Functional methylomics approaches for schizophrenia in the frontal cortex and hippocampus

项目总结/摘要 精神分裂症（SCZD）是一种严重的精神障碍，对公共卫生造成了重大负担， 尽管这种疾病具有高度遗传性，但人们对遗传因素的本质知之甚少。最近 精神病学基因组学联合现有的SCZD全基因组关联研究（GWAS）的努力 PGC协会的研究已经导致了最强有力的关于遗传与疾病相关的可信报告。 然而，相关变异增加SCZD风险的神经生物学机制是 未知在这里，我们将扩展从利伯大脑研究所产生的丰富的基因组数据 通过将基因组规模的DNA甲基化（DNAm）数据仔细地整合在同一个基因组上， 特征的主题有RNA测序（RNA-seq）和遗传数据，以更好地确定如何 SCZD的遗传风险表现在人类大脑中。我们将利用新的实验方法， 定量甲基胞嘧啶（5 mC）和羟甲基胞嘧啶（5 hmC）以解开总甲基化信号 目前在以前的较小的研究使用全基因组亚硫酸氢盐测序（WGBS）。 在本方案中，我们将对600个样本（300个供体）进行全基因组亚硫酸氢盐测序 跨2个脑区），并将所得DNAm水平与基因型、诊断和局部 表达水平，以更好地了解额叶皮层精神分裂症风险的表观遗传调节， 海马体。我们将进行甲基化。我们将首先进行甲基化数量性状基因座（meQTL） 分析PGC中确定的SCZD遗传风险变异，以及这些变异中的所有常见变异。 样本，分别为5 mC和5 hmC水平，以确定潜在的表观遗传机制的风险， 并假设通过分解总DNAm信号增加了统计功效。我们将鉴定基因组- 广泛的显着差异甲基化区域（DMR）比较精神分裂症患者与匹配 使用5 mC和5 hmC跨CpG和非CpG的脑区域内和跨脑区域的非精神病对照 网站.然后可以通过将这些区域内的DNA m水平与这些区域的DNA m水平相关联来询问这些区域的潜在功能。 通过RN-seq将DMR与匹配的表达数据进行比较。最后，我们将确定5 mC的功能相关性， 通过在整个甲基化组的相同样品上组合WGBS和RNA-seq的5 hmC DNAm水平 和转录组，在诊断组内和诊断组之间-通过进一步结合遗传数据，我们可以 识别由遗传变异与表观遗传变异驱动的DNAm表达相关性的子集。 近端细胞表型（如DNAm水平）可能最终显示出强而有意义的关联 与风险等位基因，可以进一步介导基因表达水平。在补助金中，我们的目的是阐明一些 精神分裂症的遗传风险和分子特征的分子生物学基础，从而帮助确定新的 疾病过程中的干预目标和潜在的治疗策略。

Project Summary/Abstract Schizophrenia (SCZD) is a severe mental disorder that imposes a significant burden on public health, and though the disorder is highly heritable, the nature of the genetic contribution is poorly understood. Recent efforts in combining existing genome-wide association studies (GWAS) of SCZD by the Psychiatric Genomics Consortium (PGC) have led to the strongest credible reports of genetic associations with the disorder. However, the neurobiological mechanisms by which the implicated variants increase the risk for SCZD are unknown. Here we will expand upon the rich genomic data generated from the Lieber Institute for Brain Development (LIBD) by incorporating genome-scale DNA methylation (DNAm) data on the same carefully characterized subjects that have RNA sequencing (RNA-seq) and genetic data to better determine how genetic risk for SCZD manifests in the human brain. We will utilize new experimental approaches that can quantify both methyl-cytosine (5mC) and hydroxymethyl-cytosine (5hmC) to untangle total methylation signal present in previous smaller studies using whole genome bisulfite sequencing (WGBS). In this proposal we will perform whole genome bisulfite sequencing on 600 samples (300 donors across 2 brain regions) and correlate the resulting DNAm levels with genotype, diagnosis, and local expression levels to better understand epigenetic regulation of schizophrenia risk in the frontal cortex and hippocampus. We will perform methylation. We will first perform methylation quantitative trait loci (meQTL) analysis with genetic risk variants for SCZD identified in the PGC, as well as all common variants in these samples, separately for 5mC and 5hmC levels to determine potential epigenetic mechanisms underlying risk, and hypothesize increased statistical power by decomposing total DNAm signal. We will then identify genome- wide significant differentially methylated regions (DMRs) comparing patients with schizophrenia to matched non-psychiatric controls within and across brain regions using 5mC and 5hmC across both CpG and non-CpG sites. These regions can then be interrogated for potential functionality by correlating DNAm levels within DMRs to the matched expression data via RN-seq. Lastly, we will identify functional correlates of 5mC and 5hmC DNAm levels by combining WGBS and RNA-seq on the same samples across the entire methylome and transcriptome, both within and across diagnostic groups - by further combining genetic data, we can identify the subset of DNAm-expression correlations driven by genetic versus epigenetic variation. Proximal cellular phenotypes like DNAm levels may ultimately show strong and meaningful association with risk alleles that can further mediate gene expression levels. In the grant, we aim to elucidate some of the molecular biology underlying genetic risk and molecular signatures of schizophrenia and thereby help identify novel targets for intervention in the disease process and potential treatment strategies.