Mette A. Peters

Gene expression elucidates functional impact of polygenic risk for schizophrenia.

Over 100 genetic loci harbor schizophrenia-associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of people with schizophrenia (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ∼20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Altering expression of FURIN, TSNARE1 or CNTN4 changed neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yielded abnormal migration. Of 693 genes showing significant case-versus-control differential expression, their fold changes were ≤ 1.33, and an independent cohort yielded similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show that schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

A Genomic Scan of Families with Prostate Cancer Identifies Multiple Regions of Interest

A 10-cM genomewide scan of 94 families with hereditary prostate cancer, including 432 affected men, was used to identify regions of putative prostate cancer-susceptibility loci. There was an average of 3.6 affected, genotyped men per family, and an overall mean age at diagnosis of 65.4 years. A total of 50 families were classified as early onset (mean age at diagnosis <66 years), and 44 families were classified as later onset (mean age at diagnosis > or =66 years). When the entire data set is considered, regions of interest (LOD score > or =1.5) were identified on chromosomes 10, 12, and 14, with a dominant model of inheritance. Under a recessive model LOD scores > or =1.5 were found on chromosomes 1, 8, 10, and 16. Stratification by age at diagnosis highlighted a putative susceptibility locus on chromosome 11, among the later-onset families, with a LOD score of 3. 02 (recombination fraction 0) at marker ATA34E08. Overall, this genomic scan suggests that there are multiple prostate cancer loci responsible for the hereditary form of this common and complex disease and that stratification by a variety of factors will be required for identification of all relevant genes.

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.

Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

Common inflammatome gene signatures as well as disease‐specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co‐expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue‐specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response‐related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non‐drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

Genetic linkage analysis of prostate cancer families to Xq27-28.

Objectives: A recent linkage analysis of 360 families at high risk for prostate cancer identified the q27–28 region on chromosome X as the potential location of a gene involved in prostate cancer susceptibility. Here we report on linkage analysis at this putative HPCX locus in an independent set of 186 prostate cancer families participating in the Prostate Cancer Genetic Research Study (PROGRESS). Methods: DNA samples from these families were genotyped at 8 polymorphic markers spanning 14.3 cM of the HPCX region. Results: Two-point parametric analysis of the total data set resulted in positive lod scores at only two markers, DXS984 and DXS1193, with scores of 0.628 at a recombination fraction (θ) of 0.36 and 0.012 at θ = 0.48, respectively. The stratification of pedigrees according to the assumed mode of transmission increased the evidence of linkage at DXS984 in 81 families with no evidence of male-to-male transmission (lod = 1.062 at θ = 0.28). Conclusions: Although this analysis did not show statistically significant evidence for the linkage of prostate cancer susceptibility to Xq27–28, the results are consistent with a small percentage of families being linked to this region. The analysis further highlights difficulties in replicating linkage results in an etiologically heterogeneous, complexly inherited disease.

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimers disease. The Alzheimers disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state‐of‐the‐art in predicting cognitive outcomes in Alzheimers disease based on high dimensional, publicly available genetic and structural imaging data. This meta‐analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

Human whole genome genotype and transcriptome data for Alzheimer's and other neurodegenerative diseases.

Previous genome-wide association studies (GWAS), conducted by our group and others, have identified loci that harbor risk variants for neurodegenerative diseases, including Alzheimers disease (AD). Human disease variants are enriched for polymorphisms that affect gene expression, including some that are known to associate with expression changes in the brain. Postulating that many variants confer risk to neurodegenerative disease via transcriptional regulatory mechanisms, we have analyzed gene expression levels in the brain tissue of subjects with AD and related diseases. Herein, we describe our collective datasets comprised of GWAS data from 2,099 subjects; microarray gene expression data from 773 brain samples, 186 of which also have RNAseq; and an independent cohort of 556 brain samples with RNAseq. We expect that these datasets, which are available to all qualified researchers, will enable investigators to explore and identify transcriptional mechanisms contributing to neurodegenerative diseases.

Prostate cancer: simplicity to complexity

Prostate cancer is a complex disease to which a multitude of genetic and environmental factors contribute. Two new studies offer insights as to how the disease may arise and progress. The first describes mapping and cloning of a new candidate gene, ELAC2, whereas the second demonstrates how cooperation between Cdkn1b and Pten contribute to suppression of prostate tumors.

Large-Scale Identification of Common Trait and Disease Variants Affecting Gene Expression

Genome-wide association studies (GWASs) have identified a multitude of genetic loci involved with traits and diseases. However, it is often unclear which genes are affected in such loci and whether the associated genetic variants lead to increased or decreased gene function. To mitigate this, we integrated associations of common genetic variants in 57 GWASs with 24 studies of expression quantitative trait loci (eQTLs) from a broad range of tissues by using a Mendelian randomization approach. We discovered a total of 3,484 instances of gene-trait-associated changes in expression at a false-discovery rate < 0.05. These genes were often not closest to the genetic variant and were primarily identified in eQTLs derived from pathophysiologically relevant tissues. For instance, genes with expression changes associated with lipid traits were mostly identified in the liver, and those associated with cardiovascular disease were identified in arterial tissue. The affected genes additionally point to biological processes implicated in the interrogated traits, such as the interleukin-27 pathway in rheumatoid arthritis. Further, comparing trait-associated gene expression changes across traits suggests that pleiotropy is a widespread phenomenon and points to specific instances of both agonistic and antagonistic pleiotropy. For instance, expression of SNX19 and ABCB9 is positively correlated with both the risk of schizophrenia and educational attainment. To facilitate interpretation, we provide this lexicon of how common trait-associated genetic variants alter gene expression in various tissues as the online database GWAS2Genes.

Practical Guidelines for High-Resolution Epigenomic Profiling of Nucleosomal Histones in Postmortem Human Brain Tissue

BACKGROUND The nervous system may include more than 100 residue-specific posttranslational modifications of histones forming the nucleosome core that are often regulated in cell-type-specific manner. On a genome-wide scale, some of the histone posttranslational modification landscapes show significant overlap with the genetic risk architecture for several psychiatric disorders, fueling PsychENCODE and other large-scale efforts to comprehensively map neuronal and nonneuronal epigenomes in hundreds of specimens. However, practical guidelines for efficient generation of histone chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) datasets from postmortem brains are needed. METHODS Protocols and quality controls are given for the following: 1) extraction, purification, and NeuN neuronal marker immunotagging of nuclei from adult human cerebral cortex; 2) fluorescence-activated nuclei sorting; 3) preparation of chromatin by micrococcal nuclease digest; 4) ChIP for open chromatin-associated histone methylation and acetylation; and 5) generation and sequencing of ChIP-seq libraries. RESULTS We present a ChIP-seq pipeline for epigenome mapping in the neuronal and nonneuronal nuclei from the postmortem brain. This includes a stepwise system of quality controls and user-friendly data presentation platforms. CONCLUSIONS Our practical guidelines will be useful for projects aimed at histone posttranslational modification mapping in chromatin extracted from hundreds of postmortem brain samples in cell-type-specific manner.