Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis

David R. Blair (), Thomas J. Hoffmann and Joseph T. Shieh ()
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David R. Blair: Benioff Children’s Hospital
Thomas J. Hoffmann: Institute for Human Genetics
Joseph T. Shieh: Benioff Children’s Hospital

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Clinical heterogeneity is common in Mendelian disease, but small sample sizes make it difficult to identify specific contributing factors. However, if a disease represents the severely affected extreme of a spectrum of phenotypic variation, then modifier effects may be apparent within a larger subset of the population. Analyses that take advantage of this full spectrum could have substantially increased power. To test this, we developed cryptic phenotype analysis, a model-based approach that infers quantitative traits that capture disease-related phenotypic variability using qualitative symptom data. By applying this approach to 50 Mendelian diseases in two cohorts, we identify traits that reliably quantify disease severity. We then conduct genome-wide association analyses for five of the inferred cryptic phenotypes, uncovering common variation that is predictive of Mendelian disease-related diagnoses and outcomes. Overall, this study highlights the utility of computationally-derived phenotypes and biobank-scale cohorts for investigating the complex genetic architecture of Mendelian diseases.

Date: 2022
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DOI: 10.1038/s41467-022-31030-y

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