0
Mappings
0
Definitions
0
Inheritance
6
Pathophysiology
0
Histopathology
5
Phenotypes
12
Pathograph
1
Genes
2
Treatments
0
Subtypes
2
Differentials
0
Datasets
0
Trials
0
Models
1
Literature

Pathophysiology

6
ABHD12 loss of lipid hydrolase activity
Biallelic ABHD12 deficiency impairs degradation of bioactive lysophosphatidylserine and related oxidized phospholipids.
microglial cell link
ABHD12 link
lipid catabolic process link ⚠ ABNORMAL
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene."
This directly supports ABHD12 loss as the initiating cause of PHARC syndrome.
Abnormal lysophosphatidylserine signaling
Disordered lysophospholipid handling is thought to drive inflammatory and degenerative injury in nervous system tissues.
microglial cell link
Show evidence (1 reference)
PMID:23297193 SUPPORT Model Organism
"Taken together, our data provide a molecular model for PHARC, where disruption of ABHD12 causes deregulated LPS metabolism and the accumulation of proinflammatory lipids that promote microglial and neurobehavioral abnormalities."
This directly supports dysregulated lysophosphatidylserine metabolism as a downstream consequence of ABHD12 loss in a PHARC model.
Progressive multisystem neurodegeneration
Chronic neurodegenerative injury contributes to the characteristic combination of neuropathy, ataxia, hearing loss, and retinal degeneration.
Show evidence (1 reference)
PMID:23297193 PARTIAL Model Organism
"Notably, elevations in brain LPS lipids in ABHD12(-/-) mice occur early in life (2-6 mo) and are followed by age-dependent increases in microglial activation and auditory and motor defects that resemble the behavioral phenotypes of human PHARC patients."
This supports age-dependent neurodegenerative progression downstream of ABHD12 loss in a PHARC model, while the full human multisystem trajectory is inferred across clinical domains.
Peripheral nerve degeneration
Progressive peripheral nerve injury contributes to the polyneuropathy component of PHARC syndrome.
Cerebellar degeneration
Progressive cerebellar involvement contributes to gait instability and ataxia.
Retinal degeneration
Retinal and macular degeneration contribute to the retinitis pigmentosa phenotype.
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"Fundus examination revealed macular involvement in all patients, ranging from alterations of the retinal pigment epithelium to macular atrophy."
This directly supports retinal degenerative involvement in PHARC syndrome.

Pathograph

Use the checkboxes to hide or show graph categories. Hover nodes for evidence and cross-linked metadata.
Pathograph: causal mechanism network for PHARC syndrome Interactive directed graph showing how pathophysiology mechanisms, phenotypes, genetic factors and variants, experimental models, environmental triggers, and treatments relate through causal and linked edges.

Phenotypes

5
Ear 1
Sensorineural hearing impairment Sensorineural hearing impairment (HP:0000407)
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene."
This directly supports hearing loss as part of the defining PHARC syndrome phenotype.
Eye 2
Retinitis pigmentosa Rod-cone dystrophy (HP:0000510)
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"Fundus examination revealed macular involvement in all patients, ranging from alterations of the retinal pigment epithelium to macular atrophy."
This directly supports retinal degenerative disease within the PHARC phenotype.
Cataract Cataract (HP:0000518)
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"Different types of cataract were observed in 13 out of 15 patients (87%), which also included congenital forms of cataract."
This directly supports cataract as a common PHARC phenotype.
Nervous System 2
Peripheral neuropathy Peripheral neuropathy (HP:0009830)
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene."
This directly supports peripheral neuropathy as part of the defining PHARC acronym.
Ataxia Ataxia (HP:0001251)
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene."
This directly supports ataxia as a defining component of PHARC syndrome.
🧬

Genetic Associations

1
ABHD12 (Causal biallelic loss-of-function variant)
Show evidence (1 reference)
PMID:34573385 SUPPORT Human Clinical
"This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene."
This directly supports ABHD12 as the causal gene in PHARC syndrome.
💊

Treatments

2
Supportive multidisciplinary care
Action: supportive care MAXO:0000950
Management is supportive and includes neurologic, low-vision, audiologic, and rehabilitation interventions.
Target Phenotypes: Peripheral neuropathy Ataxia
Cataract surgery
Action: surgical procedure MAXO:0000004
Cataract extraction may improve visual function when lens opacity becomes clinically significant.
Target Phenotypes: Cataract
🔀

Differential Diagnoses

2

Conditions with similar clinical presentations that must be differentiated from PHARC syndrome:

adult Refsum disease Not Yet Curated MONDO:0009958
Overlapping Features Refsum disease can overlap with retinitis pigmentosa, neuropathy, and ataxia.
Usher syndrome Not Yet Curated MONDO:0019501
Overlapping Features Usher syndrome overlaps through retinal degeneration and hearing loss but lacks the full PHARC neurodegenerative profile.
📚

Literature Summaries

1
Asta
Asta Literature Retrieval: Pathophysiology and clinical mechanisms of PHARC syndrome. Core disease mechanisms, molecular and cellular pathways,...
Asta Scientific Corpus Retrieval 20 citations 2026-04-13T13:49:18.504039

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

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

  • Papers retrieved: 20
  • Snippets retrieved: 20

Relevant Papers

[1] The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective

  • Authors: X. Nguyen, Hind Almushattat, Ine Strubbe, M. Georgiou, Catherina H. Z. Li et al.
  • Year: 2021
  • Venue: Genes
  • URL: https://www.semanticscholar.org/paper/2e906722d670c765172623c35abd048194030d61
  • DOI: 10.3390/genes12091404
  • PMID: 34573385
  • PMCID: 8467809
  • Citations: 14
  • Influential citations: 5
  • Summary: From an ophthalmic perspective, clinical manifestations in patients with PHARC demonstrate variability with regard to their onset and severity, and an early multidisciplinary assessment is recommended to assess disease severity.
  • Evidence snippets:
  • Snippet 1 (score: 0.438) > Microglial cells possibly play an initiating role in the degeneration of the retina in patients with ABHD12 variants, which aligns with the hypotheses of the microglial cell possibly being one of the driving forces behind neurodegeneration in the central nervous system and inner ear [1,8]. Establishing the causative agent for neurodegeneration in patients with ABHD12 variants is pivotal for the development of treatment modalities for this neurodegenerative disease. For inherited retinal dystrophies, promising results have been achieved with gene therapy, resulting in improvements in visual function [36,37]. Given the size of the primary transcript of ABHD12 (1.1 kb, NM_001042472.3), ABHD12 likely fits into AAV vectors and is therefore a potential candidate for gene augmentation therapy. If the underlying cause of PHARC syndrome has a metabolic and/or immunological basis, suppressing or inhibiting targets in relevant pathways, such as the previously mentioned lyso-PS pathway, could prove to be an attractive alternative approach [19]. Further research into the molecular and biochemical basis of ABHD12 would likely determine the most optimal path for treatment. > In conclusion, we report the phenotype of patients with PHARC syndrome due to biallelic ABHD12 variants. Rod-cone dystrophy is present in all patients with PHARC syndrome with early macular involvement, although this finding may vary widely in its onset and severity. Given the variability in symptoms and clinical findings in patients with PHARC syndrome, patients should be evaluated in a multidisciplinary setting, involving ophthalmologists, neurologists, audiologists/otologists and geneticists, when PHARC syndrome is either suspected or genetically confirmed.

[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: 0.430) > 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] Rare Monogenic Diseases: Molecular Pathophysiology and Novel Therapies

  • Authors: I. Condò
  • Year: 2022
  • Venue: International Journal of Molecular Sciences
  • URL: https://www.semanticscholar.org/paper/6aece75e6947f102b657851b74e8b96df5e654c1
  • DOI: 10.3390/ijms23126525
  • PMID: 35742964
  • PMCID: 9223693
  • Citations: 15
  • Influential citations: 2
  • Summary: A rare disease is defined by its low prevalence in the general population and its presence in a very small number of people.
  • Evidence snippets:
  • Snippet 1 (score: 0.423) > The selective expression or the particular role of specific genes in a single tissue explains the appearance of organ-specific inherited diseases. This is the case of genetic disorders of the kidney, which include dominant and recessive forms of cystic diseases, and renal tubulopathies. Mutations in polycystin-1 (PKD1) or -2 (PKD2) genes lead to autosomaldominant polycystic kidney disease (ADPKD), whose gender-dependent phenotype was analyzed in the study by Talbi et al. [9]. These results, obtained in mice lacking PKD1 expression, show the involvement of intracellular Ca2+ levels in the more severe phenotype affecting male ADPKD animals. Altogether, identification of the molecular mechanisms underlying enhanced Ca2+ signaling and proliferation in cells from male kidneys may contribute to develop novel therapeutics for ADPKD [9]. The autosomal-recessive form of polycystic kidney disease (ARPKD) mostly arises from defects in the gene named polycystic kidney and hepatic disease 1 (PKHD1), whereas a minority of cases is linked to a second causative gene DZIP1L. To examine the still unclear molecular pathophysiology of ARPKD, Cordido et al. recapitulate known molecular disease mechanisms and possible therapeutic approaches, from cellular and animal models to clinical trials [10]. The knowledge of ARPKD pathogenic pathways, involving the epidermal growth factor receptor (EGFR) axis, the production of adenylyl cyclase adenosine 3 ,5 -cyclic monophosphate (cAMP) and the activation of several protein kinases, begins to stimulate possible pharmacological interventions [10]. Inherited loss of function in various electrolyte transport proteins located along the nephron leads to two types of kidney tubulopathy with overlapping clinical symptoms: Gitelman and Bartter syndromes. The review by Nuñez-Gonzalez et al. aims to explain the different molecular basis of these difficult to diagnose monogenic syndromes. Moreover, the authors provide an overview of current therapeutic approaches and highlight the presence of common and specific options for Gitelman and Bartter patients [11].

[4] Targeting Hepatic Stellate Cells for the Prevention and Treatment of Liver Cirrhosis and Hepatocellular Carcinoma: Strategies and Clinical Translation

  • Authors: Hao Xiong, Jinsheng Guo
  • Year: 2025
  • Venue: Pharmaceuticals
  • URL: https://www.semanticscholar.org/paper/76e92127053136900f7e3f10e2c9278251ced5d2
  • DOI: 10.3390/ph18040507
  • PMID: 40283943
  • PMCID: 12030350
  • Citations: 8
  • Summary: HSC-targeted approaches using specific surface markers and receptors may enable the selective delivery of drugs, oligonucleotides, and therapeutic peptides that exert optimized anti-fibrotic and anti-HCC effects.
  • Evidence snippets:
  • Snippet 1 (score: 0.413) > Significant progress has been made in elucidating the cellular and molecular mechanisms of liver fibrosis; however, only a few findings have been successfully translated into clinical applications. Firstly, the high cost of drug development and target validation necessitates prolonged timelines and substantial financial investment. Secondly, as regulatory requirements become more stringent, there is an increasing demand for drugs with well-defined clinical efficacy and safety profiles. Moreover, the efficacy observed in animal models often fails to fully translate to clinical settings due to differences in pharmacokinetics, extracellular matrix (ECM) cross-linking, and disease pathophysiology. Despite advancements in anti-fibrotic drug development, accurately identifying ideal noninvasive biomarkers for fibrotic activity and establishing consensus on optimal clinical endpoints remain significant challenges [113,114]. > Currently, addressing the underlying cause remains the only proven strategy to halt or reverse liver fibrosis progression, while the development of effective anti-fibrotic therapies continues to pose a major challenge in liver disease management. Over the past few decades, substantial progress has been made in elucidating the cellular and molecular mechanisms underlying liver fibrosis. Liver fibrosis is a complex pathological change involving multiple cells, factors, and pathways, and the study of the cellular and molecular mechanisms of its occurrence and development provides an important theoretical basis and therapeutic target for clinical drug development. It is anticipated that improved animal models and well-designed clinical trials will facilitate the successful translation of anti-fibrotic research into effective clinical treatments in the near future.

[5] 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: 0.412) > 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.

[6] Clinical Phenotypes of Cardiovascular and Heart Failure Diseases Can Be Reversed? The Holistic Principle of Systems Biology in Multifaceted Heart Diseases

  • Authors: K. Lourida, G. Louridas
  • Year: 2022
  • Venue: Cardiogenetics
  • URL: https://www.semanticscholar.org/paper/3960806730c4c1115f527e22d6d0a76536570ec5
  • DOI: 10.3390/cardiogenetics12020015
  • Citations: 4
  • Influential citations: 1
  • Summary: Only by understanding the complexity of chronic heart diseases and explaining the interrelationship between different interconnected biological networks can the probability for clinical phenotypes reversal be increased.
  • Evidence snippets:
  • Snippet 1 (score: 0.409) > Treatment with ACEIs, ARBs, and β-blockers impedes deterioration of myocardial function as well as clinical deterioration caused by the deleterious impact of the compensatory systems [58,59]. Therefore, the therapy with ACEIs, ARBs, and β-blockers is the appropriate therapy to block LV remodeling and HF progression and reduce symptoms and/or mortality [55]. > In general, the HF syndrome demonstrates a modular construction with predictable behavior of functional clinical phenotypes having a strong impact on biological networks from epigenetic, cellular to regulatory systems [18]. The importance of individual genes for the pathogenesis and clinical progression of the HF syndrome is restricted to the hypertrophic and dilated cardiomyopathies. It seems that some HF patients have a complex multigenic inheritance, but the importance of individual genes is limited. In contrast, the significant role of epigenetics, proteomics, and metabolomics is increased; but, the complete genetic network system and the interactions between multiomics systems are still uncertain [60]. Multimodal systems that include genetic networks, multiomics, metabolic pathways, environmental factors, and sophisticated disease-related clinical networks are required to be integrated and provide a new holistic and realistic picture. > Significant breakthroughs have been made to understand many of the pathophysiological mechanisms of HFrEF but the natural pathophysiological history and clinical progression of HFpEF still remains inadequately defined [39]. The subclinical progression of pre-clinical diastolic dysfunction (PDD) of LV "to clinical phenotype of HFpEF and the further clinical progression to some more complex clinical models with multi-organ involvement . . . continue to be poorly understood" [40]. Prospective studies are expected to clarify the natural history and clinical progression of HFpEF and define the LV remodeling mechanisms involved. The pathophysiology of LV systolic dysfunction is different to the diastolic dysfunction, as systolic dysfunction is considered a disease of calcium handling and diastolic dysfunction is regarded as a disease of increased myofilament sensitivity to calcium [61][62][63].

[7] 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: 0.402) > 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.

[8] Cardiomyocytes Derived from Induced Pluripotent Stem Cells as a Disease Model for Propionic Acidemia

  • Authors: Esmeralda Alonso-Barroso, B. Pérez, L. Desviat, E. Richard
  • Year: 2021
  • Venue: International Journal of Molecular Sciences
  • URL: https://www.semanticscholar.org/paper/da649a0f04477c53b448c5ac5f873f8762235290
  • DOI: 10.3390/ijms22031161
  • PMID: 33503868
  • PMCID: 7865492
  • Citations: 16
  • Influential citations: 1
  • Summary: The novel results show that PA iPSC-cardiomyocytes represent a promising model for investigating the pathological mechanisms underlying PA cardiomyopathies, also serving as an ex vivo platform for therapeutic evaluation.
  • Evidence snippets:
  • Snippet 1 (score: 0.401) > The study of the mechanisms involved in disease physiopathology has been mainly performed using the hypomorphic PA mouse model that mimics the biochemical and clinical phenotype [5]. Using this model, bioenergetic failure, oxidative damage and deregulation of miRNAs induced by accumulating propionyl-CoA have been described as potential mechanisms contributing to PA physiopathology [6][7][8]. The limitations of animal models for the study of cardiac energy metabolism [9] and of the commonly available cellular human models such as fibroblasts, underline the importance of generating new relevant cell models to provide deeper insight into the underlying mechanisms of disease. The use of in vitro models with human cellular context is highly recommended and, in this sense, induced pluripotent stem cells (iPSCs) have certain advantages since they provide the genetic background of the patient and represent an unlimited source of biological material for the study of pathophysiology and treatment effectiveness [10]. We have previously generated an iPSC line from a PA patient with defects in the PCCA gene that showed full pluripotency, differentiation capacity and genetic stability [11]. > In the present study, we aimed to establish a platform that served as a disease model to study the cellular and molecular alterations operating in cardiac tissue affected by PA disease. We described the characterization of cardiomyocytes derived from the PCCA iPSC line (PCCA iPSC-CMs) and the analysis of specific pathways potentially involved in cardiac PA physiopathology.

[9] 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: 0.400) > 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.

[10] Chemotherapy and Mechanisms of Resistance in Breast Cancer

  • Authors: A. Oliveira, R. E. Santos, F. F. O. Rodrigues
  • Year: 2012
  • Venue: Unknown venue
  • URL: https://www.semanticscholar.org/paper/502a86d8bcd7208be6f539fcceba631f82f25a7d
  • DOI: 10.5772/24629
  • Summary: The addition of adjuvant polychemotherapy in advanced breast cancer showed gain by controlling survival of micrometastases in patients with lymph nodes affected by cancer or not.
  • Evidence snippets:
  • Snippet 1 (score: 0.398) > The main reasons responsible for treatment failure in cancer patients are the mechanisms of drug resistance and emergence of disseminated disease (Terek et al, 2003). We identified two types of resistance most relevant to BC: primary resistance, which corresponds to the clinical situation where the patient showed no response to therapy, and secondary or acquired resistance in which, initially, there is an observed response and a subsequent failure of the treatment regimen (Kroger et al, 1999). Several mechanisms may cause the phenotype of multidrug resistance to chemotherapy drugs and are well characterized in in vitro experiments, including alterations in systemic pharmacology (pharmacokinetics and metabolism), extracellular mechanisms (tumor environment, multicellular drug resistance), and cellular mechanisms (cellular pharmacology, activation and inactivation of drugs, modification of specific targets and regulatory pathways of apoptosis) (Leonessa et al, 2003, Riddick et al, 2005. Identification of factors that affect cell metabolism, which are related to drug resistance, will enable the identification of which patients are at particular risk of treatment failure. Among the biochemical and molecular mechanisms of drug resistance, we stress: changes in the activity of topoisomerase II, alterations in the DNA repair mechanism, overexpression of P-glycoprotein; high intracellular concentrations of enzymes purification of cellular metabolism -among them enzymes the family of glutathione S-transferases (GSTs) and changes in the mechanisms of signaling via c-Jun N-terminal kinase 1 (JNK1) -and "apoptosis signal-regulating kinase (ASK1) required for activation of the" mitogenactivated protein (MAP kinases) in apoptosis and cellular restoration. These pathways are also mediated by proteins encoded by genes of GSTs (O'Brien, Tew, 1996;Burg, Mulder, 2002, L'Ecuyer et al, 2004). Different response rates to particular chemotherapy regimens, as observed in patient groups with the same biological characteristics and stage, suggest the existence of different mechanisms of drug resistance, probably induced by genetic alterations (Hayes, Pulford, 1995;O'Brien , Tew, 1996;Pakunlu et al, 2003). Among the mechanisms of purification of cellular metabolism involved in the

[11] A Lifelike guided journey through the pathophysiology of pulmonary hypertension—from measured metabolites to the mechanism of action of drugs

  • Authors: Nathan Weinstein, Jørn Carlsen, S. Schulz, T. Stapleton, Hanne H. Henriksen et al.
  • Year: 2023
  • Venue: Frontiers in Cardiovascular Medicine
  • URL: https://www.semanticscholar.org/paper/0b2dc837dea11add7e2f67f06acf6280ac96a019
  • DOI: 10.1101/2023.11.21.23298782
  • PMID: 38845688
  • PMCID: 11153715
  • Citations: 4
  • Summary: The present study shows the power of mining knowledge graphs using Lifelike's diverse set of data analytics functionalities for developing knowledge-driven hypotheses on PH pathophysiological and drug mechanisms and their interactions.
  • Evidence snippets:
  • Snippet 1 (score: 0.396) > Pulmonary hypertension (PH) is a pathological condition that affects approximately 1% of the population. The prognosis for many patients is poor, even after treatment. Our knowledge about the pathophysiological mechanisms that cause or are involved in the progression of PH is incomplete. Additionally, the mechanism of action of many drugs used to treat pulmonary hypertension, including sotatercept, requires elucidation. Using our graph-powered knowledge mining software Lifelike in combination with a very small patient metabolite data set, we demonstrate how we derive detailed mechanistic hypotheses on the mechanisms of PH pathophysiology and clinical drugs. In PH patients, the concentration of hypoxanthine, 12(S)-HETE, glutamic acid, and sphingosine 1 phosphate is significantly higher, while the concentration of L-arginine and L-histidine is lower than in healthy controls. Using the graph-based data analysis, gene ontology, and semantic association capabilities of Lifelike, led us to connect the differentially expressed metabolites with G-protein signaling and SRC. Then, we associated SRC with IL6 signaling. Subsequently, we found associations that connect SRC, and IL6 to Activin and BMP signaling. Lastly, we analyzed the mechanisms of action of several existing and novel pharmacological treatments for PH. Lifelike elucidated the interplay between G-protein, interleukin 6, activin, and BMP signaling. Those pathways regulate hallmark pathophysiological processes of PH, including vasoconstriction, endothelial barrier function, cell proliferation, and apoptosis. The results highlight the importance of SRC, ERK1, AKT, and MLC activity in PH. The molecular pathways affected by existing and novel treatments for PH also converge on these molecules. Importantly, sotatercept affects SRC, ERK1, AKT, and MLC simultaneously. The present study shows the power of mining knowledge graphs using Lifelike's diverse set of data analytics functionalities for developing knowledge-driven hypotheses on PH pathophysiological and drug mechanisms and their interactions. We believe that Lifelike and our presented approach will be valuable for future mechanistic studies

[12] 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.

[13] Landscape of Molecular Crosstalk Perturbation between Lung Cancer and COVID-19

  • Authors: Aditi Kuchi, Jiande Wu, J. Fuloria, C. Hicks
  • Year: 2022
  • Venue: International Journal of Environmental Research and Public Health
  • URL: https://www.semanticscholar.org/paper/9094685853a78a21c392c5aed65c33e8896a6671
  • DOI: 10.3390/ijerph19063454
  • PMID: 35329141
  • PMCID: 8953719
  • Citations: 5
  • Summary: A signature of genes associated with both diseases and signatures of genes uniquely associated with each disease are revealed, confirming crosstalk in molecular perturbation between COVID-19 and lung cancer.
  • Evidence snippets:
  • Snippet 1 (score: 0.394) > Some of the major challenges in clinical management of COVID-19 include extrapulmonary manifestations of the disease and its effects on multiple organs, including the lungs [40][41][42]. Extrapulmonary manifestations include thrombotic complications, myocardial dysfunction and arrhythmia, acute coronary disease syndromes, acute kidney injury, gastrointestinal symptoms, hepatocellular injury, hyperglycemia and ketosis, neurologic illnesses, ocular symptoms and dermatologic complications [40][41][42][43]. Although we did not investigate the association of the discovered genes with extrapulmonary manifestations in COVID-19, the discovery of genes with multiple overlapping functions involved in many biological processes suggests that some of the identified genes and gene regulatory networks may be involved in extrapulmonary activities. Moreover, the lung as an organ is likely to function in unison with other organs. Under such conditions, the effects of COVID-19 on the lungs have potential to trigger a cascade of events likely to affect other organs and lead to extrapulmonary manifestations. Indeed, lungs as organs contain many cells that can play many different roles. Although we did not examine individual lung cells, previous studies have shown that transcription profiling could reveal novel mechanisms of SARS-CoV-2 infection in human lung cells [44,45]. > Another finding of significance in this investigation was the discovery of gene regulatory networks and signaling pathways associated with both diseases. This suggests that the host-pathogen interactions linking the two diseases are complex. The novel as-pect and clinical significance of this finding is that it could increase our understanding of host-pathogen interactions, a critical step in vaccine and drug development [46]. For example, the discovery of the coronavirus pathogenesis signaling pathway in this study has the promise to increase our understanding of the pathogenesis of COVID-19 and the molecular mechanisms driving the disease. Although signatures of genes associated with COVID-19 have been reported [17,21], molecular crosstalk perturbation between COVID-19 and lung cancer has not been reported.

[14] Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments

  • Authors: C. Çubuk, F. Can, M. Peña-Chilet, J. Dopazo
  • Year: 2020
  • Venue: Cells
  • URL: https://www.semanticscholar.org/paper/e40f7a3b8f72ba01374ba00fbf308a47a3fa5dd4
  • DOI: 10.3390/cells9071579
  • PMID: 32610626
  • PMCID: 7408716
  • Citations: 9
  • Summary: Despite the existence of differences in gene expression across numerous genes between males and females having been known for a long time, these have been mostly ignored in many studies, including drug development and its therapeutic use. In fact, the consequences of such differences over the disease mechanisms or the drug action mechanisms are completely unknown. Here we applied mechanistic mathematical models of signaling activity to reveal the ultimate functional consequences that gender-s...
  • Evidence snippets:
  • Snippet 1 (score: 0.393) > Therefore, a proper interpretation of the effect that differences in gene expression have over phenotypes, such as drug response or disease progression, involves understanding the mechanisms of the disease or the mode of action of drugs, which can be interpreted through mechanistic models of cell signaling [12] or cell metabolism [13]. Mechanistic models have helped to understand the disease mechanisms behind different cancers [14,15], including neuroblastoma [16,17], breast cancer [18], rare diseases [19], complex diseases [20], the mechanisms of action of drugs [21,22], and other biologically interesting scenarios such as the molecular mechanisms that explain how stress-induced activation of brown adipose tissue prevents obesity [23] or the molecular mechanisms of death and the post-mortem ischemia of a tissue [24]. Among the few available proposals of mechanistic modeling algorithms that model different aspects of signaling pathway activity, Hipathia has demonstrated having superior sensitivity and specificity [12]. > Here, we propose the use of mechanistic models [13,14] of signaling activity related with cancer hallmarks [25], other cancer-related signaling pathways, and some extra relevant cellular functions to understand the functional consequences of the gender bias in gene expression. Such mechanistic models use gene expression data to produce an estimation of profiles of signaling or metabolic circuit activity within pathways [13,14]. An interesting property of mechanistic models is that they can be used not only to understand molecular mechanisms of disease or of drug action but also to predict the potential consequences of gene perturbations over the circuit activity in a given condition [26]. Actually, in a recent work, our group has successfully predicted therapeutic targets in cancer cell lines with a precision over 60% [15]. Therefore, we will use this mechanistic framework to understand what is the molecular basis of the different effects of cancer drugs by directly simulating their effect in the patients. This approach has recently been used by us to understand the generation of resistances in cancer at the single cell level in glioblastoma [27].

[15] 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: 3
  • 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: 0.390) > 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.

[16] 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: 11
  • 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: 0.389) > The metabolome is sensitive to a variety of genetic and environmental stimuli and susceptible to genetic, environmental, and gut microbiome pressures, so subtle differences between individuals can lead to large perturbations in metabolite concentrations and fluxes (15, 24). At present, cystatin C has become an ideal endogenous marker for evaluating glomerular filtration function because it is not affected by sex, age or muscle mass (25). In addition, more and more evidence shows that serum CysC is involved in the pathological process of vascular remodeling and neovascularization, which is closely related to the occurrence and development of diabetic microangiopathy (26). > Eighty-four papers were included in this review and obtained through database searches, namely, PubMed, Cochrane Library, China national knowledge internet(CNKI), General Purpose, and VIP Database. The keywords for the searches were "metabolomics" and "type 2 diabetes mellitus" and its complications. The papers were incorporated by reading and summarizing the literature according to the classification standards (27). The profound analysis of clinical differential metabolites identified in type 2 diabetes and its complications were conducted concerning composition, frequency of category, sample type, and pathways to explore the pathological mechanism of type 2 diabetes and its complications to provide a systematic basis for clinical diagnosis, risk stratification, comprehending disease progression, prognosis assessment, and drug efficacy. Our goal is to apply metabolomics to clinical diagnostic biomarkers, metabolic mechanisms, and prognostic observations, and early diagnosis can be made through metabolites to avoid progression to more serious complications.

[17] Cardiac Complications of Propionic and Other Inherited Organic Acidemias

  • Authors: K. Park, S. Krywawych, E. Richard, L. Desviat, P. Swietach
  • Year: 2020
  • Venue: Frontiers in Cardiovascular Medicine
  • URL: https://www.semanticscholar.org/paper/d664071d94a7f662bd46cbe005f6ef5b743fbffc
  • DOI: 10.3389/fcvm.2020.617451
  • PMID: 33415129
  • PMCID: 7782273
  • Citations: 34
  • Summary: This Review provides a comprehensive historical overview of all known organic acidemias that feature cardiac complications and a state-of-the-art overview of the cardiac sequelae observed in propionic acidemia.
  • Evidence snippets:
  • Snippet 1 (score: 0.386) > Regardless of which mutation is involved, the ensuing defect in PCC results in the accumulation of propionate and a myriad of its metabolites, including propionyl-CoA, propionyl-carnitine, 3-hydroxypropionate and 2-methylcitrate. It is clear that the accumulation of these substances is what is central to the pathophysiology of PA, for several reasons: (1) PA patients develop normally in utero, despite raised concentrations of propionate metabolites (e.g., propionic acid, 2-methylcitrate), and only develop symptoms following birth, as it is assumed that propionic acid crossing into the maternal circulation will be cleared by maternal hepatic PCC (121); (2) management of PA is centered around reducing the propionate-load, through dietary interventions and suppression of the gut flora; (3) although LT has largely shown success in managing PA as a "clinical syndrome, " propionate metabolites remain elevated post-transplant and recurrence of cardiomyopathy has been reported (see preceding Section); (4) despite being closely related biochemically, cardiac complications are far more common in PA compared to MMA, where there is less accumulation of propionate metabolites. Therefore, the question remains, which of these propionate metabolites are involved in the pathological remodeling of the heart, and why does it happen? > Insights Into the Mechanisms Underlying Cardiac Dysfunction in PA From Experimental Animal Models PA is a complex, heterogeneous disease, affecting multiple organ systems and cellular pathways. It is therefore unlikely that a single mechanism is responsible for driving the heart disease in these patients (Figure 3). Whereas, the cardiomyopathy seems to appear mainly during childhood (mean onset age 7 years) (105), the long QT syndrome observed in PA has been shown to be progressive with age. The available evidence suggests that the DCM and prolonged QT are a secondary consequence of PCC dysfunction. > Here, we review the pathogenic mechanisms proposed to underpin cardiac dysfunction in PA. This knowledge-base has largely been borne from laboratory studies, exploiting a variety of experimental models.

[18] 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: 0.385) > 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

[19] Transcriptional profiling of Hutchinson-Gilford progeria patients identifies primary target pathways of progerin

  • Authors: Sandra Vidak, Sohyoung Kim, Tom Misteli
  • Year: 2026
  • Venue: Nucleus
  • URL: https://www.semanticscholar.org/paper/4bd99b0875508364d8672b6da5a50d024d485a53
  • DOI: 10.1080/19491034.2025.2611484
  • PMID: 41489464
  • PMCID: 12773485
  • Summary: To probe the clinical relevance of previously implicated cellular pathways and to address the extent of gene expression heterogeneity between patients, transcriptomic analysis of a comprehensive set of HGPS patients finds misexpression of several cellular pathways, including multiple signaling pathways, the UPR and mesodermal cell fate specification.
  • Evidence snippets:
  • Snippet 1 (score: 0.385) > Oxidative stress represents another key pathogenic mechanism in HGPS, as impaired NRF2 activity or increased reactive oxygen species (ROS) levels are sufficient to recapitulate HGPSassociated phenotypes [17,32,60]. Collectively, these findings underscore the multifactorial nature of HGPS pathogenesis, implicating interconnected signaling cascades involved in inflammation, oxidative stress, proteostasis, and vascular remodeling. Reassuringly, our findings indicate that many of the major pathways that have been described to contribute to HGPS phenotypes in mouse and cellular disease models are also misregulated in progeria patients, and targeting these pathways may provide therapeutic avenues to mitigate disease severity and improve outcomes in HGPS. > Although individuals with HGPS typically exhibit a characteristic set of clinical features, such as craniofacial abnormalities, growth retardation, and cardiovascular complications, there is notable variability in the age of onset, severity, and progression of symptoms between patients [7,9]. At the cellular level, HGPS is associated with several hallmark abnormalities, including nuclear envelope defects, decreased expression of several nuclear proteins and epigenetic marks, mitochondrial dysfunction, and increased cellular senescence [1,11,30,31,61]. These cellular phenotypes also exhibit considerable variation between patients, possibly contributing to differences in clinical outcomes. Our results indicate that even though some degree of transcriptional heterogeneity between the individual patients exists, the majority of patients exhibit misregulation of a set of shared pathways, suggesting that these pathways are universal driver mechanisms in HGPS. Further work is needed to understand the molecular and genetic factors that underlie inter-individual variability in disease expression and progression. > A limitation of pathway analysis of HGPS patient samples is to distinguish the pathways which are directly targeted by the disease-causing progerin protein and the emergence of adaptive secondary response pathways during progression of the disease in patients during their lifetime. The same caveat applies to the use of cell-based models used in the study of HGPS disease mechanisms.

[20] 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: 0.384) > : 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.

Notes

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

Source YAML

click to show
name: PHARC syndrome
creation_date: '2026-04-13T04:00:00Z'
updated_date: '2026-04-14T11:20:00Z'
description: >-
  PHARC syndrome is an autosomal recessive neurodegenerative disorder caused by
  biallelic ABHD12 loss of function. The syndrome combines polyneuropathy,
  hearing loss, ataxia, retinitis pigmentosa, and cataract, reflecting
  progressive involvement of peripheral nerves, retina, auditory pathways, and
  cerebellar systems. Current mechanistic models implicate dysregulated
  lysophosphatidylserine metabolism and lipid-driven neuroinflammation.
category: Mendelian
parents:
- hereditary disease
- neurodegenerative disease
disease_term:
  preferred_term: PHARC syndrome
  term:
    id: MONDO:0012984
    label: PHARC syndrome
pathophysiology:
- name: ABHD12 loss of lipid hydrolase activity
  description: >-
    Biallelic ABHD12 deficiency impairs degradation of bioactive lysophosphatidylserine
    and related oxidized phospholipids.
  genes:
  - preferred_term: ABHD12
    term:
      id: hgnc:15868
      label: ABHD12
  cell_types:
  - preferred_term: microglial cell
    term:
      id: CL:0000129
      label: microglial cell
  biological_processes:
  - preferred_term: lipid catabolic process
    modifier: ABNORMAL
    term:
      id: GO:0016042
      label: lipid catabolic process
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene.
    explanation: This directly supports ABHD12 loss as the initiating cause of PHARC syndrome.
  downstream:
  - target: Abnormal lysophosphatidylserine signaling
    description: Lipid substrate accumulation perturbs immune and neural homeostasis.
- name: Abnormal lysophosphatidylserine signaling
  description: >-
    Disordered lysophospholipid handling is thought to drive inflammatory and
    degenerative injury in nervous system tissues.
  cell_types:
  - preferred_term: microglial cell
    term:
      id: CL:0000129
      label: microglial cell
  evidence:
  - reference: PMID:23297193
    reference_title: ABHD12 controls brain lysophosphatidylserine pathways that are deregulated in a murine model of the neurodegenerative disease PHARC.
    supports: SUPPORT
    evidence_source: MODEL_ORGANISM
    snippet: >-
      Taken together, our data provide a molecular model for PHARC, where disruption of ABHD12 causes deregulated LPS metabolism and the accumulation of proinflammatory lipids that promote microglial and neurobehavioral abnormalities.
    explanation: This directly supports dysregulated lysophosphatidylserine metabolism as a downstream consequence of ABHD12 loss in a PHARC model.
  downstream:
  - target: Progressive multisystem neurodegeneration
    description: Retina, cochlea, cerebellum, and peripheral nerves gradually degenerate.
- name: Progressive multisystem neurodegeneration
  description: >-
    Chronic neurodegenerative injury contributes to the characteristic
    combination of neuropathy, ataxia, hearing loss, and retinal degeneration.
  evidence:
  - reference: PMID:23297193
    reference_title: ABHD12 controls brain lysophosphatidylserine pathways that are deregulated in a murine model of the neurodegenerative disease PHARC.
    supports: PARTIAL
    evidence_source: MODEL_ORGANISM
    snippet: >-
      Notably, elevations in brain LPS lipids in ABHD12(-/-) mice occur early in life (2-6 mo) and are followed by age-dependent increases in microglial activation and auditory and motor defects that resemble the behavioral phenotypes of human PHARC patients.
    explanation: This supports age-dependent neurodegenerative progression downstream of ABHD12 loss in a PHARC model, while the full human multisystem trajectory is inferred across clinical domains.
  downstream:
  - target: Peripheral nerve degeneration
    description: Peripheral nerve degeneration contributes to sensory and motor deficits.
  - target: Cerebellar degeneration
    description: Cerebellar dysfunction causes progressive gait and coordination impairment.
  - target: Retinal degeneration
    description: Retinal degeneration leads to night blindness and visual field loss.
- name: Peripheral nerve degeneration
  description: >-
    Progressive peripheral nerve injury contributes to the polyneuropathy
    component of PHARC syndrome.
- name: Cerebellar degeneration
  description: >-
    Progressive cerebellar involvement contributes to gait instability and
    ataxia.
- name: Retinal degeneration
  description: >-
    Retinal and macular degeneration contribute to the retinitis pigmentosa
    phenotype.
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Fundus examination revealed macular involvement in all patients, ranging from alterations of the retinal pigment epithelium to macular atrophy.
    explanation: This directly supports retinal degenerative involvement in PHARC syndrome.
phenotypes:
- name: Peripheral neuropathy
  category: Neurologic
  description: Length-dependent neuropathy is a core and often early manifestation.
  phenotype_term:
    preferred_term: Peripheral neuropathy
    term:
      id: HP:0009830
      label: Peripheral neuropathy
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene.
    explanation: This directly supports peripheral neuropathy as part of the defining PHARC acronym.
- name: Sensorineural hearing impairment
  category: Otolaryngologic
  description: Progressive hearing impairment contributes substantially to disability.
  phenotype_term:
    preferred_term: Sensorineural hearing impairment
    term:
      id: HP:0000407
      label: Sensorineural hearing impairment
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene.
    explanation: This directly supports hearing loss as part of the defining PHARC syndrome phenotype.
- name: Ataxia
  category: Neurologic
  description: Cerebellar involvement causes progressive gait instability and dyscoordination.
  phenotype_term:
    preferred_term: Ataxia
    term:
      id: HP:0001251
      label: Ataxia
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene.
    explanation: This directly supports ataxia as a defining component of PHARC syndrome.
- name: Retinitis pigmentosa
  category: Ophthalmologic
  description: Retinal dystrophy causes night blindness and progressive visual loss.
  phenotype_term:
    preferred_term: Retinitis pigmentosa
    term:
      id: HP:0000510
      label: Rod-cone dystrophy
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Fundus examination revealed macular involvement in all patients, ranging from alterations of the retinal pigment epithelium to macular atrophy.
    explanation: This directly supports retinal degenerative disease within the PHARC phenotype.
- name: Cataract
  category: Ophthalmologic
  description: Lens opacity is part of the canonical PHARC acronym and phenotype.
  phenotype_term:
    preferred_term: Cataract
    term:
      id: HP:0000518
      label: Cataract
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      Different types of cataract were observed in 13 out of 15 patients (87%), which also included congenital forms of cataract.
    explanation: This directly supports cataract as a common PHARC phenotype.
biochemical: []
genetic:
- name: ABHD12
  gene_term:
    preferred_term: ABHD12
    term:
      id: hgnc:15868
      label: ABHD12
  association: Causal biallelic loss-of-function variant
  evidence:
  - reference: PMID:34573385
    reference_title: "The Phenotypic Spectrum of Patients with PHARC Syndrome Due to Variants in ABHD12: An Ophthalmic Perspective."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: >-
      This study investigated the phenotypic spectrum of PHARC (polyneuropathy, hearing loss, ataxia, retinitis pigmentosa and early-onset cataract) syndrome caused by biallelic variants in the ABHD12 gene.
    explanation: This directly supports ABHD12 as the causal gene in PHARC syndrome.
environmental: []
treatments:
- name: Supportive multidisciplinary care
  treatment_term:
    preferred_term: supportive care
    term:
      id: MAXO:0000950
      label: supportive care
  description: >-
    Management is supportive and includes neurologic, low-vision, audiologic,
    and rehabilitation interventions.
  target_phenotypes:
  - preferred_term: Peripheral neuropathy
    term:
      id: HP:0009830
      label: Peripheral neuropathy
  - preferred_term: Ataxia
    term:
      id: HP:0001251
      label: Ataxia
- name: Cataract surgery
  treatment_term:
    preferred_term: surgical procedure
    term:
      id: MAXO:0000004
      label: surgical procedure
  description: >-
    Cataract extraction may improve visual function when lens opacity becomes
    clinically significant.
  target_phenotypes:
  - preferred_term: Cataract
    term:
      id: HP:0000518
      label: Cataract
diagnosis:
- name: ABHD12 genetic testing
  diagnosis_term:
    preferred_term: genetic testing
    term:
      id: MAXO:0000127
      label: genetic testing
  description: >-
    Molecular diagnosis depends on identifying biallelic pathogenic ABHD12 variants.
  results: Biallelic pathogenic ABHD12 variants support the diagnosis of PHARC syndrome.
- name: Ophthalmologic evaluation
  diagnosis_term:
    preferred_term: clinical assessment
    term:
      id: MAXO:0000487
      label: clinical assessment
  description: >-
    Retinal imaging and electrophysiology are used to document rod-cone
    dystrophy and associated cataract.
  results: Rod-cone dystrophy with cataract supports PHARC syndrome.
- name: Audiometric testing
  diagnosis_term:
    preferred_term: audiometric testing
    term:
      id: MAXO:0000125
      label: audiometric testing
  description: >-
    Formal hearing assessment documents the sensorineural hearing-loss
    component of PHARC syndrome.
  results: Sensorineural hearing loss supports PHARC syndrome.
- name: Electromyography and nerve conduction studies
  diagnosis_term:
    preferred_term: electromyography procedure
    term:
      id: MAXO:0035091
      label: electromyography procedure
  description: >-
    Peripheral nerve testing helps define the neuropathic burden and
    multisystem severity of PHARC syndrome.
  results: Peripheral neuropathy supports PHARC syndrome.
differential_diagnoses:
- name: adult Refsum disease
  disease_term:
    preferred_term: adult Refsum disease
    term:
      id: MONDO:0009958
      label: adult Refsum disease
  description: >-
    Refsum disease can overlap with retinitis pigmentosa, neuropathy, and ataxia.
- name: Usher syndrome
  disease_term:
    preferred_term: Usher syndrome
    term:
      id: MONDO:0019501
      label: Usher syndrome
  description: >-
    Usher syndrome overlaps through retinal degeneration and hearing loss but
    lacks the full PHARC neurodegenerative profile.
clinical_trials: []
datasets: []