Dataset Information

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

ABSTRACT: Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.

SUBMITTER: Matalonga L

PROVIDER: S-EPMC8440686 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAccording to the International Rare Diseases Research Consortium (IRDiRC), a known rare disease (RD) should be diagnosable within a year. This study sought: firstly, to ascertain how long it takes to obtain the diagnosis of a RD in Spain, along with its associated time trend; and secondly, to identify and measure diagnostic delay (defined by the IRDiRC as any period exceeding a year) by reference to the characteristics of RDs and the persons affected by them.MethodsUsing data sourced from the Spanish Rare Diseases Patient Registry, we performed a descriptive analysis of the time elapsed between symptom onset and diagnosis of each RD, by sex, age and date of symptom onset, and type of RD. We analysed the time trend across the period 1960-2021 and possible change points, using a Joinpoint regression model and assuming a Poisson distribution. The multivariate analysis was completed with backward stepwise logistic regression.ResultsDetailed information was obtained on 3304 persons with RDs: 56.4% had experienced delay in diagnosis of their RDs, with the mean time taken being 6.18 years (median = 2; IQR 0.2-7.5). Both the percentage of patients with diagnostic delay and the average time to diagnosis underwent a significant reduction across the study period (p < 0.001). There was a higher percentage of diagnostic delays: in women (OR 1.25; 95% CI 1.07-1.45); in cases with symptom onset at age 30-44 years (OR 1.48; 95% CI 1.19-1.84): and when analysed by type of RD, in mental and behavioural disorders (OR 4.21; 95% CI 2.26-7.85), followed by RDs of the nervous system (OR 1.39; 95% CI 1.02-1.88).ConclusionsThis is the first study to quantify time to diagnosis of RDs in Spain, based on data from a national registry open to any RD. Since over half of all persons affected by RDs experience delay in diagnosis, new studies are needed to ascertain the factors associated with this delay and the implications this has on the lives of patients and their families.

Project description:BackgroundApproximately two third of patients with a rare genetic disease remain undiagnosed after exome sequencing (ES). As part of our post-test counseling procedures, patients without a conclusive diagnosis are advised to recontact their referring clinician to discuss new diagnostic opportunities in due time. We performed a systematic study of genetically undiagnosed patients 5 years after their initial negative ES report to determine the efficiency of diverse reanalysis strategies.MethodsWe revisited a cohort of 150 pediatric neurology patients originally enrolled at Radboud University Medical Center, of whom 103 initially remained genetically undiagnosed. We monitored uptake of physician-initiated routine clinical and/or genetic re-evaluation (ad hoc re-evaluation) and performed systematic reanalysis, including ES-based resequencing, of all genetically undiagnosed patients (systematic re-evaluation).ResultsAd hoc re-evaluation was initiated for 45 of 103 patients and yielded 18 diagnoses (including 1 non-genetic). Subsequent systematic re-evaluation identified another 14 diagnoses, increasing the diagnostic yield in our cohort from 31% (47/150) to 53% (79/150). New genetic diagnoses were established by reclassification of previously identified variants (10%, 3/31), reanalysis with enhanced bioinformatic pipelines (19%, 6/31), improved coverage after resequencing (29%, 9/31), and new disease-gene associations (42%, 13/31). Crucially, our systematic study also showed that 11 of the 14 further conclusive genetic diagnoses were made in patients without a genetic diagnosis that did not recontact their referring clinician.ConclusionsWe find that upon re-evaluation of undiagnosed patients, both reanalysis of existing ES data as well as resequencing strategies are needed to identify additional genetic diagnoses. Importantly, not all patients are routinely re-evaluated in clinical care, prolonging their diagnostic trajectory, unless systematic reanalysis is facilitated. We have translated our observations into considerations for systematic and ad hoc reanalysis in routine genetic care.

Dataset Information

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets