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PubMed2026

Big data in multiple sclerosis.

PURPOSE OF REVIEW: This review summarizes recent key advancements in multiple sclerosis (MS) achieved through the utilization of big data from diverse sources and advanced analytical techniques. RECENT FINDINGS: Real-world evidence (RWE) derived from MS big data has significantly enhanced treatment strategies, redefined the concept of disease progression, refined prognostic models, and facilitated personalized medicine. RWE has highlighted the long-term benefits of early intensive treatment compared to escalation strategies, the unfavorable risk profile associated with treatment de-escalation and the importance of managing treatments during pregnancy. Additionally, it has revealed similarities and differences in the effectiveness and safety of specific high-efficacy therapies, as well as key predictors for switching treatments. RWE has also emphasized the central role of progression independent of relapse activity as a significant driver of disability and predictor of unfavorable long-term outcomes in both adult and pediatric onset MS. A data-driven approach utilizing artificial intelligence and big data has established a comprehensive framework for understanding the disease's evolution. Multimodal big data frameworks - encompassing clinical data, MRI, genomics, biomarkers, and app-based metrics - have demonstrated their ability to enhance diagnostic performance and risk stratification in MS. SUMMARY: Big data approaches are transforming MS research and clinical practice by providing stronger RWE to guide therapeutic decision-making, refining models of disease progression, and developing more precise prognostic tools.

Humans↗

PubMed2005

Gene expression analysis of peripheral blood leukocytes from discordant sib-pairs with schizophrenia and bipolar disorder reveals points of convergence between genetic and functional genomic approaches.

We performed global RNA transcript analysis and comprehensive gene group analysis of peripheral blood leukocyte (PBL) RNA from two groups of matched sib-pairs that were discordant for either schizophrenia (n = 33 sib-pairs) or bipolar disorder (n = 5 sib-pairs). The pairs chosen for these analyses were selected from families with known patterns of genetic linkage (5q for schizophrenia and 6q for bipolar disorder). At the single gene level, we obtained lists of the transcripts with the most significant changes in expression and from these lists determined those with the highest degree of predictive power for classifying subjects according to diagnosis in these samples. At the gene group level, we comprehensively analyzed pairwise expression changes of more than 4,000 functional groups and cytogenetic locations, and present a novel method of displaying these data that we term "cytogenomic" mapping. Verification of selected changes in expression was performed using quantitative real-time RT-PCR. Our results provide compelling evidence for the utility of analyzing PBL RNA for changes in expression in neuropsychiatric disorders.

Adult↗

PubMed2002

Identification of 2,3,7,8-tetrachlorodibenzo-p-dioxin-responsive genes in mouse liver by serial analysis of gene expression.

2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is one of the most toxic environmental pollutants that causes various biological effects on mammals. To identify the genes involved in hepatotoxicity and hepatocarcinogenesis induced by TCDD, we have conducted here serial analysis of gene expression of mouse liver 7 days after treatment with a single oral dose of 20 microg TCDD/kg body weight. We have sequenced total of 113,067 tags, including 56,420 tags and 56,647 tags from normal liver and TCDD-treated liver library, respectively. Statistical analysis showed that TCDD significantly altered 346 transcripts (p < 0.05) including 94 ESTs. The genes regulated by TCDD were not only the genes encoding drug metabolizing enzymes and stress response genes but also a wide variety of genes encoding cytoskeleton related proteins, signal transduction, and plasma proteins. This comprehensive gene expression analysis would provide novel genes that may help to clarify the mechanism of TCDD effects on mammalian liver, and also give a new approach for prevention and treatment.

Animals↗

PubMed2025

Spatial Genomic Approaches to Investigate HOX Genes in Mouse Brain Tissues.

Spatial transcriptomic tools are an upcoming and powerful way to investigate targeted gene expression patterns within tissues. These tools offer the unique advantage of visualizing and understanding gene expression while preserving tissue integrity, thereby maintaining the spatial context of genes. Curio is a robust spatial transcriptomic tool that facilitates high throughput comprehensive spatial gene expression analysis across the entir e transcriptome with high efficiency. Here, we present a bioinformatics protocol for performing whole transcriptome gene expression analysis of mouse brain tissue using Curio. Specifically, we demonstrate using computational techniques to visualize expression patterns of various HOX genes in the mouse brain.

Animals↗

PubMed2002

Heart-specific genes revealed by expressed sequence tag (EST) sampling.

BACKGROUND: Cardiovascular diseases are the primary cause of death worldwide; the identification of genes specifically expressed in the heart is thus of major biomedical interest. We carried out a comprehensive analysis of gene-expression profiles using expressed sequence tags (ESTs) to identify genes overexpressed in the human adult heart. The initial set of genes expressed in the heart was constructed by clustering and assembling ESTs from heart cDNA libraries. Expression profiles were then generated for each gene by counting their cognate ESTs in all libraries. Differential expression was assessed by applying a previously published statistical procedure to these profiles. RESULTS: We identified 35 cardiac-specific genes overexpressed in the heart, some of which displayed significant coexpression. Some genes had no previously recognized cardiac function. Of the 35 genes, 32 were mapped back onto the human genome sequence. According to Online Mendelian Inheritance in Man (OMIM), five genes were previously known as heart-disease genes and one gene was located in the locus of a bleeding disorder. Analysis of the promoter regions of this collection of genes provides the first list of putative regulatory elements associated with differential cardiac expression. CONCLUSION: This study shows that ESTs are still a powerful tool to identify differentially expressed genes. We present a list of genes specifically expressed in the human heart, one of which is a candidate for a bleeding disorder. In addition, we provide the first set of putative regulatory elements, the combination of which appears correlated with heart-specific gene expression.

Adult↗

PubMed2002

Global analysis of large-scale chemical and biological experiments.

Research in the life sciences is increasingly dominated by high-throughput data collection methods that benefit from a global approach to data analysis. Recent innovations that facilitate such comprehensive analyses are highlighted. Several developments enable the study of the relationships between newly derived experimental information, such as biological activity in chemical screens or gene expression studies, and prior information, such as physical descriptors for small molecules or functional annotation for genes. The way in which global analyses can be applied to both chemical screens and transcription profiling experiments using a set of common machine learning tools is discussed.

Animals↗

PubMed2004

Application of SELDI-TOF mass spectrometry for the identification of differentially expressed proteins in transformed follicular lymphoma.

Completion of the human genome project has focused scientific attention on the development of methods that permit rapid characterization of proteins that are encoded by the genome. Recent improvements in two-dimensional separation techniques in combination with protein identification software/databases and mass spectrometry (MS) now permit rapid comprehensive large-scale analysis of individual proteins within complex protein mixtures. We have performed pairwise comparisons of low-grade and transformed follicular lymphomas (FLs) in order to identify proteins that may be involved in FL progression using surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometer (ProteinChip, Ciphergen Biosystems). This system utilizes preactivated differential binding surfaces to achieve multidimensional chromatography. The protein-bound chips were then analyzed by a SELDI-TOF mass spectrometer to generate protein profiles. In preliminary experiments, we established that the MS data obtained from SELDI-TOF MS were reproducible, and that reduction in sample complexity improved the ability to detect lower abundance proteins. With specific regard to FL transformation, we rapidly identified a number of potential candidate proteins involved in this process. These included an upregulated 32 kDa protein and a down-regulated 11.8 kDa protein. Protein database searches revealed several candidates, among them cyclin D3 (32.5 kDa) and caspase 3 (11.8 kDa) whose differential expression were confirmed by immunoblotting and/or immunohistochemical analysis on the primary tissue specimens. Our studies demonstrate the utility of SELDI-TOF-MS for the rapid discovery of differentially expressed proteins using femtomolar quantities of crude protein derived from biopsy material. The versatility of this methodology supports its application to the rapid discovery of potential biomarkers in a variety of cellular systems.

Antigens, CD20↗

PubMed2026

Beyond in silico prediction: multi-omics to identify a pathogenic deep intronic HNRNPK variant in Au-Kline syndrome.

Pathogenic variants in HNRNPK are associated with autosomal dominant Au-Kline syndrome (AKS, Au-Kline-Okamoto syndrome, OMIM #616580). This syndrome is characterized by developmental delay and intellectual disability, hypotonia, and distinctive facial features. Despite the use of whole-genome sequencing (WGS) as a powerful diagnostic tool, we nearly dismissed a novel intronic variant (NM_031263.4(HNRNPK):c.214-55 T > A) affecting HNRNPK splicing and function. Although commonly used bioinformatic splice prediction tools, including SpliceAI and PDIVAS, yielded inconclusive results, Face2Gene analysis indicated a high phenotypic similarity to AKS. Characteristic facial features described by Choufani et al. [1] supported the clinical diagnosis of AKS. Subsequent functional studies demonstrated aberrant splicing with intron retention, and DNA methylation profiling revealed a positive HNRNPK-specific episignature. These insights and the de novo status support an evaluation as likely pathogenic. This case report supports the relevance of facial analysis and comprehensive variant validation strategies, particularly for deep intronic variants with ambiguous in silico splicing predictions.

Journal Article↗

PubMed2002

Identification of in vivo expressed vaccine candidate antigens from Staphylococcus aureus.

For the design of potent subunit vaccines, it is of paramount importance to identify all antigens immunologically recognized by a patient population infected with a pathogen. We have developed a rapid and efficient procedure to identify such commonly recognized antigens, and here we provide a comprehensive in vivo antigenic profile of Staphylococcus aureus, an important human pathogen. S. aureus peptides were displayed on the surface of Escherichia coli via fusion to one of two outer membrane proteins (LamB and FhuA) and probed with sera selected for high Ab titer and opsonic activity. A total of 60 antigenic proteins were identified, most of which are located or predicted to be located on the surface of the bacterium or secreted. The identification of these antigens and their reactivity with individual sera from patients and healthy individuals greatly facilitate the selection of promising vaccine candidates for further evaluation. This approach, which makes use of whole genome sequence information, has the potential to greatly accelerate and facilitate the formulation of novel vaccines and is applicable to any pathogen that induces Abs in humans and/or experimental animals.

Amino Acid Sequence↗

PubMed2025

The application of AI-driven and engineered intratumoral microbes in cancer therapy.

BACKGROUND: Although investigations of the intratumoral microbiota date back thousands of years, breakthrough transformations have only recently been achieved through high-throughput sequencing and multiomic technologies. These advances have revealed diverse and tumor type-specific microbial communities that drive carcinogenesis via immunomodulation, metabolic reprogramming, and genomic instability. Current cornerstones of cancer therapies-including chemotherapy, radiotherapy, immunotherapy, and targeted therapy-are limited by systemic toxicity, localized tissue damage, drug resistance, and low patient response rates. These constraints underscore the urgent need for more effective and precise therapeutic strategies. MAIN BODY: This review comprehensively integrates artificial intelligence (AI) technologies into the characterization of the intratumoral microbiota, facilitating the development of novel computational pipelines for mapping microbe-host crosstalk. We systematically summarize recent advances in engineered microbial therapeutics, including bacteria designed for targeted antitumor activity and engineered microorganisms that enable the localized delivery of therapeutic agents. Furthermore, this review critically evaluates the safety profiles of microbiota-based interventions and discusses key challenges in clinical translation. CONCLUSIONS: By combining cutting-edge computational technologies, biological research, and clinical insights, this review aims to bridge the gap between microbiome science and oncological practice, pioneering innovative strategies for microbiota-guided diagnostics and personalized cancer therapy.

Humans↗

PubMed2006

Putting the 'Ome' in lipid metabolism.

The recognition that altered lipid metabolism underlies many metabolic disorders challenging Western society highlights the importance of this metabolomic subset, herein referred to as the lipidome. Although comprehensive lipid analyses are not a recent concept, the novelty of a lipidomic approach lies with the application of robust statistical algorithms to highlight subtle, yet significant, changes in a population of lipid molecules. First-generation lipidomic studies have demonstrated the sensitivity of interpreting quantitative datasets with computational software; however, the innate power of comprehensive lipid profiling is often not exploited, as robust statistical models are not routinely utilized. Therefore, the current review aims to briefly describe the current technologies suitable for comprehensive lipid analysis, outline innovative mathematical models that have the ability to reveal subtle changes in metabolism, which will ameliorate our understanding of lipid biochemistry, and demonstrate the biological revelations found through lipidomic approaches and their potential implications for health management.

Biotechnology↗

PubMed2005

Sociogenomics: social life in molecular terms.

Spectacular progress in molecular biology, genome-sequencing projects and genomics makes this an appropriate time to attempt a comprehensive understanding of the molecular basis of social life. Promising results have already been obtained in identifying genes that influence animal social behaviour and genes that are implicated in social evolution. These findings - derived from an eclectic mix of species that show varying levels of sociality - provide the foundation for the integration of molecular biology, genomics, neuroscience, behavioural biology and evolutionary biology that is necessary for this endeavour.

Animals↗

PubMed2003

Expression profiling via novel multiplex assay allows rapid assessment of gene regulation in defined signalling pathways.

The current interest in expression of groups of functionally related genes creates a demand for novel experimental tools. We describe a multiplex ligation-dependent amplification procedure (RT-MLPA), which accurately quantifies up to 45 transcripts of interest in a one-tube assay. The output, a set of fluorescent DNA fragments, is analysed via capillary sequencer and spreadsheet software. The procedure is highly sensitive and reproducible over a 100-fold range of input RNA, with excellent compatibility with RT-PCR and microarrays. We targeted two comprehensive sets of human genes: 35 apoptosis regulators and 30 genes involved in inflammation. Both probe sets accurately assessed specific changes in gene expression in two relevant model systems. Stimulation of lymphocytes with various Toll-like receptor (TLR) ligands induced distinct inflammatory profiles. Furthermore, osteosarcoma cells treated with cytostatic drugs showed as primary response strong up-regulation of the apoptogenic p53-inducible PUMA transcript. Suppression by RNAi validated that indeed Puma expression was responsible for apoptosis induction. Thus, RT-MLPA enables relevant changes in transcription patterns to be quickly pinpointed and guide further experiments. This can be an advantage compared to hypothesis-free whole genome screens where large numbers of differentially expressed genes can obscure functional interpretation.

Apoptosis↗

PubMed2001

A comprehensive expression analysis of all members of a gene family encoding cell-wall enzymes allowed us to predict cis-regulatory regions involved in cell-wall construction in specific organs of Arabidopsis.

The Arabidopsis thaliana genome sequencing project has revealed that multigene families, such as those generated by genome duplications, are more abundant among plant genomes than among animal genomes. To gain insight into the evolutionary implications of the multigene families in higher plants, we examined the XTH gene family, a group of genes encoding xyloglucan endotransglucosylase/hydrolase, which are responsible for cell-wall construction in plants. Expression analysis of all members (33 genes) of this family, using quantitative real-time RT-PCR, revealed that most members exhibit distinct expression profiles in terms of tissue specificity and responses to hormonal signals, with some members exhibiting similar expression patterns. By comparing the flanking sequences of individual genes, we identified four sets of large-segment duplications and two sets of solitary gene duplications. In each set of gene duplicates, long nucleotide sequences, ranging from one to two hundred base pairs, are conserved. Furthermore, gene duplicates exhibit similar organ-specific expression profiles. These facts allowed us to predict putative cis-regulatory regions, particularly those responsible for cell-wall construction, and hence for morphogenesis, that are specific for certain organs or tissues in plants.

Arabidopsis↗

PubMed2026

Genome-Wide Identification of the Soybean GH5 Gene Family and Functional Analysis of GmGH5-22 in Salt Tolerance.

Plant GH5 family genes function in both cell wall biosynthesis and stress responses. However, comprehensive studies on GH5 genes in the soybean remain limited. Here, we identified 28 GmGH5 genes from the soybean genome. Phylogenetic analysis assigned these genes to three subfamilies (I-III), with no representatives in subfamily IV. The GmGH5 family harbors 15 conserved motifs, which are largely similar within subfamilies but differ across subfamilies. Additionally, exon-intron structures (2-7 introns) exhibit clade-specific patterns, with members within the same clade sharing similar intron numbers and lengths, whereas distinct clades show some variation. The promoter regions of GmGH5 genes contained various cis-acting regulatory elements associated with stress responses and developmental processes. Transcriptome-based expression profiling revealed distinct tissue-specific expression patterns of GmGH5 genes. RT-qPCR further confirmed their differential expression under salt, alkaline, cold, and drought stresses, especially a significant increase in GmGH5-22 expression under salt stress (approximately 22-fold at 6 h, **** p < 0.0001). Furthermore, GmGH5-22 was highly expressed in roots, and transient expression in tobacco leaves showed its peripheral localization, which aligns with its predicted extracellular localization, suggesting that GmGH5-22 is highly likely localized to the cell wall. Overexpression of GmGH5-22 in soybean hairy roots significantly improved tolerance to salt stress. These findings establish a foundation for functional characterization of GmGH5 genes and provide viable targets for molecular breeding to enhance salt tolerance in soybeans.

GH5 family↗

PubMed2005

Columnar cell lesions of the breast: the missing link in breast cancer progression? A morphological and molecular analysis.

Columnar cell lesions (CCLs) of the breast are a spectrum of lesions that have posed difficulties to pathologists for many years, prompting discussion concerning their biologic and clinical significance. We present a study of CCL in context with hyperplasia of usual type (HUT) and the more advanced lesions ductal carcinoma in situ (DCIS) and invasive ductal carcinoma. A total of 81 lesions from 18 patients were subjected to a comprehensive morphologic review based upon a modified version of Schnitt's classification system for CCL, immunophenotypic analysis (estrogen receptor [ER], progesterone receptor [PgR], Her2/neu, cytokeratin 5/6 [CK5/6], cytokeratin 14 [CK14], E-cadherin, p53) and for the first time, a whole genome molecular analysis by comparative genomic hybridization. Multiple CCLs from 3 patients were studied in particular detail, with topographic information and/or showing a morphologic spectrum of CCL within individual terminal duct lobular units. CCLs were ER and PgR positive, CK5/6 and CK14 negative, exhibit low numbers of genetic alterations and recurrent 16q loss, features that are similar to those of low grade in situ and invasive carcinoma. The molecular genetic profiles closely reflect the degree of proliferation and atypia in CCL, indicating some of these lesions represent both a morphologic and molecular continuum. In addition, overlapping chromosomal alterations between CCL and more advanced lesions within individual terminal duct lobular units suggest a commonality in molecular evolution. These data further support the hypothesis that CCLs are a nonobligate, intermediary step in the development of some forms of low grade in situ and invasive carcinoma.

Biomarkers, Tumor↗

PubMed2005

Proteomics in nutrition and health.

Proteomics, the comprehensive analysis of a protein complement in a cell, tissue or biological fluid at a given time, has been enabled by quantum leaps in mass spectrometric technology, which allowed identification of large, involatile biomolecules. Over the last two decades, this discipline evolved from the sole delivery of protein identities to a platform, which reveals clues to function through e.g. characterisation of protein modifications and interactions as well as through quantitative proteomics, i.e. the global comparison of protein amounts between two defined biological states. Proteomics is an integral part and key player in the family of -omic disciplines as there are genomics (gene analysis), transcriptomics (gene expression analysis) and metabolomics (metabolite profiling). Considering the complexity, dynamics and protein concentration range of any given proteome, proteomics is the most challenging -omic discipline and requires the most sophisticated analysis pipeline. Proteomics represents an established technology in the pharmaceutical industry mainly for biomarker and drug target discovery. The potential of proteomics for research in the food industry is increasingly being recognised and the employment of proteomic approaches to nutrition and health issues is now emerging. This review summarizes (i) major technological achievements in mass spectrometry and proteomics, (ii) deliverables of proteomics in the context of nutrition and health, and (iii) applications of proteomics, and -- if appropriate -- transcriptomics to the research fields of digestive health, obesity and diabetes, immunity and allergy, probiotics, milk, and food preference.

Complex Mixtures↗

PubMed2004

Towards a comprehensive understanding of Bacillus subtilis cell physiology by physiological proteomics.

Using Bacillus subtilis as a model system for functional genomics, this review will provide insights how proteomics can be used to bring the virtual life of genes to the real life of proteins. Physiological proteomics will generate a new and broad understanding of cellular physiology because the majority of proteins synthesized in the cell can be visualized. From a physiological point of view two major proteome fractions can be distinguished: proteomes of growing cells and proteomes of nongrowing cells. In the main analytical window almost 50% of the vegetative proteome expressed in growing cells of B. subtilis were identified. This proteomic view of growing cells can be employed for analyzing the regulation of entire metabolic pathways and thus opens the chance for a comprehensive understanding of metabolism and growth processes of bacteria. Proteomics, on the other hand, is also a useful tool for analyzing the adaptational network of nongrowing cells that consists of several partially overlapping regulation groups induced by stress/starvation stimuli. Furthermore, proteomic signatures for environmental stimuli can not only be applied to predict the physiological state of cells, but also offer various industrial applications from fermentation monitoring up to the analysis of the mode of action of drugs. Even if DNA array technologies currently provide a better overview of the gene expression profile than proteome approaches, the latter address biological problems in which they can not be replaced by mRNA profiling procedures. This proteomics of the second generation is a powerful tool for analyzing global control of protein stability, the protein interaction network, protein secretion or post-translational modifications of proteins on the way towards the elucidation of the mystery of life.

Bacillus subtilis↗