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Logo of bioMary Ann Liebert, Inc.Mary Ann Liebert, Inc.JournalsSearchAlerts
Biopreservation and Biobanking
 
Biopreserv Biobank. 2010 September; 8(3): 153–162.
PMCID: PMC3129811
NIHMSID: NIHMS251480

Gene Expression Profiles from Peripheral Blood Mononuclear Cells Are Sensitive to Short Processing Delays

Abstract

In the analysis of peripheral blood gene expression, timely processing of samples is essential to ensure that measurements reflect in vivo biology, rather than ex vivo sample processing variables. The effect of processing delays on global gene expression patterns in peripheral blood mononuclear cells (PBMCs) was assessed by isolating and stabilizing PBMC-derived RNA from 3 individuals either immediately after phlebotomy or after a 4 h delay. RNA was labeled using NuGEN Ovation labeling and probed using the Affymetrix HG U133 Plus 2.0 GeneChip®. Comparison of gene expression levels (≥2-fold expression change and P < 0.05) identified 307 probe sets representing genes with increased expression and 46 indicating decreased expression after 4 h. These differentially expressed genes include many that are important to inflammatory, immunologic, and cancer pathways. Among others, CCR2, CCR5, TLR10, CD180, and IL-16 have decreased expression, whereas VEGF, IL8, SOCS2, SOCS3, CD69, and CD83 have increased expression after a 4 h processing delay. The trends in expression patterns associated with delayed processing were also apparent in an independent set of 276 arrays of RNA from human PBMC samples with varying processing times. These data indicate that the time between sample acquisition, initiation of processing, and when the RNA is stabilized should be a prime consideration when designing protocols for translational studies involving PBMC gene expression analysis.

Introduction

Biobanking practices require support from evidence-based biospecimen science to ensure that findings are due to in vivo biological differences rather than ex vivo influences. This is especially important in global gene expression studies such as those using Affymetrix GeneChips® that monitor the expression level of ~47,000 transcripts from a single sample and can be highly sensitive to preanalytical variability.

Although several studies have examined the effect of preanalytical variables on global gene expression in solid tissues13 (among others), much less is known concerning the effect of delayed isolation of peripheral blood mononuclear cells (PBMCs). In one study comparing aliquots of PBMCs processed immediately or after overnight shipping to a single processing center, 2034 out of 6414 genes were found differentially expressed.4 Independently, Affymetrix, Inc., identified extensive expression pattern changes in PBMC samples due to overnight processing delays.5

In this study we identified gene expression changes in PBMCs related to processing delays as short as 4 h. These patterns were also apparent in an independent set of 276 arrays with variable processing times.

Materials and Methods

Subjects

Blood samples from adult volunteers were used to examine the processing time variable directly. In addition, data were available from a large, multicenter, gene expression study related to juvenile idiopathic arthritis (JIA). Patients in the JIA study were followed for up to 2 years and blood samples were collected at up to 10 time points for each patient. Blood was collected after informed consent.

Sample processing

Sample processing has been detailed elsewhere.68 Briefly, peripheral blood was collected in acid citrate dextrose (ACD) tubes, and PBMCs were isolated over Ficoll gradient (Ficoll Paque™ Plus; GE Healthcare, Piscataway, NJ) and put into TRIzol® reagent (Invitrogen, Carlsbad, CA) for 5 min at room temperature before slow cooling (−1°C/min), and storage at −80°C. The time between phlebotomy and start of processing is defined as the “processing delay.” The time between phlebotomy and storage at −80°C is defined as “time to freezing” (TTF). RNA was extracted and purified using RNeasy columns (Qiagen, Germantown, MD). cDNA was prepared using NuGEN Ovation kit version 1 (NuGEN Technologies, San Carlos, CA) from 100 ng of RNA and assayed using Affymetrix HG U133 Plus 2.0 GeneChips (Affymetrix, Santa Clara, CA). The timecourse microarray dataset has been deposited in the Gene Expression Omnibus at the National Center for Biotechnology Information (NCBI) and is accessible through GEO Series access number GSE21039.

Statistical analysis

Data were preprocessed in GeneSpring GX 7.3.1 using robust multichip analysis.9 Probe sets representing differentially expressed genes were defined as those with ≥2-fold expression difference and P < 0.05. Hierarchical clustering used Pearson correlation for probe sets and distance correlation for samples. To allow comparison to probe sets reported in the literature using an earlier version GeneChip, a conversion was performed using the GeneSpring 7.3 “translate” function.

Results

Short processing delays alter gene expression

Three tubes of blood were collected from a single venipuncture from each of 3 donors, and PBMCs were isolated after a 0 h (T0), 2 h (T2), or 4 h (T4) delay at room temperature. Comparing GeneChip signal intensity values between T0 and T4 identified 353 probe sets detecting differentially expressed genes (select probe sets in Table 1, and full list in the Appendix. Hierarchical clustering of the samples using these probe sets completely segregated the samples into their respective processing-time category (Fig. 1A).

FIG. 1.
Processing effects of gene expression signatures. (A) Samples clustered according to 353 probe sets identified (P < 0.05 and fold-change ≥2-fold) representing genes differentially expressed between samples processed immediately ...
Table 1.
Selected Genes of Immunological Importance

Response to overnight processing delays is different

In a previous report, Baechler et al. identified 2155 probe sets (2082 HG U133 Plus 2.0 equivalents) measuring differentially expressed genes between peripheral bloods processed to PBMCs immediately and those bloods shipped by overnight courier before processing.4 Understanding that there were significant experimental differences between the 2 studies, the current list of 353 probe sets was compared and showed only 62 probe sets (17%) in common. Although there were clusters of genes that appeared different in samples with delayed processing, the 2082 probe sets were unable to distinguish the current samples according to processing time (Fig. 1B).

Validation in a larger cohort

To determine whether the processing time signature would be apparent in samples that exhibit variation in gene expression for other reasons, the expression pattern (shown as the average of the expression levels for observation purposes) was examined in an independent group of 276 arrays (Fig. 2). The PBMC samples were obtained either from healthy controls or from patients with JIA and TTF ranged from 60 to 315 min. Although these samples showed some variation (possibly indicating biological variation between samples), trends of expression changes due to processing time were evident (Fig. 2). The trend was apparent in samples from each clinical site and each disease subtype showing that the processing time effect is independent of either clinical site or disease state (data not shown).

FIG. 2.
Average expression levels of time-sensitive probe sets. In a pilot experiment, 307 probe sets were identified with increased expression and 46 with decreased expression after a 4 h processing delay. Average expression of probe sets with increased ...

Discussion

Many studies have reported gene expression differences in PBMCs without providing details of sample processing procedures. This study highlights the importance of considering processing delays since periods as short as 4 h can have significant effects on gene expression. While additional studies with independent samples are necessary to define specific processing gene expression signatures, it is clear that processing delays must be considered in experimental design and data interpretation.

This study was not designed to determine the specific cause of the identified gene expression changes although several explanations can be hypothesized. Phlebotomy itself can have an influence on lab results obtained from blood samples.10 Regarding storage of samples after phlebotomy, a previous study looked at the effect of room temperature storage of serum and plasma.11 Within 4 h after phlebotomy, the environment of the plasma and serum sample changed significantly, which would cause biological stresses. Glucose levels dropped, lactate increased, pH decreased, and hypoxia were identified by a decrease in pO2 and an increase in pCO2. Although this study did not examine the effect of blood processing delays, it can be expected that similar effects would be encountered. Even the simple preanalytical variables of the additive in the collection tube (eg, ACD in this study) or interaction of cells with the surface of the tube itself (a significant change from the vasculature of the donor) for several hours may cause the identified gene expression changes.

Proteins derived from the genes listed in Table 1 are important in inflammatory, autoimmune, and cancer pathways. Vascular endothelial growth factor (VEGF) is a prototypical angiogenic factor,12 and anti-VEGF has become the standard treatment for many tumor types.13 CCR2, CCR5, and IL-8 are chemoattractants that activate and recruit immune cells to sites of infection and inflammation. Antagonists to CCR2 have been suggested as therapy for a variety of inflammatory diseases as well as obesity and pulmonary disease.14 The CCR5 (also called CD195) antagonist, Maraviroc, is currently approved for treatment of HIV infection.15 SOCS2 and 3 are key negative regulators of cytokine signaling.16 TLR10 and CD180 (RP105) are involved in toll-like receptor signaling. The fact that these genes have variable expression attributable to processing delays emphasizes the importance of attention to preanalytic variables in sample collection and processing, a fundamental component of biospecimen science.

Various strategies can be employed to address possible changes caused by processing delays. The method we chose to reduce the impact of this variable was to remove samples with extended processing times (>4 h) from analysis.68 As an alternative, time-sensitive genes may be removed from consideration.17 Both of these methods have the benefit of simplicity although specific cutoffs are arbitrary. A disadvantage of this approach is that time-sensitive genes might also be involved in pathogenic processes. An interesting, but untested, method would be to delay processing of all samples until a specified time postphlebotomy (eg, 2 h) to reduce this variability. Alternatively, statistical approaches such as linear modeling may be employed using processing time as 1 variable.

To avoid the effect of variable processing time, technologies that stabilize samples instantly have been developed. These methods collect whole blood, including neutrophils that tend to vary in number more than other cellular components, and metabolically active immature red blood cells. Together, these components may overshadow more biologically relevant PBMCs. Additionally, there are issues with the so-called globin effect, where excessive amounts of globin mRNA derived from the reticulocytes present in whole blood interfere with the microarray analysis as seen by decreased present calls.5 It is unclear if this occurs due to inhibition during the labeling or probing steps of the assay. Newer labeling systems may help overcome this issue (as indicated by recovery of detected genes; unpublished data).

It is evident from this study that processing delays affect gene expression patterns obtained from PBMCs in a very short period. It is, therefore, important for this variable to be measured so that its effect can be considered in data interpretation.

Appendix. Three Hundred Fifty-Three Probe Sets Indicating Genes with Differential Expression Between T0 and T4 Samples

 
 
Fold changeb
Probe IDaGene symbol2 h/0 hc4 h/0 hd
204622_x_atNR4A25.28778.9551
216248_s_atNR4A25.41058.8413
205239_atAREG///LOC6531934.63438.1447
36711_atMAFF4.71117.0973
213933_atPTGER33.24066.4005
219312_s_atZBTB102.72235.8898
202464_s_atPFKFB33.2665.8483
208078_s_atSNF1LK4.15685.8328
208937_s_atID13.91895.8208
203821_atHBEGF3.15825.7492
217739_s_atPBEF1///RP11-92J19.42.91295.6252
1554309_atEIF4G32.62475.4238
209967_s_atCREM3.46715.2409
233899_x_atZBTB102.40145.2317
228562_at2.9015.2283
213524_s_atG0S23.7725.1801
207630_s_atCREM3.53285.1701
224454_atETNK12.82825.1389
230511_atCREM3.79465.1284
204621_s_atNR4A23.2355.0914
214508_x_atCREM3.42165.049
222309_atC6orf622.46264.8293
219228_atZNF3312.65574.6216
218880_atFOSL22.85454.4736
222180_atYES12.53144.4144
240038_atELL22.60194.3908
202861_atPER12.69544.3866
201466_s_atJUN1.7814.2976
204141_atTUBB2A2.79174.231
202859_x_atIL82.52254.0768
241740_atCREM3.54683.9794
227613_atZNF3312.49383.8653
1552908_atC1orf1502.61133.7847
38037_atHBEGF2.15293.771
225262_atFOSL22.88673.7097
201464_x_atJUN1.91943.6948
205548_s_atBTG32.29153.6902
236495_atPBEF11.60753.6901
233952_s_atZNF2951.95523.5791
1562255_atSYTL32.3353.5712
1559975_atBTG12.41783.5277
210512_s_atVEGF1.88863.4847
204440_atCD832.19593.4748
228062_atNAP1L52.35743.4686
230133_atMNAB2.50673.4311
203543_s_atKLF92.18233.4159
222044_at2.20313.3953
1554036_atZBTB242.7723.3849
225884_s_atZNF3362.26383.3824
204286_s_atPMAIP11.85843.3814
242712_x_atLOC653086///LOC653489///LOC6535961.88873.3689
1556361_s_atANKRD13C1.88043.3257
1568665_atRNF1032.29753.3193
213134_x_atBTG32.21663.3135
1557257_atBCL102.13353.3121
217738_atPBEF12.03893.3118
1569136_atMGAT4A2.40023.3043
231182_atWASPIP2.29773.2973
242243_atTMF11.56833.2954
222815_atRNF121.75083.2557
211506_s_atIL82.26513.2343
60084_atCYLD1.8623.2292
210837_s_atPDE4D1.96353.2114
202643_s_atTNFAIP32.56433.2094
241985_atJMY1.86443.2086
1555476_atIREB22.55533.2083
211458_s_atGABARAPL1///GABARAPL32.23233.1766
203574_atNFIL32.03923.1158
219622_atRAB201.71223.0976
1569263_atSLC16A32.04313.0744
218319_atPELI11.97413.0721
208869_s_atGABARAPL11.85083.0551
242903_atIFNGR11.59033.044
243664_atTXNL11.61323.0196
232044_atRBBP62.02523.0159
225539_atZNF2951.85823.0102
219094_atARMC81.88753.001
226370_atKLHL152.03542.997
202672_s_atATF31.48942.9967
233127_atZNF3311.79272.9944
221986_s_atKLHL241.82262.966
1555167_s_atPBEF12.07412.9628
1554306_atITPKB2.17932.9596
228063_s_atNAP1L52.36322.959
243857_atMORF4L21.31432.9586
229718_atCG0182.00912.949
238796_atYTHDC11.93382.9354
233309_atTMEM22.01132.9252
203372_s_atSOCS22.05052.9183
202558_s_atSTCH1.78332.8712
235592_atELL21.66392.8409
1553134_s_atC9orf721.79962.8148
202932_atYES11.63962.8141
205214_atSTK17B2.11982.7996
1555963_x_atB3GNT71.91412.7986
204285_s_atPMAIP11.69052.795
1553861_atTCP11L21.86322.7942
231990_atUSP151.9452.7884
202644_s_atTNFAIP32.30372.7877
211924_s_atPLAUR1.65852.7822
226608_atLOC3882721.82142.7687
213281_atJUN1.39262.7683
242176_atMEF2A1.87622.7647
221563_atDUSP101.45042.7587
202499_s_atSLC2A31.93532.7522
1556239_a_atHERPUD22.09262.7461
205281_s_atPIGA1.77892.738
228846_atMXD11.8382.7347
209545_s_atRIPK21.7632.7331
210845_s_atPLAUR1.70882.7267
228181_atSLC30A11.45272.7179
1554037_a_atZBTB242.25922.7114
225955_atMED25///METRNL///LOC6535062.15262.6876
222624_s_atZNF6392.2032.6807
214696_atMGC143762.06272.6761
226275_atMXD11.77892.6754
209803_s_atPHLDA21.33852.6439
218486_atKLF111.88412.641
224352_s_atCFL21.89992.6398
202843_atDNAJB91.87692.6257
227309_atYOD11.81952.6186
222142_atCYLD1.56232.6162
227718_atPURB1.65922.6145
1555274_a_atSELI1.63112.6088
225557_atAXUD12.13342.5998
213758_atCOX4I12.10922.5914
203751_x_atJUND1.99642.5908
202988_s_atRGS11.83812.5897
1555281_x_atARMC81.96122.5884
210836_x_atPDE4D1.93322.5716
204014_atDUSP41.72192.5612
225950_atSAMD81.75272.555
228962_at2.47112.552
211137_s_atATP2C11.662.5507
209457_atDUSP52.3522.5505
209020_atC20orf1111.8692.5422
230134_s_atMNAB1.92442.5405
202241_atTRIB11.50142.539
230802_at1.87122.5229
207361_atHBP11.9722.5225
202393_s_atKLF101.74472.5212
1555962_atB3GNT72.0532.5179
218009_s_atPRC11.73052.5112
203373_atSOCS21.52952.5006
222088_s_atSLC2A32.07132.4999
202498_s_atSLC2A31.97172.499
1553133_atC9orf721.75132.4989
234993_atABHD131.80742.4978
238389_s_at1.68742.4961
204958_atPLK32.01592.4923
224739_atPIM31.86822.4803
1557285_atLOC6531931.5132.4758
211302_s_atPDE4B2.6062.4689
242669_atUFM11.5572.4684
224657_atERRFI12.19922.4629
223584_s_atKBTBD21.78452.4509
232576_at1.91552.4416
239143_x_atRNF1381.6522.4353
1552644_a_atPHC31.82042.4195
235780_atPRKACB1.70882.4114
201465_s_atJUN1.33372.4088
206374_atDUSP81.74252.4062
218311_atMAP4K31.55262.4006
226811_atFAM46C2.1152.3995
1554549_a_atWDR201.91782.3993
211423_s_atSC5DL1.85312.3989
1557459_atSNF1LK21.50472.395
216834_atRGS11.72352.3864
213805_atABHD51.48632.3721
201195_s_atSLC7A51.68342.372
37028_atPPP1R15A1.42212.3542
203542_s_atKLF91.49912.3531
212665_atTIPARP1.88482.346
243463_s_atRIT11.33482.3438
229899_s_atHSUP11.84622.3411
215501_s_atDUSP101.4842.3342
224797_atARRDC31.81742.3328
201745_atPTK91.81152.3255
224453_s_atETNK11.49332.3238
215889_atSKIL1.33782.3207
230170_atOSM2.2652.2923
226345_at1.672.2914
236223_s_atRIT11.19632.2896
234907_x_atPOLB1.64982.2841
200731_s_atPTP4A11.8112.2823
202497_x_atSLC2A322.2822
216236_s_atSLC2A32.02042.2787
214326_x_atJUND1.6972.2744
202014_atPPP1R15A1.47262.2677
204908_s_atBCL31.8242.2656
206877_atMXD11.96772.2589
201751_atJOSD11.83992.2569
214007_s_atPTK92.28652.2558
209383_atDDIT31.48272.2509
219624_atBAG41.46732.2485
1560739_a_atUBE3C1.61872.2419
225283_atARRDC41.57072.2404
209694_atPTS1.77332.2386
225954_s_atMIDN1.49182.2373
209795_atCD691.59992.2349
238035_atSP31.70862.2321
225699_atC7orf401.6912.231
206919_atELK41.382.2309
209211_atKLF51.60512.2256
208868_s_atGABARAPL11.77022.2253
223746_atSTK41.37862.2227
204299_atFUSIP1///LOC6425581.42992.2204
202657_s_atSERTAD21.59662.2196
244103_atC1orf551.47182.2185
243371_at1.24762.217
219382_atSERTAD31.59252.2096
1559582_atRHOQ1.6342.2063
227979_atRBM4B1.69852.2013
227521_atFBXO332.07172.2007
205241_atSCO21.62032.1977
205409_atFOSL21.95162.1974
201170_s_atBHLHB21.57992.1973
230380_atTHAP21.6462.1963
226732_atRBM331.62972.1953
36829_atPER11.58552.1948
220330_s_atSAMSN11.45872.1929
1555279_atARMC81.51542.1899
1559121_s_atARIH21.72872.1812
227680_atZNF3261.5562.1762
200733_s_atPTP4A11.4812.1759
209185_s_atIRS21.81392.1745
241018_atTMEM591.77472.1732
213538_atSON1.71432.1713
201502_s_atNFKBIA1.84692.1713
1556750_atLOC1535771.41752.1679
1554469_atBTBD151.3552.1672
212373_atFEM1B1.71732.1652
203659_s_atRFP21.65652.1647
223527_s_atCDADC11.58572.1636
229955_atFBXO31.5532.1617
218881_s_atFOSL21.68932.1598
226650_atZFAND2A1.79172.1594
230304_at1.63042.1564
202083_s_atSEC14L11.34392.1561
204244_s_atDBF41.54952.1544
200730_s_atPTP4A11.60722.1488
221727_at1.61972.1482
235670_atSTX111.39332.1472
221919_at1.53082.1456
209300_s_atNECAP11.64982.1448
218940_atC14orf1381.65032.1436
1554089_s_atSBDS///SBDSP1.64812.1423
230748_atSLC16A61.61122.1411
222669_s_atSBDS1.67382.14
216015_s_atCIAS11.76152.1398
227697_atSOCS31.71342.1357
1554571_atAPBB1IP1.59462.1335
231863_atING31.5822.1324
238719_at1.4712.1315
204491_atPDE4D1.88712.1279
218379_atRBM71.57622.1261
202284_s_atCDKN1A1.60652.1256
220306_atFAM46C1.84222.125
226830_x_atLOC4403091.53052.1241
212240_s_atPIK3R11.7562.1235
214060_atAMY1A///SSBP11.87572.1225
234055_s_atZNF3361.56542.1211
1556911_atALMS11.15362.1195
241385_atLARP71.44942.119
228693_atCCDC501.44262.1181
238488_atIPO111.21862.1138
226970_atFBXO331.65762.1127
222808_atGLT28D11.47852.1123
244219_atWTAP1.70842.1063
200989_atHIF1A1.41062.1018
211998_atH3F3B1.88982.1008
218708_atNXT11.65952.0998
242975_s_atGNAS1.22722.0946
226206_atMAFK1.79762.0904
41577_atPPP1R16B1.52252.0887
1554929_atKIAA09991.55222.0872
212666_atSMURF11.39852.0866
228468_atMASTL1.30222.085
218810_atZC3H12A1.74622.082
222018_atNACA///NACAP1///LOC3892401.65822.0819
213537_atHLA-DPA11.60662.0813
224663_s_atCFL22.02072.081
226390_atSTARD41.58282.0764
227577_atEXOC81.65272.0717
200664_s_atDNAJB11.84852.0689
204799_atZBED41.62692.0675
238633_atEPC11.69992.0655
228180_atSMU11.63512.0634
201169_s_atBHLHB21.71682.0625
209345_s_atPI4KII1.51472.0621
239494_atLOC646725///LOC6494311.63682.0608
238455_at1.62642.0598
201341_atENC11.90722.0533
204370_atHEAB1.70272.0516
236196_at1.50682.0429
200666_s_atDNAJB11.68742.0397
212374_atFEM1B1.69982.0381
220239_atKLHL71.59732.0372
221768_atSFPQ1.55092.0359
223598_atRAD23B1.62762.0343
203708_atPDE4B2.05922.0342
225951_s_atLOC440309///LOC6499081.59412.0342
221763_atJMJD1C1.39422.0265
242255_atWDR371.27232.0258
205681_atBCL2A11.36742.0221
1569864_atSERAC11.33652.0106
1570394_atXRN11.43042.0053
207513_s_atZNF1890.57910.4999
212407_atKIAA08590.62410.4969
218805_atGIMAP50.63860.4966
223404_s_atC1orf250.58260.4961
208893_s_atDUSP60.55030.4955
1552316_a_atGIMAP10.56090.4949
218979_atRMI10.55140.4947
207907_atTNFSF140.61680.4946
208891_atDUSP60.48880.4937
238907_atLOC2843230.62430.4922
230226_s_atJARID1A0.66060.4913
220235_s_atC1orf1030.55970.488
228920_atZNF2600.59320.4869
231576_atETNK10.77610.4838
221081_s_atDENND2D0.63060.4826
219777_atGIMAP60.55750.48
223583_atTNFAIP8L20.59940.4747
209828_s_atIL160.66590.4737
206206_atCD1800.60850.4686
226230_atSMEK20.6180.4657
228190_atCTR90.54110.4623
226481_atVPRBP0.54290.4613
235085_atDKFZp761P04230.57940.4582
226977_atLOC4923110.61340.4544
216379_x_atCD240.55120.4533
223751_x_atTLR100.63850.4482
220992_s_atC1orf250.55810.4437
224953_atYIPF50.50.4376
219243_atGIMAP40.57490.4371
218242_s_atSUV420H10.59720.4344
227335_atDIDO10.57390.4299
229367_s_atGIMAP60.58080.427
226423_atPAQR80.59850.4188
200799_atHSPA1A0.6170.4116
206978_atCCR20.54250.408
227626_atPAQR80.58850.4058
240646_atGIMAP80.53750.4037
206991_s_atCCR5///LOC6537250.52570.3864
226041_atNAPE-PLD0.53680.3817
207794_atCCR20.63090.3811
205898_atCX3CR10.56220.3734
222566_atSUV420H10.48140.3719
233461_x_atZNF2260.57940.3675
200800_s_atHSPA1A///HSPA1B0.62250.3664
235306_atGIMAP80.45540.3547
230337_atSOS10.37150.344
aAffymetrix U133 Plus 2.0 GeneChip® probe set IDs and annotations.
bFold change as ratio of geometric means.
cExpression at 2 h/expression at 0 h.
dExpression at 4 h/expression at 0 h.

Acknowledgments

This work was supported by the NIH/National Institute of Arthritis and Musculoskeletal and Skin Diseases (Grants P01AR048929, P30AR047363, and P60AR047784), the Cincinnati Children's Hospital Research Foundation, and the Ohio Valley Chapter of the Arthritis Foundation.

Author Disclosure Statement

No competing financial interests exist.

References

1. Dash A. Maine IP. Varambally S, et al. Changes in differential gene expression because of warm ischemia time of radical prostatectomy specimens. Am J Pathol. 2002;161:1743–1748. [PubMed]
2. Huang J. Qi R. Quackenbush J, et al. Effects of ischemia on gene expression. J Surg Res. 2001;99:222–227. [PubMed]
3. Spruessel A. Steimann G. Jung M, et al. Tissue ischemia time affects gene and protein expression patterns within minutes following surgical tumor excision. Biotechniques. 2004;36:1030–1037. [PubMed]
4. Baechler EC. Batliwalla FM. Karypis G, et al. Expression levels for many genes in human peripheral blood cells are highly sensitive to ex vivo incubation. Genes Immun. 2004;5:347–353. [PubMed]
5. An Analysis of Blood Processing Methods to Prepare Samples for GeneChip Expression Profiles (Technical Note) http://media.affymetrix.com/support/technical/technotes/blood_technote.pdf. 2003. http://media.affymetrix.com/support/technical/technotes/blood_technote.pdf
6. Barnes MG. Grom AA. Thompson SD, et al. Subtype-specific peripheral blood gene expression profiles in recent-onset juvenile idiopathic arthritis. Arthritis Rheum. 2009;60:2102–2112. [PMC free article] [PubMed]
7. Griffin TA. Barnes MG. Ilowite NT, et al. Gene expression signatures in polyarticular juvenile idiopathic arthritis demonstrate disease heterogeneity and offer a molecular classification of disease subsets. Arthritis Rheum. 2009;60:2113–2123. [PMC free article] [PubMed]
8. Fall N. Barnes M. Thornton S, et al. Gene expression profiling of peripheral blood from patients with untreated new-onset systemic juvenile idiopathic arthritis reveals molecular heterogeneity that may predict macrophage activation syndrome. Arthritis Rheum. 2007;56:3793–3804. [PubMed]
9. Irizarry RA. Bolstad BM. Collin F, et al. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 2003;31:e15. [PMC free article] [PubMed]
10. Bailey IR. Thurlow VR. Is suboptimal phlebotomy technique impacting on potassium results for primary care? Ann Clin Biochem. 2008;45(Pt 3):266–269. [PubMed]
11. Boyanton BL., Jr. Blick KE. Stability studies of twenty-four analytes in human plasma and serum. Clin Chem. 2002;48:2242–2247. [PubMed]
12. Shweiki D. Itin A. Soffer D, et al. Vascular endothelial growth factor induced by hypoxia may mediate hypoxia-initiated angiogenesis. Nature. 1992;359:843–845. [PubMed]
13. Bose D. Meric-Bernstam F. Hofstetter W, et al. Vascular endothelial growth factor targeted therapy in the perioperative setting: implications for patient care. Lancet Oncol. 2010;11:373–382. [PubMed]
14. Xia M. Sui Z. Recent developments in CCR2 antagonists. Expert Opin Ther Pat. 2009;19:295–303. [PubMed]
15. Emmelkamp JM. Rockstroh JK. CCR5 antagonists: comparison of efficacy, side effects, pharmacokinetics and interactions—review of the literature. Eur J Med Res. 2007;12:409–417. [PubMed]
16. Alexander WS. Suppressors of cytokine signalling (SOCS) in the immune system. Nat Rev Immunol. 2002;2:410–416. [PubMed]
17. Baechler EC. Batliwalla FM. Karypis G, et al. Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus. Proc Natl Acad Sci U S A. 2003;100:2610–2615. [PubMed]

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