Gene expression changes related to immune processes associate with cognitive endophenotypes of schizophrenia

Evidence that a working memory cognitive phenotype within schizophrenia has a unique underlying biology

It is suggested studying phenotypes within the syndrome of schizophrenia will accelerate understanding the complex molecular pathology of the disorder. Supporting this hypothesis, we have identified a sub-group within schizophrenia with impaired working memory (WM) and have used Affymetrix™ Human Exon 1.0 ST Arrays to compare their blood RNA levels (n=16) to a group of with intact WM (n=18). Levels of 72 RNAs were higher in blood from patients with impaired WM, 11 of which have proven links to the maintenance of different aspects of working memory (cognition). Overall, changed gene expression in those with impaired WM could be linked to cognition through glutamatergic activity, olfaction, immunity, inflammation as well as energy and metabolism. Our data gives preliminary support to the hypotheses that there is a working memory deficit phenotype within the syndrome of schizophrenia with has a biological underpinning. In addition, our data raises the possibility that a larger study could show that the specific changes in gene expression we have identified could prove to be the biomarkers needed to develop a blood test to identify those with impaired WM; a significant step toward allowing the use of personalised medicine directed toward improving their impaired working memory.

Genetic and functional analysis reveals TENM4 contributes to schizophrenia

TENM4, encoding a member of the teneurin protein family, is a risk gene shared by many types of mental diseases and is implicated in neuronal plasticity and signaling. However, the role and the mechanisms of TENM4 in schizophrenia (SCZ) remain unclear. We identified possible pathogenic mutations in the TENM4 gene through target sequencing of TENM4 in 68 SCZ families. We further demonstrated that aberrant expression of Ten-m leads to lower learning ability, sleep reduction, and increased aggressiveness in animal models. RNA sequencing showed that aberrant expression of Ten-m was related to stimulus perception and metabolic process, and Gene Ontology enrichment terms were neurogenesis and ATPase activity. This study provides strong evidence that TENM4 contributes to SCZ, and its functional mutations might be responsible for the impaired neural circuits and behaviors observed in SCZ.

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Possible pathogenic rare missense mutations in TENM4 gene contribute to SCZ

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Aberrant expression of Ten-m leads to behavioral disturbances related to SCZ symptoms

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Ten-m affects stimulation, metabolic process, neurogenesis, and ATPase activity

Variants in regulatory elements of PDE4D associate with major mental illness in the Finnish population

We have previously reported a replicable association between variants at the PDE4D gene and familial schizophrenia in a Finnish cohort. In order to identify the potential functional mutations underlying these previous findings, we sequenced 1.5 Mb of the PDE4D genomic locus in 20 families (consisting of 96 individuals and 79 independent chromosomes), followed by two stages of genotyping across 6668 individuals from multiple Finnish cohorts for major mental illnesses. We identified 4570 SNPs across the PDE4D gene, with 380 associated to schizophrenia (p ≤ 0.05). Importantly, two of these variants, rs35278 and rs165940, are located at transcription factor-binding sites, and displayed replicable association in the two-stage enlargement of the familial schizophrenia cohort (combined statistics for rs35278 p = 0.0012; OR = 1.18, 95% CI: 1.06-1.32; and rs165940 p = 0.0016; OR = 1.27, 95% CI: 1.13-1.41). Further analysis using additional cohorts and endophenotypes revealed that rs165940 principally associates within the psychosis (p = 0.025, OR = 1.18, 95% CI: 1.07-1.30) and cognitive domains of major mental illnesses (g-score p = 0.044, β = -0.033). Specifically, the cognitive domains represented verbal learning and memory (p = 0.0091, β = -0.044) and verbal working memory (p = 0.0062, β = -0.036). Moreover, expression data from the GTEx database demonstrated that rs165940 significantly correlates with the mRNA expression levels of PDE4D in the cerebellum (p-value = 0.04; m-value = 0.9), demonstrating a potential functional consequence for this variant. Thus, rs165940 represents the most likely functional variant for major mental illness at the PDE4D locus in the Finnish population, increasing risk broadly to psychotic disorders.

Potentially repurposable drugs for schizophrenia identified from its interactome

We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.