Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases.
McKinzie A GarrisonYeongjun JangTaejeong BaeAdriana CherskovSarah B EmeryLiana FaschingAttila JonesJohn B MoldovanCindy MolitorSirisha PochareddyMette A PetersJoo-Heon ShinYifan WangXiaoxu YangSchahram AkbarianAndrew ChessFred H GageJoseph G GleesonJeffrey M KiddMichael J McConnellRyan E MillsJohn V MoranPeter J ParkNenad SestanAlexander Eckehart UrbanFlora M VaccarinoChristopher A WalshDaniel R WeinbergerSarah J WheelanAlexej Abyzovnull nullPublished in: Scientific data (2023)
Somatic mosaicism is defined as an occurrence of two or more populations of cells having genomic sequences differing at given loci in an individual who is derived from a single zygote. It is a characteristic of multicellular organisms that plays a crucial role in normal development and disease. To study the nature and extent of somatic mosaicism in autism spectrum disorder, bipolar disorder, focal cortical dysplasia, schizophrenia, and Tourette syndrome, a multi-institutional consortium called the Brain Somatic Mosaicism Network (BSMN) was formed through the National Institute of Mental Health (NIMH). In addition to genomic data of affected and neurotypical brains, the BSMN also developed and validated a best practices somatic single nucleotide variant calling workflow through the analysis of reference brain tissue. These resources, which include >400 terabytes of data from 1087 subjects, are now available to the research community via the NIMH Data Archive (NDA) and are described here.
Keyphrases
- copy number
- bipolar disorder
- electronic health record
- mental health
- autism spectrum disorder
- big data
- white matter
- healthcare
- resting state
- genome wide
- primary care
- major depressive disorder
- risk assessment
- induced apoptosis
- dna methylation
- functional connectivity
- cerebral ischemia
- data analysis
- gene expression
- multiple sclerosis
- intellectual disability
- cell death
- machine learning
- oxidative stress
- signaling pathway
- network analysis
- subarachnoid hemorrhage