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. 2024 Jun;20(6):4366-4372.
doi: 10.1002/alz.13841. Epub 2024 May 7.

Correlation analysis of peripheral platelet markers and disease phenotypes in Alzheimer's disease

Jiajia Fu  1   2   3 , Xiaohui Lai  1 , Chongwei Zhang  4 , Qianqian Wei  1   2   3 , Xueping Chen  1   2   3 , Huifang Shang  1   2   3
Affiliations

Correlation analysis of peripheral platelet markers and disease phenotypes in Alzheimer's disease

Jiajia Fu et al. Alzheimers Dement. 2024 Jun.

Abstract

Introduction: Platelets serve as the primary peripheral reservoir of amyloid beta (Aβ). However, there is limited research on platelet markers in routine blood examinations, particularly with regard to the large platelet ratio (P-LCR) in Alzheimer's disease (AD).

Methods: This study included 512 AD patients and 205 healthy controls (HCs). Platelet markers and apolipoprotein E (APOE) 4 status were assessed in all participants.

Results: The study revealed that P-LCR was significantly elevated in AD patients compared to HCs. In AD patients carrying APOE4, P-LCR significantly negatively correlated with Montreal Cognitive Assessment scores. There was an observed increasing trend in the rate of change in P-LCR with disease progression. Binary logistic regression analysis indicated that P-LCR may constitute a risk factor for AD, after adjusting for age, sex, APOE4, and body mass index.

Discussion: P-LCR is associated with disease severity in AD patients carrying APOE4. P-LCR may be a promising marker to reflect platelet activity in AD patients.

Highlights: P-LCR significantly negatively correlated with MoCA scores in AD patients with APOE4. The rate of change in P-LCR showed an increasing trend with disease progression. P-LCR may be a risk factor for AD.

Keywords: APOE gene; Alzheimer's disease; platelet markers.

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Conflict of interest statement

We declare that there is no actual or potential financial and other conflict of interest related to the submitted manuscript. Author disclosures are available in the supporting information.

Figures

FIGURE 1
FIGURE 1
Receiver operator characteristic (ROC) cure: ROC curve plotted to test the diagnostic value of the logistic model. AUC, area under the curve.
FIGURE 2
FIGURE 2
(A) Bias‐corrected curve. (B) Decision Curve Analysis (DCA): All, all patients being diagnosed with AD; None, none of patients being diagnosed with AD.
See this image and copyright information in PMC

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