Pregnancy Health

Pregnancy Health is an active area of supported research in the lab. We use high dimensional multi-omic data to map molecular networks to understand normal pregnancy as well as changes associated with complications in an effort to identify risk factor and predict abnormal pregnancies well in advance of currently possible in the clinic. We have several on-going projects with both federal and private support, including:

Harnessing “omics”: A Systems Biology approach to discovery of biological pathways in placental development and parturition seeks to identify key genes and pathways associated with placental maturity that are quantifiable in maternal serum and urine, as well as to create a transcriptional regulatory network in the placenta using Transcriptional Regulatory Network Analysis (TRENA), which has been developed by the Price lab as part of the NIH Accelerating Medicines Program and a Big Data to Knowledge

Genetics Meets Metabolomics in Spontaneous Preterm Birth aims to leverage a multi-layered systems approach to uncover the genetic control of metabolic reprogramming in preterm birth. We are integrating targeted metabolites and SNPs as well as clinical factors and demographics from a nested case-control cohort of females drawn from a population of singleton pregnancies with live births in the state of California. We are extracting multimodal biological parameters that can estimate gestational age at the time of sampling and mechanistically depicting their biochemical interactions in preterm birth.

Recent Publications in Pregnancy Research:

Extracellular vesicle RNAs reflect placenta dysfunction and are a biomarker source for preterm labour. Fallen, S., Baxter, D., Wu, X., Kim, T.-K., Shynlova, O., Lee, M.Y., Scherler, K., Lye, S., Hood, L., Wang, K., 2018. J. Cell. Mol. Med. https://doi.org/10.1111/jcmm.13570

Genomic and molecular characterization of preterm birth. Knijnenburg, T.A., Vockley, J.G., Chambwe, N., Gibbs, D.L., Humphries, C., Huddleston, K.C., Klein, E., Kothiyal, P., Tasseff, R., Dhankani, V., Bodian, D.L., Wong, W.S.W., Glusman, G., Mauldin, D.E., Miller, M., Slagel, J., Elasady, S., Roach, J.C., Kramer, R., Leinonen, K., Linthorst, J., Baveja, R., Baker, R., Solomon, B.D., Eley, G., Iyer, R.K., Maxwell, G.L., Bernard, B., Shmulevich, I., Hood, L., Niederhuber, J.E., 2019. Proc. Natl. Acad. Sci. 116, 5819. https://doi.org/10.1073/pnas.1716314116

Temporal transcriptomic analysis of metabolic genes in maternal organs and placenta during murine pregnancy. Paquette, A., Baloni, P., Holloman, A.B., Nigam, S., Bammler, T., Mao, Q., Price, N.D. Biol. Reprod, 2018. https://doi.org/10.1093/biolre/ioy148

Distinct communication patterns of trophoblastic miRNA among the maternal-placental-fetal compartments. Paquette, A., Chu, Tianjiao, Wu, Xiaogang, Wang, Kai, Price, Nathan, Sadovsky, Yoel. Placenta, 2018. https://doi.org/10.1016/j.placenta.2018.10.004

Comparative transcriptomic analysis of human placentae at term and preterm delivery. Paquette, A.G., Brockway, H.M., Price, N.D., Muglia, L.J. 2018, Biol. Reprod.. https://doi.org/10.1093/biolre/iox163

Comparative analysis of gene expression in maternal peripheral blood and monocytes during spontaneous preterm labor. Paquette, A.G., Shynlova, O., Kibschull, M., Price, N.D., Lye, S.J. Am. J. Obstet. Gynecol, 2018. https://doi.org/10.1016/j.ajog.2017.12.234

MicroRNA-transcriptome networks in whole blood and monocytes of women undergoing preterm labor. Paquette AG, Shynlova O, Wu X, PhD, Kibschull M, Wang K, Price ND, Lye SJ . Journal of Cellular and Molecular Medicine DOI: https://doi.org/10.1111/jcmm.14567