Project Summary: Most genetic variants associated with disease in genome-wide association studies (GWAS) lie in non-coding gene regulatory elements (GRE; e.g., promoters and enhancers). GREs are tissue- and cell type-specific and are identified through their epigenomic signatures, including low DNA methylation (DNAm), DNA accessibility and certain histone modifications. The PsychENCODE Consortium has characterized brain GREs across brain regions and developmental time points, as well as in the brains of psychiatric patients using mostly DNA accessibility and histone modification marks. These marks, however, identify large regions of enrichment (~300-2,000bp), providing only low resolution coverage of the important regulatory nucleotides, e.g., transcription factor binding sites. DNAm (especially cell type-specific DNAm) has received less attention, although it has been linked to psychiatric disorders, including schizophrenia (SZ) and bipolar disorder (BD). In the adult human brain, ~80% of CG and 1.5% of non-CG (CH) sites are methylated, and can be converted to hydroxymethylcytosine (hmC) and further demethylated. In postmitotic neuronal genomes, mCH and hmC accumulate to a significantly higher level than in other tissues--a distinct feature of the brain’s epigenome. Bisulfite sequencing (BS)-based approaches that are used to measure (h)mC can pinpoint GREs with single base resolution, presenting a unique opportunity to refine the gene regulatory landscape of the brain cell types. Here we aim to create reference DNAm maps [mC and hmC, using BS and oxidative (ox)BS sequencing] and transcriptional profiles (using RNA-seq) in two major subtypes of neurons in the human dorsolateral prefrontal cortex (DLPFC), namely excitatory glutamatergic (Glu) and inhibitory GABA-ergic neurons. The proposed work is based on fluorescence-activated nuclear sorting (FANS) methods that we recently developed to separate nuclei of different cell types from autopsied human brain, and on our recent findings that showed unexpected relationships between DNA(h)m, GREs, and gene expression in the DLPFC Glu and GABA neurons. We will perform these studies at key time points of postnatal brain development and adulthood to map DNA(h)m within active neuron subtype-specific GREs that may be vulnerable to disruption during childhood and adolescence periods that coincide with the critical processes of brain maturation and circuit refinement (Aim 1). This work will be complemented with single nucleus mC profiling, which will allow us to define the developmental trajectories of mC in discrete subpopulations of Glu and GABA neurons (Aim2). Finally, we will profile Glu and GABA neurons in 150 autopsied DLPFC samples obtained from controls and cases of SZ and BD, and will then map neuron subtype-specific gene expression and (hydroxy)methylation quantitative trait loci (eQTL, mQTLS, hmQTLs) (Aim3). We will integrate QTL, transcriptome, and DNA(h)m data with the results of SZ and BP GWAS to reveal DNA(h)m and gene expression-mediated causal risk variants and genes, and to distinguish specific neuronal subtype(s) that are critical in the etiology of these disorders.

The single-base-pair resolution maps of DNA (hydroxy)methylation will be generated in sorted inhibitory and excitatory neurons at key time points of postnatal brain development and adulthood, as well as in the brains of psychiatrically normal individuals and patients with schizophrenia and bipolar disorder. The data will be integrated with genetic findings for these disorders as well as with other omics data that have been generated by the PsychEncode Consortium. We anticipate that this work will reveal the molecular and cellular mechanisms and causal relationships of genetic associations, and will suggest specific subtypes of neurons that contribute to disease risk.