Joseph Therriault, Shorena Janelidze, Andréa Lessa Benedet, Nicholas J. Ashton, Javier Arranz Martínez, Armand Gonzalez-Escalante, Bruna Bellaver, Daniel Alcolea, Agathe Vrillon, Helmet Karim, Michelle M. Mielke, Chang Hyung Hong, Hyun Woong Roh, José Contador, Albert Puig Pijoan, Alicia Algeciras-Schimnich, Prashanthi Vemuri, Jonathan Graff-Radford, Val J. Lowe, Thomas K. Karikari, Erin Jonaitis, Wagner Brum, Cécile Tissot, Stijn Servaes, Nesrine Rahmouni, Arthur C. Macedo, Jenna Stevenson, Jaime Fernandez-Arias, Yi-Ting Wang, Marcel S. Woo, Manuel A. Friese, Wan Lu Jia, Julien Dumurgier, Claire Hourregue, Emmanuel Cognat, Pamela Lukasewicz Ferreira, Paolo Vitali, Sterling Johnson, Tharick A. Pascoal, Serge Gauthier, Alberto Lleó, Claire Paquet, Ronald C. Petersen, David Salmon, Niklas Mattsson-Carlgren, Sebastian Palmqvist, Erik Stomrud, Douglas Galasko, Sang Joon Son, Henrik Zetterberg, Juan Fortea, Marc Suárez-Calvet, Clifford R. Jack Jr, Kaj Blennow, Oskar Hansson, Pedro Rosa-Neto
{"title":"利用根据临床概率调整的血浆生物标志物诊断阿尔茨海默病。","authors":"Joseph Therriault, Shorena Janelidze, Andréa Lessa Benedet, Nicholas J. Ashton, Javier Arranz Martínez, Armand Gonzalez-Escalante, Bruna Bellaver, Daniel Alcolea, Agathe Vrillon, Helmet Karim, Michelle M. Mielke, Chang Hyung Hong, Hyun Woong Roh, José Contador, Albert Puig Pijoan, Alicia Algeciras-Schimnich, Prashanthi Vemuri, Jonathan Graff-Radford, Val J. Lowe, Thomas K. Karikari, Erin Jonaitis, Wagner Brum, Cécile Tissot, Stijn Servaes, Nesrine Rahmouni, Arthur C. Macedo, Jenna Stevenson, Jaime Fernandez-Arias, Yi-Ting Wang, Marcel S. Woo, Manuel A. Friese, Wan Lu Jia, Julien Dumurgier, Claire Hourregue, Emmanuel Cognat, Pamela Lukasewicz Ferreira, Paolo Vitali, Sterling Johnson, Tharick A. Pascoal, Serge Gauthier, Alberto Lleó, Claire Paquet, Ronald C. Petersen, David Salmon, Niklas Mattsson-Carlgren, Sebastian Palmqvist, Erik Stomrud, Douglas Galasko, Sang Joon Son, Henrik Zetterberg, Juan Fortea, Marc Suárez-Calvet, Clifford R. Jack Jr, Kaj Blennow, Oskar Hansson, Pedro Rosa-Neto","doi":"10.1038/s43587-024-00731-y","DOIUrl":null,"url":null,"abstract":"Recently approved anti-amyloid immunotherapies for Alzheimer’s disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing. Therriault et al. provide a framework for the individual-level interpretation of plasma biomarkers by determining their positive and negative predictive values for amyloid positron emission tomography status in relation to patient age and clinical symptoms.","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":"4 11","pages":"1529-1537"},"PeriodicalIF":17.0000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43587-024-00731-y.pdf","citationCount":"0","resultStr":"{\"title\":\"Diagnosis of Alzheimer’s disease using plasma biomarkers adjusted to clinical probability\",\"authors\":\"Joseph Therriault, Shorena Janelidze, Andréa Lessa Benedet, Nicholas J. Ashton, Javier Arranz Martínez, Armand Gonzalez-Escalante, Bruna Bellaver, Daniel Alcolea, Agathe Vrillon, Helmet Karim, Michelle M. Mielke, Chang Hyung Hong, Hyun Woong Roh, José Contador, Albert Puig Pijoan, Alicia Algeciras-Schimnich, Prashanthi Vemuri, Jonathan Graff-Radford, Val J. Lowe, Thomas K. Karikari, Erin Jonaitis, Wagner Brum, Cécile Tissot, Stijn Servaes, Nesrine Rahmouni, Arthur C. Macedo, Jenna Stevenson, Jaime Fernandez-Arias, Yi-Ting Wang, Marcel S. Woo, Manuel A. Friese, Wan Lu Jia, Julien Dumurgier, Claire Hourregue, Emmanuel Cognat, Pamela Lukasewicz Ferreira, Paolo Vitali, Sterling Johnson, Tharick A. Pascoal, Serge Gauthier, Alberto Lleó, Claire Paquet, Ronald C. Petersen, David Salmon, Niklas Mattsson-Carlgren, Sebastian Palmqvist, Erik Stomrud, Douglas Galasko, Sang Joon Son, Henrik Zetterberg, Juan Fortea, Marc Suárez-Calvet, Clifford R. 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Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing. 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Diagnosis of Alzheimer’s disease using plasma biomarkers adjusted to clinical probability
Recently approved anti-amyloid immunotherapies for Alzheimer’s disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing. Therriault et al. provide a framework for the individual-level interpretation of plasma biomarkers by determining their positive and negative predictive values for amyloid positron emission tomography status in relation to patient age and clinical symptoms.