Gene expression profiling of aging reveals activation of a p53-mediated transcriptional program

BACKGROUND: Aging has been associated with widespread changes at the gene expression level in multiple mammalian tissues. We have used high density oligonucleotide arrays and novel statistical methods to identify specific transcriptional classes that may uncover biological processes that play a central role in mammalian aging. RESULTS: We identified 712 transcripts that are differentially expressed in young (5 month old) and old (25-month old) mouse skeletal muscle. Caloric restriction (CR) completely or partially reversed 87% of the changes in expression. Examination of individual genes revealed a transcriptional profile indicative of increased p53 activity in the older muscle. To determine whether the increase in p53 activity is associated with transcriptional activation of apoptotic targets, we performed RT-PCR on four well known mediators of p53-induced apoptosis: puma, noxa, tnfrsf10b and bok. Expression levels for these proapoptotic genes increased significantly with age (P < 0.05), while CR significantly lowered expression levels for these genes as compared to control fed old mice (P < 0.05). Age-related induction of p53-related genes was observed in multiple tissues, but was not observed in young SOD2(+/- )and GPX4(+/- )mice, suggesting that oxidative stress does not induce the expression of these genes. Western blot analysis confirmed that protein levels for both p21 and GADD45a, two established transcriptional targets of p53, were higher in the older muscle tissue. CONCLUSION: These observations support a role for p53-mediated transcriptional program in mammalian aging and suggest that mechanisms other than reactive oxygen species are involved in the age-related transcriptional activation of p53 targets

Metabolic Changes in Skin Caused by Scd1 Deficiency: A Focus on Retinol Metabolism

We previously reported that mice with skin-specific deletion of stearoyl-CoA desaturase-1 (Scd1) recapitulated the skin phenotype and hypermetabolism observed in mice with a whole-body deletion of Scd1. In this study, we first performed a diet-induced obesity experiment at thermoneutral temperature (33°C) and found that skin-specific Scd1 knockout (SKO) mice still remain resistant to obesity. To elucidate the metabolic changes in the skin that contribute to the obesity resistance and skin phenotype, we performed microarray analysis of skin gene expression in male SKO and control mice fed a standard rodent diet. We identified an extraordinary number of differentially expressed genes that support the previously documented histological observations of sebaceous gland hypoplasia, inflammation and epidermal hyperplasia in SKO mice. Additionally, transcript levels were reduced in skin of SKO mice for genes involved in fatty acid synthesis, elongation and desaturation, which may be attributed to decreased abundance of key transcription factors including SREBP1c, ChREBP and LXRα. Conversely, genes involved in cholesterol synthesis were increased, suggesting an imbalance between skin fatty acid and cholesterol synthesis. Unexpectedly, we observed a robust elevation in skin retinol, retinoic acid and retinoic acid-induced genes in SKO mice. Furthermore, SEB-1 sebocytes treated with retinol and SCD inhibitor also display an elevation in retinoic acid-induced genes. These results highlight the importance of monounsaturated fatty acid synthesis for maintaining retinol homeostasis and point to disturbed retinol metabolism as a novel contributor to the Scd1 deficiency-induced skin phenotype

Liver and Adipose Expression Associated SNPs Are Enriched for Association to Type 2 Diabetes

Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS

Genetic Networks of Liver Metabolism Revealed by Integration of Metabolic and Transcriptional Profiling

Although numerous quantitative trait loci (QTL) influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s) and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptinob/ob and the diabetes-susceptible BTBR leptinob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines). We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes

Gene expression profiling of aging reveals activation of a p53-mediated transcriptional program

Abstract Background Aging has been associated with widespread changes at the gene expression level in multiple mammalian tissues. We have used high density oligonucleotide arrays and novel statistical methods to identify specific transcriptional classes that may uncover biological processes that play a central role in mammalian aging. Results We identified 712 transcripts that are differentially expressed in young (5 month old) and old (25-month old) mouse skeletal muscle. Caloric restriction (CR) completely or partially reversed 87% of the changes in expression. Examination of individual genes revealed a transcriptional profile indicative of increased p53 activity in the older muscle. To determine whether the increase in p53 activity is associated with transcriptional activation of apoptotic targets, we performed RT-PCR on four well known mediators of p53-induced apoptosis: puma, noxa, tnfrsf10b and bok. Expression levels for these proapoptotic genes increased significantly with age (P +/- and GPX4+/- mice, suggesting that oxidative stress does not induce the expression of these genes. Western blot analysis confirmed that protein levels for both p21 and GADD45a, two established transcriptional targets of p53, were higher in the older muscle tissue. Conclusion These observations support a role for p53-mediated transcriptional program in mammalian aging and suggest that mechanisms other than reactive oxygen species are involved in the age-related transcriptional activation of p53 targets.</p