Filter and export

Publications

What is a Publication?
126 Publications visible to you, out of a total of 126
The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health.

Abstract (Expand)

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and … epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration. Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features. Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes. Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications. Keywords: age; gene expression; immune response; lifestyle and obesity; omics and phenotype integration; self-organizing maps; subtypes. Copyright © 2020 Schmidt, Hopp, Arakelyan, Kirsten, Engel, Wirkner, Krohn, Burkhardt, Thiery, Loeffler, Loeffler-Wirth and Binder.

Authors: Maria Schmidt, Lydia Hopp, Arsen Arakelyan, Holger Kirsten, Christoph Engel, Kerstin Wirkner, Knut Krohn, Ralph Burkhardt, Joachim Thiery, Markus Loeffler, Henry Loeffler-Wirth, Hans Binder

Date Published: 30th Oct 2020

Publication Type: Journal

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science.

Abstract (Expand)

Background: oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and … visualization. Results: These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns. Conclusion: The oposSOM-Browser makes available interactive data browsing for five transcriptome data sets of cancer (melanomas, B-cell lymphomas, gliomas) and of peripheral blood (sepsis and healthy individuals) at www.izbi.uni-leipzig.de/opossom-browser . Keywords: Interactive data analysis; Results browser; Transcriptomics.

Authors: Henry Loeffler-Wirth, Jasmin Reikowski, Siras Hakobyan, Jonas Wagner, Hans Binder

Date Published: 19th Oct 2020

Publication Type: Journal

SOMmelier-Intuitive Visualization of the Topology of Grapevine Genome Landscapes Using Artificial Neural Networks.

Abstract (Expand)

BACKGROUND: Whole-genome studies of vine cultivars have brought novel knowledge about the diversity, geographical relatedness, historical origin and dissemination, phenotype associations and genetic … markers. METHOD: We applied SOM (self-organizing maps) portrayal, a neural network-based machine learning method, to re-analyze the genome-wide Single Nucleotide Polymorphism (SNP) data of nearly eight hundred grapevine cultivars. The method generates genome-specific data landscapes. Their topology reflects the geographical distribution of cultivars, indicates paths of cultivar dissemination in history and genome-phenotype associations about grape utilization. RESULTS: The landscape of vine genomes resembles the geographic map of the Mediterranean world, reflecting two major dissemination paths from South Caucasus along a northern route via Balkan towards Western Europe and along a southern route via Palestine and Maghreb towards Iberian Peninsula. The Mediterranean and Black Sea, as well as the Pyrenees, constitute barriers for genetic exchange. On the coarsest level of stratification, cultivars divide into three major groups: Western Europe and Italian grapes, Iberian grapes and vine cultivars from Near East and Maghreb regions. Genetic landmarks were associated with agronomic traits, referring to their utilization as table and wine grapes. Pseudotime analysis describes the dissemination of grapevines in an East to West direction in different waves of cultivation. CONCLUSION: In analogy to the tasks of the wine waiter in gastronomy, the sommelier, our 'SOMmelier'-approach supports understanding the diversity of grapevine genomes in the context of their geographic and historical background, using SOM portrayal. It offers an option to supplement vine cultivar passports by genome fingerprint portraits.

Authors: M. Nikoghosyan, M. Schmidt, K. Margaryan, H. Loeffler-Wirth, A. Arakelyan, H. Binder

Date Published: 17th Jul 2020

Publication Type: Journal

Spectrum of TP53 Mutations in BRCA1/2 Associated High-Grade Serous Ovarian Cancer

Abstract (Expand)

Objective: Mutations in TP53 lead to loss of function (LOF) or gain of function (GOF) of the corresponding protein p53 and produce a different effect on the tumor. Our goal was to determine the spectrum … of somatic TP53 variants in BRCA1/2 associated high-grade serous ovarian cancer (HGSOC). Methods: The population under study comprised of HGSOCs with pathogenic variants in BRCA1 (n = 78) or BRCA2 (n = 21). Only chemo-naive and platinum-sensitive patients were included in this study. The case group of the IARC database (n = 1249) with HGSOC not stratified by BRCA status was used as a reference. A custom NGS panel was used for sequencing TP53 and mutational hot-spots of other genes, and p53 expression was evaluated by immunohistochemistry for 68 cases of HGSOCs. Results: Somatic TP53 variants (95) or inhibition of wild-type p53 expression (3) were observed in 98 cases. The sample with normal p53 had CDKNA1 variants. The frequency of truncating variants was significantly higher than in the reference cohort (30.3 vs. 21.0%, p = 0.01). Most of the samples (41/68) demonstrated low (or absent) expression of p53, and 17 samples overexpressed p53. LOH was typical for TP53 nonsense variants (14/15). In total, 68/95 samples were LOH positive and showed LOH in all tumorous cells, thus indicating the driver effect of TP53 mutations. Three specimens had KRAS, BAX, APC, and CTNNB1 subclones variants. Conclusion: High frequency of TP53 truncating variants, the low expression of mutant p53, and low incidence of oncogene mutations show potential GOF properties of p53 to be poorly represented in BRCA1/2 associated HGSOC. Keywords: BRCA1/2 carriers; TP53 somatic mutations; gain of function; loss of function; ovarian cancer; p53 expression.

Authors: Ulyana A. Boyarskikh, L. F. Gulyaeva, A. M. Avdalyan, A. A. Kechin, E. A. Khrapov, D. G. Lazareva, N. E. Kushlinskii, A. Melkonyan, A. Arakelyan, Maxim Leonidovich Filipenko

Date Published: 16th Jul 2020

Publication Type: Journal

Association of Genetic Variants of Dopamine and Serotonin In Schizophrenia

Abstract (Expand)

Background Several studies indicated that antipsychotic treatment response and side effect manifestation can be different due to inter-individual variability in genetic variations. Aim of the study … Here we perform a case-control study to explore a potential association between schizophrenia and variants within the antipsychotic drug molecular targets (DRD1, DRD2, DRD3, HTR2A, HTR6) and metabolizing enzymes (CYP2D6, COMT) genes in Armenian population including also analysis of their possible relationship with disease clinical symptoms. Methods A total of 18 SNPs was studied in patients with schizophrenia (n = 78) and healthy control subjects (n = 77) using MassARRAY genotyping. Results: We found that two studied genetic variants, namely DRD2 rs4436578*C and HTR2A rs6314*A are underrepresented in the group of patients compared to healthy subjects. After the correction for multiple testing, the rs4436578*C variant remained significant while the rs6314*A reported borderline significance. No significant differences in minor allele frequencies for other studied variants were identified. Also, a relationship between the genotypes and age of onset as well as disease duration has been detected. Conclusions The DRD2 rs4436578*C genetic variant might have protective role against schizophrenia, at least in Armenians.

Authors: Roksana Zakharyan, Hovsep Ghazaryan, Lenka Kocourkova, Andranik Chavushyan, Artur Mkrtchyan, Veronika Zizkova, Arsen Arakelyan, Martin Petrek

Date Published: 16th Dec 2019

Publication Type: Journal

Transcriptome-Guided Drug Repositioning.

Abstract (Expand)

Drug repositioning can save considerable time and resources and significantly speed up the drug development process. The increasing availability of drug action and disease-associated transcriptome data … makes it an attractive source for repositioning studies. Here, we have developed a transcriptome-guided approach for drug/biologics repositioning based on multi-layer self-organizing maps (ml-SOM). It allows for analyzing multiple transcriptome datasets by segmenting them into layers of drug action- and disease-associated transcriptome data. A comparison of expression changes in clusters of functionally related genes across the layers identifies "drug target" spots in disease layers and evaluates the repositioning possibility of a drug. The repositioning potential for two approved biologics drugs (infliximab and brodalumab) confirmed the drugs' action for approved diseases (ulcerative colitis and Crohn's disease for infliximab and psoriasis for brodalumab). We showed the potential efficacy of infliximab for the treatment of sarcoidosis, but not chronic obstructive pulmonary disease (COPD). Brodalumab failed to affect dysregulated functional gene clusters in Crohn's disease (CD) and systemic juvenile idiopathic arthritis (SJIA), clearly indicating that it may not be effective in the treatment of these diseases. In conclusion, ml-SOM offers a novel approach for transcriptome-guided drug repositioning that could be particularly useful for biologics drugs.

Authors: A. Arakelyan, L. Nersisyan, M. Nikoghosyan, S. Hakobyan, A. Simonyan, L. Hopp, H. Loeffler-Wirth, H. Binder

Date Published: 12th Dec 2019

Publication Type: Journal

Expression of micro-RNAs miR-31, miR-146a, miR-181c and miR-155 and their target gene IL-2 are altered in schizophrenia: a case-control study

Abstract (Expand)

Background: Schizophrenia is a severe psychiatric disorder with a heterogeneous clinical phenotype. The association of interleukins and other cytokines and their receptors with schizophrenia has been … previously reported. Additionally, a number of studies have reported altered mico-RNA (miRNA) expression in schizophrenia and other psychiatric disorders. The aim of our study was to explore the possible association of miR-31, miR-146a, miR-181c and miR-155 with schizophrenia pathogenesis, as well as their link to IL2 gene expression in disease. Methods: For this case-control study, 225 patients with paranoid schizophrenia and 225 sex- and age-matched controls with no family history of schizophrenia were recruited. The expression of studied miRNAs and the IL2 gene was measured using qPCR. DNA samples of all patients and controls were genotyped for IL2 rs2069778 single nucleotide polymorphism (SNP) using PCR with sequence specific primers (PCR-SSP). Statistical analyses include the Mann-Whitney U-test and Fischer’s exact test. Results: All studied miRNAs were over-expressed in schizophrenic patients IL2 gene expression was down-regulated in schizophrenic patients. The IL2 rs2069778 SNP is not associated with schizophrenia but regulates expression of the IL2 gene. Conclusions: Over-expression of studied miRNAs and down-regulation of IL2 gene expression may be considered as genetic risk factors for chronic schizophrenia. Abnormalities in studied miRNA expressions result in the deregulation of the T-cell receptor signaling pathway in schizophrenia.

Authors: Hovsep Ghazaryan, Roksana Zakharyan, Martin Petrek, Zdenka Navratilova, Andranik Chavushyan, Eva Novosadova, Arsen Arakelyan

Date Published: 10th Dec 2019

Publication Type: Journal

Powered by
 (v.1.15.0-main)
About ArmLifeBank | Funding and Programmes | Credits | Terms & Conditions | Privacy Policy | Cookie preferences
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH