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.

Public Health Relevance

To identify etiological and pathological changes in bipolar disorder and schizophrenia brains, as part of the previously funded PsychENCODE project, we have already or are currently genotyping and profiling the transcriptomes and chromatin states of 330 frontal cortex samples from the brains of healthy controls subjects and of patients with bipolar disorder and schizophrenia. The next step towards identifying the molecular bases of these diseases is to characterize any changes in protein production or function in cases relative to controls. Since proteins are produced from mRNA transcripts, it seems logical that transcript levels could be used to roughly predict protein levels. However, data show that there can be significant differences between transcript abundances and protein abundances, suggesting that there are intermediate mechanisms that regulate protein production. In this study, we will experimentally identify transcripts that actively encode protein or peptides with experimentally-defined open reading frames and calculate their translation efficiency. We will measure the abundance of more than 12,000 proteins in these brains using protein mass spectrometry. Case-control comparisons will identify changes in protein expression levels and associated regulatory systems that are related to disease risks.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Special Emphasis Panel (ZMH1)
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Arguello, Alexander
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Upstate Medical University
Schools of Medicine
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An, Joon-Yong; Lin, Kevin; Zhu, Lingxue et al. (2018) Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science 362:
Gandal, Michael J; Zhang, Pan; Hadjimichael, Evi et al. (2018) Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362:
Kozlenkov, Alexey; Li, Junhao; Apontes, Pasha et al. (2018) A unique role for DNA (hydroxy)methylation in epigenetic regulation of human inhibitory neurons. Sci Adv 4:eaau6190
Gandal, Michael J; Haney, Jillian R; Parikshak, Neelroop N et al. (2018) Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science 359:693-697
Zhu, Ying; Sousa, André M M; Gao, Tianliuyun et al. (2018) Spatiotemporal transcriptomic divergence across human and macaque brain development. Science 362:
Amiri, Anahita; Coppola, Gianfilippo; Scuderi, Soraya et al. (2018) Transcriptome and epigenome landscape of human cortical development modeled in organoids. Science 362:
Rhie, Suhn K; Schreiner, Shannon; Witt, Heather et al. (2018) Using 3D epigenomic maps of primary olfactory neuronal cells from living individuals to understand gene regulation. Sci Adv 4:eaav8550
Wang, Daifeng; Liu, Shuang; Warrell, Jonathan et al. (2018) Comprehensive functional genomic resource and integrative model for the human brain. Science 362:
Horwitz, Tanya; Lam, Katie; Chen, Yu et al. (2018) A decade in psychiatric GWAS research. Mol Psychiatry :
Li, Mingfeng; Santpere, Gabriel; Imamura Kawasawa, Yuka et al. (2018) Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science 362:

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