A systematic heritability analysis of the human whole blood transcriptome

Genome-wide expression quantitative trait locus (eQTL) mapping may reveal common genetic variants regulating gene expression. In addition to mapping eQTLs, we systematically evaluated the heritability of the whole blood transcriptome in 5,626 participants from the Framingham Heart Study. Of all gene expression measurements, about 40 % exhibit evidence of being heritable [hgeneExp(2) > 0, (p < 0.05)], the average heritability was estimated to be 0.13, and 10 % display hgeneExp(2) > 0.2. To identify the role of eQTLs in promoting phenotype differences and disease susceptibility, we investigated the proportion of cis/trans eQTLs in different heritability categories and discovered that genes with higher heritability are more likely to have cis eQTLs that explain large proportions of variance in the expression of the corresponding genes. Single cis eQTLs explain 0.33-0.53 of variance in transcripts on average, whereas single trans eQTLs only explain 0.02-0.07. The top cis eQTLs tend to explain more variance in the corresponding gene when its hgeneExp(2) is greater. Taking body mass index (BMI) as a case study, we cross-linked cis/trans eQTLs with both GWAS SNPs and differentially expressed genes for BMI. We discovered that BMI GWAS SNPs in 16p11.2 (e.g., rs7359397) are associated with several BMI differentially expressed genes in a cis manner (e.g. SULT1A1, SPNS1, and TUFM). These BMI signature genes explain a much larger proportion of variance in BMI than do the GWAS SNPs. Our results shed light on the impact of eQTLs on the heritability of the human whole blood transcriptome and its relations to phenotype differences.

Whole blood gene expression and interleukin-6 levels

BACKGROUND

Circulating interleukin-6 levels increase with advancing age and are a risk factor for various diseases and mortality. The characterization of gene expression profiles associated with interleukin-6 levels might suggest important molecular events underlying its regulation.

METHODS AND RESULTS

We studied the association of transcriptional profiles with interleukin-6 levels in 2422 participants from the Framingham Heart Study Offspring Cohort using Affymetrix Human Exon 1.0 ST Array. We identified 4139 genes that were significantly associated with interleukin-6 levels (FDR<0.05) after adjusting for age, sex and blood cell components. We then replicated 807 genes in the InCHIANTI study with 694 participants. Many of the top genes are involved in inflammation-related pathways or erythrocyte function, including JAK/Stat signaling pathway and interleukin-10 signaling pathway.

CONCLUSION

We identified and replicated 807 genes that were associated with circulating interleukin-6 levels. Future characterization of interleukin-6 regulation networks may facilitate the identification of additional potential targets for treating inflammation-related diseases.

RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder

RNA-sequencing (RNA-seq) is a powerful technique to investigate the complexity of gene expression in the human brain. We used RNA-seq to survey the brain transcriptome in high-quality postmortem dorsolateral prefrontal cortex from 11 individuals diagnosed with bipolar disorder (BD) and from 11 age- and gender-matched controls. Deep sequencing was performed, with over 350 million reads per specimen. At a false discovery rate of <5%, we detected five differentially expressed (DE) genes and 12 DE transcripts, most of which have not been previously implicated in BD. Among these, Prominin 1/CD133 and ATP-binding cassette-sub-family G-member2 (ABCG2) have important roles in neuroplasticity. We also show for the first time differential expression of long noncoding RNAs (lncRNAs) in BD. DE transcripts include those of serine/arginine-rich splicing factor 5 (SRSF5) and regulatory factor X4 (RFX4), which along with lncRNAs have a role in mammalian circadian rhythms. The DE genes were significantly enriched for several Gene Ontology categories. Of these, genes involved with GTPase binding were also enriched for BD-associated SNPs from previous genome-wide association studies, suggesting that differential expression of these genes is not simply a consequence of BD or its treatment. Many of these findings were replicated by microarray in an independent sample of 60 cases and controls. These results highlight common pathways for inherited and non-inherited influences on disease risk that may constitute good targets for novel therapies.

Integrative DNA, RNA, and protein evidence connects TREML4 to coronary artery calcification

Coronary artery calcification (CAC) is a heritable and definitive morphologic marker of atherosclerosis that strongly predicts risk for future cardiovascular events. To search for genes involved in CAC, we used an integrative transcriptomic, genomic, and protein expression strategy by using next-generation DNA sequencing in the discovery phase with follow-up studies using traditional molecular biology and histopathology techniques. RNA sequencing of peripheral blood from a discovery set of CAC cases and controls was used to identify dysregulated genes, which were validated by ClinSeq and Framingham Heart Study data. Only a single gene, TREML4, was upregulated in CAC cases in both studies. Further examination showed that rs2803496 was a TREML4 cis-eQTL and that the minor allele at this locus conferred up to a 6.5-fold increased relative risk of CAC. We characterized human TREML4 and demonstrated by immunohistochemical techniques that it is localized in macrophages surrounding the necrotic core of coronary plaques complicated by calcification (but not in arteries with less advanced disease). Finally, we determined by von Kossa staining that TREML4 colocalizes with areas of microcalcification within coronary plaques. Overall, we present integrative RNA, DNA, and protein evidence implicating TREML4 in coronary artery calcification. Our findings connect multimodal genomics data with a commonly used clinical marker of cardiovascular disease.

Whole blood gene expression and atrial fibrillation: the Framingham Heart Study

BACKGROUND

Atrial fibrillation (AF) involves substantial electrophysiological, structural and contractile remodeling. We hypothesize that characterizing gene expression might uncover important pathways related to AF.

METHODS AND RESULTS

We performed genome-wide whole blood transcriptomic profiling (Affymetrix Human Exon 1.0 ST Array) of 2446 participants (mean age 66 ± 9 years, 55% women) from the Offspring cohort of Framingham Heart Study. The study included 177 participants with prevalent AF, 143 with incident AF during up to 7 years follow up, and 2126 participants with no AF. We identified seven genes statistically significantly up-regulated with prevalent AF. The most significant gene, PBX1 (P = 2.8 × 10(-7)), plays an important role in cardiovascular development. We integrated differential gene expression with gene-gene interaction information to identify several signaling pathways possibly involved in AF-related transcriptional regulation. We did not detect any statistically significant transcriptomic associations with incident AF.

CONCLUSION

We examined associations of gene expression with AF in a large community-based cohort. Our study revealed several genes and signaling pathways that are potentially involved in AF-related transcriptional regulation.

Identification of candidate genes involved in coronary artery calcification by transcriptome sequencing of cell lines

Background

Massively-parallel cDNA sequencing (RNA-Seq) is a new technique that holds great promise for cardiovascular genomics. Here, we used RNA-Seq to study the transcriptomes of matched coronary artery disease cases and controls in the ClinSeq® study, using cell lines as tissue surrogates.

Results

Lymphoblastoid cell lines (LCLs) from 16 cases and controls representing phenotypic extremes for coronary calcification were cultured and analyzed using RNA-Seq. All cell lines were then independently re-cultured and along with another set of 16 independent cases and controls, were profiled with Affymetrix microarrays to perform a technical validation of the RNA-Seq results. Statistically significant changes (p < 0.05) were detected in 186 transcripts, many of which are expressed at extremely low levels (5–10 copies/cell), which we confirmed through a separate spike-in control RNA-Seq experiment. Next, by fitting a linear model to exon-level RNA-Seq read counts, we detected signals of alternative splicing in 18 transcripts. Finally, we used the RNA-Seq data to identify differential expression (p < 0.0001) in eight previously unannotated regions that may represent novel transcripts. Overall, differentially expressed genes showed strong enrichment (p = 0.0002) for prior association with cardiovascular disease. At the network level, we found evidence for perturbation in pathways involving both cardiovascular system development and function as well as lipid metabolism.

Conclusions

We present a pilot study for transcriptome involvement in coronary artery calcification and demonstrate how RNA-Seq analyses using LCLs as a tissue surrogate may yield fruitful results in a clinical sequencing project. In addition to canonical gene expression, we present candidate variants from alternative splicing and novel transcript detection, which have been unexplored in the context of this disease.

Late multiple organ surge in interferon-regulated target genes characterizes staphylococcal enterotoxin B lethality

Background

Bacterial superantigens are virulence factors that cause toxic shock syndrome. Here, the genome-wide, temporal response of mice to lethal intranasal staphylococcal enterotoxin B (SEB) challenge was investigated in six tissues.

Results

The earliest responses and largest number of affected genes occurred in peripheral blood mononuclear cells (PBMC), spleen, and lung tissues with the highest content of both T-cells and monocyte/macrophages, the direct cellular targets of SEB. In contrast, the response of liver, kidney, and heart was delayed and involved fewer genes, but revealed a dominant genetic program that was seen in all 6 tissues. Many of the 85 uniquely annotated transcripts participating in this shared genomic response have not been previously linked to SEB. Nine of the 85 genes were subsequently confirmed by RT-PCR in every tissue/organ at 24 h. These 85 transcripts, up-regulated in all tissues, annotated to the interferon (IFN)/antiviral-response and included genes belonging to the DNA/RNA sensing system, DNA damage repair, the immunoproteasome, and the ER/metabolic stress-response and apoptosis pathways. Overall, this shared program was identified as a type I and II interferon (IFN)-response and the promoters of these genes were highly enriched for IFN regulatory matrices. Several genes whose secreted products induce the IFN pathway were up-regulated at early time points in PBMCs, spleen, and/or lung. Furthermore, IFN regulatory factors including Irf1, Irf7 and Irf8, and Zbp1, a DNA sensor/transcription factor that can directly elicit an IFN innate immune response, participated in this host-wide SEB signature.

Conclusion

Global gene-expression changes across multiple organs implicated a host-wide IFN-response in SEB-induced death. Therapies aimed at IFN-associated innate immunity may improve outcome in toxic shock syndromes.

Sex- and age-interacting eQTLs in human complex diseases

Many complex human diseases exhibit sex or age differences in gene expression. However, the presence and the extent of genotype-specific variations in gene regulation are largely unknown. Here, we report results of a comprehensive analysis of expression regulation of genetic variation related to 11,672 complex disease-associated SNPs as a function of sex and age in whole-blood-derived RNA from 5254 individuals. At false discovery rate <0.05, we identified 14 sex- and 10 age-interacting expression quantitative trait loci (eQTLs). We show that these eQTLs are also associated with many sex- or age-associated traits. These findings provide important context regarding the regulation of phenotypes by genotype-environment interaction.

Integrated analysis of miRNA and mRNA during differentiation of human CD34+ cells delineates the regulatory roles of microRNA in hematopoiesis

In the process of human hematopoiesis, precise regulation of the expression of lineage-specific gene products is critical for multiple cell-fate decisions that govern cell differentiation, proliferation, and self-renewal. Given the important role of microRNAs (miRNAs) in development and differentiation, we examined the global expression of miRNA in CD34(+) cells during lineage specific hematopoiesis and found 49 miRNAs to be differentially expressed, with functional roles in cellular growth and proliferation, and apoptosis. miR-18a was upregulated during erythropoiesis and downregulated during megakaryopoiesis. miR-145 was upregulated during granulopoiesis and down regulated during erythropoiesis. Megakaryopoitic differentiation resulted in significant alteration in the expression of many miRNAs that are believed to play critical roles in the regulation of B and T cell differentiation. Target prediction analyses on three different miRNA databases indicated that TargetScan outperformed microCosm and miRDB in identifying potential miRNA targets associated with hematopoietic differentiation process. An integrated analysis of the observed miRNAs and messenger RNAs (mRNAs) resulted in 87 highly correlated miRNA-mRNA pairs that have major functional roles in cellular growth and proliferation, hematopoietic system development, and Wnt/B-catenin and Flt 3 signaling pathways. We believe that this study will enhance our understanding on the regulatory roles of miRNA in hematopoiesis by providing a library of mRNA-miRNA networks.

A systems biology framework identifies molecular underpinnings of coronary heart disease

OBJECTIVE

Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD.

APPROACH AND RESULTS

We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. Twenty-four coexpression modules were identified, including 1 case-specific and 1 control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with gene expression-associated single-nucleotide polymorphisms and with results of genome-wide association studies of CHD and its risk factors, the control-specific DM was implicated as CHD causal based on its significant enrichment for both CHD and lipid expression-associated single-nucleotide polymorphisms. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver genes. Multitissue key drivers (SPIB and TNFRSF13C) and tissue-specific key drivers (eg, EBF1) were identified.

CONCLUSIONS

Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.

Gene expression signatures of coronary heart disease

OBJECTIVE

To identify transcriptomic biomarkers of coronary heart disease (CHD) in 188 cases with CHD and 188 age- and sex-matched controls who were participants in the Framingham Heart Study.

APPROACH AND RESULTS

A total of 35 genes were differentially expressed in cases with CHD versus controls at false discovery rate<0.5, including GZMB, TMEM56, and GUK1. Cluster analysis revealed 3 gene clusters associated with CHD, 2 linked to increased erythrocyte production and a third to reduced natural killer and T cell activity in cases with CHD. Exon-level results corroborated and extended the gene-level results. Alternative splicing analysis suggested that GUK1 and 38 other genes were differentially spliced in cases with CHD versus controls. Gene Ontology analysis linked ubiquitination and T-cell-related pathways with CHD.

CONCLUSIONS

Two bioinformatically defined groups of genes show consistent associations with CHD. Our findings are consistent with the hypotheses that hematopoesis is upregulated in CHD, possibly reflecting a compensatory mechanism, and that innate immune activity is disrupted in CHD or altered by its treatment. Transcriptomic signatures may be useful in identifying pathways associated with CHD and point toward novel therapeutic targets for its treatment and prevention.

Genotype and tumor locus determine expression profile of pseudohypoxic pheochromocytomas and paragangliomas

Pheochromocytomas (PHEOs) and paragangliomas (PGLs) related to mutations in the mitochondrial succinate dehydrogenase (SDH) subunits A, B, C, and D, SDH complex assembly factor 2, and the von Hippel-Lindau (VHL) genes share a pseudohypoxic expression profile. However, genotype-specific differences in expression have been emerging. Development of effective new therapies for distinctive manifestations, e.g., a high rate of malignancy in SDHB- or predisposition to multifocal PGLs in SDHD patients, mandates improved stratification. To identify mutation/location-related characteristics among pseudohypoxic PHEOs/PGLs, we used comprehensive microarray profiling (SDHB: n = 18, SDHD-abdominal/thoracic (AT): n = 6, SDHD-head/neck (HN): n = 8, VHL: n = 13). To avoid location-specific bias, typical adrenal medulla genes were derived from matched normal medullas and cortices (n = 8) for data normalization. Unsupervised analysis identified two dominant clusters, separating SDHB and SDHD-AT PHEOs/PGLs (cluster A) from VHL PHEOs and SDHD-HN PGLs (cluster B). Supervised analysis yielded 6937 highly predictive genes (misclassification error rate of 0.175). Enrichment analysis revealed that energy metabolism and inflammation/fibrosis-related genes were most pronouncedly changed in clusters A and B, respectively. A minimum subset of 40 classifiers was validated by quantitative real-time polymerase chain reaction (quantitative real-time polymerase chain reaction vs. microarray: r = 0.87). Expression of several individual classifiers was identified as characteristic for VHL and SDHD-HN PHEOs and PGLs. In the present study, we show for the first time that SDHD-HN PGLs share more features with VHL PHEOs than with SDHD-AT PGLs. The presented data suggest novel subclassification of pseudohypoxic PHEOs/PGLs and implies cluster-specific pathogenic mechanisms and treatment strategies.

Chitinases in the salivary glands and circulation of patients with Sjögren's syndrome: macrophage harbingers of disease severity

OBJECTIVE

Sjögren's syndrome (SS) is a chronic autoimmune disease of unknown etiology that targets salivary and lacrimal glands and may be accompanied by multiorgan systemic manifestations. To further the understanding of immunopathology associated with SS and identify potential therapeutic targets, we undertook the present study comparing the gene expression profiles of salivary glands with severe inflammation versus those of salivary glands with mild or no disease.

METHODS

Using microarray profiling of salivary gland tissue from patients with SS and control subjects, we identified target genes, which were further characterized in tissue, serum, and cultured cell populations by real-time polymerase chain reaction and protein analysis.

RESULTS

Among the most highly expressed SS genes were those associated with myeloid cells, including members of the mammalian chitinase family, which had not previously been shown to be associated with exocrinopathies. Both chitinase 3-like protein 1 and chitinase 1, highly conserved chitinase-like glycoproteins (one with enzymatic activity and one lacking enzymatic activity), were evident at the transcriptome level and were detected within inflamed tissue. Chitinases were expressed during monocyte-to-macrophage differentiation and their levels augmented by stimulation with cytokines, including interferon-α (IFNα).

CONCLUSION

Because elevated expression of these and other macrophage-derived molecules corresponded with more severe SS, the present observations suggest that macrophages have potential immunopathologic involvement in SS and that the tissue macrophage transcription profile reflects multiple genes induced by IFNα.

Fatigue-related gene networks identified in CD(14)+ cells isolated from HIV-infected patients: part I: research findings

PURPOSE

Human immunodeficiency virus (HIV)-related fatigue (HRF) is multicausal and potentially related to mitochondrial dysfunction caused by antiretroviral therapy with nucleoside reverse transcriptase inhibitors (NRTIs).

METHODOLOGY

The authors compared gene expression profiles of CD14(+) cells of low versus high fatigued, NRTI-treated HIV patients to healthy controls (n = 5/group). The authors identified 32 genes predictive of low versus high fatigue and 33 genes predictive of healthy versus HIV infection. The authors constructed genetic networks to further elucidate the possible biological pathways in which these genes are involved. RELEVANCE FOR NURSING PRACTICE: Genes including the actin cytoskeletal regulatory proteins Prokineticin 2 and Cofilin 2 along with mitochondrial inner membrane proteins are involved in multiple pathways and were predictors of fatigue status. Previously identified inflammatory and signaling genes were predictive of HIV status, clearly confirming our results and suggesting a possible further connection between mitochondrial function and HIV. Isolated CD14(+) cells are easily accessible cells that could be used for further study of the connection between fatigue and mitochondrial function of HIV patients.

IMPLICATION FOR PRACTICE

The findings from this pilot study take us one step closer to identifying biomarker targets for fatigue status and mitochondrial dysfunction. Specific biomarkers will be pertinent to the development of methodologies to diagnosis, monitor, and treat fatigue and mitochondrial dysfunction.

A characterization of the oral microbiome in allogeneic stem cell transplant patients

BACKGROUND

The mouth is a complex biological structure inhabited by diverse bacterial communities. The purpose of this study is to describe the effects of allogeneic stem cell transplantation on the oral microbiota and to examine differences among those patients who acquired respiratory complications after transplantation.

METHODOLOGY/PRINCIPAL FINDINGS

All patients were consented at the National Institutes of Health, Clinical Center. Bacterial DNA was analyzed from patients' oral specimens using the Human Oral Microbe Identification Microarray. The specimens were collected from four oral sites in 45 allogeneic transplantation patients. Specimens were collected at baseline prior to transplantation, after transplantation at the nadir of the neutrophil count and after myeloid engraftment. If respiratory signs and symptoms developed, additional specimens were obtained. Patients were followed for 100 days post transplantation. Eleven patients' specimens were subjected to further statistical analysis. Many common bacterial genera, such as Streptococcus, Veillonella, Gemella, Granulicatella and Camplyobacter were identified as being present before and after transplantation. Five of 11 patients developed respiratory complications following transplantation and there was preliminary evidence that the oral microbiome changed in their oral specimens. Cluster analysis and principal component analysis revealed this change in the oral microbiota.

CONCLUSIONS/SIGNIFICANCE

After allogeneic transplantation, the oral bacterial community's response to a new immune system was not apparent and many of the most common core oral taxa remained unaffected. However, the oral microbiome was affected in patients who developed respiratory signs and symptoms after transplantation. The association related to the change in the oral microbiota and respiratory complications after transplantation will be validated by future studies using high throughput molecular methods.

HIV infection and antiretroviral therapy have divergent effects on mitochondria in adipose tissue

BACKGROUND

Although human immunodeficiency virus (HIV) infection and antiretroviral therapy (ART) affect mitochondrial DNA (mtDNA) content and function, comprehensive evaluations of their effects on mitochondria in muscle, adipose tissue, and blood cells are limited.

METHODS

Mitochondrial DNA quantification, mitochondrial genome sequencing, and gene expression analysis were performed on muscle, adipose tissue, and peripheral blood mononuclear cell (PBMC) samples from untreated HIV-positive patients, HIV-positive patients receiving nucleoside reverse transcriptase inhibitor (NRTI)-based ART, and HIV-negative controls.

RESULTS

The adipose tissue mtDNA/nuclear DNA (nDNA) ratio was increased in untreated HIV-infected patients (ratio, 353) and decreased in those receiving ART (ratio, 162) compared with controls (ratio, 255; P < .05 for both comparisons); the difference between the 2 HIV-infected groups was also significant (P = .002). In HIV-infected participants, mtDNA/nDNA in adipose tissue correlated with the level of activation (CD38+ /HLA-DR+) for CD4+ and CD8+ lymphocytes. No significant differences in mtDNA content were noted in muscle or PMBCs among groups. Exploratory DNA microarray analysis identified differential gene expression between patient groups, including a subset of adipose tissue genes.

CONCLUSIONS

HIV infection and ART have opposing effects on mtDNA content in adipose tissue; immune activation may mediate the effects of HIV, whereas NRTIs likely mediate the effects of ART.

DOMIRE: a web server for identifying structural domains and their neighbors in proteins

SUMMARY

The DOMIRE web server implements a novel, automatic, protein structural domain assignment procedure based on 3D substructures of the query protein which are also found within structures of a non-redundant protein database. These common 3D substructures are transformed into a co-occurrence matrix that offers a global view of the protein domain organization. Three different algorithms are employed to define structural domain boundaries from this co-occurrence matrix. For each query, a list of structural neighbors and their alignments are provided. DOMIRE, by displaying the protein structural domain organization, can be a useful tool for defining protein common cores and for unravelling the evolutionary relationship between different proteins.

AVAILABILITY

http://genome.jouy.inra.fr/domire

CONTACT

jean.garnier@jouy.inra.fr.

Biomarker discovery in serum from patients with carotid atherosclerosis

BACKGROUND

Blood-based biomarkers of atherosclerosis have been used to identify patients at high risk for developing stroke. We hypothesized that patients with carotid artery disease would have a distinctive proteomic signature in blood as compared to a healthy control population without carotid artery disease. In order to discover protein biomarkers associated with increased atherosclerotic risk, we used two different strategies to identify biomarkers from patients with clinically defined atherosclerosis who were undergoing endarterectomy for atherosclerotic carotid artery disease. These patients were compared with healthy matched controls.

METHODS

Serum was obtained from patients undergoing endarterectomy (EA; n = 38) and compared to a group of age-matched healthy controls (n = 40). Serum was fractionated using anion exchange chromatography and three different surface-enhanced laser desorption/ionization (SELDI) chip surfaces and then evaluated with mass spectrometry (MS) and two-dimensional difference gel electrophoresis (2D-DIGE).

RESULTS

A random forest (RF) analysis of the SELDI-MS protein peak data distinguished these two groups with 69.2% sensitivity and 73.2% specificity. Four unique SELDI peaks (4.2, 4.4, 16.7 and 28 kDa, all p< 0.01) showed the greatest influence in the RF model. The EA patients with a history of prior clinical atherosclerotic plaque rupture manifested as either stroke or transient ischemic attack (symptomatic; n = 16) were compared to patients with carotid atherosclerosis but no clinical evidence of plaque rupture (asymptomatic; n = 22). Analysis of the SELDI spectra did not separate these two patient subgroups. A subgroup analysis using 2D-DIGE images obtained from albumin-depleted serum comparing symptomatic (n = 10) to asymptomatic EA patients (n = 10) found 4 proteins that were differentially expressed (p < 0.01) in the symptomatic patients. These proteins were identified as α(1)-antitrypsin, haptoglobin and vitamin D binding protein that were downregulated and α(2)-glycoprotein precursor that was upregulated in the symptomatic EA group.

CONCLUSIONS

SELDI-MS data analysis of fractionated serum suggests that a distinct protein signature exists in patients with carotid atherosclerosis compared to age-matched healthy controls. Identification of 4 proteins in a subset of patients with symptomatic and asymptomatic carotid atherosclerosis suggests that these and other protein biomarkers may assist in identifying high-risk patients with carotid atherosclerosis.

Fatigue-related gene networks identified in CD14+ cells isolated from HIV-infected patients: part II: statistical analysis

PURPOSE

In limited samples of valuable biological tissues, univariate ranking methods of microarray analyses often fail to show significant differences among expression profiles. In order to allow for hypothesis generation, novel statistical modeling systems can be greatly beneficial. The authors applied new statistical approaches to solve the issue of limited experimental data to generate new hypotheses in CD14(+) cells of patients with HIV-related fatigue (HRF) and healthy controls.

METHODOLOGY

We compared gene expression profiles of CD14(+) cells of nucleoside reverse transcriptase inhibitor (NRTI)-treated HIV patients with low versus high fatigue to healthy controls (n = 5 each). With novel Bayesian modeling procedures, the authors identified 32 genes predictive of low versus high fatigue and 33 genes predictive of healthy versus HIV infection. Sparse association and liquid association networks further elucidated the possible biological pathways in which these genes are involved. RELEVANCE FOR NURSING PRACTICE: Genetic networks developed in a comprehensive Bayesian framework from small sample sizes allow nursing researchers to design future research approaches to address such issues as HRF.

IMPLICATION FOR PRACTICE

The findings from this pilot study may take us one step closer to the development of useful biomarker targets for fatigue status. Specific and reliable tests are needed to diagnosis, monitor and treat fatigue and mitochondrial dysfunction.

Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study

Despite a growing number of reports of gene expression analysis from blood-derived RNA sources, there have been few systematic comparisons of various RNA sources in transcriptomic analysis or for biomarker discovery in the context of cardiovascular disease (CVD). As a pilot study of the Systems Approach to Biomarker Research (SABRe) in CVD Initiative, this investigation used Affymetrix Exon arrays to characterize gene expression of three blood-derived RNA sources: lymphoblastoid cell lines (LCL), whole blood using PAXgene tubes (PAX), and peripheral blood mononuclear cells (PBMC). Their performance was compared in relation to identifying transcript associations with sex and CVD risk factors, such as age, high-density lipoprotein, and smoking status, and the differential blood cell count. We also identified a set of exons that vary substantially between participants, but consistently in each RNA source. Such exons are thus stable phenotypes of the participant and may potentially become useful fingerprinting biomarkers. In agreement with previous studies, we found that each of the RNA sources is distinct. Unlike PAX and PBMC, LCL gene expression showed little association with the differential blood count. LCL, however, was able to detect two genes related to smoking status. PAX and PBMC identified Y-chromosome probe sets similarly and slightly better than LCL.

Cooperative and redundant signaling of leukotriene B4 and leukotriene D4 in human monocytes

BACKGROUND

Leukotriene B(4) (LTB(4)) and cysteinyl leukotrienes (cysLTs) are important immune mediators, often found concomitantly at sites of inflammation. Although some of the leukotriene-mediated actions are distinctive (e.g., bronchial constriction for cysLTs), many activities such as leukocyte recruitment to tissues and amplification of inflammatory responses are shared by both classes of leukotrienes.

OBJECTIVE

We used human monocytes to characterize leukotriene-specific signaling, gene expression signatures, and functions and to identify interactions between LTB(4)- and cysLTs-induced pathways.

METHODS

Responsiveness to leukotrienes was assessed using oligonucleotide microarrays, real-time PCR, calcium mobilization, kinase activation, and chemotaxis assays.

RESULTS

Human monocytes were found to express mRNA for high- and low-affinity LTB(4) receptors, BLT(1) and BLT(2), but signal predominantly through BLT(1) in response to LTB(4) stimulation as shown using selective agonists, inhibitors, and gene knock down experiments. LTB(4) acting through BLT(1) coupled to G-protein α inhibitory subunit activated calcium signaling, p44/42 mitogen-activated protein kinase, gene expression, and chemotaxis. Twenty-seven genes, including immediate early genes (IEG), transcription factors, cytokines, and membrane receptors were significantly up-regulated by LTB(4). LTB(4) and LTD(4) had similar effects on signaling, gene expression, and chemotaxis indicating redundant cell activation pathways but costimulation with both lipid mediators was additive for many monocyte functions.

CONCLUSION

Leukotriene B(4) and LTD(4) display both redundant and cooperative effects on intracellular signaling, gene expression, and chemotaxis in human monocytes. These findings suggest that therapies targeting either leukotriene alone may be less effective than approaches directed at both.

Transcriptome profiling and sequencing of differentiated human hematopoietic stem cells reveal lineage-specific expression and alternative splicing of genes

Hematopoietic differentiation is strictly regulated by complex network of transcription factors that are controlled by ligands binding to cell surface receptors. Disruptions of the intricate sequences of transcriptional activation and suppression of multiple genes cause hematological diseases, such as leukemias, myelodysplastic syndromes, or myeloproliferative syndromes. From a clinical standpoint, deciphering the pattern of gene expression during hematopoiesis may help unravel disease-specific mechanisms in hematopoietic malignancies. Herein, we describe a human in vitro hematopoietic model system where lineage-specific differentiation of CD34(+) cells was accomplished using specific cytokines. Microarray and RNAseq-based whole transcriptome and exome analysis was performed on the differentiated erythropoietic, granulopoietic, and megakaryopoietic cells to delineate changes in expression of whole transcripts and exons. Analysis on the Human 1.0 ST exon arrays indicated differential expression of 172 genes (P < 0.0000001) and significant alternate splicing of 86 genes during differentiation. Pathway analysis identified these genes to be involved in Rac/RhoA signaling, Wnt/B-catenin signaling and alanine/aspartate metabolism. Comparison of the microarray data to next generation RNAseq analysis during erythroid differentiation demonstrated a high degree of correlation in gene (R = 0.72) and exon (R = 0.62) expression. Our data provide a molecular portrait of events that regulate differentiation of hematopoietic cells. Knowledge of molecular processes by which the cells acquire their cell-specific fate would be beneficial in developing cell-based therapies for human diseases.

Treatment-induced oxidative stress and cellular antioxidant capacity determine response to bortezomib in mantle cell lymphoma

PURPOSE

Proteasome inhibition disrupts protein homeostasis and induces apoptosis. Up to 50% of patients with relapsed mantle cell lymphoma (MCL) respond to bortezomib. We used gene expression profiling to investigate the connection between proteasome inhibition, cellular response, and clinical efficacy.

EXPERIMENTAL DESIGN

We assessed transcriptional changes in primary tumor cells from five patients during treatment with bortezomib in vivo, and in 10 MCL cell lines exposed to bortezomib in vitro, on Affymetrix microarrays. Key findings were confirmed by western blotting.

RESULTS

MCL cell lines exposed to bortezomib in vitro showed upregulation of endoplasmic reticulum and oxidative stress response pathways. Gene expression changes were strongest in bortezomib-sensitive cells and these cells were also more sensitive to oxidative stress induced by H2O2. Purified tumor cells obtained at several timepoints during bortezomib treatment in 5 previously untreated patients with leukemic MCL showed strong activation of the antioxidant response controlled by NRF2. Unexpectedly, activation of this homeostatic program was significantly stronger in tumors with the best clinical response. Consistent with its proapoptotic function, we found upregulation of NOXA in circulating tumor cells of responding patients. In resistant cells, gene expression changes in response to bortezomib were limited and upregulation of NOXA was absent. Interestingly, at baseline, bortezomib-resistant cells displayed a relatively higher expression of the NRF2 gene-expression signature than sensitive cells (P < 0.001).

CONCLUSION

Bortezomib triggers an oxidative stress response in vitro and in vivo. High cellular antioxidant capacity contributes to bortezomib resistance.