scholarly journals The molecular pathophysiology of mood disorders: from the analysis of single molecular layers to multi-omic integration.

2021 ◽  
Author(s):  
Amazigh Mokhtari ◽  
Baptiste Porte ◽  
Raoul Belzeaux ◽  
Bruno Etain ◽  
El Cherif Ibrahim ◽  
...  
Keyword(s):  
Mood Disorders ◽  
Molecular Mechanisms ◽  
Biological Data ◽  
Molecular Processes ◽  
Omics Integration ◽  
Molecular Pathophysiology ◽  
Molecular Layers ◽  
Future Work ◽  
New Algorithms ◽  
Generation Sequencing

Next-generation sequencing now enables the rapid and affordable production of reliable biological data at multiple molecular levels, collectively referred to as “omics”. To maximize the potential for discovery, computational biologists have created and adapted integrative multiomic analytical methods. When applied to diseases with traceable pathophysiology such as cancer, these new algorithms and statistical approaches have enabled the discovery of clinically relevant molecular mechanisms and biomarkers. In contrast, these methods have been much less applied to the field of molecular psychiatry, although diagnostic and prognosticbiomarkers are similarly needed. In the present review, we first briefly summarize main findings from two decades of studies that investigated single molecular processes in relation to mood disorders. Then, we conduct a systematic review of multi-omic strategies that have been proposed and used more recently. We also list databases and types of data available to researchers for future work. Finally, we present the newest methodologies that have been employed for multi-omics integration in other medical fields, and discuss their potential for molecular psychiatry studies.

Integration of Multi-omics Data Using Probabilistic Graph Models and External Knowledge

2021 ◽  
Vol 16 ◽  
Author(s):  
Bridget A. Tripp ◽  
Hasan H. Otu
Keyword(s):  
Information Integration ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Biological Data ◽  
Biological Information ◽  
Functional Networks ◽  
Omics Data ◽  
Metabolomics Data ◽  
External Knowledge ◽  
Omics Integration

Background: High-throughput sequencing technologies have revolutionized the ability to perform systems-level biology and elucidate molecular mechanisms of disease through the comprehensive characterization of different layers of biological information. Integration of these heterogeneous layers can provide insight into the underlying biology but is challenged by modeling complex interactions. Objective: We introduce OBaNK: omics integration using Bayesian networks and external knowledge, an algorithm to model interactions between heterogeneous high-dimensional biological data to elucidate complex functional clusters and emergent relationships associated with an observed phenotype. Method: Using Bayesian network learning, we modeled the statistical dependencies and interactions between lipidomics, proteomics, and metabolomics data. The strength of a learned interaction between molecules was altered based on external knowledge. Results : Networks learned from synthetic datasets based on real pathways achieved an average area under the curve score of ~0.85, an improvement of ~0.23 from baseline methods. When applied to real multi-omics data collected during pregnancy, five distinct functional networks of heterogeneous biological data were identified, and the results were compared to other multi-omics integration approaches. Conclusion: OBaNK successfully improved the accuracy of learning interaction networks from data integrating external knowledge, identified heterogeneous functional networks from real data, and suggested potential novel interactions associated with the phenotype. These findings can guide future hypothesis generation. OBaNK source code is available at https://github.com/bridgettripp/OBaNK.git, and a graphical user interface is available at http://otulab.unl.edu/OBaNK.

Lighting a path: genetic studies pinpoint neurodevelopmental mechanisms in autism and related disorders

2012 ◽  
Vol 14 (3) ◽  
pp. 239-252
Keyword(s):  
Molecular Mechanisms ◽  
Protein Localization ◽  
Regulation Of Gene Expression ◽  
Neuronal Cell ◽  
Mrna Splicing ◽  
Genetic Mutations ◽  
Scaffolding Proteins ◽  
Molecular Processes ◽  
Genetic Studies ◽  
Novel Treatments

In this review, we outline critical molecular processes that have been implicated by discovery of genetic mutations in autism. These mechanisms need to be mapped onto the neurodevelopment step(s) gone awry that may be associated with cause in autism. Molecular mechanisms include: (i) regulation of gene expression; (ii) pre-mRNA splicing; (iii) protein localization, translation, and turnover; (iv) synaptic transmission; (v) cell signaling; (vi) the functions of cytoskeletal and scaffolding proteins; and (vii) the function of neuronal cell adhesion molecules. While the molecular mechanisms appear broad, they may converge on only one of a few steps during neurodevelopment that perturbs the structure, function, and/or plasticity of neuronal circuitry. While there are many genetic mutations involved, novel treatments may need to target only one of few developmental mechanisms.

scholarly journals Next Generation Sequencing for the Prediction of the Antibiotic Resistance in Helicobacter pylori: A Literature Review

Antibiotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 437
Author(s):  
Ilaria Maria Saracino ◽  
Matteo Pavoni ◽  
Angelo Zullo ◽  
Giulia Fiorini ◽  
Tiziana Lazzarotto ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Next Generation Sequencing ◽  
Literature Review ◽  
Molecular Mechanisms ◽  
World Health ◽  
Next Generation ◽  
Culture Methods ◽  
Phenotypic Resistance ◽  
H Pylori ◽  
Generation Sequencing

Background and aims: Only a few antimicrobials are effective against H. pylori, and antibiotic resistance is an increasing problem for eradication therapies. In 2017, the World Health Organization categorized clarithromycin resistant H. pylori as a “high-priority” bacterium. Standard antimicrobial susceptibility testing can be used to prescribe appropriate therapies but is currently recommended only after the second therapeutic failure. H. pylori is, in fact, a “fastidious” microorganism; culture methods are time-consuming and technically challenging. The advent of molecular biology techniques has enabled the identification of molecular mechanisms underlying the observed phenotypic resistance to antibiotics in H. pylori. The aim of this literature review is to summarize the results of original articles published in the last ten years, regarding the use of Next Generation Sequencing, in particular of the whole genome, to predict the antibiotic resistance in H. pylori.Methods: a literature research was made on PubMed. The research was focused on II and III generation sequencing of the whole H. pylori genome. Results: Next Generation Sequencing enabled the detection of novel, rare and complex resistance mechanisms. The prediction of resistance to clarithromycin, levofloxacin and amoxicillin is accurate; for other antimicrobials, such as metronidazole, rifabutin and tetracycline, potential genetic determinants of the resistant status need further investigation.

scholarly journals MicroRNAs from Snellenius manilae bracovirus regulate innate and cellular immune responses of its host Spodoptera litura

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Cheng-Kang Tang ◽  
Chih-Hsuan Tsai ◽  
Carol-P. Wu ◽  
Yu-Hsien Lin ◽  
Sung-Chan Wei ◽  
...  
Keyword(s):  
Immune Responses ◽  
Spodoptera Litura ◽  
Molecular Mechanisms ◽  
Innate Immune ◽  
Sequencing Analysis ◽  
Innate Immune Responses ◽  
Cellular Immune Responses ◽  
Next Generation Sequencing Analysis ◽  
Cellular Immune ◽  
Generation Sequencing

AbstractTo avoid inducing immune and physiological responses in insect hosts, parasitoid wasps have developed several mechanisms to inhibit them during parasitism, including the production of venom, specialized wasp cells, and symbioses with polydnaviruses (PDVs). These mechanisms alter the host physiology to give the wasp offspring a greater chance of survival. However, the molecular mechanisms for most of these alterations remain unclear. In the present study, we applied next-generation sequencing analysis and identified several miRNAs that were encoded in the genome of Snellenius manilae bracovirus (SmBV), and expressed in the host larvae, Spodoptera litura, during parasitism. Among these miRNAs, SmBV-miR-199b-5p and SmBV-miR-2989 were found to target domeless and toll-7 in the host, which are involved in the host innate immune responses. Microinjecting the inhibitors of these two miRNAs into parasitized S. litura larvae not only severely decreased the pupation rate of Snellenius manilae, but also restored the phagocytosis and encapsulation activity of the hemocytes. The results demonstrate that these two SmBV-encoded miRNAs play an important role in suppressing the immune responses of parasitized hosts. Overall, our study uncovers the functions of two SmBV-encoded miRNAs in regulating the host innate immune responses upon wasp parasitism.

scholarly journals Applying graph database technology for analyzing perturbed co-expression networks in cancer

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Claire M Simpson ◽  
Florian Gnad
Keyword(s):  
Relational Databases ◽  
Molecular Mechanisms ◽  
Biological Data ◽  
Database Management System ◽  
Graph Database ◽  
Graph Databases ◽  
Graph Representations ◽  
Rnaseq Data ◽  
Database Technology ◽  
Speed Accuracy

Abstract Graph representations provide an elegant solution to capture and analyze complex molecular mechanisms in the cell. Co-expression networks are undirected graph representations of transcriptional co-behavior indicating (co-)regulations, functional modules or even physical interactions between the corresponding gene products. The growing avalanche of available RNA sequencing (RNAseq) data fuels the construction of such networks, which are usually stored in relational databases like most other biological data. Inferring linkage by recursive multiple-join statements, however, is computationally expensive and complex to design in relational databases. In contrast, graph databases store and represent complex interconnected data as nodes, edges and properties, making it fast and intuitive to query and analyze relationships. While graph-based database technologies are on their way from a fringe domain to going mainstream, there are only a few studies reporting their application to biological data. We used the graph database management system Neo4j to store and analyze co-expression networks derived from RNAseq data from The Cancer Genome Atlas. Comparing co-expression in tumors versus healthy tissues in six cancer types revealed significant perturbation tracing back to erroneous or rewired gene regulation. Applying centrality, community detection and pathfinding graph algorithms uncovered the destruction or creation of central nodes, modules and relationships in co-expression networks of tumors. Given the speed, accuracy and straightforwardness of managing these densely connected networks, we conclude that graph databases are ready for entering the arena of biological data.

scholarly journals Genomics of ageing in twins

2014 ◽  
Vol 73 (4) ◽  
pp. 526-531 ◽  
Author(s):  
Massimo Mangino
Keyword(s):  
Molecular Mechanisms ◽  
Twin Studies ◽  
Later Life ◽  
Twin Design ◽  
The Past ◽  
Human Ageing ◽  
Classical Twin Design ◽  
Environmental Component ◽  
Early Life Events ◽  
Generation Sequencing

Ageing is a complex multifactorial process, reflecting the progression of all degenerative pathways within an organism. Due to the increase of life expectancy, in recent years, there is a pressing need to identify early-life events and risk factors that determine health outcomes in later life. So far, genetic variation only explains ~20–25 % of the variability of human survival to age 80+. This clearly implies that other factors (environmental, epigenetic and lifestyle) contribute to lifespan and the rate of healthy ageing within an individual. Twin studies in the past two decades proved to be a very powerful tool to discriminate the genetic from the environmental component. The aim of this review is to describe the basic concepts of the twin study design and to report some of the latest studies in which high-throughput technologies (e.g. genome/epigenome-wide assay, next generation sequencing, MS metabolic profiling) combined with the classical twin design have been applied to the analysis of novel ‘omics’ to further understand the molecular mechanisms of human ageing.

scholarly journals Lateralized and Segmental Overgrowth in Children

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6166
Author(s):  
Alessandro Mussa ◽  
Diana Carli ◽  
Simona Cardaropoli ◽  
Giovanni Battista Ferrero ◽  
Nicoletta Resta
Keyword(s):  
Molecular Mechanisms ◽  
Management Strategies ◽  
Tissue Growth ◽  
Body Region ◽  
Molecular Defects ◽  
Embryonic Tissues ◽  
Cellular Signaling Pathway ◽  
Segmental Overgrowth ◽  
Generation Sequencing ◽  
Specific Management

Congenital disorders of lateralized or segmental overgrowth (LO) are heterogeneous conditions with increased tissue growth in a body region. LO can affect every region, be localized or extensive, involve one or several embryonic tissues, showing variable severity, from mild forms with minor body asymmetry to severe ones with progressive tissue growth and related relevant complications. Recently, next-generation sequencing approaches have increased the knowledge on the molecular defects in LO, allowing classifying them based on the deranged cellular signaling pathway. LO is caused by either genetic or epigenetic somatic anomalies affecting cell proliferation. Most LOs are classifiable in the Beckwith–Wiedemann spectrum (BWSp), PI3KCA/AKT-related overgrowth spectrum (PROS/AROS), mosaic RASopathies, PTEN Hamartoma Tumor Syndrome, mosaic activating variants in angiogenesis pathways, and isolated LO (ILO). These disorders overlap over common phenotypes, making their appraisal and distinction challenging. The latter is crucial, as specific management strategies are key: some LO is associated with increased cancer risk making imperative tumor screening since childhood. Interestingly, some LO shares molecular mechanisms with cancer: recent advances in tumor biological pathway druggability and growth downregulation offer new avenues for the treatment of the most severe and complicated LO.

scholarly journals Molecular Inverse Comorbidity between Alzheimer’s disease and Lung Cancer: new insights from Matrix Factorization

2019 ◽  
Author(s):  
Alessandro Greco ◽  
Jon Sanchez Valle ◽  
Vera Pancaldi ◽  
Anaïs Baudot ◽  
Emmanuel Barillot ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Matrix Factorization ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Biological Data ◽  
Biological Data Analysis ◽  
Specific Factors ◽  
Molecular Bases

AbstractMatrix Factorization (MF) is an established paradigm for large-scale biological data analysis with tremendous potential in computational biology.We here challenge MF in depicting the molecular bases of epidemiologically described Disease-Disease (DD) relationships. As use case, we focus on the inverse comorbidity association between Alzheimer’s disease (AD) and lung cancer (LC), described as a lower than expected probability of developing LC in AD patients. To the day, the molecular mechanisms underlying DD relationships remain poorly explained and their better characterization might offer unprecedented clinical opportunities.To this goal, we extend our previously designed MF-based framework for the molecular characterization of DD relationships. Considering AD-LC inverse comorbidity as a case study, we highlight multiple molecular mechanisms, among which the previously identified immune system and mitochondrial metabolism. We then discriminate mechanisms specific to LC from those shared with other cancers through a pancancer analysis. Additionally, new candidate molecular players, such as Estrogen Receptor (ER), CDH1 and HDAC, are pinpointed as factors that might underlie the inverse relationship, opening the way to new investigations. Finally, some lung cancer subtype-specific factors are also detected, suggesting the existence of heterogeneity across patients also in the context of inverse comorbidity.

scholarly journals Modeling the developmental origins of pediatric cancer to improve patient outcomes

2021 ◽  
Vol 14 (2) ◽  
Author(s):  
James F. Amatruda
Keyword(s):  
Patient Outcomes ◽  
Pediatric Cancer ◽  
Molecular Mechanisms ◽  
Cellular Transformation ◽  
Genetic Changes ◽  
Current Therapies ◽  
Physician Scientist ◽  
Improve Patient ◽  
Generation Sequencing

ABSTRACT In the treatment of children and adolescents with cancer, multimodal approaches combining surgery, chemotherapy and radiation can cure most patients, but may cause lifelong health problems in survivors. Current therapies only modestly reflect increased knowledge about the molecular mechanisms of these cancers. Advances in next-generation sequencing have provided unprecedented cataloging of genetic aberrations in tumors, but understanding how these genetic changes drive cellular transformation, and how they can be effectively targeted, will require multidisciplinary collaboration and preclinical models that are truly representative of the in vivo environment. Here, I discuss some of the key challenges in pediatric cancer from my perspective as a physician-scientist, and touch on some promising new approaches that have the potential to transform our understanding of these diseases.

scholarly journals Updates on Old and Weary Haematopoiesis

2018 ◽  
Vol 19 (9) ◽  
pp. 2567 ◽  
Author(s):  
Joanna Konieczny ◽  
Lorena Arranz
Keyword(s):  
Molecular Mechanisms ◽  
The Elderly ◽  
Progressive Decline ◽  
Cell Functions ◽  
Age Related ◽  
High Incidence ◽  
Hsc Niche ◽  
Blood Formation ◽  
External Stimuli ◽  
Future Work

Blood formation, or haematopoiesis, originates from haematopoietic stem cells (HSCs), whose functions and maintenance are regulated in both cell- and cell non-autonomous ways. The surroundings of HSCs in the bone marrow create a specific niche or microenvironment where HSCs nest that allows them to retain their unique characteristics and respond rapidly to external stimuli. Ageing is accompanied by reduced regenerative capacity of the organism affecting all systems, due to the progressive decline of stem cell functions. This includes blood and HSCs, which contributes to age-related haematological disorders, anaemia, and immunosenescence, among others. Furthermore, chronological ageing is characterised by myeloid and platelet HSC skewing, inflammageing, and expanded clonal haematopoiesis, which may be the result of the accumulation of preleukaemic lesions in HSCs. Intriguingly, haematological malignancies such as acute myeloid leukaemia have a high incidence among elderly patients, yet not all individuals with clonal haematopoiesis develop leukaemias. Here, we discuss recent work on these aspects, their potential underlying molecular mechanisms, and the first cues linking age-related changes in the HSC niche to poor HSC maintenance. Future work is needed for a better understanding of haematopoiesis during ageing. This field may open new avenues for HSC rejuvenation and therapeutic strategies in the elderly.

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