TY - JOUR
T1 - Predicting amyloid PET and tau PET stages with plasma biomarkers
AU - Jack, Clifford R.
AU - Wiste, Heather J.
AU - Algeciras-Schimnich, Alicia
AU - Figdore, Dan J.
AU - Schwarz, Christopher G.
AU - Lowe, Val J.
AU - Ramanan, Vijay K.
AU - Vemuri, Prashanthi
AU - Mielke, Michelle M.
AU - Knopman, David S.
AU - Graff-Radford, Jonathan
AU - Boeve, Bradley F.
AU - Kantarci, Kejal
AU - Cogswell, Petrice M.
AU - Senjem, Matthew L.
AU - Gunter, Jeffrey L.
AU - Therneau, Terry M.
AU - Petersen, Ronald C.
N1 - Funding Information:
C.R.J. receives funding from the NIH and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Clinic. A.A.-S. has participated in advisory boards for Roche Diagnostics, Fujirebio Diagnostics and Siemens Healthineers. B.F.B. receives honoraria for SAB activities for the Tau Consortium; grant support for clinical trials from Alector, Biogen, Transposon, Cognition Therapeutics, GE Healthcare; and grant support from the NIH, Lewy Body Dementia Association, American Brain Foundation and Little Family Foundation Professorship. K.K. received research support from Avid Radiopharmaceuticals, Eli Lilly and consults for Biogen. She is supported by the NIH. T.M.T. receives NIH support (C.R.J.’s grant). M.M.M. receives research support from the NIH and DOD and has consulted for Biogen, Brain Protection Company, LabCorp, Lilly, Merck, Roche, Siemens Healthineers and Sunbird Bio. D.S.K. serves on a Data Safety Monitoring Board for the Dominantly Inherited Alzheimer Network Treatment Unit study. He served on a Data Safety Monitoring Board for a tau therapeutic for Biogen (until 2021) but received no personal compensation. He is an investigator in clinical trials sponsored by Biogen, Lilly Pharmaceuticals and the University of Southern California. He has served as a consultant for Roche, Samus Therapeutics, Magellan Health, Biovie and Alzeca Biosciences but receives no personal compensation. He attended an Eisai advisory board meeting for lecanemab on 2 December 2022, but received no compensation. He receives funding from the NIH. J.G.-R. receives funding from the NIH. He is an investigator in clinical trials sponsored by Biogen, Eisai and the University of Southern California. V.J.L. consults for Bayer Schering Pharma, Piramal Life Sciences, Eisai, Inc., AVID Radiopharmaceuticals and Merck Research, and receives research support from GE Healthcare, Siemens Molecular Imaging, AVID Radiopharmaceuticals and the NIH (NIA, NCI). P.V. receives funding from the NIH. C.G.S. receives funding from the NIH. R.C.P. has consulted for Roche, Inc.; Genentech, Inc.; Eli Lilly, Inc.; Nestle, Inc. and Eisai, Inc.; a DSMB for Genentech, Inc. and receives royalties from Oxford University Press for Mild Cognitive Impairment and from UpToDate. His research funding is from NIH/NIA. The other authors report no competing interests.
Funding Information:
Funding was provided by the National Institutes of Health (R37 AG011378, RO1 AG041851, R01 AG056366, R01 NS097495, U01 AG06786, R01 AG034676) and the GHR Foundation. Funders had no role in design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication. The corresponding author had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Publisher Copyright:
© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Staging the severity of Alzheimer’s disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer’s Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer’s clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1–2, 3–4, 5–6) and a combined amyloid and tau PET stage (none/low versus intermediate/ high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1–42 and Aβ1–40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78–0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72–0.85 versus C = 0.73–0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer’s disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
AB - Staging the severity of Alzheimer’s disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer’s Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer’s clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1–2, 3–4, 5–6) and a combined amyloid and tau PET stage (none/low versus intermediate/ high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1–42 and Aβ1–40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78–0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72–0.85 versus C = 0.73–0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer’s disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
KW - Alzheimer’s biomarkers
KW - amyloid PET
KW - plasma biomarkers
KW - staging Alzheimer’s disease
KW - tau PET
UR - http://www.scopus.com/inward/record.url?scp=85159248719&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159248719&partnerID=8YFLogxK
U2 - 10.1093/brain/awad042
DO - 10.1093/brain/awad042
M3 - Article
C2 - 36789483
AN - SCOPUS:85159248719
SN - 0006-8950
VL - 146
SP - 2029
EP - 2044
JO - Brain
JF - Brain
IS - 5
ER -