Genome sequencing as a generic diagnostic strategy for rare disease

Abstract

Background: To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease.

Methods: We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected.

Results: Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected.

Conclusions: GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.

Keywords: Genetic diagnostic laboratories; Genome sequencing; Germline variant detection; Impact modeling; Rare disease; Reducing workflow complexity.

Fig. 1

Technical validation of 1271 variants. Schematic representation of detection rates of previously identified pathogenic variants across multiple different workflows. In total, 94.9% (1206/1271) of all variants were detected in GS data. The distribution of variants across the ten workflows shows a detection rate ranging between 79 and 100%. Abbreviations: targeted next-generation sequencing ((t)NGS), deletion polymerase chain reaction (DelPCR), multiplex ligation-dependant probe amplification (MLPA), fluorescence in situ hybridization (FISH), exome sequencing (ES), single nucleotide variants (SNV), copy number variants (CNV), short tandem repeat expansions (STRs), region of homozygosity (ROH), structural variants (SV), chromosome anomalies (CA)

Fig. 2

Diagnostic referrals for genetic testing in 2022. In total, 24,570 individuals were referred, together requiring 36,633 data-generating experiments (in 23,604 individuals) in 11 different workflows, and 2072 reanalyses of existing (exome) datasets (in 966 individuals). Abbreviations: targeted next-generation sequencing ((t)NGS), deletion polymerase chain reaction (DelPCR), multiplex ligation-dependant probe amplification (MLPA), fluorescence in situ hybridization (FISH), exome sequencing (ES), long-read sequencing (LRS)

Fig. 3

Assessing the impact of a GS-first transition. A From 833 different clinical reasons for referral in 2022, 750 can be transitioned to GS. B This transition would result in 16,777 individuals receiving GS as the only workflow. For 667 (3%), the GS should be supplemented by an additional test, whereas for the remaining 7126 (29%) GS would not be suited, either because for them the clinical indications included experiments not transferable to GS (n = 6160; 25%), or because the referral did not require data generation (n = 966; 4%). C The use of GS as a primary test has a significant impact on reducing the experimental workload in the original workflows. Proportions of the transferable number of tests per workflow are indicated in black. Abbreviations: targeted next-generation sequencing ((t)NGS), deletion polymerase chain reaction (DelPCR), multiplex ligation-dependant probe amplification (MLPA), fluorescence in situ hybridization (FISH), exome sequencing (ES), long-read sequencing (LRS)