{"title":"炎性血浆生物标记物对病理生物标记物在预测临床前阿尔茨海默病方面的附加价值。","authors":"Haley Leclerc, Athene Kw Lee, Zachary J Kunicki, Jessica Alber","doi":"10.1177/13872877241283692","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-β (Aβ) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population.</p><p><strong>Objective: </strong>Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein (<i>APOE</i>) ɛ4 status) risk factors in detecting preclinical AD.</p><p><strong>Methods: </strong>125 cognitively unimpaired older adults (mean age = 66 years) who completed Aβ PET and plasma draw were analyzed using multiple regression with Aβ PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors <i>APOE</i> ɛ4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (Aβ<sub>42/40</sub> ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted Aβ PET status, and these markers were added in Model 4.</p><p><strong>Results: </strong>The best model for predicting Aβ PET status included age, years of education, <i>APOE</i> ɛ4 status, Aβ<sub>42/40</sub> ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model.</p><p><strong>Conclusions: </strong>Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.</p>","PeriodicalId":14929,"journal":{"name":"Journal of Alzheimer's Disease","volume":"102 1","pages":"89-98"},"PeriodicalIF":3.4000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540337/pdf/","citationCount":"0","resultStr":"{\"title\":\"Added value of inflammatory plasma biomarkers to pathologic biomarkers in predicting preclinical Alzheimer's disease.\",\"authors\":\"Haley Leclerc, Athene Kw Lee, Zachary J Kunicki, Jessica Alber\",\"doi\":\"10.1177/13872877241283692\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-β (Aβ) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population.</p><p><strong>Objective: </strong>Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein (<i>APOE</i>) ɛ4 status) risk factors in detecting preclinical AD.</p><p><strong>Methods: </strong>125 cognitively unimpaired older adults (mean age = 66 years) who completed Aβ PET and plasma draw were analyzed using multiple regression with Aβ PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors <i>APOE</i> ɛ4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (Aβ<sub>42/40</sub> ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted Aβ PET status, and these markers were added in Model 4.</p><p><strong>Results: </strong>The best model for predicting Aβ PET status included age, years of education, <i>APOE</i> ɛ4 status, Aβ<sub>42/40</sub> ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model.</p><p><strong>Conclusions: </strong>Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.</p>\",\"PeriodicalId\":14929,\"journal\":{\"name\":\"Journal of Alzheimer's Disease\",\"volume\":\"102 1\",\"pages\":\"89-98\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540337/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Alzheimer's Disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/13872877241283692\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/3 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Alzheimer's Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/13872877241283692","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/3 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
背景:最近出现了一些血浆生物标志物,可用于阿尔茨海默病(AD)的诊断、评估和疾病监测,但尚未在临床前AD中得到充分验证。除了阿兹海默病病理血浆生物标志物(淀粉样蛋白-β(Aβ)和磷酸化 tau(p-tau)物种)外,蛋白质组面板还能区分有症状的阿兹海默病和痴呆症门诊人群中认知功能未受损的老年人:方法:使用多元回归法分析了 125 名完成了 Aβ PET 和血浆抽样的认知功能未受损的老年人(平均年龄 = 66 岁),以 Aβ PET 状态(阳性与阴性)为结果,确定预测临床前 AD 的最佳拟合值。模型 1 包括年龄、教育程度和性别。模型 2 和 3 分别增加了 APOE ɛ4 状态(携带者与非携带者)和 AD 病理血液生物标记物(Aβ42/40 比率、p-tau181)预测因子。随机森林模型确定了蛋白质组中最能预测 Aβ PET 状态的 5 个蛋白质组标记物,并将这些标记物添加到模型 4.结果中:结果:预测 Aβ PET 状态的最佳模型包括年龄、受教育年限、APOE ɛ4 状态、Aβ42/40 比率和 p-tau181。加入前 5 个蛋白质组标记物并不能明显改善模型:在该样本中,血浆中的蛋白质组标记物在预测临床前注意力缺失症方面没有增加标准注意力缺失症病理血浆生物标记物的预测价值。
Added value of inflammatory plasma biomarkers to pathologic biomarkers in predicting preclinical Alzheimer's disease.
Background: Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-β (Aβ) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population.
Objective: Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein (APOE) ɛ4 status) risk factors in detecting preclinical AD.
Methods: 125 cognitively unimpaired older adults (mean age = 66 years) who completed Aβ PET and plasma draw were analyzed using multiple regression with Aβ PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors APOE ɛ4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (Aβ42/40 ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted Aβ PET status, and these markers were added in Model 4.
Results: The best model for predicting Aβ PET status included age, years of education, APOE ɛ4 status, Aβ42/40 ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model.
Conclusions: Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.
期刊介绍:
The Journal of Alzheimer''s Disease (JAD) is an international multidisciplinary journal to facilitate progress in understanding the etiology, pathogenesis, epidemiology, genetics, behavior, treatment and psychology of Alzheimer''s disease. The journal publishes research reports, reviews, short communications, hypotheses, ethics reviews, book reviews, and letters-to-the-editor. The journal is dedicated to providing an open forum for original research that will expedite our fundamental understanding of Alzheimer''s disease.