Rare Genetic Diseases: Nature's Experiments on Human Development - PubMed
- ️Wed Jan 01 2020
Review
Rare Genetic Diseases: Nature's Experiments on Human Development
Chelsea E Lee et al. iScience. 2020.
Abstract
Rare genetic diseases are the result of a continuous forward genetic screen that nature is conducting on humans. Here, we present epistemological and systems biology arguments highlighting the importance of studying these rare genetic diseases. We contend that the expanding catalog of mutations in ∼4,000 genes, which cause ∼6,500 diseases and their annotated phenotypes, offer a wide landscape for discovering fundamental mechanisms required for human development and involved in common diseases. Rare afflictions disproportionately affect the nervous system in children, but paradoxically, the majority of these disease-causing genes are evolutionarily ancient and ubiquitously expressed in human tissues. We propose that the biased prevalence of childhood rare diseases affecting nervous tissue results from the topological complexity of the protein interaction networks formed by ubiquitous and ancient proteins encoded by childhood disease genes. Finally, we illustrate these principles discussing Menkes disease, an example of the discovery power afforded by rare diseases.
Keywords: Clinical Genetics; Human Genetics.
Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.
Figures
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
Principal Features of Rare Genetic Disorders

Quantitative Descriptors of Rare Genetic Disorders Curated by OMIM and Annotated by HPO We used the HPO annotated descriptors for all curated genetic disorders to assess global descriptors of disease. (A) Describes all diseases and associated genes according to Mode of inheritance
HP:0000005. (B) Presents the distribution of diseases according to the age group in which disease manifestations appear: Onset
HP:0003674. (C) Diseases were classified according to annotated clinical phenotypes. (D) Graph presents the distribution of disease according to the organ/tissue/system affected. Phenotypic abnormality
HP:0000118. (E–H) Venn diagrams present overlaps between different HPO terms listed in A–D. All bold numbers indicate overlaps of diseases with HPO terms associated to childhood converging on nervous system and behavioral HPO terms. (E and F) present data for recessive disorders. (G and H) depict data for dominant disorders. (A-D) Y axis represent % of curated OMIM diseases and Y1 axis shows the number of genes associated to the HPO terms (red symbols).

Most Rare Disease Genes are Evolutionarily Ancient We use the lists of genes associated with childhood diseases (pooled
HP:0410280,
HP:0030674,
HP:0003577, and
HP:0003623) and adult genetic diseases (
HP:0003581) and analyzed them with the CLIME engine to determine the presence of orthologues and paralogues across species (Li et al., 2014). The presence of paralogues or orthologues is marked by blue cells in the heatmap.

Rare Disease Gene Ontologies and Protein-Protein Interaction Topologies (A–C) We used the childhood and adult gene HPO lists to explore tissue expression in human tissues using the ARCHS4 transcript database (A), the Human Proteome Map Database (B), or de human brain developmental mRNA expression database CSEA (C) (Kim et al., 2014, Lachmann et al., 2018, Wells et al., 2015). A and B present top ranked tissues where gene lists are expressed. Note that only adult disease mRNAs are significantly enriched in categories describing striated muscle. Childhood diseases genes do not enrich nervous tissue or any other tissue ontologies. Figures A–C show Fisher's exact p values, followed by the Benjamini-Hochberg correction. (D and E) Gene lists for childhood and adult diseases were combined and analyzed using the Cytoscape ClueGo plugin for cellular compartment ontologies (GO:CC) (Bindea et al., 2009). Color in D depicts GO CC terms. Color in E represents the percentage of genes that belong to childhood diseases in the CC term depicted in (D). Note that only one term is equally represented by childhood and adult genes: the I- band belonging to striated muscle. All ontologies are significant with a corrected p value <0.05. Size of circle is proportional to the significance of the term. (F–H) Protein-protein interaction network data for the childhood (F) and adult disease gene lists (G) were obtained from Genemania (Franz et al., 2018). Networks were built and their topologies analyzed with Cytoscape and the NetworkAnalyzer plugin (Doncheva et al., 2012, Shannon et al., 2003). H presents centrality parameters for the childhood (blue symbols) and adult disease genes (purple symbols).
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