19 August 2013 : Original article
Plasma cortisol in Alzheimer’s disease with or without depressive symptoms
Martina ZvěřováABDEF, Zdeněk FišarABCDEF, Roman JirákABE, Eva KitzlerováABE, Jana HroudováDE, Jiří RabochAEGDOI: 10.12659/MSM.889110
Med Sci Monit 2013; 19:681-689
Abstract
BACKGROUND: Cortisol is presumed to be a risk factor for stress- and age-related disorders, such as depressive disorder and Alzheimer’s disease (AD). The aim of this study was to investigate the association of plasma cortisol concentration with AD in presence or absence of comorbid depressive symptoms.
MATERIAL AND METHODS: Plasma cortisol concentration was measured in 80 AD patients (35 of them with depressive symptoms), 27 elderly depressive patients without AD, and 37 elderly controls.
RESULTS: Compared to controls, a significant increase of mean plasma cortisol was found in AD patients but not in depressive patients. Plasma cortisol was positively correlated with cognitive impairment in AD patients. We confirmed a U-shaped association between plasma cortisol and major depression and a linear association between plasma cortisol and AD without depressive symptoms. Significantly increased relative risk of disease in people with high plasma cortisol was found for AD with depressive symptoms and for AD with mild dementia.
CONCLUSIONS: Plasma cortisol reflects the degree of cognitive impairment in AD rather than the severity of comorbid depression. We confirmed that both hypercortisolemia and hypocortisolemia are associated with depressive disorder. Significant association between high plasma cortisol and AD was found, supporting the use of high plasma cortisol as a component of a panel of biochemical markers for AD with depressive symptoms as well as AD in the early stage of dementia development.
Keywords: Linear Models, Hydrocortisone - blood, Depression - complications, Demography, Dementia - complications, Alzheimer Disease - complications, Aged, 80 and over, Neuropsychological Tests
Editorial
01 November 2024 : Editorial
Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and PrognosisDOI: 10.12659/MSM.947038
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