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Diagnostics
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Precision Medicine in Autoimmunity
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Precision Medicine in Autoimmunity

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 7010

Special Issue Editors

Dr. Michael Mahler

E-Mail Website
Guest Editor
Werfen Autoimmunity Headquarter and Technology Center, San Diego, CA, USA
Interests: autoimmunity; immunology; autoantibodies; inflammation; autoimmune disorders; artificial intelligence
Prof. Dr. Dirk Roggenbuck

E-Mail Website
Co-Guest Editor
Faculty Environment and Natural Sciences, Brandenburg Technical University Cottbus-Senftenberg, Senftenberg, Germany
Interests: organ-specific autoimmune disease; systemic rheumatic autoimmune disease; autoantibody; immunoassay; inflammatory bowel disease; mucosal loss of tolerance

Special Issue Information

Dear Colleagues, 

Autoimmune diseases are chronic and heterogeneous conditions that evolve over a long period of time. Due to their unspecific symptoms during the early stages, diagnosis can be challenging and strongly relies on reliable biomarkers and combinations thereof. More specifically, early diagnosis and treatment is imperative to prevent irreversible organ damage. In addition, stratification of patients into more homogenous and meaningful subsets regarding prognosis and treatment response opens new avenues for improved patient care in autoimmunity.

In the field of autoantibody testing, evidence is mounting that autoantibody profiles can provide valuable insights, especially when paired with artificial intelligence. Examples include (but are not limited to) diseases such as systemic lupus erythematosus, idiopathic inflammatory myopathies, rheumatoid arthritis and systemic sclerosis.

This Special Issue on Precision Medicine in Autoimmunity will focus on recent progress on novel biomarkers, novel multi-analyte technologies and the application of artificial intelligence for model development.

Dr. Michael Mahler
Prof. Dr. Dirk Roggenbuck
Guest Editors

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. Diagnostics is an international peer-reviewed open access semimonthly 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

  • autoantibodies
  • biomarker
  • multi-analyte testing
  • precision medicine
  • artificial intelligence
  • autoantibody profiling
  • companion diagnostics
  • disease prediction and prevention

Published Papers (4 papers)

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11 pages, 969 KiB  
Article
Crucial Role of Foxp3 Gene Expression and Mutation in Systemic Lupus Erythematosus, Inferred from Computational and Experimental Approaches
by Zahra Birjan, Khalil Khashei Varnamkhasti, Sara Parhoudeh, Leila Naeimi and Sirous Naeimi
Diagnostics 2023, 13(22), 3442; https://doi.org/10.3390/diagnostics13223442 - 14 Nov 2023
Cited by 1 | Viewed by 758
Abstract
The impaired suppressive function of regulatory T cells is well-understood in systemic lupus erythematosus. This is likely due to changes in Foxp3 expression that are crucial for regulatory T-cell stability and function. There are a few reports on the correlation between the [...] Read more.
The impaired suppressive function of regulatory T cells is well-understood in systemic lupus erythematosus. This is likely due to changes in Foxp3 expression that are crucial for regulatory T-cell stability and function. There are a few reports on the correlation between the Foxp3 altered expression level and single-nucleotide polymorphisms within the Foxp3 locus. Moreover, some studies showed the importance of Foxp3 expression in the same diseases. Therefore, to explore the possible effects of single-nucleotide polymorphisms, here, we evaluated the association of IVS9+459/rs2280883 (T>C) and −2383/rs3761549 (C>T) Foxp3 polymorphisms with systemic lupus erythematosus. Moreover, through machine-learning and deep-learning methods, we assessed the connection of the expression level of the gene with the disease. Single-nucleotide polymorphisms of Foxp3 (IVS9+459/rs2280883 (T>C) and −2383/rs3761549 (C>T)) were, respectively, genotyped using allele-specific PCR and direct sequencing and polymerase chain reaction-restriction fragment length polymorphism, in 199 systemic lupus erythematosus patients and 206 healthy age- and sex-matched controls. The Statistical Package for the Social Sciences version 19 and Fisher’s exact and chi-square tests were used to analyze the data. Moreover, six machine-learning models and two sequential deep-learning models were designed to classify patients from normal people in the E-MTAB-11191 dataset through the expression level of Foxp3 and its correlated genes. The allele and genotype frequencies of both polymorphisms in question were found to be significantly associated with an increased risk of systemic lupus erythematosus. Furthermore, both of the two single-nucleotide polymorphisms were associated with some systemic-lupus-erythematosus-related risk factors. Three SVM models and the logistic regression model showed an 81% accuracy in classification problems. In addition, the first deep-learning model showed an 83% and 89% accuracy for the training and validation data, respectively, while the second model had an 85% and 79% accuracy for the training and validation datasets. In this study, we are prompted to represent the predisposing loci for systemic lupus erythematosus pathogenesis and strived to provide evidence-based support to the application of machine learning for the identification of systemic lupus erythematosus. It is predicted that the recruiting of machine-learning algorithms with the simultaneous measurement of the applied single nucleotide polymorphisms will increased the diagnostic accuracy of systemic lupus erythematosus, which will be very helpful in providing sufficient predictive value about individual subjects with systemic lupus erythematosus. Full article
(This article belongs to the Special Issue Precision Medicine in Autoimmunity)
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11 pages, 552 KiB  
Article
Islet Autoantibodies to Pancreatic Insulin-Producing Beta Cells in Adolescent and Adults with Type 1 Diabetes Mellitus: A Cross-Sectional Study
by Khalid Siddiqui, Shaik Sarfaraz Nawaz, Assim A. Alfadda and Muhammad Mujammami
Diagnostics 2023, 13(10), 1736; https://doi.org/10.3390/diagnostics13101736 - 14 May 2023
Viewed by 1462
Abstract
(1) Background: Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease caused by the destruction of pancreatic insulin-producing beta cells. T1D is one of the most common endocrine and metabolic disorders occurring in children. Autoantibodies against pancreatic insulin-producing beta cells are important [...] Read more.
(1) Background: Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease caused by the destruction of pancreatic insulin-producing beta cells. T1D is one of the most common endocrine and metabolic disorders occurring in children. Autoantibodies against pancreatic insulin-producing beta cells are important immunological and serological markers of T1D. Zinc transporter 8 autoantibody (ZnT8) is a recently identified autoantibody in T1D; however, no data on ZnT8 autoantibody in the Saudi Arabian population have been reported. Thus, we aimed to investigate the prevalence of islet autoantibodies (IA-2 and ZnT8) in adolescents and adults with T1D according to age and disease duration. (2) Methods: In total, 270 patients were enrolled in this cross-sectional study. After meeting the study’s inclusion and exclusion criteria, 108 patients with T1D (50 men and 58 women) were assessed for T1D autoantibody levels. Serum ZnT8 and IA-2 autoantibodies were measured using commercial enzyme-linked immunosorbent assay kits. (3) Results: IA-2 and ZnT8 autoantibodies were present in 67.6% and 54.6% of patients with T1D, respectively. Autoantibody positivity was found in 79.6% of the patients with T1D. Both the IA-2 and ZnT8 autoantibodies were frequently observed in adolescents. The prevalence of IA-2 and ZnT8 autoantibodies in patients with a disease duration < 1 year was 100% and 62.5%, respectively, which declined with an increase in disease duration (p < 0.020). Logistic regression analysis revealed a significant relationship between age and autoantibodies (p < 0.004). (4) Conclusions: The prevalence of IA-2 and ZnT8 autoantibodies in the Saudi Arabian T1D population appears to be higher in adolescents. The current study also showed that the prevalence of autoantibodies decreased with disease duration and age. IA-2 and ZnT8 autoantibodies are important immunological and serological markers for T1D diagnosis in the Saudi Arabian population. Full article
(This article belongs to the Special Issue Precision Medicine in Autoimmunity)
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13 pages, 2308 KiB  
Article
Deciphering the Autoantibody Response to the OJ Antigenic Complex
by Marvin J. Fritzler, Chelsea Bentow, Minoru Satoh, Neil McHugh, Anna Ghirardello and Michael Mahler
Diagnostics 2023, 13(1), 156; https://doi.org/10.3390/diagnostics13010156 - 03 Jan 2023
Cited by 2 | Viewed by 2177
Abstract
(1) Background: Myositis specific antibodies (MSA) are important diagnostic biomarkers. Among the rarest and most challenging MSA are anti-OJ antibodies which are associated with anti-synthetase syndrome (ASS). In contrast to the other tRNA synthetases that are targets of ASS autoantibodies (e.g Jo-1, PL-7, [...] Read more.
(1) Background: Myositis specific antibodies (MSA) are important diagnostic biomarkers. Among the rarest and most challenging MSA are anti-OJ antibodies which are associated with anti-synthetase syndrome (ASS). In contrast to the other tRNA synthetases that are targets of ASS autoantibodies (e.g Jo-1, PL-7, PL-12, EJ, KS, Zo), OJ represents a macromolecular complex with several ribonucleoprotein subunits. Therefore, the choice of the antigen in autoantibody assays can be challenging. (2) Methods: We collected two independent cohorts with anti-OJ antibodies, one based on a commercial line immunoassay (LIA) (n = 39), the second based on protein immunoprecipitation (IP) (n = 15). Samples were tested using a particle-based multi-analyte technology (PMAT) system that allows for the simultaneous detection of antibodies to various autoantigens. For the detection of anti-OJ antibodies, two different antigens were deployed (KARS, IARS) on PMAT. The reactivity to the two antigens KARS and IARS was analyzed individually and combined in a score (sum of the median fluorescence intensities). (3) Results: In the cohort selection based on LIA, 3/39 (7.7%) samples were positive for anti-KARS and 7/39 (17.9%) for anti-IARS and 14/39 (35.9%) when the two antigens were combined. In contrast, in samples selected by IP the sensitivity of anti-KARS was higher: 6/15 (40.0%) samples were positive for anti-KARS, 4/15 (26.7%) for anti-IARS and 12/15 (80.0%) for the combination of the two antigens. 18/39 (46.2%) of the LIA samples generated a cytoplasmic IIF pattern (compatible with anti-synthetase antibodies), but there was no association with the antibody levels, neither with LIA nor with PMAT. (4) Conclusions: The combination of IARS and KARS might represent a promising approach for the detection of anti-OJ antibodies on a fully automated platform. Full article
(This article belongs to the Special Issue Precision Medicine in Autoimmunity)
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20 pages, 9111 KiB  
Systematic Review
Platelet and Red Blood Cell Volume Indices in Patients with Rheumatoid Arthritis: A Systematic Review and Meta-Analysis
by Angelo Zinellu and Arduino A. Mangoni
Diagnostics 2022, 12(11), 2633; https://doi.org/10.3390/diagnostics12112633 - 30 Oct 2022
Cited by 6 | Viewed by 1585
Abstract
Alterations in the volume of platelets (mean platelet volume, MPV; platelet distribution width, PDW) and erythrocytes (red blood cell distribution width, RDW) have been reported in rheumatoid arthritis (RA) and might serve as diagnostic biomarkers. We conducted a systematic review and meta-analysis of [...] Read more.
Alterations in the volume of platelets (mean platelet volume, MPV; platelet distribution width, PDW) and erythrocytes (red blood cell distribution width, RDW) have been reported in rheumatoid arthritis (RA) and might serve as diagnostic biomarkers. We conducted a systematic review and meta-analysis of the MPV, PDW, and RDW in RA patients and healthy controls. Relevant articles were searched in PubMed, Web of Science, Scopus, and Google Scholar from inception to June 2022. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist and certainty of evidence was assessed using GRADE. In 23 studies (2194 RA patients and 1565 healthy controls), the RDW, but not MPV or PDW, was significantly higher in RA patients (standardized mean difference, SMD = 0.96, 95% CI 0.78 to 1.15, p < 0.001; moderate certainty of evidence). The substantial heterogeneity observed (I2 = 75.1%, p < 0.001) was virtually removed in a subgroup of prospective studies. In sensitivity analysis, the magnitude of the effect size was not substantially modified by sequentially removing individual studies. There was no significant publication bias. No significant associations were observed between the effect size and pre-defined study or patient characteristics. The results of our study suggest that the RDW might be a useful biomarker for the diagnosis of RA, and complement the clinical information provided by other patient characteristics and laboratory parameters (PROSPERO registration number: CRD42022349432). Full article
(This article belongs to the Special Issue Precision Medicine in Autoimmunity)
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