CD14 and complement crosstalk and largely mediate the transcriptional response to Escherichia coli in human whole blood as revealed by DNA microarray

Systemic inflammation like in sepsis is still lacking specific diagnostic markers and effective therapeutics. The first line of defense against intruding pathogens and endogenous damage signals is pattern recognition by e.g., complement and Toll-like receptors (TLR). Combined inhibition of a key complement component (C3 and C5) and TLR-co-receptor CD14 has been shown to attenuate certain systemic inflammatory responses. Using DNA microarray and gene annotation analyses, we aimed to decipher the effect of combined inhibition of C3 and CD14 on the transcriptional response to bacterial challenge in human whole blood. Importantly, combined inhibition reversed the transcriptional changes of 70% of the 2335 genes which significantly responded to heat-inactivated Escherichia coli by on average 80%. Single inhibition was less efficient (p<0.001) but revealed a suppressive effect of C3 on 21% of the responding genes which was partially counteracted by CD14. Furthermore, CD14 dependency of the Escherichia coli-induced response was increased in C5-deficient compared to C5-sufficient blood. The observed crucial distinct and synergistic roles for complement and CD14 on the transcriptional level correspond to their broad impact on the inflammatory response in human blood, and their combined inhibition may become inevitable in the early treatment of acute systemic inflammation.

Fish oil supplementation induces expression of genes related to cell cycle, endoplasmic reticulum stress and apoptosis in peripheral blood mononuclear cells: a transcriptomic approach

BACKGROUND

Fish oil supplementation has been shown to alter gene expression of mononuclear cells both in vitro and in vivo. However, little is known about the total transcriptome profile in healthy subjects after intake of fish oil. We therefore investigated the gene expression profile in peripheral blood mononuclear cells (PBMCs) after intake of fish oil for 7 weeks using transcriptome analyses.

DESIGN

In a 7-week, double-blinded, randomized, controlled, parallel-group study, healthy subjects received 8 g day(-1) fish oil (1.6 g day(-1) eicosapentaenoic acid + docosahexaenoic acid) (n = 17) or 8 g day(-1) high oleic sunflower oil (n = 19). Microarray analyses of RNA isolated from PBMCs were performed at baseline and after 7 weeks of intervention.

RESULTS

Cell cycle, DNA packaging and chromosome organization are biological processes found to be upregulated after intake of fish oil compared to high oleic sunflower oil using a moderated t-test. In addition, gene set enrichment analysis identified several enriched gene sets after intake of fish oil. The genes contributing to the significantly different gene sets in the subjects given fish oil compared with the control group are involved in cell cycle, endoplasmic reticulum (ER) stress and apoptosis. Gene transcripts with common motifs for 35 known transcription factors including E2F, TP53 and ATF4 were upregulated after intake of fish oil.

CONCLUSION

We have shown that intake of fish oil for 7 weeks modulates gene expression in PBMCs of healthy subjects. The increased expression of genes related to cell cycle, ER stress and apoptosis suggests that intake of fish oil may modulate basic cellular processes involved in normal cellular function.

A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions

Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.

The Genomic HyperBrowser: an analysis web server for genome-scale data

The immense increase in availability of genomic scale datasets, such as those provided by the ENCODE and Roadmap Epigenomics projects, presents unprecedented opportunities for individual researchers to pose novel falsifiable biological questions. With this opportunity, however, researchers are faced with the challenge of how to best analyze and interpret their genome-scale datasets. A powerful way of representing genome-scale data is as feature-specific coordinates relative to reference genome assemblies, i.e. as genomic tracks. The Genomic HyperBrowser (http://hyperbrowser.uio.no) is an open-ended web server for the analysis of genomic track data. Through the provision of several highly customizable components for processing and statistical analysis of genomic tracks, the HyperBrowser opens for a range of genomic investigations, related to, e.g., gene regulation, disease association or epigenetic modifications of the genome.

Deep Sequencing the MicroRNA Transcriptome in Colorectal Cancer

Colorectal cancer (CRC) is one of the leading causes of cancer related deaths and the search for prognostic biomarkers that might improve treatment decisions is warranted. MicroRNAs (miRNAs) are short non-coding RNA molecules involved in regulating gene expression and have been proposed as possible biomarkers in CRC. In order to characterize the miRNA transcriptome, a large cohort including 88 CRC tumors with long-term follow-up was deep sequenced. 523 mature miRNAs were expressed in our cohort, and they exhibited largely uniform expression patterns across tumor samples. Few associations were found between clinical parameters and miRNA expression, among them, low expression of miR-592 and high expression of miR-10b-5p and miR-615-3p were associated with tumors located in the right colon relative to the left colon and rectum. High expression of miR-615-3p was also associated with poorly differentiated tumors. No prognostic biomarker candidates for overall and metastasis-free survival were identified by applying the LASSO method in a Cox proportional hazards model or univariate Cox. Examination of the five most abundantly expressed miRNAs in the cohort (miR-10a-5p, miR-21-5p, miR-22-3p, miR-143-3p and miR-192-5p) revealed that their collective expression represented 54% of the detected miRNA sequences. Pathway analysis of the target genes regulated by the five most highly expressed miRNAs uncovered a significant number of genes involved in the CRC pathway, including APC, TGFβ and PI3K, thus suggesting that these miRNAs are relevant in CRC.

Abstract 807: Eight candidate target genes of the recurrent 3p12-p14 loss in cervical cancer

Genetic gains and losses, i.e. gene dosage alterations, influence gene expressions and thereby promote tumor development and progression. Identification and functional assessment of such alterations may help to understand the biology of the disease and be useful for the discovery of diagnostic and therapeutic biomarkers. The recurrent 3p12-p14 loss in cervical cancer has been proposed as a prognostic biomarker, however, its pathogenetic role, including its target genes, remains to be clarified. The purpose of this work was to identify 3p target genes in cervical cancer, and explore their role in the development of chemoradioresistance.

Cox regression analysis of the 3p gene dosages showed that loss of 3p11.2-p14.2 was significantly associated with clinical outcome. To depict candidate target genes of the loss, pairwise gene dosage and expression profiling was performed on 77 patients by array comparative genomic hybridization and Illumina gene expression beadarrays, respectively, including all genes within the 3p11.2–p14.2 region. The expression of eight of the 147 genes within the region; i.e., THOC7, PSMD6, SLC25A26, TMF1, RYBP, SHQ1, EBLN2, and GBE1, were highly downregulated in cases with loss. This was confirmed at the protein level for RYBP and TMF1 in 150 patients by immunohistochemistry.

A gene signature with the expression values of the eight candidate genes was constructed to explore the prognostic impact of all genes combined. Unsupervised hierarchical clustering divided the patients into two groups, for which the group with downregulation of the genes had the highest frequency of 3p loss and a poor outcome compared to the other. A 3p target gene score was calculated for each tumor, and was shown to be lower for patients with 3p loss and associated with clinical outcome. The prognostic impact of the eight gene signature was confirmed in a validation cohort of 74 patients, showing a worse outcome for patients with a low 3p target gene score, confirming the clinical significance of the signature.

To assess the importance of the signature in comparison to existing clinical markers, we merged the two cohorts to a group of 151 patients. In univariate Cox regression analysis, the 3p target gene score was associated with outcome. All eight genes showed a significant or clear tendency towards a relationship to outcome in a single gene analysis, and therefore seemed to contribute to the univariate result. In multivariate analysis, the score emerged as a prognostic factor independent of lymph node status, tumor size, and stage.

These results support a role of the eight candidate genes as targets of the 3p12–p14 loss in cervical cancer and propose their use as biomarker in the clinical decision-making.

Citation Format: Malin Lando, Marit Holden, Ruth Holm, Gunnar B. Kristensen, Heidi Lyng. Eight candidate target genes of the recurrent 3p12-p14 loss in cervical cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 807. doi:10.1158/1538-7445.AM2013-807

Treatment outcome of chronic low back pain and radiographic lumbar disc degeneration are associated with inflammatory and matrix degrading gene variants: a prospective genetic association study

BACKGROUND

Inflammatory and matrix degrading gene variants have been reported to be associated with disc degeneration. Some of these variants also modulate peripheral pain. This study examines the association of these genetic variants with radiographic lumbar disc degeneration and changes in pain and disability at long-term after surgical and cognitive behavioural management.

METHODS

93 unrelated patients with chronic low back pain (CLBP) for duration of >1 year and lumbar disc degeneration were treated with lumbar fusion or cognitive intervention and exercises. Standardised questionnaires included the Oswestry Disability Index (ODI) and Visual Analog Score (VAS) for CLBP, were filled in by patients both at baseline and at 9 years follow-up. Degenerative changes at baseline Magnetic Resonance Imaging and Computed Tomography scans, were graded as moderate and severe (N=79). Yield and quality of blood and saliva DNA was assessed by nano drop spectrophotometry. Eight SNPs in 5 inflammatory and matrix degrading genes were successfully genotyped. Single marker and haplotype association with severity of degeneration, number of discs involved, changes in ODI and VAS CLBP, was done using Haploview, linear regression and R-package Haplostats.

RESULTS

Association analysis of individual SNPs revealed association of IL18RAP polymorphism rs1420100 with severe degeneration (p = 0.05) and more than one degenerated disc (p = 0.02). From the same gene two SNPs, rs917997 and rs1420106, were found to be in strong linkage disequilibrium (LD) and were associated with post treatment improvement in disability (p = 0.02). Haplotype association analysis of 5 SNPs spanning across IL18RAP, IL18R1 and IL1A genes revealed significant associations with improvement in disability (p=0.02) and reduction in pain (p=0.04). An association was found between MMP3 polymorphism rs72520913 and improvement in pain (p = 0.03) and with severe degeneration (p = 0.006).

CONCLUSIONS

The findings of the current study suggest a role of variation at inflammatory and matrix degrading genes with severity of lumbar disc degeneration, pain and disability.

Identification of eight candidate target genes of the recurrent 3p12-p14 loss in cervical cancer by integrative genomic profiling

The pathogenetic role, including its target genes, of the recurrent 3p12-p14 loss in cervical cancer has remained unclear. To determine the onset of the event during carcinogenesis, we used microarray techniques and found that the loss was the most frequent 3p event, occurring in 61% of 92 invasive carcinomas, in only 2% of 43 high-grade intraepithelial lesions (CIN2/3), and in 33% of 6 CIN3 lesions adjacent to invasive carcinomas, suggesting a role in acquisition of invasiveness or early during the invasive phase. We performed an integrative DNA copy number and expression analysis of 77 invasive carcinomas, where all genes within the recurrent region were included. We selected eight genes, THOC7, PSMD6, SLC25A26, TMF1, RYBP, SHQ1, EBLN2, and GBE1, which were highly down-regulated in cases with loss, as confirmed at the protein level for RYBP and TMF1 by immunohistochemistry. The eight genes were subjected to network analysis based on the expression profiles, revealing interaction partners of proteins encoded by the genes that were coordinately regulated in tumours with loss. Several partners were shared among the eight genes, indicating crosstalk in their signalling. Gene ontology analysis showed enrichment of biological processes such as apoptosis, proliferation, and stress response in the network and suggested a relationship between down-regulation of the eight genes and activation of tumourigenic pathways. Survival analysis showed prognostic impact of the eight-gene signature that was confirmed in a validation cohort of 74 patients and was independent of clinical parameters. These results support the role of the eight candidate genes as targets of the 3p12-p14 loss in cervical cancer and suggest that the strong selection advantage of the loss during carcinogenesis might be caused by a synergetic effect of several tumourigenic processes controlled by these targets.

Stress associated gene expression in blood cells is related to outcome in radiotherapy treated head and neck cancer patients

Background

We previously observed that a radiotherapy-induced biochemical response in plasma was associated with favourable outcome in head and neck squamous carcinoma cancer (HNSCC) patients. The aim of the present study was to compare stress associated blood cell gene expression between two sub-groups of HNSCC patients with different biochemical responses to radiotherapy.

Methods

Out of 87 patients (histologically verified), 10 biochemical ‘responders’ having a high relative increase in plasma oxidative damage and a concomitant decrease in plasma antioxidants during radiotherapy and 10 ‘poor-responders’ were selected for gene-expression analysis and compared using gene set enrichment analysis.

Results

There was a significant induction of stress-relevant gene-sets in the responders following radiotherapy compared to the poor-responders. The relevance of the involvement of similar stress associated gene expression for HNSCC cancer and radioresistance was verified using two publicly available data sets of 42 HNSCC cases and 14 controls (GEO GSE6791), and radiation resistant and radiation sensitive HNSCC xenografts (E-GEOD-9716).

Conclusions

Radiotherapy induces a systemic stress response, as revealed by induction of stress relevant gene expression in blood cells, which is associated to favourable outcome in a cohort of 87 HNSCC patients. Whether these changes in gene expression reflects a systemic effect or are biomarkers of the tumour micro-environmental status needs further study.

Trial registration

Raw data are available at ArrayExpress under accession number E-MEXP-2460.

Genetic contribution of catechol-O-methyltransferase variants in treatment outcome of low back pain: a prospective genetic association study

Background

Treatment outcome of low back pain (LBP) is associated with inter-individual variations in pain relief and functional disability. Genetic variants of catechol-O-methyltransferase (COMT) gene have previously been shown to be associated with pain sensitivity and pain medication. This study examines the association between COMT polymorphisms and 7–11 year change in Oswestry Disability Index (ODI) and Visual Analog Score (VAS) for LBP as clinical outcome variables in patients treated with surgical instrumented lumbar fusion or cognitive intervention and exercise.

Methods

93 unrelated patients with chronic LBP for duration of >1 year and lumbar disc degeneration (LDD) were treated with lumbar fusion (N = 60) or cognitive therapy and exercises (N = 33). Standardised questionnaires assessing the ODI, VAS LBP, psychological factors and use of analgesics, were answered by patients both at baseline and at 7–11 years follow-up. Four SNPs in the COMT gene were successfully genotyped. Single marker as well as haplotype association with change in ODI and VAS LBP, were analyzed using Haploview, linear regression and R-package Haplostats. P-values were not formally corrected for multiple testing as this was an explorative study.

Results

Association analysis of individual SNPs adjusted for covariates revealed association of rs4633 and rs4680 with post treatment improvement in VAS LBP (p = 0.02, mean difference (β) = 13.5 and p = 0.02, β = 14.2 respectively). SNPs, rs4633 and rs4680 were found to be genotypically similar and in strong linkage disequilibrium (LD). A significant association was found with covariates, analgesics (p = 0.001, β = 18.6); anxiety and depression (p = 0.008, β = 15.4) and age (p = 0.03, mean difference per year (β) = 0.7) at follow-up. There was a tendency for better improvement among heterozygous patients compared to the homozygous. No association was observed for the analysis of the common haplotypes, these SNPs were situated on.

Conclusions

Results suggest an influence of genetic variants of COMT gene in describing the variation in pain after treatment for low back pain. Replication in large samples with testing for other pain related genes is warranted.

Molecular disease map of bone characterizing the postmenopausal osteoporosis phenotype

Genome-wide gene expressions in bone biopsies from patients with postmenopausal osteoporosis and healthy controls were profiled, to identify osteoporosis candidate genes. All osteoporotic patients (n = 27) in an unbiased cohort of Norwegian women presented with bone mineral density (BMD) T-scores of less than -2.5 SD and one or more confirmed low-energy fracture(s). A validation group (n = 18) had clinical and laboratory parameters intermediate to the control (n = 39) and osteoporosis groups. RNA from iliac crest bone biopsies were analyzed by Affymetrix microarrays and real-time reverse-transcriptase polymerase chain reaction (RT-PCR). Differentially expressed genes in osteoporosis versus control groups were identified using the Bayesian ANOVA for microarrays (BAMarray) method, whereas the R-package Limma (Linear Models for Microarray Data) was used to determine whether these transcripts were explained by disease, age, body mass index (BMI), or combinations thereof. Laboratory tests showed normal ranges for the cohort. A total of 609 transcripts were differentially expressed in osteoporotic patients relative to controls; 256 transcripts were confirmed for disease when controlling for age or BMI. Most of the osteoporosis susceptibility genes (80%) also were confirmed to be regulated in the same direction in the validation group. Furthermore, 217 of 256 transcripts were correlated with BMD (adjusted for age and BMI) at various skeletal sites (|r| > 0.2, p < .05). Among the most distinctly expressed genes were Wnt antagonists DKK1 and SOST, the transcription factor SOX4, and the bone matrix proteins MMP13 and MEPE, all reduced in osteoporosis versus control groups. Our results identify potential osteoporosis susceptibility candidate genes adjusted for confounding factors (ie, age and BMI) with or without a significant correlation with BMD.

Membranous expression of ectodomain isoforms of the epidermal growth factor receptor predicts outcome after chemoradiotherapy of lymph node-negative cervical cancer

PURPOSE

We compared the prognostic significance of ectodomain isoforms of the epidermal growth factor receptor (EGFR), which lack the tyrosine kinase (TK) domain, with that of the full-length receptor and its autophosphorylation status in cervical cancers treated with conventional chemoradiotherapy.

EXPERIMENTAL DESIGN

Expression of EGFR isoforms was assessed by immunohistochemistry in a prospectively collected cohort of 178 patients with squamous cell cervical carcinoma, and their detection was confirmed with Western blotting and reverse transcriptase PCR. A proximity ligation immunohistochemistry assay was used to assess EGFR-specific autophosphorylation. Pathways associated with the expression of ectodomain isoforms were studied by gene expression analysis with Illumina beadarrays in 110 patients and validated in an independent cohort of 41 patients.

RESULTS

Membranous expression of ectodomain isoforms alone, without the coexpression of the full-length receptor, showed correlations to poor clinical outcome that were highly significant for lymph node-negative patients (locoregional control, P = 0.0002; progression-free survival, P < 0.0001; disease-specific survival, P = 0.005 in the log-rank test) and independent of clinical variables. The ectodomain isoforms were primarily 60-kD products of alternative EGFR transcripts. Their membranous expression correlated with transcriptional regulation of oncogenic pathways including activation of MYC and MAX, which was significantly associated with poor outcome. This aggressive phenotype of ectodomain EGFR expressing tumors was confirmed in the independent cohort. Neither total nor full-length EGFR protein level, or autophosphorylation status, showed prognostic significance.

CONCLUSION

Membranous expression of ectodomain EGFR isoforms, and not TK activation, predicts poor outcome after chemoradiotherapy for patients with lymph node-negative cervical cancer.

The differential disease regulome

Background

Transcription factors in disease-relevant pathways represent potential drug targets, by impacting a distinct set of pathways that may be modulated through gene regulation. The influence of transcription factors is typically studied on a per disease basis, and no current resources provide a global overview of the relations between transcription factors and disease. Furthermore, existing pipelines for related large-scale analysis are tailored for particular sources of input data, and there is a need for generic methodology for integrating complementary sources of genomic information.

Results

We here present a large-scale analysis of multiple diseases versus multiple transcription factors, with a global map of over-and under-representation of 446 transcription factors in 1010 diseases. This map, referred to as the differential disease regulome, provides a first global statistical overview of the complex interrelationships between diseases, genes and controlling elements. The map is visualized using the Google map engine, due to its very large size, and provides a range of detailed information in a dynamic presentation format.

The analysis is achieved through a novel methodology that performs a pairwise, genome-wide comparison on the cartesian product of two distinct sets of annotation tracks, e.g. all combinations of one disease and one TF.

The methodology was also used to extend with maps using alternative data sets related to transcription and disease, as well as data sets related to Gene Ontology classification and histone modifications. We provide a web-based interface that allows users to generate other custom maps, which could be based on precisely specified subsets of transcription factors and diseases, or, in general, on any categorical genome annotation tracks as they are improved or become available.

Conclusion

We have created a first resource that provides a global overview of the complex relations between transcription factors and disease. As the accuracy of the disease regulome depends mainly on the quality of the input data, forthcoming ChIP-seq based binding data for many TFs will provide improved maps. We further believe our approach to genome analysis could allow an advance from the current typical situation of one-time integrative efforts to reproducible and upgradable integrative analysis. The differential disease regulome and its associated methodology is available at http://hyperbrowser.uio.no.

The Genomic HyperBrowser: inferential genomics at the sequence level

The immense increase in the generation of genomic scale data poses an unmet analytical challenge, due to a lack of established methodology with the required flexibility and power. We propose a first principled approach to statistical analysis of sequence-level genomic information. We provide a growing collection of generic biological investigations that query pairwise relations between tracks, represented as mathematical objects, along the genome. The Genomic HyperBrowser implements the approach and is available at http://hyperbrowser.uio.no.

Blood cell gene expression associated with cellular stress defense is modulated by antioxidant-rich food in a randomised controlled clinical trial of male smokers

BACKGROUND

Plant-based diets rich in fruit and vegetables can prevent development of several chronic age-related diseases. However, the mechanisms behind this protective effect are not elucidated. We have tested the hypothesis that intake of antioxidant-rich foods can affect groups of genes associated with cellular stress defence in human blood cells.

TRIAL REGISTRATION NUMBER

NCT00520819 http://clinicaltrials.gov.

METHODS

In an 8-week dietary intervention study, 102 healthy male smokers were randomised to either a diet rich in various antioxidant-rich foods, a kiwifruit diet (three kiwifruits/d added to the regular diet) or a control group. Blood cell gene expression profiles were obtained from 10 randomly selected individuals of each group. Diet-induced changes on gene expression were compared to controls using a novel application of the gene set enrichment analysis (GSEA) on transcription profiles obtained using Affymetrix HG-U133-Plus 2.0 whole genome arrays.

RESULTS

Changes were observed in the blood cell gene expression profiles in both intervention groups when compared to the control group. Groups of genes involved in regulation of cellular stress defence, such as DNA repair, apoptosis and hypoxia, were significantly upregulated (GSEA, FDR q-values < 5%) by both diets compared to the control group. Genes with common regulatory motifs for aryl hydrocarbon receptor (AhR) and AhR nuclear translocator (AhR/ARNT) were upregulated by both interventions (FDR q-values < 5%). Plasma antioxidant biomarkers (polyphenols/carotenoids) increased in both groups.

CONCLUSIONS

The observed changes in the blood cell gene expression profiles suggest that the beneficial effects of a plant-based diet on human health may be mediated through optimization of defence processes.

Eight genes are highly associated with BMD variation in postmenopausal Caucasian women

Low bone mineral density (BMD) is an important risk factor for skeletal fractures which occur in about 40% of women >/=50 years in the western world. We describe the transcriptional changes in 84 trans-iliacal bone biopsies associated with BMD variations in postmenopausal females (50 to 86 years), aiming to identify genetic determinants of bone structure. The women were healthy or having a primary osteopenic or osteoporotic status with or without low energy fractures. The total cohort of 91 unrelated women representing a wide range of BMDs, were consecutively registered and submitted to global gene Affymetrix microarray expression analysis or histomorphometry. Among almost 23,000 expressed transcripts, a set represented by ACSL3 (acyl-CoA synthetase long-chain family member 3), NIPSNAP3B (nipsnap homolog 3B), DLEU2 (Deleted in lymphocytic leukemia, 2), C1ORF61 (Chromosome 1 open reading frame 61), DKK1 (Dickkopf homolog 1), SOST (Sclerostin), ABCA8, (ATP-binding cassette, sub-family A, member 8), and uncharacterized (AFFX-M27830-M-at), was significantly correlated to total hip BMD (5% false discovery rate) explaining 62% of the BMD variation expressed as T-score, 53% when adjusting for the influence of age (Z-score) and 44% when further adjusting for body mass index (BMI). Only SOST was previously associated to BMD, and the majority of the genes have previously not been associated with a bone phenotype. In molecular network analyses, SOST shows a strong, positive correlation with DKK1, both being members of the Wnt signaling pathway. The results provide novel insight in the underlying biology of bone metabolism and osteoporosis which is the ultimate consequence of low BMD.

Introduksjon til analyse av cDNA mikromatrisedata

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GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies

The power of genome-wide SNP association studies is limited, among others, by the large number of false positive test results. To provide a remedy, we combined SNP association analysis with the pathway-driven gene set enrichment analysis (GSEA), recently developed to facilitate handling of genome-wide gene expression data. The resulting GSEA-SNP method rests on the assumption that SNPs underlying a disease phenotype are enriched in genes constituting a signaling pathway or those with a common regulation. Besides improving power for association mapping, GSEA-SNP may facilitate the identification of disease-associated SNPs and pathways, as well as the understanding of the underlying biological mechanisms. GSEA-SNP may also help to identify markers with weak effects, undetectable in association studies without pathway consideration. The program is freely available and can be downloaded from our website.

Validation of oligoarrays for quantitative exploration of the transcriptome

BACKGROUND

Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and serial analysis of gene expression (SAGE). By use of the TransCount method we calculated absolute transcript concentrations from spotted oligoarray intensities, enabling direct comparisons with tag counts obtained with MPSS and SAGE. The tag counts were converted to number of transcripts per cell by assuming that the sum of all transcripts in a single cell was 5.105. Our aim was to investigate whether the less resource demanding and more widespread oligoarray technique could provide data that were correlated to and had the same absolute scale as those obtained with MPSS and SAGE.

RESULTS

A number of 1,777 unique transcripts were detected in common for the three technologies and served as the basis for our analyses. The correlations involving the oligoarray data were not weaker than, but, similar to the correlation between the MPSS and SAGE data, both when the entire concentration range was considered and at high concentrations. The data sets were more strongly correlated at high transcript concentrations than at low concentrations. On an absolute scale, the number of transcripts per cell and gene was generally higher based on oligoarrays than on MPSS and SAGE, and ranged from 1.6 to 9,705 for the 1,777 overlapping genes. The MPSS data were on same scale as the SAGE data, ranging from 0.5 to 3,180 (MPSS) and 9 to1,268 (SAGE) transcripts per cell and gene. The sum of all transcripts per cell for these genes was 3.8.105 (oligoarrays), 1.1.105 (MPSS) and 7.6.104 (SAGE), whereas the corresponding sum for all detected transcripts was 1.1.106 (oligoarrays), 2.8.105 (MPSS) and 3.8.105 (SAGE).

CONCLUSION

The oligoarrays and TransCount provide quantitative transcript concentrations that are correlated to MPSS and SAGE data, but, the absolute scale of the measurements differs across the technologies. The discrepancy questions whether the sum of all transcripts within a single cell might be higher than the number of 5.105 suggested in the literature and used to convert tag counts to transcripts per cell. If so, this may explain the apparent higher transcript detection efficiency of the oligoarrays, and has to be clarified before absolute transcript concentrations can be interchanged across the technologies. The ability to obtain transcript concentrations from oligoarrays opens up the possibility of efficient generation of universal transcript databases with low resource demands.