Using 3D epigenomic maps of primary olfactory neuronal cells from living individuals to understand gene regulation

As part of PsychENCODE, we developed a three-dimensional (3D) epigenomic map of primary cultured neuronal cells derived from olfactory neuroepithelium (CNON). We mapped topologically associating domains and high-resolution chromatin interactions using Hi-C and identified regulatory elements using chromatin immunoprecipitation and nucleosome positioning assays. Using epigenomic datasets from biopsies of 63 living individuals, we found that epigenetic marks at distal regulatory elements are more variable than marks at proximal regulatory elements. By integrating genotype and metadata, we identified enhancers that have different levels corresponding to differences in genetic variation, gender, smoking, and schizophrenia. Motif searches revealed that many CNON enhancers are bound by neuronal-related transcription factors. Last, we combined 3D epigenomic maps and gene expression profiles to predict enhancer-target gene interactions on a genome-wide scale. This study not only provides a framework for understanding individual epigenetic variation using a primary cell model system but also contributes valuable data resources for epigenomic studies of neuronal epithelium

The PsychENCODE project

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders. This paper outlines the motivation and design of PsychENCODE

Genetic variants specific to aging-related verbal memory:Insights from GWASs in a population-based cohort

Verbal memory is typically studied using immediate recall (IR) and delayed recall (DR) scores, although DR is dependent on IR capability. Separating these components may be useful for deciphering the genetic variation in age-related memory abilities. This study was conducted to (a) construct individual trajectories in IR and independent aspects of delayed recall, or residualized-DR (rDR), across older adulthood; and (b) identify genetic markers that contribute to four estimated phenotypes: IR and rDR levels and changes after age 60. A cognitively intact sample (N = 20,650 with 125,164 observations) was drawn from the U.S. Health and Retirement Study, a nationally representative study of adults aged 50 and older. Mixed effects regression models were constructed using repeated measures from data collected every two years (1996-2012) to estimate level at age 60 and change in memory post-60 in IR and rDR. Genome-wide association scans (GWAS) were conducted in the genotypic subsample (N = 7,486) using ~1.2 million single nucleotide polymorphisms (SNPs). One SNP (rs2075650) in TOMM40 associated with rDR level at the genome-wide level (p = 5.0x10-08), an effect that replicated in an independent sample from the English Longitudinal Study on Ageing (N = 6,898 with 41,328 observations). Meta-analysis of rDR level confirmed the association (p = 5.0x10-11) and identified two others in TOMM40 (rs71352238 p = 1.0x10-10; rs157582 p = 7.0x10-09), and one in APOE (rs769449 p = 3.1 x10-12). Meta-analysis of IR change identified associations with three of the same SNPs in TOMM40 (rs157582 p = 8.3x10-10; rs71352238 p = 1.9x10-09) and APOE (rs769449 p = 2.2x10-08). Conditional analyses indicate GWAS signals on rDR level were driven by APOE, whereas signals on IR change were driven by TOMM40. Additionally, we found that TOMM40 had effects independent of APOE e4 on both phenotypes. Findings from this first U.S. population-based GWAS study conducted on both age-related immediate and delayed verbal memory merit continued examination in other samples and additional measures of verbal memory

Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia

Applying tissue-specific deconvolution of transcriptional networks to identify their master regulators (MRs) in neuropsychiatric disorders has been largely unexplored. Here, using two schizophrenia (SCZ) case-control RNA-seq datasets, one on postmortem dorsolateral prefrontal cortex (DLPFC) and another on cultured olfactory neuroepithelium, we deconvolved the transcriptional networks and identified TCF4 as a top candidate MR that may be dysregulated in SCZ. We validated TCF4 as a MR through enrichment analysis of TCF4-binding sites in induced pluripotent stem cell (hiPSC)-derived neurons and in neuroblastoma cells. We further validated the predicted TCF4 targets by knocking down TCF4 in hiPSC-derived neural progenitor cells (NPCs) and glutamatergic neurons (Glut_Ns). The perturbed TCF4 gene network in NPCs was more enriched for pathways involved in neuronal activity and SCZ-associated risk genes, compared to Glut_Ns. Our results suggest that TCF4 may serve as a MR of a gene network dysregulated in SCZ at early stages of neurodevelopment

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ

Strongest associated SNPs detected by GWASs in the HRS discovery sample and comparisons in the ELSA replication sample, for immediate recall level (IR-L) and change (IR-C) and residual delayed recall level (rDR-L) and change (rDR-C).

<p>Strongest associated SNPs detected by GWASs in the HRS discovery sample and comparisons in the ELSA replication sample, for immediate recall level (IR-L) and change (IR-C) and residual delayed recall level (rDR-L) and change (rDR-C).</p

Regional plots showing meta-analyses results for rDR-L.

<p>(A) Results with the top associated SNP in the <i>APOE</i> region labeled. Two conditional meta-analyses were performed for rDR-L, (B) estimating the association with the <i>APOE</i> SNP shown (rs769449), conditioning on the top <i>TOMM40</i> SNP (rs2075650); and (C) estimating the association with the <i>TOMM40</i> SNP shown (rs2075650), conditioning on the top <i>APOE</i> SNP (rs769449). The y-axis shows -log₁₀ P-values; x-axis shows position of genes on chromosome 19 with SNPs 400-kb in both directions of the SNP of interest. The diamond represents the top SNP of interest. The circles represent each genotyped SNP in this region; the circle color indicates pairwise linkage disequilibrium (LD) in relation to the top SNP (calculated from hg19/1000 Genomes Nov 2014 EUR). The solid (blue) line indicates the recombination rate.</p

Characteristics of HRS participants at the first assessment point, tested for immediate and delayed recall between 1996 and 2012, in the HRS full and Non-Hispanic White (NHW) genotypic samples.

<p>Characteristics of HRS participants at the first assessment point, tested for immediate and delayed recall between 1996 and 2012, in the HRS full and Non-Hispanic White (NHW) genotypic samples.</p

P-values for all 1,198,956 SNP associations from GWAS on the HRS genetic sample.

<p>(A) Level of Immediate Recall (IR-L); (B) Change in Immediate Recall (IR-C); (C) Level of Residualized Delayed Recall (rDR-L); (D) Change in Residualized Delayed Recall (rDR-C). For these figures, the upper (red) horizontal line demarcates the threshold of p = -log(5.0x10^-08) and the lower (blue) horizontal line demarcates p = -log(1x10^-05). SNPs are arranged by their chromosomal position (x-axis).</p