Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis.
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ABSTRACT:
SUBMITTER: Zou XL
PROVIDER: S-EPMC8638161 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundObesity is observationally associated with altered risk of many female reproductive conditions. These include polycystic ovary syndrome (PCOS), abnormal uterine bleeding, endometriosis, infertility, and pregnancy-related disorders. However, the roles and mechanisms of obesity in the aetiology of reproductive disorders remain unclear. Thus, we aimed to estimate observational and genetically predicted causal associations between obesity, metabolic hormones, and female reproductive disorders.Methods and findingsLogistic regression, generalised additive models, and Mendelian randomisation (MR) (2-sample, non-linear, and multivariable) were applied to obesity and reproductive disease data on up to 257,193 women of European ancestry in UK Biobank and publicly available genome-wide association studies (GWASs). Body mass index (BMI), waist-to-hip ratio (WHR), and WHR adjusted for BMI were observationally (odds ratios [ORs] = 1.02-1.87 per 1-SD increase in obesity trait) and genetically (ORs = 1.06-2.09) associated with uterine fibroids (UF), PCOS, heavy menstrual bleeding (HMB), and pre-eclampsia. Genetically predicted visceral adipose tissue (VAT) mass was associated with the development of HMB (OR [95% CI] per 1-kg increase in predicted VAT mass = 1.32 [1.06-1.64], P = 0.0130), PCOS (OR [95% CI] = 1.15 [1.08-1.23], P = 3.24 × 10-05), and pre-eclampsia (OR [95% CI] = 3.08 [1.98-4.79], P = 6.65 × 10-07). Increased waist circumference posed a higher genetic risk (ORs = 1.16-1.93) for the development of these disorders and UF than did increased hip circumference (ORs = 1.06-1.10). Leptin, fasting insulin, and insulin resistance each mediated between 20% and 50% of the total genetically predicted association of obesity with pre-eclampsia. Reproductive conditions clustered based on shared genetic components of their aetiological relationships with obesity. This study was limited in power by the low prevalence of female reproductive conditions among women in the UK Biobank, with little information on pre-diagnostic anthropometric traits, and by the susceptibility of MR estimates to genetic pleiotropy.ConclusionsWe found that common indices of overall and central obesity were associated with increased risks of reproductive disorders to heterogenous extents in a systematic, large-scale genetics-based analysis of the aetiological relationships between obesity and female reproductive conditions. Our results suggest the utility of exploring the mechanisms mediating the causal associations of overweight and obesity with gynaecological health to identify targets for disease prevention and treatment.
| S-EPMC8806071 | biostudies-literature
Project description:Obesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue.To investigate whether higher BMI increases the risk of major depression.Two instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case-control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI.Linear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient -0.03, 95% CI -0.18 to 0.13, P = 0.73; GRS: coefficient -0.02, 95% CI -0.11 to 0.07, P = 0.62).Our instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.
| S-EPMC4076654 | biostudies-literature
Project description:To infer the causal association between childhood BMI and age at menarche, we performed a mendelian randomisation analysis using twelve established "BMI-increasing" genetic variants as an instrumental variable (IV) for higher BMI. In 8,156 women of European descent from the EPIC-Norfolk cohort, height was measured at age 39-77 years; age at menarche was self-recalled, as was body weight at age 20 years, and BMI at 20 was calculated as a proxy for childhood BMI. DNA was genotyped for twelve BMI-associated common variants (in/near FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, MTCH2, SEC16B, FAIM2 and SH2B1), and for each individual a "BMI-increasing-allele-score" was calculated by summing the number of BMI-increasing alleles across all 12 loci. Using this BMI-increasing-allele-score as an instrumental variable for BMI, each 1?kg/m(2) increase in childhood BMI was predicted to result in a 6.5% (95% CI: 4.6-8.5%) higher absolute risk of early menarche (before age 12 years). While mendelian randomisation analysis is dependent on a number of assumptions, our findings support a causal effect of BMI on early menarche and suggests that increasing prevalence of childhood obesity will lead to similar trends in the prevalence of early menarche.
| S-EPMC3136158 | biostudies-literature
Project description:BACKGROUND AND PURPOSE:To test whether alcohol intake, both observational and estimated by genetic instruments, is associated with risk of ischemic and haemorrhagic stroke. METHODS:We used data from the Copenhagen City Heart Study 1991 to 1994 and 2001 to 2003, and the Copenhagen General Population Study 2003 to 2012 (n=78,546). As measure of alcohol exposure, self-reported consumption and genetic variation in alcohol metabolizing genes (alcohol dehydrogenase ADH1B and ADH1C) as instrumental variables were used. Stroke diagnoses were obtained from a validated hospital register. RESULTS:During follow-up 2,535 cases of ischemic and haemorrhagic stroke occurred. Low and moderate alcohol intake (1 to 20 drinks/week) was associated with reduced risk of stroke. The hazard ratios associated with drinking 1 to 6, 7 to 13, and 14 to 20 drinks/week were 0.84 (95% confidence interval [CI], 0.76 to 0.92), 0.83 (95% CI, 0.73 to 0.94), and 0.84 (95% CI, 0.73 to 0.97), respectively, compared with drinking <1 drink/day. ADH1B and ADH1C genotypes were not associated with risk of stroke. Further analysis to test the included measures revealed that increasing alcohol intake (per 1 drink/day) was positively associated with risk of alcoholic liver cirrhosis, but not associated with risk of stroke, and that increasing blood pressure (per systolic 10 mm Hg) was not associated with risk of alcoholic liver cirrhosis, but positively associated with risk of stroke. CONCLUSIONS:Low and moderate self-reported alcohol intake was associated with reduced risk of stroke. The result was not supported by the result from the causal genetic analysis.
| S-EPMC6007300 | biostudies-literature
Project description:BackgroundObservational studies have associated adiposity with an increased risk of colorectal cancer (CRC). However, such studies do not establish a causal relationship. To minimise bias from confounding we performed a Mendelian randomisation (MR) analysis to examine the relationship between adiposity and CRC.MethodsWe used SNPs associated with adult body mass index (BMI), waist-hip ratio (WHR), childhood obesity and birth weight as instrumental variables in a MR analysis of 9254 CRC cases and 18 386 controls.ResultsIn the MR analysis, the odds ratios (ORs) of CRC risk per unit increase in BMI, WHR and childhood obesity were 1.23 (95% CI: 1.02-1.49, P=0.033), 1.59 (95% CI: 1.08-2.34, P=0.019) and 1.07 (95% CI: 1.03-1.13, P=0.018), respectively. There was no evidence for association between birth weight and CRC (OR=1.22, 95% CI: 0.89-1.67, P=0.22). Combining these data with a concurrent MR-based analysis for BMI and WHR with CRC risk (totalling to 18 190 cases, 27 617 controls) provided increased support, ORs for BMI and WHR were 1.26 (95% CI: 1.10-1.44, P=7.7 × 10(-4)) and 1.40 (95% CI: 1.14-1.72, P=1.2 × 10(-3)), respectively.ConclusionsThese data provide further evidence for a strong causal relationship between adiposity and the risk of developing CRC highlighting the urgent need for prevention and treatment of adiposity.
| S-EPMC4947703 | biostudies-literature
Project description:It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. We performed Mendelian randomisation (MR) to investigate the causal relationships between SDB, body mass index (BMI) and AF. Single-nucleotide polymorphisms associated with SDB (n = 29) and BMI (n = 453) were selected as instrumental variables to investigate the effects of SDB and BMI on AF, using genetic association data on 55,114 AF cases and 482,295 controls. Primary analysis was conducted using inverse-variance weighted MR. Higher genetically predicted SDB and BMI were associated with increased risk of AF (OR per log OR increase in snoring liability 2.09 (95% CI 1.10-3.98), p = 0.03; OR per 1-SD increase in BMI 1.33 (95% CI 1.24-1.42), p < 0.001). The association between SDB and AF was not observed in sensitivity analyses, whilst associations between BMI and AF remained consistent. Similarly, in multivariable MR, SDB was not associated with AF after adjusting for BMI (OR 0.68 (95% CI 0.42-1.10), p = 0.12). Higher BMI remained associated with increased risk of AF after adjusting for OSA (OR 1.40 (95% CI 1.30-1.51), p < 0.001). Elevated BMI appears causal for AF, independent of SDB. Our data suggest that the association between SDB, in general, and AF is attributable to mediation or confounding from obesity, though we cannot exclude that more severe SDB phenotypes (i.e., OSA) are causal for AF.
| S-EPMC8774383 | biostudies-literature
Project description:BackgroundIncreased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis.MethodsWe first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy.FindingsIn the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04-1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08-1·29), 1·10 (1·00-1·22), and 1·05 (0·92-1·20), respectively, per 1 SD increment in plasma urate.InterpretationConventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions.FundingUK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council.
| S-EPMC4805857 | biostudies-literature
Project description:BackgroundWhile dietary fat has been established as a risk factor for colorectal cancer (CRC), associations between fatty acids (FAs) and CRC have been inconsistent. Using Mendelian randomisation (MR), we sought to evaluate associations between polyunsaturated (PUFA), monounsaturated (MUFA) and saturated FAs (SFAs) and CRC risk.MethodsWe analysed genotype data on 9254 CRC cases and 18,386 controls of European ancestry. Externally weighted polygenic risk scores were generated and used to evaluate associations with CRC per one standard deviation increase in genetically defined plasma FA levels.ResultsRisk reduction was observed for oleic and palmitoleic MUFAs (OROA = 0.77, 95% CI: 0.65-0.92, P = 3.9 × 10-3; ORPOA = 0.36, 95% CI: 0.15-0.84, P = 0.018). PUFAs linoleic and arachidonic acid had negative and positive associations with CRC respectively (ORLA = 0.95, 95% CI: 0.93-0.98, P = 3.7 × 10-4; ORAA = 1.05, 95% CI: 1.02-1.07, P = 1.7 × 10-4). The SFA stearic acid was associated with increased CRC risk (ORSA = 1.17, 95% CI: 1.01-1.35, P = 0.041).ConclusionResults from our analysis are broadly consistent with a pro-inflammatory FA profile having a detrimental effect in terms of CRC risk.
| S-EPMC5630201 | biostudies-literature
Project description:OBJECTIVE:To determine whether body mass index, body fat percentage, and waist circumference influence smoking status and intensity. DESIGN:Mendelian randomisation study. SETTING:UK Biobank, with replication of results from the Tobacco and Genetics (TAG) consortium. PARTICIPANTS:European descent participants from the UK Biobank cohort (n=372?791) and the TAG consortium (n=74?035). MAIN OUTCOME MEASURES:Risk of current and past smoking, number of cigarettes smoked per day, age of smoking initiation. RESULTS:The Mendelian randomisation analysis indicated that each standard deviation increment in body mass index (4.6) increased the risk of being a smoker (odds ratio 1.18 (95% confidence interval 1.13 to 1.23), P<0.001). This association was replicated in the TAG consortium data (1.19 (1.06 to 1.33), P=0.003). Furthermore, each standard deviation increment in body mass index was estimated to increase smoking intensity by 0.88 cigarettes per day (95% confidence interval 0.50 to 1.26, P<0.001) in UK Biobank and 1.27 cigarettes per day in the TAG consortium (0.46 to 2.07, P=0.002). Similar results were also seen for body fat percentage and waist circumference in both UK Biobank and the TAG consortium data. CONCLUSIONS:These results strongly suggest that higher adiposity influences smoking behaviour and could have implications for the implementation of public health interventions aiming to reduce the prevalence of these important risk factors.
| S-EPMC5953237 | biostudies-literature
Project description:BackgroundThe prevalence of obesity has increased in the United Kingdom, and reliably measuring the impact on quality of life and the total healthcare cost from obesity is key to informing the cost-effectiveness of interventions that target obesity, and determining healthcare funding. Current methods for estimating cost-effectiveness of interventions for obesity may be subject to confounding and reverse causation. The aim of this study is to apply a new approach using mendelian randomisation for estimating the cost-effectiveness of interventions that target body mass index (BMI), which may be less affected by confounding and reverse causation than previous approaches.Methods and findingsWe estimated health-related quality-adjusted life years (QALYs) and both primary and secondary healthcare costs for 310,913 men and women of white British ancestry aged between 39 and 72 years in UK Biobank between recruitment (2006 to 2010) and 31 March 2017. We then estimated the causal effect of differences in BMI on QALYs and total healthcare costs using mendelian randomisation. For this, we used instrumental variable regression with a polygenic risk score (PRS) for BMI, derived using a genome-wide association study (GWAS) of BMI, with age, sex, recruitment centre, and 40 genetic principal components as covariables to estimate the effect of a unit increase in BMI on QALYs and total healthcare costs. Finally, we used simulations to estimate the likely effect on BMI of policy relevant interventions for BMI, then used the mendelian randomisation estimates to estimate the cost-effectiveness of these interventions. A unit increase in BMI decreased QALYs by 0.65% of a QALY (95% confidence interval [CI]: 0.49% to 0.81%) per year and increased annual total healthcare costs by £42.23 (95% CI: £32.95 to £51.51) per person. When considering only health conditions usually considered in previous cost-effectiveness modelling studies (cancer, cardiovascular disease, cerebrovascular disease, and type 2 diabetes), we estimated that a unit increase in BMI decreased QALYs by only 0.16% of a QALY (95% CI: 0.10% to 0.22%) per year. We estimated that both laparoscopic bariatric surgery among individuals with BMI greater than 35 kg/m2, and restricting volume promotions for high fat, salt, and sugar products, would increase QALYs and decrease total healthcare costs, with net monetary benefits (at £20,000 per QALY) of £13,936 (95% CI: £8,112 to £20,658) per person over 20 years, and £546 million (95% CI: £435 million to £671 million) in total per year, respectively. The main limitations of this approach are that mendelian randomisation relies on assumptions that cannot be proven, including the absence of directional pleiotropy, and that genotypes are independent of confounders.ConclusionsMendelian randomisation can be used to estimate the impact of interventions on quality of life and healthcare costs. We observed that the effect of increasing BMI on health-related quality of life is much larger when accounting for 240 chronic health conditions, compared with only a limited selection. This means that previous cost-effectiveness studies have likely underestimated the effect of BMI on quality of life and, therefore, the potential cost-effectiveness of interventions to reduce BMI.
| S-EPMC8437285 | biostudies-literature