比较血浆和神经影像生物标志物,预测非痴呆记忆门诊患者的认知能力衰退。

IF 7.9 1区 医学 Q1 CLINICAL NEUROLOGY
Augusto J Mendes, Federica Ribaldi, Aurelien Lathuiliere, Nicholas J Ashton, Henrik Zetterberg, Marc Abramowicz, Max Scheffler, Frédéric Assal, Valentina Garibotto, Kaj Blennow, Giovanni B Frisoni
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引用次数: 0

摘要

背景:阿尔茨海默病(AD)病理、神经变性和神经炎症的血浆生物标志物非常适合用于自给自足的痴呆症高危人群的二级预防计划。血浆生物标志物已被证明与传统的成像生物标志物高度相关。然而,在认知功能未受损(CU)和轻度认知功能受损(MCI)的受试者中,血浆生物标志物与传统痴呆症生物标志物的比较预测价值仍不明确:方法:对日内瓦记忆中心的218名非痴呆受试者(CU=140人;MCI=78人)的血浆(Aβ42/40、p-tau181、p-tau231、NfL和GFAP)和神经影像(海马体积、淀粉样蛋白PET的中心体和tau-SUVR的tau-PET)生物标志物进行基线评估。在基线和长达 5.7 年的随访中对总体认知能力(MMSE)进行了评估。我们使用线性混合效应模型和 Cox 比例危险回归来评估生物标志物与认知能力下降之间的关系。最后,使用线性混合效应模型对淀粉样蛋白-PET阳性、tau-PET阳性和血浆生物标志物阳性的受试者进行了样本量计算:基线血浆NfL(β=-0.55)、GFAP(β=-0.36)、海马体积(β=0.44)、中心体(β=-0.38)和tau-SUVR(β=-0.66)对MCI患者的认知能力下降有明显的预测作用(均为P结论):血浆 NfL 和 GFAP 预测淀粉样蛋白阳性 MCI 患者认知能力下降的方式与传统成像技术相似。因此,尽管它们是 AD 的非特异性生物标志物,但都可以作为重要的预后生物标志物用于记忆临床检查。同样,未来的临床试验也可以采用血浆生物标志物作为额外的纳入标准,对认知能力下降风险较高的患者进行分层,以减少样本量,提高有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients.

Background: Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI).

Methods: Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity.

Results: Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity.

Conclusions: Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.

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来源期刊
Alzheimer's Research & Therapy
Alzheimer's Research & Therapy 医学-神经病学
CiteScore
13.10
自引率
3.30%
发文量
172
审稿时长
>12 weeks
期刊介绍: Alzheimer's Research & Therapy is an international peer-reviewed journal that focuses on translational research into Alzheimer's disease and other neurodegenerative diseases. It publishes open-access basic research, clinical trials, drug discovery and development studies, and epidemiologic studies. The journal also includes reviews, viewpoints, commentaries, debates, and reports. All articles published in Alzheimer's Research & Therapy are included in several reputable databases such as CAS, Current contents, DOAJ, Embase, Journal Citation Reports/Science Edition, MEDLINE, PubMed, PubMed Central, Science Citation Index Expanded (Web of Science) and Scopus.
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