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The Role of Omics and Artificial Intelligence for the Personalized Management of Inflammatory and Neoplastic Digestive Diseases

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 9181

Special Issue Editors


grade E-Mail Website1 Website2
Guest Editor
1. Department of Translational Medicine and Surgery, School of Medicine, Catholic University, 00168 Rome, Italy
2. Center for Diagnosis and Treatment of Digestive Diseases, CEMAD, Gastroenterology Department, Fondazione Policlinico Gemelli, IRCCS, 00168 Rome, Italy
Interests: gastroenterology; oncology; digestive cancer; diverticular disease; cancer prevention; inflammatory bowel diseases; microbial communities; bioinformatics and computational biology
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
1. Department of Translational Medicine and Surgery, School of Medicine, Catholic University, 00168 Rome, Italy
2. Center for Diagnosis and Treatment of Digestive Diseases, CEMAD, Gastroenterology Department, Fondazione Policlinico Gemelli, IRCCS, 00168 Rome, Italy
Interests: inflammatory bowel disease (IBD); ulcerative colitis; Crohn’s disease; target therapy; biologic agents; small molecules; adhesion antagonists; anti-TNF; IBD vascular complications; stem-cells application in IBD; intestinal mucosal healing; gut microbiota
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Diagnostic and Laboratory Medicine, Bambino Gesù Children’s Hospital and Research Institute, 00146 Rome, Italy
Interests: microbiomics; proteomics; metaproteomics; metabolomics; microbiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Omic data are multidimensional pieces of information that can play a crucial role in the field of personalized therapies and precision medicine. Indeed, the availability of huge data sets is not only exploitable in the context of experimental and research approaches, but also in the field of clinical medicine applications.

The generation, harmonization and integration of sets of clinical and laboratory omic data is extremely important in term of a patient-centered vision of healthcare, being used to produce advanced stratifications of disease phenotypes and new pathophysiological models.

Indeed, data-driven approaches allow us to investigate complex microbial communities or single-cell biochemical atlases. These provide new mechanistic pathological insights and new disease predictors or biomarkers, without any a priori restraint, but with an agnostic approach, hence opening new avenues for the current systems medicine.

The accessibility and interoperability of biobanks and digital biobanks allow for the exploitation of open source data, handled by powerful network management systems, a process which may be very useful for the community of omics scientists and clinicians. The impact of scientific consortia, national and international networks studyng omics data and artifical intelligence (A.I.) is progressively influencing the “real life”of the clinical management via the generation of clinical decision support system (CDSS) algorithms.

In this Special Issue, we welcome authors to submit original research and review articles, contributing to a better understanding of the following topics that include, but are not limited to:

  • generation and analysis of the ecological and functional multidimentional data of microbial communities;
  • role of artificial intelligence (A.I.) in training and validating clinical and laboratory big data for disease prediction models;
  • applications of A.I. in inflammatory bowel diseases;
  • applications of A.I. in neoplastic and preneoplastic digestive diseases.

Prof. Dr. Antonio Gasbarrini
Dr. Alfredo Papa
Prof. Dr. Lorenza Putignani
Guest Editors

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Keywords

  • systems medicine
  • big data
  • data harmonization and integration
  • artificial intelligence
  • inflammatory digestive diseases
  • neoplastic digestive diseases

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Published Papers (3 papers)

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Research

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13 pages, 3661 KiB  
Article
Enrichment of Activated Fibroblasts as a Potential Biomarker for a Non-Durable Response to Anti-Tumor Necrosis Factor Therapy in Patients with Crohn’s Disease
by Soo-Kyung Park, Gi-Young Lee, Sangsoo Kim, Chil-Woo Lee, Chang-Hwan Choi, Sang-Bum Kang, Tae-Oh Kim, Jaeyoung Chun, Jae-Myung Cha, Jong-Pil Im, Kwang-Sung Ahn, Seon-Young Kim, Min-Suk Kim, Chang-Kyun Lee and Dong-Il Park
Int. J. Mol. Sci. 2023, 24(19), 14799; https://doi.org/10.3390/ijms241914799 - 30 Sep 2023
Cited by 1 | Viewed by 1821
Abstract
We investigated whether the response to anti-tumor necrosis factor (anti-TNF) treatment varied according to inflammatory tissue characteristics in Crohn’s disease (CD). Bulk RNA sequencing (RNA-seq) data were obtained from inflamed and non-inflamed tissues from 170 patients with CD. The samples were clustered based [...] Read more.
We investigated whether the response to anti-tumor necrosis factor (anti-TNF) treatment varied according to inflammatory tissue characteristics in Crohn’s disease (CD). Bulk RNA sequencing (RNA-seq) data were obtained from inflamed and non-inflamed tissues from 170 patients with CD. The samples were clustered based on gene expression profiles using principal coordinate analysis (PCA). Cellular heterogeneity was inferred using CiberSortx, with bulk RNA-seq data. The PCA results displayed two clusters of CD-inflamed samples: one close to (Inflamed_1) and the other far away (Inflamed_2) from the non-inflamed samples. Inflamed_1 was rich in anti-TNF durable responders (DRs), and Inflamed_2 was enriched in non-durable responders (NDRs). The CiberSortx results showed that the cell fraction of activated fibroblasts was six times higher in Inflamed_2 than in Inflamed_1. Validation with public gene expression datasets (GSE16879) revealed that the activated fibroblasts were enriched in NDRs over Next, we used DRs by 1.9 times pre-treatment and 7.5 times after treatment. Fibroblast activation protein (FAP) was overexpressed in the Inflamed_2 and was also overexpressed in the NDRs in both the RISK and GSE16879 datasets. The activation of fibroblasts may play a role in resistance to anti-TNF therapy. Characterizing fibroblasts in inflamed tissues at diagnosis may help to identify patients who are likely to respond to anti-TNF therapy. Full article
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20 pages, 3627 KiB  
Article
Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19
by Lucrezia Laterza, Lorenza Putignani, Carlo Romano Settanni, Valentina Petito, Simone Varca, Flavio De Maio, Gabriele Macari, Valerio Guarrasi, Elisa Gremese, Barbara Tolusso, Giulia Wlderk, Maria Antonia Pirro, Caterina Fanali, Franco Scaldaferri, Laura Turchini, Valeria Amatucci, Maurizio Sanguinetti and Antonio Gasbarrini
Int. J. Mol. Sci. 2023, 24(7), 6623; https://doi.org/10.3390/ijms24076623 - 1 Apr 2023
Cited by 8 | Viewed by 3074
Abstract
Gut microbiota (GM) modulation can be investigated as possible solution to enhance recovery after COVID-19. An open-label, single-center, single-arm, pilot, interventional study was performed by enrolling twenty patients recently recovered from COVID-19 to investigate the role of a mixed probiotic, containing Lactobacilli, Bifidobacteria [...] Read more.
Gut microbiota (GM) modulation can be investigated as possible solution to enhance recovery after COVID-19. An open-label, single-center, single-arm, pilot, interventional study was performed by enrolling twenty patients recently recovered from COVID-19 to investigate the role of a mixed probiotic, containing Lactobacilli, Bifidobacteria and Streptococcus thermophilus, on gastrointestinal symptoms, local and systemic inflammation, intestinal barrier integrity and GM profile. Gastrointestinal Symptom Rating Scale, cytokines, inflammatory, gut permeability, and integrity markers were evaluated before (T0) and after 8 weeks (T1) of probiotic supplementation. GM profiling was based on 16S-rRNA targeted-metagenomics and QIIME 2.0, LEfSe and PICRUSt computational algorithms. Multiple machine learning (ML) models were trained to classify GM at T0 and T1. A statistically significant reduction of IL-6 (p < 0.001), TNF-α (p < 0.001) and IL-12RA (p < 0.02), citrulline (p value < 0.001) was reported at T1. GM global distribution and microbial biomarkers strictly reflected probiotic composition, with a general increase in Bifidobacteria at T1. Twelve unique KEGG orthologs were associated only to T0, including tetracycline resistance cassettes. ML classified the GM at T1 with 100% score at phylum level. Bifidobacteriaceae and Bifidobacterium spp. inversely correlated to reduction of citrulline and inflammatory cytokines. Probiotic supplementation during post-COVID-19 may trigger anti-inflammatory effects though Bifidobacteria and related-metabolism enhancement. Full article
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Review

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21 pages, 7675 KiB  
Review
Omics and Multi-Omics in IBD: No Integration, No Breakthroughs
by Claudio Fiocchi
Int. J. Mol. Sci. 2023, 24(19), 14912; https://doi.org/10.3390/ijms241914912 - 5 Oct 2023
Cited by 10 | Viewed by 3477
Abstract
The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of “big data” research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until [...] Read more.
The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of “big data” research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until recently, limited to traditional in vitro and in vivo biological experimentation, but a clear switch to in silico methodologies is now under way. This review tries to provide a comprehensive assessment of state-of-the-art knowledge on omes, omics and multi-omics in inflammatory bowel disease (IBD). The notion and importance of omes, omics and multi-omics in both health and complex diseases like IBD is introduced, followed by a discussion of the various omics believed to be relevant to IBD pathogenesis, and how multi-omics “big data” can generate new insights translatable into useful clinical tools in IBD such as biomarker identification, prediction of remission and relapse, response to therapy, and precision medicine. The pitfalls and limitations of current IBD multi-omics studies are critically analyzed, revealing that, regardless of the types of omes being analyzed, the majority of current reports are still based on simple associations of descriptive retrospective data from cross-sectional patient cohorts rather than more powerful longitudinally collected prospective datasets. Given this limitation, some suggestions are provided on how IBD multi-omics data may be optimized for greater clinical and therapeutic benefit. The review concludes by forecasting the upcoming incorporation of multi-omics analyses in the routine management of IBD. Full article
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