Multiomic analyses implicate a neurodevelopmental program in the pathogenesis of cerebral arachnoid cysts.
Adam J KundishoraGarrett AllingtonStephen McGeeKedous Y MekbibVladimir GainullinAndrew T TimberlakeCarol Nelson-WilliamsEmre KiziltugHannah SmithJack OckenJohn ShohfiAugust AlloccoPhan Q DuyAladine A ElsamadicyWeilai DongShujuan ZhaoYung-Chun WangHanya M QureshiMichael L DiLunaShrikant ManeIrina R TikhonovaPo-Ying FuChristopher CastaldiFrancesc LopezJames R KnightCharuta G FureyBob S CarterShozeb M HaiderAndrés Moreno De LucaSeth L AlperMurat GünelFrancisca MillanRichard P LiftonRebecca I ToreneSheng Chih JinKristopher T KahlePublished in: Nature medicine (2023)
Cerebral arachnoid cysts (ACs) are one of the most common and poorly understood types of developmental brain lesion. To begin to elucidate AC pathogenesis, we performed an integrated analysis of 617 patient-parent (trio) exomes, 152,898 human brain and mouse meningeal single-cell RNA sequencing transcriptomes and natural language processing data of patient medical records. We found that damaging de novo variants (DNVs) were highly enriched in patients with ACs compared with healthy individuals (P = 1.57 × 10 -33 ). Seven genes harbored an exome-wide significant DNV burden. AC-associated genes were enriched for chromatin modifiers and converged in midgestational transcription networks essential for neural and meningeal development. Unsupervised clustering of patient phenotypes identified four AC subtypes and clinical severity correlated with the presence of a damaging DNV. These data provide insights into the coordinated regulation of brain and meningeal development and implicate epigenomic dysregulation due to DNVs in AC pathogenesis. Our results provide a preliminary indication that, in the appropriate clinical context, ACs may be considered radiographic harbingers of neurodevelopmental pathology warranting genetic testing and neurobehavioral follow-up. These data highlight the utility of a systems-level, multiomics approach to elucidate sporadic structural brain disease.
Keyphrases
- single cell
- acute coronary syndrome
- case report
- rna seq
- electronic health record
- cerebral ischemia
- resting state
- genome wide
- white matter
- subarachnoid hemorrhage
- big data
- transcription factor
- gene expression
- copy number
- high throughput
- machine learning
- healthcare
- functional connectivity
- dna damage
- autism spectrum disorder
- risk factors
- data analysis
- quality improvement
- late onset
- brain injury
- bioinformatics analysis
- congenital heart disease
- artificial intelligence
- cerebral blood flow
- genome wide analysis