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. Author manuscript; available in PMC: 2009 Aug 1.
Published in final edited form as: Leukemia. 2008 Jul 3;23(2):391–393. doi: 10.1038/leu.2008.176

Decreased IRF8 Expression in Aging Hematopoietic Progenitor/Stem Cells

Derek L Stirewalt 1, Yongjae Edward Choi 1, Norman E Sharpless 2, Era L Pogosova-Agadjanyan 1, Michelle R Cronk 1, Michi Yukawa 3, Eric B Larson 4, Brent L Wood 5, Frederick R Appelbaum 1, Jerald P Radich 1, Shelly Heimfeld 1
PMCID: PMC2640437  NIHMSID: NIHMS77900  PMID: 18596738

Abstract

To determine how aging impacts gene expression in hematopoietic stem cells (HSCs), human CD34+ cells from bone marrow (BMCD34+) and mobilized stem cell products (PBCD34+38-) were examined using microarray-based expression profiling. The age-associated expression changes in CD34+ cells were then compared to age-associated expression changes in murine HSCs. Interferon regulatory factor 8 (IRF8) was the only gene with age-associated expression changes in all analyses, decreasing its expression in human CD34+ cells and murine HSCs. Microarray-based expression profiling found that IRF8 expression also decreased with aging in human T-cells, suggesting that the effects of aging on IRF8 expression may extend to more differentiated populations of hematopoietic cells. Quantitative-RT/PCR studies confirmed that IRF8 mRNA expression decreased with aging in additional samples of BMCD34+, PBCD34+38-, and T-cells, and IRF8 protein expression was found to decrease with aging and to correlate with mRNA levels in PBCD34+ cells. The results suggest that IRF8 may be a novel biomarker of aging for hematopoietic cells. Given that inactivation of IRF8 causes CML-like syndromes in mice and decreased IRF8 expression occurs in human hematopoietic malignancies, it will be critical to determine if decreased IRF8 expression plays a role in the increased incidence of hematopoietic malignancies in older adults.

Keywords: IRF8, hematopoietic stem cells, microarray, aging

Introduction

Hematopoietic stem cells (HSCs) from older mice display evidence of increased proliferation, cell cycle dysregulation, reduced repopulating potential, and increased myeloid skewing with differentiation.(1-3) In humans, the incidence of bone marrow failure and hematopoietic malignancies increases with aging,(4) leading one to speculate that the biological effects of aging in HSCs promote the development of hematopoietic diseases in older adults. Although recent studies have examined age-associated expression changes in long-term repopulating (LTR) murine HSCs,(5, 6) there are no studies examining the age-associated expression changes in similar populations of undifferentiated human cells. Therefore, we examined the age-associated expression changes in human CD34+, comparing the age-associated expression changes in human CD34+ cells to murine long-term repopulating (LTR) HSCs. These studies found that interferon regulatory factor-8 (IRF8) was the only gene with strong age-associated expression changes in all analyses, decreasing its expression in each cell type.

Materials and Methods

Additional information about study design, materials and methods section are provided in Supplement 1.

Acquisition of samples from healthy human donors

Bone marrow (BM), mobilized peripheral blood stem cells (PBSC), and peripheral blood (PB) were obtained under Institutional Review Board approved protocols according to the Declaration of Helsinki. Details about the donor information are provided in Supplement 2. CD34+ cells were selected from BM (BMCD34+) and PBSC (PBCD34+) using anti-CD34 immunomagnetic beads (Miltenyi Biotec, Auburn, CA), yielding highly enriched CD34+ products.(7) PBCD34+ samples with adequate amounts of material were further purified into a highly enriched population of PBCD34+/38- cells by flow-cytometiric sorting. Naïve T-cells were obtained through negative selection and expanded to obtain enough cells for RNA extraction.(8)

RNA extraction, hybridization, and microarrays analyses

RNA from human samples was extracted and was not pooled for studies.(9, 10) For BMCD34+ and T-cells, biotin-labeling of total RNA (5 μg) was performed as per standard Affymetrix protocol.(10) For the PBCD34+/38- arrays, the single-stranded linear amplification protocol was used to process RNA (100 nanograms) for the microarrays.(10) Biotin-labeled fragmented antisense cRNA (15 μg) was hybridized to HG-U133A arrays (Affymetrix, Santa Clara, CA).(10) Expression profiles of murine HSCs were available from two data sets: Rossi et al (GEO, GEO accession: GSE 4332) and Chambers et al. (GEO, GEO accession: GSE 6503).(5, 6)

Log2 expression signals were generated using robust multi-array average (gcRMA) and analyzed in GenePlus™ software (Enodar Biologic, Seattle, WA).(9, 11) All arrays met previously published quality control guidelines.(9) Demographic data and CEL files for the human data are available at the Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo). Age-associated expression changes were deemed to be statistically significant if their Z-scores were ≥ 4.75 or ≤ −4.75.(12, 13) Statistically significant genes with age-associated expression changes were loaded into Ingenuity® Pathways Analysis (IPA) software to determine the involvement of functional pathways (Ingenuity® Systems, www.ingenuity.com).(9)

Quantitative RT/PCR and western blots for IRF8 expression

Quantitative reverse transcription/polymerase chain reactions (Q-RT/PCR) were performed using universal TaqMan® conditions (Applied Biosystems, Foster City, CA).(9, 14) Copy numbers were computed using standard curves, corrected for RNA quality using beta-2 microglobulin (B2M) copy number, and normalized to the median T-cell expression.(15) Two-tailed Student’s t-tests and linear regression analyses were performed to determine statistical significance. Western blots were performed using 20 μg of protein.(15) Semi-quantification of the IRF8 protein was performed using ImageJ software.(16)

Results and Discussion

Age-associated expression changes in human CD34+ and CD34+38- cells

Microarray analyses of the BMCD34+ samples (N = 8, age range 16 – 51) and PBCD34+/38- samples (N = 4, age range 22 – 53) identified 161 and 917 genes, respectively, with age-associated expression changes (Supplement 3). The majority of these genes (approximately 65%) displayed an increased expression with age in both populations. Ten genes had similar age-associated expression changes in both data sets (Figure 1a and Supplement 3). Functional pathways affected most significantly by aging included gene expression, cellular proliferation, cancer, and cellular development (Supplement 3).

Figure 1. Overlap of Age-Associated Expression Changes in Human CD34+ cells and Murine HSCs.

Figure 1

Figure 1

Figure 1

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a. Shows the overlap of significant genes with age-associated expression changes between human CD34+ cells from the BM (BMCD34+) and human CD34+38- cells from mobilized stem cell products (PBCD34+38-). Ten genes displayed similar age-associated expression changes in both analyses. b. Shows the overlap of significant genes with age-associated expression changes between human BMCD34+ and murine HSCs from the Chambers and Rossi data sets. Two genes (IRF8 and RAB40B) displayed similar age-associated expression changes in all three analyses. c. Shows the overlap of significant genes with age-associated expression changes between human PBCD34+38- and murine HSCs from the Chambers and Rossi data sets. Three genes (IRF8, NDRG1, and NEO1) displayed similar age-associated expression changes in all three analyses.

Overlap of age-associated expression changes between human CD34+ cells and murine HSCs

Although the human BMCD34+ and PBCD34+38- cells were enriched for HSCs, these CD34+ cells do not represent a pure population of LTR HSCs. Recently, Rossi et al. and Chambers et al. isolated near-homogeneous populations of murine LTR HSCs and examined their age-associated expression changes.(5, 6) Although these murine studies have provided important insights into the age-associated expression changes in HSCs, interspecies differences have been reported.(17) We wondered which age-associated expression changes in the human CD34+ cells also occurred in murine LTR HSCs, believing that genes with age-associated expression changes conserved across species would be of particular interest for future functional studies.

Therefore, we examined the expression profiles of murine HSCs from the Rossi and Chambers studies.(5, 6) Analyses for each data set were performed independently of one another, since different murine array platforms were used. We identified 494 and 3359 genes with age-associated expression changes from the Rossi and Chambers studies, respectively. Eighty-four genes displayed age-associated expression changes in both murine data sets (Supplement 4). We then determined those genes with age-associated expression changes in human CD34+ cells that had at least one probe set represented on either the murine 430-2 and/or MOE430 arrays. Approximately 91% (147 of 161) and 86% (789 of 917) of the genes with age-associated expression changes in human BMCD34+ and PBSC34+38- cells, respectively, had probe sets on at least one of murine arrays (Supplement 3). Examining the overlap of genes with significant expression changes with aging conserved across human CD34+ cells and murine HSCs, only one gene, IRF8, displayed an age-associated expression change in all four analyses (Figure 1), decreasing its expression with aging in all cell types examined (Supplement 4).

Age-associated expression changes in human T-Cells

To determine if similar age-associated expression changes occurred in more differentiated hematopoietic cells, we compared the expression profiles of expanded T-cells from younger (age ≤ 30) and older (age > 70) normal donors. The analyses identified 13 genes with age-associated expression changes (increased = 4 and decreased = 9, Supplement 5). IRF8 was one of the 13 genes with age-associated expression changes in human T-cells. As with the human CD34+ cells and murine LTR HSCs, IRF8 expression was significantly decreased in older adults.

Validation of decreased IRF8 expression in aging human hematopoietic cells

Q-RT/PCR studies using Taqman assays found that IRF8 expression decreased with aging in BMCD34+ (N = 6, R = 0.77, p = 0.07), PBCD34+38-, (N = 2, p = N/A), and T-cells (N = 26, p = 0.001) (Supplement 6). Thus, the Q-RT/PCR studies confirm the microarray data and age-associated decrease in IRF8 mRNA expression in human hematopoietic progenitor/HSCs and T-cells. Studies in cell lines have found that IRF8 mRNA and protein expression parallel one another, such that IRF8 mRNA expression may provide a reasonable estimate of relative amount protein expression.(18) However, to assess the relationship between mRNA and protein expression in nonimmortalized human hematopoietic cells, we simultaneously examined IRF8 mRNA and protein expression in the PBCD34+ samples from 5 donors. Q-RT/PCR and protein assays (Figure 2a) demonstrated a simultaneous age-associated decrease in IRF8 expression (mRNA, Figure 2B, R = 0.90, p = 0.04 and protein, Figure 2b, R = 0.91, p = 0.03). Together, the data indicates IRF8 mRNA and protein expression parallel one another in non-immortalized cells, and its protein expression significantly decreases in human CD34+ cells with aging.

Figure 2. Age-Associated Expression Changes of IRF8 Protein and mRNA Levels in PBCD34+ Cells.

Figure 2

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a. Western blot for IRF8 (upper blot) and GAPDH (lower blot) was performed using protein lysates (20 μg) from 5 PBCD34+ samples. IRF8 expression appeared to be highest in the 27 year old donor and lowest in the 63 and 72 year old donors. b. Q-RT/PCR was performed in triplicate using RNA from the same 5 samples. IRF8 mRNA expression (y-axis, right side) corrected for B2M and adjusted to median T-cell expression is show for each sample (closed circles, •). Regression analysis revealed a significant decrease in expression with donor age (R = 0.90, p = 0.04). Semi-quantification of IRF8 protein expression was performed using the western blot from Figure 2a and ImageJ software. IRF8 protein expression was corrected for GAPDH signal. The relative amount of corrected IRF8 protein signal is shown for each sample (closed squares, ■). As with the mRNA data, regression analysis revealed a significant age-associated decrease in IRF8 protein expression (R = 0.91, p = 0.03).

Conclusion

To our knowledge, this is the first report to identify IRF8 as a potential biomarker of aging. Likewise, it is the first study to compare the age-associated expression changes between human CD34+ cells and murine HSCs. Previous studies have established that IRF8, a transcription factor, plays a critical role in normal hematopoiesis, controlling the transcription of several pivotal regulatory genes (NF1, BCL2, p15Ink4b).(19-21) Inactivation of IRF8 causes a chronic myeloid leukemia-like syndrome in mice, (22-24) and leukemic blasts frequently display decreased IRF8 expression, suggesting a possible link to malignant transformation in humans.(25, 26) It is intriguing to postulate that perhaps the loss of IRF8 expression in the aging hematopoietic cells may contribute to the skewing toward myeloid commitment of HSC and/or increased development of hematopoietic diseases in older adults. However, additional studies are needed to better characterize the age-associated expression changes of IRF8 in other hematopoietic cells (e.g. monocytes, B-cells, etc.) and to examine the functional consequences of its decreased expression with aging.

Supplementary Material

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Acknowledgments

Acknowledgments: This research was supported by the following NIH Grants: AG06781, CA92405, CA114563, CA114563, CA018029, HL66947, CA018029, and DK56465.

Footnotes

Conflict-of-interest disclosure: The authors declare no competing financial interests

References

  • 1.Morrison SJ, Wandycz AM, Akashi K, Globerson A, Weissman IL. The aging of hematopoietic stem cells. Nat Med. 1996;2:1011–6. doi: 10.1038/nm0996-1011. [DOI] [PubMed] [Google Scholar]
  • 2.Janzen V, Forkert R, Fleming HE, Saito Y, Waring MT, Dombkowski DM, et al. Stem-cell ageing modified by the cyclin-dependent kinase inhibitor p16INK4a. Nature. 2006;443:421–6. doi: 10.1038/nature05159. [DOI] [PubMed] [Google Scholar]
  • 3.Liang Y, Van Zant G, Szilvassy SJ. Effects of aging on the homing and engraftment of murine hematopoietic stem and progenitor cells. Blood. 2005;106:1479–87. doi: 10.1182/blood-2004-11-4282. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.NCI . SEER Cancer Statistics Review 1975-2003. National Cancer Institute; 2004. [Accessed January 1, 2008]. http://seer.cancer.gov/csr/1975_2004/ [Google Scholar]
  • 5.Rossi DJ, Bryder D, Zahn JM, Ahlenius H, Sonu R, Wagers AJ, et al. Cell intrinsic alterations underlie hematopoietic stem cell aging. Proc Natl Acad Sci USA. 2005;102:9194–9. doi: 10.1073/pnas.0503280102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Chambers SM, Shaw CA, Gatza C, Fisk CJ, Donehower LA, Goodell MA. Aging hematopoietic stem cells decline in function and exhibit epigenetic dysregulation. PLoS Biol. 2007;5:e201. doi: 10.1371/journal.pbio.0050201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Colter M, Jones M, Heimfeld S. CD34+ progenitor cell selection: clinical transplantation, tumor cell purging, gene therapy, ex vivo expansion, and cord blood processing. J Hematother. 1996;5:179–84. doi: 10.1089/scd.1.1996.5.179. [DOI] [PubMed] [Google Scholar]
  • 8.Levine BL, Mosca JD, Riley JL, Carroll RG, Vahey MT, Jagodzinski LL, et al. Antiviral effect and ex vivo CD4+ T cell proliferation in HIV-positive patients as a result of CD28 costimulation. Science. 1996;272:1939–43. doi: 10.1126/science.272.5270.1939. [DOI] [PubMed] [Google Scholar]
  • 9.Stirewalt DL, Meshinchi S, Kopecky KJ, Fan W, Pogosova-Agadjanyan EL, Engel JH, et al. Identification of genes with abnormal expression changes in acute myeloid leukemia. Genes Chromosomes Cancer. 2007 doi: 10.1002/gcc.20500. [DOI] [PubMed] [Google Scholar]
  • 10.Stirewalt DL, Pogosova-Agadjanyan EL, Khalid N, Hare DR, Ladne PA, Sala-Torra O, et al. Single-stranded linear amplification protocol results in reproducible and reliable microarray data from nanogram amounts of starting RNA. Genomics. 2004;83:321–31. doi: 10.1016/j.ygeno.2003.08.008. [DOI] [PubMed] [Google Scholar]
  • 11.Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4:249–64. doi: 10.1093/biostatistics/4.2.249. [DOI] [PubMed] [Google Scholar]
  • 12.Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA. 2003;100:9440–5. doi: 10.1073/pnas.1530509100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Xu XL, Olson JM, Zhao LP. A regression-based method to identify differentially expressed genes in microarray time course studies and its application in an inducible Huntington’s disease transgenic model. Hum Mol Genet. 2002;11:1977–85. doi: 10.1093/hmg/11.17.1977. [DOI] [PubMed] [Google Scholar]
  • 14.Tse W, Meshinchi S, Alonzo TA, Stirewalt DL, Gerbing RB, Woods WG, et al. Elevated expression of the AF1q gene, an MLL fusion partner, is an independent adverse prognostic factor in pediatric acute myeloid leukemia. Blood. 2004;104:3058–3063. doi: 10.1182/blood-2003-12-4347. [DOI] [PubMed] [Google Scholar]
  • 15.Stirewalt DL, Appelbaum FR, Willman CL, Zager RA, Banker DE. Mevastatin can increase toxicity in primary AMLs exposed to standard therapeutic agents, but statin efficacy is not simply associated with ras hotspot mutations or overexpression. Leuk Res. 2003;27:133–45. doi: 10.1016/s0145-2126(02)00085-1. [DOI] [PubMed] [Google Scholar]
  • 16.Rasband WS. ImageJ. U. S. National Institutes of Health, Bethesda, Maryland, USA 1997 - 2007. http://rsb.info.nih.gov/ij/ Accessed December 03, 2007
  • 17.Mestas J, Hughes CC. Of mice and not men: differences between mouse and human immunology. J Immunol. 2004;172:2731–8. doi: 10.4049/jimmunol.172.5.2731. [DOI] [PubMed] [Google Scholar]
  • 18.Yang D, Thangaraju M, Greeneltch K, Browning DD, Schoenlein PV, Tamura T, et al. Repression of IFN regulatory factor 8 by DNA methylation is a molecular determinant of apoptotic resistance and metastatic phenotype in metastatic tumor cells. Cancer Res. 2007;67:3301–9. doi: 10.1158/0008-5472.CAN-06-4068. [DOI] [PubMed] [Google Scholar]
  • 19.Burchert A, Cai D, Hofbauer LC, Samuelsson MK, Slater EP, Duyster J, et al. Interferon consensus sequence binding protein (ICSBP; IRF-8) antagonizes BCR/ABL and down-regulates bcl-2. Blood. 2004;103:3480–9. doi: 10.1182/blood-2003-08-2970. [DOI] [PubMed] [Google Scholar]
  • 20.Schmidt M, Bies J, Tamura T, Ozato K, Wolff L. The interferon regulatory factor ICSBP/IRF-8 in combination with PU.1 up-regulates expression of tumor suppressor p15(Ink4b) in murine myeloid cells. Blood. 2004;103:4142–9. doi: 10.1182/blood-2003-01-0285. [DOI] [PubMed] [Google Scholar]
  • 21.Zhu C, Saberwal G, Lu Y, Platanias LC, Eklund EA. The interferon consensus sequence-binding protein activates transcription of the gene encoding neurofibromin 1. J Biol Chem. 2004;279:50874–85. doi: 10.1074/jbc.M405736200. [DOI] [PubMed] [Google Scholar]
  • 22.Holtschke T, Lohler J, Kanno Y, Fehr T, Giese N, Rosenbauer F, et al. Immunodeficiency and chronic myelogenous leukemia-like syndrome in mice with a targeted mutation of the ICSBP gene. Cell. 1996;87:307–17. doi: 10.1016/s0092-8674(00)81348-3. [DOI] [PubMed] [Google Scholar]
  • 23.Schwieger M, Lohler J, Friel J, Scheller M, Horak I, Stocking C. AML1-ETO inhibits maturation of multiple lymphohematopoietic lineages and induces myeloblast transformation in synergy with ICSBP deficiency. J Exp Med. 2002;196:1227–40. doi: 10.1084/jem.20020824. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Turcotte K, Gauthier S, Tuite A, Mullick A, Malo D, Gros P. A mutation in the Icsbp1 gene causes susceptibility to infection and a chronic myeloid leukemia-like syndrome in BXH-2 mice. J Exp Med. 2005;201:881–90. doi: 10.1084/jem.20042170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Schmidt M, Hochhaus A, Nitsche A, Hehlmann R, Neubauer A. Expression of nuclear transcription factor interferon consensus sequence binding protein in chronic myeloid leukemia correlates with pretreatment risk features and cytogenetic response to interferon-alpha. Blood. 2001;97:3648–50. doi: 10.1182/blood.v97.11.3648. [DOI] [PubMed] [Google Scholar]
  • 26.Diaz-Blanco E, Bruns I, Neumann F, Fischer JC, Graef T, Rosskopf M, et al. Molecular signature of CD34(+) hematopoietic stem and progenitor cells of patients with CML in chronic phase. Leukemia. 2007;21:494–504. doi: 10.1038/sj.leu.2404549. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp Five
NIHMS77900-supplement-Supp_Five.doc (34.5KB, doc)
Supp Four
NIHMS77900-supplement-Supp_Four.doc (393KB, doc)
Supp One
NIHMS77900-supplement-Supp_One.doc (120.5KB, doc)
Supp Six
NIHMS77900-supplement-Supp_Six.doc (578.5KB, doc)
Supp Three
NIHMS77900-supplement-Supp_Three.doc (2MB, doc)
Supp Two
NIHMS77900-supplement-Supp_Two.doc (117KB, doc)

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