Characterizing Families of Pediatric Patients with Rare Diseases and Their Diagnostic Odysseys: A Comprehensive Survey Analysis from a Single Tertiary Center in Korea

Purpose Rare diseases necessitate consistent access to specialized health services. In Korea, despite the growing socioeconomic burden, insufficient comprehensive research is available on patients with rare diseases and their families, particularly concerning factors influencing the length of time to diagnosis. The aim of this study was to thoroughly characterize rare pediatric diseases and explore factors impacting the diagnostic odyssey. Methods The study enrolled patients under 15 years old seeking medical care at the Seoul National University Children’s Hospital Rare Disease Center between January 2022 and December 2023. Participating patients were required to have been diagnosed with one of the 1,248 rare diseases recognized in Korea. A 33-question survey was developed to assess clinical features of the patients, characteristics of their primary caregivers, and their perceptions of ongoing medical care. Results The study included 101 patients and their families. Regarding perceived cognitive and motor functions, most families indicated moderate or severe limitations (cognitive, 62.4%; motor, 57.4%). Over half of the families (53.5%) reported discontinuing employment to provide patient care. Neurological symptoms represented the most common initial chief concern, with dermatologic symptoms and laboratory test abnormalities also noted. Three factors were associated with time to diagnosis: the number of hospitals visited, whether the districts of residence and diagnosis aligned, and the age at symptom onset. Conclusion The comprehensive characterization of patients with rare diseases and their families in Korea, along with the identification of factors impacting the diagnostic odyssey, provides key insights for the development of a tailored support system

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

The extended clinical and genetic spectrum of CTNNB1-related neurodevelopmental disorder

Purpose: Loss-of-function mutations of CTNNB1 have been established as the cause of neurodevelopmental disorder with spastic diplegia and visual defects. Although most patients share key phenotypes such as global developmental delay and intellectual disability, patients with CTNNB1-related neurodevelopmental disorder show a broad spectrum of clinical features. Methods: We enrolled 13 Korean patients with CTNNB1-related neurodevelopmental disorder who visited Seoul National University Children&apos;s Hospital (5 female and 8 male patients with ages ranging from 4 to 22 years). They were all genetically confirmed as having pathogenic loss-of-function variants in CTNNB1 using trio or singleton whole exome sequencing. Variants called from singleton analyses were confirmed to be de novo through parental Sanger sequencing. Results: We identified 11 de novo truncating variants in CTNNB1 in 13 patients, and two pathogenic variants, c.1867C &gt; T (p.Gln623Ter) and c.1420C &gt; T (p.Arg474Ter), found in two unrelated patients, respectively. Five of them were novel pathogenic variants not listed in the ClinVar database. While all patients showed varying degrees of intellectual disability, impaired motor performance, and ophthalmologic problems, none of them had structural brain abnormalities or seizure. In addition, there were three female patients who showed autistic features, such as hand stereotypy, bruxism, and abnormal breathing. A literature review revealed a female predominance of autistic features in CTNNB1-related neurodevelopmental disorder. Conclusion: This is one of the largest single-center cohorts of CTNNB1-related neurodevelopmental disorder. This study investigated variable clinical features of patients and has expanded the clinical and genetic spectrum of the disease.N

Machine learning-based diagnosis for disseminated intravascular coagulation (DIC): Development, external validation, and comparison to scoring systems

<div><p>The major challenge in the diagnosis of disseminated intravascular coagulation (DIC) comes from the lack of specific biomarkers, leading to developing composite scoring systems. DIC scores are simple and rapidly applicable. However, optimal fibrin-related markers and their cut-off values remain to be defined, requiring optimization for use. The aim of this study is to optimize the use of DIC-related parameters through machine learning (ML)-approach. Further, we evaluated whether this approach could provide a diagnostic value in DIC diagnosis. For this, 46 DIC-related parameters were investigated for both clinical findings and laboratory results. We retrospectively reviewed 656 DIC-suspected cases at an initial order for full DIC profile and labeled their evaluation results (Set 1; DIC, n = 228; non-DIC, n = 428). Several ML algorithms were tested, and an artificial neural network (ANN) model was established via independent training and testing using 32 selected parameters. This model was externally validated from a different hospital with 217 DIC-suspected cases (Set 2; DIC, n = 80; non-DIC, n = 137). The ANN model represented higher AUC values than the three scoring systems in both set 1 (ANN 0.981; ISTH 0.945; JMHW 0.943; and JAAM 0.928) and set 2 (AUC ANN 0.968; ISTH 0.946). Additionally, the relative importance of the 32 parameters was evaluated. Most parameters had contextual importance, however, their importance in ML-approach was different from the traditional scoring system. Our study demonstrates that ML could optimize the use of clinical parameters with robustness for DIC diagnosis. We believe that this approach could play a supportive role in physicians’ medical decision by integrated into electrical health record system. Further prospective validation is required to assess the clinical consequence of ML-approach and their clinical benefit.</p></div

Broadening the scope of multigene panel analysis for adult epilepsy patients

Abstract Objective Epilepsy is a suitable target for gene panel sequencing because a considerable portion of epilepsy is now explained by genetic components, especially in syndromic cases. However, previous gene panel studies on epilepsy have mostly focused on pediatric patients. Methods We enrolled adult epilepsy patients meeting any of the following criteria: family history of epilepsy, seizure onset age ≤ 19 years, neuronal migration disorder, and seizure freedom not achieved by dual anti‐seizure medications. We sequenced the exonic regions of 211 epilepsy genes in these patients. To confirm the pathogenicity of a novel MTOR truncating variant, we electroporated vectors with different MTOR variants into developing mouse brains. Results A total of 92 probands and 4 affected relatives were tested, and the proportion of intellectual disability (ID) and/or developmental disability (DD) was 21.7%. As a result, twelve probands (13.0%) had pathogenic or likely pathogenic variants in the following genes or regions: DEPDC5, 15q12‐q13 duplication (n = 2), SLC6A1, SYNGAP1, EEF1A2, LGI1, MTOR, KCNQ2, MEF2C, and TSC1 (n = 1). We confirmed the functional impact of a novel truncating mutation in the MTOR gene (c.7570C > T, p.Gln2524Ter) that disrupted neuronal migration in a mouse model. The diagnostic yield was higher in patients with ID/DD or childhood‐onset seizures. We also identified additional candidate variants in 20 patients that could be reassessed by further studies. Significance Our findings underscore the clinical utility of gene panel sequencing in adult epilepsy patients suspected of having genetic etiology, especially those with ID/DD or early‐onset seizures. Gene panel sequencing could not only lead to genetic diagnosis in a substantial portion of adult epilepsy patients but also inform more precise therapeutic decisions based on their genetic background. Plain Language Summary This study demonstrated the effectiveness of gene panel sequencing in adults with epilepsy, revealing pathogenic or likely pathogenic variants in 13.0% of patients. Higher diagnostic yields were observed in those with neurodevelopmental disorders or childhood‐onset seizures. Additionally, we have shown that expanding genetic studies into adult patients would uncover new types of pathogenic variants for epilepsy, contributing to the advancement of precision medicine for individuals with epilepsy. In conclusion, our results highlight the practical value of employing gene panel sequencing in adult epilepsy patients, particularly when genetic etiology is clinically suspected