4.7 Article

Identification of biomarkers in common chronic lung diseases by co-expression networks and drug-target interactions analysis

Journal

MOLECULAR MEDICINE
Volume 26, Issue 1, Pages -

Publisher

SPRINGER
DOI: 10.1186/s10020-019-0135-9

Keywords

Chronic lung diseases; Asthma; COPD; IPF; Gene co-expression network; Module; Consensus; Biomarker; Drug-target

Ask authors/readers for more resources

Background asthma, chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis (IPF) are three serious pulmonary diseases that contain common and unique characteristics. Therefore, the identification of biomarkers that differentiate these diseases is of importance for preventing misdiagnosis. In this regard, the present study aimed to identify the disorders at the early stages, based on lung transcriptomics data and drug-target interactions. Methods To this end, the differentially expressed genes were found in each disease. Then, WGCNA was utilized to find specific and consensus gene modules among the three diseases. Finally, the disease-disease similarity was analyzed, followed by determining candidate drug-target interactions. Results The results confirmed that the asthma lung transcriptome was more similar to COPD than IPF. In addition, the biomarkers were found in each disease and thus were proposed for further clinical validations. These genes included RBM42, STX5, and TRIM41 in asthma, CYP27A1, GM2A, LGALS9, SPI1, and NLRC4 in COPD, ATF3, PPP1R15A, ZFP36, SOCS3, NAMPT, and GADD45B in IPF, LRRC48 and CETN2 in asthma-COPD, COL15A1, GIMAP6, and JAM2 in asthma-IPF and LMO7, TSPAN13, LAMA3, and ANXA3 in COPD-IPF. Finally, analyzing drug-target networks suggested anti-inflammatory candidate drugs for treating the above mentioned diseases. Conclusion In general, the results revealed the unique and common biomarkers among three chronic lung diseases. Eventually, some drugs were suggested for treatment purposes.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Biochemistry & Molecular Biology

In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm

Mahsa Torkamanian-Afshar, Sajjad Nematzadeh, Maryam Tabarzad, Ali Najafi, Hossein Lanjanian, Ali Masoudi-Nejad

Summary: Using a genetic algorithm and binding predictor fitness function, we successfully designed an aptamer pool against aminopeptidase N (CD13) biomarker in silico. The designed aptamers based on known RNA-protein complexes showed 3 to 6 times higher fitness scores than parent oligonucleotides. The reliability of the obtained sequences was confirmed through docking and molecular dynamic simulation.

MOLECULAR DIVERSITY (2021)

Article Biology

DNA methylation association with stage progression of head and neck squamous cell carcinoma

Vahid Ghafarpour, Mohammad Khansari, Ali M. Banaei-Moghaddam, Ali Najafi, Ali Masoudi-Nejad

Summary: Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common cancer worldwide, accounting for approximately 6% of all cases and around 2% of all cancer deaths. Despite advancements in treatment, survival rates remain low. Epigenetic modifications have associations with biological processes and cancer, suggesting a need for a more systematic approach to identify potential targets and effective therapies.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Oncology

A systematic approach introduced novel targets in rectal cancer by considering miRNA/mRNA interactions in response to radiotherapy

Solmaz Khalighfard, Mohammad Reza Kalhori, Taghi Amiriani, Amirhoushang Poorkhani, Vahid Khori, Ebrahim Esmati, Marzieh Lashkari, Ali Najafi, Ali Mohammad Alizadeh

Summary: "The study revealed that the interactions of miRNA/mRNA in plasma of rectal cancer patients during radiotherapy could serve as a potential diagnostic tool to track the recovery process and evaluate the efficacy of standard treatments."

CANCER BIOMARKERS (2022)

Article Biochemistry & Molecular Biology

In Silico Analysis of Inhibiting Papain-like Protease from SARS-CoV-2 by Using Plant-Derived Peptides

Mohammad Moradi, Reza Golmohammadi, Ali Najafi, Mehrdad Moosazadeh Moghaddam, Mahdi Fasihi-Ramandi, Reza Mirnejad

Summary: The study aimed to suppress the activity of a critical enzyme in SARS-CoV-2 using plant-derived protease inhibitor peptides, with VcTI identified as a potentially effective inhibitory ligand. Molecular dynamic assay confirmed the stability of the selected receptor and ligand complex, further in vitro and in vivo investigations are needed to verify the therapeutic efficiency of this compound against SARS-CoV-2 infection.

INTERNATIONAL JOURNAL OF PEPTIDE RESEARCH AND THERAPEUTICS (2022)

Article Genetics & Heredity

Identification of shared molecular signatures between multiple sclerosis and Parkinson's disease using systems biology approach

Taleb Badri, Masoud Arabfard, Ali Najafi, Gholamreza Farnoosh, Reza Heidari, Zahra Salehi, Said Yaghoob Sehri, Kazem Hassanpour

Summary: Neurodegenerative diseases (NDs) are common disorders affecting over 40 million people worldwide. Multiple Sclerosis (MS) and Parkinson's Disease (PD) are two leading causes of disability and immune system dysregulation. This study aimed to investigate the potential role of common genes between MS and PD as biomarkers for these diseases. By analyzing gene expression data, several common genes between MS and PD were identified. These findings have practical implications for the development of diagnostic strategies and the search for new drugs and drug targets.

GENE REPORTS (2022)

Article Chemistry, Multidisciplinary

Computational study of peptide interaction with mutant γ-crystallin with the aim of preventing dimerization

Seyed-Hashem Daryabari, Hossein Aghamollaei, Khosrow Jadidi, Ali Najafi, Esmaeil Behmard

Summary: In this study, molecular docking and molecular dynamic simulations were used to investigate the binding of three putative amyloid-binding octapeptides (RVTWEGKF, RGTFEGRF, and RITFEIKF) to mutant gamma-crystallin protein. The results showed that RVTWEGKF had a more favorable binding energy and could reduce the formation of protein dimers. It is proposed that RGTFEGRF should be experimentally tested as a potential treatment for cataract disease.

STRUCTURAL CHEMISTRY (2023)

Article Respiratory System

Comparative proteomic analysis of mustard lung as a complicated disease using systems biology approach

Shahram Parvin, Masoud Arabfard, Ali Ghazvini, Mostafa Ghanei, Ali Najafi

Summary: This study compared the serum proteome of chronic gas-exposed patients and healthy controls, revealing significant differences in protein expression associated with inflammatory and cell adhesion signaling pathways. The findings suggest impaired repair cycles of cell degeneration and regeneration in the injured organs of exposed individuals. The study highlights the role of systems biology in enhancing our understanding of pathophysiological mechanisms and identifying potential disease biomarkers.

BMC PULMONARY MEDICINE (2022)

Article Agronomy

Rhizosphere soil bacteria community vary and correlate with saffron quality at four locations

Masoud Ghayoumi, Abbasali Emamjomeh, Kaveh Kavousi, Ali Najafi

Summary: This study utilized a metagenomic approach to investigate the differences in rhizosphere microbial community and quality indices of saffron in the Ghayen region of Iran. The results showed that rhizobacteria have a significant impact on enhancing the quality of saffron by improving the plant secondary metabolites.

RHIZOSPHERE (2022)

Article Chemistry, Multidisciplinary

Interaction of antibacterial CM11 peptide with the gram-positive and gram-negative bacterial membrane models: a molecular dynamics simulations study

Reza Mirnejad, Mahdi Fasihi-Ramandi, Esmaeil Behmard, Ali Najafi, Mehrdad Moosazadeh Moghaddam

Summary: All-atom molecular dynamics simulations were used to investigate the molecular mechanism of CM11 activity against Gram-positive and Gram-negative bacterial membranes. The peptide showed stronger and faster binding to the Gram-positive membrane and electrostatic interactions were the main driving force in peptide adsorption and surface localization. Residues W1, K2, K5, K6 and K9 played an important role in the activity of the peptide. These findings provide insights for the design of effective peptides against multidrug-resistant bacteria.

CHEMICAL PAPERS (2023)

Article Biochemical Research Methods

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues

Roohallah Mahdi-Esferizi, Behnaz Haji Molla Hoseyni, Amir Mehrpanah, Yazdan Golzade, Ali Najafi, Fatemeh Elahian, Amin Zadeh Shirazi, Guillermo A. Gomez, Shahram Tahmasebian

Summary: P4 medicine is a new approach to diagnosing and predicting diseases on a patient-by-patient basis. Researchers have developed a deep learning model called DeeP4med that can predict the state of the disease based on gene expression data. The model outperforms classic machine learning models in tissue and disease classification.

BMC BIOINFORMATICS (2023)

Article Microbiology

Exploring Co-occurrence patterns and microbial diversity in the lung microbiome of patients with non-small cell lung cancer

Sadaf Najafi, Sadegh Azimzadeh Jamalkandi, Ali Najafi, Jafar Salimian, Ali Ahmadi

Summary: Using integrative and network-based approaches, this study explored the relationships among members of the lung microbial community in lung cancer patients. Differential abundance analyses revealed differences in bacterial taxa between tumor and tumor-adjacent normal tissues. Clustering methods detected distinct modules of bacterial families. The network analysis approach identified key microbial taxa in lung cancer pathogenesis.

BMC MICROBIOLOGY (2023)

Article Medicine, General & Internal

In-silico evaluation of the potential of a viral protein (Apoptin) as an anticancer agent

Masoud E. Razliqi, Ali Najafi, Gholamreaza Olad, Hadi E. G. Ghaleh

Summary: Chicken anemia virus (CAV) is a common immunosuppressive virus in poultry, with its encoded protein Apoptin showing selective activity against tumor cells. In-silico analysis revealed Apoptin's stable structure, making it a promising candidate for therapeutic use as an anti-cancer agent.

ROMANIAN JOURNAL OF MILITARY MEDICINE (2021)

No Data Available