Dataset Information

Rare disorders have many faces: in silico characterization of rare disorder spectrum.

ABSTRACT:

Background

The diagnostic journey for many rare disease patients remains challenging despite use of latest genetic technological advancements. We hypothesize that some patients remain undiagnosed due to more complex diagnostic scenarios that are currently not considered in genome analysis pipelines. To better understand this, we characterized the rare disorder (RD) spectrum using various bioinformatics resources (e.g., Orphanet/Orphadata, Human Phenotype Ontology, Reactome pathways) combined with custom-made R scripts.

Results

Our in silico characterization led to identification of 145 borderline-common, 412 rare and 2967 ultra-rare disorders. Based on these findings and point prevalence, we would expect that approximately 6.53%, 0.34%, and 0.30% of individuals in a randomly selected population have a borderline-common, rare, and ultra-rare disorder, respectively (equaling to 1 RD patient in 14 people). Importantly, our analyses revealed that (1) a higher proportion of borderline-common disorders were caused by multiple gene defects and/or other factors compared with the rare and ultra-rare disorders, (2) the phenotypic expressivity was more variable for the borderline-common disorders than for the rarer disorders, and (3) unique clinical characteristics were observed across the disorder categories forming the spectrum.

Conclusions

Recognizing that RD patients who remain unsolved even after genome sequencing might belong to the more common end of the RD spectrum support the usage of computational pipelines that account for more complex genetic and phenotypic scenarios.

SUBMITTER: Frederiksen SD

PROVIDER: S-EPMC8864832 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Rare disorders have many faces: in silico characterization of rare disorder spectrum.

Frederiksen Simona D SD Avramović Vladimir V Maroilley Tatiana T Lehman Anna A Arbour Laura L Tarailo-Graovac Maja M

Orphanet journal of rare diseases 20220222 1

<h4>Background</h4>The diagnostic journey for many rare disease patients remains challenging despite use of latest genetic technological advancements. We hypothesize that some patients remain undiagnosed due to more complex diagnostic scenarios that are currently not considered in genome analysis pipelines. To better understand this, we characterized the rare disorder (RD) spectrum using various bioinformatics resources (e.g., Orphanet/Orphadata, Human Phenotype Ontology, Reactome pathways) comb ...[more]

PMID: 35193637

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Project description:BackgroundRare genetic variants contribute to the etiology of both autism spectrum disorder (ASD) and schizophrenia (SCZ). Most genetic studies limit their focus to likely gene-disrupting mutations because they are relatively easier to interpret their effects on the gene product. Interpretation of missense variants is also informative to some pathophysiological mechanisms of these neurodevelopmental disorders; however, their contribution has not been elucidated because of relatively small effects. Therefore, we characterized missense variants detected in NRXN1, a well-known neurodevelopmental disease-causing gene, from individuals with ASD and SCZ.MethodsTo discover rare variants with large effect size and to evaluate their role in the shared etiopathophysiology of ASD and SCZ, we sequenced NRXN1 coding exons with a sample comprising 562 Japanese ASD and SCZ patients, followed by a genetic association analysis in 4273 unrelated individuals. Impact of each missense variant detected here on cell surface expression, interaction with NLGN1, and synaptogenic activity was analyzed using an in vitro functional assay and in silico three-dimensional (3D) structural modeling.ResultsThrough mutation screening, we regarded three ultra-rare missense variants (T737M, D772G, and R856W), all of which affected the LNS4 domain of NRXN1α isoform, as disease-associated variants. Diagnosis of individuals with T737M, D772G, and R856W was 1ASD and 1SCZ, 1ASD, and 1SCZ, respectively. We observed the following phenotypic and functional burden caused by each variant. (i) D772G and R856W carriers had more serious social disabilities than T737M carriers. (ii) In vitro assay showed reduced cell surface expression of NRXN1α by D772G and R856W mutations. In vitro functional analysis showed decreased NRXN1α-NLGN1 interaction of T737M and D772G mutants. (iii) In silico 3D structural modeling indicated that T737M and D772G mutations could destabilize the rod-shaped structure of LNS2-LNS5 domains, and D772G and R856W could disturb N-glycan conformations for the transport signal.ConclusionsThe combined data suggest that missense variants in NRXN1 could be associated with phenotypes of neurodevelopmental disorders beyond the diagnosis of ASD and/or SCZ.

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Dataset Information

Rare disorders have many faces: in silico characterization of rare disorder spectrum.

Background

Results

Conclusions

Publications

Rare disorders have many faces: in silico characterization of rare disorder spectrum.

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