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Barone JC, Ho A, Osborne LM, Eisenlohr-Moul TA, Morrow AL, Payne JL, Epperson CN, Hantsoo L. Luteal phase sertraline treatment of premenstrual dysphoric disorder (PMDD): Effects on markers of hypothalamic pituitary adrenal (HPA) axis activation and inflammation. Psychoneuroendocrinology 2024; 169:107145. [PMID: 39096755 DOI: 10.1016/j.psyneuen.2024.107145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 07/21/2024] [Accepted: 07/22/2024] [Indexed: 08/05/2024]
Abstract
RATIONALE Premenstrual dysphoric disorder (PMDD) is characterized by severe affective symptoms during the luteal phase of the menstrual cycle. There is some evidence of altered interactions between the hypothalamic pituitary gonadal (HPG) and hypothalamic pituitary adrenal (HPA) axes in PMDD. There is also evidence that similar affective disorders such as major depression and perinatal depression are associated with dysregulation in immune factors, but this has not been characterized in PMDD. AIMS The goals of this exploratory study were to identify 1) whether HPA-HPG axis interactions and immune markers differ between PMDD patients and controls across the menstrual cycle; 2) how luteal phase sertraline treatment impacts stress and inflammatory markers. METHODS Participants were females age 18-50 with regular menstrual cycles, not using psychotropic or hormonal medications, and were assigned to a control group or PMDD group based on prospective daily symptom ratings and clinical interview. Blood was drawn in the follicular and luteal phases, during laboratory sessions involving a mildly stressful task. In a second luteal phase, PMDD participants received open-label sertraline (50 mg/d) from ovulation to menses. Serum cortisol and ACTH were measured via ELISA and operationalized as area under the curve with respect to ground (AUCg), and peak level following laboratory task. Serum TNF-α, IL-6, CXCL-8, and IL-1β were measured using multiplex kits. Serum allopregnanolone (ALLO) was measured by gas chromatography/mass spectroscopy. To characterize HPA-HPG axis interactions across the menstrual cycle in PMDD participants and controls, multilevel linear models predicted cortisol and ACTH from the interaction of cycle phase (controlling for sertraline treatment), ALLO, and group. To determine the effects of sertraline treatment on inflammatory markers and how groups might differ in cyclical change on each marker, multilevel linear models predicted inflammatory markers from cycle phase (controlling for sertraline treatment) and group. A final set of exploratory models tested whether inflammatory markers predict premenstrual symptom score severity. RESULTS The sample included n=77 participants (41 controls, 36 PMDD); 28 participants with PMDD completed sertraline treatment. Group x phase x ALLO interactions showed that higher ALLO levels predicted lower cortisol peak in the treated luteal phase (interaction between phase and ALLO, p=0.042), and there was a higher cortisol peak in the treated luteal phase than the untreated luteal phase (p=0.038). CXCL-8 was significantly associated with premenstrual symptom severity after controlling for group and cycle phase (p=0.011). There were no main effects of group, phase, or ALLO on cortisol AUCg, ACTH AUCg, IL-6, CXCL-8, IL-1β, nor TNF-α (p's>0.05). CONCLUSION Serum markers of HPA axis and immune function did not vary by menstrual cycle phase nor PMDD status. However, sertraline treatment in the luteal phase was associated with higher ALLO levels predicting lower cortisol peak in response to mild laboratory stress, suggesting that sertraline treatment may normalize HPG-HPA axis interactions among individuals with PMDD. Greater premenstrual symptomatology was associated with higher levels of the inflammatory marker CXCL-8, but further research is needed into the potential role of inflammation in PMDD.
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Affiliation(s)
- Jordan C Barone
- Department of Psychiatry, University of Illinois at Chicago College of Medicine, Chicago, IL, United States
| | - Annie Ho
- Department of Psychiatry & Behavioral Sciences, The Johns Hopkins University School of Medicine, 550 N. Broadway Street, Baltimore, MD, United States
| | - Lauren M Osborne
- Departments of Obstetrics & Gynecology and of Psychiatry, Weill Cornell Medical College, New York, NY, United States
| | - Tory A Eisenlohr-Moul
- Department of Psychiatry, University of Illinois at Chicago College of Medicine, Chicago, IL, United States
| | - A Leslie Morrow
- Departments of Psychiatry and Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, United States
| | - Jennifer L Payne
- Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, VA, United States
| | - C Neill Epperson
- Department of Psychiatry, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, United States
| | - Liisa Hantsoo
- Department of Psychiatry & Behavioral Sciences, The Johns Hopkins University School of Medicine, 550 N. Broadway Street, Baltimore, MD, United States.
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Wan W, Yu Y. Association between the triglyceride glucose index and depression: a meta-analysis. Front Psychiatry 2024; 15:1390631. [PMID: 38966187 PMCID: PMC11222386 DOI: 10.3389/fpsyt.2024.1390631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 05/27/2024] [Indexed: 07/06/2024] Open
Abstract
Background Obesity and diabetes have been associated with depressive symptoms. The aim of this systematic review and meta-analysis was to evaluate the association between the triglyceride glucose index (TyG index) a novel indicator of insulin resistance (IR) and depression in the adult population. Methods Relevant observational studies were acquired through comprehensive searches of the Medline, Web of Science, Embase, Wanfang, and China National Knowledge Internet databases. To account for heterogeneity, a random-effects model was employed to combine the findings. Additionally, multiple subgroup analyses were conducted to assess the impact of various study characteristics on the outcome. Results The meta-analysis comprised eight datasets from six cross-sectional studies, encompassing a total of 28,973 adults. The pooled findings suggested that subjects with a high TyG index, compared to those with a low TyG index, were associated with a higher prevalence of depression (odds ratio [OR]: 1.41, 95% confidence interval (CI): 1.28-1.56, p<0.001; I2 = 19%). Sensitivity analyses, by omitting one dataset at a time, showed consistent results (OR: 1.39-1.45, p<0.05). Further subgroup analyses showed consistent results in participants aged <50 years old and in those aged ≥50 years old, in men and in women, in studies with different cutoff values for the TyG index, and in studies with different methods for the diagnosis of depression (for each subgroup difference, p>0.05). Conclusion A high TyG index may be associated with a higher prevalence of depression in the adult population.
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Affiliation(s)
- Weitao Wan
- Department of Psychiatry, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Yi Yu
- Department of Psychiatry, Wuchang Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, China
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Weiss SJ, Xu L. Postpartum symptoms of anxiety, depression and stress: differential relationships to women's cortisol profiles. Arch Womens Ment Health 2024; 27:435-445. [PMID: 38214755 PMCID: PMC11116185 DOI: 10.1007/s00737-024-01421-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 01/02/2024] [Indexed: 01/13/2024]
Abstract
PURPOSE Women are at high risk of stress, anxiety, and depression during the postpartum but the ways in which these different types of psychological distress are related to cortisol regulation is not clear. We examined the distinct association of each type of distress with women's average cortisol level, cortisol awakening response (CAR), cortisol decline across the day (diurnal slope), and overall amount of cortisol secretion across the day (AUCG). METHODS At 6 months postpartum, a diverse group of 58 women completed measures of depression, anxiety, perceived stress, and life stressors. Each woman provided 4 salivary samples for cortisol assay from waking to bedtime on each of 2 consecutive days. Linear regressions were used to examine associations of stress, anxiety and depression to each of the 4 cortisol measures, controlling for number of stressful life events. RESULTS Depressive symptoms were associated with less of a rise in the CAR (β = -.46, p = 0.01), steeper diurnal slope (β = .51, p = 0.006), and higher average cortisol level (β = .42, p = .01). Women who met the clinical cutoff for an anxiety disorder had lower overall cortisol output (β = -.29, p = 0.03). Stress was not related to any cortisol metric. CONCLUSIONS Findings suggest that stress is less associated with cortisol alterations in the postpartum than are more severe types of psychological distress. Anxiety and depression may have distinct and opposite profiles of cortisol dysregulation. Results indicate that mental health assessment is critical even in the later postpartum so that interventions can be initiated to reduce emotional suffering and the risk of impaired cortisol regulation.
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Affiliation(s)
- Sandra J Weiss
- Department of Community Health Systems, University of California, San Francisco, CA, USA.
| | - Ling Xu
- Department of Community Health Systems, University of California, San Francisco, CA, USA
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Zhu L, Wang Y, Li J, Zhou H, Li N, Wang Y. Depressive symptoms and all-cause mortality among middle-aged and older people in China and associations with chronic diseases. Front Public Health 2024; 12:1381273. [PMID: 38841667 PMCID: PMC11151855 DOI: 10.3389/fpubh.2024.1381273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Accepted: 05/02/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction It remains unclear whether depressive symptoms are associated with increased all-cause mortality and to what extent depressive symptoms are associated with chronic disease and all-cause mortality. The study aims to explore the relationship between depressive symptoms and all-cause mortality, and how depressive symptoms may, in turn, affect all-cause mortality among Chinese middle-aged and older people through chronic diseases. Methods Data were collected from the China Health and Retirement Longitudinal Study (CHARLS). This cohort study involved 13,855 individuals from Wave 1 (2011) to Wave 6 (2020) of the CHARLS, which is a nationally representative survey that collects information from Chinese residents ages 45 and older to explore intrinsic mechanisms between depressive symptoms and all-cause mortality. The Center for Epidemiological Studies Depression Scale (CES-D-10) was validated through the CHARLS. Covariates included socioeconomic variables, living habits, and self-reported history of chronic diseases. Kaplan-Meier curves depicted mortality rates by depressive symptom levels, with Cox proportional hazards regression models estimating the hazard ratios (HRs) of all-cause mortality. Results Out of the total 13,855 participants included, the median (Q1, Q3) age was 58.00 (51.00, 63.00) years. Adjusted for all covariates, middle-aged and older adults with depressive symptoms had a higher all-cause mortality rate (HR = 1.20 [95% CI, 1.09-1.33]). An increased rate was observed for 55-64 years old (HR = 1.23 [95% CI, 1.03-1.47]) and more than 65 years old (HR = 1.32 [95% CI, 1.18-1.49]), agricultural Hukou (HR = 1.44, [95% CI, 1.30-1.59]), and nonagricultural workload (HR = 1.81 [95% CI, 1.61-2.03]). Depressive symptoms increased the risks of all-cause mortality among patients with hypertension (HR = 1.19 [95% CI, 1.00-1.40]), diabetes (HR = 1.41[95% CI, 1.02-1.95]), and arthritis (HR = 1.29 [95% CI, 1.09-1.51]). Conclusion Depressive symptoms raise all-cause mortality risk, particularly in those aged 55 and above, rural household registration (agricultural Hukou), nonagricultural workers, and middle-aged and older people with hypertension, diabetes, and arthritis. Our findings through the longitudinal data collected in this study offer valuable insights for interventions targeting depression, such as early detection, integrated chronic disease care management, and healthy lifestyles; and community support for depressive symptoms may help to reduce mortality in middle-aged and older people.
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Affiliation(s)
- Lan Zhu
- School of Education and Psychology, Key Research Institute of Humanities and Social Sciences of State Ethnic Affairs Commission, and Research Centre of Sichuan Minzu Education Development, Southwest Minzu University, Chengdu, China
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yixi Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiaqi Li
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Huan Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ningxiu Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuanyuan Wang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
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Hamidovic A, Davis J, Soumare F. Blunted Cortisol Response to Acute Psychosocial Stress in Women With Premenstrual Dysphoric Disorder. Int J Neuropsychopharmacol 2024; 27:pyae015. [PMID: 38451747 DOI: 10.1093/ijnp/pyae015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 03/04/2024] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND Despite being considered a stress-related condition, it is not known whether the hypothalamic-pituitary-adrenal (HPA) axis is dysfunctional in response to acute psychosocial stress in premenstrual dysphoric disorder (PMDD). This is problematic because many women with PMDD report that they are not able to control their stress levels, and a blunted cortisol output has been identified in women with related psychiatric conditions, such as anxiety and depression. The present study is a part of the Premenstrual Hormonal and Affective State Evaluation (PHASE) project, and it aimed to characterize the cortisol trajectory in response to an acute psychosocial stress challenge. METHODS Women with PMDD and healthy controls with confirmed ovulatory cycles underwent the Trier Social Stress Test (TSST) procedure in the mid-late luteal phase of the menstrual cycle, throughout which we collected serum samples of cortisol that we analyzed using ultra-performance liquid chromatography tandem mass spectrometry. RESULTS The linear mixed model analysis indicated a significant time*diagnosis interaction (P = .008) such that women with PMDD displayed significantly lower serum cortisol levels at +40 through +90 minutes from the time of stress induction. CONCLUSION This is the first study to show that women with PMDD have a blunted cortisol response to psychosocial stress. Combined with our earlier finding showing a greater parasympathetic nervous system withdrawal on heart oscillations in PMDD during acute stress, these and other results show that the dysregulated processing of stress in PMDD may be captured using objective study measures.
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Affiliation(s)
- Ajna Hamidovic
- Department of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
| | - John Davis
- School of Public Health/Psychiatric Institute (SPHPI), Chicago, Illinois, USA
| | - Fatimata Soumare
- Department of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA
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Jin Y, Wu C, Chen W, Li J, Jiang H. Gestational diabetes and risk of perinatal depression in low- and middle-income countries: a meta-analysis. Front Psychiatry 2024; 15:1331415. [PMID: 38414505 PMCID: PMC10897974 DOI: 10.3389/fpsyt.2024.1331415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/24/2024] [Indexed: 02/29/2024] Open
Abstract
Background The relationship between gestational diabetes (GDM) and the risk of depression has been thoroughly investigated in high-income countries on their financial basis, while it is largely unexplored in low- and middle- income countries. This meta-analysis aims to assess how GDM influences the risk of perinatal depression by searching multiple electronic databases for studies measuring the odds ratios between them in low- and middle-income countries. Methods Two independent reviewers searched multiple electronic databases for studies that investigated GDM and perinatal mental disorders on August 31, 2023. Pooled odds ratios (ORs) and confidence intervals (CIs) were calculated using the random effect model. Subgroup analyses were further conducted based on the type of study design and country income level. Results In total, 16 observational studies met the inclusion criteria. Only the number of studies on depression (n=10) satisfied the conditions to conduct a meta-analysis, showing the relationship between mental illness and GDM has been overlooked in low- and middle-income countries. Evidence shows an elevated risk of perinatal depression in women with GDM (pooled OR 1.92; 95% CI 1.24, 2.97; 10 studies). The increased risk of perinatal depression in patients with GDM was not significantly different between cross-sectional and prospective design. Country income level is a significant factor that adversely influences the risk of perinatal depression in GDM patients. Conclusion Our findings suggested that women with GDM are vulnerable to perinatal depressive symptoms, and a deeper understanding of potential risk factors and mechanisms may help inform strategies aimed at prevention of exposure to these complications during pregnancy.
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Affiliation(s)
- Yuqing Jin
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, China
- Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China
| | - Chengkai Wu
- Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China
| | - Wanlin Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jingsong Li
- Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China
- Engineering Research Center of Electronic Medical Record (EMR) and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Haiteng Jiang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, Ministry of Education (MOE) Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
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