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Träfflista för sökning "WFRF:(Pawitan Yudi) srt2:(2010-2014)"

Sökning: WFRF:(Pawitan Yudi) > (2010-2014)

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1.
  • Alexeyenko, Andrey, et al. (författare)
  • Network enrichment analysis : extension of gene-set enrichment analysis to gene networks
  • 2012
  • Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 13, s. 226-
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. Results: We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. Conclusions: The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps.
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2.
  • Bachmann, Julie, et al. (författare)
  • Affinity Proteomics Reveals Elevated Muscle Proteins in Plasma of Children with Cerebral Malaria
  • 2014
  • Ingår i: PLoS Pathogens. - : Public Library of Science (PLoS). - 1553-7366 .- 1553-7374. ; 10:4, s. e1004038-
  • Tidskriftsartikel (refereegranskat)abstract
    • Systemic inflammation and sequestration of parasitized erythrocytes are central processes in the pathophysiology of severe Plasmodium falciparum childhood malaria. However, it is still not understood why some children are more at risks to develop malaria complications than others. To identify human proteins in plasma related to childhood malaria syndromes, multiplex antibody suspension bead arrays were employed. Out of the 1,015 proteins analyzed in plasma from more than 700 children, 41 differed between malaria infected children and community controls, whereas 13 discriminated uncomplicated malaria from severe malaria syndromes. Markers of oxidative stress were found related to severe malaria anemia while markers of endothelial activation, platelet adhesion and muscular damage were identified in relation to children with cerebral malaria. These findings suggest the presence of generalized vascular inflammation, vascular wall modulations, activation of endothelium and unbalanced glucose metabolism in severe malaria. The increased levels of specific muscle proteins in plasma implicate potential muscle damage and microvasculature lesions during the course of cerebral malaria.
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3.
  • Berndt, Sonja I., et al. (författare)
  • Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
  • 2013
  • Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
  • Tidskriftsartikel (refereegranskat)abstract
    • Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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4.
  • Fahlén, Jessica, 1973- (författare)
  • Essays on spatial point processes and bioinformatics
  • 2010
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • This thesis consists of two separate parts. The first part consists of one paper and considers problems concerning spatial point processes and the second part includes three papers in the field of bioinformatics. The first part of the thesis is based on a forestry problem of estimating the number of trees in a region by using the information in an aerial photo, showing the area covered by the trees. The positions of the trees are assumed to follow either a binomial point process or a hard-core Strauss process. Furthermore, discs of equal size are used to represent the tree-crowns. We provide formulas for the expectation and the variance of the relative vacancy for both processes. The formulas are approximate for the hard-core Strauss process. Simulations indicate that the approximations are accurate.  The second part of this thesis focuses on pre-processing of microarray data. The microarray technology can be used to measure the expression of thousands of genes simultaneously in a single experiment. The technique is used to identify genes that are differentially expressed between two populations, e.g. diseased versus healthy individuals. This information can be used in several different ways, for example as diagnostic tools and in drug discovery. The microarray technique involves a number of complex experimental steps, where each step introduces variability in the data. Pre-processing aims to reduce this variation and is a crucial part of the data analysis. Paper II gives a review over several pre-processing methods. Spike-in data are used to describe how the different methods affect the sensitivity and bias of the experi­ment. An important step in pre-processing is dye-normalization. This normalization aims to re­move the systematic differences due to the use of different dyes for coloring the samples. In Paper III a novel dye-normalization, the MC-normalization, is proposed. The idea behind this normaliza­tion is to let the channels’ individual intensities determine the cor­rection, rather than the aver­age intensity which is the case for the commonly used MA-normali­zation. Spike-in data showed that  the MC-normalization reduced the bias for the differentially expressed genes compared to the MA-normalization. The standard method for preserving patient samples for diagnostic purposes is fixation in formalin followed by embedding in paraffin (FFPE). In Paper IV we used tongue-cancer micro­RNA-microarray data to study the effect of FFPE-storage. We suggest that the microRNAs are not equally affected by the storage time and propose a novel procedure to remove this bias. The procedure improves the ability of the analysis to detect differentially expressed microRNAs.
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5.
  • Hong, Mun-Gwan, et al. (författare)
  • A genome-wide assessment of variability in human serum metabolism
  • 2013
  • Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 34:3, s. 515-524
  • Tidskriftsartikel (refereegranskat)abstract
    • The study of the genetic regulation of metabolism in human serum samples can contribute to a better understanding of the intermediate biological steps that lead from polymorphism to disease. Here, we conducted a genome-wide association study (GWAS) to discover metabolic quantitative trait loci (mQTLs) utilizing samples from a study of prostate cancer in Swedish men, consisting of 402 individuals (214 cases and 188 controls) in a discovery set and 489 case-only samples in a replication set. A global nontargeted metabolite profiling approach was utilized resulting in the detection of 6,138 molecular features followed by targeted identification of associated metabolites. Seven replicating loci were identified (PYROXD2, FADS1, PON1, CYP4F2, UGT1A8, ACADL, and LIPC) with associated sequence variants contributing significantly to trait variance for one or more metabolites (P = 10(-13) -10(-91)). Regional mQTL enrichment analyses implicated two loci that included FADS1 and a novel locus near PDGFC. Biological pathway analysis implicated ACADM, ACADS, ACAD8, ACAD10, ACAD11, and ACOXL, reflecting significant enrichment of genes with acyl-CoA dehydrogenase activity. mQTL SNPs and mQTL-harboring genes were over-represented across GWASs conducted to date, suggesting that these data may have utility in tracing the molecular basis of some complex disease associations.
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6.
  • Lazar, Vladimir, et al. (författare)
  • Integrated molecular portrait of non-small cell lung cancers
  • 2013
  • Ingår i: BMC Medical Genomics. - : Springer Science and Business Media LLC. - 1755-8794. ; 6:1, s. 53-
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods: Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results: At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of similar to 800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions: Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.
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7.
  • Peng, Zhuochun, et al. (författare)
  • Operator Dependent Choice of Prostate Cancer Biopsy Has Limited Impact on a Gene Signature Analysis for the Highly Expressed Genes IGFBP3 and F3 in Prostate Cancer Epithelial Cells
  • 2014
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:10, s. e109610-
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Predicting the prognosis of prostate cancer disease through gene expression analysis is receiving increasing interest. In many cases, such analyses are based on formalin-fixed, paraffin embedded (FFPE) core needle biopsy material on which Gleason grading for diagnosis has been conducted. Since each patient typically has multiple biopsy samples, and since Gleason grading is an operator dependent procedure known to be difficult, the impact of the operator's choice of biopsy was evaluated. Methods: Multiple biopsy samples from 43 patients were evaluated using a previously reported gene signature of IGFBP3, F3 and VGLL3 with potential prognostic value in estimating overall survival at diagnosis of prostate cancer. A four multiplex one-step qRT-PCR test kit, designed and optimized for measuring the signature in FFPE core needle biopsy samples was used. Concordance of gene expression levels between primary and secondary Gleason tumor patterns, as well as benign tissue specimens, was analyzed. Results: The gene expression levels of IGFBP3 and F3 in prostate cancer epithelial cell-containing tissue representing the primary and secondary Gleason patterns were high and consistent, while the low expressed VGLL3 showed more variation in its expression levels. Conclusion: The assessment of IGFBP3 and F3 gene expression levels in prostate cancer tissue is independent of Gleason patterns, meaning that the impact of operator's choice of biopsy is low.
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8.
  • Pernemalm, Maria, et al. (författare)
  • Quantitative Proteomics Profiling of Primary Lung Adenocarcinoma Tumors Reveals Functional Perturbations in Tumor Metabolism
  • 2013
  • Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 12:9, s. 3934-3943
  • Tidskriftsartikel (refereegranskat)abstract
    • In this study, we have analyzed human primary lung adenocarcinoma tumors using global mass spectrometry to elucidate the biological mechanisms behind relapse post surgery. In total, we identified over 3000 proteins with high confidence. Supervised multivariate analysis was used to select 132 proteins separating the prognostic groups. Based on in-depth bioinformatics analysis, we hypothesized that the tumors with poor prognosis had a higher glycolytic activity and HIF activation. By measuring the bioenergetic cellular index of the tumors, we could detect a higher dependency of glycolysis among the tumors with poor prognosis. Further, we could also detect an up-regulation of HIF1 alpha mRNA expression in tumors with early relapse. Finally, we selected three proteins that were upregulated in the poor prognosis group (cathepsin D, ENO1, and VDAC1) to confirm that the proteins indeed originated from the tumor and not from a stromal or inflammatory component. Overall, these findings show how in-depth analysis of clinical material can lead to an increased understanding of the molecular mechanisms behind tumor progression.
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9.
  • Sboner, Andrea, et al. (författare)
  • Molecular sampling of prostate cancer: a dilemma for predicting disease progression
  • 2010
  • Ingår i: BMC Medical Genomics. - London, United Kingdom : BioMed Central. - 1755-8794. ; 3:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. Methods: We analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Results: Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Conclusions: The determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging.
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10.
  • Sjölander, Arvid, et al. (författare)
  • Between-within models for survival analysis.
  • 2013
  • Ingår i: Statistics in Medicine. - Hoboken, USA : Wiley-Blackwell. - 0277-6715 .- 1097-0258. ; 32:18, s. 3067-3076
  • Tidskriftsartikel (refereegranskat)abstract
    • A popular way to control for confounding in observational studies is to identify clusters of individuals (e.g., twin pairs), such that a large set of potential confounders are constant (shared) within each cluster. By studying the exposure-outcome association within clusters, we are in effect controlling for the whole set of shared confounders. An increasingly popular analysis tool is the between-within (BW) model, which decomposes the exposure-outcome association into a 'within-cluster effect' and a 'between-cluster effect'. BW models are relatively common for nonsurvival outcomes and have been studied in the theoretical literature. Although it is straightforward to use BW models for survival outcomes, this has rarely been carried out in practice, and such models have not been studied in the theoretical literature. In this paper, we propose a gamma BW model for survival outcomes. We compare the properties of this model with the more standard stratified Cox regression model and use the proposed model to analyze data from a twin study of obesity and mortality. We find the following: (i) the gamma BW model often produces a more powerful test of the 'within-cluster effect' than stratified Cox regression; and (ii) the gamma BW model is robust against model misspecification, although there are situations where it could give biased estimates.
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