Trends in Alzheimer's Disease Research Based upon Machine Learning Analysis of PubMed Abstracts
Trends in Alzheimer's Disease Research Based upon Machine Learning Analysis of PubMed Abstracts
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基于 PubMed 摘要机器学习分析的阿尔茨海默病研究趋势
DOI：
10.7150/ijbs.35743
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发表时间：
2019-01-01
影响因子：
9.2
通讯作者：
Feng, Xiaoyue
中科院分区：
文献类型：
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作者：
Guan, Renchu;Wen, Xiaojing;Feng, Xiaoyue
2015年，全球约有2980万人被诊断患有阿尔茨海默病（AD），预计到2050年这一数字将增加两倍。2018年，AD是美国65岁及以上人群的第五大死因，但AD药物研究进展十分有限。明确AD发病的关键因素和研究动态，有助于指导更深入、更有效的研究。我们提出了一个名为LDAP的框架，该框架结合了潜在Dirichlet分配模型和亲和传播算法，从2007年至2016年发表的95，876篇AD相关论文中提取研究主题。对LDAP结果进行趋势和热点分析。发现近10年来AD研究的重点包括15种疾病、15种氨基酸、肽和蛋白质、9种酶和辅酶、7种激素、7种碳水化合物、5种脂质、2种有机膦酸酯、18种化学物质、11种化合物、13种症状和20种现象。我们的LDAP框架使我们能够跟踪研究趋势的演变以及疾病、蛋白质、症状和现象方面最受欢迎的领域（热点）。同时，共鉴定出556个AD相关基因，这些基因主要分布在AD途径和氮代谢途径等12条KEGG途径中。我们的结果可在https://www.keaml.cn/Alzheimer上免费获得。
About 29.8 million people worldwide had been diagnosed with Alzheimer's disease (AD) in 2015, and the number is projected to triple by 2050. In 2018, AD was the fifth leading cause of death in Americans with 65 years of age or older, but the progress of AD drug research is very limited. It is helpful to identify the key factors and research trends of AD for guiding further more effective studies. We proposed a framework named as LDAP, which combined the latent Dirichlet allocation model and affinity propagation algorithm to extract research topics from 95,876 AD-related papers published from 2007 to 2016. Trends and hotspots analyses were performed on LDAP results. We found that the focus points of AD research for the past 10 years include 15 diseases, 15 amino acids, peptides, and proteins, 9 enzymes and coenzymes, 7 hormones, 7 carbohydrates, 5 lipids, 2 organophosphonates, 18 chemicals, 11 compounds, 13 symptoms, and 20 phenomena. Our LDAP framework allowed us to trace the evolution of research trends and the most popular areas of interest (hotspots) on disease, protein, symptom, and phenomena. Meanwhile, 556 AD related-genes were identified, which are enriched in 12 KEGG pathways including the AD pathway and nitrogen metabolism pathway. Our results are freely available at https://www.keaml.cn/Alzheimer.