Publications by authors named "Reza Karbalaei"

8 Publications

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Mol Pharmacol 2021 Feb 25. Epub 2021 Feb 25.

Helsinki University, Finland

Celecoxib is one of the most common medicines for treating inflammatory diseases. Recently, it has been shown that celecoxib is associated with implications in complex diseases such as Alzheimer's disease and cancer, as well as with cardiovascular risk assessment and toxicity, suggesting that celecoxib may affect multiple unknown targets. In this project, we detected targets of celecoxib within the nervous system using a label-free TPP (Thermal Proteome Profiling) method. First, proteins of the rat hippocampus were treated with multiple drug concentrations and temperatures. Next, we separated the soluble proteins from the denatured and sedimented total protein load by ultracentrifugation. Subsequently, the soluble proteins were analyzed by nano-liquid chromatography-mass spectrometry to determine the identity of the celecoxib targeted proteins based on structural changes by thermal stability variation of targeted proteins towards higher solubility in the higher temperatures. In the analysis of the soluble protein extract at 67 centigrade, 44 proteins were uniquely detected in drug-treated samples out of all 478 identified proteins at this temperature. Rab4a, one out of these 44 proteins, has previously been reported as one of the celecoxib off-targets in the rat CNS. Furthermore, we provide more molecular details through biomedical enrichment analysis to explore the potential role of all detected proteins in the biological systems. We show that the determined proteins play a role in the signaling pathways related to neurodegenerative disease - and cancer pathways. Finally, we fill out molecular supporting evidence for using celecoxib towards the drug repurposing approach by exploring drug targets. In this study, we determined forty-four off-target proteins of celecoxib, a non-steroidal anti-inflammatory, and one of the most common medicines for treating inflammatory diseases. We showed that these proteins play a role in the signaling pathways related to neurodegenerative disease and cancer pathways. Finally, we provided molecular supporting evidence for using celecoxib towards the drug repurposing approach by exploring drug targets.
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http://dx.doi.org/10.1124/molpharm.120.000210DOI Listing
February 2021

Early life adversity promotes resilience to opioid addiction-related phenotypes in male rats and sex-specific transcriptional changes.

Proc Natl Acad Sci U S A 2021 Feb;118(8)

Department of Psychology and Neuroscience Program, Temple University, Philadelphia, PA 19122;

Experiencing some early life adversity can have an "inoculating" effect that promotes resilience in adulthood. However, the mechanisms underlying stress inoculation are unknown, and animal models are lacking. Here we used the limited bedding and nesting (LBN) model of adversity to evaluate stress inoculation of addiction-related phenotypes. In LBN, pups from postnatal days 2 to 9 and their dams were exposed to a low-resource environment. In adulthood, they were tested for addiction-like phenotypes and compared to rats raised in standard housing conditions. High levels of impulsivity are associated with substance abuse, but in males, LBN reduced impulsive choice compared to controls. LBN males also self-administered less morphine and had a lower breakpoint on a progressive ratio reinforcement schedule than controls. These effects of LBN on addiction-related behaviors were not found in females. Because the nucleus accumbens (NAc) mediates these behaviors, we tested whether LBN altered NAc physiology in drug-naïve and morphine-exposed rats. LBN reduced the frequency of spontaneous excitatory postsynaptic currents in males, but a similar effect was not observed in females. Only in males did LBN prevent a morphine-induced increase in the AMPA/NMDA ratio. RNA sequencing was performed to delineate the molecular signature in the NAc associated with LBN-derived phenotypes. LBN produced sex-specific changes in transcription, including in genes related to glutamate transmission. Collectively, these studies reveal that LBN causes a male-specific stress inoculation effect against addiction-related phenotypes. Identifying factors that promote resilience to addiction may reveal novel treatment options for patients.
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http://dx.doi.org/10.1073/pnas.2020173118DOI Listing
February 2021

Showing NAFLD, as a key connector disease between Alzheimer's disease and diabetes via analysis of systems biology.

Gastroenterol Hepatol Bed Bench 2020 ;13(Suppl1):S89-S97

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: This study was designed to perform network analysis of Alzheimers҆ disease and diabetes and to find their correlation with each other and other diseases/pathways.

Background: Alzheimer's disease (AD) as a neurodegenerative disease and diabetes as a metabolic disease are two major health problems in the recent years. The recent studies have reported their correlation and same spreading pathways of these two diseases together, but details of this relation are not well known yet at molecular level..

Methods: In thermal proteome profiling (TPP) technique, after treatment of the extracted proteins by heat and drug concentration, the resulting proteins were analyzed by mass spectrometry. Enrichment analysis of these proteins led to development of AD and diabetes. First, corresponding genes for each disease were extracted from DisGeNET database and then, protein-protein interaction network was constructed for each of them using the search tool for retrieval of interacting genes and proteins (STRING). After analyzing these networks, hub-bottleneck nodes of networks were evaluated. Also, common nodes between two networks were extracted and used for further analysis.

Results: High correlation was found between AD and diabetes based on the existence of 40 common genes. Results of analyses revealed 14 genes in AD and 12 genes in diabetes as hub-bottleneck 7 of which were common including caspase 3 (CASP3), insulin-like growth factor 1 (IGF1), catalase (CAT), tumor necrosis factor (TNF), leptin (LEP), vascular endothelial growth factor A (VEGFA), and interleukin 6 ( IL-6).

Conclusion: Our results revealed a direct correlation between AD and diabetes and also a correlation between these two diseases and non-alcoholic fatty liver disease (NAFLD), suggesting that a small change in each of these three diseases can lead to development of any other diseases in the patients. Also, the enrichments exhibited the existence of common pathways between AD, diabetes, NAFLD, and male infertility.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881394PMC
January 2020

Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Biomolecules 2020 06 3;10(6). Epub 2020 Jun 3.

Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, 00270 Helsinki, Finland.

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.
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http://dx.doi.org/10.3390/biom10060850DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355924PMC
June 2020

UNaProd: A Universal Natural Product Database for of Iranian Traditional Medicine.

Evid Based Complement Alternat Med 2020 13;2020:3690781. Epub 2020 May 13.

Department of Traditional Medicine, School of Persian Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Background: Iranian traditional medicine (ITM) is a holistic medical system that uses a wide range of medicinal substances to treat disease. Reorganization and standardization of the data on ITM concepts is a necessity for optimal use of this rich source. In an initial step towards this goal, we created a database of ITM . . Primarily based on Makhzan al-Advieh, which is the most recent encyclopedia of in ITM with the largest number of monographs, a database of natural medicinal substances was created using both text mining methods and manual editing. UNaProd, a Universal Natural Product database for of ITM, is currently host to 2696 monographs, from herbal to animal to mineral compounds in 16 diverse attributes such as origin and scientific name. Currently, systems biology, and more precisely systems medicine and pharmacology, can be an aid in providing rationalizations for many traditional medicines and elucidating a great deal of knowledge they can offer to guide future research in medicine.

Conclusions: A database of is a stepping stone in creating a systems pharmacology platform of ITM that encompasses the relationships between the drugs, their targets, and diseases. UNaProd is hyperlinked to IrGO and CMAUP databases for and molecular features, respectively, and it is freely available at http://jafarilab.com/unaprod/.
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http://dx.doi.org/10.1155/2020/3690781DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7243028PMC
May 2020

The developmental origins of sex-biased expression in cardiac development.

Biol Sex Differ 2019 09 5;10(1):46. Epub 2019 Sep 5.

Fels Institute for Cancer Research, Lewis Katz School of Medicine, Temple University, 3400 N. Broad St, Philadelphia, PA, 19140, USA.

Background: Expression patterns between males and females vary in every adult tissue, even in organs with no conspicuous dimorphisms such as the heart. While studies of male and female differences have traditionally focused on the influence of sex hormones, these do not account for all the differences at the molecular and epigenetic levels. We previously reported that a substantial number of genes were differentially expressed in male and female mouse embryonic stem (ES) cells and revealed dose-dependent enhancer activity in response to Prdm14, a key pluripotency factor expressed more highly in female ES cells. In this work, we investigated the role of Prdm14 in establishing sex-specific gene expression networks. We surveyed the sex-specific landscape in early embryogenesis with special reference to cardiac development. We generated sex-specific co-expression networks from mouse ES cells, examined the presence of sex-specific chromatin domains, and analyzed previously published datasets from different developmental time points to characterize how sex-biased gene expression waxes and wanes to evaluate whether sex-biased networks are detectable throughout heart development.

Results: We performed ChIP-seq on male and female mouse ES cells to determine differences in chromatin status. Our study reveals sex-biased histone modifications, underscoring the potential for the sex chromosome complement to prime the genome differently in early development with consequences for later expression biases. Upon differentiation of ES cells to cardiac precursors, we found sex-biased expression of key transcription and epigenetic factors, some of which persisted from the undifferentiated state. Using network analyses, we also found that Prdm14 plays a prominent role in regulating a subset of dimorphic expression patterns. To determine whether sex-biased expression is present throughout cardiogenesis, we re-analyzed data from two published studies that sampled the transcriptomes of mouse hearts from 8.5 days post-coitum embryos to neonates and adults. We found sex-biased expression at every stage in heart development, and interestingly, identified a subset of genes that exhibit the same bias across multiple cardiogenic stages.

Conclusions: Overall, our results support the existence of sexually dimorphic gene expression profiles and regulatory networks at every stage of cardiac development, some of which may be established in early embryogenesis and epigenetically perpetuated.
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http://dx.doi.org/10.1186/s13293-019-0259-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6727560PMC
September 2019

Protein-protein interaction analysis of Alzheimer`s disease and NAFLD based on systems biology methods unhide common ancestor pathways.

Gastroenterol Hepatol Bed Bench 2018 ;11(1):27-33

Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: Analysis reconstruction networks from two diseases, NAFLD and Alzheimer`s diseases and their relationship based on systems biology methods.

Background: NAFLD and Alzheimer`s diseases are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on relation and same spreading pathways of these two diseases. In addition, they have some similar risk factors, exclusively lifestyle such as feeding, exercises and so on. Therefore, systems biology approach can help to discover their relationship.

Methods: DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. An R package used to define best centrality method. Finally, based on degree and Betweenness, hubs and bottleneck nodes were defined.

Results: Common genes between NAFLD and Alzheimer`s disease were 190 genes that used construct a network with STRING database. The resulting network contained 182 nodes and 2591 edges and comprises from four clusters. Enrichment of these clusters separately lead to carbohydrate metabolism, long chain fatty acid and regulation of JAK-STAT and IL-17 signaling pathways, respectively. Also seven genes selected as hub-bottleneck include: IL6, AKT1, TP53, TNF, JUN, VEGFA and PPARG. Enrichment of these proteins and their first neighbors in network by OMIM database lead to diabetes and obesity as ancestors of NAFLD and AD.

Conclusion: Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5849115PMC
January 2018

A systems biology analysis protein-protein interaction of NASH and IBD based on comprehensive gene information.

Gastroenterol Hepatol Bed Bench 2017 ;10(3):194-201

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: Analysis reconstruction networks from two diseases, IBD and NASH and their relationship, based on systems biology methods.

Background: IBD and NASH are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on co-existence of these two diseases. In addition, they have some similar risk factors such as age, obesity, and insulin resistance. Therefore, systems biology approach can help to discover their relationship.

Methods: DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. Based on degree and Betweenness, hubs and bottleneck nodes were defined.

Results: Common genes between IBD and NASH construct a network with 99 nodes. Common genes between IBD and NASH were extracted and imported to STRING database to construct PPI network. The resulting network contained 99 nodes and 333 edges. Five genes were selected as hubs: JAK2, TLR2, TP53, TLR4 and STAT3 and five genes were selected as bottleneck including: JAK2, TP53, AGT, CYP3A4 and TLR4. These genes were hubs in analysis network that was constructed from hubs of NASH and IBD networks.

Conclusion: Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5660269PMC
January 2017