Comparative gene expression analysis of blood and brain provides concurrent validation of SELENBP1 up-regulation in schizophrenia

Laval University, Quebec City, Quebec, Canada
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 11/2005; 102(43):15533-8. DOI: 10.1073/pnas.0507666102
Source: PubMed

ABSTRACT Microarray techniques hold great promise for identifying risk factors for schizophrenia (SZ) but have not yet generated widely reproducible results due to methodological differences between studies and the high risk of type I inferential errors. Here we established a protocol for conservative analysis and interpretation of gene expression data from the dorsolateral prefrontal cortex of SZ patients using statistical and bioinformatic methods that limit false positives. We also compared brain gene expression profiles with those from peripheral blood cells of a separate sample of SZ patients to identify disease-associated genes that generalize across tissues and populations and further substantiate the use of gene expression profiling of blood for detecting valid SZ biomarkers. Implementing this systematic approach, we: (i) discovered 177 putative SZ risk genes in brain, 28 of which map to linked chromosomal loci; (ii) delineated six biological processes and 12 molecular functions that may be particularly disrupted in the illness; (iii) identified 123 putative SZ biomarkers in blood, 6 of which (BTG1, GSK3A, HLA-DRB1, HNRPA3, SELENBP1, and SFRS1) had corresponding differential expression in brain; (iv) verified the differential expression of the strongest candidate SZ biomarker (SELENBP1) in blood; and (v) demonstrated neuronal and glial expression of SELENBP1 protein in brain. The continued application of this approach in other brain regions and populations should facilitate the discovery of highly reliable and reproducible candidate risk genes and biomarkers for SZ. The identification of valid peripheral biomarkers for SZ may ultimately facilitate early identification, intervention, and prevention efforts as well.

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Available from: Jacques Corbeil, Aug 16, 2015
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    • "For this purpose, and with the intent of identifying true biomarkers of these disorders, we and others in the field have turned to the peripheral blood, which already enjoys widespread use as a source of DNA for genomic studies. In our studies of SZ, for example, we have identified a number of potential biomarkers in whole-blood or PBMCs [Tsuang et al., 2005; Glatt et al., 2009], several of which were subsequently validated in post-mortem brain tissue samples from other independent samples of SZ patients [Glatt et al., 2005, 2009]. This suggests that, in addition to their biomarker potential, certain peripherally expressed and dysregulated genes (though certainly not all such genes) may be indicative of the abnormal biological processes underlying the disorder. "
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    ABSTRACT: In this article, we review studies detailing the correspondence between peripheral blood and brain tissue across various domains of high-throughput -omic analysis in order to provide a context for evaluating blood-based biomarker studies. Specifically, we reviewed seven studies comparing patterns of DNA methylation (i.e., an aspect of the epigenome), eight articles comparing patterns of gene expression (i.e., the transcriptome), and three articles comparing patterns of protein expression (i.e., the proteome). Our review of the epigenomic literature suggests that CpG-island methylation levels are generally highly correlated (r = 0.90) between blood and brain. Our review of transcriptomic studies suggests that between 35% and 80% of known transcripts are present in both brain and blood tissue samples; estimates of cross-tissue correlation in expression levels were found to range from 0.25 to 0.64, with stronger correlations observed among particular subsets of genes. Relative to the epigenome and transcriptome, the proteome has not been as fully compared between brain and blood samples, highlighting an important area for future work as whole-proteome profiling methods mature. Beyond reviewing the relevant studies, we discuss some of the assumptions, methodological issues, and gaps in knowledge that should be addressed in order to better understand how the multiple "-omes" of the brain are reflected in the peripheral blood. A better understanding of these relationships is a critical precursor to the validation of biomarkers for brain disorders. © 2013 Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 10/2013; 162(7):595-603. DOI:10.1002/ajmg.b.32150 · 3.27 Impact Factor
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    • "us, we sought to correlate blood-based gene expression of the Wnt/í µí»½í µí»½-catenin signaling pathway with negative and positive symptom severity indices of patients with a history of psychosis (i.e., schizophrenia or bipolar disorder). We were guided by previous research that has examined the relationship between psychosis symptom severity and other gene expression pathways in peripheral blood [3] [4] and has demonstrated the utility of blood as a source of biomarkers for brain disorders [5] "
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    ABSTRACT: Genes in the Wnt (wingless)/ β -catenin signaling pathway have been implicated in schizophrenia pathogenesis. No study has examined this pathway in the broader context of psychosis symptom severity. We investigated the association between symptom severity scores and expression of 25 Wnt pathway genes in blood from 19 psychotic patients. Significant correlations between negative symptom scores and deshivelled 2 (DVL2) (r adj = -0.70; P = 0.0008) and glycogen synthase kinase 3 beta (GSK3B) (r adj = 0.48; P = 0.039) were observed. No gene expression levels were associated with positive symptoms. Our findings suggest that the Wnt signaling pathway may harbor biomarkers for severity of negative but not positive symptoms.
    01/2013; 2013:852930. DOI:10.1155/2013/852930
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    • "HIST1H2BK that reside at or near this locus. Interestingly, the major histocompatibility complex, class II, DR beta 1 (HLA-DRB1) was also down-regulated in the prefrontal cortex (Glatt et al., 2005). Three genes up-regulated in our study and in Glatt's study include the Galectin family member lectin, galactoside-binding, soluble 3 (LGALS3), a negative regulator of T lymphocyte activation (Yang et al., 2008); the antiprotease, antibacterial and possibly antiinflammatory Peptidase inhibitor 3, skin-derived (PI3) (Sallenave, 2002) and the pro-inflammatory S100 calcium binding protein A12, calgranulin C (S100A12) (Glatt et al., 2005). "
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    ABSTRACT: Peripheral blood mononuclear cells (PBMCs) represent an accessible tissue source for gene expression profiling in schizophrenia that could provide insight into the molecular basis of the disorder. This study used the Illumina HT_12 microarray platform and quantitative real time PCR (QPCR) to perform mRNA expression profiling on 114 patients with schizophrenia or schizoaffective disorder and 80 non-psychiatric controls from the Australian Schizophrenia Research Bank (ASRB). Differential expression analysis revealed altered expression of 164 genes (59 up-regulated and 105 down-regulated) in the PBMCs from patients with schizophrenia compared to controls. Bioinformatic analysis indicated significant enrichment of differentially expressed genes known to be involved or associated with immune function and regulating the immune response. The differential expression of 6 genes, EIF2C2 (Ago 2), MEF2D, EVL, PI3, S100A12 and DEFA4 was confirmed by QPCR. Genome-wide expression analysis of PBMCs from individuals with schizophrenia was characterized by the alteration of genes with immune system function, supporting the hypothesis that the disorder has a significant immunological component in its etiology.
    Journal of Psychiatric Research 12/2012; 47(4). DOI:10.1016/j.jpsychires.2012.11.007 · 4.09 Impact Factor
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