The Effect of Iron Status on Risk of Coronary Artery Disease

Gill, Dipender; Greco, M Fabiola Del; Walker, Ann P.; Srai, Surjit Kaila; Laffan, Michael; Minelli, Cosetta

doi:10.1161/atvbaha.117.309757

Cited by 81 publications

(81 citation statements)

References 41 publications

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“…Epidemiologic studies have shown that iron deficiency, a common cause of microcytic anemia, is associated with artificially raised A1C, although underlying mechanisms remain poorly understood ( 8 ). Our genetic findings are consistent with a previous MR study ( 29 ) and a meta-analysis of prospective studies showing an association between higher iron status and lower CAD risk ( 30 ). Three of the five genetic variants used to instrument decreased Hb and MCV reside in or near genes implicated in iron metabolism, HFE-HIST1H2A (two variants) and TMPRSS6 (one variant).…”

Section: Discussionsupporting

confidence: 92%

Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

et al. 2019

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Observational studies show that higher hemoglobin A 1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors. RESEARCH DESIGN AND METHODS To examine the association of A1C with CAD, we selected 50 A1C-associated variants (log 10 Bayes factor ‡6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and metaanalyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD. RESULTS Genetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 3 10 212). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 3 10 29) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 3 10 26) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02). CONCLUSIONS Genetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemiaindependent factors. Hemoglobin A1c (A1C) is a convenient test used to diagnose diabetes, monitor glycemic control, and assess risk of diabetes-related complications, including coronary artery disease (CAD). Epidemiologic studies have shown in people without diabetes that A1C is strongly associated with CAD risk, even after accounting for fasting glucose

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Section: Discussionsupporting

confidence: 92%

Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

et al. 2019

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“…Its effect on cT1 however remained significant even after correcting for liver iron content in sensitivity analyses, making it unlikely that the association was secondary to bias resulting from iron correction when calculating cT1. Previous Mendelian randomisation studies have shown that higher circulating iron may be cardioprotective, 61 possibly through reduced circulating LDL-cholesterol and lower blood pressure. 62 The same mechanisms may explain why the allele associated with lower circulating iron levels is associated with higher cT1.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis

Parisinos

Wilman

Thomas

et al. 2020

Journal of Hepatology

102

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Background & Aims MRI-based corrected T1 (cT1) is a non-invasive method to grade the severity of steatohepatitis and liver fibrosis. We aimed to identify genetic variants influencing liver cT1 and use genetics to understand mechanisms underlying liver fibroinflammatory disease and its link with other metabolic traits and diseases. Methods First, we performed a genome-wide association study (GWAS) in 14,440 Europeans, with liver cT1 measures, from the UK Biobank. Second, we explored the effects of the cT1 variants on liver blood tests, and a range of metabolic traits and diseases. Third, we used Mendelian randomisation to test the causal effects of 24 predominantly metabolic traits on liver cT1 measures. Results We identified 6 independent genetic variants associated with liver cT1 that reached the GWAS significance threshold ( p <5×10 -8 ). Four of the variants (rs759359281 in SLC30A10 , rs13107325 in SLC39A8 , rs58542926 in TM6SF2 , rs738409 in PNPLA3 ) were also associated with elevated aminotransferases and had variable effects on liver fat and other metabolic traits. Insulin resistance, type 2 diabetes, non-alcoholic fatty liver and body mass index were causally associated with elevated cT1, whilst favourable adiposity (instrumented by variants associated with higher adiposity but lower risk of cardiometabolic disease and lower liver fat) was found to be protective. Conclusion The association between 2 metal ion transporters and cT1 indicates an important new mechanism in steatohepatitis. Future studies are needed to determine whether interventions targeting the identified transporters might prevent liver disease in at-risk individuals. Lay summary We estimated levels of liver inflammation and scarring based on magnetic resonance imaging of 14,440 UK Biobank participants. We performed a genetic study and identified variations in 6 genes associated with levels of liver inflammation and scarring. Participants with variations in 4 of these genes also had higher levels of markers of liver cell injury in blood samples, further validating their role in liver health. Two identified genes are involved in the transport of metal ions in our body. Further investigation of these variations may lead to better detection, assessment, and/or treatment of liver inflammation and scarring.

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“…In a GWAS consisting of 48,972 individuals of European ancestry, the Genetics of Iron Status Consortium identified five single nucleotide polymorphisms (SNP) associated with serum iron and transferrin saturation, six SNPs associated with ferritin and eight SNPs associated with transferrin at the genome-wide significance threshold (p < 5 × 10 −8 ) [13] (Table 1). Among those SNPs, three SNPs (rs1800562 and rs1799945 in HFE and rs855791 in TMPRSS6) showed a robust and consistent association with a systemic iron status and explained the majority of variance for each iron status biomarker [14] and have been used as instrumental variables for iron status in previous MR studies [14][15][16]. The SNPs were uncorrelated (R 2 < 0.01) and explained 3.4%, 7.2%, 6.9% and 0.9% of the variance for serum iron, transferrin, transferrin saturation and ferritin levels, respectively [13].…”

Section: Instrumental Variable Selectionmentioning

confidence: 99%

Iron Status and Cancer Risk in UK Biobank: A Two-Sample Mendelian Randomization Study

et al. 2020

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We conducted a two-sample Mendelian randomization study to explore the associations of iron status with overall cancer and 22 site-specific cancers. Single-nucleotide polymorphisms for iron status were obtained from a genome-wide association study of 48,972 European-descent individuals. Summary-level data for breast and other cancers were obtained from the Breast Cancer Association Consortium and UK Biobank. Genetically predicted iron status was positively associated with liver cancer and inversely associated with brain cancer but not associated with overall cancer or the other 20 studied cancer sites at p < 0.05. The odds ratios of liver cancer were 2.45 (95% CI, 0.81, 7.45; p = 0.11), 2.11 (1.16, 3.83; p = 0.02), 10.89 (2.44, 48.59; p = 0.002) and 0.30 (0.17, 0.53; p = 2 × 10−5) for one standard deviation increment of serum iron, transferrin saturation, ferritin and transferrin levels, respectively. For brain cancer, the corresponding odds ratios were 0.69 (0.48, 1.00; p = 0.05), 0.75 (0.59, 0.97; p = 0.03), 0.41 (0.20, 0.88; p = 0.02) and 1.49 (1.04, 2.14; p = 0.03). Genetically high iron status was positively associated with liver cancer and inversely associated with brain cancer.

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The Effect of Iron Status on Risk of Coronary Artery Disease

Abstract: This Mendelian randomization study supports the hypothesis that higher iron status reduces CAD risk. These findings may highlight a therapeutic target.

Cited by 81 publications

References 41 publications

Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis

Iron Status and Cancer Risk in UK Biobank: A Two-Sample Mendelian Randomization Study

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