scholarly journals Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

2008 ◽  
Vol 3 ◽  
pp. BMI.S938 ◽  
Author(s):  
Laura Kennedy ◽  
J. Keith Vass ◽  
D. Ross Haggart ◽  
Steve Moore ◽  
Michael E. Burczynski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Whole Blood ◽  
Peripheral Blood ◽  
Expression Profiles ◽  
Cell Types ◽  
Great Promise ◽  
Microarray Probe ◽  
Blood Samples ◽  
Transcriptional Profiles

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies.

Automated Sorting of Monocytes from Whole Blood for Reproducible Gene Expression Profiling.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3840-3840
Author(s):  
Carsten Poggel ◽  
Timo Adams ◽  
Sabine Martin ◽  
Carola Pickel ◽  
Nicole Prahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Gene Expression Profiling ◽  
Whole Blood ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Specific Gene

Abstract Microarray-based gene expression profiling has been used to develop clinically relevant molecular classifiers for many different diseases. Furthermore, it has been shown for various chronic diseases that specific gene expression patterns are reflected at the level of blood cells. However, blood is a complex tissue comprising numerous cell types. Therefore, the contribution of rare cell types to a whole blood expression profile might not be detected and a substantial proportion of what is usually reported as “up-regulation” or “down-regulation” might actually be the result of a shift in cell populations and not of a true regulatory process. In order to circumvent these problems, several techniques have been established to analyze purified subpopulations rather than whole blood samples. Previously, it has been shown, for example, that reproducible gene expression profiles can be generated by positive selection of blood cell subsets from PBMCs1. As the preparation of PBMCs by, for example, Ficoll is time-consuming, inconvenient, and not amenable to automation, we have set up a combined direct whole blood cell separation and gene expression profiling protocol. By using Whole Blood CD14 MicroBeads in combination with the autoMACS Pro™ Separator, the separation protocol generally allowed enrichment of monocytes from whole blood within 30 min with purities higher than 90%. In combination with the depletion of neutrophils, the major source of contaminating RNA, purities increased to over 95% for all tested blood donors. Monocytes included the CD14bright/CD16− as well as the CD14dim/CD16+ populations. To assess the reproducibility of gene expression profiles and the influence of several experimental parameters, monocytes were sorted from 5 ml whole blood. RNA was extracted and hybridized to microarrays and the Pearson correlation coefficients of pairwise comparisons were calculated. Technical repeats of monocyte analysis from blood donated at different days showed a higher correlation coefficient than whole blood RNA. Blood storage at room temperature resulted in a strong deregulation of many genes, whereas blood stored at 4°C showed minimal changes, which is in agreement with previous studies. Skipping the centrifugation step, which is used to remove unbound MicroBeads did not alter the gene expression profiles. Incubation of sorted cells in PrepProtect™ Stabilization Buffer showed no alteration of gene expression thus enabling the shipping of cells without liquid nitrogen. Monocytes play a crucial role in diseases like atherosclerosis. Our rapid and simple protocol for combined direct cell sorting from whole blood and gene expression profiling of monocytes might help to ease the discovery of new biomarkers and to screen and monitor patients. 1 Lyons et al., BMC Genomics (2007), 8:64.

scholarly journals Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation

2017 ◽  
Author(s):  
John Dou ◽  
Rebecca J. Schmidt ◽  
Kelly S. Benke ◽  
Craig Newschaffer ◽  
Irva Hertz-Picciotto ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Blood Cell ◽  
Cord Blood ◽  
Whole Blood ◽  
Cell Types ◽  
Buffy Coat ◽  
Sample Type ◽  
Blood Samples ◽  
Cell Composition ◽  
Cell Counts

AbstractBackgroundCord blood DNA methylation is associated with numerous health outcomes and environmental exposures. Whole cord blood DNA reflects all nucleated blood cell types, while centrifuging whole blood separates red blood cells by generating a white blood cell buffy coat. Both sample types are used in DNA methylation studies. Cell types have unique methylation patterns and processing can impact cell distributions, which may influence comparability.ObjectivesTo evaluate differences in cell composition and DNA methylation between buffy coat and whole cord blood samples.MethodsCord blood DNA methylation was measured with the Infinium EPIC BeadChip (Illumina) in 8 individuals, each contributing buffy coat and whole blood samples. We analyzed principal components (PC) of methylation, performed hierarchical clustering, and computed correlations of mean-centered methylation between pairs. We conducted moderated t-tests on single sites and estimated cell composition.ResultsDNA methylation PCs were associated with individual (PPC1=1.4x10-9; PPC2=2.9x10-5; PPC3=3.8x10-5; PPC4=4.2x10-6; PPC5=9.9x10-13), and not with sample type (PPC1-5>0.7). Samples hierarchically clustered by individual. Pearson correlations of mean-centered methylation between paired individual samples ranged from r=0.66 to r=0.87. No individual site significantly differed between buffy coat and whole cord blood when adjusting for multiple comparisons (5 sites had unadjusted P<10-5). Estimated cell type proportions did not differ by sample type (P=0.86), and estimated cell counts were highly correlated between paired samples (r=0.99).ConclusionsDifferences in methylation and cell composition between buffy coat and whole cord blood are much lower than inter-individual variation, demonstrating that both sample preparation types can be analytically combined and compared.

Microarray study of gene expression profiles in peripheral blood samples from lung cancer patients before and after erlotinib treatment

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e19072-e19072
Author(s):  
A. Irigoyen ◽  
C. Olmedo ◽  
J. Valdivia ◽  
A. Comino ◽  
C. Cano ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Growth Factor ◽  
Healthy Volunteers ◽  
Cancer Patients ◽  
Peripheral Blood ◽  
Expression Profiles ◽  
Control Group ◽  
Blood Samples ◽  
Lung Cancer Patients

e19072 Background: The gene expression profile in peripheral blood samples from lung cancer patients is a potential predictor to treatment response. Methods: The study has been developed using 10 healthy volunteers as the control group and 10 lung cancer patients (stage IV). Written informed consent was obtained being the protocol approved by the local Clinical Research and Ethics Committee. Peripheral blood samples were obtained from lung cancer patients before (T0) and after treatment (T15d). RNA from peripheral blood samples was extracted and purified selecting 28S/18S ratios>1.5 to obtain cDNA and cRNA for hybridization of the 20,000 genes included in Human 20K CodeLink. An array from each participant was obtained in duplicate. For each array, 2 μg of cRNA was compared to 2 μg of healthy cRNA.. Significant genes were found using Significance Analysis of Microarrays which uses repeated permutations of the data. Results: The selected genes were expressed >3-fold with a false discovery rate =0.05. Before treatment (T0) when patients were compared to healthy volunteers there was an increase in the expression of: histone 1 H4c, transforming growth factor beta 2, endothelial cell growth factor 1 (platelet-derived), glucose-6-phosphatase catalytic 2, Relaxin 3 receptor 1, Insulin-like growth factor binding protein 2, RAS-like family 11 member B, and ELK4. After treatment (T15d), when each lung cancer patient's results were compared to their own before treatment results (T0), there was an increase in the expression of: Bcl2, myosin light polypeptide 4; interferon alpha-inducible protein 27; interferon gamma receptor 1; RASSF5, ARHGEF6, IGFBP5, tumor protein p53 inducible nuclear protein 1, peroxisome proliferative activated receptor gamma. Conclusions: The data presented identifies biologically relevant over-expressed genes in lung cancer. A validation of these results and the analysis of the genes that identify patients who will respond positively to erlotinib treatment is being carried out. No significant financial relationships to disclose.

Abstract WP416: Specific Transcriptome Response in Neutrophils, Monocytes and Whole Blood in Human Intracerebral Hemorrhage and Ischemic Stroke of Different Etiologies

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Paulina Carmona-Mora ◽  
Bradley P Ander ◽  
Glen C Jickling ◽  
Xinhua Zhan ◽  
Farah Hamade ◽  
...  
Keyword(s):  
Immune Response ◽  
Ischemic Stroke ◽  
Blood Cell ◽  
Intracerebral Hemorrhage ◽  
Whole Blood ◽  
Peripheral Blood ◽  
Receptor Gene ◽  
Cell Types ◽  
Cell Receptor ◽  
Transcriptional Responses

Understanding transcriptome changes following intracerebral hemorrhage (ICH) and ischemic stroke (IS) of different etiologies, can lead to a better understanding of the molecular and cellular pathways involved in the response to acute brain injury caused by ICH and IS. We characterized the transcriptomic profiles from ICH and different IS etiologies to identify acute molecular changes in isolated monocytes, neutrophils and in whole blood. Peripheral blood was drawn from ICH (6) and IS (33) cases (cardioembolic, large vessel and lacunar) in the first 30 ± 20 hours post-onset of symptoms. We performed whole-genome RNA sequencing of whole blood (WB), and isolated neutrophils and monocytes. Control cases (10) with vascular risk factors (diabetes and/or hypertension and/or hypercholesterolemia) were also included (VRFC). A linear regression model including the interaction diagnosis x sample subtype with p<0.05 and overlap with FDR<0.2, (fold-change>1.2) was used for identifying differentially expressed (DE) genes. Gene ontology and pathway enrichment were performed for investigating the biological context of the DE. We observed specific transcriptional responses for ICH and IS, and within IS etiologies in monocytes, neutrophils and WB. Neutrophils’ response was the strongest with highest number of DE genes in both ICH and IS and its etiologies when compared to VRFC. Most of the changes were cell-type specific and involved immune response and signal transduction pathways. For example, in ICH compared to VRFC, about half of the over-represented pathways were unique to either monocytes or neutrophils. Many pathways over-represented in WB were not over-represented in monocytes or neutrophils, signifying the importance of additional blood cell types in the immune response to ICH and IS. A T-cell receptor gene was DE in WB only, and in opposite directions in ICH and IS when compared to VRFC, thus is a good biomarker candidate. The unique expression changes in neutrophils and monocytes after ICH and IS and its subtypes underscore their involvement in IS and ICH pathophysiology. The large number of unique genes and pathways in whole blood not detected in monocytes or neutrophils signify the contribution of other peripheral blood cell types to the ICH and IS responses.

scholarly journals HLA gene expression is altered in whole blood and placenta from women who later developed preeclampsia

2017 ◽  
Vol 49 (3) ◽  
pp. 193-200 ◽  
Author(s):  
Heather Y. Small ◽  
Christine Akehurst ◽  
Liliya Sharafetdinova ◽  
Martin W. McBride ◽  
John D. McClure ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Placental Tissue ◽  
Fold Change ◽  
Multisystem Disease ◽  
Blood Samples ◽  
Whole Blood Samples ◽  
Independent Cohort

Preeclampsia is a multisystem disease that significantly contributes to maternal and fetal morbidity and mortality. In this study, we used a non-biased microarray approach to identify dysregulated genes in maternal whole blood samples which may be associated with the development of preeclampsia. Whole blood samples were obtained at 28 wk of gestation from 5 women who later developed preeclampsia (cases) and 10 matched women with normotensive pregnancies (controls). Placenta samples were obtained from an independent cohort of 19 women with preeclampsia matched with 19 women with normotensive pregnancies. We studied gene expression profiles using Illumina microarray in blood and validated changes in gene expression in whole blood and placenta tissue by qPCR. We found a transcriptional profile differentiating cases from controls; 336 genes were significantly dysregulated in blood from women who developed preeclampsia. Functional annotation of microarray results indicated that most of the genes found to be dysregulated were involved in inflammatory pathways. While general trends were preserved, only HLA-A was validated in whole blood samples from cases using qPCR (2.30- ± 0.9-fold change) whereas in placental tissue HLA-DRB1 expression was found to be significantly increased in samples from women with preeclampsia (5.88- ± 2.24-fold change). We have identified that HLA-A is upregulated in the circulation of women who went on to develop preeclampsia. In placenta of women with preeclampsia we identified that HLA-DRB1 is upregulated. Our data provide further evidence for involvement of the HLA gene family in the pathogenesis of preeclampsia.

scholarly journals Eight-year longitudinal study of whole blood gene expression profiles in individuals undergoing long-term medical follow-up

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoshio Sakai ◽  
Alessandro Nasti ◽  
Yumie Takeshita ◽  
Miki Okumura ◽  
Shinji Kitajima ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Peripheral Blood ◽  
Blood Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
The Body ◽  
Peripheral Blood Cells ◽  
Peripheral Tissues ◽  
Altered Gene

AbstractBlood circulates throughout the body via the peripheral tissues, contributes to host homeostasis and maintains normal physiological functions, in addition to responding to lesions. Previously, we revealed that gene expression analysis of peripheral blood cells is a useful approach for assessing diseases such as diabetes mellitus and cancer because the altered gene expression profiles of peripheral blood cells can reflect the presence and state of diseases. However, no chronological assessment of whole gene expression profiles has been conducted. In the present study, we collected whole blood RNA from 61 individuals (average age at registration, 50 years) every 4 years for 8 years and analyzed gene expression profiles using a complementary DNA microarray to examine whether these profiles were stable or changed over time. We found that the genes with very stable expression were related mostly to immune system pathways, including antigen cell presentation and interferon-related signaling. Genes whose expression was altered over the 8-year study period were principally involved in cellular machinery pathways, including development, signal transduction, cell cycle, apoptosis, and survival. Thus, this chronological examination study showed that the gene expression profiles of whole blood can reveal unmanifested physiological changes.

scholarly journals Correction for both common and rare cell types in blood is important to identify genes that correlate with age

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Damiano Pellegrino-Coppola ◽  
◽  
Annique Claringbould ◽  
Maartje Stutvoet ◽  
Dorret I. Boomsma ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Whole Blood ◽  
Cell Types ◽  
Functional Enrichment ◽  
Extended Model ◽  
Initial Model ◽  
Platelet Activity ◽  
Blood Gene Expression ◽  
New Model

Abstract Background Aging is a multifactorial process that affects multiple tissues and is characterized by changes in homeostasis over time, leading to increased morbidity. Whole blood gene expression signatures have been associated with aging and have been used to gain information on its biological mechanisms, which are still not fully understood. However, blood is composed of many cell types whose proportions in blood vary with age. As a result, previously observed associations between gene expression levels and aging might be driven by cell type composition rather than intracellular aging mechanisms. To overcome this, previous aging studies already accounted for major cell types, but the possibility that the reported associations are false positives driven by less prevalent cell subtypes remains. Results Here, we compared the regression model from our previous work to an extended model that corrects for 33 additional white blood cell subtypes. Both models were applied to whole blood gene expression data from 3165 individuals belonging to the general population (age range of 18–81 years). We evaluated that the new model is a better fit for the data and it identified fewer genes associated with aging (625, compared to the 2808 of the initial model; P ≤ 2.5⨯10−6). Moreover, 511 genes (~ 18% of the 2808 genes identified by the initial model) were found using both models, indicating that the other previously reported genes could be proxies for less abundant cell types. In particular, functional enrichment of the genes identified by the new model highlighted pathways and GO terms specifically associated with platelet activity. Conclusions We conclude that gene expression analyses in blood strongly benefit from correction for both common and rare blood cell types, and recommend using blood-cell count estimates as standard covariates when studying whole blood gene expression.

scholarly journals Correction for both common and rare cell types in blood is important to identify genes that correlate with age

2020 ◽  
Author(s):  
Damiano Pellegrino Coppola ◽  
Annique Claringbould ◽  
Maartje Stutvoet ◽  
Dorret I. Boomsma ◽  
M. Arfan Ikram ◽  
...  
Keyword(s):  
Gene Expression ◽  
Blood Cell ◽  
Whole Blood ◽  
Cell Types ◽  
Functional Enrichment ◽  
Extended Model ◽  
Initial Model ◽  
Platelet Activity ◽  
Blood Gene Expression ◽  
New Model

AbstractBackgroundAging is a multifactorial process that affects multiple tissues and is characterized by changes in homeostasis over time, leading to increased morbidity. Whole blood gene expression signatures have been associated with aging and have been used to gain information on its biological mechanisms, which are still not fully understood. However, blood is composed of many cell types whose proportions in blood vary with age. As a result, previously observed associations between gene expression levels and aging might be driven by cell type composition rather than intracellular aging mechanisms. To overcome this, previous aging studies already accounted for major cell types, but the possibility that the reported associations are false positives driven by less prevalent cell subtypes remains.ResultsHere, we compared the regression model from our previous work to an extended model that corrects for 33 additional white blood cell subtypes. Both models were applied to whole blood gene expression data from 3165 individuals belonging to the general population (age range of 18-81 years). We evaluated that the new model is a better fit for the data and it identified fewer genes associated with aging (625, compared to the 2808 of the initial model; P ≤ 2.5 × 10−6). Moreover, 511 genes (∼18% of the 2,808 genes identified by the initial model) were found using both models, indicating that the other previously reported genes could be proxies for less abundant cell types. In particular, functional enrichment of the genes identified by the new model highlighted pathways and GO terms specifically associated with platelet activity.ConclusionsWe conclude that gene expression analyses in blood strongly benefit from correction for both common and rare blood cell types, and recommend using blood-cell count estimates as standard covariates when studying whole blood gene expression.

Interference of globin genes with biomarker discovery for allograft rejection in peripheral blood samples

2008 ◽  
Vol 32 (2) ◽  
pp. 190-197 ◽  
Author(s):  
Li Li ◽  
Lihua Ying ◽  
Maarten Naesens ◽  
Wenzhong Xiao ◽  
Tara Sigdel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Graft Rejection ◽  
Peripheral Blood ◽  
Biomarker Discovery ◽  
Transplant Rejection ◽  
Solid Organ ◽  
Globin Genes ◽  
Blood Samples ◽  
Globin Reduction

Microarray technology is a powerful tool in the discovery of new biomarkers for disease. After solid organ transplantation, where the detection of rejection is usually made on invasive biopsies, it could be hypothesized that noninvasive transcriptional profiling of peripheral blood will reveal rejection-specific expression patterns from circulating immune cells. However, in kidney transplant rejection, the analysis of gene expression data in whole blood has proven difficult for detecting significant genes specific for acute graft rejection. Previous studies have demonstrated that the abundance of globin genes in whole blood may mask the underlying biological differences between whole blood samples. In the present study, we compared the gene expression profiles of peripheral blood of nine stable renal allograft recipients with seven matched patients having an ongoing acute renal transplant rejection, using four different protocols of preparation, amplification, and synthesis of cRNA or cDNA and hybridization on the Affymetrix platform. We demonstrated that the globin reduction method is not sufficient to unmask clinically relevant rejection-specific transcriptome profiles in whole blood. Applying an additional mathematical depletion of the globin genes improves the efficacy of globin reduction but cannot remove the confounding influence of globin gene hybridization. Sampling of peripheral blood leukocytes alone, without the confounding influence of globin mRNA, provides sensitive and specific peripheral signatures for graft rejection, with many of these signals overlapping with rejection-driven tissue (kidney)-specific signatures from matched biopsies. Similar applications may exist for array-based biomarker discovery for other diseases associated with changes in leukocyte trafficking, activation, or function.

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