BackgroundModelling the prodrome to severe mental disorders (SMD), including unipolar mood disorders (UMD), bipolar mood disorders (BMD) and psychotic disorders (PSY), should consider both the evolution and interactions of symptoms and substance use (prodromal features) over time. Temporal network analysis can address this by representing prodromal features as nodes, with their connections (edges) indicating the likelihood of one feature preceding the other. Node centrality could reveal insights into important prodromal features and potential intervention targets. We developed a SMD network and compared sub-networks specific to UMD, BMD and PSY.MethodsWe analysed 7,049 individuals with an SMD diagnosis (UMD:2,306; BMD:817; PSY:3,926) from the South London and Maudsley NHS Foundation Trust electronic health records. Using validated natural language processing algorithms, we extracted the occurrence of 61 prodromal features every three months from two years to six months prior to SMD onset. To construct temporal networks of prodromal features, we employed generalized vector autoregression panel analysis, adjusting for covariates. We computed edge weights (correlation coefficients,z) in autocorrelative, unidirectional and bidirectional relationships. Centrality was calculated as the sum of connections leaving (out-centrality,cout) or entering (in-centrality,cin) a node. We compared the three sub-networks (UMD, BMD, PSY) using permutation analysis.FindingsThe strongest autocorrelation in the SMD network was tearfulness (z=·10). Unidirectional positive relationships were observed for irritability-agitation (z12=·03), mood instability-tearfulness (z12=·03) and irritability-aggression (z12=·03). Aggression-hostility (z12=·04,z21=·03), delusions-hallucinations (z12=·04,z21=·03) and aggression-agitation (z12=·03,z21=·03) were the strongest bidirectional relationships. The most central features included aggression (cout=·082) and tearfulness (cin=·124). The PSY sub-network showed few significant differences compared to UMD (3·9%) and BMD (1·6%), and UMD-BMD showed even fewer (0·4%).InterpretationsThis study represents the most extensive temporal network analysis conducted on the longitudinal interplay of SMD prodromal features. These findings provide further evidence to support early detection services across SMD.Research in contextEvidence before this studyPreventive approaches for severe mental disorders (SMD) can improve outcomes, however, their effectiveness relies on accurate knowledge of the prodromal symptoms and substance use preceding their onset and how they evolve over time. We searched PubMed from database inception to 26thJanuary 2024 for studies investigating the dynamic prodromes for unipolar mood disorders (UMD), bipolar mood disorders (BMD) or psychotic disorders (PSY) published in English. The search terms were prodrom* AND (depression OR bipolar OR psychosis) AND (timecourse OR dynamic OR “network analysis” OR longitudinal). First, while many studies have investigated the prodromal phases of SMD, particularly for PSY, the majority of studies have taken a cross-sectional rather than longitudinal approach which are unable to detect causal dependence between and within prodromal symptoms and substance use. Second, there are no studies focusing on the evolution of features during the prodromal period. Finally, studies have focused on diagnosis-specific analyses, considering UMD, BMD or PSY alone, limiting the possibility for comparison between them.Added value of this studyWe have used a temporal network analysis approach, in combination with a large electronic health record database (n=7,049) and natural language processing, to examine the dynamic evolution of symptoms and substance use in the prodrome to an SMD diagnosis in secondary mental healthcare. This is the largest network analysis investigating prodromal features in SMD, the first assessing longitudinal changes and the first to directly compare the prodromes to UMD, BMD and PSY. Our results add to the growing evidence for a transdiagnostic prodrome to SMD, by showing small differences between UMD, BMD and PSY in how symptoms and substance use evolve over the course of the prodrome.Implications of all the available evidenceOur study explores the patterns of evolution of symptom and substance use events across and within SMD diagnostic groups. We highlight the importance of understanding the dynamic progression of these prodromal features to fully characterise the prodrome to SMD. These findings, together with a growing literature base, also support the potential for broader transdiagnostic early detection services that provide preventive psychiatric care to individuals at risk for SMD.