Phenomic Network Analysis for Depression Reveals Comorbidity Architecture, Genomic Relationships, and Pleiotropic Variants

Depression is one of the most prevalent psychiatric disorders and is one of the leading causes of health ailment worldwide. It is known to be highly heritable and is frequently comorbid with other mental and physical traits. This observation motivated us to look deeper into the genetic and phenotypic connections between depression and other traits in order to identify correlations as well as potentially causal connections between them. In this study, we analyzed data from the UK biobank to systematically evaluate relationships between depression and other heritable traits both from a phenotypic and a genetic aspect. We compressed a total of 6,300 ICD codes into 412 heritable phecodes and we constructed a comorbidity network connecting depression and other disorders on over 300,000 participants of European ancestry. Additionally, we investigated the genetic correlation for each (phenotypic) connection in the resulting network. We also looked into potentially causal relationships using mendelian randomization for all pairs of significantly correlated disorders and uncovered horizontal pleiotropic genetic variants and genes contributing to disease etiologies. We found gastro-oesophageal reflux disease (GORD), body mass index, and osteoarthritis to be direct causes for depression, with GORD lying at the center of the causal network. Genes broadly expressed in various tissues, such as NEGR1, TCF4 , and BTN2A1 underlie the pathways that lead not only to depression but also to other related disorders. Our work highlights the broad connections between depression and diverse traits, indicating a complex etiology and possible existence of subtypes for depression. Our findings highlight the value of cross-trait analysis in order to better understand the neurobiology of complex psychiatric disease. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by NSF 1715202, NSF 2006929, the IBM Research Faculty Award. ### 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: This research has been conducted using the UK Biobank Resource under Application Number 61553. 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 in the present study are available upon reasonable request to the authors