Additional file 1: Table S1. of Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling

Location of epigenetic clock CpGs in relation to the nearest glucocorticoid response element (as shown by within GR ChIP-Seq peaks in a lymphoblastoid cell line) and their methylation changes in response to the glucocorticoid receptor agonist dexamethasone. (DEX). (XLSX 68 kb

Additional file 1: of Correction to: Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling

Location of epigenetic clock CpGs in relation to the nearest glucocorticoid response element (as shown by within GR ChIP-Seq peaks in a lymphoblastoid cell line) and their methylation changes in response to the glucocorticoid receptor agonist dexamethasone. (XLSX 69 kb

Additional file 3: Table S3. of Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling

WebGestalt Disease enrichment analysis of the set of unique DEX-regulated genes (n = 139) with TSS near epigenetic clock CpGs. For the primary analysis, we used as reference the set of genes expressed above background in our peripheral blood gene expression arrays. This analysis was repeated using a more condensed background comprised only of the genes neighboring 21 K CpGs that showed DEX-induced mRNA expression changes (n = 5,443). While this post-hoc analysis yielded no statistically significant results after correction for multiple testing (P values presented in the last column), the top 10 diseases were very similar (with higher but nominally significant P values for the top three hits) with the analysis using the broader reference set of genes. (XLSX 10 kb

Additional file 2: Table S2. of Lifetime stress accelerates epigenetic aging in an urban, African American cohort: relevance of glucocorticoid signaling

Annotation of genes with transcription start sites (TSS) near epigenetic clock CpGs and their expression changes in response to DEX. Gene annotation was based on [43]. (XLSX 26 kb

Flowchart for the entire experimental procedure.

<p>Summary figure illustrating the sequential steps of experiments and analyses applied in this study, indicating the experimental groups and group sizes for each condition. CORT, corticosterone; QC, quality control.</p

Enrichment of dexamethasone-regulated genes.

<p>Histogram of 100,000 random samples indicates that paroxetine response genes show higher overlap with dex-regulated genes than expected by chance. The overlap between differential microarray probes from paroxetine-response and dex-regulated microarrays is 134 and this threshold is indicated as a vertical red dashed line. In this simulation, on average, 115 probes do overlap by chance and in 70 samples, the random overlap is higher than the tested one. All raw data for Fig 6 are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002690#pbio.2002690.s001" target="_blank">S1 Data</a>. dex, dexamethasone.</p

Classification features selected from differential gene expression in a mouse model for antidepressant treatment response are informative for treatment response in a human gene expression data set.

<p>Histogram shows the distribution of prediction accuracy over 1,000 simulated classification models that were computed with randomly chosen gene expression probe sets from human gene expression data (median prediction accuracy = 69.77%). The red dashed line marks the observed prediction accuracy (76.74%) when using our informed feature selection to build classifiers. Because only 25 of the randomly chosen feature sets yield equal or better classification results, the predictive ability of our features selected from the presented mouse model is significantly greater than expected by chance (<i>p</i> = 0.026). All raw data for Fig 5 are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002690#pbio.2002690.s001" target="_blank">S1 Data</a>.</p

Murine approach modeling heterogeneity of treatment outcome in the FST.

<p>This figure illustrates the underlying hypothesis: in a large number of animals that are treated with an antidepressant, animals are stratified into subgroups of extremes according to their time-floating behavior. To allow for the distinction of effects truly related to the phenomenon of response (and not treatment per se), a second group of animals is treated with a vehicle under identical conditions. FST, forced swim test.</p

A 14-day paroxetine treatment significantly reduces depression-like behavior in the FST.

<p>(A) Paroxetine-treated animals showed a reduction in time floating compared to vehicle-treated animals. (B) Paroxetine significantly increased active coping strategies, i.e., time struggling, compared to vehicle-treated animals. (C) Identification of different responder groups according to their performance in the FST. Animals indicated in the red squares are referred as good and poor treatment responders. Animals that showed a very high time floating represent the poor treatment responder, whereas animals that showed a very low time floating represent the good treatment responder. Animals indicated in the dotted-line square represent internal control groups. Animals within the vehicle-treated group served as a vehicle-treated control group. * indicates significant difference between the vehicle-treated control group and the paroxetine-treated group, <i>p</i> < 0.000. All raw data for Fig 3 are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002690#pbio.2002690.s002" target="_blank">S2 Data</a>. FST, forced swim test.</p

Differential gene expression in animals stratified for behavioral treatment response to chronic paroxetine treatment.

<p>(A) Volcano plot showing results from blood samples. The biological effect size (difference in expression) is plotted against statistical significance (as negative log 10 transformed values of the FDR-based <i>q</i>-value). Regarded as significantly regulated, 259 probes with <i>q</i>-values < 0.1 are colored according to their difference in expression. (B) Heat map comparing patterns of differential gene expression in blood and prefrontal cortex. Each row in the plot represents the difference in expression of 1 microarray probe between poor and good responders in both blood and prefrontal cortex. The array probes are ordered according to agglomerative hierarchical clustering, but no large common gene regulation patterns are revealed between the 2 tissues. Scale for color coding difference in expression is identical for (A) and (B). All raw data for Fig 4 are available in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002690#pbio.2002690.s001" target="_blank">S1 Data</a>. FDR, false discovery rate.</p