[Marble disease (a rare disease of bones and teeth) -- with the description of one patient].
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Bone Diseases↗
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Results for “rare disease”
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Proteomics identify disease-associated variants in patients with rare diseases undiagnosed after genome sequencing.
Despite the introduction of genome sequencing (GS) for rare disease diagnostics, a genetic cause is not identified in most patients. Here, we explored the potential of proteomics to improve the diagnostic yield in 424 patients with rare diseases from the 100,000 Genomes Project (100kGP) without a genetic diagnosis. Serum proteomic profiling was performed using the Olink Explore 1536 assay (N = 1463 proteins). For 13 patients without genetic diagnoses, detection of lower serum protein "outliers" (z-score < -2) led to confirmed genetic diagnoses by resolving variants of uncertain significance or prioritizing genes for targeted GS reanalysis. For 23 additional patients without genetic diagnoses (64% of findings), we identified candidate gene-disease links and variants through convergent evidence from lower protein outliers and variants ranked through the variant prioritization tool Exomiser. For example, we identified a candidate heterozygous missense variant [Genome Aggregation Database (gnomAD) minor allele frequency = 0.006%] in tyrosine kinase with immunoglobulin-like and epidermal growth factor homology domains 1 (TIE1) that was only present in a patient with lower TIE1 serum abundance (z-score = -5.12) and their father, both of whom were affected by the same monogenic cardiac disorder, but in no other individuals from the 100kGP. Missense (52.5%) and splice region (27.5%) variants accounted for most diagnostic or candidate variants prioritized. This proof-of-principle study demonstrated that serum proteomics can support rare disease diagnosis and identify disease-causing genes in patients undiagnosed after GS, although successful implementation will likely depend on tissue specificity of protein expression, detectability in blood, proteomic platform coverage, and sensitivity.
Humans↗
Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: The example of monogenic diabetes.
Monogenic diabetes is characterized as a group of diseases caused by rare variants in single genes. Like for other rare diseases, multiple genes have been linked to monogenic diabetes with different measures of pathogenicity, but the information on the genes and variants is not unified among different resources, making it challenging to process them informatically. We have developed an automated pipeline for collecting and harmonizing data on genetic variants linked to monogenic diabetes. Furthermore, we have translated variant genetic sequences into protein sequences accounting for all protein isoforms and their variants. This allows researchers to consolidate information on variant genes and proteins linked to monogenic diabetes and facilitates their study using proteomics or structural biology. Our open and flexible implementation using Jupyter notebooks enables tailoring and modifying the pipeline and its application to other rare diseases.
Humans↗
RESCUE: An end-to-end multi-agent LLM system for proactive rare-disease patient screening in the EHR.
BACKGROUND: Rare diseases affect a significant portion of the global population, yet patients often endure a lengthy diagnostic odyssey, frequently missing the opportunity for timely diagnoses with exome or genome sequencing (ES/GS). Existing informatics tools often rely on pre-identified patients or rigid, institution-specific rule sets, failing to address the broader operational question of clinical utility and feasibility. METHODS: We introduce RESCUE (Rare Disease Detection and Escalation Support via a Learning Health System), an end-to-end, multi-agent LLM-powered workflow designed for proactive rare-disease diagnosis across the entire electronic health record (EHR). RESCUE utilizes a team of specialized agents including Ontology, Modeling, Screening, and Review, to automate the screening process to identify candidates for diagnostic testing based on their clinical features. The Ontology Agent classifies clinical data into a four-tier genetic-evidence taxonomy; the Modeling Agent builds a positive-unlabeled (PU) XGBoost classifier to identify potential cases; the Screening Agent applies these models across the EHR population; and the Review Agent evaluates candidates by sampling clinical notes to ensure medical necessity and operational feasibility for genomic testing. RESULTS: Using electronic medical record data from a pediatric hospital, our retrospective evaluation on a holdout set (n=12,591) demonstrates strong discrimination between patients who received diagnostic genomic testing and those who did not (AUC 0.808). Of nearly 500,000 patients in the institutional base, 175,842 met inclusion criteria for screening; among these, RESCUE-flagged candidates were 7.4-fold more likely to receive subsequent genomic assessments compared to controls. Blinded manual chart reviews confirmed that RESCUE identifies previously missed, medically appropriate patients for ES/GS with 80% precision, while simultaneously accounting for prior testing history. CONCLUSIONS: By decoupling expert roles into modular agents, RESCUE offers a flexible, scalable, and adaptable framework for screening patients for rare-disease diagnostic genomic testing. This approach overcomes the limitations of traditional rule-based methods and provides a reproducible, agentic pathway to reduce diagnostic delays and improve patient care at an institutional scale.
Journal Article↗
PRISM: privacy-preserving rare disease analysis using fully homomorphic encryption.
MOTIVATION: Rare diseases affect millions of people worldwide, yet their genomic foundations remain poorly understood due to limited patient data and strict privacy regulations, such as the General Data Protection Regulation (GDPR) (https://gdpr.eu/tag/gdpr/) in March 2025. These restrictions can hinder the collaborative analysis of genomic data necessary for uncovering disease-causing variants. RESULTS: We present PRISM, a novel privacy-preserving framework based on fully homomorphic encryption (FHE) that facilitates rare disease variant analysis across multiple institutions without exposing sensitive genomic information. To address the challenges of centralized trust, PRISM is built upon a Threshold FHE scheme. This approach decentralizes key management across participating institutions and ensures no single entity can unilaterally decrypt sensitive data. Our method filters disease-causing variants under recessive, dominant, and de novo inheritance models entirely on encrypted data. We propose two algorithmic variants: a multiplication-intensive (MUL-IN) approach and an addition-intensive (ADD-IN) approach. The ADD-IN algorithms minimize the number of costly multiplication operations, enabling up to a 17× improvement in runtime for recessive/dominant filtering and 22× for de novo filtering, compared to MUL-IN methods. While ADD-IN produces larger ciphertexts, efficient parallelization via SIMD and multithreading allows it to handle millions of variants in reasonable time. To the best of our knowledge, this is the first study that utilizes FHE for privacy-preserving rare disease analysis across multiple inheritance models, demonstrating its practicality and scalability in a single-cloud setting. AVAILABILITY AND IMPLEMENTATION: The source code and the data used in this work can be found in https://github.com/mdppml/PRISM.git.
Computer Security↗
Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.
Rare diseases collectively affect 1 in 10 individuals, yet current genetic testing fails to identify a causal variant for most cases. At present, cytogenetic methods and/or sequencing approaches such as exome (ES) or short-read genome sequencing (srGS) represent the state-of-the-art for comprehensive clinical discovery of sequence and structural variants (SVs), including copy number variants, balanced SVs, complex SVs, and tandem repeats (TRs). Recently, long-read genome sequencing (lrGS), coupled with multiomics data, has presented great promise to resolve variation in genomic regions recalcitrant to characterization by srGS such as highly repetitive simple repeat sequences and segmental duplications. However, there are few guidelines to enable clinical interpretation of genetic variation in these highly repetitive genomic regions, and the enthusiasm of the field in adopting lrGS has made it difficult to assess the true added diagnostic yield of this technology due to widely variable and inconsistently applied analytic pipelines and variable degrees of pre-screening by ES or srGS. Here, we investigated the contribution of SVs to rare diseases using srGS as a front-line strategy when paired with highly sensitive SV discovery and evaluate the added diagnostic yield of incorporating lrGS for a subset of cases. Our srGS analysis encompassed 1,462 families (3,450 individuals) recruited through the Broad Institute Center for Mendelian Genetics and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) programs. Diagnostic SVs were identified in 5.4% of cases (79/1,462), of which 80% were uniquely detectable by srGS compared to standard cytogenetic techniques. For 96 families (including 10 families with a heterozygous variant observed in a known recessive gene of clinical relevance), we performed lrGS with methylation profiling, as well as long-read transcriptomic analyses in a subset of 20 trios. Analyses with lrGS yielded over 25,000 SVs per genome, 63% of which were not captured by srGS, along with an additional ~200 rare SNV/indels per genome not previously captured and 12 differentially methylated regions per genome. Among these, we identified only one diagnostic variant not interpreted by srGS, an apparently mosaic de novo SNV in CASK that was absent in the srGS callset due to allelic imbalance. No new diagnoses were supported by long-read transcriptomics or episignatures. In this well characterized rare disease cohort, the added diagnostic yield was thus 1.04% (1/96 families). Following a systematic literature review of prior lrGS studies, we find that most reported diagnoses were detectable by srGS and that our added diagnostic yield is consistent with those prior studies. These studies emphasize the significant impact of comprehensive SV discovery in rare disease cases and further demonstrate the power for increased discovery of novel genomic variation and episignatures from lrGS. Nonetheless, they also serve to temper expectations of dramatic diagnostic advances in rare disease patients until there is more extensive annotation of the functional and clinical impact of all coding and noncoding variation uniquely accessible to lrGS with extensive reference databases spanning highly repetitive genomic sequencing that could be enabled by this transformative technology.
Journal Article↗
P2X7 Receptor in Rare Diseases: Shared Molecular Mechanisms and Therapeutic Implications.
Rare diseases (RDs) are individually uncommon but collectively affect a large global population, and the vast majority still lack effective disease-modifying therapies. With advances in genomics and data-sharing platforms, research has increasingly shifted from a single-disease perspective to the search for convergent molecular pathways that might be shared across clinically distinct entities. In this context, the purinergic P2X7 receptor (P2X7R) has emerged as a putative "shared molecular platform" due to its central role in inflammation amplification, cell death and immune regulation. P2X7R is an ATP-gated ion channel with unique structural and functional features: under high extracellular ATP, it not only forms a non-selective cation channel but can also dilate into a "large pore" permeable to macromolecules, thereby triggering Ca2+overload, NLRP3 inflammasome assembly, reactive oxygen species (ROS) production and apoptotic/necrotic-like cell death. This review briefly outlines the epidemiology of RDs and the structural-functional characteristics of P2X7R, then systematically summarizes current evidence linking P2X7R to multiple rare diseases, including Charcot-Marie-Tooth disease, Guillain-Barré syndrome, amyotrophic lateral sclerosis, Huntington's disease, multiple sclerosis, and selected inflammatory and metabolic RDs (CAPS, familial Mediterranean fever, Systemic sclerosis, Dravet syndrome and Gaucher disease). By comparing P2X7R expression and functional alterations, downstream signaling pathways and pharmacological data from animal models across these conditions, we propose that a P2X7R-dependent network centered on a "Ca2+-NLRP3-inflammation/cell death axis" may constitute a common pathogenic backbone for diverse RDs. At the same time, disease-specific spatiotemporal expression patterns of P2X7R in central vs peripheral nervous systems and in immune vs target organ cells confer marked context dependence and "double-edged sword" properties. Finally, we discuss opportunities and challenges for P2X7R-targeted strategies, including the impact of disease stage and sex differences on therapeutic efficacy, and key bottlenecks in translating preclinical findings into clinical benefit. A deeper understanding of both shared and disease-specific roles of P2X7R may provide a conceptual framework and therapeutic entry point for precision stratification and multi-target interventions in rare diseases.
P2X7 receptor↗
Targeted Next-Generation Sequencing in Rare Diseases.
Targeted next-generation sequencing (NGS) in rare disease focuses on genetic analysis of specific regions in genome that are linked to a rare disease. In addition to library preparation, sequencing, and data analysis, targeted NGS includes an additional step of target enrichment of selected genes and regions. It allows for more sensitive and profound sequencing, as it is a fast and cost-effective approach with less data burden and is therefore often a method of choice for identifying rare variants in known genes, especially in diagnostics of rare diseases. Several in silico tools address the pathogenicity predictions of rare variants of unknown significance (VUS) and can therefore facilitate clinical interpretation.
Rare Diseases↗
Targeted Next-Generation Sequencing for Improved Clinical Outcomes in People Living With Rare Diseases in Global South: Protocol for a Systematic Review and Meta-Synthesis.
BACKGROUND: Rare diseases affect many individuals and pose major challenges in diagnosis and treatment, especially in Global South countries where health care resources are limited. Targeted next-generation sequencing (NGS) has significantly advanced diagnostic accuracy and clinical care for rare diseases globally; however, its implementation and impact within the Global South context remain insufficiently studied. OBJECTIVE: This study aims to evaluate the use, clinical benefits, challenges, and implementation outcomes of targeted NGS for diagnosing and managing rare diseases in Global South populations. Specifically, it seeks to quantify the diagnostic yield of NGS, examine its influence on subsequent clinical decision-making, and identify principal barriers to, and facilitators of, the implementation of targeted NGS approaches in these contexts. METHODS: This protocol follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We will systematically search PubMed, Scopus, and Web of Science for studies published between 2005 and 2025 that report on the use of targeted NGS in Global South population with rare diseases. Two reviewers will independently perform study selection, data extraction, quality assessment, and evaluation of risk of bias by using QUADAS-2 for diagnostic accuracy studies and the risk of bias assessment tool for nonrandomized studies. Meta-analyses will be conducted to estimate pooled outcomes for diagnostic yield, with heterogeneity assessed using random effects models. Heterogeneity will be further examined through visual inspection of forest plots and by evaluating the chi-square test and I² statistic. RESULTS: The protocol has been registered with PROSPERO (CRD420251078455). Database search or screening, data extraction, and data synthesis are planned to commence in June 2026 and conclude by September 2026. Study findings will synthesize the diagnostic yield, clinical impact, and contextual determinants influencing the implementation of targeted NGS in Global South health care settings. CONCLUSIONS: This review will provide evidence on the application, advantages, limitations, and clinical outcomes of targeted NGS for individuals affected by rare diseases in countries of the Global South. The finding will identify priorities for capacity strengthening, policy development, and future genomic research. TRIAL REGISTRATION: PROSPERO CRD420251078455; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251078455. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/85150.
Rare Diseases↗
The cost and cost trajectory of genome sequencing and bioinformatics analysis for Indigenous children with suspected rare diseases.
PURPOSE: Indigenous peoples are underrepresented in reference genome libraries. Consequently, rare disease diagnosis may require bespoke bioinformatics analyses of genome sequences. Establishing diagnostic cost is crucial to support policy development for equitable diagnosis of rare diseases. We estimated the cost and cost trajectory of diagnostic genome sequencing and bioinformatics for Indigenous participants with suspected rare diseases. METHODS: We conducted a microcosting study of Indigenous children and their families receiving genome sequencing through Canada's Silent Genomes Project. Invoice data informed the costs of genome sequencing. We conducted a time-and-motion study for bioinformatics analyses, including labor, computing, and data storage costs. RESULTS: With standard bioinformatics, costs ranged from C$3645 (SD: 455) for singletons to C$7402 (SD: 566) for trios. With advanced, bespoke bioinformatics, costs ranged from C$5344 (SD: 634) for singletons to C$9760 (SD: 822) for trios. Genome sequencing was a primary cost driver; however, sequencing costs decreased by 61% over 4 years. Bioinformatics costs ranged from 21.3% to 58.3% of the total costs. The time required for bioinformatics ranged from 71 hours to 215 hours for standard and advanced analyses, respectively. CONCLUSION: Genome sequencing costs decreased over time. Bioinformatics is a significant cost driver, particularly for bespoke analyses arising from nonrepresentative reference libraries.
Humans↗
[Achievements and Expectations of the Rare Disease Diagnostic Support Program in the Republic of Korea].
OBJECTIVES: The Rare Disease Diagnostic Support Program in the Republic of Korea aims to improve early diagnosis and diagnostic yield for patients with rare diseases, particularly for those residing in non-metropolitan areas, by providing whole genome sequencing (WGS) services through regional medical institutions. This study evaluated the performance of the program, focusing on its clinical utility, including early diagnosis and treatment linkage, and its policy impact related to patient benefits. METHODS: From August 2024, WGS was performed on 410 patients with suspected rare diseases at 23 institutions outside the metropolitan area. A one-stop diagnostic pathway was established to perform sample collection, test referral, report delivery, and genetic counseling within a single clinical flow based on the patient’s location of residence. Sequencing was performed by external laboratories. RESULTS: Among the 410 patients, pathogenic variants were identified in 129 (31.5%), with a turnaround time of 28 days. Of those diagnosed, 78.2% received treatment benefits via national programs such as co-payment exemption and medical expense support programs. Approximately 30% of the patients were eligible for therapeutic intervention, particularly medication or dietary therapy. Family genetic testing of three members identified potential carriers or high-risk groups in 28 households (65.1%). Consent for secondary findings was 99.0%, with clinically significant variants found in 3.9% of cases. CONCLUSIONS: The program demonstrated clinical value by improving diagnostic accessibility, reducing regional disparities, facilitating timely treatment, and supporting preventive care through family risk identification. These findings support the need for sustainable expansion of genome-based diagnostic services in the national health policy.
Diagnosis↗
How AI Is Speeding Up the Diagnostic Odyssey for Rare Diseases.
The road to diagnosis can be long and sometimes unending for rare diseases, requiring training and resources that many clinics do not have. In this News and Perspectives article, JMIR Correspondent Simon Spichak reports on how AI initiatives at a children's hospital in the United States and one in Canada are helping bridge that gap and could fundamentally reshape the diagnostic experience for children and families living with rare diseases.
Rare Diseases↗
Equity in genome sequencing for rare disease diagnosis: a cross-sectional analysis of data from the UK 100,000 Genomes Project.
BACKGROUND: Genome sequencing has improved rare disease diagnosis and is now part of routine clinical care in the National Health Service in England. Automated prioritisation pipelines narrow millions of variants per patient to a small subset for clinical review, a process that relies on allele frequency resources that do not fully represent human genetic diversity. We assessed ancestry-related differences in variant prioritisation and diagnostic outcomes in patients from the UK 100,000 Genomes Project. METHODS: We analysed 29,405 rare disease probands with genome sequencing and linked clinical outcomes data. We used multivariable regression to assess ancestry-related differences in the number of variants prioritised for clinical review, the proportion of prioritised variants that were recorded as diagnostic, and diagnostic yield. We also evaluated the use of ancestry-stratified allele frequency filters derived from an independent, diverse UK cohort (n = 33,724). FINDINGS: Compared with the European ancestry group, the East African group had nearly three times more variants prioritised for clinical review (IRR 2.77, 95% CI 2.33-3.29). Other non-European groups also had significantly higher counts. Diagnostic yield was similar across ancestry groups after adjustment (LRT p = 0.1650). Prioritised variants were less likely to be recorded as diagnostic in East African (OR 0.32, 95% CI 0.22-0.46), West African (0.47, 0.39-0.57), South Asian (0.65, 0.58-0.73), and Middle Eastern (0.68, 0.54-0.86) groups. Applying ancestry-stratified allele-frequency filters removed 3.1% of prioritised variants overall-24.3% in the East African group-without loss of diagnostic sensitivity, including 29.5% of recorded VUS in this group. INTERPRETATION: Differences in the likelihood of prioritised variants being recorded as diagnostic partly reflect limitations of current allele frequency resources, which use broad population groupings that mask within-group diversity. Increased representation of diverse ancestries in reference databases and better estimation of ancestry-appropriate allele frequencies will help reduce inefficiencies and improve equity in variant prioritisation for rare disease diagnosis. FUNDING: The UK Department of Health and Social Care and the EU's Horizon 2020 Research and Innovation Programme.
Humans↗
Comparing the performance of exome and genome sequencing for rare disease diagnostics: A randomized implementation effectiveness trial.
PURPOSE: Exome sequencing (ES) and genome sequencing (GS) can improve rare disease diagnosis but are not routinely available in many jurisdictions. To inform implementation, we report on a randomized implementation effectiveness trial comparing ES and GS. METHODS: Eligible trios were randomized to receive ES or GS in the same clinically accredited laboratory. Patient-level data on diagnostic utility and turnaround times were collected. Outcomes were compared statistically between clinically important subgroups. RESULTS: Of 1048 patients, 68.5% had syndromic intellectual disability/developmental delay (ID/DD) and 20.5% had multisystem disorders without ID/DD. Most had prior genetic test(s) that were nondiagnostic (95.5%), and of these, 91.6% included chromosome microarray. Diagnostic yields were 33.8% and 33.6%, for ES (n = 526) and GS (n = 522), respectively. Within sequencing groups, diagnostic results were more frequent among those with ID/DD than those without (P < .005). For routine (ie, nonexpedited) patients (n = 1020), 87.0% were reported in <12 weeks, and the mean turnaround time was 55.5 days (SD: 24.0). Turnaround time for ES and GS did not differ; however, result type (P < .001) and age of onset (P < .005) significantly affected turnaround time. CONCLUSION: Findings provide robust evidence of diagnostic utility and timeliness of ES and GS and will inform policy related to the organization, delivery, and reimbursement of clinical-grade genome diagnostics for rare diseases.
Adolescent↗
Improved diagnosis of patients with rare diseases through the application of constrained coding region annotation and de novo status.
PURPOSE: Identifying the pathogenic variant in a patient with rare disease (RD) is the first step in ending their diagnostic odyssey. De novo (Dn) variants affecting protein-coding DNA are a well-established cause of Mendelian disorders in patients with RD. Constrained coding regions (CCRs) are specific segments of coding DNA that are devoid of functional variants in healthy individuals. METHODS: We evaluated the diagnostic utility of incorporating combined Dn/CCR status into the variant prioritization cascade for patients with RD that have undergone genomic sequencing. Using the Genomics England 100,000 Genomes Project v12, we selected 3090 trios that have undergone diagnostic evaluation and been analyzed with an advanced Dn identification pipeline. RESULTS: Our analysis shows that the diagnostic rate increased from 71% in the full cohort to 87% for Dn/CCR variants. Of note, manual evaluation of the Dn/CCR variants from undiagnosed patients with clinical follow-up revealed a diagnosis for 13 further patients. This outcome increases the diagnostic rate for Dn/CCR variants to 91% and suggests that the application of this metric can prioritize diagnostic variants in undiagnosed patients. CONCLUSION: We demonstrate the potential clinical utility of performing bespoke Dn analyses of patients with RD and for incorporating CCR information into the filtering cascade to prioritize pathogenic variants.
Humans↗
[Some rare diseases of the esophagus (author's transl)].
Cancer excepted all other diseases of the esophagus are rare. Diverticula, benign tumors, perforations and the pathology of the cardia (hiatus hernia, achalasia and esophageal varices) are not studied here. We took into consideration the following diseases only: spasm of the cricopharyngeal muscle, Plummer-Vinson or Kelly-Paterson syndrome, cervical osteophytosis, dysphagia lusoria, benign and malignant mediastinal lymphatic nodes, Schatzki ring of the lower esophagus and esophageal duplications.
Aged↗
[Kaposi sarcoma. A short review on a rare disease].
Pathological, clinical, epidemiological and immunological aspects of a rare tumor, Kaposi's sarcoma, are briefly discussed. The prevalence of the disease in an African population raises questions about genetic and environmental factors in its carcinogenesis. Immunological data indicate a probable viral origin. The clinical patterns seem to be influenced by alterations of the immune defense mechanisms. Most questions about its biological behaviour remain to be answered yet.
Adolescent↗
[Bilateral rupture of the quadriceps tendon, a rare disease pattern (author's transl)].
The article reports on the rare bilateral rupture of the quadriceps tendon. This tendon will rupture more readily after it has undergone a degenerative change. A distinctly noticeable pit, which may be masked by a haematoma, is clinically prominent, as well as an absolute active inhibition of stretching and an abnormal lateral mobility of the patella. Immediate repair is the method of choice. The article describes the method of operation.
Accidents↗