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Complimentary vertebrate Wac models exhibit phenotypes relevant to DeSanto-Shinawi Syndrome.

Kang-Han LeeApril M StaffordMaria Pacheco-VergaraKarol CichewiczCesar P CanalesNicolas SebanMelissa CoreaDarlene RahbarianKelly E BonekampGrant R GillieDariangelly Pacheco CruzAlyssa M GillHye-Eun HwangKatie L UhlTara E JagerMarwan ShinawiXiaopeng LiAndre ObenausShane R CrandallJuhee JeongAlexander S NordCheol-Hee KimDaniel L Vogt
Published in: bioRxiv : the preprint server for biology (2024)
Monogenic syndromes are associated with neurodevelopmental changes that result in cognitive impairments, neurobehavioral phenotypes including autism and attention deficit hyperactivity disorder (ADHD), and seizures. Limited studies and resources are available to make meaningful headway into the underlying molecular mechanisms that result in these symptoms. One such example is DeSanto-Shinawi Syndrome (DESSH), a rare disorder caused by pathogenic variants in the WAC gene. Individuals with DESSH syndrome exhibit a recognizable craniofacial gestalt, developmental delay/intellectual disability, neurobehavioral symptoms that include autism, ADHD, behavioral difficulties and seizures. However, no thorough studies from a vertebrate model exist to understand how these changes occur. To overcome this, we developed both murine and zebrafish Wac/wac deletion mutants and studied whether their phenotypes recapitulate those described in individuals with DESSH syndrome. We show that the two Wac models exhibit craniofacial and behavioral changes, reminiscent of abnormalities found in DESSH syndrome. In addition, each model revealed impacts to GABAergic neurons and further studies showed that the mouse mutants are susceptible to seizures, changes in brain volumes that are different between sexes and relevant behaviors. Finally, we uncovered transcriptional impacts of Wac loss of function that will pave the way for future molecular studies into DESSH. These studies begin to uncover some biological underpinnings of DESSH syndrome and elucidate the biology of Wac , with advantages in each model.
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