Mitochondrial Mutations in Subjects with Psychiatric Disorders

A considerable body of evidence supports the role of mitochondrial dysfunction in psychiatric disorders and mitochondrial DNA (mtDNA) mutations are known to alter brain energy metabolism, neurotransmission, and cause neurodegenerative disorders. Genetic studies focusing on common nuclear genome variants associated with these disorders have produced genome wide significant results but those studies have not directly studied mtDNA variants. The purpose of this study is to investigate, using next generation sequencing, the involvement of mtDNA variation in bipolar disorder, schizophrenia, major depressive disorder, and methamphetamine use. MtDNA extracted from multiple brain regions and blood were sequenced (121 mtDNA samples with an average of 8,800x coverage) and compared to an electronic database containing 26,850 mtDNA genomes. We confirmed novel and rare variants, and confirmed next generation sequencing error hotspots by traditional sequencing and genotyping methods. We observed a significant increase of non-synonymous mutations found in individuals with schizophrenia. Novel and rare non-synonymous mutations were found in psychiatric cases in mtDNA genes: ND6, ATP6, CYTB, and ND2. We also observed mtDNA heteroplasmy in brain at a locus previously associated with schizophrenia (T16519C). Large differences in heteroplasmy levels across brain regions within subjects suggest that somatic mutations accumulate differentially in brain regions. Finally, multiplasmy, a heteroplasmic measure of repeat length, was observed in brain from selective cases at a higher frequency than controls. These results offer support for increased rates of mtDNA substitutions in schizophrenia shown in our prior results. The variable levels of heteroplasmic/multiplasmic somatic mutations that occur in brain may be indicators of genetic instability in mtDNA

Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P < 10−52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P < 10−58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P < 10−113), further highlighting the advantages of incorporating data from diverse human populations

An integrative functional genomics approach for discovering biomarkers in schizophrenia

Schizophrenia (SZ) is a complex disorder resulting from both genetic and environmental causes with a lifetime prevalence world-wide of 1%; however, there are no specific, sensitive and validated biomarkers for SZ. A general unifying hypothesis has been put forward that disease-associated single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) are more likely to be associated with gene expression quantitative trait loci (eQTL). We will describe this hypothesis and review primary methodology with refinements for testing this paradigmatic approach in SZ. We will describe biomarker studies of SZ and testing enrichment of SNPs that are associated both with eQTLs and existing GWAS of SZ. SZ-associated SNPs that overlap with eQTLs can be placed into gene-gene expression, protein-protein and protein-DNA interaction networks. Further, those networks can be tested by reducing/silencing the gene expression levels of critical nodes. We present pilot data to support these methods of investigation such as the use of eQTLs to annotate GWASs of SZ, which could be applied to the field of biomarker discovery. Those networks that have association with SNP markers, especially cis-regulated expression, might lead to a more clear understanding of important candidate genes that predispose to disease and alter expression. This method has general application to many complex disorders

Supplementary Material for: Olanzapine Reversed Brain Gene Expression Changes Induced by Phencyclidine Treatment in Non-Human Primates

The NMDA receptor antagonist phencyclidine (PCP) creates schizophrenia-like symptoms in normal controls. The effect of PCP on non-human primate brain gene expression was examined and compared to changes induced by olanzapine treatment. Experimental studies of PCP and antipsychotic drugs have direct relevance to understanding the pathophysiology and treatment of schizophrenia. Genome-wide changes in prefrontal cortex gene expression revealed alterations of 146 transcripts in the PCP treatment group compared to vehicle controls. Dysregulated genes were enriched in identified classes implicated in neurological and genetic disorders, including schizophrenia genes from the Psychiatric Genomics Consortium 108 loci as well as cell death in PCP-treated primates. Canonical pathway analysis revealed a significant overrepresentation of several groups including synaptic long-term potentiation and calcium signaling. Olanzapine coadministered with PCP normalized 34% of the 146 PCP-induced probe set expression changes, and a network of 17 olanzapine-normalized genes was identified enriched in schizophrenia candidate genes containing RGS4, SYN1 and AKT as nodes. The results of this study support the use of PCP administration in non-human primates as a glutamatergic model of schizophrenia and suggest that a large number of PCP-induced expression differences can be reversed by olanzapine. The results of this study may be informative for identification of potential candidates for pharmacogenetics and biomarker research related to the treatment of schizophrenia

Supplementary Material for: Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder

This study developed potential blood-based biomarker tests for diagnosing and differentiating schizophrenia (SZ), bipolar disorder type I (BD), and normal control (NC) subjects using mRNA gene expression signatures. A total of 90 subjects (<i>n</i> = 30 each for the three groups of subjects) provided blood samples at two visits. The Affymetrix exon microarray was used to profile the expression of over 1.4 million probesets. We selected potential biomarker panels using the temporal stability of the probesets and also back-tested them at two different visits for each subject. The 18-gene biomarker panels, using logistic regression modeling, correctly differentiated the three groups of subjects with high accuracy across the two different clinical visits (83–88% accuracy). The results are also consistent with the actual data and the “leave-one-out” analyses, indicating that the models should be predictive when applied to independent data cohorts. Many of the SZ and BD subjects were taking antipsychotic and mood stabilizer medications at the time of blood draw, raising the possibility that these drugs could have affected some of the differential transcription signatures. Using an independent Illumina data set of gene expression data from antipsychotic medication-free SZ subjects, the 18-gene biomarker panels produced a receiver operating characteristic curve accuracy greater than 0.866 in patients that were less than 30 years of age and medication free. We confirmed select transcripts by quantitative PCR and the nCounter® System. The episodic nature of psychiatric disorders might lead to highly variable results depending on when blood is collected in relation to the severity of the disease/symptoms. We have found stable trait gene panel markers for lifelong psychiatric disorders that may have diagnostic utility in younger undiagnosed subjects where there is a critical unmet need. The study requires replication in subjects for ultimate proof of the utility of the differential diagnosis

Increased CNV-Region deletions in mild cognitive impairment (MCI) and Alzheimer&apos;s disease (AD) subjects in the ADNI sample

We investigated the genome-wide distribution of CNVs in the Alzheimer's disease (AD) Neuroimaging Initiative (ADNI) sample (146 with AD, 313 with Mild Cognitive Impairment (MCI), and 181 controls).Comparison of single CNVs between cases (MCI and AD) and controls shows overrepresentation of large heterozygous deletions in cases (p-value. <. 0.0001). The analysis of CNV-Regions identifies 44 copy number variable loci of heterozygous deletions, with more CNV-Regions among affected than controls (p. =.0.005). Seven of the 44 CNV-Regions are nominally significant for association with cognitive impairment. We validated and confirmed our main findings with genome re-sequencing of selected patients and controls. The functional pathway analysis of the genes putatively affected by deletions of CNV-Regions reveals enrichment of genes implicated in axonal guidance, cell-cell adhesion, neuronal morphogenesis and differentiation. Our findings support the role of CNVs in AD, and suggest an association between large deletions and the development of cognitive impairment

Supplementary Material for: Evidence of Mitochondrial Dysfunction within the Complex Genetic Etiology of Schizophrenia

<br>Genetic evidence has supported the hypothesis that schizophrenia (SZ) is a polygenic disorder caused by the disruption in function of several or many genes. The most common and reproducible cellular phenotype associated with SZ is a reduction in dendritic spines within the neocortex, suggesting alterations in dendritic architecture may cause aberrant cortical circuitry and SZ symptoms. Here, we review evidence supporting a multifactorial model of mitochondrial dysfunction in SZ etiology and discuss how these multiple paths to mitochondrial dysfunction may contribute to dendritic spine loss and/or underdevelopment in some SZ subjects. The pathophysiological role of mitochondrial dysfunction in SZ is based upon genomic analyses of both the mitochondrial genome and nuclear genes involved in mitochondrial function. Previous studies and preliminary data suggest SZ is associated with specific alleles and haplogroups of the mitochondrial genome, and also correlates with a reduction in mitochondrial copy number and an increase in synonymous and nonsynonymous substitutions of mitochondrial DNA. Mitochondrial dysfunction has also been widely implicated in SZ by genome-wide association, exome sequencing, altered gene expression, proteomics, microscopy analyses, and induced pluripotent stem cell studies. Together, these data support the hypothesis that SZ is a polygenic disorder with an enrichment of mitochondrial targets

Supplementary Material for: A Genome-Wide Search for Bipolar Disorder Risk Loci Modified by Mitochondrial Genome Variation

<p>Mitochondrial DNA mutations have been reported to be associated with bipolar disorder (BD). In this study, we performed genome-wide analyses to assess mitochondrial single-nucleotide polymorphism (mtSNP) effects on BD risk and early-onset BD (EOBD) among BD patients, focusing on interaction effects between nuclear SNPs (nSNPs) and mtSNPs. Common nSNP and mtSNP data from European American BD cases (<i>n</i> = 1,001) and controls (<i>n</i> = 1,034) from the Genetic Association Information Network BD study were analyzed to assess the joint effect of nSNP and nSNP-mtSNP interaction on the risk of BD and EOBD. The effect of nSNP-mtSNP interactions was also assessed. For BD risk, the strongest evidence of an association was obtained for nSNP rs1880924 in <i>MGAM</i> and mtSNP rs3088309 in <i>CytB</i> (<i>p</i>_joint = 8.2 × 10^-8, <i>p</i>_int = 1.4 × 10^-4). Our results also suggest that the minor allele of the nSNP rs583990 in <i>CTNNA2</i> increases the risk of EOBD among carriers of the mtSNP rs3088309 minor allele, while the nSNP has no effect among those carrying the mtSNP major allele (OR = 4.53 vs. 1.05, <i>p</i>_joint = 2.1 × 10^-7, <i>p</i>_int = 1.16 × 10^-6). While our results are not statistically significant after multiple testing correction and a large-sample replication is required, our exploratory study demonstrates the potential importance of considering the mitochondrial genome for identifying genetic factors associated with BD.</p

Schizophrenia miR-137 locus risk genotype is associated with dorsolateral prefrontal cortex hyperactivation

Background miR-137 dysregulation has been implicated in the etiology of schizophrenia, but its functional role remains to be determined. Methods Functional magnetic resonance imaging scans were acquired on 48 schizophrenia patients and 63 healthy volunteers (total sample size N = 111 subjects), with similar mean age and sex distribution, while subjects performed a Sternberg Item Response Paradigm with memory loads of one, three, and five numbers. Dorsolateral prefrontal cortex (DLPFC) retrieval activation for the working memory load of three numbers, for which hyperactivation had been shown in schizophrenia patients compared with control subjects, was extracted. The genome-wide association study confirmed schizophrenia risk single nucleotide polymorphism rs1625579 (miR-137 locus) was genotyped (schizophrenia: GG n = 0, GT n = 9, TT n = 39; healthy volunteers: GG = 2, GT n = 15, and TT n = 46). Fisher's exact test examined the effect of diagnosis on rs1625579 allele frequency distribution (p = nonsignificant). Mixed model regression analyses examined the effects of diagnosis and genotype on working memory performance measures and DLPFC activation. Results Patients showed significantly higher left DLPFC retrieval activation on working memory load 3, lower working memory performance, and longer response times compared with controls. There was no effect of genotype on working memory performance or response times in either group. However, individuals with the rs1625579 TT genotype had significantly higher left DLPFC activation than those with the GG/GT genotypes. Conclusions Our study suggests that the rs1625579 TT (miR-137 locus) schizophrenia risk genotype is associated with the schizophrenia risk phenotype DLPFC hyperactivation commonly considered a measure of brain inefficiency