Methylomic and transcriptomic predictors of one-month exposure to cortisol in healthy individuals
| Autor: | Yian Lin, Gary S. Wand, Kendall Reitz, Kelly S. Benke, Mary E. McCaul, Richard S. Lee, Fayaz Seifuddin, Peter P. Zandi |
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| Rok vydání: | 2021 |
| Předmět: |
Adult
Male Adolescent Hydrocortisone Physiology Bisulfite sequencing Disease Bedtime Behavioral Neuroscience Young Adult Medicine Humans Saliva Endocrine and Autonomic Systems business.industry Area under the curve DNA Methylation Middle Aged Allostatic load Psychiatry and Mental health Neuropsychology and Physiological Psychology Differentially methylated regions Allostasis Cohort Biomarker (medicine) Female business Transcriptome Stress Psychological |
| Zdroj: | Stress (Amsterdam, Netherlands). 24(6) |
| ISSN: | 1607-8888 |
| Popis: | Allostatic load (AL) refers to the cumulative "wear and tear" on an organism throughout its lifetime. One of the primary contributing factors to AL is prolonged exposure to stress or its primary catabolic agent cortisol. Chronic exposure to stress or cortisol is associated with numerous diseases, including cardiovascular disease, metabolic disorders, and psychiatric disorders. Therefore, a molecular marker capable of integrating a past history of cortisol exposure would be of great utility for assessing disease risk. To this end, we recruited 87 healthy males and females of European ancestry between 18 and 60 years old, extracted genomic DNA and RNA from leukocytes, and implemented a gene-centric DNA enrichment method coupled with bisulfite sequencing and RNA-Seq of total RNA for the determination of genome-wide methylation and gene transcription, respectively. Sequencing data were analyzed against awakening and bedtime cortisol data to identify differentially methylated regions (DMRs) and CpGs (DMCs) and differentially expressed genes (DEGs). Six candidate DMCs (punadjusted < 0.005) and nine DEGs (punadjusted < 0.0005) were used to construct a prediction model that could capture past 30+ days of both bedtime and awakening cortisol levels. Utilizing a cross-validation approach, we obtained a regression coefficient of R2 = 0.308 for predicting continuous awakening cortisol and an area under the curve (AUC) = 0.753 for dichotomous (high vs. low tertile) awakening cortisol, and R2 = 0.224 and AUC = 0.723 for continuous and dichotomous bedtime cortisol levels, respectively. To our knowledge, the current study represents the first attempt to identify genome-wide predictors of cortisol exposure that utilizes both methylation and transcription targets. The utility of our approach needs to be replicated in an independent cohort of samples for which similar cortisol metrics are available. |
| Databáze: | OpenAIRE |
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