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Asta Literature Retrieval: Pathophysiology and clinical mechanisms of Omodysplasia. Core disease mechanisms, molecular and cellular pathways, in...

2026-04-02
Asta MONDO:0017136 Model: Asta Scientific Corpus Retrieval 20 citations

Asta Literature Retrieval: Pathophysiology and clinical mechanisms of Omodysplasia. Core disease mechanisms, molecular and cellular pathways, in...

This report is retrieval-only and is generated directly from Asta results.

  • Papers retrieved: 20
  • Snippets retrieved: 20

Relevant Papers

[1] New therapeutic targets in rare genetic skeletal diseases

  • Authors: M. Briggs, Peter A. Bell, M. Wright, K. A. Pirog
  • Year: 2015
  • Venue: Expert Opinion on Orphan Drugs
  • URL: https://www.semanticscholar.org/paper/1363107f71ae6d2d60abca471cddf3da5d13644b
  • DOI: 10.1517/21678707.2015.1083853
  • PMID: 26635999
  • PMCID: 4643203
  • Citations: 37
  • Influential citations: 1
  • Summary: An overview of disease mechanisms that are shared amongst groups of different GSDs and potential therapeutic approaches that are under investigation are described to generate critical mass for the identification and validation of novel therapeutic targets and biomarkers.
  • Evidence snippets:
  • Snippet 1 (score: 0.442) > proteins of the cartilage ECM such as type II collagen [50]. However, emerging knowledge suggests that the primary genetic defect may be less important than the cells' response to the expression of the mutant gene product [107]. Moreover, the largely overlooked response of a cell (i.e. chondrocyte) to the abnormal extracellular environment is also important for disease progression as illustrated by several GSDs discussed in this review. > It is important that 'omics'-based approaches and technologies are systematically applied to the study of rare GSDs so that definitive reference profiles and disease signatures are generated for each phenotype. These can then be used in a Systems Biology approach to identify both common and dissimilar pathological signatures and disease mechanisms. This approach is entirely dependent upon relevant in vitro and in vivo models (and also novel 'disease-mechanism phenocopies' [107]) for testing new diagnostic and prognostic tools and for determining the molecular mechanisms that underpin the pathophysiology so that effective therapeutic treatments can be developed and validated. This approach will eventually lead to personalized treatments and care strategies centred on shared disease mechanisms with the use of relevant biomarkers to monitor the efficacy of treatment and disease progression. > It is vital that all relevant stakeholders are involved from the outset in defining the appropriate outcomes of any potential therapeutic regime. The perceptions of a successful therapy can differ widely between the clinical academic community and the relevant patient-support groups and it is vital that there is engagement on all these issues. > In summary, the identification of causative genes and mutations for GSDs over the last 20 years, coupled with the generation and in-depth analysis of a plethora of relevant cell and mouse models, has derived new knowledge on disease mechanisms and suggested potential therapeutic targets. The fast-evolving hypothesis that clinically disparate diseases can share common disease mechanisms is a powerful concept that will generate critical mass for the identification and validation of novel therapeutic targets and biomarkers.

[2] Changes in Serum Proteomic Profiles at Different Stages of Pregnancy Toxemia in Goats

  • Authors: M. Uzti̇mür, C. N. Ünal, Gurler Akpinar
  • Year: 2025
  • Venue: Journal of Veterinary Internal Medicine
  • URL: https://www.semanticscholar.org/paper/4b9c488b5dbd65d7b26fd2ad9aed70e8c4b59942
  • DOI: 10.1111/jvim.70139
  • PMID: 40492724
  • PMCID: 12150350
  • Summary: Understanding the serum proteome profiles of goats with pregnancy toxemia might help identify the proteomes and pathways responsible for the development of this disease and improve diagnosis and treatment.
  • Evidence snippets:
  • Snippet 1 (score: 0.417) > The pathophysiology and progression of this disease are not fully understood. > Traditional biomedical research has focused on the analysis of single genes, proteins, metabolites, or metabolic pathways in diseases. This molecular reductionist approach is based on the assumption that identifying genetic variations and molecular components will lead to new treatments for diseases [13][14][15][16]. However, many diseases are complex and multifactorial, and in order to determine the phenotype of such diseases, it is necessary to understand the changes that occur in more than one gene, pathway, protein, or metabolite at the cellular, tissue, and organismal levels [17][18][19]. Therefore, in recent years, proteomics, as one field of multi-omics technologies, has helped in evaluating the complex pathogenetic mechanisms of different diseases from a broad perspective and has made substantial contributions [20,21]. In veterinary medicine, proteomic analysis of metabolic diseases such as ketosis [16], hypocalcemia [22], and fatty liver [23] in dairy cows has contributed valuable insights for the definition of new pathophysiological pathways and new diagnosis and treatment protocols for these diseases. The proteomic approach can contribute importantly to a broad and detailed understanding of the changes that occur at the organismal level associated with the increase in BHBA concentration in goats with pregnancy toxemia. Our aim was to evaluate the serum protein profiles of goats with SPT or CPT using proteomic techniques to determine the proteomic profiles of these animals and to identify the relevant pathophysiological mechanisms.

[3] 18O-assisted dynamic metabolomics for individualized diagnostics and treatment of human diseases

  • Authors: E. Nemutlu, Song Zhang, N. Juranic, A. Terzic, S. Macura et al.
  • Year: 2012
  • Venue: Croatian Medical Journal
  • URL: https://www.semanticscholar.org/paper/880f053c7f060db4b990e447d0a22c4b69372ddb
  • DOI: 10.3325/cmj.2012.53.529
  • PMID: 23275318
  • PMCID: 3541579
  • Citations: 28
  • Summary: The potential use of dynamic phosphometabolomic platform for disease diagnostics currently under development at Mayo Clinic is described and discussed briefly.
  • Evidence snippets:
  • Snippet 1 (score: 0.417) > Living cells represent an integrated and interacting network of genes, transcripts, proteins, small signaling molecules, and metabolites that define cellular phenotype and function. Traditionally the focus of biomedical research was on individual genes, single protein targets, single metabolites, and metabolic or signaling pathways. This "molecular reductionist" paradigm was based on the assumption that identifying genetic variations and molecular components would lead to discovery of cures for human diseases. However, most of diseases are complex and multi-factorial and the disease phenotype is determined by the alterations of multiple genes, pathways, proteins and metabolites (at cellular, tissue, and organismal levels). Therefore, an integrated "omics" approach is more viable direction for uncovering alterations in metabolic networks, disease mechanisms, and mechanisms of drug effects. > Recent advent of large-scale metabolomics and fluxomic (metabolite dynamics and metabolic flux analysis) completed the "omics revolution" (Figure 1), where genomics, transcriptomics, proteomics, metabolomics, and fluxomics all together complement phenotype determination of living organism. Such integrated "omics" cascades provide a framework for advances in system and network biology, integrative physiology, and system medicine as well as system pharmacology and regenerative medicine. Noteworthy is the "reverse omic" approach or "metabolomicsinformed pharmacogenomics, " where discovery of specific metabolite changes have led to discovery of genetic alterations (2). Therefore, bringing new "omics" technologies to clinical practice will improve disease diagnostics and treatment by targeting drugs and procedures for each unique transcriptomic and metabolomic profiles.

[4] Organoids in gastrointestinal diseases: from bench to clinic

  • Authors: Qinying Wang, Fanying Guo, Qinyuan Zhang, Tingting Hu, Yutao Jin et al.
  • Year: 2024
  • Venue: MedComm
  • URL: https://www.semanticscholar.org/paper/9b8880d8b9d45670da950197d7e353794f51d09e
  • DOI: 10.1002/mco2.574
  • PMID: 38948115
  • PMCID: 11214594
  • Citations: 12
  • Summary: A comprehensive and systematical depiction of organoids models is drawn, providing a novel insight into the utilization of organoids models from bench to clinic and clinical adhibition.
  • Evidence snippets:
  • Snippet 1 (score: 0.402) > Organoids models offer a robust platform for investigating the potential mechanisms of GI diseases and evaluating potential therapeutic interventions.By culturing organoids derived from patients' tissues or stem cells, researchers can delve into disease-specific cellular and molecular pathways, encompassing aberrant cell signaling, perturbed immune responses, and dysfunctional metabolic processes.These disease-specific phenotypes enable the study of disease progression, screening of prospective therapeutics, as well as identification of novel drug targets and mechanisms of action for GI diseases in a clinically relevant context.

[5] Mitochondrial Dysfunction in Diabetes: Shedding Light on a Widespread Oversight

  • Authors: F. Iheagwam, A. J. Joseph, E. D. Adedoyin, Olawumi Toyin Iheagwam, Samuel Akpoyowvare Ejoh
  • Year: 2025
  • Venue: Pathophysiology
  • URL: https://www.semanticscholar.org/paper/dbf8042761c1a5fc50f8cd894cc498505abac7cb
  • DOI: 10.3390/pathophysiology32010009
  • PMID: 39982365
  • PMCID: 12077258
  • Citations: 23
  • Summary: This review aims to elucidate the complex link between mitochondrial dysfunction and diabetes, covering the spectrum of diabetes types, the role of mitochondria in insulin resistance, highlighting pathophysiological mechanisms, mitochondrial DNA damage, and altered mitochondrial biogenesis and dynamics.
  • Evidence snippets:
  • Snippet 1 (score: 0.400) > The landscape of DM research is continuously evolving, with emerging technologies and approaches offering new insights into the pathophysiology of the disease and potential therapeutic targets. Advancements in omics technologies, encompassing genomes, transcriptomics, proteomics, and metabolomics, have transformed the molecular mechanisms underlying DM [134]. High-throughput sequencing techniques enable comprehensive analysis of genetic variants, gene expression profiles, protein abundance, and metabolite levels associated with DM and its complications [135]. Single-cell omics approaches provide unprecedented resolution and granularity, allowing researchers to dissect cellular heterogeneity and identify novel cell types, subpopulations, and signalling pathways involved in DM pathogenesis. Integrating multi-omics data sets offers a systems-level perspective of DM, unravelling complex networks of molecular interactions and regulatory circuits underlying disease progression [136]. > In addition to omics technologies, advances in imaging modalities, such as MRI, PET, and optical imaging, enable non-invasive visualisation and quantification of metabolic, functional, and structural changes. Molecular imaging probes targeting specific biomarkers and metabolic pathways provide valuable insights into disease mechanisms and treatment responses in preclinical and clinical settings [85]. Despite significant progress in DM research, numerous unanswered questions and knowledge gaps persist, hindering the ability to develop effective prevention and treatment strategies. Key areas requiring further investigation include the role of epigenetics, environmental factors, and the microbiome in DM susceptibility and progression. Moreover, the interaction between environmental cues and genetic predisposition remains incompletely understood, highlighting the need for comprehensive multi-omics studies and large-scale epidemiological analyses to identify gene-environment interactions and modifiable risk factors for DM [137]. Furthermore, the heterogeneity of DM phenotypes and clinical outcomes poses a challenge for personalised medicine approaches, necessitating robust biomarkers and predictive models to stratify patients based on disease subtypes, prognosis, and treatment response [138].

[6] From molecular signatures to predictive biomarkers: modeling disease pathophysiology and drug mechanism of action

  • Authors: A. Heinzel, P. Perco, G. Mayer, R. Oberbauer, A. Lukas et al.
  • Year: 2014
  • Venue: Frontiers in Cell and Developmental Biology
  • URL: https://www.semanticscholar.org/paper/36d6c03a528c1358c0ae5b667cca5ce73b2fbee5
  • DOI: 10.3389/fcell.2014.00037
  • PMID: 25364744
  • PMCID: 4207010
  • Citations: 23
  • Summary: This work exemplifies a computational workflow for expanding from statistics-based association analysis toward deriving molecular pathway and process models for characterizing phenotypes and drug mechanism of action, in turn providing precision medicine hypotheses utilizing predictive biomarkers.
  • Evidence snippets:
  • Snippet 1 (score: 0.396) > In such scenario a biomarker needs to serve as proxy of key mechanistic factors characterizing and driving a disease on a patient-specific level, combined with educating on the specific interference of disease mechanism with drug mechanism of action. For capturing these constraints a detailed molecular map of a clinical phenotype and its interference with a drug mechanism of action is needed, and here integration of Omics profiling adds to identifying such mechanisms (Fechete et al., 2011;Mühlberger et al., 2012). > An a priori stratification of patients based on an appropriately chosen biomarker panel reflecting the pathophysiology of a given patient (group) allowing to determine a match with a specific drug's mechanism of action appears as promising approach. As recently discussed by Himmelfarb et al. fresh approaches are critical in finding therapies to kidney disease benefiting patients, outlining the importance of improving the translational aspect in clinical research (Himmelfarb and Tuttle, 2013). Here, omics technologies have added significantly to the data landscape characterizing chronic kidney disease, however, in a first instance mainly expanding the candidate set of apparently relevant processes and pathways, going in hand with a large number of biomarker candidates, which individually hamper clinically relevant assessment on disease progression (Fechete et al., 2011;Hellemons et al., 2012). > Integrative approaches in the realm of Systems Biology have been proposed for reaching a consensus description of chronic kidney disease pathophysiology, including molecular models of DN as well as of the reno-cardial axis (He et al., 2012;Komorowsky et al., 2012;Mayer et al., 2012;Heinzel et al., 2013). Still, a translation process needs to be followed, joining disease pathophysiology, stratification markers allowing enrichment strategies, combined with on a molecular mechanistic level matching drugs for allowing precision medicine (Mirnezami et al., 2012). In this work we exemplify such procedure on DN being the major clinical presentation leading to end stage renal disease.

[7] Role of Transcriptomics in Precision Oncology

  • Authors: Ruby Srivastava
  • Year: 2024
  • Venue: Reports of Radiotherapy and Oncology
  • URL: https://www.semanticscholar.org/paper/0bd862558bbb7286336111d9dfd232b5f905d3d9
  • DOI: 10.5812/rro-142195
  • Citations: 4
  • Summary: : Transcriptome profiling is one of the most widely used approaches in the field of multiomics research. It plays a crucial role in the prognostic, diagnostic, and predictive treatment of cancer patients. Novel next-generation sequencing (NGS) technologies permit the identification of cancer biomarkers, gene signatures, and their abnormal expression, affecting oncogenic and molecular targets and novel biomarkers for cancer therapies. Multiomics studies have changed the overall understanding o...
  • Evidence snippets:
  • Snippet 1 (score: 0.395) > : Transcriptome profiling is one of the most widely used approaches in the field of multiomics research. It plays a crucial role in the prognostic, diagnostic, and predictive treatment of cancer patients. Novel next-generation sequencing (NGS) technologies permit the identification of cancer biomarkers, gene signatures, and their abnormal expression, affecting oncogenic and molecular targets and novel biomarkers for cancer therapies. Multiomics studies have changed the overall understanding of cancer and opened a precise perspective for tumor diagnostics and therapy. The use of these approaches has strengthened our understanding of disease pathophysiology and classifications at the molecular level, including specific interference with drug mechanisms of action. Still, it has limited added value in the clinical setting. The omics data on precision medicine include the application of data from genes, transcripts, and proteins for diagnosis, monitoring of diseases, risk factor determination, counseling, and development of novel therapeutics. Bioinformatics applications have expanded statistics-based analysis toward deriving molecular pathways and process models for characterizing phenotypes and drug action mechanisms. In this review, we will discuss transcriptomics and interference analysis that allows the identification of predictive biomarkers at the molecular level to test drug response and analyze the molecular process interface of disease progression-relevant pathophysiology and mechanism of action to propose predictive biomarkers.

[8] Investigating the Transition of Pre-Symptomatic to Symptomatic Huntington’s Disease Status Based on Omics Data

  • Authors: Christiana C. Christodoulou, M. Zachariou, Marios Tomazou, E. Karatzas, C. Demetriou et al.
  • Year: 2020
  • Venue: International Journal of Molecular Sciences
  • URL: https://www.semanticscholar.org/paper/04a48e68a0a0ad9eca22aeffdb8c22c7fb41ed86
  • DOI: 10.3390/ijms21197414
  • PMID: 33049985
  • PMCID: 7582902
  • Citations: 26
  • Influential citations: 2
  • Summary: The genes, pathways and metabolites identified for each HD stage can provide a better understanding of the mechanisms that become altered in each disease stage, leading to an improvement in clinical symptoms and hopefully a delay in the age of onset.
  • Evidence snippets:
  • Snippet 1 (score: 0.387) > HD is a monogenetic and incurable disease and at the same time its molecular manifestations remain highly complex and involve multiple cellular processes, genes, and metabolites, which needs to be investigated to understand HD pathology. Systems bioinformatics (SB) allows the integration of different biological omics data to better understand the biological pathways, mechanisms, genes and metabolites involved in HD and lead to possible therapeutic treatments and biomarker discovery. > SB is an interdisciplinary field which combines the research fields of systems biology and bioinformatics. SB allows the integration of biological data across the omics categories such a genomics, transcriptomics, proteomics, metabolomics, lipidomics, epigenomics and several types of omics data [7]. > A major approach in this direction is the generation and construction of biological networks representing each level of omics data and their integration in a layered network that permits the exchange of information between and within the layers. The goal is to reveal synergistic relationships among numerous factors rather than explore each entity individually. This data integration approach results in the construction of highly complex molecular interaction networks. The biological data, obtained through large-scale omics analysis can provide a better understanding into biological mechanisms and pathways and how a dysfunction in these mechanisms and pathways can cause the disease [7]. Furthermore, the emerging importance of biological network-based approaches, allows for potential biological and clinical applications by suggesting an intuitive and trustworthy approach to explore the biological and molecular complexity of a disease of interest [8]. > The metabolome is defined as the complete set of small chemical molecules found within a biological samples (urine, cerebrospinal fluid (CSF), serum, plasma), tissues and cells. Changes and interactions in gene and protein expression and the environment are directly revealed in the metabolome making it more chemically and physically complex than the genome, transcriptome and proteome. Metabolites are affected by the upstream influence of the genome, proteome, environmental and lifestyle factors, as well as medication and underlying diseases [9]. > Metabolomics is an omics category focused in the study of metabolites. Metabolites are defined as small biological and low molecular weight (<1500 Da) compounds, they are the end-products of metabolism [10].

[9] Renal ciliopathies: promising drug targets and prospects for clinical trials

  • Authors: L. Devlin, Praveen Dhondurao Sudhindar, J. Sayer
  • Year: 2023
  • Venue: Expert Opinion on Therapeutic Targets
  • URL: https://www.semanticscholar.org/paper/ab2155b6e12caba53d57ac0e8ce28860d69ec9fd
  • DOI: 10.1080/14728222.2023.2218616
  • PMID: 37243567
  • Citations: 10
  • Summary: The advances in basic science and clinical research into renal ciliopathies which have yielded promising small compounds and drug targets are reviewed, within both preclinical studies and clinical trials.
  • Evidence snippets:
  • Snippet 1 (score: 0.387) > Although renal ciliopathies can be classified into distinct syndromes, causative mutations in genes encoding proteins involved in the primary cilium or centrosome mean they may share overlapping mechanisms of disease, which may be amenable for therapeutic intervention (Figure 2). Abnormal functioning of proteins involved in ciliogenesis, such as CEP164, can prevent proper cilia formation, which will effect a myriad of downstream ciliary signaling pathways. Additionally, mutations in genes encoding for proteins involved in cargo trafficking or regulation, such as CEP290, will have implications for signal pathway transduction, as well as mutations in components of signaling pathways themselves, such as PKD1. In regard to renal ciliopathies, abnormalities in signaling pathways such as cAMP, Shh, Wnt, mTOR, and AMPK, likely cause misoriented cellular divisions, increased proliferation, increased fluid secretion and subsequent cystogenesis, consequently leading to further kidney damage. Ciliary and centriolar proteins which have roles in DDR and cell cycle regulation may also be driving a renal cystogenesis phenotype alongside increased fibrosis and apoptosis. Increased inflammation and dysfunctional mitochondria are also byproducts of dysregulated signaling pathways have been shown to contribute to the progression of renal ciliopathies. Extensive reviews of mechanisms of renal ciliopathy diseases have recently been performed [23,24]. Importantly, due to the wide range of cellular processes that primary cilia regulate, it is likely that in each syndrome there are multiple pathogenic drivers of disease. In some ways, this is advantageous as it offers many points for potential therapeutic targets. However, the cross talk between pathways and feedback loops introduces complications of changing one pathway without negatively affecting another. Further challenges arise with core biological pathways, such as Shh signaling, in which modification in vitro may be beneficial, but systemic treatment is unrealistic due to the expected severe side effects [18,24,116].

[10] Baseline urinary metabolites predict albuminuria response to spironolactone in type 2 diabetes.

  • Authors: S. Mulder, P. Perco, C. Oxlund, Uzma F Mehdi, T. Hankemeier et al.
  • Year: 2020
  • Venue: Translational research : the journal of laboratory and clinical medicine
  • URL: https://www.semanticscholar.org/paper/e5f7ffaa67fba1fe09d82c2d3787ad398d175bb6
  • DOI: 10.1016/j.trsl.2020.04.010
  • PMID: 32438071
  • Citations: 9
  • Summary: The data suggest that urinary metabolites may be used as a tool to tailor optimal therapy and move in the direction of personalized medicine.
  • Evidence snippets:
  • Snippet 1 (score: 0.386) > In-silico modeling of spironolactone mechanism of action and DKD pathophysiology. Network-based molecular models reflecting spironolactone mechanism of action as well as DKD pathophysiology were generated following previously described and successfully applied computational workflows. 8,9 In brief, molecular features associated with spironolactone were consolidated from 3 data sources, namely scientific literature, DrugBank, and a transcriptomics data set from DrugMatrix. Molecular features were defined as genes, transcripts, or proteins. Scientific articles annotated with spironolactone as major MeSH term were retrieved and genes were extracted using NCBI's gene2pubmed file. This set of genes was complemented by drug targets listed in DrugBank for spironolactone. 10 We further extracted transcripts being differentially expressed between spironolactone-treated and untreated kidney samples of animal models as stored in DrugMatrix. 11 The unique set of spironolactone associated molecular features was mapped onto a hybrid interaction network including protein-protein interaction data from IntAct, BioGrid, and Reactome together with computationally inferred relations. 12 Interactions between members of the spironolactone feature set were extracted and the MCODE algorithm was used to identify clusters of highly interconnected proteins. 13 A previously published DKD molecular model was used which was constructed following the same logic using data from scientific literature as well as from Omics datasets in the context of DKD. 7 Proteomics data of the published CKD273 proteomics classifier were used in order to identify DKD processes linked with DKD progression by mapping the set of proteins in the CKD273 classifier onto the DKD molecular network thus defining progression-associated process units. 14 Network interference analysis and identification of candidate metabolites. Network alignment method was used to identify DKD molecular processes linked to DKD prognosis affected by spironolactone treatment on the molecular level. Metabolites linked to proteins in affected DKD molecular processes were identified via enzyme-metabolite associations as stored in the Human Metabolome Database and forwarded to measurements in clinical samples. 15 A

[11] Computational drug discovery approaches identify mebendazole as a candidate treatment for autosomal dominant polycystic kidney disease

  • Authors: P. Brownjohn, A. Zoufir, Daniel J O’Donovan, Saatviga Sudhahar, A. Syme et al.
  • Year: 2024
  • Venue: Frontiers in Pharmacology
  • URL: https://www.semanticscholar.org/paper/a595e78572ca02b8cb2897bfc4a989a2b021b279
  • DOI: 10.3389/fphar.2024.1397864
  • PMID: 38846086
  • PMCID: 11154008
  • Citations: 2
  • Summary: It is determined that the anthelmintic mebendazole was a potent anti-cystic agent in human cellular and in vivo models of ADPKD, and is likely acting through the inhibition of microtubule polymerisation and protein kinase activity.
  • Evidence snippets:
  • Snippet 1 (score: 0.385) > Targets and molecules were ultimately filtered for validation based on biological and chemical insights, and the potential for clinical translation.Earlier this year, Wilk et al., 2023 applied a similar transcriptomic approach to us, in that case making use of publicly available transcriptomic datasets to create Pkd2-specific ADPKD disease signatures, from which signature reversion was sought from the Library of Integrated Network-based Cellular Signatures (LINCs) drug signature database in order to identify drug repurposing candidates.While one group has previously made use of a knowledge graph-based approach to prioritise preclinically active compounds with the highest chance of clinical translation (Malas et al., 2019), to our knowledge, the current study provides the first combined application of transcriptomic and machine-learning approaches to identify and prioritise putative treatments for ADPKD, and further deconvolute potential mechanisms of action for experimental validation. > In summary we report, using computational, in vitro and in vivo approaches, that the anthelmintic drug mebendazole ameliorates disease-relevant phenotypes in cellular and animal models of ADPKD.We further show that this effect is likely primarily due to the inhibitory effect of mebendazole on the polymerisation of microtubules, which underlie cellular processes important in ADPKD, including cell proliferation, transport, and cilia signalling, and extends previous work linking the importance of the microtubule network to ADPKD pathophysiology.We also describe the inhibitory profile of mebendazole on known and novel protein kinase targets, some of which have previously been implicated in ADPKD, suggesting mebendazole may be acting via polypharmacology to impact disease mechanisms.We acknowledge that further experimental efforts will be required to confirm the actions of mebendazole on these putative targets in relevant disease model systems.It would be particularly informative to investigate these mechanisms in dedicated in vivo studies, where the effects of mebendazole on a wider range of ADPKD-relevant cell types and phenotypes could be evaluated.

[12] Cellular reprogramming and inherited peripheral neuropathies: perspectives and challenges

  • Authors: M. Saporta
  • Year: 2015
  • Venue: Neural Regeneration Research
  • URL: https://www.semanticscholar.org/paper/8c3dabb1b4abf93506e2026564b8a329c0ec37c6
  • DOI: 10.4103/1673-5374.158345
  • PMID: 26199602
  • PMCID: 4498347
  • Citations: 4
  • Summary: iPSC-based models of neuromuscular disorders, including amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and inherited peripheral neuropathies, have successfully reproduced pathophysiological findings from previous animal and cellular models and have also identified new disease mechanisms with potential therapeutical implications.
  • Evidence snippets:
  • Snippet 1 (score: 0.384) > Inherited peripheral neuropathies (or Charcot-Marie-Tooth disease, CMT) are a phenotypically and genetically heterogeneous group of disorders, which are currently untreatable. They are the most common inherited neuromuscular disorder, affecting around 1 in every 2,500 people (over 120,000 people in the US). Based on clinical neurophysiological and histopathological features, inherited neuropathies can be divided into two major forms: demyelinating (type 1) and axonal (type 2) CMT (Saporta, 2014). From a biological standpoint, these two major forms of CMT are associated with mutations in different sets of genes, affecting Schwann cell development and myelination (type 1) or peripheral axon physiology (type 2), although some overlap does exist (Figure 1). To date, over 70 genes have been associated with a CMT phenotype, making CMT an attractive natural model to study peripheral nervous system biology. Despite significant advances made in our knowledge of disease mechanisms in CMT, findings from animal models have so far translated poorly in clinical trials, underscoring the need for innovative methods to investigate the pathophysiology of these human disorders. Induced pluripotent stem cells (iPSCs) offer an unlimited source of patient specific, disease-relevant cell lines that can be used as a platform for identification of disease mechanisms, discovery of molecular targets and development of phenotypic screens for drug discovery (Saporta et al., 2011). iPSC-based models of neuromuscular disorders, including amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and inherited peripheral neuropathies, have successfully reproduced pathophysiological findings from previous animal and cellular models and have also identified new disease mechanisms with potential therapeutical implications.

[13] Human Dermal Fibroblast: A Promising Cellular Model to Study Biological Mechanisms of Major Depression and Antidepressant Drug Response

  • Authors: P. Mesdom, R. Colle, É. Lebigot, S. Trabado, Eric Deflesselle et al.
  • Year: 2020
  • Venue: Current Neuropharmacology
  • URL: https://www.semanticscholar.org/paper/79368e365458486de96794333613c12a6063bf54
  • DOI: 10.2174/1570159X17666191021141057
  • PMID: 31631822
  • PMCID: 7327943
  • Citations: 12
  • Summary: This review highlights the great and still underused potential of HDF, which stands out as a very promising tool in the understanding of MDD and AD mechanisms of action.
  • Evidence snippets:
  • Snippet 1 (score: 0.381) > Background: Human dermal fibroblasts (HDF) can be used as a cellular model relatively easily and without genetic engineering. Therefore, HDF represent an interesting tool to study several human diseases including psychiatric disorders. Despite major depressive disorder (MDD) being the second cause of disability in the world, the efficacy of antidepressant drug (AD) treatment is not sufficient and the underlying mechanisms of MDD and the mechanisms of action of AD are poorly understood. Objective The aim of this review is to highlight the potential of HDF in the study of cellular mechanisms involved in MDD pathophysiology and in the action of AD response. Methods The first part is a systematic review following PRISMA guidelines on the use of HDF in MDD research. The second part reports the mechanisms and molecules both present in HDF and relevant regarding MDD pathophysiology and AD mechanisms of action. Results HDFs from MDD patients have been investigated in a relatively small number of works and most of them focused on the adrenergic pathway and metabolism-related gene expression as compared to HDF from healthy controls. The second part listed an important number of papers demonstrating the presence of many molecular processes in HDF, involved in MDD and AD mechanisms of action. Conclusion The imbalance in the number of papers between the two parts highlights the great and still underused potential of HDF, which stands out as a very promising tool in our understanding of MDD and AD mechanisms of action

[14] Clinical metabolomics in type 2 diabetes mellitus: from pathogenesis to biomarkers

  • Authors: Chuanxin Liu, Hetao Chen, Yujin Ma, Lei Zhang, Lulu Chen et al.
  • Year: 2025
  • Venue: Frontiers in Endocrinology
  • URL: https://www.semanticscholar.org/paper/36f8d26a208b7b96763df2e9aa3211e440031c0e
  • DOI: 10.3389/fendo.2025.1501305
  • PMID: 40070584
  • PMCID: 11893406
  • Citations: 10
  • Summary: The results facilitate understanding the pathophysiology and mechanism of type 2 diabetes mellitus and supports research in accurate diagnosis, risk prediction, curative effect, distinct stages, and prognosis judgment of T2DM.
  • Evidence snippets:
  • Snippet 1 (score: 0.381) > T2DM is a chronic disease characterized by two primary pathophysiological mechanisms: ① a reduction in the mass and function of pancreatic b cells, ranging from 20% to 65%, which leads to impaired insulin secretion; ② insulin resistance, where cells in muscles, fat, and liver tissues fail to respond adequately to insulin (9). Consequently, higher levels of insulin are required to maintain normal blood glucose concentrations by inhibiting hepatic glucose production and promoting glucose uptake in muscle and adipose tissues. Prolonged exposure to elevated levels of circulating insulin leads to the development of insulin resistance in peripheral tissues, and over time, the pancreas fails to produce sufficient insulin to overcome this cellular resistance (10). However, due to the long latent period and absence of obvious symptoms initially, reversing T2DM with drug intervention is difficult after the symptoms are exposed or clinically confirmed in light of clear diagnostic criteria. According to the literature, the pathogenesis and process of metabolic syndromes such as diabetes and its complications are mainly reflected in the metabolite network, and the mechanism changes at the gene level are also found in the network. Studies have shown that some related metabolites in patients with diabetes have changed before the occurrence of obvious organic damage (11). Therefore, it is necessary to scientifically prevent T2DM in the early stages of disease onset. Fortunately, clinical metabolomics were employed to understand the progression pathologies of T2DM and its corresponding complications in detail (12). Studies have demonstrated that metabolomic analysis enables the exploration of metabolic disorders associated with T2DM, thereby deepening our understanding of disease progression (13,14). This approach has the potential to facilitate novel clinical diagnoses and the development of effective treatment strategies. Moreover, identifying specific metabolites may provide promising biomarkers for the early prediction, prevention, and management of hyperglycemia and its complications (15). In recent years, excellent progress has been made in the study of T2DM and its complications through High throughput sequencing method, i.e., a discipline specifically focused on metabolic small molecules. > Clinical metabolomics is a type of systems biology research closely linked to phenotype.

[15] Focus on Achalasia in the Omics Era

  • Authors: Anna Laura Pia Di Brina, O. Palmieri, Anna Lucia Cannarozzi, F. Tavano, Maria Guerra et al.
  • Year: 2024
  • Venue: International Journal of Molecular Sciences
  • URL: https://www.semanticscholar.org/paper/650bd88078a05683426d4e086abaa2c68729b07d
  • DOI: 10.3390/ijms251810148
  • PMID: 39337632
  • PMCID: 11431880
  • Citations: 2
  • Summary: This narrative review of the scientific literature is aimed to provide a comprehensive assessment of the state-of-the-art knowledge on omics of achalasia, with particular attention to those considered relevant to the pathogenesis of the disease.
  • Evidence snippets:
  • Snippet 1 (score: 0.380) > Basically all diseases, and not just so-called "complex diseases", are multifaceted because countless interconnected biological components contribute to their pathophysiology [8]. Any pathology has an intricate mix of genetic, epigenetic, environmental and behavioral factors that determine their onset and progression. Consequently, it is evident that studying each component of the disease in isolation, although it gives valuable information on any markers or sheds light on the different biological pathways between patients with a disease and a control group, is not sufficient to understand the intricate biological mechanisms at play [9]. For example, analysis of a single gene can reveal mutations associated with a disease, but cannot explain the entire clinical picture without considering the interaction of that gene with other genes, proteins and metabolites within the biological network. > So the need to study all components in a much more comprehensive way has emerged, hence the emphasis on omes and omics, defined, respectively, as the object of study of such field and its analysis. Substantially, omics is intended to improve our understanding of human biology and promote health and well-being through biomedical science and research [10]. Examples of omics disciplines include the identification of genes (genomics), messenger RNA (transcriptomics), epigenetic factors (epigenomics), proteins (proteomics) and finally, metabolites (metabolomics). > Thus ideally, different technologies would be combined to help diagnose disease and to generate effective clinically actionable tools to aid medical decision-making, generating a holistic picture of human phenotypes and disease. Furthermore, the integration of various types of omics data, multi-omics and clinical data, enables the production of more detailed information and is commonly used to discover potential underlying changes that trigger diseases contributing to the understanding of the pathogenic mechanisms or to identify potential targets for treatments. Indeed, it is expected that omics data will help the development of new and effective drugs, aimed at identifying biomarkers, novel molecular or protein targets for disease-modifying therapies useful for early diagnosis, disease staging and prediction progression. The National Cancer Institute defined biomarkers as biological molecules in blood, bodily fluids, or tissues that reveal whether a process, condition, or disease is normal or aberrant.

[16] Molecular Mechanisms and Risk Factors for the Pathogenesis of Hydrocephalus

  • Authors: Jing-wen Li, Xinjie Zhang, Jianfeng Guo, Chen Yu, Jun Yang
  • Year: 2022
  • Venue: Frontiers in Genetics
  • URL: https://www.semanticscholar.org/paper/d53bdf5f73f54a6d5a8be8777d23c465a13e9185
  • DOI: 10.3389/fgene.2021.777926
  • PMID: 35047005
  • PMCID: 8762052
  • Citations: 15
  • Influential citations: 2
  • Summary: Some possible fundamental molecular mechanisms and facilitating risk factors involved in the pathogenesis of hydrocephalus are elicited, and knowledge could be used to improve patient care in different ways, such as early precise diagnosis and effective therapeutic regimens.
  • Evidence snippets:
  • Snippet 1 (score: 0.379) > Cwh43 modifies the glycosylphosphatidylinositol-anchored proteins on the ependymal cells, and the mutant Cwh43 is related to iNPH in both humans and mice. The clinical features manifest as late-onset communicating hydrocephalus with symptoms of gait and balance dysfunction (Yang et al., 2021a). > The clinical manifestation and progression, as well as experimental investigations, indicate that hydrocephalus is a complex disease with polygenic involvement, rather than a simple CSF accumulation disorder. Although the current studies have revealed that some genetic mutations are involved in the pathogenesis of hydrocephalus, how these mutations are associated with the disorder of CSF circulation and their pathogenic roles in the pathological progression of hydrocephalus still remain largely unknown. Previous studies indicated that a lot of genetic mutations were relevant to the disorders of ciliary and/or centrosome, resulting in the dysfunction of the glymphatic system. However, how these mutations and their interactions contribute to the pathogenesis of hydrocephalus needs to be further elucidated. Moreover, there is still a lack of basic knowledge on the mechanisms underlying the cognitive functional impairment of hydrocephalus. Therefore, further extensive studies should be conducted to explore the underlying molecular mechanisms of identified and/or unidentified genes in the pathophysiology of hydrocephalus. Based on our knowledge, we propose that the genetic mutations relevant to ciliary and centrosomal proteins and the interaction between glymphatic system and ciliary/ centrosomal structures/functions may be a critical molecular mechanism in the pathophysiology of hydrocephalus. In addition, based on these fundamental molecular mechanisms, it is noteworthy that environmental and other acquired risks or etiological factors are also involved in the facilitation of ventricular enlargement.

[17] Mitochondrial transplantation as a promising therapy for mitochondrial diseases

  • Authors: Tian-Guang Zhang, Chaoyu Miao
  • Year: 2022
  • Venue: Acta Pharmaceutica Sinica. B
  • URL: https://www.semanticscholar.org/paper/72802097939b0bffc319c93d05128d7e3160e0eb
  • DOI: 10.1016/j.apsb.2022.10.008
  • PMID: 36970208
  • PMCID: 10031255
  • Citations: 82
  • Influential citations: 1
  • Summary: Different techniques used in mitochondrial isolation and delivery, mechanisms of mitochondrial internalization and consequences of mitochondrial transplantation, along with challenges for clinical application are presented.
  • Evidence snippets:
  • Snippet 1 (score: 0.377) > Mitochondria, the vital organelles of eukaryotic cells, are integrators of various cellular metabolic pathways, including oxidative phosphorylation, fatty acid oxidation, urea cycle, Krebs cycle, ketogenesis and gluconeogenesis 1 . Mitochondria are also important in many other essential cellular processes such as calcium homeostasis, lipid metabolism, amino acid metabolism, biosynthesis of heme, and thermogenesis 2 . However, they also have important roles in many pathways which can cause both apoptosis and necrosis 3 . Therefore, the importance of the mitochondrion in the maintenance of cellular homeostasis is well established, meanwhile a large amount of evidence shows that mitochondrial dysfunction is deleterious 4 . > Due to the essential function of mitochondria in the human body, mitochondrial dysfunction causes a great variety of mitochondrial diseases, which can affect almost all the organs in the body and present at any age 4,5 . Mitochondrial diseases are a group of metabolic disorders characterized by energy metabolism dysfunction. The pathophysiology is further complicated by the involvement of genetic mutations in nuclear DNA (nDNA) and mitochondrial DNA (mtDNA) which encode mitochondrial proteins. This means that mitochondrial diseases may result from inheritance for nDNA mutations and maternal inheritance for mtDNA mutations. The estimated minimum prevalence of mitochondrial diseases is 1 in 5000, whereas it could be higher 6 . > As advances in molecular and biochemical methodologies led to a better understanding of the mechanisms of mitochondrial disorders for various diseases, mitochondria have become a major target for research institutions and pharma companies. Pharmacological approaches include dietary supplements such as agents increasing respiratory chain function (coenzyme Q10 and riboflavin), agents inducing mitochondrial biogenesis (AICAR and bezafibrate), antioxidants (vitamin C and vitamin E), mitochondrial substrates (L-carnitine) and so on 7,8 . However, these agents fail to significantly alleviate disease symptoms or effectively slow disease progressions, there has therefore been no satisfactory therapeutic strategy available for mitochondrial diseases so far 9 . In addition, all new drugs under clinical trials for treatment of mitochondrial diseases are unable to cure these diseases permanently 9 .

[18] The ties that bind: functional clusters in limb-girdle muscular dystrophy

  • Authors: E. Barton, C. A. Pacak, Whitney L. Stoppel, P. Kang
  • Year: 2020
  • Venue: Skeletal Muscle
  • URL: https://www.semanticscholar.org/paper/653422e1a9dc9cc7f16758b10f3f203155bc68c9
  • DOI: 10.1186/s13395-020-00240-7
  • PMID: 32727611
  • PMCID: 7389686
  • Citations: 23
  • Summary: A deeper understanding of these disease pathways could yield a new generation of precision therapies that would each be expected to treat a broader range of LGMD patients than a single subtype, thus expanding the scope of the molecular medicines that may be developed for this complex array of muscular dystrophies.
  • Evidence snippets:
  • Snippet 1 (score: 0.377) > Pyridine nucleotide-disulfide reductase [55] Many of the protein functions listed require further confirmation or are disputed these methodologies. Those patients with moderate disease phenotypes regardless of the underlying causative gene mutation would likely fall into a category where there may be interest in testing a pharmacological treatment (that could be halted) but reduced interest in a more permanent experimental strategy. For all of the above-mentioned reasons, the identification of unifying therapeutic targets applicable to multiple subtypes of > LGMDs is highly desirable. > To identify such targets, we should first consider the question: What binds all of these LGMDs together? The two core phenotypic features are progressive proximal muscle weakness, along with characteristic signs of muscle fiber destruction on biopsy, referred to as "dystrophic" features. Nuances in clinical presentation have helped to distinguish some of the LGMDs, such as the frequent occurrence of difficulty walking on tiptoes in LGMD R2 (LGMD2B), caused by dysferlin deficiency. However, heterogeneity associated with variable ages of onset and ranges of severity makes it generally difficult to distinguish and diagnose LGMD subtypes based on clinical presentation alone. A change in perspective is in order to aid in understanding disease pathways responsible for clinical features even when the genetic mutation is unknown. Further, given the large number of genespecific LGMD subtypes, it could very well be that several major disease mechanisms may be shared across the family of diseases. Yet despite careful studies that have collectively determined the cellular localization of most proteins associated with LGMD (Fig. 1), there is limited knowledge of potentially unifying molecular disease mechanisms. We assert that the identification of functional clusters of these proteins, grouped by such common mechanisms, will streamline our understanding of the disease processes and identify therapeutic targets relevant to individuals in multiple disease subgroups, including individuals whose pathogenic mutations have not been found. By extension, this approach may serve as a tool to not only find common mechanisms, but may also help to distinguish LGMD subtypes that do not share similar functional patterns, and afford further refinement of potential treatments.

[19] The ties that bind: functional clusters in limb-girdle muscular dystrophy

  • Authors: E. Barton, C. A. Pacak, Whitney L. Stoppel, Peter B. Kang
  • Year: 2020
  • Venue: Skeletal Muscle
  • URL: https://www.semanticscholar.org/paper/3493c658bb8716d789a05ddf292162832e064e47
  • DOI: 10.1186/s13395-020-00240-7
  • Summary: A deeper understanding of these disease pathways could yield a new generation of precision therapies that would each be expected to treat a broader range of LGMD patients than a single subtype, thus expanding the scope of the molecular medicines that may be developed for this complex array of muscular dystrophies.
  • Evidence snippets:
  • Snippet 1 (score: 0.377) > Pyridine nucleotide-disulfide reductase [55] Many of the protein functions listed require further confirmation or are disputed these methodologies. Those patients with moderate disease phenotypes regardless of the underlying causative gene mutation would likely fall into a category where there may be interest in testing a pharmacological treatment (that could be halted) but reduced interest in a more permanent experimental strategy. For all of the above-mentioned reasons, the identification of unifying therapeutic targets applicable to multiple subtypes of > LGMDs is highly desirable. > To identify such targets, we should first consider the question: What binds all of these LGMDs together? The two core phenotypic features are progressive proximal muscle weakness, along with characteristic signs of muscle fiber destruction on biopsy, referred to as "dystrophic" features. Nuances in clinical presentation have helped to distinguish some of the LGMDs, such as the frequent occurrence of difficulty walking on tiptoes in LGMD R2 (LGMD2B), caused by dysferlin deficiency. However, heterogeneity associated with variable ages of onset and ranges of severity makes it generally difficult to distinguish and diagnose LGMD subtypes based on clinical presentation alone. A change in perspective is in order to aid in understanding disease pathways responsible for clinical features even when the genetic mutation is unknown. Further, given the large number of genespecific LGMD subtypes, it could very well be that several major disease mechanisms may be shared across the family of diseases. Yet despite careful studies that have collectively determined the cellular localization of most proteins associated with LGMD (Fig. 1), there is limited knowledge of potentially unifying molecular disease mechanisms. We assert that the identification of functional clusters of these proteins, grouped by such common mechanisms, will streamline our understanding of the disease processes and identify therapeutic targets relevant to individuals in multiple disease subgroups, including individuals whose pathogenic mutations have not been found. By extension, this approach may serve as a tool to not only find common mechanisms, but may also help to distinguish LGMD subtypes that do not share similar functional patterns, and afford further refinement of potential treatments.

[20] Nasopharyngeal Carcinoma Signaling Pathway: An Update on Molecular Biomarkers

  • Authors: W. Tulalamba, T. Janvilisri
  • Year: 2012
  • Venue: International Journal of Cell Biology
  • URL: https://www.semanticscholar.org/paper/307cb9186444d9dad6e2e3b53763be0de76de186
  • DOI: 10.1155/2012/594681
  • PMID: 22500174
  • PMCID: 3303613
  • Citations: 93
  • Influential citations: 5
  • Summary: The molecular signaling pathways in the NPC are discussed for the holistic view of NPC development and progression and the important insights toward NPC pathogenesis may offer strategies for identification of novel biomarkers for diagnosis and prognosis.
  • Evidence snippets:
  • Snippet 1 (score: 0.374) > In the pregenomic eras, highly integrated and complex circuitry of molecular signaling in NPC pathogenesis was only partially understood. Over the past decade, the knowledge of the molecular mechanisms in NPC carcinogenesis has been rapidly accumulated. Dysregulation and abnormal protein expression of molecules in certain signaling pathways involved in cellular functions including proliferation, adhesion, survival, and apoptosis has been demonstrated in the NPC cells. Detailed information on the complex network in signaling pathway leading to a coordinated pattern of gene expression and regulation in NPC will undoubtedly provide important clues to develop novel prognostic and therapeutic strategies for this cancer. Refining molecular markers into clinically relevant assays may assist in the detection of NPC in asymptomatic patients, as well as stage classification and monitoring disease progression and treatments. Furthermore, selective regulation of particular proteins targeting cancer cell proliferation, invasion, and apoptosis is a hopeful prospect for future anticancer therapy that slow disease progression and improve survival.

Notes

  • This provider combines search_papers_by_relevance with snippet_search.
  • No synthesis or second-stage model call is performed.