Development of self-phenotyping tools to empower patients and improve diagnostics

Deep phenotyping is important for improving diagnostics and rare diseases research and is especially effective when standardized using Human Phenotype Ontology (HPO). Patients are an under-utilized source of information, so to facilitate self-phenotyping we previously 'translated' HPO into plain language ('layperson HPO'). Another self-phenotyping survey, GenomeConnect, asks patient-friendly questions that map to HPO. However, self-reported data has not been assessed. Since not all HPO terms are translated to layperson HPO or in the GenomeConnect survey, we created theoretical maximum-accuracy phenotype profiles for each disease for each instrument, representing the theoretical maximum performance. Both instruments performed well in analyses of semantic similarity (area under the curve 0.991 and 0.954, respectively). To explore the real-world implications, we randomized participants with diagnosed genetic diseases to complete the GenomeConnect, Phenotypr, or both instruments. For each diagnosed disease, we compared the derived disease profile to the patient-completed profile for each instrument. Profiles resulting from participant responses to the GenomeConnect survey were more accurate than to the Phenotypr instrument. The Phenotypr instrument had a tighter distribution of scores for respondents who did both instruments and was therefore more precise. We evaluated the ability of each known Mendelian disease HPO phenotype profile to retrieve the corresponding disease. We conducted interviews and generally participants preferred the GenomeConnect multiple choice format over the autocomplete Phenotypr format. Our results demonstrate that individuals can provide rich HPO phenotype data. These results suggest that self-phenotyping source of information could be used to support diagnostics or supplement profiles created by clinicians. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was supported by PCORI grant HSRP20181624: https://www.pcori.org/research-results/2017/testing-two-patient-surveys-diagnosing-rare-genetic-conditions and was made possible through access to data in the National Genomic Research Library, which is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The National Genomic Research Library holds data provided by patients and collected by the NHS as part of their care and data collected as part of their participation in research. The National Genomic Research Library is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The IRB of Boston Children's Hospital gave ethical approval for this work (IRB-P00027106). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript or are available online at https://github.com/monarch-initiative/hpo-survey-analysis/tree/master/data/disease_profiles