当前位置: 首页 > 详情页

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]Capital Med Univ, Xuanwu Hosp, Dept Neurol, Beijing, Peoples R China [2]Beijing Normal Univ, McGovern Inst Brain Res, State Key Lab Cognit Neurosci & Learning & IDG, Beijing 100875, Peoples R China [3]Beijing Normal Univ, BABRI Ctr, Beijing, Peoples R China [4]Beijing Normal Univ, Beijing Key Lab Brain Imaging & Connect, Beijing, Peoples R China [5]Inst Biomed Engn, Shenzhen Bay Lab, Shenzhen, Peoples R China [6]China Japan Friendship Hosp, Dept Radiol, Beijing, Peoples R China [7]Hainan Univ, Sch Biomed Engn, Haikou, Peoples R China [8]Natl Clin Res Ctr Geriatr Dis, Beijing, Peoples R China [9]Beijing Inst Brain Disorders, Ctr Alzheimers Dis, Beijing, Peoples R China
出处:
ISSN:

关键词: Alzheimer's disease Biomarker Efficiency Glial fibrillary acidic protein Graph theory Network Neurofilament light chain Plasma

摘要:
Both plasma biomarkers and brain network topology have shown great potential in the early diagnosis of Alzheimer's disease (AD). However, the specific associations between plasma AD biomarkers, structural network topology, and cognition across the AD continuum have yet to be fully elucidated. This retrospective study evaluated participants from the Sino Longitudinal Study of Cognitive Decline cohort between September 2009 and October 2022 with available blood samples or 3.0-T MRI brain scans. Plasma biomarker levels were measured using the Single Molecule Array platform, including beta-amyloid (A beta), phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The topological structure of brain white matter was assessed using network efficiency. Trend analyses were carried out to evaluate the alterations of the plasma markers and network efficiency with AD progression. Correlation and mediation analyses were conducted to further explore the relationships among plasma markers, network efficiency, and cognitive performance across the AD continuum. Among the plasma markers, GFAP emerged as the most sensitive marker (linear trend: t = 11.164, p = 3.59 x 10(-24); quadratic trend: t = 7.708, p = 2.25 x 10(-13); adjusted R-2 = 0.475), followed by NfL (linear trend: t = 6.542, p = 2.9 x 10(-10); quadratic trend: t = 3.896, p = 1.22 x 10(-4); adjusted R-2 = 0.330), p-tau181 (linear trend: t = 8.452, p = 1.61 x 10(-15); quadratic trend: t = 6.316, p = 1.05 x 10(-9); adjusted R-2 = 0.346) and A beta 42/A beta 40 (linear trend: t = -3.257, p = 1.27 x 10(-3); quadratic trend: t = -1.662, p = 9.76 x 10(-2); adjusted R-2 = 0.101). Local efficiency decreased in brain regions across the frontal and temporal cortex and striatum. The principal component of local efficiency within these regions was correlated with GFAP (Pearson's R = -0.61, p = 6.3 x 10(-7)), NfL (R = -0.57, p = 6.4 x 10(-6)), and p-tau181 (R = -0.48, p = 2.0 x 10(-4)). Moreover, network efficiency mediated the relationship between general cognition and GFAP (ab = -0.224, 95% confidence interval [CI] = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA) or NfL (ab = -0.224, 95% CI = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA). Our findings suggest that network efficiency mediates the association between plasma biomarkers, specifically GFAP and NfL, and cognitive performance in the context of AD progression, thus highlighting the potential utility of network-plasma approaches for early detection, monitoring, and intervention strategies in the management of AD.

基金:
语种:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2023]版:
大类 | 2 区 医学
小类 | 2 区 神经成像 2 区 神经科学 2 区 核医学
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 神经成像 2 区 神经科学 2 区 核医学
JCR分区:
出版当年[2022]版:
Q1 NEUROIMAGING Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Q2 NEUROSCIENCES
最新[2023]版:
Q1 NEUROIMAGING Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Q2 NEUROSCIENCES

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

第一作者:
第一作者机构: [1]Capital Med Univ, Xuanwu Hosp, Dept Neurol, Beijing, Peoples R China
通讯作者:
通讯机构: [1]Capital Med Univ, Xuanwu Hosp, Dept Neurol, Beijing, Peoples R China [2]Beijing Normal Univ, McGovern Inst Brain Res, State Key Lab Cognit Neurosci & Learning & IDG, Beijing 100875, Peoples R China [3]Beijing Normal Univ, BABRI Ctr, Beijing, Peoples R China [4]Beijing Normal Univ, Beijing Key Lab Brain Imaging & Connect, Beijing, Peoples R China [5]Inst Biomed Engn, Shenzhen Bay Lab, Shenzhen, Peoples R China [7]Hainan Univ, Sch Biomed Engn, Haikou, Peoples R China [8]Natl Clin Res Ctr Geriatr Dis, Beijing, Peoples R China [9]Beijing Inst Brain Disorders, Ctr Alzheimers Dis, Beijing, Peoples R China
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:16409 今日访问量:0 总访问量:869 更新日期:2025-01-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 首都医科大学宣武医院 技术支持:重庆聚合科技有限公司 地址:北京市西城区长椿街45号宣武医院