Asta Literature Retrieval: Pathophysiology and clinical mechanisms of Mowat-Wilson syndrome. Core disease mechanisms, molecular and cellular pat...

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

• Papers retrieved: 20
• Snippets retrieved: 20

Relevant Papers

[1] Mowat-Wilson syndrome: unraveling the complexities of diagnosis, treatment, and symptom management

• Authors: Yalda Zhoulideh, Jamil Joolideh
• Year: 2024
• Venue: Egyptian Journal of Medical Human Genetics
• URL: https://www.semanticscholar.org/paper/909c4ae87c0ea609bf397ee850c448693dfcd8b5
• DOI: 10.1186/s43042-024-00517-2
• Citations: 1
• Summary: This review will examine the gene involved in this disease, phenotype, clinical manifestations, ways of diagnosis, and treatment of this disease.
• Evidence snippets:
• Snippet 1 (score: 0.429) > The altered protein fails to perform its normal regulatory functions in the intricate processes of embryonic development. This disruption has cascading effects on the expression of other genes involved in the development of the nervous system, face, and several internal organs. Individuals with Mowat-Wilson syndrome typically exhibit a distinct set of features, including characteristic facial abnormalities (such as a broad nasal bridge and prominent chin), intellectual disabilities, delayed development, seizures, and congenital heart defects. The severity of symptoms can vary among affected individuals. ZEB2 mutations are mainly of the frameshift type, creating a premature termination codon. The frequency of nonsense mutations is next. Nevertheless, sometimes the whole gene is completely deleted, which causes a very severe phenotype of the disease. On the other hand, the missense mutation causes minor disease severity. Most mutations in this gene affect the nervous system [13][14][15][16][17]. > ZEB2 protein plays a central role in cell function by participating in important pathways, especially the TGF-β/SMAD pathway. Through this interaction, the protein contributes to the regulation of cellular responses and developmental processes. Additionally, an important aspect of ZEB2 protein function is that it may play an important role in the restoration of histone deacetylase in the context of cancer. These features suggest that this protein is involved in epigenetic regulation, influencing gene expression patterns and cell behavior in the biological environment of tumors. Importantly, the relationship between the ZEB2 protein and CtBP further emphasizes its importance. This interaction implies a sophisticated level of coordination in cellular regulatory mechanisms, suggesting that the ZEB2 protein is not merely a passive participant but a key orchestrator in the complex interplay of molecular events governing cellular homeostasis and pathological processes [18,19].

[2] The hyperornithinemia–hyperammonemia-homocitrullinuria syndrome

• Authors: D. Martinelli, D. Diodato, Emanuela Ponzi, M. Monné, S. Boenzi et al.
• Year: 2015
• Venue: Orphanet Journal of Rare Diseases
• URL: https://www.semanticscholar.org/paper/ed033868ee677da141e5c926bc7c93cac242ea06
• DOI: 10.1186/s13023-015-0242-9
• PMID: 25874378
• PMCID: 4358699
• Citations: 92
• Influential citations: 5
• Summary: The clinical phenotype of HHH syndrome is extremely variable and its severity does not correlate with the genotype or with recorded ammonium/ornithine plasma levels, suggesting the need for a better understanding of the still unsolved pathophysiology of the disease.
• Evidence snippets:
• Snippet 1 (score: 0.386) > Although the disease responds well to treatment with low risk of relapse of hyperammonemia [38], slowly progressive pyramidal signs characterize the chronic course, as also seen in argininemia [89]. However, the mechanism(s) of pyramidal dysfunction in HHH syndrome still remains to be elucidated. Creatine deficiency may contribute to the pathogenetic mechanism of the syndrome, as creatine is relevant for mitochondrial energy metabolism, regulation of glycolysis, proteins synthesis, membrane stabilization and neuromodulation [77,78,85]. This could be in line with the finding of abnormally shaped mitochondria at electron microscopy studies in skin fibroblasts, hepatocytes and muscle biopsy from HHH syndrome patients [11,23,82]. Furthermore, a mitochondrial dysfunction has been recently related to the effects of ornithine and homocitrulline in causing oxidative stress and disturbed mitochondrial homeostasis [79,80]. > A further mechanism that can be involved in the pathophysiology of HHH syndrome is related to polyamines metabolism. Shimizu and colleagues reported increased total and fractional (putrescine, cadaverine, spermine, spermidine) polyamines in one HHH syndrome patient [30]. Indeed, the clinical similarities between HHH syndrome and argininemia, which has been associated to an abnormal polyamine metabolism [91,92], may suggest a common pathogenetic mechanism causing pyramidal dysfunction. > Overall, the pathogenesis of HHH syndrome is complex and not completely understood. It is likely that different mechanisms, including the impact of low mitochondrial ornithine on UC flux, the presence of hyperammonemic crises and the disturbance of other pathways in major organs play a role in determining the heterogeneous clinical presentation of ORC1 deficiency. > In addition, as molecular studies failed to disclose a correlation between type of mutations or ornithine transport capacity and disease severity, an effect of genetic modifiers, such as ORC genes redundancy, seems to be likely, but further studies are certainly needed to clarify this point.

[3] 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: 0.386) > 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.

[4] Therapies for Mitochondrial Disease: Past, Present, and Future

• Authors: Megan Ball, Nicole J. Van Bergen, A. Compton, David R Thorburn, S. Rahman et al.
• Year: 2025
• Venue: Journal of Inherited Metabolic Disease
• URL: https://www.semanticscholar.org/paper/196ee50a950f29bc4134cfb8fe6bdfa9a3a1468b
• DOI: 10.1002/jimd.70065
• PMID: 40714961
• PMCID: 12301291
• Citations: 3
• Summary: The latest developments in the pursuit to identify effective treatments for mitochondrial disease are examined and the barriers impeding their success in translation to clinical practice are discussed.
• Evidence snippets:
• Snippet 1 (score: 0.373) > Mitochondrial disease is a diverse group of clinically and genetically complex disorders caused by pathogenic variants in nuclear or mitochondrial DNA‐encoded genes that disrupt mitochondrial energy production or other important mitochondrial pathways. Mitochondrial disease can present with a wide spectrum of clinical features and can often be difficult to recognize. These conditions can be devastating; however, for the majority, there is no targeted treatment. In the last 60 years, mitochondrial medicine has experienced significant evolution, moving from the pre‐molecular era to the Age of Genomics in which considerable gene discovery and advancement in our understanding of the pathophysiology of mitochondrial disease have been made. In the last decade, in response to the urgent need for effective treatments, a wide range of emerging therapies have been developed, driven by innovative approaches addressing both the genetic and cellular mechanisms underpinning the diseases. Emerging therapies include dietary intervention, small molecule therapies aimed to restore mitochondrial function, stem cell or liver transplantation, and gene or RNA‐based therapies. However, despite these advances, translation to clinical practice is complicated by the sheer genetic and clinical complexity of mitochondrial disease, difficulty in efficient and precise delivery of therapies to affected tissues, rarity of individual genetic conditions, lack of reliable biomarkers and clinically relevant outcome measures, and the dearth of natural history data. This review examines the latest developments in the pursuit to identify effective treatments for mitochondrial disease and discusses the barriers impeding their success in translation to clinical practice. While treatment for mitochondrial disease may be on the horizon, many challenges must be addressed before it can become a reality.

[5] From the Matrix to the Nucleus and Back: Mechanobiology in the Light of Health, Pathologies, and Regeneration of Oral Periodontal Tissues

• Authors: M. Dieterle, A. Husari, T. Steinberg, Xiaoling Wang, I. Ramminger et al.
• Year: 2021
• Venue: Biomolecules
• URL: https://www.semanticscholar.org/paper/1f89347b1ccacdd13b2b69e9d3a508850b962353
• DOI: 10.3390/biom11060824
• PMID: 34073044
• PMCID: 8228498
• Citations: 23
• Summary: This review offers insights into the current trends and open aspects of periodontal MT research, and perspectives on future applications of mechanobiological principles are discussed.
• Evidence snippets:
• Snippet 1 (score: 0.373) > Envelopathies additionally include the disease of Lamin-associated proteins, such as Emerin or Nesprin [223]. The most relevant medical syndromes are Charcot-Marie-Tooth neuropathies, Emery-Dreifuss muscular dystrophies, and Hutchinson-Gilford syndrome, which is also known as Progeria [224][225][226]. Mechanically exposed tissues, such as the skeletal muscle, cardiomyocytes and tendons, are often affected by these diseases [26]. > Two different hypotheses in the current literature discuss the reasons of the deleterious effects of the laminopathies. The gene regulation hypothesis claims that the mutations or defects in LINC components or Lamin/Emerin lead to a severe dysregulation of gene expression [227]. Consequently, cellular physiology is dysregulated, impairing, e.g., stem cell differentiation, and thus resulting in the clinical disease manifestations such as premature aging or muscle weakness [228]. Contrary to this, the structural hypothesis states that nuclear deformation and fragility caused by the mutations is the most important step in the disease process. However, a more holistic "MT-hypothesis" of the pathophysiology should actually incorporate both the gene dysregulation and the mechanobiological consequences, as both are highly interdependent [229]. This can be explained by the above-discussed functions of LINC and Lamins. The mutations associated with envelopathies are, therefore, valuable models for elucidating both general and tissue-specific mechanisms of NMT and its integration into the cellular context. One interesting molecular insight is the fact that certain Lamin mutations increase the abundance of phosphorylated Lamin. This subsequently increases the solubility of the protein and promotes its dissociation from the Lamin meshwork and thus creates nuclear fragility [230,231]. Additionally, direct DNA damage and cell-cycle arrest are associated with these mutations [232].

[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: 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: 0.373) > 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] 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: 0.372) > 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.

[8] Psychobiotics at the Frontiers of Neurodegenerative and Neuropsychiatric Research

• Authors: Guillermo Roberto Jiménez-Pareyón, J. Cristóbal-Luna, Y. García-Martínez, Cynthia Garfias-Noguez, Morayma Ramírez-Damián et al.
• Year: 2025
• Venue: Microorganisms
• URL: https://www.semanticscholar.org/paper/6c92b8101905064ff4e4e8585f4fa86ebfac0826
• DOI: 10.3390/microorganisms13122718
• PMID: 41471921
• PMCID: 12735313
• Summary: A review of current evidence on the GBA’s involvement in conditions such as Alzheimer’s disease, Parkinson’s disease, depression, and anxiety examines how psychobiotics may modulate neuroinflammation, oxidative stress, and neurotransmitter signaling, thereby contributing to cognitive and emotional regulation.
• Evidence snippets:
• Snippet 1 (score: 0.370) > Neurodegenerative diseases (NDs) are a group of disorders characterized by the progressive deterioration of the central or peripheral nervous system. These diseases cause morphological changes in the brain, leading to significant cognitive or motor impairments, debilitating symptoms, and a reduced quality of life [16]. NDs involve complex cellular responses triggered by the accumulation of pathologically altered brain substances, ultimately resulting in irreversible loss of neuronal populations [17]. > The pathophysiology of NDs is multifactorial and intricate, involving cellular, molecular, and genetic mechanisms. These include protein misfolding and aggregation, oxidative stress, mitochondrial dysfunction, cytoskeletal abnormalities, disrupted synaptic networks, neuronal death, aberrant cell proliferation, neuroinflammation, demyelination, altered axonal transport, dysregulated energy metabolism, and abnormal modifications of DNA or RNA [16,[18][19][20][21][22]. > NDs can be classified according to several criteria, such as their etiology, the molecular mechanisms involved, and the anatomical regions affected [23]. Although multiple classification systems exist, these disorders often share overlapping cellular and molecular mechanisms [24], which complicates efforts to categorize them into a single scheme. From a mechanistic perspective, NDs commonly exhibit recurring pathological events such as neuroinflammation, oxidative stress, mitochondrial dysfunction, and the accumulation of misfolded proteins [16]. Recent classification systems increasingly emphasize the type of protein aggregates for diagnostic accuracy [25]. Clinically, NDs can also be classified clinically based on predominant symptoms, such as movement disorders in PD and Huntington's disease, cognitive deficits in AD, or a combination of both [12,26,27]. This approach allows for a better understanding of their heterogeneity and facilitates the development of more specific therapeutic strategies. Among the spectrum of neurodegenerative conditions, AD and PD are the most prevalent and extensively studied (Figure 1).

[9] 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: 0.368) > 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.

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

• Authors: E. Barton, C. A. Pacak, Whitney L. Stoppel, P. Kang
• Year: 2020
• Venue: Skeletal Muscle
• URL: https://www.semanticscholar.org/paper/653422e1a9dc9cc7f16758b10f3f203155bc68c9
• DOI: 10.1186/s13395-020-00240-7
• PMID: 32727611
• PMCID: 7389686
• Citations: 24
• Summary: A deeper understanding of these disease pathways could yield a new generation of precision therapies that would each be expected to treat a broader range of LGMD patients than a single subtype, thus expanding the scope of the molecular medicines that may be developed for this complex array of muscular dystrophies.
• Evidence snippets:
• Snippet 1 (score: 0.366) > Pyridine nucleotide-disulfide reductase [55] Many of the protein functions listed require further confirmation or are disputed these methodologies. Those patients with moderate disease phenotypes regardless of the underlying causative gene mutation would likely fall into a category where there may be interest in testing a pharmacological treatment (that could be halted) but reduced interest in a more permanent experimental strategy. For all of the above-mentioned reasons, the identification of unifying therapeutic targets applicable to multiple subtypes of > LGMDs is highly desirable. > To identify such targets, we should first consider the question: What binds all of these LGMDs together? The two core phenotypic features are progressive proximal muscle weakness, along with characteristic signs of muscle fiber destruction on biopsy, referred to as "dystrophic" features. Nuances in clinical presentation have helped to distinguish some of the LGMDs, such as the frequent occurrence of difficulty walking on tiptoes in LGMD R2 (LGMD2B), caused by dysferlin deficiency. However, heterogeneity associated with variable ages of onset and ranges of severity makes it generally difficult to distinguish and diagnose LGMD subtypes based on clinical presentation alone. A change in perspective is in order to aid in understanding disease pathways responsible for clinical features even when the genetic mutation is unknown. Further, given the large number of genespecific LGMD subtypes, it could very well be that several major disease mechanisms may be shared across the family of diseases. Yet despite careful studies that have collectively determined the cellular localization of most proteins associated with LGMD (Fig. 1), there is limited knowledge of potentially unifying molecular disease mechanisms. We assert that the identification of functional clusters of these proteins, grouped by such common mechanisms, will streamline our understanding of the disease processes and identify therapeutic targets relevant to individuals in multiple disease subgroups, including individuals whose pathogenic mutations have not been found. By extension, this approach may serve as a tool to not only find common mechanisms, but may also help to distinguish LGMD subtypes that do not share similar functional patterns, and afford further refinement of potential treatments.

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

• Authors: E. Barton, C. A. Pacak, Whitney L. Stoppel, Peter B. Kang
• Year: 2020
• Venue: Skeletal Muscle
• URL: https://www.semanticscholar.org/paper/3493c658bb8716d789a05ddf292162832e064e47
• DOI: 10.1186/s13395-020-00240-7
• Summary: A deeper understanding of these disease pathways could yield a new generation of precision therapies that would each be expected to treat a broader range of LGMD patients than a single subtype, thus expanding the scope of the molecular medicines that may be developed for this complex array of muscular dystrophies.
• Evidence snippets:
• Snippet 1 (score: 0.366) > Pyridine nucleotide-disulfide reductase [55] Many of the protein functions listed require further confirmation or are disputed these methodologies. Those patients with moderate disease phenotypes regardless of the underlying causative gene mutation would likely fall into a category where there may be interest in testing a pharmacological treatment (that could be halted) but reduced interest in a more permanent experimental strategy. For all of the above-mentioned reasons, the identification of unifying therapeutic targets applicable to multiple subtypes of > LGMDs is highly desirable. > To identify such targets, we should first consider the question: What binds all of these LGMDs together? The two core phenotypic features are progressive proximal muscle weakness, along with characteristic signs of muscle fiber destruction on biopsy, referred to as "dystrophic" features. Nuances in clinical presentation have helped to distinguish some of the LGMDs, such as the frequent occurrence of difficulty walking on tiptoes in LGMD R2 (LGMD2B), caused by dysferlin deficiency. However, heterogeneity associated with variable ages of onset and ranges of severity makes it generally difficult to distinguish and diagnose LGMD subtypes based on clinical presentation alone. A change in perspective is in order to aid in understanding disease pathways responsible for clinical features even when the genetic mutation is unknown. Further, given the large number of genespecific LGMD subtypes, it could very well be that several major disease mechanisms may be shared across the family of diseases. Yet despite careful studies that have collectively determined the cellular localization of most proteins associated with LGMD (Fig. 1), there is limited knowledge of potentially unifying molecular disease mechanisms. We assert that the identification of functional clusters of these proteins, grouped by such common mechanisms, will streamline our understanding of the disease processes and identify therapeutic targets relevant to individuals in multiple disease subgroups, including individuals whose pathogenic mutations have not been found. By extension, this approach may serve as a tool to not only find common mechanisms, but may also help to distinguish LGMD subtypes that do not share similar functional patterns, and afford further refinement of potential treatments.

[12] The Classification of Autosomal Recessive Cerebellar Ataxias: a Consensus Statement from the Society for Research on the Cerebellum and Ataxias Task Force

• Authors: M. Beaudin, A. Matilla-Dueñas, B. Soong, J. Pedroso, O. Barsottini et al.
• Year: 2019
• Venue: Cerebellum (London, England)
• URL: https://www.semanticscholar.org/paper/8be333265c4faffaeb605213aa48cb23b33981c1
• DOI: 10.1007/s12311-019-01052-2
• PMID: 31267374
• PMCID: 6867988
• Citations: 49
• Summary: A consensus is built on the classification of autosomal recessive ataxias in order to develop a general approach to a patient presenting with ataxia, organize disorders according to clinical presentation, and define this field of research by identifying common pathogenic molecular mechanisms in these disorders.
• Evidence snippets:
• Snippet 1 (score: 0.366) > The importance of a proper recessive ataxia classification goes beyond the clinical diagnosis perspective. Autosomal recessive ataxias can be regrouped according to the deficient cellular and metabolic pathways involved, which provide a better understanding of cerebellar physiology and of its selective vulnerability to certain metabolic defects. This is also essential from a therapeutic perspective, as disorders that belong to the same metabolic pathway may to the same treatment options, indicating potential for drug repurposing. Figure 3 presents a pathophysiological classification of autosomal recessive ataxias. Certain genes are presented more than once since some proteins are involved in several metabolic pathways or may interfere with other cellular processes as they accumulate in neurons or glial cells. Table 3 presents a more detailed listing of the pathogenic pathways involved along with relevant references. Certain pathways are predominantly involved, notably mitochondrial dysfunction, which may result from abnormal mitochondrial DNA maintenance with progressive mutagenesis, defective mitochondrial protein synthesis and quality control, increased levels of reactive oxygen species and oxidative stress, deficient coenzyme Q10 metabolism, altered mitochondrial dynamics, defective mitochondrial chain assembly, or abnormal mitochondrial RNA maturation and processing (Table 3). Interestingly, many of the disorders caused by mitochondrial dysfunction also present with a mitochondrial clinical syndrome as shown in Fig. 1. Disorders of DNA repair mechanisms are also common, with double-strand break repair pathway or single-strand break repair complexes predominantly involved. Pathogenic mutations in these genes are also associated with a susceptibility to ionizing radiations and predisposition for cancers, but the neurological syndrome is characterized by cerebellar involvement and extrapyramidal movement disorders. It remains debated whether defective DNA repair is the main pathogenic mechanism causing the neurological phenotype [230], but the fact that several interacting genes in this pathway are involved in degenerative cerebellar ataxias suggests that the cerebellum has a peculiar susceptibility to DNA damage for which the underlying mechanism is not understood. Finally, altered synaptic morphology or synaptic dysfunction of Purkinje cells (PC) is frequently involved in recessive ataxias and is associated with aberrant Fig. 1 Clinical classification of autosomal recessive ataxias.

[13] Deciphering the Basis of Molecular Biology of Selected Cardiovascular Diseases: A View on Network Medicine

• Authors: Noora Alhajri, Mohammad Rustom, Adedayo Adegbile, Weshah Ahmed, Salsabeel Kilidar et al.
• Year: 2022
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/744c5858fb22cea747b94b7511da2f10feb603aa
• DOI: 10.3390/ijms231911421
• PMID: 36232723
• PMCID: 9569471
• Citations: 4
• Summary: The principal molecular and genetic mechanisms of common cardiac pathophysiologies are summarized as well as the existing knowledge on therapeutic strategies to prevent, halt, or reverse these pathologies are discussed.
• Evidence snippets:
• Snippet 1 (score: 0.365) > The modern application of scientific knowledge to understand the mechanism of disease pathophysiology for the delivery of efficient therapeutic interventions has been guided by the "Oslerian Principles of Disease Definition" (Osler, William. The principles and practice of medicine. D. Appleton and Company, 1912). The "Oslerian Principle" defines the disease process by clinical and pathological correlations, and now in the modern era, by the molecular or genetic alterations that contribute to the disease presentation. Inherent to this principle are fundamental concepts that specific key factors function in simple molecular circuits that regulate and control disease pathology, including where interventions can target these molecules to ameliorate disease processes [1]. > Although the Oslerian principle has increased our appreciation and understanding of disease processes at the molecular level, it oversimplifies the underlying basis of certain pathologies and thus limits our full understanding of the complex interaction of multiple factors that contribute to the disease process. Since the advent of molecular biology, it has become increasingly clear that a single gene mutation can result in disease pathogenesis. However, disease manifestations rarely result from an individualized abnormality in an effector; rather they are almost always the net result of interaction between multiple pathways that interact through a complex network composed of numerous molecules and genes [2,3]. > Molecular cardiology is an innovative and rapidly expanding branch of molecular biology that aims to use results from translational cardiovascular research to diagnose, treat, and prevent cardiovascular diseases. This emerging discipline has increased our knowledge and understanding of the molecular mechanisms of various cardiovascular diseases and provided novel diagnostic and therapeutic tools. For instance, molecular and genetic cardiology has increased the awareness of possible mechanisms of inheritance of certain chronic cardiac diseases (e.g., heart failure and congenital heart anomalies) and their links to specific gene mutations [4][5][6]. In this modern era of molecular medicine, we now have a framework of potential interaction between complex pathways and molecules known as the "interactome". The interactome describes the network of interactions between various molecules in the human cells. It consists of nearly 1000 metabolites, 25,000 protein-coding genes, and a significant number of functional RNA molecules, post-translationally modified proteins, and other cellular components, together exceeding 100,000 molecules [7].

[14] 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: 6
• 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: 0.365) > A second limitation in HTA is the fact that currently population (and sometimes stratified) medicine is pursued during clinical Uncertainty not completely addressed in competent authority assessment report 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) [

[15] Towards Mutation-Specific Precision Medicine in Atypical Clinical Phenotypes of Inherited Arrhythmia Syndromes

• Authors: T. Nakajima, S. Tamura, M. Kurabayashi, Y. Kaneko
• Year: 2021
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/3d299f57f344d42eff9d3565d1581dae7fb87a54
• DOI: 10.3390/ijms22083930
• PMID: 33920294
• PMCID: 8069124
• Citations: 6
• Influential citations: 1
• Summary: Since the epileptic phenotype appears to manifest prior to cardiac events in this mutation carrier, identifying KCND3 mutations in patients with epilepsy and providing optimal therapy will help prevent sudden unexpected death in epilepsy.
• Evidence snippets:
• Snippet 1 (score: 0.365) > Recent advances in molecular genetics have identified many causal genes for inherited arrhythmia syndromes (IASs) such as long QT syndrome (LQTS) [1], short QT syndrome (SQTS) [2], Brugada syndrome (BrS) [3,4] and early repolarization (ER) syndrome (ERS) [3,5]. Most causal genes for IASs encode cardiac ion channels or their related proteins. Genotype-phenotype studies and functional analyses of mutant genes, using heterologous expression systems and experimental animal models, have revealed the pathophysiology of IASs and enabled the establishment of causal gene-specific precision medicine [6][7][8]. Furthermore, analyses of patient-specific and/or genome-edited induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have provided further insights into the pathophysiology of IASs and novel promising therapeutic strategies for IASs, although there are still some limitations of using iPSC-CMs, such as immature structure and function and mixed population of atrial, ventricular, and nodal cells, as a standard technology [9]. > The altered function of causal genes that encode cardiac ion channels is caused by multiple mechanisms, including trafficking defects, producing non-functional channels, altered channel gating properties, and a combination thereof. These altered functions of mutant channels underly the clinical phenotypes of IASs [10][11][12]. Particularly, unique electrophysiological properties of mutant channels have been shown to be associated with the atypical clinical phenotypes of IASs [10,13]. Furthermore, the elucidation of the mechanisms underlying the atypical clinical phenotypes of IASs has raised the possibility of mutation-specific precision medicine. > We herein review the current knowledge of genotype-phenotype relationships, underlying molecular and cellular mechanisms, and established pharmacological therapies of IASs, including LQTS, SQTS, and J wave syndrome (BrS and ERS).

[16] 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: 0.364) > 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

[17] From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

• Authors: Arnab Mukherjee, S. Abraham, Akshita Singh, S. Balaji, K. Mukunthan
• Year: 2024
• Venue: Molecular Biotechnology
• URL: https://www.semanticscholar.org/paper/04593d2268ccd7c26b5296d8342b468ca84ae7b1
• DOI: 10.1007/s12033-024-01133-6
• PMID: 38565775
• PMCID: 11928429
• Citations: 69
• Influential citations: 2
• Summary: This review navigates the expansive omics landscape, showcasing tailored assays for each molecular layer through genomes to metabolomes, and aims to illuminate the transformative impact of multi-omics in the big data era, shaping the future of biological research.
• Evidence snippets:
• Snippet 1 (score: 0.363) > Biological processes and molecular functions arise from intricate interactions among thousands of molecules, constituting inherent complexity. Integration of metabolomics data with other omics data holds significant promise for achieving a holistic understanding of disease mechanisms. Metabolomics, which focuses on the comprehensive analysis of small molecule metabolites within biological systems, provides unique insights into the functional status and metabolic phenotypes associated with various physiological and pathological conditions [160,161]. The integration of omics datasets with computational models and network analysis tools elucidates the complex interplay between genes, proteins, metabolites, and cellular processes underlying disease phenotypes. > Despite recent progress in omics technologies, the underlying genetic factors contributing to numerous metabolic phenotypes remain elusive. Metabolite biomarkers can be integrated with genomics and clinical parameters to enhance diagnostic accuracy or refine disease risk prediction models. Metabolites can also serve as intermediate phenotypes for genetic investigations, offering insights into underlying genetic mechanisms [162]. The integration of metabolomics data with either whole-exome sequencing or WGS-data presents a promising systematic strategy for pinpointing disease-causing variants and holds potential utility within the framework of a specific pathway under investigation [163]. Furthermore, at a more intricate biological and analytical level, metabolomics can be combined with various omic platforms, facilitating a comprehensive understanding of complex biological systems and interactions (Fig. 4). > The alterations in metabolite levels, perturbations in metabolic pathways, and the onset of disease states can be elucidated by assessing the epigenetic alterations. This approach offers molecular insights into the intricate interplay among genetic, epigenetic, and metabolic factors during the disease progression. Through the integration of epigenomic Fig. 4 The workflow for integration of metabolomics with other omics for a holistic understanding of disease progression and metabolomic data, the intricate relationships between epigenetic alterations and metabolic pathways in disease pathogenesis can be uncovered. In recent years, metabolomics and epigenomics have experienced notable advancement as prominent molecular and analytical methodologies for biomarker identification [164,165].

[18] Clinical features and genetic analysis of a family with t(5;9) (p15;p24) balanced translocation leading to Cri-du-chat syndrome in offspring

• Authors: Jing Zhao, Ping Chen, Yijia Ren, Shurong Li, Weiyi Zhang et al.
• Year: 2025
• Venue: Frontiers in Genetics
• URL: https://www.semanticscholar.org/paper/5caf88001c66b473b6565f9e75eb6a4f1a8c4a0a
• DOI: 10.3389/fgene.2025.1550937
• PMID: 40406061
• PMCID: 12094932
• Citations: 1
• Summary: This study reports a rare familial balanced translocation pedigree, particularly noting that the offspring can suffer from Cri-du-chat syndrome, which suggests a potential new genetic model for this syndrome.
• Evidence snippets:
• Snippet 1 (score: 0.363) > Using the Metascape database for GO enrichment analysis of the region containing 60 OMIM genes from 5p15.33p14.1 revealed the potential molecular mechanisms of the disease. The results showed that OMIM genes in the 5p15.33p14.1 region are mainly enriched in Na+/Cl-dependent neurotransmitter transporters, cell-cell adhesion mediated by cadherin, nephron epithelium development, and other signaling pathways (Figure 5A). Disease enrichment analysis showed that genes in this region are mainly associated with Cri-du-chat syndrome (Figure 5B) . Cri-du-chat syndrome is closely related to developmental abnormalities, neurological defects, and craniofacial malformations. Enrichment analysis supports the involvement of molecular mechanisms related to Wnt signaling, neurotransmitter transport, ubiquitination pathways, particularly through diseasegene associations from DisGeNET and GO functional enrichment. These results provide clues for revealing the molecular network of the disease and guide future research. > Using the Metascape database, GO enrichment analysis of 45 OMIM genes located in the 9p24.3-p22.3 region was performed. The results showed that OMIM genes in the 9p24.3-p22.3 region are mainly enriched in signaling pathways such as positive regulation of leukocyte activation, response to amine, cell population proliferation, positive regulation of cell development, etc. (Figure 5C). Disease enrichment analysis revealed that genes in this region are mainly associated with Chromosome 9p deletion syndrome (Figure 5D). This study, through multidimensional bioinformatics analysis, not only clarified the core biological functions of genes in the 9p24.3-p22.3 region, but also revealed their potential association mechanisms with major diseases, providing important theoretical basis and directional guidance for subsequent gene function validation, molecular mechanism research, and clinical translation. Balanced translocation carriers have the opportunity to produce phenotypically normal offspring, but they are at a higher risk of recurrent miscarriages and offspring with chromosomal abnormalities.

[19] 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: 105
• Influential citations: 3
• 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: 0.361) > 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.

[20] Cardiac Phenotype and Gene Mutations in RASopathies

• Authors: M. Faienza, G. Meliota, D. Mentino, R. Ficarella, Mattia Gentile et al.
• Year: 2024
• Venue: Genes
• URL: https://www.semanticscholar.org/paper/a4087d3b73d20a6e2f46b7fb87eed4017ec9a9be
• DOI: 10.3390/genes15081015
• PMID: 39202376
• PMCID: 11353738
• Citations: 9
• Influential citations: 1
• Summary: The molecular mechanisms underlying the development of cardiac diseases associated particularly with NS are clarified, and the main morphological and clinical characteristics of the two most frequent cardiac disorders, namely pulmonary valve stenosis (PVS) and HCM are discussed.
• Evidence snippets:
• Snippet 1 (score: 0.361) > Cardiac involvement is a major feature of RASopathies, a group of phenotypically overlapping syndromes caused by germline mutations in genes encoding components of the RAS/MAPK (mitogen-activated protein kinase) signaling pathway. In particular, Noonan syndrome (NS) is associated with a wide spectrum of cardiac pathologies ranging from congenital heart disease (CHD), present in approximately 80% of patients, to hypertrophic cardiomyopathy (HCM), observed in approximately 20% of patients. Genotype–cardiac phenotype correlations are frequently described, and they are useful indicators in predicting the prognosis concerning cardiac disease over the lifetime. The aim of this review is to clarify the molecular mechanisms underlying the development of cardiac diseases associated particularly with NS, and to discuss the main morphological and clinical characteristics of the two most frequent cardiac disorders, namely pulmonary valve stenosis (PVS) and HCM. We will also report the genotype–phenotype correlation and its implications for prognosis and treatment. Knowing the molecular mechanisms responsible for the genotype–phenotype correlation is key to developing possible targeted therapies. We will briefly address the first experiences of targeted HCM treatment using RAS/MAPK pathway inhibitors.

Notes

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

Question: You are an expert researcher providing comprehensive, well-cited information.

Provide detailed information focusing on: 1. Key concepts and definitions with current understanding 2. Recent developments and latest research (prioritize 2023-2024 sources) 3. Current applications and real-world implementations 4. Expert opinions and analysis from authoritative sources 5. Relevant statistics and data from recent studies

Format as a comprehensive research report with proper citations. Include URLs and publication dates where available. Always prioritize recent, authoritative sources and provide specific citations for all major claims.

Disease Characteristics Research Template

Target Disease

• Disease Name: Mowat-Wilson syndrome
• MONDO ID: (if available)
• Category: Mendelian

Research Objectives

Please provide a comprehensive research report on Mowat-Wilson syndrome covering all of the disease characteristics listed below. This report will be used to populate a disease knowledge base entry. Be thorough and cite primary literature (PMID preferred) for all claims.

For each section, suggested databases/resources are listed. These are the first places you should search for information on each topic.

1. Disease Information

Search first: OMIM, Orphanet, ICD-10/ICD-11, MeSH, PubMed

• What is the disease? Provide a concise overview.
• What are the key identifiers? (OMIM, Orphanet, ICD-10/ICD-11, MeSH, Mondo)
• What are the common synonyms and alternative names?
• Is the information derived from individual patients (e.g., EHR) or aggregated disease-level resources?

2. Etiology

• Disease Causal Factors: What are the primary causes? (genetic, environmental, infectious, mechanistic)
• Risk Factors:

  Search first: PubMed, Cochrane Library, UpToDate, clinical guidelines, ClinVar, ClinGen, GWAS Catalog, PheGenI, CTD, CDC, WHO, epidemiological databases

• Genetic risk factors (causal variants, susceptibility loci, modifier genes)
• Environmental risk factors (toxins, lifestyle, occupational exposures, age, sex, family history)
• Protective Factors:

  Search first: PubMed, Cochrane Library, clinical trial databases, GWAS Catalog, gnomAD, WHO, CDC, nutrition databases

• Genetic protective factors (protective variants, modifier alleles)
• Environmental protective factors (diet, lifestyle, exposures that reduce risk)
• Gene-Environment Interactions: How do genetic and environmental factors interact to influence disease?

  Search first: CTD, PubMed, PheGenI, GxE databases

3. Phenotypes

Search first: HPO (Human Phenotype Ontology), OMIM, Orphanet, PubMed, clinicaltrials.gov, MedDRA, SNOMED CT, DECIPHER, LOINC

For each phenotype, provide: - Phenotype type: symptoms, clinical signs, physical manifestations, behavioral changes, or laboratory abnormalities

For symptoms/signs: HPO, OMIM, Orphanet, PubMed For behavioral changes: HPO, DSM, RDoC (Research Domain Criteria), PubMed For laboratory abnormalities: LOINC, SNOMED CT, LabTests Online, PubMed - Phenotype characteristics: Search first: OMIM, Orphanet, HPO, PubMed - Age of symptom onset (neonatal, childhood, adult-onset, late-onset) - Symptom severity (mild, moderate, severe, variable) - Symptom progression (stable, progressive, episodic, fluctuating) - Frequency among affected individuals (percentage or qualitative) - Quality of life impact: Effects on daily functioning and well-being (per-phenotype when possible) Search first: EQ-5D database, SF-36, WHO QOL databases, PubMed - Suggest HPO (Human Phenotype Ontology) terms for each phenotype

4. Genetic/Molecular Information

• Causal Genes: Gene mutations or chromosomal abnormalities responsible for disease (gene symbols, OMIM IDs)

  Search first: OMIM, ClinVar, HGMD, Ensembl, NCBI Gene

• Pathogenic Variants:
• Affected genes (gene symbols, HGNC IDs) > Search first: OMIM, NCBI Gene, Ensembl, HGNC, UniProt, GeneCards
• Variant classification (pathogenic, likely pathogenic, VUS per ACMG/AMP guidelines) > Search first: ClinVar, ClinGen, ACMG/AMP guidelines, VarSome
• Variant type/class (missense, frameshift, nonsense, splice-site, structural)
• Allele frequency in population databases > Search first: gnomAD, 1000 Genomes, ExAC, TOPMed, dbSNP
• Somatic vs germline origin > Search first: COSMIC (somatic), ClinVar, ICGC, TCGA
• Functional consequences (loss of function, gain of function, dominant negative)
• Modifier Genes: Genes that modify disease severity or expression
• Epigenetic Information: DNA methylation, histone modifications, chromatin changes affecting disease

  Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

• Chromosomal Abnormalities: Large-scale genetic changes (aneuploidy, translocations, inversions)

  Search first: DECIPHER, ClinVar, ECARUCA, UCSC Genome Browser

5. Environmental Information

• Environmental Factors: Non-genetic contributing factors (toxins, radiation, pollution, occupational exposure)

  Search first: CTD (Comparative Toxicogenomics Database), TOXNET, PubMed, EPA databases

• Lifestyle Factors: Behavioral factors (smoking, diet, exercise, alcohol consumption)

  Search first: CDC databases, WHO, PubMed, NHANES

• Infectious Agents: If applicable, pathogens causing or triggering disease (bacteria, viruses, fungi, parasites)

  Search first: NCBI Taxonomy, ViPR, BV-BRC, MicrobeDB, GIDEON

6. Mechanism / Pathophysiology

• Molecular Pathways: Specific signaling cascades or biochemical pathways involved (Wnt, MAPK, mTOR, PI3K-AKT, etc.)

  Search first: KEGG, Reactome, WikiPathways, PathBank, BioCyc

• Cellular Processes: Cell-level mechanisms (apoptosis, autophagy, cell cycle dysregulation, inflammation, etc.)

  Search first: Gene Ontology (GO), Reactome, KEGG, PubMed

• Protein Dysfunction: How protein structure or function is altered (misfolding, aggregation, loss of function, gain of function)

  Search first: UniProt, PDB (Protein Data Bank), InterPro, Pfam, AlphaFold

• Metabolic Changes: Alterations in metabolic processes (energy metabolism, lipid metabolism, amino acid metabolism)

  Search first: KEGG, BioCyc, HMDB (Human Metabolome Database), BRENDA

• Immune System Involvement: Role of immune response (autoimmunity, immunodeficiency, chronic inflammation)

  Search first: ImmPort, Immunome Database, IEDB, Gene Ontology

• Tissue Damage Mechanisms: How tissues/ are injured (oxidative stress, ischemia, fibrosis, necrosis)

  Search first: PubMed, Gene Ontology, Reactome

• Biochemical Abnormalities: Specific molecular defects (enzyme deficiencies, receptor dysfunction, ion channel defects)

  Search first: BRENDA, UniProt, KEGG, OMIM, PubMed

• Epigenetic Changes: DNA methylation, histone modifications affecting gene expression in disease

  Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

• Molecular Profiling (if available):
• Transcriptomics/gene expression changes > Search first: GEO (Gene Expression Omnibus), ArrayExpress, GTEx, Human Cell Atlas, SRA
• Proteomics findings > Search first: PRIDE, ProteomeXchange, Human Protein Atlas, STRING, BioGRID
• Metabolomics signatures > Search first: MetaboLights, Metabolomics Workbench, HMDB, METLIN
• Lipidomics alterations > Search first: LIPID MAPS, SwissLipids, LipidHome, Metabolomics Workbench
• Genomic structural features > Search first: UCSC Genome Browser, Ensembl, NCBI, dbVar, DGV
• Advanced Technologies (if applicable):
• Single-cell analysis findings (cell-type specific mechanisms, cellular heterogeneity) > Search first: Human Cell Atlas, Single Cell Portal, GEO, CELLxGENE
• Spatial transcriptomics findings > Search first: GEO, Spatial Research, Vizgen, 10x Genomics data
• Multi-omics integration results > Search first: TCGA, ICGC, cBioPortal, LinkedOmics, PubMed
• Functional genomics screens (CRISPR, RNAi) > Search first: DepMap, GenomeRNAi, PubMed, BioGRID ORCS

For each mechanism, describe: - The causal chain from initial trigger to clinical manifestation - Which mechanisms are upstream vs downstream - What cell types and biological processes are involved - Suggest GO terms for biological processes and CL terms for cell types

7. Anatomical Structures Affected

• Organ Level:
• Primary organs directly affected
• Secondary organ involvement (complications, secondary effects)
• Body systems involved (cardiovascular, nervous, digestive, respiratory, endocrine, etc.)

  Search first: Uberon, FMA (Foundational Model of Anatomy), OMIM, HPO, ICD-11, MeSH, SNOMED CT

• Tissue and Cell Level:
• Specific tissue types affected (epithelial, connective, muscle, nervous)
• Specific cell populations targeted (with Cell Ontology terms)

  Search first: Uberon, Human Protein Atlas, Cell Ontology, Human Cell Atlas, CellMarker, PanglaoDB

• Subcellular Level:
• Cellular compartments involved (mitochondria, nucleus, ER, lysosomes) (with GO Cellular Component terms)

  Search first: Gene Ontology (Cellular Component), UniProt, Human Protein Atlas

• Localization:
• Specific anatomical sites (with UBERON terms) > Search first: FMA, Uberon, NeuroNames (for brain), SNOMED CT
• Lateralization (unilateral, bilateral, asymmetric) > Search first: HPO, clinical literature, imaging databases

8. Temporal Development

• Onset:
• Typical age of onset (congenital, pediatric, adult, geriatric)
• Onset pattern (acute, subacute, chronic, insidious)

  Search first: OMIM, Orphanet, HPO, PubMed

• Progression:
• Disease stages (early, intermediate, advanced, end-stage) > Search first: Cancer Staging Manual (AJCC), WHO classifications, PubMed
• Progression rate (rapid, slow, variable)
• Disease course pattern (episodic, relapsing-remitting, progressive, stable)
• Disease duration (self-limited, chronic lifelong)

  Search first: Disease registries, longitudinal cohort databases, natural history studies, PubMed, Orphanet, OMIM

• Patterns:
• Remission patterns (spontaneous, treatment-induced) > Search first: Clinical trial databases, disease registries, PubMed
• Critical periods (time windows of vulnerability or opportunity for intervention) > Search first: PubMed, developmental biology databases, clinical guidelines

9. Inheritance and Population

• Epidemiology:
• Prevalence (cases per 100,000 at given time)
• Incidence (new cases per 100,000 per year)

  Search first: Orphanet, CDC, WHO, GBD (Global Burden of Disease), national registries, SEER, disease registries

• For Genetic Etiology:
• Inheritance pattern (AD, AR, X-linked, mitochondrial, multifactorial, polygenic) > Search first: OMIM, Orphanet, ClinVar, GTR (Genetic Testing Registry)
• Penetrance (complete, incomplete, age-dependent) > Search first: ClinVar, OMIM, PubMed, ClinGen
• Expressivity (variable, consistent) > Search first: OMIM, ClinVar, PubMed
• Genetic anticipation (increasing severity in successive generations) > Search first: OMIM, PubMed (especially for repeat expansion disorders)
• Germline mosaicism > Search first: ClinVar, OMIM, genetic counseling literature, PubMed
• Founder effects (population-specific mutations) > Search first: gnomAD, population genetics databases, PubMed
• Consanguinity role > Search first: OMIM, population studies, genetic counseling resources
• Carrier frequency > Search first: gnomAD, carrier screening databases, GeneReviews, GTR
• Population Demographics:
• Affected populations (ethnic or demographic groups with higher prevalence) > Search first: gnomAD, 1000 Genomes, PAGE Study, PubMed, population registries
• Geographic distribution (endemic areas, regional variation) > Search first: WHO, CDC, GBD, Orphanet, geographic epidemiology databases
• Geographic distribution of specific variants
• Sex ratio (male:female) > Search first: Disease registries, OMIM, PubMed, epidemiological databases
• Age distribution of affected individuals > Search first: CDC, disease registries, SEER, Orphanet

10. Diagnostics

• Clinical Tests:
• Laboratory tests (blood, urine, tissue chemistry, specific enzyme assays) > Search first: LOINC, LabTests Online, PubMed
• Biomarkers (proteins, metabolites, genetic markers, circulating biomarkers) > Search first: FDA Biomarker List, BEST (Biomarkers, EndpointS, and other Tools), PubMed
• Imaging studies (X-ray, CT, MRI, PET, ultrasound) > Search first: RadLex, DICOM, Radiopaedia, imaging databases
• Functional tests (pulmonary function, cardiac stress tests) > Search first: LOINC, clinical guidelines, PubMed
• Electrophysiology (EEG, EMG, ECG, nerve conduction studies) > Search first: LOINC, clinical neurophysiology databases, PubMed
• Biopsy findings (histopathology, immunohistochemistry) > Search first: SNOMED CT, College of American Pathologists resources, PubMed
• Pathology findings (microscopic examination) > Search first: SNOMED CT, Digital Pathology databases, PubMed
• Genetic Testing:

  Search first: GTR (Genetic Testing Registry), GeneReviews, ClinGen

• Overview of recommended genetic testing approach
• Whole genome sequencing (WGS) utility > Search first: GTR, ClinVar, GEL (Genomics England), gnomAD
• Whole exome sequencing (WES) utility > Search first: GTR, ClinVar, OMIM, GeneMatcher
• Gene panels (which panels, which genes) > Search first: GTR, ClinVar, laboratory-specific databases
• Single gene testing > Search first: GTR, ClinVar, OMIM, GeneReviews
• Chromosomal microarray (CMA) > Search first: DECIPHER, ClinVar, dbVar, ECARUCA
• Karyotyping > Search first: Chromosome Abnormality Database, ClinVar, cytogenetics resources
• FISH > Search first: ClinVar, cytogenetics databases, PubMed
• Mitochondrial DNA testing > Search first: MITOMAP, MSeqDR, ClinVar, GTR
• Repeat expansion testing > Search first: GTR, ClinVar, repeat expansion databases, PubMed
• Omics-Based Diagnostics (if applicable):
• RNA sequencing / transcriptomics > Search first: GEO, ArrayExpress, GTEx, RNA-seq databases
• Proteomics > Search first: PRIDE, ProteomeXchange, FDA Biomarker database
• Metabolomics > Search first: MetaboLights, Metabolomics Workbench, HMDB
• Epigenomics > Search first: GEO, ENCODE, Roadmap Epigenomics, MethBase
• Liquid biopsy > Search first: COSMIC, ClinVar, liquid biopsy databases, PubMed
• Clinical Criteria:
• Standardized diagnostic criteria (DSM, ICD, society guidelines) > Search first: DSM-5, ICD-11, clinical society guidelines, UpToDate
• Differential diagnosis (other conditions to rule out, with distinguishing features) > Search first: DynaMed, UpToDate, clinical decision support systems
• Screening:
• Screening methods for asymptomatic individuals (newborn screening, carrier screening, cascade screening) > Search first: ACMG recommendations, CDC newborn screening, GTR

11. Outcome/Prognosis

• Survival and Mortality:
• Survival rate (5-year, 10-year, overall) > Search first: SEER, cancer registries, disease-specific registries, PubMed
• Life expectancy (with and without treatment if applicable) > Search first: Orphanet, disease registries, actuarial databases, PubMed
• Mortality rate > Search first: CDC, WHO, GBD, national mortality databases
• Disease-specific mortality (deaths directly attributable to disease) > Search first: Disease registries, CDC Wonder, GBD, PubMed
• Morbidity and Function:
• Morbidity (disease-related disability and health impacts) > Search first: GBD, WHO, disability databases, PubMed
• Disability outcomes (long-term functional impairments) > Search first: ICF (International Classification of Functioning), disability registries
• Quality of life measures (EQ-5D, SF-36, PROMIS, disease-specific tools) > Search first: EQ-5D database, SF-36, PROMIS, PubMed
• Disease Course:
• Complications (secondary problems: infections, organ failure, etc.) > Search first: ICD codes, disease registries, clinical databases, PubMed
• Recovery potential (likelihood and extent of recovery, with vs without treatment) > Search first: Natural history studies, rehabilitation databases, PubMed
• Prediction:
• Prognostic factors (age, disease severity, biomarkers, treatment response) > Search first: Prognostic models databases, clinical calculators, PubMed
• Prognostic biomarkers (molecular markers predicting disease course) > Search first: FDA Biomarker database, PubMed, cancer prognostic databases

12. Treatment

• Pharmacotherapy:
• Pharmacological treatments (drug names, drug classes, mechanisms of action) > Search first: DrugBank, RxNorm, ATC classification, DailyMed, FDA databases
• Pharmacogenomics (how genetic variants affect drug metabolism, efficacy, toxicity) > Search first: PharmGKB, CPIC (Clinical Pharmacogenetics), FDA Table of PGx Biomarkers
• Advanced Therapeutics:
• Gene therapy (viral vectors, CRISPR, gene replacement, gene editing) > Search first: ClinicalTrials.gov, FDA gene therapy database, ASGCT resources
• Cell therapy (stem cell transplant, CAR-T, cellular therapeutics) > Search first: ClinicalTrials.gov, FDA cell therapy database, FACT standards
• RNA-based therapies (ASOs, siRNA, mRNA therapies) > Search first: ClinicalTrials.gov, FDA approvals, PubMed
• Targeted therapies (treatments directed at specific molecular targets) > Search first: My Cancer Genome, OncoKB, ClinicalTrials.gov, FDA approvals
• Immunotherapies (checkpoint inhibitors, monoclonal antibodies) > Search first: Cancer Immunotherapy Database, FDA approvals, ClinicalTrials.gov
• Surgical and Interventional:
• Surgical interventions (types of surgery, timing, outcomes) > Search first: CPT codes, surgical registries, clinical guidelines, PubMed
• Supportive and Rehabilitative:
• Supportive care (symptom management, pain control, nutrition) > Search first: Clinical guidelines, Cochrane Library, PubMed
• Rehabilitation (physical therapy, occupational therapy, speech therapy) > Search first: Rehabilitation medicine databases, clinical guidelines, PubMed
• Experimental:
• Experimental treatments in clinical trials (with NCT identifiers if available) > Search first: ClinicalTrials.gov, EU Clinical Trials Register, WHO ICTRP
• Treatment Outcomes:
• Treatment response rates > Search first: Clinical trial databases, FDA reviews, systematic reviews, PubMed
• Side effects and adverse events > Search first: FDA Adverse Event Reporting System (FAERS), MedWatch, PubMed
• Treatment Strategy:
• Treatment algorithms (clinical pathways, decision trees) > Search first: Clinical practice guidelines, NCCN Guidelines, UpToDate
• Combination therapies > Search first: ClinicalTrials.gov, treatment guidelines, PubMed
• Personalized medicine approaches (genotype-guided treatment) > Search first: My Cancer Genome, CIViC, PharmGKB, precision medicine databases

For each treatment, suggest MAXO (Medical Action Ontology) terms where applicable.

13. Prevention

• Prevention Levels:
• Primary prevention (preventing disease occurrence: vaccination, risk factor modification) > Search first: CDC, WHO, USPSTF recommendations, Cochrane Library
• Secondary prevention (early detection and treatment: screening programs, early intervention) > Search first: USPSTF, CDC screening guidelines, WHO
• Tertiary prevention (preventing complications in those with disease) > Search first: Clinical guidelines, disease management protocols, PubMed
• Immunization: Vaccine strategies (if applicable)

  Search first: CDC vaccine schedules, WHO immunization, FDA vaccine database

• Screening and Early Detection:
• Screening programs (population-based: newborn screening, cancer screening) > Search first: CDC screening programs, USPSTF, cancer screening databases
• Genetic screening (carrier screening, preimplantation genetic diagnosis, prenatal testing) > Search first: ACMG recommendations, ACOG guidelines, GTR
• Risk stratification (identifying high-risk individuals for targeted prevention) > Search first: Risk prediction models, clinical calculators, PubMed
• Behavioral Interventions: Lifestyle modifications to reduce risk

  Search first: CDC, WHO, behavioral intervention databases, Cochrane Library

• Counseling: Genetic counseling (risk assessment, family planning guidance)

  Search first: NSGC resources, ACMG guidelines, GeneReviews

• Public Health:
• Public health interventions (sanitation, vector control, health education) > Search first: CDC, WHO, public health databases, PubMed
• Environmental interventions (reducing environmental risk factors) > Search first: EPA databases, WHO environmental health, PubMed
• Prophylaxis: Preventive medications or procedures

  Search first: Clinical guidelines, FDA approvals, PubMed

14. Other Species / Natural Disease

• Taxonomy: Species affected (with NCBI Taxon identifiers)

  Search first: NCBI Taxonomy

• Breed: Specific breeds affected (with VBO identifiers if applicable)

  Search first: VBO (Vertebrate Breed Ontology)

• Gene: Orthologous genes in other species (with NCBI Gene IDs)

  Search first: NCBI Gene

• Natural Disease:
• Naturally occurring disease in other species (companion animals, wildlife) > Search first: OMIA (Online Mendelian Inheritance in Animals), VetCompass, PubMed
• Veterinary relevance and importance in animal health > Search first: OMIA, veterinary databases, PubMed
• Comparative Biology:
• Comparative pathology (similarities and differences across species) > Search first: OMIA, comparative pathology databases, PubMed
• Evolutionary conservation of disease mechanisms > Search first: HomoloGene, OrthoMCL, Alliance of Genome Resources
• Transmission (if applicable):
• Zoonotic potential > Search first: CDC zoonotic diseases, WHO zoonoses, GIDEON
• Cross-species susceptibility > Search first: NCBI Taxonomy, veterinary databases, PubMed

15. Model Organisms

• Model Types:
• Model organism type (mammalian, invertebrate, cellular, in vitro) > Search first: Alliance of Genome Resources, model organism databases
• Specific model systems (mouse, rat, zebrafish, Drosophila, C. elegans, yeast, cell lines, organoids, iPSCs) > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, SGD, ATCC, Cellosaurus
• Induced models (drug treatment, surgical intervention, environmental manipulation) > Search first: MGI, model organism databases, PubMed
• Genetic Models:
• Types available (knockout, knock-in, transgenic, conditional, humanized) > Search first: MGI, IMPC, KOMP, EuMMCR, IMSR
• Model Characteristics:
• Phenotype recapitulation (how well model reproduces human disease features) > Search first: Model organism databases, comparative studies, PubMed
• Model limitations (aspects of human disease not captured) > Search first: Model organism databases, PubMed, review articles
• Applications:
• Research applications (what aspects of disease can be studied) > Search first: Model organism databases, PubMed
• Resources:
• Model databases > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, IMSR, EMMA, MMRRC

Citation Requirements

• Cite primary literature (PMID preferred) for all mechanistic and clinical claims
• Prioritize recent reviews and landmark papers
• Include direct quotes from abstracts where possible to support key statements
• Distinguish evidence source types: human clinical, model organism, in vitro, computational

Output Format

Structure your response as a comprehensive narrative organized by the sections above. For each section, provide: - Factual content with specific details (numbers, percentages, gene names, variant nomenclature) - Ontology term suggestions (HPO, GO, CL, UBERON, CHEBI, MAXO, MONDO) where applicable - Evidence citations with PMIDs - Direct quotes from abstracts to support key claims - Clear indication when information is not available or not applicable for this disease

This report will be used to populate a disease knowledge base entry with: - Pathophysiology descriptions with causal chains - Gene/protein annotations (HGNC, GO terms) - Phenotype associations (HP terms) with frequencies - Cell type involvement (CL terms) - Anatomical locations (UBERON terms) - Chemical entities (CHEBI terms) - Treatment annotations (MAXO terms) - Evidence items with PMIDs and exact abstract quotes - Epidemiology, prognosis, diagnostic, and prevention information - Animal model descriptions with phenotype recapitulation details

Mowat–Wilson syndrome: comprehensive disease-characteristics report

Executive summary

Mowat–Wilson syndrome (MOWS) is a congenital, lifelong, multisystem Mendelian neurodevelopmental disorder caused primarily by heterozygous loss of function of ZEB2 at chromosome 2q22.3. Its defining pattern combines moderate-to-profound intellectual disability and severe speech impairment with a recognizable facial gestalt, delayed motor development, frequent epilepsy, and variably penetrant congenital anomalies—especially Hirschsprung disease, congenital heart disease, genitourinary abnormalities, and malformations of the corpus callosum or hippocampus. The estimated prevalence is approximately 1 per 50,000–70,000 live births, although underdiagnosis is likely. Most cases are sporadic and de novo; inheritance is formally autosomal dominant. (zou2020genotypephenotypeanalysisin pages 1-2, birkhoff2021zeb2themowatwilson pages 1-2, peter2024mowat–wilsonsyndromecase pages 1-2)

The most important recent development is the 2024 discovery of a highly reproducible blood DNA-methylation episignature. In 29 molecularly confirmed individuals, investigators identified 296 differentially methylated probes, 98.6% hypomethylated, and separated MOWS from controls and 56 other neurodevelopmental-disorder episignatures. This is a promising functional diagnostic adjunct for atypical phenotypes and uncertain ZEB2 variants, but not a population-screening test. (giuseppe2024identificationofthe pages 5-6, giuseppe2024identificationofthe pages 1-2, giuseppe2024identificationofthe pages 2-2)

No approved disease-modifying, gene, cell, or RNA therapy was identified. Present implementation is multidisciplinary supportive care, developmental rehabilitation, antiseizure treatment, nutritional support, and surgical correction of Hirschsprung disease and congenital anomalies.

The following compact table provides a knowledge-base-oriented synopsis.

Table: This compact table summarizes high-yield disease knowledge-base facts for Mowat-Wilson syndrome, including identifiers, ZEB2 genetics, major phenotype frequencies, 2024 episignature data, diagnostics, management, and model systems. It is designed to support rapid curation with evidence type labeling and source-linked citations.

1. Disease information

Definition and classification

MOWS is a Mendelian, autosomal-dominant developmental disorder/chromatin-transcription disorder and neurocristopathy resulting from ZEB2 haploinsufficiency. ZEB2 is a DNA-binding, SMAD-interacting transcriptional regulator required during embryonic neural, neural-crest, cardiac, enteric, craniofacial, and urogenital development. The information summarized here is principally aggregated disease-level evidence from molecularly confirmed cohorts, literature/database compilations, and mechanistic models—not individual EHR-derived data—although some reports contain individual case histories. (zou2020genotypephenotypeanalysisin pages 1-2, peter2024mowat–wilsonsyndromecase pages 2-4, birkhoff2021zeb2themowatwilson pages 1-2)

Identifiers and synonyms

• OMIM: Mowat–Wilson syndrome, #235730; ZEB2, 605802.
• MONDO: Mowat–Wilson syndrome; the exact MONDO accession was not verified in the retrieved evidence and should be reconciled directly against the current MONDO release before database import.
• Gene: ZEB2, formerly ZFHX1B or SIP1; chromosome 2q22.3.
• Synonyms: Mowat-Wilson syndrome; MWS/MOWS; ZEB2-related Mowat-Wilson syndrome; ZFHX1B-related syndrome; historically, Hirschsprung disease–intellectual disability syndrome.
• A unique ICD-10-CM or MeSH disease code was not established in the retrieved literature. In practice, cases may be represented through congenital-malformation, intellectual-disability, epilepsy, or genetic-syndrome codes. ICD-11/SNOMED mappings should be checked against current terminology services rather than inferred.

2. Etiology, risk, protection, and gene–environment interaction

Causal factor

The primary cause is a heterozygous pathogenic ZEB2 variant or deletion producing loss of function and haploinsufficiency. Reported classes include nonsense, frameshift, splice-altering, missense/hypomorphic variants, intragenic or whole-gene deletions, larger 2q22 rearrangements, and rare duplications or regulatory lesions. More than 220 pathogenic variants had been catalogued by 2020. (zou2020genotypephenotypeanalysisin pages 1-2)

A 2024 aggregation of 298 individuals found that exon 8 contained 198/298 variants (66%), that more than 90% were nonsense or frameshift changes, and that recurrent c.2083C>T represented approximately 11% of reported patients. These figures describe an assembled literature/database series and should not be interpreted as unbiased population frequencies. (peter2024mowat–wilsonsyndromecase pages 1-2, peter2024mowat–wilsonsyndromecase pages 4-5)

Risk and protective factors

• Genetic risk: A constitutional pathogenic ZEB2 allele is sufficient. Most cases are de novo. Rare parental germline mosaicism makes sibling recurrence low but not zero.
• Modifier genes: No clinically validated modifier is established. A 2026, non-peer-reviewed two-trio preprint proposed a common RET enhancer risk haplotype as a modifier of Hirschsprung penetrance. The high-risk haplotype had a reported OR of 11.01 and had previously been associated with greater than 50% reduction of RET expression in neural-crest-derived cells/fetal gut. This result is hypothesis-generating, not ready for clinical risk prediction. (collins2026wholegenomesequencing pages 6-9, collins2026wholegenomesequencing pages 13-19)
• Environmental/lifestyle/infectious risk: None is known to cause MOWS or materially alter its penetrance. Smoking, diet, alcohol, toxins, radiation, occupation, infection, and parental lifestyle are not established causal factors.
• Protective factors: No protective allele, exposure, diet, medication, or behavior has been validated as preventing the syndrome.
• Gene–environment interactions: No reproducible MOWS-specific interaction is established. Environment and access to care can influence complications and functional outcomes, but not the underlying congenital genotype.

3. Phenotypes

Phenotypes are congenital or emerge during infancy/childhood. Severity is variable, but developmental disability is generally chronic and substantial. Aggregate percentages differ because cohorts are small and ascertainment is phenotype-biased.

Neurodevelopment and behavior

• Global developmental delay/intellectual disability: Nearly universal; typically moderate to severe or profound. Suggested terms: Global developmental delay, Intellectual disability, Severe intellectual disability.
• Speech: Severe expressive-language impairment; many individuals remain nonverbal or use a few words/signs or augmentative communication. Suggested term: Severely delayed speech and language development.
• Motor development/hypotonia: Delayed sitting, standing, and walking; mean walking age in aggregate review data was about 4 years. In one four-person molecular series, two were not walking, one walked at approximately 3 years, and one at approximately 2 years. Suggested terms: Delayed walking, Muscular hypotonia, Abnormality of gait. (peter2024mowat–wilsonsyndromecase pages 1-2, zou2020genotypephenotypeanalysisin pages 3-5)
• Behavior: A frequently described sociable or happy demeanor does not exclude autism-like behaviors, stereotypies, pain-expression differences, or sleep disturbance. Quantified quality-of-life and behavioral prevalence estimates remain sparse.

Developmental impairments substantially affect communication, self-care, mobility, education, independent living, and caregiver burden. Formal MOWS-specific EQ-5D, SF-36, PROMIS, or validated quality-of-life natural-history datasets were not found.

Neurologic and structural brain phenotypes

• Epilepsy/abnormal EEG: Aggregate review estimate 84%; onset is usually in infancy or childhood, with variable seizure types and medication response. A four-child series observed epilepsy in 3/4, including spontaneous remission in one. Suggested terms: Seizure, Epilepsy, Abnormal EEG. (peter2024mowat–wilsonsyndromecase pages 1-2, zou2020genotypephenotypeanalysisin pages 3-5)
• Brain malformations: Corpus-callosum and hippocampal abnormalities, ventriculomegaly, white-matter abnormalities, cortical atrophy/dysplasia, enlarged basal ganglia, and cerebellar anomalies are reported; one synthesis estimated CNS malformations at approximately 80%. Suggested terms: Agenesis/hypoplasia of corpus callosum, Hippocampal abnormality, Ventriculomegaly, Cerebral white-matter abnormality. (peter2024mowat–wilsonsyndromecase pages 1-2, birkhoff2021zeb2themowatwilson pages 2-4)
• Microcephaly: Common and may become more evident postnatally. Suggested term: Microcephaly.
• Sleep: Sleep disturbance and sleep-activated epileptiform abnormalities can occur, but robust syndrome-specific frequencies are unavailable.

Neurologic involvement is described by experts as one of the principal determinants of prognosis and quality of life. (cordelli2021neurologicalphenotypeof pages 1-2)

Craniofacial, growth, and musculoskeletal findings

The evolving facial gestalt includes hypertelorism/deep-set eyes, broad or medially flared eyebrows, a prominent or broad nasal tip, open mouth, pointed/triangular chin, and uplifted earlobes with central depression. Suggested HPO labels include Hypertelorism, Deeply set eye, Broad eyebrow, Prominent nasal tip, Pointed chin, and Uplifted earlobe. Short stature, microcephaly, slender habitus, hypotonia, scoliosis, pes planus, contractures, and delayed motor milestones may develop. Facial features were present in all four patients in one molecular case series. (zou2020genotypephenotypeanalysisin pages 1-2, zou2020genotypephenotypeanalysisin pages 3-5)

Gastrointestinal and feeding phenotypes

• Hirschsprung disease: Approximately 50%, usually congenital/early infancy; reflects enteric aganglionosis and can cause neonatal obstruction, abdominal distension, delayed meconium, or enterocolitis. Suggested term: Hirschsprung disease. (peter2024mowat–wilsonsyndromecase pages 1-2, birkhoff2021zeb2themowatwilson pages 2-4)
• Constipation/dysmotility: Common even without confirmed aganglionosis. Suggested terms: Constipation, Gastrointestinal dysmotility.
• Feeding/growth: Oral-motor dysfunction, gastroesophageal reflux, gastroparesis, aspiration risk, and poor growth may require enteral feeding. A severe 2024 case required gastrostomy feeding. (peter2024mowat–wilsonsyndromecase pages 2-4)

Cardiovascular, genitourinary, ophthalmic, and other manifestations

• Congenital heart disease: Approximately 58% in a 2024 aggregate review; lesions include septal defects, pulmonary-artery/valve anomalies and, rarely, complex disease. Suggested term: Congenital heart defect. (peter2024mowat–wilsonsyndromecase pages 1-2)
• Genitourinary: Hypospadias, cryptorchidism, renal tract anomalies, vesicoureteral reflux, and structural genital anomalies. Suggested terms: Hypospadias, Cryptorchidism, Renal structural abnormality.
• Eyes/vision: Strabismus, refractive error, ptosis and cerebral visual impairment may occur. Suggested terms: Strabismus, Refractive error, Visual impairment.
• Dental/oral: Dental anomalies and oral-health burdens are recognized, but quantified data remain limited; this gap motivated observational study NCT07476417.
• Laboratory abnormalities: There is no characteristic biochemical, enzyme, hematologic, metabolic, or inflammatory laboratory signature used clinically.

4. Genetic and molecular information

Gene and protein

ZEB2 encodes a nuclear zinc-finger E-box-binding transcription factor with N- and C-terminal zinc-finger clusters, a homeodomain, SMAD-binding and CtBP-interacting regions. It can repress or activate transcription depending on promoter, cell type, and binding partners. ZEB2 interacts with receptor-regulated and co-SMADs, CtBP, p300 and KAT2B/PCAF, HDAC/methyltransferase-associated machinery, and the NuRD corepressor complex. (giuseppe2024identificationofthe pages 2-2, epifanova2019roleofzeb2sip1 pages 2-3, putte2007neuralcrestspecificremoval pages 1-2)

Variant interpretation

• Typical pathogenic variants: Germline heterozygous nonsense, frameshift, canonical splice, exon-level/multiexon, whole-gene, or 2q22.3 deletions. Their expected consequence is nonsense-mediated decay or absent/truncated protein.
• Missense variants: Rare; some zinc-finger missense alleles are hypomorphic and can produce milder/atypical disease. Many remain VUS: one 2024 source noted 290 ClinVar ZEB2 missense VUS at the time of analysis. Functional evidence, segregation, phenotype match, and potentially the methylation episignature are therefore important. (giuseppe2024identificationofthe pages 2-2, birkhoff2021zeb2themowatwilson pages 2-4)
• ACMG/AMP: A de novo null variant in a gene where haploinsufficiency is established generally supports pathogenic/likely pathogenic classification, subject to transcript relevance, population absence, sequencing quality, and full ACMG evidence assessment. Four truncating variants in a 2020 series were classified pathogenic and confirmed de novo. (zou2020genotypephenotypeanalysisin pages 3-5)
• Population frequency: Pathogenic loss-of-function alleles are expected to be absent or extremely rare in population databases. No reliable carrier frequency was identified; because the disorder is dominant and predominantly de novo, conventional recessive carrier frequency is not meaningful.
• Somatic versus germline: The disease is a constitutional germline disorder. Somatic ZEB2 changes relevant to cancer are not the cause of MOWS.

Chromosomal abnormalities and epigenetics

Whole-gene and larger 2q22 deletions can produce MOWS, sometimes with additional deletion-dependent features. CMA is therefore essential when sequencing is negative or a larger imbalance is suspected. Conventional karyotyping or FISH is useful mainly for visible rearrangements or targeted familial follow-up, not as first-line testing for small intragenic variants.

The 2024 episignature study used blood leukocyte DNA from 29 people—24 discovery and 5 validation cases—and retained 772,557 array probes after filtering. It identified 296 DMPs, of which 98.6% were hypomethylated; 208 mapped to 167 annotated genes and 16 highly significant hypomethylated sites lay within the ZEB2 locus. All MOWS cases received classifier scores near 1 and segregated from controls and 56 other neurodevelopmental episignatures. The authors’ exact conclusion was that the signature is “highly sensitive and reproducible, providing a useful tool to facilitate diagnosis.” Formal independent, population-scale sensitivity and specificity estimates are still needed. (giuseppe2024identificationofthe pages 5-6, giuseppe2024identificationofthe pages 1-2, giuseppe2024identificationofthe pages 2-2)

No validated prognostic methylation, proteomic, metabolomic, or lipidomic signature is available.

5. Environmental information

MOWS is not environmentally caused. No toxin, pollutant, radiation exposure, occupation, diet, smoking, alcohol use, exercise pattern, bacterium, virus, fungus, or parasite has been established as a trigger. Standard nutrition, exercise, sleep, vaccination, infection prevention, and avoidance of smoke are appropriate for general health and complication reduction but are not primary prevention for the genotype.

6. Mechanism and pathophysiology

Upstream causal chain

Pathogenic ZEB2 allele/deletion → reduced functional nuclear ZEB2 → altered DNA binding, SMAD-dependent/independent transcription and chromatin-coregulator recruitment → mistimed lineage specification, migration and cell–cell signaling during embryogenesis → tissue-specific malformations and postnatal neurologic dysfunction.

Neural crest and enteric disease

ZEB2 limits BMP-SMAD signaling at the neural plate border, represses epithelial genes such as CDH1 during epithelial-to-mesenchymal transition, and regulates neural-crest specifiers including FOXD3 and SOX10. Loss impairs induction, delamination, migration, and differentiation of cranial, cardiac, vagal, melanocytic, and autonomic neural-crest lineages. The downstream clinical chain is defective vagal crest colonization of bowel → enteric ganglion deficiency → Hirschsprung disease/constipation; defective cranial/cardiac crest → facial and cardiovascular anomalies. Neural-crest-specific mouse deletion reproduced craniofacial, GI, cardiac, melanoblast, and autonomic defects. (epifanova2019roleofzeb2sip1 pages 3-4, putte2007neuralcrestspecificremoval pages 1-2)

Suggested terms: GO neural crest cell development; neural crest cell migration; epithelial-to-mesenchymal transition; enteric nervous system development; BMP signaling. Suggested cell types: neural crest cell, enteric neural progenitor, enteric neuron, melanoblast, autonomic neuron.

Cortex, hippocampus, and corpus callosum

Conditional mouse studies indicate that ZEB2 controls neurogenesis/gliogenesis timing partly through non-cell-autonomous signaling from postmitotic neurons to progenitors. ZEB2 normally restrains Ntf3; excess Ntf3 shifts apical/basal progenitor balance and promotes premature upper-layer neurogenesis. Dorsal telencephalic loss also increases Sfrp1, suppressing Wnt signaling, reducing hippocampal progenitor proliferation, increasing apoptosis, and contributing to hippocampal/callosal agenesis. (epifanova2019roleofzeb2sip1 pages 7-7, cordelli2021neurologicalphenotypeof pages 1-2)

Suggested terms: GO cerebral cortex development; hippocampus development; corpus callosum development; regulation of neurogenesis; gliogenesis; Wnt signaling; neuron-to-progenitor signaling. Cell types: radial glial cell, neural progenitor cell, cortical projection neuron.

GABAergic interneurons and epilepsy

In ventral telencephalic models, Zeb2 loss disrupts interneuron migration and subtype maturation; increased Unc5b repulsive signaling contributes to abnormal interneuron positioning/numbers. Heterozygous mice show reduced parvalbumin interneurons on some genetic backgrounds. The plausible chain is altered inhibitory-neuron development → excitation/inhibition imbalance → epilepsy and neurobehavioral impairment. This is strong animal-model biology but is not yet a validated patient biomarker. (epifanova2019roleofzeb2sip1 pages 3-4, epifanova2019roleofzeb2sip1 pages 2-3)

Suggested terms: GO GABAergic neuron differentiation; interneuron migration; regulation of synaptic transmission, GABAergic. Cell types: GABAergic interneuron, parvalbumin-positive interneuron.

Glia and cerebellum

ZEB2 regulates neuro-/gliogenic timing and FGF, Notch, and TGF-β/BMP components. Cerebellar radial-glia deletion in mice impairs Bergmann-glia specification, granule-neuron migration, cerebellar lamination, and locomotion. These findings offer a mechanism for motor dysfunction but do not prove that all human motor impairment is cerebellar. (birkhoff2021zeb2themowatwilson pages 1-2, cordelli2021neurologicalphenotypeof pages 1-2)

Suggested terms: GO gliogenesis; Bergmann glial cell differentiation; cerebellar cortex morphogenesis; granule-cell migration. Cell types: Bergmann glial cell, cerebellar radial glial cell, granule neuron progenitor.

Molecular profiling and advanced technology

The best validated human molecular profile is the blood episignature. Transcriptomic animal studies identify broad, context-dependent target sets; a universal human disease transcriptome, proteome, metabolome, lipidome, spatial-transcriptomic atlas, or CRISPR-screen-derived therapeutic target was not established. Patient iPSCs are an important emerging platform for mutation-specific neural phenotyping, but the retrieved evidence emphasizes that no model yet captures the full human syndrome. (birkhoff2021zeb2themowatwilson pages 24-25)

7. Anatomical structures affected

• Primary systems: CNS and peripheral/enteric nervous system; heart; GI tract; craniofacial structures; genitourinary tract.
• Secondary structures: Musculoskeletal system, eyes/visual pathways, teeth/oral cavity, feeding/respiratory apparatus.
• Suggested UBERON labels: brain, cerebral cortex, hippocampus, corpus callosum, cerebellum, enteric nervous system, colon, heart, kidney, urethra, eye.
• Tissues/cells: neuroepithelium, neural crest, cortical neurons/progenitors, GABAergic interneurons, radial and Bergmann glia, enteric neurons, cardiac/craniofacial neural-crest derivatives.
• Subcellular localization: ZEB2 acts principally in the nucleus/chromatin; suggested GO cellular components are nucleus, chromatin, and transcription regulator complex.
• Lateralization: Most findings are midline, bilateral, or systemic; no consistent unilateral predilection is established.

8. Temporal development

MOWS begins prenatally, because ZEB2 dosage affects early lineage and organ development. Congenital manifestations include facial patterning, heart/genitourinary anomalies, brain malformations, and Hirschsprung disease. Hypotonia, developmental delay, poor growth, microcephaly, epilepsy, constipation, scoliosis, and functional limitations become apparent or evolve during infancy and childhood.

The course is chronic and lifelong, not relapsing-remitting. Congenital structural defects are stable unless corrected, while manifestations such as seizures, constipation, sleep disturbance, orthopedic complications, and feeding problems may fluctuate. Developmental gains occur, often slowly, but complete recovery is not expected. There is no established stage system, remission definition, or end-stage disease. Critical windows include prenatal neurodevelopment and early childhood, when seizure control, nutrition, communication support, and intensive developmental therapies may maximize function.

9. Inheritance and population

• Prevalence: Approximately 1:50,000–70,000 live births, equivalent to about 1.4–2 per 100,000. True prevalence may be higher because mild/atypical cases are missed. Incidence per year has not been robustly measured. (zou2020genotypephenotypeanalysisin pages 1-2, birkhoff2021zeb2themowatwilson pages 1-2)
• Inheritance: Autosomal dominant; predominantly de novo.
• Penetrance: ZEB2 loss-of-function has high penetrance for neurodevelopmental disease, but individual manifestations—especially Hirschsprung disease, epilepsy, cardiac disease, and malformations—show incomplete penetrance.
• Expressivity: Markedly variable. Rare hypomorphic missense variants may be milder than null alleles; larger deletions may add contiguous-gene features. Proposed position/severity correlations remain imperfect. (zou2020genotypephenotypeanalysisin pages 1-2, zou2020genotypephenotypeanalysisin pages 3-5, birkhoff2021zeb2themowatwilson pages 2-4)
• Anticipation: Not described; no repeat-expansion mechanism.
• Mosaicism: Parental germline mosaicism is a recognized counseling concern in de novo dominant disease, although quantitative MOWS-specific recurrence data were not retrieved.
• Founder effect/consanguinity: No established founder variant or consanguinity association. Consanguinity is not mechanistically relevant to a predominantly de novo dominant disorder.
• Sex/ethnicity/geography: Both sexes and diverse populations are affected. No robust sex bias, ethnic enrichment, or endemic geographic distribution is established.

10. Diagnostics

Clinical recognition

Suspect MOWS in a child with developmental delay/severe speech impairment and characteristic facies, especially when accompanied by epilepsy, postnatal microcephaly, Hirschsprung disease/constipation, corpus-callosum abnormality, congenital heart disease, or male genital anomalies. Facial recognition can guide testing, but molecular confirmation is required because neonatal and mild cases can be subtle.

Recommended molecular workflow

1. Sequence and deletion/duplication analysis of ZEB2, either as a single gene or within a developmental-delay/epilepsy/Hirschsprung panel.
2. If the phenotype is nonspecific, use trio exome or genome sequencing; WGS can detect coding, splice, structural, and selected regulatory lesions. A 2020 WGS study found four de novo truncating ZEB2 variants among 530 children referred for epilepsy/developmental delay. (zou2020genotypephenotypeanalysisin pages 3-5)
3. Chromosomal microarray for exon-level/whole-gene or broader 2q22 deletions; ensure the laboratory’s sequencing assay has validated CNV detection or add MLPA/qPCR/CMA.
4. RNA studies may clarify suspected splice variants; routine diagnostic proteomics/metabolomics is unsupported.
5. Blood DNA methylation/EpiSign may provide functional support for an atypical presentation or VUS, based on the 2024 episignature, but should complement—not replace—sequence/CNV analysis. (giuseppe2024identificationofthe pages 5-6, giuseppe2024identificationofthe pages 1-2)
6. Karyotype/FISH only when a balanced/large rearrangement is suspected or for targeted familial studies. Mitochondrial and repeat-expansion testing are not disease-specific.

Baseline clinical evaluation after diagnosis

Recommended phenotype-directed assessments include growth/head circumference; developmental, speech-language and augmentative-communication evaluation; neurologic examination and EEG when seizures or regression are suspected; brain MRI; echocardiogram; renal ultrasound and urologic review; examination for Hirschsprung disease/constipation; feeding/swallow and nutritional assessment; vision/hearing, dental, orthopedic, and sleep evaluation.

Differential diagnosis

Important alternatives include Pitt–Hopkins syndrome (TCF4), Angelman syndrome, Rett syndrome, Kleefstra syndrome, Goldberg–Shprintzen syndrome, Koolen–de Vries syndrome, DYRK1A-related disorder, CHARGE syndrome, and other syndromic Hirschsprung/neurodevelopmental disorders. MOWS is favored by its characteristic ears/nasal tip/chin, ZEB2 variant, Hirschsprung disease, and callosal/hippocampal pattern. Molecular testing resolves overlap.

Screening

There is no population newborn or carrier-screening program. Cascade testing is appropriate only after a familial variant is identified. Newborn biochemical screening does not detect MOWS.

11. Outcome and prognosis

Reliable 5-year/10-year survival curves, disease-specific mortality rates, and median life expectancy are unavailable. Survival into adulthood occurs, but evidence is limited by rarity and young historical cohorts. Mortality and serious morbidity are driven by complex heart disease, Hirschsprung-associated enterocolitis/obstruction, aspiration or feeding complications, severe epilepsy, infection, and perioperative risk—not by a known progressive metabolic degeneration. A reported 2024 child with severe cardiac and GI disease died around age five, illustrating possible severity but not population prognosis. (peter2024mowat–wilsonsyndromecase pages 2-4)

Long-term disability usually includes intellectual and expressive-language impairment, dependence in activities of daily living, and variable mobility and epilepsy. Recovery from the underlying syndrome is not expected, although seizures, nutrition, mobility, communication, and participation can improve with treatment. No validated molecular prognostic biomarker exists. Variant class/domain, deletion size, congenital anomaly burden, epilepsy control, aspiration, and Hirschsprung complications are clinically relevant but incompletely quantified prognostic factors.

12. Treatment and real-world implementation

Current strategy

There is no approved disease-modifying pharmacotherapy and no established ZEB2-specific pharmacogenomic recommendation. Treatment is individualized and multidisciplinary:

• Epilepsy: Standard antiseizure medication selected by seizure type/EEG; rescue medication and safety planning when indicated. Suggested MAXO labels: antiseizure pharmacotherapy, EEG monitoring.
• Hirschsprung disease: Pediatric surgical evaluation and pull-through surgery; urgent treatment of obstruction or enterocolitis. Persistent constipation requires structured bowel management. Suggested MAXO: surgical correction of Hirschsprung disease, bowel-management therapy.
• Cardiac/GU anomalies: Guideline-based cardiology surveillance and surgical/interventional correction; urology/nephrology management for hypospadias, cryptorchidism, reflux or renal anomalies.
• Feeding/nutrition: Swallow assessment, reflux/constipation treatment, caloric support, and gastrostomy when oral feeding is unsafe or inadequate. A severe case required G-tube feeding. (peter2024mowat–wilsonsyndromecase pages 2-4)
• Rehabilitation: Early physical, occupational, speech-language, feeding, behavioral, educational and augmentative/alternative-communication services. Suggested MAXO: physical therapy, occupational therapy, speech therapy, augmentative communication assessment.
• Other: Vision/hearing correction, dental care, orthopedic surveillance, sleep evaluation, vaccination, and family psychosocial support.

There are no syndrome-specific response rates or comparative trials; adverse effects follow those of each conventional intervention.

Experimental therapy and trials

No interventional gene-replacement, CRISPR, cell, ASO, siRNA, mRNA, targeted small-molecule, or immunotherapy trial was identified. ClinicalTrials.gov searching found NCT07476417, a not-yet-recruiting observational University of Milan study of oral health, dentofacial status, and oral-health-related quality of life, planned enrollment 25. This is natural-history/implementation research, not treatment.

13. Prevention

Primary prevention by lifestyle or vaccination is not possible. Prevention consists mainly of reproductive counseling and complication reduction:

• Genetic counseling: Explain de novo autosomal-dominant causation, low but nonzero sibling recurrence from possible germline mosaicism, and 50% transmission risk for an affected reproductive individual.
• Reproductive options: If the familial variant is known, prenatal diagnosis by CVS/amniocentesis and preimplantation genetic testing are technically possible. A negative parental blood test does not make recurrence zero.
• Secondary prevention: Early molecular diagnosis; prompt evaluation for cardiac, bowel, renal, feeding, seizure, vision/hearing, and developmental complications.
• Tertiary prevention: Seizure safety, aspiration prevention, bowel regimens/enterocolitis education, nutrition, rehabilitation, orthopedic surveillance, oral care, and routine immunization.
• No MOWS-specific prophylactic drug or public-health/environmental intervention exists.

14. Other species and natural disease

ZEB2 is evolutionarily conserved in vertebrates. Relevant taxa include Homo sapiens, Mus musculus (mouse), and Danio rerio (zebrafish). A naturally occurring, breed-associated veterinary counterpart was not identified; available animal phenotypes are engineered or experimentally induced. There is no infectious transmission, zoonotic potential, or cross-species contagion.

Comparative biology supports conserved roles in neural-crest specification, neural patterning, cortical development, interneuron migration, gliogenesis, and organogenesis, but species differences in brain development and dosage sensitivity limit direct translation.

15. Model organisms and experimental systems

Mouse

• Constitutive Zeb2 knockout: Embryonic death around E9.5 with neural-tube closure and neural-crest defects; useful for upstream embryology but too severe for postnatal MOWS. (epifanova2019roleofzeb2sip1 pages 3-4)
• Wnt1-Cre neural-crest conditional knockout: Craniofacial, GI/enteric, cardiac, melanoblast and autonomic defects resembling MOWS neurocristopathy. (putte2007neuralcrestspecificremoval pages 1-2)
• Emx1-Cre/Nex-Cre cortical models: Hippocampal/callosal abnormalities and altered cortical layer/neurogenic timing involving Sfrp1/Wnt, Ntf3 and Fgf9 signaling. (epifanova2019roleofzeb2sip1 pages 3-4, epifanova2019roleofzeb2sip1 pages 7-7, cordelli2021neurologicalphenotypeof pages 1-2)
• Nestin-Cre or ventral telencephalic conditional models: Perinatal lethality or GABAergic interneuron migration/subtype abnormalities; useful for epilepsy mechanisms. (epifanova2019roleofzeb2sip1 pages 3-4, epifanova2019roleofzeb2sip1 pages 2-3)
• Heterozygous Δex7 models: Some backgrounds show facial change, reduced motor activity, and fewer parvalbumin interneurons; background dependence is a major limitation. (epifanova2019roleofzeb2sip1 pages 2-3)

Zebrafish

Knockdown/perturbation models show neural patterning and neural-crest defects and support conserved anti-BMP functions. Limitations include genome duplication, developmental differences, and incomplete correspondence to human cognition/facial anatomy. (birkhoff2021zeb2themowatwilson pages 2-4)

Cellular/iPSC systems

Patient-derived iPSCs and differentiated neural progenitors/neurons are well suited to mutation-specific transcription, neurogenesis, and GABAergic phenotyping and to testing dosage-restoration strategies. Expert reviews emphasize their importance because most patients have unique alleles and no mouse model reproduces the entire syndrome. However, validated therapeutic screening endpoints and mature organoid/spatial or multi-omic standards remain under development. (birkhoff2021zeb2themowatwilson pages 24-25)

Recent developments and expert interpretation

1. 2024 episignature: The clearest recent translational advance. The exact abstract states that investigators “identified and validated a DNA methylation signature involving 296 differentially methylated probes.” Its near-universal hypomethylation is biologically consistent with ZEB2’s major repressor role. Independent prospective validation—especially in missense VUS, mosaic cases and differential diagnoses—is the next step. (giuseppe2024identificationofthe pages 5-6, giuseppe2024identificationofthe pages 1-2)
2. 2024 variant synthesis: The abstract reports that “more than 90% of the defects were due to nonsense or frameshift changes,” reinforcing haploinsufficiency as the dominant mechanism and exon 8 as a diagnostic hotspot. Nevertheless, complete-gene coverage and CNV analysis remain necessary; hotspot-only testing would miss many cases. (peter2024mowat–wilsonsyndromecase pages 1-2, peter2024mowat–wilsonsyndromecase pages 4-5)
3. Mechanistic convergence: Experts view MOWS not as a single-pathway disorder but as a developmental transcription/chromatin-dosage disorder affecting neural crest, cortical progenitor feedback, inhibitory interneurons, and glia through TGF-β/BMP-SMAD, Wnt, Notch, FGF and chromatin-coregulator networks. (birkhoff2021zeb2themowatwilson pages 1-2, epifanova2019roleofzeb2sip1 pages 3-4, cordelli2021neurologicalphenotypeof pages 1-2)
4. Evidence gap: Clinical care remains extrapolated from organ-specific standards and expert consensus. Prospective natural-history cohorts, adult outcome studies, standardized quality-of-life measures, genotype-aware biomarkers, and interventional trials are major unmet needs.

Evidence-quality and curation notes

• Phenotype percentages are mostly derived from small or aggregated, referral-biased cohorts and should carry a “variable/estimated” qualifier.
• The 2024 methylation work is human molecular evidence; mechanistic pathway chains are primarily conditional-mouse or cellular evidence and should not be represented as proven human biomarkers.
• The RET-modifier finding is a 2026 preprint based on two trios and must remain explicitly labeled preliminary. (collins2026wholegenomesequencing pages 6-9, collins2026wholegenomesequencing pages 13-19)
• PMIDs were not consistently present in the retrieved source metadata; therefore none were fabricated. DOI URLs and publication dates have been supplied for the major sources.

Key source URLs and publication dates

• Caraffi et al., February 2024, European Journal of Human Genetics: https://doi.org/10.1038/s41431-024-01548-4. (giuseppe2024identificationofthe pages 5-6)
• Peter et al., February 2024, International Journal of Molecular Sciences: https://doi.org/10.3390/ijms25052838. (peter2024mowat–wilsonsyndromecase pages 1-2)
• Cordelli et al., June 2021, Genes: https://doi.org/10.3390/genes12070982. (cordelli2021neurologicalphenotypeof pages 1-2)
• Birkhoff et al., July 2021, Genes: https://doi.org/10.3390/genes12071037. (birkhoff2021zeb2themowatwilson pages 1-2)
• Zou et al., October 2020, Experimental and Therapeutic Medicine: https://doi.org/10.3892/etm.2020.9393. (zou2020genotypephenotypeanalysisin pages 1-2)
• Epifanova et al., February 2019, Brain Research: https://doi.org/10.1016/j.brainres.2018.09.034. (epifanova2019roleofzeb2sip1 pages 3-4)
• Van de Putte et al., June 2007, Human Molecular Genetics: https://doi.org/10.1093/hmg/ddm093. (putte2007neuralcrestspecificremoval pages 1-2)

References

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