Significance of Singlet Oxygen Molecule in Pathologies

Reactive oxygen species, including singlet oxygen, play an important role in the onset and progression of disease, as well as in aging. Singlet oxygen can be formed non-enzymatically by chemical, photochemical, and electron transfer reactions, or as a byproduct of endogenous enzymatic reactions in phagocytosis during inflammation. The imbalance of antioxidant enzymes and antioxidant networks with the generation of singlet oxygen increases oxidative stress, resulting in the undesirable oxidation and modification of biomolecules, such as proteins, DNA, and lipids. This review describes the molecular mechanisms of singlet oxygen production in vivo and methods for the evaluation of damage induced by singlet oxygen. The involvement of singlet oxygen in the pathogenesis of skin and eye diseases is also discussed from the biomolecular perspective. We also present our findings on lipid oxidation products derived from singlet oxygen-mediated oxidation in glaucoma, early diabetes patients, and a mouse model of bronchial asthma. Even in these diseases, oxidation products due to singlet oxygen have not been measured clinically. This review discusses their potential as biomarkers for diagnosis. Recent developments in singlet oxygen scavengers such as carotenoids, which can be utilized to prevent the onset and progression of disease, are also described

Multi-Biomarkers for Early Detection of Type 2 Diabetes, Including 10- and 12-(Z,E)-Hydroxyoctadecadienoic Acids, Insulin, Leptin, and Adiponectin.

We have previously found that fasting plasma levels of totally assessed 10- and 12-(Z,E)-hydroxyoctadecadienoic acid (HODE) correlated well with levels of glycated hemoglobin (HbA1c) and glucose during oral glucose tolerance tests (OGTT); these levels were determined via liquid chromatography-mass spectrometry after reduction and saponification. However, 10- and 12-(Z,E)-HODE alone cannot perfectly detect early impaired glucose tolerance (IGT) and/or insulin resistance, which ultimately lead to diabetes. In this study, we randomly recruited healthy volunteers (n = 57) who had no known history of any diseases, and who were evaluated using the OGTT, the HODE biomarkers, and several additional proposed biomarkers, including retinol binding protein 4 (RBP4), adiponectin, leptin, insulin, glycoalbumin, and high sensitivity-C-reactive protein. The OGTT revealed that our volunteers included normal individuals (n = 44; Group N), "high-normal" individuals (fasting plasma glucose 100-109 mg/dL) with IGT (n = 11; Group HN+IGT), and diabetic individuals (n = 2; Group D). We then used these groups to evaluate the potential biomarkers for the early detection of type 2 diabetes. Plasma levels of RBP4 and glycoalbumin were higher in Group HN+IGT, compared to those in Group N, and fasting levels of 10- and 12-(Z,E)-HODE/linoleic acids were significantly correlated with levels of RBP4 (p = 0.003, r = 0.380) and glycoalbumin (p = 0.006, r = 0.316). Furthermore, we developed a stepwise multiple linear regression models to predict the individuals' insulin resistance index (the Matsuda Index 3). Fasting plasma levels of 10- and 12-(Z,E)-HODE/linoleic acids, glucose, insulin, and leptin/adiponectin were selected as the explanatory variables for the models. The risks of type 2 diabetes, early IGT, and insulin resistance were perfectly predicted by comparing fasting glucose levels to the estimated Matsuda Index 3 (fasting levels of 10- and 12-(Z,E)-HODE/linoleic acids, insulin, and leptin/adiponectin)

Attenuation of lipopolysaccharide (LPS)-induced cytotoxicity by tocopherols and tocotrienols

Lipopolysaccharide (LPS) induces host inflammatory responses and tissue injury and has been implicated in the pathogenesis of various age-related diseases such as acute respiratory distress syndrome, vascular diseases, and periodontal disease. Antioxidants, particularly vitamin E, have been shown to suppress oxidative stress induced by LPS, but the previous studies with different vitamin E isoforms gave inconsistent results. In the present study, the protective effects of α- and γ-tocopherols and α- and γ-tocotrienols on the oxidative stress induced by LPS against human lung carcinoma A549 cells were studied. They suppressed intracellular reactive oxygen formation, lipid peroxidation, induction of inflammatory mediator cytokines, and cell death. Tocopherols were incorporated into cultured cells much slower than tocotrienols but could suppress LPS-induced oxidative stress at much lower intracellular concentration than tocotrienols. Considering the bioavailability, it was concluded that α-tocopherol may exhibit the highest protective capacity among the vitamin E isoforms against LPS-induced oxidative stress

Selecting biomarkers for practical use.

<p>Matsuda Index 3 is estimated using 10- and 12-<i>(Z</i>,<i>E)</i>-hydroxyoctadecadienoic acid, insulin, and leptin/adiponectin (Model 2) (A), and the risk of glucose tolerance and insulin resistance is predicted using fasting levels of glucose and estimated Matsuda Index 3 (B). Blue, normal insulin resistance; red, borderline insulin resistance; green, insulin resistance determined by homeostasis model assessment of insulin resistance and Matsuda Index 3. Circle, Group N (normal); square, Group HN+IGT (“high-normal” and impaired glucose tolerance); triangle, Group D (diabetic).</p

Predicting the risk of glucose tolerance and insulin resistance.

<p>Matsuda Index 3 is estimated using the 9 biomarkers that are shown in Model 1. Blue, normal insulin resistance; red, borderline insulin resistance; green, insulin resistance determined by homeostasis model assessment of insulin resistance and Matsuda Index 3. Circle, Group N (normal); square, Group HN+IGT (“high-normal” and impaired glucose tolerance); triangle, Group D (diabetic).</p

Classification of insulin resistance using the oral glucose tolerance test.

<p>Blue, normal insulin resistance; red, borderline insulin resistance; green, insulin resistance determined by homeostasis model assessment of insulin resistance and Matsuda Index 3. Circle, Group N (normal); square, Group HN+IGT (“high-normal” and impaired glucose tolerance); triangle, Group D (diabetic).</p

Classification of glucose tolerance using the oral glucose tolerance test.

<p>Circle, Group N (normal); square, Group HN+IGT (“high-normal” and impaired glucose tolerance); triangle, Group D (diabetic). Blue, normal insulin resistance; red, borderline insulin resistance; green, insulin resistance determined by homeostasis model assessment of insulin resistance and Matsuda Index 3.</p

Characteristics of subjects at entry into the oral glucose tolerance test.

<p>Data are presented as mean ± standard deviation. One-facter completely randomized design analysis of variance (ANOVA) was used to examine the main effect of subject group on each index.</p><p>Shignificant effects were followed by Tukey's HSD multiple comparisons.</p><p>^a, fasting</p><p>^B, 60 min after 75g of oral glucose</p><p>^C, 120 min after 75 g of oral glucose</p><p>^d, fasting sugar, 100–109 mg/dl (defined by the Japan Diabetes Society)</p><p>Abbreviations: BMI, body mass index; RBP4, Retinol-Binding Protein 4; hs-CRP, high sensitivity C—reactive protein; HOMA-IR, homeostasis model assessment of insulin resistance; L/A, Leptin/Adiponectin</p><p>*p<0.05</p><p>**<0.01 compared with Group N.</p><p>Characteristics of subjects at entry into the oral glucose tolerance test.</p