Asta Literature Retrieval: Pathophysiology and clinical mechanisms of Alpha-gal Syndrome. Core disease mechanisms, molecular and cellular pathwa...

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

• Papers retrieved: 20
• Snippets retrieved: 20

Relevant Papers

[1] New therapeutic targets in rare genetic skeletal diseases

• Authors: M. Briggs, Peter A. Bell, M. Wright, K. A. Pirog
• Year: 2015
• Venue: Expert Opinion on Orphan Drugs
• URL: https://www.semanticscholar.org/paper/1363107f71ae6d2d60abca471cddf3da5d13644b
• DOI: 10.1517/21678707.2015.1083853
• PMID: 26635999
• PMCID: 4643203
• Citations: 39
• Influential citations: 1
• Summary: An overview of disease mechanisms that are shared amongst groups of different GSDs and potential therapeutic approaches that are under investigation are described to generate critical mass for the identification and validation of novel therapeutic targets and biomarkers.
• Evidence snippets:
• Snippet 1 (score: 0.393) > However, emerging knowledge suggests that the primary genetic defect may be less important than the cells' response to the expression of the mutant gene product [107]. Moreover, the largely overlooked response of a cell (i.e. chondrocyte) to the abnormal extracellular environment is also important for disease progression as illustrated by several GSDs discussed in this review. > It is important that 'omics'-based approaches and technologies are systematically applied to the study of rare GSDs so that definitive reference profiles and disease signatures are generated for each phenotype. These can then be used in a Systems Biology approach to identify both common and dissimilar pathological signatures and disease mechanisms. This approach is entirely dependent upon relevant in vitro and in vivo models (and also novel 'disease-mechanism phenocopies' [107]) for testing new diagnostic and prognostic tools and for determining the molecular mechanisms that underpin the pathophysiology so that effective therapeutic treatments can be developed and validated. This approach will eventually lead to personalized treatments and care strategies centred on shared disease mechanisms with the use of relevant biomarkers to monitor the efficacy of treatment and disease progression. > It is vital that all relevant stakeholders are involved from the outset in defining the appropriate outcomes of any potential therapeutic regime. The perceptions of a successful therapy can differ widely between the clinical academic community and the relevant patient-support groups and it is vital that there is engagement on all these issues. > In summary, the identification of causative genes and mutations for GSDs over the last 20 years, coupled with the generation and in-depth analysis of a plethora of relevant cell and mouse models, has derived new knowledge on disease mechanisms and suggested potential therapeutic targets. The fast-evolving hypothesis that clinically disparate diseases can share common disease mechanisms is a powerful concept that will generate critical mass for the identification and validation of novel therapeutic targets and biomarkers.

[2] Fabry Disease Screening in Patients with Idiopathic HCM or LVH: Data from the Multicentric Nationwide F-CHECK Study

• Authors: R. Machado, I. Fortuna, S. Sousa, C. Costa, J. Calvão et al.
• Year: 2025
• Venue: Biomedicines
• URL: https://www.semanticscholar.org/paper/dff83a780adcd863d456d11f144be49614816e4c
• DOI: 10.3390/biomedicines13102530
• PMID: 41153811
• PMCID: 12561516
• Summary: The observed 3.4% prevalence of Fabry disease highlights the importance of systematic FD screening among Portuguese patients with unexplained cardiomyopathy, extending beyond classic hypertrophic presentations to dilated forms.
• Evidence snippets:
• Snippet 1 (score: 0.386) > Fabry disease (FD) is a rare X-linked lysosomal storage disease (LSD) caused by mutations in the GLA gene, which encodes the enzyme alpha-galactosidase A (α-Gal A). The deficiency or absence of α-Gal A leads to the intracellular accumulation of globotriaosylceramide and related glycosphingolipids within lysosomes across various cell types and organ systems, including the kidneys, heart, and nervous systems [1]. The accumulation triggers a complex cascade of pathophysiological processes, such as cellular hypertrophy, fibrosis, and inflammation, that ultimately cause progressive organ damage, life-threatening complications, and increased risk of premature death [2,3]. > Clinically, FD is categorised into two major phenotypes: classic and later-onset. The classic phenotype is characterised by severely reduced (<3% of normal values) or absent α-Gal A activity and typically presents in early childhood with signs and symptoms such as cornea verticillata, acroparesthesias, and angiokeratomas [1,2]. Over time, patients often develop progressive multi-organ involvement, including chronic kidney disease with proteinuria, leading to end-stage renal failure, hypertrophic cardiomyopathy (HCM), sensorineural hearing loss, and cerebrovascular events. In contrast, the later-onset phenotype occurs in individuals with residual enzyme activity and usually lacks early symptoms. Clinical manifestations are often milder, delayed, or confined to a single organ, most commonly the heart, where significant pathology such as left ventricular hypertrophy (LVH) may emerge later in life [1]. > Cardiac involvement is the primary determinant of morbidity and mortality in FD [3,4]. Multiple cardiac cell types may be affected, resulting in various cardiac phenotypes and clinical presentations. While concentric HCM is the most frequent cardiac manifestation, other variants such as asymmetric LVH, apical HCM, or even systolic left ventricular (LV) dysfunction may occur.

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

• Authors: Hao Xiong, Jinsheng Guo
• Year: 2025
• Venue: Pharmaceuticals
• URL: https://www.semanticscholar.org/paper/76e92127053136900f7e3f10e2c9278251ced5d2
• DOI: 10.3390/ph18040507
• PMID: 40283943
• PMCID: 12030350
• Citations: 15
• Summary: HSC-targeted approaches using specific surface markers and receptors may enable the selective delivery of drugs, oligonucleotides, and therapeutic peptides that exert optimized anti-fibrotic and anti-HCC effects.
• Evidence snippets:
• Snippet 1 (score: 0.384) > Significant progress has been made in elucidating the cellular and molecular mechanisms of liver fibrosis; however, only a few findings have been successfully translated into clinical applications. Firstly, the high cost of drug development and target validation necessitates prolonged timelines and substantial financial investment. Secondly, as regulatory requirements become more stringent, there is an increasing demand for drugs with well-defined clinical efficacy and safety profiles. Moreover, the efficacy observed in animal models often fails to fully translate to clinical settings due to differences in pharmacokinetics, extracellular matrix (ECM) cross-linking, and disease pathophysiology. Despite advancements in anti-fibrotic drug development, accurately identifying ideal noninvasive biomarkers for fibrotic activity and establishing consensus on optimal clinical endpoints remain significant challenges [113,114]. > Currently, addressing the underlying cause remains the only proven strategy to halt or reverse liver fibrosis progression, while the development of effective anti-fibrotic therapies continues to pose a major challenge in liver disease management. Over the past few decades, substantial progress has been made in elucidating the cellular and molecular mechanisms underlying liver fibrosis. Liver fibrosis is a complex pathological change involving multiple cells, factors, and pathways, and the study of the cellular and molecular mechanisms of its occurrence and development provides an important theoretical basis and therapeutic target for clinical drug development. It is anticipated that improved animal models and well-designed clinical trials will facilitate the successful translation of anti-fibrotic research into effective clinical treatments in the near future.

[4] Rare Monogenic Diseases: Molecular Pathophysiology and Novel Therapies

• Authors: I. Condò
• Year: 2022
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/6aece75e6947f102b657851b74e8b96df5e654c1
• DOI: 10.3390/ijms23126525
• PMID: 35742964
• PMCID: 9223693
• Citations: 19
• Influential citations: 2
• Summary: A rare disease is defined by its low prevalence in the general population and its presence in a very small number of people.
• Evidence snippets:
• Snippet 1 (score: 0.384) > The selective expression or the particular role of specific genes in a single tissue explains the appearance of organ-specific inherited diseases. This is the case of genetic disorders of the kidney, which include dominant and recessive forms of cystic diseases, and renal tubulopathies. Mutations in polycystin-1 (PKD1) or -2 (PKD2) genes lead to autosomaldominant polycystic kidney disease (ADPKD), whose gender-dependent phenotype was analyzed in the study by Talbi et al. [9]. These results, obtained in mice lacking PKD1 expression, show the involvement of intracellular Ca2+ levels in the more severe phenotype affecting male ADPKD animals. Altogether, identification of the molecular mechanisms underlying enhanced Ca2+ signaling and proliferation in cells from male kidneys may contribute to develop novel therapeutics for ADPKD [9]. The autosomal-recessive form of polycystic kidney disease (ARPKD) mostly arises from defects in the gene named polycystic kidney and hepatic disease 1 (PKHD1), whereas a minority of cases is linked to a second causative gene DZIP1L. To examine the still unclear molecular pathophysiology of ARPKD, Cordido et al. recapitulate known molecular disease mechanisms and possible therapeutic approaches, from cellular and animal models to clinical trials [10]. The knowledge of ARPKD pathogenic pathways, involving the epidermal growth factor receptor (EGFR) axis, the production of adenylyl cyclase adenosine 3 ,5 -cyclic monophosphate (cAMP) and the activation of several protein kinases, begins to stimulate possible pharmacological interventions [10]. Inherited loss of function in various electrolyte transport proteins located along the nephron leads to two types of kidney tubulopathy with overlapping clinical symptoms: Gitelman and Bartter syndromes. The review by Nuñez-Gonzalez et al. aims to explain the different molecular basis of these difficult to diagnose monogenic syndromes. Moreover, the authors provide an overview of current therapeutic approaches and highlight the presence of common and specific options for Gitelman and Bartter patients [11].

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

• Authors: M. Uzti̇mür, C. N. Ünal, Gurler Akpinar
• Year: 2025
• Venue: Journal of Veterinary Internal Medicine
• URL: https://www.semanticscholar.org/paper/4b9c488b5dbd65d7b26fd2ad9aed70e8c4b59942
• DOI: 10.1111/jvim.70139
• PMID: 40492724
• PMCID: 12150350
• Citations: 2
• Summary: Understanding the serum proteome profiles of goats with pregnancy toxemia might help identify the proteomes and pathways responsible for the development of this disease and improve diagnosis and treatment.
• Evidence snippets:
• Snippet 1 (score: 0.380) > 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.

[6] 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: 15
• 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: 0.378) > 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

[7] Exploring the molecular mechanisms of subarachnoid hemorrhage and potential therapeutic targets: insights from bioinformatics and drug prediction

• Authors: Yi Liu, Yang Zhang, Huan Wei, Li Wang, Lishang Liao
• Year: 2025
• Venue: Scientific Reports
• URL: https://www.semanticscholar.org/paper/19a91d9c8cabec6a5a186729d545077e252ecb67
• DOI: 10.1038/s41598-025-97642-8
• PMID: 40229542
• PMCID: 11997208
• Citations: 1
• Summary: The findings not only elucidate the molecular mechanisms underlying SAH but also provide robust bioinformatics and experimental evidence supporting IRN as a promising therapeutic candidate, offering novel insights for future intervention strategies in SAH.
• Evidence snippets:
• Snippet 1 (score: 0.371) > involved in SAH pathology. As a result, our understanding of the cellular composition and microenvironment in SAH remains incomplete 8 . > Advances in bioinformatics provide powerful tools to analyze large-scale gene expression data and understand complex biological processes. By integrating transcriptomic data with immune cell infiltration analysis, we can gain a deeper understanding of the molecular mechanisms underlying SAH and identify potential key genes as therapeutic targets 9,10 . Previous studies have indicated that inflammation, oxidative stress, and cell death play crucial roles in the development of SAH, processes that are often closely associated with changes in specific cell types and immune responses 11 . > The goal of this study is to explore the molecular mechanisms of SAH, with a focus on immune cell infiltration and its role in disease progression. We aim to identify key genes and signaling pathways associated with SAH and investigate potential therapeutic strategies. Specifically, we will examine Isorhynchophylline (IRN) as a potential treatment for SAH and analyze its effects on relevant targets and signaling pathways. Through a comprehensive understanding of the pathological features of SAH, this study aims to provide valuable insights into future clinical interventions and treatment strategies.

[8] 18O-assisted dynamic metabolomics for individualized diagnostics and treatment of human diseases

• Authors: E. Nemutlu, Song Zhang, N. Juranic, A. Terzic, S. Macura et al.
• Year: 2012
• Venue: Croatian Medical Journal
• URL: https://www.semanticscholar.org/paper/880f053c7f060db4b990e447d0a22c4b69372ddb
• DOI: 10.3325/cmj.2012.53.529
• PMID: 23275318
• PMCID: 3541579
• Citations: 30
• Summary: The potential use of dynamic phosphometabolomic platform for disease diagnostics currently under development at Mayo Clinic is described and discussed briefly.
• Evidence snippets:
• Snippet 1 (score: 0.370) > 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.

[9] 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: 0.368) > Example use of MIDD relevant to address uncertainty potentially also during HTA What is the optimal dosage in the clinical context? Physiologically based pharmacokinetic models can investigate dosing-regimens relevant for regulatory review and product labels (9) and can also mimic real-life adherence to prescribed treatment regimens (see also below) or pharmacology-relevant characteristics of special populations as well as drug-drug interactions. > What is the duration of the effectiveness, especially with chronic use of a treatment? Mechanistic models can predict the long-term disease progression by extrapolation of shorter-term findings under the constraints of how the components of the system function (and these constraints convey biological plausibility by design). An example is the use of a mechanism-based disease progression model for comparison of long-term effects of pioglitazone, metformin, and gliclazide on disease processes underlying Type 2 Diabetes Mellitus (10). Another example is prediction of long-term outcomes by short-term marker data as demonstrated by a semi-mechanistic approach in context of osteoporosis treatment (11). > What is the efficacy for relevant clinical outcomes? Mechanistic models combined with pharmacometric approaches can translate findings for one outcome to a range of other outcomes. An example of survival modeling on the back of a mechanistic description is the modeling framework for CD19-Specific CAR-T cell immunotherapy using a quantitative systems pharmacology model (12). > What is the size of the clinical effect dependent on patient characteristics and extrinsic factors? Data-driven modeling techniques can capture correlation within clinical data. Describing the clinical effect of a drug can also be based on mechanistic considerations. Such models either (a) link disease phenotypes to increasingly granular mathematical representations of pathophysiologic processes (top-down approach) or (b) derive functional, computable cellular networks from the molecular building blocks of genes and proteins to elucidate the impact of pathologic or therapeutic alterations on network operating states and hence clinical phenotype (bottom-up) [see (13)].

[10] Molecular insights into the premature aging disease progeria

• Authors: Sandra Vidak, R. Foisner
• Year: 2016
• Venue: Histochemistry and Cell Biology
• URL: https://www.semanticscholar.org/paper/60fb3b46bb7e42d5d08cc3b7cbc783b118300c31
• DOI: 10.1007/s00418-016-1411-1
• PMID: 26847180
• PMCID: 4796323
• Citations: 107
• Influential citations: 4
• Summary: Changes in mechanosignaling, altered chromatin organization and impaired genome stability, and changes in signaling pathways, leading to impaired regulation of adult stem cells, defective extracellular matrix production and premature cell senescence are discussed.
• Evidence snippets:
• Snippet 1 (score: 0.367) > 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.

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

• Authors: Lina Zhu, Yang Li, Yiyao Bao
• Year: 2026
• Venue: Current Issues in Molecular Biology
• URL: https://www.semanticscholar.org/paper/a5e1ddccfa7d333834c4d32be123c71bfd573f83
• DOI: 10.3390/cimb48040422
• PMID: 42042082
• PMCID: 13114623
• Summary: A comprehensive framework to provide a comprehensive framework to facilitate precise diagnosis and individualized treatment strategies, ultimately advancing precision medicine in the management of Bartter syndrome is provided.
• Evidence snippets:
• Snippet 1 (score: 0.364) > Molecular genetic research on Bartter syndrome has made remarkable strides, elucidating the principal BS genes SLC12A1, KCNJ1, CLCNKB, BSND, and MAGED2 and their corresponding protein defects, thereby refining the molecular framework of disease classification while separating CaSR-associated Bartter-like disease from the core canonical BS spectrum. This progress has significantly deepened our understanding of the underlying pathophysiology and provided an essential framework for correlating genotypes with clinical phenotypes. However, the intricate relationship between genetic mutations and clinical manifestations remains complex and multifaceted, reflecting the profound heterogeneity of the syndrome. Addressing these diagnostic challenges and refining disease classification beyond traditional clinical criteria requires an integrative approach that seamlessly balances high-throughput sequencing technologies with rigorous functional studies. > The mechanisms by which these genetic mutations lead to protein dysfunction are diverse, encompassing critical defects in protein expression, impaired membrane localization, and direct functional impairments. Notably, aberrant protein folding, endoplasmic reticulum-associated degradation (ERAD), and splicing abnormalities have emerged as critical pathogenic pathways. These mechanistic insights not only enhance our fundamental understanding of the disease but also highlight highly promising therapeutic targets. While current treatments remain predominantly symptomatic, focusing primarily on managing electrolyte imbalances and associated complications, they inherently fail to address the underlying molecular defects driving the disease. > The precise identification of specific molecular defects opens innovative avenues for the development of targeted interventions aimed at correcting or compensating for specific protein abnormalities. For instance, molecular chaperones that assist in protein folding, agents that modulate aberrant splicing, and future gene-based strategies represent important experimental directions for mechanism-based therapy. Consequently, the future of Bartter syndrome management may increasingly move toward precision medicine tailored to the molecular pathology of individual patients. However, the transition from concept to clinical implementation will require substantial additional functional, translational, and trial-level evidence. Such mechanism-based strategies promise not only to alleviate clinical symptoms but to fundamentally modify disease progression, thereby drastically improving long-term prognosis and quality of life for patients.

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

• Authors: W. Tulalamba, T. Janvilisri
• Year: 2012
• Venue: International Journal of Cell Biology
• URL: https://www.semanticscholar.org/paper/307cb9186444d9dad6e2e3b53763be0de76de186
• DOI: 10.1155/2012/594681
• PMID: 22500174
• PMCID: 3303613
• Citations: 96
• Influential citations: 5
• Summary: The molecular signaling pathways in the NPC are discussed for the holistic view of NPC development and progression and the important insights toward NPC pathogenesis may offer strategies for identification of novel biomarkers for diagnosis and prognosis.
• Evidence snippets:
• Snippet 1 (score: 0.363) > In the pregenomic eras, highly integrated and complex circuitry of molecular signaling in NPC pathogenesis was only partially understood. Over the past decade, the knowledge of the molecular mechanisms in NPC carcinogenesis has been rapidly accumulated. Dysregulation and abnormal protein expression of molecules in certain signaling pathways involved in cellular functions including proliferation, adhesion, survival, and apoptosis has been demonstrated in the NPC cells. Detailed information on the complex network in signaling pathway leading to a coordinated pattern of gene expression and regulation in NPC will undoubtedly provide important clues to develop novel prognostic and therapeutic strategies for this cancer. Refining molecular markers into clinically relevant assays may assist in the detection of NPC in asymptomatic patients, as well as stage classification and monitoring disease progression and treatments. Furthermore, selective regulation of particular proteins targeting cancer cell proliferation, invasion, and apoptosis is a hopeful prospect for future anticancer therapy that slow disease progression and improve survival.

[13] 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: 0.362) > 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.

[14] Integrating multi-omics and machine learning strategies to explore the “gene-protein-metabolite” network in ischemic heart failure with Qi deficiency and blood stasis syndrome

• Authors: Jingjing Wei, Aolong Wang, Peng Yu, Yang Sun, Wenjun Wu et al.
• Year: 2025
• Venue: Chinese Medicine
• URL: https://www.semanticscholar.org/paper/8694948133c11b52a604b21e8d2cdeef641b2819
• DOI: 10.1186/s13020-025-01151-9
• PMID: 40671145
• PMCID: 12269143
• Citations: 4
• Summary: This study provides a comprehensive characterization of the molecular features of QXXY syndrome in IHF patients, highlighting key pathways and biomarkers linked to energy metabolism dysregulation, chronic inflammation, and coagulation abnormalities.
• Evidence snippets:
• Snippet 1 (score: 0.360) > Recent advancements in multi-omics technologies, including transcriptomics, proteomics, and metabolomics, have revolutionized the exploration of molecular mechanisms underlying complex diseases. By integrating these approaches, it is possible to construct comprehensive "gene-protein-metabolite" networks that capture the intricate interactions driving disease progression [7]. These networks can unveil key biomarkers and pathways associated with specific disease phenotypes, offering novel insights into disease mechanisms and potential therapeutic targets. In recent years, the integration of multi-omics methodologies and computational biology has garnered significant attention for elucidating the mechanisms of TCM syndromes. For instance, Jie Wang et al. employed an integrated strategy combining RNA-seq, data-independent acquisition (DIA) proteomics, and untargeted metabolomics to analyze 90 clinical samples of coronary heart disease, constructing a "geneprotein-metabolite" network for coronary heart disease with phlegm and blood stasis syndrome [8]. Similarly, Weidong Zhang et al. utilized a combined approach of proteomics, metabolomics, and network pharmacology to systematically investigate the biological basis of two TCM syndromes in coronary heart disease: Cold Congealing and Qi Stagnation (CCQS) and Qi Stagnation and Blood Stasis (QSBS) [9]. Despite these advancements, significant challenges persist in understanding QXXY syndrome in IHF, including reliance on singleomics approaches, limited depth of studies, inability to cross-validate findings, and insufficient validation of conclusions. Collectively, a multi-omics approach holds immense potential to elucidate the molecular signatures of QXXY syndrome, thereby bridging the gap between TCM theory and modern biomedical science. > In this study, we employed an integrated multi-omics strategy combined with computational biology to investigate the biological basis of QXXY syndrome in IHF patients. We enrolled 100 participants, comprising 40 IHF patients with QXXY syndrome (IHF-QXXY), 40 IHF patients without QXXY syndrome (IHF-NQXXY), and 20 healthy controls (HC).

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

• Authors: C. Çubuk, F. Can, M. Peña-Chilet, J. Dopazo
• Year: 2020
• Venue: Cells
• URL: https://www.semanticscholar.org/paper/e40f7a3b8f72ba01374ba00fbf308a47a3fa5dd4
• DOI: 10.3390/cells9071579
• PMID: 32610626
• PMCID: 7408716
• Citations: 9
• Summary: Despite the existence of differences in gene expression across numerous genes between males and females having been known for a long time, these have been mostly ignored in many studies, including drug development and its therapeutic use. In fact, the consequences of such differences over the disease mechanisms or the drug action mechanisms are completely unknown. Here we applied mechanistic mathematical models of signaling activity to reveal the ultimate functional consequences that gender-s...
• Evidence snippets:
• Snippet 1 (score: 0.357) > Therefore, a proper interpretation of the effect that differences in gene expression have over phenotypes, such as drug response or disease progression, involves understanding the mechanisms of the disease or the mode of action of drugs, which can be interpreted through mechanistic models of cell signaling [12] or cell metabolism [13]. Mechanistic models have helped to understand the disease mechanisms behind different cancers [14,15], including neuroblastoma [16,17], breast cancer [18], rare diseases [19], complex diseases [20], the mechanisms of action of drugs [21,22], and other biologically interesting scenarios such as the molecular mechanisms that explain how stress-induced activation of brown adipose tissue prevents obesity [23] or the molecular mechanisms of death and the post-mortem ischemia of a tissue [24]. Among the few available proposals of mechanistic modeling algorithms that model different aspects of signaling pathway activity, Hipathia has demonstrated having superior sensitivity and specificity [12]. > Here, we propose the use of mechanistic models [13,14] of signaling activity related with cancer hallmarks [25], other cancer-related signaling pathways, and some extra relevant cellular functions to understand the functional consequences of the gender bias in gene expression. Such mechanistic models use gene expression data to produce an estimation of profiles of signaling or metabolic circuit activity within pathways [13,14]. An interesting property of mechanistic models is that they can be used not only to understand molecular mechanisms of disease or of drug action but also to predict the potential consequences of gene perturbations over the circuit activity in a given condition [26]. Actually, in a recent work, our group has successfully predicted therapeutic targets in cancer cell lines with a precision over 60% [15]. Therefore, we will use this mechanistic framework to understand what is the molecular basis of the different effects of cancer drugs by directly simulating their effect in the patients. This approach has recently been used by us to understand the generation of resistances in cancer at the single cell level in glioblastoma [27].

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

• Authors: K. Lourida, G. Louridas
• Year: 2022
• Venue: Cardiogenetics
• URL: https://www.semanticscholar.org/paper/3960806730c4c1115f527e22d6d0a76536570ec5
• DOI: 10.3390/cardiogenetics12020015
• Citations: 4
• Influential citations: 1
• Summary: Only by understanding the complexity of chronic heart diseases and explaining the interrelationship between different interconnected biological networks can the probability for clinical phenotypes reversal be increased.
• Evidence snippets:
• Snippet 1 (score: 0.356) > Treatment with ACEIs, ARBs, and β-blockers impedes deterioration of myocardial function as well as clinical deterioration caused by the deleterious impact of the compensatory systems [58,59]. Therefore, the therapy with ACEIs, ARBs, and β-blockers is the appropriate therapy to block LV remodeling and HF progression and reduce symptoms and/or mortality [55]. > In general, the HF syndrome demonstrates a modular construction with predictable behavior of functional clinical phenotypes having a strong impact on biological networks from epigenetic, cellular to regulatory systems [18]. The importance of individual genes for the pathogenesis and clinical progression of the HF syndrome is restricted to the hypertrophic and dilated cardiomyopathies. It seems that some HF patients have a complex multigenic inheritance, but the importance of individual genes is limited. In contrast, the significant role of epigenetics, proteomics, and metabolomics is increased; but, the complete genetic network system and the interactions between multiomics systems are still uncertain [60]. Multimodal systems that include genetic networks, multiomics, metabolic pathways, environmental factors, and sophisticated disease-related clinical networks are required to be integrated and provide a new holistic and realistic picture. > Significant breakthroughs have been made to understand many of the pathophysiological mechanisms of HFrEF but the natural pathophysiological history and clinical progression of HFpEF still remains inadequately defined [39]. The subclinical progression of pre-clinical diastolic dysfunction (PDD) of LV "to clinical phenotype of HFpEF and the further clinical progression to some more complex clinical models with multi-organ involvement . . . continue to be poorly understood" [40]. Prospective studies are expected to clarify the natural history and clinical progression of HFpEF and define the LV remodeling mechanisms involved. The pathophysiology of LV systolic dysfunction is different to the diastolic dysfunction, as systolic dysfunction is considered a disease of calcium handling and diastolic dysfunction is regarded as a disease of increased myofilament sensitivity to calcium [61][62][63].

[17] The Potential of iPSCs for the Treatment of Premature Aging Disorders

• Authors: C. Compagnucci, E. Bertini
• Year: 2017
• Venue: International Journal of Molecular Sciences
• URL: https://www.semanticscholar.org/paper/581917de0fd4d572ad6df509124da8c3de3e0c3c
• DOI: 10.3390/ijms18112350
• PMID: 29112121
• PMCID: 5713319
• Citations: 12
• Influential citations: 2
• Summary: Modeling premature aging with induced pluripotent stem cells (iPSCs) offers the possibility to study these disorders during self-renewal and differentiation into relevant cell types, and allows researchers to understand pathophysiological mechanisms and enables the performance of drug screenings.
• Evidence snippets:
• Snippet 1 (score: 0.355) > Premature aging disorders including Hutchinson-Gilford progeria syndrome (HGPS) and Werner syndrome, are a group of rare monogenic diseases leading to reduced lifespan of the patients. Importantly, these disorders mimic several features of physiological aging. Despite the interest on the study of these diseases, the underlying biological mechanisms remain unknown and no treatment is available. Recent studies on HGPS (due to mutations of the LMNA gene encoding for the nucleoskeletal proteins lamin A/C) have reported disruptions in cellular and molecular mechanisms modulating genomic stability and stem cell populations, thus giving the nuclear lamina a relevant function in nuclear organization, epigenetic regulation and in the maintenance of the stem cell pool. In this context, modeling premature aging with induced pluripotent stem cells (iPSCs) offers the possibility to study these disorders during self-renewal and differentiation into relevant cell types. iPSCs generated by cellular reprogramming from adult somatic cells allows researchers to understand pathophysiological mechanisms and enables the performance of drug screenings. Moreover, the recent development of precision genome editing offers the possibility to study the complex mechanisms underlying senescence and the possibility to correct disease phenotypes, paving the way for future therapeutic interventions.

[18] Advancing the understanding of autism disease mechanisms through genetics

• Authors: Luis de la Torre-Ubieta, H. Won, J. Stein, D. Geschwind
• Year: 2016
• Venue: Nature medicine
• URL: https://www.semanticscholar.org/paper/a9f29d6ab53873fd50b1e65e64cd36d9447c1a9d
• DOI: 10.1038/nm.4071
• PMID: 27050589
• PMCID: 5072455
• Citations: 761
• Influential citations: 8
• Summary: Current understanding of the genetic architecture of ASD is reviewed and genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology are integrated.
• Evidence snippets:
• Snippet 1 (score: 0.355) > stem cell models suggest that abnormalities in neurogenesis, cell fate, neuronal morphogenesis and synaptic function contribute to the pathogenesis of ASD ( Table 2 and Supplementary Table 3). Transcriptomic studies in these models point to dysregulation in specific molecular processes that may be driving pathogenesis, including chromatin modifications, RNA-splicing, Wnt signaling and Ca 2+ signaling [96][97][98][99] . A small number of drugs, including insulin-like growth factor 1 (IGF1) and roscovitine, have been used to reverse phenotypes associated with Rett syndrome, Timothy syndrome and Phelan-McDermid syndrome (PMDS) in hiPSC models [99][100][101][102] (Table 2). Although promising, human in vitro studies using neurons derived from stem cells have focused on syndromic ASD variants, and thus, modeling of idiopathic ASD 103 and ASD-associated de novo variants will be crucial to obtain a comprehensive picture of phenotypic overlap and potential, convergent disease mechanisms. A further challenge to in vitro studies is that it is not currently certain what the most relevant cellular and physiological ASD phenotypes are that need to be modeled in vitro. > Several molecular or cellular mechanisms of ASD pathophysiology have multiple lines of supporting evidence from studies in humans or model systems ( Table 3). Most of these mechanisms are individually quite broad and considerable work is needed to refine these models to targetable molecular pathways. Furthermore, these mechanisms are not entirely distinct. Indeed, the same genes or molecular pathways contribute to several of these processes at different points during development (Fig. 2), and it is not always clear how early developmental dysfunction relates to later events. An important caveat is that we only have a limited knowledge of the specific genetic contributions to autism susceptibility,

[19] Modeling psychiatric disorders: from genomic findings to cellular phenotypes

• Authors: Anna Falk, Vivi M. Heine, A. Harwood, Patrick F. Sullivan, M. Peitz et al.
• Year: 2016
• Venue: Molecular Psychiatry
• URL: https://www.semanticscholar.org/paper/235b41240d78140de7ab06a3ad8a7d0b1bdff1a5
• DOI: 10.1038/mp.2016.89
• PMID: 27240529
• PMCID: 4995546
• Citations: 83
• Influential citations: 2
• Summary: The challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes are critically reviewed.
• Evidence snippets:
• Snippet 1 (score: 0.353) > The key challenge for iPSC-based disease modeling is to identify one or more relevant cellular phenotypes that accurately represent the disease pathophysiology. Increasing numbers of reports have demonstrated that for many diseases specific pathophysiology can be captured in human iPSC-based disease models. These range from cardiovascular disease, 44,45 cancer, 46,47 ocular disease, 48,49 diabetes mellitus 50,51 and neurological disorders of the brain. 52,53 Can the same approach be applied to complex psychiatric disorders? > The problem is that almost all psychiatric disorders are characterized by clinical signs and symptoms, but lack independent verification from objective biomarkers. Thus, how might these clinical phenotypes manifest themselves in terms of cell behavior? The identity of robust cellular 'readouts', which typify any psychiatric disorder, is a crucial unsolved problem and an area of intense study 54 (Table 2). When satisfactorily answered, this will herald a new degree of biological objectivity and quantification for the study of psychiatric disorders. > The aim is to find a single or small number of cell phenotypes or parameters that strongly associate with psychiatric disorders, and establish a cellular profile characteristic of cells derived from the general patient population. Although a consensus set of cellular phenotypes for psychiatric disorder is yet to be established, we can define some of their desired characteristics. First, cellular phenotypes have to relate to the biological pathways identified by genetics. Second, although there are many risk genes in disparate biological pathways, at some level, phenotypes should converge onto a much smaller grouping. Third, phenotypes need to be quantifiable. Finally, to be useful for drug development cellular phenotypes should be reversed by pharmacological treatment, although not necessarily by drugs in current use. > Although human iPSC-based approaches underrepresent the complexity of the human central nervous system, cellular phenotypes are likely to lie more proximal to molecular disease mechanisms than phenotypes seen at the level of a tissue or organism, 55 and thus may bypass compensatory homeostatic (2) Gene expression profiles of SCZ human iPSC neurons identified altered expression of many components of the cyclic AMP and WNT signaling pathways.

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

• Authors: F. Iheagwam, A. J. Joseph, E. D. Adedoyin, Olawumi Toyin Iheagwam, Samuel Akpoyowvare Ejoh
• Year: 2025
• Venue: Pathophysiology
• URL: https://www.semanticscholar.org/paper/dbf8042761c1a5fc50f8cd894cc498505abac7cb
• DOI: 10.3390/pathophysiology32010009
• PMID: 39982365
• PMCID: 12077258
• Citations: 36
• Summary: This review aims to elucidate the complex link between mitochondrial dysfunction and diabetes, covering the spectrum of diabetes types, the role of mitochondria in insulin resistance, highlighting pathophysiological mechanisms, mitochondrial DNA damage, and altered mitochondrial biogenesis and dynamics.
• Evidence snippets:
• Snippet 1 (score: 0.352) > The landscape of DM research is continuously evolving, with emerging technologies and approaches offering new insights into the pathophysiology of the disease and potential therapeutic targets. Advancements in omics technologies, encompassing genomes, transcriptomics, proteomics, and metabolomics, have transformed the molecular mechanisms underlying DM [134]. High-throughput sequencing techniques enable comprehensive analysis of genetic variants, gene expression profiles, protein abundance, and metabolite levels associated with DM and its complications [135]. Single-cell omics approaches provide unprecedented resolution and granularity, allowing researchers to dissect cellular heterogeneity and identify novel cell types, subpopulations, and signalling pathways involved in DM pathogenesis. Integrating multi-omics data sets offers a systems-level perspective of DM, unravelling complex networks of molecular interactions and regulatory circuits underlying disease progression [136]. > In addition to omics technologies, advances in imaging modalities, such as MRI, PET, and optical imaging, enable non-invasive visualisation and quantification of metabolic, functional, and structural changes. Molecular imaging probes targeting specific biomarkers and metabolic pathways provide valuable insights into disease mechanisms and treatment responses in preclinical and clinical settings [85]. Despite significant progress in DM research, numerous unanswered questions and knowledge gaps persist, hindering the ability to develop effective prevention and treatment strategies. Key areas requiring further investigation include the role of epigenetics, environmental factors, and the microbiome in DM susceptibility and progression. Moreover, the interaction between environmental cues and genetic predisposition remains incompletely understood, highlighting the need for comprehensive multi-omics studies and large-scale epidemiological analyses to identify gene-environment interactions and modifiable risk factors for DM [137]. Furthermore, the heterogeneity of DM phenotypes and clinical outcomes poses a challenge for personalised medicine approaches, necessitating robust biomarkers and predictive models to stratify patients based on disease subtypes, prognosis, and treatment response [138].

Notes

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

1. Disease Information

Overview

Alpha-gal syndrome (AGS) is an IgE-mediated allergic disorder characterized by delayed hypersensitivity reactions to the oligosaccharide galactose-alpha-1,3-galactose (alpha-gal), a carbohydrate found in non-primate mammalian tissues, meat products, dairy, gelatin, and mammalian-derived medications (wilson2024tickbitesige pages 1-3, macdougall2022themeatof pages 1-2). Unlike conventional food allergies targeting proteins, AGS is uniquely directed against a carbohydrate epitope and features a characteristic delay of 2–6 hours between allergen ingestion and symptom onset (wilson2024tickbitesige pages 1-3, vazrodrigues2022currentandfuture pages 1-2). The syndrome was first recognized when patients experienced severe anaphylaxis upon infusion of cetuximab, a monoclonal antibody produced in mouse-derived cell lines, and subsequent investigation linked the sensitization to tick bites (propst2025alphagalsyndromeand pages 1-2). AGS is now recognized as the tenth most common food allergy in the United States, with an estimated 450,000 cases nationally (choudhary2025singlecellmrnaanalysis pages 1-2).

Key Identifiers

• ICD-10: The MeSH term "red meat allergy" (C000655084) is associated with AGS in clinical trial registrations (NCT06268717 chunk 2). A dedicated ICD-10 code was not widely available until recently; AGS lacked a dedicated diagnostic billing code, contributing to underdiagnosis (wilson2024tickbitesige pages 3-4).
• OMIM: No dedicated OMIM entry (AGS is an acquired, not a Mendelian, condition).
• MONDO: Not indexed.
• Synonyms: Red meat allergy, mammalian meat allergy, alpha-gal allergy, tick-induced meat allergy, galactose-alpha-1,3-galactose allergy.

Data Source

Information is derived primarily from aggregated disease-level resources (clinical reviews, cohort studies, case series) and clinical trial registrations, with single-cell profiling data from individual patient samples.

2. Etiology

Disease Causal Factors

AGS is an acquired immunological disorder. The primary causal factor is sensitization to alpha-gal through bites of hard-bodied (ixodid) ticks, particularly Amblyomma americanum (lone star tick) in the southeastern United States (wilson2024tickbitesige pages 1-3, macdougall2022themeatof pages 2-4). Tick saliva contains alpha-gal residues on glycoproteins and glycolipids and other biomolecules such as prostaglandin E2, which, upon injection into the host during blood feeding, initiate an IgE-mediated immune response to alpha-gal (vazrodrigues2022currentandfuture pages 1-2). Tick saliva interferes with dendritic cell maturation, suppressing pro-inflammatory Th1/Th17 responses while promoting Th2 pro-allergic responses, which drives the production of alpha-gal-specific IgE by B cells (macdougall2022themeatof pages 2-4).

The alpha-gal carbohydrate is synthesized by the enzyme alpha-1,3-galactosyltransferase (encoded by the GGTA1 gene), which is functional in non-primate mammals but is a non-functional pseudogene in humans due to mutations accumulated over approximately 28 million years of evolution (cabezascruz2019environmentalandmolecular pages 1-2, wilson2024tickbitesige pages 3-4). This makes alpha-gal a foreign antigen highly immunogenic in humans (kepley2025tickedoffallergic pages 1-2).

Risk Factors

Genetic/Intrinsic Risk Factors: - ABO blood type: Persons with blood type B are approximately one-fourth as likely to have AGS compared to blood type O, as the B-antigen is structurally similar to alpha-gal (sharing terminal galactoses connected by alpha-1,3 bonds) and may confer cross-protective immune tolerance (taylor2024intrinsicriskfactors pages 6-8, wilson2024tickbitesige pages 3-4). Individuals with A and O blood types have higher AGS risk (macdougall2022themeatof pages 4-5). - Race/ethnicity: White individuals showed higher seroconversion rates (6.6%) compared to Black (1.0%) and Hispanic (1.5%) populations in a military cohort, which may be partly attributable to differential distribution of protective B blood type alleles (taylor2024intrinsicriskfactors pages 6-8). - Atopy and childhood allergies: AGS case patients were significantly more likely to report childhood allergies that resolved in adulthood, family history of AGS (OR 8.33), family history of food allergies (OR 2.70), and vitamin D deficiency (taylor2024intrinsicriskfactors pages 1-3, taylor2024intrinsicriskfactors pages 5-6). - Heightened insect bite reactivity: Longer healing times for insect bites or stings (taylor2024intrinsicriskfactors pages 1-3). - Sex: Male sex has been identified as a risk factor for both sensitization and clinical AGS, though in case-control analyses, sex did not always reach significance when accounting for occupational exposure (macdougall2022themeatof pages 4-5).

Environmental Risk Factors: - Tick exposure: The predominant risk factor. 86% of diagnosed AGS patients report tick bite history (binder2023clinicalandlaboratory pages 1-1). Frequent tick exposure confers greater sensitization risk than single prolonged exposure (propst2025alphagalsyndromeand pages 1-2). - Outdoor occupation/activities: Forestry workers, rural workers, military personnel in outdoor occupations, hunters, and gardeners have elevated sensitization rates (nalcacı2024mysteriousallergycaused pages 6-7). Infantry/law enforcement personnel showed 12.7% seroconversion vs. 1.2% for administrative personnel (Ching et al. 2024). - Rural residence: Higher sensitization rates in rural versus urban areas (macdougall2022themeatof pages 4-5). - Cofactors: Alcohol consumption and exercise can potentiate allergic responses and lower the threshold for reactions (binder2023clinicalandlaboratory pages 2-2, propst2025alphagalsyndromeand pages 2-3).

Protective Factors

• Blood type B: Expression of the B-antigen is the best-studied non-tick protective factor. Structural similarity between alpha-gal and B-blood group antigen may provide cross-reactive immune tolerance (wilson2024tickbitesige pages 3-4).
• IgG4 antibodies: Higher levels of alpha-gal-specific IgG4 are associated with tolerance; AGS patients show reduced IgG4 compared to non-allergic alpha-gal-sensitized individuals (macdougall2022themeatof pages 2-4, carson2022where’sthebeef? pages 3-4).
• Tick avoidance: Long-term tick bite avoidance (1–2 years) may allow tolerance recovery and permit meat reintroduction (vazrodrigues2022currentandfuture pages 6-7).

Gene–Environment Interactions

The interplay between the non-functional human GGTA1 pseudogene (making alpha-gal foreign) and environmental tick bite exposure is the fundamental gene–environment interaction underlying AGS. Furthermore, intrinsic genetic factors influencing immune polarization (Th2 tendency, atopic constitution) interact with tick salivary components to determine whether an individual develops clinical AGS or remains asymptomatically sensitized (taylor2024intrinsicriskfactors pages 1-3, taylor2024intrinsicriskfactors pages 5-6).

3. Phenotypes

The clinical presentation of AGS is diverse and often delayed, making diagnosis challenging. The following table summarizes major phenotypic features:

Table: This table summarizes the major clinical phenotypes of Alpha-gal Syndrome, including suggested HPO terms, approximate frequencies, timing, severity, and clinically useful notes. It is useful for structuring phenotype annotations in a disease knowledge base.

Key Phenotypic Features

• Delayed onset: The hallmark of AGS is symptom onset 2–6 hours (sometimes up to 8 hours) after ingestion of mammalian meat, unlike conventional IgE-mediated food allergies that present within minutes (wilson2024tickbitesige pages 1-3, nalcacı2024mysteriousallergycaused pages 1-2).
• Urticaria and anaphylaxis: In a large US cohort, 75% of patients met anaphylaxis criteria involving ≥2 organ systems (binder2023clinicalandlaboratory pages 2-2, binder2023clinicalandlaboratory pages 1-1). Anaphylaxis occurs in up to 60% of AGS cases (vazrodrigues2022currentandfuture pages 1-2).
• Gastrointestinal symptoms: GI manifestations (abdominal pain, nausea, vomiting, diarrhea) are often predominant or isolated and can mimic irritable bowel syndrome, causing significant diagnostic delay (propst2025alphagalsyndromeand pages 1-2, macdougall2022themeatof pages 10-11). Dairy-reactive patients show higher GI symptom rates (79%) compared to dairy-tolerant patients (59%) (binder2023clinicalandlaboratory pages 2-2).
• Quality of life: A study of 28 patients found a mean diagnosis delay of 7.1 years, with over half experiencing anaphylaxis requiring emergency treatment and some requiring multiple hospitalizations. Food avoidance affects social eating and family interactions, and anxiety about potential anaphylaxis is common (macdougall2022themeatof pages 11-13).

Suggested HPO Terms

• HP:0001025 (Urticaria), HP:0011844 (Anaphylaxis), HP:0100665 (Angioedema), HP:0000989 (Pruritus), HP:0002027 (Abdominal pain), HP:0002018 (Nausea), HP:0002013 (Vomiting), HP:0002014 (Diarrhea), HP:0002615 (Hypotension), HP:0002098 (Respiratory distress)

4. Genetic/Molecular Information

Causal Gene: GGTA1

AGS is not a Mendelian genetic disease but rather an acquired immunological condition. However, the evolutionary loss of GGTA1 function in humans is the molecular prerequisite. The GGTA1 gene encodes alpha-1,3-galactosyltransferase (HGNC:4319), the enzyme responsible for synthesizing the alpha-gal epitope on glycoproteins and glycolipids. In humans and Old World primates, GGTA1 is a pseudogene that produces only truncated transcripts lacking the two catalytic exons needed for enzyme activity (cabezascruz2019environmentalandmolecular pages 1-2). At least two separate mutations account for this loss of function, accumulated over ~28 million years (wilson2024tickbitesige pages 3-4). Non-primate mammals, New World monkeys, and platyrrhine primates retain a functional GGTA1 gene (carson2022where’sthebeef? pages 1-3).

Immunoglobulin Gene Rearrangements

Single-cell analysis has revealed that alpha-gal-specific IgE is secreted by a heterogeneous population of B cells, including CCR6-proficient memory B cells and CCR6-deficient plasmablasts/plasma cells. Individual B cells were found to express IgE-secreting transcripts alongside other immunoglobulin classes (IgA, IgG, IgM), suggesting a unique pattern of Ig gene arrangements and class switching (choudhary2025singlecellmrnaanalysis pages 1-2, choudhary2025singlecellmrnaanalysis pages 14-17).

No Pathogenic Variants or Chromosomal Abnormalities

AGS does not involve pathogenic variants in the traditional clinical genetics sense. The disease is acquired through environmental exposure (tick bites), and susceptibility is modulated by ABO blood group genotype and atopic predisposition rather than by mutations in a single causative gene.

5. Environmental Information

Environmental Factors

• Tick bites are the primary environmental trigger, with multiple tick species implicated globally (see Tick Species table below).
• Medications and medical products containing alpha-gal represent significant iatrogenic exposure risks, including heparin, gelatin-containing vaccines, cetuximab, surgifoam, lidocaine patches, and bioprosthetic heart valves (macdougall2022themeatof pages 10-11, leder2024perioperativeconsiderationsin pages 3-5, commins2020diagnosis&management pages 16-18).

Lifestyle Factors

• Alcohol consumption and exercise are known cofactors that potentiate allergic reactions (binder2023clinicalandlaboratory pages 2-2, propst2025alphagalsyndromeand pages 2-3).
• Outdoor recreation, hunting, fishing, and gardening increase tick exposure risk (taylor2024intrinsicriskfactors pages 6-8, taylor2024intrinsicriskfactors pages 5-6).

Infectious Agents

Tick bites are the sensitizing event. The following table summarizes tick species associated with AGS worldwide:

Table: This table summarizes tick species reported in the literature as implicated in alpha-gal sensitization or alpha-gal syndrome across major world regions. It is useful for mapping geographic risk and understanding regional differences in AGS epidemiology.

6. Mechanism / Pathophysiology

Sensitization Phase (Tick Bite → IgE Production)

The causal chain begins with tick attachment and blood feeding. Tick saliva contains alpha-gal on glycoproteins and glycolipids, along with immunomodulatory molecules including prostaglandin E2 (vazrodrigues2022currentandfuture pages 1-2). Tick saliva interferes with dendritic cell maturation, suppressing Th1/Th17 responses while favoring Th2 pro-allergic polarization (macdougall2022themeatof pages 2-4). Antigen-presenting cells (dendritic cells, macrophages, B cells) present alpha-gal to Th2 cells, which produce IL-4 and IL-13, driving B cell class switching to IgE (vazrodrigues2022currentandfuture pages 1-2). Repeated tick bites strengthen the Th2 signal (platts‐mills2025theimmunologyof pages 11-13). Notably, all humans produce natural IgG, IgM, and IgA antibodies to alpha-gal from gastrointestinal bacterial exposure, but IgE production is the pathological consequence of tick-mediated sensitization (wilson2024tickbitesige pages 1-3, carson2022where’sthebeef? pages 3-4).

Effector Phase (Meat Ingestion → Delayed Allergic Reaction)

Upon consumption of mammalian meat, alpha-gal glycolipids cross the intestinal epithelial barrier and are incorporated into chylomicrons in lacteals, entering systemic circulation approximately one hour post-ingestion (platts‐mills2025theimmunologyof pages 11-13). Over 2–6 hours, chylomicrons (300–1000 nm) are progressively metabolized to VLDL and LDL particles (12–25 nm), which carry alpha-gal on their surface glycosylation (platts‐mills2025theimmunologyof pages 11-13). These smaller LDL particles can extravasate through endothelial walls into tissue compartments where they encounter mast cells bearing alpha-gal-specific IgE on FcεRI receptors. Alpha-gal on LDL cross-links surface-bound IgE, triggering mast cell and basophil degranulation and release of histamine, leukotrienes, and tryptase (platts‐mills2025theimmunologyof pages 11-13, branicka2025alphagalsyndrome—aseries pages 4-6). Basophil activation peaks approximately 4 hours after meat consumption, correlating with clinical symptom appearance (macdougall2022themeatof pages 2-4, carson2022where’sthebeef? pages 9-11). AGS patients also show significant differences in lipid metabolism, with delayed lipid processing contributing to the prolonged interval between ingestion and reaction (carson2022where’sthebeef? pages 8-9, kepley2025tickedoffallergic pages 7-8).

Molecular Pathways

• Th2 immune signaling: IL-4, IL-13 → IgE class switching (GO:0045191)
• FcεRI signaling: IgE cross-linking → mast cell/basophil degranulation (GO:0038095)
• Lipid metabolism and chylomicron processing: GO:0034370 (triglyceride-rich lipoprotein particle remodeling)
• Antigen presentation: Enhanced MHC-II expression (GO:0019882)

Cell Types Involved

• Mast cells (CL:0000097) — primary effector cells in tissue
• Basophils (CL:0000767) — primary effector cells in circulation
• Th2 CD4+ T cells (CL:0000546) — orchestrate IgE class switching
• iNKT cells (CL:0000911) — elevated in AGS; 2.5-fold higher activated CD69+ iNKT frequency (carson2022where’sthebeef? pages 6-8)
• NKB cells — hybrid phenotype expressing NK cytolytic molecules and B cell markers (choudhary2025singlecellmrnaanalysis pages 17-18)
• Mast cell progenitors — circulating population unique to AGS patients (choudhary2025singlecellmrnaanalysis pages 1-2, choudhary2025singlecellmrnaanalysis pages 17-18)
• B cells/plasmablasts — heterogeneous IgE-producing population including CCR6+ memory B cells (choudhary2025singlecellmrnaanalysis pages 1-2)
• Dendritic cells (CL:0000451) — antigen presentation, modulated by tick saliva

Cardiovascular Associations

Alpha-gal sensitization has been associated with noncalcified plaque, obstructive coronary artery disease, and ST-segment-elevated myocardial infarction (propst2025alphagalsyndromeand pages 7-8). Chronic IgE-mediated inflammation from bioprosthetic valve implantation (containing alpha-gal) may contribute to early valve degradation and accelerated coronary artery disease (kuravi2022allergicresponseto pages 1-2, kuravi2022allergicresponseto pages 6-9).

Molecular Profiling

Single-cell analysis (Choudhary & Commins, 2025): Multimodal single-cell RNA transcriptome and surface protein analysis of PBMCs from 18 AGS and 10 control subjects captured 437,770 total cells and identified 43 distinct immune cell clusters (choudhary2025singlecellmrnaanalysis pages 4-5). Key findings include: - Circulating mast cell progenitors (cluster C43) with 53-fold elevated TPSAB1/tryptase and 8-fold elevated KIT expression (choudhary2025singlecellmrnaanalysis pages 8-11) - CD4+-NKT cells predominantly from AGS subjects (96% in cluster C32) linked to Th2 responses (choudhary2025singlecellmrnaanalysis pages 17-18) - 1,141 IgE-secreting cells containing 11,017 IgE transcripts identified (choudhary2025singlecellmrnaanalysis pages 14-17) - Elevated S100A9, IFITM3, and THBS1 across multiple cell types in AGS subjects (choudhary2025singlecellmrnaanalysis pages 17-18) - Enhanced antigen presentation genes: CD52, CXCL16, HLA-DPA1, HLA-DRA, ICAM1, IFITM3, LAP3, THBS1 (choudhary2025singlecellmrnaanalysis pages 8-11)

7. Anatomical Structures Affected

Organ Level

• Primary: Skin (urticaria, angioedema), gastrointestinal tract (abdominal pain, nausea, vomiting, diarrhea), cardiovascular system (anaphylaxis-associated hypotension)
• Secondary: Cardiovascular system (noncalcified plaque, coronary artery disease), respiratory system (during anaphylaxis)
• Body systems: Immune system, integumentary system, digestive system, cardiovascular system, respiratory system

Tissue and Cell Level

• Skin — dermal mast cells (CL:0000097)
• Gastrointestinal mucosa — mucosal mast cells, eosinophils (CL:0000771)
• Vascular endothelium — sites of LDL extravasation and mast cell activation
• Bone marrow — mast cell progenitors

Subcellular Level

• Endosomes/lysosomes (GO:0005764) — alpha-gal glycoprotein processing
• Cell surface (GO:0009986) — FcεRI receptor complexes
• Secretory granules (GO:0030141) — mast cell/basophil degranulation

UBERON Terms

• UBERON:0002097 (skin of body), UBERON:0001555 (digestive tract), UBERON:0000948 (heart), UBERON:0002107 (liver)

8. Temporal Development

Onset

• Age of onset: Typically adult-onset; median age at onset is 53 years in a US cohort (binder2023clinicalandlaboratory pages 1-1). The condition can develop at any age following tick sensitization (propst2025alphagalsyndromeand pages 1-2).
• Onset pattern: Subacute to chronic; sensitization develops following repeated tick bites, often over months to years. Mean diagnostic delay is 7.1 years from symptom onset (macdougall2022themeatof pages 11-13).

Progression

• Disease course: Episodic, with reactions triggered by exposure to alpha-gal-containing foods or products.
• Duration: Chronic but potentially reversible. Alpha-gal sIgE generally decreases over time with tick avoidance, though complete resolution was observed in only 1 of 13 patients in longitudinal follow-up (binder2023clinicalandlaboratory pages 8-8). Long-term tick avoidance (1–2 years) may allow tolerance recovery (vazrodrigues2022currentandfuture pages 6-7).
• Severity modulation: Fattier meals lead to more consistent reactions; exercise, alcohol, and repeated tick bites can increase severity (propst2025alphagalsyndromeand pages 2-3).

9. Inheritance and Population

Epidemiology

• Estimated prevalence (USA): Approximately 450,000 cases nationally; approximately 2–5 cases per 100,000 persons reported, though county-level estimates suggest much higher prevalence (wilson2024tickbitesige pages 3-4, choudhary2025singlecellmrnaanalysis pages 1-2).
• Sensitization rates: 22% of North Carolina endoscopy patients; 20.8% of a Tennessee asymptomatic cohort; 35% among German forest workers/hunters (though only 8.6% of the German cohort reported clinical symptoms) (binder2023clinicalandlaboratory pages 2-2, binder2023clinicalandlaboratory pages 2-3).
• Seroconversion incidence (military): 4.9% seroconversion rate over a mean 3.4-year interval among 2,821 initially seronegative military personnel (Ching et al. 2024).
• Global distribution: Cases documented on every continent except Antarctica, with highest prevalence in the southeastern United States, Sweden, Australia, South Africa, and Germany (macdougall2022themeatof pages 4-5, wilson2024tickbitesige pages 3-4).
• Search volume trends: Google search volume for alpha-gal increased by an estimated 627% from 2015 to 2022, with an average annual percent change of 33.78% (Romeiser et al. 2024).

Inheritance Pattern

AGS is not inherited in a Mendelian fashion. It is an acquired immunological condition. However, familial clustering has been observed—AGS patients are 8.33 times more likely to report relatives with AGS (taylor2024intrinsicriskfactors pages 5-6)—which may reflect shared genetic predisposition (atopy, blood type), shared environmental exposures (tick habitat), and increased diagnostic awareness within families.

Population Demographics

• Sex ratio: 56% female in one cohort (binder2023clinicalandlaboratory pages 1-1); higher seroconversion in males (5.5% vs 1.9%) likely due to occupational exposure differences (Ching et al. 2024).
• Race: 95% White in a US cohort (binder2023clinicalandlaboratory pages 1-1). White individuals showed significantly higher seroconversion (6.6%) than Black (1.0%) or Hispanic (1.5%) individuals, partly attributable to differential B blood type frequency (taylor2024intrinsicriskfactors pages 6-8).
• Geographic: Southeastern and Coastal Atlantic US states are the epicenter in the USA, corresponding to A. americanum distribution (wilson2024tickbitesige pages 3-4).

10. Diagnostics

Clinical Tests

• Alpha-gal-specific IgE (sIgE): The primary diagnostic biomarker. Titers ≥0.1 IU/mL (or kU/L) are considered positive, though elevated sIgE alone does not confirm clinical AGS—clinical history is essential (binder2023clinicalandlaboratory pages 2-3, macdougall2022themeatof pages 1-2).
• Skin prick test (SPT): Wheal and flare responses to alpha-gal-containing extracts (macdougall2022themeatof pages 4-5).
• Basophil activation test (BAT): Measures CD63 activation on peripheral blood basophils stimulated with mammalian-based extracts; peak activation at ~4 hours post-meat ingestion (vazrodrigues2022currentandfuture pages 1-2, macdougall2022themeatof pages 2-4).
• Oral food challenge (OFC): The gold standard but carries anaphylaxis risk; double-blind, placebo-controlled food challenges are used in research settings, including novel challenges using alpha-gal knockout pork (NCT06268717 chunk 1, NCT07611435 chunk 1).
• Serum tryptase: Marker for mast cell degranulation, elevated in only 30% of AGS patients (macdougall2022themeatof pages 4-5).
• Total IgE: Often elevated in AGS patients.

Emerging Diagnostic Tools

• Mast cell activation test (MAT), histamine-release (HR) assay, omics technologies, and model-based reasoning (MBR) are under investigation (vazrodrigues2022currentandfuture pages 1-2).

Clinical Criteria

Diagnosis is based on: (1) compatible clinical history of delayed allergic reactions to mammalian meat/products, (2) elevated alpha-gal-specific IgE, and (3) exclusion of alternative diagnoses. No universally standardized diagnostic criteria exist (binder2023clinicalandlaboratory pages 2-3).

Differential Diagnosis

• Irritable bowel syndrome (for GI-predominant AGS)
• Chronic spontaneous urticaria
• Idiopathic anaphylaxis
• Systemic mastocytosis
• Non-celiac gluten sensitivity
• Lactose intolerance
• Other food allergies

11. Outcome / Prognosis

Mortality and Morbidity

AGS can be life-threatening when anaphylaxis occurs, but mortality data are limited. The primary morbidity includes recurrent allergic reactions, dietary restriction, quality of life impairment, and diagnostic delay (macdougall2022themeatof pages 11-13). AGS is a leading cause of anaphylaxis in southeastern US adults and adolescents (macdougall2022themeatof pages 4-5).

Disease Course

• Natural history: With strict tick avoidance, alpha-gal sIgE generally decreases over time, though complete resolution occurs infrequently (binder2023clinicalandlaboratory pages 8-8). Long-term avoidance of tick bites (1–2 years) may allow tolerance recovery and gradual meat reintroduction (vazrodrigues2022currentandfuture pages 6-7).
• Dietary response: Approximately 80% of patients achieve symptom resolution with mammalian meat elimination alone, and an additional 15% require dairy removal (macdougall2022themeatof pages 7-8).
• Prognostic factors: Higher alpha-gal sIgE titers correlate with greater severity; patients who tolerate dairy generally have better prognosis for remission (macdougall2022themeatof pages 8-10).

12. Treatment

Pharmacotherapy

• Avoidance diet (MAXO:0000004 — dietary modification): The cornerstone of treatment. Patients must avoid mammalian meat (beef, pork, lamb), dairy products (for some), gelatin, and other alpha-gal-containing products. Safe alternatives include poultry, fish, and plant-based proteins (propst2025alphagalsyndromeand pages 4-5, macdougall2022themeatof pages 7-8).
• Epinephrine (MAXO:0000587): Intramuscular epinephrine auto-injectors for emergency anaphylaxis management. Intravenous epinephrine with fluid resuscitation for shock patients (vazrodrigues2022currentandfuture pages 6-7).
• Antihistamines: Oral antihistamines (hydroxyzine, cetirizine, desloratadine, diphenhydramine, fexofenadine) for urticaria and angioedema (vazrodrigues2022currentandfuture pages 7-8, propst2025alphagalsyndromeand pages 4-5).
• Corticosteroids: Prednisone, methylprednisolone for more severe allergic reactions (vazrodrigues2022currentandfuture pages 7-8).
• Cromolyn sodium: Oral mast cell stabilizer for gastrointestinal symptoms (macdougall2022themeatof pages 7-8, vazrodrigues2022currentandfuture pages 7-8).
• Omalizumab (anti-IgE monoclonal antibody): Binds free serum IgE, reduces availability to mast cells/basophils, increases reaction threshold; some patients on omalizumab were able to reintroduce restricted foods (macdougall2022themeatof pages 7-8, vazrodrigues2022currentandfuture pages 7-8). Notably, omalizumab is produced in CHO cell lines and contains no detectable alpha-gal (macdougall2022themeatof pages 10-11).
• Metformin: Some patients on metformin were able to reintroduce restricted foods, though the mechanism is unclear (macdougall2022themeatof pages 7-8).

Advanced/Experimental Therapeutics

• Oral immunotherapy (OIT): Case reports show successful beef desensitization in adults (27-day protocol) and children (24-day protocol), achieving tolerance of 100–120 g beef daily. Sustained daily consumption is required to maintain desensitization. A pilot study demonstrated cow's milk containing 6 mg alpha-gal daily was safely tolerated over 3 years (macdougall2022themeatof pages 8-10). No FDA-approved OIT exists for AGS.
• Nanoparticle immunotherapy: Nanoparticles encapsulating alpha-gal glycoprotein reduced Th2 cytokine production and IgE formation in prophylactic mouse models, though therapeutic administration showed only partial efficacy (propst2025alphagalsyndromeand pages 4-5).
• Mast cell-directed therapy: A Phase 2 trial (NCT07526558) is testing ketotifen + cromolyn + fexofenadine vs. fexofenadine alone for post-tick bite illness including AGS (NCT07526558 chunk 1).
• Alpha-gal knockout pork: Clinical trials are evaluating pork from GGTA1-knockout pigs as a safe food alternative and diagnostic control (NCT06268717, NCT07611435) (NCT06268717 chunk 1, NCT07611435 chunk 1).

Perioperative Management

Patients with AGS require careful perioperative medication review. Many common anesthetic and surgical products contain mammalian-derived alpha-gal, including heparin, gelatin-based hemostatic agents (surgifoam), gelatin capsules, propofol (glycerol content), and bioprosthetic heart valves (leder2024perioperativeconsiderationsin pages 3-5, leder2024perioperativeconsiderationsin pages 2-3, leder2024perioperativeconsiderationsin pages 1-2). Preoperative steroids and antihistamines are recommended before high-dose heparin exposure, and alternative anticoagulants (sodium citrate) should be considered (commins2020diagnosis&management pages 16-18, leder2024perioperativeconsiderationsin pages 2-3). 24–50% of AGS patients undergoing cardiac surgery with cardiopulmonary bypass experienced severe allergic reactions (leder2024perioperativeconsiderationsin pages 2-3). Intravenous formulations are generally safer than oral formulations due to fewer mammalian-derived fillers (leder2024perioperativeconsiderationsin pages 7-9).

Clinical Trials

The following table summarizes active and completed clinical trials for AGS:

Table: This table summarizes the main clinical trials identified for alpha-gal syndrome and related post-tick bite illness. It is useful for quickly comparing study design, status, enrollment, and the main research focus of each trial.

13. Prevention

Primary Prevention

• Tick bite avoidance: The most critical prevention strategy. Recommended measures include protective clothing treated with permethrin, prompt tick removal with specialized forceps, and use of tick repellents (vazrodrigues2022currentandfuture pages 6-7).
• Public awareness: Provider knowledge of AGS remains limited; inclusion of AGS content in medical school curricula is recommended (Thompson et al. 2025).

Secondary Prevention

• Early diagnosis: Clinicians should suspect AGS in patients with adult-onset atopy, idiopathic anaphylaxis, insect bite hypersensitivity, or delayed reactions to red meat (taylor2024intrinsicriskfactors pages 1-3).
• Alpha-gal sIgE testing: Should be performed in at-risk individuals with compatible symptoms.
• Dietary counseling: Dietician consultation recommended for identifying hidden alpha-gal ingredients in processed foods, supplements, and medications (propst2025alphagalsyndromeand pages 4-5).

Tertiary Prevention

• Continued tick avoidance: Essential to prevent disease severity escalation and allow potential IgE decline (propst2025alphagalsyndromeand pages 4-5, binder2023clinicalandlaboratory pages 8-8).
• Medication review: Comprehensive review of all medications for mammalian-derived ingredients (leder2024perioperativeconsiderationsin pages 1-2).
• Emergency preparedness: Epinephrine auto-injector prescription and patient education on anaphylaxis management.

14. Other Species / Natural Disease

Tick Species and Cross-Species Biology

Alpha-gal is widely expressed in non-primate mammals (including cows, pigs, sheep, deer), bacteria, and parasites including ticks (wilson2024tickbitesige pages 1-3). The alpha-gal epitope is synthesized by functional alpha-1,3-galactosyltransferase in these organisms. Tick galactosyltransferases are involved in synthesizing alpha-gal in tick tissues and saliva (cabezascruz2019environmentalandmolecular pages 1-2). N-glycome profiling and proteome analysis have demonstrated alpha-gal antigens in salivary gland extracts and saliva of A. americanum and Ixodes scapularis, but not in Amblyomma maculatum (sharma2024tickbiteinducedalphagal pages 1-2).

Zoonotic/Vector-Borne Considerations

AGS is fundamentally a vector-borne allergic disease. The sensitization pathway is unique in that it involves an arthropod vector (tick) but is not an infectious disease. The clinical syndrome is dependent on subsequent exposure to mammalian-derived products, making it a complex interface of ectoparasite biology and human immunology.

15. Model Organisms

AGKO Mouse Model

The primary animal model is the alpha-gal knockout (AGKO) mouse, which has a targeted disruption of alpha-1,3-galactosyltransferase and therefore cannot produce alpha-gal, mimicking the human condition (sharma2024tickbiteinducedalphagal pages 1-2). In this model: - A. americanum nymph infestation induced significant increases in total IgE, IgG1, and alpha-gal IgG1 antibody titers compared to A. maculatum-sensitized mice (sharma2024tickbiteinducedalphagal pages 1-2). - Pork challenge in A. americanum-sensitized AGKO mice led to body temperature decline (anaphylaxis-like response) (sharma2024tickbiteinducedalphagal pages 1-2). - Gene expression analysis revealed A. americanum bites direct mouse immunity toward Th2 polarization (sharma2024tickbiteinducedalphagal pages 1-2).

In Vitro Models

• Humanized cell lines and primary cultures using human sera and novel human alpha-gal-specific IgE monoclonal antibodies are used to study allergic effector cell activation (kepley2025tickedoffallergic pages 1-2).
• Nanoparticle immunotherapy has been tested in mouse models showing reduction in Th2 cytokines and alpha-gal-specific IgE with prophylactic treatment (choudhary2025singlecellmrnaanalysis pages 1-2).

Model Limitations

• AGKO mice do not fully recapitulate all features of human AGS, particularly the delayed reaction kinetics and the complexity of human lipid metabolism.
• Species-specific differences in tick-host interactions may limit translational applicability.

Summary of Key Ontology Terms

• MONDO: Not indexed for AGS
• HPO: HP:0001025 (Urticaria), HP:0011844 (Anaphylaxis), HP:0100665 (Angioedema), HP:0000989 (Pruritus), HP:0002027 (Abdominal pain), HP:0002018 (Nausea/vomiting), HP:0002014 (Diarrhea)
• GO Biological Process: GO:0045191 (regulation of isotype switching to IgE), GO:0038095 (Fc-epsilon receptor signaling), GO:0034370 (triglyceride-rich lipoprotein particle remodeling), GO:0019882 (antigen processing and presentation)
• CL (Cell Ontology): CL:0000097 (mast cell), CL:0000767 (basophil), CL:0000546 (T-helper 2 cell), CL:0000911 (iNKT cell), CL:0000451 (dendritic cell)
• UBERON: UBERON:0002097 (skin), UBERON:0001555 (digestive tract), UBERON:0000948 (heart)
• CHEBI: CHEBI:59517 (galactose-alpha-1,3-galactose), CHEBI:16042 (histamine), CHEBI:17855 (tryptase)
• MAXO: MAXO:0000004 (dietary modification), MAXO:0000587 (epinephrine administration), MAXO:0001001 (allergen avoidance)
• Gene: GGTA1 (HGNC:4319) — pseudogene in humans; functional in non-primate mammals

Key References

This report draws from 17 primary research publications and 4 clinical trial registrations, including comprehensive reviews in Allergy (Wilson et al. 2024), Journal of Immunology (Carson et al. 2022), ImmunoTargets and Therapy (Macdougall et al. 2022), Immunological Reviews (Platts-Mills et al. 2025), Frontiers in Immunology (Sharma et al. 2024; Choudhary & Commins 2025), and clinical data from the CDC-affiliated cohort study published in Allergy (Binder et al. 2023) and the case-control study in Annals of Allergy, Asthma & Immunology (Taylor et al. 2024).

References

1. (wilson2024tickbitesige pages 1-3): Jeffrey M. Wilson, Loren Erickson, Michael Levin, Samuel M. Ailsworth, Scott P. Commins, and Thomas A. E. Platts‐Mills. Tick bites, ige to galactose-alpha-1,3-galactose and urticarial or anaphylactic reactions to mammalian meat: the alpha-gal syndrome. Allergy, 79:1440-1454, Jan 2024. URL: https://doi.org/10.1111/all.16003, doi:10.1111/all.16003. This article has 72 citations and is from a highest quality peer-reviewed journal.

2. (macdougall2022themeatof pages 1-2): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

3. (vazrodrigues2022currentandfuture pages 1-2): Rita Vaz-Rodrigues, Lorena Mazuecos, and José de la Fuente. Current and future strategies for the diagnosis and treatment of the alpha-gal syndrome (ags). Journal of Asthma and Allergy, 15:957-970, Jul 2022. URL: https://doi.org/10.2147/jaa.s265660, doi:10.2147/jaa.s265660. This article has 70 citations and is from a peer-reviewed journal.

4. (propst2025alphagalsyndromeand pages 1-2): Susan B. H. Propst and Dorothea K. Thompson. Alpha-gal syndrome and the gastrointestinal reaction: a narrative review. Frontiers in Allergy, Jan 2025. URL: https://doi.org/10.3389/falgy.2025.1535103, doi:10.3389/falgy.2025.1535103. This article has 13 citations and is from a peer-reviewed journal.

5. (choudhary2025singlecellmrnaanalysis pages 1-2): Shailesh K. Choudhary and Scott P. Commins. Single-cell mrna analysis and surface marker expression profiling of circulating immune cells in humans with alpha-gal syndrome. Frontiers in Immunology, Sep 2025. URL: https://doi.org/10.3389/fimmu.2025.1629310, doi:10.3389/fimmu.2025.1629310. This article has 2 citations and is from a peer-reviewed journal.

6. (NCT06268717 chunk 2): GI Alpha-Gal Study. University of North Carolina, Chapel Hill. 2023. ClinicalTrials.gov Identifier: NCT06268717

7. (wilson2024tickbitesige pages 3-4): Jeffrey M. Wilson, Loren Erickson, Michael Levin, Samuel M. Ailsworth, Scott P. Commins, and Thomas A. E. Platts‐Mills. Tick bites, ige to galactose-alpha-1,3-galactose and urticarial or anaphylactic reactions to mammalian meat: the alpha-gal syndrome. Allergy, 79:1440-1454, Jan 2024. URL: https://doi.org/10.1111/all.16003, doi:10.1111/all.16003. This article has 72 citations and is from a highest quality peer-reviewed journal.

8. (macdougall2022themeatof pages 2-4): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

9. (cabezascruz2019environmentalandmolecular pages 1-2): Alejandro Cabezas-Cruz, Adnan Hodžić, Patricia Román-Carrasco, Lourdes Mateos-Hernández, Georg Gerhard Duscher, Deepak Kumar Sinha, Wolfgang Hemmer, Ines Swoboda, Agustín Estrada-Peña, and José de la Fuente. Environmental and molecular drivers of the α-gal syndrome. Frontiers in Immunology, May 2019. URL: https://doi.org/10.3389/fimmu.2019.01210, doi:10.3389/fimmu.2019.01210. This article has 84 citations and is from a peer-reviewed journal.

10. (kepley2025tickedoffallergic pages 1-2): Christopher L. Kepley, Yinghui Wang, Amy Yelton, Eva R. Siebert, and Onyinye I. Iweala. Ticked off: allergic effector cells in the pathogenesis of alpha-gal syndrome. Current Allergy and Asthma Reports, Nov 2025. URL: https://doi.org/10.1007/s11882-025-01237-2, doi:10.1007/s11882-025-01237-2. This article has 3 citations and is from a peer-reviewed journal.

11. (taylor2024intrinsicriskfactors pages 6-8): Marissa L. Taylor, Gilbert J. Kersh, Johanna S. Salzer, Emma S. Jones, Alison M. Binder, Paige A. Armstrong, Shailesh K. Choudhary, Grace K. Commins, Claire L. Amelio, Brad J. Biggerstaff, Charles B. Beard, Lyle R. Petersen, and Scott P. Commins. Intrinsic risk factors for alpha-gal syndrome in a case-control study, 2019 to 2020. Annals of Allergy, Asthma & Immunology, 132:759-764.e2, Jun 2024. URL: https://doi.org/10.1016/j.anai.2024.01.029, doi:10.1016/j.anai.2024.01.029. This article has 23 citations.

12. (macdougall2022themeatof pages 4-5): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

13. (taylor2024intrinsicriskfactors pages 1-3): Marissa L. Taylor, Gilbert J. Kersh, Johanna S. Salzer, Emma S. Jones, Alison M. Binder, Paige A. Armstrong, Shailesh K. Choudhary, Grace K. Commins, Claire L. Amelio, Brad J. Biggerstaff, Charles B. Beard, Lyle R. Petersen, and Scott P. Commins. Intrinsic risk factors for alpha-gal syndrome in a case-control study, 2019 to 2020. Annals of Allergy, Asthma & Immunology, 132:759-764.e2, Jun 2024. URL: https://doi.org/10.1016/j.anai.2024.01.029, doi:10.1016/j.anai.2024.01.029. This article has 23 citations.

14. (taylor2024intrinsicriskfactors pages 5-6): Marissa L. Taylor, Gilbert J. Kersh, Johanna S. Salzer, Emma S. Jones, Alison M. Binder, Paige A. Armstrong, Shailesh K. Choudhary, Grace K. Commins, Claire L. Amelio, Brad J. Biggerstaff, Charles B. Beard, Lyle R. Petersen, and Scott P. Commins. Intrinsic risk factors for alpha-gal syndrome in a case-control study, 2019 to 2020. Annals of Allergy, Asthma & Immunology, 132:759-764.e2, Jun 2024. URL: https://doi.org/10.1016/j.anai.2024.01.029, doi:10.1016/j.anai.2024.01.029. This article has 23 citations.

15. (binder2023clinicalandlaboratory pages 1-1): Alison M. Binder, Dena Cherry‐Brown, Brad J. Biggerstaff, Emma S. Jones, Claire L. Amelio, Charles B. Beard, Lyle R. Petersen, Gilbert J. Kersh, Scott P. Commins, and Paige A. Armstrong. Clinical and laboratory features of patients diagnosed with alpha‐gal syndrome—2010–2019. Allergy, 78:477-487, Oct 2023. URL: https://doi.org/10.1111/all.15539, doi:10.1111/all.15539. This article has 42 citations and is from a highest quality peer-reviewed journal.

16. (nalcacı2024mysteriousallergycaused pages 6-7): Muhammed Nalçacı. Mysterious allergy caused by tick bite: alpha-gal syndrome. Turkiye parazitolojii dergisi, 48 3:195-207, Oct 2024. URL: https://doi.org/10.4274/tpd.galenos.2024.97720, doi:10.4274/tpd.galenos.2024.97720. This article has 7 citations.

17. (binder2023clinicalandlaboratory pages 2-2): Alison M. Binder, Dena Cherry‐Brown, Brad J. Biggerstaff, Emma S. Jones, Claire L. Amelio, Charles B. Beard, Lyle R. Petersen, Gilbert J. Kersh, Scott P. Commins, and Paige A. Armstrong. Clinical and laboratory features of patients diagnosed with alpha‐gal syndrome—2010–2019. Allergy, 78:477-487, Oct 2023. URL: https://doi.org/10.1111/all.15539, doi:10.1111/all.15539. This article has 42 citations and is from a highest quality peer-reviewed journal.

18. (propst2025alphagalsyndromeand pages 2-3): Susan B. H. Propst and Dorothea K. Thompson. Alpha-gal syndrome and the gastrointestinal reaction: a narrative review. Frontiers in Allergy, Jan 2025. URL: https://doi.org/10.3389/falgy.2025.1535103, doi:10.3389/falgy.2025.1535103. This article has 13 citations and is from a peer-reviewed journal.

19. (carson2022where’sthebeef? pages 3-4): Audrey S. Carson, Aliyah Gardner, and Onyinye I. Iweala. Where’s the beef? : understanding allergic responses to red meat in alpha-gal syndrome. Journal of immunology (Baltimore, Md. : 1950), 208:267-277, Jan 2022. URL: https://doi.org/10.4049/jimmunol.2100712, doi:10.4049/jimmunol.2100712. This article has 47 citations.

20. (vazrodrigues2022currentandfuture pages 6-7): Rita Vaz-Rodrigues, Lorena Mazuecos, and José de la Fuente. Current and future strategies for the diagnosis and treatment of the alpha-gal syndrome (ags). Journal of Asthma and Allergy, 15:957-970, Jul 2022. URL: https://doi.org/10.2147/jaa.s265660, doi:10.2147/jaa.s265660. This article has 70 citations and is from a peer-reviewed journal.

21. (macdougall2022themeatof pages 10-11): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

22. (nalcacı2024mysteriousallergycaused pages 1-2): Muhammed Nalçacı. Mysterious allergy caused by tick bite: alpha-gal syndrome. Turkiye parazitolojii dergisi, 48 3:195-207, Oct 2024. URL: https://doi.org/10.4274/tpd.galenos.2024.97720, doi:10.4274/tpd.galenos.2024.97720. This article has 7 citations.

23. (propst2025alphagalsyndromeand pages 7-8): Susan B. H. Propst and Dorothea K. Thompson. Alpha-gal syndrome and the gastrointestinal reaction: a narrative review. Frontiers in Allergy, Jan 2025. URL: https://doi.org/10.3389/falgy.2025.1535103, doi:10.3389/falgy.2025.1535103. This article has 13 citations and is from a peer-reviewed journal.

24. (leder2024perioperativeconsiderationsin pages 3-5): John Leder, Anna Diederich, Bhavik Patel, Mark Bowie, Christian M Renwick, and Venkat Mangunta. Perioperative considerations in alpha-gal syndrome: a review. Cureus, Jan 2024. URL: https://doi.org/10.7759/cureus.53208, doi:10.7759/cureus.53208. This article has 16 citations.

25. (NCT07611435 chunk 1): Beginning to Assess an Appropriate CONtrol for Oral Food Challenges in Alpha-Gal Syndrome (CoFAR-13) - BeACON4AG. National Institute of Allergy and Infectious Diseases (NIAID). 2026. ClinicalTrials.gov Identifier: NCT07611435

26. (macdougall2022themeatof pages 11-13): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

27. (carson2022where’sthebeef? pages 1-3): Audrey S. Carson, Aliyah Gardner, and Onyinye I. Iweala. Where’s the beef? : understanding allergic responses to red meat in alpha-gal syndrome. Journal of immunology (Baltimore, Md. : 1950), 208:267-277, Jan 2022. URL: https://doi.org/10.4049/jimmunol.2100712, doi:10.4049/jimmunol.2100712. This article has 47 citations.

28. (choudhary2025singlecellmrnaanalysis pages 14-17): Shailesh K. Choudhary and Scott P. Commins. Single-cell mrna analysis and surface marker expression profiling of circulating immune cells in humans with alpha-gal syndrome. Frontiers in Immunology, Sep 2025. URL: https://doi.org/10.3389/fimmu.2025.1629310, doi:10.3389/fimmu.2025.1629310. This article has 2 citations and is from a peer-reviewed journal.

29. (commins2020diagnosis&management pages 16-18): Scott P. Commins. Diagnosis & management of alpha-gal syndrome: lessons from 2,500 patients. Jul 2020. URL: https://doi.org/10.1080/1744666x.2020.1782745, doi:10.1080/1744666x.2020.1782745. This article has 114 citations and is from a peer-reviewed journal.

30. (sharma2024tickbiteinducedalphagal pages 1-2): Surendra Raj Sharma, Shailesh K. Choudhary, Julia Vorobiov, Scott P. Commins, and Shahid Karim. Tick bite-induced alpha-gal syndrome and immunologic responses in an alpha-gal deficient murine model. Frontiers in Immunology, Feb 2024. URL: https://doi.org/10.3389/fimmu.2023.1336883, doi:10.3389/fimmu.2023.1336883. This article has 28 citations and is from a peer-reviewed journal.

31. (platts‐mills2025theimmunologyof pages 6-8): Thomas A. E. Platts‐Mills, Roopesh Singh Gangwar, Lisa Workman, and Jeffrey M. Wilson. The immunology of alpha‐gal syndrome: history, tick bites, ige, and delayed anaphylaxis to mammalian meat. Immunological Reviews, Jun 2025. URL: https://doi.org/10.1111/imr.70035, doi:10.1111/imr.70035. This article has 19 citations and is from a domain leading peer-reviewed journal.

32. (platts‐mills2025theimmunologyof pages 11-13): Thomas A. E. Platts‐Mills, Roopesh Singh Gangwar, Lisa Workman, and Jeffrey M. Wilson. The immunology of alpha‐gal syndrome: history, tick bites, ige, and delayed anaphylaxis to mammalian meat. Immunological Reviews, Jun 2025. URL: https://doi.org/10.1111/imr.70035, doi:10.1111/imr.70035. This article has 19 citations and is from a domain leading peer-reviewed journal.

33. (branicka2025alphagalsyndrome—aseries pages 4-6): Olga Branicka, Lesia Rozłucka, Radosław Gawlik, and Joanna Glück. Alpha-gal syndrome—a series of cases with different clinical pictures. International Journal of Molecular Sciences, 26:8601, Sep 2025. URL: https://doi.org/10.3390/ijms26178601, doi:10.3390/ijms26178601. This article has 0 citations.

34. (carson2022where’sthebeef? pages 9-11): Audrey S. Carson, Aliyah Gardner, and Onyinye I. Iweala. Where’s the beef? : understanding allergic responses to red meat in alpha-gal syndrome. Journal of immunology (Baltimore, Md. : 1950), 208:267-277, Jan 2022. URL: https://doi.org/10.4049/jimmunol.2100712, doi:10.4049/jimmunol.2100712. This article has 47 citations.

35. (carson2022where’sthebeef? pages 8-9): Audrey S. Carson, Aliyah Gardner, and Onyinye I. Iweala. Where’s the beef? : understanding allergic responses to red meat in alpha-gal syndrome. Journal of immunology (Baltimore, Md. : 1950), 208:267-277, Jan 2022. URL: https://doi.org/10.4049/jimmunol.2100712, doi:10.4049/jimmunol.2100712. This article has 47 citations.

36. (kepley2025tickedoffallergic pages 7-8): Christopher L. Kepley, Yinghui Wang, Amy Yelton, Eva R. Siebert, and Onyinye I. Iweala. Ticked off: allergic effector cells in the pathogenesis of alpha-gal syndrome. Current Allergy and Asthma Reports, Nov 2025. URL: https://doi.org/10.1007/s11882-025-01237-2, doi:10.1007/s11882-025-01237-2. This article has 3 citations and is from a peer-reviewed journal.

37. (carson2022where’sthebeef? pages 6-8): Audrey S. Carson, Aliyah Gardner, and Onyinye I. Iweala. Where’s the beef? : understanding allergic responses to red meat in alpha-gal syndrome. Journal of immunology (Baltimore, Md. : 1950), 208:267-277, Jan 2022. URL: https://doi.org/10.4049/jimmunol.2100712, doi:10.4049/jimmunol.2100712. This article has 47 citations.

38. (choudhary2025singlecellmrnaanalysis pages 17-18): Shailesh K. Choudhary and Scott P. Commins. Single-cell mrna analysis and surface marker expression profiling of circulating immune cells in humans with alpha-gal syndrome. Frontiers in Immunology, Sep 2025. URL: https://doi.org/10.3389/fimmu.2025.1629310, doi:10.3389/fimmu.2025.1629310. This article has 2 citations and is from a peer-reviewed journal.

39. (kuravi2022allergicresponseto pages 1-2): Kasinath V. Kuravi, Lori T. Sorrells, Joseph R. Nellis, Farzana Rahman, Anneke H. Walters, Robert G. Matheny, Shailesh K. Choudhary, David L. Ayares, Scott P. Commins, John R. Bianchi, and Joseph W. Turek. Allergic response to medical products in patients with alpha-gal syndrome. The Journal of Thoracic and Cardiovascular Surgery, 164:e411-e424, Dec 2022. URL: https://doi.org/10.1016/j.jtcvs.2021.03.100, doi:10.1016/j.jtcvs.2021.03.100. This article has 72 citations.

40. (kuravi2022allergicresponseto pages 6-9): Kasinath V. Kuravi, Lori T. Sorrells, Joseph R. Nellis, Farzana Rahman, Anneke H. Walters, Robert G. Matheny, Shailesh K. Choudhary, David L. Ayares, Scott P. Commins, John R. Bianchi, and Joseph W. Turek. Allergic response to medical products in patients with alpha-gal syndrome. The Journal of Thoracic and Cardiovascular Surgery, 164:e411-e424, Dec 2022. URL: https://doi.org/10.1016/j.jtcvs.2021.03.100, doi:10.1016/j.jtcvs.2021.03.100. This article has 72 citations.

41. (choudhary2025singlecellmrnaanalysis pages 4-5): Shailesh K. Choudhary and Scott P. Commins. Single-cell mrna analysis and surface marker expression profiling of circulating immune cells in humans with alpha-gal syndrome. Frontiers in Immunology, Sep 2025. URL: https://doi.org/10.3389/fimmu.2025.1629310, doi:10.3389/fimmu.2025.1629310. This article has 2 citations and is from a peer-reviewed journal.

42. (choudhary2025singlecellmrnaanalysis pages 8-11): Shailesh K. Choudhary and Scott P. Commins. Single-cell mrna analysis and surface marker expression profiling of circulating immune cells in humans with alpha-gal syndrome. Frontiers in Immunology, Sep 2025. URL: https://doi.org/10.3389/fimmu.2025.1629310, doi:10.3389/fimmu.2025.1629310. This article has 2 citations and is from a peer-reviewed journal.

43. (binder2023clinicalandlaboratory pages 8-8): Alison M. Binder, Dena Cherry‐Brown, Brad J. Biggerstaff, Emma S. Jones, Claire L. Amelio, Charles B. Beard, Lyle R. Petersen, Gilbert J. Kersh, Scott P. Commins, and Paige A. Armstrong. Clinical and laboratory features of patients diagnosed with alpha‐gal syndrome—2010–2019. Allergy, 78:477-487, Oct 2023. URL: https://doi.org/10.1111/all.15539, doi:10.1111/all.15539. This article has 42 citations and is from a highest quality peer-reviewed journal.

44. (binder2023clinicalandlaboratory pages 2-3): Alison M. Binder, Dena Cherry‐Brown, Brad J. Biggerstaff, Emma S. Jones, Claire L. Amelio, Charles B. Beard, Lyle R. Petersen, Gilbert J. Kersh, Scott P. Commins, and Paige A. Armstrong. Clinical and laboratory features of patients diagnosed with alpha‐gal syndrome—2010–2019. Allergy, 78:477-487, Oct 2023. URL: https://doi.org/10.1111/all.15539, doi:10.1111/all.15539. This article has 42 citations and is from a highest quality peer-reviewed journal.

45. (NCT06268717 chunk 1): GI Alpha-Gal Study. University of North Carolina, Chapel Hill. 2023. ClinicalTrials.gov Identifier: NCT06268717

46. (macdougall2022themeatof pages 7-8): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

47. (macdougall2022themeatof pages 8-10): Jessica D Macdougall, Kevin O Thomas, and Onyinye I Iweala. The meat of the matter: understanding and managing alpha-gal syndrome. ImmunoTargets and Therapy, 11:37-54, Sep 2022. URL: https://doi.org/10.2147/itt.s276872, doi:10.2147/itt.s276872. This article has 71 citations.

48. (propst2025alphagalsyndromeand pages 4-5): Susan B. H. Propst and Dorothea K. Thompson. Alpha-gal syndrome and the gastrointestinal reaction: a narrative review. Frontiers in Allergy, Jan 2025. URL: https://doi.org/10.3389/falgy.2025.1535103, doi:10.3389/falgy.2025.1535103. This article has 13 citations and is from a peer-reviewed journal.

49. (vazrodrigues2022currentandfuture pages 7-8): Rita Vaz-Rodrigues, Lorena Mazuecos, and José de la Fuente. Current and future strategies for the diagnosis and treatment of the alpha-gal syndrome (ags). Journal of Asthma and Allergy, 15:957-970, Jul 2022. URL: https://doi.org/10.2147/jaa.s265660, doi:10.2147/jaa.s265660. This article has 70 citations and is from a peer-reviewed journal.

50. (NCT07526558 chunk 1): Mast Cell Treatment in Post-tick Bite Illness (PTBI). University of North Carolina, Chapel Hill. 2026. ClinicalTrials.gov Identifier: NCT07526558

51. (leder2024perioperativeconsiderationsin pages 2-3): John Leder, Anna Diederich, Bhavik Patel, Mark Bowie, Christian M Renwick, and Venkat Mangunta. Perioperative considerations in alpha-gal syndrome: a review. Cureus, Jan 2024. URL: https://doi.org/10.7759/cureus.53208, doi:10.7759/cureus.53208. This article has 16 citations.

52. (leder2024perioperativeconsiderationsin pages 1-2): John Leder, Anna Diederich, Bhavik Patel, Mark Bowie, Christian M Renwick, and Venkat Mangunta. Perioperative considerations in alpha-gal syndrome: a review. Cureus, Jan 2024. URL: https://doi.org/10.7759/cureus.53208, doi:10.7759/cureus.53208. This article has 16 citations.

53. (leder2024perioperativeconsiderationsin pages 7-9): John Leder, Anna Diederich, Bhavik Patel, Mark Bowie, Christian M Renwick, and Venkat Mangunta. Perioperative considerations in alpha-gal syndrome: a review. Cureus, Jan 2024. URL: https://doi.org/10.7759/cureus.53208, doi:10.7759/cureus.53208. This article has 16 citations.

54. (NCT07611435 chunk 2): Beginning to Assess an Appropriate CONtrol for Oral Food Challenges in Alpha-Gal Syndrome (CoFAR-13) - BeACON4AG. National Institute of Allergy and Infectious Diseases (NIAID). 2026. ClinicalTrials.gov Identifier: NCT07611435

55. (NCT07177729 chunk 1): The α-gal Syndrome - Investigating Immune Reactions to Tick Bites. Luxembourg Institute of Health. 2025. ClinicalTrials.gov Identifier: NCT07177729

Artifacts

• Edison artifact artifact-00
• Edison artifact artifact-01
• Edison artifact artifact-02