James D Doecke, Simon M Laws, Noel G Faux, William Wilson, Samantha C Burnham, Chiou-Peng Lam, Alinda Mondal, Justin Bedo, Ashley I Bush, Belinda Brown, Karl De Ruyck, Kathryn A Ellis, Christopher Fowler, Veer B Gupta, Richard Head, S Lance Macaulay, Kelly Pertile, Christopher C Rowe, Alan Rembach, Mark Rodrigues, Rebecca Rumble, Cassandra Szoeke, Kevin Taddei, Tania Taddei, Brett Trounson, David Ames, Colin L Masters, Ralph N Martins
{"title":"用于阿尔茨海默病诊断的血液蛋白生物标志物。","authors":"James D Doecke, Simon M Laws, Noel G Faux, William Wilson, Samantha C Burnham, Chiou-Peng Lam, Alinda Mondal, Justin Bedo, Ashley I Bush, Belinda Brown, Karl De Ruyck, Kathryn A Ellis, Christopher Fowler, Veer B Gupta, Richard Head, S Lance Macaulay, Kelly Pertile, Christopher C Rowe, Alan Rembach, Mark Rodrigues, Rebecca Rumble, Cassandra Szoeke, Kevin Taddei, Tania Taddei, Brett Trounson, David Ames, Colin L Masters, Ralph N Martins","doi":"10.1001/archneurol.2012.1282","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD).</p><p><strong>Design: </strong>Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data.</p><p><strong>Setting: </strong>General community-based, prospective, longitudinal study of aging.</p><p><strong>Participants: </strong>A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort.</p><p><strong>Results: </strong>A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve.</p><p><strong>Conclusions: </strong>This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.</p>","PeriodicalId":8321,"journal":{"name":"Archives of neurology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archneurol.2012.1282","citationCount":"362","resultStr":"{\"title\":\"Blood-based protein biomarkers for diagnosis of Alzheimer disease.\",\"authors\":\"James D Doecke, Simon M Laws, Noel G Faux, William Wilson, Samantha C Burnham, Chiou-Peng Lam, Alinda Mondal, Justin Bedo, Ashley I Bush, Belinda Brown, Karl De Ruyck, Kathryn A Ellis, Christopher Fowler, Veer B Gupta, Richard Head, S Lance Macaulay, Kelly Pertile, Christopher C Rowe, Alan Rembach, Mark Rodrigues, Rebecca Rumble, Cassandra Szoeke, Kevin Taddei, Tania Taddei, Brett Trounson, David Ames, Colin L Masters, Ralph N Martins\",\"doi\":\"10.1001/archneurol.2012.1282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD).</p><p><strong>Design: </strong>Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data.</p><p><strong>Setting: </strong>General community-based, prospective, longitudinal study of aging.</p><p><strong>Participants: </strong>A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort.</p><p><strong>Results: </strong>A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve.</p><p><strong>Conclusions: </strong>This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.</p>\",\"PeriodicalId\":8321,\"journal\":{\"name\":\"Archives of neurology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1001/archneurol.2012.1282\",\"citationCount\":\"362\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of neurology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1001/archneurol.2012.1282\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1001/archneurol.2012.1282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blood-based protein biomarkers for diagnosis of Alzheimer disease.
Objective: To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD).
Design: Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data.
Setting: General community-based, prospective, longitudinal study of aging.
Participants: A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort.
Results: A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve.
Conclusions: This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.