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Chu L, Liu S, Wu Y, Yang J, Qiao S, Zhou Y, Deng H, Li X, Shen Z. Hair levels of steroid, endocannabinoid, and the ratio biomarkers predict viral suppression among people living with HIV/AIDS in China. Clin Chim Acta 2022; 535:143-152. [PMID: 36041548 DOI: 10.1016/j.cca.2022.08.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Predicting viral suppression early is crucial to improving treatment outcomes among people living with HIV/AIDS (PLWH) in clinics. Viral suppression is affected by stress, making stress indicators a potential predictive factor. Most of previous studies used the self-report questionnaire as stress indicators, but there were great drawbacks due to its subjective. In contrast, end products of neuroendocrine systems such as hypothalamic-pituitaryadrenal (HPA) and hypothalamic-pituitary-gonadal (HPG) axes and endogenous cannabinoid system (ECS) that involved in regulating stress as objective stress indicators are urgently needed to predict viral suppression. Therefore, this study aimed to investigate whether neuroendocrine indictors can strongly predict viral suppression among PLWH in China. METHODS This cross-sectional study recruited 1198 PLWH on antiretroviral therapy (ART) in Guangxi, China. The concentrations of steroids (i.e., cortisol, cortisone, dehydroepiandrosterone, testosterone and progesterone) and endocannabinoids (i.e., N-arachidonoyl-ethanolamine and 1-arachidonyl glycerol) in hair were quantitated using the LC-APCI+-MS/MS method. To screen biomarkers that were used to predict viral suppression, association between hair biomarkers and viral suppression was examined by Mann-Whitney U test and partial correlation analyses. Receiver operating characteristic (ROC) curves and binary logistic regression based on the optimal classification threshold determined with ROC curves were used to estimate the prediction effects of the screened biomarkers on viral suppression (HIV-1 RNA < 200 copies/mL). RESULTS Hair levels of dehydroepiandrosterone (DHEA), and N-arachidonoyl-ethanolamine (AEA), and the cortisol to DHEA ratio exhibited significant intergroup differences (ps < 0.05) and were correlated with HIV viral load (ps < 0.05). Hair DHEA concentrations strongly predicted viral suppression, showing good classification performance (area under the ROC curve = 0.651, p < 0.01) and strong predictive utility (adjusted odd ratio = 2.324, 95 % confidence interval = 1.211-4.899, p < 0.05) with an optimal threshold of 10.5 pg/mg. A hair AEA concentration of 2.4 pg/mg was the optimal threshold for predicting viral suppression based on good classification performance (area under the ROC curve = 0.598, p < 0.05) and predictive power (adjusted odd ratio = 2.124, 95 % confidence interval = 1.045-4.244, p < 0.05). In hair levels of cortisol to DHEA, viral suppression was observed to be highly predictive, with a threshold of 10.5 pg/mg being optimal for classification (area under the ROC curve = 0.624, p < 0.05) and prediction (adjusted odd ratio = 0.421, 95 % confidence interval = 0.201-0.785, p < 0.05). CONCLUSION Hair levels of DHEA, and AEA and the cortisol to DHEA ratio were screened and verified to have significant predictive power with optimal thresholds for predicting viral suppression in a large-scale cohort. The data may provide new insights into predictors of successful virological outcomes and inform public health intervention and clinical practice to assist PLWH in achieving and sustaining viral suppression.
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Affiliation(s)
- Liuxi Chu
- Department of Brain and Learning Science, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China; Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing 210096, China; Institute of Child Development and Education, Research Center for Learning Science, Southeast University, Nanjing 210096, China
| | - Shuaifeng Liu
- Guangxi Center for Disease Control and Prevention, Nanning 530028, China
| | - Yan Wu
- Department of Brain and Learning Science, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China; Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing 210096, China; Institute of Child Development and Education, Research Center for Learning Science, Southeast University, Nanjing 210096, China
| | - Jin Yang
- Institute of Child Development and Education, Research Center for Learning Science, Southeast University, Nanjing 210096, China; School of Public Health, Southeast University, Nanjing 210009, China
| | - Shan Qiao
- Department of Health Promotion, Education and Behavior, South Carolina SmartState Center for Healthcare Quality (CHQ), Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Yuejiao Zhou
- Guangxi Center for Disease Control and Prevention, Nanning 530028, China
| | - Huihua Deng
- Department of Brain and Learning Science, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China; Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing 210096, China; Institute of Child Development and Education, Research Center for Learning Science, Southeast University, Nanjing 210096, China.
| | - Xiaoming Li
- Department of Health Promotion, Education and Behavior, South Carolina SmartState Center for Healthcare Quality (CHQ), Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA.
| | - Zhiyong Shen
- Guangxi Center for Disease Control and Prevention, Nanning 530028, China.
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Zhang Q, Li X, Qiao S, Liu S, Zhou Y, Shen Z. The relationship of hair glucocorticoid levels to immunological and virological outcomes in a large cohort of combination antiretroviral therapy treated people living with HIV. BMC Infect Dis 2022; 22:268. [PMID: 35307019 PMCID: PMC8935838 DOI: 10.1186/s12879-022-07257-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 03/07/2022] [Indexed: 12/02/2022] Open
Abstract
Background Existing literature mostly investigated the relationship of acute or short-term glucocorticoid exposure to HIV disease progression using cortisol levels in serum, saliva, or urine. Data are limited on the relationship of long-term glucocorticoid exposure to HIV disease progression. This study examined whether hair glucocorticoid levels, novel retrospective indicators of long-term glucocorticoid exposure, are associated with two common indicators of HIV disease progression (CD4 count and HIV viral load) among a large cohort of combination antiretroviral therapy treated Chinese people living with HIV (PLHIV). Methods A total of 1198 treated PLHIV provided hair samples for glucocorticoid (cortisol and cortisone) assay and completed a survey assessing sociodemographic, lifestyle, and HIV-related characteristics. Meanwhile, CD4 count and HIV viral load were retrieved from their medical records. Spearman correlation was used to examine the associations of hair cortisol and cortisone levels to continuous CD4 count and HIV viral load. Multivariate logistic regression was used to predict CD4 count < 500 cells/mm3. Results Both hair cortisol and cortisone levels were negatively associated with CD4 count but not with HIV viral load. The odds ratio for CD4 count < 500 cells/mm3 was 1.41 [95% CI 0.99–2.00] and 2.15 [95% CI 1.51–3.05] for those with hair cortisol and cortisone levels in the highest quartile compared to the lowest when controlling for sociodemographic, lifestyle, HIV-related covariates, and HIV viral load. Conclusion Hair glucocorticoid levels were associated with CD4 count but not viral load in treated Chinese PLHIV. Our data furtherly supported the hypothesis that elevated glucocorticoid levels are associated with the lower CD4 count.
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