Journal
EXPERIMENTAL NEUROLOGY
Volume 335, Issue -, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.expneurol.2020.113523
Keywords
Congenital hydrocephalus; Telomeres; A plus T content mutation; Chromosome homologous recombination; familial Parkinson's disease; Alzheimer's disease
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Funding
- state of West Virginia
- WV-INBRE grant [NIH P20GM103434]
- COBRE ACCORD grant [P20GM121299]
- West Virginia Clinical and Translational Science Institute (WV-CTSI) [2U54GM104942]
- Office of the President at Marshall University
- West Virginia Space Grant Consortium (WVSGC) - NASA
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The study found that 98 of 108 genes causing congenital hydrocephalus (CH) matched with telomere proximity or high A+T content, resulting in a matching rate of over 90%. This disease-specific matching of CH genes outperformed neurodegenerative diseases and other CNS conditions, likely due to a sufficient number of known causative genes and precise determination and classification of genotype and phenotype.
Congenital hydrocephalus (CH) is caused by genetic mutations, but whether factors impacting human genetic mutations are disease-specific remains elusive. Given two factors associated with high mutation rates, we reviewed how many disease-susceptible genes match with (i) proximity to telomeres or (ii) high adenine and thymine (A + T) content in human CH as compared to other disorders of the central nervous system (CNS). We extracted genomic information using a genome data viewer. Importantly, 98 of 108 genes causing CH satisfied (i) or (ii), resulting in >90% matching rate. However, such a high accordance no longer sustained as we checked two factors in Alzheimer's disease (AD) and/or familial Parkinson's disease (fPD), resulting in 84% and 59% matching, respectively. A disease-specific matching of telomere proximity or high A + T content predicts causative genes of CH much better than neurodegenerative diseases and other CNS conditions, likely due to sufficient number of known causative genes (n = 108) and precise determination and classification of the genotype and phenotype. Our analysis suggests a need for identifying genetic basis of both factors before human clinical studies, to prioritize putative genes found in preclinical models into the likely (meeting at least one) and more likely candidate (meeting both), which predisposes human genes to mutations.
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