Abstract
Neurodevelopmental disorders (NDD) are characterized by impairments in brain development that affect motor and cognitive systems. Early identification of NDD risk factors is crucial for prevention. Metabolomic profiling holds promise for early detection but remains underexplored in longitudinal studies. Here, we map the longitudinal metabolomic profiles in 3212 samples covering 683 metabolites from 581 mother-child pairs at six timepoints in the Danish COPSAC(2010) cohort to assess childhood NDD risk over a 10-years follow-up period. Cross-validated sPLS models identify metabolic biomarkers and patterns associated with NDD, with maternal gestational week 24 metabolic profile showing the best prediction. Metabolite trajectories prior 18-month of age are linked to NDD risk. Quinolinate is consistently associated with NDD across timepoints and mediated the effect of maternal inflammation on NDD. In the single metabolite analysis, no metabolites remained significant after multiple testing correction. In this work, we provide valuable insights into the role of the longitudinal metabolome in neurodevelopment.