Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging.

IF 2.7 3区 医学 Q2 CLINICAL NEUROLOGY Frontiers in Neurology Pub Date : 2024-11-07 eCollection Date: 2024-01-01 DOI:10.3389/fneur.2024.1470727
Gabriella Yakemow, Tiffany A Kolesar, Natalie Wright, Iman Beheshti, Eun Hyung Choi, Lawrence Ryner, Sarah Chaulk, Ronak Patel, Ji Hyun Ko
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Abstract

Introduction: Posttraumatic stress disorder (PTSD) is a mental health disorder caused by experiencing or witnessing traumatic events. Recent studies show that patients with PTSD have an increased risk of developing dementia, including Alzheimer's disease (AD), but there is currently no way to predict which patients will go on to develop AD. The objective of this study was to identify structural and functional neural changes in patients with PTSD that may contribute to the future development of AD.

Methods: Neuroimaging (pseudo-continuous arterial spin labeling [pCASL] and structural magnetic resonance imaging [MRI]) and behavioral data for the current study (n = 67) were taken from our non-randomized open label clinical trial (ClinicalTrials.gov Identifier: NCT03229915) for treatment-seeking individuals with PTSD (n = 40) and age-matched healthy controls (HC; n = 27). Only the baseline measures were utilized for this study. Mean cerebral blood flow (CBF) and gray matter (GM) volume were compared between groups. Additionally, we utilized two previously established machine learning-based algorithms, one representing AD-like brain activity (Machine learning-based AD Designation [MAD]) and the other focused on AD-like brain structural changes (AD-like Brain Structure [ABS]). MAD scores were calculated from pCASL data and ABS scores were calculated from structural T1-MRI images. Correlations between neuroimaging data (regional CBF, GM volume, MAD scores, ABS scores) and PTSD symptom severity scores measured by the clinician-administered PTSD scale for DSM-5 (CAPS-5) were assessed.

Results: Decreased CBF was observed in two brain regions (left caudate/striatum and left inferior parietal lobule/middle temporal lobe) in the PTSD group, compared to the HC group. Decreased GM volume was also observed in the PTSD group in the right temporal lobe (parahippocampal gyrus, middle temporal lobe), compared to the HC group. GM volume within the right temporal lobe cluster negatively correlated with CAPS-5 scores and MAD scores in the PTSD group.

Conclusion: Results suggest that patients with PTSD with reduced GM volume in the right temporal regions (parahippocampal gyrus) experienced greater symptom severity and showed more AD-like brain activity. These results show potential for early identification of those who may be at an increased risk for future development of dementia.

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利用机器学习算法和磁共振成像研究创伤后应激障碍中阿尔茨海默病的神经标记。
导言创伤后应激障碍(PTSD)是一种因经历或目睹创伤事件而导致的精神疾病。最近的研究表明,创伤后应激障碍患者患痴呆症(包括阿尔茨海默病)的风险增加,但目前尚无法预测哪些患者会发展成阿尔茨海默病。本研究的目的是确定创伤后应激障碍患者的神经结构和功能变化,这些变化可能会导致未来阿尔茨海默病的发展:本研究的神经影像学(伪连续动脉自旋标记[pCASL]和结构磁共振成像[MRI])和行为学数据(n = 67)来自我们的非随机开放标签临床试验(ClinicalTrials.gov Identifier:NCT03229915),对象是寻求治疗的创伤后应激障碍患者(n = 40)和年龄匹配的健康对照组(HC;n = 27)。本研究仅使用基线测量值。我们对各组的平均脑血流量(CBF)和灰质(GM)体积进行了比较。此外,我们还使用了之前建立的两种基于机器学习的算法,一种代表类似于 AD 的大脑活动(基于机器学习的 AD 指定 [MAD]),另一种侧重于类似于 AD 的大脑结构变化(类似于 AD 的大脑结构 [ABS])。MAD 评分由 pCASL 数据计算得出,ABS 评分由结构性 T1-MRI 图像计算得出。评估了神经影像学数据(区域 CBF、GM 容量、MAD 评分、ABS 评分)与临床医师自制的创伤后应激障碍量表 DSM-5(CAPS-5)中创伤后应激障碍症状严重程度评分之间的相关性:结果:与HC组相比,创伤后应激障碍组两个脑区(左侧尾状/纹状体和左侧下顶叶/中颞叶)的CBF下降。与 HC 组相比,创伤后应激障碍组右侧颞叶(海马旁回、颞叶中部)的 GM 体积也有所减少。创伤后应激障碍组患者右侧颞叶GM体积与CAPS-5评分和MAD评分呈负相关:结果表明,右侧颞叶区域(海马旁回)GM体积减少的创伤后应激障碍患者的症状严重程度更高,并表现出更多类似于AD的大脑活动。这些结果表明,及早识别那些未来患痴呆症风险可能会增加的患者是很有潜力的。
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来源期刊
Frontiers in Neurology
Frontiers in Neurology CLINICAL NEUROLOGYNEUROSCIENCES -NEUROSCIENCES
CiteScore
4.90
自引率
8.80%
发文量
2792
审稿时长
14 weeks
期刊介绍: The section Stroke aims to quickly and accurately publish important experimental, translational and clinical studies, and reviews that contribute to the knowledge of stroke, its causes, manifestations, diagnosis, and management.
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