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Figure 1.
Schematic Diagram of the Mendelian Randomization Assumptions Underpinning a Mendelian Randomization Analysis of the Association Between Serum Calcium Levels and Coronary Artery Disease
Schematic Diagram of the Mendelian Randomization Assumptions Underpinning a Mendelian Randomization Analysis of the Association Between Serum Calcium Levels and Coronary Artery Disease

SNPs indicate single-nucleotide polymorphisms. The dashed lines represent potential causal associations between variables that would represent violations of the mendelian randomization assumptions. For a formal treatment of the assumptions, see Greenland.14

Figure 2.
Data Sources and Analysis Plan Using Mendelian Randomization
Data Sources and Analysis Plan Using Mendelian Randomization

BMI indicates body mass index; DIAGRAM, Diabetes Genetics Replication and Meta-analysis; GIANT, Genetic Investigation of Anthropometric Traits; GLGC, Global Lipids Genetics Consortium; ICBP, International Consortium of Blood Pressure; MAGIC, Meta-Analyses of Glucose and Insulin-related traits Consortium; SNPs, single-nucleotide polymorphisms.

aFor sample sizes of each study, see Methods.

bAny SNP with pleiotropic effects (ie, associated with more than 1 risk factor) violates the Mendelian randomization assumptions. One SNP (rs780094 in the GCKR gene region) had pleiotropic associations with cardiometabolic risk factors and was excluded, leaving 6 calcium-related SNPs for inclusion in the mendelian randomization analyses.

cThe estimates for the association of each SNP with coronary artery disease were combined using the inverse-variance weighted method, with summary statistics for coronary artery disease obtained from the CardiogramplusC4D consortium.23

Figure 3.
Mendelian Randomization Estimates of the Association Between Genetically Predicted Serum Calcium Levels and Coronary Artery Disease
Mendelian Randomization Estimates of the Association Between Genetically Predicted Serum Calcium Levels and Coronary Artery Disease

OR indicates odds ratio; SNP, single-nucleotide polymorphisms. Data markers indicate the OR for the association of each calcium-associated SNP with coronary artery disease. Size of the data marker is inversely proportional to variance of the estimate. Error bars indicate 95% CIs.

Table 1.  
Descriptive Information of the 48 Studies Included in the CardiogramplusC4D Consortium’s 1000 Genomes-Based Genome-Wide Association Meta-analysis
Descriptive Information of the 48 Studies Included in the CardiogramplusC4D Consortium’s 1000 Genomes-Based Genome-Wide Association Meta-analysis
Table 2.  
Characteristics of the Calcium-Associated Genetic Variants
Characteristics of the Calcium-Associated Genetic Variants
1.
Reid  IR, Gamble  GD, Bolland  MJ.  Circulating calcium concentrations, vascular disease and mortality: a systematic review.  J Intern Med. 2016;279(6):524-540.PubMedGoogle ScholarCrossref
2.
Rohrmann  S, Garmo  H, Malmström  H,  et al.  Association between serum calcium concentration and risk of incident and fatal cardiovascular disease in the prospective AMORIS study.  Atherosclerosis. 2016;251:85-93.PubMedGoogle ScholarCrossref
3.
Bristow  SM, Gamble  GD, Stewart  A,  et al.  Acute and 3-month effects of microcrystalline hydroxyapatite, calcium citrate and calcium carbonate on serum calcium and markers of bone turnover: a randomised controlled trial in postmenopausal women.  Br J Nutr. 2014;112(10):1611-1620.PubMedGoogle ScholarCrossref
4.
Barry  EL, Mott  LA, Melamed  ML,  et al.  Calcium supplementation increases blood creatinine concentration in a randomized controlled trial.  PLoS One. 2014;9(10):e108094.PubMedGoogle ScholarCrossref
5.
Bolland  MJ, Grey  A, Avenell  A, Gamble  GD, Reid  IR.  Calcium supplements with or without vitamin D and risk of cardiovascular events: reanalysis of the Women’s Health Initiative limited access dataset and meta-analysis.  BMJ. 2011;342:d2040.PubMedGoogle ScholarCrossref
6.
Van Hemelrijck  M, Michaelsson  K, Linseisen  J, Rohrmann  S.  Calcium intake and serum concentration in relation to risk of cardiovascular death in NHANES III.  PLoS One. 2013;8(4):e61037.PubMedGoogle ScholarCrossref
7.
Mangano  KM, Walsh  SJ, Insogna  KL, Kenny  AM, Kerstetter  JE.  Calcium intake in the United States from dietary and supplemental sources across adult age groups: new estimates from the National Health and Nutrition Examination Survey 2003-2006.  J Am Diet Assoc. 2011;111(5):687-695.PubMedGoogle ScholarCrossref
8.
An  R, Chiu  CY, Andrade  F.  Nutrient intake and use of dietary supplements among US adults with disabilities.  Disabil Health J. 2015;8(2):240-249.PubMedGoogle ScholarCrossref
9.
Dickinson  A, MacKay  D.  Health habits and other characteristics of dietary supplement users: a review.  Nutr J. 2014;13:14.PubMedGoogle ScholarCrossref
10.
Reid  IR, Bristow  SM, Bolland  MJ.  Cardiovascular complications of calcium supplements.  J Cell Biochem. 2015;116(4):494-501.PubMedGoogle ScholarCrossref
11.
Margolis  KL, Manson  JE.  Calcium supplements and cardiovascular disease risk: what do clinicians and patients need to know?  Ann Intern Med. 2016;165(12):884-885.PubMedGoogle ScholarCrossref
12.
Bauer  DC.  The calcium supplement controversy: now what?  J Bone Miner Res. 2014;29(3):531-533.PubMedGoogle ScholarCrossref
13.
Burgess  S, Thompson  SG.  Mendelian randomization: methods for using genetic variants in causal estimation. London, UK: Chapman & Hall; 2015.
14.
Greenland  S.  An introduction to instrumental variables for epidemiologists.  Int J Epidemiol. 2000;29(4):722-729.PubMedGoogle ScholarCrossref
15.
Burgess  S, Scott  RA, Timpson  NJ, Davey Smith  G, Thompson  SG; EPIC- InterAct Consortium.  Using published data in mendelian randomization: a blueprint for efficient identification of causal risk factors.  Eur J Epidemiol. 2015;30(7):543-552.PubMedGoogle ScholarCrossref
16.
O’Seaghdha  CM, Wu  H, Yang  Q,  et al; SUNLIGHT Consortium; GEFOS Consortium.  Meta-analysis of genome-wide association studies identifies six new Loci for serum calcium concentrations.  PLoS Genet. 2013;9(9):e1003796.PubMedGoogle ScholarCrossref
17.
Willer  CJ, Schmidt  EM, Sengupta  S,  et al; Global Lipids Genetics Consortium.  Discovery and refinement of loci associated with lipid levels.  Nat Genet. 2013;45(11):1274-1283.PubMedGoogle ScholarCrossref
18.
Dupuis  J, Langenberg  C, Prokopenko  I,  et al.  New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.  Nat Genet. 2010;42(2):105-116.PubMedGoogle ScholarCrossref
19.
Mahajan  A, Go  MJ, Zhang  W,  et al.  Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.  Nat Genet. 2014;46(3):234-244.PubMedGoogle ScholarCrossref
20.
Locke  AE, Kahali  B, Berndt  SI,  et al.  Genetic studies of body mass index yield new insights for obesity biology.  Nature. 2015;518(7538):197-206.PubMedGoogle ScholarCrossref
21.
Shungin  D, Winkler  TW, Croteau-Chonka  DC,  et al.  New genetic loci link adipose and insulin biology to body fat distribution.  Nature. 2015;518(7538):187-196.PubMedGoogle ScholarCrossref
22.
Ehret  GB, Munroe  PB, Rice  KM,  et al.  Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.  Nature. 2011;478(7367):103-109.PubMedGoogle ScholarCrossref
23.
Nikpay  M, Goel  A, Won  HH,  et al; CARDIoGRAMplusC4D Consortium.  A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease.  Nat Genet. 2015;47(10):1121-1130.PubMedGoogle ScholarCrossref
24.
Burgess  S, Bowden  J, Fall  T, Ingelsson  E, Thompson  SG.  Sensitivity analyses for robust causal inference from mendelian randomization analyses with multiple genetic variants.  Epidemiology. 2017;28(1):30-42.PubMedGoogle ScholarCrossref
25.
White  J, Swerdlow  DI, Preiss  D,  et al.  Association of lipid fractions with risks for coronary artery disease and diabetes.  JAMA Cardiol. 2016;1(6):692-699.PubMedGoogle ScholarCrossref
26.
van Iperen  EP, Sivapalaratnam  S, Holmes  MV, Hovingh  GK, Zwinderman  AH, Asselbergs  FW.  Genetic analysis of emerging risk factors in coronary artery disease.  Atherosclerosis. 2016;254:35-41.PubMedGoogle ScholarCrossref
27.
Hägg  S, Fall  T, Ploner  A,  et al; European Network for Genetic and Genomic Epidemiology Consortium.  Adiposity as a cause of cardiovascular disease: a mendelian randomization study.  Int J Epidemiol. 2015;44(2):578-586.PubMedGoogle ScholarCrossref
28.
Bristow  SM, Gamble  GD, Pasch  A,  et al.  Acute and 3-month effects of calcium carbonate on the calcification propensity of serum and regulators of vascular calcification: secondary analysis of a randomized controlled trial.  Osteoporos Int. 2016;27(3):1209-1216.PubMedGoogle ScholarCrossref
29.
Bristow  SM, Gamble  GD, Stewart  A, Kalluru  R, Horne  AM, Reid  IR.  Acute effects of calcium citrate with or without a meal, calcium-fortified juice and a dairy product meal on serum calcium and phosphate: a randomised cross-over trial.  Br J Nutr. 2015;113(10):1585-1594.PubMedGoogle ScholarCrossref
30.
Anderson  JJ, Kruszka  B, Delaney  JA,  et al.  Calcium intake from diet and supplements and the risk of coronary artery calcification and its progression among older adults: 10-year follow-up of the Multi-Ethnic Study of Atherosclerosis (MESA).  J Am Heart Assoc. 2016;5(10):e003815.PubMedGoogle ScholarCrossref
31.
Li  K, Kaaks  R, Linseisen  J, Rohrmann  S.  Associations of dietary calcium intake and calcium supplementation with myocardial infarction and stroke risk and overall cardiovascular mortality in the Heidelberg cohort of the European Prospective Investigation into Cancer and Nutrition study (EPIC-Heidelberg).  Heart. 2012;98(12):920-925.PubMedGoogle ScholarCrossref
32.
Xiao  Q, Murphy  RA, Houston  DK, Harris  TB, Chow  WH, Park  Y.  Dietary and supplemental calcium intake and cardiovascular disease mortality: the National Institutes of Health-AARP diet and health study.  JAMA Intern Med. 2013;173(8):639-646.PubMedGoogle ScholarCrossref
33.
Burgess  S, Davies  NM, Thompson  SG.  Bias due to participant overlap in two-sample mendelian randomization.  Genet Epidemiol. 2016;40(7):597-608.PubMedGoogle ScholarCrossref
34.
Kapur  K, Johnson  T, Beckmann  ND,  et al.  Genome-wide meta-analysis for serum calcium identifies significantly associated SNPs near the calcium-sensing receptor (CASR) gene.  PLoS Genet. 2010;6(7):e1001035.PubMedGoogle ScholarCrossref
Original Investigation
July 25, 2017

Association of Genetic Variants Related to Serum Calcium Levels With Coronary Artery Disease and Myocardial Infarction

Author Affiliations
  • 1Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
  • 2MRC Biostatistics Unit, University of Cambridge, United Kingdom
  • 3Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
  • 4Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
JAMA. 2017;318(4):371-380. doi:10.1001/jama.2017.8981
Key Points

Question  Are genetically elevated serum calcium levels associated with an increased risk of coronary artery disease or myocardial infarction?

Findings  In this mendelian randomization study including 60 801 cases of coronary artery disease and 123 504 noncases, genetically elevated serum calcium levels were associated with increased odds of coronary artery disease and myocardial infarction (odds ratio per 0.5-mg/dL increase in genetically predicted serum calcium levels, 1.25 and 1.24, respectively).

Meaning  A genetic predisposition to higher serum calcium levels was associated with increased risk of coronary artery disease and myocardial infarction.

Abstract

Importance  Serum calcium has been associated with cardiovascular disease in observational studies and evidence from randomized clinical trials indicates that calcium supplementation, which raises serum calcium levels, may increase the risk of cardiovascular events, particularly myocardial infarction.

Objective  To evaluate the potential causal association between genetic variants related to elevated serum calcium levels and risk of coronary artery disease (CAD) and myocardial infarction using mendelian randomization.

Design, Setting, and Participants  The analyses were performed using summary statistics obtained for single-nucleotide polymorphisms (SNPs) identified from a genome-wide association meta-analysis of serum calcium levels (N = up to 61 079 individuals) and from the Coronary Artery Disease Genome-wide Replication and Meta-analysis Plus the Coronary Artery Disease Genetics (CardiogramplusC4D) consortium’s 1000 genomes-based genome-wide association meta-analysis (N = up to 184 305 individuals) that included cases (individuals with CAD and myocardial infarction) and noncases, with baseline data collected from 1948 and populations derived from across the globe. The association of each SNP with CAD and myocardial infarction was weighted by its association with serum calcium, and estimates were combined using an inverse-variance weighted meta-analysis.

Exposures  Genetic risk score based on genetic variants related to elevated serum calcium levels.

Main Outcomes and Measures  Co-primary outcomes were the odds of CAD and myocardial infarction.

Results  Among the mendelian randomized analytic sample of 184 305 individuals (60 801 CAD cases [approximately 70% with myocardial infarction] and 123 504 noncases), the 6 SNPs related to serum calcium levels and without pleiotropic associations with potential confounders were estimated to explain about 0.8% of the variation in serum calcium levels. In the inverse-variance weighted meta-analysis (combining the estimates of the 6 SNPs), the odds ratios per 0.5-mg/dL increase (about 1 SD) in genetically predicted serum calcium levels were 1.25 (95% CI, 1.08-1.45; P = .003) for CAD and 1.24 (95% CI, 1.05-1.46; P = .009) for myocardial infarction.

Conclusions and Relevance  A genetic predisposition to higher serum calcium levels was associated with increased risk of CAD and myocardial infarction. Whether the risk of CAD associated with lifelong genetic exposure to increased serum calcium levels can be translated to a risk associated with short-term to medium-term calcium supplementation is unknown.

Introduction

Calcium has a vital role in many biological processes in the body such as nerve transmission, blood clotting, blood pressure regulation, enzyme activation, hormone regulation, and muscle contraction. Observational studies have suggested that serum calcium levels are positively associated with risk of cardiovascular disease, including myocardial infarction.1,2 Moreover, evidence from randomized clinical trials indicates that calcium supplementation, which results in an acute and sustained elevation in serum calcium,3,4 may modestly increase the risk of cardiovascular events, particularly myocardial infarction.5

However, it remains unclear whether lifelong elevated serum calcium may be causally associated with coronary artery disease (CAD) risk. Nationally representative data show that one-fifth of US adults use calcium supplements,6 and the proportion is even higher among middle-aged and older women and individuals with disabilities, with more than half of this group being regular calcium supplement users.7-9 Because of the widespread use of calcium supplements, any association between raised serum calcium and CAD risk by a high calcium intake could have clinical and public health implications. The findings of an elevated risk of cardiovascular events with calcium supplement use5 have been debated in recent years without consensus being reached.10-12

Genetic variants that have a specific influence on possible risk factors can be used to assess associations with explicit outcomes.13 This method, known as mendelian randomization, avoids some of the limitations of observational studies (because genetic information should be free from confounding) and is not affected by disease status, thereby avoiding reverse causation bias.13 Hence, genetic variants that influence serum calcium levels could serve as instrumental variables (proxies) to determine the association of lifelong elevated serum calcium with CAD risk. We conducted a mendelian randomization study to investigate the association of serum calcium with CAD and myocardial infarction.

Methods
Study Design and Data Sources

The mendelian randomization approach builds upon 3 principal assumptions (Figure 1).15 First, the genetic variants utilized as instrumental variables should be associated with the risk factor. Second, the genetic variants should not be associated with confounders. Third, the genetic variants should affect the risk of the outcome through the risk factor, not via other pathways.

This study involved analysis of publicly available, deidentified data; specific ethical review and informed consent had been obtained in all of the original studies. This mendelian randomization study was designed to use summary statistics from large-scale genome-wide association studies (GWAS) (Figure 2). GWAS identified 7 single-nucleotide polymorphisms (SNPs) associated with serum calcium levels in a meta-analysis of 39 400 individuals of European ancestry and which were replicated in up to 21 679 additional individuals (up to 61 079 individuals).16 These 7 SNPs were associated with serum calcium levels at genome-wide significance level ([P < 5.0] × 10−8) in the meta-analysis of the discovery and replication cohorts.16 All the SNPs were in different gene regions and were distributed independently, not in linkage disequilibrium.

Among the GWAS, each calcium-associated SNP was evaluated for pleiotropic associations with potential confounders, including major lipids in up to 188 577 individuals (Global Lipids Genetics Consortium)17; glycemic traits in up to 46 186 individuals without diabetes (Meta-Analyses of Glucose and Insulin-Related Traits Consortium)18; type 2 diabetes in up to 110 452 individuals (Diabetics Genetics Replication and Meta-analysis)19; body mass index (BMI) in up to 339 224 individuals20 and waist-to-hip ratio adjusted for BMI in up to 224 459 individuals21 (Genetic Investigation of Anthropometric Traits); and systolic and diastolic blood pressure in up to 69 395 individuals (International Consortium for Blood Pressure)22 (Figure 2). Of the 7 SNPs associated with serum calcium, 1 variant (rs780094 in the GCKR gene region) had pleiotropic associations at the Bonferroni-corrected significance threshold ([P < .05]/7 SNPs = .007) with lipids, glycemic traits, type 2 diabetes, and measures of adiposity (eTable in the Supplement). To avoid violations of the mendelian randomization assumptions (Figure 1), the pleiotropic SNP was omitted. Thus, 6 SNPs associated with serum calcium were used as instrumental variables in the mendelian randomization analyses.

Summary statistics for the associations of the 6 remaining calcium-associated SNPs with the prespecified primary outcomes of CAD and myocardial infarction were extracted from the Coronary Artery Disease Genome-Wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics (CardiogramplusC4D) consortium’s 1000 genomes-based genome-wide association meta-analysis of 48 studies.23 Case status was determined using a broad definition of CAD, including myocardial infarction (approximately 70% of the total number of cases), acute coronary syndrome, chronic stable angina, or coronary artery stenosis greater than 50% (Table 1).23

Statistical Analysis

SNPs were matched across the data sources by assigning them to the same effect allele. The association of each SNP with CAD and myocardial infarction was weighted by its association with serum calcium, and estimates were combined using an inverse-variance weighted meta-analysis.24 Complementary analyses using the weighted median and MR-Egger regression methods were performed.24 The odds ratios (ORs) of CAD and myocardial infarction were scaled per 0.5-mg/dL increase (about 1 SD) in serum calcium levels. For the calcium-associated SNPs, the summary statistics were based on 44 to all 48 studies included in the CardiogramplusC4D consortium. All statistical tests were 2-sided. The threshold of statistical significance for the analyses of 6 SNPs by Bonferroni correction was P < .008 ([P < .05]/6 SNPs); statistical tests for the mendelian randomization analyses of CAD and myocardial infarction were considered statistically significant at P < .025 ([P < .05]/2 outcome measures). All analyses were conducted in Stata (StataCorp), version 14.2, and R (R Foundation), version 3.2.5.

Results

The analytic sample included up to 60 801 CAD cases (approximately 70% with myocardial infarction) and 123 504 noncases from 48 cohort and case-control studies. The majority of participants were of European (77%), South Asian (13%), and East Asian (6%) ancestry (Table 1).

The 6 SNPs related to serum calcium levels and without pleiotropic associations with potential confounders were estimated to explain about 0.8% of the variation in serum calcium levels. None of the individual 6 SNPs was associated with CAD at Bonferroni corrected significance level (P < .008) (Table 2). In the overall inverse-variance weighted meta-analysis of the 6 SNPs, the OR of CAD per 0.5-mg/dL increase (about 1 SD) in genetically predicted serum calcium was 1.25 (95% CI, 1.08-1.45; P = .003) (Figure 3). In a sensitivity analysis excluding the SNP in the CASR gene, which provided the most weight to the overall estimate, the OR of CAD was 1.25 (95% CI, 0.97-1.62). An analysis of patients with only myocardial infarction as the outcome (about 70% of all study cases) yielded similar results (OR, 1.24 [95% CI, 1.05-1.46]; P = .009) (eFigure in the Supplement).

The association between genetically predicted serum calcium levels and CAD was consistent in complementary analyses using the weighted median method (OR, 1.25 [95% CI, 1.06-1.48]) and MR-Egger regression, although with a wider CI (OR, 1.26 [95% CI, 0.96-1.63]). There was no evidence of pleiotropy (MR-Egger intercept, −0.00035; P = .96), or heterogeneity between the mendelian randomization estimates from different SNPs (I2 = 0%, P = .78 for heterogeneity).

Discussion

This mendelian randomization study showed that a genetic predisposition to higher serum calcium levels was associated with increased risk of CAD and myocardial infarction. The OR per 0.5-mg/dL increase (about 1 SD) in serum calcium levels was 1.25 for CAD and 1.24 for myocardial infarction. The risk increase is similar or weaker in magnitude to previously reported genetic associations (per 1-SD increase) with triglyceride levels (OR, 1.28),25 low-density lipoprotein cholesterol levels (OR, 1.68),25 systolic and diastolic blood pressure (OR, 1.49),26 and body mass index (OR, 1.40).27

The finding from this study corroborates results from several observational studies showing a positive association of serum calcium levels with risk of cardiovascular disease.1,2 A meta-analysis of 8 observational studies found a hazard ratio of cardiovascular disease of 1.08 (95% CI, 1.04-1.13) per 1-SD increment of serum calcium levels and a corresponding OR of 1.22 (95% CI, 1.11-1.32) in 2 studies that reported ORs.1

Data from randomized clinical trials indicate that calcium supplementation leads to hypercalcemia3,4 and increased transition of soluble calcium-related protein particles to insoluble calciprotein particles reflecting higher concentrations of activators of calcification present in serum,28 as well as an increased risk of myocardial infarction.5 Based on results from interventions, there is a peak in ionized and total serum calcium levels 4 hours after ingestion of 1000-mg supplemental calcium and the increase in total serum calcium corresponds to about 1 SD.3

A similar increase in serum calcium from baseline over 6 hours is observed following the ingestion of a 500-mg calcium supplement, whereas the increase in serum calcium after a corresponding calcium dose by a dairy product intake is less pronounced.29 In a meta-analysis of 9 randomized clinical trials, calcium supplementation with or without vitamin D increased the risk of myocardial infarction by 24%,5 but the result is disputed.10-12

Findings from observational studies further show that calcium supplement use is associated with increased risk of incident coronary artery calcification,30 incident myocardial infarction,31 and coronary heart disease mortality.32 Possible mechanisms whereby elevated serum calcium levels may increase the risk of CAD include effects on vascular calcification, vascular cells, blood coagulation, and altered gene expression induced by effects on arterial wall calcium-sensing receptor.10 The potential mechanisms underlying the association need to be more thoroughly evaluated.

Strengths of this mendelian randomization analysis include the large sample size and the use of multiple uncorrelated SNPs associated with serum calcium levels, which increases the precision of the estimate.

Limitations

This study has several limitations. First, the genetic variant in the CASR gene provided more weight, explained by the stronger relation between this SNP and serum calcium, than the other variants to the overall estimate of the genetic association between serum calcium levels and CAD. However, 4 of the other 5 variants associated with serum calcium had positive estimates for association with CAD, and 3 variants had higher ORs for association with CAD per 0.5 mg/dL increase in serum calcium compared with the genetic variant in the CASR gene. Moreover, the overall estimate was identical although with lower precision after omitting the variant in CASR. CASR encodes the calcium-sensing receptor, which plays a key role in calcium homeostasis.

Second, there was partial overlap between studies included in the GWAS meta-analysis of calcium (N = 61 069) and the CardiogramplusC4D consortium (N = 184 305). This could result in model overfitting if the SNP-calcium associations were estimated in studies that were included in the CardiogramplusC4D consortium. Of the 28 studies included in the GWAS meta-analysis of calcium, 9 were also included in CardiogramplusC4D. If all the individuals in each of these studies appeared in both meta-analyses, then there would be an overlap of 26 776 of the 61 069 individuals in the calcium GWAS meta-analysis. This could potentially lead to a small bias in mendelian randomization estimates. However, if genetic associations with serum calcium levels were estimated in noncases only (as is usual for continuous phenotypes such as serum calcium levels), then this sample overlap would not lead to bias or type 1 error inflation.33

Third, the study lacked complete information on sex and age, and that a potential nonlinear association between serum calcium levels and CAD could not be evaluated.

Fourth, a replication data set with a similar large number of CAD cases was not available.

The reliability of the findings from a mendelian randomization study depends on 3 key assumptions (Figure 1), which could be violated by population stratification, canalization, pleiotropy, and linkage disequilibrium. It cannot be completely ruled out that population stratification may have had some influence on the results because the CardiogramplusC4D consortium included individuals of different ancestry with potentially different allele frequencies. However, analyses for the CardiogramplusC4D consortium were conducted separately in each study and then combined, and adjustment was made for genetic principal components, mitigating the potential effect of population stratification.

Furthermore, the vast majority of participants in CardiogramplusC4D were of European descent and the effect allele frequencies of the 6 calcium-associated SNPs were very similar in CardiogramplusC4D and the GWAS meta-analysis of calcium. The SNP in the CASR gene has been consistently associated with serum calcium in populations of different ancestry, including Europeans, Indian Asians, and Japanese.16,34 The other 5 SNPs were robustly associated with serum calcium in a GWAS meta-analysis of about 61 000 individuals.16

Whether canalization, which is defined as compensatory feedback mechanisms, may have affected the results could not be directly tested. Because canalization assumes that there are other mechanisms that mitigate the genetic effect, such feedback mechanisms would bias the results toward the null and cannot explain the observed association.

Several approaches were undertaken to assess and adjust for potential confounding or pleiotropic effects. First, each SNP associated with serum calcium was assessed for associations with known cardiometabolic risk factors for CAD, and 1 SNP with pleiotropic associations was excluded. In addition, sensitivity analyses using the weighted median and MR-Egger regression approaches to explore and adjust for pleiotropy were conducted. The results were consistent in these analyses, indicating that confounding is unlikely to explain the observed association. Linkage disequilibrium with directly causal variants (violating the third assumption) was likely avoided owing to the use of multiple SNPs of which most were positively associated with CAD.

Conclusions

A genetic predisposition to higher serum calcium levels was associated with increased risk of CAD and myocardial infarction. Whether the risk of CAD associated with lifelong genetic exposure to increased serum calcium levels can be translated to a risk associated with short-term to medium-term calcium supplementation is unknown.

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Article Information

Corresponding Author: Susanna C. Larsson, PhD, Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, SE-17177 Stockholm, Sweden (susanna.larsson@ki.se).

Accepted for Publication: June 23, 2017.

Author Contributions: Dr Larsson had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Larsson.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Larsson, Burgess.

Critical revision of the manuscript for important intellectual content: Larsson, Michaëlsson.

Statistical analysis: Larsson, Burgess.

Obtained funding: Larsson.

Administrative, technical, or material support: Larsson.

Supervision: Larsson, Michaëlsson.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This work was supported by a Junior Researcher Award grant from the Strategic Research Area in Epidemiology at Karolinska Institutet (Dr Larsson).

Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Data on genetic associations with coronary artery disease and myocardial infarction have been contributed by CardiogramplusC4D investigators and have been downloaded from http://www.cardiogramplusc4d.org.

References
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3.
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4.
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Bolland  MJ, Grey  A, Avenell  A, Gamble  GD, Reid  IR.  Calcium supplements with or without vitamin D and risk of cardiovascular events: reanalysis of the Women’s Health Initiative limited access dataset and meta-analysis.  BMJ. 2011;342:d2040.PubMedGoogle ScholarCrossref
6.
Van Hemelrijck  M, Michaelsson  K, Linseisen  J, Rohrmann  S.  Calcium intake and serum concentration in relation to risk of cardiovascular death in NHANES III.  PLoS One. 2013;8(4):e61037.PubMedGoogle ScholarCrossref
7.
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