TABLE 3.
Comparison of reanalysis studies in the literature
| Publication | Diagnostic platform | Cohort of undiagnosed cases with non‐diagnostic ES/GS | Approach to reanalysis | % New diagnoses (number of diagnoses in published genes OR detection of CNV or SV/number of unsolved cases reanalyzed after initial negative report) | Reasons for new diagnoses | Reanalysis timeframe | Recommendation |
|---|---|---|---|---|---|---|---|
| Exome sequencing (ES) | |||||||
| Wenger et al. (2017) | Singleton ES | 40 probands (mostly paediatric), heterogeneous conditions | Reannotation of ES data | 10 (4/40) | New gene publication, relevant literature located at the time of reanalysis | 20 months (average) | Reanalysis at 2‐ to 3‐year interval could result in a 10% diagnostic yield |
| Shamseldin et al. (2017) | Singleton ES | 33 probands (parental consanguinity in all cases), presumed heterogeneous conditions | Repeat ES as data from original ES not available for reanalysis | 48.48 (16/33) | Improved variant filtration via positional mapping | Not reported | Incorporation of positional mapping in the analysis of ES whenever applicable |
| Need et al. (2017) | Family ES | 6 families, heterogeneous conditions | Realignment to new human genome reference build, increased coverage | 83.33 (5/6) | New gene publication, realignment to new human genome reference build | ~4 years | Multifaceted approach to reanalyzing ES data should be a standard part of clinical diagnostic paradigms |
| Eldomery et al. (2017) | ES (68 family studies, 6 singleton) | 74 families, heterogeneous conditions | Expansion to family ES studies, improved data filtering (SNV prioritization, de novo SNVs), CNV detection from ES data | 36.49 (27/74) | New gene publication, gene discovery publication, putative parental mosaicism, biallelic or hemizygous variants identified via family ES studies, CNV detection from ES data (loss of heterozygosity, uniparental disomy, small CNV), translational research (GeneMatcher) | <3 years | Reanalysis of data coupled with the incorporation of additional family member ES data can improve the molecular diagnostic rate |
| Epilepsy Genetics Initiative (2018) | ES (2 family studies, 1 singleton) | 3 probands, epilepsy conditions | Expansion to family ES studies, reannotation of ES variant data | 0.08 (3/3747) | Newly published alternate exon (updated consensus coding sequence database; CCDS) | ~3 to 4 years for family ES cases, singleton case not reported | Iterative interrogation of ES data, with re‐evaluation of other well‐defined alternative exons in known epilepsy genes |
| Nambot et al. (2018) | Singleton ES | 156 probands, neurodevelopmental disorder with or without congenital anomalies | Reannotation of ES data, CNV detection from ES data | 15.38 (24/156) | New gene publication, gene discovery publication, reclassification of originally reported variant, CNV detection from ES data, translational research (Matchmaker Exchange) | <3 years | Prospective reanalysis of ES data in patients with no diagnosis, with consideration for trio ES (before GS) for cases that remain unsolved despite recurrent reanalyses |
| Xiao et al. (2018) | Singleton ES or targeted sequencing | 19 probands (proportion of singleton ES not reported), neurodevelopmental disorder with or without congenital anomalies | Reannotation of ES data, CNV detection from ES data | 26.32 (5/19) | New gene publication, phenotype expansion publication, CNV detection from ES data | 8–18 months | Re‐evaluation at 1‐ to 2‐year interval |
| Wright et al. (2018) | Family ES | 861 families, neurodevelopmental disorders with or without congenital anomalies, abnormal growth parameters, dysmorphic features, unusual behavioral phenotypes | Reannotation of ES data, CNV detection from ES data | 21.14 (182/861) | New gene publication, improved analysis pipelines (updated annotations and variant filtering thresholds), additional analytical methods (to detect chromosomal aneuploidy, CNV detection from ES data, mosaicism, non‐essential splice variants, uniparental disomy) | ~3 years | Iterative reinterpretation of already reported clinical sequencing data should become routine |
| Ewans et al. (2018) | ES (28 family studies, 9 singleton) | 37 families, heterogeneous conditions | Reannotation of ES data | 15.38 (4/26) | New gene publication, improved analysis pipelines, updated patient phenotype information | 12 months | Reanalysis after 12 months or when instigated by referrers |
| Stark et al. (2019) | Singleton ES | 29 probands, infants with suspected monogenic disorders | Re‐evaluation of existing ES data | 13.79 (4/29) | New gene publication | 6–18 months | Reanalysis at 18 months is a cost‐effective model for the storage and re‐examination of genomic data in clinical service delivery |
| Al‐Nabhani et al. (2018) | Singleton ES | 50 probands, intellectual disability | Reannotation of ES data | 12 (6/50) | New gene publication, improved analysis pipelines, updated patient phenotype information | 22 months (average) | Reanalysis of negative exomes in this study of intellectual disability cases solved at least 12% of cases |
| Salmon et al. (2019 | Singleton ES | 84 probands, heterogeneous conditions | Reannotation of ES data | 15.48 (13/84) | New gene publication, updated patient phenotype information | Not reported | Reanalysis of exome data can increase the diagnostic yield and reduce the need for additional costly tests such as genome sequencing |
| Baker et al. (2019) | ES (230 family studies, 10 singleton) | 240 probands, heterogeneous conditions | Reannotation of ES data | 15.83 (38/240) | New gene publication, phenotype expansion publication, candidate gene publication, reclassification of originally reported variant | 1.5 years (reported median) | Automated reanalysis methods can facilitate efficient re‐evaluation of non‐diagnostic samples using up‐to‐date literature |
| Jalkh et al. (2019) | Singleton ES | 101 probands, heterogeneous conditions | Reannotation of ES data, variant filtration based on local ES control dataset | 12.87 (13/101) | New gene publication, updated patient phenotype information | Not reported | ES reanalysis should take into consideration updated bioinformatics tools, novel gene discoveries, and new clinical information |
| Li et al. (2019) | Family ES | 76 families, epilepsy with intellectual disability | Reannotation of ES data | 10.53 (8/76) | New gene publication, relevant literature located at the time of reanalysis, updated patient phenotype information, reclassification of synonymous variant affecting splicing | 0–12+ months | Suitable time points for reanalysis might be 6–12 months after the initial report |
| Epilepsy Genetics Initiative (2019) | ES (singleton and family studies) | 137 probands, epilepsy conditions (excludes 2 probands previously reported in Epilepsy Genetics Initiative, 2018) | Reannotation of ES data | 4.38 (6/137) | New gene publication, gene discovery publication, newly published alternate exon (updated consensus coding sequence database; CCDS), new OMIM entry, translational research (GeneMatcher) | 2.3 years (average) | Periodic reinterrogation of unresolved exomes is critical to improving the diagnostic rate |
| Schmitz‐Abe et al. (2019 | ES (singleton and family studies) | 75 probands, heterogeneous conditions | Reannotation of ES data, improved data filtering (SNV calling and prioritization) | 8 (6/75) | New gene publication, improved variant calling using custom‐built pipeline (VExP) | 1.9 ± 1.4 years (average) | Important to reanalyze negative ES data periodically, preferably annually |
| Liu et al. (2019) | Singleton ES | 188 probands (cohort 1) and 1496 probands (cohort 2), presumed heterogeneous conditions | Reannotation of ES data | 31.91 (60/188 cohort 1) and 15.37 (230/1496 cohort 2) | New gene publication, reclassification of originally reported variant, variant‐specific atypical phenotypic presentations, gene‐specific multiple disease inheritance patterns and mechanisms, newly discovered isoforms encompassing previously unknown exons, complex patient phenotypes obscured by multilocus molecular diagnoses | 5 years (sporadic cases performed earlier) | Periodic, cost‐effective reanalysis may benefit patients and their families and physicians |
| Bruel et al. (2019) | Singleton ES | 313 probands, ID/epileptic encephalopathy with or without congenital anomalies | Re‐evaluation of existing ES data, extending variant interpretation to genes not associated with human disease in OMIM | 15.34 (48/313) | Novel gene discovery, relevant literature located at the time of reanalysis, phenotype expansion publication, translational research (GeneMatcher) | Nil (reanalysis performed immediately after original ES result obtained) | Limitations of singleton ES reanalysis could be overcome utilizing trio ES as a second step |
| Trinh et al. (2019) | ES (singleton and family studies) | 3015 probands (heterogeneous conditions) | Reannotation of ES data | 0.46 (14/3015) | Focus on 14 genes recently nominated by the DDD study (new gene publications for 13 of 14 genes) | Not reported | Importance of re‐evaluating ES data in light of new publications |
| Ngo et al. (2020) | ES (singleton and family studies) | 60 probands (ataxic disorders) | Reannotation of ES data, CNV detection from exome data | 8.33 (5/60) | Known pathogenic variant detected, CNV detection from ES data | 5 years | Key focus for undiagnosed cases on repeating bioinformatic analysis at regular intervals, and use of more comprehensive genomic tools and complete methods to identify mutation types currently not observed in ES as they become available |
| Genome sequencing (GS) | |||||||
| Costain et al. (2018) | Singleton GS | 100 patients (paediatric), heterogeneous conditions | Reannotation of GS variant calls | 10.94 (7/64) | New gene publication, phenotype expansion publication, additional case reports | 3 years | Reanalysis every 1–2 years until diagnosis, or sooner if phenotype evolves |
| Machini et al. (2019) | Singleton GS | 100 patients (50 with cardiomyopathy and 50 healthy) | Reannotation of GS variant calls | 22 (22/100) | New gene and variant publications, reclassification of originally reported variant, improved analysis pipelines | 13 months (mean) | Reanalysis on an annual basis, with the frequency and utility of reanalysis to be guided by the presence of new symptoms or availability of new treatments |
| ES and/or GS | |||||||
| Bowling et al. (2017) | ES or GS (singleton and family studies) | 211 families, neurodevelopmental disorders | Reannotation of ES/GS data | 4.74 (10/211) | New gene publication, improved analysis pipelines, updated patient phenotype information, translational research (GeneMatcher) | Not reported | Systematic reanalysis of genomic data should become standard practice |
| Hiatt et al. (2018) | ES or GS (singleton and family studies) | Number of undiagnosed probands not reported, total cohort of 494 individuals with neurodevelopmental disorders | Reannotation of ES/GS data | 1.57 (6/383) | New gene publication, additional analytical methods (to detect uniparental disomy), translational research (GeneMatcher) | Not reported | Datasets first analyzed over two years ago should be prioritised for reanalysis |
| Alfares et al. (2018) | Singleton ES and GS | 108 patients, presumed heterogeneous conditions | Reanalysis of ES data if a pathogenic variant was detected on GS | 30 (3/10) | New gene publication | 5 months (average) | Until the cost of GS approximates that of ES, reanalyzing ES raw data is recommended before performing GS |
| Shashi et al. (2019) | ES and GS (singleton and family studies) | 38 probands (37 ES, 1 GS), heterogeneous conditions | Reannotation of ES data, improved data filtering (in‐house bioinformatics tools), CNV detection from ES data, repeat ES/GS, GS following/in parallel with ES | 50 (19/38) | Deep phenotyping of patients, new gene publication, CNV/SV, translational research (GeneMatcher) | Not reported | GS should be utilized only after ES data have been extensively mined and combined with the phenotypic data to maximize its yield |
Abbreviations: CNV, copy number variation; SNV, single nucleotide variation; SV, structural variant.