Identifying factors affecting resilience in atrophy-based subtypes of vascular cognitive impairment

IF 1.9 Q3 CLINICAL NEUROLOGY
Vikram Venkatraghavan , Betty Tijms , Hugo Kuijf , Alberto de Luca , Esther Bron , Argonde van Harten , Lieza Exalto , Frederik Barkhof , Rik Ossenkoppele , Geert Jan Biessels , Wiesje van der Flier
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引用次数: 0

Abstract

Introduction

Vascular cognitive impairment (VCI) is heterogeneous in brain atrophy patterns, clinical symptoms, and possibly in the factors affecting resilience to symptoms. The objective of this study was to investigate the heterogeneity of VCI by estimating different atrophy-driven subtypes and use those for identifying resilience factors in each subtype.

Methods

We used cross-sectional data from the Trace-VCI cohort comprising of memory-clinic patients with vascular brain injury on MRI (n=361 all-cause dementia, n=190 MCI, and n=188 SCD). White matter hyper-intensities (WMH) were segmented, and SLF toolbox was used to refill them on the MRIs for accurate parcellation. Freesurfer volumes were used for identifying subtypes with non-negative matrix factorization. Subtype-specific pseudo-timelines of progression were estimated using a previously validated discriminative event-based model. Severity of atrophy (SA) in patients was estimated using cross-validation based on their position on the pseudo-timeline. Using linear-regression, cognition and disability (MMSE, Global deterioration scale, disability assessment for dementia) were modelled to be dependent on SA and its interactions with genetic factors, vascular markers and risk-factors, and co-pathology independently (variables in Figure-3). Resilience factors were identified by testing if the model with the interaction explains the symptoms significantly more than the one without.

Results

The algorithm identified three atrophy-based VCI subtypes: Frontal, Subcortical/Temporal, and Parietal subtype. Their prevalence, vascular and clinical presentations are summarized in Figure-1. The pseudo-timelines of atrophy are shown in Figure-2. SA's interaction with education positively influenced cognition in all subtypes, but negatively influenced disability in subcortical/temporal subtype. In frontal and parietal subtypes, APOE ε4, AD co-pathology resulted in more SA without worsening symptoms. SA's interaction with smoking and microbleeds negatively influenced disability. In the subcortical/temporal subtype, SA's interaction with WMH, lacunes, infarcts negatively impacted disability. In parietal subtype, men have more cognitive resilience than women. SA's interaction with hypercholesterolemia, and smoking were significantly negative for cognition. Lacunes were associated with more SA without affecting cognition. Figure-3 summarizes the interactions for all subtypes.

Discussion

We identified three atrophy-based VCI subtypes where the risk-factors have different influence on atrophy and symptoms highlighting differences in resilience. These results could aid in prognosis and in personalizing patients’ intervention strategy.

确定影响基于萎缩亚型血管性认知障碍恢复能力的因素
导言血管性认知障碍(VCI)在脑萎缩模式、临床症状以及可能影响症状恢复能力的因素方面都存在异质性。本研究的目的是通过估计不同的萎缩驱动亚型来研究血管性认知障碍的异质性,并利用这些亚型来确定每种亚型的恢复力因素。方法我们使用了Trace-VCI队列的横断面数据,该队列由磁共振成像上有血管性脑损伤的记忆门诊患者组成(n=361全因痴呆,n=190 MCI和n=188 SCD)。对白质高密度(WMH)进行了分割,并使用 SLF 工具箱在核磁共振成像上对其进行重新填充,以实现准确的分割。使用非负矩阵因式分解法确定亚型。亚型特异性的假性进展时间线是使用之前验证过的基于事件的判别模型估算的。患者的萎缩严重程度(SA)是根据其在伪时间轴上的位置通过交叉验证估算出来的。通过线性回归,建立了认知和残疾(MMSE、全球恶化量表、痴呆症残疾评估)取决于萎缩严重程度及其与遗传因素、血管标志物和风险因素以及共病理学相互作用的模型(图-3中的变量)。通过测试有交互作用的模型对症状的解释是否明显多于无交互作用的模型,确定了恢复力因素:该算法确定了三种基于萎缩的 VCI 亚型:额叶亚型、皮层下/颞叶亚型和顶叶亚型。其发病率、血管和临床表现见图-1。萎缩的假时间轴见图-2。SA与教育的相互作用对所有亚型的认知能力都有积极影响,但对皮层下/颞叶亚型的残疾有消极影响。在额叶和顶叶亚型中,APOE ε4和AD共同病理导致更多的SA,但症状并未恶化。SA与吸烟和微出血的相互作用对残疾有负面影响。在皮层下/颞叶亚型中,SA与WMH、裂隙、梗死的相互作用对残疾产生负面影响。在顶叶亚型中,男性比女性具有更强的认知恢复能力。SA与高胆固醇血症和吸烟的相互作用对认知能力有显著的负面影响。黑斑与更多的 SA 相关,但不影响认知。讨论我们发现了三种基于萎缩的 VCI 亚型,这些亚型的风险因素对萎缩和症状的影响不同,凸显了恢复能力的差异。这些结果有助于预后判断和患者干预策略的个性化。
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来源期刊
Cerebral circulation - cognition and behavior
Cerebral circulation - cognition and behavior Neurology, Clinical Neurology
CiteScore
2.00
自引率
0.00%
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审稿时长
14 weeks
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