The Role of GPR161 in the Etiology of Neural Tube Defects

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ABSTRACT Neural tube defects (NTDs) are the second most common human structural birth defect. They result from the failure of neural tube closure (NTC) during neurulation. There are multiple developmentally-related signaling pathways involved as NTC processes spatially and temporally. The causes of NTDs are known to be multi- factorial, including genetic and environmental factors. Given that the genetic factors contribute significantly to the etiology of NTDs, the identification of specific gene variants and the characterization of their underlying molecular and cellular mechanisms leading to the etiology of NTDs has progressed slowly over the last several decades. We have identified novel rare variants of GPR161 using whole genome sequencing (WGS) from large human cohorts. GPR161 is a known negative regulator of the Shh signaling pathway, and Shh null mice express NTD phenotypes. The GPR161vl and null mice models suggest the involvement of other signaling pathways. The Shh, Wnt and PCP signaling pathways are involved in the neural tube patterning, neural stem cell proliferation, and neural crest cell migration via cell polarization during NTC. We will test the following specific hypothesis with in vitro and in vivo models. (1) GPR161 can regulate Wnt and PCP signaling pathways, and the novel rare gene variants of GPR161 adversely impact these signaling pathways, which dysregulate NTC. (2) GPR161 can impact cell proliferation and cell polarity via Wnt and PCP signaling, respectively, thus the NTD variants of GPR161 will increase NTD susceptibility by compromising these processes. (3) The identified human GPR161 NTD variants, alone or in combination with other PCP genes, will produce NTD phenotypes in knock in (KI) mouse models. The proposed research program will provide the novel molecular, cellular, developmental and genetic links between GPR161, Wnt and PCP signaling pathways, as they relate to morphogenetic processes involved in normal NTC. Filling this large datagap can lead us to novel therapeutic strategies for both intervention and treatment.