Rare diseases may affect the quality of life of patients and be life-threatening. Therapeutic opportunities are often limited, in part because of the lack of understanding of the molecular mechanisms underlying these diseases. This can be ascribed to the low prevalence of rare diseases and therefore the lower sample sizes available for research. A way to overcome this is to integrate experimental rare disease data with prior knowledge using network-based methods. Taking this one step further, we hypothesized that combining and analyzing the results from multiple network-based methods could provide data-driven hypotheses of pathogenic mechanisms from multiple perspectives.We analyzed a Huntington's disease transcriptomics dataset using six network-based methods in a collaborative way. These methods either inherently reported enriched annotation terms or their results were fed into enrichment analyses. The resulting significantly enriched Reactome pathways were then summarized using the ontological hierarchy which allowed the integration and interpretation of outputs from multiple methods. Among the resulting enriched pathways, there are pathways that have been shown previously to be involved in Huntington's disease and pathways whose direct contribution to disease pathogenesis remains unclear and requires further investigation.In summary, our study shows that collaborative network analysis approaches are well-suited to study rare diseases, as they provide hypotheses for pathogenic mechanisms from multiple perspectives. Applying different methods to the same case study can uncover different disease mechanisms that would not be apparent with the application of a single method.
Spatial transcriptomics is revolutionizing modern biology, offering researchers an unprecedented ability to unravel intricate gene expression patterns within tissues. From pioneering techniques to newly commercialized platforms, the field of spatial transcriptomics has evolved rapidly, ushering in a new era of understanding across various disciplines, from developmental biology to disease research. This dynamic expansion is reflected in the rapidly growing number of technologies and data analysis techniques developed and introduced. However, the expanding landscape presents a considerable challenge for researchers, especially newcomers to the field, as staying informed about these advancements becomes increasingly complex. To address this challenge, we have prepared an updated review with a particular focus on technologies that have reached commercialization and are, therefore, accessible to a broad spectrum of potential new users. In this review, we present the fundamental principles of spatial transcriptomic methods, discuss the challenges in data analysis, provide insights into experimental considerations, offer information about available resources for spatial transcriptomics, and conclude with a guide for method selection and a forward-looking perspective. Our aim is to serve as a guiding resource for both experienced users and newcomers navigating the complex realm of spatial transcriptomics in this era of rapid development. We intend to equip researchers with the necessary knowledge to make informed decisions and contribute to the cutting-edge research that spatial transcriptomics offers.
- MeSH
- Humans MeSH
- Gene Expression Profiling * methods MeSH
- Transcriptome * MeSH
- Computational Biology methods MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
BACKGROUND: Inebilizumab is an anti-CD19 antibody approved for the treatment of neuromyelitis optica spectrum disorder (NMOSD) in adults with aquaporin-4 autoantibodies. The relationship between B-cell, plasma-cell (PC), and immunoglobulin depletion with longitudinal reductions in NMOSD activity after inebilizumab treatment was characterised post hoc in an exploratory analysis from the N-MOmentum study (NCT02200770). METHODS: Peripheral blood CD20+ B cells, PC gene signature, and immunoglobulin levels were assessed throughout N-MOmentum (follow-up ≥2.5 years); correlations with clinical metrics and magnetic resonance imaging (MRI) lesion activity were assessed. FINDINGS: Inebilizumab induced durable B-cell and PC depletion within 1 week versus placebo. Although no association was observed between B-cell counts at time of attack and NMOSD activity, depth of B-cell depletion after the first dosing period correlated with clinical outcomes. All participants receiving inebilizumab demonstrated a robust long-term therapeutic response, and participants with ≤4 cells/μL after the first 6-month dosing interval had persistently deeper B-cell depletion, lower annualised attack rates (estimated rate [95% CI]: 0.034 [0.024-0.04] vs 0.086 [0.056-0.12]; p = 0.045), fewer new/enlarging T2 MRI lesions (0.49 [0.43-0.56] vs 1.36 [1.12-1.61]; p < 0.0001), and a trend towards decreased Expanded Disability Status Scale worsening (0.076 [0.06-0.10] vs 0.14 [0.10-0.18]; p = 0.093). Antibodies to inebilizumab, although present in a proportion of treated participants, did not alter outcomes. INTERPRETATION: This analysis suggests that compared with placebo, inebilizumab can provide specific, rapid, and durable depletion of B cells in participants with NMOSD. Although deep and persistent CD20+ B-cell depletion correlates with long-term clinical stability, early, deep B-cell depletion correlates with improved disease activity metrics in the first 2 years. FUNDING: Horizon Therapeutics (formerly from Viela Bio/MedImmune).
- MeSH
- Antigens, CD19 MeSH
- Autoantibodies MeSH
- B-Lymphocytes MeSH
- Adult MeSH
- Double-Blind Method MeSH
- Humans MeSH
- Magnetic Resonance Imaging MeSH
- Neuromyelitis Optica * drug therapy pathology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Clinical Trial, Phase II MeSH
- Clinical Trial, Phase III MeSH
- Multicenter Study MeSH
- Randomized Controlled Trial MeSH
Spontaneous preterm birth is a serious medical condition responsible for substantial perinatal morbidity and mortality. Its phenotypic characteristics, preterm labor with intact membranes (PTL) and preterm premature rupture of the membranes (PPROM), are associated with significantly increased risks of neurological and behavioral alterations in childhood and later life. Recognizing the inflammatory milieu associated with PTL and PPROM, here, we examined expression signatures of placental tryptophan metabolism, an important pathway in prenatal brain development and immunotolerance. The study was performed in a well-characterized clinical cohort of healthy term pregnancies (n = 39) and 167 preterm deliveries (PTL, n = 38 and PPROM, n = 129). Within the preterm group, we then investigated potential mechanistic links between differential placental tryptophan pathway expression, preterm birth and both intra-amniotic markers (such as amniotic fluid interleukin-6) and maternal inflammatory markers (such as maternal serum C-reactive protein and white blood cell count). We show that preterm birth is associated with significant changes in placental tryptophan metabolism. Multifactorial analysis revealed similarities in expression patterns associated with multiple phenotypes of preterm delivery. Subsequent correlation computations and mediation analyses identified links between intra-amniotic and maternal inflammatory markers and placental serotonin and kynurenine pathways of tryptophan catabolism. Collectively, the findings suggest that a hostile inflammatory environment associated with preterm delivery underlies the mechanisms affecting placental endocrine/transport functions and may contribute to disruption of developmental programming of the fetal brain.
- MeSH
- Biomarkers MeSH
- Humans MeSH
- Metabolic Networks and Pathways MeSH
- Disease Susceptibility MeSH
- Placenta metabolism MeSH
- Premature Birth diagnosis etiology metabolism MeSH
- Gene Expression Regulation MeSH
- Risk Factors MeSH
- Gene Expression Profiling MeSH
- Pregnancy MeSH
- Transcriptome * MeSH
- Tryptophan metabolism MeSH
- Computational Biology methods MeSH
- Pregnancy Outcome MeSH
- Inflammation complications etiology MeSH
- Check Tag
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: Prostate cancer is caused by genomic aberrations in normal epithelial cells, however clinical translation of findings from analyses of cancer cells alone has been very limited. A deeper understanding of the tumour microenvironment is needed to identify the key drivers of disease progression and reveal novel therapeutic opportunities. RESULTS: In this study, the experimental enrichment of selected cell-types, the development of a Bayesian inference model for continuous differential transcript abundance, and multiplex immunohistochemistry permitted us to define the transcriptional landscape of the prostate cancer microenvironment along the disease progression axis. An important role of monocytes and macrophages in prostate cancer progression and disease recurrence was uncovered, supported by both transcriptional landscape findings and by differential tissue composition analyses. These findings were corroborated and validated by spatial analyses at the single-cell level using multiplex immunohistochemistry. CONCLUSIONS: This study advances our knowledge concerning the role of monocyte-derived recruitment in primary prostate cancer, and supports their key role in disease progression, patient survival and prostate microenvironment immune modulation.
- MeSH
- Molecular Sequence Annotation MeSH
- Immunophenotyping MeSH
- Immunohistochemistry MeSH
- Kaplan-Meier Estimate MeSH
- Humans MeSH
- Monocytes metabolism pathology MeSH
- Tumor Microenvironment genetics MeSH
- Prostatic Neoplasms diagnosis genetics metabolism mortality MeSH
- Prognosis MeSH
- Disease Progression MeSH
- Gene Expression Profiling * methods MeSH
- Transcriptome * MeSH
- Computational Biology methods MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
Statins have been widely used for the treatment of hypercholesterolemia due to their ability to inhibit HMG-CoA reductase, the rate-limiting enzyme of de novo cholesterol synthesis, via the so-called mevalonate pathway. However, their inhibitory action also causes depletion of downstream intermediates of the pathway, resulting in the pleiotropic effects of statins, including the beneficial impact in the treatment of cancer. In our study, we compared the effect of all eight existing statins on the expression of genes, the products of which are implicated in cancer inhibition and suggested the molecular mechanisms of their action in epigenetic and posttranslational regulation, and in cell-cycle arrest, death, migration, or invasion of the cancer cells.
- MeSH
- Cell Death MeSH
- Epigenesis, Genetic MeSH
- Mevalonic Acid metabolism MeSH
- Humans MeSH
- Cell Line, Tumor MeSH
- Pancreatic Neoplasms drug therapy genetics metabolism pathology MeSH
- Cell Movement MeSH
- Cell Proliferation MeSH
- Antineoplastic Agents pharmacology MeSH
- Hydroxymethylglutaryl-CoA Reductase Inhibitors pharmacology MeSH
- Transcriptome drug effects MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Comparative Study MeSH
Gene expression profiling was made more cost-effective by the NIH LINCS program that profiles only ∼1, 000 selected landmark genes and uses them to reconstruct the whole profile. The D-GEX method employs neural networks to infer the entire profile. However, the original D-GEX can be significantly improved. We propose a novel transformative adaptive activation function that improves the gene expression inference even further and which generalizes several existing adaptive activation functions. Our improved neural network achieves an average mean absolute error of 0.1340, which is a significant improvement over our reimplementation of the original D-GEX, which achieves an average mean absolute error of 0.1637. The proposed transformative adaptive function enables a significantly more accurate reconstruction of the full gene expression profiles with only a small increase in the complexity of the model and its training procedure compared to other methods.
Bacterial pathogens sense specific cues associated with different host niches and integrate these signals to appropriately adjust the global gene expression. Bordetella pertussis is a Gram-negative, strictly human pathogen of the respiratory tract and the etiological agent of whooping cough (pertussis). Though B. pertussis does not cause invasive infections, previous results indicated that this reemerging pathogen responds to blood exposure. Here, omics RNA-seq and LC-MS/MS techniques were applied to determine the blood-responsive regulon of B. pertussis. These analyses revealed that direct contact with blood rewired global gene expression profiles in B. pertussis as the expression of almost 20% of all genes was significantly modulated. However, upon loss of contact with blood, the majority of blood-specific effects vanished, with the exception of several genes encoding the T3SS-secreted substrates. For the first time, the T3SS regulator BtrA was identified in culture supernatants of B. pertussis. Furthermore, proteomic analysis identified BP2259 protein as a novel secreted T3SS substrate, which is required for T3SS functionality. Collectively, presented data indicate that contact with blood represents an important cue for B. pertussis cells.
- MeSH
- Molecular Sequence Annotation MeSH
- Bacterial Proteins metabolism MeSH
- Bordetella pertussis physiology MeSH
- Chromatography, Liquid MeSH
- Virulence Factors MeSH
- Genomics * methods MeSH
- Humans MeSH
- Proteomics * methods MeSH
- Gene Expression Regulation, Bacterial MeSH
- Type III Secretion Systems genetics metabolism MeSH
- Gene Expression Profiling MeSH
- Tandem Mass Spectrometry MeSH
- Transcriptome MeSH
- Virulence MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
The Banff 2019 kidney allograft pathology update excluded isolated tubulitis without interstitial inflammation (ISO-T) from the category of borderline (suspicious) for acute T cell-mediated rejection due to its proposed benign clinical outcome. In this study, we explored the molecular assessment of ISO-T. ISO-T or interstitial inflammation with tubulitis (I + T) was diagnosed in indication biopsies within the first 14 postoperative days. The molecular phenotype of ISO-T was compared to I + T either by using RNA sequencing (n = 16) or by Molecular Microscope Diagnostic System (MMDx, n = 51). RNA sequencing showed lower expression of genes related to interferon-y (p = 1.5 *10-16), cytokine signaling (p = 2.1 *10-20) and inflammatory response (p = 1.0*10-13) in the ISO-T group than in I + T group. Transcripts with increased expression in the I + T group overlapped significantly with previously described pathogenesis-based transcript sets associated with cytotoxic and effector T cell transcripts, and with T cell-mediated rejection (TCMR). MMDx classified 25/32 (78%) ISO-T biopsies and 12/19 (63%) I + T biopsies as no-rejection. ISO-T had significantly lower MMDx scores for interstitial inflammation (p = 0.014), tubulitis (p = 0.035) and TCMR (p = 0.016) compared to I + T. Fewer molecular signals of inflammation in isolated tubulitis suggest that this is also a benign phenotype on a molecular level.
- MeSH
- Allografts metabolism pathology MeSH
- Biomarkers * MeSH
- Biopsy MeSH
- Nephritis, Interstitial diagnosis etiology MeSH
- Humans MeSH
- Graft Survival genetics immunology MeSH
- Graft Rejection etiology metabolism pathology MeSH
- Gene Expression Profiling MeSH
- Transcriptome MeSH
- Kidney Transplantation * adverse effects MeSH
- Computational Biology MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The objective of the present study is to identify and evaluate informative indicators for the welfare of rainbow trout exposed to (A) a water temperature of 27 °C and (B) a stocking density of 100 kg/m3 combined with a temperature of 27 °C. The spleen-somatic and condition index, haematocrit and the concentrations of haemoglobin, plasma cortisol and glucose revealed non-significant differences between the two stress groups and the reference group 8 days after the onset of the experiments. The transcript abundance of almost 1,500 genes was modulated at least twofold in in the spleen of rainbow trout exposed to a critical temperature alone or a critical temperature combined with crowding as compared to the reference fish. The number of differentially expressed genes was four times higher in trout that were simultaneously challenged with high temperature and crowding, compared to trout challenged with high temperature alone. Based on these sets of differentially expressed genes, we identified unique and common tissue- and stress type-specific pathways. Furthermore, our subsequent immunologic analyses revealed reduced bactericidal and inflammatory activity and a significantly altered blood-cell composition in challenged versus non-challenged rainbow trout. Altogether, our data demonstrate that heat and overstocking exert synergistic effects on the rainbow trout's physiology, especially on the immune system.
- MeSH
- Glucose metabolism MeSH
- Hemoglobins analysis MeSH
- Hydrocortisone blood MeSH
- Immune System immunology MeSH
- Crowding * MeSH
- Oncorhynchus mykiss genetics immunology MeSH
- Heat-Shock Response * MeSH
- Fish Proteins genetics metabolism MeSH
- Spleen immunology metabolism MeSH
- Gene Expression Profiling MeSH
- Transcriptome * MeSH
- Computational Biology MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
