Aging Linked to Type 2 Diabetes Increases Oxidative Stress and Chronic Inflammation

Abstract

Oxidative stress (OxS) and inflammation are physiopathological mechanisms related to diabetes and aging. We evaluated the additive effect of diabetes and aging on OxS and inflammation in a cross-sectional comparative study of 228 subjects: (1) 56 healthy adults (mean age, 47 ± 7 years); (2) 60 diabetic adults (mean age, 52 ± 6 years); (3) 40 healthy elderly adults (mean age, 67 ± 7 years); and (4) 72 diabetic elderly adults (mean age, 68 ± 7 years). We measured levels of glycosylated hemoglobin (HbA1c), plasma lipid peroxides, superoxide dismutase, glutathione peroxidase, total antioxidants, and tumor necrosis factor-alpha (TNF-α). The results indicate that diabetes is a risk factor for subjects with high serum levels of TNF-α (odds ratio [OR] = 12.1; 95% confidence interval [95% CI], 5.0–28; p < 0.001); this correlation becomes stronger when it is also associated with aging (OR = 14; 95% CI, 3.7–53.7; p < 0.05). Likewise, we observed that diabetes is an independent risk factor for OxS (OR = 2.1; 95% CI, 1.2–3.8; p < 0.05), and a stronger factor in older patients (OR = 3.1; 95% CI, 1.3–7.5; p < 0.05). Our findings suggest that aging, in concert with diabetes, exerts an additive effect on OxS and inflammation.

Introduction

A ging is a gradual and adaptive process characterized by a diminished homeostatic response resulting from accumulated physiologic, biochemical, psychological, and social wear on an organism over time.¹ Although this is a normal physiological process, it can be accelerated in the presence of high levels of oxidative stress (OxS) or by chronic inflammatory processes (CIP).² These biochemical alterations increase vulnerability to chronic, degenerative diseases such as type 2 diabetes mellitus (T2DM).³

OxS is the consequence of an excess of metabolic oxidant species at the levels of biomolecules, cells, tissues, and organs. OxS and CIP have been associated with the T2DM etiology and physiopathology and are determining factors for the prognosis of elderly diabetic individuals, because they have been linked with T2DM-related complications (angiopathies and neuropathies, retinopathies and neuropathies).³

The chronic hyperglycemia that presents in T2DM activates several unusual metabolic pathways in the organism, such as the sorbitol pathway (or that of aldose reductase), nonenzymatic protein glycosylation, glucose autooxidation, modification of protein kinase C activity, pseudohypoxia, lipoprotein-altered metabolism, and cytokine-associated alteration, all of which generate reactive oxygen species (ROS) and, consequently, OxS.⁴

Several studies have demonstrated that aging and/or T2DM increase synthesis and secretion of cytokines such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and free radicals, all of which are recognized as factors that increase the risk of disease-related complications.^4

–7 However, the effect of the interaction between T2DM and aging on inflammation and OxS markers has not been evaluated. Thus, the aim of the present study is to determine the additive effect of aging and T2DM on OxS and chronic inflammation.

Methods

Design and subjects

A case-controlled study was performed in a sample of 224 subjects, which were partitioned into the following four groups: (1) 56 healthy adults (HA), average age, 47 ± 7 years; (2) 60 diabetic adults (DA), average age, 52 ± 6 years; (3) 40 healthy elderly adults (HE), average age, 67 ± 7 years, and (4) 72 diabetic elderly adults (DE), average age, 68 ± 7 years. All diabetic subjects were diagnosed in the past 3–5 years, and were prescribed the oral hypoglycemic agents glibenclamide and metformin.

All subjects were physically and mentally functional, and none ingested antioxidant supplements during the course of the experiment. The Ethics Committee of the Universidad Nacional Autónoma de México (UNAM) Zaragoza Campus approved the research protocol, and all subjects gave their informed consent.

Anthropometric measurements

After the clinical history was taken and the physical examination was conducted, we performed the following anthropometric measurements: Weight was measured while the subject was in a fasted state (after evacuation). The Torino^® scale (Tecno Lógica, Mexicana, México, TLM^®) used was calibrated before each weight measurement. Height was obtained with an aluminum cursor stadiometer graduated in millimeters while the subject was barefoot, with back and head in contact with the stadiometer in Frankfurt horizontal plane. Body mass index (BMI) was calculated by dividing weight (in kilograms) by height (in squared meters). Waist circumference was measured with a tape measure to the nearest 0.5 cm at the umbilical scar level.

Blood pressure

Blood pressure was measured in both arms three times in the morning, in a fasting condition or 2 h after breakfast, in sitting and standing positions. A mercurial manometer was used to measure blood pressure. Subjects with pseudohypertension were identified with the Osler technique; the radial pulse was taken when the manometer registered values above the true systolic pressure. Blood pressure was taken using a standardized procedure, which was performed by trained medical technicians; measurements were supervised to avoid possible biases. We used the Official Mexican Norm (Norma Oficial Mexicana) for high blood pressure (HBP): previous diagnosis and detection of systolic blood pressure ≥140 mmHg and/or diastolic blood pressure of ≥90 mmHg.⁸

Metabolic syndrome

Metabolic syndrome was defined according to criteria established in the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III).⁹

Biochemical analysis

Blood samples were collected by venopuncture after a 12-h fasting period and placed in a vacutainer in siliconized test tubes containing a separating gel without additives. Heparin and ethylenediaminetetraacetic acid (EDTA) were used as anticoagulant agents. Blood samples containing heparin were analyzed using the complete hemoglobin test protocol (including hemoglobin, hematocrit, and leukocyte counts). All reagents used in biochemical tests were obtained from Randox Laboratories, Ltd. (Crumlin Co., Antrim, UK).

Glycosylated hemoglobin

Glycosylated hemoglobin (HbA1c) was measured by immunoturbidimetric assay with a Shimadzu UV-1601 UV-Vis spectrophotometer (Kyoto, Japan).

Insulin and adiponectin

Serum insulin was quantified by radioimmunoassay (RIA)¹⁰; the cutoff value for hyperinsulinemia was ≥20 IU/mL, which is in agreement with the 90th percentile of subjects with normal weight and euglycemics.

Homeostasis model assessment of insulin resistance (HOMA-IR) was determined by the formula proposed by Matthews et al. in 1985:¹¹ IR = [fasting insulin in μU/mL × fasting glucose in mM]/22.5.

Adiponectin levels were determined by RIA assay with a Cobra II Auto-Gamma analyzer (Linco Research USA). The cutoff value for hypoadiponectinemia was ≤11.4 μg/mL for women and ≤8.8 μg/mL for men, which is in agreement with the 25^th percentile of healthy subjects.

Markers of inflammation

The presence of cytokines IL-6 and TNF-α was determined by enzyme-linked immunoassay (ELISA; Quantikine, R&D Systems, USA). The cutoff value used represents the levels found in the 90^th percentile of healthy subjects: IL-6 ≥ 4.0 pg/mL and TNF-α ≥8.5 pg/mL. C-reactive protein (CRP) was measured manually with a latex agglutination slide test for the semiquantitative in vitro determination in serum (Randox Laboratories).

Plasma thiobarbituric acid reactive substances

The plasma thiobarbituric acid reactive substances (TBARS) assay was prepared as described by Jentzsch et al.¹² In the TBARS assay, one molecule of malondialdehyde reacts with two molecules of thiobarbituric acid and thereby produces a pink pigment with absorption peak at 535 nm. Amplification of peroxidation during the assay is prevented by the addition of the chain-breaking antioxidant, butylhydroxytoluene.

Plasma total antioxidant status

Plasma total antioxidant status (TAS) levels were quantified using 2, 2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS⁺) radical formation kinetics (Randox Laboratories, Ltd., Crumlin Co., UK). The antioxidants present in plasma suppressed the bluish-green staining of the ABTS⁺ cation. The kinetics were measured at 600 nm with a Shimadzu UV-1601 UV-Vis spectrophotometer (Kyoto, Japan).

Red blood cell superoxide dismutase

Our method used xanthine and xanthine oxidase (XOD) to generate superoxide radicals, which react with 2-(4-iodophenyl)-3-(4-nitrophenol)-5-phenyltetrazolium chloride to form a red formazan dye. Superoxide dismutase (SOD) activity was measured by degree of inhibition of the reaction (Randox Laboratories Ltd., Crumlin Co., UK). The kinetics were measured at 600 nm with a Shimadzu UV-1601 UV-Vis spectrophotometer (Kyoto, Japan).

Red blood cell glutathione peroxidase

In the presence of glutathione reductase and nicotinamide adenine dinucleotide phosphate (NADPH), the oxidation of glutathione (GSH) by cumene hydroperoxide is catalyzed by glutathione peroxidase (GPx). Oxidized glutathione (GSSG) is immediately converted into the reduced form with the subsequent oxidation of NADPH to NADP⁺ (Randox Laboratories, Ltd., Crumlin Co., UK). The decrease in absorbance was measured at 340 nm with a Shimadzu UV-1601 UV-Vis spectrophotometer (Kyoto, Japan).

Oxidative stress

Alternative cutoff values for each parameter were defined on the basis of the 90th percentile of young healthy subjects: Lipid peroxidation (LPO) ≥0.340 mmol/L, superoxide dismutase (SOD) ≤170 IU/L, glutathione peroxidase (GPx) ≤5,500 IU/L, total antioxidant status (TAS) ≤0.9 mmol/L, SOD-to-GPx ratio (SOD/GPx) ≥0.023, antioxidant gap (GAP) ≤190 mmol/L. A stress score (SS) ranging from 1 to 6, representing the severity of biomarkers modifications, was assigned; a score of 1 was given to each value higher than the cutoff for LPO and SOD/GPx and to each value lower than the cutoff for SOD, GPx, TAS, and GAP. We categorized subjects as follows according to their SS score: No OxS if SS was 0, slight OxS if SS was 1–2, moderate OxS if SS was 3–4, and severe OxS if SS was 5–6. These groups were pooled into subjects “without OxS” (SS ranging from 0 to 2) and “subjects with OxS” (SS ranging from 3 to 6).¹³

Statistical analysis

Data were processed by use of standard statistical software SPSS 10.0 (SPSS Inc. Chicago, IL). Descriptive statistics are means ± standard deviations (SD). Results were analyzed using the paired t-test and chi-squared test. Also, a multivariate analysis of logistic regression was calculated for a risk factor when odds ratio (OR) >1. A p value <0.05 was considered significant.

Results

Biochemical and anthropometric characteristics

In Table 1, the anthropometric and biochemical characteristics of healthy and diabetic groups are shown. We found that HOMA-IR was significantly higher in elderly subjects in healthy and diabetic groups. However, it was observed that the frequency of hyperinsulinemia and high HOMA-IR (≥6.12) were significantly higher in the group of diabetic elderly than in that of diabetic adult subjects (Table 2).

Table 1.

Anthropometric and Biochemical Characteristics in Healthy and Diabetic Groups

	Healthy subjects		Diabetic subjects
	Adult	Elderly	Adult	Elderly
n	56	40	60	72
Age (years)	47 ± 7	67 ± 7	52 ± 6	68 ± 7
BMI (kg/m²)
Women	27 ± 4	28 ± 4	29 ± 3	28 ± 4
Men	27 ± 4	26 ± 3	28 ± 3	27 ± 3
Waist circumference
Women	100 ± 6	104 ± 9	99 ± 17	100 ± 10
Men	100 ± 7	96 ± 6	99 ± 9	95 ± 6
Hip circumference (cm)
Women	83 ± 10	89 ± 10	90 ± 9	91 ± 10
Men	91 ± 10	93 ± 11	94 ± 7	98 ± 7
Waist-to-hip ratio
Women	0.83 ± 0.06	0.85 ± 0.05	1.1 ± 1.3	0.91 ± 0.07
Men	0.90 ± 0.04	0.97 ± 0.07	0.97 ± 0.07	1.03 ± 0.05
SBP (mmHg)	114 ± 10	120 ± 25	124 ± 15	135 ± 20
DBP (mmHg)	75 ± 7	78 ± 9	81 ± 9	79 ± 10
Fasting serum glucose (mg/dL)	89 ± 19	94 ± 17	152 ± 64	160 ± 66
HbA1c (%)	4.7 ± 0.7	4.9 ± 1.7	6.8 ± 1.4	7.9 ± 2.2
Insulin IU/mL	9 ± 6	12 ± 7	14 ± 10	20 ± 15
HOMA-IR	2.0 ± 1.4	2.6 ± 1.8^†	5.1 ± 4	8.2 ± 7^*
Hemoglobin (g/dL)	15.3 ± 2	15.1 ± 1.2	15.2 ± 1.6	15.1 ± 1.6
Hematocrit (%)	48 ± 4	47 ± 4	57 ± 8	47 ± 5
Total leukocytes/mm³	6382 ± 2003	9078 ± 3327	7470 ± 4187	8011 ± 4064
Albumin (g/dL)	5 ± 0.8	4.5 ± 0.46	4.4 ± 0.7	4.5 ± 0.43
Colesterol mg/dL	208 ± 12	203 ± 7	204 ± 8	216 ± 5
LDL-C (mg/dL)	118 ± 43	109 ± 34	114 ± 38	124 ± 35
HDL-C (mg/dL)	56 ± 12	54 ± 9	54 ± 14	53 ± 14
Triglycerides (mg/dL)	172 ± 44	197 ± 36	206 ± 41	214 ± 38
Urea (mg/dL)	38 ± 5	39 ± 6	42 ± 6	41 ± 10
Creatinine (mg/dL)	0.98 ± 0.29	0.95 ± 0.23	1.04 ± 0.33	1.04 ± 0.7

Data show mean ± standard error (SE). Student t-test, *p < 0.05; †p < 0.001.

BMI, Body mass index; WHR, waist-to-hip ratio; HbA1c, glycosylated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; SBP, systolic blood pressure; DBP, diastolic blood pressure; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol.

Table 2.

Hyperinsulinemia and Chronic Inflammation Markers in Healthy and Diabetic Groups

	Healthy subjects		Diabetic subjects
	Adult n = 56 (%)	Elderly n = 40 (%)	Adult n = 60 (%)	Elderly n = 72 (%)
Hyperinsulinemia (≥20 UI/mL)	4 (7)	5 (12)	12 (20)	27 (37)^†
HOMA-IR (≥6.12)	0 (0)	0 (0)	17 (28)	29 (40)^†
Hyperleptinemia	9 (16)	7 (17)	13 (22)	34 (47)^†
C-reactive protein (≥6mg/L)	6 (11)	5 (12)	12 (20)	29 (40)^†
IL-6 (≥4.0pg/mL)	4 (7)	11 (27)^*	14 (23)	31 (43)^*
TNF-α (≥8.5 pg/mL)	5 (9)	4 (10)	30 (50)	47 (65)
Hypoadiponectinemia	7 (12)	5 (12)	14 (23)	12 (17)

Chi-squared test: *p < 0.05;^† p < 0.01.

HOMA-IR, homeostasis model assessment of insulin resistance; hyperleptinemia: [leptin, women (≥27.4 ng/mL); men (≥9.4 ng/mL)];IL-6, interleukin-6; TNF-α, tumor necrosis factor-α; hypoadiponectinemia: [adiponectin, women (≤10 μg/mL), men (≤5 μg/mL)].

Inflammation markers

With regard to chronic inflammation markers, we observed a significantly greater percentage of hyperleptinemia (47 vs. 22%; p < 0.05), and high levels of CRP (40 vs. 20%; p < 0,05), and IL-6 (43 vs. 23%; p < 0.05) in the group of diabetic elderly in comparison with the group of diabetic adults (Table 2). Similarly, we found that T2DM is a risk factor for subjects with high serum levels of TNF-α (OR = 12.1; 95% CI, 5.0–28; p < 0.001), which increases with aging (OR = 14; 95% CI, 3.7–53.7; p < 0.001). This additive effect was observed for CRP (OR = 4.4; 95% CI, 1.5–12; p < 0.01) (Table 3).

Table 3.

Diabetes Mellitus and Age as Risk Factors For High Levels of TNF-α, IL-6, and CRP

	OR	CI	p value
TNF-α
Diabetes mellitus	12.1	5.0–28	<0.001
Age (≥60 years)	1.89	1.1–3.5	0.029
Interaction (diabetes mellitus by age)	14.0	3.7–53.7	<0.001
IL6
Diabetes mellitus	3.2	1.3–7.5	0.007
Age (≥60 years)	2.9	1.4–6.2	0.005
Interaction (diabetes mellitus by age)	2.0	0.6–6.1	0.171
CRP
Diabetes mellitus	3.8	1.8–8	<0.001
Age (≥60 years)	2.4	1.3–4.6	0.005
Interaction (diabetes mellitus by age)	4.4	1.5–12	0.003

TNF-α, Tumor necrosis factor alpha; IL-6, interleukin-6; CRP, C-reactive protein; OR, odds ratio; CI, 95% confidence interval.

On the other hand, we found that the high serum levels of TNF-α were a stronger risk factor for metabolic syndrome in the adult group than in the elderly group (adults, OR = 6.3, 95% CI, 2.5–16; p < 0.001 vs. elderly, 3.2, 95% CI, 1.2–2.8; p < 0.05), and likewise for high serum levels of IL6 (adults, OR = 3.2, 95% CI, 1.0–10; p < 0.05 vs. elderly, OR = 1.8, 95% CI, 0.6–5.2; p > 0.05) (Table 4).

Table 4.

High Levels of TNF-α, IL-6, and CRP as Risk Factors For Metabolic Syndrome in Adults and Elderly

	OR	CI	p value
Adults
TNF-α (≥8.5 pg/mL)	6.3	2.5–16	<0.001
IL-6 (≥4.0 pg/mL)	3.2	1.0–10	0.038
CRP (≥6 mg/L)	1.5	0.5–4	0.29
Elderly
TNF-α (≥8.5 pg/mL)	3.2	1.2–2.8	0.012
IL-6 (≥4.0 pg/mL)	1.8	0.65–5.2	0.183
CRP(≥6 mg/L)	0.98	0.5–4.2	0.56

TNF-α, Tumor necrosis factor alpha; IL-6, interleukin-6; CRP, C-reactive protein; OR, odds ratio; CI, 95% confidence interval.

Oxidative stress markers

With respect to OxS, we found that T2DM is an independent risk factor for OxS (OR = 2.1; 95% CI, 1.2–3.8; p < 0.05), which increases when it is associated with aging (OR = 3.1; 95% CI, 1.3–7.5; p < 0.05) (Table 5). In addition, we observed a higher percentage of subjects with OxS in the elderly metabolic syndrome group than in the adult syndrome metabolic group (elderly, 44% vs., adult, 24%, p = 0.059) (Table 6).

Table 5.

Diabetes Mellitus and Age as Risk Factors for Oxidative Stress

	OR	CI	p value
Diabetes mellitus	2.1	1.2–3.8	0.015
Age (≥60 years)	1.6	1.1–3.3	0.020
Interaction (diabetes mellitus by age)	3.1	1.3–7.5	0.014

OR, odds ratio; CI, 95% confidence interval.

Table 6.

Oxidative Stress in Healthy and Metabolic Syndrome Groups

	Healthy subjects		Metabolic Syndrome subjects
	Adult n = 56 (%)	Elderly n = 40 (%)	Adult n = 42 (%)	Elderly n = 59 (%)
Without oxidative stress	43 (76)	30 (75)	32 (74)	33 (56)
Oxidative stress	13 (24)	10 (25)	10 (24)	26 (44)^*

Chi-squared test: *p = 0.059.

Discussion

Several studies have shown that OxS and CIP are implicated in the complications of T2DM; at the same time, these biochemical alterations have been linked with the normal aging process.^14

–18 Thus, a possible synergistic effect has been proposed between T2DM and aging on some metabolic alterations,¹⁹ among which OxS and CIP could be implicated.

In our study, we found a significantly higher percentage of subjects with hyperinsulinemia and insulin resistance in the group of diabetic elderly than in that of diabetic adults, which suggests that aging exerts an influence on the physiopathology of T2DM by increasing insulin resistance. In this regard, it has been pointed out that aging affects the secretion and action of insulin, rendering disease control difficult and increasing the risk of complications, including cardiovascular diseases.²⁰ Four pathways have been proposed to explain the link between insulin resistance and aging: (1) Anthropometric changes, characterized by an increase in body fat combined with a decline in fat free mass, which is cause of a reduction in active metabolic tissue; (2) TNF-α environmental causes related to the diet and physical activity; (3) neurohormonal variations, mainly a decline in plasma levels of dehydroepiandrosterone sulfate (DHEAS) and insulin-like growth factor I (IGF-1); and (4) rise in OxS. However, these disturbances are not inherent characteristics of aging, per se. It has been demonstrated that age-related insulin resistance is not an obligatory finding in the elderly and that healthy centenarians have preserved insulin action due to adaptive metabolic changes.^{21, 22}

Concerning inflammation-associated biochemical markers, in the present study we observed similar percentages of hyperleptinemia in both groups of healthy subjects. At the same time, we found a significantly higher percentage of subjects with hyperleptinemia in the group of elderly diabetics as compared with the group of diabetic adults. It has been reported that serum leptin levels do not change or gradually diminish with aging²³; for this reason, hyperleptinemia is considered a risk factor for several aging-related diseases such as arterial hypertension, cancer, and chronic obstructive pulmonary disease.^24

–29 On the other hand, it has been pointed out that the interaction between high levels of leptin and TNF-α is a biochemical marker for the prognosis of chronic disease linked to proinflammatory and prooxidant action.^30
–32 In our current study, we observed a greater percentage of subjects with hyperleptinemia and high levels of TNF-α in the diabetic elderly group. These findings suggest that T2DM coupled with aging increases the risk for chronic diseases the result from high levels of TNF-α and leptin. It has been proposed that TNF-α plays a fundamental role in the pathogenesis of cardiovascular diseases linked with T2DM. Advanced glycosylation end-products AGEs)/receptor for AGEs (RAGE), lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), and nuclear factor-κB (NF-κB) signaling play key roles in TNF-α expression through an increase in circulating and/or local vascular TNF-α production, which induces OxS.³³ In this sense, it is has been demonstrated that diet can be a significant environmental source of AGEs.³⁴

Additionally, several studies have reported that high levels of CRP, IL-6, and TNFα constitute risk factors for cardiovascular diseases.^35,36 We found a significantly higher percentage of subjects with high levels of TNF-α, CRP, and IL-6 in both groups of diabetics than in the healthy groups. An additive effect between T2DM and age ≥60 years was observed overall for subjects with high levels of TNF-α. These findings suggest that elderly diabetics can have higher risk for cardiovascular disease than diabetic adults due to an increase of proinflammatory factors linked to a possible additive effect of age-related inflammation and T2DM physiopathology.^{17,18, 37,38}

We found greater levels of OxS in the group of elderly individuals with T2DM in comparison with the group of diabetic adults. These findings support the proposal of a possible additive effect between aging and T2DM on the frequency and severity of OxS.^39,40 Nevertheless, our study is limited in its design and cross-sectional analysis, and therefore it is not possible establish causal directionality. For this reason, we also performed an analysis of TNF-α, CRP, and IL-6 as risk factors for metabolic syndrome in adults and elderly, and we found that TNF-α and IL-6 are greater risk factors for metabolic syndrome in adults than in the elderly. These findings suggest that elderly adults with metabolic syndrome may develop antiinflammatory mechanisms, as has been proposed by Franceschi et al.¹⁷ for healthy long-lived elderly.

In conclusion, our results suggest that aging linked with T2DM has an additive effect on inflammatory processes and OxS. These findings support the idea that prescription of antioxidant supplements and antiinflammatory drugs as a coadjuvant in the treatment of T2DM in the aged may be beneficial.⁴⁰

Footnotes

Acknowledgments

This work was supported by the Universidad Nacional Autónoma de México, DGAPA UNAM. Project PAPIIT IN303407.

Author Disclosure Statement

No competing financial interests exist.

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