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

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

• Papers retrieved: 19
• Snippets retrieved: 20

Relevant Papers

[1] 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
• Citations: 2
• 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: 0.415) > 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.

[2] 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: 27
• 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: 0.371) > Omics profiling significantly expanded the molecular landscape describing clinical phenotypes. Association analysis resulted in first diagnostic and prognostic biomarker signatures entering clinical utility. However, utilizing Omics for deepening our understanding of disease pathophysiology, and further including specific interference with drug mechanism of action on a molecular process level still sees limited added value in the clinical setting. We exemplify 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. Interference analysis on the molecular model level allows identification of predictive biomarker candidates for testing drug response. We discuss this strategy on diabetic nephropathy (DN), a complex clinical phenotype triggered by diabetes and presenting with renal as well as cardiovascular endpoints. A molecular pathway map indicates involvement of multiple molecular mechanisms, and selected biomarker candidates reported as associated with disease progression are identified for specific molecular processes. Selective interference of drug mechanism of action and disease-associated processes is identified for drug classes in clinical use, in turn providing precision medicine hypotheses utilizing predictive biomarkers.
• Snippet 2 (score: 0.345) > 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.

[3] Valosin-Containing Protein (VCP): A Review of Its Diverse Molecular Functions and Clinical Phenotypes

• Authors: Carly S. Pontifex, Mashiat Zaman, R. Fanganiello, T. Shutt, G. Pfeffer
• Year: 2024
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/a0717d977acc61d9c08343d1ac6aed94c33f2138
• DOI: 10.3390/ijms25115633
• PMID: 38891822
• PMCID: 11172259
• Citations: 30
• Summary: In this review we examine the functionally diverse ATPase associated with various cellular activities (AAA-ATPase), valosin-containing protein (VCP/p97), its molecular functions, the mutational landscape of VCP and the phenotypic manifestation of VCP disease. VCP is crucial to a multitude of cellular functions including protein quality control, endoplasmic reticulum-associated degradation (ERAD), autophagy, mitophagy, lysophagy, stress granule formation and clearance, DNA replication and mito...
• Evidence snippets:
• Snippet 1 (score: 0.367) > Although the major roles of VCP in protein quality control are presumed to be the major mechanisms implicated in MSP, the incredible functional diversity and pleiotropic effects of VCP also imply that other mechanisms may be relevant and require further study.VCP cooperates with the 26S proteasome, the main pathway for protein degradation, to manage the protein quality control system.In the nucleus, VCP regulates cell cycle control and the DNA damage response by coordinating proteins at DNA damage sites.In the cytosol, VCP regulates responses to cellular stress by forming and clearing stress granules, facilitating ERAD, autophagy, mitophagy and lysophagy, and VCP may also be involved in apoptosis.The complexity of VCP's diverse molecular functions is also mirrored by the variability in clinical dysfunction caused by pathogenic variants in VCP.The relationship between specific molecular functions of VCP and the spectrum of clinical presentations remains poorly understood, and, in general, genotype-phenotype correlation is still difficult to demonstrate.Certainly, VCP plays many yet-to-be-identified roles in different cellular systems.Given that the role of VCP extends to so many cellular systems, it makes it difficult to ascertain which dysfunction leads to which clinical phenotype.The majority of MSP cases are related to variants at positions 155 and 159, but the phenotypic variability is extensive, suggesting that other genetic or epigenetic factors and/or environmental factors may interact.To better narrow down a causative mechanism in a given tissue, we advise that, when possible, experiments should include one or two other MSP genes such as SQSTM1 or HNRNPA2B1, as this may help identify common mechanisms of dysfunction in MSP.Studies of large cohorts of patients who have common variants in VCP may allow for the identification of genetic modifiers or other factors that contribute to phenotypic variability.Even though pathogenic variants in VCP typically lead to multisystem disease, in general, the affected systems predictably include certain tissue types (primarily skeletal muscle, the cerebrum, motor neurons and osteoclasts).Even though VCP is ubiquitously expressed and participates in numerous crucial cellular functions, pan-systemic disease is not observed.

[4] The Lamin Proteins in Nuclear Structure, Functions, and Laminopathies

• Authors: Gan Zhao, Ziheng Chen, Caifeng Yang, Mingzheng Liu, Weiyong Wang et al.
• Year: 2026
• Venue: Cells
• URL: https://www.semanticscholar.org/paper/9db8088d893cc5c3de80d3afda68b52e1cf501fc
• DOI: 10.3390/cells15121051
• PMID: 42346079
• PMCID: 13296569
• Citations: 1
• Summary: Collectively, studies of lamin protein function reveal how the nucleus maintains its structures and functions, while studies of laminopathies demonstrate how nuclear dysfunction drives systemic disease and points toward mechanism-based therapies.
• Evidence snippets:
• Snippet 1 (score: 0.362) > Laminopathies represent a clinically diverse class of human diseases caused by mutations in genes encoding components of the nuclear lamina and associated nuclear envelope proteins. Here, we summarize the mutation sites, phenotypes, and underlying molecular mechanisms of laminopathies (Table 1). Although mutations in LMNA account for the majority of reported cases, disease-causing alterations in B-type lamins, particularly LMNB1, as well as mutations in other nuclear envelope proteins, also give rise to distinct laminopathy phenotypes [13,77]. The pathogenesis of laminopathies is explained through several interconnected mechanistic frameworks. The classical structural hypothesis attributes disease to compromised nuclear integrity and impaired mechanical signaling, leading to stress-induced cellular damage, particularly in striated muscle tissues [23]. In contrast, the "gene expression hypothesis" emphasizes that lamin mutations disrupt chromatin organization and intracellular signaling pathways, thereby altering transcriptional programs [12,119]. More recently, these perspectives have been integrated with models highlighting cellular senescence, stem cell exhaustion, and chronic inflammation as additional pathogenic contributors, especially in progeroid syndromes [112]. Current evidence suggests that these mechanisms are not mutually exclusive but operate within an interconnected and synergistic network that drives disease progression [120]. > In laminopathies, mutations affect structural components present in nearly all nucleated cells. Nevertheless, laminopathies exhibit marked tissue-specific vulnerability, predominantly affecting striated muscle, adipose tissue, peripheral nerves, or, in some cases, causing systemic premature aging [12,15]. This tissue selectivity likely arises from the interaction between a specific lamin mutation and the distinct mechanical demands, transcriptional programs, and developmental context of individual tissues [15,119]. Consequently, although laminopathies share common molecular roots, their clinical manifestations are highly system-oriented. > For this reason, laminopathies are conventionally classified according to the primary tissue or organ system affected, despite substantial phenotypic overlap among categories [14]. This classification provides a clinically practical framework while acknowledging that shared pathogenic mechanisms underlie seemingly distinct disease entities. > Striated muscle laminopathies represent a major disease category.

[5] 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: 39
• 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: 0.359) > 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.

[6] 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: 30
• 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: 0.351) > 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.

[7] Solving the Evidence Interpretability Crisis in Health Technology Assessment: A Role for Mechanistic Models?

• Authors: E. Courcelles, J. Boissel, J. Massol, I. Klingmann, R. Kahoul et al.
• Year: 2022
• Venue: Frontiers in Medical Technology
• URL: https://www.semanticscholar.org/paper/877d5b1b75599745f704a9c8371f74601ff17e2f
• DOI: 10.3389/fmedt.2022.810315
• PMID: 35281671
• PMCID: 8907708
• Citations: 7
• Summary: Light is shed on different stakeholder's contributions and needs in the appraisal phase and how mechanistic modeling strategies and reporting can contribute to this effort to implement mechanistic models central in the evidence generation, synthesis, and appraisal of HTA so that the totality of mechanistic and clinical evidence can be leveraged by all relevant stakeholders.
• Evidence snippets:
• Snippet 1 (score: 0.348) > Example use of MIDD relevant to address uncertainty potentially also during HTA What is the optimal dosage in the clinical context? Physiologically based pharmacokinetic models can investigate dosing-regimens relevant for regulatory review and product labels (9) and can also mimic real-life adherence to prescribed treatment regimens (see also below) or pharmacology-relevant characteristics of special populations as well as drug-drug interactions. > What is the duration of the effectiveness, especially with chronic use of a treatment? Mechanistic models can predict the long-term disease progression by extrapolation of shorter-term findings under the constraints of how the components of the system function (and these constraints convey biological plausibility by design). An example is the use of a mechanism-based disease progression model for comparison of long-term effects of pioglitazone, metformin, and gliclazide on disease processes underlying Type 2 Diabetes Mellitus (10). Another example is prediction of long-term outcomes by short-term marker data as demonstrated by a semi-mechanistic approach in context of osteoporosis treatment (11). > What is the efficacy for relevant clinical outcomes? Mechanistic models combined with pharmacometric approaches can translate findings for one outcome to a range of other outcomes. An example of survival modeling on the back of a mechanistic description is the modeling framework for CD19-Specific CAR-T cell immunotherapy using a quantitative systems pharmacology model (12). > What is the size of the clinical effect dependent on patient characteristics and extrinsic factors? Data-driven modeling techniques can capture correlation within clinical data. Describing the clinical effect of a drug can also be based on mechanistic considerations. Such models either (a) link disease phenotypes to increasingly granular mathematical representations of pathophysiologic processes (top-down approach) or (b) derive functional, computable cellular networks from the molecular building blocks of genes and proteins to elucidate the impact of pathologic or therapeutic alterations on network operating states and hence clinical phenotype (bottom-up) [see (13)].

[8] Recent Evidences of Epigenetic Alterations in Chronic Obstructive Pulmonary Disease (COPD): A Systematic Review

• Authors: R. Ragusa, P. Bufano, A. Tognetti, M. Laurino, Chiara Caselli
• Year: 2025
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/2660cdbbe1f205c631fe890e5c6a3c8d9b81ce5f
• DOI: 10.3390/ijms26062571
• PMID: 40141213
• PMCID: 11942187
• Citations: 12
• Summary: A systematic review of the latest knowledge on epigenetic modifications that characterize COPD, summarizing epigenetic factors that could serve as potential novel biomarkers and therapeutic targets for the treatment of COPD patients.
• Evidence snippets:
• Snippet 1 (score: 0.348) > The papers included were clustered according to epigenetic mechanisms involved in COPD (molecular and cellular processes, as biomarker or therapeutic target). Tables 4-9 describe the extracted information, including the following: Study = name of first author et al., year; Country (Region) = where the study took place; Number of participants = sample size; Type of sample = biological sample employed; Gene affected = gene or group of genes whose expression can be "regulated" by epigenetic mechanisms; Epigenetic alteration = type of epigenetic alteration observed in the presence of disease; Activity in COPD = involvement of epigenetic elements in different molecular and cellular mechanisms associated with COPD; and Role of epigenetic mechanisms = epigenetic modifications that can be used to explain the pathophysiology of COPD or as biomarkers and therapeutic targets.

[9] Post-Translational Modifications of Histones and Non-Histones in Liver Disease and Traditional Chinese Medicine Treatment: A Narrative Review

• Authors: Zhuohua Xie, Yanting Deng, Xinru Zhang, Jieyi Chen, Jiasheng Deng et al.
• Year: 2026
• Venue: Pharmacogenomics and Personalized Medicine
• URL: https://www.semanticscholar.org/paper/fc27e05d5797aea14c621925ed04e3fc1afa015b
• DOI: 10.2147/PGPM.S555701
• PMID: 41908737
• PMCID: 13022904
• Summary: How traditional Chinese medicine (TCM) can intervene in liver diseases by modulating protein post-translational modifications, providing new strategies for future prevention and treatment of liver diseases is outlined.
• Evidence snippets:
• Snippet 1 (score: 0.347) > This paper outlines the roles and pathway mechanisms mediated by PTMs in liver diseases, especially for TCM that can interfere in liver diseases by regulating protein post-translational modification. It indicates that PTMs function in regulating protein function, maintaining cell homeostasis, regulating signaling and regulating gene expression in normal cellular molecular mechanisms. PTMs themselves and their crosstalk play an important role in the progression of liver disease. For example, studies conducted a thorough comprehensive analysis of HCC by driving PTMs, proposed PTPN 2-STAT 1-AOX1 for HCC development, and provided multiple databases of PTMs in HCC. 170 Increasing evidence TCM has great advantages in the treatment of chronic liver disease, containing rich bioactive ingredients has the function of protecting the liver and gallbladder. In the study of the molecular mechanism of TCM treatment of liver diseases, it plays a role through multi-components, multi-targets and multi-pathway ways. Crucially, PTMs as the key mechanism of regulating protein function, may be one of the important molecular basis of traditional Chinese medicine. For instance, with the clinical application of Salvia miltiorrhiza Bunge-Reynoutria japonica Houtt. drug pair in the treatment of chronic liver disease, its core metabolite, Luteolin, can relieve NAFLD by inhibiting the phosphorylation of PI3K-AKT-mTOR signaling pathway and inducing autophagy. 171 Danphenolic acid B (Salvianolic acid B, SalB) of Salvia miltiorrhiza inhibited the activation of HSCs and alleviated liver fibrosis by mediating TGF-β/ SMAD and MAPK pathway ways and phosphorylation of SMAD2/3 and SMAD2 at the C end (P-SMAD2C), while increasing the phosphorylation of SMAD 3 at the C end (P-SMAD3C). 172 TMs combined with TCM has important scientific significance and clinical application value. By regulating PTMs, TCM can intervene in the pathological process of liver diseases through multiple targets and multiple ways, providing new ideas and methods for the treatment of liver diseases.

[10] 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: 96
• 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: 0.346) > 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.

[11] Prioritizing Molecular Biomarkers in Asthma and Respiratory Allergy Using Systems Biology

• Authors: Lucía Cremades-Jimeno, M. D. de Pedro, M. López-Ramos, J. Sastre, P. Mínguez et al.
• Year: 2021
• Venue: Frontiers in Immunology
• URL: https://www.semanticscholar.org/paper/d8ca6e130adec2dfa39545eb1763827d9450e4f5
• DOI: 10.3389/fimmu.2021.640791
• PMID: 33936056
• PMCID: 8081895
• Citations: 15
• Influential citations: 1
• Summary: This study has enabled it to prioritize biomarkers depending on the functionality associated with each disease and with specific molecular motifs, which could improve the definition and usefulness of new molecular biomarkers.
• Evidence snippets:
• Snippet 1 (score: 0.345) > Firstly, the molecular characterization of the three pathophysiological processes of interest (respiratory allergy, allergic asthma, and nonallergic asthma) was performed using the Therapeutic Performance Mapping System (TPMS) technology (Anaxomics Biotech, Barcelona, Catalonia, Spain) (31). Briefly, systems biology generates models that are able to reproduce the behavior of a disease in a patient, thus identifying the key genes, proteins, or metabolites in the development of the disease. A dictionary has been created to translate clinical and medical terms into molecular biology data, effectively linking the molecular and the clinical words. This dictionary, called the Biological Effectors Database (BED), relates biological processes (adverse events of drugs, drug indications, diseases, etc.) with the proteins most closely associated with them. Thus, the dictionary acts as a translator of clinical phenotypes into terms comprehensible for protein networks, and conversely allows for the translation of molecular measures toward clinical outcomes. The BED is structured hierarchically, where the biggest level is the entire disease, which is divided into different pathophysiological molecular motifs, which in turn contain the proteins involved in the development of the disease. The motifs are classified into two levels depending on their respective implication, i.e. causal motifs, which are directly related to the onset or pathophysiology of the condition, and symptomatic (manifestative) motifs, which are a consequence of the disease. > In the present study, respiratory allergy, allergic asthma, and non-allergic asthma have been characterized at the molecular level. Therefore, the analysis of high throughput data by means of TPMS allows for identification of those proteins closely associated with the disease of interest and can provide a mechanistic rationale for their involvement. The effector proteins of the manifestative and causal molecular motifs of these three diseases have been identified through bibliographic review and curate data. Figure 1 summarizes the workflow used for this study.

[12] 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: 12
• 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: 0.344) > 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].

[13] Major pathophysiological changes in pulmonary disease provided a molecular insight based on deep learning approach

• Authors: Swaraj Mohanty, Poornima Sharma, Yasmin Ahmad
• Year: 2025
• Venue: Scientific Reports
• URL: https://www.semanticscholar.org/paper/e10fbd9bd751f596a649b26ab14ae0e86d94aeeb
• DOI: 10.1038/s41598-025-15539-y
• PMID: 40887476
• PMCID: 12399767
• Summary: Bioinformatics analysis of the disease was analyzed based on the expression profiles of the genes and the major proteins from the protein-protein interaction STRING network, concluding that the perturbed molecules interplay a vital role in the progression of airway diseases and targeting the major pathways can be a possible therapeutic intervention for curing the disease.
• Evidence snippets:
• Snippet 1 (score: 0.342) > Elucidating the outcomes of this study with the machine learning approach not only simplified in getting the compilation of major signaling pathways discovered to date but also draws a conclusion on the key molecules like VEGF, STAT, PI3K, AKT signaling and the interrelated molecular cascade of eNOS, HSP90, CDK, GPCR in the progression of the disease. And from the gene ontology study, it also clear that the expression pattern may differ in disease type, but the molecular mechanism has an interlinking molecular cascade activation in all types of pulmonary diseases with a common mode of pathophysiological principle triggering its molecular signatures. Although in our present study we tried to reveal the possible mechanism relation among the major pathways from a data mining approach for different pulmonary diseases in a concise manner, focusing on various aspects like inflammation, redox signaling and metabolic perturbed signaling processes, there are many gaps and solid evidence on the molecular mechanism of hypoxia that need serious attention from the global researchers. The futuristic studies on these lagging areas should involve the high-throughput techniques to explore the pathophysiology and molecular mechanistic approach in understanding the therapeutic possibilities by targeting the major common pathways in between gene and protein expression studies at the cellular and subcellular level. And the exploration of these pathophysiological studies will definitely open new doors in understanding the target molecules and the development of pre-diagnostic therapeutic strategies, leading to a pharmaceutical revolution in upcoming days to a disease-free life.

[14] Molecular Genetics of Bartter Syndrome: Bridging Genotype–Phenotype Correlations and Precision Therapeutics

• Authors: Lina Zhu, Yang Li, Yiyao Bao
• Year: 2026
• Venue: Current Issues in Molecular Biology
• URL: https://www.semanticscholar.org/paper/a5e1ddccfa7d333834c4d32be123c71bfd573f83
• DOI: 10.3390/cimb48040422
• PMID: 42042082
• PMCID: 13114623
• Summary: A comprehensive framework to provide a comprehensive framework to facilitate precise diagnosis and individualized treatment strategies, ultimately advancing precision medicine in the management of Bartter syndrome is provided.
• Evidence snippets:
• Snippet 1 (score: 0.341) > Molecular genetic research on Bartter syndrome has made remarkable strides, elucidating the principal BS genes SLC12A1, KCNJ1, CLCNKB, BSND, and MAGED2 and their corresponding protein defects, thereby refining the molecular framework of disease classification while separating CaSR-associated Bartter-like disease from the core canonical BS spectrum. This progress has significantly deepened our understanding of the underlying pathophysiology and provided an essential framework for correlating genotypes with clinical phenotypes. However, the intricate relationship between genetic mutations and clinical manifestations remains complex and multifaceted, reflecting the profound heterogeneity of the syndrome. Addressing these diagnostic challenges and refining disease classification beyond traditional clinical criteria requires an integrative approach that seamlessly balances high-throughput sequencing technologies with rigorous functional studies. > The mechanisms by which these genetic mutations lead to protein dysfunction are diverse, encompassing critical defects in protein expression, impaired membrane localization, and direct functional impairments. Notably, aberrant protein folding, endoplasmic reticulum-associated degradation (ERAD), and splicing abnormalities have emerged as critical pathogenic pathways. These mechanistic insights not only enhance our fundamental understanding of the disease but also highlight highly promising therapeutic targets. While current treatments remain predominantly symptomatic, focusing primarily on managing electrolyte imbalances and associated complications, they inherently fail to address the underlying molecular defects driving the disease. > The precise identification of specific molecular defects opens innovative avenues for the development of targeted interventions aimed at correcting or compensating for specific protein abnormalities. For instance, molecular chaperones that assist in protein folding, agents that modulate aberrant splicing, and future gene-based strategies represent important experimental directions for mechanism-based therapy. Consequently, the future of Bartter syndrome management may increasingly move toward precision medicine tailored to the molecular pathology of individual patients. However, the transition from concept to clinical implementation will require substantial additional functional, translational, and trial-level evidence. Such mechanism-based strategies promise not only to alleviate clinical symptoms but to fundamentally modify disease progression, thereby drastically improving long-term prognosis and quality of life for patients.

[15] Molecular insights into the premature aging disease progeria

• Authors: Sandra Vidak, R. Foisner
• Year: 2016
• Venue: Histochemistry and Cell Biology
• URL: https://www.semanticscholar.org/paper/60fb3b46bb7e42d5d08cc3b7cbc783b118300c31
• DOI: 10.1007/s00418-016-1411-1
• PMID: 26847180
• PMCID: 4796323
• Citations: 107
• Influential citations: 4
• Summary: Changes in mechanosignaling, altered chromatin organization and impaired genome stability, and changes in signaling pathways, leading to impaired regulation of adult stem cells, defective extracellular matrix production and premature cell senescence are discussed.
• Evidence snippets:
• Snippet 1 (score: 0.340) > The number of molecular biological studies aiming at the identification of lamin-mediated molecular disease mechanisms involved in HGPS increased tremendously following the surprising discovery that LMNA is causally linked to the premature aging disease HGPS in 2003. Despite numerous cellular pathways that were identified to be affected by the expression of the mutant lamin A protein (Fig. 2), the mechanistic details behind these effects are still unclear in most cases. Knowledge based on what was already known on lamin biology before the protein was linked to HGPS and findings on novel roles of lamins in diverse pathways in recent years allowed the launch of translational studies and the efficient search for drug targets and therapeutic approaches within a short time period. The results of the first clinical trials taught us that some improvements of the disease phenotypes can be achieved by FTI treatment, but they also made clear that we need a much better understanding of the underlying disease mechanisms to be able to tackle specific aspects of the disease in a more focused approach. It will also be important to elucidate which of the numerous pathways found to be impaired in HGPS are most relevant for and causally involved in the pathologies, and which ones are just bystanders.

[16] New Insights into Mitochondria in Health and Diseases

• Authors: Ya Li, Huhu Zhang, Chunjuan Yu, Xiaolei Dong, Fanghao Yang et al.
• Year: 2024
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/23002a4ffabfd043f52c664f4d5acab85b8dcac0
• DOI: 10.3390/ijms25189975
• PMID: 39337461
• PMCID: 11432609
• Citations: 46
• Summary: This overview outlines the various mechanisms by which mitochondria are involved in numerous illnesses and cellular physiological activities and provides new discoveries regarding the involvement of mitochondria in both disorders and the maintenance of good health.
• Evidence snippets:
• Snippet 1 (score: 0.339) > Mitochondria are essential organelles within cells, playing critical roles not only in energy metabolism but also in various cellular activities, such as cell differentiation, signal transduction, and apoptosis. Mitochondrial dysfunction is implicated in a range of diseases, including but not limited to diabetes and its complications, neurodegenerative disorders, myocardial ischemia-reperfusion injury, and heart failure. Therefore, investigating the structure and function of mitochondria as well as the mechanisms underlying mitochondrial dysfunction in disease contexts holds significant scientific and clinical importance. > Basic scientific research: Diseases manifest systemically and exhibit complexity; thus, it is imperative to understand mitochondrial structure at the molecular level along with known pathways while characterizing novel pathways that influence mitochondrial behavior and functionality. For instance, mapping genetic interactions among genes encoding mitochondrial proteins can elucidate interrelations between different aspects of mitochondrial function. The first focused map of mitochondria has been constructed in yeast models, revealing dense and significant connections among localization pathways distributed across various mitochondrial compartments [126]. > Disease diagnosis: A comprehensive understanding of the mechanisms governing mitochondrial dysfunction can facilitate the development of innovative diagnostic tools. By monitoring specific indicators related to mitochondrial function, earlier diagnosis of diseases associated with mitochondrial impairment becomes feasible. Employing nextgeneration sequencing technologies for analyzing the mitochondrial proteome aids in identifying novel proteins and pathways linked to mitochondria while enabling streamlined diagnostics alongside genetic counseling opportunities for patients with mitochondrial diseases [127]. > Drug development: Advancements in our comprehension of how mitochondria contribute to disease processes may promote targeted therapeutic strategies. For example, metformin-a widely used antidiabetic agent-has recently been repurposed as an anticancer drug; its combination with standard epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) significantly improves progression-free survival rates and overall survival outcomes for patients with advanced lung adenocarcinoma [125]. > Personalized medicine: Given that manifestations of mitochondrial dysfunction may vary among individuals, research into mitochondria provides a theoretical foundation for personalized medicine by allowing tailored treatment plans based on individual states of mitochondrial functionality [127].

[17] 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: 5
• 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: 0.339) > : 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.

[18] 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: 40
• Influential citations: 1
• 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: 0.339) > 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].

[19] Finding patterns in lung cancer protein sequences for drug repurposing

• Authors: Belén Otero-Carrasco, Paloma Tejera Nevado, Rafael Muñoz, Gema Díaz Ferreiro, Aurora Pérez et al.
• Year: 2025
• Venue: PLOS One
• URL: https://www.semanticscholar.org/paper/a40939b7bcedabfd6cf4db42cdadb0caacba73f4
• DOI: 10.1371/journal.pone.0322546
• PMID: 40334012
• PMCID: 12058034
• Citations: 2
• Summary: A novel computational framework was developed to extend this pattern-based analysis to proteins linked to other diseases, and relationships between lung cancer drug-target proteins and proteins associated with four additional cancer types were uncovered.
• Evidence snippets:
• Snippet 1 (score: 0.339) > Proteins, made up of 20 amino acids, are crucial for biological functions like structure and catalysis. Their structure is organized into four levels: the primary structure is the linear sequence of amino acids; the secondary involves shapes like alpha helix and beta sheets form through hydrogen bonds; the tertiary structure is the 3D shape resulting from protein folding; and the quaternary structure occurs when multiple polypeptide chains (subunits) combine into complex structures [1]. Protein sequences are essential for understanding diseases as they regulate cellular functions, gene expression, and immune responses. Identifying important regions within these sequences helps uncover disease mechanisms, detect patterns, mutations, or attention due to their ability to model complex interactions between drugs, targets, and disease pathways. Recent studies have demonstrated the effectiveness of these methods in identifying potential therapeutic agents by leveraging network topology and multi-omics data integration [8][9][10][11]. Their application has provided relevant insights into disease mechanisms and drug action, complementing other computational methodologies. > In this context, computational drug repurposing approaches have gained attention in recent years and utilize databases that enable gene and protein function prediction by comparing amino acid sequences, with tools like BLAST and FASTA [12]. Mutations in the DNA's protein-coding regions are often linked to human genetic disorders, providing insights into disease mechanisms through protein structure analysis. Understanding disease severity requires identifying specific basepair mutations, which vary based on protein function, the number of affected amino acids, and mutation type. For example, base pair substitutions can cause silent mutations, while insertions or deletions may result in frameshift mutations, potentially resulting in nonfunctional proteins. Additionally, mutations involving multiples of three base pairs can affect protein functionality differently [13]. > The proposed shift in genetic disease classification focuses on molecular pathways rather than traditional categories like monogenic, oligogenic, or polygenic/multifactorial. This pathway-based system organizes disease according to the affected molecular pathways that produce specific phenotypes, enhancing our understanding of disease presentation and progression [14]. Additionally, the classification highlights correlations between disease-related proteins and the sequences of charged residues, aiding in function determination and evolutionary tracking. Effective communication between distant residues is vital for protein functionality, with bioinformatics tools helping identify correlated residues.

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