A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease

doi:10.1093/gigascience/giy085

	A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease
	Zhang, Hongjiu 7; Zhu, Fan 7,8; Dodge, Hiroko H.1,2,9,10; Higgins, Gerald A.7; Omenn, Gilbert S.3,4,6,7; Guan, Yuanfang 3,5,7
刊名	GIGASCIENCE
	2018-07-11
卷号	7 期号:7 页码:10
关键词	Gaussian Process Regression Alzheimer's Disease Patient similarity network Kernel method Machine learning
ISSN号	2047-217X
DOI	10.1093/gigascience/giy085
通讯作者	Guan, Yuanfang(gyuanfan@umich.edu)
英文摘要	Motivation: Heterogeneous diseases such as Alzheimer's disease (AD) manifest a variety of phenotypes among populations. Early diagnosis and effective treatment offer cost benefits. Many studies on biochemical and imaging markers have shown potential promise in improving diagnosis, yet establishing quantitative diagnostic criteria for ancillary tests remains challenging. Results: We have developed a similarity-based approach that matches individuals to subjects with similar conditions. We modeled the disease with a Gaussian process, and tested the method in the Alzheimer's Disease Big Data DREAM Challenge. Ranked the highest among submitted methods, our diagnostic model predicted cognitive impairment scores in an independent dataset test with a correlation score of 0.573. It differentiated AD patients from control subjects with an area under the receiver operating curve of 0.920. Without knowing longitudinal information about subjects, the model predicted patients who are vulnerable to conversion from mild-cognitive impairment to AD through the similarity network. This diagnostic framework can be applied to other diseases with clinical heterogeneity, such as Parkinson's disease.
资助项目	National Institutes of Health and National Institute of Aging (Michigan Alzheimer Disease Core Center)[P30AG053760] ; National Science Foundation[1452656] ; Alzheimer's Association ; Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health)[U01 AG024904] ; Department of Defense ADNI[W81XWH-12-2-0012] ; National Institute on Aging ; National Institute of Biomedical Imaging and Bioengineering ; Canadian Institutes of Health Research ; Michael J. Fox Foundation for Parkinson's Research ; Avid Radiopharmaceutical ; Biogen ; Biolegend ; Bristol-Myers Squibb Company ; GE Healthcare ; Genentech ; GlaxoSmithKline ; Golub Capital ; Eli Lilly Co. ; Lundbeck; Merck Co., Inc. ; Meso Scale Discovery ; Pfizer, Inc. ; Piramal Imaging ; Roche ; Sanofi Genzyme ; Servier ; Takeda Pharmaceutical Company ; Teva ; UCB
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	OXFORD UNIV PRESS
WOS记录号	WOS:000439312000002
内容类型	期刊论文
源URL	[http://119.78.100.138/handle/2HOD01W0/9726]
专题	中国科学院重庆绿色智能技术研究院
通讯作者	Guan, Yuanfang
作者单位	1.Oregon Hlth & Sci Univ, Layton Aging & Alzheimers Dis Ctr, 3181 SW Sam Jackson Pk Rd,L226, Portland, OR 97239 USA 2.Oregon Hlth & Sci Univ, Dept Neurol, 3181 SW Sam Jackson Pk Rd,L226, Portland, OR 97239 USA 3.Univ Michigan, Dept Internal Med, 3110 Taubman Ctr,SPC 5368,1500 East Med Ctr Dr, Ann Arbor, MI 48109 USA 4.Univ Michigan, Dept Human Genet, 4909 Buhl Bldg,1241 E Catherine St, Ann Arbor, MI 48109 USA 5.Univ Michigan, Dept Elect Engn & Comp Sci, Bob & Betty Beyster Bldg,2260 Hayward St, Ann Arbor, MI 48109 USA 6.Univ Michigan, Sch Publ Hlth, 1415 Washington Hts, Ann Arbor, MI 48109 USA 7.Univ Michigan, Dept Computat Med & Bioinformat, 2017G Palmer Commons,100 Washtenaw Ave, Ann Arbor, MI 48109 USA 8.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, 266 Fangzheng Ave,Shuitu Hitech Ind Pk, Chongqing 400714, Peoples R China 9.Univ Michigan, Michigan Alzheimers Dis Ctr, 2101 Commonwealth Blvd, Ann Arbor, MI 48105 USA 10.Univ Michigan, Dept Neurol, 1500 E Med Ctr Dr,1914 Taubman Ctr SPC 5316, Ann Arbor, MI 48109 USA
推荐引用方式 GB/T 7714	Zhang, Hongjiu,Zhu, Fan,Dodge, Hiroko H.,et al. A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease[J]. GIGASCIENCE,2018,7(7):10.
APA	Zhang, Hongjiu,Zhu, Fan,Dodge, Hiroko H.,Higgins, Gerald A.,Omenn, Gilbert S.,&Guan, Yuanfang.(2018).A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease.GIGASCIENCE,7(7),10.
MLA	Zhang, Hongjiu,et al."A similarity-based approach to leverage multi-cohort medical data on the diagnosis and prognosis of Alzheimer's disease".GIGASCIENCE 7.7(2018):10.