Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data.

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants.

We searched a gene expression dataset comprised of 634 schizophrenia (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of transcript expression values) with SZ cases overrepresented compared with controls. These outlier genes were enriched for brain expression and for genes known to be associated with neurodevelopmental disorders. SZ cases showed higher outlier burden (i.e., total outlier events per subject) than controls for genes within copy number variants (CNVs) associated with SZ or neurodevelopmental disorders. Outlier genes were enriched for CNVs and for rare putative regulatory variants, but this only explained a small proportion of the outlier subjects, highlighting the underlying presence of additional genetic and potentially, epigenetic mechanisms.

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.

MicroRNA-9 and microRNA-326 regulate human dopamine D2 receptor expression, and the microRNA-mediated expression regulation is altered by a genetic variant.

The human dopamine receptor D2 (DRD2) has been implicated in the pathophysiology of schizophrenia and other neuropsychiatric disorders. Most antipsychotic drugs influence dopaminergic transmission through blocking dopamine receptors, primarily DRD2. We report here the post-transcriptional regulation of DRD2 expression by two brain-expressed microRNAs (miRs), miR-326 and miR-9, in an ex vivo mode, and show the relevance of miR-mediated DRD2 expression regulation in human dopaminergic neurons and in developing human brains. Both miRs targeted the 3'-UTR (untranslated region) of DRD2 in NT2 (neuron-committed teratocarcinoma, which endogenously expresses DRD2) and CHO (Chinese hamster ovary) cell lines, decreasing luciferase activity measured by a luciferase reporter gene assay. miR-326 overexpression reduced DRD2 mRNA and DRD2 receptor synthesis. Both antisense miR-326 and antisense miR-9 increased DRD2 protein abundance, suggesting an endogenous repression of DRD2 expression by both miRs. Furthermore, a genetic variant (rs1130354) within the DRD2 3'-UTR miR-targeting site interferes with miR-326-mediated repression of DRD2 expression. Finally, co-expression analysis identified an inverse correlation of DRD2 expression with both miR-326 and miR-9 in differentiating dopaminergic neurons derived from human induced pluripotent stem cells (iPSCs) and in developing human brain regions implicated in schizophrenia. Our study provides empirical evidence suggesting that miR-326 and miR-9 may regulate dopaminergic signaling, and miR-326 and miR-9 may be considered as potential drug targets for the treatment of disorders involving abnormal DRD2 function, such as schizophrenia.

Transcriptome study of differential expression in schizophrenia.

Schizophrenia genome-wide association studies (GWAS) have identified common SNPs, rare copy number variants (CNVs) and a large polygenic contribution to illness risk, but biological mechanisms remain unclear. Bioinformatic analyses of significantly associated genetic variants point to a large role for regulatory variants. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines (LCLs) from 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate (FDR) of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, microRNA (miRNA) processing and immunity. This functional diversity is consistent with schizophrenia's likely significant pathophysiological heterogeneity. The overall enrichment of immune-related genes among those differentially expressed by affection status is consistent with hypothesized immune contributions to schizophrenia risk. The observed differential expression of extended major histocompatibility complex (xMHC) region histones (HIST1H2BD, HIST1H2BC, HIST1H2BH, HIST1H2BG and HIST1H4K) converges with the genetic evidence from GWAS, which find the xMHC to be the most significant susceptibility locus. Among the differentially expressed immune-related genes, B3GNT2 is implicated in autoimmune disorders previously tied to schizophrenia risk (rheumatoid arthritis and Graves' disease), and DICER1 is pivotal in miRNA processing potentially linking to miRNA alterations in schizophrenia (e.g. MIR137, the second strongest GWAS finding). Our analysis provides novel candidate genes for further study to assess their potential contribution to schizophrenia.

Finite element method for finite-size scaling in quantum mechanics.

We combined the finite-size scaling method with the finite element method to provide a systematic procedure for obtaining quantum critical parameters for a quantum system. We present results for the Yukawa potential solved with the finite element approach. The finite-size scaling approach was then used to find the critical parameters of the system. The critical values lambda c, alpha, and nu were found to be 0.83990345, 2.0002, and 1.002, respectively, for l = 0. These results compare well with the theoretically exact values for alpha and nu and with the best numerical estimations for lambda c. The finite element method is general and can be extended to larger systems.

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.

Open chromatin dynamics reveals stage-specific transcriptional networks in hiPSC-based neurodevelopmental model.

Chromatin accessibility to transcription factors (TFs) strongly influences gene transcription and cell differentiation. However, a mechanistic understanding of the transcriptional control during the neuronal differentiation of human induced pluripotent stem cells (hiPSCs), a promising cellular model for mental disorders, remains elusive. Here, we carried out additional analyses on our recently published open chromatin regions (OCRs) profiling at different stages of hiPSC neuronal differentiation. We found that the dynamic changes of OCR during neuronal differentiation highlighted cell stage-specific gene networks, and the chromatin accessibility at the core promoter region of a gene correlates with the corresponding transcript abundance. Within the cell stage-specific OCRs, we identified the binding of cell stage-specific TFs and observed a lag of a neuronal TF binding behind the mRNA expression of the corresponding TF. Interestingly, binding footprints of NEUROD1 and NEUROG2, both of which induce high efficient conversion of hiPSCs to glutamatergic neurons, were among those most enriched in the relatively mature neurons. Furthermore, TF network analysis showed that both NEUROD1 and NEUROG2 were present in the same core TF network specific to more mature neurons, suggesting a pivotal mechanism of epigenetic control of neuronal differentiation and maturation. Our study provides novel insights into the epigenetic control of glutamatergic neurogenesis in the context of TF networks, which may be instrumental to improving hiPSC modeling of neuropsychiatric disorders.

Open Chromatin Profiling in hiPSC-Derived Neurons Prioritizes Functional Noncoding Psychiatric Risk Variants and Highlights Neurodevelopmental Loci.

Most disease variants lie within noncoding genomic regions, making their functional interpretation challenging. Because chromatin openness strongly influences transcriptional activity, we hypothesized that cell-type-specific open chromatin regions (OCRs) might highlight disease-relevant noncoding sequences. To investigate, we mapped global OCRs in neurons differentiating from hiPSCs, a cellular model for studying neurodevelopmental disorders such as schizophrenia (SZ). We found that the OCRs are highly dynamic and can stratify GWAS-implicated SZ risk variants. Of the more than 3,500 SZ-associated variants analyzed, we prioritized ∼100 putatively functional ones located in neuronal OCRs, including rs1198588, at a leading risk locus flanking MIR137. Excitatory neurons derived from hiPSCs with CRISPR/Cas9-edited rs1198588 or a rare proximally located SZ risk variant showed altered MIR137 expression, dendrite arborization, and synapse maturation. Our study shows that noncoding disease variants in OCRs can affect neurodevelopment, and that analysis of open chromatin regions can help prioritize functionally relevant noncoding variants identified by GWAS.

Genome-wide survey of interindividual differences of RNA stability in human lymphoblastoid cell lines.

The extent to which RNA stability differs between individuals and its contribution to the interindividual expression variation remain unknown. We conducted a genome-wide analysis of RNA stability in seven human HapMap lymphoblastoid cell lines (LCLs) and analyzed the effect of DNA sequence variation on RNA half-life differences. Twenty-six percent of the expressed genes exhibited RNA half-life differences between LCLs at a false discovery rate (FDR) < 0.05, which accounted for ~ 37% of the gene expression differences between individuals. Nonsense polymorphisms were associated with reduced RNA half-lives. In genes presenting interindividual RNA half-life differences, higher coding GC3 contents (G and C percentages at the third-codon positions) were correlated with increased RNA half-life. Consistently, G and C alleles of single nucleotide polymorphisms (SNPs) in protein coding sequences were associated with enhanced RNA stability. These results suggest widespread interindividual differences in RNA stability related to DNA sequence and composition variation.