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  • 1.
    Abdellah, Tebani
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Gummesson, Anders
    Zhong, Wen
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Koistinen, Ina Schuppe
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lakshmikanth, Tadepally
    Olsson, Lisa M.
    Boulund, Fredrik
    Neiman, Maja
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Stenlund, Hans
    Hellström, Cecilia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Karlsson, Max
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Dodig-Crnkovic, Tea
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Kings Coll London, Fac Dent Oral & Craniofacial Sci, Ctr Host Microbiome Interact, London, England.
    Lee, Sunjae
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Zhang, Cheng
    Chen, Yang
    Olin, Axel
    Mikes, Jaromir
    Danielsson, Hanna
    von Feilitzen, Kalle
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Jansson, Per-Anders
    Angerås, Oskar
    Huss, Mikael
    Kjellqvist, Sanela
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Edfors, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Tremaroli, Valentina
    Forsström, Björn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Nilsson, Peter
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Moritz, Thomas
    Bäckhed, Fredrik
    Engstrand, Lars
    Brodin, Petter
    Bergström, Göran
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Danish Tech Univ, Ctr Biosustainabil, Copenhagen, Denmark.
    Fagerberg, Linn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Integration of molecular profiles in a longitudinal wellness profiling cohort2020In: Nature Communications, E-ISSN 2041-1723, Vol. 11, no 1, article id 4487Article in journal (Refereed)
  • 2.
    Agaton, Charlotta
    et al.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Unneberg, Per
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Sievertzon, Maria
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Holmberg, Anders
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Ehn, Maria
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Larsson, Magnus
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Uhlén, Mathias
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Gene expression analysis by signature pyrosequencing2002In: Gene, ISSN 0378-1119, E-ISSN 1879-0038, Vol. 289, no 1-2, p. 31-39Article in journal (Refereed)
    Abstract [en]

     We describe a novel method for transcript profiling based on high-throughput parallel sequencing of signature tags using a non-gel-based microtiter plate format. The method relies on the identification of cDNA clones by pyrosequencing of the region corresponding to the 3'-end of the mRNA preceding the poly(A) tail. Simultaneously, the method can be used for gene discovery, since tags corresponding to unknown genes can be further characterized by extended sequencing. The protocol was validated using a model system for human atherosclerosis. Two 3'-tagged cDNA libraries, representing macrophages and foam cells, which are key components in the development of atherosclerotic plaques, were constructed using a solid phase approach. The libraries were analyzed by pyrosequencing, giving on average 25 bases. As a control, conventional expressed sequence tag (EST) sequencing using slab gel electrophoresis was performed. Homology searches were used to identify the genes corresponding to each tag. Comparisons with EST sequencing showed identical, unique matches in the majority of cases when the pyrosignature was at least 18 bases. A visualization tool was developed to facilitate differential analysis using a virtual chip format. The analysis resulted in identification of genes with possible relevance for development of atherosclerosis. The use of the method for automated massive parallel signature sequencing is discussed.

  • 3. Agerberth, B
    et al.
    Gunne, H
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Kogner, P
    Boman, H G
    Gudmundsson, G H
    FALL-39, a putative human peptide antibiotic, is cysteine-free and expressed in bone marrow and testis.1995In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 92, no 1, p. 195-9Article in journal (Refereed)
    Abstract [en]

    PR-39, a proline/arginine-rich peptide antibiotic, has been purified from pig intestine and later shown to originate in the bone marrow. Intending to isolate a clone for a human counterpart to PR-39, we synthesized a PCR probe derived from the PR-39 gene. However, when this probe was used to screen a human bone marrow cDNA library, eight clones were obtained with information for another putative human peptide antibiotic, designated FALL-39 after the first four residues. FALL-39 is a 39-residue peptide lacking cysteine and tryptophan. All human peptide antibiotics previously isolated (or predicted) belong to the defensin family and contain three disulfide bridges. The clone for prepro-FALL-39 encodes a cathelin-like precursor protein with 170 amino acid residues. We have postulated a dibasic processing site for the mature FALL-39 and chemically synthesized the putative peptide. In basal medium E, synthetic FALL-39 was highly active against Escherichia coli and Bacillus megaterium. Residues 13-34 in FALL-39 can be predicted to form a perfect amphiphatic helix, and CD spectra showed that medium E induced 30% helix formation in FALL-39. RNA blot analyses disclosed that the gene for FALL-39 is expressed mainly in human bone marrow and testis.

  • 4.
    Ahmadian, Afshin
    et al.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Gharizadeh, B.
    O'Meara, D.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Genotyping by apyrase-mediated allele-specific extension2001In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 29, no 24Article in journal (Refereed)
    Abstract [en]

    This report describes a single-step extension approach suitable for high-throughput single-nucleotide polymorphism typing applications. The method relies on extension of paired allele-specific primers and we demonstrate that the reaction kinetics were slower for mismatched configurations compared with matched configurations. In our approach we employ apyrase, a nucleotide degrading enzyme, to allow accurate discrimination between matched and mismatched primer-template configurations. This apyrase-mediated allele-specific extension (AMASE) protocol allows incorporation of nucleotides when the reaction kinetics are fast (matched 3'-end primer) but degrades the nucleotides before extension when the reaction kinetics are slow (mismatched 3'-end primer). Thus, AMASE circumvents the major limitation of previous allele-specific extension assays in which slow reaction kinetics will still give rise to extension products from mismatched 3'-end primers, hindering proper discrimination. It thus represents a significant improvement of the allele-extension method. AMASE was evaluated by a bioluminometric assay in which successful incorporation of unmodified nucleotides is monitored in real-time using an enzymatic cascade.

  • 5.
    Ahmadian, Afshin
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Ren, Z P
    Williams, Cecilia
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Pontén, F
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Pontén, J
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology.
    Genetic instability in the 9q22.3 region is a late event in the development of squamous cell carcinoma.1998In: Oncogene, ISSN 0950-9232, E-ISSN 1476-5594, Vol. 17, no 14Article in journal (Refereed)
    Abstract [en]

    Squamous cell carcinoma (SCC) of the skin represents a group of neoplasms which is associated with exposure to UV light. Recently, we obtained data suggesting that invasive skin cancer and its precursors derive from one original neoplastic clone. Here, the analysis were extended by loss of heterozygosity (LOH) analysis in the chromosome 9q22.3 region. A total of 85 samples, taken from twenty-two sections of sun-exposed sites, corresponding to normal epidermis, morphological normal cells with positive immuno-staining for the p53 protein (p53 patches), dysplasias, cancer in situ (CIS) and squamous cell carcinomas (SCC) of the skin were analysed. Overall, about 70% of p53 patches had mutations in the p53 gene but not LOH in the p53 gene or 9q22.3 region. Approximately 70% of the dysplasias showed p53 mutations of which about 40% had LOH in the p53 region but not in the 9q22.3 region. In contrast, about 65% of SCC and CIS displayed LOH in the 9q22.3 region, as well as frequent (80%) mutations and/or LOH in the p53 gene. These findings strongly suggest that alterations in the p53 gene is an early event in the progression towards SCC, whereas malignant development involves LOH and alterations in at least one (or several) tumor suppressor genes located in chromosome 9q22.3.

  • 6.
    Andersen, Malin
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Engström, Pär
    Lithwick, Stuart
    Arenillas, David
    Eriksson, Per
    Lenhard, Boris
    Wasserman, Wyeth
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    In silico detection of sequence variations modifying transcriptional regulation2008In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 4, no 1, p. e5-Article in journal (Refereed)
    Abstract [en]

    Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN ( regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.

  • 7.
    Andersen, Malin
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Fisher, Rachel
    Holmberg, Kristina
    KTH, School of Biotechnology (BIO), Gene Technology.
    Samnegård, Ann
    Hamsten, Anders
    Eriksson, Per
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    In silico prediction of regulatory SNPs in the CD36 gene and evaluation of their effect in a clinical study for coronary artery diseaseManuscript (Other academic)
  • 8.
    Andersen, Malin
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lenhard, Boris
    Whatling, Carl
    Eriksson, Per
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    Alternative promoter usage of the membrane glycoprotein CD362006In: BMC Molecular Biology, E-ISSN 1471-2199, Vol. 7, p. 8-Article in journal (Refereed)
    Abstract [en]

    Background: CD36 is a membrane glycoprotein involved in a variety of cellular processes such as lipid transport, immune regulation, hemostasis, adhesion, angiogenesis and atherosclerosis. It is expressed in many tissues and cell types, with a tissue specific expression pattern that is a result of a complex regulation for which the molecular mechanisms are not yet fully understood. There are several alternative mRNA isoforms described for the gene. We have investigated the expression patterns of five alternative first exons of the CD36 gene in several human tissues and cell types, to better understand the molecular details behind its regulation.

    Results: We have identified one novel alternative first exon of the CD36 gene, and confirmed the expression of four previously known alternative first exons of the gene. The alternative transcripts are all expressed in more than one human tissue and their expression patterns vary highly in skeletal muscle, heart, liver, adipose tissue, placenta, spinal cord, cerebrum and monocytes. All alternative first exons are upregulated in THP-1 macrophages in response to oxidized low density lipoproteins. The alternative promoters lack TATA-boxes and CpG islands. The upstream region of exon 1b contains several features common for house keeping gene and monocyte specific gene promoters.

    Conclusion: Tissue-specific expression patterns of the alternative first exons of CD36 suggest that the alternative first exons of the gene are regulated individually and tissue specifically. At the same time, the fact that all first exons are upregulated in THP-1 macrophages in response to oxidized low density lipoproteins may suggest that the alternative first exons are coregulated in this cell type and environmental condition. The molecular mechanisms regulating CD36 thus appear to be unusually complex, which might reflect the multifunctional role of the gene in different tissues and cellular conditions.

  • 9. Andersson, T.
    et al.
    Borang, S.
    Larsson, M.
    Wirta, V.
    Wennborg, A.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Novel candidate genes for atherosclerosis are identified by representational difference analysis-based transcript profiling of cholesterol-loaded macrophages2001In: Pathobiology (Basel), ISSN 1015-2008, E-ISSN 1423-0291, Vol. 69, no 6, p. 304-314Article in journal (Refereed)
    Abstract [en]

    Objectives: To analyze the early gene expression in macrophages accompanying the phenotypic changes into foam cells upon exposure to oxidized low-density lipoprotein. To identify candidate genes and markers for further studies into the pathogenesis of atherosclerosis. Methods: Cells of the monocytic cell line THP-1 were activated by PMA and exposed to oxidized low-density lipoprotein. Gene expression profiles were investigated after 24 h, using a solid phase cDNA representational difference analysis (RDA) method and shotgun sequencing. Results were verified by microarray hybridization, and analyzed in the virtual chip display of a novel software tool for transcript profile exploration. Results: By comparing transcript profiles of exposed/unexposed cells, 1,984 transcript sequences, representing a total of 921 genes with altered expression levels in response to oxidized low-density lipoprotein exposure, were identified. Genes that are central to cell cycle control and proliferation, inflammatory response, and of pathways not previously implicated in atherosclerosis were identified. The data obtained is also made available on-line at http:// biobase.biotech.kth.se/thp1a for further exploration. Conclusion: The identification of new candidate genes for atherosclerotic disease through RDA-based transcript profiling facilitates further functional genomic studies in coronary artery disease. Candidate genetic polymorphism markers of potential clinical relevance can be identified by filtering information in genome variation databases through the virtual chip analysis of the transcript profiles and subsequently tested in association studies.

  • 10. Andersson, T.
    et al.
    Borang, S.
    Unneberg, P.
    Wirta, V.
    Thelin, A.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Shotgun sequencing and microarray analysis of RDA transcripts2003In: Gene, ISSN 0378-1119, E-ISSN 1879-0038, Vol. 310, p. 39-47Article in journal (Refereed)
    Abstract [en]

    Monitoring of differential gene expression is an important step towards understanding of gene function. We describe a comparison of the representational difference analysis (RDA) subtraction process with corresponding microarray analysis. The subtraction steps are followed in a quantitative manner using a shotgun cloning and sequencing procedure that includes over 1900 gene sequences. In parallel, the enriched transcripts are spotted onto microarrays facilitating large scale hybridization analysis of the representations and the difference products. We show by the shotgun procedure that there is a high diversity of gene fragments represented in the iterative RDA products (92-67% singletons) with a low number of shared sequences (<9%) between subsequent subtraction cycles. A non redundant set of 1141 RDA clones were immobilized on glass slides and the majority of these clones (97%) gave repeated good fluorescent signals in a subsequent hybridization of the labelled and amplified original cDNA. We observed only a low number of false positives (<2%) and a more than twofold differential expression for 32% (363) of the immobilized RDA clones. In conclusion, we show that by random sequencing of the difference products we obtained an accurate transcript profile of the individual steps and that large-scale confirmation of the obtained transcripts can be achieved by microarray analysis.

  • 11. Andersson, T.
    et al.
    Unneberg, P.
    Nilsson, Peter
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Quackenbush, J.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Monitoring of representational difference analysis subtraction procedures by global microarrays2002In: BioTechniques, ISSN 0736-6205, E-ISSN 1940-9818, Vol. 32, no 6, p. 1348-+Article in journal (Refereed)
    Abstract [en]

    Various approaches to the study of differential gene expression are applied to compare cell lines and tissue samples in a wide range of biological contexts. The compromise between focusing on only the important genes in certain cellular processes and achieving a complete picture is critical for the selection of strategy. We demonstrate how global microarray technology can be used for the exploration of the differentially expressed genes extracted through representational difference analysis (RDA). The subtraction of ubiquitous gene fragments from the two samples was demonstrated using cDNA microarrays including more than 32 000 spotted, PCR-amplified human clones. Hybridizations indicated the expression of 9100 of the microarray elements in a macrophage/foam cell atherosclerosis model system, of which many were removed during the RDA process. The stepwise subtraction procedure was demonstrated to yield an efficient enrichment of gene fragments overrepresented in either sample (18% in the representations, 86% after the first subtraction, and 88% after the second subtraction), many of which were impossible to detect in the starting material. Interestingly, the method allowed for the observation of the differential expression of several members of the low-abundant nuclear receptor gene family. We also observed a certain background level in the difference products of nondifferentially expressed gene fragments, warranting a verification strategy for selected candidate genes. The differential expression of several genes was verified by real-time PCR.

  • 12.
    Andrade, Jorge
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Andersen, Malin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Proteomics.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    Applications of grid computing in genetics and proteomics2007In: Applied Parallel Computing: State Of The Art In Scientific Computing / [ed] Kagstrom, B; Elmroth, E; Dongarra, J; Wasniewski, J, 2007, Vol. 4699, p. 791-798Conference paper (Refereed)
    Abstract [en]

    The potential for Grid technologies in applied bioinformatics is largely unexplored. We have developed a model for solving computationally demanding bioinformatics tasks in distributed Grid environments, designed to ease the usability for scientists unfamiliar with Grid computing. With a script-based implementation that uses a strategy of temporary installations of databases and existing executables on remote nodes at submission, we propose a generic solution that do not rely on predefined Grid runtime environments and that can easily be adapted to other bioinformatics tasks suitable for parallelization. This implementation has been successfully applied to whole proteome sequence similarity analyses and to genome-wide genotype simulations, where computation time was reduced from years to weeks. We conclude that computational Grid technology is a useful resource for solving high compute tasks in genetics and proteomics using existing algorithms.

  • 13.
    Andrade, Jorge
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Andersen, Malin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Sillén, Anna
    Graff, Caroline
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    The use of grid computing to drive data-intensive genetic research2007In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 15, no 6, p. 694-702Article in journal (Refereed)
    Abstract [en]

    In genetics, with increasing data sizes and more advanced algorithms for mining complex data, a point is reached where increased computational capacity or alternative solutions becomes unavoidable. Most contemporary methods for linkage analysis are based on the Lander-Green hidden Markov model (HMM), which scales exponentially with the number of pedigree members. In whole genome linkage analysis, genotype simulations become prohibitively time consuming to perform on single computers. We have developed 'Grid-Allegro', a Grid aware implementation of the Allegro software, by which several thousands of genotype simulations can be performed in parallel in short time. With temporary installations of the Allegro executable and datasets on remote nodes at submission, the need of predefined Grid run-time environments is circumvented. We evaluated the performance, efficiency and scalability of this implementation in a genome scan on Swedish multiplex Alzheimer's disease families. We demonstrate that 'Grid-Allegro' allows for the full exploitation of the features available in Allegro for genome-wide linkage. The implementation of existing bioinformatics applications on Grids (Distributed Computing) represent a cost-effective alternative for addressing highly resource-demanding and data-intensive bioinformatics task, compared to acquiring and setting up clusters of computational hardware in house (Parallel Computing), a resource not available to most geneticists today.

  • 14.
    Andrade, Jorge
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Berglund, Lisa
    KTH, School of Biotechnology (BIO), Gene Technology.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Gene Technology.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    Using Grid Technology for Computationally Intensive Applied Bioinformatics Analyses2006In: In Silico Biology, ISSN 1386-6338, Vol. 6, no 6, p. 495-504Article in journal (Refereed)
    Abstract [en]

    For several applications and algorithms used in applied bioinformatics, a bottle neck in terms of computational time may arise when scaled up to facilitate analyses of large datasets and databases. Re-codification, algorithm modification or sacrifices in sensitivity and accuracy may be necessary to accommodate for limited computational capacity of single work stations. Grid computing offers an alternative model for solving massive computational problems by parallel execution of existing algorithms and software implementations. We present the implementation of a Grid-aware model for solving computationally intensive bioinformatic analyses exemplified by a blastp sliding window algorithm for whole proteome sequence similarity analysis, and evaluate the performance in comparison with a local cluster and a single workstation. Our strategy involves temporary installations of the BLAST executable and databases on remote nodes at submission, accommodating for dynamic Grid environments as it avoids the need of predefined runtime environments (preinstalled software and databases at specific Grid-nodes). Importantly, the implementation is generic where the BLAST executable can be replaced by other software tools to facilitate analyses suitable for parallelisation. This model should be of general interest in applied bioinformatics. Scripts and procedures are freely available from the authors.

  • 15.
    Berglund, Lisa
    et al.
    KTH, School of Biotechnology (BIO).
    Andrade, Jorge
    KTH, School of Biotechnology (BIO).
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO).
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO).
    The epitope space of the human proteome2008In: Protein Science, ISSN 0961-8368, E-ISSN 1469-896X, Vol. 17, no 4, p. 606-613Article in journal (Refereed)
    Abstract [en]

    In the post-genome era, there is a great need for protein-specific affinity reagents to explore the human proteome. Antibodies are suitable as reagents, but generation of antibodies with low cross-reactivity to other human proteins requires careful selection of antigens. Here we show the results from a proteomewide effort to map linear epitopes based on uniqueness relative to the entire human proteome. The analysis was based on a sliding window sequence similarity search using short windows (8, 10, and 12 amino acid residues). A comparison of exact string matching (Hamming distance) and a heuristic method (BLAST) was performed, showing that the heuristic method combined with a grid strategy allows for whole proteome analysis with high accuracy and feasible run times. The analysis shows that it is possible to find unique antigens for a majority of the human proteins, with relatively strict rules involving low sequence identity of the possible linear epitopes. The implications for human antibody-based proteomics efforts are discussed.

  • 16.
    Bocher, Ozvan
    et al.
    Univ Brest, INSERM, EFS, UMR 1078,GGB, Brest, France.;Helmholtz Zentrum Munchen, Inst Translat Genom, Munich, Germany..
    Ludwig, Thomas E.
    Univ Brest, INSERM, EFS, UMR 1078,GGB, Brest, France.;CHU Brest, Brest, France..
    Oglobinsky, Marie-Sophie
    Univ Brest, INSERM, EFS, UMR 1078,GGB, Brest, France..
    Marenne, Gaeelle
    Univ Brest, INSERM, EFS, UMR 1078,GGB, Brest, France..
    Deleuze, Jean-Francois
    Univ Paris Saclay, Ctr Natl Rech Genom Humaine CNRGH, Inst Biol Francois Jacob, CEA, Evry, France..
    Suryakant, Suryakant
    Univ Bordeaux, INSERM, Bordeaux Populat Hlth Res Ctr, Team ELEANOR,UMR 1219, Bordeaux, France..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Arctic Univ Tromso, Dept Clin Med, Fac Hlth Sci, Tromso, Norway..
    Morange, Pierre-Emmanuel
    Aix Marseille Univ, INSERM, INRAE, C2VN, Marseille, France..
    Tregoueet, David-Alexandre
    Univ Bordeaux, INSERM, Bordeaux Populat Hlth Res Ctr, Team ELEANOR,UMR 1219, Bordeaux, France..
    Perdry, Herve
    Univ Paris Saclay, Univ Paris Sud, UFR Med, CESP Inserm,U1018, Villejuif, France..
    Genin, Emmanuelle
    Univ Brest, INSERM, EFS, UMR 1078,GGB, Brest, France.;CHU Brest, Brest, France..
    Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score2022In: PLOS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 18, no 9, p. e1009923-, article id e1009923Article in journal (Refereed)
    Abstract [en]

    Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.

  • 17. Borang, S.
    et al.
    Andersson, T.
    Thelin, A.
    Larsson, M.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Monitoring of the subtraction process in solid-phase representational difference analysis: characterization of a candidate drug2001In: Gene, ISSN 0378-1119, E-ISSN 1879-0038, Vol. 271, no 2, p. 183-192Article in journal (Refereed)
    Abstract [en]

    In this study, we have applied and evaluated a modified cDNA representational difference analysis (RDA) protocol based on magnetic bead technology to study the molecular effects of a candidate drug (N,N'-diacetyl-L-cystine, DiNAC) in a model for atherosclerosis. Alterations in a gene expression profile induced by DiNAC were investigated in a human monocytic cell line (THP-1) differentiated into macrophage-like cells by lipopolysaccharide and further exposed to DiNAC. Three rounds of subtraction have been performed and the difference products from the second and third rounds have been characterized in detail by analysis of over 1000 gene sequences. Two protocols for analysis of the subtraction products have been evaluated, a shotgun approach and size selection of both distinct fragments and band-patterned smear. We demonstrate that in order to obtain a representative view of the most abundant gene fragments, the shotgun procedure is preferred. The obtained sequences were analyzed against the UniGene and Expressed Gene Anatomy Database (EGAD) databases and the results were visualized and analyzed with the ExProView software enabling rapid pair-wise comparison and identification of individual genes or functional groups of genes with altered expression levels. The identified differentially expressed gene sequences were comprised of both genes with known involvement in atherosclerosis or cholesterol biosynthesis and genes previously not implicated in these processes. The applicability of a solid-phase shotgun RDA protocol, combined with virtual chip monitoring, results in new starting points for characterization of novel candidate drugs.

  • 18.
    Boräng, Stina
    et al.
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Andersson, Tove
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Thelin, A.
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Lundeberg, Joakim
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Vascular gene expression in atherosclerotic plaque-prone regions analyzed by representational difference analysis2004In: Pathobiology (Basel), ISSN 1015-2008, E-ISSN 1423-0291, Vol. 71, no 2, p. 107-114Article in journal (Refereed)
    Abstract [en]

    Objectives: Atherosclerotic plaques are known to develop and progress where the endothelium is subjected to turbulent blood flow. We have applied cDNA representational difference analysis (RDA) to study vascular gene expression in mouse aorta in a model for atherosclerosis. Methods: Gene expression profiles were investigated in plaque-prone and plaque-resistant localizations in the ascending aorta and arch in 8-week-oldApoE-/- and LDLR-/- mice. Total RNA was extracted and two rounds of subtraction were performed; the difference products were characterized in detail by shotgun cloning and analysis of more than 2,700 gene sequences. Results: The identified differentially expressed gene sequences include both genes with known involvement in vascular gene expression and genes previously not implicated in vascular processes. For example, CD36 and caveolin, previously reported for their participation in the progression of atherosclerosis, were found to have an increased expression in vessel localizations thought to be especially susceptible to plaque formation. Conclusions: This report provides new in vivo information of expressed genes that can be useful for further investigations of the molecular mechanisms in focal localization of atherosclerosis.

  • 19. Bruzelius, M.
    et al.
    Bottai, M.
    Sabater-Lleal, M.
    Strawbridge, R. J.
    Bergendal, A.
    Silveira, A.
    Sundstrom, A.
    Kieler, H.
    Hamsten, A.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital Solna, Sweden; Karolinska Institutet, Sweden .
    Predicting venous thrombosis in women using a combination of genetic markers and clinical risk factors2015In: Journal of Thrombosis and Haemostasis, ISSN 1538-7933, E-ISSN 1538-7836, Vol. 13, no 2, p. 219-227Article in journal (Refereed)
    Abstract [en]

    BackgroundFamily history of venous thromboembolism (VTE) has been suggested to be more useful in risk assessment than thrombophilia testing. ObjectivesWe investigated established genetic susceptibility variants for association with VTE and evaluated a genetic risk score in isolation and combined with known trigger factors, including family history of VTE. Patients/MethodA total of 18 single nucleotide polymorphisms (SNPs) selected from the literature were genotyped in 2835 women participating in a Swedish nationwide case-control study (the ThromboEmbolism Hormone Study [TEHS]). Association with VTE was assessed by odds ratios (ORs) with 95% confidence interval (CI) using logistic regression. Clinical and genetic predictors that contributed significantly to the fit of the logistic regression model were included in the prediction models. SNP-SNP interactions were investigated and incorporated into the models if found significant. Risk scores were evaluated by calculating the area under the receiver-operating characteristics curve (AUC). ResultsSeven SNPs (F5 rs6025, F2 rs1799963, ABO rs514659, FGG rs2066865, F11 rs2289252, PROC rs1799810 and KNG1 rs710446) with four SNP-SNP interactions contributed to the genetic risk score for VTE, with an AUC of 0.66 (95% CI, 0.64-0.68). After adding clinical risk factors, which included family history of VTE, the AUC reached 0.84 (95% CI, 0.82-0.85). The goodness of fit of the genetic and combined scores improved when significant SNP-SNP interaction terms were included. ConclusionPrediction of VTE in high-risk individuals was more accurate when a combination of clinical and genetic predictors with SNP-SNP interactions was included in a risk score.

  • 20. Bruzelius, M.
    et al.
    Iglesias, Maria Jesus
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hong, Mun-Gwan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sanchez-Rivera, Laura
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Gyorgy, B.
    Souto, J. C.
    Franberg, M.
    Fredolini, Claudia
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Strawbridge, R. J.
    Holmström, M.
    Hamsten, A.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Silveira, A.
    Soria, J. M.
    Smadja, D. M.
    Butler, L. M.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Morange, P. -E
    Trégouët, D. -A
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden; Karolinska Institutet, Sweden.
    PDGFB, a new candidate plasma biomarker for venous thromboembolism: Results from the VEREMA affinity proteomics study2016In: Blood, ISSN 0006-4971, E-ISSN 1528-0020, Vol. 128, no 23, p. e59-e66Article in journal (Refereed)
    Abstract [en]

    There is a clear clinical need for high-specificity plasma biomarkers for predicting risk of venous thromboembolism (VTE), but thus far, such markers have remained elusive. Utilizing affinity reagents from the Human Protein Atlas project and multiplexed immuoassays, we extensively analyzed plasma samples from 2 individual studies to identify candidate protein markers associated with VTE risk. We screened plasma samples from 88 VTE cases and 85 matched controls, collected as part of the Swedish ¡°Venous Thromboembolism Biomarker Study,¡± using suspension bead arrays composed of 755 antibodies targeting 408 candidate proteins. We identified significant associations between VTE occurrence and plasma levels of human immunodeficiency virus type I enhancer binding protein 1 (HIVEP1), von Willebrand factor (VWF), glutathione peroxidase 3 (GPX3), and platelet-derived growth factor β (PDGFB). For replication, we profiled plasma samples of 580 cases and 589 controls from the French FARIVE study. These results confirmed the association of VWF and PDGFB with VTE after correction for multiple testing, whereas only weak trends were observed for HIVEP1 and GPX3. Although plasma levels of VWF and PDGFB correlated modestly (p ~ 0.30) with each other, they were independently associated with VTE risk in a joint model in FARIVE (VWF P < .001; PDGFB P 5 .002). PDGF was verified as the target of the capture antibody by immunocapture mass spectrometry and sandwich enzyme-linked immunosorbent assay. In conclusion, we demonstrate that high-throughput affinity plasma proteomic profiling is a valuable research strategy to identify potential candidate biomarkers for thrombosis-related disorders, and our study suggests a novel association of PDGFB plasma levels with VTE.

  • 21. Bruzelius, M.
    et al.
    Iglesias, Maria Jesus
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hong, Mun-Gwan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tregouet, D. A.
    Souto, J. C.
    Holmström, M.
    Frånberg, M.
    Strawbridge, R. J.
    Sabater-Lleal, M.
    Sennblad, B.
    Silveira, A.
    Soria, J. M.
    Morange, P. E.
    Butler, L.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hamsten, A.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Verema - an affinity proteomics study to identify and translate plasma biomarkers for venous thromboembolism2015In: Journal of Thrombosis and Haemostasis, ISSN 1538-7933, E-ISSN 1538-7836, Vol. 13, p. 954-954Article in journal (Refereed)
  • 22. Bruzelius, M.
    et al.
    Ljungqvist, M.
    Bottai, M.
    Bergendal, A.
    Strawbridge, R. J.
    Silveira, A.
    Kieler, H.
    Hamsten, A.
    Laerfars, G.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    F11 is associated with recurrent event of VTE in women: a prospective cohort study2015In: Journal of Thrombosis and Haemostasis, ISSN 1538-7933, E-ISSN 1538-7836, Vol. 13, p. 198-198Article in journal (Refereed)
  • 23. Bruzelius, Maria
    et al.
    Ljungqvist, Maria
    Bottai, Matteo
    Bergendal, Annica
    Strawbridge, Rona J.
    Holmstrom, Margareta
    Silveira, Angela
    Kieler, Helle
    Hamsten, Anders
    Larfars, Gerd
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska Institutet & Karolinska universitetssjukhus, Sweden.
    F11 is associated with recurrent VTE in women A prospective cohort study2016In: Thrombosis and Haemostasis, ISSN 0340-6245, E-ISSN 2567-689X, Vol. 115, no 2, p. 406-414Article in journal (Refereed)
    Abstract [en]

    Genetic associations for the reoccurrence of venous thromboembolism (VTE) are not well described. Our aim was to investigate if common genetic variants, previously found to contribute to the prediction of first time thrombosis in women, were associated with risk of recurrence. The Thromboembolism Hormone Study (TEHS) is a Swedish nationwide case-control study (2002-2009). A cohort of 1,010 women with first time VTE was followed up until a recurrent event, death or November 2011. The genetic variants in F5 rs6025, F2 rs1799963, ABO rs514659, FGG rs2066865, F11 rs2289252, PROC rs1799810 and KNG1 rs710446 were assessed together with clinical variables. Recurrence rate was calculated as the number of events over the accumulated patient-time. Cumulative recurrence was calculated by Kaplan-Meier curve. Cox proportional-hazard model was used to estimate hazard ratios (HR) and 95 % confidence intervals (95 % CI) between groups. A total of 101 recurrent events occurred during a mean follow-up time of five years. The overall recurrence rate was 20 per 1,000 person-years (95 % CI; 16-24). The recurrence rate was highest in women with unprovoked first event and obesity. Carriers of the risk alleles of F5 rs6025 (HR=1.7 (95 % CI; 1.1-2.6)) and F11 rs2289252 (HR=1.8 (95 % CI; 1.1-3.0)) had significantly higher rates of recurrence compared to non-carriers. The cumulative recurrence was 2.5-fold larger in carriers of both F5 rs6025 and F11 rs2289252 than in non-carriers at five years follow-up. In conclusion, F5 rs6025 and F11 rs2289252 contributed to the risk of recurrent VTE and the combination is of potential clinical relevance for risk prediction.

  • 24. Bruzelius, Maria
    et al.
    Strawbridge, Rona J.
    Tregouet, David-Alexandre
    Wiggins, Kerri L.
    Gertow, Karl
    Sabater-Lleal, Maria
    Ohrvik, John
    Bergendal, Annica
    Silveira, Angela
    Sundström, Anders
    Kieler, Helle
    Syvanen, Ann-Christine
    Smith, Nicholas L.
    Morange, Pierre-Emmanuel
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Coagulation Unit, Hematology Centre; Atherosclerosis Research Unit, Centre for Molecular Medicine Karolinska University Hospital Solna, Sweden.
    Hamsten, Anders
    Influence of coronary artery disease-associated genetic variants on risk of venous thromboembolism2014In: Thrombosis Research, ISSN 0049-3848, E-ISSN 1879-2472, Vol. 134, no 2, p. 426-432Article in journal (Refereed)
    Abstract [en]

    Introduction: We investigated whether genetic variations robustly associated with coronary artery disease are also associated with risk of venous thromboembolism in a well-defined, female case-control study (n = 2753) from Sweden. Materials and Methods: 39 single nucleotide polymorphisms in 32 loci associated with coronary artery disease in genome-wide association studies were identified in a literature search and genotyped in the ThromboEmbolism Hormone Study (TEHS). Association with venous thromboembolism was assessed by logistic regression. Results: Only rs579459 in the ABO locus demonstrated a significant association with VTE. A tentative association between ANRIL and VTE in the discovery analysis failed to replicate in a meta-analysis of 4 independent cohorts (total n = 7181). Conclusions: It appears that only the ABO locus is a shared risk factor for coronary artery disease and VTE.

  • 25. Butler, L. M.
    et al.
    Hallström, Björn Mikael
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Renné, T.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Analysis of Body-wide Unfractionated Tissue Data to Identify a Core Human Endothelial Transcriptome2016In: Cell Systems, ISSN 2405-4712, Vol. 3, no 3, p. 287-301.e3Article in journal (Refereed)
    Abstract [en]

    Endothelial cells line blood vessels and regulate hemostasis, inflammation, and blood pressure. Proteins critical for these specialized functions tend to be predominantly expressed in endothelial cells across vascular beds. Here, we present a systems approach to identify a panel of human endothelial-enriched genes using global, body-wide transcriptomics data from 124 tissue samples from 32 organs. We identified known and unknown endothelial-enriched gene transcripts and used antibody-based profiling to confirm expression across vascular beds. The majority of identified transcripts could be detected in cultured endothelial cells from various vascular beds, and we observed maintenance of relative expression in early passage cells. In summary, we describe a widely applicable method to determine cell-type-specific transcriptome profiles in a whole-organism context, based on differential abundance across tissues. We identify potential vascular drug targets or endothelial biomarkers and highlight candidates for functional studies to increase understanding of the endothelium in health and disease.

  • 26.
    Chemaly, M.
    et al.
    Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden..
    Marlevi, D.
    Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden..
    Iglesias, Maria Jesus
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Lengquist, M.
    Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden..
    Kronqvist, M.
    Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden..
    Bos, D.
    Univ Med Ctr Rotterdam, Dept Radiol & Nucl Med, Erasmus MC, Rotterdam, Netherlands.;Univ Med Ctr Rotterdam, Dept Epidemiol, Erasmus MC, Rotterdam, Netherlands..
    Van Dam-Nolen, D. H. K.
    Univ Med Ctr Rotterdam, Dept Radiol & Nucl Med, Erasmus MC, Rotterdam, Netherlands..
    Van Der Kolk, A.
    Radboudumc, Dept Med Imaging, Nijmegen, Netherlands.;Univ Med Ctr Utrecht, Dept Radiol, Utrecht, Netherlands..
    Hendrikse, J.
    Univ Med Ctr Utrecht, Dept Radiol, Utrecht, Netherlands..
    Kassem, M.
    Maastricht Univ, CARIM Sch Cardiovasc Dis, Dept Radiol & Nucl Med, Med Ctr, Maastricht, Netherlands..
    Matic, L.
    Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Karolinska Univ Hosp, Dept Hematol, Stockholm, Sweden.;UiT Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    De Vries, M. R.
    Leiden Univ, Einthoven Lab, Med Ctr, Leiden, Netherlands.;Leiden Univ, Dept Surg, Med Ctr, Leiden, Netherlands..
    Kooi, M. E.
    Maastricht Univ, CARIM Sch Cardiovasc Dis, Dept Radiol & Nucl Med, Med Ctr, Maastricht, Netherlands..
    Hedin, U.
    Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden.;Karolinska Univ Hosp, Dept Vasc Surg, Solna, Sweden..
    Biliverdin Reductase B is a Plasma Biomarker for Intraplaque Hemorrhage and A Predictor of Ischemic Stroke in Symptomatic Carotid Stenosis2023In: Atherosclerosis, ISSN 0021-9150, E-ISSN 1879-1484, Vol. 379, p. S180-S180Article in journal (Other academic)
  • 27.
    Chemaly, Melody
    et al.
    Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden..
    Marlevi, David
    Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden.;MIT, Inst Med Engn & Sci, Cambridge, MA 02142 USA..
    Iglesias, Maria Jesus
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Lengquist, Mariette
    Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden..
    Kronqvist, Malin
    Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden..
    Bos, Daniel
    Erasmus MC, Univ Med Ctr Rotterdam, Dept Radiol & Nucl Med, NL-3015 GD Rotterdam, Netherlands.;Erasmus MC, Univ Med Ctr, Dept Epidemiol, NL-3000 CA Rotterdam, Netherlands..
    van Dam-Nolen, Dianne H. K.
    Erasmus MC, Univ Med Ctr Rotterdam, Dept Radiol & Nucl Med, NL-3015 GD Rotterdam, Netherlands..
    van der Kolk, Anja
    Radboud Univ Nijmegen, Dept Med Imaging, Med Ctr, NL-6500 HB Nijmegen, Netherlands.;Univ Med Ctr Utrecht, Dept Radiol, NL-3508 GA Utrecht, Netherlands..
    Hendrikse, Jeroen
    Univ Med Ctr Utrecht, Dept Radiol, NL-3508 GA Utrecht, Netherlands..
    Kassem, Mohamed
    Maastricht Univ, CARIM Sch Cardiovasc Dis, Dept Radiol & Nucl Med, Med Ctr, NL-6229 ER Maastricht, Netherlands..
    Matic, Ljubica
    Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Karolinska Univ Hosp, Dept Hematol, S-14152 Huddinge, Stockholm, Sweden.;UiT The Arctic Univ Norway, Dept Clin Med, N-9019 Tromso, Norway..
    de Vries, Margreet R.
    Leiden Univ, Dept Surg, Einthoven Lab, Med Ctr, NL-2333 ZA Leiden, Netherlands..
    Kooi, M. Eline
    Maastricht Univ, CARIM Sch Cardiovasc Dis, Dept Radiol & Nucl Med, Med Ctr, NL-6229 ER Maastricht, Netherlands..
    Hedin, Ulf
    Karolinska Inst, Dept Mol Med & Surg, S-17177 Stockholm, Sweden.;Karolinska Univ Hosp, Dept Vasc Surg, S-17176 Stockholm, Sweden..
    Biliverdin Reductase B Is a Plasma Biomarker for Intraplaque Hemorrhage and a Predictor of Ischemic Stroke in Patients with Symptomatic Carotid Atherosclerosis2023In: Biomolecules, E-ISSN 2218-273X, Vol. 13, no 6, article id 882Article in journal (Refereed)
    Abstract [en]

    Background: Intraplaque hemorrhage (IPH) is a hallmark of atherosclerotic plaque instability. Biliverdin reductase B (BLVRB) is enriched in plasma and plaques from patients with symptomatic carotid atherosclerosis and functionally associated with IPH. Objective: We explored the biomarker potential of plasma BLVRB through (1) its correlation with IPH in carotid plaques assessed by magnetic resonance imaging (MRI), and with recurrent ischemic stroke, and (2) its use for monitoring pharmacotherapy targeting IPH in a preclinical setting. Methods: Plasma BLVRB levels were measured in patients with symptomatic carotid atherosclerosis from the PARISK study (n = 177, 5 year follow-up) with and without IPH as indicated by MRI. Plasma BLVRB levels were also measured in a mouse vein graft model of IPH at baseline and following antiangiogenic therapy targeting vascular endothelial growth factor receptor 2 (VEGFR-2). Results: Plasma BLVRB levels were significantly higher in patients with IPH (737.32 & PLUSMN; 693.21 vs. 520.94 & PLUSMN; 499.43 mean fluorescent intensity (MFI), p = 0.033), but had no association with baseline clinical and biological parameters. Plasma BLVRB levels were also significantly higher in patients who developed recurrent ischemic stroke (1099.34 & PLUSMN; 928.49 vs. 582.07 & PLUSMN; 545.34 MFI, HR = 1.600, CI [1.092-2.344]; p = 0.016). Plasma BLVRB levels were significantly reduced following prevention of IPH by anti-VEGFR-2 therapy in mouse vein grafts (1189 & PLUSMN; 258.73 vs. 1752 & PLUSMN; 366.84 MFI; p = 0.004). Conclusions: Plasma BLVRB was associated with IPH and increased risk of recurrent ischemic stroke in patients with symptomatic low- to moderate-grade carotid stenosis, indicating the capacity to monitor the efficacy of IPH-preventive pharmacotherapy in an animal model. Together, these results suggest the utility of plasma BLVRB as a biomarker for atherosclerotic plaque instability.

  • 28. Cheung, Louisa
    et al.
    Andersen, Malin
    KTH, School of Biotechnology (BIO), Gene Technology.
    Gustavsson, Carolina
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Biochemistry.
    Fernández-Pérez, Leandro
    Norsteds, Gunnar
    Tollet-Egnell, Petra
    Hormonal and nutritional regulation of alternative CD36 transcripts in rat liver: a role for growth hormone in alternative exon usage2007In: BMC Molecular Biology, E-ISSN 1471-2199, Vol. 8, no 60, p. 12-Article in journal (Refereed)
    Abstract [en]

    Background: CD36 is a multiligand receptor involved in various metabolic pathways, including cellular uptake of long-chain fatty acids. Defect function or expression of CD36 can result in dyslipidemia or insulin resistance. We have previously shown that CD36 expression is female-predominant in rat liver. In the present study, hormonal and nutritional regulation of hepatic CD36 expression was examined in male and female rats. Since alternative transcription start sites have been described in murine and human Cd36, we investigated whether alternative CD36 transcripts are differentially regulated in rat liver during these conditions.

    Results: Sequence information of the rat Cd36 5'-UTR was extended, showing that the gene structure of Cd36 in rat is similar to that previously described in mouse with at least two alternative first exons. The rat Cd36 exon 1a promoter was sequenced and found to be highly similar to murine and human Cd36. We show that alternative first exon usage is involved in the female-predominant expression of CD36 in rat liver and during certain hormonal states that induce CD36 mRNA abundance. Estrogen treatment or continuous infusion of growth hormone (GH) in male rats induced CD36 expression preferentially through the exon 1a promoter. Old age was associated with increased CD36 expression in male rats, albeit without any preferential first exon usage. Intermittent GH treatment in old male rats reversed this effect. Mild starvation (12 hours without food) reduced CD36 expression in female liver, whereas its expression was increased in skeletal muscle.

    Conclusion: The results obtained in this study confirm and extend our previous observation that GH is an important regulator of hepatic CD36, and depending on the mode of treatment (continuous or intermittent) the gene might be either induced or repressed. We suggest that the effects of continuous GH secretion in females (which is stimulatory) and intermittent GH secretion in males (which is inhibitory) explains the sex-different expression of this gene. Furthermore, a female-specific repression of hepatic CD36 in response to food deprivation was found, which was in contrast to a stimulatory effect in skeletal muscle. This demonstrates a tissue-specific regulation of Cd36.

  • 29.
    Dodig-Crnkovic, Tea
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hong, Mun-Gwan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Thomas, Cecilia Engel
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Häussler, Ragna S.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bendes, Annika
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Dale, Matilda
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edfors, Fredrik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Forsström, Björn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Magnusson, Patrik K.E
    Schuppe-Koistinen, Ina
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fagerberg, Linn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Gummesson, Anders
    Bergström, Göran
    Uhlén, Mathias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling2020In: EBioMedicine, E-ISSN 2352-3964, Vol. 57, article id 102854Article in journal (Refereed)
    Abstract [en]

    Background: Precision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular phenotypes, the descriptions of human health on an individual level have been far less elaborate. Methods: To provide insights into the longitudinal protein signatures of well-being, we profiled blood plasma collected over one year from 101 clinically healthy individuals using multiplexed antibody assays. After applying an antibody validation scheme, we utilized > 700 protein profiles for in-depth analyses of the individuals’ short-term health trajectories. Findings: We found signatures of circulating proteomes to be highly individual-specific. Considering technical and longitudinal variability, we observed that 49% of the protein profiles were stable over one year. We also identified eight networks of proteins in which 11–242 proteins covaried over time. For each participant, there were unique protein profiles of which some could be explained by associations to genetic variants. Interpretation: This observational and non-interventional study identifyed noticeable diversity among clinically healthy subjects, and facets of individual-specific signatures emerged by monitoring the variability of the circulating proteomes over time. To enable more personal hence precise assessments of health states, longitudinal profiling of circulating proteomes can provide a valuable component for precision medicine approaches. Funding: This work was supported by the Erling Persson Foundation, the Swedish Heart and Lung Foundation, the Knut and Alice Wallenberg Foundation, Science for Life Laboratory, and the Swedish Research Council.

  • 30. dos Remedios, Cristobal G.
    et al.
    Estigoy, Colleen
    Cameron, Darryl
    Ho, Joshua W. K.
    Herbert, Benjamin
    Padula, Matthew
    Pickford, Russel
    Guilhaus, Michael
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics.
    Ponten, Fredrik
    Proteomics of the Human Cardiac Intercalated Disc: A More Complex Multi-Functional Structure than was Previously Thought2010In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 98, no 3, p. 755A-756AArticle in journal (Other academic)
  • 31.
    Dusart, Philip
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO).
    Fagerberg, Linn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO).
    Perisic, L.
    Civelek, M.
    Struck, Eike
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hedin, U.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO).
    Trégouët, D. -A
    Renné, T.
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO). Coagulation Unit, Centre for Hematology, Karolinska University Hospital, SE-171 76, Stockholm, Sweden.
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO). Clinical Chemistry and Blood Coagulation, Department of Molecular Medicine and Surgery, Karolinska Institute, SE-171 76, Stockholm, Sweden Institute for Clinical Chemistry and Laboratory Medicine, University Medical Centre Hamburg-Eppendorf, D-20246, Hamburg, Germany.
    A systems-approach reveals human nestin is an endothelial-enriched, angiogenesis-independent intermediate filament protein2018In: Scientific Reports, E-ISSN 2045-2322, Vol. 8, no 1, article id 14668Article in journal (Refereed)
    Abstract [en]

    The intermediate filament protein nestin is expressed during embryonic development, but considered largely restricted to areas of regeneration in the adult. Here, we perform a body-wide transcriptome and protein-profiling analysis to reveal that nestin is constitutively, and highly-selectively, expressed in adult human endothelial cells (EC), independent of proliferative status. Correspondingly, we demonstrate that it is not a marker for tumour EC in multiple malignancy types. Imaging of EC from different vascular beds reveals nestin subcellular distribution is shear-modulated. siRNA inhibition of nestin increases EC proliferation, and nestin expression is reduced in atherosclerotic plaque neovessels. eQTL analysis reveals an association between SNPs linked to cardiovascular disease and reduced aortic EC nestin mRNA expression. Our study challenges the dogma that nestin is a marker of proliferation, and provides insight into its regulation and function in EC. Furthermore, our systems-based approach can be applied to investigate body-wide expression profiles of any candidate protein. 

  • 32.
    Dusart, Philip
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Renne, Thomas
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, D-20246 Hamburg, Germany..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    A Systems-Based Map of Human Brain Cell-Type Enriched Genes and Malignancy-Associated Endothelial Changes2019In: Cell Reports, E-ISSN 2211-1247, Vol. 29, no 6, p. 1690-+Article in journal (Refereed)
    Abstract [en]

    Changes in the endothelium of the cerebral vasculature can contribute to inflammatory, thrombotic, and malignant disorders. The importance of defining cell-type-specific genes and their modification in disease is increasingly recognized. Here, we develop a bioinformatics-based approach to identify normal brain cell-enriched genes, using bulk RNA sequencing (RNA-seq) data from 238 normal human cortex samples from 2 independent cohorts. We compare endothelial cell-enriched gene profiles with astrocyte, oligodendrocyte, neuron, and microglial cell profiles. Endothelial changes in malignant disease are explored using RNA-seq data from 516 lower-grade gliomas and 401 glioblastomas. Lower-grade gliomas appear to be an "endothelial intermediate'' between normal brain and glioblastoma. We apply our method for the prediction of glioblastoma-specific endothelial biomarkers, providing potential diagnostic or therapeutic targets. In summary, we provide a roadmap of endothelial cell identity in normal and malignant brain, using a method developed to resolve bulk RNA-seq into constituent cell-type-enriched profiles.

  • 33.
    Edfors, Fredrik
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Karolinska Univ Hosp, Karolinska Univ Lab, Stockholm, Sweden..
    Iglesias, Maria Jesus
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Karolinska Inst, Clin Chem & Blood Coagulat Res, Dept Mol Med & Surg, Stockholm, Sweden.;Karolinska Univ Hosp, Karolinska Univ Lab, Clin Chem, Stockholm, Sweden.;Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Arctic Univ Norway, Dept Clin Med, Tromso, Norway.;Univ Hosp North Norway, Div Internal Med, Tromso, Norway.;Karolinska Univ Hosp, Dept Hematol, Coagulat Unit, Stockholm, Sweden.;Karolinska Inst, Dept Med Solna, Stockholm, Sweden..
    Proteomics in thrombosis research2022In: RESEARCH AND PRACTICE IN THROMBOSIS AND HAEMOSTASIS, ISSN 2475-0379, Vol. 6, no 3, article id e12706Article in journal (Refereed)
    Abstract [en]

    A State of the Art lecture titled "Proteomics in Thrombosis Research" was presented at the ISTH Congress in 2021. In clinical practice, there is a need for improved plasma biomarker-based tools for diagnosis and risk prediction of venous thromboembolism (VTE). Analysis of blood, to identify plasma proteins with potential utility for such tools, could enable an individualized approach to treatment and prevention. Technological advances to study the plasma proteome on a large scale allows broad screening for the identification of novel plasma biomarkers, both by targeted and nontargeted proteomics methods. However, assay limitations need to be considered when interpreting results, with orthogonal validation required before conclusions are drawn. Here, we review and provide perspectives on the application of affinity-and mass spectrometry-based methods for the identification and analysis of plasma protein biomarkers, with potential application in the field of VTE. We also provide a future perspective on discovery strategies and emerging technologies for targeted proteomics in thrombosis research. Finally, we summarize relevant new data on this topic, presented during the 2021 ISTH Congress.

  • 34.
    Edsgärd, Daniel
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Iglesias, Maria Jesus
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden; Karolinska Institutet, Sweden .
    Reilly, Sarah-Jayne
    Hamsten, Anders
    Tornvall, Per
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden; Karolinska Institutet, Sweden; .
    Emanuelsson, Olof
    KTH, School of Biotechnology (BIO). KTH, Centres, Science for Life Laboratory, SciLifeLab.
    GeneiASE: Detection of condition-dependent and static allele-specific expression from RNA-seq data without haplotype information2016In: Scientific Reports, E-ISSN 2045-2322, Vol. 6, article id 21134Article in journal (Refereed)
    Abstract [en]

    Allele-specific expression (ASE) is the imbalance in transcription between maternal and paternal alleles at a locus and can be probed in single individuals using massively parallel DNA sequencing technology. Assessing ASE within a single sample provides a static picture of the ASE, but the magnitude of ASE for a given transcript may vary between different biological conditions in an individual. Such condition-dependent ASE could indicate a genetic variation with a functional role in the phenotypic difference. We investigated ASE through RNA-sequencing of primary white blood cells from eight human individuals before and after the controlled induction of an inflammatory response, and detected condition-dependent and static ASE at 211 and 13021 variants, respectively. We developed a method, GeneiASE, to detect genes exhibiting static or condition-dependent ASE in single individuals. GeneiASE performed consistently over a range of read depths and ASE effect sizes, and did not require phasing of variants to estimate haplotypes. We observed condition-dependent ASE related to the inflammatory response in 19 genes, and static ASE in 1389 genes. Allele-specific expression was confirmed by validation of variants through real-time quantitative RT-PCR, with RNA-seq and RT-PCR ASE effect-size correlations r = 0.67 and r = 0.94 for static and condition-dependent ASE, respectively.

  • 35.
    Englert, Hanna
    et al.
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Goebel, Josephine
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Khong, Danika
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Omidi, Maryam
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Wolska, Nina
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Konrath, Sandra
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Frye, Maike
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Mailer, Reiner K.
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Beerens, Manu
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Gerwers, Julian C.
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany..
    Preston, Roger J. S.
    Royal Coll Surgeons Ireland, Sch Pharm & Biomol Sci, Irish Ctr Vasc Biol, Dublin, Ireland..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany.;Arctic Univ Norway, Dept Clin Med, Tromso, Norway.;Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden..
    Maas, Coen
    Univ Utrecht, Univ Med Ctr Utrecht, Dept Clin Chem & Haematol, Utrecht, Netherlands..
    Stavrou, Evi X.
    Louis Stokes Vet Adm Med Ctr, Med Serv, Sect Hematol Oncol, Cleveland, OH USA.;Case Western Reserve Univ, Sch Med, Dept Med, Hematol & Oncol Div, Cleveland, OH USA..
    Fuchs, Tobias A.
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany.;Neutrolis Inc, Cambridge, MA USA..
    Renne, Thomas
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany.;Royal Coll Surgeons Ireland, Sch Pharm & Biomol Sci, Irish Ctr Vasc Biol, Dublin, Ireland.;Johannes Gutenberg Univ Mainz, Med Ctr, Ctr Thrombosis & Hemostasis CTH, Mainz, Germany..
    Targeting NETs using dual-active DNase1 variants2023In: Frontiers in Immunology, E-ISSN 1664-3224, Vol. 14, article id 1181761Article in journal (Refereed)
    Abstract [en]

    BackgroundNeutrophil Extracellular Traps (NETs) are key mediators of immunothrombotic mechanisms and defective clearance of NETs from the circulation underlies an array of thrombotic, inflammatory, infectious, and autoimmune diseases. Efficient NET degradation depends on the combined activity of two distinct DNases, DNase1 and DNase1-like 3 (DNase1L3) that preferentially digest double-stranded DNA (dsDNA) and chromatin, respectively.

    MethodsHere, we engineered a dual-active DNase with combined DNase1 and DNase1L3 activities and characterized the enzyme for its NET degrading potential in vitro. Furthermore, we produced a mouse model with transgenic expression of the dual-active DNase and analyzed body fluids of these animals for DNase1 and DNase 1L3 activities. We systematically substituted 20 amino acid stretches in DNase1 that were not conserved among DNase1 and DNase1L3 with homologous DNase1L3 sequences.

    ResultsWe found that the ability of DNase1L3 to degrade chromatin is embedded into three discrete areas of the enzyme's core body, not the C-terminal domain as suggested by the state-of-the-art. Further, combined transfer of the aforementioned areas of DNase1L3 to DNase1 generated a dual-active DNase1 enzyme with additional chromatin degrading activity. The dual-active DNase1 mutant was superior to native DNase1 and DNase1L3 in degrading dsDNA and chromatin, respectively. Transgenic expression of the dual-active DNase1 mutant in hepatocytes of mice lacking endogenous DNases revealed that the engineered enzyme was stable in the circulation, released into serum and filtered to the bile but not into the urine.

    ConclusionTherefore, the dual-active DNase1 mutant is a promising tool for neutralization of DNA and NETs with potential therapeutic applications for interference with thromboinflammatory disease states.

  • 36. Estigoy, C. B.
    et al.
    Pontén, F.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Gene Technology.
    Herbert, B.
    Guilhaus, M.
    Charleston, M.
    Ho, J. W. K.
    Cameron, D.
    dos Remedios, C. G.
    Intercalated discs: Multiple proteins perform multiple functions in non-failing and failing human hearts2009In: Biophysical Reviews, ISSN 1867-2450, Vol. 1, no 1, p. 43-49Article, review/survey (Refereed)
    Abstract [en]

    The intercalated disc (ICD) occupies a central position in the transmission of force, electrical continuity and chemical communication between cardiomyocytes. Changes in its structure and composition are strongly implicated in heart failure. ICD functions include: maintenance of electrical continuity across the ICD; physical links between membranes and the cytoskeleton; intercellular adhesion; maintenance of ICD structure and function; and growth. About 200 known proteins are associated with ICDs, 40% of which change in disease. We systemically reviewed cardiac immunohistochemical data on the Human Protein Atlas (HPA) web site, ExPASy protein binding data and published papers on ICDs. We identified 43 proteins not previously reported, and confirmed 37 proteins that have previously been described. In addition, 102 proteins not present on the HPA web site but were described in ICDs in the literature. We group these into clusters that demonstrate functionally interactive groups of proteins demonstrating that ICDs play a key role in cardiomyocyte function.

  • 37.
    Fagerberg, Linn
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, C.
    Djureinovic, D.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Habuka, Masato
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tahmasebpoor, S.
    Danielsson, A.
    Edlund, K.
    Asplund, A.
    Sjöstedt, E.
    Lundberg, E.
    Szigyarto, Cristina Al-Khalili
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Skogs, Marie
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ottosson Takanen, J.
    Berling, H.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Mulder, J.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindskog, C.
    Danielsson, Frida
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Mardinoglu, A.
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Von Feilitzen, Kalle
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Forsberg, Mattias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Olsson, I.
    Navani, S.
    Huss, Mikael
    Nielsen, Jens
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics2014In: Molecular & Cellular Proteomics, ISSN 1535-9476, E-ISSN 1535-9484, Vol. 13, no 2, p. 397-406Article in journal (Refereed)
    Abstract [en]

    Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody- based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to 80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.

  • 38.
    Fagerberg, Linn
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Oksvold, Per
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Skogs, Marie
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Älgenäs, C.
    Lundberg, Emma
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Pontén, F.
    Sivertsson, Åsa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Klevebring, Daniel
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, C.
    Asplund, A.
    Sjöstedt, E.
    Al-Khalili Szigyarto, Cristina
    Edqvist, P. -H
    Olsson, I.
    Rydberg, U.
    Hudson, P.
    Ottosson Takanen, J.
    Berling, H.
    Björling, Lisa
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tegel, Hanna
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology.
    Rockberg, J.
    Nilsson, Peter
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Navani, S.
    Jirström, K.
    Mulder, J.
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hober, Sophia
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Forsberg, Mattias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Von Feilitzen, Kalle
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Contribution of antibody-based protein profiling to the human chromosome-centric proteome project (C-HPP)2013In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 12, no 6, p. 2439-2448Article in journal (Refereed)
    Abstract [en]

    A gene-centric Human Proteome Project has been proposed to characterize the human protein-coding genes in a chromosome-centered manner to understand human biology and disease. Here, we report on the protein evidence for all genes predicted from the genome sequence based on manual annotation from literature (UniProt), antibody-based profiling in cells, tissues and organs and analysis of the transcript profiles using next generation sequencing in human cell lines of different origins. We estimate that there is good evidence for protein existence for 69% (n = 13985) of the human protein-coding genes, while 23% have only evidence on the RNA level and 7% still lack experimental evidence. Analysis of the expression patterns shows few tissue-specific proteins and approximately half of the genes expressed in all the analyzed cells. The status for each gene with regards to protein evidence is visualized in a chromosome-centric manner as part of a new version of the Human Protein Atlas (www.proteinatlas.org).

  • 39. Gudmundsson, G H
    et al.
    Agerberth, B
    Odeberg, Jacob
    KTH, Superseded Departments (pre-2005), Biotechnology.
    Bergman, T
    Olsson, B
    Salcedo, R
    The human gene FALL39 and processing of the cathelin precursor to the antibacterial peptide LL-37 in granulocytes.1996In: European Journal of Biochemistry, ISSN 0014-2956, E-ISSN 1432-1033, Vol. 238, no 2, p. 325-32Article in journal (Refereed)
    Abstract [en]

    The peptide FA-LL-37, previously termed FALL-39, was originally predicted from on ORF of a cDNA clone isolated from a human bone marrow library. This peptide was synthesized and found to have antibacterial activity. We have now characterized and sequenced the complete gene for FA-LL-37, termed FALL39. It is a compact gene of 1963 bp with four exons. Exons 1-3 code for a signal sequence and the cathelin region. Exon 4 contains the information for the mature antibacterial peptide. Our results indicate that FALL39 is the only member of the cathelin gene family present in the human genome. Potential binding sites for acute-phase-response factors are identified in the promoter and in intron 2. A possible role for the cytokine interleukin-6 in the regulation of FALL 39 is discussed. Anti-(FA-LL-37) IgG located the peptide in granulocytes and we isolated the mature peptide from these cells after degranulation. Structural analysis determined the mature peptide to be LL-37. To obtain LL-37 for antibacterial assays, synthetic FA-LL-37 was degraded with dipeptidyl-peptidase I. This analysis showed that mature LL-37 is a potent antibacterial peptide.

  • 40.
    Habuka, Masato
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden .
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn M.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Kampf, Caroline
    Edlund, Karolina
    Sivertsson, Åsa
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Yamamoto, Tadashi
    Pontén, Fredrik
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska University Hospital, Sweden.
    The Kidney Transcriptome and Proteome Defined by Transcriptomics and Antibody-Based Profiling2014In: PLOS ONE, E-ISSN 1932-6203, Vol. 9, no 12, p. e116125-Article in journal (Refereed)
    Abstract [en]

    To understand renal functions and disease, it is important to define the molecular constituents of the various compartments of the kidney. Here, we used comparative transcriptomic analysis of all major organs and tissues in the human body, in combination with kidney tissue micro array based immunohistochemistry, to generate a comprehensive description of the kidney-specific transcriptome and proteome. A special emphasis was placed on the identification of genes and proteins that were elevated in specific kidney subcompartments. Our analysis identified close to 400 genes that had elevated expression in the kidney, as compared to the other analysed tissues, and these were further subdivided, depending on expression levels, into tissue enriched, group enriched or tissue enhanced. Immunohistochemistry allowed us to identify proteins with distinct localisation to the glomeruli (n=11), proximal tubules (n=120), distal tubules (n=9) or collecting ducts (n=8). Among the identified kidney elevated transcripts, we found several proteins not previously characterised or identified as elevated in kidney. This description of the kidney specific transcriptome and proteome provides a resource for basic and clinical research to facilitate studies to understand kidney biology and disease.

  • 41. Holmberg, K.
    et al.
    Persson, M. L.
    Uhlén, Mathias
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics.
    Pyrosequencing analysis of thrombosis-associated risk markers2005In: Clinical Chemistry, ISSN 0009-9147, E-ISSN 1530-8561, Vol. 51, no 8, p. 1549-1552Article in journal (Refereed)
  • 42.
    Hong, Mun-Gwan
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Dodig-Crnkovic, Tea
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Chen, Xu
    Drobin, Kimi
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lee, Woojoo
    Wang, Yunzhang
    Edfors, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Kotol, David
    Thomas, Cecilia Engel
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sjöberg, Ronald
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Hamsten, Anders
    Silveira, Angela
    Hall, Per
    Nilsson, Peter
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Pawitan, Yudi
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Pedersen, Nancy L
    Hägg, Sara
    Magnusson, Patrik KE
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Profiles of histidine-rich glycoprotein associate with age and risk of all-cause mortality2020In: Life Science Alliance, E-ISSN 2575-1077, Vol. 3, no 10, p. e202000817-Article in journal (Refereed)
    Abstract [en]

    Despite recognizing aging as a common risk factor of many human diseases, little is known about its molecular traits. To identify age-associated proteins circulating in human blood, we screened 156 individuals aged 50–92 using exploratory and multiplexed affinity proteomics assays. Profiling eight additional study sets (N = 3,987), performing antibody validation, and conducting a meta-analysis revealed a consistent age association (P = 6.61 × 10−6) for circulating histidine-rich glycoprotein (HRG). Sequence variants of HRG influenced how the protein was recognized in the immunoassays. Indeed, only the HRG profiles affected by rs9898 were associated with age and predicted the risk of mortality (HR = 1.25 per SD; 95% CI = 1.12–1.39; P = 6.45 × 10−5) during a follow-up period of 8.5 yr after blood sampling (IQR = 7.7–9.3 yr). Our affinity proteomics analysis found associations between the particular molecular traits of circulating HRG with age and all-cause mortality. The distinct profiles of this multipurpose protein could serve as an accessible and informative indicator of the physiological processes related to biological aging.

  • 43.
    Iglesias, Maria Jesus
    et al.
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Bruzelius, M.
    Hong, M-Gwan
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tregouet, D. A.
    Perisic, L.
    Frånberg, M.
    Parini, P.
    Ganna, A.
    Ingelsson, E.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hedin, U.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Silveira, A.
    Morange, P. E.
    Hamsten, A.
    Schwenk, JM, Jochen
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    An affinity proteomics study for plasma biomarker candidates of cardiovascular disease in venous thromboembolism2015In: Journal of Thrombosis and Haemostasis, ISSN 1538-7933, E-ISSN 1538-7836, Vol. 13, p. 956-956Article in journal (Refereed)
  • 44.
    Iglesias, Maria Jesus
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Univ Hosp North Norway, Div Internal Med, Tromso, Norway..
    Kruse, Larissa D.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sanchez-Rivera, Laura
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Enge, Linnea
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Dusart, Philip
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hong, Mun-Gwan
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Renne, Thomas
    Univ Med Ctr Hamburg Eppendorf, Inst Clin Chem & Lab Med, Hamburg, Germany.;Royal Coll Surgeons Ireland, Irish Ctr Vasc Biol, Sch Pharm & Biomol Sci, Dublin, Ireland.;Johannes Gutenberg Univ Mainz, Ctr Thrombosis & Hemostasis CTH, Med Ctr, Mainz, Germany..
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Bergstrom, Goran
    Univ Gothenburg, Inst Med, Sahlgrenska Acad, Gothenburg, Sweden..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Univ Hosp North Norway, Div Internal Med, Tromso, Norway.;Arctic Univ Norway, Dept Clin Med, Tromso, Norway.;Karolinska Univ Hosp, Dept Hematol, Coagulat Unit, Stockholm, Sweden..
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Karolinska Inst, Dept Mol Med & Surg, Clin Chem & Blood Coagulat Res, SE-17176 Stockholm, Sweden.;Arctic Univ Norway, Dept Clin Med, Tromso, Norway.;Karolinska Univ Hosp, Karolinska Univ Lab, Clin Chem, Stockholm, Sweden..
    Identification of Endothelial Proteins in Plasma Associated With Cardiovascular Risk Factors2021In: Arteriosclerosis, Thrombosis and Vascular Biology, ISSN 1079-5642, E-ISSN 1524-4636, Vol. 41, no 12, p. 2990-3004Article in journal (Refereed)
    Abstract [en]

    Objective: Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease risk factors, such as smoking and obesity. Risk factor exposure can modify EC signaling and behavior, leading to arterial and venous disease development. Here, we aimed to identify biomarker panels for the assessment of EC dysfunction, which could be useful for risk stratification or to monitor treatment response. Approach and Results: We used affinity proteomics to identify EC proteins circulating in plasma that were associated with cardiovascular disease risk factor exposure. Two hundred sixteen proteins, which we previously predicted to be EC-enriched across vascular beds, were measured in plasma samples (N=1005) from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study) pilot. Thirty-eight of these proteins were associated with body mass index, total cholesterol, low-density lipoprotein, smoking, hypertension, or diabetes. Sex-specific analysis revealed that associations predominantly observed in female- or male-only samples were most frequently with the risk factors body mass index, or total cholesterol and smoking, respectively. We show a relationship between individual cardiovascular disease risk, calculated with the Framingham risk score, and the corresponding biomarker profiles. Conclusions: EC proteins in plasma could reflect vascular health status.

  • 45. Iglesias, Maria Jesus
    et al.
    Reilly, Sarah-Jayne
    Emanuelsson, Olof
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sennblad, Bengt
    Najafabadi, Mohammad Pirmoradian
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Folkersen, Lasse
    Mälarstig, Anders
    Lagergren, Jens
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Eriksson, Per
    Hamsten, Anders
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Combined Chromatin and Expression Analysis Reveals Specific Regulatory Mechanisms within Cytokine Genes in the Macrophage Early Immune Response2012In: PLOS ONE, E-ISSN 1932-6203, Vol. 7, no 2, p. e32306-Article in journal (Refereed)
    Abstract [en]

    Macrophages play a critical role in innate immunity, and the expression of early response genes orchestrate much of the initial response of the immune system. Macrophages undergo extensive transcriptional reprogramming in response to inflammatory stimuli such as Lipopolysaccharide (LPS). To identify gene transcription regulation patterns involved in early innate immune responses, we used two genome-wide approaches - gene expression profiling and chromatin immunoprecipitation-sequencing (ChIP-seq) analysis. We examined the effect of 2 hrs LPS stimulation on early gene expression and its relation to chromatin remodeling (H3 acetylation; H3Ac) and promoter binding of Sp1 and RNA polymerase II phosphorylated at serine 5 (S5P RNAPII), which is a marker for transcriptional initiation. Our results indicate novel and alternative gene regulatory mechanisms for certain proinflammatory genes. We identified two groups of upregulated inflammatory genes with respect to chromatin modification and promoter features. One group, including highly up-regulated genes such as tumor necrosis factor (TNF), was characterized by H3Ac, high CpG content and lack of TATA boxes. The second group, containing inflammatory mediators (interleukins and CCL chemokines), was up-regulated upon LPS stimulation despite lacking H3Ac in their annotated promoters, which were low in CpG content but did contain TATA boxes. Genome-wide analysis showed that few H3Ac peaks were unique to either +/-LPS condition. However, within these, an unpacking/expansion of already existing H3Ac peaks was observed upon LPS stimulation. In contrast, a significant proportion of S5P RNAPII peaks (approx 40%) was unique to either condition. Furthermore, data indicated a large portion of previously unannotated TSSs, particularly in LPS-stimulated macrophages, where only 28% of unique S5P RNAPII peaks overlap annotated promoters. The regulation of the inflammatory response appears to occur in a very specific manner at the chromatin level for specific genes and this study highlights the level of fine-tuning that occurs in the immune response.

  • 46.
    Iglesias, Maria Jesus
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Division of Internal Medicine, University Hospital of North Norway (UNN), PB100, 9038, Tromsø, Norway; Translational Vascular Research, Department of Clinical Medicine, UiT The Arctic University of Norway, 9019, Tromsø, Norway.
    Sanchez-Rivera, Laura
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Ibrahim-Kosta, Manal
    Aix-Marseille Univ, INSERM, INRAE, C2VN, Laboratory of Haematology, CRB Assistance Publique—Hôpitaux de Marseille, HemoVasc (CRB AP-HM HemoVasc), Marseille, France, HemoVasc (CRB AP-HM HemoVasc).
    Naudin, Clément
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Translational Vascular Research, Department of Clinical Medicine, UiT The Arctic University of Norway, 9019, Tromsø, Norway.
    Munsch, Gaëlle
    University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, ELEANOR, Bordeaux, France, ELEANOR.
    Goumidi, Louisa
    Aix-Marseille Univ, INSERM, INRAE, C2VN, Laboratory of Haematology, CRB Assistance Publique—Hôpitaux de Marseille, HemoVasc (CRB AP-HM HemoVasc), Marseille, France, HemoVasc (CRB AP-HM HemoVasc).
    Farm, Maria
    Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden; Department of Clinical Chemistry, Karolinska University Hospital, Stockholm, Sweden.
    Smith, Philip M.
    Department of Medicine Solna, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden; Theme of Emergency and Reparative Medicine, Karolinska University Hospital, Stockholm, Sweden.
    Thibord, Florian
    Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA, USA; The Framingham Heart Study, Boston University, Framingham, MA, USA.
    Kral-Pointner, Julia Barbara
    Center for Physiology and Pharmacology, Institute of Vascular Biology and Thrombosis Research, Medical University of Vienna, Vienna, Austria.
    Hong, Mun-Gwan
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Suchon, Pierre
    Aix-Marseille Univ, INSERM, INRAE, C2VN, Laboratory of Haematology, CRB Assistance Publique—Hôpitaux de Marseille, HemoVasc (CRB AP-HM HemoVasc), Marseille, France, HemoVasc (CRB AP-HM HemoVasc).
    Germain, Marine
    University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, ELEANOR, Bordeaux, France, ELEANOR; Laboratory of Excellence GENMED (Medical Genomics), Bordeaux, France.
    Schottmaier, Waltraud
    Center for Physiology and Pharmacology, Institute of Vascular Biology and Thrombosis Research, Medical University of Vienna, Vienna, Austria.
    Dusart, Philip
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Translational Vascular Research, Department of Clinical Medicine, UiT The Arctic University of Norway, 9019, Tromsø, Norway.
    Boland, Anne
    Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), 91057, Evry, France; Laboratory of Excellence GENMED (Medical Genomics), Evry, France.
    Kotol, David
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edfors, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Koprulu, Mine
    MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, CB2 0QQ, UK.
    Pietzner, Maik
    MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, CB2 0QQ, UK; Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, UK.
    Langenberg, Claudia
    MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, CB2 0QQ, UK; Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, UK.
    Damrauer, Scott M.
    Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA; Department of Surgery and Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
    Johnson, Andrew D.
    Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, MA, USA; The Framingham Heart Study, Boston University, Framingham, MA, USA.
    Klarin, Derek M.
    VA Palo Alto Healthcare System, Palo Alto, CA, USA; Department of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, USA.
    Smith, Nicholas L.
    Department of Epidemiology, University of Washington, Seattle, WA, USA; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA.
    Smadja, David M.
    Hematology Department and Biosurgical Research Lab (Carpentier Foundation), European Georges Pompidou Hospital, Assistance Publique Hôpitaux de Paris, 20 rue Leblanc, Paris, 75015, France, 20 rue Leblanc; Innovative Therapies in Haemostasis, INSERM, Université de Paris, 4 avenue de l’Observatoire, Paris, 75270, France, 4 avenue de l’Observatoire.
    Holmström, Margareta
    Coagulation Unit, Department of Haematology, Karolinska University Hospital, SE-171 76, Stockholm, Sweden, SE-171 76.
    Magnusson, Maria
    Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden; Coagulation Unit, Department of Haematology, Karolinska University Hospital, SE-171 76, Stockholm, Sweden, SE-171 76; Department of Clinical Science, Intervention and Technology, Karolinska Institute, 171 77, Stockholm, Sweden, 171 77.
    Silveira, Angela
    Department of Medicine Solna, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Renné, Thomas
    Institute for Clinical Chemistry and Laboratory Medicine, University Medical Centre Hamburg-Eppendorf, D-20246, Hamburg, Germany; Center for Thrombosis and Hemostasis (CTH), Johannes Gutenberg University Medical Center, D-, 55131, Mainz, Germany; Irish Centre for Vascular Biology, School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin 2, D02 YN77, Ireland.
    Martinez-Perez, Angel
    Genomics of Complex Diseases Group, Research Institute Hospital de la Santa Creu i Sant Pau. IIB Sant Pau, Barcelona, Spain.
    Emmerich, Joseph
    Department of vascular medicine, Paris Saint-Joseph Hospital Group, INSERM 1153-CRESS, University of Paris Cité, 185 rue Raymond Losserand, Paris, 75674, France, 185 rue Raymond Losserand.
    Deleuze, Jean Francois
    Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), 91057, Evry, France; Laboratory of Excellence GENMED (Medical Genomics), Evry, France; Centre D’Etude du Polymorphisme Humain, Fondation Jean Dausset, Paris, France.
    Antovic, Jovan
    Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden; Department of Clinical Chemistry, Karolinska University Hospital, Stockholm, Sweden.
    Soria Fernandez, Jose Manuel
    Genomics of Complex Diseases Group, Research Institute Hospital de la Santa Creu i Sant Pau. IIB Sant Pau, Barcelona, Spain.
    Assinger, Alice
    Center for Physiology and Pharmacology, Institute of Vascular Biology and Thrombosis Research, Medical University of Vienna, Vienna, Austria.
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Souto Andres, Joan Carles
    Unitat d’Hemostàsia i Trombosi. Hospital de la Santa Creu i Sant Pau and IIB-Sant Pau, Barcelona, Spain.
    Morange, Pierre Emmanuel
    Aix-Marseille Univ, INSERM, INRAE, C2VN, Laboratory of Haematology, CRB Assistance Publique—Hôpitaux de Marseille, HemoVasc (CRB AP-HM HemoVasc), Marseille, France, HemoVasc (CRB AP-HM HemoVasc).
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Translational Vascular Research, Department of Clinical Medicine, UiT The Arctic University of Norway, 9019, Tromsø, Norway; Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden; Department of Clinical Chemistry, Karolinska University Hospital, Stockholm, Sweden.
    Trégouët, David Alexandre
    University of Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, ELEANOR, Bordeaux, France, ELEANOR; Laboratory of Excellence GENMED (Medical Genomics), Bordeaux, France.
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Division of Internal Medicine, University Hospital of North Norway (UNN), PB100, 9038, Tromsø, Norway; Translational Vascular Research, Department of Clinical Medicine, UiT The Arctic University of Norway, 9019, Tromsø, Norway; Department of Medicine Solna, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden; Coagulation Unit, Department of Haematology, Karolinska University Hospital, SE-171 76, Stockholm, Sweden, SE-171 76.
    Elevated plasma complement factor H related 5 protein is associated with venous thromboembolism2023In: Nature Communications, E-ISSN 2041-1723, Vol. 14, no 1, article id 3280Article in journal (Refereed)
    Abstract [en]

    Venous thromboembolism (VTE) is a common, multi-causal disease with potentially serious short- and long-term complications. In clinical practice, there is a need for improved plasma biomarker-based tools for VTE diagnosis and risk prediction. Here we show, using proteomics profiling to screen plasma from patients with suspected acute VTE, and several case-control studies for VTE, how Complement Factor H Related 5 protein (CFHR5), a regulator of the alternative pathway of complement activation, is a VTE-associated plasma biomarker. In plasma, higher CFHR5 levels are associated with increased thrombin generation potential and recombinant CFHR5 enhanced platelet activation in vitro. GWAS analysis of ~52,000 participants identifies six loci associated with CFHR5 plasma levels, but Mendelian randomization do not demonstrate causality between CFHR5 and VTE. Our results indicate an important role for the regulation of the alternative pathway of complement activation in VTE and that CFHR5 represents a potential diagnostic and/or risk predictive plasma biomarker.

  • 47.
    Iglesias, Maria Jesus
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Schwenk, Jochen M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics.
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Department of Clinical Medicine, Faculty of Health Science, The Arctic University of Tromsø,Tromsø, Norway; Department of Medicine, Karolinska Institutet, Stockholm, Sweden.
    Affinity Proteomics Assays for Cardiovascular and Atherosclerotic Disease Biomarkers2021In: Protein Microarrays for Disease Analysis: Methods and Protocols, Springer Nature , 2021, p. 163-179Chapter in book (Refereed)
    Abstract [en]

    Systematic exploration of the dynamic human plasma proteome enables the discovery of novel protein biomarkers. Using state-of-the-art technologies holds the promise to facilitate a better diagnosis and risk prediction of diseases. Cardiovascular disease (CVD) pathophysiology is characterized for unbalancing of processes such as vascular inflammation, endothelial dysfunction, or lipid profiles among others. Such processes have a direct impact on the dynamic and complex composition of blood and hence the plasma proteome. Therefore, the study of the plasma proteome comprises an excellent exploratory source of biomarker research particularly for CVD. We describe the protocol for performing the discovery of protein biomarker candidates using the suspension bead array technology. The process does not require depletion steps to remove abundant proteins and consumes only a few microliters of sample from the body fluid of interest. The approach is scalable to measure many analytes as well as large numbers of samples. Moreover, we describe a bead-assisted antibody-labeling process that helps to develop quantitative assays for validation purposes and facilitate the translation of the identified candidates into clinical studies. 

  • 48.
    Karlsson, Max
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zhang, Cheng
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Mear, Loren
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Zhong, Wen
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Digre, Andreas
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Katona, Borbala
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Sjöstedt, Evelina
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Butler, Lynn M.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden.;Karolinska Univ Hosp, Karolinska Univ Lab, Clin Chem, Stockholm, Sweden.;Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science. Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Dusart, Philip
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Arctic Univ Norway, Dept Clin Med, Tromso, Norway..
    Edfors, Fredrik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Oksvold, Per
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    von Feilitzen, Kalle
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Zwahlen, Martin
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Arif, Muhammad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Altay, Özlem
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Li, Xiangyu
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ozcan, Mehmet
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Mardinoglu, Adil
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Fagerberg, Linn
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.
    Mulder, Jan
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Luo, Yonglun
    BGI Qingdao, BGI Shenzhen, Lars Bolund Inst Regenerat Med & Qingdao Europe A, Qingdao, Peoples R China.;Aarhus Univ, Dept Biomed, Aarhus, Denmark..
    Ponten, Fredrik
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology. Karolinska Inst, Dept Neurosci, Stockholm, Sweden..
    Lindskog, Cecilia
    Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    A single-cell type transcriptomics map of human tissues2021In: Science Advances, E-ISSN 2375-2548, Vol. 7, no 31, article id eabh2169Article in journal (Refereed)
    Abstract [en]

    Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in the human body. Here, we combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution single-cell type map of human tissues. An open access atlas has been launched to allow researchers to explore the expression of human protein-coding genes in 192 individual cell type clusters. An expression specificity classification was performed to determine the number of genes elevated in each cell type, allowing comparisons with bulk transcriptomics data. The analysis highlights distinct expression clusters corresponding to cell types sharing similar functions, both within the same organs and between organs.

  • 49.
    Karlöf, Eva
    et al.
    Karolinska Univ Hosp, Dept Vasc Surg, Stockholm, Sweden.;Karolinska Inst, Dept Mol Med & Surg, L8 03, SE-17176 Stockholm, Sweden..
    Seime, Till
    Karolinska Inst, Dept Mol Med & Surg, L8 03, SE-17176 Stockholm, Sweden..
    Dias, Nuno
    Skane Univ Hosp, Dept Vasc Surg, Vasc Ctr, Malmo, Sweden..
    Lengquist, Mariette
    Karolinska Inst, Dept Mol Med & Surg, L8 03, SE-17176 Stockholm, Sweden..
    Witasp, Anna
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Div Renal Med, Stockholm, Sweden..
    Almqvist, Hakan
    Karolinska Inst, Dept Clin Neurosci, Stockholm, Sweden..
    Kronqvist, Malin
    Karolinska Inst, Dept Mol Med & Surg, L8 03, SE-17176 Stockholm, Sweden..
    Gadin, Jesper R.
    Karolinska Inst, Dept Med, Ctr Mol Med, Stockholm, Sweden..
    Odeberg, Jacob
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Maegdefessel, Lars
    Karolinska Inst, Dept Med, Ctr Mol Med, Stockholm, Sweden.;Tech Univ Munich, Klinikum Klinikum Rechts Isar Isar, Dept Vasc & Endovasc Surg, Munich, Germany..
    Stenvinkel, Peter
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Div Renal Med, Stockholm, Sweden..
    Matic, Ljubica Perisic
    Karolinska Inst, Dept Mol Med & Surg, L8 03, SE-17176 Stockholm, Sweden..
    Hedin, Ulf
    Karolinska Univ Hosp, Dept Vasc Surg, Stockholm, Sweden.;Karolinska Inst, Dept Mol Med & Surg, L8 03, SE-17176 Stockholm, Sweden..
    Correlation of computed tomography with carotid plaque transcriptomes associates calcification with lesion-stabilization2019In: Atherosclerosis, ISSN 0021-9150, E-ISSN 1879-1484, Vol. 288, p. 175-185Article in journal (Refereed)
    Abstract [en]

    Background and aims: Unstable carotid atherosclerosis causes stroke, but methods to identify patients and lesions at risk are lacking. We recently found enrichment of genes associated with calcification in carotid plaques from asymptomatic patients. Here, we hypothesized that calcification represents a stabilising feature of plaques and investigated how macro-calcification, as estimated by computed tomography (CT), correlates with gene expression profiles in lesions. Methods: Plaque calcification was measured in pre-operative CT angiographies. Plaques were sorted into high- and low-calcified, profiled with microarrays, followed by bioinformatic analyses. Immunohistochemistry and qPCR were performed to evaluate the findings in plaques and arteries with medial calcification from chronic kidney disease patients. Results: Smooth muscle cell (SMC) markers were upregulated in high-calcified plaques and calcified plaques from symptomatic patients, whereas macrophage markers were downregulated. The most enriched processes in high-calcified plaques were related to SMCs and extracellular matrix (ECM) organization, while inflammation, lipid transport and chemokine signaling were repressed. These findings were confirmed in arteries with high medial calcification. Proteoglycan 4 (PRG4) was identified as the most upregulated gene in association with plaque calcification and found in the ECM, SMA+ and CD68+/TRAP + cells. Conclusions: Macro-calcification in carotid lesions correlated with a transcriptional profile typical for stable plaques, with altered SMC phenotype and ECM composition and repressed inflammation. PRG4, previously not described in atherosclerosis, was enriched in the calcified ECM and localized to activated macrophages and smooth muscle-like cells. This study strengthens the notion that assessment of calcification may aid evaluation of plaque phenotype and stroke risk.

  • 50.
    Käller, Max
    et al.
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Hultin, Emilie
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Holmberg, Kristina
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Persson, Marie-Louise
    Clinical Chemistry Laboratory, Blekinge Hospital, Karlskrona.
    Odeberg, Jacob
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Ahmadian, Afshin
    KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Comparison of PrASE and Pyrosequencing for SNP Genotyping2006In: BMC Genomics, E-ISSN 1471-2164, Vol. 7, p. 291-Article in journal (Refereed)
    Abstract [en]

    Background: There is an imperative need for SNP genotyping technologies that are cost-effective per sample with retained high accuracy, throughput and flexibility. We have developed a microarray-based technique and compared it to Pyrosequencing. In the protease-mediated allele-specific extension (PrASE), the protease constrains the elongation reaction and thus prevents incorrect nucleotide incorporation to mismatched 3'-termini primers.

    Results: The assay is automated for 48 genotyping reactions in parallel followed by a tag-microarray detection system. A script automatically visualizes the results in cluster diagrams and assigns the genotypes. Ten polymorphic positions suggested as prothrombotic genetic variations were analyzed with Pyrosequencing and PrASE technologies in 442 samples and 99.8 % concordance was achieved. In addition to accuracy, the robustness and reproducibility of the technique has been investigated.

    Conclusion: The results of this study strongly indicate that the PrASE technology can offer significant improvements in terms of accuracy and robustness and thereof increased number of typeable SNPs.

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