Understanding Genetic Complexity in Spina Bifida

NIH Pandemic-Era Grants

Pandemic Era Grants

2024

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Principal Investigator: RICHARD H. FINNELL
Organization: WEILL MEDICAL COLL OF CORNELL UNIV
Fiscal Year: 2024
Award: $695,911
Funding agency: Eunice Kennedy Shriver National Institute of Child Health and Human Development

ABSTRACT: UNDERSTANDING GENETIC COMPLEXITY IN SPINA BIFIDA
 Among neural tube defects (NTDs), myelomeningocele (spina bifida:SB), is a devastating but survivable,
human structural malformation. Up to 70% of SB cases are attributed to genetic predisposition, with intrauterine
environment precipitating SB manifestation in those at risk. Despite decades of research into genetic factors that
underlie NTDs in mouse models, translation to human risk assessment and amelioration of SB cases remain
elusive. This is largely attributable to limitations of the typical candidate gene approaches used in genetic studies
of human NTDs. Here, our comprehensive systems biology approach to mutation burden in whole genome
sequence (WGS) analyses is illuminating molecular pathways to human SB through interrogation of protein
coding and non-coding regions, and introduces machine learning to select, in an untargeted fashion, genes with
SB discriminatory potential based on gene enrichment by rare, likely deleterious protein coding variants.
 The project extends our comprehensive genomic effort, generating new WGS on 200 recently collected
patient-parent trio (600 genomes) samples. Studies aim to identify specific gene drivers of human SB, illuminate
gene-gene interactions leading to SB, and improve mechanistic understanding of this complex birth defect.
 Aim 1 uses family study and systems biology approaches to seek genes with transmitted or de novo rare
variants suggesting SB-association. This begins assessment of parental vs de novo, “second hit”, contributions
to SB. Analyses include protein-coding and noncoding sequence single nucleotide variants (SNVs), rare copy
number variants (rCNVs), and state-of-the art computational probes leveraging genome 3D structure.
 Aim 2 tests the functional significance and interactions of these detected genes and variations to: (a) use
CRISPR edited isogenic, double heterozygous human stem cells in a novel SOSRS, 3-D in vitro method to
evaluate proliferation, self-organization, and differentiation, (b) test the transcriptional impact of these mutations
using bulk and single cell RNAseq in mutagenized cells.
 Aim 3 examines double/multiple-heterozygous protein coding mutations using existing and CRISPR-
edited mice to test the histological and gene expression impact of gene interactions on NT closure.
 Our computational approaches are highly innovative in the field, using machine learning to build network
models of human SB risk. We then apply advanced technology for the functional testing of these genetic risk
models, including gene editing of human stem cells, compared to isogenic controls, and mice for cellular and
systems based hypothesis testing in vitro and in vivo, along with evaluation of the cell-type gene expression
changes induced by these variants. Insights from our studies will pave the way for a precision medicine capability
to individualize NTD prevention and care for families and the hundreds of thousands of patients living with SB.

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biology><Child><Child Youth><Children (0-21)><Clustered Regularly Interspaced Short Palindromic Repeats><Clustered Regularly Interspaced Short Palindromic Repeats approach><Clustered Regularly Interspaced Short Palindromic Repeats method><Clustered Regularly Interspaced Short Palindromic Repeats methodology><Clustered Regularly Interspaced Short Palindromic Repeats technique><Clustered Regularly Interspaced Short Palindromic Repeats technology><Code><Coding System><Collaborations><Combining Site><Complex><Computational Biology><Computational toolkit><Computing Methodologies><Congenital Abnormality><Congenital Anatomical Abnormality><Congenital Defects><Congenital Deformity><Congenital Malformation><Copy Number Polymorphism><Couples><DNA seq><DNA sequencing><DNAseq><Data><Disease><Disorder><Embryo><Embryonic><Encephalon><Enhancers><Environmental Factor><Environmental Risk Factor><Epistasis><Epistatic Deviation><Equilibrium><Etiology><Evaluation><Event><Exons><Failure><Family><Family Study><Folate><Folic Acid><Food Supply><Fortification><Frequencies><Functional RNA><Gene Combinations><Gene Expression><Gene Transcription><Gene variant><General Transcription Factor Gene><General Transcription Factors><Genes><Genetic><Genetic Alteration><Genetic Change><Genetic Diversity><Genetic Epistasis><Genetic Predisposition><Genetic Predisposition to Disease><Genetic Risk><Genetic Susceptibility><Genetic Transcription><Genetic Variation><Genetic defect><Genetic propensity><Genetic study><Genome><Genomic Segment><Genomic approach><Genomics><Genotoxins><Gestation><Goals><Hand><Hereditary><Heterozygote><Histologic><Histologically><Human><Human Genome><Impairment><In Vitro><Individual><Inherited><Inherited Predisposition><Inherited Susceptibility><Innate Immunity><Interaction Deviation><MAX gene><MYC-Associated Factor X><MYC-Associated Factor X Gene><Machine Learning><Maps><Max protein><Meningomyelocele><Meningomyelocoele><Methods><Mice><Mice Mammals><Modeling><Modern 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