Human brain development remains an incompletely understood process, yet congenital abnormalities of this complex structure affect approximately 3/1,000 pregnancies and more than 2000 newborns annually in the United States, posing a substantial burden on the health care system. Congenital brain abnormalities, hallmarked by vast phenotypic heterogeneity, include but are not limited to holoprosencephaly, schizencephaly, anencephaly, encephalocele, microcephaly, ventriculomegaly, cerebellar hypoplasia, and disorders of cortical development, such as lissencephaly. The paired approach of: (1) prenatal diagnosis using a combination of ultrasound and fetal MRI to characterize aberrant phenotypes; with (2) genetic analysis to determine causal lesions, has greatly improved the ability to accurately counsel families about diagnosis, prognosis, and recurrence risk. More recently, prenatal whole exome sequencing (WES) has been applied in cases of lethal or multiple fetal abnormalities to make a molecular diagnosis that otherwise could not be identified with traditional testing. Pilot data from our group and others using WES show a diagnostic rate of 16- 30% in cases of multiple fetal abnormalities, but only 1-2% in isolated brain abnormalities, indicating a critical need to improve diagnostic capabilities and identify novel genes critical to human brain development. We posit that the overabundance of unresolved fetal cases is in large part due to: (1) a knowledge gap in our understanding of the repertoire of genotypes underlying brain abnormalities with prenatal onset; and (2) limitations of population genetics to establish causality of rare variants in novel candidate genes. Here, two CTSA-funded teams who are at the forefronts of prenatal genetic diagnostics and in vivo zebrafish modeling of human disease, at UNC and Duke, respectively, will team up to overcome the current challenges of diagnosing brain abnormalities with a prenatal onset. We will intersect exome- and genome-wide variation data with experimentally tractable and relevant model systems, zebrafish (Danio rerio). We hypothesize that bioinformatics filters using prenatal WES data will reveal novel candidate genes, which can be applied to a zebrafish model to generate initial discoveries critical to human brain development and translate into improved clinical care. First, we will perform bioinformatic analysis of 10 clinically ascertained fetuses with CNS anomalies and their parents using a tiered filtering strategy; and we will apply this analysis paradigm iteratively to 32 prospectively enrolled fetuses and their families. Second, we will establish relevance of candidate genes to brain development and determine variant pathogenicity using state-of-the-art genome editing and phenotyping tools in zebrafish. Completion of our work will expand our understanding of the molecular processes governing prenatal brain development; establish a clinical-research hybrid platform readily applicable to other anatomical organ defects detectable by fetal imaging; and build a suite of animal models of aberrant CNS development with potential for future use in therapeutic target identification.
Diagnostic tools, such as fetal MRI, prenatal ultrasound, and prenatal gene sequencing, have the capability to increase our understanding of the human brain. Intersecting human prenatal gene sequencing in pregnancies affected with congenital brain abnormalities, bioinformatics filters to identify novel candidate genes, and functional modeling in zebrafish, we aim to develop a workflow that can be adapted broadly across organ systems for investigation of novel candidate genes. Our findings will shed light on the molecular underpinnings of human brain development and has the potential to lead to novel preventive and therapeutic strategies that can be applied in the perinatal period.
