Clinotator: analyzing ClinVar variation reports to prioritize reclassification efforts [version 2; referees: 2 approved]

While ClinVar has become an indispensable resource for clinical variant interpretation, its sophisticated structure provides it with a daunting learning curve. Often the sheer depth of types of information provided can make it difficult to analyze variant information with high throughput. Clinotator is a fast and lightweight tool to extract important aspects of criteria-based clinical assertions; it uses that information to generate several metrics to assess the strength and consistency of the evidence supporting the variant clinical significance. Clinical assertions are weighted by significance type, age of submission and submitter expertise category to filter outdated or incomplete assertions that otherwise confound interpretation. This can be accomplished in batches: either lists of Variation IDs or dbSNP rsIDs, or with vcf files that are additionally annotated. Using sample sets ranging from 15,000–50,000 variants, we slice out problem variants in minutes without extensive computational effort (using only a personal computer) and corroborate recently reported trends of discordance hiding amongst the curated masses. With the rapidly growing body of variant evidence, most submitters and researchers have limited resources to devote to variant curation. Clinotator provides efficient, systematic prioritization of discordant variants in need of reclassification. The hope is that this tool can inform ClinVar curation and encourage submitters to keep their clinical assertions current by focusing their efforts. Additionally, researchers can utilize new metrics to analyze variants of interest in pursuit of new insights into pathogenicity

Dopamine perturbation of gene co-expression networks reveals differential response in schizophrenia for translational machinery.

The dopaminergic hypothesis of schizophrenia (SZ) postulates that positive symptoms of SZ, in particular psychosis, are due to disturbed neurotransmission via the dopamine (DA) receptor D2 (DRD2). However, DA is a reactive molecule that yields various oxidative species, and thus has important non-receptor-mediated effects, with empirical evidence of cellular toxicity and neurodegeneration. Here we examine non-receptor-mediated effects of DA on gene co-expression networks and its potential role in SZ pathology. Transcriptomic profiles were measured by RNA-seq in B-cell transformed lymphoblastoid cell lines from 514 SZ cases and 690 controls, both before and after exposure to DA ex vivo (100 μM). Gene co-expression modules were identified using Weighted Gene Co-expression Network Analysis for both baseline and DA-stimulated conditions, with each module characterized for biological function and tested for association with SZ status and SNPs from a genome-wide panel. We identified seven co-expression modules under baseline, of which six were preserved in DA-stimulated data. One module shows significantly increased association with SZ after DA perturbation (baseline: P = 0.023; DA-stimulated: P = 7.8 × 10-5; ΔAIC = -10.5) and is highly enriched for genes related to ribosomal proteins and translation (FDR = 4 × 10-141), mitochondrial oxidative phosphorylation, and neurodegeneration. SNP association testing revealed tentative QTLs underlying module co-expression, notably at FASTKD2 (top P = 2.8 × 10-6), a gene involved in mitochondrial translation. These results substantiate the role of translational machinery in SZ pathogenesis, providing insights into a possible dopaminergic mechanism disrupting mitochondrial function, and demonstrates the utility of disease-relevant functional perturbation in the study of complex genetic etiologies

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

We undertook an RNA sequencing (RNAseq)-based transcriptomic profiling study on lymphoblastoid cell lines of a European ancestry sample of 529 schizophrenia cases and 660 controls, and found 1058 genes to be differentially expressed by affection status. These differentially expressed genes were enriched for involvement in immunity, especially the 697 genes with higher expression in cases. Comparing the current RNAseq transcriptomic profiling to our previous findings in an array-based study of 268 schizophrenia cases and 446 controls showed a highly significant positive correlation over all genes. Fifteen (18%) of the 84 genes with significant (false discovery rateo0.05) expression differences between cases and controls in the previous study and analyzed here again were differentially expressed by affection status here at a genome-wide significance level (Bonferroni Po0.05 adjusted for 8141 analyzed genes in total, or Po ~ 6.1 × 10− 6), all with the same direction of effect, thus providing corroborative evidence despite each sample of fully independent subjects being studied by different technological approaches. Meta-analysis of the RNAseq and array data sets (797 cases and 1106 controls) showed 169 additional genes (besides those found in the primary RNAseq-based analysis) to be differentially expressed, and provided further evidence of immune gene enrichment. In addition to strengthening our previous array-based gene expression differences in schizophrenia cases versus controls and providing transcriptomic support for some genes implicated by other approaches for schizophrenia, our study detected new genes differentially expressed in schizophrenia. We highlight RNAseq-based differential expression of various genes involved in neurodevelopment and/or neuronal function, and discuss caveats of the approach

Dopamine perturbation of gene co-expression networks reveals differential response in schizophrenia for translational machinery

The dopaminergic hypothesis of schizophrenia (SZ) postulates that positive symptoms of SZ, in particular psychosis, are due to disturbed neurotransmission via the dopamine (DA) receptor D2 (DRD2). However, DA is a reactive molecule that yields various oxidative species, and thus has important non-receptor-mediated effects, with empirical evidence of cellular toxicity and neurodegeneration. Here we examine non-receptor-mediated effects of DA on gene co-expression networks and its potential role in SZ pathology. Transcriptomic profiles were measured by RNA-seq in B-cell transformed lymphoblastoid cell lines from 514 SZ cases and 690 controls, both before and after exposure to DA ex vivo (100 μM). Gene co-expression modules were identified using Weighted Gene Co-expression Network Analysis for both baseline and DA-stimulated conditions, with each module characterized for biological function and tested for association with SZ status and SNPs from a genome-wide panel. We identified seven co-expression modules under baseline, of which six were preserved in DA-stimulated data. One module shows significantly increased association with SZ after DA perturbation (baseline: P = 0.023; DA-stimulated: P = 7.8 × 10-5; ΔAIC = −10.5) and is highly enriched for genes related to ribosomal proteins and translation (FDR = 4 × 10−141), mitochondrial oxidative phosphorylation, and neurodegeneration. SNP association testing revealed tentative QTLs underlying module co-expression, notably at FASTKD2 (top P = 2.8 × 10−6), a gene involved in mitochondrial translation. These results substantiate the role of translational machinery in SZ pathogenesis, providing insights into a possible dopaminergic mechanism disrupting mitochondrial function, and demonstrates the utility of disease-relevant functional perturbation in the study of complex genetic etiologies

Transcriptomic signatures of schizophrenia revealed by dopamine perturbation in an ex vivo model

The dopaminergic hypothesis of schizophrenia (SZ) postulates that dopaminergic over activity causes psychosis, a central feature of SZ, based on the observation that blocking dopamine (DA) improves psychotic symptoms. DA is known to have both receptor- and non-receptor-mediated effects, including oxidative mechanisms that lead to apoptosis. The role of DA-mediated oxidative processes in SZ has been little studied. Here, we have used a cell perturbation approach and measured transcriptomic profiles by RNAseq to study the effect of DA exposure on transcription in B-cell transformed lymphoblastoid cell lines (LCLs) from 514 SZ cases and 690 controls. We found that DA had widespread effects on both cell growth and gene expression in LCLs. Overall, 1455 genes showed statistically significant differential DA response in SZ cases and controls. This set of differentially expressed genes is enriched for brain expression and for functions related to immune processes and apoptosis, suggesting that DA may play a role in SZ pathogenesis through modulating those systems. Moreover, we observed a non-significant enrichment of genes near genome-wide significant SZ loci and with genes spanned by SZ-associated copy number variants (CNVs), which suggests convergent pathogenic mechanisms detected by both genetic association and gene expression. The study suggests a novel role of DA in the biological processes of immune and apoptosis that may be relevant to SZ pathogenesis. Furthermore, our results show the utility of pathophysiologically relevant perturbation experiments to investigate the biology of complex mental disorders

Segment-Wise Genome-Wide Association Analysis Identifies a Candidate Region Associated with Schizophrenia in Three Independent Samples

Recent studies suggest that variation in complex disorders (e.g., schizophrenia) is explained by a large number of genetic variants with small effect size (Odds Ratio∼1.05–1.1). The statistical power to detect these genetic variants in Genome Wide Association (GWA) studies with large numbers of cases and controls (∼15,000) is still low. As it will be difficult to further increase sample size, we decided to explore an alternative method for analyzing GWA data in a study of schizophrenia, dramatically reducing the number of statistical tests. The underlying hypothesis was that at least some of the genetic variants related to a common outcome are collocated in segments of chromosomes at a wider scale than single genes. Our approach was therefore to study the association between relatively large segments of DNA and disease status. An association test was performed for each SNP and the number of nominally significant tests in a segment was counted. We then performed a permutation-based binomial test to determine whether this region contained significantly more nominally significant SNPs than expected under the null hypothesis of no association, taking linkage into account. Genome Wide Association data of three independent schizophrenia case/control cohorts with European ancestry (Dutch, German, and US) using segments of DNA with variable length (2 to 32 Mbp) was analyzed. Using this approach we identified a region at chromosome 5q23.3-q31.3 (128–160 Mbp) that was significantly enriched with nominally associated SNPs in three independent case-control samples. We conclude that considering relatively wide segments of chromosomes may reveal reliable relationships between the genome and schizophrenia, suggesting novel methodological possibilities as well as raising theoretical questions

Runs of Homozygosity Implicate Autozygosity as a Schizophrenia Risk Factor

Autozygosity occurs when two chromosomal segments that are identical from a common ancestor are inherited from each parent. This occurs at high rates in the offspring of mates who are closely related (inbreeding), but also occurs at lower levels among the offspring of distantly related mates. Here, we use runs of homozygosity in genome-wide SNP data to estimate the proportion of the autosome that exists in autozygous tracts in 9,388 cases with schizophrenia and 12,456 controls. We estimate that the odds of schizophrenia increase by ∼17% for every 1% increase in genome-wide autozygosity. This association is not due to one or a few regions, but results from many autozygous segments spread throughout the genome, and is consistent with a role for multiple recessive or partially recessive alleles in the etiology of schizophrenia. Such a bias towards recessivity suggests that alleles that increase the risk of schizophrenia have been selected against over evolutionary time

Additive genetic variation in schizophrenia risk is shared by populations of African and European descent

Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRβ1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 × 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His > Phe > Arg > Tyr ≅ Gly > Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 × 10(-33)) and 74 (conditional Pomnibus = 1.1 × 10(-8)). Outside of HLA-DRβ1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 × 10(-6)) and HLA-DPβ1 (Phe9, conditional P = 3.0 × 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC

A Rare Functional Noncoding Variant at the GWAS-Implicated MIR137/MIR2682 Locus Might Confer Risk to Schizophrenia and Bipolar Disorder

Schizophrenia (SZ) genome-wide association studies (GWASs) have identified common risk variants in >100 susceptibility loci; however, the contribution of rare variants at these loci remains largely unexplored. One of the strongly associated loci spans MIR137 (miR137) and MIR2682 (miR2682), two microRNA genes important for neuronal function. We sequenced ∼6.9 kb MIR137/MIR2682 and upstream regulatory sequences in 2,610 SZ cases and 2,611 controls of European ancestry. We identified 133 rare variants with minor allele frequency (MAF) <0.5%. The rare variant burden in promoters and enhancers, but not insulators, was associated with SZ (p = 0.021 for MAF < 0.5%, p = 0.003 for MAF < 0.1%). A rare enhancer SNP, 1:g.98515539A>T, presented exclusively in 11 SZ cases (nominal p = 4.8 × 10−4). We further identified its risk allele T in 2 of 2,434 additional SZ cases, 11 of 4,339 bipolar (BP) cases, and 3 of 3,572 SZ/BP study controls and 1,688 population controls; yielding combined p values of 0.0007, 0.0013, and 0.0001 for SZ, BP, and SZ/BP, respectively. The risk allele T of 1:g.98515539A>T reduced enhancer activity of its flanking sequence by >50% in human neuroblastoma cells, predicting lower expression of MIR137/MIR2682. Both empirical and computational analyses showed weaker transcription factor (YY1) binding by the risk allele. Chromatin conformation capture (3C) assay further indicated that 1:g.98515539A>T influenced MIR137/MIR2682, but not the nearby DPYD or LOC729987. Our results suggest that rare noncoding risk variants are associated with SZ and BP at MIR137/MIR2682 locus, with risk alleles decreasing MIR137/MIR2682 expression