Sci Rep. 2024 May 9;14(1):10672. doi: 10.1038/s41598-024-61201-4.

ABSTRACT

To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent homology (PH), a topological tool for studying the pattern of data, to analyze echocardiography-based strain data and differentiate between rare diseases like constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Patient population (retrospectively registered) included those presenting with heart failure due to CP (n = 51), RCM (n = 47), and patients without heart failure symptoms (n = 53). Longitudinal, radial, and circumferential strains/strain rates for left ventricular segments were processed into topological feature vectors using Machine learning PH workflow. In differentiating CP and RCM, the PH workflow model had a ROC AUC of 0.94 (Sensitivity = 92%, Specificity = 81%), compared with the GLS model AUC of 0.69 (Sensitivity = 65%, Specificity = 66%). In differentiating between all three conditions, the PH workflow model had an AUC of 0.83 (Sensitivity = 68%, Specificity = 84%), compared with the GLS model AUC of 0.68 (Sensitivity = 52% and Specificity = 76%). By employing persistent homology to differentiate the "pattern" of cardiac deformations, our machine-learning approach provides reasonable accuracy when evaluating small datasets and aids in understanding and visualizing patterns of cardiac imaging data in clinically challenging disease states.

PMID:38724564 | DOI:10.1038/s41598-024-61201-4

Ann Neurol. 2024 May 9. doi: 10.1002/ana.26948. Online ahead of print.

ABSTRACT

OBJECTIVE: This study was undertaken to characterize quantitative electroencephalographic (EEG) features in participants from the Natural history study of RTT and Related Disorders and to assess the potential for these features to act as objective measures of cortical function for Rett syndrome (RTT).

METHODS: EEG amplitude and power features were derived from the resting EEG of 60 females with RTT (median age = 10.7 years) and 26 neurotypical females (median age = 10.6 years). Analyses focus on group differences and within the RTT group, associations between the EEG parameters and clinical severity. For a subset of participants (n = 20), follow-up data were available for assessing the reproducibility of the results and the stability in the parameters over 1 year.

RESULTS: Compared to neurotypical participants, participants with RTT had greater amplitude variability and greater low-frequency activity as reflected by greater delta power, more negative 1/f slope, and lower theta/delta, alpha/delta, beta/delta, alpha/theta, and beta/theta ratios. Greater delta power, more negative 1/f slope, and lower power ratios were associated with greater severity. Analyses of year 1 data replicated the associations between 1/f slope and power ratios and clinical severity and demonstrated good within-subject consistency in these measures.

INTERPRETATION: Overall, group comparisons reflected a greater predominance of lower versus higher frequency activity in participants with RTT, which is consistent with prior clinical interpretations of resting EEG in this population. The observed associations between the EEG power measures and clinical assessments and the repeatability of these measures underscore the potential for EEG to provide an objective measure of cortical function and clinical severity for RTT. ANN NEUROL 2024.

PMID:38721759 | DOI:10.1002/ana.26948

Orphanet J Rare Dis. 2024 May 7;19(1):190. doi: 10.1186/s13023-024-03189-8.

NO ABSTRACT

PMID:38715067 | DOI:10.1186/s13023-024-03189-8

Health Expect. 2024 Jun;27(3):e14063. doi: 10.1111/hex.14063.

ABSTRACT

INTRODUCTION: Advanced therapies offer unprecedented opportunities for treating rare neurological disorders (RNDs) in children. However, health literacy, perceptions and understanding of novel therapies need elucidation across the RND community. This study explored healthcare professionals' and carers' perspectives of advanced therapies in childhood-onset RNDs.

METHODS: In this mixed-methodology cross-sectional study, 20 healthcare professionals (clinicians, genetic counsellors and scientists) and 20 carers completed qualitative semistructured interviews and custom-designed surveys. Carers undertook validated psychosocial questionnaires. Thematic and quantitative data analysis followed.

RESULTS: Participants described high positive interest in advanced therapies, but low knowledge of, and access to, reliable information. The substantial 'therapeutic gap' and 'therapeutic odyssey' common to RNDs were recognised in five key themes: (i) unmet need and urgency for access; (ii) seeking information; (iii) access, equity and sustainability; (iv) a multidisciplinary and integrated approach to care and support and (v) difficult decision-making. Participants were motivated to intensify RND clinical trial activity and access to advanced therapies; however, concerns around informed consent, first-in-human trials and clinical trial procedures were evident. There was high-risk tolerance despite substantial uncertainties and knowledge gaps. RNDs with high mortality, increased functional burdens and no alternative therapies were consistently prioritised for the development of advanced therapies. However, little consensus existed on prioritisation to treatment access.

CONCLUSIONS: This study highlights the need to increase clinician and health system readiness for the clinical translation of advanced therapeutics for RNDs. Co-development and use of educational and psychosocial resources to support clinical decision-making, set therapeutic expectations and promotion of equitable, effective and safe delivery of advanced therapies are essential.

PATIENT OR PUBLIC CONTRIBUTION: Participant insights into the psychosocial burden and information need to enhance the delivery of care in this formative study are informing ongoing partnerships with families, including co-production and dissemination of psychoeducational resources featuring their voices hosted on the Sydney Children's Hospitals Network website SCHN Brain-Aid Resources.

PMID:38711219 | DOI:10.1111/hex.14063

Orphanet J Rare Dis. 2024 May 6;19(1):187. doi: 10.1186/s13023-024-03193-y.

ABSTRACT

BACKGROUND: Rare disease registries (RDRs) are valuable tools for improving clinical care and advancing research. However, they often vary qualitatively, structurally, and operationally in ways that can determine their potential utility as a source of evidence to support decision-making regarding the approval and funding of new treatments for rare diseases.

OBJECTIVES: The goal of this research project was to review the literature on rare disease registries and identify best practices to improve the quality of RDRs.

METHODS: In this scoping review, we searched MEDLINE and EMBASE as well as the websites of regulatory bodies and health technology assessment agencies from 2010 to April 2023 for literature offering guidance or recommendations to ensure, improve, or maintain quality RDRs.

RESULTS: The search yielded 1,175 unique references, of which 64 met the inclusion criteria. The characteristics of RDRs deemed to be relevant to their quality align with three main domains and several sub-domains considered to be best practices for quality RDRs: (1) governance (registry purpose and description; governance structure; stakeholder engagement; sustainability; ethics/legal/privacy; data governance; documentation; and training and support); (2) data (standardized disease classification; common data elements; data dictionary; data collection; data quality and assurance; and data analysis and reporting); and (3) information technology (IT) infrastructure (physical and virtual infrastructure; and software infrastructure guided by FAIR principles (Findability; Accessibility; Interoperability; and Reusability).

CONCLUSIONS: Although RDRs face numerous challenges due to their small and dispersed populations, RDRs can generate quality data to support healthcare decision-making through the use of standards and principles on strong governance, quality data practices, and IT infrastructure.

PMID:38711103 | DOI:10.1186/s13023-024-03193-y

Cancer Res Commun. 2024 May 6. doi: 10.1158/2767-9764.CRC-24-0019. Online ahead of print.

ABSTRACT

PURPOSE: Appendiceal Adenocarcinoma (AA) remains an orphan disease with limited treatment options for patients unable to undergo surgical resection. Evidence supporting the efficacy of combined VEGF and PD-1 inhibition in other tumor types provided a compelling rationale for investigating this combination in AA, where immune checkpoint inhibitors (ICIs) have not been previously explored.

PATIENTS AND METHODS: We conducted a prospective, single arm phase 2 study evaluating efficacy and safety of atezolizumab in conjunction with bevacizumab (Atezo+Bev) in advanced, unresectable AA.

RESULTS: Patients treated with the Atezo+Bev combination had 100% disease control rate (1 PR, 15 SD) with progression free survival (PFS) of 18.3 months and overall survival not-yet-reached with median duration of follow up of 40 months. These survival intervals were significantly longer relative to a clinically and molecularly matched synthetic control cohort treated with cytotoxic chemotherapy designed for colorectal cancer (PFS of 4.4 months, p = .041).

CONCLUSIONS: In light of recent data demonstrating a lack of efficacy of 5-FU based chemotherapy, Atezo+Bev is a promising treatment option for patients with low-grade unresectable AA; further study is warranted.

PMID:38709066 | DOI:10.1158/2767-9764.CRC-24-0019

J Am Acad Dermatol. 2024 May 4:S0190-9622(24)00675-3. doi: 10.1016/j.jaad.2024.04.054. Online ahead of print.

NO ABSTRACT

PMID:38705198 | DOI:10.1016/j.jaad.2024.04.054

J Am Acad Dermatol. 2024 May 2:S0190-9622(24)00686-8. doi: 10.1016/j.jaad.2024.04.063. Online ahead of print.

NO ABSTRACT

PMID:38704036 | DOI:10.1016/j.jaad.2024.04.063

Pediatrics. 2024 Jun 1;153(6):e2023064557. doi: 10.1542/peds.2023-064557.

ABSTRACT

BACKGROUND AND OBJECTIVE: Pediatric rare diseases are often life-limiting conditions and/or require constant caregiving. Investigators assessed the initial efficacy of the FAmily CEntered (FACE) pediatric advance care planning (pACP), FACE-Rare, intervention on families' quality of life.

METHODS: A pilot-phase, single-blinded, intent-to-treat, randomized controlled clinical trial enrolled families from 1 pediatric quaternary hospital between 2021 and 2023. Intervention families received 3 weekly 60-minute (FACE-Rare pACP) sessions: (1) Carer Support Needs Assessment Tool or Action Plan, (2) Carer Support Needs Assessment Tol Action Plan Review, and (3) Pediatric Next Steps: Respecting Choices pACP. Controls received treatment as usual (TAU). Outcome measures were Beck Anxiety Inventory, Family Appraisal of Caregiving, Functional Assessment of Chronic Illness Therapy (FACIT)-Spirituality, and health care utilization. Generalized mixed effect models with γ response assessed the intervention effect at 3-month follow-up.

RESULTS: Children (n = 21) were aged 1 to 10 years, 48% male, 24% Black; and 100% technology dependent. Primary family caregivers (n = 21) were aged 30 to 43 years, 19% male, 19% Black; and 27% household income below the Federal poverty level. Dyads underwent 1:1 randomization: 9 to FACE-Rare and 12 to TAU. TAU caregivers reported statistically lower meaning and peace than FACE-Rare caregivers (0.9, P = .03, confidence interval [CI]: 0.75-0.99). Black caregivers reported significantly less caregiver distress (0.7, P = .04, CI: 0.47-0.98) than non-Black caregivers. Poor families reported more anxiety (3.5, P = .002, CI: 1.62-7.94), more caregiver strain (1.2, P = .006, CI: 1.07-1.42); and less family well-being (0.8, P = .02, CI: 0.64-0.95).

CONCLUSIONS: FACE®-Rare was feasible, acceptable, safe, and demonstrated initial efficacy, providing greater feelings of meaning and peace to caregivers. Poverty impacted well-being. A multisite trial is needed to determine generalizability.

PMID:38699801 | DOI:10.1542/peds.2023-064557

Curr Opin Nephrol Hypertens. 2024 Jul 1;33(4):375-382. doi: 10.1097/MNH.0000000000000999. Epub 2024 May 3.

ABSTRACT

PURPOSE OF REVIEW: Parathyroid hormone (PTH) is the major peptide hormone regulator of blood calcium homeostasis. Abnormal PTH levels can be observed in patients with various congenital and acquired disorders, including chronic kidney disease (CKD). This review will focus on rare human diseases caused by PTH mutations that have provided insights into the regulation of PTH synthesis and secretion as well as the diagnostic utility of different PTH assays.

RECENT FINDINGS: Over the past years, numerous diseases affecting calcium and phosphate homeostasis have been defined at the molecular level that are responsible for reduced or increased serum PTH levels. The underlying genetic mutations impair parathyroid gland development, involve the PTH gene itself, or alter function of the calcium-sensing receptor (CaSR) or its downstream signaling partners that contribute to regulation of PTH synthesis or secretion. Mutations in the pre sequence of the mature PTH peptide can, for instance, impair hormone synthesis or intracellular processing, while amino acid substitutions affecting the secreted PTH(1-84) impair PTH receptor (PTH1R) activation, or cause defective cleavage of the pro-sequence and thus secretion of a pro- PTH with much reduced biological activity. Mutations affecting the secreted hormone can alter detection by different PTH assays, thus requiring detailed knowledge of the utilized diagnostic test.

SUMMARY: Rare diseases affecting PTH synthesis and secretion have offered helpful insights into parathyroid biology and the diagnostic utility of commonly used PTH assays, which may have implications for the interpretation of PTH measurements in more common disorders such as CKD.

PMID:38701324 | DOI:10.1097/MNH.0000000000000999

Adv Rheumatol. 2024 May 3;64(1):35. doi: 10.1186/s42358-024-00374-y.

ABSTRACT

Immunoglobulin G4-related disease is a systemic immune-mediated disease with insidious evolution characterized by fibroinflammatory lesions over virtually any organ system. Despite the remarkable progression of knowledge, its etiology remains undefined. Due to its relapse-remitting pattern, it could accumulate irreversible damage, increasing comorbidities and mortality. This paper emphasizes key concepts for diagnosing and treating patients with this condition.

PMID:38702764 | DOI:10.1186/s42358-024-00374-y

Balkan Med J. 2024 May 3;41(3):206-212. doi: 10.4274/balkanmedj.galenos.2024.2023-12-57.

ABSTRACT

BACKGROUND: Bronchiectasis is a chronic lung disease characterized by permanent bronchial wall dilatation. Although it has been known as an orphan disease, it has recently gained attention because of registry-based studies and drug research.

AIMS: We aimed to use a multicenter database to analyze and compare data regarding the etiology, associated comorbidities, microbiological characteristics, and preventive strategies of bronchiectasis in Türkiye to those of other countries.

STUDY DESIGN: A multicenter prospective cohort study.

METHODS: The multicenter, prospective cohort study was conducted between March 2019 and January 2022 using the Turkish Adult Bronchiectasis Database, in which 25 centers in Türkiye participated. Patients aged > 18 years who presented with respiratory symptoms such as cough, sputum, and dyspnea and were diagnosed with non-cystic fibrosis bronchiectasis using computed tomography were included in the study. Demographic information, etiologies, comorbidities, pulmonary functions, and microbiological, radiological, and clinical data were collected from the patients.

RESULTS: Of the 1,035 study participants, 518 (50%) were females. The mean age of the patients was 56.1 ± 16.1 years. The underlying etiology was detected in 565 (54.6%) patients. While postinfectious origin was the most common cause of bronchiectasis (39.5%), tuberculosis was identified in 11.3% of the patients. An additional comorbidity was detected in 688 (66.5%) patients. The most common comorbidity was cardiovascular disease, and chronic obstructive pulmonary disease (COPD) and bronchiectasis was identified in 19.5% of the patients. The most commonly detected microbiological agent was Pseudomonas aeruginosa (29.4%). Inhaled corticosteroids (ICS) were used in 70.1% of the patients, and the frequency of exacerbations in the last year was significantly higher in patients using ICS than in nonusers (p < 0.0001). Age [odds ratio (OR): 1.028; 95% confidence interval (CI): 1.005-1.051], cachexia (OR: 4.774; 95% CI: 2,054-11,097), high modified medical research council dyspnea scale score (OR: 1,952; 95% CI: 1,459-2,611), presence of chronic renal failure (OR: 4,172; 95% CI: 1,249-13,938) and use of inhaled steroids (OR: 2,587; 95% CI: 1,098-6,098) were significant risk factors for mortality. Mortality rates were higher in patients with COPD than in those with no COPD (21.7-9.1%, p = 0.016). Patients with bronchiectasis and COPD exhibited more frequent exacerbations, exacerbation-related hospitalizations, and hospitalization in the intensive care unit in the previous year than patients without COPD.

CONCLUSION: This is the first multicenter study of bronchiectasis in Türkiye. The study results will provide important data that can guide the development of health policies in Türkiye on issues such as infection control, vaccination, and the unnecessary use of antibiotics and steroids.

PMID:38700365 | DOI:10.4274/balkanmedj.galenos.2024.2023-12-57

J Comp Eff Res. 2024 Jun;13(6):e240052. doi: 10.57264/cer-2024-0052. Epub 2024 May 2.

NO ABSTRACT

PMID:38696698 | DOI:10.57264/cer-2024-0052

Int J Biol Macromol. 2024 Jun;269(Pt 1):131960. doi: 10.1016/j.ijbiomac.2024.131960. Epub 2024 May 1.

ABSTRACT

Rare diseases, defined by their low prevalence, present significant challenges, including delayed detection, expensive treatments, and limited research. This study delves into the genetic basis of two noteworthy rare diseases in Saudi Arabia: Phenylketonuria (PKU) and Spinal Muscular Atrophy (SMA). PKU, resulting from mutations in the phenylalanine hydroxylase (PAH) gene, exhibits geographical variability and impacts intellectual abilities. SMA, characterized by motor neuron loss, is linked to mutations in the survival of motor neuron 1 (SMN1) gene. Recognizing the importance of unveiling signature genomics in rare diseases, we conducted a quantitative study on PAH and SMN1 proteins of multiple organisms by employing various quantitative techniques to assess genetic variations. The derived signature-genomics contributes to a deeper understanding of these critical genes, paving the way for enhanced diagnostics for disorders associated with PAH and SMN1.

PMID:38697430 | DOI:10.1016/j.ijbiomac.2024.131960

Orphanet J Rare Dis. 2024 May 2;19(1):183. doi: 10.1186/s13023-024-03188-9.

ABSTRACT

BACKGROUND: With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0-3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders.

RESULTS: Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy.

CONCLUSIONS: The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

PMID:38698482 | DOI:10.1186/s13023-024-03188-9

Orphanet J Rare Dis. 2024 May 2;19(1):184. doi: 10.1186/s13023-024-03185-y.

ABSTRACT

Regulatory marketing authorisation is not enough to ensure patient access to new medicinal products. Health Technology Assessment bodies may require data on effectiveness, relative effectiveness, and cost-effectiveness. Healthcare systems may require data on clinical utility, savings, and budget impact. Furthermore, the exact requirements of these bodies vary country by country and sometimes even region to region, resulting in a patchwork of different data requirements to achieve effective, reimbursed patient access to new therapies. In addition, clinicians require data to make informed clinical management decisions. This requirement is of key importance in rare diseases where there is often limited data and clinical experience at the time of regulatory approval.This paper describes an innovative initiative that is called Project SATURN: Systematic Accumulation of Treatment practices and Utilization, Real world evidence, and Natural history data for the rare disease Osteogenesis Imperfecta. The objective of this project is to generate a common core dataset by utilising existing data sources to meet the needs of the various stakeholders and avoiding fragmentation through multiple approaches (e.g., a series of individual national requests/approaches, and unconnected with the regulators' potential requirements). It is expected that such an approach will reduce the time for patient access to life-changing medications. Whilst Project SATURN applies to Osteogenesis Imperfecta, it is anticipated that the principles could also be applied to other rare diseases and reduce the time for patient access to new medications.

PMID:38698457 | DOI:10.1186/s13023-024-03185-y

Cell Mol Gastroenterol Hepatol. 2024 Apr 30:S2352-345X(24)00100-0. doi: 10.1016/j.jcmgh.2024.04.006. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Humans with WNT2B deficiency have severe intestinal disease, including significant inflammatory injury, highlighting a critical role for WNT2B. We sought to understand how WNT2B contributes to intestinal homeostasis.

METHODS: We investigated the intestinal health of Wnt2b knock out (KO) mice. We assessed the baseline histology and health of the small intestine and colon, as well as the impact of inflammatory challenge using dextran sodium sulfate (DSS). We also evaluated human intestinal tissue.

RESULTS: Mice with WNT2B deficiency had normal baseline histology but enhanced susceptibility to DSS colitis due to an increased early injury response. While ISC markers were decreased, epithelial proliferation was similar to controls. Wnt2b KO mice showed an enhanced inflammatory signature after DSS treatment. Wnt2b KO colon and human WNT2B-deficient organoids both had increased levels of CXCR4 and IL6, and biopsy tissue from humans showed increased neutrophils.

CONCLUSION: WNT2B is important for regulation of inflammation in the intestine. Absence of WNT2B leads to increased expression of inflammatory cytokines and increased susceptibility to gastrointestinal inflammation, particularly in the colon.

PMID:38697357 | DOI:10.1016/j.jcmgh.2024.04.006

Zh Nevrol Psikhiatr Im S S Korsakova. 2024;124(4. Vyp. 2):86-91. doi: 10.17116/jnevro202412404286.

ABSTRACT

Multiple system atrophy (MSA) is a severe, orphan disease characterized by a steady increase in symptoms of parkinsonism, cerebellar disorders, and autonomic failure. In addition to autonomic failure, which is considered the defining symptom of this type of atypical parkinsonism, there are a range of other non-motor clinical manifestations, such as sleep disorders, pain syndrome, anxiety-depressive disorders, cognitive impairment (CI). CI, especially severe CI, has long been considered as a distinctive feature of MCA. Recently, there have been many clinical studies with pathomorphological or neuroimaging confirmation, indicating a high prevalence of cognitive disorders in MCA. In this article, we discuss the pathogenetic mechanisms of the development of MCA and CI in MCA, as well as the range of clinical manifestations of cognitive dysfunction.

PMID:38696156 | DOI:10.17116/jnevro202412404286

AAPS J. 2024 Apr 30;26(3):57. doi: 10.1208/s12248-024-00925-7.

ABSTRACT

The aim of this study was to develop a model to predict individual subject disease trajectories including parameter uncertainty and accounting for missing data in rare neurological diseases, showcased by the ultra-rare disease Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS). We modelled the change in SARA (Scale for Assessment and Rating of Ataxia) score versus Time Since Onset of symptoms using non-linear mixed effect models for a population of 173 patients with ARSACS included in the prospective real-world multicenter Autosomal Recessive Cerebellar Ataxia (ARCA) registry. We used the Multivariate Imputation Chained Equation (MICE) algorithm to impute missing covariates, and a covariate selection procedure with a pooled p-value to account for the multiply imputed data sets. We then investigated the impact of covariates and population parameter uncertainty on the prediction of the individual trajectories up to 5 years after their last visit. A four-parameter logistic function was selected. Men were estimated to have a 25% lower SARA score at disease onset and a moderately higher maximum SARA score, and time to progression (T50) was estimated to be 35% lower in patients with age of onset over 15 years. The population disease progression rate started slowly at 0.1 points per year peaking to a maximum of 0.8 points per year (at 36.8 years since onset of symptoms). The prediction intervals for SARA scores 5 years after the last visit were large (median 7.4 points, Q1-Q3: 6.4-8.5); their size was mostly driven by individual parameter uncertainty and individual disease progression rate at that time.

PMID:38689016 | DOI:10.1208/s12248-024-00925-7

Hum Genomics. 2024 Apr 29;18(1):44. doi: 10.1186/s40246-024-00604-w.

ABSTRACT

BACKGROUND: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting.

METHODS: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values.

RESULTS: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency.

CONCLUSIONS: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

PMID:38685113 | DOI:10.1186/s40246-024-00604-w