Molecular and phylogenetic characterization of the monkeypox outbreak in the South of Spain.

Background and Aim: Until the May 2022 Monkeypox (MPXV) outbreak, which spread rapidly to many non-endemic countries, the virus was considered a viral zoonosis limited to some African countries. The Andalusian circuit of genomic surveillance was rapidly applied to characterize the MPXV outbreak in the South of Spain. Methods: Whole genome sequencing was used to obtain the genomic profiles of samples collected across the south of Spain, representative of all the provinces of Andalusia. Phylogenetic analysis was used to study the relationship of the isolates and the available sequences of the 2022 outbreak. Results: Whole genome sequencing of a total of 160 MPXV viruses from the different provinces that reported cases were obtained. Interestingly, we report the sequences of MPXV viruses obtained from two patients who died. While one of the isolates bore no noteworthy mutations that explain a potential heightened virulence, in another patient the second consecutive genome sequence, performed after the administration of tecovirimat, uncovered a mutation within the A0A7H0DN30 gene, known to be a prime target for tecovirimat in its Vaccinia counterpart. In general, a low number of mutations were observed in the sequences reported, which were very similar to the reference of the 2022 outbreak (OX044336), as expected from a DNA virus. The samples likely correspond to several introductions of the circulating MPXV viruses from the last outbreak. The virus sequenced from one of the two patients that died presented a mutation in a gene that bears potential connections to drug resistance. This mutation was absent in the initial sequencing before treatment.

drexml: A command line tool and Python package for drug repurposing.

We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.

Evidence of the association between increased use of direct oral anticoagulants and a reduction in the rate of atrial fibrillation-related stroke and major bleeding at the population level (2012–2019) / Evidencia a nivel poblacional de la asociación entre el aumento del uso de anticoagulantes orales directos y una reducción de la incidencia de ictus y hemorragias mayores relacionados con fibrilación auricular (2012-2019)

Background: The introduction of direct-acting oral anticoagulants (DOACs) has shown to decrease atrial fibrillation (AF)-related stroke and bleeding rates in clinical studies, but there is no certain evidence about their effects at the population level. Our aim was to assess changes in AF-related stroke and major bleeding rates between 2012 and 2019 in Andalusia (Spain), and the association between DOACs use and events rates at the population level. Methods: All patients with an AF diagnosis from 2012 to 2019 were identified using the Andalusian Health Population Base, that provides clinical information on all Andalusian people. Annual ischemic and hemorrhagic stroke, major bleeding rates, and used antithrombotic treatments were determined. Marginal hazard ratios (HR) were calculated for each treatment. Results: A total of 95,085 patients with an AF diagnosis were identified. Mean age was 76.1±10.2 years (49.7% women). An increase in the use of DOACs was observed throughout the study period in both males and females (p<0.001). The annual rate of ischemic stroke decreased by one third, while that of hemorrhagic stroke and major bleeding decreased 2–3-fold from 2012 to 2019. Marginal HR was lower than 0.50 for DOACs compared to VKA for all ischemic or hemorrhagic events. Conclusions: In this contemporary population-based study using clinical and administrative databases in Andalusia, a significant reduction in the incidence of AF-related ischemic and hemorrhagic stroke and major bleeding was observed between 2012 and 2019. The increased use of DOACs seems to be associated with this reduction.(AU)

Introducción: La introducción de los anticoagulantes orales de acción directa (ACOD) ha demostrado disminuir las tasas de accidentes cerebrovasculares y hemorragias relacionados con fibrilación auricular (FA) en estudios clínicos, pero no hay tanta evidencia sobre sus efectos a nivel poblacional. Nuestro objetivo fue evaluar los cambios en la incidencia de ictus y hemorragias mayores relacionados con FA entre 2012 y 2019 en Andalucía (España), y estudiar la asociación entre el uso de ACOD y estos eventos a nivel poblacional. Métodos: Se incluyeron pacientes con diagnóstico de FA entre los años 2012 y 2019 en la Base de Población Sanitaria de Andalucía, que proporciona información clínica de todos los andaluces. Se determinaron los accidentes cerebrovasculares isquémicos y hemorrágicos anuales, las tasas de sangrado mayor y los tratamientos antitrombóticos utilizados. Se estimaron los hazard ratio para cada tratamiento. Resultados: Se identificaron un total de 95.085 pacientes con diagnóstico de FA. La edad media fue de 76,1±10,2 años (49,7% mujeres). Se observó un aumento en el uso de ACOD a lo largo del período de estudio, tanto en varones como en mujeres (p<0,001). La tasa anual de ictus isquémico disminuyó en un tercio, mientras que la de ictus hemorrágico y hemorragia mayor se redujo de 2 a 3 veces entre 2012 y 2019. Los hazard ratio fueron inferiores a 0,50 para los ACOD en comparación con los antivitamina K para todos los eventos isquémicos o hemorrágicos. Conclusiones: En este estudio poblacional contemporáneo, se observó, utilizando bases de datos clínicas y administrativas de Andalucía, una reducción significativa en la incidencia de ictus isquémico y hemorrágico, y hemorragia mayor relacionados con FA entre los años 2012 y 2019. El mayor uso de ACOD parece estar asociado con esta reducción.(AU)

The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery.

BACKGROUND: Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP. METHODS: By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa. RESULTS: A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa. CONCLUSIONS: The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.

Evidence of the association between increased use of direct oral anticoagulants and a reduction in the rate of atrial fibrillation-related stroke and major bleeding at the population level (2012-2019).

BACKGROUND: The introduction of direct-acting oral anticoagulants (DOACs) has shown to decrease atrial fibrillation (AF)-related stroke and bleeding rates in clinical studies, but there is no certain evidence about their effects at the population level. Our aim was to assess changes in AF-related stroke and major bleeding rates between 2012 and 2019 in Andalusia (Spain), and the association between DOACs use and events rates at the population level. METHODS: All patients with an AF diagnosis from 2012 to 2019 were identified using the Andalusian Health Population Base, that provides clinical information on all Andalusian people. Annual ischemic and hemorrhagic stroke, major bleeding rates, and used antithrombotic treatments were determined. Marginal hazard ratios (HR) were calculated for each treatment. RESULTS: A total of 95,085 patients with an AF diagnosis were identified. Mean age was 76.1±10.2 years (49.7% women). An increase in the use of DOACs was observed throughout the study period in both males and females (p<0.001). The annual rate of ischemic stroke decreased by one third, while that of hemorrhagic stroke and major bleeding decreased 2-3-fold from 2012 to 2019. Marginal HR was lower than 0.50 for DOACs compared to VKA for all ischemic or hemorrhagic events. CONCLUSIONS: In this contemporary population-based study using clinical and administrative databases in Andalusia, a significant reduction in the incidence of AF-related ischemic and hemorrhagic stroke and major bleeding was observed between 2012 and 2019. The increased use of DOACs seems to be associated with this reduction.

Evaluation of a combined detection of SARS-CoV-2 and its variants using real-time allele-specific PCR strategy: an advantage for clinical practice.

This study aimed to assess the ability of a real-time reverse transcription polymerase chain reaction (RT-PCR) with multiple targets to detect SARS-CoV-2 and its variants in a single test. Nasopharyngeal specimens were collected from patients in Granada, Spain, between January 2021 and December 2022. Five allele-specific RT-PCR kits were used sequentially, with each kit designed to detect a predominant variant at the time. When the Alpha variant was dominant, the kit included the HV69/70 deletion, E and N genes. When Delta replaced Alpha, the kit incorporated the L452R mutation in addition to E and N genes. When Omicron became dominant, L452R was replaced with the N679K mutation. Before incorporating each variant kit, a comparative analysis was carried out with SARS-CoV-2 whole genome sequencing (WGS). The results demonstrated that RT-PCR with multiple targets can provide rapid and effective detection of SARS-CoV-2 and its variants in a single test. A very high degree of agreement (96.2%) was obtained between the comparison of RT-PCR and WGS. Allele-specific RT-PCR assays make it easier to implement epidemiological surveillance systems for effective public health decision making.

Real-world evidence with a retrospective cohort of 15,968 COVID-19 hospitalized patients suggests 21 new effective treatments.

PURPOSE: Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19. METHODS: Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. RESULTS: Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality. CONCLUSIONS: In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively.

Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models.

Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.

Rapid degeneration of iPSC-derived motor neurons lacking Gdap1 engages a mitochondrial-sustained innate immune response.

Charcot-Marie-Tooth disease is a chronic hereditary motor and sensory polyneuropathy targeting Schwann cells and/or motor neurons. Its multifactorial and polygenic origin portrays a complex clinical phenotype of the disease with a wide range of genetic inheritance patterns. The disease-associated gene GDAP1 encodes for a mitochondrial outer membrane protein. Mouse and insect models with mutations in Gdap1 have reproduced several traits of the human disease. However, the precise function in the cell types affected by the disease remains unknown. Here, we use induced-pluripotent stem cells derived from a Gdap1 knockout mouse model to better understand the molecular and cellular phenotypes of the disease caused by the loss-of-function of this gene. Gdap1-null motor neurons display a fragile cell phenotype prone to early degeneration showing (1) altered mitochondrial morphology, with an increase in the fragmentation of these organelles, (2) activation of autophagy and mitophagy, (3) abnormal metabolism, characterized by a downregulation of Hexokinase 2 and ATP5b proteins, (4) increased reactive oxygen species and elevated mitochondrial membrane potential, and (5) increased innate immune response and p38 MAP kinase activation. Our data reveals the existence of an underlying Redox-inflammatory axis fueled by altered mitochondrial metabolism in the absence of Gdap1. As this biochemical axis encompasses a wide variety of druggable targets, our results may have implications for developing therapies using combinatorial pharmacological approaches and improving therefore human welfare. A Redox-immune axis underlying motor neuron degeneration caused by the absence of Gdap1. Our results show that Gdap1-/- motor neurons have a fragile cellular phenotype that is prone to degeneration. Gdap1-/- iPSCs differentiated into motor neurons showed an altered metabolic state: decreased glycolysis and increased OXPHOS. These alterations may lead to hyperpolarization of mitochondria and increased ROS levels. Excessive amounts of ROS might be the cause of increased mitophagy, p38 activation and inflammation as a cellular response to oxidative stress. The p38 MAPK pathway and the immune response may, in turn, have feedback mechanisms, leading to the induction of apoptosis and senescence, respectively. CAC, citric acid cycle; ETC, electronic transport chain; Glc, glucose; Lac, lactate; Pyr, pyruvate.

Visualization of automatically combined disease maps and pathway diagrams for rare diseases.

Introduction: Investigation of molecular mechanisms of human disorders, especially rare diseases, require exploration of various knowledge repositories for building precise hypotheses and complex data interpretation. Recently, increasingly more resources offer diagrammatic representation of such mechanisms, including disease-dedicated schematics in pathway databases and disease maps. However, collection of knowledge across them is challenging, especially for research projects with limited manpower. Methods: In this article we present an automated workflow for construction of maps of molecular mechanisms for rare diseases. The workflow requires a standardized definition of a disease using Orphanet or HPO identifiers to collect relevant genes and variants, and to assemble a functional, visual repository of related mechanisms, including data overlays. The diagrams composing the final map are unified to a common systems biology format from CellDesigner SBML, GPML and SBML+layout+render. The constructed resource contains disease-relevant genes and variants as data overlays for immediate visual exploration, including embedded genetic variant browser and protein structure viewer. Results: We demonstrate the functionality of our workflow on two examples of rare diseases: Kawasaki disease and retinitis pigmentosa. Two maps are constructed based on their corresponding identifiers. Moreover, for the retinitis pigmentosa use-case, we include a list of differentially expressed genes to demonstrate how to tailor the workflow using omics datasets. Discussion: In summary, our work allows for an ad-hoc construction of molecular diagrams combined from different sources, preserving their layout and graphical style, but integrating them into a single resource. This allows to reduce time consuming tasks of prototyping of a molecular disease map, enabling visual exploration, hypothesis building, data visualization and further refinement. The code of the workflow is open and accessible at https://gitlab.lcsb.uni.lu/minerva/automap/.

microRNAs-mediated regulation of insulin signaling in white adipose tissue during aging: Role of caloric restriction.

Caloric restriction is a non-pharmacological intervention known to ameliorate the metabolic defects associated with aging, including insulin resistance. The levels of miRNA expression may represent a predictive tool for aging-related alterations. In order to investigate the role of miRNAs underlying insulin resistance in adipose tissue during the early stages of aging, 3- and 12-month-old male animals fed ad libitum, and 12-month-old male animals fed with a 20% caloric restricted diet were used. In this work we demonstrate that specific miRNAs may contribute to the impaired insulin-stimulated glucose metabolism specifically in the subcutaneous white adipose tissue, through the regulation of target genes implicated in the insulin signaling cascade. Moreover, the expression of these miRNAs is modified by caloric restriction in middle-aged animals, in accordance with the improvement of the metabolic state. Overall, our work demonstrates that alterations in posttranscriptional gene expression because of miRNAs dysregulation might represent an endogenous mechanism by which insulin response in the subcutaneous fat depot is already affected at middle age. Importantly, caloric restriction could prevent this modulation, demonstrating that certain miRNAs could constitute potential biomarkers of age-related metabolic alterations.

SigPrimedNet: A Signaling-Informed Neural Network for scRNA-seq Annotation of Known and Unknown Cell Types.

Single-cell RNA sequencing is increasing our understanding of the behavior of complex tissues or organs, by providing unprecedented details on the complex cell type landscape at the level of individual cells. Cell type definition and functional annotation are key steps to understanding the molecular processes behind the underlying cellular communication machinery. However, the exponential growth of scRNA-seq data has made the task of manually annotating cells unfeasible, due not only to an unparalleled resolution of the technology but to an ever-increasing heterogeneity of the data. Many supervised and unsupervised methods have been proposed to automatically annotate cells. Supervised approaches for cell-type annotation outperform unsupervised methods except when new (unknown) cell types are present. Here, we introduce SigPrimedNet an artificial neural network approach that leverages (i) efficient training by means of a sparsity-inducing signaling circuits-informed layer, (ii) feature representation learning through supervised training, and (iii) unknown cell-type identification by fitting an anomaly detection method on the learned representation. We show that SigPrimedNet can efficiently annotate known cell types while keeping a low false-positive rate for unseen cells across a set of publicly available datasets. In addition, the learned representation acts as a proxy for signaling circuit activity measurements, which provide useful estimations of the cell functionalities.

Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer.

The reprogramming of metabolism is a recognized cancer hallmark. It is well known that different signaling pathways regulate and orchestrate this reprogramming that contributes to cancer initiation and development. However, recent evidence is accumulating, suggesting that several metabolites could play a relevant role in regulating signaling pathways. To assess the potential role of metabolites in the regulation of signaling pathways, both metabolic and signaling pathway activities of Breast invasive Carcinoma (BRCA) have been modeled using mechanistic models. Gaussian Processes, powerful machine learning methods, were used in combination with SHapley Additive exPlanations (SHAP), a recent methodology that conveys causality, to obtain potential causal relationships between the production of metabolites and the regulation of signaling pathways. A total of 317 metabolites were found to have a strong impact on signaling circuits. The results presented here point to the existence of a complex crosstalk between signaling and metabolic pathways more complex than previously was thought.

A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact.

The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.

A crowdsourcing database for the copy-number variation of the Spanish population.

BACKGROUND: Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants. RESULTS: Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ . CONCLUSION: SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.

Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging.

ATP-citrate lyase is a central integrator of cellular metabolism in the interface of protein, carbohydrate, and lipid metabolism. The physiological consequences as well as the molecular mechanisms orchestrating the response to long-term pharmacologically induced Acly inhibition are unknown. We report here that the Acly inhibitor SB-204990 improves metabolic health and physical strength in wild-type mice when fed with a high-fat diet, while in mice fed with healthy diet results in metabolic imbalance and moderated insulin resistance. By applying a multiomic approach using untargeted metabolomics, transcriptomics, and proteomics, we determined that, in vivo, SB-204990 plays a role in the regulation of molecular mechanisms associated with aging, such as energy metabolism, mitochondrial function, mTOR signaling, and folate cycle, while global alterations on histone acetylation are absent. Our findings indicate a mechanism for regulating molecular pathways of aging that prevents the development of metabolic abnormalities associated with unhealthy dieting. This strategy might be explored for devising therapeutic approaches to prevent metabolic diseases.

Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia.

Recombination is an evolutionary strategy to quickly acquire new viral properties inherited from the parental lineages. The systematic survey of the SARS-CoV-2 genome sequences of the Andalusian genomic surveillance strategy has allowed the detection of an unexpectedly high number of co-infections, which constitute the ideal scenario for the emergence of new recombinants. Whole genome sequence of SARS-CoV-2 has been carried out as part of the genomic surveillance programme. Sample sources included the main hospitals in the Andalusia region. In addition to the increase of co-infections and known recombinants, three novel SARS-CoV-2 delta-omicron and omicron-omicron recombinant variants with two break points have been detected. Our observations document an epidemiological scenario in which co-infection and recombination are detected more frequently. Finally, we describe a family case in which co-infection is followed by the detection of a recombinant made from the two co-infecting variants. This increased number of recombinants raises the risk of emergence of recombinant variants with increased transmissibility and pathogenicity.

Polystyrene nanoplastics affect transcriptomic and epigenomic signatures of human fibroblasts and derived induced pluripotent stem cells: Implications for human health.

Plastic pollution is increasing at an alarming rate yet the impact of this pollution on human health is poorly understood. Because human induced pluripotent stem cells (hiPSC) are frequently derived from dermal fibroblasts, these cells offer a powerful platform for the identification of molecular biomarkers of environmental pollution in human cells. Here, we describe a novel proof-of-concept for deriving hiPSC from human dermal fibroblasts deliberately exposed to polystyrene (PS) nanoplastic particles; unexposed hiPSC served as controls. In parallel, unexposed hiPSC were exposed to low and high concentrations of PS nanoparticles. Transcriptomic and epigenomic signatures of all fibroblasts and hiPSCs were defined using RNA-seq and whole genome methyl-seq, respectively. Both PS-treated fibroblasts and derived hiPSC showed alterations in expression of ESRRB and HNF1A genes and circuits involved in the pluripotency of stem cells, as well as in pathways involved in cancer, inflammatory disorders, gluconeogenesis, carbohydrate metabolism, innate immunity, and dopaminergic synapse. Similarly, the expression levels of identified key transcriptional and DNA methylation changes (DNMT3A, ESSRB, FAM133CP, HNF1A, SEPTIN7P8, and TTC34) were significantly affected in both PS-exposed fibroblasts and hiPSC. This study illustrates the power of human cellular models of environmental pollution to narrow down and prioritize the list of candidate molecular biomarkers of environmental pollution. This knowledge will facilitate the deciphering of the origins of environmental diseases.