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L G M van Baarsen

Researcher at University of Amsterdam

Publications -  27
Citations -  942

L G M van Baarsen is an academic researcher from University of Amsterdam. The author has contributed to research in topics: Arthritis & Rheumatoid arthritis. The author has an hindex of 10, co-authored 24 publications receiving 850 citations. Previous affiliations of L G M van Baarsen include VU University Medical Center.

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Rheumatoid Arthritis subtypes identified by genomic profiling of peripheral blood cells: Assignment of a type I interferon signature in a subpopulation of patients

TL;DR: The IFN type I signature defines a subgroup of patients with RA, with a distinct biomolecular phenotype, characterised by increased activity of the innate defence system, coagulation and complement cascades, and fatty acid metabolism.
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Features of the synovium of individuals at risk of developing rheumatoid arthritis: implications for understanding preclinical rheumatoid arthritis

TL;DR: Examination of the relationship between the presence of autoantibodies, changes in the synovium, and development of arthritis over time in a markedly larger, prospective study found that subclinical inflammation of thesynovium does not coincide with the appearance of rheumatoid arthritis.
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A subtype of multiple sclerosis defined by an activated immune defense program.

TL;DR: It is concluded that the transcriptional signature of the PB cells reflects the heterogeneity of MS and defines a sub-population of RRMS patients, who exhibit an activated immune defense program that resembles a virus response program, which is supportive for a link between viruses and MS.
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Responsiveness to anti-tumour necrosis factor alpha therapy is related to pre-treatment tissue inflammation levels in rheumatoid arthritis patients.

TL;DR: It is indicated that patients with a high level of tissue inflammation are more likely to benefit from anti-TNFα treatment, compared to those who did not show clinical improvement.
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Gene expression analysis in RA: towards personalized medicine

TL;DR: This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools.