Epigenetic basis of psychiatric disorders: a narrative review

2021 ◽  
Vol 20 ◽  
Author(s):  
Fabio Panariello ◽  
Giuseppe Fanelli ◽  
Chiara Fabbri ◽  
Anna Rita Atti ◽  
Diana De Ronchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Environmental Factors ◽  
Psychiatric Disorders ◽  
Genetic Variants ◽  
Neural Circuit ◽  
Expression Patterns ◽  
Brain Regions ◽  
Epigenetic Modifications ◽  
Cochrane Library ◽  
Specific Gene

Background: Psychiatric disorders are complex, multifactorial illnesses with a demonstrated biological component in their etiopathogenesis. Epigenetic modifications, through the modulation of DNA methylation, histone modifications and RNA interference, tune tissue-specific gene expression patterns and play a relevant role in the etiology of psychiatric illnesses. Objective: This review aims to discuss the epigenetic mechanisms involved in psychiatric disorders, their modulation by environmental factors and their interactions with genetic variants, in order to provide a comprehensive picture of their mutual crosstalk. Methods: In accordance with the PRISMA guidelines, systematic searches of Medline, EMBASE, PsycINFO, Web of Science, Scopus, and the Cochrane Library were conducted. Results: Exposure to environmental factors, such as poor socio-economic status, obstetric complications, migration, and early life stressors, may lead to stable changes in gene expression and neural circuit function, playing a role in the risk of psychiatric diseases. The most replicated genes involved by studies using different techniques are discussed. Increasing evidence indicates that these sustained abnormalities are maintained by epigenetic modifications in specific brain regions and they interact with genetic variants in determining the risk of psychiatric disorders. Conclusion: An increasing amount of evidence suggests that epigenetics plays a pivotal role in the etiopathogenesis of psychiatric disorders. New therapeutic approaches may work by reversing detrimental epigenetic changes that occurred during the lifespan.

scholarly journals Epigenetic signaling in psychiatric disorders: stress and depression

2014 ◽  
Vol 16 (3) ◽  
pp. 281-295 ◽  
Keyword(s):  
Environmental Factors ◽  
Psychiatric Disorders ◽  
Neural Circuit ◽  
Brain Regions ◽  
Transcriptional Dysregulation ◽  
Epigenetic Machinery ◽  
Multifactorial Disorders ◽  
As Stress ◽  
And Function ◽  
Circuit Function

Psychiatric disorders are complex multifactorial disorders involving chronic alterations in neural circuit structure and function. While genetic factors play a role in the etiology of disorders such as depression, addiction, and schizophrenia, relatively high rates of discordance among identical twins clearly point to the importance of additional factors. Environmental factors, such as stress, play a major role in the psychiatric disorders by inducing stable changes in gene expression, neural circuit function, and ultimately behavior. Insults at the developmental stage and in adulthood appear to induce distinct maladaptations. Increasing evidence indicates that these sustained abnormalities are maintained by epigenetic modifications in specific brain regions. Indeed, transcriptional dysregulation and associated aberrant epigenetic regulation is a unifying theme in psychiatric disorders. Aspects of depression can be modeled in animals by inducing disease-like states through environmental manipulations, and these studies can provide a more general understanding of epigenetic mechanisms in psychiatric disorders. Understanding how environmental factors recruit the epigenetic machinery in animal models is providing new insights into disease mechanisms in humans.

A Global Vista of the Epigenomic State of the Mouse Submandibular Gland

2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Control ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Submandibular Salivary Gland ◽  
Data Sets ◽  
Control Mechanisms ◽  
Chromatin Immunoprecipitation Sequencing

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

scholarly journals Enabling out-of-clinic human immunity studies via single-cell profiling of capillary blood

2020 ◽  
Author(s):  
Tatyana Dobreva ◽  
David Brown ◽  
Jong Hwee Park ◽  
Matt Thomson
Keyword(s):  
Gene Expression ◽  
Immune System ◽  
Environmental Factors ◽  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Capillary Blood ◽  
Specific Gene ◽  
Human Immune ◽  
Over Time

AbstractAn individual’s immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days.SummaryIncreasing evidence implicates the immune system in an overwhelming number of diseases, and distinct cell types play specific roles in their pathogenesis.1,2 Studies of peripheral blood have uncovered a wealth of associations between gene expression, environmental factors, disease risk, and therapeutic efficacy.4 For example, in rheumatoid arthritis, multiple mechanistic paths have been found that lead to disease, and gene expression of specific immune cell types can be used as a predictor of therapeutic non-response.12 Furthermore, vaccines, drugs, and chemotherapy have been shown to yield different efficacy based on time of administration, and such findings have been linked to the time-dependence of gene expression in downstream pathways.21,22,23 However, human immune studies of gene expression between individuals and across time remain limited to a few cell types or time points per subject, constraining our understanding of how networks of heterogeneous cells making up each individual’s immune system respond to adverse events and change over time.

scholarly journals To hum or not to hum: Neural transcriptome signature of courtship vocalization in a teleost fish

2020 ◽  
Author(s):  
Joel A. Tripp ◽  
Ni Y. Feng ◽  
Andrew H. Bass
Keyword(s):  
Gene Expression ◽  
Vocal Communication ◽  
Brain Regions ◽  
Vocal Behavior ◽  
Specific Gene ◽  
Motor Nucleus ◽  
Motor Behaviors ◽  
Behavioral States ◽  
Courtship Activity ◽  
Courtship Behaviors

AbstractFor many animal species, vocal communication is a critical social behavior, often a necessary component of reproductive success. In addition to the role of vocal behavior in social interactions, vocalizations are often demanding motor acts. Through understanding the genes involved in regulating and permitting vertebrate vocalization, we can better understand the mechanisms regulating vocal and, more broadly, motor behaviors. Here, we use RNA-sequencing to investigate neural gene expression underlying the performance of an extreme vocal behavior, the courtship hum of the plainfin midshipman fish (Porichthys notatus). Single hums can last up to two hours and may be repeated throughout an evening of courtship activity. We asked whether vocal behavioral states are associated with specific gene expression signatures in key brain regions that regulate vocalization by comparing transcript levels in humming versus non-humming males. We find that the circadian-related genes period3 and Clock are significantly upregulated in the vocal motor nucleus and preoptic area-anterior hypothalamus, respectively, in humming compared to non-humming males, indicating that internal circadian clocks may differ between these divergent behavioral states. In addition, we identify suites of differentially expressed genes related to synaptic transmission, ion channels and transport, hormone signaling, and metabolism and antioxidant activity that may permit or support humming behavior. These results underscore the importance of the known circadian control of midshipman humming and provide testable candidate genes for future studies of the neuroendocrine and motor control of energetically demanding courtship behaviors in midshipman fish and other vertebrate groups.

scholarly journals An integrative multi-omics approach in Sjögren’s Syndrome identifies novel genetic drivers with regulatory function and disease-specificity

2020 ◽  
Author(s):  
María Teruel ◽  
Guillermo Barturen ◽  
Manuel Martínez-Bueno ◽  
Miguel Barroso ◽  
Olivia Castelli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Sjögren’S Syndrome ◽  
Genetic Variants ◽  
Sjögren's Syndrome ◽  
Expression Patterns ◽  
Sjogren’S Syndrome ◽  
Sjogren's Syndrome ◽  
Regulatory Function ◽  
Sjögren‘S Syndrome

ABSTRACTPrimary Sjögren’s syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study we identified vast coordinated hypomethylation and overexpression effects, that also exhibit increased variability, in many already known IFN-regulated genes. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of novel genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified new genetic variants associated with SS that mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, DNA methylation, gene expression and SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

scholarly journals Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression

2019 ◽  
Vol 36 (3) ◽  
pp. 782-788 ◽  
Author(s):  
Jiebiao Wang ◽  
Bernie Devlin ◽  
Kathryn Roeder
Keyword(s):  
Gene Expression ◽  
Empirical Bayes ◽  
Brain Regions ◽  
Tissue Level ◽  
Supplementary Information ◽  
Specific Gene ◽  
Expression Data ◽  
Cell Type ◽  
Multiple Measurements ◽  
Cell Type Specific

Abstract Motivation Patterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects. Results Complementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g. multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL). Availability and implementation We implement this method as an R package MIND, hosted on https://github.com/randel/MIND. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Regional and cell-specific gene expression patterns during petal development.

1992 ◽  
Vol 4 (11) ◽  
pp. 1383-1404 ◽  
Author(s):  
G N Drews ◽  
T P Beals ◽  
A Q Bui ◽  
R B Goldberg
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Petal Development

scholarly journals Transcriptome Profiling of Adipose Tissue Reveals Depot-Specific Metabolic Alterations Among Patients with Colorectal Cancer

2019 ◽  
Vol 104 (11) ◽  
pp. 5225-5237 ◽  
Author(s):  
Mariam Haffa ◽  
Andreana N Holowatyj ◽  
Mario Kratz ◽  
Reka Toth ◽  
Axel Benner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Adipose Tissue ◽  
Large Scale ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Human Study ◽  
Subcutaneous Fat ◽  
Specific Gene ◽  
Adipose Tissue Depots

Abstract Context Adipose tissue inflammation and dysregulated energy homeostasis are key mechanisms linking obesity and cancer. Distinct adipose tissue depots strongly differ in their metabolic profiles; however, comprehensive studies of depot-specific perturbations among patients with cancer are lacking. Objective We compared transcriptome profiles of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) from patients with colorectal cancer and assessed the associations of different anthropometric measures with depot-specific gene expression. Design Whole transcriptomes of VAT and SAT were measured in 233 patients from the ColoCare Study, and visceral and subcutaneous fat area were quantified via CT. Results VAT compared with SAT showed elevated gene expression of cytokines, cell adhesion molecules, and key regulators of metabolic homeostasis. Increased fat area was associated with downregulated lipid and small molecule metabolism and upregulated inflammatory pathways in both compartments. Comparing these patterns between depots proved specific and more pronounced gene expression alterations in SAT and identified unique associations of integrins and lipid metabolism–related enzymes. VAT gene expression patterns that were associated with visceral fat area poorly overlapped with patterns associated with self-reported body mass index (BMI). However, subcutaneous fat area and BMI showed similar associations with SAT gene expression. Conclusions This large-scale human study demonstrates pronounced disparities between distinct adipose tissue depots and reveals that BMI poorly correlates with fat mass–associated changes in VAT. Taken together, these results provide crucial evidence for the necessity to differentiate between distinct adipose tissue depots for a correct characterization of gene expression profiles that may affect metabolic health of patients with colorectal cancer.

scholarly journals Limit cycle dynamics can guide the evolution of gene regulatory networks towards point attractors

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Stuart P. Wilson ◽  
Sebastian S. James ◽  
Daniel J. Whiteley ◽  
Leah A. Krubitzer
Keyword(s):  
Gene Expression ◽  
Limit Cycles ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Expression Patterns ◽  
Specific Gene ◽  
Boolean Models ◽  
A Genome ◽  
Order Of Magnitude ◽  
Accelerate Evolution

AbstractDevelopmental dynamics in Boolean models of gene networks self-organize, either into point attractors (stable repeating patterns of gene expression) or limit cycles (stable repeating sequences of patterns), depending on the network interactions specified by a genome of evolvable bits. Genome specifications for dynamics that can map specific gene expression patterns in early development onto specific point attractor patterns in later development are essentially impossible to discover by chance mutation alone, even for small networks. We show that selection for approximate mappings, dynamically maintained in the states comprising limit cycles, can accelerate evolution by at least an order of magnitude. These results suggest that self-organizing dynamics that occur within lifetimes can, in principle, guide natural selection across lifetimes.

Sign in / Sign up

Export Citation Format

Share Document