Serum cortisol as a predictor for posttraumatic stress disorder symptoms in post-myocardial infarction patients

Schaffter, Nadja; Ledermann, Katharina; Pazhenkottil, Aju P.; Barth, Jürgen; Schnyder, Ulrich; Znoj, Hansjörg; Schmid, Jean‐Paul; Meister-Langraf, Rebecca E.; Känel, Roland von; Princip, Mary

doi:10.1016/j.jad.2021.05.065

Cited by 9 publications

(2 citation statements)

References 42 publications

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“…As our preliminary experiments found a strong genome-wide effect of HCort treatment, we used HCort treatment for neuronal glucocorticoid exposure. Serum measurements of cortisol in patients with and without PTSD have been found to average around 492.52 nM 90 , intermediate between our 100 and 1,000 nM doses. HCort treatment medium was prepared by first dissolving HCort (Sigma-Aldrich, catalog no.…”

Section: Methodscontrasting

confidence: 55%

Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression

Seah

Breen²,

Rusielewicz³

et al. 2022

Nat Neurosci

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Post-traumatic stress disorder (PTSD) can develop following severe trauma, but the extent to which genetic and environmental risk factors contribute to individual clinical outcomes is unknown. Here, we compared transcriptional responses to hydrocortisone exposure in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons and peripheral blood mononuclear cells (PBMCs) from combat veterans with PTSD (n = 19 hiPSC and n = 20 PBMC donors) and controls (n = 20 hiPSC and n = 20 PBMC donors). In neurons only, we observed diagnosis-specific glucocorticoid-induced changes in gene expression corresponding with PTSD-specific transcriptomic patterns found in human postmortem brains. We observed glucocorticoid hypersensitivity in PTSD neurons, and identified genes that contribute to this PTSD-dependent glucocorticoid response. We find evidence of a coregulated network of transcription factors that mediates glucocorticoid hyper-responsivity in PTSD. These findings suggest that induced neurons represent a platform for examining the molecular mechanisms underlying PTSD, identifying biomarkers of stress response, and conducting drug screening to identify new therapeutics.

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Section: Methodscontrasting

confidence: 55%

Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression

Seah

Breen²,

Rusielewicz³

et al. 2022

Nat Neurosci

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show abstract

“…A previous study has shown that the symptoms of PTSD in patients with AMI may be related to the patient's age, gender, and personality characteristics (8). Hippocampal damage, serum cortisol, C-reactive protein are predictors of PTSD symptoms (9)(10)(11). However, there are currently no guidelines or risk prediction models to guide clinical personnel in reducing or preventing PTSD symptoms in patients with AMI.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a risk prediction model for post-traumatic stress disorder symptoms in patients with acute myocardial infarction in China

Cui¹,

Sui²,

Zang³

et al. 2022

Ann Palliat Med

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Background: At present, there are many influencing factors of post-traumatic stress disorder (PTSD) symptoms in patients with acute myocardial infarction (AMI), but based on this, there are few studies on the risk prediction model of PTSD symptoms. The aim of this study was to investigate the risk factors of PTSD symptoms in patients with AMI and to construct a risk prediction model. Methods: From April 2021 to March 2022, 287 patients were enrolled from a hospital in Shandong Province, China. According to the PTSD Checklist (PCL-C) scores 30 days after discharge, the participants were divided into a PTSD symptoms group (92 cases) and a non-PTSD symptoms group (195 cases). The demographic data, disease factors, treatment factors, and laboratory examination indicators were compared between the 2 groups; independent risk factors were screened out, and a risk prediction model was constructed by logistic regression. Area under the curve (AUC) was used as the internal verification of the model prediction. From April 2022 to June 2022, 72 patients with AMI in a hospital in Shandong Province were selected. PCL-C data were collected 30 days after discharge, and finally external validation of the model was performed. Results: Five factors, including gender [odds ratio (OR) =3.325], diabetes history (OR =2.292), creatine kinase isozyme (OR =1.046), insomnia score (OR =2.045), and fear of disease progression score (OR =1.126) were included to construct the risk prediction model. According to the Hosmer-Lemeshow test, P=0.785.The AUC was 0.910, the maximum value of Youden index was 0.751, the sensitivity was 0.870, the specificity was 0.881, and the accuracy rate of practical application was 67.64%. Conclusions:The risk prediction model of PTSD symptoms in patients with AMI established in this study is consistent and effective. It can provide a reference for clinical assessment of PTSD symptoms risk in patients with AMI.

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Associating Aversive Task Exposure with Pharmacological Intervention to Model Traumatic Memories in Laboratory Rodents

2023

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Serum cortisol as a predictor for posttraumatic stress disorder symptoms in post-myocardial infarction patients

Cited by 9 publications

References 42 publications

Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression

Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression

Development and validation of a risk prediction model for post-traumatic stress disorder symptoms in patients with acute myocardial infarction in China

Associating Aversive Task Exposure with Pharmacological Intervention to Model Traumatic Memories in Laboratory Rodents

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