Coordinated Changes in Xenobiotic Metabolizing ... - Oxford Academic

TOXICOLOGICAL SCIENCES 106(1), 263–283 (2008) doi:10.1093/toxsci/kfn144 Advance Access publication July 24, 2008

Coordinated Changes in Xenobiotic Metabolizing Enzyme Gene Expression in Aging Male Rats Janice S. Lee,* William O. Ward,* Douglas C. Wolf,* James W. Allen,* Camilla Mills,† Michael J. DeVito,* and J. Christopher Corton*,‡,1 *NHEERL/ORD, US EPA, Research Triangle Park, North Carolina 27711; †North Carolina Central University, Durham, North Carolina 27707; and ‡NHEERL Toxicogenomics Core, US EPA, Research Triangle Park, North Carolina 27711 Received April 25, 2008; accepted July 11, 2008

In order to gain insight into the effects of aging on susceptibility to environmental toxins, we characterized the expression of xenobiotic metabolizing enzymes (XMEs) from the livers of male F344 and Brown Norway (BN) rats across the adult lifespan. Using full-genome Affymetrix arrays, principal component analysis showed a clear age-dependent separation between young and old animals in both rat strains. Out of 1135 or 1435 genes altered between the old and young groups in the F344 or BN rats, 7 or 3% were XMEs and included members of the phase I, II, and III classes of genes. There was a 20 or 32% overlap in the gene expression profile between the two strains for F344 or BN, respectively. Lipid, ergosterol, alcohol, and fatty acid metabolism genes were also altered with age in both strains. Some of the genes altered by age exhibited a gender-dependent expression pattern in young adult rats, suggesting an increasingly feminized pattern of gene expression with age in male rats. To examine transcriptional responses across lifespan after challenge with a xenobiotic compound, BN rats were exposed to toluene by oral gavage. Toluene exposure decreased the expression of glutathione synthetase, and dramatically increased the number of phase III genes being downregulated. The expression of CYP2B2 and glutathione-S-transferase decreased with age but increased in all age groups after toluene exposure. Decreased ability to detoxify and transport chemicals out of the body with age could result in increased susceptibility to some classes of chemicals in the aging population. Key Words: xenobiotic metabolism; aging; liver; gene expression; susceptibility; microarrays.

Disclaimer: It has been subjected to review by the National Health and Environmental Effects Research Laboratory and approved for publication. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. 1 To whom correspondence should be addressed at Chris Corton, Environmental Carcinogenesis Division, National Health and Environmental Effects Research Laboratory, US Environmental Protection Agency, 109 T.W. Alexander Dr., MD-B143-06, Research Triangle Park, NC 27711. Fax: (919) 541-0694. E-mail: [email protected].

In the United States, more than 12% of the population is over the age of 65, and estimates indicate that this percentage will increase to nearly 20% by the year 2030 (He et al., 2005). Exposures to environmental toxicants in older adults may be similar to those experienced by the general population, but there are a number of pharmacokinetic changes associated with aging that may increase susceptibility in this segment of the population (Geller and Zenick, 2005). This paper examines genomic indicators of changes in hepatic xenobiotic metabolizing enzymes (XMEs) in two strains of rats as a step toward defining potential mediators of susceptibility and identifying specific environmental compounds targeted by those XMEs. The increased sensitivity of older adults to drugs is well known and a product of both pharmacokinetic and pharmacodynamic changes with aging (McLean and Le Couteur, 2004). Slower elimination of drugs in older adults compared with younger adults has been clearly demonstrated, and age-related differences in drug and toxicant responsiveness have been shown to be due to altered absorption, distribution, metabolism, and excretion (ADME) (Kinirons and O’Mahony, 2004). Many factors have been suggested as causes of age-dependent changes such as decreased blood flow to the liver, decreased liver mass, and decreased content of specific cytochrome P450s (CYPs), the combination of which could result in decreased hepatic clearance of chemicals in older adults (Ginsberg et al., 2005). For example, decreases in the metabolism of analgesics and anti-inflammatory, cardiovascular, and psychoactive drugs are due in part to a 30–40% decrease in drug clearance (Gurwitz, 2005). In addition to alterations in drug metabolism, some segments of the aging population may also be more sensitive to environmentally relevant chemicals compared with younger adults or children because of alterations in pharmacokinetic parameters (Birnbaum, 1991). Detoxification and elimination of xenobiotics are major functions of the liver and are important in maintaining metabolic homeostasis. Xenobiotics are metabolized by a large number of XMEs which fall into three broad categories. Phase I enzymes are mainly monooxygenases that convert hydrophobic xenobiotics into hydrophilic molecules and include

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CYP family members, alcohol and aldehyde dehydrogenases, and amine oxidases. Phase II enzymes convert the products of phase I metabolism into amphiphilic anionic conjugates that are water soluble and include glutathione transferases, uridine diphosphate-glucuronosyltransferases, and sulfotransferases. Phase III transporters export conjugated xenobiotics out of the liver and include ATP-binding cassette subfamily members, organic anion and cation transporters, and solute carriers (Francis et al., 2003). A large number of genetic and biochemical studies have shown that expression and activity of individual XMEs in part determines the metabolic fate and toxicity of xenobiotics (Bleasby et al., 2006; Kohle and Bock, 2007). Expression of many XMEs in mammals is regulated by a set of ligand-activated transcription factors (TFs). These include the nuclear receptors constitutive androstane/activated receptor (CAR), pregnane X receptor (PXR), and to a lesser extent, the peroxisome proliferator–activated receptor (PPAR-a). Overlapping sets of XMEs are also regulated by other TFs including the aryl hydrocarbon receptor (AhR) and the nuclear factor erythroid 2 p45–related factor (Nrf2), which contain helix-loop-helix-per/arnt/sim and cap-N-collar DNA binding domains, respectively. AhR regulates the expression of CYP1A1/2, CYP1B1, UGT1A1/6, and ABCG2 (Nakata et al., 2006). CAR activation increases the expression of CYP2A6, CYP2B1/6, CYP2C9/19, UGT1A1, ABCC2/3/4 (Nakata et al., 2006). Nrf2 regulates the expression of Phase II enzymes (cGCS, GST, NQO1, UGT, HO-1) and Phase III transporters (ABCC2/3) (Nakata et al., 2006). PPAR-a mainly regulates the expression of fatty acid metabolizing enzymes, CYP4A1 and CYP4A3, as well as UGT1A9, UGT2B4, ABCA1, ABCC2, and ABCD2/3 (Nakata et al., 2006). PXR is a key regulator of CYP3A4, responsible for metabolism and clearance of over 50% of clinically prescribed drugs (Guengerich, 1999). PXR also regulates a large number of Phase I (CYP1A2, CYP2B6, CYP2C9/19, CYP3A7, CYP7A1), Phase II (SULT2A1, UGT1A1/3/4), and Phase III (ABCA1, ABCB1/11, ABCC1/2/3, ABCG2) genes. The network of genes under control of these factors can also include those that determine hepatocyte fate. For the AhR, PPAR-a, and CAR there is a clear relationship between activation of the receptor by a wide variety of environmental chemicals and the induction of liver cancer through increases in oxidative stress and alteration in hepatocyte fate (Klaunig et al., 2003; Walisser et al., 2005; Yamazaki et al., 2005). Constitutive expression of many XMEs is determined by the gender-dependent pattern of growth hormone (GH) secretion (Waxman and O’Connor, 2006). GH regulates transcription of gender-dependent CYP genes, including members of the CYP2A, CYP2C, and CYP3A families. Up to 500-fold differences between males and females in CYP expression have been observed in rats and mice. Differences between genders were observed in human samples, but the magnitudes were much smaller (Waxman and O’Connor, 2006). A number of specific

XMEs have been investigated for gender differences in rats including CYP2C11, which is strongly induced at puberty in male but not female rat liver, and CYP2C12 which is only expressed in the female rat liver. In addition to CYP family members, sulfotransferases (Klaassen et al., 1998) and glutathione-S-transferases (Srivastava and Waxman, 1993) are also sex-dependent and regulated by GH. The relationship between the expression of XMEs, age and gender-specificity has not been comprehensively examined. Age-associated changes in gene expression of XMEs in the liver have been found in both rats and humans. In the aged male rat liver, the gene expression of CYP2C7, CYP2J3, and CYP3A1 increased by 13-, 4-, and 4-fold, respectively (Thomas et al., 2002). In their comparison between 32- and 84-week-old F344 rats, Mori et al. (2007) determined changes in the transcript profiles of the liver and found that 21 phase I and 13 phase II enzymes exhibited age-dependent differences in expression. They did not report changes in phase III genes. In the aged human liver, CYP1A1, CYP1A2, and CYP2C18 increased by nine-, five-, and threefold, respectively (Thomas et al., 2002). Further information is necessary to determine the global changes in expression of XMEs with age in the rodent liver. There is some evidence that age impacts the metabolism and toxicity of aromatic hydrocarbons (Sukhodub and Padalko, 1999) such as toluene. Toluene is produced in the process of making gasoline and other fuels from crude oil and making coke from coal. It is widely used in commercial and industrial applications, is a solvent in paints, lacquers, thinners, glues, and nail polish remover, and is used in printing and leather tanning processes. The main route of human exposure is inhalation of vapor, but exposure can also occur by ingesting the liquid or via skin contact. Toluene depresses neuronal activity and reversibly enhances gamma-aminobutyric acid A receptormediated synaptic currents and 1-glycine receptor-activated ion channel function (Beckstead et al., 2000). Toluene also inhibits glutamatergic neurotransmission via N-methyl D-aspartate receptors and alters dopaminergic transmission (Cruz et al., 1998). This chemical is well-absorbed following oral ingestion and rapidly absorbed following inhalation. High concentrations are found in the liver, kidney, brain and blood. Toluene cannot exit the body via urine, feces or sweat because of its low water solubility, and therefore it must be metabolized for excretion. Ninety five percent of toluene is metabolized to benzyl alcohol by CYP2E1 and the rest is metabolized to benzaldehyde, o-cresol, and p-cresol by CYP2B6, CYP2C8, and CYP1A1/2 (Chapman et al., 1990; Hanioka et al., 1995; Nakajima et al., 1997). Benzyl alcohol is further oxidized by the sequential action of alcohol dehydrogenase and aldehyde dehydrogenase to produce benzaldehyde and then benzoic acid (Antti-Poika et al., 1987). Although most toluene metabolites are detoxified by conjugation to glutathione, those remaining may severely damage cells (van Doorn et al., 1981). There is no information about the effects of age in determining the transcriptional changes upon toluene exposure.

COORDINATED CHANGES IN XENOBIOTIC METABOLIZING ENZYME GENE EXPRESSION

Despite the understanding of the biological mechanisms of aging and interventions that slow aging, remarkably little is known about the risks to older adults from exposure to toxic chemicals in the environment. The present study was designed to identify age-dependent differences in hepatic expression of phase I, II, and III xenobiotic metabolizing genes in F344 and Brown Norway (BN) rats. We also determined if these agedependent differences affected toluene-induced changes in hepatic gene expression. MATERIALS AND METHODS Animals and study design. Male F344 rats were obtained from Charles River Laboratory and acclimated for 1 week. Control animals at 6, 11, 18, and 24 months of age were sacrificed using CO2 asphyxiation. Livers were removed and weighed, and sections from the left and median lobes were fixed in formalin, embedded, sectioned, and stained with H&E. The remainder of the liver was cubed and stored at 80C until RNA isolation. Male BN rats (4, 12, and 24 months old) (Harlan Laboratory and the National Institute of Aging) were acclimated for one week. Six animals per age and dose group were administered 1.0 g/kg body weight toluene by gavage (Burdick and Jackson Chemical, Muskegon, MI) in corn oil (4 ml/kg body weight) or corn oil alone. The animals were necropsied 4 h after dosing. Livers were removed and weighed, and sections from the left and median lobes were fixed in formalin. The remainder of the liver was cubed and stored at 80C until RNA isolation. Necropsies started in the morning and were completed within a 3- to 4-h time window. Details of the effects of toluene exposure including toxicity will be published in separate manuscripts. All aspects of these studies were conducted in compliance with the guidelines of the Association for Assessment and Accreditation of Laboratory Animal CareInternational and approved by the United States Environmental Protection Agency/National Health and Environmental Effects Research Laboratory Institutional Animal Care and Use Committee. RNA isolation. Liver tissue for RNA isolation was selected based on minimal histological findings to eliminate incidental changes in gene expression unrelated to hepatocyte aging. Total RNA was isolated from rat livers according to the TriReagent procedure (Molecular Research Center, Cincinnati, OH) and purified using the Qiagen RNeasy mini RNA cleanup protocol (Qiagen, Valencia, CA). The integrity of each RNA sample was determined using an Agilent 2100 Bioanalyzer (Agilent, Foster City, CA), and RNA quantity was determined using a Nanodrop ND-1000 (Thermo Fisher Scientific, Wilmington, DE). Microarray hybridizations. Liver gene expression analysis was performed according to the Affymetrix recommended protocol using Affymetrix Rat Genome 230 2.0 GeneChips containing probes for over 28,000 well-annotated genes. Total RNA (5 lg per sample) was labeled using the Affymetrix One-Cycle cDNA Synthesis protocol and hybridized to Affymetrix Rat 230 2.0 arrays as described by the manufacturer (Affymetrix, Santa Clara, CA). The cRNA hybridization cocktail was incubated overnight at 45C while rotating in a hybridization oven. After 16 h of hybridization, the cocktail was removed and the arrays were washed and stained in an Affymetrix GeneChip fluidics station 450 according to the Affymetrixrecommended protocol. Arrays were scanned on an Affymetrix GeneChip scanner. Four F344 and three BN rats per age/dose group were examined. A detailed description of the microarray experiment is available through Gene Expression Omnibus at the National Center for Biotechnology Information at http:// www.ncbi.nlm.nih.gov/geo/, as accession number GSE11097. Analyses of microarray data. Differentially expressed genes (DEGs) were identified using the following algorithm: background correction was performed using MAS 5.0 followed by a quantile normalization (robust multiarray analysis [RMA]), perfect match adjustment (MAS 5.0), median polish (RMA),

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LOESS normalization and Cyber-T statistics. This algorithm was adapted from Choe et al. (2005) because these procedures detect DEGs while minimizing the false discovery rate (FDR). A Benjamini–Hochberg multiple test correction (MTC) with p-value 0.05 was applied during a global analysis of F344 rats. A fold change of ± 1.5 and a p-value 0.05 was used as the cutoff. Hierarchical clustering was performed using CLUSTER and visualized with TREEVIEW (Eisen et al., 1998). The genes altered by aging in the present study were compared with those that are differentially expressed between male and female rats identified in a recent study examining baseline gene expression in the liver (Boedigheimer et al., 2008). Pathway and global function analyses were performed using Ingenuity (Mountain View, CA) and GATHER (Gene Annotation Tool to Help Explain Relationships) (Chang and Nevins, 2006). Gene Set Enrichment Analysis (GSEA; http://www.broad.mit.edu/gsea/) was used to evaluate whether a predefined set of genes shows statistically significant, concordant differences between two biological states (Subramanian et al., 2005). Expression profiles for combined young and old F344 and BN rats were submitted to GSEA using default settings and searched for enriched gene sets among C2 and C3 gene sets. Gene set C2 (curated gene sets) includes genes from online pathway databases, publications in PubMed, and knowledge from domain experts. Gene set C3 (motif gene sets) contains genes that share a TF binding site defined in TRANSFAC, a database for TFs and their genomic binding sites. TF analyses were run using Bibliosphere in Genomatix (Munich, Germany) to identify enriched binding sites in the promoters of genes significantly altered in our studies. Real-time polymerase chain reaction. Confirmation of gene expression was performed using the TaqMan procedure (Applied Biosystems, Foster City, CA). Nine XME genes were examined to confirm microarray results in F344 control rats, and five XME genes were examined to confirm results in the BN control and treated animals. Table 1 lists the TaqMan primers used. RNA was reverse transcribed into first-strand cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the AB protocol. RNA and 2X RT master mix containing random primers, dNTP mixture, and Multiscribe RT enzyme were placed in individual tubes. Tubes were incubated for 10 min at 25C, 120 min at 37C, and 85C for 5 s in a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA). cDNA template and PCR Reaction Mix containing TaqMan Gene Expression Assay (203) and TaqMan 23 Universal PCR Master Mix were prepared according to the TaqMan Gene Expression Assay Protocol (Applied Biosystems, Foster City, CA). Reaction volumes of 20 ll for each well on a 384-well reaction plate were used and run in duplicate. PCR reactions were performed in a Perkin-Elmer ABI PRISM 7700 Sequence Detection System (Perkin-Elmer Inc., Waltham, MA). Amplification was carried out following the standard run conditions: 50C for 2 min, 95C for 10 min, and 40 cycles of 95C for 15 s and 60C for 1 min. Manual threshold values were used and expression of each gene was normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH). In aging rats, HPRT has been found to be the most stable housekeeping gene followed by GAPDH (Chen et al., 2006). We tested hypoxanthine-guanine phosphoribosyltransferase (HPRT) and GAPDH on our samples and found GAPDH to be more stable with age than HPRT. Hepatic enzyme activity assays. Rat microsomal fractions were prepared as described previously (DeVito et al., 1996). Ethoxyresorufin O-deethylase (EROD), methoxyresorufin O-deethylase (MROD), and pentoxyresorufin O-deethylase (PROD) are enzymatic markers for CYP2C6, CYP1A2, and CYP2B2 activity, respectively. Caffeine, a substrate for CYP1A2 activity, is metabolized to theophylline (133), paraxanthine (173), and theobromine (373). These activities were detected spectrofluorimetrically using a method previously described (Staskal et al., 2005). The deltamethrin metabolism assay determines CYP2C6 and CYP2C11 activity and was determined according to the method of Godin et al. (2007). The T4 glucuronidation assay assesses UGT1A1 and UGT1A6 activities and is based on the method of Zhou et al. (2001). All data comparisons were performed by a one-way ANOVA (GraphPad Prizm 4.0). Differences between groups were considered significant when p < 0.05. All data are presented as mean ± SD.

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TABLE 1 TaqMan Primers Used for RT-PCR TaqMan assay ID

Symbol

Gene name

Context/target sequence

Rn00581304_m1 Rn00580082_m1 Rn00564842_m1 Rn99999916_s1 Rn00581081_m1 Rn01640761_gH Rn01511827_m1 Rn00569868_m1 Rn00591030_m1 Rn00579867_m1 Rn00821792_g1 Rn00583932_m1 Rn00595199_m1

SLCO1B2/SLC21A10 SLC22A8 ABCC9 GAPDH CYP4A12 CYP3A3 YC2 CYP2C CES3 GSTM3 GSTP2 GSTT1 FMO5

Solute carrier organic anion transporter family, member 1b2 Solute carrier family 22 (organic anion transporter), member 8 ATP-binding cassette, subfamily C (CFTR/MRP), member 9 Glyceraldehyde-3-phosphate dehydrogenase Cytochrome P450, 4a12 Cytochrome P450, subfamily 3A, polypeptide 3 Glutathione S-transferase Yc2 subunit Cytochrome P450, subfamily IIC (mephenytoin 4-hydroxylase) Carboxylesterase 3 Glutathione S-transferase, mu type 3 Glutathione S-transferase, pi 2 Glutathione S-transferase theta 1 Flavin-containing monooxygenase 5

CTACGATGGAATGAACCCAGTGGAC CTCCTTGTTGTCCTGGTGGGTACCA AATAACACGACGAGATTTTCAGAGA AACCCATCACCATCTTCCAGGAGCG CCTGGATTGGGTATGGTTTGCTTCT GTGAAAGAAGTGTTTGGTGCCTACA TGCTAAAGGCCCTGAGAACCAGAGT AATGGAACAGGAAAAGCACAATCCG ACCCAACACTGAAAATCTCTGAGAA CCTGACTTTGAGAAGCTGAAGCCAG TCCCAGTTCGAGGGCGCTGTGAGGC CTTCACCTTGTGTGAGAGTGTGGCC CAGCCAAGCAGGTGTTCCTCAGTAC

Note. GAPDH, glyceraldehyde 3-phosphate dehydrogenase.

RESULTS

Microarray Analysis of Gene Expression Profiles throughout the Rat Adult Life We examined gene expression in the livers of F344 rats 6, 11, 18, and 24 months of age. Principal component analysis (PCA) was able to clearly separate young (6 month) and old (24 month) rats along PC1 (Fig. 1A). Although not shown, there is greater separation by age along PC2. A total of 1135 genes were found to be significantly different in the 24 versus 6 month comparison, and 155 genes were significantly different in the 18 versus 6 month comparison. No significant differences in expression were observed between 11- and 6-monthold rats. Xenobiotic metabolism genes that changed with age were identified by comparing our results to a microarray-based compendium of ADME genes, including a number that regulate XME expression or activity (Slatter et al., 2006). In the 24- versus 6-month comparison, we found 30 phase I, 12 phase II, and 39 phase III metabolism genes that exhibited significant differences in expression (Table 2). In the 18- versus 6-month comparison, there were 7 phase I, 7 phase II, and 20 phase III metabolism genes significantly different (Table 2). We also examined the transcript profiles in the livers of 4-, 12-, and 24-month-old BN rats. PCA showed clear separation among the three age groups along PC1, with much less separation by age along PC2 or PC3 (Fig. 1B). There were 1435 genes significantly different in the 24 versus 4 month comparison, and 975 genes were significantly different in the 12 versus 4 month comparison. The top gene ontology (GO) categories identified in the old versus young BN rats were similar to those found in the aged F344 rats (Supplementary Tables 1–2). Xenobiotic metabolism genes significantly different in the 24 versus 4 month comparison included 17 phase I, 5 phase II, and 23 phase III metabolism genes (Table 2). In the 12- versus 4-month comparison, we found five phase I,

one phase II, and seven phase III metabolism genes significantly different (Table 2). Hierarchical clustering of XMEs in F344 and BN rats is shown in Figures 2A and 2B, respectively. Analogous to the PCA results for both strains, the 24-month-old animals segregate from the younger age groups. Reverse transcription–polymerase chain reaction (RT-PCR) analysis of selected genes were in good agreement with microarray results (Table 3). Analysis of Enzymatic Activity In the F344, EROD (CYP2C6) activity increased with age, with the 24-month-old group exhibiting the greatest activity and achieving statistical significance (Fig. 3). PROD (CYP2B) activity decreased for the 18- and 24-month-old groups but was not statistically significant. No significant changes in MROD (CYP1A1/2) activity were seen in F344. No significant changes were observed at the different ages for EROD (CYP2C6), MROD (CYP1A1/2), and PROD (CYP2B) for the BN rat. No consistent age-related changes were observed in the F344 rats in the caffeine biotransformation assay. For BN rats, although not statistically significant, minimal changes in CYP1A2 enzyme activity were seen at the different ages, and activity was the highest in the 24-month-old group for all three caffeine metabolites (theobromine [37X], paraxanthine [17X], and theophylline [13X]). Using thyroxine as a substrate no changes in UGT1A1 or UGT1A6 enzyme activity with age were observed in either strain. In both strains, deltamethrin metabolism (CYP2C6/CYP2C11) decreased with age, but did not attain statistical significance. These activity data are consistent with the trends from mRNA results for these specific genes, with the exception of CYP2C6 activity which increased in the 24-month-old F344 rats whereas gene expression was not significantly changed.


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compared 18-month F344 to 24-month BN (~90% survival for both strains). There were 303 genes in common between F344 (18 vs. 6 month) and BN (24 vs. 4 month), with 93% concordance in direction of change. Using significantly altered genes, the top networks identified by Ingenuity in old versus young male F344 and BN rats are shown in Table 5. Consistent functions identified between the two groups include inflammatory disease, dermatological diseases and conditions, immunological disease, cell-to-cell signaling and interaction, cell morphology, hematological system development and function, tissue development, and nervous system development and function. Using the program GATHER (Chang and Nevins, 2006), the 462 genes significantly different by age that are in common between F344 and BN rats were involved in the following kyoto encyclopedia of genes and genomes pathways (Bayes Factor cutoff of 6): MAPK signaling pathway, focal adhesion, and cytokine-cytokine receptor interaction. GATHER also identified the top GO categories: carbohydrate metabolism, energy derivation by oxidation of organic compounds, alcohol metabolism, pyruvate metabolism, and cellular carbohydrate metabolism. In the old versus young group, many GO categories identified by GATHER fall under intermediary metabolism, including lipid metabolism, ergosterol metabolism, alcohol metabolism, and fatty acid metabolism.

FIG. 1. PCA after LOESS normalization. PCA of DEGs from 24 versus 6-month-old F344 rats (A) or PCA of all DEGs in BN rats (B).

Comparison of Age-Related Genes between F344 and BN Rats A direct comparison of the significantly altered genes between youngest and oldest for the two rat strains revealed 462 genes that overlapped (Fig. 4). The six XMEs in common between strains were all Phase III genes and five out of six exhibited similar direction of change (Table 4). Based on 50% survival of aging rats, a 24-month-old F344 rat and a 32month-old BN rat are at approximately equivalent physiological ages (Nadon, 2004). Therefore, in our study we also

Comparison of Genes Altered by Aging and Gender From our analysis above, genes known to be regulated by GH in a male predominant manner (e.g., CYP2A1, CYP2A2, CYP2C13, CYP2C40) were downregulated with age. We hypothesized that many of the gene expression changes in old rats were due to changes in GH secretory pattern that determines gender expression in the liver (Legraverend et al., 1992; Sundseth et al., 1992). To test this hypothesis, we compared the expression of all genes altered by aging in the F344 and BN rats to genes that were consistently different between male and female rats identified in a study of baseline gene expression in the livers of control rats. Control rats were from eight different studies performed at two institutions (Boedigheimer et al., 2008). We compared 223 genes differentially expressed in at least one of the aging rat strains and in at least one of the two institutions from the baseline study. Gender differences impacted 19% (213/1135) and 8% (116/1435) of the genes significantly altered by aging in the F344 and BN rat, respectively. Remarkably, most genes upregulated in the aging rat were expressed at greater levels in young adult female rats compared with males, whereas most genes downregulated by aging were expressed at greater levels in young adult male rats (Fig. 5). These results suggest that the aging male rat liver exhibits a ‘‘feminized’’ pattern of gene expression which impacts the expression of 25 (31%) and 17 (38%) XMEs in the F344 and BN comparisons, respectively (Supplementary Table 3).

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TABLE 2 XME Genes with Altered Expression in Aged F344 and BN Rats

GenBank# Phase I AA817761 NM_022407 M23995 NM_133586 L46791 K02422

Symbol

ADH1 ALDH1A1 ALDH1A4 CES2 CES3 CYP1A2

BE105541 CYP26B1 BF397093 CYP26B1 NM_012692 CYP2A1 NM_012693 CYP2A2 NM_019184 CYP2C J02861 CYP2C13 NM_031572 CYP2C40 U48219

CYP2D22

U48220

CYP2D22

U39943

CYP2J9

U09742

CYP3A2

U46118

CYP3A13

AA893326

CYP4A14

M29853

CYP4B1

NM_012941 CYP51 NM_012942 CYP7A1 BF283070

CYP7B1

NM_031241 CYP8B1 NM_130819 DHRS9 AA859049 NM_012792 AI454611 NM_012742 NM_012580 J02679 AI407454 NM_031576 AI454613

ES2 FMO1 FMO5 FOXA1 HMOX1 NQO1 POR POR RGD:2467

NM_134369 RGD:620086 NM_130408 RGD:620161 NM_134407 RGD:620311 M20406

RGD:628627

Gene name

Alcohol dehydrogenase 1 Aldehyde dehydrogenase family 1, member A1 Aldehyde dehydrogenase family 1, subfamily A4 Carboxylesterase 2 (intestine, liver) Carboxylesterase 3 Cytochrome P450, family 1, subfamily a, polypeptide 2 Cytochrome P450, family 26, subfamily b, polypeptide 1 Cytochrome P450, family 26, subfamily b, polypeptide 1 Cytochrome P450 IIA1 (hepatic steroid hydroxylase IIA1) gene Cytochrome P450, subfamily 2A, polypeptide 1 Cytochrome P450, subfamily IIC (mephenytoin 4-hydroxylase) Cytochrome P450 2c13 Cytochrome P450, family 2, subfamily c, polypeptide 40 Cytochrome P450, family 2, subfamily d, polypeptide 22 Cytochrome P450, family 2, subfamily d, polypeptide 22 Cytochrome P450, family 2, subfamily j, polypeptide 9 Cytochrome P450, family 3, subfamily a, polypeptide 11 Cytochrome P450, family 3, subfamily a, polypeptide 13 Cytochrome P450, family 4, subfamily a, polypeptide 14 Cytochrome P450, family 4, subfamily b, polypeptide 1 Cytochrome P450, subfamily 51 Cytochrome P450, family 7, subfamily a, polypeptide 1 Cytochrome P450, family 7, subfamily b, polypeptide 1 Cytochrome P450, family 8, subfamily b, polypeptide 1 Dehydrogenase/reductase (SDR family) member 9 Esterase 2 Flavin-containing monooxygenase 1 Flavin-containing monooxygenase 5 Forkhead box A1 Heme oxygenase (decycling) 1 NAD(P)H dehydrogenase, quinone 1 P450 (cytochrome) oxidoreductase P450 (cytochrome) oxidoreductase Cytochrome P450, family 2, subfamily b, polypeptide 2 Cytochrome P450 monooxygenase CYP2T1 Cytochrome P450, family 26, subfamily A, polypeptide 1 Aldo-keto reductase family 7, member A2 (aflatoxin aldehyde reductase) Cytochrome P450IIB3

F344 18v6 mo. F344 24v6 mo. BN 12v4 mo. BN 24v4 mo. fold-change fold-change fold-change fold-change

1.72 1.57 2.67 1.52 1.89 1.6 2.61 2.67 1.79

1.59

1.57

11.5 18.5

3.32 2.01

1.54 1.65

3.78 19.4 2.11

1.94

2.32 1.71 18.46 3.05 2.08 1.64 1.93 2.39 1.82

1.98 1.54 4.28

2.48 1.52 1.89

1.56 2.14 2.35 1.99 1.86

1.89

2.12

1.58 1.75 3.82 1.76

3.1

7.18 1.65 1.76

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TABLE 2—Continued GenBank#

Symbol

Gene name

D38381 AW142784 NM_031605 U39206 Phase II BI296610 NM_017084 AA800587 L38615 AI175604 BM385856 NM_031154 NM_020540 X02904

RGD:628709 RGD:628846 RGD:628846 RGD:708363

Cytochrome Cytochrome Cytochrome Cytochrome

GLUL GNMT GPX2 GSS GSTA5 GSTM2 GSTM3 GSTM4 GSTP1; GSTP2

NM_053293 AI232716 NM_022635 NM_012883 NM_031732 BI300997 NM_031641 NM_022228 AA945082 Phase III NM_024396

GSTT1 LOC368066 NAT8 STE SULT1A2 SULT1C2 SULT4A1 UGT2A1 YC2

Glutamine synthetase 1 Glycine N-methyltransferase Glutathione peroxidase 2 Glutathione synthetase Glutathione S-transferase A5 Glutathione S-transferase, mu 2 Glutathione S-transferase, mu type 3 Glutathione S-transferase M4 Glutathione-S-transferase, pi 1; glutathione S-transferase, pi 2 Glutathione S-transferase theta 1 Similar to thioether S-methyltransferase N-acetyltransferase 8 (camello like) Sulfotransferase, estrogen preferring Sulfotransferase family 1A, member 2 Sulfotransferase family, cytosolic, 1C, member 2 Sulfotransferase family 4A, member 1 UDP glycosyltransferase 2 family, polypeptide A1 Glutathione S-transferase Yc2 subunit

ABCA2

P450, 3a18 P450, 4a12 P450, 4a12 P450 4F4

ATP-binding cassette, subfamily A (ABC1), member 2 AY082609 ABCB1; ABCB1A ATP-binding cassette, subfamily B (MDR/TAP), member 1; member 1A AF286167 ABCB1A ATP-binding cassette, subfamily B (MDR/TAP), member 1A NM_080582 ABCB6 ATP-binding cassette, subfamily B (MDR/TAP), member 6 NM_022238 ABCB9 ATP-binding cassette, subfamily B (MDR/TAP), member 9 AF072816 ABCC3 ATP-binding cassette, subfamily C (CFTR/MRP), member 3 NM_031013 ABCC6 ATP-binding cassette, subfamily C (CFTR/MRP), member 6 NM_013040 ABCC9 ATP-binding cassette, subfamily C (CFTR/MRP), member 9 NM_033352 ABCD2 ATP-binding cassette, subfamily D (ALD), member 2 AI175616 ABCG2 ATP-binding cassette, subfamily G (WHITE), member 2 NM_053754 ABCG5 ATP-binding cassette, subfamily G (WHITE), member 5 BI291872 LOC500973 Similar to solute carrier family 37 (glycerol-3-phosphate transporter), member 2 AA817715 MGC93911 Similar to solute carrier family 25 (mitochondrial deoxynucleotide carrier), member 19 NM_017222 SLC10A2 Solute carrier family 10, member 2 BF387032 SLC12A5 Solute carrier family 12, (potassium chloride transporter) member 5 U51153 SLC13A2 Solute carrier family 13 (sodium-dependent dicarboxylate transporter), member 2

F344 18v6 mo. F344 24v6 mo. BN 12v4 mo. BN 24v4 mo. fold-change fold-change fold-change fold-change

3.12 3.43

2.83 3.39 3.05 1.6

1.83 3.02

1.83 1.93 3.01

2.09 1.65

3.01 2.08 2.51 1.63

1.8 1.81 1.65 2.73

2.88

1.55 1.54 10.4

1.56

1.79

22.75 1.74 2.18 2.44 1.62 2.45

2.13 1.6

1.57

4.63

1.51 1.55 2.57 3.04

3.86 1.55 2.77 2.35 1.93 5.03

1.5 1.76

1.91 2.56

1.5

1.89 2.93

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Symbol

NM_022866 SLC13A3 BG381311

SLC13A5

AB026665 AA859652

SLC15A3 SLC16A6

NM_053859 SLC17A7 NM_017299 SLC19A1 NM_032065 SLC1A6 AB000489

SLC20A1

NM_031650 SLC21A10 NM_031332 SLC22A8 AY009158

SLC24A3

NM_133614 SLC25A21 AI177358

SLC25A25

BG666999

SLC25A4

NM_031684 SLC29A1 BM392280

SLC29A3

AA799760

SLC2A4

NM_031741 SLC2A5 NM_053494 SLC2A8 NM_053380 SLC34A2 AA924432

SLC34A3

BI293600 SLC35B2 NM_031589 SLC37A4 AF249673 AF276870 AI229664

SLC38A2 SLC38A5 SLC40A1

AI407028

SLC40A1

NM_133315 SLC40A1 BE113640 AF210250 BF392130 BF416861 NM_012694

SLC4A1 SLC4A4 SLC4A4 SLC4A4 SLC6A3

BG378480

SLC6A6

NM_017206 SLC6A6

Gene name Solute carrier family 13 (sodium-dependent dicarboxylate transporter), member 3 Solute carrier family 13 (sodium-dependent citrate transporter), member 5 Peptide/histidine transporter PHT2 Solute carrier family 16 (monocarboxylic acid transporters), member 6 Solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 7 Solute carrier family 19, member 1 Solute carrier family 1 (high affinity aspartate/glutamate transporter), member 6 Solute carrier family 20 (phosphate transporter), member 1 Solute carrier family 21, member 10 Solute carrier family 22 (organic anion transporter), member 8 Solute carrier family 24 (sodium/potassium/ calcium exchanger), member 3 Solute carrier family 25 (mitochondrial oxodicarboxylate carrier), member 21 Solute carrier family 25 (mitochondrial carrier, phosphate carrier), member 25 Solute carrier family 25 (mitochondrial adenine nucleotide translocator) member 4 Solute carrier family 29 (nucleoside transporters), member 1 Solute carrier family 29 (nucleoside transporters), member 3 Solute carrier family 2 (facilitated glucose transporter), member 4 Solute carrier family 2, member 5 Solute carrier family 2, (facilitated glucose transporter) member 8 Solute carrier family 34 (sodium phosphate), member 2 Solute carrier family 34 (sodium phosphate), member 3 Solute carrier family 35, member B2 Solute carrier family 37 (glycerol-6phosphate transporter), member 4 Solute carrier family 38, member 2 Solute carrier family 38, member 5 Solute carrier family 39 (iron-regulated transporter), member 1 Solute carrier family 39 (iron-regulated transporter), member 1 Solute carrier family 39 (iron-regulated transporter), member 1 Solute carrier family 4, member 1 Solute carrier family 4, member 4 Solute carrier family 4, member 4 Solute carrier family 4, member 4 Solute carrier family 6 (neurotransmitter transporter, dopamine), member 3 Solute carrier family 6 (neurotransmitter transporter, taurine), member 6 Solute carrier family 6 (neurotransmitter transporter, taurine), member 6

F344 18v6 mo. F344 24v6 mo. BN 12v4 mo. BN 24v4 mo. fold-change fold-change fold-change fold-change 1.71 2.51 1.93 1.63 3.21 2.25

2.55

1.67 1.53

1.67 1.64 40.25

1.67

2.43 1.59

1.53

1.51

1.72

8.94

1.64

1.64 1.6 1.52 3

1.57 1.54

1.54 1.88 3.09 4.6

1.6 1.64 2.39 2.05 1.7

1.84 1.63

1.57

3.23

1.6

1.53

2.1

1.67 2.85 2.04 1.6 2.99

1.88 1.96

271



Symbol

AA943735

SLC6A9

AW141210

SLC6A9

M95413

SLC6A9

NM_017353 SLC7A5 AF200684 SLC7A7 NM_021594 SLC9A3R1 AF294257 SLC9A3R2 NM_131906 SLCO1A4 U95011

SLCO1A4

NM_032056 TAP2 Y09945 NM_134379 NM_134380 Other AB012600

UST1R UST4R UST5R ARNTL

NM_022941 NR1I3, CAR

Gene name Solute carrier family 6 (neurotransmitter transporter, glycine), member 9 Solute carrier family 6 (neurotransmitter transporter, glycine), member 9 Solute carrier family 6 (neurotransmitter transporter, glycine), member 9 Tumor-associated protein 1 Solute carrier family 7 (cationic amino acid transporter, yþ system), member 7 ERM-binding phosphoprotein Solute carrier family 9 (sodium/hydrogen exchanger), isoform 3 regulator 2 Solute carrier organic anion transporter family, member 1a4 Solute carrier organic anion transporter family, member 1a4 Transporter 2, ATP-binding cassette, subfamily B (MDR/TAP) Integral membrane transport UST1r Integral membrane transport protein UST4r Integral membrane transport protein UST5r Aryl hydrocarbon receptor nuclear translocator-like Nuclear receptor subfamily 1, group I, member 3

GSEA Results Expression profiles for combined young (4–6 months) and old (24 months) F344 and BN rats were analyzed using GSEA. Twelve gene sets were found to be significantly enriched in young versus old (FDR < 25%). Of these sets, six were related to Myc, two were related to androgen, and one was related to amino acid metabolism. There were 717 gene sets found to be significantly enriched in the old versus young comparison (FDR < 25%). Many of these gene sets were related to apoptosis in the liver, inflammation, and aging. We also used GSEA to search for TFs (C3 gene set) enriched in the old or young populations potentially regulating the gene expression profiles. There were zero and 258 significant gene sets enriched in the young and old phenotypes, respectively (FDR < 25%). Some top ranked motifs in the old phenotype included binding motifs for AhR and xenobiotic metabolism signaling (NF-kB, AhR-ARNT), as well as LXR/RXR activation (SREBF1). Effect of Age on the Transcriptional Response to Toluene Exposure The expression of CYP1A2 and CYP2D22, involved in organic solvent metabolism, decreased with age in both rat strains. The expression of glutathione-S-transferase M3 (GSTM3), an important phase II enzyme involved in detoxification, also decreased with age, whereas the expression of

F344 18v6 mo. F344 24v6 mo. BN 12v4 mo. BN 24v4 mo. fold-change fold-change fold-change fold-change 1.7 2.25 2.39

2.88 2.28 1.96 1.5

1.83

1.59

1.9

1.75

1.55

1.55

1.5

1.56

1.69 5.2 2.58 14.87

1.62 2.43

glutathione synthetase (GSS) increased with age. To test the hypothesis that older rats exhibit altered transcriptional responses to environmental chemicals, we exposed BN rats of three ages to 1 g/kg of toluene for 4 h. Control rats received corn oil alone. We found 1133, 946, and 1772 genes significantly altered in the 4-, 12-, and 24-month-old rats, respectively. The top GO categories for the age groups dosed with toluene are listed in Supplementary Tables 4–6. Toluene is mainly metabolized by CYP1A1/2, CYP2A1, CYP2B1/2, CYP2C6, CYP2C11, and CYP2E1 in the rat liver (Nakajima and Wang, 1994). The gene expression of CYP2B2 after acute toluene exposure increased 3.2-, 6.6-, and 7.1-fold in the 4-, 12-, and 24-month groups, respectively. Although age did not have an appreciable effect on the number of phase I genes that were altered by toluene exposure, there was a dramatic effect on the number of phase II and phase III genes altered, increasing the number altered from 14 and 15 in the 4- and 12-month age groups to 33 in the 24-month-old group (Table 6). After exposure to toluene, the expression of many glutathione-Stransferases increased in the 4-month (GSTA5), 12-month (GSTM2, YC2), and 24-month-old groups (GSTM3, GSTM2, GSTA5). Age being the only parameter, 30% (7/23) of the Phase III genes were downregulated in the control 24-month-old group compared with the control 4-month-old group, and this increased to 70% (19/27) after exposure to toluene. In the 24-month-old toluene exposed group the expression of glutathione synthetase

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(GSS) and glutathione S-transferase YC2 subunit decreased, suggesting a decreased production of glutathione with age. Hierarchical clustering of XMEs in BN rats exposed to 1 g/kg toluene is shown in Figure 6. As seen in the heat map, there is segregation of the exposed and nonexposed animals. Top functions identified by Ingenuity are shown in Table 7. In summary, toluene exposure mainly affected the expression of phase II and phase III genes in the aging rats. TF Analysis Potential targets of aging are the TFs that regulate the changes in XME gene expression. TFs involved in XME expression that were altered in aging rats (F344 and BN) and rats exposed to toluene (BN) were clustered (Fig. 7). Most of the TFs (85%) altered by age were unique to F344 rats. TFs were almost always upregulated in BN rats after exposure to toluene. In F344 rats, Nr1i3 (CAR) expression decreased 2.4-fold at 24 months compared with the 6 month group. Expression of many CYPs and other XMEs regulated by CAR also decreased in the 24 versus 6 month F344 rats, including CYP1A2, CYP2C, CYP3A2, CYP2B2, CYP2B3, STE, SLC21A10, and SLC29A1. Toluene exposure increased the expression of CAR 1.9-fold in 24-monthold BN rats. The expression of CYP2B2, regulated by CAR, increased in all age groups exposed to toluene with the highest fold change (7.1-fold) observed in the 24-month-old group. The expression of CYP2C and GSTA5, also regulated by CAR, increased in the 24-month-old BN rats exposed to toluene. Thus, the expression changes in the XMEs regulated by CAR are in good agreement with the expression changes in CAR itself. As a complement to the analysis of TF expression, we also identified enriched binding sites in the promoters of genes significantly altered in our studies. Many of the XMEs altered by age, GH, or toluene contain AHR, FXR, RXR, PPAR, STAT5B, STAT3, STAT1, and STAT6 sites (Supplementary Figs. 1A and 1B). Many of these same TFs exhibited altered expression with age or toluene exposure or both. Potential Effect of Age on Chemical Sensitivity To predict classes of chemicals to which the aging population exhibit differential sensitivity, we used the Comparative Toxicogenomics Database (http://ctd.mdibl.org/) to identify chemicals that interact with individual CYPs affected by age in our study. We focused our search for chemicals that increase the expression of CYPs that were decreased with age in our study, that is, CYPs likely involved in metabolism of the chemical. CYP1A2, CYP2C, and CYP2B2

FIG. 2. Hierarchical clustering of XMEs in (A) F344 or (B) BN rats. XMEs observed to be statistically altered after Cyber-T analysis were clustered by gene and array (median centered). Values represent the log2 of the expression value. Red indicates an increase in gene expression, whereas green indicates a decrease in gene expression. Black represents no change in gene expression.

273


TABLE 3 RT-PCR Results (a)

Microarray

RT-PCR

24v6 month F344 2.8 1.9 1.6 40.3 1.8 2.7 1.6 2.4 18.5 12v4 month BN 1.0 1.1 3.0 1.4 2.1

ABCC9 CES3 GSTT1 SLC22A8 GSTM3 GSTP1;2 SLC21A10 FMO5 CYP2C2 CYP2C2 CYP3A3 CYP4A12 SLC22A8 Glutathione S-transferase YC2 subunit

1.4 2.9 1.9 321.4 2.1 1.5 2.1 2.0 61.9

± ± ± ± ± ± ± ± ±

0.2 0.3 0.2 0.4 0.2 0.5 0.3 0.6 0.1

1.1 1.1 1.5 1.1 1.4

± ± ± ± ±

0.2 0.2 0.3 0.2 0.2

Microarray 18v6 month F344 2.0 1.1 1.2 1.3 1.2 1.6 1.1 2.5 1.1 24v4 month BN 1.6 2.4 1.9 1.7 1.0

RT-PCR

1.1 1.3 1.6 1.7 1.5 1.2 1.1 2.0 2.1

± ± ± ± ± ± ± ± ±

0.5 0.4 0.3 0.4 0.3 0.7 0.5 0.9 0.2

4.6 2.7 1.5 2.2 1.0

± ± ± ± ±

0.2 0.2 1.5 0.4 0.9

BN rats exposed to 1 g/kg toluene (b)

Microarray

ABCC9 CYP2C2 GSTM3 SLC22A8 Glutathione S-transferase YC2 subunit

4 months 1.1 1.1 1.0 1.1 1.2

RT-PCR

1.4 1.1 1.5 1.0 1.3

± ± ± ± ±

0.3 0.5 0.3 0.4 0.4

Microarray 12 months 1.4 1.1 1.3 1.6 2.4

RT-PCR

1.6 2.0 1.9 2.3 1.0

± ± ± ± ±

0.5 0.4 0.3 0.4 0.9

Microarray 24 months 1.4 1.6 2.0 1.2 2.1

RT-PCR

1.6 2.6 2.4 1.1 1.5

± ± ± ± ±

0.6 2.4 2.2 1.1 0.9

Note. (a) Numbers are presented as fold-change relative to the younger age group. (b) Numbers are presented as fold-change relative to the untreated group of the same age.

expression decreased in old F344 and BN rats. CYP3A2 expression decreased in old F344 rats only. Based on these gene expression changes, we identified a number of chemicals that may exhibit altered metabolism in the livers of aged rats. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), a chemical byproduct from incineration processes, induces CYP1A2 through activation of the Ah receptor. Insecticides (Mirex, methoxychlor, chlordecone), the pesticide dichloro-diphenyl-trichloroethane (DDT), the herbicide alachlor, some polychlorinated biphenyls, and the organic solvent dioxane are chemicals that induce CYP2B2 through activation of CAR. Aflatoxin B1, DDT, and propiconazole fungicides interact with CYP3A2. Thus, it follows that old male F344 and BN rats might be more sensitive to the effects of TCDD, insecticides, DDT, alachlor, some polychlorinated biphenyls (PCBs), and dioxane due to reduced metabolism. Old male F344 might also be more sensitive to the effects of aflatoxin B1 and propiconazole fungicides. In addition to gene expression data, protein and enzyme activity data would strengthen our predictions. DISCUSSION

The expression and activity of genes involved in chemical metabolism can have a profound impact on the biological fate

of the chemical and whether exposure results in toxicity. Very little is known about the impact of aging on the transcript profile of XMEs and the relationships between age-dependent differences in expression and chemical susceptibility. In this study changes in XME expression in aging male rat livers were characterized to hypothesize altered responses to environmental chemicals with age. A comparison was performed between two rat strains commonly used for toxicology and aging studies (F344 and BN) to identify strain-dependent and -independent gene expression changes. We used this information to hypothesize that there would be differences in transcriptomic responses between young and old rats after exposure to an environmentally relevant chemical (toluene). Our study finds age-related changes in phase I, phase II, and phase III genes in two strains of rats up to 24 months old, as well as age-related differences in XME gene expression due to toluene exposure. Aging had an impact on the overall transcript profile as well as the expression of XMEs in the liver. Almost 16 and 7% of the genome exhibited some change in expression in F344 and BN rats, respectively (p-value < 0.05). Many of the gene sets for the old phenotype, identified by GSEA, were related to inflammation and aging. Aging is associated with dysregulated inflammatory response, and increased inflammatory response has been implicated in the pathogenesis of several age-related

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LEE ET AL.

FIG. 3. Alterations in XME activity with age in rat livers. Enzymatic activity was determined in hepatic microsomal fractions from 4-, 12-, and 24-month-old male BN (n ¼ 6) and 6-, 11-, 18-, and 24-month-old male F344 rats (n ¼ 4). Data are presented as mean ± SD. *Represents statistically different (p < 0.05) from youngest animals for each strain.


FIG. 4. A comparison of genes significantly altered between young and old F344 and BN rats. A fold change of 1.5 and p-value 0.05 were used as cutoffs. (A) Heat map comparison of gene expression between the two rat strains. Genes altered by age in the F344 rat were divided into those that overlapped with BN rats and those unique to F344 rats. Genes in each category were rank ordered based on their fold-change. Red indicates an increase in gene expression, whereas green indicates a decrease in gene expression. Black represents no change in gene expression. (B) Venn diagram showing overlap of genes between young and old F344 and BN rats.

diseases (Wu and Meydani, 2008). Out of the 491 XME genes examined in our profiling studies, 22 or 14% were altered by aging in F344 or BN rats, respectively. The greater number of age-related gene expression changes in F344 than BN rats at equivalent ages is not surprising, because survival data indicates BN rats age more slowly than F344 rats. The median survival for F344 rats is 24 months whereas for BN rats it is 32 months (Turturro et al., 1999). The 462 genes significantly altered in both strains between young and old were 89% concordant, that is, exhibited similar direction of change with age. Using Ingenuity, the top associated network functions for

275

genes significantly altered in both strains were related to drug metabolism, free radical scavenging, and fatty acid metabolism. This is similar to the GO categories that fall under intermediary metabolism as identified by GATHER. Genes altered only in F344 with age were related to cancer, gastrointestinal disease, and gene expression. Genes altered only in BN rats with age were related to embryonic development, tissue development, and tissue morphology. It is not surprising that cancer is one of the top diseases identified in aged F344 rats (Table 5) because aged F344 rats have a greater incidence of certain diseases than other rat strains, including leukemia, which is rare in BN rats (Nadon, 2006). Reproductive system development and function is also uniquely identified in aged BN rats (Table 5), and this correlates with the high rate of testicular atrophy seen in aged males (Lipman et al., 1999). The incidence of many diseases increases with age, making it hard to separate the effects of aging from the effects of various diseases (Sprott and Ramirez, 1997). BN rats have far fewer strain-specific lesions with age compared with the F344, and these lesions are similar to the ones seen in the human population (Nadon, 2006). Further, there are physiological similarities to humans that make BN rats useful models for human senescence, particularly in the male reproductive system (Nadon, 2006). Our comparison of the gene expression profiles in the aging rat liver will be a useful resource for future studies in these rat strains to correlate changes in gene expression with age-dependent diseases in liver and other tissues. Most of the age-dependent phase I genes in F344 rats are involved in oxidation-reduction reactions, including alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), esterase (ES), heme oxygenase (HMOX), and the cytochrome P450 family (CYP) of enzymes. Hydrolases including epoxide hydrolase were not altered with age. We found increased expression of ADH1 and ALDH1A4, which play important roles in the metabolism of alcohols and aldehydes. ADH and ALDH family members are involved in the pathway leading to fatty acid biosynthesis; alterations in lipid homeostasis were indicated for 24-month F344 rats as top GO categories included lipid metabolism, sterol biosynthesis, sterol metabolism, and fatty acid

TABLE 4 XMEs Altered by Age in Both F344 and BN Rats

GenBank# NM_024396 AB000489 NM_133614 BG666999 NM_133315 M95413

Symbol

Gene name

Fold-change, F344 (18v6 mo)

Fold-change, BN (24v4 mo)

ABCA2 SLC20A1 SLC25A21 SLC25A4 SLC40A1 SLC6A9

ATP-binding cassette, subfamily A (ABC1), member 2 Solute carrier family 20 (phosphate transporter), member 1 Solute carrier family 25 (mitochondrial oxodicarboxylate carrier), member 21 Solute carrier family 25 (mitochondrial adenine nucleotide translocator) member 4 Solute carrier family 39 (iron-regulated transporter), member 1 Solute carrier family 6 (neurotransmitter transporter, glycine), member 9

1.79 1.53 1.59 1.64 1.57 2.39

1.60 1.67 8.94 1.64 2.10 2.88

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LEE ET AL.

TABLE 5 Top Functions in Aged F344 and BN Rats Identified through Ingenuity F344, 18 versus 6 month Diseases and disorders Inflammatory disease Cancer Dermatological diseases and conditions Immunological disease Hematological disease Molecular and cellular functions Cellular movement Cell-to-cell signaling and interaction Cell morphology Lipid metabolism Small molecule biochemistry Physiological system development and function Hematological system development and function Immune response Tissue development Tumor morphology Nervous system development and function

BN, 24 versus 4 month Diseases and disorders Neurological disease Dermatological diseases and conditions Immunological disease Inflammatory disease Organismal injury and abnormalities Molecular and cellular functions Cell morphology Cellular function and maintenance Cell-to-cell signaling and interaction Cell death Cellular development Physiological system development and function Tissue development Hematological system development and function Immune and lymphatic system development and function Nervous system development and function Reproductive system development and function

metabolism. FMO converts lipophilic compounds to hydrophilic metabolites via oxidation. We found a greater than twofold decline in FMO1 transcript levels between 6 and 24 months of age, and increases in FMO5 gene expression between 6 and 24 months (2.4-fold) and 6 and 18 months of age (2.5-fold). HMOX1 transcript levels increased almost 2fold with age. Most of the genes altered with age that encode phase I enzymes are members of the CYP1, CYP2, and CYP3 families (Table 2). Transcript levels for CYP2A1 and CYP2C40 increased with age, whereas transcript levels for CYP1A2, CYP2A2, CYP2B2, CYP2B3, CYP2C, CYP2C13, CYP3A2, and CYP3A18 all decreased with age. This pattern suggests an overall decline in Phase I reactions with increasing age. We also observed an increased age-related expression of carboxylesterase 2 (CES2) and a decreased age-related expression of CES3. Carboxylesterases are important in the detoxification of organophosphorous pesticides (Karanth and Pope, 2000) and pyrethroid insecticides (Huang et al., 2005), leading to the prediction of increased levels and responses to these chemicals with age. In BN rats, ALDH, dehydrogenase/reductase (DHRS), and CYP enzymes were significantly altered with age. Transcript levels for ALDH1A1 increased 1.6-fold and decreased 4.3-fold for DHRS9 in the 24-month-old group. Transcript levels for all

FIG. 5. Comparison of aging genes to those that exhibit gender differences in expression. Genes were selected for comparison as detailed in the ‘‘Materials and Methods.’’ In F344 and BN columns, red, green, and black represents respectively an increase, decrease or no change in gene expression between old and young animals. Baseline data originated from control animals in previous studies from institutions 11 and 17 in the Boedigheimer et al. (2008) study. Green represents female predominant genes, red represents male predominant genes, and black represents genes that do not exhibit significant differences between genders.

significantly altered members of CYP1, CYP2, and CYP3 families decreased with age (CYP1A2, CYP2A2, CYP2B2, CYP2C, CYP3A13, CYP3A18). Phase II biotransformation processes altered with age in F344 rats included glucuronidation (UGT2A1), sulfation (SULT1A2, SULT1C2, SULT4A1), and glutathione conjugation (GPX2, GSTM2, GSTM3, GSTM4, GSTP1/2, GSTT1, YC2). Transcript profiles for glucuronidation genes decreased in 24-month-old F344 rats. Gene expression profiles for all sulfation genes, except for SULT4A1, also decreased in the oldest age group. Three of the glutathione conjugation genes were downregulated with age (GSTM2, GSTM3, GSTT1), whereas four were upregulated with age (GPX2, GSTM4, GSTP1/GSTP2, YC2). In 18-month-old BN rats, glutathione conjugation is the main process affected by age with glutathione S-transferase YC2 subunit decreasing by 2.1-fold. In 24-month-old BN rats, GSS was increased by 1.7-fold and GSTM3 was decreased by 2.9-fold. The biological impact of

277


TABLE 6 XME Genes with Altered Expression after Toluene Exposure (1 g/kg) in BN Rats

GenBank# Phase I NM_013215

Symbol

AKR7A3

CYP4A14 CYP4B1 CYP51 CYP51 CYP7A1 CYP8B1 DHRS9 POR POR RGD:2467 RGD:735174

Aldo-keto reductase family 7, member A3 (aflatoxin aldehyde reductase) Aldehyde dehydrogenase family 1, member A1 Aldehyde dehydrogenase family 1, subfamily A4 Cytochrome P450, family 11, subfamily B, polypeptide 2/3; cytochrome P450, subfamily 11B, polypeptide 1 Cytochrome P450, family 26, subfamily b, polypeptide 1 Cytochrome P450, family 26, subfamily b, polypeptide 1 Cytochrome P450, subfamily IIC (mephenytoin 4-hydroxylase) Cytochrome P450, family 2, subfamily d, polypeptide 22 Cytochrome P450, subfamily 3A, polypeptide 3 Cytochrome P450, family 4, subfamily a, polypeptide 10; cytochrome P450, family 4, subfamily A, polypeptide 22 Cytochrome P450, family 4, subfamily a, polypeptide 14 Cytochrome P450, family 4, subfamily b, polypeptide 1 Cytochrome P450, subfamily 51 Cytochrome P450, subfamily 51 Cytochrome P450, family 7, subfamily a, polypeptide 1 Cytochrome P450, family 8, subfamily b, polypeptide 1 Dehydrogenase/reductase (SDR family) member 9 P450 (cytochrome) oxidoreductase P450 (cytochrome) oxidoreductase Cytochrome P450, family 2, subfamily b, polypeptide 2 Cytochrome P450 CYP2B21

GPX2 GSS GSTA5 GSTM2 GSTM3 GSTP1; GSTP2 YC2

Glutathione peroxidase 2 Glutathione synthetase Glutathione S-transferase A5 Glutathione S-transferase, mu 2 Glutathione S-transferase, mu type 3 Glutathione-S-transferase, pi 1; glutathione S-transferase, pi 2 Glutathione S-transferase Yc2 subunit

ABCA1; LOC497803

ATP-binding cassette, subfamily A (ABC1), member 1; hypothetical gene supported by NM_178095 ATP-binding cassette, subfamily A (ABC1), member 1; hypothetical gene supported by NM_178095 ATP-binding cassette, subfamily A (ABC1), member 2 ATP-binding cassette, subfamily B (MDR/TAP), member 1; ATP-binding cassette, subfamily B (MDR/TAP), member 1A ATP-binding cassette, subfamily B (MDR/TAP), member 1A ATP-binding cassette, subfamily B (MDR/TAP), member 1A ATP-binding cassette, subfamily C (CFTR/MRP), member 1 ATP-binding cassette, subfamily G (WHITE), member 2 ATP-binding cassette, subfamily G (WHITE), member 5 ATP-binding cassette, subfamily G (WHITE), member 8 Solute carrier family 17 (sodium phosphate), member 1 Solute carrier family 10, member 2 Solute carrier family 13 (sodium-dependent dicarboxylate transporter), member 2 Solute carrier family 13 (sodium-dependent dicarboxylate transporter), member 3 Solute carrier family 13 (sodium-dependent citrate transporter), member 5

BE105541 BF397093 NM_019184

ALDH1A1 ALDH1A4 CYP11B2; RGD:727886; CYP11B1 CYP26B1 CYP26B1 CYP2C

U48220 AI639276 NM_016999

CYP2D22 CYP3A3 CYP4A10; CYP4A22

NM_022407 M23995 D11354

Gene name

M33936 M29853 BG664123 NM_012941 NM_012942 NM_031241 NM_130819 AI407454 NM_031576 AI454613 AF159245 Phase II AA800587 L38615 AI175604 BM385856 NM_031154 X02904 AA945082 Phase III AW918387 BF284523

ABCA1; LOC497803

NM_024396 AY082609

ABCA2 ABCB1; ABCB1A

AF257746 AF286167 AI059506 AI175616 NM_053754 NM_130414 NM_133554 NM_017222 U51153

ABCB1A ABCB1A ABCC1 ABCG2 ABCG5 ABCG8 RGD:620099 SLC10A2 SLC13A2

NM_022866

SLC13A3

BG381311

SLC13A5

4-month fold-change

12-month fold-change


1.76 1.61 2.39 4.6 2.04 1.64

1.77

8.75

1.53 5.71

2.31 1.58

8.38 1.97 1.5

1.6 1.8 1.76 3.75 2.91 1.98 2.1 3.18 2.53

1.81 2.56 1.78 1.77 6.56

2.37

2.42

5.44

7.06

3.04 1.62 6.1 3.29 1.98 1.51 2.12 1.54 1.63

1.58 1.73

2.02 2.19

2.75

1.7 2.43

1.86

2.44

2.46 2.19 1.67 1.58 1.58 2.51 1.76 1.83

1.61

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Symbol

AF230638

SLC14A2

AB026665 BE108640

SLC15A3 SLC16A4

NM_017215

SLC1A2

BM384337

SLC1A4

AB000489

SLC20A1

AB051836

SLC22A19

NM_019269

SLC22A5

NM_031332

SLC22A8

NM_017315

SLC23A1

BE116526

SLC23A2

NM_133614

SLC25A21

BG666999

SLC25A4

NM_031664

SLC28A2

NM_031741 AA924432 AF249673 NM_017216 NM_133623

SLC2A5 SLC34A3 SLC38A2 SLC3A1 SLC6A13

NM_012694

SLC6A3

AI412218 NM_017348 M95413

SLC6A8 SLC6A8 SLC6A9

AF200684

SLC7A7

NM_053442

SLC7A8; SYNGAP1

AI577532 NM_021594 AI101171 Other AA858521 AF082125 BI278838

Gene name

SLC9A3R1 SLC9A3R1 SLCO3A1

Solute carrier family 14 (urea transporter), member 2 Peptide/histidine transporter PHT2 Similar to solute carrier family 16 (monocarboxylic acid transporters), member 4 Solute carrier family 1 (glial high affinity glutamate transporter), member 2 Solute carrier family 1 (glutamate/neutral amino acid transporter), member 4 Solute carrier family 20 (phosphate transporter), member 1 Solute carrier family 22 (organic anion transporter), member 19 Solute carrier family 22 (organic cation transporter), member 5 Solute carrier family 22 (organic anion transporter), member 8 Solute carrier family 23 (nucleobase transporters), member 1 Solute carrier family 23 (nucleobase transporters), member 2 Solute carrier family 25 (mitochondrial oxodicarboxylate carrier), member 21 Solute carrier family 25 (mitochondrial adenine nucleotide translocator) member 4 Solute carrier family 28 (sodium-coupled nucleoside transporter), member 2 Solute carrier family 2, member 5 Solute carrier family 34 (sodium phosphate), member 3 Solute carrier family 38, member 2 Solute carrier family 3, member 1 Solute carrier family 6 (neurotransmitter transporter, GABA), member 13 Solute carrier family 6 (neurotransmitter transporter, dopamine), member 3 Choline transporter Choline transporter Solute carrier family 6 (neurotransmitter transporter, glycine), member 9 Solute carrier family 7 (cationic amino acid transporter, yþ system), member 7 Solute carrier family 7 (cationic amino acid transporter, yþ system), member 8; synaptic Ras GTPase activating protein 1 homolog (rat) ERM-binding phosphoprotein ERM-binding phosphoprotein Solute carrier organic anion transporter family, member 3a1

AHR AHR NR1I3/CAR

Aryl hydrocarbon receptor Aryl hydrocarbon receptor Nuclear receptor subfamily 1, group I, member 3

4-month fold-change



2.18 1.8 1.73 1.86

1.65 11.32

1.56 1.58 3.17 1.63 1.63 7.44 3.09 3.7 1.62 2.39 3.76

4.12 1.55

2.75

1.89 1.54 4.12 1.63 1.51 1.75 2.27 3.06

2.03 4.02 1.94 1.82

2.24 2.13 1.92

Note. GABA, gamma-aminobutyric acid.

these complex age-related changes in XME expression will need to be determined using specific biochemical assays. Mori et al. (2007) determined changes in the expression of phase I and II genes between 32- and 84-week-old F344 rats

(Mori et al., 2007). Eleven out of the 21 phase I enzymes identified in our F344 study overlap with Mori’s list (ADH1, CES2, CES3, CYP1A2, CYP2A1, CYP2A2, CYP2C, CYP2D22, CYP3A2, FMO1, CYP3A18), and exhibit similar direction of


change. There were 4 out of 13 phase II enzymes from Mori’s list in common with our study and they all showed the same

279

direction of change; GSTP2 was upregulated, whereas GSST1, SULT1A2, and SULT1C2 were downregulated with age. In our study we showed that 7 efflux transporters were altered by age in either the F344 or BN rat (Table 2). ABCB1A, ABCC6, and ABCG5 were downregulated with age, whereas ABCB1, ABCC3, ABCG2, and TAP2 were upregulated with age. ABCB1A, ABCG5, ABCB1, and ABCG2 are transporters expressed on the canalicular membrane, responsible for biliary excretion of chemicals (Klaassen and Lu, 2008). ABCC6 and ABCC3 are present at high levels on the basolateral membrane of hepatocytes, responsible for efflux of substrates back into the blood (Klaassen and Lu, 2008). Two uptake transporters, SLC29A1 and SLCO1A4, which are expressed highly on the basolateral membrane of hepatocytes, were both downregulated with age. Overall these changes indicate complex effects of age on the expression of drug and xenobiotic transporters that may affect uptake and excretion. For the most part, enzymatic activity data were consistent with the trends from mRNA results, with the exception of CYP2C6. Several factors, including the rate of transcription initiation, mRNA stability, the efficiency of translation, as well as protein stability and modification, may account for discrepancies between gene expression and enzyme activity levels (Glanemann et al., 2003). A lack of specificity in the assays may also help to explain the differences seen between enzyme activity and gene expression. For example, EROD activity measures CYP1A1 as well as CYP2C6 activity. A number of studies in the literature examine age-related changes in CYP activity in rodents and humans. There are inconsistencies in these data. For example, in the present study, no changes were observed with PROD activity, a marker for CYP2B. In contrast, Birnbaum and Baird (1978) using 28- to 30-month-old male Wistar rats, showed a 25% decrease in CYP2B activity using benzphetamine as a substrate. It is likely that these differences are due to either the use of older animals or a different probe substrate in the studies by Birnbaum and Baird. In our F344 and BN rat comparison, we observed a limited overlap in the genes altered by age in the two strains (20 or 32% for F344 or BN, respectively). Out of these genes there was a remarkable concordance in the magnitude and direction of change due to age. One explanation for the number of nonoverlapping genes may originate in the way in which the control animals were treated. F344 rats were untreated whereas the BN rat controls received corn oil. There has been concern that oil vehicle used in administering chemicals by gavage may

FIG. 6. Hierarchical clustering of XMEs in BN rats exposed to 1 g/kg toluene. XMEs observed to be statistically altered after Cyber T analysis, in control (C) animals and animals exposed to the high dose (HD) of toluene, were clustered by gene and array (median centered). Values represent the log2 of the expression value. Red indicates an increase in gene expression, whereas green indicates a decrease in gene expression. Black represents no change in gene expression.

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TABLE 7 Top Functions in BN Rats Exposed to Toluene Identified Using Ingenuity 4 months Diseases and disorders Cancer Gastrointestinal disease Dermatological diseases and conditions Organismal injury and abnormalities Cardiovascular disease Molecular and cellular functions Cell morphology Lipid metabolism Molecular transport Small molecule chemistry Drug metabolism Physiological system development and function Tissue morphology Skeletal and muscular system development and function Nervous system development and function Organ morphology Endocrine system development and function

12 months

24 months

Hematological disease Immunological disease Cancer Reproductive system disease Skeletal and muscular disorders

Cancer Inflammatory disease Metabolic disease Gastrointestinal disease Connective tissue disorders

Cell cycle Cell death Cell-to-cell signaling and interaction Cellular growth and proliferation Cell morphology

Cell death Carbohydrate metabolism Lipid metabolism Molecular transport Small molecule biochemistry

Connective tissue development and function Hepatic system development and function Nervous system development and function Reproductive system development and function Tissue morphology

Immune response Connective tissue development and function Tissue morphology Organ morphology Hepatic system development and function

change the rate of ADME of a chemical, or may affect hormonal status, cell division or other factors that modify tumorigenic responses (Baker et al., 1981; Herzberg and Rogerson, 1981; Newberne et al., 1979). Vehicle controls from 2 year toxicological studies resulted in unusually high incidences of focal acinar hyperplasia and acinar adenoma in control F344/N rats receiving corn oil by gavage (Boorman and Eustis, 1984). Despite these limitations, data from gavage studies are valuable (Perera et al., 1989) and in our experiments show generally consistent age-dependent patterns of gene expression. Our study involved only a single gavage dose, and the dosing was completed four hours prior to the collection of tissues. Our age-dependent patterns of gene expression are also consistent with those found in previous studies (Mori et al., 2007; Thomas et al., 2002). Although we cannot rule out that corn oil may have affected gene expression, there is no indication that the effect is profound. We identified genes that exhibited differences in expression between males and females that are also targets for agedependent changes in expression. A comprehensive list of genes that exhibit gender differences in the young adult rat liver (Boedigheimer et al., 2008) was used to show that 9 and 8% of the aging genes in F344 and BN rats, respectively also exhibit differences in expression between genders. Most of the overlapping aging genes exhibited a more female-like expression pattern. This feminization of the gene expression pattern in the male rat liver with old age can be explained in part by decreases in plasma testosterone and increases in circulating estrogen levels with age (Fujita et al., 1990). Consistent with this, sulfotransferase 1E (STE) which metabolizes estrogen exhibited expression decreases by 23-fold in

our study. These hormonal changes can affect gene expression directly or indirectly by altering the gender-dependent release of GH from the pituitary gland (Waxman and O’Connor, 2006). Results from GSEA were consistent with our studies as the young animals exhibited expression changes that significantly overlapped with gene sets for androgen and androgen metabolism Based on the gene expression changes in the aged liver, we hypothesized that rats would exhibit altered transcriptional responses to xenobiotics including organic solvents. We tested this hypothesis by exposing young and old rats to toluene, with the understanding that baseline changes may not necessarily predict age-specific chemical induction responses. Toluene is metabolized to benzyl alcohol by CYPs, which is then oxidized by alcohol and aldehyde dehydrogenases to benzaldehyde and benzoic acid. Older rats exhibited a greater number of gene expression changes than younger rats after toluene exposure. There were four significantly altered genes in common among all age groups exposed to toluene, all of which were phase I genes (CYP26B1, CYP3A3, DHRS9, CYP2B2) with fold changes monotonically increasing. In a study by Nakajima and Wang (1994), six CYP isoenzymes were found to be involved in the metabolism of toluene in rat liver. They found toluene exposures induced CYP1A1/2, CYP2B1/2, CYP2E1, and CYP3A1, but decreased CYP2C11/6 and CYP2A1 in adult males. The inductive effect was more prominent in younger than in older animals and more prominent in males than in females. The male-specific CYP2C11 and CYP2E1 are the main P450 isoforms involved in toluene metabolism at high and low concentrations, respectively (Nakajima, 1997). Based on gene expression results in our study, CYP2B2 expression


281

FIG. 8. Changes in gene expression of CYP2B2 and CYP3A3 with age and toluene exposure (1 g/kg) in BN rats from microarray data.

FIG. 7. TFs altered by age and toluene exposure (p-value 0.05).

increased with increasing age and toluene exposure whereas CYP3A3 expression is similar in the 4 and 24 month groups exposed to 1 g/kg toluene (Fig. 8). Although involved in toluene metabolism, CYP2E1 expression may not have been detected because it is regulated at the protein level after ligand stabilization (Chien et al., 1997). Glutathione-S-transferase genes were altered to similar extents in all age groups by toluene exposure. However, a decrease in glutathione synthetase in the 24-month group was observed, suggesting increased toxicity with age due to diminished detoxification via conjugation by glutathione. The number of phase III genes being downregulated in the 24-month group increased from 7 to 19, (this includes efflux transporters ABCA1, ABCB1, ABCC1, ABCG2, ABCG5), whereas the number of phase III genes being upregulated decreased from 16 to 8, after exposure to toluene. Because efflux transporters were downregulated and no uptake transporters were altered after toluene exposure in aged rats, this suggests a reduced capacity to transport metabolites out of the body with age. Decreased amounts of glutathione, along with decreased levels of Phase III efflux transporters, may lead to increased levels of environmental chemicals in the livers of aging rats. These results suggest that an age-related decreased ability to detoxify and transport chemicals out of the body may lead to an increased susceptibility to chemicals in the aging population. In conclusion, we have comprehensively identified agedependent changes in genes involved in xenobiotic metabolism in the livers of untreated F344 and BN rats, and BN rats treated

with toluene. The long-term goal is to use this information to improve pharmacokinetic models of the aged by incorporating transcript profile information of the differences in XME gene expression between young and old populations and to predict the sensitivity of the aged to particular classes of chemicals. Based on gene expression changes, sulfation, glucuronidation, and glutathione conjugation pathways are affected by age. Age-related declines in many of the XMEs suggest decreased metabolic capacity with age in male rats. This finding has important implications for life stage susceptibility to environmental toxicants and impacts the interpretation of chronic studies when compared with short-term studies using young animals. An understanding of xenobiotic metabolism in young animals may not be relevant when analyzing gene expression or toxicity data from long-term studies, because internal dosimetry may change with the animal’s metabolic capacity. This decreased metabolic capacity in aging rats also impacts the response to chemicals and could increase susceptibility to chemicals such as pesticides, insecticides, herbicides, fungicides, PCBs, and organic solvents in aged animals. However, it may be possible that in cases in which the metabolite is more toxic than the chemical itself, decreases in gene expression of certain XMEs may provide a protective effect. Because humans metabolize chemicals in a manner similar to rodents, our comprehensive assessment of XME expression provides scientific support for conducting risk assessments that consider the aged as a susceptible subpopulation.

SUPPLEMENTARY DATA

Supplementary data are available online at http://toxsci. oxfordjournals.org/.

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FUNDING

U.S. Environmental Protection Agency; and Cooperative Training Agreement between the United States Environmental Protection Agency and North Carolina Central University (CT 829460) funded C.M.

ACKNOWLEDGMENTS

We thank the NHEERL Toxicogenomics Core for their input and advice, as well as assistance in using their equipment. We thank Mr Geremy Knapp for his guidance on qPCR experiments and Mr David Ross and Ms Vicki Richardson for technical assistance with the enzymatic assays. We thank Drs Don Delker, Robert MacPhail, Linda Birnbaum, and Andrew Geller for review of the manuscript. We also thank Ms Tanya Moore and Mr Mike George for their help during necropsies.

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