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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Gerontol A Biol Sci Med Sci. Author manuscript; available in PMC 2010 October 26.
Published in final edited form as:
J Gerontol A Biol Sci Med Sci. 2008 May; 63(5): 505–509.
PMCID: PMC2964084
NIHMSID: NIHMS240546

Glutathione Peroxidase Enzyme Activity in Aging

Abstract

Background

It is hypothesized that free radical damage contributes to aging. Age-related decline in activity of the antioxidant enzyme glutathione peroxidase (GPx) may contribute to increased free radicals. We hypothesized that GPx activity decreases with age in a population of older women with disability.

Methods

Whole blood GPx activity was measured in baseline stored samples from participants in the Women's Health and Aging Study I, a cohort of disabled community-dwelling older women. Linear regression was used to determine cross-sectional associations between GPx activity and age, adjusting for hemoglobin, coronary disease, diabetes, selenium, and body mass index.

Results

Six hundred one participants had complete demographic, disease, and laboratory information. An inverse association was observed between GPx and age (regression coefficient = −2.9, p < .001), indicating that for each 1-year increase in age, GPx activity decreased by 2.9 μmol/min/L. This finding remained significant after adjustment for hemoglobin, coronary disease, diabetes, and selenium, but not after adjustment for body mass index and weight loss.

Conclusion

This is the first study to examine the association between age and GPx activity in an older adult cohort with disability and chronic disease. These findings suggest that, after age 65, GPx activity declines with age in older women with disability. This decline does not appear to be related to diseases that have been previously reported to alter GPx activity. Longitudinal examination of GPx activity and other antioxidant enzymes in diverse populations of older adults will provide additional insight into age- and disease-related changes in these systems.

Keywords: Glutathione peroxidase, Oxidative stress, Aging, Older adult

Increases in oxygen-derived free radicals and resulting molecular damage and inflammatory pathway activation are hypothesized to contribute to biologic aging (13). The antioxidant system consists of intrinsic enzymes and extrinsic antioxidant nutrients, which serve to reduce free radicals to less toxic states (4). The identification of altered components of this complex regulatory system could provide important insights into the biological basis of increased oxidative stress in aging humans and into potential targets of clinical intervention (5,6).

Glutathione peroxidase (GPx), an enzyme dependent on the micronutrient selenium (Se), plays a critical role in the reduction of lipid and hydrogen peroxides (Figure 1) (6). If GPx activity is decreased, more hydrogen peroxide is present, which leads to direct tissue damage and activation of nuclear factor-κB–related inflammatory pathways (2,3). There are four subspecies of GPx that catalyze the reduction of hydrogen peroxides in specific tissue locations (68). GPx1 is ubiquitous and found in the cytosol of most cells, including red blood cells (RBCs). GPx2 is also cytosolic but is confined to the gastrointestinal tract. GPx3 occurs in the plasma as a glycoprotein, and GPx4 interacts with complex lipids, such as cholesterol and lipoproteins damaged by free radicals, and is found in mitochondria (8). Some studies in adult populations suggest an age-related decrease in activity of antioxidant enzymes (9,10), consistent with the hypothesis that increased free radical damage contributes to aging (1). A recent study provides evidence that lower levels of Se may contribute to inflammation and mortality in older women (11). However, few studies have examined the activity of GPx, which depends on Se for its activity, in adults older than 65 years, and fewer studies have examined GPx activity in adults older than 65 years with comorbid illness and disability. This population best reflects the accumulation of free radical damage that results in age-associated conditions, in keeping with the free radical theory of aging (1). We hypothesized that GPx activity varies by age and would be lower in older, compared to younger, adults.

Figure 1
Glutathione peroxidase reduces hydrogen peroxide and lipid peroxides to water and lipid alcohols.

Methods

Participants were individuals enrolled in the Women's Health and Aging Study (WHAS) I, a cohort study of the one-third most disabled community-dwelling older women in Baltimore, Maryland. Participants were recruited from a random sample of the Health Care Financing Administration's Medicare enrollment file for 32,538 women 65 years old or older and residing in 12 contiguous ZIP codes as of September 1, 1992. Criteria for inclusion in WHAS I were women with moderate to severe disability determined by the presence of self-reported difficulty in performing tasks in two or more of the following areas: basic self-care, higher-functioning tasks of daily living, upper extremity activities, and mobility. Further details on participant recruitment and examination have been previously published (11,12). Baseline demographic and health information was obtained, including blood pressure, weight, height, physician-diagnosed chronic diseases, difficulty with walking one-quarter mile, activities of daily living (ADL), instrumental activities of daily living (IADL), weight loss, and physical activity obtained from the Minnesota Leisure Time Activities Questionnaire. Chronic disease and condition information was adjudicated by physicians based on examination, medications, and medical records. Total and high-density lipoprotein (HDL) cholesterol, hemoglobin (Hgb), Se, albumin, and interleukin-6 (IL-6) information was also available in these individuals. Of the 5316 that were eligible for screening, 4135 were screened in the home, 1409 met study criteria, 1002 signed informed consent and agreed to participate in the study, and 783 agreed to have blood drawn starting in 1992. Of these 783 persons, 619 had stored serum samples. Blood samples for GPx analysis were collected between July 1993 and January 1996.

After venipuncture, whole blood from EDTA tubes was aliquoted into cryovials containing 10% dimethyl sulfoxide (DMSO) and stored at −70°C until analysis. GPx activity was determined in whole blood by spectrophotometry at 340 nm and 25°C using a commercially available kit (Zepto-Metrix Corp., Buffalo, NY). All samples were run in duplicate in a masked fashion.

Descriptive statistics were used to summarize GPx activity, demographic variables, and health-related characteristics. Simple linear regression was used to determine the univariate association of GPx activity with age, race, body mass index (BMI), smoking status, coronary disease (a composite variable including participants with definite angina, myocardial infarction, or congestive heart failure), diabetes, Se, albumin, IL-6, total cholesterol, HDL, Hgb, systolic blood pressure, physical activity, and weight loss. Sequential multiple linear regression models were used to examine the association of GPx with age, adjusting for Hgb, coronary disease, diabetes, and Se. In sequential analysis, these covariates were added one at a time to examine the effect of each addition on the association between GPx activity and age. Covariates for inclusion in multivariate analysis were chosen based on literature review for diseases that have been found to influence GPx activity in several previous human studies (10,13,14), and not specifically based on results of univariate analysis. Hgb was added to the model to adjust GPx activity for Hgb concentration, as is convention. The presence of a nonlinear association between GPx activity, age, and BMI was investigated using quadratic and spline terms in regression analyses. Log transformations were taken for variables that were not normally distributed. Based on the results, the relationship between GPx activity, age, and diabetes and the presence of potential effect modification, and interaction was examined using stratified multiple linear regression models and interaction terms.

Results

Six hundred one participants in the study sample had complete information for age, race, prevalent chronic disease information, diabetes, smoking status, and GPx activity. Baseline characteristics are summarized in Table 1. Age ranged from 65 to 100 years, with mean age of 77.6 (±7.8). The mean number of diseases per participant was 2.5 (±1.3). More than half of the participants had difficulty with at least one ADL task, at least one IADL task, and walking one-quarter mile. Almost one third of the participants (n = 191) reported that they were not able to provide physical activity information due to a health reason. Table 2 summarizes the results of univariate analysis of the association of GPx activity with the covariates. Age was strongly and significantly inversely associated with GPx activity with a regression coefficient of −2.89 (p < .001), indicating that for each year of increasing age, GPx activity was 2.89 μmol/min/L lower. Results of regression analyses using quadratic and spline terms to test the presence of a nonlinear association between GPx activity and age were not statistically signifi+cant. After examining scatterplots of GPx activity versus age, a potential outlier at age 100 years was identified. The direction and significance of the relationship between GPx activity and age did not change after removing this data point from the analyses; therefore, this value was included in all analyses. Significant positive associations were also observed, in separate models, between GPx activity and BMI, total cholesterol, Hgb, and weight loss (p < .05), but not with race, smoking status, coronary disease, diabetes, Se, albumin, IL-6, HDL, systolic blood pressure, or physical activity.

Table 1
Baseline Characteristics for the Study Sample (N = 601)
Table 2
Association of GPx with Age and Covariates Separately (Simple Linear Regression Results Between GPx and Individual Covariate)

To further investigate the finding that GPx activity decreases with age and whether this is an independent association and if it is potentially explained by the presence of disease, we analyzed the association between GPx activity and age by using sequential multiple linear regression models, adjusting for covariates (Table 3). Because we found Se to be inversely associated with age (Pearson correlation coefficient = −0.2, p < .001), Se was also added to the model. The results demonstrate that the association between GPx activity and age is significant even after adjusting for Hgb, coronary disease, diabetes, and Se level, with a β coefficient of −2.38, p = .01. The addition of coronary disease into the model adjusted for Hgb concentration minimally changed the regression coefficient, implying that the relationship between GPx activity and age is not confounded by coronary disease. However, although not statistically significant, the effect of coronary disease was of appreciable size, with a regression coefficient ranging from −17 to −21 in these models. When diabetes was added to this model, the regression coefficient was found to decrease modestly (from 2.5 to 2.2). However, an interaction term (Diabetes × Age) added to the model was not significant, indicating that diabetes is not a statistically significant effect modifier in the association between GPx activity and age.

Table 3
Association of GPx With Age, Adjusted for Covariates (Multivariate Linear Regression Models of GPx Versus Age, Sequentially Adjusting for Hemoglobin, Coronary Disease, Diabetes, and Selenium Using a Common Sample of 538 Women With Complete Data on These ...

To more closely examine the relationship between GPx activity and BMI, a scatterplot of GPx activity versus BMI was performed, which suggested that below a BMI of 30 kg/m2, the association between GPx activity and BMI appears to be positively correlated; such an association becomes less apparent above this point. We added a spline term at BMI = 30 kg/m2 to determine if it represents a threshold in the association between GPx activity and BMI (results shown in Table 2). This result shows that, for participants with BMI < 30 kg/m2, the association between GPx activity and BMI is significantly positively correlated (p = .012). However, no significant association was found between GPx activity and BMI for participants with BMI > 30 kg/m2 (p = .64). In a final multiple linear regression model with BMI and weight loss as covariates, the association between GPx activity and age was no longer significant (p = .061) (Table 4). In this model, BMI was considered with the previously modeled spline term for a nonlinear association. Because there were 38 missing values for BMI, and because all but one of these participants with missing BMI had a missing value for weight, we performed subsequent analyses to characterize these individuals. A higher proportion of those participants missing BMI information were older and had difficulty with high functioning and self-care tasks (p < .05). GPx activity for individuals with missing BMI information was 470.0 ± 157.5 μmol/min/L and was no different than for those with BMI information (p = .30).

Table 4
Association of GPx With Age, Adjusted for Covariates and BMI Below/Above 30 kg/m2 (Linear Regression Model of GPx Versus Age, Including Spline Term for BMI of 30 kg/m2 Using a Common Sample of 501 Women With Complete Data on These Covariates and GPx)

Discussion

This study tested the hypotheses that GPx activity decreases with age in a cohort of community-dwelling, moderately disabled women. We identified a significant and independent inverse relationship between GPx activity and age that persisted after adjusting for diabetes, coronary disease, and Se level. Although this has been studied in older adults who are healthy or who have single disease states (13), this is the first study to report the activity of GPx in a cohort of older adults with significant comorbidity and disability.

Previous population studies have provided conflicting evidence as to how GPx activity is altered with age (15). Whereas smaller studies have shown that it increases (9,16), most large studies have shown that GPx activity decreases with age (13,17). It appears that the age range of the participants is an important factor. In a study of middle-aged participants ages 55–69, there was no correlation found between GPx activity and age (18); however, a study that included participants aged 4–97 years found that GPx activity is relatively stable until age 65, and then begins to decline (17). This finding is supported by in vitro studies of neutrophils from older adults showing lower levels of GPx activity and higher concentrations of hydrogen peroxide compared to younger individuals (19). Our results provide additional evidence that GPx activity decline is substantial, consistent, and age-related after age 65 even after adjustment for potentially influential covariates. Because the mean age in our study is equal to the maximum age of many of the studies previously cited and because we were able to adjust for many known confounders of GPx activity, this study provides important evidence that GPx activity declines in the subset of the population that faces the greatest burden from increased levels of free radicals (20).

GPx and Disease

Although several studies have evaluated GPx activity in healthy aging individuals, this is one of few reports of GPx activity in older adults with comorbid diseases and disability (21,22). Many studies have looked at GPx activity in specific disease states independently, and cardiovascular disease and diabetes have both been shown to be associated with alterations in GPx activity (2326). Low GPx activity appears to be predictive of cardiovascular events in individuals with suspected coronary disease (27). Although the relationship between cardiovascular disease and GPx activity was not significant in our study, the direction of the relationship was consistent with previous studies (24,27). Diabetes and glucose intolerance have been associated with increased GPx activity in some studies (28) and decreased activity in others (14). It is unclear why GPx activity is decreased in cardiovascular disease and increased in diabetes, two closely related diseases. Animal studies show that induction of oxidative stress via the addition of hydrogen peroxide leads to upregulation of GPx expression (29). With chronic oxidative stress, as in diabetes, one may expect increased GPx activity as a result of upregulation of the enzyme. However, with acute oxidative stress, as would be seen with myocardial infarction, one may expect an overproduction of free radicals beyond the enzyme's capacity and resultant depletion of glutathione, which is required for GPx activity maintenance (30). These issues are beyond the scope of our study, but warrant consideration in future studies of GPx activity.

GPx and Body Composition

Our finding that the association between GPx activity and age approached statistical significance only after adjustment for BMI and weight loss may be the result of decreased power because of missing values for BMI. Additionally, because of missing data for BMI, which may represent obese individuals, our findings may not be truly representative of obese individuals. However, despite this shortcoming, our data provide evidence that there is a nonlinear association between GPx activity and BMI. GPx activity is positively correlated up to a BMI of 30 kg/m2, the standard clinical threshold for obesity. After this point, our findings suggest the trend is for GPx activity to decrease. Our finding is consistent with two previous reports showing that individuals with a BMI within what is considered a healthy range (19–25 kg/m2) have higher GPx activity than do individuals with a BMI in the obese range [>30 kg/m2 (31) and >40 kg/m2 (32)]. Our finding that weight loss, which is an important clinical indicator of poor health status, was inversely correlated with GPx activity is particularly interesting as this suggests that individuals with weight loss are less able to tolerate oxidative stress. Future studies of the relationship between GPx activity and body composition may be improved by including information on dietary intake, anthropomorphic data, or other obesity-related hormones such as leptin in the analyses.

Besides the missing BMI data, there are other limitations of this study. First, our findings are cross-sectional. Although associations may be observed, we cannot determine if GPx activity declines with the aging of these individuals. Longitudinal analysis will help determine if alteration in GPx activity over time drives its association with inflammation and disease, or if inflammation and disease drive GPx activity. Another potential limitation is the fact that the samples used in this analysis have been stored for up to 10 years. Although there is no definitive evidence that length of storage time influences the activity of GPx in RBCs, long-term storage may still influence laboratory measurement. However, these results are similar in range to those of previous studies in which samples were analyzed immediately following venipuncture (13,27). Trevisan and colleagues (13) were able to show no change in enzyme activity for at least 4 years. A final limitation to be noted is the fact that this study uses secondary data to consider the relationship of GPx activity with age while adjusting for other potentially confounding factors. Although we took measures to include all potentially confounding covariates in the analyses by including covariates that have been found in previous studies to influence GPx activity, even if not significantly associated with GPx activity in our analyses, there is certainly potential for residual confounding.

These findings suggest that GPx activity varies with age, and may be altered by specific diseases and perhaps body composition. They also suggest that, although disease does influence GPx activity, age may exert a stronger influence in this population of older women. Further understanding of the relationships between GPx and other antioxidant enzymes, disease, and age in the oldest, most ill and disabled subset of older adults may greatly improve our ability to develop interventions aimed at decreasing oxidative stress and its pathological influence late in life (5).

Acknowledgments

This work was supported by the National Institute on Aging (NIA), Claude D. Pepper Older Americans Independence Centers (grant P30 AG021334), by contract NO1-AG12112 and National Institutes of Health (NIH)-NIA grant R37 AG1990 5, by the General Clinical Research Centers (GCRC) NIH-NCRR (grant M01-RR000052 at the Johns Hopkins School of Medicine), by the Johns Hopkins Bayview Medical Center GCRC (grant M01-RR-02719), and in part by NIA T32 AG000120.

References

1. Harman D. The aging process. Basic Life Sci. 1988;49:1057–1065. [PubMed]
2. Meyer M, Pahl HL, Baeuerle PA. Regulation of the transcription factors NF-kappa B and AP-1 by redox changes. Chem Biol Interact. 1994;91:91–100. [PubMed]
3. Yu BP, Chung HY. Adaptive mechanisms to oxidative stress during aging. Mech Ageing Dev. 2006;127:436–443. [PubMed]
4. Vertuani S, Angusti A, Manfredini S. The antioxidants and pro-antioxidants network: an overview. Curr Pharm Des. 2004;10:1677–1694. [PubMed]
5. Voss P, Siems W. Clinical oxidation parameters of aging. Free Radic Res. 2006;40:1339–1349. [PubMed]
6. Arthur JR. The glutathione peroxidases. Cell Mol Life Sci. 2000;57:1825–1835. [PubMed]
7. Brigelius-Flohe R. Tissue-specific functions of individual glutathione peroxidases. Free Radic Biol Med. 1999;27:951–965. [PubMed]
8. Imai H, Nakagawa Y. Biological significance of phospholipid hydroperoxide glutathione peroxidase (PHGPx, GPx4) in mammalian cells. Free Radic Biol Med. 2003;34:145–169.S089 1584902011978 [PubMed]
9. Jozwiak Z, Jasnowska B. Changes in oxygen-metabolizing enzymes and lipid peroxidation in human erythrocytes as a function of age of donor. Mech Ageing Dev. 1985;32:77–83. [PubMed]
10. Habdous M, Herbeth B, Vincent-Viry M, et al. Serum total antioxidant status, erythrocyte superoxide dismutase and whole-blood glutathione peroxidase activities in the stanislas cohort: Influencing factors and reference intervals. Clin Chem Lab Med. 2003;41:209–215. [PubMed]
11. Walston J, Xue Q, Semba RD, et al. Serum antioxidants, inflammation, and total mortality in older women. Am J Epidemiol. 2006;163:18–26. [PubMed]
12. Volpato S, Ferrucci L, Blaum C, et al. Progression of lower-extremity disability in older women with diabetes: The Women's Health and Aging Study. Diabetes Care. 2003;26:70–75. [PubMed]
13. Trevisan M, Browne R, Ram M, et al. Correlates of markers of oxidative status in the general population. Am J Epidemiol. 2001;154:348–356. [PubMed]
14. Atli T, Keven K, Avci A, et al. Oxidative stress and antioxidant status in elderly diabetes mellitus and glucose intolerance patients. Arch Gerontol Geriatr. 2004;39:269–275. doi: 10.1016/j.archger.2004.04.065.S0167494304001219 [PubMed] [Cross Ref]
15. Junqueira VB, Barros SB, Chan SS, et al. Aging and oxidative stress. Mol Aspects Med. 2004;25:5–16. doi: 10.1016/j.mam.2004.02.003.S0098299704000056 [PubMed] [Cross Ref]
16. Inal ME, Kanbak G, Sunal E. Antioxidant enzyme activities and malondialdehyde levels related to aging. Clin Chim Acta. 2001;305:75–80.S0009898100004228 [PubMed]
17. Artur Y, Herbeth B, Guemouri L, et al. Age-related variations of enzymatic defenses against free radicals and peroxides. EXS. 1992;62:359–367. [PubMed]
18. Mulholland CW, Elwood PC, Davis A, et al. Antioxidant enzymes, inflammatory indices and lifestyle factors in older men: a cohort analysis. QJM. 1999;92:579–585. [PubMed]
19. Ito Y, Kajkenova O, Feuers RJ, et al. Impaired glutathione peroxidase activity accounts for the age-related accumulation of hydrogen peroxide in activated human neutrophils. J Gerontol Med Sci. 1998;53A:M169–M175. [PubMed]
20. Ames BN, Shigenaga MK. Oxidants are a major contributor to aging. Ann N Y Acad Sci. 1992;663:85–96. [PubMed]
21. Akesson B, Steen B. Plasma selenium and glutathione peroxidase in relation to cancer, angina pectoris and short-term mortality in 68-year-old men. Compr Gerontol [A] 1987;1:61–64. [PubMed]
22. Tho LL, Candlish JK. Superoxide dismutase and glutathione peroxidase activities in erythrocytes as indices of oxygen loading in disease: a survey of one hundred cases. Biochem Med Metab Biol. 1987;38:74–80. [PubMed]
23. El Kossi MM, Zakhary MM. Oxidative stress in the context of acute cerebrovascular stroke. Stroke. 2000;31:1889–1892. [PubMed]
24. Kedziora-Kornatowska K, Czuczejko J, Pawluk H, et al. The markers of oxidative stress and activity of the antioxidant system in the blood of elderly patients with essential arterial hypertension. Cell Mol Biol Lett. 2004;9:635–641. [PubMed]
25. Nadeem A, Raj HG, Chhabra SK. Increased oxidative stress in acute exacerbations of asthma. J Asthma. 2005;42:45–50. [PubMed]
26. Locatelli F, Canaud B, Eckardt KU, et al. Oxidative stress in end-stage renal disease: an emerging threat to patient outcome. Nephrol Dial Transplant. 2003;18:1272–1280. [PubMed]
27. Blankenberg S, Rupprecht HJ, Bickel C, et al. Glutathione peroxidase 1 activity and cardiovascular events in patients with coronary artery disease. N Engl J Med. 2003;349:1605–1613. doi: 10.1056/NEJMoa030535.349/17/1605 [PubMed] [Cross Ref]
28. Menon V, Ram M, Dorn J, et al. Oxidative stress and glucose levels in a population-based sample. Diabet Med. 2004;21:1346–1352. doi: 10.1111/j.1464-5491.2004.01417.x.DME1417 [PubMed] [Cross Ref]
29. Zhou LZ, Johnson AP, Rando TA. NF kappa B and AP-1 mediate transcriptional responses to oxidative stress in skeletal muscle cells. Free Radic Biol Med. 2001;31:1405–1416.S0891584901007195 [PubMed]
30. Comhair SA, Erzurum SC. The regulation and role of extracellular glutathione peroxidase. Antioxid Redox Signal. 2005;7:72–79. doi: 10.1089/ars.2005.7.72. [PubMed] [Cross Ref]
31. Ozata M, Mergen M, Oktenli C, et al. Increased oxidative stress and hypozincemia in male obesity. Clin Biochem. 2002;35:627–631.S0009912002003636 [PubMed]
32. Olusi SO. Obesity is an independent risk factor for plasma lipid peroxidation and depletion of erythrocyte cytoprotectic enzymes in humans. Int J Obes Relat Metab Disord. 2002;26:1159–1164. doi: 10.1038/sj.ijo.0802066. [PubMed] [Cross Ref]