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Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine

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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 January 2024) | Viewed by 19865

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Special Issue Editors

Dr. Hung-Yu Lin

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Guest Editor

Research Assistant Center, Show Chwan Memorial Hospital, Changhua 500, Taiwan
Interests: lncRNA; miRNA; epigenetics; cancers; ageing-related diseases; RNA-targeting therapy
Special Issues, Collections and Topics in MDPI journals

Dr. Pei-Yi Chu

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Guest Editor

Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 402, Taiwan
Interests: lncRNA; miRNA; epigenetics; cancers; ageing-related diseases; RNA-targeting therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the past decade, an unprecedented breakthrough has been made in the wake of the application of next-generation sequencing technologies and advanced artificial intelligence methods. The advances accordingly bring a remarkable opportunity for the determination of key companion biomarkers and biosignatures, efficient diagnosis, prognostic predictions, potent drug identification, and possible mechanisms in a comprehensive way based on multi-omics data.

Bioinformatics is widely employed to cope with the above challenges. A variety of bioinformatics tools and open-access datasets have been developed to promote the integration of omics data, such as epigenomics, metabolomics, transcriptomics, and genomics, in a comprehensive way. In contrast to the traditional approach, bioinformatics has considerably boosted the accuracy of diagnosis and prognosis, expedited the discovery of novel drug targets, and deepened the functional understanding of disease mechanisms, paving a path to advance precision medicine.

We are pleased to invite you to contribute original research articles with reference to (but not limited to) bioinformatics-centric identification of biomarkers/biosignature/drugs/mechanism/prediction algorithm for diagnosis, prognosis, and potential therapeutics in human diseases. Critical review manuscripts with a perspective vision setting the stage for future research are also especially welcome.

Please kindly note: new methods must be compared to existing state-of-the-art methods, using real biological data. The inclusion of experimental data is very much encouraged.

We look forward to receiving your contributions.

Dr. Hung-Yu Lin
Dr. Pei-Yi Chu
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

cancers
ageing-related diseases
bioinformatics
multi-omics
pharmacogenetics
deep learning
evolutionary learning
diagnosis
prognosis
companion biomarker
drug screening
mechanism dissection

Published Papers (13 papers)

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22 pages, 2665 KiB

Open AccessArticle

Integrating Genome-Scale Metabolic Models with Patient Plasma Metabolome to Study Endothelial Metabolism In Situ

by Fernando Silva-Lance, Isabel Montejano-Montelongo, Eric Bautista, Lars K. Nielsen, Pär I. Johansson and Igor Marin de Mas

Int. J. Mol. Sci. 2024, 25(10), 5406; https://doi.org/10.3390/ijms25105406 - 15 May 2024

Viewed by 200

Abstract

Patient blood samples are invaluable in clinical omics databases, yet current methodologies often fail to fully uncover the molecular mechanisms driving patient pathology. While genome-scale metabolic models (GEMs) show promise in systems medicine by integrating various omics data, having only exometabolomic data remains a limiting factor. To address this gap, we introduce a comprehensive pipeline integrating GEMs with patient plasma metabolome. This pipeline constructs case-specific GEMs using literature-based and patient-specific metabolomic data. Novel computational methods, including adaptive sampling and an in-house developed algorithm for the rational exploration of the sampled space of solutions, enhance integration accuracy while improving computational performance. Model characterization involves task analysis in combination with clustering methods to identify critical cellular functions. The new pipeline was applied to a cohort of trauma patients to investigate shock-induced endotheliopathy using patient plasma metabolome data. By analyzing endothelial cell metabolism comprehensively, the pipeline identified critical therapeutic targets and biomarkers that can potentially contribute to the development of therapeutic strategies. Our study demonstrates the efficacy of integrating patient plasma metabolome data into computational models to analyze endothelial cell metabolism in disease contexts. This approach offers a deeper understanding of metabolic dysregulations and provides insights into diseases with metabolic components and potential treatments. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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19 pages, 4692 KiB

Open AccessArticle

Landscape of FLT3 Variations Associated with Structural and Functional Impact on Acute Myeloid Leukemia: A Computational Study

by Zeenat Mirza, Dalal A. Al-Saedi, Nofe Alganmi and Sajjad Karim

Int. J. Mol. Sci. 2024, 25(6), 3419; https://doi.org/10.3390/ijms25063419 - 18 Mar 2024

Viewed by 796

Abstract

Acute myeloid leukemia (AML) is hallmarked by the clonal proliferation of myeloid blasts. Mutations that result in the constitutive activation of the fms-like tyrosine kinase 3 (FLT3) gene, coding for a class III receptor tyrosine kinase, are significantly associated with this heterogeneous hematologic malignancy. The fms-related tyrosine kinase 3 ligand binds to the extracellular domain of the FLT3 receptor, inducing homodimer formation in the plasma membrane, leading to autophosphorylation and activation of apoptosis, proliferation, and differentiation of hematopoietic cells in bone marrow. In the present study, we evaluated the association of FLT3 as a significant biomarker for AML and tried to comprehend the effects of specific variations on the FLT3 protein’s structure and function. We also examined the effects of I836 variants on binding affinity to sorafenib using molecular docking. We integrated multiple bioinformatics tools, databases, and resources such as OncoDB, UniProt, COSMIC, UALCAN, PyMOL, ProSA, Missense3D, InterProScan, SIFT, PolyPhen, and PredictSNP to annotate the structural, functional, and phenotypic impact of the known variations associated with FLT3. Twenty-nine FLT3 variants were analyzed using in silico approaches such as DynaMut, CUPSAT, AutoDock, and Discovery Studio for their impact on protein stability, flexibility, function, and binding affinity. The OncoDB and UALCAN portals confirmed the association of FLT3 gene expression and its mutational status with AML. A computational structural analysis of the deleterious variants of FLT3 revealed I863F mutants as destabilizers of the protein structure, possibly leading to functional changes. Many single-nucleotide variations in FLT3 have an impact on its structure and function. Thus, the annotation of FLT3 SNVs and the prediction of their deleterious pathogenic impact will facilitate an insight into the tumorigenesis process and guide experimental studies and clinical implications. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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16 pages, 4152 KiB

Open AccessArticle

Downregulation of LAMB3 Altered the Carcinogenic Properties of Human Papillomavirus 16-Positive Cervical Cancer Cells

by Warattaya Wattanathavorn, Masahide Seki, Yutaka Suzuki, Supranee Buranapraditkun, Nakarin Kitkumthorn, Thanayod Sasivimolrattana, Parvapan Bhattarakosol and Arkom Chaiwongkot

Int. J. Mol. Sci. 2024, 25(5), 2535; https://doi.org/10.3390/ijms25052535 - 22 Feb 2024

Viewed by 867

Abstract

Nearly all cervical cancer cases are caused by infection with high-risk human papillomavirus (HR-HPV) types. The mechanism of cervical cell transformation is related to the powerful action of viral oncoproteins and cellular gene alterations. Transcriptomic data from cervical cancer and normal cervical cells were utilized to identify upregulated genes and their associated pathways. The laminin subunit beta-3 (LAMB3) mRNAwas overexpressed in cervical cancer and was chosen for functional analysis. The LAMB3 was predominantly expressed in the extracellular region and the plasma membrane, which play a role in protein binding and cell adhesion molecule binding, leading to cell migration and tissue development. LAMB3 was found to be implicated in the pathway in cancer and the PI3K-AKT signaling pathway. LAMB3 knockdown decreased cell migration, invasion, anchorage-dependent and anchorage-independent cell growth and increased the number of apoptotic cells. These effects were linked to a decrease in protein levels involved in the PI3K-AKT signaling pathway and an increase in p53 protein. This study demonstrated that LAMB3 could promote cervical cancer cell migration, invasion and survival. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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0 pages, 12711 KiB

Open AccessArticle

Transcriptional Signatures and Network-Based Approaches Identified Master Regulators Transcription Factors Involved in Experimental Periodontitis Pathogenesis

by Emiliano Vicencio, Josefa Nuñez-Belmar, Juan P. Cardenas, Bastian I. Cortés, Alberto J. M. Martin, Vinicius Maracaja-Coutinho, Adolfo Rojas, Emilio A. Cafferata, Luis González-Osuna, Rolando Vernal and Cristian Cortez

Int. J. Mol. Sci. 2023, 24(19), 14835; https://doi.org/10.3390/ijms241914835 - 2 Oct 2023

Cited by 2 | Viewed by 1310 | Correction

Abstract

Periodontitis is a chronic inflammatory disease characterized by the progressive and irreversible destruction of the periodontium. Its aetiopathogenesis lies in the constant challenge of the dysbiotic biofilm, which triggers a deregulated immune response responsible for the disease phenotype. Although the molecular mechanisms underlying periodontitis have been extensively studied, the regulatory mechanisms at the transcriptional level remain unclear. To generate transcriptomic data, we performed RNA shotgun sequencing of the oral mucosa of periodontitis-affected mice. Since genes are not expressed in isolation during pathological processes, we disclose here the complete repertoire of differentially expressed genes (DEG) and co-expressed modules to build Gene Regulatory Networks (GRNs) and identify the Master Transcriptional Regulators of periodontitis. The transcriptional changes revealed 366 protein-coding genes and 42 non-coding genes differentially expressed and enriched in the immune response. Furthermore, we found 13 co-expression modules with different representation degrees and gene expression levels. Our GRN comprises genes from 12 gene clusters, 166 nodes, of which 33 encode Transcription Factors, and 201 connections. Finally, using these strategies, 26 master regulators of periodontitis were identified. In conclusion, combining the transcriptomic analyses with the regulatory network construction represents a powerful and efficient strategy for identifying potential periodontitis-therapeutic targets. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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17 pages, 1675 KiB

Open AccessArticle

A Comparison of Methods of Gut Microbiota Transplantation for Preclinical Studies

by Jonas Mingaila, Alessandro Atzeni and Aurelijus Burokas

Int. J. Mol. Sci. 2023, 24(15), 12005; https://doi.org/10.3390/ijms241512005 - 26 Jul 2023

Cited by 1 | Viewed by 1083

Abstract

The experimental details reported in preclinical fecal microbiota transplantation (FMT) protocols are highly inconsistent, variable, and/or incomplete. We therefore evaluated FMT from a human donor to antibiotic-induced microbial-depleted mice by exploring the effects of six techniques based on antibiotic (AB) or antibiotic + antimycotic (AB + T) gut decontamination, different administration routes, and different dosing intervals on the gut microbial population, assessed using 16S and 18S sequencing. In addition, we explored the effectiveness of FMT in terms of inflammation, physiological, and behavioral outcomes. Our results showed that intrarectal FMT at low dosing intervals better preserved the donor’s gut bacterial community at genus level. Furthermore, we showed a lower abundance of several genera of fungi in animals treated with AB + T. In addition, we observed that AB + T gut decontamination followed by per os FMT, once every 3 days, affected behavioral parameters when compared to other FMT techniques. Accordingly, the same FMT groups that showed an association with some of the behavioral tests were also related to specific gut fungal genera, suggesting a possible mediation. Our findings may be useful for optimizing the practice of FMT and also in terms of donor microbiota preservation. This information may help to improve the reproducibility and reliability of FMT studies. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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6 pages, 2562 KiB

Open AccessCommunication

COVID-19 Infection May Drive EC-like Myofibroblasts towards Myofibroblasts to Contribute to Pulmonary Fibrosis

by Xiuju Wu, Daoqin Zhang, Kristina I. Boström and Yucheng Yao

Int. J. Mol. Sci. 2023, 24(14), 11500; https://doi.org/10.3390/ijms241411500 - 15 Jul 2023

Cited by 1 | Viewed by 1118

Abstract

COVID-19 has an extensive impact on Homo sapiens globally. Patients with COVID-19 are at an increased risk of developing pulmonary fibrosis. A previous study identified that myofibroblasts could be derived from pulmonary endothelial lineage cells as an important cell source that contributes to pulmonary fibrosis. Here, we analyzed publicly available data and showed that COVID-19 infection drove endothelial lineage cells towards myofibroblasts in pulmonary fibrosis of patients with COVID-19. We also discovered a similar differentiation trajectory in mouse lungs after viral infection. The results suggest that COVID-19 infection leads to the development of pulmonary fibrosis partly through the activation of endothelial cell (EC)-like myofibroblasts. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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38 pages, 10604 KiB

Open AccessArticle

Integrating Microbiome Analysis, Metabolomics, Bioinformatics, and Histopathology to Elucidate the Protective Effects of Pomegranate Juice against Benzo-alpha-pyrene-Induced Colon Pathologies

by Heba Attia, Shahira A. ElBanna, Rania A. Khattab, Mohamed A. Farag, Aymen S. Yassin and Ramy K. Aziz

Int. J. Mol. Sci. 2023, 24(13), 10691; https://doi.org/10.3390/ijms241310691 - 27 Jun 2023

Cited by 6 | Viewed by 3544

Abstract

Polycyclic aromatic hydrocarbons, e.g., benzo[a]pyrene (BaP), are common dietary pollutants with potential carcinogenic activity, while polyphenols are potential chemopreventive antioxidants. Although several health benefits are attributed to polyphenol-rich pomegranate, little is known about its interaction with BaP. This study integrates histochemical, microbiomic, and metabolomic approaches to investigate the protective effects of pomegranate juice from BaP-induced pathologies. To this end, 48 Sprague–Dawley rats received, for four weeks, either pomegranate, BaP, both, or neither (n = 12 rats per group). Whereas histochemical examination of the colon indicated tissue damage marked by mucin depletion in BaP-fed animals, which was partially restored by administration of pomegranate juice, the fecal microbiome and metabolome retained their resilience, except for key changes related to pomegranate and BaP biotransformation. Meanwhile, dramatic microbiome restructuring and metabolome shift were observed as a consequence of the elapsed time (age factor). Additionally, the analysis allowed a thorough examination of fecal microbiome–metabolome associations, which delineated six microbiome clusters (marked by a differential abundance of Lactobacillaceae and Prevotellaceae, Rumincococcaceae, and Erysipelotrichaceae) and two major metabolome clusters (a sugar- and amino-acids-dominated metabotype vs. a cluster of fatty acids and hydrocarbons), with sugar alcohols maintaining a unique signature. In conclusion, using paired comparisons to minimize inter-individual animal variations allowed the dissection of temporal vs. treatment-derived variations. Microbiome–metabolome association clusters may be further exploited for metabotype prediction and gut-health biomarker discovery. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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16 pages, 14912 KiB

Open AccessArticle

An Exploration of the Coherent Effects between METTL3 and NDUFA10 on Alzheimer’s Disease

by Lin Yang, Xinping Pang, Wenbo Guo, Chengjiang Zhu, Lei Yu, Xianghu Song, Kui Wang and Chaoyang Pang

Int. J. Mol. Sci. 2023, 24(12), 10111; https://doi.org/10.3390/ijms241210111 - 14 Jun 2023

Cited by 3 | Viewed by 1750

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized primarily by a decline in cognitive function. However, the etiopathogenesis of AD is unclear. N6-methyladenosine (m6A) is abundant in the brain, and it is interesting to explore the relationship between m6A and AD causes. In this paper, the gene expression of METTL3 and NDUFA10 were found to correlate with the Mini-mental State Examination (MMSE), which is a clinical indicator of the degree of dementia. METTL3 is involved in post-transcriptional methylation and the formation of m6A. NDUFA10 encodes the protein with NADH dehydrogenase activity and oxidoreductase activity in the mitochondrial electron transport chain. The following three characteristics were observed in this paper: 1. The lower the expression level of NDUFA10, the smaller the MMSE, and the higher the degree of dementia. 2. If the expression level of METTL3 dropped below its threshold, the patient would have a risk of AD with a probability close to 100%, suggesting a basic necessity for m6A to protect mRNA. 3. The lower the expression levels of both METTL3 and NDUFA10, the more likely the patient would suffer from AD, implying the coherence between METTL3 and NDUFA10. Regarding the above discovery, the following hypothesis is presented: METTL3 expression level is downregulated, then the m6A modification level of NDUFA10 mRNA is also decreased, thereby reducing the expression level of NDUFA10-encoded protein. Furthermore, the abnormal expression of NDUFA10 contributes to the assembly disorder of mitochondrial complex I and affects the process of the electron respiratory chain, with the consequent development of AD. In addition, to confirm the above conclusions, the AI Ant Colony Algorithm was improved to be more suitable for discovering the characteristics of AD data, and the SVM diagnostic model was applied to mine the coherent effects on AD between METTL3 and NDUFA10. In conclusion, our findings suggest that dysregulated m6A leads to altered expression of its target genes, thereby affecting AD’s development. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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19 pages, 10232 KiB

Open AccessArticle

by Peng Xia, Siwei Ouyang, Rong Shen, Zhao Guo, Guokun Zhang, Xiangwen Liu, Xuguang Yang, Kun Xie and Degui Wang

Int. J. Mol. Sci. 2023, 24(10), 8819; https://doi.org/10.3390/ijms24108819 - 16 May 2023

Viewed by 2095

Abstract

Male infertility is a global issue that seriously affects reproductive health. This study aimed to understand the underlying causes of idiopathic non-obstructive azoospermia (iNOA), which is a type of male infertility with unknown origins that accounts for 10–15% of cases. By using single-cell analysis techniques, we aimed to uncover the mechanisms of iNOA and gain insight into the cellular and molecular changes in the testicular environment. In this study, we performed bioinformatics analysis using scRNA-seq and microarray data obtained from the GEO database. The analysis included techniques such as pseudotime analysis, cell–cell communication, and hdWGCNA. Our study showed a significant difference between the iNOA and the normal groups, indicating a disorder in the spermatogenic microenvironment in iNOA. We observed a reduction in the proportion of Sertoli cells and blocked germ cell differentiation. Additionally, we found evidence of testicular inflammation related to macrophages and identified ODF2 and CABYR as potential biomarkers for iNOA. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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13 pages, 4053 KiB

Open AccessArticle

Supervised Learning and Multi-Omics Integration Reveals Clinical Significance of Inner Membrane Mitochondrial Protein (IMMT) in Prognostic Prediction, Tumor Immune Microenvironment and Precision Medicine for Kidney Renal Clear Cell Carcinoma

by Chun-Chi Chen, Pei-Yi Chu and Hung-Yu Lin

Int. J. Mol. Sci. 2023, 24(10), 8807; https://doi.org/10.3390/ijms24108807 - 15 May 2023

Cited by 2 | Viewed by 2335

Abstract

Kidney renal clear cell carcinoma (KIRC) accounts for approximately 75% of all renal cancers. The prognosis for patients with metastatic KIRC is poor, with less than 10% surviving five years after diagnosis. Inner membrane mitochondrial protein (IMMT) plays a crucial role in shaping the inner mitochondrial membrane (IMM), regulation of metabolism and innate immunity. However, the clinical relevance of IMMT in KIRC is not yet fully understood, and its role in shaping the tumor immune microenvironment (TIME) remains unclear. This study aimed to investigate the clinical significance of IMMT in KIRC using a combination of supervised learning and multi-omics integration. The supervised learning principle was applied to analyze a TCGA dataset, which was downloaded and split into training and test datasets. The training dataset was used to train the prediction model, while the test and the entire TCGA dataset were used to evaluate its performance. Based on the risk score, the cutoff between the low and high IMMT group was set at median value. A Kaplan-Meier curve, receiver operating characteristic (ROC) curve, principal component analysis (PCA) and Spearman’s correlation were conducted to evaluate the prediction ability of the model. Gene Set Enrichment Analysis (GSEA) was used to investigate the critical biological pathways. Immunogenicity, immunological landscape and single-cell analysis were performed to examine the TIME. Databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were employed for inter-database verification. Pharmacogenetic prediction was analyzed via single-guide RNA (sgRNA)-based drug sensitivity screening using Q-omics v.1.30. Low expressions of IMMT in tumor predicted dismal prognosis in KIRC patients and correlated with KIRC progression. GSEA revealed that low expressions of IMMT were implicated in mitochondrial inhibition and angiogenetic activation. In addition, low IMMT expressions had associations with reduced immunogenicity and an immunosuppressive TIME. Inter-database verification corroborated the correlation between low IMMT expressions, KIRC tumors and the immunosuppressive TIME. Pharmacogenetic prediction identified lestaurtinib as a potent drug for KIRC in the context of low IMMT expressions. This study highlights the potential of IMMT as a novel biomarker, prognostic predictor and pharmacogenetic predictor to inform the development of more personalized and effective cancer treatments. Additionally, it provides important insights into the role of IMMT in the mechanism underlying mitochondrial activity and angiogenesis development in KIRC, which suggests IMMT as a promising target for the development of new therapies. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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17 pages, 3919 KiB

Open AccessArticle

Identification of Potential Biomarkers for Diagnosis of Patients with Methamphetamine Use Disorder

by Won-Jun Jang, Sang-Hoon Song, Taekwon Son, Jung Woo Bae, Sooyeun Lee and Chul-Ho Jeong

Int. J. Mol. Sci. 2023, 24(10), 8672; https://doi.org/10.3390/ijms24108672 - 12 May 2023

Cited by 1 | Viewed by 1381

Abstract

The current method for diagnosing methamphetamine use disorder (MUD) relies on self-reports and interviews with psychiatrists, which lack scientific rigor. This highlights the need for novel biomarkers to accurately diagnose MUD. In this study, we identified transcriptome biomarkers using hair follicles and proposed a diagnostic model for monitoring the MUD treatment process. We performed RNA sequencing analysis on hair follicle cells from healthy controls and former and current MUD patients who had been detained in the past for illegal use of methamphetamine (MA). We selected candidate genes for monitoring MUD patients by performing multivariate analysis methods, such as PCA and PLS-DA, and PPI network analysis. We developed a two-stage diagnostic model using multivariate ROC analysis based on the PLS-DA method. We constructed a two-step prediction model for MUD diagnosis using multivariate ROC analysis, including 10 biomarkers. The first step model, which distinguishes non-recovered patients from others, showed very high accuracy (prediction accuracy, 98.7%). The second step model, which distinguishes almost-recovered patients from healthy controls, showed high accuracy (prediction accuracy, 81.3%). This study is the first report to use hair follicles of MUD patients and to develop a MUD prediction model based on transcriptomic biomarkers, which offers a potential solution to improve the accuracy of MUD diagnosis and may lead to the development of better pharmacological treatments for the disorder in the future. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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Review

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19 pages, 5190 KiB

Open AccessReview

The Role of TGF-β Signaling in Saphenous Vein Graft Failure after Peripheral Arterial Disease Bypass Surgery

by Changhuai He, Pin Ye, Xuecheng Zhang, Elham Esmaeili, Yiqing Li, Ping Lü and Chuanqi Cai

Int. J. Mol. Sci. 2023, 24(12), 10381; https://doi.org/10.3390/ijms241210381 - 20 Jun 2023

Cited by 2 | Viewed by 1426

Abstract

Saphenous vein bypass grafting is an effective technique used to treat peripheral arterial disease (PAD). However, restenosis is the major clinical challenge for the graft vessel among people with PAD postoperation. We hypothesize that there is a common culprit behind arterial occlusion and graft restenosis. To investigate this hypothesis, we found TGF-β, a gene specifically upregulated in PAD arteries, by bioinformatics analysis. TGF-β has a wide range of biological activities and plays an important role in vascular remodeling. We discuss the molecular pathway of TGF-β and elucidate its mechanism in vascular remodeling and intimal hyperplasia, including EMT, extracellular matrix deposition, and fibrosis, which are the important pathways contributing to stenosis. Additionally, we present a case report of a patient with graft restenosis linked to the TGF-β pathway. Finally, we discuss the potential applications of targeting the TGF-β pathway in the clinic to improve the long-term patency of vein grafts. Full article

(This article belongs to the Special Issue Bioinformatics Study in Human Diseases: Integration of Omics Data for Personalized Medicine)

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