A resource to explore the discovery of rare diseases and their causative genes

Ehrhart, Friederike; Willighagen, Egon; Kutmon, Martina; Hoften, Max van; Curfs, Leopold; Evelo, Chris T.

doi:10.1038/s41597-021-00905-y

Cited by 16 publications

(20 citation statements)

References 28 publications

(17 reference statements)

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“…More differences were observed across the two PSAP strategies for the AD than for the AR model (Fig 3A). There were 362 variants ranked first and 1,017 variants ranked [2][3][4][5][6][7][8][9][10] in common between the two strategies. However, 908 variants that were ranked [2][3][4][5][6][7][8][9][10] with PSAP-genes-CADD were with PSAP-genomic-regions-CADD, and 395 variants that were ranked [2][3][4][5][6][7][8][9][10] with PSAP-genes-CADD were ranked first with PSAPgenomic-regions-CADD.…”

Section: Prioritization Of Coding Pathogenic Variantsmentioning

confidence: 99%

“…There were 362 variants ranked first and 1,017 variants ranked [2][3][4][5][6][7][8][9][10] in common between the two strategies. However, 908 variants that were ranked [2][3][4][5][6][7][8][9][10] with PSAP-genes-CADD were with PSAP-genomic-regions-CADD, and 395 variants that were ranked [2][3][4][5][6][7][8][9][10] with PSAP-genes-CADD were ranked first with PSAPgenomic-regions-CADD. Regarding variants that are ranked more than a 100 with PSAP-genomic-regions-CADD, 278 of them are ranked and are ranked [51-100] by PSAP-genes-CADD.…”

Section: Prioritization Of Coding Pathogenic Variantsmentioning

confidence: 99%

“…Even more promising results can be found when looking at the same comparison of ranks within the FREX exomes ( S6 Fig). For instance, in the AD model, 592 variants that were ranked [2][3][4][5][6][7][8][9][10] with PSAP-genes-CADD are ranked first with PSAPgenomic-regions-CADD, against 115 variants ranked [2-10] with PSAP-genomic-regions-CADD that become first with PSAP-genes-CADD.…”

Section: Prioritization Of Coding Pathogenic Variantsmentioning

confidence: 99%

“…However, as a whole, rare diseases affect about 350 million people world-wide (1). Approximately 80% of rare diseases have a genetic origin that mostly follows a Mendelian mode of inheritance (2)(3)(4). The advent of Next Generation Sequencing (NGS) and the development of variant pathogenicity prediction tools have allowed, in recent years, the identification of many genes involved in rare Mendelian diseases.…”

Section: Introductionmentioning

confidence: 99%

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PSAP-genomic-regions: a method leveraging population data to prioritize coding and non-coding variants in whole genome sequencing for rare disease diagnosis

Ogloblinsky,

Bocher,

Aloui

et al. 2024

Preprint

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The introduction of next generation sequencing technologies in the clinics has improved rare disease diagnosis. Nonetheless, for very heterogeneous or very rare diseases, more than half of cases still lack molecular diagnosis. Novel strategies are needed to prioritize variants within a single individual. The PSAP (Population Sampling Probability) method was developed to meet this aim but only for coding variants in exome data. To address the challenge of the analysis of non-coding variants in whole genome sequencing data, we propose an extension of the PSAP method to the non-coding genome called PSAP-genomic-regions. In this extension, instead of considering genes as testing units (PSAP-genes strategy), we use genomic regions defined over the whole genome that pinpoint potential functional constraints. We conceived an evaluation protocol for our method using artificially-generated disease exomes and genomes, by inserting coding and non-coding pathogenic ClinVar variants in large datasets of exomes and genomes from the general population. We found that PSAP-genomic-regions significantly improves the ranking of these variants compared to using a pathogenicity score alone. Using PSAP-genomic-regions, more than fifty percent of non-coding ClinVar variants, especially those involved in splicing, were among the top 10 variants of the genome. In addition, our approach gave similar results compared to PSAP-genes regarding the scoring of coding variants. On real sequencing data from 6 patients with Cerebral Small Vessel Disease and 9 patients with male infertility, all causal variants were ranked in the top 100 variants with PSAP-genomic-regions. By revisiting the testing units used in the PSAP method to include non-coding variants, we have developed PSAP-genomic-regions, an efficient whole-genome prioritization tool which offers promising results for the diagnosis of unresolved rare diseases. PSAP-genomic-regions is implemented as a user-friendly Snakemake workflow, accessible to both researchers and clinicians which can easily integrate up-to-date annotation from large databases.

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Section: Prioritization Of Coding Pathogenic Variantsmentioning

confidence: 99%

Section: Prioritization Of Coding Pathogenic Variantsmentioning

confidence: 99%

Section: Prioritization Of Coding Pathogenic Variantsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PSAP-genomic-regions: a method leveraging population data to prioritize coding and non-coding variants in whole genome sequencing for rare disease diagnosis

Ogloblinsky,

Bocher,

Aloui

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…According to the SysNDD (Kochinke et al 2016 ) database, pathogenic variants in 1780 (gene statistics from October 26, 2023) different genes are currently established as causes of diverse neurodevelopmental disorders (NDD). Although the rate of discovery of new rare disease–gene associations has declined in recent years (Ehrhart et al 2021 ), several disease-causing genes remain undiscovered, as demonstrated by a recent analysis of the X chromosome (Leitão et al 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Heterozygous loss-of-function variants in DOCK4 cause neurodevelopmental delay and microcephaly

Herbst,

Bothe,

Wegler

et al. 2024

Hum. Genet.

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Neurons form the basic anatomical and functional structure of the nervous system, and defects in neuronal differentiation or formation of neurites are associated with various psychiatric and neurodevelopmental disorders. Dynamic changes in the cytoskeleton are essential for this process, which is, inter alia, controlled by the dedicator of cytokinesis 4 (DOCK4) through the activation of RAC1. Here, we clinically describe 7 individuals (6 males and one female) with variants in DOCK4 and overlapping phenotype of mild to severe global developmental delay. Additional symptoms include coordination or gait abnormalities, microcephaly, nonspecific brain malformations, hypotonia and seizures. Four individuals carry missense variants (three of them detected de novo) and three individuals carry null variants (two of them maternally inherited). Molecular modeling of the heterozygous missense variants suggests that the majority of them affect the globular structure of DOCK4. In vitro functional expression studies in transfected Neuro-2A cells showed that all missense variants impaired neurite outgrowth. Furthermore, Dock4 knockout Neuro-2A cells also exhibited defects in promoting neurite outgrowth. Our results, including clinical, molecular and functional data, suggest that loss-of-function variants in DOCK4 probable cause a variable spectrum of a novel neurodevelopmental disorder with microcephaly.

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PSAP‐Genomic‐Regions: A Method Leveraging Population Data to Prioritize Coding and Non‐Coding Variants in Whole Genome Sequencing for Rare Disease Diagnosis

Ogloblinsky,

Bocher,

Aloui

et al. 2024

Genetic Epidemiology

View full text Add to dashboard Cite

The introduction of Next‐Generation Sequencing technologies in the clinics has improved rare disease diagnosis. Nonetheless, for very heterogeneous or very rare diseases, more than half of cases still lack molecular diagnosis. Novel strategies are needed to prioritize variants within a single individual. The Population Sampling Probability (PSAP) method was developed to meet this aim but only for coding variants in exome data. Here, we propose an extension of the PSAP method to the non‐coding genome called PSAP‐genomic‐regions. In this extension, instead of considering genes as testing units (PSAP‐genes strategy), we use genomic regions defined over the whole genome that pinpoint potential functional constraints. We conceived an evaluation protocol for our method using artificially generated disease exomes and genomes, by inserting coding and non‐coding pathogenic ClinVar variants in large data sets of exomes and genomes from the general population. PSAP‐genomic‐regions significantly improves the ranking of these variants compared to using a pathogenicity score alone. Using PSAP‐genomic‐regions, more than 50% of non‐coding ClinVar variants were among the top 10 variants of the genome. On real sequencing data from six patients with Cerebral Small Vessel Disease and nine patients with male infertility, all causal variants were ranked in the top 100 variants with PSAP‐genomic‐regions. By revisiting the testing units used in the PSAP method to include non‐coding variants, we have developed PSAP‐genomic‐regions, an efficient whole‐genome prioritization tool which offers promising results for the diagnosis of unresolved rare diseases.

show abstract

A resource to explore the discovery of rare diseases and their causative genes

Cited by 16 publications

References 28 publications

PSAP-genomic-regions: a method leveraging population data to prioritize coding and non-coding variants in whole genome sequencing for rare disease diagnosis

PSAP-genomic-regions: a method leveraging population data to prioritize coding and non-coding variants in whole genome sequencing for rare disease diagnosis

Heterozygous loss-of-function variants in DOCK4 cause neurodevelopmental delay and microcephaly

PSAP‐Genomic‐Regions: A Method Leveraging Population Data to Prioritize Coding and Non‐Coding Variants in Whole Genome Sequencing for Rare Disease Diagnosis

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