Major Depressive Disorder and Hypothalamic-Pituitary-Adrenal Axis Activity

Vreeburg, Sophie A.; Hoogendijk, Witte J.G.; Pelt, Johannes van; DeRijk, Roel H.; Verhagen, Jolanda C. M.; Dyck, Richard van; Smit, Johannes H.; Zitman, Frans G.; Penninx, Brenda W. J. H.

doi:10.1001/archgenpsychiatry.2009.50

Cited by 669 publications

(504 citation statements)

References 63 publications

Supporting

Mentioning

446

Contrasting

Unclassified

Order By: Relevance

“…The direction of these relationships is somewhat in keeping with previous research. For example, greater early morning peak levels have been associated with greater depressive symp- toms [20]; and while lower evening cortisol levels are usually associated with fewer depressive symptoms [35], there is evidence that evening levels are indeed lower in individuals reporting burnout [36]. Baseline levels of pro-MMP2 were also increased in patients whose ulcers remained unhealed.…”

Section: Discussionmentioning

confidence: 99%

Coping style and depression influence the healing of diabetic foot ulcers: observational and mechanistic evidence

et al. 2010

View full text Add to dashboard Cite

Aims/hypothesis Experimental evidence suggests that the healing of diabetic foot ulcers is affected by psychosocial factors such as distress. We examined this proposal in a prospective study, in which we considered the role of psychological distress and coping style in the healing of diabetic foot ulcers over a 24 week period. We also explored the role of salivary cortisol and matrix metalloproteinases (MMPs) as potential mechanisms. Methods For this prospective observational study we recruited 93 (68 men; mean age 60 years) patients with neuropathic or neuroischaemic diabetic foot ulcers from specialist podiatry clinics in secondary care. Clinical and demographic determinants of healing, psychological distress, coping, salivary cortisol and both MMP2 and MMP9 were assessed at baseline. Ulcers were assessed at baseline and at 6, 12 and 24 weeks post-baseline. Diabetologia (2010) 53:1590-1598 DOI 10.1007/s00125-010-1743 However, change in ulcer size over the observation period was associated with depression only (p=0.04, d=0.31). Healed ulcers by 24 weeks were also associated with lower evening cortisol, higher precursor MMP2 and a greater cortisol awakening response. Conclusions/interpretation Confrontation coping and depression predict ulcer healing. Our preliminary enquiry into biological mechanisms suggests that cortisol and precursor MMP2 may underlie these relationships.

show abstract

Section: Discussionmentioning

confidence: 99%

Coping style and depression influence the healing of diabetic foot ulcers: observational and mechanistic evidence

et al. 2010

View full text Add to dashboard Cite

show abstract

“…In addition, one study reported no difference in the pattern of the diurnal profile between depressed patients and controls (McClure, 1966). With regard to the CAR, participants who were currently or previously depressed ( [Bhagwager et al, 2005] and [Vreeburg et al, 2009a]) or had higher depressive symptoms (Pruessner et al, 2003b) exhibited a higher CAR. In contrast, one study showed a blunted CAR in depressed participants (Stetler and Miller, 2005).…”

Section: Depression Anxiety Social Support and Cortisolmentioning

confidence: 99%

“…For example, depressed participants with co-morbid anxiety had a higher CAR compared to those with depression alone (Vreeburg et al, 2009a), suggesting that anxiety may exacerbate the effects of depression on diurnal cortisol. There is also evidence that anxiety is independently associated with diurnal cortisol; individuals with high levels of anxiety showed a different pattern of decline across the day compared to those with lower levels of anxiety (Vedhara et al, 2003).…”

Section: Depression Anxiety Social Support and Cortisolmentioning

confidence: 99%

“…International Journal of Psychophysiology, 78, 201-208. http://dx.doi.org/10.1016Psychophysiology, 78, 201-208. http://dx.doi.org/10. /j.ijpsycho.2010 of consensus may also be partly explained by methodological considerations such as the age of the participants and failure to control for possible confounders ( [Chida and Steptoe, 2009] and [Vreeburg et al, 2009a]). …”

Section: Depression Anxiety Social Support and Cortisolmentioning

confidence: 99%

See 1 more Smart Citation

Ageing, depression, anxiety, social support and the diurnal rhythm and awakening response of salivary cortisol

Heaney¹,

Phillips²,

Carroll³

2010

International Journal of Psychophysiology

View full text Add to dashboard Cite

The present study compared the cortisol awakening response and diurnal rhythm in 24 young healthy students and 48 community-dwelling older adults. The associations with diurnal cortisol and depression, anxiety and social support were also examined in relation to age. Salivary cortisol was measured over the course of one day: immediately upon awakening, 30 min later, and then 3 h, 6 h, 9 h and 12 h post-awakening. Participants completed a questionnaire measuring symptoms of anxiety and depression and social support was assessed. Older adults exhibited a significantly reduced awakening response, overall cortisol levels, area under the curve (AUC) and diurnal slopes than younger adults, resulting in a flatter diurnal rhythm. Younger adults with higher depression scores had significantly higher overall cortisol and higher levels upon awakening and 30 min postawakening. In the younger adults, anxiety and depression correlated positively with AUC and the cortisol awakening response (CAR). Older adults with lower social support had a reduced AUC where younger adults with lower social support displayed a larger AUC. These findings suggest that the diurnal rhythm and awakening response of salivary cortisol are significantly reduced in older adults and the associations between anxiety, depression and social support and diurnal cortisol vary with age.

show abstract

“…This finding is in line with previous research. Previous studies reported differences between GAD or MDD compared to healthy controls for cortisol (Bhagwagar et al., 2005; Hek et al., 2013; Hinkelmann et al., 2012; Mantella et al., 2008; Phillips et al., 2011; Steudte et al., 2011; Ulrike, Reinhold, & Dirk, 2013; Vreeburg et al., 2009; Wei et al., 2015) but the exact nature of these differences was mixed and some studies did not find such differences (Burke, Davis, Otte, & Mohr, 2005; see also the meta‐analysis by Vythilingam et al., 2004). The heterogeneity of prior studies can be attributed to methodological differences in data collection (e.g.…”

Section: Discussionmentioning

confidence: 99%

Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study

et al. 2017

View full text Add to dashboard Cite

BackgroundGeneralized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral data from a sample of GAD, MD and healthy subjects to differentiate subjects with a disorder from healthy subjects (case‐classification) and to differentiate GAD from MD (disorder‐classification).MethodsSubjects with GAD (n = 19), MD without GAD (n = 14), and healthy comparison subjects (n = 24) were included. The sample was matched regarding age, sex, handedness and education and free of psychopharmacological medication. Binary support vector machines were used within a nested leave‐one‐out cross‐validation framework. Clinical questionnaires, cortisol release, gray matter (GM), and white matter (WM) volumes were used as input data separately and in combination.ResultsQuestionnaire data were well‐suited for case‐classification but not disorder‐classification (accuracies: 96.40%, p < .001; 56.58%, p > .22). The opposite pattern was found for imaging data (case‐classification GM/WM: 58.71%, p = .09/43.18%, p > .66; disorder‐classification GM/WM: 68.05%, p = .034/58.27%, p > .15) and for cortisol data (38.02%, p = .84; 74.60%, p = .009). All data combined achieved 90.10% accuracy (p < .001) for case‐classification and 67.46% accuracy (p = .0268) for disorder‐classification.ConclusionsIn line with previous evidence, classification of GAD was difficult using clinical questionnaire data alone. Particularly cortisol and GM volume data were able to provide incremental value for the classification of GAD. Findings suggest that neurobiological biomarkers are a useful target for further research to delineate their potential contribution to diagnostic processes.

show abstract

Major Depressive Disorder and Hypothalamic-Pituitary-Adrenal Axis Activity

Cited by 669 publications

References 63 publications

Coping style and depression influence the healing of diabetic foot ulcers: observational and mechanistic evidence

Coping style and depression influence the healing of diabetic foot ulcers: observational and mechanistic evidence

Ageing, depression, anxiety, social support and the diurnal rhythm and awakening response of salivary cortisol

Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study

Contact Info

Product

Resources

About