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Diagnosis and Therapies of Rheumatoid Arthritis
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Diagnosis and Therapies of Rheumatoid Arthritis

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Mechanisms of Diseases".

Deadline for manuscript submissions: closed (1 September 2021) | Viewed by 6357

Special Issue Editor

Dr. Hatem A. Elshabrawy

E-Mail Website
Guest Editor
Department of Biochemistry, Cell Biology & Genetics at the College of Osteopathic Medicine, Sam Houston State University, Huntsville, TX, USA
Interests: development of antiviral small molecules and antibodies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that affects 1.5 million Americans and can lead to complete joint destruction and sever disability if left untreated. To date, there is no cure for RA, and up to 40% of RA patients do not respond to standard therapies. including anti-TNF-α. Therefore, there is an immediate need for novel diagnostics, therapeutic targets, and therapeutics for the effective diagnosis and management of RA.

In this Special Issue, we aim to publish a wide range of manuscripts that investigate RA disease development, pathogenesis, diagnosis/diagnostic tools, evaluation of novel host cell proteins as potential drug targets, and studies that report novel antibodies or small molecules as potential RA therapeutics.

Dr. Hatem A. Elshabrawy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • RA
  • therapeutics
  • antibodies
  • diagnostics
  • small molecules
  • pathogenesis

Published Papers (2 papers)

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Research

19 pages, 359 KiB  
Article
Association of the Adipokines Chemerin, Apelin, Vaspin and Omentin and Their Functional Genetic Variants with Rheumatoid Arthritis
by Alaa S. Wahba, Maha E. Ibrahim, Dina M. Abo-elmatty and Eman T. Mehanna
J. Pers. Med. 2021, 11(10), 976; https://0-doi-org.brum.beds.ac.uk/10.3390/jpm11100976 - 29 Sep 2021
Cited by 6 | Viewed by 1921
Abstract
Adipokines were shown to exert crucial roles in rheumatic diseases. This study aimed to assess the role of chemerin, apelin, vaspin, and omentin adipokines and their genetic variants rs17173608, rs2235306, rs2236242, and rs2274907, respectively, in rheumatoid arthritis (RA) pathogenesis in Egyptian patients. A [...] Read more.
Adipokines were shown to exert crucial roles in rheumatic diseases. This study aimed to assess the role of chemerin, apelin, vaspin, and omentin adipokines and their genetic variants rs17173608, rs2235306, rs2236242, and rs2274907, respectively, in rheumatoid arthritis (RA) pathogenesis in Egyptian patients. A total of 150 RA patients and 150 healthy individuals were recruited. Blood samples were collected and used for genotyping. Serum was separated and used for expression analysis by quantitative PCR, and various biochemical markers determination by ELISA. Serum protein levels of chemerin and vaspin, as well as their gene expression levels were higher, while those of apelin and omentin were lower in RA patients and were associated with most of RA clinical and laboratory characteristics. G allele of chemerin rs17173608, T allele of vaspin rs2236242, and T allele of omentin rs2274907 were more frequent in RA patients. Serum levels and gene expression levels of chemerin in GG genotype carriers and vaspin in TT genotype group were significantly higher, while those of omentin in TT genotype carriers were significantly lower than RA patients with other genotypes. There was no association between apelin rs2235306 and RA. Chemerin rs17173608, vaspin rs2236242, and omentin rs2274907 polymorphisms were associated with increased susceptibility to RA. Full article
(This article belongs to the Special Issue Diagnosis and Therapies of Rheumatoid Arthritis)
19 pages, 5328 KiB  
Article
Inference of an Integrative, Executable Network for Rheumatoid Arthritis Combining Data-Driven Machine Learning Approaches and a State-of-the-Art Mechanistic Disease Map
by Quentin Miagoux, Vidisha Singh, Dereck de Mézquita, Valerie Chaudru, Mohamed Elati, Elisabeth Petit-Teixeira and Anna Niarakis
J. Pers. Med. 2021, 11(8), 785; https://0-doi-org.brum.beds.ac.uk/10.3390/jpm11080785 - 12 Aug 2021
Cited by 10 | Viewed by 3350
Abstract
Rheumatoid arthritis (RA) is a multifactorial, complex autoimmune disease that involves various genetic, environmental, and epigenetic factors. Systems biology approaches provide the means to study complex diseases by integrating different layers of biological information. Combining multiple data types can help compensate for missing [...] Read more.
Rheumatoid arthritis (RA) is a multifactorial, complex autoimmune disease that involves various genetic, environmental, and epigenetic factors. Systems biology approaches provide the means to study complex diseases by integrating different layers of biological information. Combining multiple data types can help compensate for missing or conflicting information and limit the possibility of false positives. In this work, we aim to unravel mechanisms governing the regulation of key transcription factors in RA and derive patient-specific models to gain more insights into the disease heterogeneity and the response to treatment. We first use publicly available transcriptomic datasets (peripheral blood) relative to RA and machine learning to create an RA-specific transcription factor (TF) co-regulatory network. The TF cooperativity network is subsequently enriched in signalling cascades and upstream regulators using a state-of-the-art, RA-specific molecular map. Then, the integrative network is used as a template to analyse patients’ data regarding their response to anti-TNF treatment and identify master regulators and upstream cascades affected by the treatment. Finally, we use the Boolean formalism to simulate in silico subparts of the integrated network and identify combinations and conditions that can switch on or off the identified TFs, mimicking the effects of single and combined perturbations. Full article
(This article belongs to the Special Issue Diagnosis and Therapies of Rheumatoid Arthritis)
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