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

Publisher Copyright: © 2021, The Author(s).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.Peer reviewe

Genome-wide variant calling in reanalysis of exome sequencing data uncovered a pathogenic TUBB3 variant.

Almost half of all individuals affected by intellectual disability (ID) remain undiagnosed. In the Solve-RD project, exome sequencing (ES) datasets from unresolved individuals with (syndromic) ID (n = 1,472 probands) are systematically reanalyzed, starting from raw sequencing files, followed by genome-wide variant calling and new data interpretation. This strategy led to the identification of a disease-causing de novo missense variant in TUBB3 in a girl with severe developmental delay, secondary microcephaly, brain imaging abnormalities, high hypermetropia, strabismus and short stature. Interestingly, the TUBB3 variant could only be identified through reanalysis of ES data using a genome-wide variant calling approach, despite being located in protein coding sequence. More detailed analysis revealed that the position of the variant within exon 5 of TUBB3 was not targeted by the enrichment kit, although consistent high-quality coverage was obtained at this position, resulting from nearby targets that provide off-target coverage. In the initial analysis, variant calling was restricted to the exon targets ± 200 bases, allowing the variant to escape detection by the variant calling algorithm. This phenomenon may potentially occur more often, as we determined that 36 established ID genes have robust off-target coverage in coding sequence. Moreover, within these regions, for 17 genes (likely) pathogenic variants have been identified before. Therefore, this clinical report highlights that, although compute-intensive, performing genome-wide variant calling instead of target-based calling may lead to the detection of diagnostically relevant variants that would otherwise remain unnoticed

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

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

A MT-TL1 variant identified by whole exome sequencing in an individual with intellectual disability, epilepsy, and spastic tetraparesis.

Funder: The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257The genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n = 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1 (NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1 variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line

Genome-wide variant calling in reanalysis of exome sequencing data uncovered a pathogenic TUBB3 variant

Almost half of all individuals affected by intellectual disability (ID) remain undiagnosed. In the Solve-RD project, exome sequencing (ES) datasets from unresolved individuals with (syndromic) ID (n = 1,472 probands) are systematically reanalyzed, starting from raw sequencing files, followed by genome-wide variant calling and new data interpretation. This strategy led to the identification of a disease-causing de novo missense variant in TUBB3 in a girl with severe developmental delay, secondary microcephaly, brain imaging abnormalities, high hypermetropia, strabismus and short stature. Interestingly, the TUBB3 variant could only be identified through reanalysis of ES data using a genome-wide variant calling approach, despite being located in protein coding sequence. More detailed analysis revealed that the position of the variant within exon 5 of TUBB3 was not targeted by the enrichment kit, although consistent high-quality coverage was obtained at this position, resulting from nearby targets that provide off-target coverage. In the initial analysis, variant calling was restricted to the exon targets ± 200 bases, allowing the variant to escape detection by the variant calling algorithm. This phenomenon may potentially occur more often, as we determined that 36 established ID genes have robust off-target coverage in coding sequence. Moreover, within these regions, for 17 genes (likely) pathogenic variants have been identified before. Therefore, this clinical report highlights that, although compute-intensive, performing genome-wide variant calling instead of target-based calling may lead to the detection of diagnostically relevant variants that would otherwise remain unnoticed.This work was financially supported by Aspasia grants of the Dutch Research Council (015.014.036 to TK and 015.014.066 to LELMV) and Netherlands Organization for Health Research and Development (917.183.10 to TK). The Solve-RD project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 779257

Genome-wide variant calling in reanalysis of exome sequencing data uncovered a pathogenic TUBB3 variant

Almost half of all individuals affected by intellectual disability (ID) remain undiagnosed. In the Solve-RD project, exome sequencing (ES) datasets from unresolved individuals with (syndromic) ID (n = 1,472 probands) are systematically reanalyzed, starting from raw sequencing files, followed by genome-wide variant calling and new data interpretation. This strategy led to the identification of a disease-causing de novo missense variant in TUBB3 in a girl with severe developmental delay, secondary microcephaly, brain imaging abnormalities, high hypermetropia, strabismus and short stature. Interestingly, the TUBB3 variant could only be identified through reanalysis of ES data using a genome-wide variant calling approach, despite being located in protein coding sequence. More detailed analysis revealed that the position of the variant within exon 5 of TUBB3 was not targeted by the enrichment kit, although consistent high-quality coverage was obtained at this position, resulting from nearby targets that provide off-target coverage. In the initial analysis, variant calling was restricted to the exon targets ± 200 bases, allowing the variant to escape detection by the variant calling algorithm. This phenomenon may potentially occur more often, as we determined that 36 established ID genes have robust off-target coverage in coding sequence. Moreover, within these regions, for 17 genes (likely) pathogenic variants have been identified before. Therefore, this clinical report highlights that, although compute-intensive, performing genome-wide variant calling instead of target-based calling may lead to the detection of diagnostically relevant variants that would otherwise remain unnoticed.This work was financially supported by Aspasia grants of the Dutch Research Council (015.014.036 to TK and 015.014.066 to LELMV) and Netherlands Organization for Health Research and Development (917.183.10 to TK). The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257.S

Correction: A MT-TL1 variant identified by whole exome sequencing in an individual with intellectual disability, epilepsy, and spastic tetraparesis (European Journal of Human Genetics, (2021), 29, 9, (1359-1368), 10.1038/s41431-021-00900-2)

In the original publication of the article, consortium author lists were missing in the article. The details are as below