Show simple item record

dc.contributor.authorKhan, Mostafa J.
dc.contributor.authorDesaire, Heather
dc.contributor.authorLopez, Oscar L.
dc.contributor.authorKamboh, M. Ilyas
dc.contributor.authorRobinson, Renã A.S.
dc.identifier.citationKhan, M. J., Desaire, H., Lopez, O. L., Kamboh, M. I., & Robinson, R. (2021). Why Inclusion Matters for Alzheimer's Disease Biomarker Discovery in Plasma. Journal of Alzheimer's disease : JAD, 79(3), 1327–1344.
dc.description.abstractBackground:African American/Black adults have a disproportionate incidence of Alzheimer’s disease (AD) and are underrepresented in biomarker discovery efforts. Objective:This study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults. Methods:We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates. Results:In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD. Conclusion:These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.en_US
dc.publisherIOS Pressen_US
dc.rightsCopyright Kahn et. alen_US
dc.subjectAfrican Americanen_US
dc.subjectAlzheimer’s diseaseen_US
dc.subjectMachine learningen_US
dc.titleWhy Inclusion Matters for Alzheimer’s Disease Biomarker Discovery in Plasmaen_US
kusw.kuauthorDesaire, Heather
kusw.oanotesPer Sherpa Romeo 06/22/2022:

Journal of Alzheimer's Disease [Open panel below]Publication Information TitleJournal of Alzheimer's Disease [English] ISSNsPrint: 1387-2877 URL PublishersIOS Press [Commercial Publisher] [Open panel below]Publisher Policy Open Access pathways permitted by this journal's policy are listed below by article version. Click on a pathway for a more detailed view.

Published Version [pathway a]

None Institutional Repository, Funder Designated Location, Institutional Website, +2 OA FeeThis pathway has an Open Access fee associated with it OA PublishingThis pathway includes Open Access publishing EmbargoNo Embargo Copyright OwnerAuthors Location Author's Homepage Funder Designated Location Institutional Repository Institutional Website Journal Website
kusw.oaversionScholarly/refereed, author accepted manuscripten_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US

Files in this item


This item appears in the following Collection(s)

Show simple item record