Adiposity as a cause of cardiovascular disease: a Mendelian randomization study

Hägg, Sara; Fall, Tove; Ploner, Alexander; Mägi, Reedik; Fischer, Krista; Draisma, Harmen H.M.; Kals, Mart; Vries, Paul S. de; Dehghan, Abbas; Willems, Sara M.; Sarin, Antti‐Pekka; Kristiansson, Kati; Nuotio, Marja-Liisa; Havulinna, Aki S.; Bruijn, Renée F.A.G. de; Ikram, M Arfan; Kuningas, Maris; Stricker, Bruno H.; Franco, Oscar H.; Benyamin, Beben; Gieger, Christian; Hall, Alistair S.; Huikari, Ville; Jula, Antti; Järvelin, Marjo‐Riitta; Kaakinen, Marika; Kaprio, Jaakko; Kobl, Michael; Mangino, Massimo; Nelson, Christopher P.; Palotie, Aarno; Samani, Nilesh J.; Spector, Tim D.; Strachan, David P.; Tobin, Martin D.; Whitfield, John B.; Uitterlinden, André G.; Salomaa, Veikko; Syvänen, Ann‐Christine; Kuulasmaa, Kari; Magnusson, Patrik K. E.; Esko, Tõnu; Hofman, Albert; Geus, Eco J. C. de; Lind, Lars; Giedraitis, Vilmantas; Perola, Markus; Evans, Alun; Ferrières, Jean; Virtamo, Jarmo; Kee, Frank; Trégouët, David‐Alexandre; Arveiler, Dominique; Amouyel, Philippe; Gianfagna, Francesco; Brambilla, Paolo; Ripatti, Samuli; Duijn, Cornelia M. van; Metspalu, Andres; Prokopenko, Inga; McCarthy, Mark I.; Pedersen, Nancy L.; Ingelsson, Erik

doi:10.1093/ije/dyv094

Cited by 131 publications

(104 citation statements)

References 29 publications

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“…Consistent with previous studies [11][12][13][14] All results are β coefficients (SE) from the MR instrumental variable estimates using IVW and so reflect differences in mean outcome per one unit difference of the exposures for continuously measured outcomes and difference in log odds for binary outcomes (CHD/type 2 diabetes) *p < 0.05, **p < 0.01, ***p < 0.001 FI, fasting insulin; FPG, fasting plasma glucose; HDL-C, HDL-cholesterol; LDL-C, LDL-cholesterol; T2DM, type 2 diabetes mellitus; TG, triacylglycerols our understanding of which CHD risk factors mediate BMI effects. Our findings provide strong support for undertaking RCTs in obese people to test the effect of triacylglycerol reduction and glycaemic control on CHD risk.…”

Section: Discussionsupporting

confidence: 93%

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The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

Borges

Hemani

et al. 2017

Diabetologia

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Aims/hypothesis The extent to which effects of BMI on CHD are mediated by glycaemic and lipid risk factors is unclear. In this study we examined the effects of these traits using genetic evidence. Methods We used two-sample Mendelian randomisation to determine: (1) the causal effect of BMI on CHD (60,801 case vs 123,504 control participants), type 2 diabetes (34,840 case vs 114,981 control participants), fasting glucose (n = 46,186), insulin (n = 38,238), HbA 1c (n = 46,368) and LDL-cholesterol, HDL-cholesterol and triacylglycerols (n = 188,577); (2) the causal effects of glycaemic and lipids traits on CHD; and (3) the extent to which these traits mediate any effect of BMI on CHD.

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Section: Discussionsupporting

confidence: 93%

“…1) [11][12][13][14]. These studies used one-sample MR and were unable to undertake sensitivity analyses that have been developed for testing likely bias by pleiotropy [15].…”

Section: Introductionmentioning

confidence: 99%

The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

Borges

Hemani

et al. 2017

Diabetologia

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“…In total, the genetic variants from the 3 identified loci explained 0.9% variation of plasma PAI‐1 levels in the Framingham Heart Study 28. This strength of IV is in the range of others that have been employed in successful MR studies, suggesting these variants could serve as a potential IV in MR analyses with risk factor, subclinical, and clinical outcomes 26, 29, 30…”

Section: Introductionmentioning

confidence: 86%

Causal Effect of Plasminogen Activator Inhibitor Type 1 on Coronary Heart Disease

Song

Burgess

Eicher

et al. 2017

JAHA

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BackgroundPlasminogen activator inhibitor type 1 (PAI‐1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI‐1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI‐1 on CHD risk.Methods and ResultsTo evaluate the association between PAI‐1 and CHD, we applied a 3‐step strategy. First, we investigated the observational association between PAI‐1 and CHD incidence using a systematic review based on a literature search for PAI‐1 and CHD studies. Second, we explored the causal association between PAI‐1 and CHD using a Mendelian randomization approach using summary statistics from large genome‐wide association studies. Finally, we explored the causal effect of PAI‐1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta‐analysis, the highest quantile of blood PAI‐1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age‐ and sex‐adjusted model. The effect size was reduced in studies using a multivariable‐adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI‐1 level on CHD risk (odds ratio=1.22 per unit increase of log‐transformed PAI‐1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI‐1 on elevating blood glucose and high‐density lipoprotein cholesterol.ConclusionsOur study indicates a causal effect of elevated PAI‐1 level on CHD risk, which may be mediated by glucose dysfunction.

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“…37 However, another MR study including 20,055 participants and 1,500 ischemic stroke cases found a statistically significant association of genetically predicted higher BMI, assessed with a genetic instrument comprising 32 BMI-associated SNPs, with increased risk of ischemic stroke (hazard ratio 1.83, 95% CI 1.05-3.20 per 4.5-kg/m 2 increase in BMI). 38 Chief strengths of this study include the large number of total ischemic stroke cases and data on etiologic subtypes of ischemic stroke. Moreover, as a result of the MR design, reverse causation bias was prevented and potential confounding was reduced because genetic variants are not associated with self-selected dietary and lifestyle factors that may affect results from observational studies.…”

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confidence: 99%

Type 2 diabetes, glucose, insulin, BMI, and ischemic stroke subtypes

Larsson¹,

Scott²,

Traylor³

et al. 2017

Neurology

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Objective: To implement a mendelian randomization (MR) approach to determine whether type 2 diabetes mellitus (T2D), fasting glucose, fasting insulin, and body mass index (BMI) are causally associated with specific ischemic stroke subtypes.Methods: MR estimates of the association between each possible risk factor and ischemic stroke subtypes were calculated with inverse-variance weighted (conventional) and weighted median approaches, and MR-Egger regression was used to explore pleiotropy. The number of single nucleotide polymorphisms (SNPs) used as instrumental variables was 49 for T2D, 36 for fasting glucose, 18 for fasting insulin, and 77 for BMI. Genome-wide association study data of SNPstroke associations were derived from METASTROKE and the Stroke Genetics Network (n 5 18,476 ischemic stroke cases and 37,296 controls).Results: Conventional MR analysis showed associations between genetically predicted T2D and large artery stroke (odds ratio [OR] 1.28, 95% confidence interval [CI] 1.16-1.40, p 5 3.3 3 10 27 ) and small vessel stroke (OR 1.21, 95% CI 1.10-1.33, p 5 8.9 3 10 25 ) but not cardioembolic stroke (OR 1.06, 95% CI 0.97-1.15, p 5 0.17). The association of T2D with large artery stroke but not small vessel stroke was consistent in a sensitivity analysis using the weighted median method, and there was no evidence of pleiotropy. Genetically predicted fasting glucose and fasting insulin levels and BMI were not statistically significantly associated with any ischemic stroke subtype. Conclusions:This study provides support that T2D may be causally associated with large artery stroke. Neurology ® 2017;89:454-460 GLOSSARY BMI 5 body mass index; CI 5 confidence interval; GWAS 5 genome-wide association studies; MR 5 mendelian randomization; NINDS 5 National Institute of Neurologic Disorders and Stroke; 1KG 5 1000 Genomes; OR 5 odds ratio; SiGN 5 Stroke Genetics Network; SNP 5 single nucleotide polymorphism; TOAST 5 Trial of Org 10172 in Acute Stroke Treatment; T2D 5 type 2 diabetes mellitus.Stroke is one of the leading causes of disability and death worldwide.1 The burden of stroke is projected to increase considerably in the next decades. Hence, there is a need to develop effective prevention strategies for stroke, which necessitates a better understanding of the underlying risk factors. About 80% of all strokes are ischemic, 1 but this term describes a syndrome caused by a number of different pathologies, which may have different treatments.2 The major etiologies of ischemic stroke are large artery atherosclerosis (large artery stroke), small vessel atherosclerosis (small vessel stroke), and cardioembolism (cardioembolic stroke). Recent data from genomewide association studies (GWAS) have shown that these subtypes have distinctive risk factor profiles and, by implication, diverse pathophysiologic bases. Type 2 diabetes mellitus (T2D) is associated with an increased risk of ischemic stroke, 4 but its relative contribution to different ischemic stroke subtypes is unknown. Moreover, several risk factors t...

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Adiposity as a cause of cardiovascular disease: a Mendelian randomization study

Abstract: Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke.

Cited by 131 publications

References 29 publications

The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

Causal Effect of Plasminogen Activator Inhibitor Type 1 on Coronary Heart Disease

Type 2 diabetes, glucose, insulin, BMI, and ischemic stroke subtypes

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