Submit to Biomedicines Review for Biomedicines Propose a Special Issue

Journal Browser

► Journal Browser

Omics Approaches on Immune-Mediated Inflammatory Diseases: Towards Novel Biomarkers and Potential Therapeutic Targets Vol. 2

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Gene and Cell Therapy".

Deadline for manuscript submissions: closed (15 March 2024) | Viewed by 7870

Share This Special Issue

Special Issue Editor

Dr. Maria-Ioanna (Marianna) Christodoulou

E-Mail Website
Guest Editor

1. Department of Life Sciences, European University Cyprus, Nicosia 2404, Cyprus
2. School of Infection and Immunity, University of Glasgow, Glasgow G12 8TA, UK
Interests: tumor immunology; autoimmunity; RNA sequencing; immunotranscriptomics; translational oncology; immunoregulatory cytokines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, chronic immune-mediated inflammatory diseases (IMIDs), including but not restricted to autoimmune conditions present ever-increasing prevalence worldwide. Rheumatoid and psoriatic arthritis, systemic lupus erythematosus, inflammatory bowel disease, Crohn’s disease, ulcerative colitis, multiple sclerosis, and others affect a significant proportion of human population. Further to the irreversible impairment of the target tissue, IMIDs may be also accompanied by life-threatening comorbidities, such as cardiovascular disease and neoplasia development, while their course is characterized by relapsing exacerbations leading to life-long morbidity. Unfortunately, current therapeutics are not able to efficiently manage all patients with a significant proportion of non-responders; this is possibly associated with the remaining missing insights of their underlying pathophysiology.

Recent technological advances facilitated high-throughput omics approaches (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) for the evaluation of critical molecular compartments involved in the development and perpetuation of IMIDs. Unveiling key players governing their pathogenesis and progression may pave the way for the detection of novel biomarkers for disease prognosis and response-to-therapy monitoring, while suggesting potential therapeutic targets.

Bulk and single-cell omics, multi-omics flow cytometry, new-generation microscopy, and systems biology are among the current approaches expected to provide useful tools to be applied in the daily clinical practice, for the improvement of patients’ management and quality of life.

After the success in collecting significant number of valuable manuscripts, the Special Issue of “Biomedicines”, “Omics Approaches on Immune-Mediated Inflammatory Diseases: Towards Novel Biomarkers and Potential Therapeutic Targets”, is now launching its second volume, aiming at hosting more original research, review, or systematic review articles describing the most recent advances in the field of omics on IMIDs, possibly suggesting novel biomarkers and/or therapeutic targets.

Dr. Marianna Christodoulou
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. Biomedicines 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

IMIDs
IBD
Crohn’s disease
ulcerative colitis
SLE
Sjogren’s syndrome
rheumatoid arthritis
psoriatic arthritis
multiple sclerosis
bulk and single-cell omics
multi-omics flow cytometry
next-generation microscopy
tissue microarrays
systems biology

Published Papers (4 papers)

Download All Papers

Research

Jump to: Review

18 pages, 1725 KiB

Open AccessArticle

Supervised Parametric Learning in the Identification of Composite Biomarker Signatures of Type 1 Diabetes in Integrated Parallel Multi-Omics Datasets

by Jerry Bonnell, Oscar Alcazar, Brandon Watts, Peter Buchwald, Midhat H. Abdulreda and Mitsunori Ogihara

Biomedicines 2024, 12(3), 492; https://doi.org/10.3390/biomedicines12030492 - 22 Feb 2024

Viewed by 831

Abstract

Background: Type 1 diabetes (T1D) is a devastating autoimmune disease, and its rising prevalence in the United States and around the world presents a critical problem in public health. While some treatment options exist for patients already diagnosed, individuals considered at risk for developing T1D and who are still in the early stages of their disease pathogenesis without symptoms have no options for any preventive intervention. This is because of the uncertainty in determining their risk level and in predicting with high confidence who will progress, or not, to clinical diagnosis. Biomarkers that assess one’s risk with high certainty could address this problem and will inform decisions on early intervention, especially in children where the burden of justifying treatment is high. Single omics approaches (e.g., genomics, proteomics, metabolomics, etc.) have been applied to identify T1D biomarkers based on specific disturbances in association with the disease. However, reliable early biomarkers of T1D have remained elusive to date. To overcome this, we previously showed that parallel multi-omics provides a more comprehensive picture of the disease-associated disturbances and facilitates the identification of candidate T1D biomarkers. Methods: This paper evaluated the use of machine learning (ML) using data augmentation and supervised ML methods for the purpose of improving the identification of salient patterns in the data and the ultimate extraction of novel biomarker candidates in integrated parallel multi-omics datasets from a limited number of samples. We also examined different stages of data integration (early, intermediate, and late) to assess at which stage supervised parametric models can learn under conditions of high dimensionality and variation in feature counts across different omics. In the late integration scheme, we employed a multi-view ensemble comprising individual parametric models trained over single omics to address the computational challenges posed by the high dimensionality and variation in feature counts across the different yet integrated multi-omics datasets. Results: the multi-view ensemble improves the prediction of case vs. control and finds the most success in flagging a larger consistent set of associated features when compared with chance models, which may eventually be used downstream in identifying a novel composite biomarker signature of T1D risk. Conclusions: the current work demonstrates the utility of supervised ML in exploring integrated parallel multi-omics data in the ongoing quest for early T1D biomarkers, reinforcing the hope for identifying novel composite biomarker signatures of T1D risk via ML and ultimately informing early treatment decisions in the face of the escalating global incidence of this debilitating disease. Full article

(This article belongs to the Special Issue Omics Approaches on Immune-Mediated Inflammatory Diseases: Towards Novel Biomarkers and Potential Therapeutic Targets Vol. 2)

► Show Figures

Figure 1

20 pages, 3753 KiB

Open AccessArticle

Application of SWATH Mass Spectrometry and Machine Learning in the Diagnosis of Inflammatory Bowel Disease Based on the Stool Proteome

by Elmira Shajari, David Gagné, Mandy Malick, Patricia Roy, Jean-François Noël, Hugo Gagnon, Marie A. Brunet, Maxime Delisle, François-Michel Boisvert and Jean-François Beaulieu

Biomedicines 2024, 12(2), 333; https://doi.org/10.3390/biomedicines12020333 - 01 Feb 2024

Viewed by 985

Abstract

Inflammatory bowel disease (IBD) flare-ups exhibit symptoms that are similar to other diseases and conditions, making diagnosis and treatment complicated. Currently, the gold standard for diagnosing and monitoring IBD is colonoscopy and biopsy, which are invasive and uncomfortable procedures, and the fecal calprotectin test, which is not sufficiently accurate. Therefore, it is necessary to develop an alternative method. In this study, our aim was to provide proof of concept for the application of Sequential Window Acquisition of All Theoretical Mass Spectra-Mass spectrometry (SWATH-MS) and machine learning to develop a non-invasive and accurate predictive model using the stool proteome to distinguish between active IBD patients and symptomatic non-IBD patients. Proteome profiles of 123 samples were obtained and data processing procedures were optimized to select an appropriate pipeline. The differentially abundant analysis identified 48 proteins. Utilizing correlation-based feature selection (Cfs), 7 proteins were selected for proceeding steps. To identify the most appropriate predictive machine learning model, five of the most popular methods, including support vector machines (SVMs), random forests, logistic regression, naive Bayes, and k-nearest neighbors (KNN), were assessed. The generated model was validated by implementing the algorithm on 45 prospective unseen datasets; the results showed a sensitivity of 96% and a specificity of 76%, indicating its performance. In conclusion, this study illustrates the effectiveness of utilizing the stool proteome obtained through SWATH-MS in accurately diagnosing active IBD via a machine learning model. Full article

(This article belongs to the Special Issue Omics Approaches on Immune-Mediated Inflammatory Diseases: Towards Novel Biomarkers and Potential Therapeutic Targets Vol. 2)

► Show Figures

Figure 1

Review

Jump to: Research

52 pages, 1221 KiB

Open AccessReview

A Narrative Review of Cytokine Networks: Pathophysiological and Therapeutic Implications for Inflammatory Bowel Disease Pathogenesis

by Marek Vebr, Renáta Pomahačová, Josef Sýkora and Jan Schwarz

Biomedicines 2023, 11(12), 3229; https://doi.org/10.3390/biomedicines11123229 - 06 Dec 2023

Cited by 1 | Viewed by 1613

Abstract

Inflammatory bowel disease (IBD) is a lifelong inflammatory immune mediated disorder, encompassing Crohn’s disease (CD) and ulcerative colitis (UC); however, the cause and specific pathogenesis of IBD is yet incompletely understood. Multiple cytokines produced by different immune cell types results in complex functional networks that constitute a highly regulated messaging network of signaling pathways. Applying biological mechanisms underlying IBD at the single omic level, technologies and genetic engineering enable the quantification of the pattern of released cytokines and new insights into the cytokine landscape of IBD. We focus on the existing literature dealing with the biology of pro- or anti-inflammatory cytokines and interactions that facilitate cell-based modulation of the immune system for IBD inflammation. We summarize the main roles of substantial cytokines in IBD related to homeostatic tissue functions and the remodeling of cytokine networks in IBD, which may be specifically valuable for successful cytokine-targeted therapies via marketed products. Cytokines and their receptors are validated targets for multiple therapeutic areas, we review the current strategies for therapeutic intervention and developing cytokine-targeted therapies. New biologics have shown efficacy in the last few decades for the management of IBD; unfortunately, many patients are nonresponsive or develop therapy resistance over time, creating a need for novel therapeutics. Thus, the treatment options for IBD beyond the immune-modifying anti-TNF agents or combination therapies are expanding rapidly. Further studies are needed to fully understand the immune response, networks of cytokines, and the direct pathogenetic relevance regarding individually tailored, safe and efficient targeted-biotherapeutics. Full article

(This article belongs to the Special Issue Omics Approaches on Immune-Mediated Inflammatory Diseases: Towards Novel Biomarkers and Potential Therapeutic Targets Vol. 2)

► Show Figures

Figure 1

19 pages, 686 KiB

Open AccessReview

DNA Methylation Signatures of Response to Conventional Synthetic and Biologic Disease-Modifying Antirheumatic Drugs (DMARDs) in Rheumatoid Arthritis

by Susan Siyu Wang, Myles J. Lewis and Costantino Pitzalis

Biomedicines 2023, 11(7), 1987; https://doi.org/10.3390/biomedicines11071987 - 13 Jul 2023

Cited by 2 | Viewed by 3143

Abstract

Rheumatoid arthritis (RA) is a complex condition that displays heterogeneity in disease severity and response to standard treatments between patients. Failure rates for conventional, target synthetic, and biologic disease-modifying rheumatic drugs (DMARDs) are significant. Although there are models for predicting patient response, they have limited accuracy, require replication/validation, or for samples to be obtained through a synovial biopsy. Thus, currently, there are no prediction methods approved for routine clinical use. Previous research has shown that genetics and environmental factors alone cannot explain the differences in response between patients. Recent studies have demonstrated that deoxyribonucleic acid (DNA) methylation plays an important role in the pathogenesis and disease progression of RA. Importantly, specific DNA methylation profiles associated with response to conventional, target synthetic, and biologic DMARDs have been found in the blood of RA patients and could potentially function as predictive biomarkers. This review will summarize and evaluate the evidence for DNA methylation signatures in treatment response mainly in blood but also learn from the progress made in the diseased tissue in cancer in comparison to RA and autoimmune diseases. We will discuss the benefits and challenges of using DNA methylation signatures as predictive markers and the potential for future progress in this area. Full article

(This article belongs to the Special Issue Omics Approaches on Immune-Mediated Inflammatory Diseases: Towards Novel Biomarkers and Potential Therapeutic Targets Vol. 2)

► Show Figures