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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.date.accessioned2022-06-22T19:20:57Z
dc.date.available2022-06-22T19:20:57Z
dc.date.issued2021-02-02
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. https://doi.org/10.3233/JAD-201318en_US
dc.identifier.urihttp://hdl.handle.net/1808/32789
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.subjectBiomarkeren_US
dc.subjectBlacken_US
dc.subjectDiscoveryen_US
dc.subjectDisparitiesen_US
dc.subjectMachine learningen_US
dc.subjectPlasmaen_US
dc.subjectProteomicsen_US
dc.subjectRaceen_US
dc.titleWhy Inclusion Matters for Alzheimer’s Disease Biomarker Discovery in Plasmaen_US
dc.typeArticleen_US
kusw.kuauthorDesaire, Heather
kusw.kudepartmentChemistryen_US
dc.identifier.doi10.3233/JAD-201318en_US
kusw.oaversionScholarly/refereed, author accepted manuscripten_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC9126484en_US
dc.rights.accessrightsopenAccessen_US


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