Biology subjects

Hidalgo, M. R.

Publications and source records attributed to Hidalgo, M. R..

18 recordsLinked to original sources

bioRxiv2026

Transposable elements as new players to decipher sex differences in Parkinson Disease

We present a novel integrative analysis of transposable elements (TEs) in 4 single cell RNA-seq (scRNA-seq) datasets of postmortem substantia nigra pars compacta samples of Parkinson Disease (PD) patients matched healthy controls, with the objective of building a cell-type specific trustworthy atlas of TEs that may clarify the role of TEs in sex differences in PD. We have used the soloTE tool to evaluate the TEs expression changes across all snRNA-seq studies identified in our previous systematic review, and then integrated the results using meta-analysis techniques. Finally, we evaluated the possible associations between TEs and protein coding genes by integrating our previous results in this matter with the information of TEs obtained, in order to propose the possible action mechanism by which some of the TEs contribute to PD.

bioinformatics↗

bioRxiv2024

Uncovering sex differences in Parkinson's Disease through metaanalysis of single cell transcriptomic studies

Abundant evidence supports the significant impact of biological sex on various aspects of Parkinson Disease (PD), including incidence, progression, symptoms or response to treatment. The incidence and prevalence of the disease is higher in males, while its age of onset is earlier than in females. There are also sex differences in the symptomatology, both motor and non-motor. In female PD, tremor, pain, depression and dysphagia are predominant, whereas in male PD, freezing of gait, camptocormia, cognitive impairment and urinary dysfunction are more common. Likewise, there are sex differences in the pathophysiology of the disease, related to most of the pathological processes of PD, as is the case of the greater activation of microglia in males or the lower oxidative stress in females. All these findings support the idea that different molecular mechanisms may be involved in PD depending on the sex of the patient. Some explanations for these events are related to biological, genetic, hormonal or environmental factors, such as the possible anti-inflammatory and neuroprotective effect of estrogens. However, the underlying molecular mechanisms have not yet been fully described. Our results show sex differences in gene expression, cell-cell communication and pathway activation in all major brain cell types, highlighting the presence of greater neuroinflammation in men and greater neurodegeneration in the SNpc in men, with the latter appearing to be inverted between sexes when observed in the cortical zone. Finally, we have made all the results available in a publicly accessible webtool, in order to allow the exploration of results to other researchers and to broaden the molecular-level understanding of PD sex differences.

neuroscience↗

bioRxiv2024

Transcriptomic landscape of sex differences in obesity and type 2 diabetes in subcutaneous adipose tissue

Obesity represents a significant risk factor in the development of type 2 diabetes (T2D), a chronic metabolic disorder characterized by elevated blood glucose levels. Significant sex differences have been identified in the prevalence, development, and pathophysiology of obesity and T2D; however, the underlying molecular mechanisms remain unclear. This study aims to identify sex-specific biomarkers in obesity and T2D and enhance our understanding of the underlying mechanisms associated with sex differences by integrating expression data. A systematic review, individual transcriptomic analysis, gene-level meta-analysis, and functional characterization were performed to achieve this aim. Eight studies and 236 subcutaneous adipose tissue samples were analyzed, identifying common and sex-specific biomarkers, many of which were previously associated with obesity or T2D. The obesity meta-analysis yielded nineteen differentially-expressed biomarkers from a sex-specific perspective (e.g., SPATA18, KREMEN1, NPY4R, and PRM3), while a comparison of the expression profiles between sexes in T2D prompted the identification and validation of specific transcriptomic signatures in males (SAMD9, NBPF3, LDHD, and EHD3) and females (RETN, HEY1, PLPP2, and PM20D2). At the functional level, we highlighted the fundamental role of the Wnt pathway in the development of obesity and T2D in females and the roles of more significant mitochondrial damage and free fatty acids in males. Overall, our sex-specific meta-analyses supported the detection of differentially expressed genes in males and females associated with the development of obesity and T2D, emphasizing the relevance of sex-based information in biomedical data and opening new avenues for research. HighlightsO_LIFirst meta-analysis on WAT with sex as a central perspective in obesity and T2D C_LIO_LIThis study identifies 19 sex-differential biomarkers in obesity, highlighting NPY4 C_LIO_LISex specific transcriptional signatures in SAT in the development of T2D C_LIO_LIWnt pathway genes show sex-specific roles in obesity and T2D, notably in females C_LIO_LIObesity increases mitogenesis in male, mediated by SPATA18, with an increased role of free fatty acids in T2D C_LI

molecular biology↗

bioRxiv2024

Single cell landscape of sex differences in the progression of multiple sclerosis

BackgroundOne of the major challenges in addressing multiple sclerosis is to understand its progression trajectory. The pathological process transitions from acute phases predominantly driven by inflammation to progressive clinical profiles where neurodegeneration takes precedence. It is known that sex plays a crucial role in this heterogeneity; females are two to three times more likely to suffer from multiple sclerosis, while males suffer from more rapid neurodegeneration with greater severity. ResultsTo gain insight into the sex-based molecular differences, we processed single cell datasets from the central nervous system and the peripheral blood, covering the different courses of multiple sclerosis. We generated cell-type specific landscapes, including gene signatures from differentially expressed genes, functional profiling, pathway activation, and cell-cell communication networks for females, males, and their sex differential profiles. Among our findings, we revealed that female neurons may exhibit protective mechanisms against neurodegeneration. In the inflammatory-predominant forms, female immune cells present an inflammatory core driven by the AP-1 transcription factor, while male adaptive immune cells exhibit higher mitochondrial impairment. Conversely, larger differences are reported in CD8+ T cells progressive forms, with males exhibiting cytolytic profiles that may promote neurodegeneration. Complete results can be explored in the interactive webtool https://bioinfo.cipf.es/cbl-atlas-ms/. ConclusionsWe identified cell-type specific sex differences in brain and immune cells that vary in the spectrum of multiple sclerosis. We consider this molecular description a valuable resource to promote future targeted approaches considering the sex of the individual.

neuroscience↗

bioRxiv2024

A spinal cord injury time and severity consensus transcriptomic reference suite in rat reveals translationally-relevant biomarker genes

Spinal cord injury (SCI) is a devastating condition that leads to motor, sensory, and autonomic dysfunction. Current therapeutic options remain limited, emphasizing the need for a comprehensive understanding of the underlying SCI-associated molecular mechanisms. This study characterized distinct SCI phases and severities at the gene and functional levels, focusing on biomarker gene identification. Our approach involved a systematic review, individual transcriptomic analysis, gene meta-analysis, and functional characterization. We compiled a total of fourteen studies with 273 samples, leading to the identification of severity-specific biomarker genes for injury prognosis (e.g., Srpx2, Hoxb8, Acap1, Snai1, and Aadat) and phase-specific genes for the precise classification of the injury profile (e.g., Il6, Fosl1, Cfp, C1qc, Cp). We investigated the potential transferability of severity-associated biomarkers and identified a twelve-gene signature that predicted injury prognosis from human blood samples. We also report the development of MetaSCI-app - an interactive web application designed for researchers - that allows the exploration and visualization of all generated results (https://metasci-cbl.shinyapps.io/metaSCI). Overall, we present a transcriptomic reference and provide a comprehensive framework for assessing SCI considering severity and time perspectives. TeaserA transcriptomic meta-analysis of spinal cord injury provides a consensus reference and biomarker genes for injury phase/severity.

neuroscience↗

bioRxiv2024

Unveiling common transcriptomic features between melanoma brain metastases and neurodegenerative diseases

Melanoma represents a critical clinical challenge due to its high incidence rates and unfavorable clinical outcomes. This type of skin cancer presents unique adaptability to the brain microenvironment, but its underlying molecular mechanisms are poorly understood. To further characterize its tumor neurobiology, we explore the relation between the transcriptional profiles of melanoma brain metastasis (MBM) and the neurodegenerative diseases Alzheimers disease, Parkinsons disease, and multiple sclerosis. Through an in silico approach, we unveiled the neurodegenerative signature of MBM when compared to melanoma non-brain metastasis (53 dysregulated genes enriched in 11 functional terms) and to non tumor-bearing brain controls (195 dysregulated genes, mostly involved in development and cell differentiation, chromatin remodeling and nucleosome organization, and translation). Two genes, ITGA10 and DNAJC6, emerged as key potential markers, as they are dysregulated in both scenarios. Lastly, we developed a user-friendly web tool (https://bioinfo.cipf.es/metafun-mbm/) as an open source, so that any user can interactively delve into the results.

cancer biology↗

bioRxiv2023

An integrated approach to identify sex-specific genes, transcription factors, and pathways in Alzheimer's disease

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/556293v3_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@4a60d7org.highwire.dtl.DTLVardef@11bd7eborg.highwire.dtl.DTLVardef@fc9b69org.highwire.dtl.DTLVardef@3f239f_HPS_FORMAT_FIGEXP M_FIG C_FIG BackgroundAge represents a significant risk factor for the development of Alzheimers disease (AD); however, recent research has documented an influencing role of sex in several features of AD. Understanding the impact of sex on specific molecular mechanisms associated with AD remains a critical challenge to creating tailored therapeutic interventions. MethodsThe exploration of the sex-based differential impact on disease (SDID) in AD used a systematic review to first select transcriptomic studies of AD with data regarding sex in the period covering 2002 to 2021 with a focus on the primary brain regions affected by AD - the cortex (CT) and the hippocampus (HP). A differential expression analysis for each study and two tissue-specific meta-analyses were then performed. Focusing on the CT due to the presence of significant SDID-related alterations, a comprehensive functional characterization was conducted: protein-protein network interaction and over-representation analyses to explore biological processes and pathways and a VIPER analysis to estimate transcription factor activity. ResultsWe selected 8 CT and 5 HP studies from the Gene Expression Omnibus (GEO) repository for tissue-specific meta-analyses. We detected 389 significantly altered genes in the SDID comparison in the CT. Generally, female AD patients displayed more affected genes than males; we grouped said genes into six subsets according to their expression profile in female and male AD patients. Only subset I (repressed genes in female AD patients) displayed significant results during functional profiling. Female AD patients demonstrated more significant impairments in biological processes related to the regulation and organization of synapsis and pathways linked to neurotransmitters (glutamate and GABA) and protein folding, A{beta} aggregation, and accumulation compared to male AD patients. These findings could partly explain why we observe more pronounced cognitive decline in female AD patients. Finally, we detected 23 transcription factors with different activation patterns according to sex, with some associated with AD for the first time. All results generated during this study are readily available through an open web resource Metafun-AD (https://bioinfo.cipf.es/metafun-ad/). ConclusionOur meta-analyses indicate the existence of differences in AD-related mechanisms in female and male patients. These sex-based differences will represent the basis for new hypotheses and could significantly impact precision medicine and improve diagnosis and clinical outcomes in AD patients. HighlightsO_LIFemale AD patients possess more affected genes than male AD patients. C_LIO_LI389 genes from the sex-based differential impact on disease comparison significantly impact the cerebral cortex and suggest a more significant effect on cognitive function in female AD patients. C_LIO_LIThe cluster of repressed genes in female AD patients functionally impacts glutamate and GABA neurotransmitters and A{beta} deposition. C_LIO_LIFemale AD patients exhibit several transcription factors with significantly different activity patterns compared to male AD patients. C_LIO_LIThis work includes Metafun-AD, an open and interactive web tool to explore all generated data and results. C_LI

neuroscience↗

bioRxiv2023

The role of microRNAs to understand sex-based differences in Alzheimer's disease

BackgroundThe incidence of Alzheimers disease (AD) - the most frequent cause of dementia - is expected to increase as life expectancies rise across the globe. While sex-based differences in AD have previously been described, there remain uncertainties regarding any association between sex and disease-associated molecular mechanisms. Studying sex-specific expression profiles of regulatory factors such as microRNAs (miRNAs) could contribute to more accurate disease diagnosis and treatment. MethodsA systematic review identified five studies of microRNA expression in AD patients that incorporated information regarding the biological sex of samples in the Gene Expression Omnibus repository. A differential microRNA expression analysis was performed, considering disease status and patient sex. Subsequently, results were integrated within a meta-analysis methodology, with a functional enrichment of meta-analysis results establishing an association between altered miRNA expression and relevant Gene Ontology terms. ResultsMeta-analyses of miRNA expression profiles in blood samples revealed the alteration of sixteen miRNAs in female and twenty-two miRNAs in male AD patients. We discovered nine miRNAs commonly overexpressed in both sexes, suggesting a shared miRNA dysregulation profile. Functional enrichment results based on miRNA profiles revealed sex-based differences in biological processes; most affected processes related to ubiquitination, regulation of different kinase activities, and apoptotic processes in males, but RNA splicing and translation in females. Meta-analyses of miRNA expression profiles in brain samples revealed the alteration of six miRNAs in female and four miRNAs in male AD patients. We observed a single underexpressed miRNA in female and male AD patients (hsa-miR-767-5p); however, the functional enrichment analysis for brain samples did not reveal any specifically affected biological process. ConclusionsSex-specific meta-analyses supported the detection of differentially expressed miRNAs in female and male AD patients, highlighting the relevance of sex-based information in biomedical data. Further studies on miRNA regulation in AD patients should meet the criteria for comparability and standardization of information. HighlightsO_LIDeregulation of miRNA expression profiles occurs in a tissue- and sex-specific manner in AD patients C_LIO_LIMeta-analysis of blood samples revealed a partial overlapping pattern of altered miRNA expression in female and male AD patients C_LIO_LIFunctional enrichment based on AD-associated miRNA expression profiles in blood samples reveals sex-based differences: RNA splicing and translation in female AD patients and ubiquitination, regulation of different kinase activities, and apoptotic process in male AD patients C_LIO_LILinks between AD development and miRNA expression in brain tissue also demonstrate the influence of sex C_LI Plain English SummaryAlzheimers disease (AD) - a neurodegenerative disease mainly affecting older patients - is characterized by cognitive deterioration, memory loss, and progressive incapacitation in daily activities. While AD affects almost twice as many females as males, and cognitive deterioration and brain atrophy develop more rapidly in females, the biological causes of these differences remain poorly understood. MicroRNAs (miRNAs) regulate gene expression and impact a wide variety of biological processes; therefore, studying the differential expression of miRNAs in female and male AD patients could contribute to a better understanding of the disease. We reviewed studies of miRNA expression in female and male AD patients and integrated results using a meta-analysis methodology and then identified those genes regulated by the altered miRNAs to establish an association with biological processes. We found sixteen (females) and twenty-two (males) miRNAs altered in the blood of AD patients. Functional enrichment revealed sex-based differences in the affected altered biological processes - protein modification and degradation and cell death in male AD patients and RNA processing in female AD patients. A similar analysis in the brains of AD patients revealed six (females) and four (males) miRNAs with altered expression; however, our analysis failed to highlight any specifically altered biological processes. Overall, we highlight the sex-based differential expression of miRNAs (and biological processes affected) in the blood and brain of AD patients.

neuroscience↗

bioRxiv2023

A comprehensive transcriptional signature in pancreatic ductal adenocarcinoma reveals new insights into the immune and desmoplastic microenvironment

Pancreatic ductal adenocarcinoma (PDAC) prognosis and treatment response remains devastatingly poor due partly to the highly heterogeneous, aggressive, and immunosuppressive nature of this tumor type. The intricate relationship between stroma, inflammation, and immunity remains vaguely understood in the PDAC microenvironment. Here, we performed a meta-analysis of stroma-, and immune-related gene expression in the PDAC microenvironment to improve disease prognosis and therapeutic development. We selected twenty-one PDAC studies from the Gene Expression Omnibus and ArrayExpress databases, including 922 samples (320 controls and 602 cases). Differential gene enrichment analysis identified 1153 significant dysregulated genes in PDAC patients that contribute to a desmoplastic stroma and an immunosuppressive environment (the hallmarks of PDAC tumors). The results highlighted two gene signatures related to the immune and stromal environments that cluster PDAC patients in high- and low-risk groups, impacting patient stratification and therapeutic decision-making. Moreover, HCP5, SLFN13, IRF9, IFIT2, and IFI35 immune genes were related to prognosis value in PDAC patients, for the first time. Simple SummaryPancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with few curative options. Desmoplastic stroma and immune system evasion in PDAC represent challenges to the success of therapeutic strategies that function well in other tumor types. Characterizing the PDAC microenvironment (including the immune environment) remains critical to developing safe and efficient therapies. Here, we present a comprehensive meta-analysis identifying 1153 significantly dysregulated genes, which mainly impact extracellular matrix remodeling and the immune system. We identify two signatures of twenty-eight immune-related genes and eleven stroma-related genes influencing PDAC patient survival. Additionally, five immune genes are associated with PDAC prognosis for the first time.

cancer biology↗

bioRxiv2023

Systematic review and meta-analysis of transcriptomic studies on different brain regions reveals different sex-based profiles in schizophrenic patients

BackgroundSchizophrenia is a severe neuropsychiatric disorder characterized by altered perception, mood, and behavior that profoundly impacts patients and society despite its relatively low prevalence. Previous studies have suggested that the dopamine D2 receptor gene and genes involved in glutamatergic neurotransmission, synaptic plasticity, and immune function as genetic risk factors. Sex-based differences also exist in schizophrenia epidemiology, symptomatology and outcomes; however, we lack a transcriptomic profile that considers sex and differentiates specific cerebral regions. MethodsWe performed a systematic review on bulk RNA-sequencing studies of post-mortem brain samples. Then, we fulfilled differential expression analysis on each study and summarized their results with regions-specific meta-analyses (prefrontal cortex and hippocampus) and a global all-studies meta-analysis. Finally, we used the consensus transcriptomic profiles to functionally characterize the impact of schizophrenia in males and females by protein-protein interaction networks, enriched biological processes and dysregulated transcription factors. ResultsWe discovered the sex-based dysregulation of 265 genes in the prefrontal, 1.414 genes in the hippocampus and 66 genes in the all-studies meta-analyses. The functional characterization of these gene sets unveiled increased processes related to immune response functions in the prefrontal cortex in male and the hippocampus in female schizophrenia patients and the overexpression of genes related to neurotransmission and synapses in the prefrontal cortex of female schizophrenia patients. Considering a meta-analysis of all brain regions available, we encountered the relative overexpression of genes related to synaptic plasticity and transmission in female and the overexpression of genes involved in organizing genetic information and protein folding in male schizophrenia patients. The protein-protein interaction networks and transcription factors activity analyses supported these sex-based profiles. ConclusionsOur results report multiple sex-based transcriptomic alterations in specific brain regions of schizophrenia patients, which provides new insight into the role of sex in schizophrenia. Moreover, we unveil a partial overlapping of inflammatory processes in the prefrontal cortex of males and the hippocampus of females. Plain language summarySchizophrenia is a severe neuropsychiatric disorder characterized by altered perception, mood, and behavior that profoundly impacts patients and society. Previous studies have suggested dopamine and glutamate neurotransmission genes, as well as immune function alteration as genetic risk factors. Schizophrenia epidemiology, symptomatology and outcomes are different for women and men, but the biological reason is not understood. Therefore, we reviewed all RNA-sequencing studies of post-mortem brain samples of women and men affected by schizophrenia available. Then, we compared the gene expression on each study for males and females and integrated the results of studies on different regions meta-analyses: prefrontal cortex, hippocampus and all-studies. Finally, we functionally characterize the impact of schizophrenia in males and females by protein-protein interaction networks, enriched biological processes and dysregulated transcription factors. We discovered the sex-based dysregulation of 265 genes in the prefrontal cortex, 1.414 genes in the hippocampus and 66 genes in the all-studies meta-analyses. The functional characterization of these genes unveiled increased immune response functions in the prefrontal cortex in men and the hippocampus in women schizophrenia patients, as well as increased neurotransmission and synapses in the prefrontal cortex of female schizophrenia patients. The protein-protein interaction networks and transcription factors activity analyses supported these sex-based profiles. Our results report multiple transcriptomic alterations in specific brain regions of schizophrenia patients, which provides new insight into the role of sex in schizophrenia. Moreover, we unveil a partial overlapping of inflammatory processes in the prefrontal cortex of males and the hippocampus of females. HighlightsO_LIThe expression of 265 genes is altered in the prefrontal cortex of schizophrenic patients, being overexpressed in females those related to synaptic transmission. C_LIO_LIIn the prefrontal cortex of males, overexpressed genes and overactivated transcription factors are linked to immune response and inflammation. C_LIO_LIConversely, genes and transcription factors more activated in the hippocampus of females are related to immune response, whereas those genes more expressed in males are linked to protein processing. C_LIO_LIThe global meta-analysis unveils groups of long non-coding genes and pseudogenes differentially expressed in males and females. C_LIO_LIThe effects of schizophrenia are closely related in the prefrontal cortex of males and the hippocampus of females. C_LI

molecular biology↗

bioRxiv2022

DNA Methylation Signatures in Breast Cancer: A Systematic Review and Meta-Analysis

Epigenetic changes are involved in the onset and progression of cancer, and the detection of DNA methylation signatures may foster the improvement of diagnosis and prognosis. While the emergence of innovative technologies has fostered numerous studies in breast cancer, many lack statistical power due to the small sample sizes generally involved. In this study, we present a novel meta-analysis that identifies a common pattern of DNA methylation in all breast cancer subtypes. We obtained DNA methylation signatures at the gene and biological function level, identifying those significant groups of genes and functional pathways affected. To achieve this, we conducted a thorough systematic review following PRISMA statement guidelines for the selection of studies on DNA methylation in breast cancer. In total, we gathered four studies (GSE52865, GSE141338, GSE59901 and GSE101443) that were split into 13 comparisons comprising a set of 144 individuals. We discovered that most breast cancer subtypes share a significant deregulation in the immune system and alterations to the cell cycle. This integrative approach combines all available information from public data repositories and possesses greater statistical power than any individual study. Further evaluations of the identified differential biological processes and pathways may support the identification of novel biomarkers and therapeutic targets. Simple summaryThe identification of DNA methylation patterns in breast cancer represents a potentially valuable approach in defining more accurate diagnoses and treatment options. In this study, we applied a novel methodology that integrates the DNA methylation profiles of all studies available in public repositories via systematic review and meta-analysis. The results provide evidence of a common DNA methylation signature in distinct breast cancer subtypes, which reflects a significant deregulation of the immune system and alterations to the cell cycle. Overall, these results may support the selection of disease/treatment biomarkers and the identification of therapeutic targets.

cancer biology↗

bioRxiv2021

Sex bias evaluation of classic and novel Housekeeping Genes in adipose tissue through the massive analysis of transcriptomics data

BackgroundAs the housekeeping genes (HKG) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, HKG may vary gene expression profile according to different variables introducing systematic errors into experimental results. Sex bias can indeed affect expression display, however, up to date, sex has not been typically considered as a biological variable. MethodsIn this study, we evaluate the expression profiles of six classical housekeeping genes (four metabolic: GAPDH, HPRT, PPIA, and UBC, and two ribosomal: 18S and RPL19) to determine expression stability in adipose tissues (AT) of Homo sapiens and Mus musculus and check sex bias and their overall suitability as internal controls. We also assess the expression stability of all genes included in distinct whole-transcriptome microarrays available from the Gene Expression Omnibus database to identify sex-unbiased housekeeping genes (suHKG) suitable for use as internal controls. We perform a novel computational strategy based on meta-analysis techniques to identify any sexual dimorphisms in mRNA expression stability in AT and to properly validate potential candidates. ResultsJust above half of the considered studies informed properly about the sex of the human samples, however, not enough female mouse samples were found to be included in this analysis. We found differences in the HKG expression stability in humans between female and male samples, with females presenting greater instability. We propose a suHKG signature including experimentally validated classical HKG like PPIA and RPL19 and novel potential markers for human AT and discarding others like the extensively used 18S gene due to a sex-based variability display in adipose tissue. Orthologs have also been assayed and proposed for mouse WAT suHKG signature. All results generated during this study are readily available by accessing an open web resource (https://bioinfo.cipf.es/metafun-HKG) for consultation and reuse in further studies. ConclusionsThis sex-based research proves that certain classical housekeeping genes fail to function adequately as controls when analyzing human adipose tissue considering sex as a variable. We confirm RPL19 and PPIA suitability as sex-unbiased human and mouse housekeeping genes derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB. HighlightsO_LIA computational strategy based on massive data analysis revealed that an accurate experimental design for adipose tissue requires the adequate selection of a sex-unbiased housekeeping genes (HKG). C_LIO_LIThe extensively used 18S gene displays sex-based variability in adipose tissue, although PPIA and RPL19 do not, and hence, represent robust HKG. C_LIO_LINew sex-unbiased human and mouse candidate HKG: RPS8 and UBB. C_LIO_LImetafun-HKG (https://bioinfo.cipf.es/metafun-HKG): a freely available web tool to allow users to review stable expression levels of candidate HKG along the large volume of FAIR data. C_LI

genomics↗

bioRxiv2021

MetaFun: Unveiling sex differences in multiple omics studies through comprehensive functional meta-analysis

While sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack a deep analysis of sex as a variable in this context. To fill this knowledge gap, we created MetaFun as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness. Furthermore, MetaFun can be used to perform case-control meta-analyses, allowing researchers with basic programming skills to access this methodology. Availability and implementationMetaFun is freely available at http://bioinfo.cipf.es/metafun The back end was implemented in R and Java, and the front end was developed using Angular Contactfgarcia@cipf.es, mhidalgo@cipf.es Supplementary informationR code available at https://gitlab.com/ubb-cipf/metafunr

bioinformatics↗

bioRxiv2020

Unveiling sex-based differences in the effects of alcohol abuse: a comprehensive functional meta-analysis of transcriptomic studies

The abuse of alcohol, one of the most popular psychoactive substances, can cause several pathological and psychological consequences, including alcohol use disorder (AUD). An impaired ability to stop or control alcohol intake despite adverse health or social consequences characterize AUD. While AUDs predominantly occur in men, growing evidence suggests the existence of distinct cognitive and biological consequences of alcohol dependence in women. The molecular and physiological mechanisms participating in these differential effects remain unknown. Transcriptomic technology permits the detection of the biological mechanisms responsible for such sex-based differences, which supports the subsequent development of novel personalized therapeutics to treat AUD. We conducted a systematic review and meta-analysis of transcriptomics studies regarding alcohol dependence in humans with representation from both sexes. For each study, we processed and analyzed transcriptomic data to obtain a functional profile of pathways and biological functions and then integrated the resulting data by meta-analysis to characterize any sex-based transcriptomic differences associated with AUD. Global results of the transcriptomic analysis revealed the association of decreased tissue regeneration, embryo malformations, altered intracellular transport, and increased rate of RNA and protein replacement with female AUD patients. Meanwhile, our analysis indicated that increased inflammatory response and blood pressure and a reduction in DNA repair capabilities associated with male AUD patients. In summary, our functional meta-analysis of transcriptomic studies provides evidence for differential biological mechanisms that AUD patients of differing sex. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/254185v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@13c9becorg.highwire.dtl.DTLVardef@20aac4org.highwire.dtl.DTLVardef@ab5502org.highwire.dtl.DTLVardef@5a0d37_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

Mechanistic modeling of the SARS-CoV-2 disease map

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map in which the detailed activity of the human signaling circuits related to the viral infection and the different antiviral responses, including immune and inflammatory activities, can be inferred from gene expression experiments. Moreover, given to the mechanistic properties of the model, the effect of potential interventions, such as knock-downs, over-expression or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied in specific conditions. By providing a holistic, systems biology approach to the understanding of the complexities of the viral infection process, this tool will become an important asset in the search for efficient antiviral treatments. The tool is freely available at: http://hipathia.babelomics.org/covid19/

systems biology↗

bioRxiv2019

Mechanistic models of signaling pathways deconvolute the functional landscape of glioblastoma at single cell resolution

The rapid development of single cell RNA-sequencing (scRNA-seq) technologies is revealing an unexpectedly large degree of heterogeneity in gene expression levels across the different cells that compose the same tissue sample. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell-fate decisions to the collective behavior of the tissues these cells are part of. Mechanistic models of signaling pathways have already proven to be useful tools for understanding relevant aspects of cell functionality. Here we propose to use this mechanistic modeling strategy to deconvolute the complexity of the functional behavior of a tissue by dissecting it into the individual functional landscapes of its component cells by using a single-cell RNA-seq experiment of glioblastoma cells. This mechanistic modeling analysis revealed a high degree of heterogeneity at the scale of signaling circuits, suggesting the existence of a complex functional landscape at single cell level. Different clusters of neoplastic glioblastoma cells have been characterized according to their differences in signaling circuit activity profiles, which only partly overlap with the conventional glioblastoma subtype classification. The activity of signaling circuits that trigger cell functionalities which can easily be assimilated to cancer hallmarks reveals different functional strategies with different degrees of aggressiveness followed by any of the clusters. In addition, mechanistic modeling allows simulating the effect of interventions on the components of the signaling circuits, such as drug inhibitions. Thus, effects of drug inhibitions at single cell level can be dissected, revealing for the first time the mechanisms that individual cells use to avoid the effect of a targeted therapy which explain why and how a small proportion of cells display, in fact, different degrees of resistance to the treatment. The results presented here strongly suggest that mechanistic modeling at single cell level not only allows uncovering the molecular mechanisms of the tumor progression but also can predict the success of a treatment and can contribute to a better definition of therapeutic targets in the future.

systems biology↗

bioRxiv2018

Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models

Backgroundin spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling.\n\nResultswe present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway module metabolic activities that can also be used for class prediction and in silico prediction of Knock-Out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer.\n\nConclusionsMetabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.\n\nMetabolizer can be found at: http://metabolizer.babelomics.org.

bioinformatics↗

bioRxiv2017

Signaling Pathway Activities Improve Prognosis for Breast Cancer

With the advent of high-throughput technologies for genome-wide expression profiling, a large number of methods have been proposed to discover gene-based signatures as biomarkers to guide cancer prognosis. However, it is often difficult to interpret the list of genes in a prognostic signature regarding the underlying biological processes responsible for disease progression or therapeutic response. A particularly interesting alternative to gene-based biomarkers is mechanistic biomarkers, derived from signaling pathway activities, which are known to play a key role in cancer progression and thus provide more informative insights into cellular functions involved in cancer mechanism. In this study, we demonstrate that pathway-level features, such as the activity of signaling circuits, outperform conventional gene-level features in prediction performance in breast cancer prognosis. We also show that the proposed classification scheme can even suggest, in addition to relevant signaling circuits related to disease outcome, a list of genes that do not code for signaling proteins whose contribution to cancer prognosis potentially supplements the mechanisms detected by pathway analysis.

bioinformatics↗