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Glutathione S‑Transferase (GST) M1, but Not GSTT1, Genotype Influences Plasma Proteomic Profiles in Caucasian and East Asian Young Adults Karina Fischer,†,‡ Laura A. Da Costa,† Bibiana García-Bailo,† Christoph H. Borchers,§ and Ahmed El-Sohemy*,† †

Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 3E2, Canada Institute of Food, Nutrition and Health, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland § University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria, Victoria, British Columbia, Canada ‡

S Supporting Information *

ABSTRACT: Glutathione S-transferase (GST) M1 and T1 are major detoxifying enzymes that have been associated with a number of chronic diseases, but their effect on various physiological pathways remains unclear. We investigated the association between the common GSTM1 and GSTT1 genotypes and multiple disease-related high-abundance proteins of the plasma proteome in young Caucasian (n = 476) and East Asian (n = 352) adults. Overnight fasting blood samples were collected, and 54 high-abundance plasma proteins from several physiological pathways were quantified by mass spectrometry-based multiple reaction monitoring (LC−MRM/MS). Subjects were genotyped for GSTM1 and GSTT1 deletion polymorphisms. Principal component analysis was used to identify proteomic profiles, and differences in individual protein concentrations between genotypes were assessed by ANCOVA. Among Caucasians, 19 proteins differed between GSTM1 genotypes (P < 0.05), with all protein concentrations being higher among the null genotypes. However, only complement C3 reached the Bonferroni-corrected significance threshold for multiple testing (P < 0.0009). Among East Asians, three proteins differed between GSTM1 genotypes (P < 0.05) with higher concentrations among the null genotypes, but none reached the Bonferroni level of significance. Protein concentrations did not differ between GSTT1 genotypes in either ethnicity. These findings suggest that GSTM1 may have novel physiological effects related to immunity and cardiometabolic disease. KEYWORDS: proteomics, plasma proteins, glutathione S-transferases, GSTM1, GSTT1, acute phase proteins, innate immunity, inflammation, coagulation, blood pressure, HDL metabolism, complement system, complement component 3, complement activation, C3

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compounds.1,10 This reaction usually inactivates these compounds and renders them more water-soluble for elimination.10,11 In the case of toxic compounds, this can be regarded as “detoxification”. 12 Because of this role in cellular detoxification, the null and functional GSTM1 and GSTT1 genotypes have been widely studied with regard to a number of chronic conditions, including cancer and cardiometabolic and immune-related diseases.13 In most cases, however, only a weak association or inconsistent outcomes have been observed.13,14 Apart from these roles in biotransformation and detoxification, GSTs can carry out a range of other biological functions.2 Accordingly, GST M1 and/or T1 have been shown to possess secondary catalytic activities, including (1) peroxidase activity to reduce lipid or other organic hydroperoxides15,16 and protect against oxidative cell stress17,18 and

INTRODUCTION

Glutathione S-transferase (GST) M1 and T1 are multifunctional isoforms of the mu and theta class of cytosolic GSTs, respectively, that can function as enzymes and intracellular binding proteins.1,2 The genes of both transferases, GSTM1 and GSTT1, exhibit a common deletion polymorphism,3,4 which in the case of homozygosity for the deletion allele leads to the complete absence of enzyme activity4,5 and is referred to as the “null” genotype. On the other hand, carriers of at least one “functional” allele produce a functional protein.6,7 The prevalence of both null genotypes differs across ethnic groups and has been reported to range from about 20 to 70% for GSTM1 and about 10 to 80% for GSTT1.6,8,9 As cytosolic enzymes, GSTs are known for their role in conjugation of phase II biotransformation where they catalyze the nucleophile addition of the sulfhydryl (“thiol”) group of reduced glutathione (GSH) to electrophilic centers in a large number of structurally diverse physiological and xenobiotic © 2012 American Chemical Society

Received: June 30, 2012 Published: September 4, 2012 5022

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apoptosis;19,20 (2) isomerase activity;21 (3) the ability to modulate serum vitamin C concentrations13 and protect against serum ascorbic acid deficiency;22 and (4) a role in biological signaling systems.19 As intracellular transport proteins, GSTs are capable of noncatalytically binding a wide range of endogenous and exogenous ligands,1,23 such as bilirubin, heme, steroids, thyroid hormones and bile salts.1 Compared to detoxification, however, such additional roles for GST M1 and T1 in endogenous metabolism have been less well studied, and thus their effect on various physiological pathways remains unclear. The blood plasma proteome comprises over 3000 identified proteins,24,25 many of which play a role in clinical diagnosis of diseases.26 High-abundance plasma proteins, ranging between about 0.04 and 800 μmol/L in concentration,25 represent many physiologically important molecules, including inflammatory proteins, coagulation factors, complement components (C), complement factors (CF), apolipoproteins (Apo(s)), carrier molecules and protease inhibitors, most of which are acute phase proteins (APP(s)) or related to the acute phase response.25−27 Accordingly, high-abundance proteins are critical to systemic physiology,25 and many of them have been implicated as putative biomarkers for cardiovascular disease, cancer or other chronic diseases.28,29 Given the role of plasma proteins in many important physiological processes, identifying proteins and protein patterns in pathways that are affected by the GSTM1 or GSTT1 genotype may help detect new mechanisms and roles of these two GSTs in health and disease. Moreover, examining the association between GSTM1 and GSTT1 genotypes and plasma proteins in young, healthy and nonsmoking adults may help identify pathways modulated by GSTM1 or GSTT1 that become dysregulated early in life and thus may account for later disease development. The aim of the present study was to examine the association between the GSTM1 and GSTT1 genotypes and concentrations of multiple high-abundance plasma proteins from several physiological pathways in Caucasian and East Asian healthy, young adults.

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the Caucasian and East Asian groups. Of the initial total number of Caucasians (n = 778) and East Asians (n = 565) recruited for the study, at the time of the proteomics analysis, plasma samples for 529 Caucasian and 391 East Asian subjects were available. From these, current smokers, subjects who may have over- (>3500 kcal/day for women, >4000 kcal/day for men) or under-reported (1) and Scree test criterion are shown by different colored lines (referred to as profile 1−4). For each protein, the component loadings for the individual four profiles are indicated on the circular axis (component loading scores ranging between −0.2 and 1) by different colored symbols. Each component represents an independent proteomic profile including all proteins that yielded a component loading ≥0.5 (shown as a dashed circular line) for this profile. For visual representation, proteins that did not obtain a component loading ≥0.5 for any profile were assigned to the profile for which they had the highest component loading; however, they were not considered as a member of that profile for analysis. Proteins that differed in mean plasma concentrations between GSTM1 genotypes (P < 0.05, ANCOVA with adjustment for age, sex and body mass index) are indicated (*). All indicated proteins had higher plasma concentrations among the GSTM1 null genotypes. See Results section for PCA data for hsCRP that was measured separately from the other 54 proteins.

have been linked to various health outcomes, including cardiovascular disease, inflammation, and cancer.28,29,35 All

plasma samples were run in singles. The intra-assay coefficient of variation (CV) was 2, were identified by PCA (Figure 1). Profile 1 included inflammation-, coagulation-, blood pressure- and HDL-related positive and negative APPs. Profile 2 comprised several anti-inflammatory and anticoagulation negative APPs. Profile 3 consisted of innate immunity-related complement components and factors as well as adaptive and innate immunity-related APPs. Profile 4 was comprised of fibrogenesis-related proteins. The variance (%) explained by profile 1 to 4 in Caucasians was 16.2, 7.9, 6.8 and 4.6, respectively, and in East Asians was 12.5, 8.4, 7.4 and 4.7, respectively. In Caucasians (Figure 1A), six proteins (C3, alpha-2-antiplasmin, ApoC-I, transthyretin, CFB and serum amyloid P-component) had component loadings ≥0.5 for two profiles and were included in both profiles. Three other proteins (alpha-1Bglycoprotein, adiponectin and zinc-alpha-2-glycoprotein 1) did not have a component loading ≥0.5 for any profile. In East Asians (Figure 1B), six proteins (alpha-2-antiplasmin, ApoA-I, complement C1 inactivator, ApoC-I, serum amyloid Pcomponent and C3) had a component loading ≥0.5 for two profiles and were included in both profiles. Three additional proteins (ApoB-100, alpha-1B-glycoprotein and zinc-alpha-2glycoprotein 1) did not load ≥0.5 onto any profile. When hsCRP was included as a 55th protein in the PCA (data not shown), among Caucasians hs-CRP loaded onto profile 1 and 3 with a component loading of 0.5 for both profiles, whereas among East Asians, hs-CRP loaded only onto profile 1 with a component loading of 0.5. When PCA was conducted in Caucasians and East Asians by GSTM1 and GSTT1 genotypes separately, the same four proteomic profiles were revealed (data not shown).

Characterization of the Proteomic Profiles

In the first step, the biological roles of the individual 54 proteins were examined through a thorough search of available literature on Pubmed and through querying of public online databases, such as UniProt and Reactome. The individual proteins were involved in various disease-associated pathways, namely the acute phase response, inflammation, immunity (innate and adaptive), coagulation, fibrogenesis, mineral and vitamin transport, lipid transport and metabolism, and blood 5026

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Table 2. Differences in Mean Plasma Protein Concentrations between Glutathione S-Transferase (GST) M1 Functional and Null Genotypes in Caucasians and East Asiansa GSTM1 Caucasians plasma proteins (μmol/L) Complement C3 Plasminogen Angiotensinogen Hemopexin Complement factor B Apolipoprotein A-I Apolipoprotein A-II precursor Vitamin D-binding protein Alpha-1B-glycoprotein Complement C4 beta chain Alpha-1-antitrypsin Vitronectin Afamin Kininogen-1 Heparin cofactor II Apolipoprotein L1 Hs-C-reactive proteinb Coagulation factor XIIa HC Retinol-binding protein 4 Complement C4 gamma chain Alpha-2-HS-glycoprotein Ceruloplasmin Serum amyloid P-component Interalpha-trypsin inhibitor HC Alpha-2-antiplasmin Alpha-2-macroglobulin Complement C9 Fibronectin Transthyretin Apolipoprotein B-100 Prothrombin Antithrombin-III Complement factor H Apolipoprotein C-I Clusterin Transferrin Apolipoprotein C-III Apolipoprotein A-IV Haptoglobin beta chain Alpha-1-acid glycoprotein 1 L-Selectin Albumin Adiponectin Zinc-alpha-2-glycoprotein Apolipoprotein D Fibrinogen gamma chain Beta-2-glycoprotein I Fibrinogen beta chain Gelsolin, isoform 1 Fibrinopeptide A Histidine-rich glycoprotein Apolipoprotein E Alpha-1-antichymotrypsin Fibrinogen alpha chain Complement C1 inactivator

functional 19.35 1.21 1.06 10.22 1.42 43.45 25.29 2.91 1.67 1.33 11.30 3.75 0.25 2.23 0.71 0.42 1.53 0.31 0.97 1.47 8.72 2.46 0.44 0.61 1.89 5.91 2.62 0.70 5.71 0.80 0.57 3.50 0.61 3.25 1.51 12.66 2.46 1.45 10.51 1.82 0.073 942 0.072 1.06 0.35 9.63 2.85 9.53 1.21 7.08 1.26 0.47 3.41 12.04 4.44

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

4.50 0.29 0.78 2.18 0.37 10.20 5.51 0.80 0.50 0.46 3.16 0.90 0.057 0.55 0.21 0.16 3.18 0.11 0.29 0.52 2.18 1.03 0.15 0.14 0.42 1.81 0.84 1.41 1.30 0.24 0.12 0.63 0.16 0.92 0.31 3.07 0.80 0.50 4.91 0.64 0.020 160 0.035 0.38 0.085 4.96 0.67 4.55 0.31 3.08 0.40 0.17 0.75 6.85 1.24

East Asians

null

P-value

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.0009 0.006 0.008 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.04 0.05 0.05 0.08 0.09 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.4 0.4 0.5 0.5 0.5 0.5 0.6 0.6 0.7 0.7 0.7 0.8 0.8 0.8 0.8 0.8 0.9 0.9

20.70 1.29 1.23 10.63 1.50 45.40 26.66 3.07 1.78 1.43 11.96 3.94 0.26 2.34 0.75 0.47 1.55 0.33 1.02 1.55 9.05 2.61 0.47 0.63 1.94 5.66 2.71 0.55 5.89 0.83 0.59 3.57 0.63 3.34 1.54 12.93 2.56 1.49 10.83 1.88 0.075 954 0.072 1.09 0.35 9.30 2.84 9.43 1.21 7.00 1.26 0.46 3.43 11.75 4.45

5.04 0.34 0.94 2.22 0.42 10.43 6.54 0.84 0.54 0.48 3.65 1.06 0.069 0.63 0.23 0.22 2.50 0.11 0.29 0.55 2.42 1.30 0.16 0.14 0.43 1.80 0.82 0.76 1.24 0.24 0.12 0.59 0.15 0.88 0.31 3.31 0.95 0.43 5.06 0.73 0.020 148 0.029 0.42 0.078 3.57 0.76 3.39 0.31 2.44 0.43 0.16 0.84 4.73 1.23

functional 17.84 1.17 0.72 9.35 1.31 43.42 23.81 2.61 1.54 1.35 10.08 3.44 0.23 1.97 0.62 0.36 0.66 0.19 0.83 1.48 8.40 1.93 0.41 0.60 1.85 5.85 2.58 0.67 5.58 0.75 0.56 3.55 0.54 3.17 1.48 11.81 2.28 1.39 9.48 1.53 0.069 969 0.061 1.02 0.33 9.40 2.64 9.50 1.19 7.00 1.39 0.54 3.11 12.05 4.82

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

3.84 0.24 0.40 1.91 0.35 10.07 5.14 0.51 0.45 0.48 2.20 0.67 0.058 0.40 0.17 0.14 1.78 0.072 0.25 0.54 1.70 0.63 0.15 0.12 0.38 1.54 0.82 1.27 1.20 0.21 0.11 0.64 0.12 0.89 0.33 2.67 0.89 0.40 5.25 0.50 0.018 155 0.031 0.43 0.090 4.31 0.55 4.24 0.24 2.89 0.40 0.21 0.67 6.00 1.00

null

P-value

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.2 0.2 0.056 0.1 0.2 0.6 0.08 0.3 0.08 0.2 0.3 0.1 0.7 0.2 0.1 0.2 0.1 0.2 0.08 0.2 0.3 0.1 0.3 0.009 0.02 0.9 0.5 0.4 0.1 0.2 0.04 0.3 0.7 0.8 0.1 0.6 0.3 0.5 0.3 0.7 0.7 0.6 0.9 0.6 0.8 0.9 0.3 0.8 0.7 0.7 0.7 0.6 0.1 0.6 0.5

18.33 1.20 0.80 9.66 1.35 43.81 24.67 2.66 1.62 1.41 10.28 3.55 0.25 2.01 0.65 0.38 0.94 0.20 0.86 1.55 8.60 2.02 0.42 0.63 1.94 5.91 2.65 0.57 5.77 0.77 0.59 3.60 0.54 3.17 1.51 11.98 2.34 1.36 9.89 1.56 0.069 974 0.060 0.99 0.33 9.28 2.68 9.29 1.20 6.86 1.37 0.55 3.23 11.75 4.90

4.01 0.24 0.48 1.94 0.34 9.70 5.44 0.56 0.47 0.49 2.30 0.71 0.066 0.43 0.17 0.14 2.90 0.087 0.24 0.55 1.87 0.69 0.15 0.13 0.43 1.50 0.83 0.83 1.32 0.22 0.11 0.59 0.12 0.80 0.29 2.93 0.74 0.41 5.12 0.54 0.019 145 0.026 0.38 0.077 4.47 0.54 3.68 0.27 2.92 0.42 0.17 0.80 6.18 1.13

a Data are unadjusted means ± standard deviations. Functional, *1/*1+*1/0 genotype; null, *0/*0 genotype; Hs-C-reactive protein, high sensitivity C-reactive protein (measured separately); HC, heavy chain; HS, Heremans-Schmid. P-Values are given for differences in mean plasma protein

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Table 2. continued concentrations between GSTM1 functional and null genotypes assessed by ANCOVA with, where necessary, loge or square-root transformed protein concentrations adjusted for age, sex and body mass index. All proteins are ordered by ascending P-values for the differences in mean plasma concentrations between GSTM1 genotypes in Caucasians. Bold and italicized P-values indicate a statistical significance at the 0.05 level. The Bonferroni threshold P-value is 0.0009. bHs-CRP was measured separately from the proteomics analysis of the other 54 proteins.

Differences in Mean Protein Concentrations between Genotypes

efficient GST T2B or T2 enzymes. Finally, as evolutionary forerunners of the wider adapted mu and other GST classes10,47 and with a narrower range of substrates, theta-class GSTs may possibly be more easily compensated by other GST classes14 than mu-class GSTs, suggesting a less pronounced effect of the GSTT1 than GSTM1 null genotype on multiple proteins of the plasma proteome. In Caucasians, considerably more proteins were influenced by the GSTM1 genotype than in East Asians. Although we did not test for differences between ethnic groups, we noted that independent of GST genotype many of the 55 proteins measured tended to have higher plasma concentrations among Caucasians than East Asians. Furthermore, Caucasians had significantly higher BMI, waist circumference and systolic blood pressure than East Asians. According to previous findings, East Asian individuals may be less prone to inflammation48 and chronic disease49 than Caucasians, and thus probably less susceptible to the GSTM1 null genotype. Most of the high-abundance proteins analyzed in the present study are APPs or proteins related to the acute-phase response,25,27,28 and have been implicated as putative nonspecific, rather than specific, biomarkers for metabolic stress25,27 and chronic diseases.28,29 PCA revealed that in Caucasians the proteins affected by the GSTM1 genotype from profile 1 comprised pro- and anti-inflammatory and pro- and anticoagulant positive APPs related to inflammation (hs-CRP, alpha-1-antitrypsin, C3), coagulation (plasminogen, kininogen1, vitronectin, heparin cofactor II, coagulation factor XIIa HC), blood pressure (angiotensinogen) and iron transport (hemopexin), as well as negative APPs related to antioxidant vitamin transport (vitamin D-binding protein, retinol-binding protein 4, afamin) and HDL metabolism (ApoA-I, ApoA-II, ApoL1). The proteins of profile 3, instead, were positive APPs related to complement activation and innate immunity (C3, C4, CFB). In East Asians, the proteins affected by the GSTM1 genotype from profile 1 and 2 were positive APPs related to inflammation (interalpha-trypsin inhibitor HC, prothrombin) and coagulation (interalpha-trypsin inhibitor HC, alpha-2-antiplasmin, prothrombin). These results suggest that the GSTM1 null genotype may predispose to higher plasma concentrations of proteins related to complement activation, inflammation, coagulation, blood pressure and HDL metabolism in Caucasians, and to coagulation and inflammation, but not complement activation, in East Asians. C3 was the only protein influenced by the GSTM1 genotype in Caucasians that reached Bonferroni-level significance, suggesting a more direct or specific effect on C3 than on the other proteins assessed. As the central component of the complement system, C3 mediates the immune and inflammatory response50 and interacts with the coagulation system.51,52 In line with this, C3 loaded ≥0.5 onto both the immunityrelated profile 3 and the inflammation/coagulation-related profile 1 in PCA. Recently, C3 has been recognized as a cardiometabolic risk factor51,53,54 and potential biomarker of chronic inflammatory55 and cardiometabolic disease.54,56 C3 can be activated via the classical, lectin or alternative complement pathway.50 Activation of C3 by cleavage via the

Regarding GSTM1 (Table 2 and Figure 1), among Caucasians (Figure 1A) a total of 19 proteins from profile 1 and 3, and alpha-1B-glycoprotein, which did not belong to any of the four profiles, differed in mean plasma concentrations between genotypes (P < 0.05), with the individual protein concentrations being higher among the null than functional genotypes. However, only C3 reached the Bonferroni level of significance for multiple testing (P = 0.0009, for 55 independent tests). Among East Asians (Figure 1B), only three proteins from profile 1 and 2 differed in mean plasma concentrations between GSTM1 genotypes (P < 0.05), with each of the three proteins having higher concentrations among those with the null genotype. However, none of the three proteins reached Bonferroni-corrected significance. Regarding GSTT1 (Table 3), no differences in mean plasma concentrations between genotypes were observed for any of the proteins in either ethnic group, with the exception of fibronectin in Caucasians (P < 0.05), but this did not meet the Bonferroni level of significance.

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DISCUSSION The present study examined the association between the null and functional GSTM1 and GSTT1 genotypes and multiple high-abundance plasma proteins in Caucasian and East Asian healthy, young adults. Our results suggest that the GSTM1, but not GSTT1, genotype influences concentrations of several highabundance plasma proteins in both ethnicities. Indeed, in Caucasians, 20 proteins, and in East Asians three proteins, differed in plasma concentrations between GSTM1 genotypes, with all the proteins having higher concentrations among the GSTM1 null genotypes. However, only C3 in Caucasians reached the Bonferroni level of significance. To our knowledge, this is the first study to examine the association between the common GSTM1 and GSTT1 genotypes and multiple proteins of the plasma proteome. Our finding that the GSTM1, but not GSTT1, genotype influenced concentrations of several high-abundance plasma proteins was not expected. Generally, the null genotype of both genes has been considered to predispose individuals to an increased susceptibility to toxic xenobiotics14,37 and elevated oxidative stress18 or, conversely, to a benefit from food-derived bioactive compounds.38,39 However, there are several explanations why the GSTM1, but not GSTT1, genotype, may affect proteins of the plasma proteome. GST M1 and GST T1 differ in amino acid sequence, three-dimensional structure,10 catalytic and kinetic mechanism for GSH binding and activation,40−42 as well as in substrate,43,44 organ and cell specificity.43,45,46 Importantly, due to a difference in a conserved key residue for binding and activation of GSH,41,42 theta-class, compared to mu-class, GSTs have a substantially higher catalytic efficiency and are not sensitive to product (analogue) inhibition.2,40 With this in mind, for the GSTT1 deletion allele, a strong linkage to the functional allele of GSTT2B, a duplicated copy of the GSTT1 paralogue GSTT2, has been reported,14 suggesting a possible compensation of the GST T1 function by highly 5028

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Table 3. Differences in Mean Plasma Protein Concentrations between Glutathione S-Transferase (GST) T1 Functional and Null Genotypes in Caucasians and East Asiansa GSTT1 Caucasians plasma proteins (μmol/L) Complement C3 Plasminogen Angiotensinogen Hemopexin Complement factor B Apolipoprotein A-I Apolipoprotein A-II precursor Vitamin D-binding protein Alpha-1B-glycoprotein Complement C4 beta chain Alpha-1-antitrypsin Vitronectin Afamin Kininogen-1 Heparin cofactor II Apolipoprotein L1 Hs-C-reactive proteinb Coagulation factor XIIa HC Retinol-binding protein 4 Complement C4 gamma chain Alpha-2-HS-glycoprotein Ceruloplasmin Serum amyloid P-component Interalpha-trypsin inhibitor HC Alpha-2-antiplasmin Alpha-2-macroglobulin Complement C9 Fibronectin Transthyretin Apolipoprotein B-100 Prothrombin Antithrombin-III Complement factor H Apolipoprotein C-I Clusterin Transferrin Apolipoprotein C-III Apolipoprotein A-IV Haptoglobin beta chain Alpha-1-acid glycoprotein 1 L-Selectin Albumin Adiponectin Zinc-alpha-2-glycoprotein Apolipoprotein D Fibrinogen gamma chain Beta-2-glycoprotein I Fibrinogen beta chain Gelsolin, isoform 1 Fibrinopeptide A Histidine-rich glycoprotein Apolipoprotein E Alpha-1-antichymotrypsin Fibrinogen alpha chain Complement C1 inactivator

functional 20.05 1.25 1.13 10.42 1.46 43.99 25.75 2.97 1.73 1.38 11.57 3.82 0.25 2.27 0.73 0.44 1.52 0.32 0.98 1.51 8.90 2.53 0.46 0.62 1.91 5.78 2.67 0.65 5.78 0.82 0.58 3.53 0.62 3.28 1.51 12.72 2.48 1.48 10.79 1.86 0.074 947 0.072 1.08 0.35 9.60 2.83 9.58 1.20 7.14 1.26 0.46 3.44 12.05 4.48

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

4.82 0.32 0.85 2.23 0.40 10.13 5.85 0.82 0.53 0.48 3.49 0.98 0.065 0.60 0.23 0.19 3.01 0.11 0.29 0.54 2.31 1.22 0.15 0.14 0.42 1.75 0.83 1.21 1.26 0.24 0.12 0.59 0.15 0.87 0.31 3.16 0.86 0.46 5.13 0.71 0.019 149 0.032 0.42 0.081 4.58 0.70 4.24 0.30 2.94 0.40 0.15 0.81 6.30 1.19

East Asians

null

P-value

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.9 0.4 0.6 0.9 0.7 0.08 0.1 0.4 0.7 0.8 0.4 0.4 0.4 0.4 0.6 0.5 0.5 0.9 0.07 0.8 0.6 0.9 0.2 0.99 0.5 0.6 0.5 0.05 0.5 0.6 0.8 0.6 0.8 0.6 0.09 0.4 0.2 0.7 0.3 0.8 0.9 0.6 0.8 0.6 0.08 0.2 0.4 0.2 0.4 0.08 0.8 0.3 0.5 0.2 0.4

20.05 1.28 1.22 10.45 1.45 46.08 26.84 3.07 1.71 1.37 11.90 3.94 0.26 2.33 0.74 0.46 1.60 0.33 1.03 1.51 8.85 2.56 0.44 0.62 1.95 5.78 2.65 0.52 5.87 0.81 0.58 3.56 0.62 3.37 1.57 13.08 2.62 1.45 10.26 1.82 0.074 953 0.072 1.04 0.33 8.96 2.89 9.11 1.22 6.68 1.25 0.48 3.37 11.35 4.33

4.86 0.33 0.93 2.14 0.40 10.98 6.83 0.83 0.49 0.45 3.26 1.03 0.060 0.58 0.20 0.20 2.18 0.11 0.27 0.49 2.31 1.04 0.16 0.13 0.45 2.01 0.83 0.73 1.31 0.25 0.12 0.67 0.15 0.99 0.32 3.31 0.93 0.48 4.42 0.63 0.022 170 0.035 0.36 0.082 3.08 0.74 2.95 0.34 2.00 0.47 0.19 0.75 3.86 1.35

functional 18.25 1.18 0.76 9.61 1.34 43.87 24.42 2.66 1.58 1.40 10.28 3.51 0.25 2.00 0.64 0.37 0.91 0.20 0.85 1.54 8.50 1.99 0.42 0.62 1.92 6.00 2.67 0.60 5.69 0.77 0.57 3.59 0.54 3.22 1.50 12.04 2.33 1.35 9.52 1.57 0.070 978 0.062 1.01 0.33 9.37 2.67 9.41 1.20 6.92 1.40 0.55 3.23 11.85 4.91

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

4.13 0.25 0.46 2.06 0.36 11.34 5.77 0.59 0.49 0.49 2.40 0.74 0.065 0.44 0.17 0.13 3.17 0.08 0.25 0.56 1.92 0.66 0.15 0.13 0.44 1.64 0.92 0.74 1.36 0.23 0.12 0.66 0.12 0.92 0.35 3.11 0.90 0.39 5.00 0.52 0.019 157 0.031 0.41 0.084 3.70 0.59 3.37 0.27 2.35 0.43 0.21 0.79 4.69 1.17

null

P-value

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.4 0.6 0.6 0.4 0.7 0.6 0.96 0.7 0.7 0.5 0.7 0.9 0.2 0.9 0.9 0.6 0.8 0.5 0.97 0.6 0.8 0.8 0.2 0.6 0.6 0.4 0.5 0.6 0.95 0.9 0.6 0.99 0.1 0.5 0.9 0.6 0.8 0.5 0.5 0.2 0.2 0.6 0.5 0.9 0.9 0.6 0.7 0.6 0.9 0.7 0.3 0.8 0.2 0.7 0.5

17.99 1.19 0.77 9.44 1.33 43.40 24.19 2.62 1.60 1.36 10.10 3.49 0.25 1.99 0.64 0.38 0.72 0.19 0.85 1.50 8.54 1.97 0.41 0.62 1.89 5.75 2.57 0.63 5.70 0.76 0.58 3.57 0.53 3.11 1.49 11.75 2.30 1.38 9.94 1.52 0.068 965 0.058 0.99 0.33 9.29 2.66 9.33 1.20 6.91 1.35 0.53 3.12 11.91 4.82

3.72 0.23 0.44 1.78 0.33 7.75 4.78 0.47 0.43 0.48 2.08 0.64 0.061 0.39 0.17 0.15 1.35 0.08 0.24 0.53 1.67 0.68 0.16 0.12 0.38 1.33 0.70 1.29 1.16 0.20 0.10 0.56 0.12 0.72 0.25 2.45 0.68 0.41 5.36 0.53 0.017 139 0.024 0.38 0.082 5.11 0.49 4.49 0.24 3.45 0.39 0.15 0.70 7.44 0.96

a Data are unadjusted means ± standard deviations. Functional, *1/*1+*1/0 genotype; null, *0/*0 genotype; Hs-C-reactive protein, high sensitivity C-reactive protein (measured separately); HC, heavy chain; HS, Heremans-Schmid. P-Values are given for differences in mean plasma protein

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Table 3. continued concentrations between GSTT1 functional and null genotypes assessed by ANCOVA with, where necessary, loge or square-root transformed protein concentrations adjusted for age, sex and body mass index. All proteins are ordered by ascending P-values for the differences in mean plasma concentrations between GSTM1 genotypes in Caucasians. A bold and italicized P-value indicates a statistical significance at the 0.05 level. The Bonferroni threshold P-value is 0.0009. bHs-CRP was measured separately from the proteomics analysis of the other 54 proteins.

alternative pathway depends on spontaneous hydrolysis of C3′s internal thioester.50,57,58 Recently, inhibition of C3 cleavage to C3a and C3b by GSH has been reported.59 GSH, as a strong nucleophile, may have prevented hydrolysis of the thioester, and thus cleavage of C3, by formation of an inactivated C3 intermediate.60 Functional GST M1 proteins might, therefore, be able to prevent thioester hydrolysis and cleavage of C3 by a GSH-dependent mechanism, for example, directly by a mechanism similar to nucleophile addition of GSH10,11 or indirectly by maintaining blood levels of GSH.61 Carriers of the GSTM1 null genotype, instead, would lack this ability and thus show increased C3 activation probably concomitant with chronically stimulated gene expression and thus higher plasma concentrations of C3 as observed in this study. Binding of CFB or CFH to C3b, results in amplification or inhibition of complement activation, respectively.50 In the present study, plasma concentrations of CFB were higher among Caucasian GSTM1 null genotypes, and CFH was not affected by the GSTM1 genotype, which supports that complement activation may have been enhanced among the GSTM1 null genotypes. In contrast to C3, C4 plays a central role in activation of the classical pathway.50 Compared to C3, the influence of the GSTM1 genotype on C4 concentrations was less pronounced, suggesting an effect of the GSTM1 genotype on the alternative rather than classical pathway. CRP is involved in both inflammation and innate immunity.62 In line with this, much like C3, hs-CRP loaded ≥0.5 onto both profile 1 and 3 in Caucasians. Similar to our results, an association of the GSTM1 null genotype to higher CRP levels in relation to oxidative stress and inflammation has been reported.18 Moreover, CRP can directly activate C3,62 again suggesting an association of the GSTM1 genotype with pathways linking complement activation and inflammation. ApoA-II, ApoA-I and ApoL1 are components of HDL. ApoA-II and ApoA-I are known to be anti-inflammatory and, at least concerning ApoA-I, cardioprotective negative APPs. Both were members of profile 1 that mainly included proinflammatory positive APPs. The higher plasma concentrations of these Apos among the GSTM1 null genotypes could, therefore, suggest a beneficial effect on inflammation and plasma lipid metabolism. Alternatively, in chronic low-grade inflammation, HDL and its related apolipoproteins, including ApoA-I and ApoA-II,63,64 can change in structure and function65 to become pro-inflammatory and pro-atherogenic,64,66 suggesting a negative impact of the GSTM1 null genotype on health. In such a state, a direct association of ApoA-I67 and ApoA-II63 with complement C3 has been reported, similar to the direct correlation of these proteins as members of profile 1 revealed by PCA. ApoL1, for its part, has recently been suggested to play a role in cytokine-induced proinflammatory response.68 Angiotensinogen was the only protein that was different between GSTM1 genotypes in Caucasians and also tended to be different between GSTM1 genotypes in East Asians. Angiotensinogen plays a major role in blood pressure regulation.69 Accordingly, a role of the GSTM1 null genotype in resistant hypertension has been suggested.70

The major roles of GSTs in detoxification and antioxidant defense suggest that the higher concentrations of plasma proteins among the GSTM1 null genotypes resulted from chronically increased systemic metabolic and/or oxidative stress.18 As all study subjects were healthy, young nonsmokers and without a preceding acute inflammatory event, the elevated concentrations of APPs among the GSTM1 null genotypes may have resulted from a chronic low-level activation of the acutephase response, similar to a subclinical low-grade inflammation.71 Low-grade inflammation is characterized by a prooxidative, inflammatory and atherogenic state,64 but also compensatory antioxidant and anti-inflammatory mechanisms to restrain systemic inflammation and immune response.72 Assuming a trend toward such a state of low-grade inflammation among the GSTM1 null genotypes, this might explain why in the present study plasma levels of both proinflammatory and procoagulant positive APPs and compensatory anti-inflammatory and anticoagulant negative APPs, were increased among the GSTM1 null genotypes. Although only C3 reached the Bonferroni level of significance, the differences observed between GSTM1 genotypes in our healthy, young subjects may account for disease development or progression later in life, particularly in combination with other risk factors of chronic disease. Furthermore, it is likely that the trend toward dysregulated health-related pathways we observed among GSTM1 null genotypes is considerably more pronounced in older and/or diseased subjects. The present study has several limitations. First, we did not discriminate between homo- and heterozygous functional genotypes and copy number variants. Thus, the differences observed would likely have been more pronounced between only homozygous null and functional genotypes. Further, in ANCOVA models we only adjusted for age, sex and BMI, and the two study populations differed in sample size and gender ratio. Inclusion of additional covariates, matched sample sizes and gender balance may alter the observed results. In summary, the GSTM1, but not GSTT1, genotype influenced concentrations of several high-abundance proteins of the plasma proteome. Among Caucasians, 19 proteins with counter-regulatory roles related to complement activation, inflammation, coagulation, blood pressure and HDL metabolism, and among East Asians three proteins related to inflammation and coagulation were influenced by the GSTM1 genotype, with all proteins having higher concentrations among the GSTM1 null genotypes.

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CONCLUSION Together, our results suggest that the GSTM1, but not GSTT1, genotype influences several high-abundance proteins of the plasma proteome, possibly with a trend toward low-grade inflammation among the GSTM1 null genotypes linked to complement activation by C3. However, as several of the affected proteins have anti-inflammatory and anticoagulant roles, a general impact of the GSTM1 genotype on health cannot be concluded. More likely, the GSTM1 null genotype 5030

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may affect some physiological pathways negatively, while others positively. This might help explain why evolutionary the GSTM1 null allele is still present in about 50% of the human population.

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ASSOCIATED CONTENT

* Supporting Information S

Data tables with measured values of absolute plasma protein concentrations across all Caucasian (Table S1) and East Asian (Table S2) study subjects. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel: 1 (416) 946-5776. Fax: 1 (416) 978-5882. E-mail: a.el. [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This study was funded by the Canadian Institutes of Health Research. AE-S holds a Canada Research Chair in Nutrigenomics. KF was supported by a research grant (No. 473) from the Swiss Foundation for Nutrition Research (SFEFS).

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ABBREVIATIONS GST, glutathione S-transferase; GSH, glutathione; C, complement component; CF, complement factor; Apo, apolipoprotein; APP, acute phase protein; BMI, body mass index; hs-CRP, high-sensitivity C-reactive protein; HOMA-IR, homeostasis model insulin resistance; HOMA-Beta, homeostasis model beta-cell function; MRM, multiple reaction monitoring; CV, coefficient of variation; LC, liquid chromatography; MS, mass spectrometry; PCA, principle component analysis; ANCOVA, analysis of covariance; HDL, high-density lipoprotein.

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