Schizophrenia is a severe neuropsychiatric disorder with a longstanding history of neurobiological investigation. Although the underlying causal mechanisms remain unknown, early neurodevelopmental events have been implicated in pathogenesis, initially by epidemiological and circumstantial data but more recently by brain-specific molecular and genetic findings. Notably, genomic research has recently uncovered discrete risk variants and risk loci associated with schizophrenia, with the potential to elucidate disease mechanisms. This Review revisits the neurodevelopmental model of schizophrenia from a current genetics perspective, delineating the complex genetic basis of the disorder and highlighting gene expression and epigenetic analyses of post-mortem cortical tissue that suggest that early brain development mediates genetic risk associated with schizophrenia. Future functional genomics investigations will accordingly need to characterize schizophrenia risk loci in relevant neurodevelopmental models.

Objective Neurodevelopmental disorders presumably involve events that occur during brain development. We hypothesized that neuropsychiatric disorders considered to be developmental in etiology are associated with susceptibility genes that are relatively upregulated during fetal life (i.e. differentially expressed). Method We investigated the presence of prenatal expression enrichment of susceptibility genes systematically, as composite gene sets associated with 6 neuropsychiatric disorders in the microarray-based “BrainCloud” dorsolateral prefrontal cortex (DLPFC) transcriptome. Results Using a fetal/post-natal log2 fold change threshold of 0.5, genes associated with syndromic neurodevelopmental disorders (n = 31 genes, p = 3.37×10−3), intellectual disability (n = 88 genes, p = 5.53×10−3), and autism spectrum disorder (n = 242 genes, p = 3.45×10−4) were relatively enriched in prenatal transcript abundance, compared to the overall transcriptome. Genes associated with schizophrenia by GWAS were not preferentially fetal expressed (n = 106 genes, p = 0.46), nor were genes associated with schizophrenia by exome sequencing (n = 212 genes, p = .21), but specific genes within CNV regions associated with schizophrenia were relatively enriched in prenatal transcript abundance, and genes associated with schizophrenia by meta-analysis were functionally enriched for some neurodevelopmental processes. In contrast, genes associated with neurodegenerative disorders were significantly underexpressed during fetal life (n = 46 genes, p = 1.67×10−3). Conclusions We found evidence for relative prenatal enrichment of putative susceptibility genes for syndromic neurodevelopmental disorders, intellectual disability, and autism spectrum disorders. Future transcriptome-level association studies should evaluate regions other than the DLPFC, at other time points, and incorporate further RNA sequencing analyses.

Background: Midbrain dopaminergic neurons (MDN) represent 0.0005% of the brain's neuronal population and mediate cognition, food intake, and metabolism. MDN are also posited to underlay the neurobiological dysfunction of schizophrenia (SCZ), a severe neuropsychiatric disorder that is characterized by psychosis as well as multifactorial medical co-morbidities, including metabolic disease, contributing to markedly increased morbidity and mortality. Paradoxically, however, the genetic risk sequences of psychosis and traits associated with metabolic disease, such as body mass, show very limited overlap. Methods: We investigated the genomic interaction of SCZ with medical conditions and traits, including body mass index (BMI), by exploring the MDN's "spatial genome," including chromosomal contact landscapes as a critical layer of cell type-specific epigenomic regulation. Low-input Hi-C protocols were applied to 5-10 × 10 3 dopaminergic and other cell-specific nuclei collected by fluorescence-activated nuclei sorting from the adult human midbrain. Results: The Hi-C-reconstructed MDN spatial genome revealed 11 "Euclidean hot spots" of clustered chromatin domains harboring risk sequences for SCZ and elevated BMI. Inter-and intra-chromosomal contacts interconnecting SCZ and BMI risk sequences showed massive enrichment for brain-specific expression quantitative trait loci (eQTL), with gene ontologies, regulatory motifs and proteomic interactions related to adipogenesis and lipid regulation, dopaminergic neurogenesis and neuronal connectivity, and reward-and addiction-related pathways. Conclusions: We uncovered shared nuclear topographies of cognitive and metabolic risk variants. More broadly, our PsychENCODE sponsored Hi-C study offers a novel genomic approach for the study of psychiatric and medical co-morbidities constrained by limited overlap of their respective genetic risk architectures on the linear genome.

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