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27 Publications visible to you, out of a total of 27

Abstract (Expand)

Mediterranean fever (FMF) is a systemic autoinflammatory disorder caused by inherited mutations in the MEFV (Mediterranean FeVer) gene, located on chromosome 16 (16p13.3) and encoding the pyrin protein. Despite the existing data on MEFV mutations, the exact mechanism of their effect on the development of the pathological processes leading to the spontaneous and recurrent autoinflammatory attacks observed in FMF, remains unclear. Induced pluripotent stem cells (iPSCs) are considered an important tool to study the molecular genetic mechanisms of various diseases due to their ability to differentiate into any cell type, including macrophages, which contribute to the development of FMF. In this study, we developed iPSCs from an Armenian patient with FMF carrying the M694V, p.(Met694Val) (c.2080A>G, rs61752717) pathogenic mutation in exon 10 of the MEFV gene. As a result of direct differentiation, macrophages expressing CD14 and CD45 surface markers were obtained. We found that the morphology of macrophages derived from iPSCs of a patient with the MEFV mutation significantly differed from that of macrophages derived from iPSCs of a healthy donor carrying the wild-type MEFV gene.

Authors: Elena V. Grigor’eva, Lana V. Karapetyan, Anastasia A. Malakhova, Sergey P. Medvedev, Julia M. Minina, Varduhi H. Hayrapetyan, Valentina S. Vardanyan, Suren M. Zakian, Arsen Arakelyan, Roksana Zakharyan

Date Published: 1st Jun 2024

Publication Type: Journal

Abstract (Expand)

The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little is known about the early dynamics of gene expression in these disorders due to their relatively late manifestation. To address this, we conducted a secondary analysis of post-mortem prefrontal cortex datasets using bioinformatics and machine learning techniques to identify differentially expressed gene modules associated with aging and the diseases, determine their time-perturbation points, and assess enrichment with expression quantitative trait loci (eQTL) genes. Our findings revealed early, mid, and late deregulation of expression of functional gene modules involved in neurodevelopment, plasticity, homeostasis, and immune response. This supports the hypothesis that multiple hits throughout life contribute to disease manifestation rather than a single early-life event. Moreover, the time-perturbed functional gene modules were associated with genetic loci affecting gene expression, highlighting the role of genetic factors in gene expression dynamics and the development of disease phenotypes. Our findings emphasize the importance of investigating time-dependent perturbations in gene expression before the age of onset in elucidating the molecular mechanisms of psychiatric disorders.

Authors: A. Arakelyan, S. Avagyan, A. Kurnosov, T. Mkrtchyan, G. Mkrtchyan, R. Zakharyan, K. R. Mayilyan, H. Binder

Date Published: 17th Feb 2024

Publication Type: Journal

Abstract (Expand)

The present study is the first in-depth research evaluating the genetic diversity and potential resistance of Armenian wild grapes utilizing DNA-based markers to understand the genetic signature of this unexplored germplasm. In the proposed research, five geographical regions with known viticultural history were explored. A total of 148 unique wild genotypes were collected and included in the study with 48 wild individuals previously collected as seed. A total of 24 nSSR markers were utilized to establish a fingerprint database to infer information on the population genetic diversity and structure. Three nSSR markers linked to the Ren1 locus were analyzed to identify potential resistance against powdery mildew. According to molecular fingerprinting data, the Armenian V. sylvestris gene pool conserves a high genetic diversity, displaying 292 different alleles with 12.167 allele per loci. The clustering analyses and diversity parameters supported eight genetic groups with 5.6% admixed proportion. The study of genetic polymorphism at the Ren1 locus revealed that 28 wild genotypes carried three R-alleles and 34 wild genotypes carried two R-alleles associated with PM resistance among analyzed 107 wild individuals. This gene pool richness represents an immense reservoir of under-explored genetic diversity and breeding potential. Therefore, continued survey and research efforts are crucial for the conservation, sustainable management, and utilization of Armenian wild grape resources in the face of emerging challenges in viticulture.

Authors: K. Margaryan, R. Topfer, B. Gasparyan, A. Arakelyan, O. Trapp, F. Rockel, E. Maul

Date Published: 25th Dec 2023

Publication Type: Journal

Abstract (Expand)

INTRODUCTION: The escalating challenge of climate change has underscored the critical need to understand cold defense mechanisms in cultivated grapevine Vitis vinifera. Temperature variations can affect the growth and overall health of vine. METHODS: We used Self Organizing Maps machine learning method to analyze gene expression data from leaves of five Vitis vinifera cultivars each treated by four different temperature conditions. The algorithm generated sample-specific "portraits" of the normalized gene expression data, revealing distinct patterns related to the temperature conditions applied. RESULTS: Our analysis unveiled a connection with vitamin B1 (thiamine) biosynthesis, suggesting a link between temperature regulation and thiamine metabolism, in agreement with thiamine related stress response established in Arabidopsis before. Furthermore, we found that epigenetic mechanisms play a crucial role in regulating the expression of stress-responsive genes at low temperatures in grapevines. DISCUSSION: Application of Self Organizing Maps portrayal to vine transcriptomics identified modules of coregulated genes triggered under cold stress. Our machine learning approach provides a promising option for transcriptomics studies in plants.

Authors: T. Konecny, M. Nikoghosyan, H. Binder

Date Published: 21st Dec 2023

Publication Type: Journal

Abstract (Expand)

Most high throughput genomic data analysis pipelines currently rely on over-representation or gene set enrichment analysis (ORA/GSEA) approaches for functional analysis. In contrast, topology-based pathway analysis methods, which offer a more biologically informed perspective by incorporating interaction and topology information, have remained underutilized and inaccessible due to various limiting factors. These methods heavily rely on the quality of pathway topologies and often utilize predefined topologies from databases without assessing their correctness. To address these issues and make topology-aware pathway analysis more accessible and flexible, we introduce the PSF (Pathway Signal Flow) toolkit R package. Our toolkit integrates pathway curation and topology-based analysis, providing interactive and command-line tools that facilitate pathway importation, correction, and modification from diverse sources. This enables users to perform topology-based pathway signal flow analysis in both interactive and command-line modes. To showcase the toolkit's usability, we curated 36 KEGG signaling pathways and conducted several use-case studies, comparing our method with ORA and the topology-based signaling pathway impact analysis (SPIA) method. The results demonstrate that the algorithm can effectively identify ORA enriched pathways while providing more detailed branch-level information. Moreover, in contrast to the SPIA method, it offers the advantage of being cut-off free and less susceptible to the variability caused by selection thresholds. By combining pathway curation and topology-based analysis, the PSF toolkit enhances the quality, flexibility, and accessibility of topology-aware pathway analysis. Researchers can now easily import pathways from various sources, correct and modify them as needed, and perform detailed topology-based pathway signal flow analysis. In summary, our PSF toolkit offers an integrated solution that addresses the limitations of current topology-based pathway analysis methods. By providing interactive and command-line tools for pathway curation and topology-based analysis, we empower researchers to conduct comprehensive pathway analyses across a wide range of applications.

Authors: S. Hakobyan, A. Stepanyan, L. Nersisyan, H. Binder, A. Arakelyan

Date Published: 8th Sep 2023

Publication Type: Journal

Abstract (Expand)

BACKGROUND: Long-term environmental exposure to metals leads to epigenetic changes and may increase risks to human health. The relationship between the type and level of metal exposure and epigenetic changes in subjects exposed to high concentrations of metals in the environment is not yet clear. The aim of our study is to find the possible association of environmental long-term exposure to metals with DNA methylation changes of genes related to immune response and carcinogenesis. We investigated the association of plasma levels of 21 essential and non-essential metals detected by ICP-MS and the methylation level of 654 CpG sites located on NFKB1, CDKN2A, ESR1, APOA5, IGF2 and H19 genes assessed by targeted bisulfite sequencing in a cohort of 40 subjects living near metal mining area and 40 unexposed subjects. Linear regression was conducted to find differentially methylated positions with adjustment for gender, age, BMI class, smoking and metal concentration. RESULTS: In the metal-exposed group, five CpGs in the NFKB1 promoter region were hypomethylated compared to unexposed group. Four differentially methylated positions (DMPs) were associated with multiple metals, two of them are located on NFKB1 gene, and one each on CDKN2A gene and ESR1 gene. Two DMPs located on NFKB1 (chr4:102500951, associated with Be) and IGF2 (chr11:2134198, associated with U) are associated with specific metal levels. The methylation status of the seven CpGs located on NFKB1 (3), ESR1 (2) and CDKN2A (2) positively correlated with plasma levels of seven metals (As, Sb, Zn, Ni, U, I and Mn). CONCLUSIONS: Our study revealed methylation changes in NFKB1, CDKN2A, IGF2 and ESR1 genes in individuals with long-term human exposure to metals. Further studies are needed to clarify the effect of environmental metal exposure on epigenetic mechanisms and pathways involved.

Authors: A. Stepanyan, A. Petrackova, S. Hakobyan, J. Savara, S. Davitavyan, E. Kriegova, A. Arakelyan

Date Published: 7th Aug 2023

Publication Type: Journal

Abstract (Expand)

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Authors: O. Ashekyan, N. Shahbazyan, Y. Bareghamyan, A. Kudryavzeva, D. Mandel, M. Schmidt, H. Loeffler-Wirth, M. Uduman, D. Chand, D. Underwood, G. Armen, A. Arakelyan, L. Nersisyan, H. Binder

Date Published: 28th Jul 2023

Publication Type: Journal

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