Reanalysis of exome negative patients with rare disease: a pragmatic workflow for diagnostic applications

Abstract

Background Approximately 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. Methods We 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). Results Ad 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. Conclusions We 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.

Long-read genome sequencing and variant reanalysis increase diagnostic yield in neurodevelopmental disorders

“…For example, we previously showed that the probability of a negative srGS dataset harboring a clinically relevant variant increased from 1% within one year of a previous analysis to ~22% if more than three years have passed since a previous analysis (Hiatt et al 2018). Several other studies found similar results, with many reanalysis findings being due to recent publications of new gene-disease associations (Liu et al 2019;Schobers et al 2022;Hartley et al 2023).…”

“…In addition to changes in sequencing technology, the scope of knowledge about genes and our ability to annotate genetic variants has steadily increased. As such, systematic reanalysis of GS/ES data also leads to the discovery of previously overlooked clinically relevant variants, with diagnostic yield increases ranging from 4-31% depending on a variety of factors, most notably time since the previous analysis (Hiatt et al 2018; Liu et al 2019; Schobers et al 2022; Hartley et al 2023). While a variety of factors contribute to reanalysis discoveries, they often result from the discovery of new disease genes, which contributes to 42-75% of reanalysis findings (Hiatt et al 2018; Liu et al 2019; Schobers et al 2022; Hartley et al 2023).…”

“…As such, systematic reanalysis of GS/ES data also leads to the discovery of previously overlooked clinically relevant variants, with diagnostic yield increases ranging from 4-31% depending on a variety of factors, most notably time since the previous analysis (Hiatt et al 2018; Liu et al 2019; Schobers et al 2022; Hartley et al 2023). While a variety of factors contribute to reanalysis discoveries, they often result from the discovery of new disease genes, which contributes to 42-75% of reanalysis findings (Hiatt et al 2018; Liu et al 2019; Schobers et al 2022; Hartley et al 2023). This reflects the rapid pace of discovery of new disease genes in the rare disease research community, which has been facilitated by data sharing via the MatchMaker Exchange and GeneMatcher (Philippakis et al 2015; Sobreira et al 2017).…”

High number of candidate gene variants are identified as disease‐causing in a period of 4 years

“…This study evaluates the relationship between CGVs and their perceived roles in disease causation over time. There are some existing studies on nondiagnostic exome or genome reanalysis that have solved a portion of undiagnosed cases in addition to identifying CGVs (Eldomery et al, 2017;Hagman et al, 2017;Liu et al, 2019;Schobers et al, 2022;Shashi et al, 2019). However, few articles have discussed the follow-up of these CGVs and how many are ultimately determined to be diseasecausing over a period of time.…”

Loss-of-Function Variants in DRD1 in Infantile Parkinsonism-Dystonia

“…Following identification of the candidate gene, seven international genomic databases with over 120,000 exomes or genomes were interrogated for biallelic variants in DRD1 . These included three large databases of individuals with a range of rare diseases (Deciphering Developmental Disorders study [ 16 ]; NIH Undiagnosed Diseases Program [ 17 ]; Genomics England 100,000 Genomes Project [ 18 ]) and three databases of patients with undiagnosed neurological disorders (Radboud University Medical Centre Nijmegen [ 19 ]; the Institut für Humangenetik, Munich [ 20 ] and the Istituto Neurologico “Carlo Besta”, Milan [ 10 ]).…”