Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

Arloth, Janine; Bogdan, Ryan; Weber, Peter; Frishman, Goar; Menke, Andreas; Wagner, Klaus V.; Balsevich, Georgia; Schmidt, Mathias; Karbalai, Nazanin; Czamara, Darina; Altmann, André; Trümbach, Dietrich; Wurst, Wolfgang; Mehta, Divya; Uhr, Manfred; Klengel, Torsten; Erhardt, Angelika; Carey, Caitlin E.; Conley, Emily Drabant; Ruepp, Andreas; Müller‐Myhsok, Bertram; Hariri, Ahmad R.; Binder, Elisabeth B.

doi:10.1016/j.neuron.2015.05.034

Cited by 118 publications

(136 citation statements)

References 49 publications

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“…Many of the identified biological processes have previously been implicated in depression (Arloth et al, 2015; Chang et al, 2014; Ding et al, 2015; Fabbri and Serretti, 2015; Kang et al, 2012; Philip et al, 2010; Sequeira et al, 2009; Tham et al, 2011; NPAS of PGI, 2015). GOs enriched in the susceptible network modules included microtubule cytoskeleton (Lightcyan; p=8.8×10 −20 9.85x), extracellular matrix (Lightyellow; p=2.9×10 −15 , 6.36x), synaptic transmission (Yellow; p=4.8 × 10 −14 3.7x), cell-cell signaling (Midnightblue; p=9.0×10 −9 , 3.16x), transcriptional activation (Purple; p=1.1×10 −6 , 3.1x) and NF-κB signaling (Red; p=6.3×10 −4 , 7.13x).…”

Section: Resultsmentioning

confidence: 99%

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility

Bagot

Cates

Purushothaman

et al. 2016

Neuron

294

339

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Summary Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here we performed RNA-sequencing on 4 brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery.

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Section: Resultsmentioning

confidence: 99%

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility

Bagot

Cates

Purushothaman

et al. 2016

Neuron

294

339

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“…For example, imaging genetics could use GWAS-based results from psychiatric genetics to prioritize variants within a given system or systems. Using this framework, a recent study discovered common genetic moderators of the transcriptome response to stress hormone activation, that were also associated with depression (8). A PRS/BIMPS polygenic profile of variants associated with both stress hormone transcriptome response and depression was associated with overgeneralized amygdala responsiveness, providing a putative neural mechanism through which the transcriptome response to stress may influence depression risk (8).…”

Section: Polygenic Approachesmentioning

confidence: 99%

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Bogdan¹,

Salmeron

Carey³

et al. 2017

Biological Psychiatry

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147

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Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions including the development of consortia and large scale data collection projects as well as the use of novel methods (e.g., polygenic approaches, machine learning), which enhance the quality of imaging genetic studies, but also introduce new challenges. Here, we critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in its translational and integrative potential with other research approaches (e.g., non-human animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology.

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“…Further, it will be important to understand the molecular and neural mechanisms through which such effects emerge (e.g. epigenetic modification (94), stress-related gene expression (95)). Indeed, such mechanistic understanding will facilitate the development of treatments that may target links within the etiologic chain.…”

Section: Future Directionsmentioning

confidence: 99%

Genetic and Environmental Factors Associated with Cannabis Involvement

2016

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Approximately 50-70% of the variation in cannabis use and use disorders can be attributed to heritable factors. For cannabis use, the remaining variance can be parsed in to familial and person-specific environmental factors while for use disorders, only the latter contribute. While numerous candidate gene studies have identified the role of common variation influencing liability to cannabis involvement, replication has been elusive. To date, no genomewide association study has been sufficiently powered to identify significant loci. Despite this, studies adopting polygenic techniques and integrating genetic variation with neural phenotypes and measures of environmental risk, such as childhood adversity, are providing promising new leads. It is likely that the small effect sizes associated with variants related to cannabis involvement will only be robustly identified in substantially larger samples. Results of such large-scale efforts will provide valuable single variant targets for translational research in neurogenetic, pharmacogenetic and non-human animal models as well as polygenic risk indices that can be used to explore a host of other genetic hypotheses related to cannabis use and misuse.

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Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

Cited by 118 publications

References 49 publications

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Genetic and Environmental Factors Associated with Cannabis Involvement

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