2/2-Measuring translational dynamics and the proteome to identify potential brain biomarkers for psychiatric disease

摘要 为了进一步确定双相情感障碍和精神分裂症的分子基础，我们建议研究 300例患者额叶皮质组织全基因组水平的蛋白质翻译和丰度 和健康的对照组。我们已经从这些大脑中积累了大量数据，包括 基因分型、转录组图谱和染色质状态。下一步是寻找蛋白质功能的变化 同样的大脑，因为蛋白质是基因表达的最终产物，也是基因之间的关键纽带 变异和更高级别的表型，包括疾病诊断。由于蛋白质由信使核糖核酸编码 在转录水平上，蛋白质水平似乎与转录水平大致相关。然而，经过衡量， MRNAs及其相应蛋白质的表达水平通常是不一致的，它们各自的图谱也是如此 数量性状基因座。由于我们无法解释这些差异，我们的分子变化图景 潜在的精神障碍显然是不完整的。 以前对神经精神病学中的蛋白质的大多数基于群体的研究仅限于候选蛋白质，例如 已经有哪些抗体可用。例如，在我们的MedicENCODE项目中，我们正在使用 用于分析约1000个蛋白质的微蛋白质阵列。在这项研究中，我们将使用最近开发的技术 核糖体图谱和下一代蛋白质组学以确定哪些转录本正在大脑中活跃地翻译 并对超过12,000种蛋白质的丰度进行量化。通过综合数据分析，我们使用了两种方法 用于检测翻译产品并衡量其数量关系的补充技术。 此外，这些蛋白质及其翻译效率将被评估是否与疾病有关。至 进一步提高量化的特异性，我们将使用最先进的去卷积方法来量化细胞 键入翻译效率和蛋白质产品的具体衡量标准。这将允许蛋白质翻译和 在特定的主要脑细胞类型中的丰度有待研究它们在受影响大脑中的变化。 这项研究具有创新性，因为它是第一个全基因组、基于人群的蛋白质翻译和 精神病人大脑中的丰富物质。它提供了一个独特的机会来填补转录组和 蛋白质组数据，以及遗传变异和高阶表型之间的差异。这将是一个巨大的进步 研究人类大脑的蛋白质和与精神障碍相关的调节变化，这是 应该最终导致对这些疾病的更好的诊断和治疗。

Abstract To further our efforts in identifying the molecular bases of bipolar disorder and schizophrenia, we propose to study protein translation and abundances at the genome-wide level in frontal cortex tissue from 300 brains from patients and healthy controls. We have already amassed an enormous amount of data from these brains, including genotypes, transcriptome profiles and chromatin states. The next step is to look for alterations in protein function in the same brains, since proteins are the ultimate products of gene expression and a critical link between genetic variants and higher order phenotypes, including disease diagnosis. Since proteins are encoded by mRNA transcripts, it appears that protein levels should roughly correlate with transcript levels. However, measured expression levels of mRNAs and their corresponding proteins are often discordant, as are maps of their respective quantitative trait loci. Since we are unable to explain these discrepancies, our picture of molecular changes underlying psychiatric disorders is clearly incomplete. Most previous population-based studies of proteins in neuropsychiatry have been limited to candidate proteins, for which antibodies are already available. For example, in our PsychENCODE project, we are the process of using microwestern arrays to assay ~1000 proteins. In this study, we will use the recently developed technique of ribosome profiling and next-generation proteomics to identify which transcripts are actively being translated in brain and to quantify the abundance of more than 12,000 proteins. Through integrative data analysis, we use the two complementary technologies to detect translational products and to measure their quantitative relationships. Furthermore, these proteins and their translation efficiencies will be assessed for association with disorders. To further improve the specificity of quantification, we will use state-of-the-art deconvolution methods to quantify cell type specific measures of translation efficiency and protein products. This will allow protein translation and abundance in specific major brain cell types to be studied for their changes in affected brains. This study is innovative for being the first genome-wide, population-based study of protein translation and abundance in brains of psychiatric patients. It offers a unique opportunity to fill the gaps between transcriptome and proteome data, and between genetic variants and higher-order phenotypes. It will be a huge step forward in studying the proteins of human brains and the regulatory changes associated with psychiatric disorders, which should ultimately lead to better diagnosis and treatment of these diseases.