Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment.

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2024-09-18 eCollection Date: 2024-09-01 DOI:10.1162/imag_a_00293
Aditi Sathe, Yisu Yang, Kurt G Schilling, Niranjana Shashikumar, Elizabeth Moore, Logan Dumitrescu, Kimberly R Pechman, Bennett A Landman, Katherine A Gifford, Timothy J Hohman, Angela L Jefferson, Derek B Archer
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Abstract

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD. We leveraged data from a longitudinal cohort (nparticipants = 296, nobservations = 870, age at baseline: 73 ± 7 years, 40% mild cognitive impairment [MCI]) of older adults who underwent serial neuropsychological assessment (episodic memory, information processing speed, executive function, language, and visuospatial skills) and brain MRI over a maximum of four time points, including baseline (n = 284), 18-month (n = 246), 3-year (n = 215), and 5-year (n = 125) visits. The mean follow-up period was 2.8 ± 1.3 years. Structural MRI was used to quantify hippocampal volume, in addition to Schwarz and McEvoy AD Signatures. FW and FW-corrected fractional anisotropy (FAFWcorr) were quantified in the hippocampus (hippocampal FW) and the AD signature areas (SchwarzFW, McEvoyFW) from diffusion-weighted (dMRI) images using bi-tensor modeling (FW elimination and mapping method). Linear regression assessed the association of each biomarker with baseline cognitive performance. Additionally, linear mixed-effects regression assessed the association between baseline biomarker values and longitudinal cognitive performance. A subsequent competitive model analysis was conducted on both baseline and longitudinal data to determine how much additional variance in cognitive performance was explained by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein-ε4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. All analyses were corrected for multiple comparisons using an FDR procedure. Cross-sectional results indicate that hippocampal volume, hippocampal FW, Schwarz and McEvoy AD Signatures, and the SchwarzFW and McEvoyFW metrics are all significantly associated with memory performance. Baseline competitive model analyses showed that the McEvoy AD Signature and SchwarzFW explain the most unique variance beyond covariates for memory (ΔRadj 2 = 3.47 ± 1.65%) and executive function (ΔRadj 2 = 2.43 ± 1.63%), respectively. Longitudinal models revealed that hippocampal FW explained substantial unique variance for memory performance (ΔRadj 2 = 8.13 ± 1.25%), and outperformed all other biomarkers examined in predicting memory decline (pFDR = 1.95 x 10-11). This study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

自由水:老龄化和轻度认知障碍中认知能力下降的一种前景看好的结构性生物标志物。
弥散核磁共振成像(Diffusion MRI)衍生的自由水(FW)指标有望预测老年痴呆症和阿尔茨海默病(AD)的认知障碍和衰退。自由水对大脑微观结构的细微变化很敏感,因此这些指标可能比传统的结构性神经影像生物标志物更敏感。在这项研究中,我们研究了 FW 指标(在海马体和两个 AD 标志性元 ROIs 中测量)与认知表现之间的关联,并将 FW 研究结果与更传统的 AD 神经影像生物标志物进行了比较。我们利用了一个纵向队列的数据(nparticipants = 296, nobservations = 870, age at baseline:73±7岁,40%为轻度认知障碍[MCI])的老年人,他们在最多四个时间点接受了连续的神经心理学评估(情节记忆、信息处理速度、执行功能、语言和视觉空间技能)和脑磁共振成像,包括基线(n = 284)、18个月(n = 246)、3年(n = 215)和5年(n = 125)随访。平均随访时间为 2.8 ± 1.3 年。结构性核磁共振成像用于量化海马体积,以及施瓦茨和麦科沃伊AD特征。使用双张量建模(FW消除和映射法)从扩散加权(dMRI)图像中量化了海马(海马FW)和AD特征区域(SchwarzFW、McEvoyFW)的FW和FW校正分数各向异性(FAFWcorr)。线性回归评估了每个生物标志物与基线认知表现的关联。此外,线性混合效应回归评估了基线生物标志物值与纵向认知表现之间的关联。随后对基线数据和纵向数据进行了竞争模型分析,以确定与只包含年龄、性别、种族/民族、载脂蛋白-ε4状态、认知状态和修正的弗雷明汉卒中风险档案评分的协变量模型相比,每个生物标志物能解释多少额外的认知能力差异。所有分析均采用 FDR 程序进行多重比较校正。横断面结果表明,海马体积、海马FW、Schwarz和McEvoy AD Signatures以及SchwarzFW和McEvoyFW指标均与记忆表现有显著相关性。基线竞争模型分析表明,在记忆(ΔRadj 2 = 3.47 ± 1.65%)和执行功能(ΔRadj 2 = 2.43 ± 1.63%)方面,McEvoy AD Signature 和 SchwarzFW 可分别解释协变量之外的最大独特变异。纵向模型显示,海马FW能解释记忆表现的大量独特变异(ΔRadj 2 = 8.13 ± 1.25%),在预测记忆力衰退方面优于所有其他生物标志物(pFDR = 1.95 x 10-11)。这项研究表明,海马FW是认知功能损伤和衰退的灵敏生物标志物,并为进一步探索该指标在衰老和AD中的应用提供了有力证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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