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Description: Emerging evidence shows that mood disorders can be plausibly conceptualized as networks of causally interacting symptoms rather than as latent variables where symptoms are passive indicators. Here we introduce an empirical application of network analysis to nursing research by estimating the network structure of 20 perinatal depressive (PND) symptoms. Further, we conduct two proof-of-principle analyses: incorporating stress and reproductive biomarkers into the network, and comparing the network structure of PND symptoms between healthy and depressed women. We analyzed a cross-sectional sample of 515 Latina women at the second trimester of pregnancy, and estimated networks using state-of-the-art regularized partial correlation network models. The main analysis yielded five strong symptom-to-symptom associations (e.g., cry—sadness), and five symptoms of potential clinical importance (i.e. high centrality) in the network. In exploring the relationship of PND symptoms with stress and reproductive biomarkers (proof-of-principle 1), a few weak relationships emerged. A comparison of healthy and depressed networks (proof-of-principle 2) showed that depressed participants had an overall more connected network, but the networks did not differ regarding their types of relationships (the network structures). Our study is the first to show that PND symptoms can be conceived of as a network of interacting symptoms, and we hope it will encourage future network studies in the realm of PND research, including investigations of symptom-to-biomarker mechanisms and interactions related to PND. Future directions and challenges are discussed.