Predictive Modeling of Alzheimer's and Parkinson's Disease Using Metabolomic and Lipidomic Profiles from Cerebrospinal Fluid

作者全名："Hwangbo, Nathan; Zhang, Xinyu; Raftery, Daniel; Gu, Haiwei; Hu, Shu-Ching; Montine, Thomas J.; Quinn, Joseph F.; Chung, Kathryn A.; Hiller, Amie L.; Wang, Dongfang; Fei, Qiang; Bettcher, Lisa; Zabetian, Cyrus P.; Peskind, Elaine R.; Li, Ge; Promislow, Daniel E. L.; Davis, Marie Y.; Franks, Alexander"

作者地址："[Hwangbo, Nathan; Franks, Alexander] Univ Calif Santa Barbara, Dept Stat & Appl Probabil, Santa Barbara, CA 93106 USA; [Zhang, Xinyu; Raftery, Daniel; Gu, Haiwei; Wang, Dongfang; Fei, Qiang; Bettcher, Lisa] Univ Washington, Northwest Metabol Res Ctr, Dept Anesthesiol & Pain Med, Sch Med, Seattle, WA 98195 USA; [Hu, Shu-Ching; Zabetian, Cyrus P.; Peskind, Elaine R.; Li, Ge; Davis, Marie Y.] Vet Affairs Puget Sound Hlth Care Syst, Seattle, WA 98108 USA; [Hu, Shu-Ching; Zabetian, Cyrus P.; Davis, Marie Y.] Univ Washington, Dept Neurol, Sch Med, Seattle, WA 98195 USA; [Montine, Thomas J.] Stanford Univ, Dept Pathol, Sch Med, Palo Alto, CA 94304 USA; [Quinn, Joseph F.; Chung, Kathryn A.; Hiller, Amie L.] Portland VA Med Ctr, Portland, OR 97239 USA; [Quinn, Joseph F.; Chung, Kathryn A.; Hiller, Amie L.] Oregon Hlth & Sci Univ, Dept Neurol, Portland, OR 97239 USA; [Peskind, Elaine R.; Li, Ge] Univ Washington, Dept Psychiat & Behav Sci, Sch Med, Seattle, WA 98102 USA; [Promislow, Daniel E. L.] Univ Washington, Dept Biol, Seattle, WA 98105 USA; [Promislow, Daniel E. L.] Univ Washington, Dept Lab Med & Pathol, Sch Med, Seattle, WA 98195 USA; [Wang, Dongfang] Chongqing Med Univ, Affiliated Hosp 1, Chongqing 400016, Peoples R China"

通信作者："Hwangbo, N (通讯作者)，Univ Calif Santa Barbara, Dept Stat & Appl Probabil, Santa Barbara, CA 93106 USA."

来源：METABOLITES

ESI学科分类：BIOLOGY & BIOCHEMISTRY

WOS号：WOS:000785036700001

JCR分区：Q2

影响因子：4.1

年份：2022

卷号：12

期号：4

开始页：　

结束页：　

文献类型：Article

关键词：predictive modeling; biomarker; cerebrospinal fluid; cross-sectional study; neurodegenerative disease

摘要："In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies."

基金机构："National Institutes of Health [P50 AG05136, S10 OD021562, R03 CA211160, R01 AG057330, P50 NS062684, R01 NS119897]; Veterans Affairs Puget Sound Healthcare System [I01 CX001702]; Veterans Affairs Northwest Mental Illness Research, Education, and Clinical Center [IK2 BX003244]"

基金资助正文："This research was funded by the National Institutes of Health (Grant Nos. P50 AG05136 and S10 OD021562, R03 CA211160, R01 AG057330, P50 NS062684, R01 NS119897), the Veterans Affairs Puget Sound Healthcare System (Grant No. I01 CX001702), and the Veterans Affairs Northwest Mental Illness Research, Education, and Clinical Center (Grant No. IK2 BX003244), and an anonymous foundation."