Journal
WOMEN & HEALTH
Volume 63, Issue 4, Pages 285-295Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/03630242.2023.2185750
Keywords
Cognitive dysfunction; dementia; inflammation; lipids; MCI
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The detection of specific markers of dementia and mild cognitive decline (MCI) is crucial for disease prevention and early treatment. Female gender is a major risk factor for dementia. This study compared the concentration of factors related to lipid metabolism and the immune system in MCI and dementia patients. It was found that Apo A1 and HDL levels were significantly decreased in dementia patients, and Apo A1 levels were also decreased in MCI patients. Furthermore, certain markers were elevated in dementia patients compared to controls, while others were decreased in MCI patients and increased in dementia patients compared to controls.
The detection of specific markers of dementia and mild cognitive decline (MCI) could be the key to disease prevention and forehanded treatment. Female gender is one of the major risk factor for dementia. The aim of our study was to compare serum concentration of some factors related to lipid metabolism and the immune system in patients with MCI and dementia. The study was performed on women >65 years old: controls (n = 75), diagnosed with dementia (n = 73) and MCI (n = 142). Patients were evaluated using Mini-Mental State Examination, Clock Drawing Test and Montreal Cognitive Assessment scales in the period 2020-2021. The level of Apo A1 and HDL was significantly decreased in patients with dementia; the level of Apo A1 was also decreased in MCI. EGF, eotaxin-1, GRO-alpha, and IP-10 were elevated in patients with dementia compared to the controls. IL-8, MIP-1 beta, sCD40L, and TNF-alpha levels were decreased in MCI patients and increased in patients with dementia compared to the control. Serum VEGF levels were decreased in MCI and dementia patients in comparison with the control. We hypothesize that no single marker can indicate a neurodegenerative process. Future research should focus on identifying markers to determine possible diagnostic combinations that can reliably predict neurodegeneration.
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