Urol Clin North Am. 2025 May;52(2):287-296. doi: 10.1016/j.ucl.2025.01.010. Epub 2025 Feb 28.

ABSTRACT

This article covers rare adrenal tumors including functional adenomas, myelolipomas, ganglioneuromas and neuroblastomas, and metastasis to the adrenal gland. It explores their clinical presentation and behavior, hormonal activity, imaging features, other diagnostic considerations, and approaches to management. The variety of rare tumors and their unique behaviors covered in this article underscores the need to maintain up-to-date knowledge and surgical skills, as well as the importance of a multidisciplinary approach to patient care.

PMID:40250895 | DOI:10.1016/j.ucl.2025.01.010

Cancer Med. 2025 Apr;14(8):e70853. doi: 10.1002/cam4.70853.

ABSTRACT

BACKGROUND: Genetic testing and sequencing technologies offer a comprehensive understanding of cancer genetics, providing rapid and cost-effective solutions. In particular, these advanced technologies play an important role in assessing the complexities of the rare cancer types affecting several systems including the bone, endocrine, digestive, vascular, and soft tissue. This review will explore how genetic testing and sequencing technologies have contributed to the identification of biomarkers across several rare cancer types in diagnostic, therapeutic, and prognostic stages, thereby advancing PM.

METHODS: A comprehensive literature search was conducted across PubMed (MEDLINE), EMBASE, and Web of Science using keywords related to sequencing technologies, genetic testing, and cancer. There were no restrictions on language, methodology, age, or publication date. Both primary and secondary research involving humans or animals were considered.

RESULTS: In practice, fluorescence in situ hybridization, karyotype, microarrays and other genetic tests are mainly applied to identify specific genetic alterations and mutations associated with cancer progression. Sequencing technologies, such as next generation sequencing, polymerase chain reaction, whole genome or exome sequencing, enable the rapid analysis of millions of DNA fragments. These techniques assess genome structure, genetic changes, gene expression profiles, and epigenetic variations. Consequently, they help detect main intrinsic markers that are crucial for personalizing diagnosis, treatment options, and prognostic assessments, leading to better patient prognosis. This highlights why these methods are now considered as primary tools in rare cancer research. However, these methods still face multiple limitations, including false positive results, limited precision, and high costs.

CONCLUSION: Genetic testing and sequencing technologies have significantly advanced the field of rare cancer research by enabling the identification of key biomarkers for precision diagnosis, treatment, and prognosis. Despite existing limitations, their integration into clinical and research fields continues to improve the development of personalized medicine strategies for rare and complex cancer types.

PMID:40249565 | DOI:10.1002/cam4.70853

Am J Med Genet C Semin Med Genet. 2025 Apr 18:e32142. doi: 10.1002/ajmg.c.32142. Online ahead of print.

ABSTRACT

Usher syndrome, the most common form of deaf-blindness, displays extensive genetic, allelic, and phenotypic heterogeneity. The dual sensory impairment associated with this autosomal recessive disorder makes Usher syndrome an important target for gene therapy, with dozens of published preclinical studies targeting multiple Usher syndrome genes and using multiple gene therapy strategies. Nine genes have been conclusively linked to Usher syndrome; however, data on the prevalence and contribution of specific genetic variants is lacking. Such information is essential to choosing a favorable target gene or therapeutic approach during clinical trial design. Here, we used large genomic databases to systematically evaluate the genomics of Usher syndrome. We ascertained pathogenic Usher syndrome variants from three clinical databases and determined the occurrence of these pathogenic Usher syndrome variants within: (1) a publicly available dataset including worldwide populations (GnomAD), (2) a cohort of 3888 children without hearing loss, and (3) 637 children with hearing loss. Results show significant variability in the frequency of Usher syndrome variants by gene and genetic ancestry. 1% of control subjects carry a pathogenic USH variant. Pathogenic variants in USH2A are the most prevalent, at 1 in 150 individuals (0.0062). Calculated general population prevalence for all Usher syndrome subtypes is 1 in ~29,000, indicating that 30,405 individuals in the United States and 721,769 individuals worldwide are affected. We estimate that 324 babies in the United States and 12,090 worldwide are born with Usher syndrome each year. We identify key targets for genetic therapy based on population-level prevalence including a focus on alternatives to gene replacement therapies, specifically for USH2A.

PMID:40248902 | DOI:10.1002/ajmg.c.32142

Am J Hum Genet. 2025 May 1;112(5):1158-1172. doi: 10.1016/j.ajhg.2025.03.014. Epub 2025 Apr 16.

ABSTRACT

Rare diseases (RDs) are conditions affecting fewer than 1 in 2,000 people, with over 7,000 identified, primarily genetic in nature, and more than half impacting children. Although each RD affects a small population, collectively, between 3.5% and 5.9% of the global population, or 262.9-446.2 million people, live with an RD. Most RDs lack established treatment protocols, highlighting the need for proper care pathways addressing prognosis, diagnosis, and management. Advances in generative AI and large language models (LLMs) offer new opportunities to document the temporal progression of phenotypic features, addressing gaps in current knowledge bases. This study proposes an LLM-based framework to capture the natural history of diseases, specifically focusing on Noonan syndrome. The framework aims to document phenotypic trajectories, validate against RD knowledge bases, and integrate insights into care coordination using electronic health record (EHR) data from the Undiagnosed Diseases Program Singapore.

PMID:40245863 | DOI:10.1016/j.ajhg.2025.03.014

Orphanet J Rare Dis. 2025 Apr 17;20(1):186. doi: 10.1186/s13023-025-03655-x.

ABSTRACT

BACKGROUND: Use of artificial intelligence (AI) in rare diseases has grown rapidly in recent years. In this review we have outlined the most common machine-learning and deep-learning methods currently being used to classify and analyse large amounts of data, such as standardized images or specific text in electronic health records. To illustrate how these methods have been adapted or developed for use with rare diseases, we have focused on Fabry disease, an X-linked genetic disorder caused by lysosomal α-galactosidase. A deficiency that can result in multiple organ damage.

METHODS: We searched PubMed for articles focusing on AI, rare diseases, and Fabry disease published anytime up to 08 January 2025. Further searches, limited to articles published between 01 January 2021 and 31 December 2023, were also performed using double combinations of keywords related to AI and each organ affected in Fabry disease, and AI and rare diseases.

RESULTS: In total, 20 articles on AI and Fabry disease were included. In the rare disease field, AI methods may be applied prospectively to large populations to identify specific patients, or retrospectively to large data sets to diagnose a previously overlooked rare disease. Different AI methods may facilitate Fabry disease diagnosis, help monitor progression in affected organs, and potentially contribute to personalized therapy development. The implementation of AI methods in general healthcare and medical imaging centres may help raise awareness of rare diseases and prompt general practitioners to consider these conditions earlier in the diagnostic pathway, while chatbots and telemedicine may accelerate patient referral to rare disease experts. The use of AI technologies in healthcare may generate specific ethical risks, prompting new AI regulatory frameworks aimed at addressing these issues to be established in Europe and the United States.

CONCLUSION: AI-based methods will lead to substantial improvements in the diagnosis and management of rare diseases. The need for a human guarantee of AI is a key issue in pursuing innovation while ensuring that human involvement remains at the centre of patient care during this technological revolution.

PMID:40247315 | DOI:10.1186/s13023-025-03655-x

Sci Rep. 2025 Apr 17;15(1):13252. doi: 10.1038/s41598-025-97836-0.

ABSTRACT

Rare diseases present a significant economic burden on patients, families, and healthcare systems worldwide. As the prevalence of these diseases rises in China, data regarding their impact, specifically in Hainan Province, is scarce. Thus, this study aims to evaluate insurance coverage, economic costs, and the factors contributing to the burden of rare diseases in Hainan. We employed a bottom-up approach to analyse the prevalence and economic burden from 2019 to 2023, utilising data from the Hainan Provincial Health Commission Databases. We assessed insurance coverage as well as expenditures related to hospitalisation, diagnostics, medications, surgery, and out-of-pocket costs. Of 4,975 patients diagnosed with 99 distinct rare diseases, 83.01% were insured. From 2019 to 2023, the number of patients increased from 760 to 1,328, while economic costs surged from 34.26 million CNY (US$ 4.89 million) to 64.74 million CNY (US$ 8.86 million). Thalassemia major, one of the most prevalent conditions, generated the highest costs. Hospitalisation expenses accounted for 49.16% of the total costs, with out-of-pocket expenses averaging 17.52%. The findings reveal a significant economic burden associated with rare diseases in Hainan, highlighting the necessity for targeted policy interventions. Furthermore, additional research is needed to refine estimates of this economic burden.

PMID:40247032 | DOI:10.1038/s41598-025-97836-0

Pediatr Pulmonol. 2025 Apr;60(4):e71096. doi: 10.1002/ppul.71096.

ABSTRACT

The field of pediatric rare and diffuse lung diseases continues to advance, with ongoing research deepening our understanding of the diagnosis and treatment of conditions such as children's interstitial and diffuse lung disease (chILD), non-cystic fibrosis (CF) bronchiectasis, and pulmonary complications of childhood cancer. Recent publications in Pediatric Pulmonology and other journals in 2024 have highlighted new insights into the pathophysiology, disease progression, and emerging diagnostic tools for these rare lung conditions, as well as innovative therapeutic approaches. This review features these important advancements within the context of current diagnostic practices and clinical care for pediatric patients with rare and diffuse lung diseases.

PMID:40243387 | DOI:10.1002/ppul.71096

Front Public Health. 2025 Apr 2;13:1484286. doi: 10.3389/fpubh.2025.1484286. eCollection 2025.

ABSTRACT

The participation of patient organizations in the construction of medical security systems for rare diseases is an important proposition in the theory of welfare pluralism, which indicates that individualized services and diversified connections of patient organizations can fully meet the multiple medical insurance needs of patients with rare diseases. In actual practice, however, patient organizations continue to experience institutional and structural difficulties, such as improper supervision, insufficient capacity and insufficient coordination. The theory of welfare pluralism and the developmental experience of foreign rare disease organizations have suggested that patient organizations should clarify the bridge positioning and specialized development path in the multi-subject cooperation of organizations providing medical security for rare diseases, thereby improving the efficient implementation of medical security policies for rare diseases.

PMID:40241973 | PMC:PMC11999925 | DOI:10.3389/fpubh.2025.1484286

BMC Med Educ. 2025 Apr 16;25(1):545. doi: 10.1186/s12909-025-07149-z.

ABSTRACT

BACKGROUND: Rare diseases (RDs) affect 10% of the global population but have inadequate medical resources. Early detection and treatment are crucial, yet many emergency physicians lack awareness of RDs. This study aims to evaluate the effects of continuing medical education (CME) on the knowledge and attitude of emergency physicians.

METHODS: This retrospective study was conducted from April to June 2023, involving 218 Chinese emergency physicians. The online questionnaire consisted of four groups and 30 questions, covering demographic data, knowledge, and attitudes regarding RDs. Respondents were divided into two groups based on their recent CME training experience with RDs.

RESULTS: Two hundred and eighteen emergency physicians completed the questionnaire, of which 108 received RD CME training and 110 did not receive RD CME training. Most respondents (98.2%) felt their knowledge about RDs was insufficient. The CME training group showed increased awareness of RD incidence (p = 0.047) and improved case analysis after training, but only slight improvement in knowledge of RD professional websites. Among the CME training group, CME was identified as the most prominent avenue for acquiring knowledge about RDs, with 72 respondents (66.7%, p < 0.001). In contrast, in the non-training group, clinical work was identified as the primary source of learning, with 47 respondents (42.7%, p < 0.001).

CONCLUSION: Emergency physicians generally lacked knowledge about rare diseases. CME training can improve their awareness and knowledge of RDs.

PMID:40241072 | DOI:10.1186/s12909-025-07149-z

Health Expect. 2025 Apr;28(2):e70260. doi: 10.1111/hex.70260.

ABSTRACT

BACKGROUND: Research about patient engagement for people with rare diseases has identified how the experiences of some members of the public are overlooked in relation to clinical trial design and trial participation. As part of a knowledge transfer partnership (KTP), the authors were granted access to patient insight reports about the needs of people with idiopathic pulmonary fibrosis (IPF), to inform clinical trial design and marketing strategy. These were contrasted with data from qualitative interviews, informed by and collected from people with IPF and the clinical staff who recruit them to trials.

OBJECTIVE: To identify patient and professional perspectives for IPF drug trials to create opportunities for innovation in patient engagement.

DESIGN: Ethnography. Qualitative researcher embedded in a pharmaceutical organisation.

SETTING AND PARTICIPANTS: International patient insight reports to inform a clinical trial protocol (n = 1) and marketing strategy (n = 6), including the experiences of over 100 patients with IPF. In the United Kingdom, interviews with patients with IPF (n = 32) and the staff who support them clinically and recruit them to trials of new medicines (n = 19) at one specialist interstitial lung disease (ILD) centre.

RESULTS: Methodological practices inherent in inpatient insight reports ensured the perspectives of some people with IPF were overlooked. Interviews with a more marginalised population of people with IPF, and the staff who support them, identified that some found trial information confusing, trial practices frustrating and the opportunities to engage in trial design absent.

DISCUSSION: Current pharmaceutical practices of working with contract research organisations and patient organisations exclude the perspectives of patients with IPF who do not engage with either. Trial recruitment information needs to be tailored to the needs of individuals, and trial processes need to enable a wider group of patients to participate.

CONCLUSIONS: People with IPF want the opportunity to participate in drug trials and trial science. However, methodological rigour and deliberative practices are required to enable a wider group of patients to have a stake in the design and conduct of drug trials for rare diseases. The challenge now is for regulators to mandate such inclusive practices and for pharmaceutical organisations to adopt them.

PATIENT OR PUBLIC CONTRIBUTION: A Patient Advisory Group (PAG) comprising six people with IPF gave input on the research protocol and then on the scope and content of the ongoing research. Two patients from international patient organisations served as a Steering Group (SG). Members of these groups provided their interpretations of the study findings and gave insight on their experiences in clinical design and participation.

PMID:40235185 | DOI:10.1111/hex.70260

Sci Data. 2025 Apr 15;12(1):634. doi: 10.1038/s41597-025-04922-z.

ABSTRACT

Distinctive facial phenotypes serve as crucial diagnostic markers for many rare genetic diseases. Although AI-driven image recognition achieves high diagnostic accuracy, it often fails to explain its predictions. In this study, we present the Facial phenotype-Gene-Disease Dataset (FGDD), an explainable dataset collected from 509 research publications. It contains 1,147 data records encompassing 197 disease-causing genes, 437 facial phenotypes, and 211 disease entities, with 689 records having disease labels. Each data record represents a patient group and includes demographic information, variation information, and phenotype information. Baseline and explainability validations conducted on FGDD confirmed the dataset's effectiveness. FGDD supports the training of diagnostic models for rare genetic diseases while delivering explainable results, and provides a foundation for exploring intricate connections between genes, diseases, and facial phenotypes.

PMID:40234471 | DOI:10.1038/s41597-025-04922-z

Genome Med. 2025 Apr 14;17(1):40. doi: 10.1186/s13073-025-01464-2.

ABSTRACT

BACKGROUND: Both promoters and untranslated regions (UTRs) have critical regulatory roles, yet variants in these regions are largely excluded from clinical genetic testing due to difficulty in interpreting pathogenicity. The extent to which these regions may harbour diagnoses for individuals with rare disease is currently unknown.

METHODS: We present a framework for the identification and annotation of potentially deleterious proximal promoter and UTR variants in known dominant disease genes. We use this framework to annotate de novo variants (DNVs) in 8040 undiagnosed individuals in the Genomics England 100,000 genomes project, which were subject to strict region-based filtering, clinical review, and validation studies where possible. In addition, we performed region and variant annotation-based burden testing in 7862 unrelated probands against matched unaffected controls.

RESULTS: We prioritised eleven DNVs and identified an additional variant overlapping one of the eleven. Ten of these twelve variants (82%) are in genes that are a strong match to the individual's phenotype and six had not previously been identified. Through burden testing, we did not observe a significant enrichment of potentially deleterious promoter and/or UTR variants in individuals with rare disease collectively across any of our region or variant annotations.

CONCLUSIONS: Whilst screening promoters and UTRs can uncover additional diagnoses for individuals with rare disease, including these regions in diagnostic pipelines is not likely to dramatically increase diagnostic yield. Nevertheless, we provide a framework to aid identification of these variants.

PMID:40229884 | DOI:10.1186/s13073-025-01464-2

Am Soc Clin Oncol Educ Book. 2025 Jun;45(3):e100051. doi: 10.1200/EDBK-25-100051. Epub 2025 Apr 14.

ABSTRACT

The field of rare cancer research is rapidly transforming, marked by significant progress in clinical trials and treatment strategies. Rare cancers, as defined by the National Cancer Institute, occur in fewer than 150 cases per million people each year, yet they collectively represent a significant portion of all cancer diagnoses. Because of their infrequency, these cancers pose distinct challenges for clinical trials, including limited patient populations, geographical dispersion, and a general lack of awareness of treatment options. Economic limitations further complicate drug development, making initiatives such as the Orphan Drug Act essential for incentivizing research. The advent of next-generation sequencing (NGS) and precision medicine has been instrumental in identifying actionable genetic alterations in parallel with an explosion in the development of genomically targeted therapies, immunotherapies, and antibody drug conjugates. Advances in clinical NGS, precision medicine, and tumor-agnostic therapies have become central to the progress in rare cancer research. The development and approval of tumor-agnostic drugs, such as BRAF, NTRK, and RET inhibitors, and immunotherapy for mismatch repair deficient/microsatellite instability-high status cancers highlight the potential of personalized treatments across diverse cancer types and across the age spectrum. Collaborative trials from cooperative groups including SWOG DART, ASCO TAPUR, NCI-MATCH, pediatric COG-match, DRUP, IMPRESS, and innovative registrational basket and platform trials (eg, VE-Basket, ROAR, LIBRETTO-001, ARROW), along with patient advocacy group-run trials like TRACK, are enhancing access to clinical trials. In addition, artificial intelligence has the potential to improve the trial matching process. An integrated approach, combining these innovations in collaboration with multiple stakeholders, is crucial for advancing rare cancer research, offering hope for better patient outcomes and quality of life.

PMID:40228175 | DOI:10.1200/EDBK-25-100051

Hum Mutat. 2025 Feb 27;2025:6096758. doi: 10.1155/humu/6096758. eCollection 2025.

ABSTRACT

Affecting fewer than 20,000 people as defined in South Korea, rare diseases pose significant diagnostic challenges due to their diverse manifestations and genetic heterogeneity. Genome sequencing (GS) offers a promising solution by enabling simultaneous screening for thousands of rare genetic disorders. This study explores the diagnostic utility and necessity of GS within the government-funded Korean Regional Rare Disease Diagnostic Support Program (KR-RDSP), a collaborative initiative involving 11 regional rare disease centers across Korea. The program was launched as a proof-of-concept study in 2023 to equip the genetic clinics with a diagnostic tool to expedite the diagnoses for rare disease patients who reside outside the urban Seoul region where diagnostic resources are limited. The study leveraged GS to diagnose a cohort of 400 patients exhibiting a wide spectrum of symptoms. The overall diagnostic yield was 36.3% (145/400), with 4.8% (7/145) of the diagnosed patients being reported with variants that could not have been identified by chromosomal microarray or exome sequencing (ES), highlighting the added value of comprehensive genomic analysis. The implementation of a centralized GS analysis system streamlined the diagnostic process, enabling timely reporting within a reasonable turnaround time of ≤ 35 days. Segregation analysis by Sanger sequencing played a crucial role in confirming or reclassifying variant pathogenicity by elucidating inheritance patterns. Here, we summarize diagnostic statistics from the 400 GS dataset gathered from June 2023 to December 2023 and show interesting and informative case examples that illustrate the diagnostic efficacy of GS, highlighting its ability to uncover elusive genetic etiologies and provide personalized treatment insights. The study also highlights the successful implementation of the program for the 11 regional rare disease centers across Korea with a practical workflow, comprehensive testing, comparable diagnostic yield to previous reports, and, most importantly, reasonable turnaround time.

PMID:40226308 | PMC:PMC11987077 | DOI:10.1155/humu/6096758

Hum Mutat. 2024 Apr 29;2024:6411444. doi: 10.1155/2024/6411444. eCollection 2024.

ABSTRACT

Clinical exome and genome sequencing (ES/GS) have become indispensable diagnostic tools for rare genetic diseases (RGD). However, the interpretation of ES/GS presents a substantial operational challenge in clinical settings. Test interpretation requires the review of hundreds of genetic variants, a task that has become increasingly challenging given the rising use of ES/GS. In response, we present Clinical Assessment of Variants by Likelihood Ratios (CAVaLRi), which employ a modified likelihood ratio (LR) framework to assign diagnostic probabilities to candidate germline disease genes. CAVaLRi models aspects of the clinical variant assessment process, taking into consideration the predicted impact of the variant, the proband and parental genotypes, and the proband's clinical characteristics. It also factors in computational phenotype noise and weighs the relative significance of genotype, phenotype, and variant segregation information. We trained and tested CAVaLRi on variant and phenotype data from an internal cohort of 655 clinical ES cases. For validation, CAVaLRi's performance was benchmarked against four leading gene prioritization algorithms (Exomiser's hiPHIVE and PhenIX prioritizers, LIRICAL, and XRare) using a distinct cohort of 12,832 ES cases. Our findings reveal that CAVaLRi significantly outperforms its counterparts when clinician-curated phenotype sets are used, as evidenced by its superior precision-recall curve (PR AUC: 0.701) and average diagnostic gene rank (1.59). Notably, even when substituting highly focused clinician-curated phenotype sets with large and potentially nonspecific computationally derived phenotypes, CAVaLRi retains its precision (PR AUC: 0.658; diagnostic gene average rank: 1.68) and markedly outperforms other tools. In a large, heterogeneous validation cohort, CAVaLRi stood out as the most precise prioritization algorithm (PR AUC: 0.335; average diagnostic rank: 1.91). In conclusion, CAVaLRi presents a robust solution for prioritizing diagnostic genes, surpassing current methods. It demonstrates resilience to noisy, computationally-derived phenotypes, providing a scalable strategy to help labs focus on the most diagnostically relevant variants, thus addressing the growing demand for ES/GS interpretation.

PMID:40225936 | PMC:PMC11918498 | DOI:10.1155/2024/6411444

Hum Mutat. 2024 Apr 18;2024:9920230. doi: 10.1155/2024/9920230. eCollection 2024.

ABSTRACT

Although around 6% of the world's population is affected by rare diseases, only a small number of disease-modifying therapies are available. In recent years, antisense oligonucleotides (ASOs) have emerged as one option for the development of therapeutics for orphan diseases. In particular, ASOs can be utilized for individualized genetic treatments, addressing patients with a known disease-causing genetic variant, who would otherwise not be able to receive therapy. Careful prioritization of genetic variants amenable to an ASO approach is crucial to increase chances for successful treatments and reduce costs and time for drug development. At present, there is no consensus on how to systematically approach this selection procedure. Here, we present practical guidelines to evaluate disease-causing variants and standardize the process of selecting n-of-1 cases. We focus on variants leading to a loss of function in monogenic disorders and consider which splice-switching ASO-mediated treatments are applicable in each case. To ease the understanding and application of our guidelines, we created a hypothetical transcript covering different pathogenic variants and explained their evaluation in detail. We support our recommendations with real-life examples and add further considerations to be applied to specific cases to provide a comprehensive framework for selecting eligible variants.

PMID:40225926 | PMC:PMC11919232 | DOI:10.1155/2024/9920230

BMJ Paediatr Open. 2025 Apr 10;9(1):e003286. doi: 10.1136/bmjpo-2024-003286.

ABSTRACT

BACKGROUND: The National Health Service in the UK is the first national healthcare system to offer genomic sequencing for rare disease diagnosis as routine care. Non-genetic medical specialists, including paediatricians, can now request genomic testing for certain clinical indications. The primary purpose of this study was to evaluate the preparedness and confidence of paediatricians providing genomic sequencing in England. In addition, we assessed current practice, perceived utility of testing, barriers and enablers, prior genomics education and training preferences.

METHODS: A 26-item electronic survey for completion by paediatric specialists. Participants were recruited through national associations and a conference. Quantitative items were analysed using descriptive and inferential statistics. Open-ended question responses were analysed by qualitative content analysis.

RESULTS: 157 responses were included in the analysis. Only 49.0% reported feeling prepared for mainstreaming despite 75.0% reporting they had requested testing in the past 12 months, 47.7% indicating they had returned genomic sequencing results and 67.1% feeling genomic testing was useful. Mean confidence scores were lowest for tasks including using human phenotype ontology terminology on test request forms (3.9/10), interpreting genomic test results (4.8/10), discussing complex genomic results with patients and families (4.3/10) and integrating test results into patient care (4.7/10). Significantly higher average ranked genomic confidence was identified among those who had requested testing in the last 12 months compared with those who had not (Z=5.063, p<0.001, r=0.412). The most frequent barriers to mainstreaming were lack of training and knowledge (43.3%), determining patient eligibility (28.0%), lack of time (27.4%) and confidence (25.5%). Webinars (48.4%), followed by continued professional development meetings and/or conferences (38.9%), were the preferred mode of training.

CONCLUSIONS: Our data suggest that preparedness and confidence among paediatricians in genomics is currently lacking. Support from clinical genetics services, simplified referral forms and webinar training sessions could improve current practice.

PMID:40216446 | DOI:10.1136/bmjpo-2024-003286

Cell Mol Life Sci. 2025 Apr 10;82(1):156. doi: 10.1007/s00018-025-05652-6.

ABSTRACT

Rare disorders often represent a molecular deviation from hi-fidelity genomic integrity networks and are often perceived as too difficult or unimportant for further mechanistic studies. Here, we synthesize evidence demonstrating how valuable knowledge of biochemical pathways related to rare disorders can be for biomedicine. To this end, we describe several rare congenital lipid, protein, organic acid, and glycan metabolism disorders and discuss how rare phenotypes (such as "extreme responders") and case reports (such as the lenalidomide cases) have provided clues for drug discovery or repurposing. We also discuss how rare disorders such as Gaucher disease and ultra-rare genetic syndromes can provide insights into cancer and mTOR-driven metabolism, respectively. Our discussion highlights the continued value of biochemical pathways and studies in understanding human pathophysiology and drug discovery even in the genomics era.

PMID:40210765 | DOI:10.1007/s00018-025-05652-6

J Clin Transl Hepatol. 2025 Apr 28;13(4):339-357. doi: 10.14218/JCTH.2024.00402. Epub 2025 Jan 17.

ABSTRACT

Liver injury in Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) is a multifaceted disorder, lacking cohort homogeneity due to a variety of potential causes, including drugs, arsenic and other heavy metals, glyphosate, infections, and ultraviolet radiation. The goals of this review were (1) to analyze the role of diagnostic algorithms in assessing causality for potential culprits involved in the development of liver injury associated with immune-mediated SJS and TEN, which represent immune-based variant disorders within a continuous spectrum. Milder forms are classified as SJS or SJS/TEN overlap, while TEN is known as the most serious form; and (2) to interpret the findings that allow for the characterization of the different types of these disorders. The manuscript is based on an extensive literature search for single case reports, case cohorts, and review articles. Search terms included: Stevens-Johnson Syndrome, Toxic Epidermal Necrolysis, and specific diagnostic algorithms such as the Roussel Uclaf Causality Assessment Method (RUCAM) and the Algorithm of Drug Causality for Epidermal Necrolysis (ALDEN). For the purpose of basic feature description, the uniform term SJS/TEN is used in the current analysis. SJS/TEN presents with five different cohort types: SJS/TEN type (1), which refers to a cohort of SJS/TEN caused by drugs, as assessed by both ALDEN and RUCAM; type (2), representing SJS/TEN due to drugs and assessed by ALDEN only, but not by RUCAM; type (3), which includes a cohort of SJS/TEN caused by drugs, assessed by non-ALDEN and non-RUCAM tools; type (4), which focuses on a cohort of SJS/TEN caused by non-drug culprits, assessed by various tools; and type (5), which considers a cohort of SJS/TEN caused by unknown culprits. Using this new SJS/TEN typology will help better characterize individual features, personalize treatment, and clarify pathogenetic specifics for each of the five disease types. This new SJS/TEN typology provides clarity by replacing issues of inhomogeneity with cohort homogeneity.

PMID:40206276 | PMC:PMC11976437 | DOI:10.14218/JCTH.2024.00402

Pharm Stat. 2025 May-Jun;24(3):e70011. doi: 10.1002/pst.70011.

ABSTRACT

Patient enrollment can be a substantial burden in rare disease trials. One potential approach is to incorporate external control (EC) into concurrent randomized trials, or EC borrowing, to reduce such burden. Extensive research has been conducted to explore statistical methodologies. As in all designs, type I error control is essential. Conditional type I error rate has been used in the literature as the de facto metrics for type I error rate. However, research has shown that controlling the conditional type I error rate at the alpha level will disallow EC borrowing. Therefore, EC borrowing is practically at an impasse. Kopp-Schneider et al. concluded that a more appropriate metrics for type I error is necessary. We show that a trial with EC borrowing can be considered as a two-stage adaptive design. With this perspective, we propose to define type I error as the weighted averages of conditional type I error rate in trials with EC borrowing. Dynamic borrowing methods for controlling type I error are proposed.

PMID:40205746 | DOI:10.1002/pst.70011