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FHAIVE

Finnish Hub for Development and Validation of Integrated Approaches

Publications

2026

2025

  • Unmasking metabolic disruptors: The NEMESIS project's quest for Novel Biomarkers, Evidence on Adverse Effects, and Efficient Methodologies

    Metabolism disrupting chemicals (MDCs) elicit negative effects on metabolically active organs such as the liver and the pancreas, altering normal metabolic processes. Chemicals that are known, or suspected MDCs include compounds found in everyday consumer products and food, making low-dose, continuous exposure inevitable for humans. Through the discovery of chemically induced metabolic disruption, a concern has surfaced whether and how MDCs impact human health and the development of metabolic...

  • CHIASMA: Advancing chemicals and materials safety and sustainability assessments through innovative integration of in vitro and in silico (new approach) methodologies

    Traditional in vivo methodologies have long formed the foundation of chemical and material safety assessment, yet they are increasingly inadequate to meet modern regulatory, ethical, and sustainability demands. These conventional approaches are resource-intensive, ethically questionable, and often fail to accurately predict human or environmental toxicity, particularly for emerging pollutants such as PFAS, (nano-) pesticides, and 2D materials. In response, the EU has launched initiatives like...

  • BMDx2: A Tool for Integrating Toxicogenomics-Based Dose-Dependency Analysis and AOP-Based Mechanistic Insights

    Despite the advent of mechanistic toxicology using omics data to link molecular perturbations with systemic outcomes, regulatory toxicology still lacks the application of mechanism-anchored metrics from such data. This is partially because traditional gene-centric analysis often falls short of linking molecular changes to adverse outcomes. To address this gap, BMDx2, an open-source tool that transforms multi-dose toxicogenomics datasets into quantitative, mechanistic evidence for human chemical...

  • OpTiles: an R package for adaptive tiling and methylation variability profiling

    SUMMARY: OpTiles is an R package that dynamically defines tiling windows based on the distribution of sequenced CpGs, addressing the limitations of traditional fixed-tiling approaches in targeted methylation datasets. By integrating CpG density with intra-region methylation variability, it provides a reliability metric and extended functionality for annotating, prioritizing, and interpreting complex methylation data.

  • Curated and harmonised transcriptomics datasets of interstitial lung diseases

    This study provides manually curated and homogenised transcriptomics data of interstitial lung disease (ILD) patients retrieved from the NCBI Gene Expression Omnibus and European Nucleotide Archive repositories. The compendium includes 30 transcriptomics datasets generated with DNA microarrays and RNA sequencing (RNA-seq) technologies for a total of 1371 samples. All the datasets underwent metadata curation and harmonisation, data quality check, and preprocessing with standardised procedures....

  • Comparison of Lung Inflammatory and Transcriptional Responses in Mice and Rats Following Pulmonary Exposure to a Fiber Paradigm-Compatible and Non-Compatible MWCNT

    Inhalation of multi-walled carbon nanotubes (MWCNTs) poses potential health risks due to their structural similarity to asbestos and their ability to induce chronic lung inflammation, fibrosis, and lung cancer in animal models. This study investigated the pulmonary inflammatory and transcriptomic responses of two distinct MWCNTs-NM-401 (long, rigid) and NM-403 (short, thin)-in rats and mice using intratracheal instillation at matched dose levels at two post-exposure time points. Both MWCNTs...

  • Wisdom of Crowds for Supporting the Safety Evaluation of Nanomaterials

    The development of new approach methodologies (NAMs) to replace current in vivo testing for the safety assessment of engineered nanomaterials (ENMs) is hindered by the scarcity of validated experimental data for many ENMs. We introduce a framework to address this challenge by harnessing the collective expertise of professionals from multiple complementary and related fields ("wisdom of crowds" or WoC). By integrating expert insights, we aim to fill data gaps and generate consensus concern scores...

  • Two roads to fibrosis: Contrasting initiating mechanisms of Bleomycin and TGFβ-1 in lung fibroblasts

    Pulmonary fibrosis, a progressive and debilitating disease, presents a significant global health challenge. Even though often idiopathic, drug-induced fibrosis is increasing its incidence. Traditional chemical safety assessments, relying on apical endpoints from in-vivo models, are limited in capturing the early molecular events initiating fibrosis, consequently limiting the potential for early diagnosis and mechanism-driven treatment. This study employed a toxicogenomic approach on in-vitro...

  • Endothelial sensitivity to pro-fibrotic signals links systemic exposure to pulmonary fibrosis

    Pulmonary fibrosis (PF) is a life-threatening condition characterised by excessive extracellular matrix deposition and tissue scarring. While much of PF research has focused on alveolar epithelial cells and fibroblasts, endothelial cells have emerged as active contributors to the disease initiation, especially in the context of systemic exposure to pro-fibrotic substances. Here, we investigate early transcriptomic and secretory responses of human umbilical vein endothelial cells (HUVEC) to...

  • Going digital to boost safe and sustainable materials innovation markets. The digital safe-and-sustainability-by-design innovation approach of the PINK project

    In this innovation report, we present the vision of the PINK project to foster Safe-and-Sustainable-by-Design (SSbD) advanced materials and chemicals (AdMas&Chems) development by integrating state-of-the-art computational modelling, simulation tools and data resources. PINK proposes a novel approach for the use of the SSbD Framework, whose innovative approach is based on the application of a multi-objective optimisation procedure for the criteria of functionality, safety, sustainability and cost...

  • INSIGHT: An integrated framework for safe and sustainable chemical and material assessment

    The assessment of chemicals and materials has traditionally been fragmented, with health, environmental, social, and economic impacts evaluated independently. This disjointed approach limits the ability to capture trade-offs and synergies necessary for comprehensive decision-making under the Safe and Sustainable by Design (SSbD) framework. The EU INSIGHT project addresses this challenge by developing a novel computational framework for integrated impact assessment, based on the Impact Outcome...

  • An update on knowledge graphs and their current and potential applications in drug discovery

    INTRODUCTION: Knowledge graphs are becoming prominent tools in computational drug discovery. They effectively integrate heterogeneous biomedical data and generate new hypotheses and knowledge.

  • CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials

    The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs,...

  • Taxonomic and functional profiling of skin microbiome in psoriasis

    No abstract

2024

  • Unmasking metabolic disruptors: The NEMESIS project's quest for Novel Biomarkers, Evidence on Adverse Effects, and Efficient Methodologies

    Metabolism disrupting chemicals (MDCs) elicit negative effects on metabolically active organs such as the liver and the pancreas, altering normal metabolic processes. Chemicals that are known, or suspected MDCs include compounds found in everyday consumer products and food, making low-dose, continuous exposure inevitable for humans. Through the discovery of chemically induced metabolic disruption, a concern has surfaced whether and how MDCs impact human health and the development of metabolic...

  • CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials

    The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs,...

  • Easy-MODA: Simplifying standardised registration of scientific simulation workflows through MODA template guidelines powered by the Enalos Cloud Platform

    Modelling Data (MODA) reporting guidelines have been proposed for common terminology and for recording metadata for physics-based materials modelling and simulations in a CEN Workshop Agreement (CWA 17284:2018). Their purpose is similar to that of the Quantitative Structure-Activity Relationship (QSAR) model report form (QMRF) that aims to increase industry and regulatory confidence in QSAR models, but for a wider range of model types. Recently, the WorldFAIR project's nanomaterials case study...

  • Toxicogenomic assessment of in vitro macrophages exposed to profibrotic challenge reveals a sustained transcriptomic immune signature

    Immune signalling is a crucial component in the progression of fibrosis. However, approaches for the safety assessment of potentially profibrotic substances, that provide information on mechanistic immune responses, are underdeveloped. This study aimed to develop a novel framework for assessing the immunotoxicity of fibrotic compounds. We exposed macrophages in vitro to multiple sublethal concentrations of the profibrotic agent bleomycin, over multiple timepoints, and generated RNA sequencing...

  • Beyond basic characterization and omics: Immunomodulatory roles of platelet-derived extracellular vesicles unveiled by functional testing

    Renowned for their role in haemostasis and thrombosis, platelets are also increasingly recognized for their contribution in innate immunity, immunothrombosis and inflammatory diseases. Platelets express a wide range of receptors, which allows them to reach a variety of activation endpoints and grants them immunomodulatory functions. Activated platelets release extracellular vesicles (PEVs), whose formation and molecular cargo has been shown to depend on receptor-mediated activation and...

  • Exploring the Link Between Genetic Predictors of Cardiovascular Disease and Psoriasis

    CONCLUSIONS AND RELEVANCE: Findings of this mendelian randomization study indicate that genetic predictors of cardiovascular disease were associated with increased psoriasis risk with no reciprocal effect or association with other IMIDs. Elucidating mechanisms underpinning this association could lead to novel therapeutic approaches in both diseases.

  • Methylation and transcriptomic profiling reveals short term and long term regulatory responses in polarized macrophages

    Macrophage plasticity allows the adoption of distinct functional states in response to environmental cues. While unique transcriptomic profiles define these states, focusing solely on transcription neglects potential long-term effects. The investigation of epigenetic changes can be used to understand how temporary stimuli can result in lasting effects. Epigenetic alterations play an important role in the pathophysiology of macrophages, including their trained innate immunity, enabling faster and...

  • A Network Toxicology Approach for Mechanistic Modelling of Nanomaterial Hazard and Adverse Outcomes

    Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to...

  • A Multi-Dimensional Approach to Map Disease Relationships Challenges Classical Disease Views

    The categorization of human diseases is mainly based on the affected organ system and phenotypic characteristics. This is limiting the view to the pathological manifestations, while it neglects mechanistic relationships that are crucial to develop therapeutic strategies. This work aims to advance the understanding of diseases and their relatedness beyond traditional phenotypic views. Hence, the similarity among 502 diseases is mapped using six different data dimensions encompassing molecular,...

  • Polyphenol- and Glucuronoxylan-Rich Fiber Extract from Birch (<em>Betula</em> sp.) Wood Regulates Colonic Barrier Function and Cell Proliferation in Healthy Rats

    Birch wood-derived fiber extracts containing glucuronoxylans (GX) and polyphenols show potential for various food technological applications. This study investigated the effect of two extracts, GXpoly and pureGX, differing in lignin content on colonic barrier function. Healthy rats were fed diets containing 10% GXpoly, pureGX, or cellulose for 4 weeks. Colon crypt depth was lower in the GX groups than in the control group, but in the proximal colon, the result was significant only in GXpoly. An...

  • Integrative network analysis suggests prioritised drugs for atopic dermatitis

    CONCLUSIONS: Overall, our study reveals a core disease module providing unprecedented information about genetic, transcriptional and pharmacological relationships that foster drug discovery in atopic dermatitis.

2023

  • Advancing chemical safety assessment through an omics-based characterization of the test system-chemical interaction

    Assessing chemical safety is essential to evaluate the potential risks of chemical exposure to human health and the environment. Traditional methods relying on animal testing are being replaced by 3R (reduction, refinement, and replacement) principle-based alternatives, mainly depending on in vitro test methods and the Adverse Outcome Pathway framework. However, these approaches often focus on the properties of the compound, missing the broader chemical-biological interaction perspective....

  • Expanding adverse outcome pathways towards one health models for nanosafety

    The ever-growing production of nano-enabled products has generated the need for dedicated risk assessment strategies that ensure safety for humans and the environment. Transdisciplinary approaches are needed to support the development of new technologies while respecting environmental limits, as also highlighted by the EU Green Deal Chemicals Strategy for Sustainability and its safe and sustainable by design (SSbD) framework. The One Health concept offers a holistic multiscale approach for the...

  • DREAM: an R package for druggability evaluation of human complex diseases

    MOTIVATION: De novo drug development is a long and expensive process that poses significant challenges from the design to the preclinical testing, making the introduction into the market slow and difficult. This limitation paved the way to the development of drug repurposing, which consists in the re-usage of already approved drugs, developed for other therapeutic indications. Although several efforts have been carried out in the last decade in order to achieve clinically relevant drug...

  • Identification of a Gene Signature Predicting (Nano)Particle-Induced Adverse Lung Outcome in Rats

    Nanoparticles are extensively used in industrial products or as food additives. However, despite their contribution to improving our quality of life, concerns have been raised regarding their potential impact on occupational and public health. To speed up research assessing nanoparticle-related hazards, this study was undertaken to identify early markers of harmful effects on the lungs. Female Sprague Dawley rats were either exposed to crystalline silica DQ-12 with instillation, or to titanium...

  • The in vitro immunomodulatory effect of multi-walled carbon nanotubes by multilayer analysis

    The study of multi-walled carbon nanotube (MWCNT) induced immunotoxicity is crucial for determining hazards posed to human health. MWCNT exposure most commonly occurs via the airways, where macrophages are first line responders. Here we exploit an in vitro assay, measuring dose-dependent secretion of a wide panel of cytokines, as a measure of immunotoxicity following the non-lethal, multi-dose exposure (IC5, IC10 and IC20) to 7 MWCNTs with different intrinsic properties. We find that a tangled...

  • ESPERANTO: a GLP-field sEmi-SuPERvised toxicogenomics metadAta curatioN TOol

    SUMMARY: Biological data repositories are an invaluable source of publicly available research evidence. Unfortunately, the lack of convergence of the scientific community on a common metadata annotation strategy has resulted in large amounts of data with low FAIRness (Findable, Accessible, Interoperable and Reusable). The possibility of generating high-quality insights from their integration relies on data curation, which is typically an error-prone process while also being expensive in terms of...

  • A curated gene and biological system annotation of adverse outcome pathways related to human health

    Adverse outcome pathways (AOPs) are emerging as a central framework in modern toxicology and other fields in biomedicine. They serve as an extension of pathway-based concepts by depicting biological mechanisms as causally linked sequences of key events (KEs) from a molecular initiating event (MIE) to an adverse outcome. AOPs guide the use and development of new approach methodologies (NAMs) aimed at reducing animal experimentation. While AOPs model the systemic mechanisms at various levels of...

  • KNeMAP: a network mapping approach for knowledge-driven comparison of transcriptomic profiles

    MOTIVATION: Transcriptomic data can be used to describe the mechanism of action (MOA) of a chemical compound. However, omics data tend to be complex and prone to noise, making the comparison of different datasets challenging. Often, transcriptomic profiles are compared at the level of individual gene expression values, or sets of differentially expressed genes. Such approaches can suffer from underlying technical and biological variance, such as the biological system exposed on or the...

  • OxLDL sensitizes platelets for increased formation of extracellular vesicles capable of finetuning macrophage gene expression

    Platelet extracellular vesicles (PEVs) generated upon platelet activation may play a role in inflammatory pathologies such as atherosclerosis. Oxidized low-density lipoprotein (oxLDL), a well-known contributor to atherogenesis, activates platelets and presensitizes them for activation by other agonists. We studied the effect of oxLDL on the secretion, composition, and inflammatory functions of PEVs using contemporary EV analytics. Platelets were activated by co-stimulation with thrombin (T) and...

  • Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach

    Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals and the development of safe-by-design compounds. Although toxicogenomics supports mechanistic evaluation of chemical exposures, its implementation into the regulatory framework is hindered by uncertainties in the analysis and interpretation of such data. The use of mechanistic evidence through the adverse outcome pathway (AOP) concept is promoted for the development of new approach methodologies (NAMs) that...

2022

  • Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach

    Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals and the development of safe-by-design compounds. Although toxicogenomics supports mechanistic evaluation of chemical exposures, its implementation into the regulatory framework is hindered by uncertainties in the analysis and interpretation of such data. The use of mechanistic evidence through the adverse outcome pathway (AOP) concept is promoted for the development of new approach methodologies (NAMs) that...

  • The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis

    In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic...

  • The potential of a data centred approach &amp; knowledge graph data representation in chemical safety and drug design

    Big Data pervades nearly all areas of life sciences, yet the analysis of large integrated data sets remains a major challenge. Moreover, the field of life sciences is highly fragmented and, consequently, so is its data, knowledge, and standards. This, in turn, makes integrated data analysis and knowledge gathering across sub-fields a demanding task. At the same time, the integration of various research angles and data types is crucial for modelling the complexity of organisms and biological...

  • Representing and describing nanomaterials in predictive nanoinformatics

    Engineered nanomaterials (ENMs) enable new and enhanced products and devices in which matter can be controlled at a near-atomic scale (in the range of 1 to 100 nm). However, the unique nanoscale properties that make ENMs attractive may result in as yet poorly known risks to human health and the environment. Thus, new ENMs should be designed in line with the idea of safe-and-sustainable-by-design (SSbD). The biological activity of ENMs is closely related to their physicochemical characteristics,...

  • Factors Modulating COVID-19: A Mechanistic Understanding Based on the Adverse Outcome Pathway Framework

    Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway...

  • Biomarkers of nanomaterials hazard from multi-layer data

    There is an urgent need to apply effective, data-driven approaches to reliably predict engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational framework based on the molecular and phenotypic effects of a large panel of ENMs across multiple in vitro and in vivo models. Our methodology allows for the grouping of ENMs based on multi-omics approaches combined with robust toxicity tests. Importantly, we identify mRNA-based toxicity markers and extensively replicate them...

  • Characterization of ENM Dynamic Dose-Dependent MOA in Lung with Respect to Immune Cells Infiltration

    The molecular effects of exposures to engineered nanomaterials (ENMs) are still largely unknown. In classical inhalation toxicology, cell composition of bronchoalveolar lavage (BAL) is a toxicity indicator at the lung tissue level that can aid in interpreting pulmonary histological changes. Toxicogenomic approaches help characterize the mechanism of action (MOA) of ENMs by investigating the differentially expressed genes (DEG). However, dissecting which molecular mechanisms and events are...

  • Influence of FLG loss-of-function mutations in host-microbe interactions during atopic skin inflammation

    CONCLUSIONS: Our integrative approach provides molecular insights for the concept that FLG loss-of-function mutations are a genetic shortcut to atopic inflammation and unravels the complex interplay between genotype, transcriptome and microbiome in the human holobiont.

  • Association of neighbourhood disadvantage and individual socioeconomic position with all-cause mortality: a longitudinal multicohort analysis

    BACKGROUND: Few studies have examined the interactions between individual socioeconomic position and neighbourhood deprivation and the findings so far are heterogeneous. Using a large sample of diverse cohorts, we investigated the interaction effect of neighbourhood socioeconomic deprivation and individual socioeconomic position, assessed using education, on mortality.

  • Integrated Network Pharmacology Approach for Drug Combination Discovery: A Multi-Cancer Case Study

    Despite remarkable efforts of computational and predictive pharmacology to improve therapeutic strategies for complex diseases, only in a few cases have the predictions been eventually employed in the clinics. One of the reasons behind this drawback is that current predictive approaches are based only on the integration of molecular perturbation of a certain disease with drug sensitivity signatures, neglecting intrinsic properties of the drugs. Here we integrate mechanistic and chemocentric...

  • Nextcast: A software suite to analyse and model toxicogenomics data

    The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and analysis hampers the full exploitation of toxicogenomics-based evidence in regulatory risk assessment. Moreover, the pipelines for the preprocessing and downstream analyses of toxicogenomic data sets can...

  • Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

    No abstract

  • Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation

    The pharmacological arsenal against the COVID-19 pandemic is largely based on generic anti-inflammatory strategies or poorly scalable solutions. Moreover, as the ongoing vaccination campaign is rolling slower than wished, affordable and effective therapeutics are needed. To this end, there is increasing attention toward computational methods for drug repositioning and de novo drug design. Here, multiple data-driven computational approaches are systematically integrated to perform a virtual...

  • Prospects and challenges for FAIR toxicogenomics data

    No abstract

  • Network Analysis of Microarray Data

    DNA microarrays are widely used to investigate gene expression. Even though the classical analysis of microarray data is based on the study of differentially expressed genes, it is well known that genes do not act individually. Network analysis can be applied to study association patterns of the genes in a biological system. Moreover, it finds wide application in differential coexpression analysis between different systems. Network based coexpression studies have for example been used in...

2021

  • Multi-walled carbon nanotubes elicit concordant changes in DNA methylation and gene expression following long-term pulmonary exposure in mice

    Pulmonary exposure to multi-walled carbon nanotubes (MWCNTs) causes inflammation and fibrosis. Our previous work has shown that industrially produced MWCNTs trigger specific changes in gene expression in the lungs of exposed animals. To elucidate whether epigenetic effects play a role for these gene expression changes, we performed whole genome bisulphite sequencing to assess DNA methylation patterns in the lungs 56 days after exposure to MWCNTs. Lung tissues were also evaluated with respect to...

  • Prospects and challenges for FAIR toxicogenomics data

    No abstract

  • Transcriptome-based identification of novel endotypes in adult atopic dermatitis

    CONCLUSION: Our study revealed unrecognized AD endotypes with specific underlying biological pathways, highlighting novel pathophysiological mechanisms. These data could provide new insights into personalized treatment strategies.

  • PeptiCHIP: A Microfluidic Platform for Tumor Antigen Landscape Identification

    Identification of HLA class I ligands from the tumor surface (ligandome or immunopeptidome) is essential for designing T-cell mediated cancer therapeutic approaches. However, the sensitivity of the process for isolating MHC-I restricted tumor-specific peptides has been the major limiting factor for reliable tumor antigen characterization, making clear the need for technical improvement. Here, we describe our work from the fabrication and development of a microfluidic-based chip (PeptiCHIP) and...

  • VOLTA: adVanced mOLecular neTwork Analysis

    MOTIVATION: Network analysis is a powerful approach to investigate biological systems. It is often applied to study gene co-expression patterns derived from transcriptomics experiments. Even though co-expression analysis is widely used, there is still a lack of tools that are open and customizable on the basis of different network types and analysis scenarios (e.g. through function accessibility), but are also suitable for novice users by providing complete analysis pipelines.

  • A systematic comparison of data- and knowledge-driven approaches to disease subtype discovery

    Typical clustering analysis for large-scale genomics data combines two unsupervised learning techniques: dimensionality reduction and clustering (DR-CL) methods. It has been demonstrated that transforming gene expression to pathway-level information can improve the robustness and interpretability of disease grouping results. This approach, referred to as biological knowledge-driven clustering (BK-CL) approach, is often neglected, due to a lack of tools enabling systematic comparisons with more...

  • The power and potential of BIOMAP to elucidate host-microbiome interplay in skin inflammatory diseases

    The two most common chronic inflammatory skin diseases are atopic dermatitis (AD) and psoriasis. The underpinnings of the remarkable degree of clinical heterogeneity of AD and psoriasis are poorly understood and, as a consequence, disease onset and progression are unpredictable and the optimal type and time point for intervention are as yet unknown. The BIOMAP project is the first IMI (Innovative Medicines Initiative) project dedicated to investigating the causes and mechanisms of AD and...

  • Viral Molecular Mimicry Influences the Antitumor Immune Response in Murine and Human Melanoma

    Molecular mimicry is one of the leading mechanisms by which infectious agents can induce autoimmunity. Whether a similar mechanism triggers an antitumor immune response is unexplored, and the role of antiviral T cells infiltrating the tumor has remained anecdotal. To address these questions, we first developed a bioinformatic tool to identify tumor peptides with high similarity to viral epitopes. Using peptides identified by this tool, we demonstrated that, in mice, preexisting immunity toward...

  • Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

    Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats...

  • CpGmotifs: a tool to discover DNA motifs associated to CpG methylation events

    CONCLUSIONS: CpGmotifs is an open source software. Its source code is available on GitHub https://github.com/Greco-Lab/CpGmotifs and a ready-to-use docker image is provided on DockerHub at https://hub.docker.com/r/grecolab/cpgmotifs .

  • Toxicogenomic Profiling of 28 Nanomaterials in Mouse Airways

    Toxicogenomics opens novel opportunities for hazard assessment by utilizing computational methods to map molecular events and biological processes. In this study, the transcriptomic and immunopathological changes associated with airway exposure to a total of 28 engineered nanomaterials (ENM) are investigated. The ENM are selected to have different core (Ag, Au, TiO(2), CuO, nanodiamond, and multiwalled carbon nanotubes) and surface chemistries (COOH, NH(2), or polyethylene glycosylation (PEG))....

  • Signals of pseudo-starvation unveil the amino acid transporter SLC7A11 as key determinant in the control of Treg cell proliferative potential

    Human CD4^(+)CD25^(hi)FOXP3^(+) regulatory T (Treg) cells are key players in the control of immunological self-tolerance and homeostasis. Here, we report that signals of pseudo-starvation reversed human Treg cell in vitro anergy through an integrated transcriptional response, pertaining to proliferation, metabolism, and transmembrane solute carrier transport. At the molecular level, the Treg cell proliferative response was dependent on the induction of the cystine/glutamate antiporter solute...

  • Clustering based approach for population level identification of condition-associated T-cell receptor β-chain CDR3 sequences

    CONCLUSION: We conclude that immune sub-repertoires of similar immuno-genomic features shared across unrelated individuals can serve as viable units of immune repertoire comparison, serving as proxy for identification of condition-associated CDR3s.

  • Integrated network analysis reveals new genes suggesting COVID-19 chronic effects and treatment

    The COVID-19 disease led to an unprecedented health emergency, still ongoing worldwide. Given the lack of a vaccine or a clear therapeutic strategy to counteract the infection as well as its secondary effects, there is currently a pressing need to generate new insights into the SARS-CoV-2 induced host response. Biomedical data can help to investigate new aspects of the COVID-19 pathogenesis, but source heterogeneity represents a major drawback and limitation. In this work, we applied data...

  • Advances in de Novo Drug Design: From Conventional to Machine Learning Methods

    . De novo drug design is a computational approach that generates novel molecular structures from atomic building blocks with no a priori relationships. Conventional methods include structure-based and ligand-based design, which depend on the properties of the active site of a biological target or its known active binders, respectively. Artificial intelligence, including machine learning, is an emerging field that has positively impacted the drug discovery process. Deep reinforcement learning is...

2020

  • Effects of <em>In Vivo</em> Gluten Challenge on PBMC Gene Expression Profiles in Diet Treated Celiac Disease

    The pathological mechanisms that lead to the onset and reactivation of celiac disease (CD) remain largely unknown. While gluten free diet (GFD) improves the intestinal damage and associated clinical symptoms in majority of cases, it falls short of providing full recovery. Additionally, late or misdiagnosis is also common as CD presents with a wide range of symptoms. Clear understanding of CD pathogenesis is thus critical to address both diagnostic and treatment concerns. We aimed to study the...

  • Can an InChI for Nano Address the Need for a Simplified Representation of Complex Nanomaterials across Experimental and Nanoinformatics Studies?

    Chemoinformatics has developed efficient ways of representing chemical structures for small molecules as simple text strings, simplified molecular-input line-entry system (SMILES) and the IUPAC International Chemical Identifier (InChI), which are machine-readable. In particular, InChIs have been extended to encode formalized representations of mixtures and reactions, and work is ongoing to represent polymers and other macromolecules in this way. The next frontier is encoding the multi-component...

  • Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis

    Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits; however, distinguishing the clinical phenotype of irritant and allergic contact dermatitis remains challenging. Employing integrative transcriptomic analysis and machine-learning approaches, we aimed to decipher disease-related signature genes to find suitable sets of biomarkers. A total of 89 positive patch-test...

  • Multiparametric Profiling of Engineered Nanomaterials: Unmasking the Surface Coating Effect

    Despite considerable efforts, the properties that drive the cytotoxicity of engineered nanomaterials (ENMs) remain poorly understood. Here, the authors inverstigate a panel of 31 ENMs with different core chemistries and a variety of surface modifications using conventional in vitro assays coupled with omics-based approaches. Cytotoxicity screening and multiplex-based cytokine profiling reveals a good concordance between primary human monocyte-derived macrophages and the human monocyte-like cell...

  • Epigenetic alterations in skin homing CD4<sup>+</sup>CLA<sup>+</sup> T cells of atopic dermatitis patients

    T cells expressing the cutaneous lymphocyte antigen (CLA) mediate pathogenic inflammation in atopic dermatitis (AD). The molecular alterations contributing to their dysregulation remain unclear. With the aim to elucidate putative altered pathways in AD we profiled DNA methylation levels and miRNA expression in sorted T cell populations (CD4^(+), CD4^(+)CD45RA^(+) naïve, CD4^(+)CLA^(+), and CD8^(+)) from adult AD patients and healthy controls (HC). Skin homing CD4^(+)CLA^(+) T cells from AD...

  • Manually curated and harmonised transcriptomics datasets of psoriasis and atopic dermatitis patients

    We present manually curated transcriptomics data of psoriasis and atopic dermatitis patients retrieved from the NCBI Gene Expression Omnibus and EBI ArrayExpress repositories. We collected 39 transcriptomics datasets, deriving from DNA microarrays and RNA-Sequencing technologies, for a total of 1677 samples. We provide quality-checked, homogenised and preprocessed gene expression matrices and their corresponding metadata tables along with the estimated surrogate variables. These data represent a...

  • Microbial and transcriptional differences elucidate atopic dermatitis heterogeneity across skin sites

    It is well established that different sites in healthy human skin are colonized by distinct microbial communities due to different physiological conditions. However, few studies have explored microbial heterogeneity between skin sites in diseased skin, such as atopic dermatitis (AD) lesions. To address this issue, we carried out deep analysis of the microbiome and transcriptome in the skin of a large cohort of AD patients and healthy volunteers, comparing two physiologically different sites:...

  • Immune-microbiota interaction in Finnish and Russian Karelia young people with high and low allergy prevalence

    CONCLUSIONS AND CLINICAL RELEVANCE: Young populations living in the Finnish and Russian Karelia show marked differences in genome-wide gene expression and host contrasting skin and nasal epithelium microbiota. The rich gene-microbe network in Russians seems to result in a better-balanced innate immunity and associates with low allergy prevalence.

  • Covid-19 acute responses and possible long term consequences: What nanotoxicology can teach us

    Long-term effects of Covid-19 disease are still poorly understood. However, similarities between the responses to SARS-CoV-2 and certain nanomaterials suggest fibrotic pulmonary disease as a concern for public health in the next future. Cross-talk between nanotoxicology and other relevant disciplines can help us to deploy more effective Covid-19 therapies and management strategies.

  • TinderMIX: Time-dose integrated modelling of toxicogenomics data

    CONCLUSIONS: To showcase the TinderMIX method, we analysed 2 drugs from the Open TG-GATEs dataset, namely, cyclosporin A and thioacetamide. We first identified the dynamic dose-dependent mechanism of action of each drug and compared them. Our analysis highlights that different time- and dose-integrated point of departure recapitulates the toxicity potential of the compounds as well as their dynamic dose-dependent mechanism of action.

  • Transcriptomics in Toxicogenomics, Part II: Preprocessing and Differential Expression Analysis for High Quality Data

    Preprocessing of transcriptomics data plays a pivotal role in the development of toxicogenomics-driven tools for chemical toxicity assessment. The generation and exploitation of large volumes of molecular profiles, following an appropriate experimental design, allows the employment of toxicogenomics (TGx) approaches for a thorough characterisation of the mechanism of action (MOA) of different compounds. To date, a plethora of data preprocessing methodologies have been suggested. However, in most...

  • Mechanistic Similarities between 3D Human Bronchial Epithelium and Mice Lung, Exposed to Copper Oxide Nanoparticles, Support Non-Animal Methods for Hazard Assessment

    The diversity and increasing prevalence of products derived from engineered nanomaterials (ENM), warrants implementation of non-animal approaches to health hazard assessment for ethical and practical reasons. Although non-animal approaches are becoming increasingly popular, there are almost no studies of side-by-side comparisons with traditional in vivo assays. Here, transcriptomics is used to investigate mechanistic similarities between healthy/asthmatic models of 3D air-liquid interface (ALI)...

  • Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects

    The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental,...

  • Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment

    Transcriptomics data are relevant to address a number of challenges in Toxicogenomics (TGx). After careful planning of exposure conditions and data preprocessing, the TGx data can be used in predictive toxicology, where more advanced modelling techniques are applied. The large volume of molecular profiles produced by omics-based technologies allows the development and application of artificial intelligence (AI) methods in TGx. Indeed, the publicly available omics datasets are constantly...

  • Carbon Nanomaterials Promote M1/M2 Macrophage Activation

    Toxic effects of certain carbon nanomaterials (CNM) have been observed in several exposure scenarios both in vivo and in vitro. However, most of the data currently available has been generated in a high-dose/acute exposure setup, limiting the understanding of their immunomodulatory mechanisms. Here, macrophage-like THP-1 cells, exposed to ten different CNM for 48 h in low-cytotoxic concentration of 10 µg mL^(-1) , are characterized by secretion of different cytokines and global transcriptional...

2019

2018

  • Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation

    New strategies to characterize the effects of engineered nanomaterials (ENMs) based on omics technologies are emerging. However, given the intricate interplay of multiple regulatory layers, the study of a single molecular species in exposed biological systems might not allow the needed granularity to successfully identify the pathways of toxicity (PoT) and, hence, portraying adverse outcome pathways (AOPs). Moreover, the intrinsic diversity of different cell types composing the exposed organs...

  • Tape-stripping alters the microbe-host correlations in mouse skin

    No abstract

  • Integration of genome-wide mRNA and miRNA expression, and DNA methylation data of three cell lines exposed to ten carbon nanomaterials

    We present data derived from an exposure experiment in which three cell-lines representative of cell types of the respiratory tissue (epithelial type-I A549, epithelial type-II BEAS-2B, and macrophage THP-1) have been exposed to ten different carbon-based nanomaterials for 48 h. In particular, we provide: genome-wide mRNA and miRNA expression, and DNA methylation; gene tables, containing information on the aberrations induced in these three genomic data layers at the gene level; mechanism of...

  • Genetic Control of Myelin Plasticity after Chronic Psychosocial Stress

    Anxiety disorders often manifest in genetically susceptible individuals after psychosocial stress, but the mechanisms underlying these gene-environment interactions are largely unknown. We used the chronic social defeat stress (CSDS) mouse model to study resilience and susceptibility to chronic psychosocial stress. We identified a strong genetic background effect in CSDS-induced social avoidance (SA) using four inbred mouse strains: 69% of C57BL/6NCrl (B6), 23% of BALB/cAnNCrl, 19% of...

  • IntEREst: intron-exon retention estimator

    CONCLUSION: IntEREst is an R package for Intron retention and exon-exon junction levels analysis of RNA-seq data. Both the human and plant analyses show that the U12-type introns are retained at higher level compared to the U2-type introns already in the control samples, but the retention is exacerbated in patient or plant samples carrying a mutated ZRSR2 gene. Intron retention events caused by ZRSR2 mutation that we discovered using IntEREst (DESeq2 based function) show considerable overlap...

  • miR-34b/c Regulates Wnt1 and Enhances Mesencephalic Dopaminergic Neuron Differentiation

    The differentiation of dopaminergic neurons requires concerted action of morphogens and transcription factors acting in a precise and well-defined time window. Very little is known about the potential role of microRNA in these events. By performing a microRNA-mRNA paired microarray screening, we identified miR-34b/c among the most upregulated microRNAs during dopaminergic differentiation. Interestingly, miR-34b/c modulates Wnt1 expression, promotes cell cycle exit, and induces dopaminergic...

  • DNA methylation in childhood asthma: an epigenome-wide meta-analysis

    BACKGROUND: DNA methylation profiles associated with childhood asthma might provide novel insights into disease pathogenesis. We did an epigenome-wide association study to assess methylation profiles associated with childhood asthma.

  • Allostatic load and subsequent all-cause mortality: which biological markers drive the relationship? Findings from a UK birth cohort

    The concept of allostatic load (AL) refers to the idea of a global physiological 'wear and tear' resulting from the adaptation to the environment through the stress response systems over the life span. The link between socioeconomic position (SEP) and mortality has now been established, and there is evidence that AL may capture the link between SEP and mortality. In order to quantitatively assess the role of AL on mortality, we use data from the 1958 British birth cohort including eleven year...

  • Strong conservation of inbred mouse strain microRNA loci but broad variation in brain microRNAs due to RNA editing and isomiR expression

    Diversity in the structure and expression of microRNAs, important regulators of gene expression, arises from SNPs, duplications followed by divergence, production of isomiRs, and RNA editing. Inbred mouse strains and crosses using them are important reference populations for genetic mapping, and as models of human disease. We determined the nature and extent of interstrain miRNA variation by (i) identifying miRNA SNPs in whole-genome sequence data from 36 strains, and (ii) examining miRNA...

  • INfORM: Inference of NetwOrk Response Modules

    SUMMARY: Detecting and interpreting responsive modules from gene expression data by using network-based approaches is a common but laborious task. It often requires the application of several computational methods implemented in different software packages, forcing biologists to compile complex analytical pipelines. Here we introduce INfORM (Inference of NetwOrk Response Modules), an R shiny application that enables non-expert users to detect, evaluate and select gene modules with high...