Finding commonalities in rare diseases through the undiagnosed diseases network.

ABSTRACT:

Objective

When studying any specific rare disease, heterogeneity and scarcity of affected individuals has historically hindered investigators from discerning on what to focus to understand and diagnose a disease. New nongenomic methodologies must be developed that identify similarities in seemingly dissimilar conditions.

Materials and methods

This observational study analyzes 1042 patients from the Undiagnosed Diseases Network (2015-2019), a multicenter, nationwide research study using phenotypic data annotated by specialized staff using Human Phenotype Ontology terms. We used Louvain community detection to cluster patients linked by Jaccard pairwise similarity and 2 support vector classifier to assign new cases. We further validated the clusters' most representative comorbi

SUBMITTER: Yates J 

PROVIDER: S-EPMC8324228 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature