Poster CC6 - Depression during Pregnancy is Associated with a Dysregulated Maternal Microbiota-Gut-Brain Axis

Introduction: Depression during pregnancy affects more than 20% of pregnancies and disproportionately affects non-Hispanic Black women and Latinas. Rates of PND in the United States have doubled since 2000, a trend with profound implications for public health. Depression during pregnancy is associated with increased risk of preterm birth, delays in infant neurodevelopment, and future mental health disorders for both mother and infant, among other adverse outcomes. Yet we still do not fully understand the pathobiology of prenatal depression, limiting efforts to improve its prevention, identification and treatment. Interactions between the host and microbial communities that reside in the gut are essential for human health, including mental health. An underexplored mechanism that could contribute to the onset of prenatal depression is the microbiome-gut-brain axis (MGBA). Gut microorganisms play an important role in producing many beneficial metabolites, including the neurotransmitters serotonin and gamma-aminobutyric acid (GABA) and bidirectionally communicate with the brain through the mediation of the neurological, immune, and endocrine systems. Here we aim to identify the associations between elevated symptoms of depression during pregnancy and quantifiable characteristics of the MGBA, including maternal fecal microbiota, serum metabolites and cytokines.

Materials and

Methods: We enrolled 74 women at less than 16 gestational weeks from a public urban hospital in Chicago (USA) and followed them longitudinally at each trimester during pregnancy. At each visit, participants answered a battery of questionnaires pertaining to their prior and current physical and mental health (e.g., depression, anxiety, diet, and sleep habits) and provided fecal samples. Participants also provided blood samples at the first two visits. Gut microbial composition, immune activity, and plasma metabolomics and lipidomics were characterized with 16S rRNA sequencing, Luminex and LC/MS/MS, respectively. Amplicon Sequence Variance (ASVs) were identified using DADA2 and differentially abundant taxa as a function of depression levels and gestational weeks were obtained using Generalized Mixed Models correcting for participants’ age, race/ethnicity, BMI, prior history of depression, constipation, and federal aid insurance. Significant cytokines, and metabolic and lipodomics were identified using Linear Mixed Models (LMMs) correcting by the same covariates. Identification of the most important members of the microbial communities that drive their structure, we generated personalized co-abundance microbial networks for each sample SPIEC-EASI and LIONESS, in which each edge has an associated weight based on their importance for a given sample. We also employed LMMs to select the significant edges as a function of depression severity and gestational weeks correcting by the same covariates.

Results, Conclusions, and Discussions: Participants were 63.5% Black and 27% Latina and 77% of them were in federal aid health insurance with a 23% rate of antenatal depression (greater than the national average). Individuals that reported elevated levels of depression had more similar microbial community structures independently of the gestational trimester (Bray-Curtis distance, p< 0.01). In line with this observation, we identified a total of 23 ASVs associated with depression, including multiple members of the genus Peptoniphilus and Blatia, and strains of Parabacteroides distasonis, Anaerostipes hadrus, and Gardnerella vaginalis. We also identified a total of 32 metabolic features that were significantly associated with depression: amino acids (e.g., taurine, methionine, glutamine, phenylalanine), saturated fatty acids (e.g., palmoleic acid), unsaturated fatty acids (e.g., oleic acid), and long-chain fatty acids (behenic and docosadienoic acids). While the association between most of the metabolic markers with depression depended on the gestational weeks, the microbially-regulated glutamate, one of the most important neurotransmitters in the brain and precursor of gamma-aminobutyrate, was decreased in individuals that reported elevated levels of depression symptoms for depression independently of their gestational weeks. We also observed a pro-inflammatory profile, which depends on the gestational weeks, including chemokines MIP1a and MIP3a and cytokines IL-23, IL-2, and IL-10. For sample-individual co-abundance networks revealed that communities composed by members of the genus Peptoniphilus and Prevotella become more important as depression levels increased with P. lacrimalis, a well-known pathogen, as one of the most relevant taxa. MGBA is dynamically altered during pregnancy and distinct in women with depression versus those without. Our results showed the potential of the MGBA to diagnose and predict the onset of antenatal depression.

Acknowledgements (Optional): We would like to thank to all the participants in the study. This work has been supported by the Arnold O. Beckman Postdoctoral Award and the K12 BIRWCH Award (K12AR084225) to BPB and by the NICHD (R03HD095056).