Using Genomic Context Informed Genotype Data and Within‐model Ancestry Adjustment to Classify Type 2 Diabetes

Despite high heritability estimates, complex genetic disorders have proven difficult to predict with genetic data. Genomic research has documented polygenic inheritance, cross-disorder genetic correlations, and enrichment of risk by functional genomic annotation, but the vast potential of that combined knowledge has not yet been leveraged to build optimal risk models. Additional methods are likely required to progress genetic risk models of complex genetic disorders towards clinical utility. We developed a framework that uses annotations providing genomic context alongside genotype data as input to convolutional neural networks to predict disorder risk. We validated models in a matched-pairs type 2 diabetes dataset. A neural network using genotype data (AUC: 0.66) and a convolutional neural network using context-informed genotype data (AUC: 0.65) both significantly outperformed polygenic risk score approaches in classifying type-2 diabetes. Adversarial ancestry tasks eliminated the predictability of ancestry without changing model performance. ### Competing Interest Statement Yanli Zhang-James is supported by the European Unions Seventh Framework Programme for research, technological development and demonstration under grant agreement no 602805 and the European Unions Horizon 2020 research and innovation programme under grant agreements No 667302. Jonathan Hess is supported by the U.S. National Institutes of Health (R21MH126494, R01NS128535) and NARSAD: The Brain & Behavior Research Foundation. Stephen J. Glatt is supported by grants from the U.S. National Institutes of Health (R01MH101519, R01AG054002, R01AG064955), the Sidney R. Baer, Jr. Foundation, and NARSAD: The Brain & Behavior Research Foundation. Stephen V. Faraone received income, potential income, travel expenses continuing education support and/or research support from Aardvark, Aardwolf, AIMH, Akili, Atentiv, Axsome, Genomind, Ironshore, Johnson & Johnson/Kenvue, Kanjo, KemPharm/Corium, Noven, Otsuka, Sky Therapeutics, Sandoz, Supernus, Tris, and Vallon. With his institution, he has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD. He also receives royalties from books published by Guilford Press: Straight Talk about Your Childs Mental Health, Oxford University Press: Schizophrenia: The Facts and Elsevier: ADHD: Non-Pharmacologic Interventions. He is Program Director of www.ADHDEvidence.org and www.ADHDinAdults.com. Dr. Faraone's research is supported by the Upstate Foundation, the European Unions Horizon 2020 research and innovation programme under grant agreement 965381; NIH/NIMH grants U01AR076092, R01MH116037, 1R01NS128535, R01MH131685, 1R01MH130899, U01MH135970, and Supernus Pharmaceuticals. His continuing medical education programs are supported by The Upstate Foundation, Corium Pharmaceuticals, Tris Pharmaceuticals and Supernus Pharmaceuticals. Eric J. Barnett has no conflicts of interest to report. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes 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 This research was conducted using genotype and phenotype data from the UK Biobank resource under application number 60050. All other data are available from the authors upon request.