Orphanet J Rare Dis. 2024 Feb 10;19(1):55. doi: 10.1186/s13023-024-03063-7.

ABSTRACT

BACKGROUND: Rare diseases affect approximately 400 million people worldwide. Many of them suffer from delayed diagnosis. Among them, NPHP1-related renal ciliopathies need to be diagnosed as early as possible as potential treatments have been recently investigated with promising results. Our objective was to develop a supervised machine learning pipeline for the detection of NPHP1 ciliopathy patients from a large number of nephrology patients using electronic health records (EHRs).

METHODS AND RESULTS: We designed a pipeline combining a phenotyping module re-using unstructured EHR data, a semantic similarity module to address the phenotype dependence, a feature selection step to deal with high dimensionality, an undersampling step to address the class imbalance, and a classification step with multiple train-test split for the small number of rare cases. The pipeline was applied to thirty NPHP1 patients and 7231 controls and achieved good performances (sensitivity 86% with specificity 90%). A qualitative review of the EHRs of 40 misclassified controls showed that 25% had phenotypes belonging to the ciliopathy spectrum, which demonstrates the ability of our system to detect patients with similar conditions.

CONCLUSIONS: Our pipeline reached very encouraging performance scores for pre-diagnosing ciliopathy patients. The identified patients could then undergo genetic testing. The same data-driven approach can be adapted to other rare diseases facing underdiagnosis challenges.

PMID:38336713 | PMC:PMC10858490 | DOI:10.1186/s13023-024-03063-7

Orphanet J Rare Dis. 2024 Feb 7;19(1):47. doi: 10.1186/s13023-024-03041-z.

ABSTRACT

Health technology assessment (HTA) decisions for pharmaceuticals are complex and evolving. New rare disease treatments are often approved more quickly through accelerated approval schemes, creating more uncertainties about clinical evidence and budget impact at the time of market entry. The use of real-world evidence (RWE), including early coverage with evidence development, has been suggested as a means to support HTA decisions for rare disease treatments. However, the collection and use of RWE poses substantial challenges. These challenges are compounded when considered in the context of treatments for rare diseases. In this paper, we describe the methodological challenges to developing and using prospective and retrospective RWE for HTA decisions, for rare diseases in particular. We focus attention on key elements of study design and analyses, including patient selection and recruitment, appropriate adjustment for confounding and other sources of bias, outcome selection, and data quality monitoring. We conclude by offering suggestions to help address some of the most vexing challenges. The role of RWE in coverage and pricing determination will grow. It is, therefore, necessary for researchers, manufacturers, HTA agencies, and payers to ensure that rigorous and appropriate scientific principles are followed when using RWE as part of decision-making.

PMID:38326894 | PMC:PMC10848432 | DOI:10.1186/s13023-024-03041-z

BMJ Open. 2024 Feb 6;14(2):e080529. doi: 10.1136/bmjopen-2023-080529.

ABSTRACT

INTRODUCTION: Rapid genomic sequencing (rGS) in critically ill infants with suspected genetic disorders has high diagnostic and clinical utility. However, rGS has primarily been available at large referral centres with the resources and expertise to offer state-of-the-art genomic care. Critically ill infants from racial and ethnic minority and/or low-income populations disproportionately receive care in safety-net and/or community settings lacking access to state-of-the-art genomic care, contributing to unacceptable health equity gaps. VIrtual GenOme CenteR is a 'proof-of-concept' implementation science study of an innovative delivery model for genomic care in safety-net neonatal intensive care units (NICUs).

METHODS AND ANALYSIS: We developed a virtual genome centre at a referral centre to remotely support safety-net NICU sites predominantly serving racial and ethnic minority and/or low-income populations and have limited to no access to rGS. Neonatal providers at each site receive basic education about genomic medicine from the study team and identify eligible infants. The study team enrols eligible infants (goal n of 250) and their parents and follows families for 12 months. Enrolled infants receive rGS, the study team creates clinical interpretive reports to guide neonatal providers on interpreting results, and neonatal providers return results to families. Data is collected via (1) medical record abstraction, (2) surveys, interviews and focus groups with neonatal providers and (3) surveys and interviews with families. We aim to examine comprehensive implementation outcomes based on the Proctor Implementation Framework using a mixed methods approach.

ETHICS AND DISSEMINATION: This study is approved by the institutional review board of Boston Children's Hospital (IRB-P00040496) and participating sites. Participating families are required to provide electronic written informed consent and neonatal provider consent is implied through the completion of surveys. The results will be disseminated via peer-reviewed publications and data will be made accessible per National Institutes of Health (NIH) policies.

TRIAL REGISTRATION NUMBER: NCT05205356/clinicaltrials.gov.

PMID:38320840 | PMC:PMC10859977 | DOI:10.1136/bmjopen-2023-080529

Mayo Clin Proc. 2024 Feb;99(2):318-335. doi: 10.1016/j.mayocp.2023.03.003.

ABSTRACT

Research cannot maximize population health unless it improves health for all members of the public, including special populations such as children, older adults, and people living with rare diseases. Each of these categories require special considerations when planning and performing clinical trials, and common threads of ethical conduct of research in vulnerable populations appear throughout. In this review, definitions of each of the three categories of special population (children, older adults, and rare diseases) are discussed in terms of US research regulations, the unique challenges to conducting clinical trials for these special populations, critical ethical issues, and opportunities for innovative ways to design and operationalize clinical trials in special populations. Additional critical attention is focused on factors that influence the generalizability of study results to reduce health disparities, as well as the importance of community engagement and advocacy groups that can help to educate potential trial participants of the benefits of clinical trial participation.

PMID:38309939 | PMC:PMC10842263 | DOI:10.1016/j.mayocp.2023.03.003

Int J Palliat Nurs. 2024 Jan 2;30(1):12-19. doi: 10.12968/ijpn.2024.30.1.12.

ABSTRACT

BACKGROUND: Neuromuscular diseases are inherited and the prevalance of neuromuscular disease is estimated to be around 1:2000.

METHODS: This cross-sectional research was conducted with a qualitative research model. Data were collected from patients with an online survey using the snowball sampling method. The study was conducted in accordance with the STROBE checklist methodology. Frequencies and percentages were used to analyse demographic data, and content analysis was used for qualitative opinions.

RESULTS: Most of the participants were men and their education levels were low. Participants reported experiencing physical and socio-economic barriers to accessing healthcare. Participants also stated that these barriers have worsened since COVID-19.

CONCLUSIONS: Patients with hereditary myopathy are stigmatised by society and face different problems depending on the type of disease and level of function. It is recommended that decision-makers enable patients with hereditary myopathy in exceptional situations to access healthcare services and take steps to resolve their problems.

PMID:38308604 | DOI:10.12968/ijpn.2024.30.1.12

Neuromuscul Disord. 2024 Mar;36:16-22. doi: 10.1016/j.nmd.2024.01.001. Epub 2024 Jan 9.

ABSTRACT

The European Joint Programme on Rare Diseases (EJPRD) funded the workshop "LAMA2-Muscular Dystrophy: Paving the road to therapy", bringing together 40 health-care professionals, researchers, patient-advocacy groups, Early-Career Scientists and other stakeholders from 14 countries. Progress in natural history, pathophysiology, trial readiness, and treatment strategies was discussed together with efforts to increase patient-awareness and strengthen collaborations. Key outcomes were (a) ongoing natural history studies in 7 countries already covered more than 350 patients. The next steps are to include additional countries, harmonise data collection and define a minimal dataset; (b) therapy development was largely complementary. Approaches included LAMA2-replacement and correction, LAMA1-reactivation, mRNA modulation, linker-protein expression, targeting downstream processes and identifying modifiers, using viral vectors, muscle stem cells, iPSC and mouse models and patient lines; (c) LAMA2-Europe will inform patients (-representatives) worldwide on standards of care and scientific progress, and enable sharing experiences. Follow-up monthly online meetings and research repositories have been established to create sustainable collaborations.

PMID:38306718 | DOI:10.1016/j.nmd.2024.01.001

RMD Open. 2024 Feb 2;10(1):e003591. doi: 10.1136/rmdopen-2023-003591.

ABSTRACT

OBJECTIVES: To estimate prevalence, incidence and mortality rates, and annual healthcare costs of primary Sjögren's syndrome (pSS) and SS associated with other autoimmune disorders (SS+AID) in France.

METHODS: French national healthcare claims-based study within the prospective Système National des Données de Santé database that includes the majority of the French population. An algorithm was developed to identify patients with SS and SS-related healthcare claims were analysed between 2011 and 2018.

RESULTS: Overall, 23 848 patients with pSS and 14 809 with SS+AID were identified. From 2011 to 2018, the prevalence rate increased slightly for pSS (23-32 per 100000) and SS+AID (16-20 per 100 000), with females comprising 90%-91% and 92%-93% of cases, respectively. The incidence rate of SS per 100 000 persons decreased from 2012 (pSS: 4.3; SS+AID: 2.0) to 2017 (pSS: 0.7; SS+AID: 0.3). Mortality rates per 100 000 persons increased from 2012 to 2018 in patients with pSS (0.2-0.8) or SS+AID (0.1-0.5); mean age of death also increased. Artificial tears and hydroxychloroquine were the most common drug reimbursements. Less than half of patients received annual specialist care from a dentist or ophthalmologist. Healthcare costs associated with SS increased from 2011 to 2018 and exceeded the national estimate of expected costs for chronic diseases.

CONCLUSION: In this large French population database study, the low prevalence of pSS confirms that it is an orphan disease. SS is clinically and economically burdensome; these findings may help clinicians better understand routine healthcare received by patients.

PMID:38307699 | PMC:PMC10840052 | DOI:10.1136/rmdopen-2023-003591

Clin Hemorheol Microcirc. 2024 Feb 1. doi: 10.3233/CH-232071. Online ahead of print.

ABSTRACT

BACKGROUND: Differentiation of high-flow from low-flow vascular malformations (VMs) is crucial for therapeutic management of this orphan disease.

OBJECTIVE: A convolutional neural network (CNN) was evaluated for differentiation of peripheral vascular malformations (VMs) on T2-weighted short tau inversion recovery (STIR) MRI.

METHODS: 527 MRIs (386 low-flow and 141 high-flow VMs) were randomly divided into training, validation and test set for this single-center study. 1) Results of the CNN's diagnostic performance were compared with that of two expert and four junior radiologists. 2) The influence of CNN's prediction on the radiologists' performance and diagnostic certainty was evaluated. 3) Junior radiologists' performance after self-training was compared with that of the CNN.

RESULTS: Compared with the expert radiologists the CNN achieved similar accuracy (92% vs. 97%, p = 0.11), sensitivity (80% vs. 93%, p = 0.16) and specificity (97% vs. 100%, p = 0.50). In comparison to the junior radiologists, the CNN had a higher specificity and accuracy (97% vs. 80%, p < 0.001; 92% vs. 77%, p < 0.001). CNN assistance had no significant influence on their diagnostic performance and certainty. After self-training, the junior radiologists' specificity and accuracy improved and were comparable to that of the CNN.

CONCLUSIONS: Diagnostic performance of the CNN for differentiating high-flow from low-flow VM was comparable to that of expert radiologists. CNN did not significantly improve the simulated daily practice of junior radiologists, self-training was more effective.

PMID:38306026 | DOI:10.3233/CH-232071

Schmerz. 2024 Feb;38(1):3-5. doi: 10.1007/s00482-024-00789-y. Epub 2024 Feb 2.

NO ABSTRACT

PMID:38305884 | DOI:10.1007/s00482-024-00789-y

Lancet Haematol. 2024 Feb;11(2):e85. doi: 10.1016/S2352-3026(24)00011-5.

NO ABSTRACT

PMID:38302225 | DOI:10.1016/S2352-3026(24)00011-5

Rev Med Suisse. 2024 Jan 31;20(859):255-258. doi: 10.53738/REVMED.2024.20.859.255.

ABSTRACT

The sequential effects of romosozumab and denosumab in osteoporosis are shown in real-life, while the mechanisms of post-denosumab rebound are reviewed extensively. A network meta-analysis confirms the superiority of anabolics vs anti-resorptives on fracture reduction, while the latter shown a reduction of mortality in a large population-based study. Fracture risk prediction by FRAXPlus is improved. New meta-analyses confirm the benefits of Vitamin D on fractures and falls. Finally, multiples trials with new molecules for the treatment of rare bone diseases, including osteogenesis imperfecta, fibrous dysplasia and hypoparathyroidism, shown promising results.

PMID:38299957 | DOI:10.53738/REVMED.2024.20.859.255

Med Sci (Paris). 2024 Jan;40(1):30-34. doi: 10.1051/medsci/2023192. Epub 2024 Feb 1.

ABSTRACT

TITLE: La Filière de Santé Maladies Rares TÊTECOU - Améliorer le parcours de soins, la formation et la recherche des malformations de la tête, du cou et des dents.

ABSTRACT: Les Filières de Santé Maladies Rares (FSMR) sont des structures nationales, labellisées par les ministères en charge de la Santé et de la Recherche, dans le cadre des Plans nationaux maladies rares (PNMR). Depuis 2004, les maladies rares sont en effet définies comme un enjeu de santé publique et bénéficient d’une organisation et de moyens spécifiques mis en œuvre dans les PNMR successifs.

PMID:38299900 | DOI:10.1051/medsci/2023192

HGG Adv. 2024 Jan 30:100273. doi: 10.1016/j.xhgg.2024.100273. Online ahead of print.

ABSTRACT

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 14 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism, reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated an overall milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, and some had alternative symptomatologies with rational biological links to SMC3. Analyses of tumor and model system transcriptomic data and epigenetic data in a subset of cases suggest that SMC3 pLoF variants reduce SMC3 expression but do not strongly support clustering with functional genomic signatures of typical CdLS. Our finding of substantial population-scale LoF intolerance in concert with variable growth and developmental features in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multi-layered genomic data paired with careful phenotyping.

PMID:38297832 | DOI:10.1016/j.xhgg.2024.100273

BMC Med Inform Decis Mak. 2024 Jan 31;24(1):30. doi: 10.1186/s12911-024-02439-w.

ABSTRACT

OBJECTIVE: Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field. These processes rely on using ontology concepts, often from the Human Phenotype Ontology, in conjunction with a phenotype concept recognition task (supported usually by machine learning methods) to curate patient profiles or existing scientific literature. With the significant shift in the use of large language models (LLMs) for most NLP tasks, we examine the performance of the latest Generative Pre-trained Transformer (GPT) models underpinning ChatGPT as a foundation for the tasks of clinical phenotyping and phenotype annotation.

MATERIALS AND METHODS: The experimental setup of the study included seven prompts of various levels of specificity, two GPT models (gpt-3.5-turbo and gpt-4.0) and two established gold standard corpora for phenotype recognition, one consisting of publication abstracts and the other clinical observations.

RESULTS: The best run, using in-context learning, achieved 0.58 document-level F1 score on publication abstracts and 0.75 document-level F1 score on clinical observations, as well as a mention-level F1 score of 0.7, which surpasses the current best in class tool. Without in-context learning, however, performance is significantly below the existing approaches.

CONCLUSION: Our experiments show that gpt-4.0 surpasses the state of the art performance if the task is constrained to a subset of the target ontology where there is prior knowledge of the terms that are expected to be matched. While the results are promising, the non-deterministic nature of the outcomes, the high cost and the lack of concordance between different runs using the same prompt and input make the use of these LLMs challenging for this particular task.

PMID:38297371 | PMC:PMC10829255 | DOI:10.1186/s12911-024-02439-w

J Am Heart Assoc. 2024 Feb 6;13(3):e031377. doi: 10.1161/JAHA.123.031377. Epub 2024 Jan 31.

ABSTRACT

BACKGROUND: Supravalvar aortic stenosis (SVAS) is a characteristic feature of Williams-Beuren syndrome (WBS). Its severity varies: ~20% of people with Williams-Beuren syndrome have SVAS requiring surgical intervention, whereas ~35% have no appreciable SVAS. The remaining individuals have SVAS of intermediate severity. Little is known about genetic modifiers that contribute to this variability.

METHODS AND RESULTS: We performed genome sequencing on 473 individuals with Williams-Beuren syndrome and developed strategies for modifier discovery in this rare disease population. Approaches include extreme phenotyping and nonsynonymous variant prioritization, followed by gene set enrichment and pathway-level association tests. We next used GTEx v8 and proteomic data sets to verify expression of candidate modifiers in relevant tissues. Finally, we evaluated overlap between the genes/pathways identified here and those ascertained through larger aortic disease/trait genome-wide association studies. We show that SVAS severity in Williams-Beuren syndrome is associated with increased frequency of common and rarer variants in matrisome and immune pathways. Two implicated matrisome genes (ACAN and LTBP4) were uniquely expressed in the aorta. Many genes in the identified pathways were previously reported in genome-wide association studies for aneurysm, bicuspid aortic valve, or aortic size.

CONCLUSIONS: Smaller sample sizes in rare disease studies necessitate new approaches to detect modifiers. Our strategies identified variation in matrisome and immune pathways that are associated with SVAS severity. These findings suggest that, like other aortopathies, SVAS may be influenced by the balance of synthesis and degradation of matrisome proteins. Leveraging multiomic data and results from larger aorta-focused genome-wide association studies may accelerate modifier discovery for rare aortopathies like SVAS.

PMID:38293922 | DOI:10.1161/JAHA.123.031377

Recenti Prog Med. 2024 Feb;115(2):67-75. doi: 10.1701/4197.41839.

ABSTRACT

INTRODUCTION: The text examines the impact of artificial intelligence (AI) in the context of rare diseases, exploring how patients turn to AI resources for health information, especially in situations where doctor-patient communication is limited. The article features the case of a doctor specializing in clinical psychology and psychotherapy, diagnosed with thymoma and Good's syndrome, who uses AI resources during his illness.

METHODS: The capabilities of five chatbots based on Large Language Models (LLMs), such as GPT-3.5, GPT-4, Bing Chat, Google Bard, and Anthropic Claude are explored. The AIs were queried on various aspects of the disease, from pre-diagnosis and diagnosis to therapeutic, psychological, and caregiver management issues. The responses were evaluated by five experts based on criteria such as: accuracy, relevance, coherence, clarity, practical utility, ethical considerations, empathy, and capacity to respond to questions and concerns.

RESULTS: The results indicate consistency in the evaluators' assessments, with generally high scores across all dimensions. Particularly, systems like Bard and GPT-4 received high ratings in terms of information accuracy and the ability to respond to questions and concerns. Bing and Claude were appreciated for their empathy and tone. Overall, the AI systems' responses were considered appropriate, respectful of ethics and privacy, and useful in the clinical context.

DISCUSSION: The article emphasizes the importance of understanding the reliability and precision of responses provided by AI systems in the clinical field. Although these systems offer high-quality responses, there is significant variability in their performance. Healthcare professionals must be aware of these differences and use such tools cautiously. AI can provide support in some aspects of care but cannot replace genuine human empathy and understanding. Integrating AI into clinical practice presents potential but also challenges, particularly the possibility of providing incorrect information.

CONCLUSIONS: The AI systems demonstrate the ability to provide useful advice on clinical and psychological issues, but their use requires caution. It is crucial to distinguish the benefits of AI for patients from the challenges it presents for healthcare professionals. As AI technology continues to evolve, it is essential that its integration into the clinical field is accompanied by continuous research and evaluations, to ensure safe and effective use in the healthcare sector.

PMID:38291931 | DOI:10.1701/4197.41839

Orphanet J Rare Dis. 2024 Jan 30;19(1):33. doi: 10.1186/s13023-024-03033-z.

ABSTRACT

BACKGROUND: Before COVID-19, people with rare diseases (RD) experienced numerous disparities in quality of life and healthcare access and quality, yet little is known about the experiences of this underserved group during the pandemic.

RESULTS: During the first wave of the COVID-19 pandemic in the United States, spring and summer of 2020, 759 participants representing 231 unique RDs responded to open-ended questions about the impact of the pandemic on life with a RD, healthcare access, and coping. Qualitative conventional content analysis was used to analyze responses. Identified themes represented positive and negative dimensions of change, including a shock to the (health) system, coping with uncertainty, and the value of social support while isolated.

CONCLUSIONS: Limitations in healthcare access and quality were the most frequently described as impacts of COVID-19. Other major negative impacts included exacerbation of symptoms, psychological distress, and a lack of usual social support and reliable information. However, participants also noted silver linings, especially in healthcare. For some, expanded telehealth enhanced their ability to access medical and mental health providers and RD specialists. Finally, many participants hoped that, by highlighting social and health inequities faced by people with RDs and other minorities, the pandemic would prompt greater understanding and policies that could improve the quality of life of the RD community.

PMID:38291466 | PMC:PMC10829377 | DOI:10.1186/s13023-024-03033-z

Commun Biol. 2024 Jan 30;7(1):140. doi: 10.1038/s42003-024-05820-7.

ABSTRACT

Plasma-derived therapeutic proteins are produced through an industrial fractionation process where proteins are purified from individual intermediates, some of which remain unused and are discarded. Relatively few plasma-derived proteins are exploited clinically, with most of available plasma being directed towards the manufacture of immunoglobulin and albumin. Although the plasma proteome provides opportunities to develop novel protein replacement therapies, particularly for rare diseases, the high cost of plasma together with small patient populations impact negatively on the development of plasma-derived orphan drugs. Enabling therapeutics development from unused plasma fractionation intermediates would therefore constitute a substantial innovation. To this objective, we characterized the proteome of unused plasma fractionation intermediates and prioritized proteins for their potential as new candidate therapies for human disease. We selected ceruloplasmin, a plasma ferroxidase, as a potential therapy for aceruloplasminemia, an adult-onset ultra-rare neurological disease caused by iron accumulation as a result of ceruloplasmin mutations. Intraperitoneally administered ceruloplasmin, purified from an unused plasma fractionation intermediate, was able to prevent neurological, hepatic and hematological phenotypes in ceruloplasmin-deficient mice. These data demonstrate the feasibility of transforming industrial waste plasma fraction into a raw material for manufacturing of new candidate proteins for replacement therapies, optimizing plasma use and reducing waste generation.

PMID:38291108 | PMC:PMC10828504 | DOI:10.1038/s42003-024-05820-7

JNMA J Nepal Med Assoc. 2023 Oct 1;61(266):819-821. doi: 10.31729/jnma.8303.

ABSTRACT

Klippel-Feil syndrome is a rare congenital bone disorder characterised by a triad of short neck, low posterior hairline and limited lateral bending of the neck with an annual incidence of 1 in 40,000 live births. It has remained an obscure term in the medical literature because of its variability in presentation and wide spectrum of anomalies involving multiple organ systems. It is unusual to find a case that has all three classical triad features. Here, we present a case of a 9-month-old infant who manifests not only all three classical triad features associated with Klippel-Feil syndrome but also demonstrates the presence of congenital heart disease, scoliosis, and renal ectopia. An early comprehensive evaluation of a suspected case is essential for diagnosis and counselling which impacts its prognosis, helps minimize social stigma and affords parents the opportunity to consider cosmetic surgery as an option, should they choose to pursue it.

KEYWORDS: case reports; congenital; heart diseases; Klippel-Feil syndrome; scoliosis.

PMID:38289771 | PMC:PMC10579768 | DOI:10.31729/jnma.8303

Int J Rheum Dis. 2024 Jan;27(1):e15051. doi: 10.1111/1756-185X.15051.

NO ABSTRACT

PMID:38287536 | DOI:10.1111/1756-185X.15051