Joint and interactive associations of body mass index and genetic factors with cardiovascular disease: a prospective study in UK Biobank
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SUBMITTER: Huang R
PROVIDER: S-EPMC11367834 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:AimsThe causal role of adiposity for several cardiovascular diseases (CVDs) is unclear. Our primary aim was to apply the Mendelian randomization design to investigate the associations of body mass index (BMI) with 13 CVDs and arterial hypertension. We also assessed the roles of fat mass and fat-free mass on the same outcomes.Methods and resultsSingle-nucleotide polymorphisms associated with BMI and fat mass and fat-free mass indices were used as instrumental variables to estimate the associations with the cardiovascular conditions among 367 703 UK Biobank participants. After correcting for multiple testing, genetically predicted BMI was significantly positively associated with eight outcomes, including and with decreasing magnitude of association: aortic valve stenosis, heart failure, deep vein thrombosis, arterial hypertension, peripheral artery disease, coronary artery disease, atrial fibrillation, and pulmonary embolism. The odds ratio (OR) per 1 kg/m2 increase in BMI ranged from 1.06 [95% confidence interval (CI) 1.02-1.11; P = 2.6 × 10-3] for pulmonary embolism to 1.13 (95% CI 1.05-1.21; P = 1.2 × 10-3) for aortic valve stenosis. There was suggestive evidence of positive associations of genetically predicted fat mass index with nine outcomes (P < 0.05). The strongest magnitude of association was with aortic valve stenosis (OR per 1 kg/m2 increase in fat mass index 1.46, 95% CI 1.13-1.88; P = 3.9 × 10-3). There was suggestive evidence of inverse associations of fat-free mass index with atrial fibrillation, ischaemic stroke, and abdominal aortic aneurysm.ConclusionThis study provides evidence that higher BMI and particularly fat mass index are associated with increased risk of aortic valve stenosis and most other cardiovascular conditions.
| S-EPMC6945523 | biostudies-literature
Project description:BackgroundGrowing evidence suggests that individuals with anxiety disorder have an elevated risk of cardiovascular disease (CVD) but few studies have assessed this association independently of or jointly with depression.MethodsWe conducted a prospective cohort study using UK Biobank. Diagnoses of anxiety disorder, depression, and CVDs were ascertained through linked hospital admission and mortality data. Individual and joint associations between anxiety disorder and depression and CVD overall, as well as each of myocardial infarction, stroke/transient ischemic attack, and heart failure, were analyzed using Cox proportional hazard models and interaction tests.ResultsAmong the 431,973 participants, the risk of CVD was higher among those who had been diagnosed with anxiety disorder only (hazard ratio [HR] 1.72; 95% confidence interval [CI] 1.32-2.24), depression only (HR 2.07; 95% CI 1.79-2.40), and both conditions (HR 2.89; 95% CI 2.03-4.11) compared to those without these conditions, respectively. There was very little evidence of multiplicative or additive interaction. Results were similar for myocardial infarction, stroke/transient ischemic attack, and heart failure.ConclusionsHaving anxiety is associated with the same magnitude of increased risk of CVD among people who do not have depression and those who do. Anxiety disorder should be considered for inclusion in CVD risk prediction and stratification, in addition to depression.
| S-EPMC10377450 | biostudies-literature
Project description:ObjectiveTo determine whether height and body mass index (BMI) have a causal role in five measures of socioeconomic status.DesignMendelian randomisation study to test for causal effects of differences in stature and BMI on five measures of socioeconomic status. Mendelian randomisation exploits the fact that genotypes are randomly assigned at conception and thus not confounded by non-genetic factors.SettingUK Biobank.Participants119,669 men and women of British ancestry, aged between 37 and 73 years.Main outcome measuresAge completed full time education, degree level education, job class, annual household income, and Townsend deprivation index.ResultsIn the UK Biobank study, shorter stature and higher BMI were observationally associated with several measures of lower socioeconomic status. The associations between shorter stature and lower socioeconomic status tended to be stronger in men, and the associations between higher BMI and lower socioeconomic status tended to be stronger in women. For example, a 1 standard deviation (SD) higher BMI was associated with a £210 (€276; $300; 95% confidence interval £84 to £420; P=6 × 10(-3)) lower annual household income in men and a £1890 (£1680 to £2100; P=6 × 10(-15)) lower annual household income in women. Genetic analysis provided evidence that these associations were partly causal. A genetically determined 1 SD (6.3 cm) taller stature caused a 0.06 (0.02 to 0.09) year older age of completing full time education (P=0.01), a 1.12 (1.07 to 1.18) times higher odds of working in a skilled profession (P=6 × 10(-7)), and a £1130 (£680 to £1580) higher annual household income (P=4 × 10(-8)). Associations were stronger in men. A genetically determined 1 SD higher BMI (4.6 kg/m(2)) caused a £2940 (£1680 to £4200; P=1 × 10(-5)) lower annual household income and a 0.10 (0.04 to 0.16) SD (P=0.001) higher level of deprivation in women only.ConclusionsThese data support evidence that height and BMI play an important partial role in determining several aspects of a person's socioeconomic status, especially women's BMI for income and deprivation and men's height for education, income, and job class. These findings have important social and health implications, supporting evidence that overweight people, especially women, are at a disadvantage and that taller people, especially men, are at an advantage.
| S-EPMC4783516 | biostudies-literature
Project description:PurposeOsteoporosis is a degenerative disease that affects women and men of all races. We studied the association between body mass index (BMI), rs2908004 polymorphism of the WNT16 gene, and osteoporosis using data from Taiwan Biobank (TWB).Patients and methodsWe analyzed data from 10,942 subjects aged 30 to 70. We defined osteoporosis based on a mean T-score of -2.5 and below in the hip. Body mass index was classified following the guidelines of the Health Promotion Administration. Imputation was carried out using the IMPUTE2 (v2.3.1) program. Multiple logistic regression was used for analysis. The odds ratios (ORs) and 95% confidence interval (CI) for osteoporosis were determined.ResultsIn the multivariate regression model, variant rs2908004 had a significant association with osteoporosis. That is, the rs2908004-GA+AA genotype was associated with lower osteoporosis risk than the GG genotype (OR, 0.651; 95% CI = 0.544 to 0.780). Compared to normal-weight, underweight was significantly associated with a higher risk of osteoporosis (OR, 6.517; 95% CI = 4.624 to 9.186) while overweight and obesity were protective (OR, 0.176; 95% CI = 0.140 to 0.221 and 0.057; 95% CI = 0.039 to 0.083, respectively). There was an interaction between rs2908004 and BMI (p = 0.0148). Subgroup analyses (using rs2908004-GG/normal-weight as the reference group) indicated ORs of 7.66 (95% CI = 5.153 to 11.394) in the rs2908004-GG/underweight group and 3.002 (95% CI = 1.509 to 5.974) in the rs2908004-GA+AA/underweight group (95% CI = 1.509 to 5.974). Odds ratios were substantially lower in rs2908004-GG/obese, rs2908004-GG/overweight, GA+AA/normal-weight, rs2908004-GA+AA/overweight, and rs2908004-GA+AA/obese groups, respectively.ConclusionAccording to our study, underweight was associated with an increased risk of osteoporosis irrespective of WNT16 rs2908004 genotypes, while overweight and obesity were associated with a lower risk.
| S-EPMC9738159 | biostudies-literature
Project description:BackgroundAn increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants.MethodsIn Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation.ResultsComplete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter).ConclusionBoth methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them.
| S-EPMC10114047 | biostudies-literature
Project description:BackgroundLow skeletal muscle volume may increase dementia risk through mechanisms affecting brain structure. However, it is unclear whether this relationship exists outside of sarcopenia and/or varies by other factors. We aimed to study the interplay between skeletal muscle volume and factors, such as age, sex, and body mass index (BMI), in explaining brain structure at midlife in a cohort without sarcopenia.MethodsWe used abdominal and brain magnetic resonance imaging (MRI) data from a population-based cohort enrolled in the UK Biobank. The following measures were derived: thigh fat-free muscle volume (FFMV), total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), total hippocampal volume (THV), and white matter hyperintensity volume (WMHV). Participants below sex-based grip strength thresholds suggesting probable sarcopenia were excluded. Linear regression analysis was used to study the interaction or mediation effects of age, sex, and BMI on the associations between FFMV and brain volumes.ResultsData were available for 20,353 participants (median age 64 years, 53% female). We found interactions between thigh FFMV, BMI, and age (all p < 0.05). Greater thigh FFMV was associated with better brain volumes in those aged <64 years with normal (TBV: β = 2.0 ml/L, p = 0.004; GMV: β = 0.8 ml/L, p = 0.04; WMV: β = 1.1 ml/L, p = 0.006; WMHV: β = -0.2 ml/L, p = 3.7 × 10-5) or low BMI (TBV: β = 21.2 ml/L, p = 0.003; WMV: β = 13.3 ml/L, p = 0.002, WMHV: β = -1.1 ml/L, p = 0.04).ConclusionGreater thigh muscle volume correlates with better brain volumes at midlife in people without sarcopenia, but this relationship weakens with greater age and BMI. Further study is required to investigate the underlying mechanisms to understand which components of body composition are potentially modifiable risk factors for dementia.
| S-EPMC11456486 | biostudies-literature
Project description:Background There is debate whether body mass index is a good predictor of health outcomes because different tissues, namely skeletal muscle mass (SMM) and fat mass (FM), may be differentially associated with risk. We investigated the association of appendicular SMM (aSMM) and FM with fatal and nonfatal cardiovascular disease (CVD) and all-cause mortality. We compared their prognostic value to that of body mass index. Methods and Results We studied 356 590 UK Biobank participants aged 40 to 69 years with bioimpedance analysis data for whole-body FM and predicted limb muscle mass (to calculate aSMM). Associations between aSMM and FM with CVD and all-cause mortality were examined using multivariable Cox proportional hazards models. Over 3 749 501 person-years of follow-up, there were 27 784 CVD events and 15 844 all-cause deaths. In men, aSMM was positively associated with CVD incidence (hazard ratio [HR] per 1 SD 1.07; 95% CI, 1.06-1.09) and there was a curvilinear association in women. There were stronger positive associations between FM and CVD with HRs per SD of 1.20 (95% CI, 1.19-1.22) and 1.25 (95% CI, 1.23-1.27) in men and women respectively. Within FM tertiles, the associations between aSMM and CVD risk largely persisted. There were J-shaped associations between aSMM and FM with all-cause mortality in both sexes. Body mass index was modestly better at discriminating CVD risk. Conclusions FM showed a strong positive association with CVD risk. The relationship of aSMM with CVD risk differed between sexes, and potential mechanisms need further investigation. Body fat and SMM bioimpedance measurements were not superior to body mass index in predicting population-level CVD incidence or all-cause mortality.
| S-EPMC8200765 | biostudies-literature
Project description:ImportanceHigher body mass index (BMI) is a risk factor for cardiometabolic disease; however, the underlying causal associations remain unclear.ObjectivesTo use UK Biobank data to report causal estimates of the association between BMI and cardiometabolic disease outcomes and traits, such as pulse rate, using mendelian randomization.Design, setting, and participantsCross-sectional baseline data from a population-based cohort study including 119 859 UK Biobank participants with complete phenotypic (medical and sociodemographic) and genetic data. Participants attended 1 of 22 assessment centers across the United Kingdom between 2006 and 2010. The present study was conducted from May 1 to July 11, 2016.Main outcomes and measuresPrevalence of hypertension, coronary heart disease, and type 2 diabetes were determined at assessment, based on self-report. Blood pressure was measured clinically. Participants self-reported sociodemographic information pertaining to relevant confounders. A polygenic risk score comprising 93 single-nucleotide polymorphisms associated with BMI from previous genome-wide association studies was constructed, and the genetic risk score was applied to derive causal estimates using a mendelian randomization approach.ResultsOf the 119 859 individuals included in the study, 56 816 (47.4%) were men; mean (SD) age was 56.87 (7.93) years. Mendelian randomization analysis showed significant positive associations between genetically instrumented higher BMI and risk of hypertension (odds ratio [OR] per 1-SD higher BMI, 1.64; 95% CI, 1.48-1.83; P = 1.1 × 10-19), coronary heart disease (OR, 1.35; 95% CI, 1.09-1.69; P = .007) and type 2 diabetes (OR, 2.53; 95% CI, 2.04-3.13; P = 1.5 × 10-17), as well as systolic blood pressure (β = 1.65 mm Hg; 95% CI, 0.78-2.52 mm Hg; P = 2.0 × 10-04) and diastolic blood pressure (β = 1.37 mm Hg; 95% CI, 0.88-1.85 mm Hg; P = 3.6 × 10-08). These associations were independent of age, sex, Townsend deprivation scores, alcohol intake, and smoking history.Conclusions and relevanceThe results of this study add to the burgeoning evidence of an association between higher BMI and increased risk of cardiometabolic diseases. This finding has relevance for public health policies in many countries with increasing obesity levels.
| S-EPMC5710596 | biostudies-literature
Project description:BackgroundWhether cancer risk associated with a higher body mass index (BMI), a surrogate measure of adiposity, differs among adults with and without cardiovascular diseases (CVD) and/or type 2 diabetes (T2D) is unclear. The primary aim of this study was to evaluate separate and joint associations of BMI and CVD/T2D with the risk of cancer.MethodsThis is an individual participant data meta-analysis of two prospective cohort studies, the UK Biobank (UKB) and the European Prospective Investigation into Cancer and nutrition (EPIC), with a total of 577,343 adults, free of cancer, T2D, and CVD at recruitment. We used Cox proportional hazard regressions to estimate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between BMI and incidence of obesity-related cancer and in turn overall cancer with a multiplicative interaction between BMI and the two cardiometabolic diseases (CMD). HRs and 95% CIs for separate and joint associations for categories of overweight/obesity and CMD status were estimated, and additive interaction was quantified through relative excess risk due to interaction (RERI).ResultsIn the meta-analysis of both cohorts, BMI (per ~ 5 kg/m2) was positively associated with the risk of obesity-related cancer among participants without a CMD (HR: 1.11, 95%CI: 1.07,1.16), among participants with T2D (HR: 1.11, 95% CI: 1.05,1.18), among participants with CVD (HR: 1.17, 95% CI: 1.11,1.24), and suggestively positive among those with both T2D and CVD (HR: 1.09, 95% CI: 0.94,1.25). An additive interaction between obesity (BMI ≥ 30 kg/m2) and CVD with the risk of overall cancer translated into a meta-analytical RERI of 0.28 (95% CI: 0.09-0.47).ConclusionsIrrespective of CMD status, higher BMI increased the risk of obesity-related cancer among European adults. The additive interaction between obesity and CVD suggests that obesity prevention would translate into a greater cancer risk reduction among population groups with CVD than among the general population.
| S-EPMC10666332 | biostudies-literature
Project description:Associations of liver, metabolic, and inflammatory biomarkers in blood with body shape are unclear, because waist circumference (WC) and hip circumference (HC) are dependent on overall body size, resulting in bias. We have used the allometric "a body shape index" (ABSI = WC(mm)[Formula: see text]Weight(kg)-2/3[Formula: see text]Height(m)5/6) and hip index (HIwomen = HC(cm)[Formula: see text]Weight(kg)-0.482[Formula: see text]Height(cm)0.310, HImen = HC(cm)[Formula: see text]Weight(kg)-2/5[Formula: see text]Height(cm)1/5), which are independent of body mass index (BMI) by design, in multivariable linear regression models for 121,879 UK Biobank men and 135,559 women. Glucose, glycated haemoglobin (HbA1c), triglycerides, low-density-lipoprotein cholesterol, apolipoprotein-B, alanine aminotransferase (ALT), gamma-glutamyltransferase, and lymphocytes were associated positively with BMI and ABSI but inversely with HI. High-density-lipoprotein cholesterol and apolipoprotein-A1 were associated inversely with BMI and ABSI but positively with HI. Lipid-related biomarkers and ALT were associated only with HI in obese men. C-reactive protein, neutrophils, monocytes, and alkaline phosphatase were associated positively, while bilirubin was associated inversely, with BMI and ABSI but not with HI. Associations were consistent within the clinical reference ranges but were lost or changed direction for low or high biomarker levels. Our study confirms associations with waist and hip size, independent of BMI, for metabolic biomarkers but only with waist size for inflammatory biomarkers, suggesting different contribution of the mechanistic pathways related to body shape.
| S-EPMC9133113 | biostudies-literature