Concerted neuron-astrocyte gene expression declines in aging and schizophrenia.
Emi LingJames NemeshMelissa GoldmanNolan KamitakiNora ReedRobert E HandsakerGiulio GenoveseJonathan S VogelgsangSherif GergesSeva KashinSulagna GhoshJohn M EspositoKiely FrenchDaniel MeyerAlyssa LutservitzChristopher D MullallyAlec WysokerLiv SpinaAnna NeumannMarina HoganKiku IchiharaSabina BerrettaSteven A McCarrollPublished in: bioRxiv : the preprint server for biology (2024)
Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron- and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.
Keyphrases
- prefrontal cortex
- bipolar disorder
- endothelial cells
- genome wide
- rna seq
- gene expression
- spinal cord
- single cell
- induced pluripotent stem cells
- dna methylation
- bioinformatics analysis
- induced apoptosis
- poor prognosis
- oxidative stress
- machine learning
- copy number
- genome wide analysis
- quality improvement
- deep learning
- binding protein
- transcription factor
- artificial intelligence
- signaling pathway
- blood brain barrier
- endoplasmic reticulum stress
- spinal cord injury
- brain injury