Effects of childhood obesity on heart failure and its associated risk factors in the European population: A Mendelian randomization study

BACKGROUND AND AIMS

Observational studies have shown that obesity considerably affects the cardiovascular system. Thus we conducted this Mendelian randomization (MR) analysis to evaluate the causal effect of childhood obesity on heart failure (HF) and its risk factors.

METHODS AND RESULTS

We obtained genetic instruments from genome-wide association studies (GWAS) that investigated childhood obesity, HF, type 2 diabetes mellitus (T2DM), atrial fibrillation (AF), coronary artery disease (CAD), myocardial infarction (MI), chronic kidney disease (CKD), valvular heart disease, myocarditis, hypertrophic cardiomyopathy, and hyperthyroidism. Inverse variance weighting (IVW), weighted median analysis, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) were employed for MR analyses. In addition, the leave-one-out sensitivity test, MR-PRESSO global test, and Cochran's Q test were used for sensitivity analyses. Genetic evaluations showed that childhood obesity increases the risk of HF (odds ratio [OR] = 1.11, 95%CI: 1.05-1.17, p = 1.26 × 10-4), T2DM (OR = 1.17, 95%CI: 1.12-1.23, p = 8.80 × 10-12), AF (OR = 1.08, 95%CI: 1.05-1.12, p = 2.66 × 10-7), MI (OR = 1.08, 95%CI: 1.04-1.13, p = 3.35 × 10-4), and CAD (OR = 1.08, 95%CI: 1.03-1.13, p = 1.48 × 10-3). We found no association between childhood obesity and CKD, valvular heart disease, myocarditis, hypertrophic cardiomyopathy, or hyperthyroidism. Sensitivity analysis and Bonferroni's correction showed consistent results.

CONCLUSIONS

Our study provides new evidence for the relationship between childhood obesity and HF and its risk factors. The results indicate that individuals with a history of childhood obesity require more clinical attention to prevent the development of HF.

Risk of cardiovascular comorbidity in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a systemic inflammatory disorder associated with increased comorbid prevalence of cardiovascular diseases. We aimed to quantify the magnitudes of association between overall and specific types of cardiovascular disease, major cardiovascular risk factors, and COPD.

METHODS

We searched Cochrane, Medline, and Embase databases for studies published between Jan 1, 1980, and April 30, 2015, on the prevalence of cardiovascular disease and its risk factors in patients with COPD versus matched controls or random samples from the general public. We assessed associations with random-effects meta-analyses. We studied heterogeneity and biases with random-effects meta-regressions, jackknife sensitivity analyses, assessment of funnel plots, and Egger tests.

FINDINGS

We identified 18,176 unique references and included 29 datasets in the meta-analyses. Compared with the non-COPD population, patients with COPD were more likely to be diagnosed with cardiovascular disease (odds ratio [OR] 2·46; 95% CI 2·02-3·00; p<0·0001), including a two to five times higher risk of ischaemic heart disease, cardiac dysrhythmia, heart failure, diseases of the pulmonary circulation, and diseases of the arteries. Additionally, patients with COPD reported hypertension more often (OR 1·33, 95% CI 1·13-1·56; p=0·0007), diabetes (1·36, 1·21-1·53; p<0·0001], and ever smoking (4·25, 3·23-5·60; p<0·0001). The associations between COPD and these cardiovascular disease types and cardiovascular disease risk factors were consistent and valid across studies. Enrolment period, age, quality of data, and COPD diagnosis partly explained the heterogeneity.

INTERPRETATION

The coexistence of COPD, cardiovascular disease, and major risk factors for cardiovascular disease highlights the crucial need for the development of strategies to screen for and reduce cardiovascular risks associated with COPD.

FUNDING

Canadian Institutes of Health Research.

Molecular damage in Fabry disease: characterization and prediction of alpha-galactosidase A pathological mutations

Loss-of-function mutations of the enzyme alpha-galactosidase A (GLA) causes Fabry disease (FD), that is a rare and potentially fatal disease. Identification of these pathological mutations by sequencing is important because it allows an early treatment of the disease. However, before taking any treatment decision, if the mutation identified is unknown, we first need to establish if it is pathological or not. General bioinformatic tools (PolyPhen-2, SIFT, Condel, etc.) can be used for this purpose, but their performance is still limited. Here we present a new tool, specifically derived for the assessment of GLA mutations. We first compared mutations of this enzyme known to cause FD with neutral sequence variants, using several structure and sequence properties. Then, we used these properties to develop a family of prediction methods adapted to different quality requirements. Trained and tested on a set of known Fabry mutations, our methods have a performance (Matthews correlation: 0.56-0.72) comparable or better than that of the more complex method, Polyphen-2 (Matthews correlation: 0.61), and better than those of SIFT (Matthews correl.: 0.54) and Condel (Matthews correl.: 0.51). This result is validated in an independent set of 65 pathological mutations, for which our method displayed the best success rate (91.0%, 87.7%, and 73.8%, for our method, PolyPhen-2 and SIFT, respectively). These data confirmed that our specific approach can effectively contribute to the identification of pathological mutations in GLA, and therefore enhance the use of sequence information in the identification of undiagnosed Fabry patients.