Biology subjects

Campbell, K. A.

Publications and source records attributed to Campbell, K. A..

3 recordsLinked to original sources

bioRxiv2026

Tracing PFAS Transfer from Mother to the Fetoplacental Unit: Insights from Trimester-Specific Maternal Serum Profiles

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous endocrine-disrupting pollutants that cross the placenta and affect offspring health, but the extent and timing of their transfer to placental and fetal compartments remain poorly understood. We characterized the relationship between trimester-specific prenatal maternal serum PFAS levels and paired placental and cord plasma levels at term. Data came from the Central Arkansas Glowing prospective cohort (n=151, 2010-2014). Four well-detected PFAS were measured using liquid chromatography-tandem mass spectrometry. Regression, elastic net, and parametric g-formula models tested the association between maternal levels in each trimester and placental or cord PFAS levels. In g-formula models, trimester one (T1) or trimester two (T2) measures consistently had the largest effect sizes associated with placental levels (p<0.001-0.05). Similarly, T1 (PFHxS, PFNA, PFOS, PFOA), T2 (PFNA, PFOS, PFOA), and placental PFOA were associated with cord plasma levels (p<0.05-p<0.001). Results were robust to time-varying adjustment for estimated glomerular filtration rate, serum albumin, or maternal weight. Predictive models improved with additional timepoint measures. Our findings suggest PFOA may transfer more efficiently from the placenta to cord plasma and early-to-mid gestation maternal serum PFAS measures may serve as the most robust sentinels of fetoplacental exposure burden, suggesting early exposure prevention should be prioritized.

pharmacology and toxicology↗

bioRxiv2024

Placental and Immune Cell DNA Methylation Reference Panel for Bulk Tissue Cell Composition

To distinguish DNA methylation (DNAm) from cell proportion changes in whole placental tissue research, we developed a robust cell type-specific DNAm reference to estimate cell composition. We collated newly collected and existing cell type DNAm profiles quantified via Illumina EPIC or 450k microarrays. To estimate cell composition, we deconvoluted whole placental samples (n=36) with robust partial correlation based on the top 50 hyper- and hypomethylated sites per cell type. To test deconvolution performance, we evaluated RMSE in predicting principal component one of DNAm variation in 204 external placental samples. We analyzed DNAm profiles (n=368,435 sites) from 12 cell types: cytotrophoblasts (n=18), endothelial cells (n=19), Hofbauer cells (n=26), stromal cells (n=21), syncytiotrophoblasts (n=4), six lymphocyte types (n=36), and nucleated red blood cells (n=11). Median cell composition was consistent with placental biology: 60.4% syncytiotrophoblast, 17.1% stromal, 8.8% endothelial, 4.5% cytotrophoblast, 3.9% Hofbauer, 1.7% nucleated red blood cells, and 1.2% neutrophils. Our expanded reference outperformed an existing reference in predicting DNAm variation (15.4% variance explained, IQR=21.61) with cell composition estimates (RMSE:10.51 vs. 11.43, p-value<0.001). This cell type reference can robustly estimate cell composition from whole placental DNAm data to detect important cell types, reveal biological mechanisms, and improve casual inference.

genomics↗

bioRxiv2021

Placental gene expression-based cell type deconvolution: Cell proportions drive preeclampsia gene expression differences

The placenta mediates adverse pregnancy outcomes, including preeclampsia, which is characterized by gestational hypertension and proteinuria. Placental cell type heterogeneity in preeclampsia is not well-understood and limits mechanistic interpretation of bulk gene expression measures. We generated single-cell RNA-sequencing samples for integration with existing data to create the largest deconvolution reference of 19 fetal and 8 maternal cell types from placental villous tissue at term (n=15,532 cells). We deconvoluted eight published microarray case-control studies of preeclampsia (n=330). Deconvolution revealed excess extravillous trophoblasts and fewer mesenchymal cells. Adjustment for cellular composition reduced preeclampsia-associated differentially expressed genes (FDR<0.05) from 1,224 to 0, whereas pathway alterations exhibiting a metabolic adaptation to hypoxia were robust to cell type adjustment. Cellular composition explained 35.1% of the association between preeclampsia and FLT1 overexpression. Our findings indicate substantial placental cellular heterogeneity in preeclampsia that predicts previously observed bulk gene expression differences. Our deconvolution reference lays the groundwork for cellular heterogeneity-aware investigation into placental dysfunction and adverse birth outcomes.

developmental biology↗