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COMPUTATIONAL INVESTIGATION OF BIOLOGICAL NETWORKS AND PROGESTERONE SIGNALING DYNAMICS IN PRETERM BIRTH

Brubaker, Douglas K
http://orcid.org/0000-0001-5083-0334
http://rave.ohiolink.edu/etdc/view?acc_num=case1457963814

Abstract Details

2016, Doctor of Philosophy, Case Western Reserve University, Systems Biology and Bioinformatics.
Preterm birth (PTB) is a major public health issue that is the leading cause of infant mortality worldwide. To identify dysregulation and therapeutic opportunities in PTB a better understanding of healthy term labor is required. Further understanding of how the interaction of progesterone signaling with inflammatory pathways maintains quiescence is essential to assessing the therapeutic potential of progesterone for PTB. It has also been observed that PTB has a strong heritability from mother to daughter. This has motivated several genome wide association studies (GWAS) to try to identify single nucleotide polymorphisms (SNP) with genome wide significance that predispose a woman to PTB. To date, no SNPs have been identified and replicated with genome wide significance raising concerns about the effectiveness of GWAS in identifying the genetic predisposition of PTB. The myometrium, uterine smooth muscle tissue, undergoes a dramatic phenotypic transition from quiescent to forcefully contracting to deliver the conceptus. Understanding the biological signaling networks driving this transition, how genetic factors may modulate it, and the role of progesterone signaling in labor are essential factors to addressing the challenge of PTB. This dissertation addresses each of these issues to better characterize PTB. A meta-analysis approach is used to characterize the signaling events governing the quiescent to laboring transition of the myometrium. We show that while inflammatory pathways are crucial to term labor and inflammation indicated PTB, spontaneous PTB has a unique set of signaling pathways governing the myometrium’s transition. By organizing insignificant PTB-GWAS SNPs in a protein-protein interaction (PPI) network context, groups of modest effect SNPs were tested for combined effects on modules of a PPI network. Module function was assessed with term and preterm labor myometrium transcriptome data to identify modules dysregulated with labor onset. A module characterized by myocyte enhancer factor -2C (MEF2C) and 9 PTB-SNPs was implicated in term labor. Finally, we modeled progesterone signaling with inflammation using a dynamical systems model and used the model to precisely predict laboring phenotypes. Progesterone signaling dynamics are well characterized by this competitive interaction model, but the lack of inflammatory pathways in spontaneous PTB suggest limited effectiveness of progesterone modulation as a PTB therapy in that context. This dissertation illustrates how understanding a complex disorder like PTB requires a systems level approach. Such an approach is only possible when high dimensional data is carefully modeled, assessed, and the dimensionality reduced using appropriate and diverse computational approaches.
Mark Chance (Advisor)
Jill Barnholtz-Sloan (Committee Chair)
Sam Mesiano (Committee Member)
Alethea Barbaro (Committee Member)
98 p.
Bioinformatics

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Citations

  • Brubaker, D. K. (2016). COMPUTATIONAL INVESTIGATION OF BIOLOGICAL NETWORKS AND PROGESTERONE SIGNALING DYNAMICS IN PRETERM BIRTH [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1457963814

    APA Style (7th edition)

  • Brubaker, Douglas. COMPUTATIONAL INVESTIGATION OF BIOLOGICAL NETWORKS AND PROGESTERONE SIGNALING DYNAMICS IN PRETERM BIRTH. 2016. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1457963814.

    MLA Style (8th edition)

  • Brubaker, Douglas. "COMPUTATIONAL INVESTIGATION OF BIOLOGICAL NETWORKS AND PROGESTERONE SIGNALING DYNAMICS IN PRETERM BIRTH." Doctoral dissertation, Case Western Reserve University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1457963814

    Chicago Manual of Style (17th edition)

case1457963814
213
© 2016, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.