018 12;72(24):3142-3154

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Background: Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear.

Objectives: The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood.

Methods: BMI was examined alongside total, trunk, arm, and leg fat indexes (each in kilograms per square meter) from dual-energy x-ray absorptiometry at ages 10 and 18 years in relation to 230 traits from targeted metabolomics at age 18 years in 2,840 offspring from the Avon Longitudinal Study of Parents and Children.

Results: Higher total fat mass index and BMI at age 10 years were similarly associated with cardiometabolic traits at age 18 years, including higher systolic and diastolic blood pressure, higher very low-density lipoprotein and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher triglycerides, and higher insulin and glycoprotein acetyls. Associations were stronger for both indexes measured at age 18 years and for gains in each index from age 10 to 18 years (e.g., 0.45 SDs [95% confidence interval: 0.38 to 0.53] in glycoprotein acetyls per SD unit gain in fat mass index vs. 0.38 SDs [95% confidence interval: 0.27 to 0.48] per SD unit gain in BMI). Associations resembled those for trunk fat index. Higher lean mass index was weakly associated with traits and was not protective against higher fat mass index.

Conclusions: The results of this study support abdominal fatness as a primary driver of cardiometabolic dysfunction and BMI as a useful tool for detecting its effects.
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http://dx.doi.org/10.1016/j.jacc.2018.09.066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290112PMC
December 2018

Assessing the causal role of body mass index on cardiovascular health in young adults: Mendelian randomization and recall-by-genotype analyses.

Circulation 2018 11 30;138(20):2187-2201. Epub 2018 Jul 30.

MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.

Background: Body mass index (BMI) has been suggested to be causally related to cardiovascular health in mid-to-late life, but this has not been explored systematically at younger ages - nor with detailed cardiovascular phenotyping. Recall-by-Genotype (RbG) is an approach that enables the collection of precise phenotypic measures in smaller studies, whilst maintaining statistical power and ability for causal inference.

Methods: In this study, we used a combination of conventional multivariable regression analysis, Mendelian randomization (MR) and sub-sample RbG methodologies to estimate the causal effect of BMI on gross-level and detailed cardiovascular health in healthy participants from the Avon Longitudinal Study of Parents and Children at age 17 (N=1420-3108 for different outcomes) and an independent sample from the same cohort (for RbG) study at age 21 (N=386-418).

Results: In both MR and RbG analyses, results suggested that higher BMI causes higher blood pressure (BP) and left ventricular mass index (LVMI) in young adults (e.g., difference in LVMI per kg/m using MR: 1.07g/m; 95% CI: 0.62, 1.52; =3.87x10 and per 3.58kg/m using RbG: 1.65g/m 95% CI: 0.83, 2.47; =0.0001). Additionally, RbG results suggested a causal role of higher BMI on higher stroke volume (SV: difference per 3.58kg/m: 1.49ml/m; 95% CI: 0.62, 2.35; =0.001) and cardiac output (CO: difference per 3.58kg/m: 0.11l/min/m; 95% CI: 0.03, 0.19; =0.01) but no strong evidence for a causal role on systemic vascular resistance or total arterial compliance. Neither analysis supported a causal role of higher BMI on heart rate.

Conclusions: Complementary MR and RbG causal methodologies, together with a range of sensitivity analyses, suggest that higher BMI is likely to cause worse cardiovascular health, specifically higher BP and LVMI, even in youth. Higher BMI also resulted in increased CO in the RbG study, which appeared to be solely driven by SV, as neither MR nor RbG analyses suggested a causal effect of BMI on heart rate. These consistent results support efforts to reduce BMI from a young age to prevent later adverse cardiovascular health and illustrate the potential for phenotypic resolution with maintained analytical power using RbG.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.117.033278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250296PMC
November 2018

BMI and Mortality in UK Biobank: Revised Estimates Using Mendelian Randomization.

Obesity (Silver Spring) 2018 11;26(11):1796-1806

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Objective: The aim of this study was to obtain estimates of the causal relationship between BMI and mortality.

Methods: Mendelian randomization (MR) with BMI-associated genotypic variation was used to test the causal effect of BMI on all-cause and cause-specific mortality in UK Biobank participants of White British ancestry.

Results: MR analyses supported a causal association between higher BMI and greater risk of all-cause mortality (hazard ratio [HR] per 1 kg/m : 1.03; 95% CI: 0.99-1.07) and mortality from cardiovascular diseases (HR: 1.10; 95% CI: 1.01-1.19), specifically coronary heart disease (HR: 1.12; 95% CI: 1.00-1.25) and those excluding coronary heart disease/stroke/aortic aneurysm (HR: 1.24; 95% CI: 1.03-1.48), stomach cancer (HR: 1.18; 95% CI: 0.87-1.62), and esophageal cancer (HR: 1.22; 95% CI: 0.98-1.53), and a decreased risk of lung cancer mortality (HR: 0.96; 95% CI: 0.85-1.08). Sex stratification supported the causal role of higher BMI increasing bladder cancer mortality risk (males) but decreasing respiratory disease mortality risk (males). The J-shaped observational association between BMI and mortality was visible with MR analyses, but the BMI at which mortality was minimized was lower and the association was flatter over a larger BMI range.

Conclusions: Results support a causal role of higher BMI in increasing the risk of all-cause mortality and mortality from several specific causes.
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http://dx.doi.org/10.1002/oby.22313DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334168PMC
November 2018

secretor genotype and susceptibility to infections and chronic conditions in the ALSPAC cohort.

Wellcome Open Res 2018 25;3:65. Epub 2018 Sep 25.

Medical Research Council Integrative Epidemiology Unit, Avon Longitudinal Study of Parents and Children, Population Health Science, Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK.

The (fucosyltransferase-2) gene determines blood group secretor status. Being homozygous for the inactive "non-secretor" rs601338(A) allele confers resistance to certain infections (e.g. , ) and susceptibility to others (e.g. , ). Non-secretors also have an increased risk of type 1 diabetes and inflammatory bowel disease. We examined genotype, infections and chronic conditions in a population-based cohort. We studied 7,582 pregnant women from the ALSPAC pregnancy cohort. Infections (measles, mumps, chicken pox, whooping cough, meningitis, herpes, gonorrhea and urinary infections) and chronic conditions (kidney disease, hypertension, diabetes, rheumatism, arthritis, psoriasis, hay fever, asthma, eczema and allergies) were self-reported. secretor status was determined from the rs601338 genotype. ABO blood type was obtained from clinical records. Overall, 1920 women (25.3%) were homozygous for the non-secretor allele (AA). Secretor status was associated with mumps, with 68% of non-secretors experiencing this infection, compared to 48% of secretors (RR, 1.40; 95% CI, 1.34-1.46). A weaker association was observed for measles infection (76% vs. 72%; RR, 1.05; 95% CI, 1.02-1.09). Non-secretors also experienced an increased risk of kidney disease (5.4% vs. 3.9%; RR, 1.39; 95% CI, 1.11-1.75). Independent of secretor status, AB blood type was a risk factor for mumps (RR 1.15; 95%CI, 1.03, 1.28 compared to type O). We found no evidence of interaction between secretor status and blood type.  For some conditions, including asthma and arthritis, heterozygosity (GA) appeared to confer an intermediate phenotype. There was no strong evidence of association between secretor status and other infections or chronic conditions, although statistical power was limited for rare outcomes. Our results identify an association between secretor status and self-reported kidney disease, and confirm a recently reported association with susceptibility to mumps infection. The clinical implications of these associations warrant further investigation.
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http://dx.doi.org/10.12688/wellcomeopenres.14636.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6171556PMC
September 2018

Influence of puberty timing on adiposity and cardiometabolic traits: A Mendelian randomisation study.

PLoS Med 2018 08 28;15(8):e1002641. Epub 2018 Aug 28.

Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Background: Earlier puberty is widely linked with future obesity and cardiometabolic disease. We examined whether age at puberty onset likely influences adiposity and cardiometabolic traits independent of childhood adiposity.

Methods And Findings: One-sample Mendelian randomisation (MR) analyses were conducted on up to 3,611 white-European female and male offspring from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort recruited at birth via mothers between 1 April 1991 and 31 December 1992. Time-sensitive exposures were age at menarche and age at voice breaking. Outcomes measured at age 18 y were body mass index (BMI), dual-energy X-ray absorptiometry-based fat and lean mass indices, blood pressure, and 230 cardiometabolic traits derived from targeted metabolomics (150 concentrations plus 80 ratios from nuclear magnetic resonance [NMR] spectroscopy covering lipoprotein subclasses of cholesterol and triglycerides, amino acids, inflammatory glycoproteins, and others). Adjustment was made for pre-pubertal BMI measured at age 8 y. For negative control MR analyses, BMI and cardiometabolic trait measures taken at age 8 y (before puberty, and which therefore cannot be an outcome of puberty itself) were used. For replication analyses, 2-sample MR was conducted using summary genome-wide association study data on up to 322,154 adults for post-pubertal BMI, 24,925 adults for post-pubertal NMR cardiometabolic traits, and 13,848 children for pre-pubertal obesity (negative control). Like observational estimates, 1-sample MR estimates in ALSPAC using 351 polymorphisms for age at menarche (explaining 10.6% of variance) among 2,053 females suggested that later age at menarche (per year) was associated with -1.38 kg/m2 of BMI at age 18 y (or -0.34 SD units, 95% CI -0.46, -0.23; P = 9.77 × 10-09). This coefficient attenuated 10-fold upon adjustment for BMI at age 8 y, to -0.12 kg/m2 (or -0.03 SDs, 95% CI -0.13, 0.07; P = 0.55). Associations with blood pressure were similar, but associations across other traits were small and inconsistent. In negative control MR analyses, later age at menarche was associated with -0.77 kg/m2 of pre-pubertal BMI measured at age 8 y (or -0.39 SDs, 95% CI -0.50, -0.29; P = 6.28 × 10-13), indicating that variants influencing menarche also influence BMI before menarche. Cardiometabolic trait associations were weaker and less consistent among males and both sexes combined. Higher BMI at age 8 y (per 1 kg/m2 using 95 polymorphisms for BMI explaining 3.4% of variance) was associated with earlier menarche among 2,648 females (by -0.26 y, 95% CI -0.37, -0.16; P = 1.16 × 10-06), likewise among males and both sexes combined. In 2-sample MR analyses using 234 polymorphisms and inverse variance weighted (IVW) regression, each year later age at menarche was associated with -0.81 kg/m2 of adult BMI (or -0.17 SD units, 95% CI -0.21, -0.12; P = 4.00 × 10-15). Associations were weaker with cardiometabolic traits. Using 202 polymorphisms, later menarche was associated with lower odds of childhood obesity (IVW-based odds ratio = 0.52 per year later, 95% CI 0.48, 0.57; P = 6.64 × 10-15). Study limitations include modest sample sizes for 1-sample MR, lack of inference to non-white-European populations, potential selection bias through modest completion rates of puberty questionnaires, and likely disproportionate measurement error of exposures by sex. The cardiometabolic traits examined were heavily lipid-focused and did not include hormone-related traits such as insulin and insulin-like growth factors.

Conclusions: Our results suggest that puberty timing has a small influence on adiposity and cardiometabolic traits and that preventive interventions should instead focus on reducing childhood adiposity.
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http://dx.doi.org/10.1371/journal.pmed.1002641DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6112630PMC
August 2018

Epigenetic gestational age acceleration: a prospective cohort study investigating associations with familial, sociodemographic and birth characteristics.

Clin Epigenetics 2018 27;10:86. Epub 2018 Jun 27.

1MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, England.

Background: Gestational age at delivery is associated with health and social outcomes. Recently, cord blood DNA methylation data has been used to predict gestational age. The discrepancy between gestational age predicted from DNA methylation and determined by ultrasound or last menstrual period is known as gestational age acceleration. This study investigated associations of sex, socioeconomic status, parental behaviours and characteristics and birth outcomes with gestational age acceleration.

Results: Using data from the Avon Longitudinal Study of Parents and Children ( = 863), we found that pre-pregnancy maternal overweight and obesity were associated with greater gestational age acceleration (mean difference = 1.6 days, 95% CI 0.7 to 2.6, and 2.9 days, 95% CI 1.3 to 4.4, respectively, compared with a body mass index < 25 kg/m,  < .001). There was evidence of an association between male sex and greater gestational age acceleration. Greater gestational age acceleration was associated with higher birthweight, birth length and head circumference of the child (mean differences per week higher gestational age acceleration: birthweight 0.1 kg, 95% CI 0.1 to 0.2,  < .001; birth length 0.4 cm, 95% CI 0.2 to 0.7,  < .001; head circumference 0.2 cm, 95% CI 0.1 to - 0.4,  < .001). There was evidence of an association between gestational age acceleration and mode of delivery (assisted versus unassisted delivery, odds ratio = 0.9 per week higher gestational age acceleration, 95% CI 0.7, 1.3 ( = .05); caesarean section versus unassisted delivery, odds ratio = 0.6, 95% CI 0.4 to 0.9 per week higher gestational age acceleration ( = .05)). There was no evidence of association for other parental and perinatal characteristics.

Conclusions: The associations of higher maternal body mass index and larger birth size with greater gestational age acceleration may imply that maternal overweight and obesity is associated with more rapid development of the fetus in utero. The implications of gestational age acceleration for postnatal health warrant further investigation.
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http://dx.doi.org/10.1186/s13148-018-0520-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6020346PMC
July 2019

Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?

Cancer Epidemiol Biomarkers Prev 2018 09 25;27(9):995-1010. Epub 2018 Jun 25.

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

Observational epidemiologic studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) uses genetic variants to proxy modifiable exposures to generate more reliable estimates of the causal effects of these exposures on diseases and their outcomes. MR has seen widespread adoption within cardio-metabolic epidemiology, but also holds much promise for identifying possible interventions for cancer prevention and treatment. However, some methodologic challenges in the implementation of MR are particularly pertinent when applying this method to cancer etiology and prognosis, including reverse causation arising from disease latency and selection bias in studies of cancer progression. These issues must be carefully considered to ensure appropriate design, analysis, and interpretation of such studies. In this review, we provide an overview of the key principles and assumptions of MR, focusing on applications of this method to the study of cancer etiology and prognosis. We summarize recent studies in the cancer literature that have adopted a MR framework to highlight strengths of this approach compared with conventional epidemiological studies. Finally, limitations of MR and recent methodologic developments to address them are discussed, along with the translational opportunities they present to inform public health and clinical interventions in cancer. .
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http://dx.doi.org/10.1158/1055-9965.EPI-17-1177DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522350PMC
September 2018

The MR-Base platform supports systematic causal inference across the human phenome.

Elife 2018 05 30;7. Epub 2018 May 30.

Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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http://dx.doi.org/10.7554/eLife.34408DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5976434PMC
May 2018
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