Mendelian Randomization Analyses Suggest Childhood Body Size Indirectly Influences End Points From Across the Cardiovascular Disease Spectrum Through Adult Body Size.
Ontology highlight
ABSTRACT:
SUBMITTER: Power GM
PROVIDER: S-EPMC8649247 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The rising prevalence of childhood obesity has been postulated as an explanation for the increasing rate of individuals diagnosed with type 1 diabetes (T1D). In this study, we use Mendelian randomization (MR) to provide evidence that childhood body size has an effect on T1D risk (OR = 2.05 per change in body size category, 95% CI = 1.20 to 3.50, P = 0.008), which remains after accounting for body size at birth and during adulthood using multivariable MR (OR = 2.32, 95% CI = 1.21 to 4.42, P = 0.013). We validate this direct effect of childhood body size using data from a large-scale T1D meta-analysis based on n = 15,573 cases and n = 158,408 controls (OR = 1.94, 95% CI = 1.21 to 3.12, P = 0.006). We also provide evidence that childhood body size influences risk of asthma, eczema and hypothyroidism, although multivariable MR suggested that these effects are mediated by body size in later life. Our findings support a causal role for higher childhood body size on risk of being diagnosed with T1D, whereas its influence on the other immune-associated diseases is likely explained by a long-term effect of remaining overweight for many years over the lifecourse.
| S-EPMC9051135 | biostudies-literature
Project description:Fat mass may be a causal determinant of bone mass, but the evidence is conflicting, possibly reflecting the influence of confounding factors. The recent identification of common genetic variants related to obesity in children provides an opportunity to implement a Mendelian randomization study of obesity and bone outcomes, which is less subject to confounding and several biases than conventional approaches. Genotyping was retrieved for variants of two loci reliably associated with adiposity (the fat mass and obesity-related gene FTO and that upstream of the MC4R locus) within 7470 children from the Avon Longitudinal Study of Parents and Children (ALSPAC) who had undergone total body DXA scans at a mean of 9.9 yr. Relationships between both fat mass/genotypes and bone measures were assessed in efforts to determine evidence of causality between adiposity and bone mass. In conventional tests of association, both with and without height adjustment, total fat mass was strongly related to total body, spinal, and upper and lower limb BMC (ratio of geometric means [RGM]: 1.118 [95% CI: 1.112, 1.123], 1.110 [95% CI: 1.102, 1.119], 1.101 [95% CI: 1.093, 1.108], 1.146 [95% CI: 1.143, 1.155]; p < 10(-10) [adjusted for sex, height, and sitting height]). Equivalent or larger effects were obtained from instrumental variable (IV) regression including the same covariates (1.139 [95% CI: 1.064, 1.220], 1.090 [95% CI: 1.010, 1.177], 1.142 [95% CI: 1.049, 1.243], 1.176 [95% CI: 1.099, 1.257]; p = 0.0002, 0.03, 0.002, and 2.3(-6) respectively). Similar results were obtained after adjusting for puberty, when truncal fat mass was used in place of total fat, and when bone area was used instead of bone mass. In analyses where total body BMC adjusted for bone area (BA) was the outcome (reflecting volumetric BMD), linear regression with fat mass showed evidence for association (1.004 [95% CI: 1.002, 1.007], p = 0.0001). IV regression also showed a positive effect (1.031 [95% CI: 1.000, 1.062], p = 0.05). When MC4R and FTO markers were used as instruments for fat mass, similar associations with BMC were seen to those with fat mass as measured by DXA. This suggests that fat mass is on the causal pathway for bone mass in children. In addition, both directly assessed and IV-assessed relationships between fat mass and volumetric density showed evidence for positive effects, supporting a hypothesis that fat effects on bone mass are not entirely accounted for by association with overall bone size.
| S-EPMC2875165 | biostudies-literature
Project description:ObjectiveTo evaluate the causal relationship between childhood body-mass index (BMI) at different ages and adult cardiometabolic traits.MethodsWe retrieved genetic instrument variables (IVs) for exposures (standardized BMI at newborn, infant, toddler and late childhood), cardiometabolic traits and potential confounders or mediators (adult BMI, SHBG, testosterone and age at menarche) from the corresponding genome-wide association analysis. We performed univariate and multivariable Mendelian randomization (MR) to dissect associations between age-specific childhood BMI and adult cardiometabolic outcomes. Odds ratio was used to present the direction of the causal association.ResultsIn univariate MR, higher newborn BMI was causally associated with reduced risk for type 2 diabetes in women. Late childhood BMI was associated with increased risk for female diabetes and coronary artery disease (CAD), myocardial infarction (MI), and chronic kidney disease (CKD) in general population. Among these associations, only association between late childhood BMI with MI remained significant after adjusting for adult male BMI and sex hormones, (OR = 1.120, 95% CI 1.023-1.226, p = 0.014). Besides, in multivariable MR, we found evidence for causal association between newborn BMI with reduced risk for CAD (OR = 0.862, 95% CI 0.751-0.989, p = 0.034) and MI (OR = 0.864, 95% CI 0.752-0.991, p = 0.037) in men. No obvious impact of infant or toddler BMI was identified on the above-mentioned diseases. For continuous cardiometabolic traits, in all age epochs except infant, higher BMI was associated with increased level of fasting glucose in women.ConclusionBMI at birth and late childhood exerts different impact on adult cardiometabolic diseases, while BMI at infant and toddler ages is not causally associated with these outcomes. The effect of childhood BMI may be influenced by sex disparities.
| S-EPMC10822942 | biostudies-literature
Project description:BACKGROUND:Evidence linking breast size to breast cancer risk has been inconsistent, and its interpretation is often hampered by confounding factors such as body mass index (BMI). Here, we used linkage disequilibrium score regression and two-sample Mendelian randomization (MR) to examine the genetic associations between BMI, breast size and breast cancer risk. METHODS:Summary-level genotype data from 23andMe, Inc (breast size, n = 33 790), the Breast Cancer Association Consortium (breast cancer risk, n = 228 951) and the Genetic Investigation of ANthropometric Traits (BMI, n = 183 507) were used for our analyses. In assessing causal relationships, four complementary MR techniques [inverse variance weighted (IVW), weighted median, weighted mode and MR-Egger regression] were used to test the robustness of the results. RESULTS:The genetic correlation (rg) estimated between BMI and breast size was high (rg = 0.50, P = 3.89x10-43). All MR methods provided consistent evidence that higher genetically predicted BMI was associated with larger breast size [odds ratio (ORIVW): 2.06 (1.80-2.35), P = 1.38x10-26] and lower overall breast cancer risk [ORIVW: 0.81 (0.74-0.89), P = 9.44x10-6]. No evidence of a relationship between genetically predicted breast size and breast cancer risk was found except when using the weighted median and weighted mode methods, and only with oestrogen receptor (ER)-negative risk. There was no evidence of reverse causality in any of the analyses conducted (P > 0.050). CONCLUSION:Our findings indicate a potential positive causal association between BMI and breast size and a potential negative causal association between BMI and breast cancer risk. We found no clear evidence for a direct relationship between breast size and breast cancer risk.
| S-EPMC6659372 | biostudies-literature
Project description:It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for 6 obesity-related cancers, we performed univariable and multivariable analyses using 1) Mendelian randomization (MR) analysis and 2) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger early life body size was associated with higher risk of endometrial (odds ratioMR = 1.61, 95% confidence interval = 1.23 to 2.11) and kidney (odds ratioMR = 1.40, 95% confidence interval = 1.09 to 1.80) cancer. These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life body mass index (BMI) was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.
| S-EPMC9468294 | biostudies-literature
Project description:BackgroundRaised C-reactive protein (CRP) is a risk factor for type 2 diabetes. According to the Mendelian randomization method, the association is likely to be causal if genetic variants that affect CRP level are associated with markers of diabetes development and diabetes. Our objective was to examine the nature of the association between CRP phenotype and diabetes development using CRP haplotypes as instrumental variables.Methods and findingsWe genotyped three tagging SNPs (CRP + 2302G > A; CRP + 1444T > C; CRP + 4899T > G) in the CRP gene and measured serum CRP in 5,274 men and women at mean ages 49 and 61 y (Whitehall II Study). Homeostasis model assessment-insulin resistance (HOMA-IR) and hemoglobin A1c (HbA1c) were measured at age 61 y. Diabetes was ascertained by glucose tolerance test and self-report. Common major haplotypes were strongly associated with serum CRP levels, but unrelated to obesity, blood pressure, and socioeconomic position, which may confound the association between CRP and diabetes risk. Serum CRP was associated with these potential confounding factors. After adjustment for age and sex, baseline serum CRP was associated with incident diabetes (hazard ratio = 1.39 [95% confidence interval 1.29-1.51], HOMA-IR, and HbA1c, but the associations were considerably attenuated on adjustment for potential confounding factors. In contrast, CRP haplotypes were not associated with HOMA-IR or HbA1c (p = 0.52-0.92). The associations of CRP with HOMA-IR and HbA1c were all null when examined using instrumental variables analysis, with genetic variants as the instrument for serum CRP. Instrumental variables estimates differed from the directly observed associations (p = 0.007-0.11). Pooled analysis of CRP haplotypes and diabetes in Whitehall II and Northwick Park Heart Study II produced null findings (p = 0.25-0.88). Analyses based on the Wellcome Trust Case Control Consortium (1,923 diabetes cases, 2,932 controls) using three SNPs in tight linkage disequilibrium with our tagging SNPs also demonstrated null associations.ConclusionsObserved associations between serum CRP and insulin resistance, glycemia, and diabetes are likely to be noncausal. Inflammation may play a causal role via upstream effectors rather than the downstream marker CRP.
| S-EPMC2504484 | biostudies-literature
Project description:AimsIncreases in fat-free mass and fat mass have been associated with higher risk of atrial fibrillation (AF) in observational studies. It is not known whether these associations reflect independent causal processes. Our aim was to evaluate independent causal roles of fat-free mass and fat mass on AF.Methods and resultsWe conducted a large observational study to estimate the associations between fat-free mass and fat mass on incident AF in the UK Biobank (N = 487 404, N events = 10 365). Genome-wide association analysis was performed to obtain genetic instruments for Mendelian randomization (MR). We evaluated the causal effects of fat-free mass and fat mass on AF with two-sample method by using genetic associations from AFGen consortium as outcome. Finally, we evaluated independent causal effects of fat-free mass and fat mass with multivariate MR. Both fat-free mass and fat mass had observational associations with incident AF [hazard ratio (HR) = 1.77, 95% confidence interval (CI) 1.72-1.83; HR = 1.40, 95% CI 1.37-1.43 per standard deviation increase in fat-free and fat mass, respectively]. The causal effects using the inverse-variance weighted method were 1.55 (95% CI 1.38-1.75) for fat-free mass and 1.30 (95% CI 1.17-1.45) for fat mass. Weighted median, Egger regression, and penalized methods showed similar estimates. The multivariate MR analysis suggested that the causal effects of fat-free and fat mass were independent of each other (causal risk ratios: 1.37, 95% CI 1.06-1.75; 1.28, 95% CI 1.03-1.58).ConclusionGenetically programmed increases in fat-free mass and fat mass independently cause an increased risk of AF.
| S-EPMC6475522 | biostudies-literature
Project description:Obesity has been reported to be related to memory impairment and decline in cognitive function, possibly further leading to the development of Alzheimer's disease (AD). However, observational studies revealed both negative and positive associations between body shape (BS) and AD, thereby making it difficult to confirm causality due to residual confounds and reverse causation. Thus, using genome-wide association study summary data, two-sample Mendelian randomization (MR) analyses were applied to identify whether there exists a causal association between BS and AD. BS was measured using anthropometric traits (ATs) in this study, including body mass index (BMI), waist-to-hip ratio (WHR), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), and waist circumference (WC). The associations of single nucleotide polymorphisms (SNP) with each AT and AD were obtained separately from aggregated data from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and International Genomics of Alzheimer's Project (IGAP) summary data (17,008 cases with AD and 37,154 controls). An inverse-variance weighted method was applied to obtain the overall causal estimate for multiple instrumental SNPs. The odds ratio (OR) [95% confidence interval (CI)] for AD risk per 1-SD difference in BMI was 1.04 (0.88, 1.23), in WHR was 1.01 (0.77, 1.33), in WHRadjBMI was 1.12 (0.89, 1.41), and in WC was 1.02 (0.82, 1.27). Furthermore, simulation analyses of survivor bias indicated the overall causal effect of BMI on risk of AD was not biased. In conclusion, the evidence from MR analyses showed no casual effect of BS on AD risk, which is inconsistent with the results from previous observational studies. The biological mechanism underlying the findings warrants further study.
| S-EPMC6795688 | biostudies-literature
Project description:BackgroundBody size (BS) is one of the risk factors for the development of many clinical diseases, but the relationship between BS and glaucoma is controversial. Herein, we try to use Mendelian randomization (MR) method to study BS causal association with glaucoma risk from the genetic level.MethodsThe Body Size was determined through anthropometric traits (ATs), such as body mass index (BMI), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), waist-to-hip ratio (WHR), and waist circumference (WC). Association of single nucleotide polymorphisms (SNPs) with each AT and glaucoma were determined individually from the aggregated data of the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the FinnGen study summary data (8,591 cases with glaucoma and 210,201 controls). To explore the role of BS and glaucoma, a two-sample MR analysis was performed on genome-wide association study (GWAS) data. Besides, three MR methods [inverse variance weighted (IVW), Weighted median, and MR-Egger regression] were used to get the whole causal estimate for multiple instrumental SNPs.ResultsBMI (OR = 1.20; 95% CI = 1.02-1.41; P = 0.03) and WC (OR = 1.32; 95% CI =1.04-1.69; P = 0.03) were associated with a risk of glaucoma. Besides, genetically predicted WHRadjBMI (OR = 1.10; 95% CI = 0.88-1.35; P = 0.43) and WHR (OR = 1.22; 95% CI = 0.93-1,572; P = 0.14) were not associated with glaucoma. No heterogeneity and directional pleiotropy were detected.ConclusionThe data of this study revealed that increased BMI and WC are potential risk factors for glaucoma, and WHRadjBMI and WHR are not associated with the occurrence of glaucoma.
| S-EPMC9538570 | biostudies-literature
Project description:BACKGROUND:Observational studies have illustrated that maternal central obesity is associated with birth size, including of birth weight, birth length and head circumference, but the causal nature of these associations remains unclear. Our study aimed to test the causal effect of maternal central obesity on birth size and puberty height growth using a Mendelian randomization (MR) analysis. METHODS:We performed two-sample MR using summary-level genome-wide public data. Thirty-five single nucleotide polymorphisms (SNPs), 25 SNPs and 41 SNPs were selected as instrumental variables for waist-to-hip ratio adjusted for BMI, waist circumference adjusted for BMI and hip circumference adjusted for BMI, respectively to test the causal effects of maternal central obesity on birth size and puberty height using an inverse-variance-weighted approach. RESULTS:In this MR analysis, we found no evidence of a causal association between waist circumference or waist-to-hip ratio and the outcomes. However, we observed that one standard deviation (SD) increase in hip circumference (HIP) was associated with a 0.392 SD increase in birth length (p?=?1.1?×?10-?6) and a 0.168 SD increase in birth weight (p?=?7.1?×?10-?5), respectively at the Bonferroni-adjusted level of significance. In addition, higher genetically predicted maternal HIP was strongly associated with the puberty heights (0.835 SD, p?=?8.4?×?10-?10). However, HIP was not associated with head circumference (p?=?0.172). CONCLUSIONS:A genetic predisposition to higher maternal HIP was causally associated with larger offspring birth size independent of maternal BMI. However, we found no evidence of a causal association between maternal waist circumference, waist-to-hip ratio and birth size.
| S-EPMC6069873 | biostudies-literature