Abstract
Postpartum depression (PPD) is a multifaceted mental health disorder manifesting as enduring sadness, anxiety, and exhaustion following childbirth. Emerging evidence points to a metabolic dimension in its pathology. Our research examines the causal links between cerebrospinal fluid (CSF) metabolites and PPD via Mendelian randomization (MR). A bi-directional MR framework was applied to explore the causative connections between 338 CSF metabolites and PPD. The study harnessed data from 2 targeted genome-wide association studies: one encompassing single nucleotide polymorphism data from mothers diagnosed with PPD, and another concerning CSF metabolite profiles, both centered on European descendants. Instrumental variables from these datasets were meticulously selected to enhance MR analysis' robustness. Our integrated approach provided a profound exploration of the genetic underpinnings influencing CSF metabolites related to PPD. Statistical analyses employed methods like inverse variance weighting, the weighted median, and mode-based estimation to fortify the causal inferences drawn from the associations. PPD was characterized according to diagnostic standards sanctioned by the FinnGen study's clinical expert panels, incorporating insights from leading domain specialists. Our MR investigation pinpointed several CSF metabolites potentially linked to PPD. Notably, metabolites such as 3-hydroxy-3-methylglutarate, 3-methoxytyrosine, and argininosuccinate appeared protective, whereas arachidonate, benzoate, and carnitine correlated with heightened risk. The findings demonstrated consistency across diverse MR methodologies, affirming a significant linkage. This investigation underscores the potential of CSF metabolomics in decoding PPD's etiology. Identifying particular metabolites associated with the disorder enhances our understanding of its underlying mechanisms and fosters avenues for future research into tailored therapeutic strategies.