An Integrative Genomic Study Implicates the Postsynaptic Density in the Pathogenesis of Bipolar Disorder

Akula, Nirmala; Wendland, Jens R.; Choi, Kwang Ho; McMahon, Francis J.

doi:10.1038/npp.2015.218

Cited by 29 publications

(25 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Gene set expression studies have reproducibly implicated a few key functions in particular disorders, but the core processes that are common across diagnostic groups and brain regions are not well established. Most expression studies of functionally related gene sets in postmortem brains have focused on a single brain region 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 and/or a single disorder. 6 , 7 , 9 , 13 …”

Section: Introductionmentioning

confidence: 99%

Consistently altered expression of gene sets in postmortem brains of individuals with major psychiatric disorders

Darby¹,

Yolken²,

Sabunciyan³

2016

Transl Psychiatry

View full text Add to dashboard Cite

The measurement of gene expression in postmortem brain is an important tool for understanding the pathogenesis of serious psychiatric disorders. We hypothesized that major molecular deficits associated with psychiatric disease would affect the entire brain, and such deficits may be shared across disorders. We performed RNA sequencing and quantified gene expression in the hippocampus of 100 brains in the Stanley Array Collection followed by replication in the orbitofrontal cortex of 57 brains in the Stanley Neuropathology Consortium. We then identified genes and canonical pathway gene sets with significantly altered expression in schizophrenia and bipolar disorder in the hippocampus and in schizophrenia, bipolar disorder and major depression in the orbitofrontal cortex. Although expression of individual genes varied, gene sets were significantly enriched in both of the brain regions, and many of these were consistent across diagnostic groups. Further examination of core gene sets with consistently increased or decreased expression in both of the brain regions and across target disorders revealed that ribosomal genes are overexpressed while genes involved in neuronal processes, GABAergic signaling, endocytosis and antigen processing have predominantly decreased expression in affected individuals compared to controls without a psychiatric disorder. Our results highlight pathways of central importance to psychiatric health and emphasize messenger RNA processing and protein synthesis as potential therapeutic targets for all three of the disorders.

show abstract

Section: Introductionmentioning

confidence: 99%

Consistently altered expression of gene sets in postmortem brains of individuals with major psychiatric disorders

Darby¹,

Yolken²,

Sabunciyan³

2016

Transl Psychiatry

View full text Add to dashboard Cite

show abstract

“…To reveal whether Sherlock-identified risk genes in the discovery stage (corrected P < 0.05: N = 147 genes; raw P < 0.05: N = 2064 genes) were significantly overlapped with genes identified from Sherlock validation analysis (corrected P < 0.05: N = 98 genes; raw P < 0.05: N = 2031 genes) or MAGMA analysis (corrected P < 0.05: N = 1106 genes), respectively, we conducted a computer-based permutation analysis [32]. For this permutation analysis, we randomly selected the number of genes as same as significantly identified genes from background genes for 100,000 times and documented the overlapped rate with genes from the Sherlock discovery stage.…”

Section: Computer-based Permutation Analysismentioning

confidence: 99%

Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes

Zhai

Shao

et al. 2020

Bioscience Reports

View full text Add to dashboard Cite

In recent years, multiple genome-wide association studies (GWAS) have identified numerous susceptibility variants and risk genes that demonstrate significant associations with bone mineral density (BMD). However, exploring how these genetic variants contribute risk to BMD remains a major challenge. We systematically integrated two independent expression quantitative trait loci (eQTL) data (N = 1890) and GWAS summary statistical data of BMD (N = 142,487) using Sherlock integrative analysis to reveal whether expression-associated variants confer risk to BMD. By using Sherlock integrative analysis and MAGMA gene-based analysis, we found there existed 36 promising genes, for example, PPP1CB, XBP1, and FDFT1, whose expression alterations may contribute susceptibility to BMD. Through a protein–protein interaction (PPI) network analysis, we further prioritized the PPP1CB as a hub gene that has interactions with predicted genes and BMD-associated genes. Two eSNPs of rs9309664 (PeQTL = 1.42 × 10−17 and PGWAS = 1.40 × 10−11) and rs7475 (PeQTL = 2.10 × 10−6 and PGWAS = 1.70 × 10−7) in PPP1CB were identified to be significantly associated with BMD risk. Consistently, differential gene expression analysis found that the PPP1CB gene showed significantly higher expression in low BMD samples than that in high BMD samples based on two independent expression datasets (P = 0.0026 and P = 0.043, respectively). Together, we provide a convergent line of evidence to support that the PPP1CB gene involves in the etiology of osteoporosis.

show abstract

“…The use of the TOM transformation makes it possible to interpret the resulting clusters as network modules that possess the scale‐free property. In post‐mortem human brain tissue, analysis of gene expression data with WGCNA—reducing complexity through encouraging scale‐free network behavior of the gene expression relationships—has already been key to demonstrating alterations in patterns of gene expression associated with Alzheimer's disease [Sekar et al, ], bipolar disorder [Akula et al, ], and altered methylation patterns indicating neuronal differentiation in schizophrenia [Maschietto et al, ].…”

Section: Introductionmentioning

confidence: 99%

Gene networks show associations with seed region connectivity

Forest

Iturria-Medina

Goldman

et al. 2017

Human Brain Mapping

View full text Add to dashboard Cite

Primary patterns in adult brain connectivity are established during development by coordinated networks of transiently expressed genes; however, neural networks remain malleable throughout life. The present study hypothesizes that structural connectivity from key seed regions may induce effects on their connected targets, which are reflected in gene expression at those targeted regions. To test this hypothesis, analyses were performed on data from two brains from the Allen Human Brain Atlas, for which both gene expression and DW-MRI were available. Structural connectivity was estimated from the DW-MRI data and an approach motivated by network topology, that is, weighted gene coexpression network analysis (WGCNA), was used to cluster genes with similar patterns of expression across the brain. Group exponential lasso models were then used to predict gene cluster expression summaries as a function of seed region structural connectivity patterns. In several gene clusters, brain regions located in the brain stem, diencephalon, and hippocampal formation were identified that have significant predictive power for these expression summaries. These connectivity-associated clusters are enriched in genes associated with synaptic signaling and brain plasticity. Furthermore, using seed region based connectivity provides a novel perspective in understanding relationships between gene expression and connectivity. Hum Brain Mapp 38:3126-3140, 2017. © 2017 Wiley Periodicals, Inc.

show abstract

An Integrative Genomic Study Implicates the Postsynaptic Density in the Pathogenesis of Bipolar Disorder

Cited by 29 publications

References 47 publications

Consistently altered expression of gene sets in postmortem brains of individuals with major psychiatric disorders

Consistently altered expression of gene sets in postmortem brains of individuals with major psychiatric disorders

Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes

Gene networks show associations with seed region connectivity

Contact Info

Product

Resources

About