Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

An informatics map for understanding rare mitochondrial disease symptomology (#532)

Anders O Garlid 1 , Vladimir Guevara-Gonzalez 1 , Calvin T Schaffer 1 , Ding Wang 1 , Keith D Garlid 1 , Peipei Ping 1 2
  1. University of California, Los Angeles, Los Angeles, CA, United States
  2. Cardiovascular Data Science Training Program at UCLA, Los Angeles, CA, United States

Introduction: Mitochondrial diseases are complex, rare, and fatal, frequently leading to disruption of mitochondrial proteomes and function. Our limited understanding of these diseases leads to delayed diagnoses and a dearth of treatment options. Advancing our ability to provide timely and accurate diagnosis as well as effective treatment depends on FAIR (Findable, Accessible, Interoperable, Reusable) data resources to decode clinical narratives, interfacing with proteomics knowledgebases to facilitate molecular phenotyping of disease.

Methods: To impose structure on unstructured clinical information on rare mitochondrial diseases (RMDs), we created a metadata template for clinical case reports (CCRs) and aggregated over 400 CCRs on 9 RMDs, including deficiencies in respiratory complexes I-V, carnitine deficiency, Charcot-Marie-Tooth disease, MDCMC, and Barth syndrome. A digital map of ICD-10 codes is constructed to gain systematic understanding of symptoms in RMDs. For example, among 52 CCRs on 111 patients with Barth syndrome, we extracted 1,051 instances of 211 unique ICD-10 codes, along with detailed metadata.

Applications: The metadata and ICD-10 codes are housed on the MitoCases platform (, providing a highly indexed and searchable interface through which to acquire CCRs of relevance for RMD clinicians and researchers. Searching sets of symptoms returns relevant CCRs categorized by disease, aiding in literature curation, case review, and diagnosis. Beginning with an input list of proteins from PRIDE using UniProtKB IDs, users are presented with a collection of CCRs involving the proteins of interest. Use cases are provided with sample Jupyter notebooks to assist in downstream analysis of demographics, symptoms, and biomolecules.

Conclusion: The landscape of the MitoCases digital map highlights shared and common symptoms as well as rare and unique characteristics, revealing pathogenesis and mechanistic insights underlying RMDs. Text data standardization and integration with existing protein resources as well as ontologies render metadata FAIR, enabling elevated understanding and improved patient care.