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Risk factors for cognitive decline in non-demented elders with amyloid-beta positivity.
Wang, An-Yi; Hu, He-Ying; Huang, Liang-Yu; Xiao, Chu-Yun; Li, Qiong-Yao; Tan, Lan; Hu, Hao.
Afiliación
  • Wang AY; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China.
  • Hu HY; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China.
  • Huang LY; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China.
  • Xiao CY; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China.
  • Li QY; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China.
  • Tan L; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China. dr.tanlan@163.com.
  • Hu H; Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No.5 Donghai Middle Road, Qingdao, China. qingdaoshennei@163.com.
Alzheimers Res Ther ; 16(1): 189, 2024 Aug 19.
Article en En | MEDLINE | ID: mdl-39160609
ABSTRACT

BACKGROUND:

As a currently incurable but preventable disease, the prevention and early diagnosis of Alzheimer's disease (AD) has long been a research hotspot. Amyloid deposition has been shown to be a major pathological feature of AD. Notably, not all the people with amyloid-beta (Aß) pathology will have significant cognitive declines and eventually develop AD. Therefore, the aim of this study was to explore the risk factors for cognitive decline in Aß-positive participants.

METHODS:

We included 650 non-demented participants who were Aß-positive at baseline from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Mixed effects and COX regression models were applied to assess 37 potential risk factors. Mixed effects models were employed to assess the temporal associations between potential risk factors and four cognitive assessment scales. COX regression models were used to assess the impact of potential risk factors on cognitive diagnosis conversion. Univariate and multivariate analyses were applied to the above models. Additionally, we used the Cochran-Armitage trend test to examine whether the incidence of cognitive decline increased with the number concurrent of risk factors.

RESULTS:

Six factors (low diastolic pressure, low body mass index, retired status, a history of drug abuse, Parkinsonism, and depression) were the identified risk factors and four factors (a history of urinary disease, musculoskeletal diseases, no major surgical history, and no prior dermatologic-connective tissue diseases) were found to be suggestive risk factors. The incidence of cognitive decline in the Aß-positive participants gradually increased as the number of concurrent risk factors increased (p for trend = 0.0005).

CONCLUSIONS:

Our study may facilitate the understanding of the potential pathological processes in AD and provide novel targets for the prevention of cognitive decline among participants with Aß positivity.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos beta-Amiloides / Disfunción Cognitiva Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Alzheimers Res Ther Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Péptidos beta-Amiloides / Disfunción Cognitiva Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Alzheimers Res Ther Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido