Phen2Disease: a phenotype-driven model for disease and gene prioritization by bidirectional maximum matching semantic similarities

Human Phenotype Ontology (HPO)-based approaches have gained popularity in recent times as a tool for genomic diagnostics of rare diseases. However, these approaches do not make full use of the available information on disease and patient phenotypes. We present a new method called Phen2Disease, which utilizes the bidirectional maximum matching semantic similarity between two phenotype sets of patients and diseases to prioritize diseases and genes. Our comprehensive experiments have been conducted on six real data cohorts with 2051 cases (Cohort 1, n = 384; Cohort 2, n = 281; Cohort 3, n = 185; Cohort 4, n = 784; Cohort 5, n = 208; and Cohort 6, n = 209) and two simulated data cohorts with 1000 cases. The results of the experiments showed that Phen2Disease outperforms the three state-of-the-art methods when only phenotype information and HPO knowledge base are used, particularly in cohorts with fewer average numbers of HPO terms. We also observed that patients with higher information content scores have more specific information, leading to more accurate predictions. Moreover, Phen2Disease provides high interpretability with ranked diseases and patient HPO terms presented. Our method provides a novel approach to utilizing phenotype data for genomic diagnostics of rare diseases, with potential for clinical impact. Phen2Disease is freely available on GitHub at .

Automated summary

HPO-based approaches are popular for genomic diagnostics of rare diseases, but they do not fully utilize available information on disease and patient phenotypes. We present a new method called Phen2Disease that prioritizes diseases and genes using semantic similarity between phenotype sets. Our experiments show that Phen2Disease outperforms state-of-the-art methods, especially in cohorts with fewer HPO terms. We also find that patients with higher information content scores have more accurate predictions. Phen2Disease provides ranked diseases and patient HPO terms, offering a novel approach for rare disease diagnostics.