Suppr超能文献

载脂蛋白 E 在转基因阿尔茨海默病小鼠认知中的聚集趋势。

Aggregate Trends of Apolipoprotein E on Cognition in Transgenic Alzheimer's Disease Mice.

机构信息

Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, GA, USA.

Institute for Machine Learning, Georgia Institute of Technology, Atlanta, GA, USA.

出版信息

J Alzheimers Dis. 2021;83(1):435-450. doi: 10.3233/JAD-210492.

Abstract

BACKGROUND

Apolipoprotein E (APOE) genotypes typically increase risk of amyloid-β deposition and onset of clinical Alzheimer's disease (AD). However, cognitive assessments in APOE transgenic AD mice have resulted in discord.

OBJECTIVE

Analysis of 31 peer-reviewed AD APOE mouse publications (n = 3,045 mice) uncovered aggregate trends between age, APOE genotype, gender, modulatory treatments, and cognition.

METHODS

T-tests with Bonferroni correction (significance = p < 0.002) compared age-normalized Morris water maze (MWM) escape latencies in wild type (WT), APOE2 knock-in (KI2), APOE3 knock-in (KI3), APOE4 knock-in (KI4), and APOE knock-out (KO) mice. Positive treatments (t+) to favorably modulate APOE to improve cognition, negative treatments (t-) to perturb etiology and diminish cognition, and untreated (t0) mice were compared. Machine learning with random forest modeling predicted MWM escape latency performance based on 12 features: mouse genotype (WT, KI2, KI3, KI4, KO), modulatory treatment (t+, t-, t0), mouse age, and mouse gender (male = g_m; female = g_f, mixed gender = g_mi).

RESULTS

KI3 mice performed significantly better in MWM, but KI4 and KO performed significantly worse than WT. KI2 performed similarly to WT. KI4 performed significantly worse compared to every other genotype. Positive treatments significantly improved cognition in WT, KI4, and KO compared to untreated. Interestingly, negative treatments in KI4 also significantly improved mean MWM escape latency. Random forest modeling resulted in the following feature importance for predicting superior MWM performance: [KI3, age, g_m, KI4, t0, t+, KO, WT, g_mi, t-, g_f, KI2] = [0.270, 0.094, 0.092, 0.088, 0.077, 0.074, 0.069, 0.061, 0.058, 0.054, 0.038, 0.023].

CONCLUSION

APOE3, age, and male gender was most important for predicting superior mouse cognitive performance.

摘要

背景

载脂蛋白 E(APOE)基因型通常会增加淀粉样蛋白-β沉积和临床阿尔茨海默病(AD)发病的风险。然而,在 APOE 转基因 AD 小鼠中的认知评估结果却存在差异。

目的

分析 31 篇经过同行评审的 AD APOE 小鼠研究出版物(n=3045 只小鼠),揭示了年龄、APOE 基因型、性别、调节治疗与认知之间的综合趋势。

方法

采用具有 Bonferroni 校正(显著性= p<0.002)的 t 检验比较野生型(WT)、APOE2 基因敲入(KI2)、APOE3 基因敲入(KI3)、APOE4 基因敲入(KI4)和 APOE 基因敲除(KO)小鼠的年龄归一化 Morris 水迷宫(MWM)逃逸潜伏期。阳性治疗(t+)有利于调节 APOE 以改善认知,阴性治疗(t-)干扰病因并降低认知,未治疗(t0)的小鼠进行比较。采用随机森林建模的机器学习方法根据 12 个特征预测 MWM 逃逸潜伏期性能:小鼠基因型(WT、KI2、KI3、KI4、KO)、调节治疗(t+、t-、t0)、小鼠年龄和小鼠性别(雄性=g_m;雌性=g_f,混合性别=g_mi)。

结果

KI3 小鼠在 MWM 中的表现明显更好,但 KI4 和 KO 小鼠的表现明显差于 WT 小鼠。KI2 小鼠的表现与 WT 相似。KI4 小鼠的表现明显比其他所有基因型都差。与未治疗组相比,阳性治疗组在 WT、KI4 和 KO 小鼠中的认知能力显著提高。有趣的是,在 KI4 小鼠中,阴性治疗也显著提高了平均 MWM 逃逸潜伏期。随机森林模型预测优异 MWM 表现的特征重要性如下:[KI3、年龄、g_m、KI4、t0、t+、KO、WT、g_mi、t-、g_f、KI2]=[0.270、0.094、0.092、0.088、0.077、0.074、0.069、0.061、0.058、0.054、0.038、0.023]。

结论

APOE3、年龄和雄性是预测小鼠认知表现优异的最重要因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cee/8461675/fb93c4f0b65b/jad-83-jad210492-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验