Mining the Proteome Associated with Rheumatic and Autoimmune Diseases
(2019) In Journal of Proteome Research 18(12). p.4231-4239- Abstract
A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining... (More)
A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders.
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- author
- Ruiz-Romero, Cristina
; Lam, Maggie P.Y.
; Nilsson, Peter
; Önnerfjord, Patrik
LU
; Utz, Paul J. ; Van Eyk, Jennifer E. ; Venkatraman, Vidya ; Fert-Bober, Justyna ; Watt, Fiona E. and Blanco, Francisco J.
- organization
- publishing date
- 2019-10-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- autoimmune diseases, bioinformatics, Human Proteome Project, osteoarthritis, rheumatic diseases
- in
- Journal of Proteome Research
- volume
- 18
- issue
- 12
- pages
- 4231 - 4239
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- pmid:31599600
- scopus:85074420794
- ISSN
- 1535-3893
- DOI
- 10.1021/acs.jproteome.9b00360
- language
- English
- LU publication?
- yes
- id
- 2198e9d5-305a-4e66-a234-aceb1d2f1671
- date added to LUP
- 2019-11-26 13:58:22
- date last changed
- 2024-07-10 06:35:15
@article{2198e9d5-305a-4e66-a234-aceb1d2f1671, abstract = {{<p>A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders. </p>}}, author = {{Ruiz-Romero, Cristina and Lam, Maggie P.Y. and Nilsson, Peter and Önnerfjord, Patrik and Utz, Paul J. and Van Eyk, Jennifer E. and Venkatraman, Vidya and Fert-Bober, Justyna and Watt, Fiona E. and Blanco, Francisco J.}}, issn = {{1535-3893}}, keywords = {{autoimmune diseases; bioinformatics; Human Proteome Project; osteoarthritis; rheumatic diseases}}, language = {{eng}}, month = {{10}}, number = {{12}}, pages = {{4231--4239}}, publisher = {{The American Chemical Society (ACS)}}, series = {{Journal of Proteome Research}}, title = {{Mining the Proteome Associated with Rheumatic and Autoimmune Diseases}}, url = {{http://dx.doi.org/10.1021/acs.jproteome.9b00360}}, doi = {{10.1021/acs.jproteome.9b00360}}, volume = {{18}}, year = {{2019}}, }