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. Author manuscript; available in PMC: 2015 Apr 1.
Published in final edited form as: Circ Cardiovasc Genet. 2014 Feb 21;7(2):144–150. doi: 10.1161/CIRCGENETICS.113.000271

A Novel Genetic Approach to Investigate the Role of Plasma Secretory Phospholipase A2 (sPLA2)-V Isoenzyme in Coronary Heart Disease: A Modified Mendelian Randomization Analysis Using PLA2G5 Expression Levels

Michael V Holmes 1,2, Holly J Exeter 3, Lasse Folkersen 4, Christopher P Nelson 5,6, Montse Guardiola 3,7, Jackie A Cooper 3, Reecha Sofat 8, S Matthijs Boekholdt 9, Kay-Tee-Khaw 10, Ka-Wah Li 3, Andrew J P Smith 3, Ferdinand van’t Hooft 11,12; CARDIoGRAM*, Per Eriksson 11,12, Anders Franco-Cereceda 13, Folkert W Asselbergs 14,15,16, Jolanda M A Boer 17, N Charlotte Onland-Moret 15,18, Marten Hofker 19, Jeanette Erdmann 20, Mika Kivimaki 2, Meena Kumari 2, Alex P Reiner 21, Brendan J Keating 1,22, Steve E Humphries 3, Aroon D Hingorani 2, Ziad Mallat 23, Nilesh J Samani 5,6, Philippa J Talmud 3
PMCID: PMC4212409  NIHMSID: NIHMS570284  PMID: 24563418

Abstract

Background

Secretory phospholipase A2 (sPLA2) enzymes are considered to play a role in atherosclerosis. sPLA2 activity encompasses several sPLA2 isoenzymes, including sPLA2-V. While observational studies show strong association between elevated sPLA2 activity and CHD, no assay to measure sPLA2-V levels exists and the only evidence linking the sPLA2-V isoform to atherosclerosis progression comes from animal studies. In the absence of an assay that directly quantifies sPLA2-V levels, we used PLA2G5 mRNA levels in a novel, modified Mendelian randomization approach to investigate the hypothesized causal role of sPLA2-V in coronary heart disease (CHD) pathogenesis.

Methods and Results

Using data from the Advanced Study of Aortic Pathology, we identified the single nucleotide polymorphism (SNP) in PLA2G5 showing strongest association with PLA2G5 mRNA expression levels, as a proxy for sPLA2-V levels. We tested the association of this SNP with sPLA2 activity and CHD events in four prospective and 14 case-control studies with 27,230 events and 70,500 controls. rs525380C>A showed the strongest association with PLA2G5 mRNA expression (P=5.1×10−6). There was no association of rs525380C>A with plasma sPLA2 activity (difference in geometric mean of sPLA2 activity per rs525380 A-allele 0.4% (95%CI: −0.9%, 1.6%), P=0.56). In meta-analyses, the odds ratio for CHD per A allele was 1.02 (95% CI: 0.99, 1.04; P=0.20).

Conclusions

This novel approach for SNP selection for this modified Mendelian randomization analysis showed no association between rs525380 (the lead SNP for PLA2G5 expression, a surrogate for sPLA2-V levels) and CHD events. The evidence does not support a causal role for sPLA2-V in CHD.

Keywords: Mendelian randomization, cardiovascular disease risk factors, DNA polymorphisms, GATA2, sPLA2-V, PLA2G5

The secretory phospholipases (sPLA2s) are a family of enzymes that hydrolyse phospholipids on lipoprotein particles, initially in the plasma, leading to the modification of low density lipoproteins (LDL) to small, dense, pro-atherogenic LDL particles that can transcytose the endothelial layer of the arterial wall.1 Further modification of these intimal apolipoprotein B (apo B)-containing lipoproteins2, by sPLA2s in the arterial wall, leads to their accumulation and retention on the proteoglycans within the intima, a pro-atherosclerotic process.3 Additionally, by hydrolysing lipoprotein phospholipids, sPLA2s generate lysophospholipid and non-esterified free fatty acids (NEFAs), such as arachidonic acid, a precursor of eicosanoids and leukotreines4,5 that are pro-inflammatory cytokines.

Three sPLA2 isoenzymes have been identified in human atherosclerotic lesions: sPLA2-IIa, sPLA2-V and sPLA2-X.3 It is thought that sPLA2-V may contribute to the quantitative trait “sPLA2 activity”, a composite measure of sPLA2-IIa, -V and –X,6 although there is no direct biological proof for this. There is converging evidence from both the prospective EPIC-Norfolk study,6 and GRACE,7 a study of patients with acute coronary syndrome[15], that sPLA2 activity shows stronger association with cardiovascular risk than sPLA2-IIa levels alone. This provides some indirect evidence that sPLA2 activity might encompass more than just sPLA2-IIa and this identifies sPLA2-V as a potential contributor to CHD risk in humans. While a large body of observational studies support the relationship between higher sPLA2-IIa levels and risk of CHD in humans,7–11 no such studies exist for sPLA2-V. A specific ELISA assay exists that enables the quantification of sPLA2-IIa levels, but there is currently no assay to specifically measure sPLA2-V levels. Despite the lack of observational studies in man for sPLA2-V, animal studies report a pro-atherogenic role for sPLA2-V as well as -IIa, showing increased susceptibility to atherosclerosis in sPLA2-V (Pla2g5)12,13 and sPLA2-IIa (Pla2g2a) transgenic mice.14,15 Studies of human tissue also indicate that sPLA2-V is expressed in human endothelial cells, macrophages and lipid-loaded macrophages.16 Suggested mechanisms by which sPLA2-V is thought to increase risk of CHD include increasing the entrapment of LDL in the atherosclerotic plaque, and modification of LDL to encourage generation of foam cells.16

The specific catalytic dyad found in sPLA2 enzymes 17 makes them suitable drug targets, and indeed a sPLA2 inhibitor has been developed. The drug varespladib, with a primary target of sPLA2-IIa, also inhibits sPLA2-V.18 However, since the exact contribution of sPLA2-V to plasma sPLA2 activity is unknown, this provides a challenge for inferring the nature of the relationship between sPLA2-V and CHD events.

Genetics provides a powerful tool to examine whether a relationship between a biomarker and a disease outcome is likely to be causal. This process, called Mendelian randomization (MR), makes use of a genetic variant that associates with the biomarker of interest as a means to investigate whether the biomarker is causally related to disease.19 There are three steps in traditional MR analysis, often referred to as MR triangulation. The first side of the triangle usually is the starting point of the analysis and arises from observational studies which report the association of the biomarker with CHD, in this case it would be sPLA2-V levels. However, in the absence of measures of plasma sPLA2-V levels, observational studies report the association of elevated levels of the composite measure of sPLA2 activity with CHD risk.6,7 The second side of the MR triangle validates the association of the genetic variant with the biomarker of interest. In this modified MR study, the absence of a specific assay to quantify sPLA2-V levels motivated us to pursue a novel approach that exploited the availability of vascular tissue mRNA expression of PLA2G5 (the gene encoding sPLA2-V) as a proxy for sPLA2-V levels and for this we identified a common PLA2G5 gene variant most strongly associated with PLA2G5 mRNA expression. We feel this novel approach is justified as a recent study we conducted for sPLA2-IIa found that the SNP showing strongest association with PLA2G2A mRNA was in very strong linkage disequilibrium with the SNP that showed strongest association with sPLA2-IIa (a specific assay for sPLA2-IIa).20 Finally, to validate if the biomarker is causal or not, the MR triangle is completed by examining the association of the PLA2G5 variant with CHD risk and comparing this value to the observational estimate for a similar difference in biomarker.

Methods

SNP selection for Mendelian randomization using mRNA expression

We searched publicly available eQTL data sets to identify SNPs in PLA2G5 associated with eQTL effects at genome-wide significance in circulating cells in blood.21–24 This did not identify any associations and we therefore focused on mRNA expression in tissue samples in our own dataset. We used the Advanced Study of Aortic Pathology (ASAP) (n=272) as a source of PLA2G5 mRNA expression. Individuals undergoing valve surgery had tissue biobanked from liver (n=212), mammary artery intima-media (n=89), ascending aorta intima-media (n=138), aorta adventitia (n=133) and heart (n=127), and subsequently mRNA levels extracted. mRNA levels were quantified using Affymetrix Gene Chip Human Exon 1.0 ST expression arrays and DNA was genotyped using Illumina Human 610W-Quad Bead array.25 We investigated the association between SNPs in and within 200kb of the PLA2G5 gene with mRNA expression of PLA2G5 and selected the SNP that showed strongest differential association with PLA2G5 expression levels. SNPs with a call rate <80% or Hardy-Weinberg Chi-square statistic >3.84 were excluded. The overall call rate per SNP was 99.84%. 12 samples were genotyped in duplicate and the concordance was 99.99%. The rs525380 SNP was in Hardy-Weinberg equilibrium (P=0.54) and had a call rate of 100%.

Association of the gene variant with non-index mRNA expression and sPLA2 activity

In order to investigate the specificity of our genetic variant, we examined the relationship between the SNP with mRNA levels of PLA2G2A and PLA2G10. To gauge insight into the relative contribution of sPLA2-V to sPLA2 activity, we investigated the per-allele association of the SNP with sPLA2 activity in EPIC-Norfolk (measured by a selective fluorometric assay).7

Genotyping of rs525380

The lead SNP in the analysis, rs525380, was present on various GWAs platforms used by the CARDioGRAM studies.26 For EPIC-Netherlands, Whitehall II and Women’s Health Initiative, genotyping was carried out using the IBC CardioChip array (Illumina HumanCVD).27 For the remaining study (EPIC-Norfolk), the rs525380 SNP was genotyped using TaqMan technology (Applied Biosciences, ABI, Warrington UK) (Supplementary Table 1). In each study, rs525380 was in Hardy Weinberg equilibrium with call rates >97%.

Association of the gene variant with LDL-C levels

We previously reported an association of PLA2G5 SNPs with LDL-cholesterol levels in a small study of patients with type 2 diabetes.28 To investigate whether LDL-C may represent a mediator between sPLA2-V and CHD, we looked up the association of rs525380 in a recent large gene-centric analysis of 32 studies including 66,240 individuals of European ancestry.29

Association of the gene variant with CHD events

Data from 18 studies were used in the analysis of the association between the PLA2G5 lead SNP and CHD risk, comprising three nested case-control studies (Women’s Health Initiative,30 EPIC-Norfolk8 and EPIC-Netherlands31), one prospective cohort (Whitehall II32) and 14 case-control studies (participants in the CARDIoGRAM GWA meta-analysis of coronary artery disease (CAD)). 26 All studies were approved by their institutional review committees and subjects gave informed consent.

These studies are described in Supplementary Table 1 and the details of the CARDIoGRAM consortium in Supplementary Table 2.

Statistical Analysis

All gene expression values were log2 transformed prior to analysis as part of the microarray preprocessing algorithm. Association strength between genotype and gene expression levels were calculated using a linear regression model with the gene expression as response variable and the genotype recoded numerically (as 0, 1, and 2) as the explanatory variable. A Bonferroni-adjusted P-value threshold of P< 8.4×10−5 was taken as the level of significance for the association of SNPs with mRNA expression. The mRNA analysis was conducted using R 2.13.0 and Bioconductor.

sPLA2 activity was log(e) transformed prior to analysis due to a skewed distribution. We used an additive model for the genetic association analysis of rs525380 with sPLA2 activity and CHD events. The univariate per-minor A allele estimates for the rs525380 variant with sPLA2 activity and CHD events were estimated using linear and logistic regression, respectively. Study-level estimates (beta coefficients or log odds with their respective standard errors) were pooled using fixed-effects (inverse variance) meta-analysis and heterogeneity was quantified using the I2 statistic. For the association of rs525380 with sPLA2 activity, summary estimates were exponentiated and converted into a percentage difference in the geometric mean. All analyses, unless otherwise stated, were performed using Stata 12.1 (StataCorp, College Station, Texas USA).

Results

Identification of the SNP showing strongest the association with PLA2G5 expression

The SNP showing strongest association with PLA2G5 mRNA expression was rs525380 at P=5.1×10−6 (n=272, Figure 1), which surpassed our Bonferroni-adjusted P-value threshold. PLA2G5 was most highly expressed in the heart (Figure 2) where it was amongst the top 11% most highly expressed genes and in the top 50% of expression in other investigated tissues (mammary artery, liver, aorta media and adventitia). The rs525380C>A was associated with the strongest differential mRNA expression of PLA2G5 in the aortic adventitia explaining 14.5% of the PLA2G5 mRNA variance (n=133, Figure 2, Supplementary Figure 1); the rare A allele was associated with 37.6% higher mRNA levels than the common C allele. Associations of rs525380 with PLA2G5 mRNA expression were also identified in the aortic media and mammary artery (P<0.001) (Figure 2). The regional plot for rs525380, showing the linkage disequilibrium (LD) with SNPs in the vicinity, is presented in Supplementary Figure 1. This plot shows that the LD falls off around the lead SNP, rs525380 in PLA2G5 and shows very little LD with PLA2G2A SNPs, with R2 ≤ 0.2.

Figure 1. Manhattan plot of the association between SNPs in the PLA2G5 region and PLA2G5 mRNA expression by tissue type.

Figure 1

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rs525380 A>C showed the strongest association with PLA2G5 mRNA expression in the aorta adventitia (P=5.05×10−6). The black horizontal line above the scale represents the position of PLA2G5. Total number of individuals providing tissue samples for analysis = 272 (samples available for each tissue: Mammary Artery 89, Liver 212, Aorta Med 138, Aorta Adventitia 133, Heart 127).

Figure 2. Overall expression of all probe-sets and the differential expression of PLA2G5.

Figure 2

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rs525380 C>A with PLA2G5 mRNA in the five tissue types. MMed: Mammary artery intima-media; AMed: dilated and non-dilated ascending aorta intima-media; Aorta ADV: aorta adventitia. For CC/AC/AA the sample sizes are as follows: heart 43/68/16, MMed 21/51/17, AMed 44/70/24, Aorta ADV 38/73/22, Liver 59/120/32.

Bioinformatic analysis of rs525380

rs525380 is located ~12.5 kb downstream of the PLA2G5 transcription start site within a potential enhancer motif, experimentally determined by DNaseI-seq and FAIRE-seq open chromatin marks (liver and vascular cells), and by ChIP-seq for the transcription factor GATA-2 (UCSC Genome Browser GRCh37/hg19)33 (Supplementary Figure 2), suggesting rs525380 may be functional, potentially playing a distal regulatory role and altering PLA2G5 expression.

Association of PLA2G5 SNPs with PLA2G2A and PLA2G10 mRNA expression levels and sPLA2 activity

We next examined the association of PLA2G5 rs525380 with PLA2G2A (lying head to tail with PLA2G5 on chr1) and PLA2G10 (chr10) mRNA expression levels. We did not observe an association of rs525380 and PLA2G2A mRNA expression in vascular tissues, but we did identify an association of rs525380 with liver PLA2G2A mRNA expression (n=212, p=0.001, Supplementary Figure 3). rs525380 showed no association with PLA2G10 mRNA expression in any tissue (P>0.05 for all associations).

There was no association between the A allele of rs525380 and plasma sPLA2 activity (n=3095, 0.4% difference in geometric mean per A-allele of rs525380; 95% CI: −0.9%, 1.6%; P=0.56).

Association of rs525380 with LDL-cholesterol levels

A look-up in a large meta-analysis across 32 studies29 yielded a pooled per-A allele estimate of 0.002 mmol/l (95%CI: −0.008, 0.012) difference in LDL-C in 66,240 individuals (P=0.71), thus showing no association between rs525380 and LDL-C levels.

Association of rs525380 with CHD events

The pooled estimate of the association of rs525380 with CHD events in meta-analysis of 18 studies with 27,230 CHD events in 97,730 individuals did not identify any evidence of association. The per-A-allele estimate was OR 1.02 (95%CI: 0.99, 1.04), and the heterogeneity was low (I2=0%; 95%CI: 0%, 48%) (Figure 3). When we restricted the analysis to only large studies with >1000 CHD events (11 studies with 22,757 cases in 85,494 individuals), the estimate remained unchanged (OR 1.01; 95%CI: 0.99, 1.04).

Figure 3. Forest plot of the association of PLA2G5 rs525380 (per A-allele) with CHD in 27,230 cases in a total of 97,730 individuals.

Figure 3

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When limited to studies with fewer than 1000 CHD events, the OR was 1.04 (95%CI: 0.97, 1.11) with an I2 of 31% (95%CI: 0% to 71%). For studies with more than 1000 CHD events, the OR was 1.01 (95%CI: 0.99, 1.04) with an I2 of 0% (95%CI: 0% to 43%).

Discussion

We conducted a modified Mendelian randomization analysis to evaluate whether the relationship between sPLA2-V and CHD events is likely to be causal. In the absence of a suitable assay to directly quantify sPLA2-V levels, we took the novel approach of using vascular mRNA expression levels of the gene encoding sPLA2-V, PLA2G5, as a proxy measure. We found PLA2G5 to be highly expressed in all available tissues, being amongst the top 11% genes expressed in the heart and in the top 50% of expression in other investigated tissues. We identified a SNP that surpassed the pre-defined Bonferroni-adjusted P-value threshold for association with PLA2G2A mRNA expression, explaining 14% of the variance in PLA2G5 mRNA levels. We took this genetic variant forward to investigate the association with CHD in a large collection of studies. In analysis of 27,230 CHD events across 97,730 total individuals, the SNP was not associated with CHD, suggesting that sPLA2-V may not be causally involved in CHD pathogenesis.

We recently used a similar technique for SNP selection when we investigated the role of sPLA2-IIa in CHD.20 In the case of sPLA2-IIa, we did have access to a trait that directly quantified circulating levels of sPLA2-IIa. We showed that the SNP showing strongest association with circulating sPLA2-IIa levels was in very high linkage disequilibrium with the SNP showing strongest association with PLA2G2A mRNA expression. This serves to justify the method we used here: that is we assume that if we could quantify circulating sPLA2-V levels, we would find that the SNP that showed strongest association with sPLA2-V levels would also show strongest association with PLA2G5 mRNA expression.

mRNA expression is considered a good proxy for its encoded protein, although it might only reflect a proportion of protein expression, since post transcriptional and post translational modifications may further influence protein levels.34 Thus, the association of rs525380 with PLA2G5 mRNA in vascular tissue may be a good marker of sPLA2-V expression. This is supported by immunohistochemistry and in situ hybridization of sPLA2-V in human atherosclerotic aortas showing that sPLA2-V protein expression was limited to smooth muscle cells and this correlated well with PLA2G5 mRNA expression.35

One of the limitations of our study is the lack of observational data on the association of sPLA2-V levels and risk of CHD, limited by the absence of an available sPLA2-V ELISA. PLA2G5 mRNA expression measures are limited by availability of datasets with tissue mRNA expression in individuals with and without CHD. The lack of a quantitative trait also means that a formal Mendelian “triangulation” analysis is not possible.19 However, the genetic analysis that we present is a form of Mendelian randomization as the SNP (rs525380) will, according to Mendel’s second law, be randomized at conception, meaning that individuals grouped by rs525380 genotype should be equal in all respects apart from exposure to differing PLA2G5 mRNA expression levels. Several animal studies support an atherosclerotic role of sPLA2-V,12,13,36,37 although we accept that positive findings from animal studies do not always translate into meaningful advances in combatting human disease.38 Even in the absence of availability of an observational quantification of the association of sPLA2-V (or for that matter PLA2G5 mRNA) with CHD events in humans, our genetic findings show that if such an associat ion were to exist, it would most likely be attributable to confounding and/or reverse causality rather than a causal relationship. We have made the assumption that vascular expression of sPLA2-V is a likely pro-atherogenic mediator and therefore we have considered vascular PLA2G5 mRNA as a good proxy for circulating levels of sPLA2-V levels. Our findings do not support those from animal studies and suggest sPLA2-V is not an important cause of CHD in man. The outcome of this study is in part validated by the phase III Vista 16 trial of varespladib (a drug that inhibits sPLA2-IIA, sPLA2-V and sPLA2-X), prematurely terminated due to lack of efficacy.39

Since we had no measure of sPLA2-V levels, we were unable to estimate the effect of the PLA2G5 SNP on sPLA2-V levels, and without an estimate of the observed association between sPLA2-V and CHD to obtain the expected effect size, we were unable to perform a power calculation. However, for comparison, in our Mendelian randomization analysis of sPLA2-IIA,20 in studies set in the general population we had a total of 15,534 incident and prevalent cardiovascular events out of a total of 74,683 individuals. In this current study we almost doubled the number of events with 27,230 events in 97,730 individuals. With an OR of 1.02 (95%CI 0.99, 1.04) between rs525380 and CHD, we are able to exclude a large effect of the SNP on CHD. Furthermore, the I2 value of 0%, indicating low heterogeneity, means that the values reported in the individual studies included in this meta-analysis were very similar (i.e. low between- study heterogeneity), adding further confidence to a “true negative” finding.

Plasma sPLA2 activity is suggested to represent a composite of the activities of the -IIa, -V and -X isoenzymes,6 however there is currently no experimental evidence supporting this. In a recent Mendelian randomization investigation of sPLA2-IIa,20 we reported that the SNP showing strongest association with sPLA2-IIa levels explained 31% of PLA2G2A mRNA expression and 21% of sPLA2-IIa variance, yet accounted for only 0.5% of the variance of sPLA2 activity. In a similar fashion, the rs525380 SNP, which explained 15% of the variance of PLA2G5 mRNA may only explain a very small variance of sPLA2 activity (for which we may be underpowered to detect with precision in the current analysis). Thus, sPLA2-V may only make a minor contribution to plasma sPLA2 activity. An alternative explanation is that despite rs525380 showing strongest association with PLA2G5 mRNA in the aortic adventitia of the vasculature, rs525380 may not represent a suitable proxy for circulating sPLA2-V. The high level of expression of PLA2G5 mRNA in several relevant atherosclerosis-prone tissues, such as heart, mammary artery intima-media, ascending aorta intima-media and aorta adventitia that we identified) suggest that sPLA2-V may have its greatest biological effect in these tissues and not in the plasma. Thus circulating plasma sPLA2 activity may not reflect tissue levels of sPLA2-V.

PLA2G5 rs525380 showed a weak association with PLA2G2A expression in the liver, but not in the other tissues we examined. This association could be a spurious finding since it did not exceed the Bonferoni adjusted P-value threshold. Alternatively, it could represent a real association. Our Bioinformatic analysis suggests that rs525380, 12.5 kb downstream of the PLA2G5, disrupts the binding site of the transcription factor GATA-2. GATA-2 is a transcription factor implicated in endothelial inflammatory responses.40 This might be particularly relevant to PLA2G5 given that Pla2g5 knock-out mice show 50% reduction in eicosanoid generation in response to zymosan stimulus, thus suggesting that sPLA2-V plays an important role in innate immunity.12 The association of the PLA2G5 SNP rs525380 with PLA2G2A expression in the liver suggests that GATA-2 might also act as a transcription factor for the control of expression of PLA2G2A. However, while the rare A allele of rs525380 is associated with higher PLA2G5 expression levels it is the common C allele that is associated with higher PLA2G2A expression levels. We previously showed that of the five tissues available in ASAP, PLA2G2A was most highly expressed in the liver,41 a tissue that showed the lowest level of PLA2G5 expression in this current study. This suggests a potential complementarity expression of these two transcripts in the liver, possibly under the control of GATA-2.

In conclusion, we identified no association between a SNP strongly linked to PLA2G5 mRNA tissue levels in atherosclerosis prone tissues and risk of CHD. Although the findings we report are by no means definitive, they do not support the hypothesis that sPLA2-V plays an important role in CHD. The methods we present demonstrate that in the absence of a specific plasma biomarker measure, it may be possible to use mRNA expression levels of the coding gene as a surrogate to examine the potential causal relationship of a biomarker.

Supplementary Material

000271 - Clinical Perspective
000271 - PAP
000271 - Supplemental Material

Acknowledgments

Funding Source: This work was funded the British Heart Foundation RG008/014 (SEH, ADH and PJT), RG/10/001/27643 (ZM), PG07/133/24260 (SEH, ADH, PJT, MKivimaki), FS 08/048/25628 (PJT and ADH) and FS/13/6/29977 (AJPS) and by the Medical Research Council UK (Population Health Scientist Fellowship G0802432: MVH; K013351, MKivimaki). SEH, ZM and NJS hold Chairs funded by the British Heart Foundation. MKumari is supported by the National Heart, Lung and Blood Institute, NIH (HL036310). CPN is funded by the National Institute of Health Research Leicester Cardiovascular Biomedical Research Unit. RS is a National Institute of Health Research Clinical Lecturer in Translational Medicine. FWA is supported by UCL Hospitals NIHR Biomedical Research Centre. The EPIC-Norfolk study is supported by a programme grant from the Medical Research Council UK (G1000143). The ASAP study was funded by the Swedish Research Unit Council (12660), the Swedish Heart-Lung foundation (20120272) and through a private donation from Fredrik Lundberg. The EPIC-NL study was funded by ‘Europe against Cancer’ Programme of the European Commission (SANCO), Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch Cancer Society; ZonMW the Netherlands Organisation for Health Research and Development, World Cancer Research Fund (WCRF) (The Netherlands). Genotyping was funded by IOP Genomics grant IGE05012 from Agentschap NL (NL Agency).

Footnotes

Conflict of Interest Disclosures: None

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Supplementary Materials

000271 - Clinical Perspective
NIHMS570284-supplement-000271_-_Clinical_Perspective.docx (14.5KB, docx)
000271 - PAP
NIHMS570284-supplement-000271_-_PAP.pdf (1.3MB, pdf)
000271 - Supplemental Material
NIHMS570284-supplement-000271_-_Supplemental_Material.pdf (512.6KB, pdf)

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