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Review
. 2019 Jul:102:195-207.
doi: 10.1016/j.neubiorev.2019.04.015. Epub 2019 Apr 24.

Postmortem brain tissue as an underutilized resource to study the molecular pathology of neuropsychiatric disorders across different ethnic populations

Eric Vornholt  1 , Dan Luo  2 , Wenying Qiu  3 , Gowon O McMichael  4 , Yangyang Liu  5 , Nathan Gillespie  6 , Chao Ma  7 , Vladimir I Vladimirov  8
Affiliations
Review

Postmortem brain tissue as an underutilized resource to study the molecular pathology of neuropsychiatric disorders across different ethnic populations

Eric Vornholt et al. Neurosci Biobehav Rev. 2019 Jul.

Abstract

In recent years, large scale meta-analysis of genome-wide association studies (GWAS) have reliably identified genetic polymorphisms associated with neuropsychiatric disorders such as schizophrenia (SCZ), bipolar disorder (BPD) and major depressive disorder (MDD). However, the majority of disease-associated single nucleotide polymorphisms (SNPs) appear within functionally ambiguous non-coding genomic regions. Recently, increased emphasis has been placed on identifying the functional relevance of disease-associated variants via correlating risk polymorphisms with gene expression levels in etiologically relevant tissues. For neuropsychiatric disorders, the etiologically relevant tissue is brain, which requires robust postmortem sample sizes from varying genetic backgrounds. While small sample sizes are of decreasing concern, postmortem brain databases are composed almost exclusively of Caucasian samples, which significantly limits study design and result interpretation. In this review, we highlight the importance of gene expression and expression quantitative loci (eQTL) studies in clinically relevant postmortem tissue while addressing the current limitations of existing postmortem brain databases. Finally, we introduce future collaborations to develop postmortem brain databases for neuropsychiatric disorders from Chinese and Asian subpopulations.

Keywords: Ethnic diversity; GWAS; Gene expression; Neuropsychiatric disorders; Postmortem brain; eQTL.

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Figures

Figure 1:
Figure 1:. GWAS to Postmortem Gene Expression.
The workflow diagram outlines the steps involved in the integration of GWAS and gene expression data. The GWAS data are generated by genotyping and subsequent imputation of millions of SNPs in thousands of carefully selected cases and matched controls. Similarly, gene expression and SNP data are generated in brain tissues from various brain banks to identify brain specific eQTLs affecting gene expression. In the final steps, GWAS and eQTL data from these two sources are integrated to identify potentially causal GWAS variants.
Figure 2:
Figure 2:. U2-Type Spliceosome Facilitated pre-mRNA Splicing Mechanism.
Small nuclear ribonuceoprotein (snRNP) U2 facilitated spliceosome assembly begins with the U1 snRNP associating with the 5’ splice site and U2 at the branch point (complex A). The pre-assembled U4/U5/U6 tri-snRNP is recruited to form the pre-catalytic spliceosome (complex B1). U1 and U4 snRNPs are then destabilized by various protein interactions resulting in the catalytically active spliceosome (complex B2). The U2/U5/U6 spliceosome complex then facilitates intron excision and exon ligation via two step catalytic process (complex C).
Figure 3:
Figure 3:. Gene Expression Analysis Methods.
A visual summary of the main steps for each of the three most commonly used methods for quantifying gene expression.
Figure 4:
Figure 4:. Power Estimation for eQTL Studies.
The graph shows the relationship between statistical power, minor allele frequency (MAF) and sample size for detection of eQTLs. As shown by the graph successful detection of less common eQTLs is only possible with larger sample sizes, i.e. to detect eQTLs with MAF of 5% we need at least a sample size of N ≥800 brains.
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