Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis

Abstract

Background: The causal relationship between childhood obesity and stroke remains unclear. Our objective was to elucidate the causal relationship between childhood obesity and the risk of stroke and its subtypes by performing Mendelian randomisation (MR) analyses.Methods: Genetic instruments for childhood obesity were obtained from a genome-wide association study (GWAS) of 13,848 European participants. Summary level data for stroke, intracerebral haemorrhage, ischaemic stroke (IS), and its subtypes were evaluated using the MEGASTROKE GWAS dataset, which included 446,696 European adults. Inverse-variance weighting, weighted-median analysis, MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR-Robust Adjusted Profile Score were applied in this MR analysis. The leave-one-out sensitivity test, MR-PRESSO Global test, and Cochran’s Q test were conducted to confirm the accuracy and robustness of our results.Results: Genetic evaluations revealed that childhood obesity was associated with a higher risk of stroke (OR = 1.04, 95%CI: 1.01–1.07, p = 0.005) and IS (OR = 1.05, 95%CI: 1.02–1.08, p = 0.003), but not with intracerebral haemorrhage (ICH, OR = 0.93, 95%CI: 0.80–1.09, p = 0.39). In the subtype analysis, childhood obesity was also associated with large artery stroke (LAS, OR = 1.12, 95%CI: 1.02–1.22, p = 0.016) but not with cardioembolic stroke (OR = 1.06, 95%CI: 0.96–1.18, p = 0.21) and small vessel stroke (OR = 1.06, 95%CI: 0.98–1.15, p = 0.17). These results were stable in the sensitivity analysis and remained significant after Bonferroni correction.Conclusion: Our study provides evidence that childhood obesity is associated with a higher risk of stroke, IS, and LAS. The prevention of stroke, especially IS and LAS, should be promoted in populations with childhood obesity.

Causal Association Between Inflammatory Bowel Disease and Psoriasis: A Two-Sample Bidirectional Mendelian Randomization Study

“…Due to the reduced significance threshold, F statistics were used to evaluate the risk of weak instrument bias, producing a bias level of F <10. Selected SNPs were also matched to databases for phenome-wide association studies (pheWAS) to avoid the potential association between the SNPs and outcomes confounders with a threshold of p < 5 x 10 -6 (26,28).…”

A causal relationship between childhood obesity and risk of osteoarthritis: results from a two-sample Mendelian randomization analysis

“…As such, we selected SNPs using a less stringent significance of 5 × 10 −6 . This approach has been suggested in previous studies [ 21 , 22 ], with the limitation that it can cause weak instrumental variable bias. We calculated F statistics to assess the risk of such bias and did not find strong evidence of its existence (except for rs9568856 [ F = 9.1367] and rs17697518 [ F = 8.9828], other IVs all showed an F value greater than 10).…”

“…When the threshold was set as p < 5 × 10 −8 , only six SNPs could be identified thus failing to meet the minimum requirements for MR studies of at least 10 eligible IVs [ 19 , 20 ]. As such, 15 SNPs were selected using a less stringent threshold of p < 5 × 10 −6 [ 21 , 22 ] and were detected at phenome-wide association studies (pheWAS) catalog databases to identify whether there was a potential association of these SNPs with confounders of outcomes, with a threshold of p < 5 × 10 −6 [ 22 , 23 ]. F statistics were calculated to estimate the sample overlap effect and weak instrument bias considering the relatively relaxed threshold, and an F < 10 was considered dubious bias [ 24 ].…”

Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study

“…It has been shown that after the linear regression of each genetic variant on risk factors at p < 1 × 10 −5 as a screening criterion, the results showed the low possibility of weak instrumental variable bias in MR analysis. Therefore, we chose SNPs as IVs associated at this significance level since there were not enough SNPs associated at the genome-wide significant threshold of 5 × 10 −8 [ 27 , 28 ]. Secondly, we used the PhenoScanner tool to ensure whether the IVs were significantly correlated with the risk factors for GDM [ 29 , 30 ].…”