Transcriptomic profiles of aging in purified human immune cells

Springer Science and Business Media LLC - Tập 16 - Trang 1-17 - 2015
Lindsay M Reynolds1, Jingzhong Ding2, Jackson R Taylor3, Kurt Lohman4, Nicola Soranzo5, Alberto de la Fuente6, Tie Fu Liu2, Craig Johnson7, R Graham Barr8, Thomas C Register9, Kathleen M Donohue8, Monica V Talor10, Daniela Cihakova10, Charles Gu11, Jasmin Divers4, David Siscovick12, Gregory Burke1, Wendy Post10, Steven Shea8, David R Jacobs13, Ina Hoeschele14, Charles E McCall2,15, Stephen B Kritchevsky2,3, David Herrington2, Russell P Tracy16, Yongmei Liu1
1Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, USA
2Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, USA
3Department of Gerontology and Geriatric Medicine, J. Paul Sticht Center on Aging, Wake Forest School of Medicine, Winston-Salem, USA
4Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, USA
5CRS4 Bioinformatica, Pula, Italy
6FBN, Leibniz Institute for Farm Animal Biology, Genetics and Biometry, Mecklenburg-Vorpommern, Germany
7Departments of Medicine and Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, USA
8Departments of Medicine and Epidemiology, Columbia University, New York, USA
9Department of Pathology, Wake Forest School of Medicine, Winston-Salem, USA
10Department of Pathology, Johns Hopkins University, Baltimore, USA
11Division of Biostatistics, Washington University School of Medicine, St. Louis, USA
12New York Academy of Medicine, New York, USA
13Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, USA
14Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, USA
15Department of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, USA
16Department of Pathology, University of Vermont, Colchester, USA

Tóm tắt

Transcriptomic studies hold great potential towards understanding the human aging process. Previous transcriptomic studies have identified many genes with age-associated expression levels; however, small samples sizes and mixed cell types often make these results difficult to interpret. Using transcriptomic profiles in CD14+ monocytes from 1,264 participants of the Multi-Ethnic Study of Atherosclerosis (aged 55–94 years), we identified 2,704 genes differentially expressed with chronological age (false discovery rate, FDR ≤ 0.001). We further identified six networks of co-expressed genes that included prominent genes from three pathways: protein synthesis (particularly mitochondrial ribosomal genes), oxidative phosphorylation, and autophagy, with expression patterns suggesting these pathways decline with age. Expression of several chromatin remodeler and transcriptional modifier genes strongly correlated with expression of oxidative phosphorylation and ribosomal protein synthesis genes. 17% of genes with age-associated expression harbored CpG sites whose degree of methylation significantly mediated the relationship between age and gene expression (p < 0.05). Lastly, 15 genes with age-associated expression were also associated (FDR ≤ 0.01) with pulse pressure independent of chronological age. Comparing transcriptomic profiles of CD14+ monocytes to CD4+ T cells from a subset (n = 423) of the population, we identified 30 age-associated (FDR < 0.01) genes in common, while larger sets of differentially expressed genes were unique to either T cells (188 genes) or monocytes (383 genes). At the pathway level, a decline in ribosomal protein synthesis machinery gene expression with age was detectable in both cell types. An overall decline in expression of ribosomal protein synthesis genes with age was detected in CD14+ monocytes and CD4+ T cells, demonstrating that some patterns of aging are likely shared between different cell types. Our findings also support cell-specific effects of age on gene expression, illustrating the importance of using purified cell samples for future transcriptomic studies. Longitudinal work is required to establish the relationship between identified age-associated genes/pathways and aging-related diseases.

Tài liệu tham khảo

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