A large-scale genome-wide gene expression analysis in peripheral blood identifies very few differentially expressed genes related to antidepressant treatment and response in patients with major depressive disorder

Nøhr, Anne Krogh; Lindow, Morten; Forsingdal, Annika; Demharter, Samuel; Nielsen, Troels Tolstrup; Buller, R.; Moltke, Ida; Vitezic, Morana; Albrechtsen, Anders

doi:10.1038/s41386-021-01002-9

Cited by 9 publications

(8 citation statements)

References 40 publications

(56 reference statements)

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“…Investigating gene expression of all participants, visual inspection of the PCA revealed no obvious grouping of samples ( Supplementary Figure S5 ). This is in line with rather subtle gene expression changes that one may expect in blood in the context of mental disorders ( 56 , 57 ). Analyzing DGE using DESeq2 ( 43 ), 13 significantly (FDR-corrected p ≤ 0.1 for multiple correction) differentially expressed genes (DEGs) were identified which had a |l2fc| ≥ 0.3 in SAD condition compared to healthy individuals without SAD ( Figure 1A ; Supplementary Table S4 ), while no significant differences in expression were identified in ELA condition compared to individuals without the experience of ELA ( Supplementary Table S5 ).…”

Section: Resultssupporting

confidence: 70%

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

et al. 2023

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Social anxiety disorder (SAD) is a psychiatric disorder characterized by severe fear in social situations and avoidance of these. Multiple genetic as well as environmental factors contribute to the etiopathology of SAD. One of the main risk factors for SAD is stress, especially during early periods of life (early life adversity; ELA). ELA leads to structural and regulatory alterations contributing to disease vulnerability. This includes the dysregulation of the immune response. However, the molecular link between ELA and the risk for SAD in adulthood remains largely unclear. Evidence is emerging that long-lasting changes of gene expression patterns play an important role in the biological mechanisms linking ELA and SAD. Therefore, we conducted a transcriptome study of SAD and ELA performing RNA sequencing in peripheral blood samples. Analyzing differential gene expression between individuals suffering from SAD with high or low levels of ELA and healthy individuals with high or low levels of ELA, 13 significantly differentially expressed genes (DEGs) were identified with respect to SAD while no significant differences in expression were identified with respect to ELA. The most significantly expressed gene was MAPK3 (p = 0.003) being upregulated in the SAD group compared to control individuals. In contrary, weighted gene co-expression network analysis (WGCNA) identified only modules significantly associated with ELA (p ≤ 0.05), not with SAD. Furthermore, analyzing interaction networks of the genes from the ELA-associated modules and the SAD-related MAPK3 revealed complex interactions of those genes. Gene functional enrichment analyses indicate a role of signal transduction pathways as well as inflammatory responses supporting an involvement of the immune system in the association of ELA and SAD. In conclusion, we did not identify a direct molecular link between ELA and adult SAD by transcriptional changes. However, our data indicate an indirect association of ELA and SAD mediated by the interaction of genes involved in immune-related signal transduction.

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Section: Resultssupporting

confidence: 70%

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

et al. 2023

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“…Investigating gene expression of all participants, visual inspection of the PCA revealed no obvious grouping of samples (Fig S5). This is in line with rather subtle gene expression changes that one may expect in blood in the context of mental disorders [51,52]. Analyzing differential gene expression using DESeq2 [39], 13 significantly (FDR-corrected p ≤ 0.1) differentially expressed genes (DEGs) were identified which had a |l2fc| ≥ 0.3 with respect to SAD (Fig.…”

Section: Differential Gene Expression With Respect To Sad But Not Elasupporting

confidence: 62%

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

Edelmann

Wiegand

Hentrich

et al. 2022

Preprint

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Social anxiety disorder (SAD) is a psychiatric disorder characterized by severe fear in social situations and avoidance of these. Multiple genetic as well as environmental factors contribute to the etiopathology of SAD. One of the main risk factors for SAD is stress, especially during early periods of life (early life adversity; ELA). ELA leads to structural and regulatory alterations contributing to disease vulnerability. This includes the dysregulation of the immune response. However, the molecular link between ELA and the risk for SAD in adulthood remain largely unclear. Evidence is emerging that long-lasting changes of gene expression patterns play an important role in the biological mechanisms linking ELA and SAD. Therefore, we performed a transcriptome study of SAD and ELA using RNA sequencing. Analyzing differential gene expression, 13 significantly differentially expressed genes (DEGs) were identified with respect to SAD whilst no significant differences in expression were identified with respect to ELA. The most significantly expressed gene was MAPK3 being upregulated in the SAD group compared to control individuals. In contrary, weighted gene co-expression network analyses (WGCNA) identified only modules significantly associated with ELA, not with SAD. Furthermore, analyzing interaction networks of the genes from the ELA-associated modules and the SAD-related MAPK3 ) revealed complex interactions of those genes. Gene functional enrichment analyses indicate a role of signal transduction pathways as well as inflammatory responses supporting an involvement of the immune system in the association of ELA and SAD. In conclusion, we did not identify a direct molecular link between ELA and adult SAD by transcriptional changes. However, our data indicate an indirect association of ELA and SAD mediated by the interaction of genes involved in immune-related signal transduction.

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“…This study did include multiple limitations that should be addressed to better understand antidepressant effectiveness. Only two studies provided gene expression data for responders and non-responders prior to treatment, so it is not possible to derive strong inferences for predictive markers of fluoxetine response; even large-scale patient studies have struggled to identify general predictive markers to this point(18,97). Only two patient cohorts were included in our meta-analyses: while other studies have been conducted in patients, they tend to focus on a small number of biomarkers or otherwise do not submit full expression data to GEO(18).…”

Section: Discussionmentioning

confidence: 99%

Gene expression signatures of response to fluoxetine treatment: systematic review and meta-analyses

Cooper,

Cowden,

Stanley

et al. 2024

Preprint

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BackgroundSelecting the best antidepressant for a patient with major depressive disorder (MDD) remains a challenge, and some have turned to genomic (and other ‘omic) data to identify an optimal therapy. In this work, we synthesized gene expression data for fluoxetine treatment in both human patients and rodent models, to better understand biological pathways affected by treatment, as well as those that may distinguish clinical or behavioral response.MethodsFollowing the PRISMA guidelines, we searched the Gene Expression Omnibus (GEO) for studies profiling humans or rodent models with treatment of the antidepressant fluoxetine, excluding those not done in the context of depression or anxiety, in an irrelevant tissue type, or with fewer than three samples per group. Included studies were systematically reanalyzed by differential expression analysis and Gene Set Enrichment Analysis (GSEA). Individual pathway and gene statistics were synthesized across studies by three p-value combination methods, and then corrected for multiple testing.ResultsOf the 74 data series that were screened, 20 were included: 18 in rodents, and two in tissue from human patients. Studies were highly heterogeneous in the comparisons of both treated vs. control samples and responders vs. non-responders, with 737 and 356 pathways, respectively, identified as significantly different between groups in at least one study. 19 pathways were identified as consistently different in responders vs. non-responders, including Toll Like Receptor (TLR) and other immune pathways. Signal transduction pathways were identified as consistently affected by fluoxetine treatment in depressed patients and rodent models.DiscussionThese meta-analyses confirm known pathways and provide new hints toward antidepressant resistance, but more work is needed. Most included studies involved rodent models, and both patient studies had small cohorts. Additional large-cohort studies applying additional ‘omics technologies are necessary to understand the intricacies and heterogeneity of antidepressant response.

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A large-scale genome-wide gene expression analysis in peripheral blood identifies very few differentially expressed genes related to antidepressant treatment and response in patients with major depressive disorder

Cited by 9 publications

References 40 publications

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

Gene expression signatures of response to fluoxetine treatment: systematic review and meta-analyses

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