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Proteomic analysis of plasma proteins in Japanese semisuper centenarians
Experimental Gerontology 46 (2011) 81–85
Contents lists available at ScienceDirect
Experimental Gerontology j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / e x p g e r o
Short Report
Proteomic analysis of plasma proteins in Japanese semisuper centenarians Yuri Miura a, Yuji Sato a,1, Yasumichi Arai b, Yukiko Abe b, Michiyo Takayama b, Tosifusa Toda a, Nobuyoshi Hirose b, Tamao Endo a,⁎ a b
Research Team for Mechanism of Aging, Tokyo Metropolitan Institute of Gerontology, Tokyo 173-0015, Japan Department of Geriatric Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
a r t i c l e
i n f o
Article history: Received 27 May 2010 Received in revised form 22 September 2010 Accepted 6 October 2010 Available online 14 October 2010 Section Editor: R. Westendorp Keywords: Aging Semisuper centenarian Proteomics Oxidative stress Plasma proteins
a b s t r a c t We performed proteomic analysis of plasma proteins in Japanese semisuper centenarians (SSCs) (N 105 years) and young controls (20-39 years), and found that 18 protein spots were altered in the plasma of SSCs. From peptide mass fingerprinting following in-gel digestion, it was demonstrated that paraoxonase/arylesterase 1 (PON 1) and apolipoprotein E were decreased, while haptoglobin β-chain, α1-microglobulin, and clusterin precursor were increased in SSCs. Interestingly, proteins related to oxidative stress, PON1, haptoglobin, α1microglobulin, and clusterin, were altered in SSCs. These results suggest that systemic redox regulation is important for the longevity of SSCs. Overall, proteomics analysis is a powerful technique to search for useful biomarkers for future studies in gerontology and to characterize the individual proteins associated with successful aging of SSCs. © 2010 Elsevier Inc. All rights reserved.
1. Introduction Aging is a universal phenomenon. It can be considered as the product of interactions among genetic, environmental and lifestyle factors, which in turn influence longevity, a biological phenomenon which shows inter-individual variability. Recent progress in genome studies indicates that gene polymorphisms contribute to human longevity. These gene polymorphisms are thought to influence longevity through several potential mechanisms, including the immune system and the metabolic system (Atzmon et al., 2006; Barzilai et al., 2003; Franceschi et al., 2005; Kojima et al., 2004). It is likely that more genes involved in human aging remain to be discovered. Recently, RNA editing genes have been reported to be important regulators of aging in humans (Sebastiani et al., 2009). Taken together, whole genome association study of extreme old age, living to extreme old age, such as 100 years and older, is a powerful strategy to discover the genes associated with human longevity. Another strategy is to focus on the proteins being expressed in all human tissues and fluids. Proteins, such as enzymes, structural components, mediating and modulating cell adhesion and signaling components, etc., play important roles in many biological events. They
also influence longevity through their functions (Arai et al., 2008). However, such studies are limited. Technical advances over recent decades have allowed comprehensive analysis of the protein composition of biological samples, such as tissues, cells, organelles, and serum. Proteomic analysis offers great potential for studies of cellular and tissue protein alterations in various disease states and aging (Hwang et al., 2009; Schiffer et al., 2009; Sun and Cavalli, 2010). Exceptional longevity (100 years and older) is the fastest growing segment of the population in the world, and the increase results from a reduction in mortality rate. Since mortality rate in human was proposed to reach a plateau at age 105 (Vaupel et al., 1998), we assume that semisuper centenarians (SSCs; older than 105 years) are the best example of human longevity. SSCs probably escape many chronic and serious diseases, and are probably able to cope with a variety of stresses, including oxidative stress. Therefore, in the present study, we used SSCs as a model of human longevity. We performed proteomic analyses to look for differences in the plasma protein profiles of controls and SSCs. It is expected that this approach will lead to the discovery of proteins related to healthy aging. 2. Materials and Methods
⁎ Corresponding author. Research Team for Mechanism of Aging, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo, Japan. Tel.: +81 3 3964 3241; fax: +81 3 3579 4776. E-mail address: [email protected] (T. Endo). 1 Deceased. 0531-5565/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.exger.2010.10.002
2.1. Subjects Ten female SSCs (106-109 years, mean age 107.3 ± 1.0) and 10 female centenarians (100 years) were recruited to participate in this study. None were in an acute care situation, and none were receiving
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tube feeding. The past disease history of the SSCs was coronary artery disease, stroke, diabetes and cancer. The control subjects were 10 female healthy volunteers aged 20-39 years (mean age 27.5 ± 7.5) recruited from hospital and institutional workers. The control subjects were free from diseases and had no relevant history, such as coronary artery disease, stroke, diabetes and cancer. All subjects enrolled in this study were Japanese. Twenty milliliters of non-fasting venous blood was collected, and plasma was immediately separated by centrifugation at 4 °C and stored at -80 °C until subsequent assays. This study was approved by the ethics committees of both Tokyo Metropolitan Institute of Gerontology and Keio University School of Medicine. 2.2. Materials
Mascot search engine (Matrix Science, London, UK, see http://www. matrixscience.com) using the SwissProt protein database. Mascot search parameters were as follows: type of search, peptide mass fingerprinting; fixed modifications, carbamidomethyl (C); enzyme, trypsin; peptide mass tolerance, ± 0.2 Da; max missed cleavage, 1.
2.5. Western blot analysis Each mixture of controls and SSCs was desalted by acetone precipitation similar to the sample preparation of 2D-PAGE, and was separated by SDS-PAGE. Western blot analyses were performed as described previously (Miura et al., 2005) using specific antibodies.
Immobiline Drystrip pH 4-7 and Pharmalyte 3-10 were purchased from GE Healthcare (Buckinghamshire, UK). Dithiothreitol (DTT) and thiourea were purchased from Sigma-Aldrich (St. Louis, MO, USA). SYPRO-Ruby protein gel stain and Alexa Fluor 488-conjugated antirabbit IgG were purchased from Bio-Rad Laboratories (Hercules, CA, USA) and Invitrogen (Carlsbad, CA, USA), respectively. Affinitypurified anti-PON1 antibody was purchased from Japan Biotest (Tokyo, Japan). Anti-apolipoprotein E, anti-haptoglobin, anti-α1microglobulin, and anti-clusterin antibodies were purchased from Epitomics Inc. (Burlingame, CA, USA), DAKO Cytomation (Glostrup, Denmark), Abcam Co. (Cambridge, UK), and Santa Cruz Biotechnology (Santa Cruz, CA, USA), respectively. All other reagents were of the highest quality available. 2.3. Protein extraction and 2D-PAGE For 2D-PAGE analyses, we used mixed plasma samples, one for controls and one for SSCs. Each mixture was prepared from 2-μl samples from 10 individuals and desalted by acetone precipitation. The samples were mixed for two reasons, first because 2D electrophoresis analyses are laborious and time consuming and second because mixed samples would diminish individual differences but retain common characteristics in the group. Proteins of plasma mixtures were extracted by the addition of 4 ml extraction buffer (5 M urea, 2 M thiourea, 10 mM DTT, 2% Triton X-100, 1% Pharmalyte 3-10, 2.5 mM acetic acid, and 0.0025% Orange G). Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) was performed as previously described (Miura et al., 2005; Sato et al., 2006) (see also http://www.proteome.jp/2D/J_2DEmethod.html) with slight modifications. Three gels were run for each group. After separation on 2DPAGE, protein spots on the gel were fixed in 50% methanol and 10% acetic acid for 30 min, followed by staining with SYPRO-Ruby protein gel stain. The gels were scanned with a Molecular Imager® FX Pro (Bio-Rad Laboratories). The images were processed with PDQuest 2D image processing software (Bio-Rad Laboratories). Image processing consisted of noise reduction, background subtraction, spot detection, spot normalization, gel-to-gel matching, spot quantification, and differential-display analyses between controls and SSCs. The spot intensities were represented as parts per million (ppm) of the total spots integrated on each gel using “total quantity in valid spots” within PDQuest software. SSC spots whose intensities were either less than one-half or more than twice those of the controls were defined as changed proteins in SSCs. Additionally, spots in SSCs and controls that differed in intensity with p-values of 0.05 or less were also defined as changed proteins. 2.4. In-gel protein digestion and peptide mass fingerprinting In-gel digestion of selected gel spots was performed as described previously (Miura et al., 2005). Peptide mass fingerprinting was acquired using a MALDI-TOF/MS spectrometer (AXIMA-CFR; Shimadzu Biotech, Kyoto, Japan). Proteins were identified with the
Fig. 1. Protein profiles of 2D-PAGE of controls (A) and SSCs (B). 2D-PAGE was performed with isoelectric focusing (pI 4-7) in the first dimension and SDS-PAGE in the second dimension followed by SYPRO-Ruby staining, as described in Materials and methods. Circles indicate protein spots, the expression levels of which were decreased (A) or increased (B) in SSCs. Vertical axes are designated as molecular mass (kDa) and horizontal axes as pI.
Y. Miura et al. / Experimental Gerontology 46 (2011) 81–85
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Table 1 Identification of protein spots in Fig. 1. Spot
Protein
UniProt knowledgebase accesion No.
Theoretical value mass (kDa)/pIa
Fold changeb
a b c d e f g h i j k l m n o p q r
Paraoxonase / arylesterase 1 (PON1) Paraoxonase / arylesterase 1 (PON1) Apolipoprotein E Not identified Not identified Not identified Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain α1-Microglobulin α1-Microglobulin Clusterin precursor Not identified Not identified Not identified
P27169 P27169 P02649 P00738 P00738 P00738 P00738 P00738 P00738 P02760 P02760 P10909 -
39.7 39.7 36.1 27.2 27.2 27.2 27.2 27.2 27.2 20.8 20.8 52.5 -
0.2 0.0 0.5 0.3 0.5 0.4 9.0 3.5 2.0 2.0 5.8 2.1 1.6c 2.0 2.1 3.7 2.4 3.2
/ 5.08 / 5.08 / 5.65
/ / / / / / / / /
6.32 6.32 6.32 6.32 6.32 6.32 6.13 6.13 5.89
Proteins were identified with the Mascot search engine using the SwissProt protein database. a Compute pI/Mw tool of ExPASy Proteomics Server [Uniprot Knowledgebase (http://www.expasy.org/sprot/)]. b Mean protein abundance in SSCs relative to that in controls from three independent experiments. c Although abundance of this spot was less than twice the abundance of the corresponding control spot, the spot in SSC gels was significantly increased compared with that in control gels (Student's t-test, p = 0.021, n = 3).
PON1 in plasma samples was individually analyzed by western blotting. One control sample (No. EN-C1) was always used as the standard sample. Immunopositive band intensities were determined using Quantity One (Bio-Rad Laboratories) and the intensities relative to the standard sample on each membrane were calculated.
et al., 2005). The PON1 level is known to be correlated with arylesterase activity, and PON1 activity significantly decreases with aging. For example, Marchegiani et al. reported that PON1 activity was decreased significantly in centenarians (90-104 years) compared with young (22-65 years) and elderly (66-89 years) controls
2.6. Statistics One-way ANOVA (SPSS software version 15.0 for Windows; SPSS Japan, Inc., Tokyo, Japan) was used for statistical analysis. Multiple comparisons were performed by the Tukey HSD method. For all cases, p b 0.05 was considered to indicate significance. 3. Results and Discussion To examine changes in the protein expression pattern of SSCs, a comparative 2D-PAGE study was performed on a mixture of 10 controls and a mixture of 10 SSCs, respectively. Three 2D-PAGE gels were run for both the control sample and the SSC sample. The spots in individual gels of the same group were fairly reproducible. Representative control and SSC gels are shown in Fig. 1A and B, respectively. The intensities of 18 spots (spots a-r) were found to differ between the controls and SSCs (Table 1). Spots a to f were less intense in SSCs, while spots g to r were more intense in SSCs. Using peptide mass fingerprinting, we were able to identify 12 of changed spots (Table 1). Paraoxonase/arylesterase 1 (PON1) and apolipoprotein E (apo E) were decreased, while haptoglobin β-chain, α1-microglobulin, and clusterin (CLU) precursor were increased in SSCs compared to controls. These results were confirmed by western blot. PON1 (Fig. 2A) and apo E were decreased, while CLU, α1microglobulin, and haptoglobin were increased in SSCs compared with controls (Supplementary Fig. S1). The levels of PON1 were determined by western blot. Single immunopositive bands were detected at about 45 kDa, which was predicted as the molecular weight of PON1 (Fig. 2A) (Mackness et al., 1998). In addition, the levels of PON1 in individuals tended to be lower in the SSCs than in the controls (Fig. 2B). The mean level in SSCs (0.39 ± 0.24 (mean ± SD)) was significantly lower than that in the controls (1.11 ± 0.40). PON1 is a high-density lipoprotein (HDL)bound arylesterase, which hydrolyzes lipoperoxides (Mackness et al., 1998) and protects against the development of atherosclerosis by preventing the oxidative modification of low-density lipoproteins (Ng
Fig. 2. Detection of PON1 in plasma of controls and SSCs. (A) Western blot analysis by anti-PON1 antibody. Western analysis was performed as described in Materials and methods. The migration of PON1 is indicated by an arrow. Lane C, controls; lane S, SSCs. Molecular mass markers are indicated on the left. (B) Correlation of PON1 levels with age. Each point represents the PON1 level in individual plasma determined by densitometry. Controls (closed circles); centenarians (closed diamonds); SSCs (closed triangles). Data was analyzed by one-way ANOVA (post-hoc Tukey HSD, p b 0.001, controls vs SSCs; p = 0.016, controls vs centenarians).
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(Marchegiani et al., 2006); therefore, in addition to SSCs, we analyzed PON1 levels of 10 individual centenarians (Fig. 2B). Our results demonstrated that PON1 levels of SSCs were as low as those of centenarians (mean relative amount, 0.68; SD, ± 0.32), suggesting that the risk of diseases related to oxidative stress, such as atherosclerosis, may not change when over 100 years old. Apo E was also reduced in SSCs compared with controls (mean age 27.5). We previously reported that plasma levels of apo E were not decreased in centenarians (Arai et al., 2001), but this might be because the age difference between the controls (mean age 63.1) and the centenarians was much less than the age difference in the present study. It is necessary to analyze more samples to confirm the reduction of apo E in SSCs. On the other hand, α1-microglobulin was elevated in SSCs by proteomic analyses. α1-Microglobulin, an ubiquitous plasma and tissue protein, was shown to be involved in the defense against cellfree hemoglobin and heme (Allhorn et al., 2002; Larsson et al., 2004), and to have radical-scavenging capacity (Akerstrom et al., 2007), reductase activity (Allhorn et al., 2005), and antioxidant properties (Olsson et al., 2008). The synthesis of α1-microglobulin is known to be up-regulated by cell-free hemoglobin and reactive oxygen species (ROS) (Olsson et al., 2007). The elevation of α1microglobulin in SSCs suggests increased levels of cell-free hemoglobin and/or ROS in SSCs. Haptoglobin was also elevated in SSCs. Since the synthesis of haptoglobin in the liver is induced by pro-inflammatory cytokines, such as IL-6 (Moshage, 1997), it is considered an inflammationsensitive protein, as is C-reactive protein (CRP). We reported previously that CRP was significantly elevated in centenarians due to enhanced inflammation (Arai et al., 2001). The levels of CRP were significantly elevated in SSCs (p = 0.026, Supplementary Fig. S2), as was found to be the case in centenarians (Arai et al., 2001). The tendency of haptoglobin elevation in SSCs also suggests the enhancement of inflammation in SSCs, similar to centenarians. Further, haptoglobin has hemoglobin-binding capacity and is involved in iron homeostasis (Sullivan, 2009; Van Vlierberghe et al., 2004) as well as α1-microglobulin. Taken together, these results suggest that the increased hemoglobin levels induce the elevation of haptoglobin and α1-microglobulin in the SSCs’ plasma. However, 2DPAGE analyses did not show hemoglobin as a significantly changed protein in SSCs. This suggests that the elevations of haptoglobin and α1-microglobulin in plasma of SSCs are due to oxidative stress rather than the increase of cell-free hemoglobin. Plasma haptoglobin might be elevated in order to reduce oxidative stress systemically. Finally, CLU was elevated in SSCs. CLU is synthesized as a CLU precursor that is posttranslationally cleaved into two subunits. These subunits, CLU-α and β are linked by disulfide bonds. CLU has been functionally implicated in several pathological conditions characterized by increased oxidative injury, such as aging, atherosclerosis, diabetes, and cancer progression (Trougakos and Gonos, 2006, 2009). Because the CLU gene is regulated by both a heat shock transcription factor-1 (HSF-1) and an activator protein-1 element (AP-1) that is activated by oxidative stress, CLU levels are a sensitive biosensor of ROS (Trougakos and Gonos, 2006, 2009). Therefore, the elevated CLU levels in SSCs suggest that SSCs have increased levels of ROS. In the present study, we performed proteomic analyses of SSC plasma proteins and demonstrated that four proteins associated with oxidative stress regulation, PON1, haptoglobin, α1-microglobulin, and clusterin, were altered in SSCs. This is of interest because the regulatory mechanism of oxidative stress is generally thought to be related to the aging process. These results suggest that systemic redox regulation is important for the longevity of SSCs. We have demonstrated that proteomics analysis is a powerful technique to search for useful biomarkers to study gerontology and to characterize individual proteins in the successful aging of SSCs. Our laboratory is currently collecting more SSC samples.
Supplementary materials related to this article can be found online at doi:10.1016/j.exger.2010.10.002. Acknowledgements We dedicate this manuscript to the life and career of Yuji Sato, who died on June 21, 2006. We thank Dr. Yoko Sugihara (TMIG) for her helpful advice on statistical analysis, and Shimadzu Biotech and Bio-Rad Laboratories for technical assistance with MALDI-TOF/MS and the analyses of gel images, respectively. We also thank Drs. Yasuyuki Gondo and Hiroki Inagaki for helpful discussions. This study was partly supported by a Grant-in-Aid for Scientific Research (B) (No. 20390031 to T.E.) from the Japan Society for the Promotion of Science, and partly by Mitsui Sumitomo Insurance Welfare Foundation (to Y.M.). References Akerstrom, B., Maghzal, G.J., Winterbourn, C.C., Kettle, A.J., 2007. The lipocalin α1microglobulin has radical scavenging activity. J. Biol. Chem. 282, 31493–31503. Allhorn, M., Berggard, T., Nordberg, J., Olsson, M.L., Akerstrom, B., 2002. Processing of the lipocalin α1-microglobulin by hemoglobin induces heme-binding and hemedegradation properties. Blood 99, 1894–1901. Allhorn, M., Klapyta, A., Akerstrom, B., 2005. Redox properties of the lipocalin α1microglobulin: reduction of cytochrome c, hemoglobin, and free iron. Free Radic. Biol. Med. 38, 557–567. Arai, Y., Hirose, N., Nakazawa, S., Yamamura, K., Shimizu, K., Takayama, M., Ebihara, Y., Osono, Y., Homma, S., 2001. Lipoprotein metabolism in Japanese centenarians: effects of apolipoprotein E polymorphism and nutritional status. J. Am. Geriatr. Soc. 49, 1434–1441. Arai, Y., Takayama, M., Gondo, Y., Inagaki, H., Yamamura, K., Nakazawa, S., Kojima, T., Ebihara, Y., Shimizu, K., Masui, Y., Kitagawa, K., Takebayashi, T., Hirose, N., 2008. Adipose endocrine function, insulin-like growth factor-1 axis, and exceptional survival beyond 100 years of age. J. Gerontol. A Biol. Sci. Med. Sci. 63, 1209–1218. Atzmon, G., Rincon, M., Schechter, C.B., Shuldiner, A.R., Lipton, R.B., Bergman, A., Barzilai, N., 2006. Lipoprotein genotype and conserved pathway for exceptional longevity in humans. PLoS Biol. 4, e113. Barzilai, N., Atzmon, G., Schechter, C., Schaefer, E.J., Cupples, A.L., Lipton, R., Cheng, S., Shuldiner, A.R., 2003. Unique lipoprotein phenotype and genotype associated with exceptional longevity. JAMA 290, 2030–2040. Berggard, T., Thelin, N., Falkenberg, C., Enghild, J.J., Akerstrom, B., 1997. Prothrombin, albumin and immunoglobulin A form covalent complexes with α1-microglobulin in human plasma. Eur. J. Biochem. 245, 676–683. Franceschi, C., Olivieri, F., Marchegiani, F., Cardelli, M., Cavallone, L., Capri, M., Salvioli, S., Valensin, S., De Benedictis, G., Di Iorio, A., Caruso, C., Paolisso, G., Monti, D., 2005. Genes involved in immune response/inflammation, IGF1/insulin pathway and response to oxidative stress play a major role in the genetics of human longevity: the lesson of centenarians. Mech. Ageing Dev. 126, 351–361. Hwang, H.J., Quinn, T., Zhang, J., 2009. Identification of glycoproteins in human cerebrospinal fluid. Meth. Mol. Biol. 566, 263–276. Kojima, T., Kamei, H., Aizu, T., Arai, Y., Takayama, M., Nakazawa, S., Ebihara, Y., Inagaki, H., Masui, Y., Gondo, Y., Sakaki, Y., Hirose, N., 2004. Association analysis between longevity in the Japanese population and polymorphic variants of genes involved in insulin and insulin-like growth factor 1 signaling pathways. Exp. Gerontol. 39, 1595–1598. Larsson, J., Allhorn, M., Kerstrom, B., 2004. The lipocalin α1-microglobulin binds heme in different species. Arch. Biochem. Biophys. 432, 196–204. Mackness, B., Durrington, P.N., Mackness, M.I., 1998. Human serum paraoxonase. Gen. Pharmacol. 31, 329–336. Marchegiani, F., Marra, M., Spazzafumo, L., James, R.W., Boemi, M., Olivieri, F., Cardelli, M., Cavallone, L., Bonfigli, A.R., Franceschi, C., 2006. Paraoxonase activity and genotype predispose to successful aging. J. Gerontol. A Biol. Sci. Med. Sci. 61, 541–546. Miura, Y., Kano, M., Abe, K., Urano, S., Suzuki, S., Toda, T., 2005. Age-dependent variations of cell response to oxidative stress: proteomic approach to protein expression and phosphorylation. Electrophoresis 26, 2786–2796. Moshage, H., 1997. Cytokines and the hepatic acute phase response. J. Pathol. 181, 257–266. Ng, C.J., Shih, D.M., Hama, S.Y., Villa, N., Navab, M., Reddy, S.T., 2005. The paraoxonase gene family and atherosclerosis. Free Radic. Biol. Med. 38, 153–163. Olsson, M.G., Allhorn, M., Olofsson, T., Akerstrom, B., 2007. Up-regulation of α1microglobulin by hemoglobin and reactive oxygen species in hepatoma and blood cell lines. Free Radic. Biol. Med. 42, 842–851. Olsson, M.G., Olofsson, T., Tapper, H., Akerstrom, B., 2008. The lipocalin α1microglobulin protects erythroid K562 cells against oxidative damage induced by heme and reactive oxygen species. Free Radic. Res. 42, 725–736. Sato, Y., Suzuki, Y., Ito, E., Shimazaki, S., Ishida, M., Yamamoto, T., Yamamoto, H., Toda, T., Suzuki, M., Suzuki, A., Endo, T., 2006. Identification and characterization of an increased glycoprotein in aging: age-associated translocation of cathepsin D. Mech. Ageing Dev. 127, 771–778.
Y. Miura et al. / Experimental Gerontology 46 (2011) 81–85 Schiffer, E., Mischak, H., Zimmerli, L.U., 2009. Proteomics in gerontology: current applications and future aspects–a mini-review. Gerontology 55, 123–137. Sebastiani, P., Montano, M., Puca, A., Solovieff, N., Kojima, T., Wang, M.C., Melista, E., Meltzer, M., Fischer, S.E.J., Andersen, S., Hartley, S.H., Sedgewick, A., Arai, Y., Bergman, A., Barzilai, N., Terry, D.F., Riva, A., Anselmi, C.V., Malovini, A., Kitamoto, A., Sawabe, M., Arai, T., Gondo, Y., Steinberg, M.H., Hirose, N., Atzmon, G., Ruvkun, G., Baldwin, C.T., Perls, T.T., 2009. RNA editing genes associated with extreme old age in humans and with lifespan in C. elegans. PLoS ONE 4, e8210. Sullivan, J.L., 2009. Iron in arterial plaque: modifiable risk factor for atherosclerosis. Biochim. Biophys. Acta 1790, 718–723. Sun, F., Cavalli, V., 2010. Neuroproteomics approaches to decipher neuronal regeneration and degeneration. Mol. Cell. Proteomics 9, 963–975.
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Trougakos, I.P., Gonos, E.S., 2006. Regulation of clusterin/apolipoprotein J, a functional homologue to the small heat shock proteins, by oxidative stress in ageing and agerelated diseases. Free Radic. Res. 40, 1324–1334. Trougakos, I.P., Gonos, E.S., 2009. Chapter 9: Oxidative stress in malignant progression: The role of Clusterin, a sensitive cellular biosensor of free radicals. Adv. Cancer Res. 104, 171–210. Van Vlierberghe, H., Langlois, M., Delanghe, J., 2004. Haptoglobin polymorphisms and iron homeostasis in health and in disease. Clin. Chim. Acta 345, 35–42. Vaupel, J.W., Carey, J.R., Christensen, K., Johnson, T.E., Yashin, A.I., Holm, N.V., Iachine, I.A., Kannisto, V., Khazaeli, A.A., Liedo, P., Longo, V.D., Zeng, Y., Manton, K.G., Curtsinger, J.W., 1998. Biodemographic trajectories of longevity. Science 280, 855–860.
Contents lists available at ScienceDirect
Experimental Gerontology j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / e x p g e r o
Short Report
Proteomic analysis of plasma proteins in Japanese semisuper centenarians Yuri Miura a, Yuji Sato a,1, Yasumichi Arai b, Yukiko Abe b, Michiyo Takayama b, Tosifusa Toda a, Nobuyoshi Hirose b, Tamao Endo a,⁎ a b
Research Team for Mechanism of Aging, Tokyo Metropolitan Institute of Gerontology, Tokyo 173-0015, Japan Department of Geriatric Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
a r t i c l e
i n f o
Article history: Received 27 May 2010 Received in revised form 22 September 2010 Accepted 6 October 2010 Available online 14 October 2010 Section Editor: R. Westendorp Keywords: Aging Semisuper centenarian Proteomics Oxidative stress Plasma proteins
a b s t r a c t We performed proteomic analysis of plasma proteins in Japanese semisuper centenarians (SSCs) (N 105 years) and young controls (20-39 years), and found that 18 protein spots were altered in the plasma of SSCs. From peptide mass fingerprinting following in-gel digestion, it was demonstrated that paraoxonase/arylesterase 1 (PON 1) and apolipoprotein E were decreased, while haptoglobin β-chain, α1-microglobulin, and clusterin precursor were increased in SSCs. Interestingly, proteins related to oxidative stress, PON1, haptoglobin, α1microglobulin, and clusterin, were altered in SSCs. These results suggest that systemic redox regulation is important for the longevity of SSCs. Overall, proteomics analysis is a powerful technique to search for useful biomarkers for future studies in gerontology and to characterize the individual proteins associated with successful aging of SSCs. © 2010 Elsevier Inc. All rights reserved.
1. Introduction Aging is a universal phenomenon. It can be considered as the product of interactions among genetic, environmental and lifestyle factors, which in turn influence longevity, a biological phenomenon which shows inter-individual variability. Recent progress in genome studies indicates that gene polymorphisms contribute to human longevity. These gene polymorphisms are thought to influence longevity through several potential mechanisms, including the immune system and the metabolic system (Atzmon et al., 2006; Barzilai et al., 2003; Franceschi et al., 2005; Kojima et al., 2004). It is likely that more genes involved in human aging remain to be discovered. Recently, RNA editing genes have been reported to be important regulators of aging in humans (Sebastiani et al., 2009). Taken together, whole genome association study of extreme old age, living to extreme old age, such as 100 years and older, is a powerful strategy to discover the genes associated with human longevity. Another strategy is to focus on the proteins being expressed in all human tissues and fluids. Proteins, such as enzymes, structural components, mediating and modulating cell adhesion and signaling components, etc., play important roles in many biological events. They
also influence longevity through their functions (Arai et al., 2008). However, such studies are limited. Technical advances over recent decades have allowed comprehensive analysis of the protein composition of biological samples, such as tissues, cells, organelles, and serum. Proteomic analysis offers great potential for studies of cellular and tissue protein alterations in various disease states and aging (Hwang et al., 2009; Schiffer et al., 2009; Sun and Cavalli, 2010). Exceptional longevity (100 years and older) is the fastest growing segment of the population in the world, and the increase results from a reduction in mortality rate. Since mortality rate in human was proposed to reach a plateau at age 105 (Vaupel et al., 1998), we assume that semisuper centenarians (SSCs; older than 105 years) are the best example of human longevity. SSCs probably escape many chronic and serious diseases, and are probably able to cope with a variety of stresses, including oxidative stress. Therefore, in the present study, we used SSCs as a model of human longevity. We performed proteomic analyses to look for differences in the plasma protein profiles of controls and SSCs. It is expected that this approach will lead to the discovery of proteins related to healthy aging. 2. Materials and Methods
⁎ Corresponding author. Research Team for Mechanism of Aging, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo, Japan. Tel.: +81 3 3964 3241; fax: +81 3 3579 4776. E-mail address: [email protected] (T. Endo). 1 Deceased. 0531-5565/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.exger.2010.10.002
2.1. Subjects Ten female SSCs (106-109 years, mean age 107.3 ± 1.0) and 10 female centenarians (100 years) were recruited to participate in this study. None were in an acute care situation, and none were receiving
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tube feeding. The past disease history of the SSCs was coronary artery disease, stroke, diabetes and cancer. The control subjects were 10 female healthy volunteers aged 20-39 years (mean age 27.5 ± 7.5) recruited from hospital and institutional workers. The control subjects were free from diseases and had no relevant history, such as coronary artery disease, stroke, diabetes and cancer. All subjects enrolled in this study were Japanese. Twenty milliliters of non-fasting venous blood was collected, and plasma was immediately separated by centrifugation at 4 °C and stored at -80 °C until subsequent assays. This study was approved by the ethics committees of both Tokyo Metropolitan Institute of Gerontology and Keio University School of Medicine. 2.2. Materials
Mascot search engine (Matrix Science, London, UK, see http://www. matrixscience.com) using the SwissProt protein database. Mascot search parameters were as follows: type of search, peptide mass fingerprinting; fixed modifications, carbamidomethyl (C); enzyme, trypsin; peptide mass tolerance, ± 0.2 Da; max missed cleavage, 1.
2.5. Western blot analysis Each mixture of controls and SSCs was desalted by acetone precipitation similar to the sample preparation of 2D-PAGE, and was separated by SDS-PAGE. Western blot analyses were performed as described previously (Miura et al., 2005) using specific antibodies.
Immobiline Drystrip pH 4-7 and Pharmalyte 3-10 were purchased from GE Healthcare (Buckinghamshire, UK). Dithiothreitol (DTT) and thiourea were purchased from Sigma-Aldrich (St. Louis, MO, USA). SYPRO-Ruby protein gel stain and Alexa Fluor 488-conjugated antirabbit IgG were purchased from Bio-Rad Laboratories (Hercules, CA, USA) and Invitrogen (Carlsbad, CA, USA), respectively. Affinitypurified anti-PON1 antibody was purchased from Japan Biotest (Tokyo, Japan). Anti-apolipoprotein E, anti-haptoglobin, anti-α1microglobulin, and anti-clusterin antibodies were purchased from Epitomics Inc. (Burlingame, CA, USA), DAKO Cytomation (Glostrup, Denmark), Abcam Co. (Cambridge, UK), and Santa Cruz Biotechnology (Santa Cruz, CA, USA), respectively. All other reagents were of the highest quality available. 2.3. Protein extraction and 2D-PAGE For 2D-PAGE analyses, we used mixed plasma samples, one for controls and one for SSCs. Each mixture was prepared from 2-μl samples from 10 individuals and desalted by acetone precipitation. The samples were mixed for two reasons, first because 2D electrophoresis analyses are laborious and time consuming and second because mixed samples would diminish individual differences but retain common characteristics in the group. Proteins of plasma mixtures were extracted by the addition of 4 ml extraction buffer (5 M urea, 2 M thiourea, 10 mM DTT, 2% Triton X-100, 1% Pharmalyte 3-10, 2.5 mM acetic acid, and 0.0025% Orange G). Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) was performed as previously described (Miura et al., 2005; Sato et al., 2006) (see also http://www.proteome.jp/2D/J_2DEmethod.html) with slight modifications. Three gels were run for each group. After separation on 2DPAGE, protein spots on the gel were fixed in 50% methanol and 10% acetic acid for 30 min, followed by staining with SYPRO-Ruby protein gel stain. The gels were scanned with a Molecular Imager® FX Pro (Bio-Rad Laboratories). The images were processed with PDQuest 2D image processing software (Bio-Rad Laboratories). Image processing consisted of noise reduction, background subtraction, spot detection, spot normalization, gel-to-gel matching, spot quantification, and differential-display analyses between controls and SSCs. The spot intensities were represented as parts per million (ppm) of the total spots integrated on each gel using “total quantity in valid spots” within PDQuest software. SSC spots whose intensities were either less than one-half or more than twice those of the controls were defined as changed proteins in SSCs. Additionally, spots in SSCs and controls that differed in intensity with p-values of 0.05 or less were also defined as changed proteins. 2.4. In-gel protein digestion and peptide mass fingerprinting In-gel digestion of selected gel spots was performed as described previously (Miura et al., 2005). Peptide mass fingerprinting was acquired using a MALDI-TOF/MS spectrometer (AXIMA-CFR; Shimadzu Biotech, Kyoto, Japan). Proteins were identified with the
Fig. 1. Protein profiles of 2D-PAGE of controls (A) and SSCs (B). 2D-PAGE was performed with isoelectric focusing (pI 4-7) in the first dimension and SDS-PAGE in the second dimension followed by SYPRO-Ruby staining, as described in Materials and methods. Circles indicate protein spots, the expression levels of which were decreased (A) or increased (B) in SSCs. Vertical axes are designated as molecular mass (kDa) and horizontal axes as pI.
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Table 1 Identification of protein spots in Fig. 1. Spot
Protein
UniProt knowledgebase accesion No.
Theoretical value mass (kDa)/pIa
Fold changeb
a b c d e f g h i j k l m n o p q r
Paraoxonase / arylesterase 1 (PON1) Paraoxonase / arylesterase 1 (PON1) Apolipoprotein E Not identified Not identified Not identified Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain Haptoglobin β chain α1-Microglobulin α1-Microglobulin Clusterin precursor Not identified Not identified Not identified
P27169 P27169 P02649 P00738 P00738 P00738 P00738 P00738 P00738 P02760 P02760 P10909 -
39.7 39.7 36.1 27.2 27.2 27.2 27.2 27.2 27.2 20.8 20.8 52.5 -
0.2 0.0 0.5 0.3 0.5 0.4 9.0 3.5 2.0 2.0 5.8 2.1 1.6c 2.0 2.1 3.7 2.4 3.2
/ 5.08 / 5.08 / 5.65
/ / / / / / / / /
6.32 6.32 6.32 6.32 6.32 6.32 6.13 6.13 5.89
Proteins were identified with the Mascot search engine using the SwissProt protein database. a Compute pI/Mw tool of ExPASy Proteomics Server [Uniprot Knowledgebase (http://www.expasy.org/sprot/)]. b Mean protein abundance in SSCs relative to that in controls from three independent experiments. c Although abundance of this spot was less than twice the abundance of the corresponding control spot, the spot in SSC gels was significantly increased compared with that in control gels (Student's t-test, p = 0.021, n = 3).
PON1 in plasma samples was individually analyzed by western blotting. One control sample (No. EN-C1) was always used as the standard sample. Immunopositive band intensities were determined using Quantity One (Bio-Rad Laboratories) and the intensities relative to the standard sample on each membrane were calculated.
et al., 2005). The PON1 level is known to be correlated with arylesterase activity, and PON1 activity significantly decreases with aging. For example, Marchegiani et al. reported that PON1 activity was decreased significantly in centenarians (90-104 years) compared with young (22-65 years) and elderly (66-89 years) controls
2.6. Statistics One-way ANOVA (SPSS software version 15.0 for Windows; SPSS Japan, Inc., Tokyo, Japan) was used for statistical analysis. Multiple comparisons were performed by the Tukey HSD method. For all cases, p b 0.05 was considered to indicate significance. 3. Results and Discussion To examine changes in the protein expression pattern of SSCs, a comparative 2D-PAGE study was performed on a mixture of 10 controls and a mixture of 10 SSCs, respectively. Three 2D-PAGE gels were run for both the control sample and the SSC sample. The spots in individual gels of the same group were fairly reproducible. Representative control and SSC gels are shown in Fig. 1A and B, respectively. The intensities of 18 spots (spots a-r) were found to differ between the controls and SSCs (Table 1). Spots a to f were less intense in SSCs, while spots g to r were more intense in SSCs. Using peptide mass fingerprinting, we were able to identify 12 of changed spots (Table 1). Paraoxonase/arylesterase 1 (PON1) and apolipoprotein E (apo E) were decreased, while haptoglobin β-chain, α1-microglobulin, and clusterin (CLU) precursor were increased in SSCs compared to controls. These results were confirmed by western blot. PON1 (Fig. 2A) and apo E were decreased, while CLU, α1microglobulin, and haptoglobin were increased in SSCs compared with controls (Supplementary Fig. S1). The levels of PON1 were determined by western blot. Single immunopositive bands were detected at about 45 kDa, which was predicted as the molecular weight of PON1 (Fig. 2A) (Mackness et al., 1998). In addition, the levels of PON1 in individuals tended to be lower in the SSCs than in the controls (Fig. 2B). The mean level in SSCs (0.39 ± 0.24 (mean ± SD)) was significantly lower than that in the controls (1.11 ± 0.40). PON1 is a high-density lipoprotein (HDL)bound arylesterase, which hydrolyzes lipoperoxides (Mackness et al., 1998) and protects against the development of atherosclerosis by preventing the oxidative modification of low-density lipoproteins (Ng
Fig. 2. Detection of PON1 in plasma of controls and SSCs. (A) Western blot analysis by anti-PON1 antibody. Western analysis was performed as described in Materials and methods. The migration of PON1 is indicated by an arrow. Lane C, controls; lane S, SSCs. Molecular mass markers are indicated on the left. (B) Correlation of PON1 levels with age. Each point represents the PON1 level in individual plasma determined by densitometry. Controls (closed circles); centenarians (closed diamonds); SSCs (closed triangles). Data was analyzed by one-way ANOVA (post-hoc Tukey HSD, p b 0.001, controls vs SSCs; p = 0.016, controls vs centenarians).
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(Marchegiani et al., 2006); therefore, in addition to SSCs, we analyzed PON1 levels of 10 individual centenarians (Fig. 2B). Our results demonstrated that PON1 levels of SSCs were as low as those of centenarians (mean relative amount, 0.68; SD, ± 0.32), suggesting that the risk of diseases related to oxidative stress, such as atherosclerosis, may not change when over 100 years old. Apo E was also reduced in SSCs compared with controls (mean age 27.5). We previously reported that plasma levels of apo E were not decreased in centenarians (Arai et al., 2001), but this might be because the age difference between the controls (mean age 63.1) and the centenarians was much less than the age difference in the present study. It is necessary to analyze more samples to confirm the reduction of apo E in SSCs. On the other hand, α1-microglobulin was elevated in SSCs by proteomic analyses. α1-Microglobulin, an ubiquitous plasma and tissue protein, was shown to be involved in the defense against cellfree hemoglobin and heme (Allhorn et al., 2002; Larsson et al., 2004), and to have radical-scavenging capacity (Akerstrom et al., 2007), reductase activity (Allhorn et al., 2005), and antioxidant properties (Olsson et al., 2008). The synthesis of α1-microglobulin is known to be up-regulated by cell-free hemoglobin and reactive oxygen species (ROS) (Olsson et al., 2007). The elevation of α1microglobulin in SSCs suggests increased levels of cell-free hemoglobin and/or ROS in SSCs. Haptoglobin was also elevated in SSCs. Since the synthesis of haptoglobin in the liver is induced by pro-inflammatory cytokines, such as IL-6 (Moshage, 1997), it is considered an inflammationsensitive protein, as is C-reactive protein (CRP). We reported previously that CRP was significantly elevated in centenarians due to enhanced inflammation (Arai et al., 2001). The levels of CRP were significantly elevated in SSCs (p = 0.026, Supplementary Fig. S2), as was found to be the case in centenarians (Arai et al., 2001). The tendency of haptoglobin elevation in SSCs also suggests the enhancement of inflammation in SSCs, similar to centenarians. Further, haptoglobin has hemoglobin-binding capacity and is involved in iron homeostasis (Sullivan, 2009; Van Vlierberghe et al., 2004) as well as α1-microglobulin. Taken together, these results suggest that the increased hemoglobin levels induce the elevation of haptoglobin and α1-microglobulin in the SSCs’ plasma. However, 2DPAGE analyses did not show hemoglobin as a significantly changed protein in SSCs. This suggests that the elevations of haptoglobin and α1-microglobulin in plasma of SSCs are due to oxidative stress rather than the increase of cell-free hemoglobin. Plasma haptoglobin might be elevated in order to reduce oxidative stress systemically. Finally, CLU was elevated in SSCs. CLU is synthesized as a CLU precursor that is posttranslationally cleaved into two subunits. These subunits, CLU-α and β are linked by disulfide bonds. CLU has been functionally implicated in several pathological conditions characterized by increased oxidative injury, such as aging, atherosclerosis, diabetes, and cancer progression (Trougakos and Gonos, 2006, 2009). Because the CLU gene is regulated by both a heat shock transcription factor-1 (HSF-1) and an activator protein-1 element (AP-1) that is activated by oxidative stress, CLU levels are a sensitive biosensor of ROS (Trougakos and Gonos, 2006, 2009). Therefore, the elevated CLU levels in SSCs suggest that SSCs have increased levels of ROS. In the present study, we performed proteomic analyses of SSC plasma proteins and demonstrated that four proteins associated with oxidative stress regulation, PON1, haptoglobin, α1-microglobulin, and clusterin, were altered in SSCs. This is of interest because the regulatory mechanism of oxidative stress is generally thought to be related to the aging process. These results suggest that systemic redox regulation is important for the longevity of SSCs. We have demonstrated that proteomics analysis is a powerful technique to search for useful biomarkers to study gerontology and to characterize individual proteins in the successful aging of SSCs. Our laboratory is currently collecting more SSC samples.
Supplementary materials related to this article can be found online at doi:10.1016/j.exger.2010.10.002. Acknowledgements We dedicate this manuscript to the life and career of Yuji Sato, who died on June 21, 2006. We thank Dr. Yoko Sugihara (TMIG) for her helpful advice on statistical analysis, and Shimadzu Biotech and Bio-Rad Laboratories for technical assistance with MALDI-TOF/MS and the analyses of gel images, respectively. We also thank Drs. Yasuyuki Gondo and Hiroki Inagaki for helpful discussions. This study was partly supported by a Grant-in-Aid for Scientific Research (B) (No. 20390031 to T.E.) from the Japan Society for the Promotion of Science, and partly by Mitsui Sumitomo Insurance Welfare Foundation (to Y.M.). References Akerstrom, B., Maghzal, G.J., Winterbourn, C.C., Kettle, A.J., 2007. The lipocalin α1microglobulin has radical scavenging activity. J. Biol. Chem. 282, 31493–31503. Allhorn, M., Berggard, T., Nordberg, J., Olsson, M.L., Akerstrom, B., 2002. Processing of the lipocalin α1-microglobulin by hemoglobin induces heme-binding and hemedegradation properties. Blood 99, 1894–1901. Allhorn, M., Klapyta, A., Akerstrom, B., 2005. Redox properties of the lipocalin α1microglobulin: reduction of cytochrome c, hemoglobin, and free iron. Free Radic. Biol. Med. 38, 557–567. Arai, Y., Hirose, N., Nakazawa, S., Yamamura, K., Shimizu, K., Takayama, M., Ebihara, Y., Osono, Y., Homma, S., 2001. Lipoprotein metabolism in Japanese centenarians: effects of apolipoprotein E polymorphism and nutritional status. J. Am. Geriatr. Soc. 49, 1434–1441. Arai, Y., Takayama, M., Gondo, Y., Inagaki, H., Yamamura, K., Nakazawa, S., Kojima, T., Ebihara, Y., Shimizu, K., Masui, Y., Kitagawa, K., Takebayashi, T., Hirose, N., 2008. Adipose endocrine function, insulin-like growth factor-1 axis, and exceptional survival beyond 100 years of age. J. Gerontol. A Biol. Sci. Med. Sci. 63, 1209–1218. Atzmon, G., Rincon, M., Schechter, C.B., Shuldiner, A.R., Lipton, R.B., Bergman, A., Barzilai, N., 2006. Lipoprotein genotype and conserved pathway for exceptional longevity in humans. PLoS Biol. 4, e113. Barzilai, N., Atzmon, G., Schechter, C., Schaefer, E.J., Cupples, A.L., Lipton, R., Cheng, S., Shuldiner, A.R., 2003. Unique lipoprotein phenotype and genotype associated with exceptional longevity. JAMA 290, 2030–2040. Berggard, T., Thelin, N., Falkenberg, C., Enghild, J.J., Akerstrom, B., 1997. Prothrombin, albumin and immunoglobulin A form covalent complexes with α1-microglobulin in human plasma. Eur. J. Biochem. 245, 676–683. Franceschi, C., Olivieri, F., Marchegiani, F., Cardelli, M., Cavallone, L., Capri, M., Salvioli, S., Valensin, S., De Benedictis, G., Di Iorio, A., Caruso, C., Paolisso, G., Monti, D., 2005. Genes involved in immune response/inflammation, IGF1/insulin pathway and response to oxidative stress play a major role in the genetics of human longevity: the lesson of centenarians. Mech. Ageing Dev. 126, 351–361. Hwang, H.J., Quinn, T., Zhang, J., 2009. Identification of glycoproteins in human cerebrospinal fluid. Meth. Mol. Biol. 566, 263–276. Kojima, T., Kamei, H., Aizu, T., Arai, Y., Takayama, M., Nakazawa, S., Ebihara, Y., Inagaki, H., Masui, Y., Gondo, Y., Sakaki, Y., Hirose, N., 2004. Association analysis between longevity in the Japanese population and polymorphic variants of genes involved in insulin and insulin-like growth factor 1 signaling pathways. Exp. Gerontol. 39, 1595–1598. Larsson, J., Allhorn, M., Kerstrom, B., 2004. The lipocalin α1-microglobulin binds heme in different species. Arch. Biochem. Biophys. 432, 196–204. Mackness, B., Durrington, P.N., Mackness, M.I., 1998. Human serum paraoxonase. Gen. Pharmacol. 31, 329–336. Marchegiani, F., Marra, M., Spazzafumo, L., James, R.W., Boemi, M., Olivieri, F., Cardelli, M., Cavallone, L., Bonfigli, A.R., Franceschi, C., 2006. Paraoxonase activity and genotype predispose to successful aging. J. Gerontol. A Biol. Sci. Med. Sci. 61, 541–546. Miura, Y., Kano, M., Abe, K., Urano, S., Suzuki, S., Toda, T., 2005. Age-dependent variations of cell response to oxidative stress: proteomic approach to protein expression and phosphorylation. Electrophoresis 26, 2786–2796. Moshage, H., 1997. Cytokines and the hepatic acute phase response. J. Pathol. 181, 257–266. Ng, C.J., Shih, D.M., Hama, S.Y., Villa, N., Navab, M., Reddy, S.T., 2005. The paraoxonase gene family and atherosclerosis. Free Radic. Biol. Med. 38, 153–163. Olsson, M.G., Allhorn, M., Olofsson, T., Akerstrom, B., 2007. Up-regulation of α1microglobulin by hemoglobin and reactive oxygen species in hepatoma and blood cell lines. Free Radic. Biol. Med. 42, 842–851. Olsson, M.G., Olofsson, T., Tapper, H., Akerstrom, B., 2008. The lipocalin α1microglobulin protects erythroid K562 cells against oxidative damage induced by heme and reactive oxygen species. Free Radic. Res. 42, 725–736. Sato, Y., Suzuki, Y., Ito, E., Shimazaki, S., Ishida, M., Yamamoto, T., Yamamoto, H., Toda, T., Suzuki, M., Suzuki, A., Endo, T., 2006. Identification and characterization of an increased glycoprotein in aging: age-associated translocation of cathepsin D. Mech. Ageing Dev. 127, 771–778.
Y. Miura et al. / Experimental Gerontology 46 (2011) 81–85 Schiffer, E., Mischak, H., Zimmerli, L.U., 2009. Proteomics in gerontology: current applications and future aspects–a mini-review. Gerontology 55, 123–137. Sebastiani, P., Montano, M., Puca, A., Solovieff, N., Kojima, T., Wang, M.C., Melista, E., Meltzer, M., Fischer, S.E.J., Andersen, S., Hartley, S.H., Sedgewick, A., Arai, Y., Bergman, A., Barzilai, N., Terry, D.F., Riva, A., Anselmi, C.V., Malovini, A., Kitamoto, A., Sawabe, M., Arai, T., Gondo, Y., Steinberg, M.H., Hirose, N., Atzmon, G., Ruvkun, G., Baldwin, C.T., Perls, T.T., 2009. RNA editing genes associated with extreme old age in humans and with lifespan in C. elegans. PLoS ONE 4, e8210. Sullivan, J.L., 2009. Iron in arterial plaque: modifiable risk factor for atherosclerosis. Biochim. Biophys. Acta 1790, 718–723. Sun, F., Cavalli, V., 2010. Neuroproteomics approaches to decipher neuronal regeneration and degeneration. Mol. Cell. Proteomics 9, 963–975.
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Trougakos, I.P., Gonos, E.S., 2006. Regulation of clusterin/apolipoprotein J, a functional homologue to the small heat shock proteins, by oxidative stress in ageing and agerelated diseases. Free Radic. Res. 40, 1324–1334. Trougakos, I.P., Gonos, E.S., 2009. Chapter 9: Oxidative stress in malignant progression: The role of Clusterin, a sensitive cellular biosensor of free radicals. Adv. Cancer Res. 104, 171–210. Van Vlierberghe, H., Langlois, M., Delanghe, J., 2004. Haptoglobin polymorphisms and iron homeostasis in health and in disease. Clin. Chim. Acta 345, 35–42. Vaupel, J.W., Carey, J.R., Christensen, K., Johnson, T.E., Yashin, A.I., Holm, N.V., Iachine, I.A., Kannisto, V., Khazaeli, A.A., Liedo, P., Longo, V.D., Zeng, Y., Manton, K.G., Curtsinger, J.W., 1998. Biodemographic trajectories of longevity. Science 280, 855–860.