Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients

Significance of an altered lncRNA landscape in schizophrenia and cognition: clues from a case-control association study

Genetic etiology of schizophrenia is poorly understood despite large genome-wide association data. Long non-coding RNAs (lncRNAs) with a probable regulatory role are emerging as important players in neuro-psychiatric disorders including schizophrenia. Prioritising important lncRNAs and analyses of their holistic interaction with their target genes may provide insights into disease biology/etiology. Of the 3843 lncRNA SNPs reported in schizophrenia GWASs extracted using lincSNP 2.0, we prioritised n = 247 based on association strength, minor allele frequency and regulatory potential and mapped them to lncRNAs. lncRNAs were then prioritised based on their expression in brain using lncRBase, epigenetic role using 3D SNP and functional relevance to schizophrenia etiology. 18 SNPs were finally tested for association with schizophrenia (n = 930) and its endophenotypes-tardive dyskinesia (n = 176) and cognition (n = 565) using a case-control approach. Associated SNPs were characterised by ChIP seq, eQTL, and transcription factor binding site (TFBS) data using FeatSNP. Of the eight SNPs significantly associated, rs2072806 in lncRNA hsaLB_IO39983 with regulatory effect on BTN3A2 was associated with schizophrenia (p = 0.006); rs2710323 in hsaLB_IO_2331 with role in dysregulation of ITIH1 with tardive dyskinesia (p < 0.05); and four SNPs with significant cognition score reduction (p < 0.05) in cases. Two of these with two additional variants in eQTL were observed among controls (p < 0.05), acting likely as enhancer SNPs and/or altering TFBS of eQTL mapped downstream genes. This study highlights important lncRNAs in schizophrenia and provides a proof of concept of novel interactions of lncRNAs with protein-coding genes to elicit alterations in immune/inflammatory pathways of schizophrenia.

Working memory deficits in schizophrenia are associated with the rs34884856 variant and expression levels of the NR4A2 gene in a sample Mexican population: a case control study

BACKGROUND

Cognitive functions represent useful endophenotypes to identify the association between genetic variants and schizophrenia. In this sense, the NR4A2 gene has been implicated in schizophrenia and cognition in different animal models and clinical trials. We hypothesized that the NR4A2 gene is associated with working memory performance in schizophrenia. This study aimed to analyze two variants and the expression levels of the NR4A2 gene with susceptibility to schizophrenia, as well as to evaluate whether possession of NR4A2 variants influence the possible correlation between gene expression and working memory performance in schizophrenia.

METHODS

The current study included 187 schizophrenia patients and 227 controls genotyped for two of the most studied NR4A2 genetic variants in neurological and neuropsychiatric diseases. Genotyping was performed using High Resolution Melt and sequencing techniques. In addition, mRNA expression of NR4A2 was performed in peripheral mononuclear cells of 112 patients and 118 controls. A group of these participants, 54 patients and 87 controls, performed the working memory index of the WAIS III test.

RESULTS

Both genotypic frequencies of the two variants and expression levels of the NR4A2 gene showed no significant difference when in patients versus controls. However, patients homozygous for the rs34884856 promoter variant showed a positive correlation between expression levels and auditory working memory.

CONCLUSIONS

Our finding suggested that changes in expression levels of the NR4A2 gene could be associated with working memory in schizophrenia depending on patients' genotype in a sample from a Mexican population.

Neural and molecular correlates of psychological pain during major depression, and its link with suicidal ideas

OBJECTIVES

Psychological pain increases the risk of suicidal ideas and acts, and represents a potential therapeutic target. However, the mechanisms of mental pain remain unclear. Here, we assessed the peripheral transcriptomic and central neural correlates of mental pain during a depressive episode.

METHODS

172 adult un-medicated depressed patients were recruited. Leucocytes were extracted for RNA quantification at baseline (T0) and after 8 weeks (T8) of an antidepressant treatment. Ninety-nine genes of the cortisol, immune, opioid, serotonergic, and kynurenine systems were a priori selected, and 41 were sufficiently expressed to be analyzed. At both T0 and T8, mean level of mental pain over the last 15 days was measured with a visual analog scale. A subset of 38 patients was additionally scanned with Magnetic Resonance Imaging at T0. Resting-state sequences of 4 networks (default-mode, basal ganglia, central executive, salience) were examined.

RESULTS

Mean psychological pain scores significantly decreased between T0 and T8. At conservative p-corrected levels, T0 mental pain was significantly correlated with 11 brain clusters encompassing the prefrontal, parietal, and temporal cortices, the striatum, and the cerebellum. There was no direct association between peripheral gene expression and mean mental pain at any time points or in terms of temporal changes. However, expressions of 5HTR2B at p-corrected levels, and 5HTR3A, TPH1, and OPRL1 were correlated with the activity of several identified brain clusters at T0. Finally, while suicidal ideas and mental pain were correlated, the neural and molecular correlates of suicidal ideas were not the same.

CONCLUSION

Our study suggests that the serotonergic and nociceptin systems are associated with the activity of a cortico-subcortical brain network underlying the perception of mental pain during depression. Mental pain may be a necessary but insufficient condition for the emergence of suicidal ideation during depression.

Enzymatic activity of palmitoyl-protein thioesterase-1 in serum from schizophrenia significantly associates with schizophrenia diagnosis scales

Genome-wide association studies have confirmed that schizophrenia is an inheritable multiple-gene mental disorder. Longitudinal studies about depression, first episode psychosis (FEP) and acute psychotic relapse have mostly searched for brain imaging biomarkers and inflammatory markers from the blood. However, to the best of our knowledge, the association between enzymatic activities with diagnosis or prediction of treatment response in people with schizophrenia has barely been validated. Under the Longitudinal Study of National Mental Health Work Plan (2015-2020), we have studied a subsample of approximately 36 individuals from the cohort with data on palmitoyl-protein thioesterase-1 enzymatic activity from FEP and performed a bivariate correlation analysis with psychiatric assessment scores. After adjusting for sex, age, body mass index (BMI) and total serum protein, our data demonstrated that PPT1 enzymatic activity is significantly associated with schizophrenia and its Positive and Negative Syndrome Scale (PANSS) scores. This longitudinal study compared the PPT1 enzymatic activity in FEP schizophrenia patients and healthy volunteers, and the former exhibited a significant 1.5-fold increase in PPT1 enzymatic levels (1.79 mmol/L/h/mL, and 1.18 mmol/L/h/mL; P < 0.05; 95% CI, 2.3-2.9 and 1.4-1.8). The higher PPT1 enzymatic levels in FEP schizophrenia patients were positively associated with larger PANSS scaling scores (r = 0.32, P = 0.0079 for positive scaling; r = 0.41, P = 0.0006 for negative scaling; r = 0.45, P = 0.0001 for general scaling; and r = 0.34, P = 0.0048 for PNASS-S scaling). Higher enzymatic PPT1 in FEP schizophrenia patients is significantly associated with increased PANSS scaling values, indicating more serious rates of developing psychosis. Enzymatic activity of PPT1 may provide an important new view for schizophrenia disorders.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Genetic association and meta-analysis of a schizophrenia GWAS variant rs10489202 in East Asian populations

Previous genome-wide association studies (GWAS) suggest that rs10489202 in the intron of MPC2 (mitochondrial pyruvate carrier 2) is a risk locus for schizophrenia in Han Chinese populations. To validate this discovery, we conducted a replication analysis in an independent case-control sample of Han Chinese ancestry (437 cases and 2031 controls), followed by a meta-analytic investigation in multiple East Asian samples. In the replication analysis, rs10489202 showed marginal association with schizophrenia (two-tailed P = 0.071, OR = 1.192 for T allele); in the meta-analysis using a total of 14,340 cases and 20,349 controls from ten East Asian samples, rs10489202 was genome-wide significantly associated with schizophrenia (two-tailed P = 3.39 × 10^-10, OR = 1.161 for T allele, under the fixed-effect model). We then performed an explorative investigation of the association between this SNP and bipolar disorder, as well as a major depressive disorder, and the schizophrenia-predisposing allele was associated with an increased risk of major depressive disorder in East Asians (two-tailed P = 2.49 × 10^-2, OR = 1.103 for T allele). Furthermore, expression quantitative trait loci (eQTL) analysis in lymphoblastoid cell lines from East Asian donors (N = 85 subjects) revealed that rs10489202 was specifically and significantly associated with the expression of TIPRL gene (P = 5.67 × 10^-4). Taken together, our data add further support for the genetic involvement of this genomic locus in the susceptibility to schizophrenia in East Asian populations, and also provide preliminary evidence for the underlying molecular mechanisms.