Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs

Autor: Åsa K. Hedman, Eitan Winter, Niyaz Yoosuf, Yair Benita, Louise Berg, Boel Brynedal, Lasse Folkersen, Lars Klareskog, Mateusz Maciejewski, Alexandra Sirota-Madi, Yael Spector, Daniel Ziemek, Leonid Padyukov, Shai S. Shen-Orr, Scott A. Jelinsky

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)

Abstract Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work, we aimed to determine the relevance of changes in cell proportions in peripheral blood mon

Externí odkaz: https://doaj.org/article/015c0a27681d422fa2a149b768171efd

Molecular signature of methotrexate response among rheumatoid arthritis patients

Autor: Boel Brynedal, Niyaz Yoosuf, Tinna Bjorg Ulfarsdottir, Daniel Ziemek, Mateusz Maciejewski, Lasse Folkersen, Helga Westerlind, Malin Müller, Peter Sahlström, Scott A. Jelinsky, Aase Hensvold, Leonid Padyukov, Nancy Vivar Pomiano, Anca Catrina, Lars Klareskog, Louise Berg

Publikováno v: Frontiers in Medicine, Vol 10 (2023)

BackgroundMethotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but failure of satisfying treatment response occurs in a significant proportion of patients. Here we present a longitudinal multi-omics study aimed at detecting m

Externí odkaz: https://doaj.org/article/75fb2c0635c442d4bc63cec8b8b58bca

Distinct clinical phenotypes for Crohn’s disease derived from patient surveys

Autor: Tianyun Liu, Lichy Han, Mera Tilley, Lovisa Afzelius, Mateusz Maciejewski, Scott Jelinsky, Chao Tian, Matthew McIntyre, the 23andMe Research Team, Nan Bing, Kenneth Hung, Russ B. Altman

Publikováno v: BMC Gastroenterology, Vol 21, Iss 1, Pp 1-11 (2021)

Abstract Background Defining clinical phenotypes provides opportunities for new diagnostics and may provide insights into early intervention and disease prevention. There is increasing evidence that patient-derived health data may contain information

Externí odkaz: https://doaj.org/article/c3ccf1a423d24b01bd3f9a121dd5a241

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data

Autor: Aaron M. Smith, Jonathan R. Walsh, John Long, Craig B. Davis, Peter Henstock, Martin R. Hodge, Mateusz Maciejewski, Xinmeng Jasmine Mu, Stephen Ra, Shanrong Zhao, Daniel Ziemek, Charles K. Fisher

Publikováno v: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-18 (2020)

Abstract Background The ability to confidently predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. Yet, the goal of developing actionable, robust, and reproducible predictive signatures of phenotypes suc

Externí odkaz: https://doaj.org/article/4a80ce019b8d4e889e86cf97f5025413

Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics

Autor: Nisha Nair, Mateusz Maciejewski, Stephanie Ling, Daniel Ziemek, Darren Plant, Matthew R. Lewis, Suzanne M M Verstappen, Caroline Sands, Kimme L. Hyrich, Anne Barton

Publikováno v: Scientific Reports, Vol 11, Iss 1, Pp 1-6 (2021)
Scientific Reports
Maciejewski, M, Sands, C, Nair, N, Ling, S, Verstappen, S, Hyrich, K, Barton, A, Ziemek, D, Lewis, M R & Plant, D 2021, ' Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics ', Scientific Reports, vol. 11, no. 1, 7266 . https://doi.org/10.1038/s41598-021-86729-7

Methotrexate (MTX) is a common first-line treatment for new-onset rheumatoid arthritis (RA). However, MTX is ineffective for 30–40% of patients and there is no way to know which patients might benefit. Here, we built statistical models based on ser

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d6346c275e35a129a5650e0b9aa40fa
https://doaj.org/article/15aaa01033fa4c62b85b8be3ce377903