Ter Arkh. 2025 Jul 31;97(7):593-599. doi: 10.26442/00403660.2025.07.203352.

ABSTRACT

The article presents a clinical case of Fabry disease in a woman, characterized by multisystemic lesions, late onset and predominant clinical picture of heart failure. The features of this pathology are described in detail with an emphasis on instrumental studies of the cardiovascular system, and the progressive course of Fabry disease is analyzed. This clinical observation illustrates the importance of family screening and detailed anamnesis, shows the process of supervision of a patient with an orphan disease by a cardiologist of a regional hospital in real clinical practice, thereby increasing awareness of the Russian medical community about this pathology.

PMID:40778921 | DOI:10.26442/00403660.2025.07.203352

Stud Health Technol Inform. 2025 Aug 7;329:1942-1943. doi: 10.3233/SHTI251290.

ABSTRACT

This study develops a knowledge graph-based intelligent Q&A system for rare diseases, integrating data from 126 diseases, 2,609 symptoms, and related departments. The Bert-BiLSTM-CRF model achieved 82.13% accuracy in entity extraction, and TextCNN achieved 94.54% accuracy in intent recognition. The system improves access to medical knowledge but requires further optimization to reduce response times and handle a broader range of user queries.

PMID:40776307 | DOI:10.3233/SHTI251290

Stud Health Technol Inform. 2025 Aug 7;329:1054-1058. doi: 10.3233/SHTI251000.

ABSTRACT

Generating differential diagnoses for rare disease patients can be time intensive and highly dependent on the background and training of the evaluating physicians. Large language models (LLMs) have the potential to complement this process by automatically generating differentials to support physicians, but their performance in real-world patient populations remains underexplored. To this end, we assessed the diagnostic accuracy of ChatGPT-4o, Llama 3.1-8B-Instruct, and Exomiser in 424 rare disease patients at the Undiagnosed Diseases Network. ChatGPT-4o had the highest differential diagnostic accuracy (22.4% [95% CI: 18.4, 26.4]), outperforming Exomiser (13.9% [10.6, 17.2]; p < 0.001) and Llama 3.1-8B-Instruct (11.6% [8.5, 14.6]; p < 0.001). Adjusting for other factors, age at symptom onset was a significant predictor of ChatGPT-4o's diagnostic accuracy with the model performing better in patients with later symptom onset, potentially due to more distinct phenotypic presentations in older individuals. The combined accuracy of ChatGPT-4o and Exomiser was 30% [25.6, 34.3] and higher than that of either model alone (p < 0.01). This improvement highlights the potential of combining LLMs and bioinformatic models to generate differential diagnoses for rare diseases.

PMID:40776018 | DOI:10.3233/SHTI251000

Stud Health Technol Inform. 2025 Aug 7;329:683-687. doi: 10.3233/SHTI250927.

ABSTRACT

Developmental and Epileptic Encephalopathies (DEEs) are rare, severe conditions often discussed by families on social media, offering valuable insights into their experiences. Identifying these messages amidst unrelated content is crucial but challenging due to data imbalance. This study evaluates different uses of generative large language models (LLMs) for binary classification of DEE-related experiences within social media posts. Using CamemBERT as a baseline, we compared two strategies: zero-shot prompt-based classification and synthetic data generation for minority class augmentation. While zero-shot prompting underperformed, the addition of 2% synthetic data improved all metrics (macro/positive F1, precision and recall). Higher proportions of synthetic data led to decreased precision. These findings underscore the potential of hybrid approaches combining fine-tuning and domain-specific synthetic data for addressing data imbalance in rare disease contexts. Further validation across models and datasets is needed.

PMID:40775945 | DOI:10.3233/SHTI250927

Orphanet J Rare Dis. 2025 Aug 7;20(1):407. doi: 10.1186/s13023-025-03894-y.

ABSTRACT

BACKGROUND: Obtaining health-state utility values (HSUVs) aids in making scientific decisions in patient health management, especially for rare disease patients. However, there is currently no research specifically measuring the HSUVs of Chinese hemophilia B patients. Therefore, this study aims to assess the HSUVs of hemophilia B patients in China and explore its potential influencing factors.

METHODS: The sociodemographic characteristics of patients were obtained from the Beijing Hemophilia Home Care Center (BHHCC) database. And the HSUVs were further obtained by reaching hemophilia B patients through an application of BHHCC and the Chinese version of the EQ-5D-5L. The beta regression model was used to explore the potential influencing factors of the HSUVs of patients.

RESULTS: A total of 167 male patients (hemophilia B is an X-chromosome recessive disorder and female patients are rare) were included in the study. The mean age, HSUV and EQ-VAS were 20.01 ± 15.83, 0.755 ± 0.291 and 71.7 ± 22.7, respectively. The ceiling effects was 29.24%, and patients were more likely to experience problems in Pain/discomfort (57.49%). Compared to self-completion, proxy may overestimate HSUVs of patients. Pain (p < 0.000), disability (p < 0.000), complications (p < 0.001), inhibitors (p < 0.01), drug usage (p < 0.001), and bleeds (p < 0.000) were significantly associated with HSUVs in Chinese hemophilia B patients.

CONCLUSIONS: This study first assessed the HSUVs of Chinese hemophilia B patients, which provides support for further economic studies. Potential factors that affect the HSUVs of Chinese hemophilia B patients were also explored, which can provide a reference for developing health management measures. However, to enact more comprehensive and reliable disease management decisions, the effects of self-completion and proxy on the HSUVs of hemophilia B patients in China need to be further explored as well as the effects of specific factors.

PMID:40775730 | DOI:10.1186/s13023-025-03894-y

Orphanet J Rare Dis. 2025 Aug 7;20(1):410. doi: 10.1186/s13023-025-03933-8.

ABSTRACT

BACKGROUND: Rare diseases, though individually uncommon, collectively affect a significant portion of the population. However, their epidemiology in China remains underexplored. A population-based rare disease registry comprising 14.31 million individuals was conducted between 2012 and 2023 by the Beijing Municipal Health Big Data and Policy Research Center. Rare disease cases were identified via ICD-10 codes mapped to China's national rare disease lists (2018 and 2023) and international databases. Age-standardized incidence rates (ASIR) were calculated per 100,000 person-years with 95% confidence intervals.

RESULTS: Our analysis identified 12,371 rare disease cases, with the overall ASIR increasing from 6.109 in 2012 to 7.394 in 2023. Rare neurologic diseases accounted for 52.12% of cases, followed by systemic and rheumatologic diseases (16.89%) and rare neoplastic diseases (9.99%). The most frequently diagnosed rare diseases included generalized myasthenia gravis, ANCA-associated vasculitis, and malignant melanoma. Significant sex-based differences were observed, with female patients more affected by systemic and rheumatologic conditions, while male patients showed a higher incidence of respiratory disorders. Pediatric patients predominantly presented with inborn errors of metabolism and rare immune diseases. Comparisons with global data revealed notable disparities, such as a higher prevalence of Wilson's disease and a lower incidence of amyotrophic lateral sclerosis (ALS) in China.

CONCLUSIONS: This study represents the first large-scale, population-based analysis of rare diseases in China, revealing distinct epidemiological patterns. These findings underscore the critical need for healthcare policies that address the unique challenges posed by rare diseases in China.

PMID:40775651 | DOI:10.1186/s13023-025-03933-8

Stat Med. 2025 Aug;44(18-19):e70206. doi: 10.1002/sim.70206.

ABSTRACT

Many rare disease clinical trials are underpowered to detect a moderate treatment effect of an investigational product due to the limited number of participants available for the trials. In addition, given the complex, multisystemic nature of many rare diseases, it is challenging to confidently prespecify a single primary efficacy endpoint that is applicable to all trial participants with a heterogeneous clinical manifestation of their disease. Traditional trial designs and analysis methods often used in more common diseases to analyze the same endpoint(s) for all patients may be inefficient or impractical for a rare disease with heterogeneous clinical manifestations. To address these issues, we propose a novel trial design and analytic approach that allows for an evaluation of stratum-specific efficacy endpoints in a broader population of participants. We develop several nonparametric global test methods that can accommodate the novel design and provide global evaluation of treatment effects. Using a case example in patients with Fabry disease, our simulation studies illustrate that the novel design evaluated using the global test methods may be more sensitive to detect a treatment effect compared to the traditional design that uses the same endpoint(s) for all patients.

PMID:40772797 | DOI:10.1002/sim.70206

Nat Commun. 2025 Aug 7;16(1):7267. doi: 10.1038/s41467-025-61712-2.

ABSTRACT

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform in-depth analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development. The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale case-based diagnostic analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser ( https://dbmi-bgm.github.io/udn-browser/ ). These results show that case-level diagnostic efforts should be supplemented by a joint genomic analysis across cohorts.

PMID:40770127 | DOI:10.1038/s41467-025-61712-2

Curr Osteoporos Rep. 2025 Aug 6;23(1):34. doi: 10.1007/s11914-025-00928-z.

ABSTRACT

PURPOSE OF REVIEW: Calcification, the deposition of phosphate-calcium crystals, is essential for the development and function of mineralized tissues. When dysregulated, it can cause harmful effects. This review focuses on the critical role of the balance between phosphate (Pi) and pyrophosphate (PPi) in maintaining healthy mineralization and explains how disruptions in this balance contribute to rare calcifying disorders.

RECENT FINDINGS: Studies have identified key regulators of PPi production and Pi generation. Recent research on rare calcifying diseases and animal models has revealed how Pi/PPi imbalances lead to ectopic calcification in soft tissues, driving disease progression. The balance of Pi/PPi is vital for bone health and preventing pathological calcification. Disruptions in this equilibrium contribute to rare diseases. Understanding these mechanisms, supported by preclinical models, opens potential therapeutic avenues to restore balance and mitigate the impact of these diseases.

PMID:40768170 | DOI:10.1007/s11914-025-00928-z

J Genet Couns. 2025 Aug;34(4):e70085. doi: 10.1002/jgc4.70085.

ABSTRACT

Parenting a child with a rare undiagnosed genetic condition can impact psychological well-being, including anxiety and health-related quality-of-life. We conducted a multi-site quantitative survey with parents to understand which parent and child characteristics are predictive of poorer psychological outcomes. 1366 surveys were sent out across seven NHS Trusts in England; 383 were returned and included in analysis (27% response rate). We used the GAD-7 to measure parents' generalized anxiety and the PedsQL Family Impact Module (FIM) to measure self-reported physical, emotional, social, and cognitive functioning (the health-related quality-of-life [HRQOL] summary score), communication, worry, daily activities, and family relationships (the family functioning [FF] summary score). Participant characteristics included: the 6-item Brief Resilience Scale to measure parental resilience, a bespoke single question to assess parents' tolerance for uncertainty, the EQ-5D-Y-3L to measure child health-related quality-of-life, two bespoke questions to assess the perceived seriousness/consequences of the child's condition, and standard characteristics questions (e.g., age, ethnicity, education, income). Overall, parental anxiety was low (mean = 5.31; SD = 5.82, range 0-21), although 21.9% had moderate (11.4%) or severe (10.5%) anxiety. A multivariable analysis indicated that higher anxiety scores were significantly associated with younger parental age (p = 0.010), lower education attainment (0.004), lower resilience (p = 0.049), and lower tolerance for uncertainty (p = 0.021). FIM total scores ranged from 0 to 100 (mean = 53.68, SD 20.45). Parents scored lowest on the subscale daily activities (43.68), worry (47.29), communication (51.31), and physical functioning (52.45). Family functioning summary scores were significantly lower for parents of children with developmental disorders compared to other conditions (p = 0.016). Multivariable analysis identified that lower scores (reflecting poorer outcomes) were significantly associated with lower parental resilience and lower tolerance for uncertainty (p < 0.001, respectively). Our findings highlight the significant psychological burden parenting a child with a rare undiagnosed condition can have on some parents and the importance of developing tailored support strategies.

PMID:40767117 | DOI:10.1002/jgc4.70085

J Intellect Disabil Res. 2025 Aug 5. doi: 10.1111/jir.70017. Online ahead of print.

ABSTRACT

OBJECTIVES: Kabuki syndrome (KS), Wiedemann-Steiner syndrome (WSS) and O'Donnell-Luria-Rodan (ODLURO) syndrome are rare disorders caused by pathogenic variants in histone lysine methyltransferases, specifically the KMT2 gene family. All of these disorders are commonly associated with intellectual disability. Recent studies found overlap between KS and WSS cognitive phenotypes, suggesting shared disease pathogenesis. In contrast, the neuropsychological profile of ODLURO remains largely unknown. This study examines the academic learning concerns across the syndromes to better understand their cognitive profiles and provide guidance for clinical care.

METHODS: Fifty caregivers participated in this study, 25 with a child with WSS (Mean age = 12.85 years, SD = 1.82), 14 with KS (Mean age = 12.06, SD = 5.91) and 11 with ODLURO (Mean age = 12.43, SD = 4.69). All caregivers completed the Colorado Learning Difficulties Questionnaire, a parent-screening inventory of learning/academic challenges, specifically in reading, math and spatial skills.

RESULTS: Results suggest shared deficits in spatial skills, but different patterns of academic learning concerns across syndromes. Those with WSS were rated to show unique challenges in math and spatial domains, while those with ODLURO show global difficulties across areas. Individuals with KS were rated to show the most significant challenges in spatial skills, but comparable reading and math concerns.

CONCLUSIONS: Study results support recent publications on the overlapping cognitive profile in WSS and KS, specifically with distinct deficits in visual spatial processing. In contrast, ODLURO is associated with more generalised cognitive difficulties that warrant further investigation. Disruption of KMT2 genes may have common and individual effects on neurodevelopment that necessitate cross-syndrome research to illuminate gene-brain-behaviour relationships.

PMID:40762104 | DOI:10.1111/jir.70017

Orphanet J Rare Dis. 2025 Aug 4;20(1):399. doi: 10.1186/s13023-025-03632-4.

ABSTRACT

BACKGROUND: The SLSMDS Research Network is a collaborative network comprising patient advocates, researchers, clinicians, and affected families seeking to improve outcomes for individuals with single large-scale mitochondrial DNA deletion syndromes (SLSMDS). Building off of jointly developed research infrastructures, including a patient registry and natural history study, advocates and clinicians cohosted the SLSMDS Family and Scientific Conference, enabling the collection of patient data from an ultra-rare and geographically dispersed patient population. Here we describe the data collection procedures for single-time point laboratory assessments and patient reported outcomes for a subset of individuals with SLSMDS.

RESULTS: Utilizing a reproducible model of rare disease data collection, we expand our understanding of the common psychiatric manifestations, describe variability in terms of self-care and quality of life, and emphasize potential biomarkers for individuals with SLSMDS.

CONCLUSION: Our study describes how efficient patient-researcher partnerships can develop and sustain novel mechanisms to collect rare disease data, improve our understanding of the natural history of these disorders, and support development of future treatments.

PMID:40760494 | DOI:10.1186/s13023-025-03632-4

Stem Cells Transl Med. 2025 Jul 24;14(8):szaf032. doi: 10.1093/stcltm/szaf032.

ABSTRACT

Induced pluripotent stem cells (iPSCs) are widely used to model human genetic diseases. The most common strategy involves collecting cells from relevant individuals and then reprogramming them into iPSCs. This strategy is very powerful, but finding enough individuals with a specific genetic disease can be challenging, especially since most are rare. In addition, making numerous iPSC lines is time-consuming and expensive. As a result, most studies have included relatively small numbers of iPSC lines, sometimes from the same individual. Considering the experimental variability obtained using different iPSC lines, there has been great interest in delineating the most efficient number of lines needed to achieve a robust and reproducible result. Several recommendations have been published, although most conclusions have been based on methods where experimental variance from individual cases is difficult to separate from technical issues related to the preparation of iPSCs. The current study used gene expression profiles determined by RNA sequencing (RNAseq) to empirically evaluate the impact of the number of unique individuals and the number of replicate iPSC lines from each individual for modeling Lesch-Nyhan disease (LND). This disease is caused by mutations in the HPRT1 gene, which encodes the enzyme hypoxanthine-guanine phosphoribosyltransferase. Results for detecting disease-relevant changes in gene expression depended on the analytical method employed, and whether or not statistical procedures were used to address multiple iPSC lines from the same individual. In keeping with prior studies, the best results were obtained with iPSC lines from 3-4 unique individuals per group. In contrast to prior studies, results were improved with 2 lines per individual, without statistical corrections for duplicate lines from the same individual. In the current study where all lines were produced in parallel using the same methods, most variance in gene expression came from technical factors unrelated to the individual from whom the iPSC lines were prepared.

PMID:40751518 | DOI:10.1093/stcltm/szaf032

Orphanet J Rare Dis. 2025 Aug 1;20(1):393. doi: 10.1186/s13023-025-03941-8.

ABSTRACT

Rare genetic diseases (RDs) with primary neuropsychiatric symptoms pose unique challenges for diagnosis and management. While the majority of these RDs have neuropsychiatric symptoms that are secondary to the RD, a subset presents with primary neuropsychiatric symptoms directly linked to their underlying pathophysiology. This subset has significant unmet medical need with delayed diagnoses leading to prolonged delays in treatment optimization and the trialing of medications that fail to target the underlying pathophysiology. This comprehensive review identifies 108 RDs with central neuropsychiatric symptoms that have a 7.7-year average diagnostic delay. Optimal management strategies for these RDs typically includes non-psychotropic medications, dietary adjustment, avoidance of certain drug classes and other treatments that target the underlying pathophysiology before improvement of the neuropsychiatric symptoms is observed. Surprisingly, despite the limited number of RDs that fit this unique profile, the annual economic burden for these conditions had an annual mental health care-related inpatient charges totaling $4.2 billion USD. Addressing the diagnostic delay and optimizing management for these specific conditions must include increased involvement across multiple specialties, including psychiatry, family medicine, pediatrics, medical genetics, as well as an enhanced strategy for genetic testing to ensure the prompt initiation of condition-specific therapies for affected individuals.

PMID:40750893 | DOI:10.1186/s13023-025-03941-8

BMC Med Res Methodol. 2025 Jul 30;25(1):179. doi: 10.1186/s12874-025-02626-x.

ABSTRACT

Parallel designs with an end-of-treatment analysis are commonly used for randomised trials, but they remain challenging to conduct in rare diseases due to small sample size and heterogeneity. A more powerful alternative could be to use model-based approaches. We investigated the performance of longitudinal modelling to evaluate disease-modifying treatments in rare diseases using simulations. Our setting was based on a model describing the progression of the standard clinician-reported outcome SARA score in patients with ARCA (Autosomal Recessive Cerebellar Ataxia), a group of ultra-rare, genetically defined, neurodegenerative diseases. We performed a simulation study to evaluate the influence of trials settings on their ability to detect a treatment effect slowing disease progression, using a previously published non-linear mixed effect logistic model. We compared the power of parallel, crossover and delayed start designs, investigating several trial settings: trial duration (2 or 5 years); disease progression rate (slower or faster); magnitude of residual error (σ=2 or σ=0.5); number of patients (100 or 40); method of statistical analysis (longitudinal analysis with non-linear or linear models; standard statistical analysis), and we investigated their influence on the type 1 error and corrected power of randomised trials. In all settings, using non-linear mixed effect models resulted in controlled type 1 error and higher power (88% for a parallel design) than a rich (75% for a parallel design) or sparse (49% for a parallel design) linear mixed effect model or standard statistical analysis (36% for a parallel design). Parallel and delayed start designs performed better than crossover designs. With slow disease progression and high residual error, longer durations are needed for power to be greater than 80%, 5 years for slower progression and 2 years for faster progression ataxias. In our settings, using non-linear mixed effect modelling allowed all three designs to have more power than a standard end-of-treatment analysis. Our analysis also showed that delayed start designs are promising as, in this context, they are as powerful as parallel designs, but with the advantage that all patients are treated within this design.

PMID:40739200 | DOI:10.1186/s12874-025-02626-x

Blood. 2025 Jul 30:blood.2024026805. doi: 10.1182/blood.2024026805. Online ahead of print.

ABSTRACT

Chronic active Epstein-Barr virus (EBV) infection (CAEBV) is an orphan disease characterized by the proliferation and infiltration of EBV-infected T/natural killer (NK) cells into multiple organs. Although CAEBV is a heterogeneous disease with diverse clinical courses, its pathogenesis remains poorly understood. In this study, we explored the molecular mechanisms underlying CAEBV by performing a comprehensive multi-omics analysis, including genome, transcriptome, epigenome, and single-cell transcriptome and surface proteome analyses, of 65 CAEBV patients. Methylation analysis identified two distinct subtypes of NK cell-type CAEBV based on the CpG island methylator phenotype (CIMP). In CIMP-positive CAEBV, regions associated with enhancer of zeste homolog 2 binding sites and histone H3 lysine 27 trimethylation exhibited increased DNA hypermethylation, resulting in downregulation of tumor suppressor and anti-herpes virus genes. CIMP-positive CAEBV had a particularly poor prognosis and displayed a "neoplastic" phenotype with a DNA methylation pattern similar to that of extranodal NK/T-cell lymphoma, a higher tumor mutation burden, and frequent copy number alterations. In addition, both in vitro and in vivo functional assays demonstrated that 5-Azacytidine, a hypomethylating agent, was a potentially effective agent for high-risk CIMP-positive CAEBV. Finally, we established a method to effectively detect EBV-infected cells in single-cell analysis, suggesting that EBV-infected NK cells have tissue-resident properties and that innate and adaptive immunity to EBV is compromised in patients with CAEBV. The present findings provide insight into the complex molecular features of CAEBV and suggest potential molecular therapies.

PMID:40737598 | DOI:10.1182/blood.2024026805

Pharmaceutics. 2025 Jun 20;17(7):801. doi: 10.3390/pharmaceutics17070801.

ABSTRACT

To make the sentences clearer and easier for readers to read, the grammatical format of some sentences has been modified, as follows:Change "on the prevalence of AEs and incidents" into "on the prevalence and incidence of AEs " and change "The review" into "This review" in abstract [...].

PMID:40733155 | DOI:10.3390/pharmaceutics17070801

Eur J Pediatr. 2025 Jul 29;184(8):510. doi: 10.1007/s00431-025-06293-4.

ABSTRACT

Globally the number of children and adolescents living with a rare disease is increasing due to improved periconceptional care, advances in diagnostics and treatments. This exploratory study aimed to examine parents' perceptions of the quality of life of children with rare diseases. The results will provide important insights to healthcare professionals who aim to offer child-centered and family-oriented care. Participating parents were recruited via the knowledge network for children with rare diseases (KMSK). Qualitative data from an open-ended survey question on parents' perceptions of children's quality of life was analyzed using content analysis. Data collection took place from January-June 2023. The study included 108 primary caregivers of children with rare diseases. Five categories of parental perceptions of children's quality of life were identified: (1) pain-free living & joy; (2) partaking in everyday life; (3) the quest for integration: desire for normality & appreciation of difference; (4) obtaining developmental milestones and (5) having access to individualized child- and family-centered care.Conclusions: In addition to positive health outcomes, social integration, respect for diverse developmental paths and holistic healthcare services were reported as essential to quality of life. Healthcare professionals should be aware that parents may worry about stigma and address these concerns thoughtfully. It is also important to ensure that parents feel their knowledge and experiences are valued, and to support families in building confidence in their decisions, as part of a personalized, child- and family-centered approach.

PMID:40730885 | DOI:10.1007/s00431-025-06293-4

Acta Biochim Pol. 2025 Jul 14;72:14777. doi: 10.3389/abp.2025.14777. eCollection 2025.

ABSTRACT

Although there no single, widely accepted definition of a "rare disease," this group of disorders includes conditions that affect only a small fraction of the population. A large number of rare diseases is caused by defined molecular defects, predominantly the occurrence of pathogenic variant(s) of genes. Thus, they are classified as "genetic diseases," among which there are many neurodegenerative disorders. Despite a low incidence of each such disease, majority of them are severe and no effective treatment is available. This creates a battery of problems for millions of people suffering from these disease as well as to their relatives and caregivers. However, the set of problems is larger; therefore, in this narrative review we summarize and discuss various kinds of problems caused by rare disease, including severe symptoms of patients, everyday problems of patients and caregivers, loneliness and social exclusion, diagnostic difficulties, unavailability of effective therapies and economic difficulties in introducing orphan drugs, and a complexity of studies on rare diseases due to low availability of biological material and complicated pathomechanisms. The global picture of the complex problems caused by rare diseases is presented.

PMID:40726965 | PMC:PMC12301258 | DOI:10.3389/abp.2025.14777

Orphanet J Rare Dis. 2025 Jul 28;20(1):386. doi: 10.1186/s13023-025-03882-2.

ABSTRACT

BACKGROUND: Diagnosing rare diseases traditionally requires patients to endure lengthy and challenging journeys to find specialists familiar with their conditions. This study advocates a paradigm shift in rare disease diagnosis, moving from patients seeking physicians to physicians actively identifying patients. Using hereditary angioedema (HAE) as an example, we demonstrate how this approach, supported by electronic medical records (EMRs), enables proactive care for patients with rare diseases. Our EMR system incorporates a free-text search engine to screen for patients with potential HAE based on clinical symptoms and laboratory tests. Search terms include recurrent skin edema, abdominal pain, laryngeal edema, and/or decreased C4 levels. Suspected cases are followed up by telephone calls from trained physicians, inviting patients to undergo confirmatory C1-INH and C4 testing and genetic testing to ensure accurate diagnosis and appropriate treatment.

RESULTS: Of 2,689 patients who met the screening criteria, 3,441 records were analyzed. Ninety-five patients had already been diagnosed with HAE. After excluding those with a known etiology for edema or characteristics inconsistent with HAE, three patients with unexplained cutaneous edema, abdominal pain, and/or laryngeal edema were included in the final screening. Laboratory tests confirmed HAE in all three, highlighting the effectiveness of this proactive approach.

CONCLUSIONS: This study underscores the transformative potential of EMRs in diagnosing rare diseases. By shifting the responsibility of identifying rare diseases from patients to healthcare professionals, we expedite diagnosis and exemplify the spirit of service in medicine, ensuring patients with rare diseases receive timely and effective care.

PMID:40722186 | DOI:10.1186/s13023-025-03882-2