A concerted neuron-astrocyte program declines in ageing and schizophrenia.
Emi LingJames NemeshMelissa GoldmanNolan KamitakiNora ReedRobert E HandsakerGiulio GenoveseJonathan S VogelgsangSherif GergesSeva KashinSulagna Dia GhoshJohn M EspositoKiely MorrisDaniel MeyerAlyssa LutservitzChristopher D MullallyAlec WysokerLiv SpinaAnna NeumannMarina HoganKiku IchiharaSabina BerrettaSteven A McCarrollPublished in: Nature (2024)
Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding 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 ageing-two conditions that involve declines in cognitive flexibility and plasticity 1,2 -cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed 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 people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.
Keyphrases
- prefrontal cortex
- bipolar disorder
- endothelial cells
- genome wide
- spinal cord
- induced pluripotent stem cells
- pluripotent stem cells
- bioinformatics analysis
- single cell
- quality improvement
- genome wide analysis
- machine learning
- transcription factor
- copy number
- long non coding rna
- endoplasmic reticulum stress
- cerebral ischemia