An integrated approach to identifying sex-specific genes, transcription factors, and pathways relevant to Alzheimer's disease.

BACKGROUND: Age represents a significant risk factor for the development of Alzheimer's 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. METHODS: The 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. RESULTS: We 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, Aß 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/). CONCLUSION: Our 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.

A deep transcriptome meta-analysis reveals sex differences in multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2-3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females. METHODS: We performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. For each selected study, we analyzed differential gene expression to explore the impact of the disease in females (IDF), in males (IDM) and our main goal: the sex differential impact of the disease (SDID). Then, for each scenario (IDF, IDM and SDID) we performed 2 meta-analyses in the main tissues involved in the disease (brain and blood). Finally, we performed a gene set analysis in brain tissue, in which a higher number of genes were dysregulated, to characterize sex differences in biological pathways. RESULTS: After screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in brain tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and brain tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females (SDID comparison). Functional analyses in the brain revealed different altered immune patterns in females and males (IDF and IDM comparisons). The pro-inflammatory environment and innate immune responses related to myeloid lineage appear to be more affected in females, while adaptive responses associated with the lymphocyte lineage in males. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport. CONCLUSION: We found transcriptomic and functional differences between MS males and MS females (especially in the immune system), which may support the development of new sex-based research of this disease. Our study highlights the importance of understanding the role of biological sex in MS to guide a more personalized medicine.

Vascular differences between IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 at imaging and transcriptomic levels.

Global agreement in central nervous system (CNS) tumor classification is essential for predicting patient prognosis and determining the correct course of treatment, as well as for stratifying patients for clinical trials at international level. The last update by the World Health Organization of CNS tumor classification and grading in 2021 considered, for the first time, IDH-wildtype glioblastoma and astrocytoma IDH-mutant grade 4 as different tumors. Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 occur early and, importantly, contribute to gliomagenesis. IDH mutation produces a metabolic reprogramming of tumor cells, thus affecting the processes of hypoxia and vascularity, resulting in a clear advantage for those patients who present with IDH-mutated astrocytomas. Despite the clinical relevance of IDH mutation, current protocols do not include full sequencing for every patient. Alternative biomarkers could be useful and complementary to obtain a more reliable classification. In this sense, magnetic resonance imaging (MRI)-perfusion biomarkers, such as relative cerebral blood volume and flow, could be useful from the moment of presurgery, without incurring additional financial costs or requiring extra effort. The main purpose of this work is to analyze the vascular and hemodynamic differences between IDH-wildtype glioblastoma and IDH-mutant astrocytoma. To achieve this, we evaluate and validate the association between dynamic susceptibility contrast-MRI perfusion biomarkers and IDH mutation status. In addition, to gain a deeper understanding of the vascular differences in astrocytomas depending on the IDH mutation, we analyze the transcriptomic bases of the vascular differences.

Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review.

Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)-one of the most commonly used non-invasive neuroimaging methods for evaluating the structure of the brain-is often implemented along with automatic methods to diagnose FCD. In this review, we define three categories for FCD identification based on MRI: visual, semi-automatic, and fully automatic methods. By conducting a systematic review following the PRISMA statement, we identified 65 relevant papers that have contributed to our understanding of automatic FCD identification techniques. The results of this review present a comprehensive overview of the current state-of-the-art in the field of automatic FCD identification and highlight the progress made and challenges ahead in developing reliable, efficient methods for automatic FCD diagnosis using MRI images. Future developments in this area will most likely lead to the integration of these automatic identification tools into medical image-viewing software, providing neurologists and radiologists with enhanced diagnostic capabilities. Moreover, new MRI sequences and higher-field-strength scanners will offer improved resolution and anatomical detail for precise FCD characterization. This review summarizes the current state of automatic FCD identification, thereby contributing to a deeper understanding and the advancement of FCD diagnosis and management.

The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs.

We describe the curation, annotation methodology, and characteristics of the dataset used in an artificial intelligence challenge for detection and localization of COVID-19 on chest radiographs. The chest radiographs were annotated by an international group of radiologists into four mutually exclusive categories, including "typical," "indeterminate," and "atypical appearance" for COVID-19, or "negative for pneumonia," adapted from previously published guidelines, and bounding boxes were placed on airspace opacities. This dataset and respective annotations are available to researchers for academic and noncommercial use.

The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data.

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.

Visual analysis of automated segmentation in the diagnosis of focal cortical dysplasias with magnetic resonance imaging.

Focal cortical dysplasias (FCDs) are a frequent cause of epilepsy. It has been reported that up to 40% of them cannot be visualized with conventional magnetic resonance imaging (MRI). The main objective of this work was to evaluate by means of a retrospective descriptive observational study whether the automated brain segmentation is useful for detecting FCD. One hundred and fifty-five patients, who underwent surgery between the years 2009 and 2016, were reviewed. Twenty patients with FCD confirmed by histology and a preoperative segmentation study, with ages ranging from 3 to 43 years (14 men), were analyzed. Three expert neuroradiologists visually analyzed conventional and advanced MRI with automated segmentation. They were classified into positive and negative concerning visualization of FCD by consensus. Of the 20 patients evaluated with conventional MRI, 12 were positive for FCD. Of the negative studies for FCD with conventional MRI, 2 (25%) were positive when they were analyzed with automated segmentation. In 13 of the 20 patients (with positive segmentation for FCD), cortical thickening was observed in 5 (38.5%), while pseudothickening was observed in the rest of patients (8, 61.5%) in the anatomical region of the brain corresponding to the dysplasia. This work demonstrated that automated brain segmentation helps to increase detection of FCDs that are unable to be visualized in conventional MRI images.

Clinical decision support systems in child and adolescent psychiatry: a systematic review.

Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.

The impact of sex on gene expression in the brain of schizophrenic patients: a systematic review and meta-analysis of transcriptomic studies.

BACKGROUND: Schizophrenia is a severe neuropsychiatric disorder characterized by altered perception, mood, and behavior that profoundly impacts patients and society despite its relatively low prevalence. Sex-based differences have been described in schizophrenia epidemiology, symptomatology and outcomes. Different studies explored the impact of schizophrenia in the brain transcriptome, however we lack a consensus transcriptomic profile that considers sex and differentiates specific cerebral regions. METHODS: We 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. RESULTS: 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 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 females 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. CONCLUSIONS: Our 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.

Schizophrenia is a serious illness characterised by changes in perception, mood and behaviour that profoundly affect patients and society. The frequency, symptoms and progression of schizophrenia are different in women and men, but the biological reason for this is not understood. The identification of disease mechanisms specific in men and women, is relevant because it would allow a better understanding of this pathology, as well as improving the personalisation of diagnoses and treatments for patients. To achieve this goal, in this work we reviewed all available RNA sequencing studies of post-mortem brain samples from women and men affected by schizophrenia. Then, we compared gene expression in each study by sex, and integrated all study results in different brain regions: prefrontal cortex, hippocampus and all-studies. We discovered significant changes between men and women: 265 genes differentially expressed in the prefrontal cortex, 1414 genes in the hippocampus and 66 genes in meta-analyses of all-studies. The study of these genes revealed increased immune response functions in the prefrontal cortex of men and in the hippocampus of women with schizophrenia, as well as increased neurotransmission and synapses in the prefrontal cortex of women with schizophrenia. Our results report multiple gene expression changes in specific brain regions of patients with schizophrenia, providing new insights into the role of sex in schizophrenia.

Orbitofrontal cortex hypergyrification in hallucinating schizophrenia patients: Surface ratio as a promising brain biomarker.

The study of brain gyrification may provide useful information on the cytoarchitecture and connectivity of the brain. One of the methods that have been developed to estimate brain gyrification, known as surface ratio (SR), has not yet been studied in schizophrenia. Here we aimed to assess whether SR could provide new insights on the brain structure of schizophrenia patients and the severity of symptoms. We also computed a more established brain gyrification measure, namely absolute mean curvature (AMC). We analyzed 63 magnetic resonance images, 25 from schizophrenia patients with treatment-resistant auditory verbal hallucinations (SCH-H), 18 from schizophrenia patients without hallucinations (SCH-NH), and 20 from healthy controls (HC). The SR measure revealed that SCH-H patients had a more folded orbitofrontal cortex than SCH-NH patients and HC. Gyrification in this region was also negatively associated with positive symptoms, specifically with the delusions and conceptual disorganization items, only in the SCH-H group. Regarding the AMC measure, we identified two areas where HC showed more gyrification than SCH-H patients, but no relationships arose with symptoms. The hypergyrification of the orbitofrontal cortex displayed by SCH-H patients, as captured by the SR measure, suggests aberrant and/or excessive wiring in these patients, which in turn could give rise to auditory verbal hallucinations. Alternatively, we comment on potential compensatory mechanisms that may better explain the negative association between orbitofrontal gyrification and positive symptomatology. The SR measure captured the most relevant differences and associations, making it a promising biomarker in schizophrenia.

MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis.

BACKGROUND: While sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack sufficient tools and methods that allow for an in-depth analysis of sex as a variable in biomedical research. 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. DESCRIPTION: MetaFun is a complete suite that allows the analysis of transcriptomics data and the exploration of the results at all levels, performing single-dataset exploratory analysis, differential gene expression, gene set functional enrichment, and finally, combining results in a functional meta-analysis. Which biological processes, molecular functions or cellular components are altered in a common pattern in different transcriptomic studies when comparing male and female patients? This and other biological questions of interest can be answered with the use of MetaFun. This tool is available at https://bioinfo.cipf.es/metafun while additional help can be found at https://gitlab.com/ubb-cipf/metafunweb/-/wikis/Summary . CONCLUSIONS: Overall, Metafun is the first open-access web-based tool to identify consensus biological functions across multiple transcriptomic datasets, helping to elucidate sex differences in numerous diseases. Its use will facilitate the generation of novel biological knowledge that can be used in the research and application of Personalized Medicine considering the sex of patients.

The role of microRNAs in understanding sex-based differences in Alzheimer's disease.

BACKGROUND: The incidence of Alzheimer's 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. METHODS: A systematic review identified six 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. RESULTS: Meta-analyses of miRNA expression profiles in blood samples revealed the alteration of sixteen miRNAs in female and 22 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. CONCLUSIONS: Sex-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.

Alzheimer's disease (AD)­a neurodegenerative disease mainly affecting older patients­is 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 16 (females) and 22 (males) miRNAs altered in the blood of AD patients. Functional enrichment revealed sex-based differences in the affected altered biological processes­protein 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.

Unveiling common transcriptomic features between melanoma brain metastases and neurodegenerative diseases.

Melanoma represents a critical clinical challenge due to its unfavorable outcomes. This type of skin cancer exhibits unique adaptability to the brain microenvironment, but its underlying molecular mechanisms are poorly understood. Recent findings have suggested that melanoma brain metastases (MBM) may share biological processes similar to those found in various neurodegenerative diseases. To further characterize MBM development, we explore the relationship between the transcriptional profiles of MBM and the neurodegenerative diseases Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We take an in silico approach to unveil a neurodegenerative signature of MBM when compared to melanoma non-brain metastasis (53 dysregulated genes enriched in 11 functional terms, such as associated terms to the extracellular matrix and development) 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 being dysregulated in both scenarios. Lastly, we developed an open source, user-friendly web tool (https://bioinfo.cipf.es/metafun-mbm/) that allows interactive exploration of the complete results.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS).

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

The past, present, and future of the brain imaging data structure (BIDS).

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Automatic semantic segmentation of the lumbar spine: Clinical applicability in a multi-parametric and multi-center study on magnetic resonance images.

Significant difficulties in medical image segmentation include the high variability of images caused by their origin (multi-center), the acquisition protocols (multi-parametric), the variability of human anatomy, illness severity, the effect of age and gender, and notable other factors. This work addresses problems associated with the automatic semantic segmentation of lumbar spine magnetic resonance images using convolutional neural networks. We aimed to assign a class label to each pixel of an image, with classes defined by radiologists corresponding to structural elements such as vertebrae, intervertebral discs, nerves, blood vessels, and other tissues. The proposed network topologies represent variants of the U-Net architecture, and we used several complementary blocks to define the variants: three types of convolutional blocks, spatial attention models, deep supervision, and multilevel feature extractor. Here, we describe the topologies and analyze the results of the neural network designs that obtained the most accurate segmentation. Several proposed designs outperform the standard U-Net used as a baseline, primarily when used in ensembles, where the outputs of multiple neural networks are combined according to different strategies.

Deciphering the sex bias in housekeeping gene expression in adipose tissue: a comprehensive meta-analysis of transcriptomic studies.

BACKGROUND: As 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. METHODS: In 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. RESULTS: Just 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. CONCLUSIONS: This 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.

Housekeeping genes (HKG) are involved in the maintenance of essential cellular functions. They usually present constant expression levels and are relevant because of their usefulness as internal controls in gene expression studies. However, HKG can vary the gene expression profile depending on different variables such as sex, introducing errors in the experimental results. In this study, we have performed an exhaustive systematic review and applied a massive analysis of expression data to check which HKG presents this bias and which do not. The results confirm that certain classical HKG do not perform adequately as controls when analyzing human adipose tissue considering sex as a variable. We further confirm the suitability of RPL19 and PPIA as human and mouse HKG without sex bias derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB. These results will be of great use in upcoming studies where expression data need to be normalized without the inclusion of sex bias.

A Comprehensive Transcriptional Signature in Pancreatic Ductal Adenocarcinoma Reveals New Insights into the Immune and Desmoplastic Microenvironments.

Pancreatic ductal adenocarcinoma (PDAC) prognoses and treatment responses remain devastatingly poor due partly to the highly heterogeneous, aggressive, and immunosuppressive nature of this tumor type. The intricate relationship between the 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 21 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 into high- and low-risk groups, impacting patients' stratification and therapeutic decision making. Moreover, HCP5, SLFN13, IRF9, IFIT2, and IFI35 immune genes are related to the prognosis of PDAC patients for the first time.

Beyond the Brain: MIDS Extends BIDS to Multiple Modalities and Anatomical Regions.

Brain Imaging Data Structure (BIDS) provides a valuable tool to organise brain imaging data into a clear and easy standard directory structure. Moreover, BIDS is widely supported by the scientific community and has been established as a powerful standard for medical imaging management. Nonetheless, the original BIDS is restricted to magnetic resonance imaging (MRI) of the brain, limiting its implantation to other techniques and anatomical regions. We developed Medical Imaging Data Structure (MIDS), conceived to extend BIDS methodology to other anatomical regions and multiple imaging systems in these areas. The MIDS standard was developed to store and manage medical images as an extension of BIDS. It allows the user to handily save studies of multiple anatomical regions and imaging techniques. Besides, MIDS improves the classification of multiple images within the structure, allowing the possibility to unify them in a single study to apply on them preprocessing or artificial intelligence algorithms. Finally, the results generated are saved in the derivatives folder.

Unveiling sex-based differences in Parkinson's disease: a comprehensive meta-analysis of transcriptomic studies.

BACKGROUND: In recent decades, increasing longevity (among other factors) has fostered a rise in Parkinson's disease incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in Parkinson's disease as epidemiological and clinical features differ between males and females. METHODS: To study sex bias in Parkinson's disease, we conducted a systematic review to select sex-labeled transcriptomic data from three relevant brain tissues: the frontal cortex, the striatum, and the substantia nigra. We performed differential expression analysis on each study chosen. Then we summarized the individual differential expression results with three tissue-specific meta-analyses and a global all-tissues meta-analysis. Finally, results from the meta-analysis were functionally characterized using different functional profiling approaches. RESULTS: The tissue-specific meta-analyses linked Parkinson's disease to the enhanced expression of MED31 in the female frontal cortex and the dysregulation of 237 genes in the substantia nigra. The global meta-analysis detected 15 genes with sex-differential patterns in Parkinson's disease, which participate in mitochondrial function, oxidative stress, neuronal degeneration, and cell death. Furthermore, functional analyses identified pathways, protein-protein interaction networks, and transcription factors that differed by sex. While male patients exhibited changes in oxidative stress based on metal ions, inflammation, and angiogenesis, female patients exhibited dysfunctions in mitochondrial and lysosomal activity, antigen processing and presentation functions, and glutamic and purine metabolism. All results generated during this study are readily available by accessing an open web resource ( http://bioinfo.cipf.es/metafun-pd/ ) for consultation and reuse in further studies. CONCLUSIONS: Our in silico approach has highlighted sex-based differential mechanisms in typical Parkinson Disease hallmarks (inflammation, mitochondrial dysfunction, and oxidative stress). Additionally, we have identified specific genes and transcription factors for male and female Parkinson Disease patients that represent potential candidates as biomarkers to diagnosis.