Multi-Omics for Diagnosing Diseases: Bioinformatics Approaches and Integrative Data Analyses

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Genetics and Genomics".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 1367

Special Issue Editors


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Guest Editor
RISE-Health, Department of Medical Sciences, Faculty of Health Sciences, University of Beira Interior, Covilhã, Portugal
Interests: Bioinformatics and computational biology; computer architecture; systems design; data management and integration; big data; omics; personalized medicine; clinical and evolutionary genomics; WGS and WES; bioinformatics laboratory management
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Guest Editor
Institute of Biotechnology, University of Helsinki, Helsinki, Finland
Interests: comparative genomics; metagenomics; transcriptomics; single-cell RNA-seq; evo-devo
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The study and diagnosis of many human diseases are often difficult due to a number of factors. Diseases have diverse causes, such as, for instance, interactions with the environment, food habits, the microbiome, and/or genetics. Specifically, in this latter case, we are chiefly concerned with hereditary genetics, in particular with the identification of the causes that induce the symptoms presented by the patients. Here, the physician often requires the collection of samples, something that will allow the performance of the genetics diagnosis. These samples often undergo the process of sequencing (i.e., whole-exome sequencing (WES)), which enables the detection of deleterious genetic changes and other variation found in the protein-coding regions of the human genome. However, the genetic causes may also be located outside of the coding regions, i.e., in noncoding DNA, which comprises more than 90% of the human genome. Here, whole-genome sequencing (WGS) methods become necessary. Additionally, GWAS, epigenomics, transcriptomics, and other omics can reveal themselves to be useful in the study and molecular diagnosis of human diseases.

Moreover, several bioinformatics advances have enabled the analysis of data originating from these sequencing technologies and often benefit from tools and methods previously developed in the context of evolutionary and comparative genomics. To better understand the molecular changes, various omics could be further combined into multi-omics strategies; however, this might require the design of powerful high-throughput and high-performance computing resources as well as novel bioinformatics methods.

This Special Issue of Life invites authors to publish original research on all aspects of (i) multi-omics biology and (ii) human molecular disease diagnosis (WES, WGS, etc.), with preference for articles in the former demonstrating the potential of application to the latter. Potential areas for consideration include: (1) bioinformatics hardware systems design, software, and methods, possibly incorporating evolutionary and/or comparative omics aspects; (2) analyses of cohorts suspected of rare genetics diseases, considering the identification of their causes; (3) omics analyses involving the human and/or other evolutionarily close species; and (4) manuscripts considering the analyses of the human microbiome with potential to detect correlations with the affected human genetics and/or disease.

We have successfully published the first volume, and you can read the related publications through the following link: https://www.mdpi.com/journal/life/special_issues/5BE4W6K4N3

You may choose our Joint Special Issue in Computation.

Dr. Emanuel Maldonado
Dr. Imran Khan
Guest Editors

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Keywords

  • bioinformatics
  • computer hardware, software, and methods
  • first-/second-/third-generation sequencing
  • clinical genomics
  • mendelian diseases
  • whole-exome sequencing
  • evolutionary and comparative genomics
  • whole-genome sequencing
  • multi-omics
  • microbiome diseases

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Published Papers (1 paper)

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Research

17 pages, 2193 KiB  
Article
Inherited Hypertrabeculation? Genetic and Clinical Insights in Blood Relatives of Genetically Affected Left Ventricular Excessive Trabeculation Patients
by Balázs Mester, Zoltán Lipták, Kristóf Attila Farkas-Sütő, Kinga Grebur, Flóra Klára Gyulánczi, Alexandra Fábián, Bálint András Fekete, Tamás Attila György, Csaba Bödör, Attila Kovács, Béla Merkely and Andrea Szűcs
Life 2025, 15(2), 150; https://doi.org/10.3390/life15020150 - 22 Jan 2025
Viewed by 827
Abstract
Genetically determined left ventricular excessive trabeculation (LVET) has a wide clinical spectrum ranging from asymptomatic subjects to severe heart failure with arrhythmias and thromboembolic events. Unlike other cardiomyopathies, the relatives of LVET patients never reach the spotlight of guidelines and clinical practice, although [...] Read more.
Genetically determined left ventricular excessive trabeculation (LVET) has a wide clinical spectrum ranging from asymptomatic subjects to severe heart failure with arrhythmias and thromboembolic events. Unlike other cardiomyopathies, the relatives of LVET patients never reach the spotlight of guidelines and clinical practice, although these family members can be often affected by these conditions. Thus, we aimed to investigate the relatives of LVET by multidimensional analysis, such as genetic testing, ECG and cardiac ultrasound (ECHO). We included 55 blood relatives from the family of 18 LVET patients (male = 27, age = 44 ± 20.8y), who underwent anamnesis registration. With Sanger sequencing, the relatives were classified into genetically positive (GEN-pos) and unaffected (GEN-neg) subgroups. In addition to regular ECG parameters, Sokolow-Lyon Index (SLI) values were calculated. 2D ECHO images were analysed with TomTec Arena, evaluating LV volumetric, functional (EF) and strain parameters. Individuals were categorized into JENNI-pos and JENNI-neg morphological subgroups according to the Jenni LVET ECHO criteria. Family history showed frequent involvement (arrhythmia 61%, stroke 56%, syncope 39%, sudden cardiac death 28%, implanted device 28%), as well as personal anamnesis (subjective symptoms 75%, arrhythmias 44%). ECG and ECHO parameters were within the normal range. In terms of genetics, 78% of families and 38% of relatives carried the index mutation. LV_SLI and QT duration were lower in the GEN-pos group; ECHO parameters were comparable in the subgroups. Morphologically, 33% of the relatives met Jenni-LVET criteria were genetically affected and showed lower LV_EF values. The frequently found genetic, morphological and clinical involvement may indicate the importance of screening and, if necessary, regular follow-up of relatives in the genetically affected LVET population. Full article
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