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Publications (6 of 6) Show all publications
Jensen, P. E., Warnke, C., Ingenhoven, K., Piccoli, L., Gasis, M., Hermanrud, C., . . . Sorensen, P. S. (2019). Detection and kinetics of persistent neutralizing anti-interferon-beta antibodies in patients with multiple sclerosis: Results from the ABIRISK prospective cohort study. Journal of Neuroimmunology, 326, 19-27
Open this publication in new window or tab >>Detection and kinetics of persistent neutralizing anti-interferon-beta antibodies in patients with multiple sclerosis: Results from the ABIRISK prospective cohort study
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2019 (English)In: Journal of Neuroimmunology, ISSN 0165-5728, E-ISSN 1872-8421, Vol. 326, p. 19-27Article in journal (Refereed) Published
Abstract [en]

Two validated assays, a bridging ELISA and a luciferase-based bioassay, were compared for detection of anti-drug antibodies (ADA) against interferon-beta (IFN-β) in patients with multiple sclerosis. Serum samples were tested from patients enrolled in a prospective study of 18 months. In contrast to the ELISA, when IFN-β-specific rabbit polyclonal and human monoclonal antibodies were tested, the bioassay was the more sensitive to detect IFN-β ADA in patients' sera. For clinical samples, selection of method of ELISA should be evaluated prior to the use of a multi-tiered approach. A titer threshold value is reported that may be used as a predictor for persistently positive neutralizing ADA.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Anti-drug antibodies, Bridging ELISA, Interferon-beta, Luciferase-based bioassay, Multiple sclerosis, Neutralizing antibodies
National Category
Medical and Health Sciences Neurology Rheumatology and Autoimmunity
Identifiers
urn:nbn:se:his:diva-17654 (URN)10.1016/j.jneuroim.2018.11.002 (DOI)000455693200004 ()30447419 (PubMedID)2-s2.0-85056449193 (Scopus ID)
Note

On behalf of the ABIRISK Consortium

Available from: 2019-09-07 Created: 2019-09-07 Last updated: 2019-09-20Bibliographically approved
Bachelet, D., Albert, T., Mbogning, C., Hässler, S., Zhang, Y., Schultze-Strasser, S., . . . Broët, P. (2019). Risk stratification integrating genetic data for factor VIII inhibitor development in patients with severe hemophilia A. PLoS ONE, 14(6), Article ID e0218258.
Open this publication in new window or tab >>Risk stratification integrating genetic data for factor VIII inhibitor development in patients with severe hemophilia A
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2019 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 14, no 6, article id e0218258Article in journal (Refereed) Published
Abstract [en]

Replacement therapy in severe hemophilia A leads to factor VIII (FVIII) inhibitors in 30% of patients. Factor VIII gene (F8) mutation type, a family history of inhibitors, ethnicity and intensity of treatment are established risk factors, and were included in two published prediction tools based on regression models. Recently investigated immune regulatory genes could also play a part in immunogenicity. Our objective is to identify bio-clinical and genetic markers for FVIII inhibitor development, taking into account potential genetic high order interactions. The study population consisted of 593 and 79 patients with hemophilia A from centers in Bonn and Frankfurt respectively. Data was collected in the European ABIRISK tranSMART database. A subset of 125 severely affected patients from Bonn with reliable information on first treatment was selected as eligible for risk stratification using a hybrid tree-based regression model (GPLTR). In the eligible subset, 58 (46%) patients developed FVIII inhibitors. Among them, 49 (84%) were "high risk" F8 mutation type. 19 (33%) had a family history of inhibitors. The GPLTR model, taking into account F8 mutation risk, family history of inhibitors and product type, distinguishes two groups of patients: a high-risk group for immunogenicity, including patients with positive HLA-DRB1*15 and genotype G/A and A/A for IL-10 rs1800896, and a low-risk group of patients with negative HLA-DRB1*15 / HLA-DQB1*02 and T/T or G/T for CD86 rs2681401. We show associations between genetic factors and the occurrence of FVIII inhibitor development in severe hemophilia A patients taking into account for high-order interactions using a generalized partially linear tree-based approach.

Keywords
class-II, dendritic cells, HLA alleles, polymorphism, interleukin-10, prediction, protects, impact
National Category
Hematology Medical Genetics
Identifiers
urn:nbn:se:his:diva-17651 (URN)10.1371/journal.pone.0218258 (DOI)000471238300075 ()31194850 (PubMedID)2-s2.0-85067866441 (Scopus ID)
Note

ABIRISK consortium

Available from: 2019-09-05 Created: 2019-09-05 Last updated: 2019-09-11Bibliographically approved
Delsing, L., Dönnes, P., Sánchez, J., Clausen, M., Voulgaris, D., Falk, A., . . . Synnergren, J. (2018). Barrier properties and transcriptome expression in human iPSC-derived models of the blood-brain barrier. Stem Cells, 36(12), 1816-1827
Open this publication in new window or tab >>Barrier properties and transcriptome expression in human iPSC-derived models of the blood-brain barrier
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2018 (English)In: Stem Cells, ISSN 1066-5099, E-ISSN 1549-4918, Vol. 36, no 12, p. 1816-1827Article in journal (Refereed) Published
Abstract [en]

Cell-based models of the blood-brain barrier (BBB) are important for increasing the knowledge of BBB formation, degradation and brain exposure of drug substances. Human models are preferred over animal models because of inter-species differences in BBB structure and function. However, access to human primary BBB tissue is limited and has shown degeneration of BBB functions in vitro. Human induced pluripotent stem cells (iPSCs) can be used to generate relevant cell types to model the BBB with human tissue. We generated a human iPSC-derived model of the BBB that includes endothelial cells in co-culture with pericytes, astrocytes and neurons. Evaluation of barrier properties showed that the endothelial cells in our co-culture model have high transendothelial electrical resistance, functional efflux and ability to discriminate between CNS permeable and non-permeable substances. Whole genome expression profiling revealed transcriptional changes that occur in co-culture, including upregulation of tight junction proteins such as claudins and neurotransmitter transporters. Pathway analysis implicated changes in the WNT, TNF and PI3K-Akt pathways upon co-culture. Our data suggests that co-culture of iPSC-derived endothelial cells promotes barrier formation on a functional and transcriptional level. The information about gene expression changes in co-culture can be used to further improve iPSC-derived BBB models through selective pathway manipulation.

Keywords
blood–brain barrier, co-culture, hiPSC, in vitro models, transcriptome, endothelial cells
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
urn:nbn:se:his:diva-16283 (URN)10.1002/stem.2908 (DOI)000455838500004 ()30171748 (PubMedID)2-s2.0-85056115357 (Scopus ID)
Available from: 2018-10-08 Created: 2018-10-08 Last updated: 2019-09-04Bibliographically approved
Synnergren, J. & Dönnes, P. (2018). Current Perspectives on Multi-Omics Data Integration With Application on Toxicity Biomarkers Discovery. Open Access journal of Toxicology, 2(5), 1-2, Article ID OAJT.MS.ID.555597.
Open this publication in new window or tab >>Current Perspectives on Multi-Omics Data Integration With Application on Toxicity Biomarkers Discovery
2018 (English)In: Open Access journal of Toxicology, ISSN 2474-7599, Vol. 2, no 5, p. 1-2, article id OAJT.MS.ID.555597Article, review/survey (Refereed) Published
Place, publisher, year, edition, pages
Juniper publishers, 2018
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics; INF501 Integration of -omics Data
Identifiers
urn:nbn:se:his:diva-15851 (URN)10.19080/OAJT.2018.02.555597 (DOI)
Available from: 2018-06-28 Created: 2018-06-28 Last updated: 2019-09-04Bibliographically approved
Synnergren, J., Ghosheh, N. & Dönnes, P. (2018). Integration of Biomedical Big Data Requires Efficient Batch Effect Reduction. In: Hisham Al-Mubaid, Qin Ding, Oliver Eulenstein (Ed.), 10th International Conference on Bioinformatics and Computational Biology (BICOB): Las Vegas, Nevada, USA 19 – 21 March 2018. Paper presented at 10th International Conference on Bioinformatics and Computational Biology (BICOB) March 19 - 21, 2018, Las Vegas, NV, USA (pp. 76-82).
Open this publication in new window or tab >>Integration of Biomedical Big Data Requires Efficient Batch Effect Reduction
2018 (English)In: 10th International Conference on Bioinformatics and Computational Biology (BICOB): Las Vegas, Nevada, USA 19 – 21 March 2018 / [ed] Hisham Al-Mubaid, Qin Ding, Oliver Eulenstein, 2018, p. 76-82Conference paper, Published paper (Refereed)
Abstract [en]

 Efficiency in dealing with batch effects will be the next frontier in large-scale biological data analysis, particularly when involving the integration of different types of datasets. Large-scale omics techniques have quickly developed during the last decade and huge amounts of data are now generated, which has started to revolutionize the area of medical research. With the increase in the volume of data across the whole spectrum of biology, problems related to data analytics are continuously increasing as analysis and interpretation of these large volumes of molecular data has become a real challenge. Tremendous efforts have been made to obtain data from various molecular levels and the most recent trends show that more and more researchers now are trying to integrate data of various molecular types to inform hypotheses and biological questions. Tightly connected to this work are the batch-related biases that commonly are apparent between different datasets, but these problems are often not tackled. In present study the ComBat algorithm was applied and evaluated on two different data integration problems. Results show that the batch effects present in the integrated datasets efficiently could be removed by applying the ComBat algorithm.

National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics; INF501 Integration of -omics Data
Identifiers
urn:nbn:se:his:diva-15850 (URN)2-s2.0-85048592521 (Scopus ID)978-1-943436-11-8 (ISBN)978-1-5108-5866-4 (ISBN)
Conference
10th International Conference on Bioinformatics and Computational Biology (BICOB) March 19 - 21, 2018, Las Vegas, NV, USA
Available from: 2018-06-28 Created: 2018-06-28 Last updated: 2019-09-04Bibliographically approved
Feldhahn, M., Dönnes, P., Schubert, B., Schilbach, K., Rammensee, H.-G. & Kohlbacher, O. (2012). miHA-Match: Computational detection of tissue-specific minor histocompatibility antigens. JIM - Journal of Immunological Methods, 386(1-2), 94-100
Open this publication in new window or tab >>miHA-Match: Computational detection of tissue-specific minor histocompatibility antigens
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2012 (English)In: JIM - Journal of Immunological Methods, ISSN 0022-1759, E-ISSN 1872-7905, Vol. 386, no 1-2, p. 94-100Article in journal (Refereed) Published
Abstract [en]

Allogenic stem cell transplantation has shown considerable success in a number of hematological malignancies, in particular in leukemia. The beneficial effect is mediated by donor T cells recognizing patient-specific HLA-binding peptides. These peptides are called minor histocompatibility antigens (miHAs) and are typically caused by single nucleotide polymorphisms. Tissue-specific miHAs have successfully been used in anti-tumor therapy without causing unspecific graft-versus-host reactions. However, only a small number of miHAs have been identified to date, limiting the clinical use.

Here we present an immunoinformatics pipeline for the identification of miHAs. The pipeline can be applied to large-scale miHA screening, for example, in the development of diagnostic tests. Another interesting application is the design of personalized miHA-based cancer therapies based on patient-donor pair-specific miHAs detected by this pipeline. The suggested method covers various aspects of genetic variant detection, effects of alternative transcripts, and HLA-peptide binding. A comparison of our computational pipeline and experimentally derived datasets shows excellent agreement and coverage of the computationally predicted miHAs.

Place, publisher, year, edition, pages
Elsevier, 2012
Keywords
Minor histocompatibility antigens, Immunoinformatics, Transplantation
National Category
Bioinformatics and Systems Biology
Research subject
Natural sciences
Identifiers
urn:nbn:se:his:diva-7141 (URN)10.1016/j.jim.2012.09.004 (DOI)000311132800012 ()22985828 (PubMedID)2-s2.0-84867445887 (Scopus ID)
Available from: 2013-02-13 Created: 2013-02-07 Last updated: 2019-09-04Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-4613-2952

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