Disease Phenotype Research Articles

Background Dilated cardiomyopathy (DCM) is one of the leading causes of heart failure and the most common indication for cardiac transplantation in young adults. The clinical spectrum of DCM is heterogeneous, ranging from asymptomatic left ventricular dysfunction to advanced heart failure, arrhythmias, and sudden cardiac death. Methods Whole-exome sequencing (WES) was performed on germline DNA of the index case followed by segregation analysis of the identified variants on family ‘members by Sanger sequencing. Results We identified in the proband, a boy aged of 2-years, heterozygous germline nonsense variant in the TTN gene (c.95008C>T, p.Arg31670*), combined with other nonsense variant in the CTNNA3 gene (c.2023G>T, p.Glu675*). Segregation analysis revealed that both variants co-segregate with the disease phenotype within the family. This is the first report of the co-occurrence of pathogenic/likely pathogenic nonsense variants in TTN and CTNNA3 genes in DCM patients. Conclusions Our findings expand the mutational spectrum of DCM in North African populations and underscore the importance of genetic screening in familial cardiomyopathies.

Sex specific differences in the determinants, occurrence, and distribution of osteoporosis and osteoporotic fractures play a pivotal role in the implementation of timely surveillance, prevention and effective treatment approaches. This review is aimed at synthesizing recently published scientific evidence on disparities in the epidemiology and management of osteoporosis and related fragility fractures in men. Several studies have identified race-, sex-, geographic-, socioeconomic-, and comorbidity-based disparities in osteoporosis care. Over the last decade, the awareness and imperative for identifying osteoporosis in men have increased. Nonetheless, the treatment gap is increasing and osteoporosis in men remains severely underappreciated and undertreated. Fewer studies in men have focused on the factors beyond osteoporosis awareness. Recent data of individuals aged 50 years and older show an alarmingly greater increase in hip fractures in men compared to women. This coupled with the existing knowledge of greater disability burden and excess mortality due to fragility fractures in men is a cause of public health concern. This review offers a comprehensive examination of widespread and profound disparities across the spectrum of osteoporosis care and post-fracture management in men and highlights the considerable health economic aspect of this burden. We call for targeted multifaceted interventions: develop novel methods to engage patients and health professionals, increase screening and treatment of osteoporosis in men, conduct epidemiological studies focused on disease phenotyping and risk factor assessment, studies on the identification of perceptions and barriers to effective screening and treatment, expansion and further evaluation of cost-effective therapies and primary prevention strategies for fractures, implementation of fracture liaison services to address the treatment gap in secondary prevention, and promote inclusivity in outcome studies and therapeutic trials. These interventions are paramount to reduce inequities in osteoporosis care and post-fracture care in men.

Phenylketonuria (PKU), pseudoxanthoma elasticum (PXE) and hereditary tyrosinemia type 1 (HT1) are autosomal recessive disorders linked to the PAH, ABCC6, and FAH and HPD genes, respectively. Here we evaluate the off-target editing profiles of clinical lead guide RNAs (gRNAs) that, when combined with adenine base editors (ABEs), correct the recurrent PAH P281L variant, PAH R408W variant or ABCC6 R1164X variant, or disrupt either of two sites in the HPD gene (a modifier gene of HT1) in human hepatocytes. To mitigate off-target mutagenesis, we systematically screen hybrid gRNAs with DNA nucleotide substitutions. Comprehensive and variant-aware specificity profiling of these hybrid gRNAs reveals dramatically reduced off-target editing and reduced bystander editing in cells. In humanized PAH P281L and ABCC6 R1164X mouse models of PKU and PXE, we show that when formulated in lipid nanoparticles with ABE messenger RNA, selected hybrid gRNAs revert disease phenotypes, reduce off-target editing, increase on-target editing and reduce bystander editing in vivo. These studies highlight the use of hybrid gRNAs to improve the safety and efficiency of adenine base-editing therapies.

Budesonide is a glucocorticoid with strong topical anti-inflammatory properties and minimal systemic effects due to extensive first-pass hepatic metabolism. It is designed for targeted delivery within the gastrointestinal (GI) tract and is available in oral and rectal formulations. Budesonide is indicated for various GI disorders, including Crohn's disease (CD, ulcerative colitis (UC) and eosinophilic oesophagitis (EoE), with specific formulations approved for different disease locations and severities. This narrative review evaluates the pharmacological profile, clinical applications and guideline recommendations surrounding the use of budesonide in both paediatric and adult GI disorders. Evidence from randomised controlled trials and real-world studies supports the efficacy of budesonide in inducing remission in mild to moderate ileocaecal CD. It is recommended by ESPGHAN/ECCO guidelines as a therapeutic alternative in selected paediatric patients when exclusive enteral nutrition is not feasible. In UC, budesonide-multimatrix tablets and rectal foam formulations may be effective for distal and left-sided disease, though they are generally less effective than systemic corticosteroids or 5-aminosalicylic acid and are reserved for patients with contraindications to standard therapies. In EoE, topical swallowed budesonide has shown promising results in inducing clinical and histological remission, with increasing data supporting its use in children. Although budesonide is associated with fewer systemic adverse effects, long-term use may still pose risks such as growth suppression and hypothalamic-pituitary adrenal axis suppression, necessitating careful monitoring. Budesonide offers a valuable treatment option when used in alignment with disease phenotype, formulation properties and patient-specific considerations.

Case-control studies focused on the urinary tract microbiome, or urobiome, have consistently reported significant associations with disease. However, clinical urobiome studies have typically been small, averaging ~50 patients per study. While these sample sizes are sufficient to detect large effect sizes, they have not been able to differentiate disease phenotypes within a larger disease complex (e.g., different types of kidney stones), which have unique etiological origins. Biobanked urine specimens can help fill this void. However, since these specimens were not collected specifically for urobiome studies, they must be validated before drawing any strong conclusions. The objective of this study was to evaluate microbiome data derived from metagenomic analysis of biobanked urine specimens against the following criteria: (i) level of contaminants; (ii) retention of high-quality DNA; (iii) overgrowth of a few dominant bacteria; and (iv) preservation of sex-specific taxa. A total of 174 samples were assessed from biobanked or freshly collected specimens (N = 118 patients total), in addition to multiple positive and negative controls. While there were significant differences in diversity (alpha/beta; P < 0.001) based on whether or not samples were biobanked, these differences can largely be explained by study-specific variation. With these criteria, we find that biobanked urine specimens provide similar data to fresh specimens collected using standardized protocols and can be used for clinical urobiome studies.IMPORTANCEThe urinary tract microbiome, or urobiome, is an emerging field of study that has shown promise as an important contributor to urologic health and disease. However, since this field is relatively new, clinical studies to evaluate the urobiome in the context of urologic disease have been relatively small. The use of biobanked urine specimens would allow for much larger studies to be conducted in a relatively short period of time. However, the use of biobanked urine specimens must first be validated. In this study, we sought to evaluate the use of biobanked urine specimens through multiple metrics, compared to previous studies conducted specifically to assess the impact of the urobiome. Results of our study suggest that biobanked urine specimens produce similar data to urine samples collected under rigorously controlled conditions and can be used in casecontrol studies of urologic conditions.

Background: Systemic Sclerosis (SSc) is a heterogeneous autoimmune disease with variable clinical expression influenced by genetic, environmental, and sex-related factors. Understanding sex-based differences in disease phenotypes and severity can improve personalized management strategies, especially in underrepresented populations. This study aims to explore sex-based differences in disease phenotypes and severity in a population with a distinct genetic background. Materials and Methods: This cross-sectional study included 197 SSc patients (177 females and 20 males) enrolled from 5 tertiary care centres across Egypt. All participants met the 2013 ACR/EULAR classification criteria for SSc and the criteria proposed by LeRoy and Medsger. The demographic, clinical, and serological data were collected and defined according to the previously developed severity score and activity index. Results: This study highlights key sex-related differences in disease severity and management. Egyptian male patients exhibited more severe skin involvement and were more likely to receive more aggressive treatment regimens, including corticosteroids and phosphodiesterase inhibitors. Conversely, female patients demonstrated a higher frequency of moderate general systemic involvement and comparatively lower rates of pulmonary complications. Conclusions: Sex-related differences in Egyptian SSc patients appear limited, suggesting that population-specific genetic and environmental factors may play a more prominent role in disease expression than sex alone.

Nusinersen is a designer drug for spinal muscular atrophy (SMA) and was the first approved treatment for this once deadly disease. It is an antisense oligonucleotide that pairs with a specific locus of the Survival Motor Neuron 2 (SMN2) gene, to modify splicing and generate an increase in full-length SMN2 transcript. This in turn increases expression of survival motor neuron protein, deficiency of which results in motor neuron dysfunction and reduced cellular survival, the principal cause of SMA. Pre-clinical studies of nusinersen in animal models of SMA demonstrated substantial clinical responses and proof-of-concept, leading to successful clinical trials in symptomatic children and then in infants. Nusinersen's favorable safety profile after repeated lumbar intrathecal delivery as well as improvement in motor function and survival resulted in US regulatory approval for SMA in 2016. Other countries have followed with variable coverage policies depending upon age, weight, genotype and/or clinical severity. In the current treatment era, two populations of individuals with SMA exist: symptomatic patients identified in the clinic and pre-symptomatic patients (having no or few early clinical features of disease) largely identified by newborn screening. Real-world experience with nusinersen, the topic of this focused review, presents post-approval data in a broad range of patients beyond those studied in clinical trials. The favorable clinical response and safety profile are discussed, as well as the emerging new phenotypes of disease. Nusinersen, one of three FDA-approved drugs for SMA (as of 2025) remains an important therapeutic consideration for infants, children and adults with SMA.

Primary congenital glaucoma (PCG) is a rare genetic disorder affecting the ocular drainage system, accounting for only 0.01-0.04% blindness related cases. However, its prevalence varies significantly in ethnicities, being higher in populations that practice consanguinity, such as Pakistan where approximately 70% of marriages are consanguineous. This study aimed to investigate the genetic cause of PCG in a large Pakistani family with autosomal recessive inheritance. A large multigenerational family having multiple consanguineous marriages resulting in fifteen affected individuals was recruited for the current study. All relevant clinical information was collected and venous blood drawn for further genetic analysis. The family was subjected to direct sequencing of CYP1B1 which is the most plausible candidate of PCG. The resulting candidate variant was further confirmed using BanII restriction enzyme analysis. The sequence analysis revealed a novel indel (c.862delinsCC) in exon 2 of the CYP1B1 gene, resulting in a frameshift mutation (p.Ala288Profs*39) thereby creating a premature stop codon 39 amino acids downstream. BanII restriction enzyme analysis further confirmed this putative null mutation co-segregating with the disease trait in all the family members of the pedigree. The novel indel, putative null mutation causes PCG related disease phenotypes. This genetic variant has a high penetrance but shows variable expressivity among the affected members of the family. This putative null mutation enhances the mutation spectrum of CYP1B1 globally and from Pakistan in particular.

Asthma is a chronic, heterogeneous disease characterised by airway remodelling, inflammation, and mucus production. Airway macrophages' functions are underpinned by changes in cellular metabolism. The TCA cycle-derived metabolite itaconic acid (whose synthesis is mediated by aconitate decarboxylase) is a master regulator of macrophage function; however, its role during inhaled allergen challenge is not clear. The objective of this study was to define the role of itaconate during inhaled allergen challenge. Sputum metabolite levels were measured in participants with mild allergic asthma undergoing allergen inhalation challenge, and in a second cohort, baseline levels in mild, moderate, and severe asthmatics. Airway inflammation, lung function, and bronchoalveolar lavage metabolite levels were assessed in wild-type and aconitate decarboxylase-deficient mice, or in mice treated with inhaled itaconate. Allergen inhalation in mild asthmatics led to a significant reduction in sputum itaconate. We found no difference in baseline sputum itaconate levels when comparing healthy controls to mild, moderate, or severe asthmatics. Continuous exposure to aeroallergen in wild type and aconitate decarboxylase-deficient mice showed no change in disease phenotype after 48 h, 1, 3, or 5 weeks of allergen exposure. Treatment of house dust mite-exposed mice with inhaled itaconate reduced airway inflammation. Levels of itaconate are altered after allergen challenge in mild asthmatics and in murine models of disease. Itaconate deficiency did not alter house dust mite-induced pathology at any of the timepoints tested; however, inhaled itaconate ameliorated inflammatory responses to inhaled allergen.

Through the integration of machine-learning approaches, we aim to assess the effect of ANA positivity and a triple-positive serological profile (RF + /ACPA + /ANA +) on disease activity and achieving sustained remission in a Colombian cohort of rheumatoid arthritis (RA) patients. This retrospective cohort study included adult RA patients and used clinical and serological data collected from an outpatient follow-up program. Machine learning models, including Support Vector Machines, Random Forest, Extreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and K-Nearest Neighbors, were employed to predict sustained remission based on DAS28-ESR, DAS28-CRP, CDAI, and SDAI. Feature selection was performed using Shapley Additive Explanations values; cross-validation and area under the ROC curves (AUC) were used to assess model performance. Triple positivity was consistently associated with higher disease activity at baseline and 12 months of follow-up and lower rates of sustained remission compared to RF + /ACPA + /ANA-. This trend was also true when comparing ANA + vs. ANA- patients. The Random Forest model best predicted sustained remission for the different disease activity indices, with an AUC ranging from 0.815 to 0.839. Important features and their SHAP values for DAS28-ESR-based sustained remission included baseline DAS28-ESR (0.252), HAQ (0.147), TJC (0.119), BMI (0.115), age (0.108), SJC (0.095), and RF + /ACPA + /ANA + versus RF + /ACPA + /ANA- (0.021). ANA positivity and a triple-positive serological profile are key factors in increased disease activity and poorer outcomes in RA. Furthermore, our predictive modeling results support integrating clinical data and machine learning methods to enhance individualized care and advance precision medicine in treating RA. Key Points • Triple seropositivity (RF +/ACPA +/ANA +) predicts worse disease activity and lower sustained remission in RA, highlighting its potential as a marker of more severe disease phenotypes. • ANA + patients exhibited delayed improvement and persistently higher disease activity, even when not triple-positive, suggesting a distinct role of ANA in RA pathogenesis and outcomes that warrants further attention in clinical evaluation. • Machine learning accurately predicted sustained remission using routine clinical and serological data. The Random Forest model demonstrated the best performance (AUC 0.815-0.839), identifying key predictors such as baseline DAS28-ESR, HAQ, and triple seropositivity, and underscoring the potential of AI in clinical decision support. • CDAI-based analyses revealed clearer distinctions between serological subgroups and more accurately reflected disease trajectories, reinforcing its value as a sensitive, accessible, and patient-centered index, especially in resource-limited settings.

BackgroundObstructive respiratory conditions, including asthma, bronchiectasis, and chronic obstructive pulmonary disease (COPD), are increasingly recognised as heterogeneous syndromes with significant overlap. Multiple disease pathways contribute to phenotypes that do not always align with textbook definitions, limiting the effectiveness of a one-size-fits-all approach. This study aims to identify, validate, and characterise clinically meaningful airway disease subtypes using electronic healthcare records (EHR) and unsupervised machine learning clustering techniques.MethodsWe applied k-means clustering to 626,651 patients with a diagnosis of asthma, bronchiectasis, or COPD, using linked national structured EHRs in England. Twenty-one clinical features, including risk factors and comorbidities, were analysed, with dimensionality reduction via principal component and multiple correspondence analyses. Associations between cluster membership and exacerbations, as well as respiratory and cardiovascular mortality, were assessed. Over 3,696,962 person-years of follow-up, 102,522 deaths were recorded. Cluster stability was evaluated after five years, and genome-wide association studies (GWAS) were conducted to explore genetic associations with cluster membership.ResultsSeven clusters were identified, each encompassing patients across traditional diagnostic labels. Distinct clinical patterns emerged as follows: (1) High BMI female predominant, (2) Older male-predominant with diabetes and cardiovascular disease, (3) Eosinophilic atopic, (4) Older non-comorbid, (5) Non-comorbid low BMI, (6) Neutrophilic smoker, (7) Anxious/depressed female-predominant.The cluster with cardiovascular comorbidities showed the highest rates of hospital admissions for exacerbations. Neutrophilic cluster 6 is a potential novel subtype marked by persistent neutrophilia and poor outcomes. Cluster stability over five years ranged from 38% to 78%. GWAS revealed significant genetic loci in a cluster enriched for allergic disease and eosinophilia, suggesting shared genetic mechanisms.ConclusionsThis study provides a data-driven dissection of the heterogeneity underlying obstructive airway diseases in a large, real-world population. Unsupervised machine learning applied to national-scale EHR data revealed distinct and partially stable subtypes that transcend conventional diagnostic boundaries. These findings highlight the complexity and overlap of airway disease phenotypes and demonstrate the value of clustering approaches for uncovering clinically and biologically meaningful subgroups. This work lays the foundation for further exploration into mechanisms and prognosis within and across airway disease phenotypes.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12890-025-03953-x.

This study describes a family of patients with distal muscle atrophy and oculopharyngodistal myopathy (OPDM). Patients with distal muscle atrophy exhibited slowly progressive distal-predominant muscle weakness without ptosis, ophthalmoplegia, or facial weakness. Long-read sequencing confirmed the presence of intermediate and pathogenic CGG repeat expansions in LRP12 in the patients with distal muscle atrophy and OPDM, respectively. This family demonstrated a similar phenotype-genotype correlation dependent on the LRP12 repeat length, as in a previous study, but the case with intermediate repeats could not be classified into a single etiology, even after comprehensive electrophysiological assessments and muscle biopsy.

Phenotypic drug screening remains constrained by the vastness of chemical space and technical challenges scaling experimental workflows. To overcome these barriers, computational methods have been developed to prioritize compounds, but they rely on either single-task models lacking generalizability or heuristic-based genomic proxies that resist optimization. We designed an active deep-learning framework that leverages omics to enable scalable, optimizable identification of compounds that induce complex phenotypes. Our generalizable algorithm outperformed state-of-the-art models on classical recall, translating to a 13-17x increase in phenotypic hit-rate across two hematological discovery campaigns. Combining this algorithm with a lab-in-the-loop signature refinement step, we achieved an additional two-fold increase in hit-rate and molecular insights. In sum, our framework enables efficient phenotypic hit identification campaigns, with broad potential to accelerate drug discovery.

Phenylketonuria (PKU), an autosomal recessive genetic disorder, has been documented to exhibit over 950 distinct mutations. This condition primarily affects the metabolism of phenylalanine, which is affected by a deficiency in the hepatic enzyme phenylalanine hydroxylase. The optimal treatment for PKU disease remains to be determined, necessitating further research. The severity of the disease and the most effective treatment method vary depending on the specific mutation, which necessitates the development of personalized treatment strategies. In this study, we successfully established induced pluripotent stem cell (iPSC) lines from the blood of a PKU patient with the R243Q mutation via Sendai virus-based reprogramming (R243Q-iPSCs). The established R243Q-iPSCs exhibited characteristics of pluripotency, as confirmed through quantitative reverse transcription polymerase chain reaction, western blot, immunocytochemistry, and karyotype analysis. Furthermore, these iPSCs not only successfully differentiated into hepatocytes but also exhibited a complete PKU disease phenotype. These results provide a valuable foundation for PKU disease research, including physiological studies of PKU, gene therapy, drug screening, and the development of platforms for novel cell therapy approaches.

Disease phenotypes can be described as the consequence of interactions among molecular processes that are altered beyond resilience. Here, we address the challenge of assessing the possible alteration of intra- and inter-cellular molecular interactions among processes or cells. We present an approach, designated as “Ulisse”, which complements the existing methods in the domains of enrichment analysis, pathway crosstalk analysis and cell-cell communication analysis. It applies to gene lists that contain quantitative information about gene-related alterations, typically derived in the context of omics or multi-omics studies. Ulisse highlights the presence of alterations in those components that control the interactions between processes or cells. Considering the complexity of statistical assessment of network-based analyses, crosstalk quantification is supported by two distinct null models, which systematically sample alternative configurations of gene-related changes and gene-gene interactions. Further, the approach provides an additional way of identifying the genes associated with the phenotype. As a proof-of-concept, we applied Ulisse to study the alteration of pathway crosstalks and cell-cell communications in triple negative breast cancer samples, based on single-cell RNA sequencing. In conclusion, our work supports the usefulness of crosstalk analysis as an additional instrument in the “toolkit” of biomedical research for translating complex biological data into actionable insights.

Disclosure: H.M. Hooker: None. N. Khovanova: None. D. Grammatopoulos: None.Pre-eclampsia (PE) is a serious complication of 3-5% of pregnancies and a leading cause of maternal and neonatal morbidity and mortality worldwide. Accurate prediction of symptomatic patients that will develop PE is vital to improve patient outcomes. The pathogenesis of the condition originates in the placenta, where dysfunction results in the release of proinflammatory and antiangiogenic molecules into the maternal bloodstream, causing maternal endothelial dysfunction. The ratio between two of these markers, soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF), has recently been adopted into clinical practice for PE prediction and diagnosis, offering acceptable ability to rule-out, but sub-optimal sensitivity to accurately rule-in, PE. Investigation into additional serum biomarkers to improve the predictive performance of the sFlt-1/PlGF ratio is therefore urgently required. The aetiology of PE is multifactorial and includes metabolic dysregulation, making the metabolome an important source of potential biomarkers. Therefore, this study aimed to use broad metabolic profiling to identify biomarkers that improve performance of the current clinical biomarkers, sFlt-1 and PlGF, for improved PE prediction and greater understanding into disease phenotype. 250 metabolite biomarkers were measured using an NMR-based metabolomics platform in retrospective serum samples from 124 symptomatic patients with suspected PE, investigated by measurements of sFlt-1/PlGF ratio by NICE-approved assays and defined pregnancy outcomes. Univariate analysis using modified Z-scores identified 38 significantly altered metabolite biomarkers in those diagnosed with PE, with glycerol exhibiting the most significant increase (2.8-fold, p<0.001). Glycerol also significantly correlated with the sFlt-1/PlGF ratio (ρ=0.359, p<0.001) and showed significant differences in patients stratified by clinical sFlt-1/PlGF cut-offs (p<0.001). Importantly, Decision Tree regression models demonstrated improved sensitivity, specificity and overall predictive accuracy using sFlt-1/PlGF ratio alongside glycerol, compared to current models using ratio alone.Combining the univariate analysis with dimensionality reduction techniques and multivariate regression analysis resulted in the identification of a 24-biomaker metabolite signature of PE. These biomarkers cover multiple metabolic pathways including amino acid metabolism, fatty acid metabolism, glycolysis, lipid and cholesterol pathways, capturing the complex, multi-factorial nature of PE. Identification of new unique biomarker signatures associated with both the sFlt-1/PlGF ratio and PE diagnosis broadens our insight into metabolic disruptions in this condition but also demonstrates the potential utility of metabolomic biomarkers to refine clinical prediction models for pre-eclampsia.Presentation: Saturday, July 12, 2025

Disclosure: A. Sharma: None. K. Ambulkar: None. M. Karlekar: None. S. Memon: None. V. Patil: None. N. Agarwal: None. V. Sarathi: None. A. Lila: None. S. Rege: None. H. Thakkar: None. G. Malhotra: None. R. Barnabas: None. N. Shah: None. T. Bandgar: None.Background: Data on pediatric/adolescent von Hippel-Lindau (VHL) disease is sparse, and comprehensive studies detailing the phenotype of all the associated neoplasms are lacking. Their current surveillance and management rely on expert opinion/extrapolation from adults, not individualized to the mutation type.Objective: To characterize the childhood/adolescent-onset VHL disease phenotype, compare it to adult-onset disease, and identify genotype-phenotype correlations.Methods: This was a retrospective review of children/adolescents (≤19 years) and adults (≥20 years) with a clinical (15%) or genetic (85%: 66% missense, and 19% truncating variants) diagnosis of VHL disease from a single endocrine center (2000-2024). Only neoplasms diagnosed until 19 years of age were included in the childhood/adolescent group and compared with the last follow-up of adults. The demographic, clinical data, genetics, anatomical/functional imaging, operative details, and histopathology (in operated patients) were noted for each VHL-associated neoplasm.Results: In 26 children/adolescents, by age 19 years, 81% (21/26) developed pheochromocytoma/paraganglioma (PPGL, of which 10% head and neck), 42% (10/24) central nervous system hemangioblastoma (CNS-HB), 31% each retinal RHB (5/16) and pancreatic neuroendocrine tumor (PNET, 8/26), and none endolymphatic sac tumor/renal cell carcinoma. At diagnosis, all those with PPGLs were symptomatic (median size 4.5 cm, 52 lesions). CNS-HBs showed female preponderance, a high disease burden (60% symptomatic, 50% synchronous in ≥2/3 components of the neuroaxis), and surgical requirement by age 19. Two pediatric patients needed surgery for a symptomatic PNET before the recommended surveillance initiation age (15 years). Two developed polycythemia on follow-up. Compared to adults (n=39), pediatric/adolescent PPGL patients had significantly higher baseline plasma free-normetanephrine (median 1099 vs. 2513 pg/mL), more bilateral (47% vs. 76%) and extra-adrenal (19% vs. 48%) disease by 19 years, and 8.3-fold higher operative-site recurrence over a similar follow-up duration (median 108 months in adults vs. 75 months in children/adolescents) independent of cortical-sparing surgery. CNS/RHB and PNET frequency and burden by 19 years resembled adults. Childhood/adolescent PPGLs occurred predominantly (16/17) and PNETs exclusively, with missense variants. Codon 167 missense variants were associated with synchronous bilateral pheochromocytomas.Conclusion: In pediatric/adolescent VHL disease, we report a severe phenotype, more extensive (PPGL) or comparable to adults, and the need for head and neck PGL and earlier PNET surveillance. The occurrence of PPGLs and PNETs almost exclusively in children and adolescents with missense VHL variants suggests the genotype may guide the pediatric surveillance strategy for these neoplasms.Presentation: Monday, July 14, 2025

BackgroundOral lichen planus (OLP) and oral lichenoid lesions (OLL) are chronic immune-mediated mucosal disorders with heterogeneous clinical presentations. While T cell-mediated mechanisms have been extensively studied, the role of humoral immunity, particularly B cell activation and plasma cell differentiation, remains insufficiently understood.MethodsRNA sequencing datasets from healthy oral mucosa and OLP lesions were integrated and analyzed to identify differentially expressed genes. Consensus clustering based on a validated tertiary lymphoid structure (TLS) signature genes (TSGs) was used to define immune subtypes. Associations with clinical severity and recurrence were validated in an independent RNA-seq cohort. Immunohistochemistry analysis of CD20+ B cells and CD38+ plasma cells was conducted in a separate clinical cohort of OLP/OLL patients.ResultsBased on TSGs, two immune subtypes were identified: Subtype A was enriched for CCL3, IL2RA, and IL1R2. Subtype B exhibited elevated expression of humoral activation markers IRF4 and TNFRSF17 and enrichment of B cell-related pathways. Transcriptomic features of Subtype B were significantly associated with erosive and recurrent OLP cases. Immunohistochemistry confirmed that CD20+ B cells were enriched in TLS-like structures (P < 0.001), whereas CD38+ plasma cells were closely linked to erosive phenotypes (P = 0.038).ConclusionsTLS-associated B cell maturation and plasma cell infiltration define a humoral activation axis linked to unfavorable clinical outcomes in OLP/OLL. The presence of activated B cells and plasma cells correlates with erosive and recurrent disease phenotypes, highlighting their potential as prognostic biomarkers and therapeutic targets for improving disease management.

Molecular chaperones are crucial for maintaining protein homeostasis by assisting in the proper folding, stabilization, and function of proteins. Among them, Heat shock protein 90 (Hsp90), represents a highly conserved protein family of molecular chaperones that plays an essential role in diverse biological processes and is fundamental to cellular health and survival. As a highly abundant molecular chaperone, Hsp90 comprises 1–2% of cellular proteins, increasing to 4–6% under stress conditions. It interacts with client proteins, assisting them in proper folding and stability. Unlike classical chaperonins, Hsp90 operates through a highly regulated, ATP-dependent cycle that involves multiple co-chaperones. This process allows Hsp90 to selectively engage with numerous client proteins, including signaling proteins, kinases, hormone receptors, and transcription factors. Recent discoveries have revealed its involvement in processes beyond protein folding, demonstrating its role in diverse cellular functions such as epigenetic regulation, immune signaling, and oncogenic transformation. This current review highlighted the specific characteristics of cytoplasmic and endoplasmic reticulum (ER) as well as mitochondrial paralogs and functions, focusing on its contribution to buffering genetic variation, facilitating oncogene addiction, and modulating disease phenotypes in conditions such as cancer, neurodegeneration, cardiovascular diseases (CVD), and diabetes. We also discuss the therapeutic potential of targeting Hsp90 and its co-chaperones, outlining the challenges and prospects in drug development. These insights not only reshape our understanding of chaperone biology but also present opportunities for precision medicine in various human diseases.

The increasing availability of large-scale omics data calls for robust analytical frameworks capable of handling complex gene expression datasets while offering interpretable results. Recent advances in artificial intelligence have enabled the identification of aberrant molecular patterns distinguishing disease states from healthy controls. Coupled with improvements in model interpretability, these tools now support the identification of genes potentially driving disease phenotypes. However, current approaches to gene anomaly detection often remain limited to single datasets and lack accessible graphical interfaces. We introduce E-ABIN, a general-purpose, explainable framework for anomaly detection in biological networks. E-ABIN combines classical machine learning and graph-based deep learning techniques within a unified, user-friendly platform, enabling the detection and interpretation of anomalies from gene expression or methylation-derived networks. By integrating algorithms such as support vector machines, random forests, graph autoencoders, and graph adversarial attributed networks, E-ABIN ensures high predictive accuracy while maintaining interpretability. We demonstrate the utility of E-ABIN through case studies of bladder cancer and celiac disease, where it effectively uncovers biologically relevant anomalies and offers insights into disease mechanisms. E-ABIN is freely available on the Zenodo platform at https://doi.org/10.5281/zenodo.17062501.