Blar i ODA Open Digital Archive på forfatter "Bos, Steffan Daniel"

Viser treff 1-7 av 7

    • Exploring the role of the multiple sclerosis susceptibility gene CLEC16A in T cells 

      Eriksson, Anna Maria; Leikfoss, Ingvild Sørum; Abrahamsen, Greger; Sundvold, Vibeke; Isom, Martine Mesel; Keshari, Pankaj; Rognes, Torbjørn; Landsverk, Ole J. B.; Bos, Steffan Daniel; Harbo, Hanne Flinstad; Spurkland, Anne; Berge, Tone (Scandinavian Journal of Immunology;, Peer reviewed; Journal article, 2021-05-02)
      C-type lectin-like domain family 16 member A (CLEC16A) is associated with autoimmune disorders, including multiple sclerosis (MS), but its functional relevance is not completely understood. CLEC16A is expressed in several ...

    • Increased DNA methylation of SLFN12 in CD4+ and CD8+ T cells from multiple sclerosis patients 

      Rhead, Brooke; Brorson, Ina Skaara; Berge, Tone; Adams, Cameron; Quach, Hong; Moen, Stine Marit; Berg-Hansen, Pål; Celius, Elisabeth Gulowsen; Sangurdekar, Dipen; Bronson, Paola G.; Lea, Rodney A.; Burnard, Sean; Maltby, Vicky E.; Scott, Rodney J; Lechner-Scott, Jeannette; Harbo, Hanne Flinstad; Bos, Steffan Daniel; Barcellos, Lisa F (PLoS ONE;13 (10): e0206511, Journal article; Journal article; Peer reviewed, 2018-10-31)
      DNA methylation is an epigenetic mark that is influenced by environmental factors and is associated with changes to gene expression and phenotypes. It may link environmental exposures to disease etiology or indicate important ...

    • No differential gene expression for CD4+ T cells of MS patients and healthy controls. 

      Brorson, Ina Skaara; Eriksson, Anna; Leikfoss, Ingvild Sørum; Celius, Elisabeth Gulowsen; Berg-Hansen, Pål; Barcellos, Lisa F.; Berge, Tone; Harbo, Hanne Flinstad; Bos, Steffan Daniel (Multiple Sclerosis Journal - Experimental, Translational and Clinical;Volume 5(2), Journal article; Peer reviewed, 2019-05-20)
      Background: Multiple sclerosis-associated genetic variants indicate that the adaptive immune system plays an important role in the risk of developing multiple sclerosis. It is currently not well understood how these multiple ...

    • Predicting disease severity in multiple sclerosis using multimodal data and machine learning 

      Andorra, Magi; Freire, Ana; Zubizarreta, Irati; de Rosbo, Nicole Kerlero; Bos, Steffan Daniel; Rinas, Melanie; Høgestøl, Einar August; de Rodez Benavent, Sigrid Aune; Berge, Tone; Brune, Synne; Ivaldi, Federico; Cellerino, Maria; Pardini, Matteo; Vila, Gemma; Pulido-Valdeolivas, Irene; Martinez-Lapiscina, Elena H.; Llufriu, Sara; Saiz, Albert; Blanco, Yolanda; Martinez-Heras, Eloy; Solana, Elisabeth; Bäcker-Koduah, Priscilla; Behrens, Janina; Kuchling, Joseph; Asseyer, Susanna; Scheel, Michael; Chien, Claudia; Zimmermann, Hanna; Motamedi, Seyedamirhosein; Kauer-Bonin, Josef; Brandt, Alex; Saez-Rodriguez, Julio; Alexopoulos, Leonidas G.; Paul, Friedemann; Harbo, Hanne-Cathrin Flinstad; Shams, Hengameh; Oksenberg, Jorge; Uccelli, Antonio; Baeza-Yates, Ricardo; Villoslada, Pablo (Peer reviewed; Journal article, 2023)
      Background Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. Methods We have analysed a prospective ...

    • Quantitative proteomic analyses of CD4+ and CD8+ T cells reveal differentially expressed proteins in multiple sclerosis patients and healthy controls 

      Berge, Tone; Eriksson, Anna; Brorson, Ina Skaara; Høgestøl, Einar August; Berg-Hansen, Pål; Døskeland, Anne Marie Simonne; Mjaavatten, Olav; Bos, Steffan Daniel; Harbo, Hanne Flinstad; Berven, Frode (Clinical Proteomics;16, Article number: 19 (2019), Peer reviewed; Journal article, 2019-04-27)
      Background: Multiple sclerosis (MS) is an autoimmune, neuroinflammatory disease, with an unclear etiology. How‑ ever, T cells play a central role in the pathogenesis by crossing the blood–brain‑barrier, leading to inflammation ...

    • A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis 

      Madireddy, Lohith; Patsopoulos, Nikolaos A.; Cotsapas, Chris; Bos, Steffan Daniel; Beecham, Ashley; McCauley, Jacob; Kim, Kicheol; Jia, Xiaoming; Santaniello, Adam; Caillier, Stacy J.; Andlauer, Till F.M.; Barcellos, Lisa F.; Berge, Tone; Bernardinelli, Luisa; Martinelli-Boneschi, Filippo; Booth, David R.; Briggs, Farren; Celius, Elisabeth Gulowsen; Comabella, Manuel; Comi, Giancarlo; Cree, Bruce A.C.; D'Alfonso, Sandra; Dedham, Katrina; Duquette, Pierre; Efthimios, Dardiotis; Esposito, Federica; Fontaine, Bertrand; Gasperi, Christiane; Goris, An; Dubois, Bénédicte; Gourraud, Pierre-Antoine; Hadjigeorgiou, Georgios; Haines, Jonathan; Hawkins, Clive; Hemmer, Bernhard; Hintzen, Rogier; Horakova, Dana; Isobe, Noriko; Kalra, Seema; Kira, Jun-ichi; Khalil, Michael; Kockum, Ingrid; Lill, Christina M.; Lincoln, Matthew R; Luessi, Felix; Martin, Roland; Oturai, Annette; Palotie, Aarno; Pericak-Vance, Margaret A.; Henry, Roland; Saarela, Janna; Ivinson, Adrian; Olsson, Tomas; Taylor, Bruce V.; Stewart, Graeme J.; Harbo, Hanne Flinstad; Compston, Alastair; Hauser, Stephen L.; Hafler, David A.; Zipp, Frauke; De Jager, Philip; Sawcer, Stephen; Oksenberg, Jorge R.; Baranzini, Sergio E. (Nature Communications;10, Article number: 2236 (2019), Journal article; Peer reviewed, 2019-05-20)
      Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations ...

    • A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis. 

      Madireddy, L; Patsopoulos, NA; Cotsapas, C; Bos, Steffan Daniel; Beecham, Ashley; McCauley, J; Kim, K; Jia, X; Santaniello, A; Caillier, SJ; Andlauer, TFM; Barcellos, Lisa; Berge, Tone; Bernardinelli, L; Martinelli-Boneschi, F; Booth, D; Briggs, Farren; Celius, Elisabeth Gulowsen; Comabella, M; Comi, G; Cree, BAC; D'Alfonso, S; Dedham, K; Duquette, P.; Dardiotis, E; Esposito, F; Gasperi, Christiane; Goris, A; Dubois, B; Gourraud, PA; Hadjigeorgiou, GM; Haines, J; Hawkins, C; Hemmer, B; Hintzen, R; Horakova, D; Isobe, N; Kalra, S; Kira, Jun-ichi; Khalil, M; Kockum, I; Lill, CM; Lincoln, Michelle; Luessi, F; Martin, R; Oturai, A; Palotie, A; Pericak-Vance, MA; Henry, R; Saarela, J; Ivinson, Adrian; Olsson, Thomas; Taylor, Bruce; Stewart, GJ; Harbo, Hanne Flinstad; Compston, A; Hauser, SL; Hafler, DA; Zipp, F; De Jager, P; Sawcer, S; Oksenberg, JR; Baranzini, SE (Nature Communications;10, Article number: 2236 (2019), Journal article; Peer reviewed, 2019-03-26)
      Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations ...