Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Unveiling the hidden: revisiting the potential of old genetic data for rare disease research

European Journal of Human Genetics volume 31, pages 1093–1094 (2023)Cite this article

Subjects

Unlike many other diagnostic tests, a negative exome sequencing does not rule out a genetic disorder; instead, it only implies that a genetic diagnosis could not be identified, given the clinical and genetic information available at the time of analysis. Reanalyzing exome data from unsolved cohorts with neurodevelopmental disorders (NDD) holds significant importance for several reasons [1]. Firstly, it allows for the identification of potentially missed or misclassified genetic variants. The initial analysis of exome data may have been limited by the available knowledge at the time, as well as the algorithms and filtering strategies employed. Revisiting the data with improved variant calling algorithms and updated databases can unmask previously concealed genomic variations and lead to the discovery of disease-causing variants that were initially overlooked. Secondly, the reanalysis provides an opportunity to evaluate diagnostic variants according to current standards and guidelines [2]. Over time, our understanding of variant pathogenicity and gene-disease associations evolves, necessitating a reassessment of previously reported variants. By applying updated classification criteria and incorporating additional evidence, such as functional studies or confirmatory publications, the pathogenicity of variants can be more accurately determined. Furthermore, reanalyzing exome data allows for the confirmation or removal of gene-disease associations (GDA). As new research emerges, some previously reported associations may be called into question or require further validation. By critically evaluating the evidence supporting the GDAs, we refine our understanding of the genetic basis of NDD and establish more reliable genotype-phenotype correlations. Lastly, reanalysis can uncover previously unknown gene associations. The constantly expanding knowledge base of gene-disease relationships, with hundreds of new associations being identified each year, provides a valuable resource for revisiting unsolved cohorts. By leveraging this wealth of information and employing advanced computational tools and filtering strategies, researchers can identify novel gene candidates and establish their role in NDD.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

References

  1. Ji J, Leung ML, Baker S, Deignan JL, Santani A. Clinical exome reanalysis: current practice and beyond. Mol Diagn Ther. 2021;25:529–36.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Richards S, Aziz N, Bale S, Bick D, Das S, Gastrier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–24.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Tobias Bartolomaeus JH, Jamra RA, Popp B: Re-evaluation and Re-analysis of 152 research exomes five years after the initial report reveals clinically relevant changes in 18%. Eur J Human Genet. 2023. https://doi.org/10.1038/s41431-023-01425-6

  4. Reuter MS, Tawamie H, Buchert R, Gebril OH, Froukh T, Thiel C, et al. Diagnostic yield and novel candidate genes by exome sequencing in 152 consanguineous families with neurodevelopmental disorders. JAMA Psychiatry. 2017;74:293–9.

    Article  PubMed  Google Scholar 

  5. Lieberwirth JK, Buttner B, Klockner C, Platzer K, Popp B, Abou Jamra R. AutoCaSc: prioritizing candidate genes for neurodevelopmental disorders. Hum Mutat. 2022;43:1795–807.

    Article  PubMed  Google Scholar 

  6. SoRelle JA, Thodeson DM, Arnold S, Gotway G, Park JY. Clinical utility of reinterpreting previously reported genomic epilepsy test results for pediatric patients. JAMA Pediatr. 2019;173:e182302.

    Article  PubMed  Google Scholar 

  7. Xiang J, Yang J, Chen L, Chen Q, Yang H, Sun C, et al. Reinterpretation of common pathogenic variants in ClinVar revealed a high proportion of downgrades. Sci Rep. 2020;10:331.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

Funding

There was no specific funding.

Author information

Authors and Affiliations

  1. Department of Epilepsy Genetics and Personalized Medicine, Danish Epilepsy Center, Dianalund, Denmark

    Allan Bayat

  2. Department of Regional Health Research, University of Southern Denmark, Odense, Denmark

    Allan Bayat

  3. Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark

    Allan Bayat

Authors
  1. Allan Bayat
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Allan Bayat.

Ethics declarations

Competing interests

The author declares no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bayat, A. Unveiling the hidden: revisiting the potential of old genetic data for rare disease research. Eur J Hum Genet 31, 1093–1094 (2023). https://doi.org/10.1038/s41431-023-01435-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41431-023-01435-4

Search

Advanced search

Quick links