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Exploring the similarity between genetic diseases improves their differential diagnosis and the understanding of their etiology

European Journal of Human Genetics volume 32, pages 373–374 (2024)Cite this article

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The Original Article was published on 10 January 2024

The article “LanDis: The Disease Landscape Explorer” by Horacio Caniza et al. ([1], in this issue) is an unvaluable tool to support geneticists in discovering and achieving new insights into the etiology of genetic diseases. LanDis also offers to clinicians an unprecedented opportunity to support the differential diagnosis of genetic diseases, offering an easy-to-use tool also for genetic researchers not particularly skilled in computational biology and bioinformatics.

The rationale of this work is grounded in recent Network Medicine research that showed that: a) disease causal genes usually cluster in “disease modules”, i.e. pathways and sub-networks describing the mechanisms of complex disorders, and b) diseases having common disease modules or that more in general share causal genes are likely to exhibit phenotypical similarity [2]. These findings have led to the design of novel methods and results in disease gene prediction and differential diagnosis [3].

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References

  1. Caniza H, Cáceres JJ, Torres M, Paccanaro A. LanDis: the disease landscape explorer. Eur J Hum Genet. 2024. https://doi.org/10.1038/s41431-023-01511-9.

  2. Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Fang T, Lamparter T, et al. Assessment of network module identification across complex diseases. Nat Methods. 2019;16:843–52.

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Authors and Affiliations

  1. AnacletoLab, Department of Computer Science, University of Milan, Via Celoria 18, Milan, Italy

    Giorgio Valentini

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  1. Giorgio Valentini
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Correspondence to Giorgio Valentini.

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Cite this article

Valentini, G. Exploring the similarity between genetic diseases improves their differential diagnosis and the understanding of their etiology. Eur J Hum Genet 32, 373–374 (2024). https://doi.org/10.1038/s41431-024-01535-9

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