Learning phenotypic patterns in genetic diseases by symptom interaction modeling

Observing phenotyping practices from an international cohort of 1,686 cases revealed heterogeneity of phenotype reporting among clinicians. Heterogeneity limited their exploitation for diagnosis as only 43% of symptom-gene associations in the cohort were available in public databases. We developed a symptom interaction model that summarized 16,600 terms into 390 groups of interacting symptoms and detected 3,222,053 novel symptom-gene associations. By learning phenotypic patterns in genetic diseases, symptom interaction modeling handled heterogeneity in phenotyping, to the extent of covering 98% of our cohort’s symptom-gene associations. Using these symptom interactions improved the diagnostic performance in gene prioritization by 42% (median rank 80 to 41) compared to the best algorithms. Symptom interaction modeling will provide new discoveries in precision medicine by standardizing clinical descriptions. One sentence summary Learning phenotypic patterns in genetic disease by symptom interaction modeling addresses physicians’ heterogeneous phenotype reporting. ### Competing Interest Statement K.Y., N.D-F., S.B., J.A., D.L., M.B., D.B., and N.P. are partially or fully employed by SeqOne Genomics; D.L, S.B, J.A., and N.P. hold shares in SeqOne Genomics. K.Y., N.D-F, S.B., D.L., J.A., N.P., and J.T. has filed two patent applications based on this work. ### Funding Statement This study was been jointly funded by Association Nationale de la recherche et de la Technologie (ANRT) and SeqOne Genomics. ### 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: Local Ethics Committee of the CHU Grenoble-Alpes gave ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the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 and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced are available in Supplementary Materials and online at https://github.com/kyauy/PhenoGenius