Browsing by Author "Petersen, Ronald C."
Now showing 1 - 10 of 41
Results Per Page
Sort Options
Item 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception(Elsevier, 2016-06-01) Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Luthman, Johan; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W.; Trojanowski, John Q.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineThe Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.Item The Alzheimer's Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans(Elsevier, 2015-07) Kang, Ju-Hee; Korecka, Magdalena; Figurski, Michal J.; Toledo, Jon B.; Blennow, Kaj; Zetterberg, Henrik; Waligorska, Teresa; Brylska, Magdalena; Fields, Leona; Shah, Nirali; Soares, Holly; Dean, Robert A.; Vanderstichele, Hugo; Petersen, Ronald C.; Aisen, Paul S.; Saykin, Andrew J.; Weiner, Michael W.; Trojanowski, John Q.; Shaw, Leslie M.; Alzheimer's Disease Neuroimaging Initiative; Department of Radiology and Imaging Sciences, School of MedicineINTRODUCTION: We describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids. METHODS: Review publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data. RESULTS: CSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies. DISCUSSION: Further studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials.Item The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement(Elsevier, 2017-05) Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R., Jr.; Jagust, William; Morris, John C.; Petersen, Ronald C.; Salazar, Jennifer; Saykin, Andrew J.; Shaw, Leslie M.; Toga, Arthur W.; Trojanowski, John Q.; Radiology and Imaging Sciences, School of MedicineINTRODUCTION: The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study. METHODS: ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. RESULTS: Multimodal analyses will provide insight into AD pathophysiology and disease progression. DISCUSSION: ADNI-3 will aim to inform AD treatment trials and facilitate development of AD disease-modifying treatments.Item Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer's disease(Springer Nature, 2017-05-24) Nho, Kwangsik; Kim, Sungeun; Horgusluoglu, Emrin; Risacher, Shannon L.; Shen, Li; Kim, Dokyoon; Lee, Seunggeun; Foroud, Tatiana; Shaw, Leslie M.; Trojanowski, John Q.; Aisen, Paul S.; Petersen, Ronald C.; Jack, Clifford R., Jr.; Weiner, Michael W.; Green, Robert C.; Toga, Arthur W.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineBACKGROUND: The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer's disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD. METHODS: Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sequence data from 757 non-Hispanic Caucasian participants was used in the present analysis. We extracted all rare variants (MAF (minor allele frequency) < 0.05) within a 312 kb window in APOE's vicinity encompassing 12 genes. We assessed CSF and neuroimaging (MRI and PET) biomarkers as LOAD-related quantitative endophenotypes. Gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). RESULTS: A total of 3,334 rare variants (MAF < 0.05) were found within the APOE region. Among them, 72 rare non-synonymous variants were observed. Eight genes spanning the APOE region were significantly associated with CSF Aβ1-42 (p < 1.0 × 10-3). After controlling for APOE genotype and adjusting for multiple comparisons, 4 genes (CBLC, BCAM, APOE, and RELB) remained significant. Whole-brain surface-based analysis identified highly significant clusters associated with rare variants of CBLC in the temporal lobe region including the entorhinal cortex, as well as frontal lobe regions. Whole-brain voxel-wise analysis of amyloid PET identified significant clusters in the bilateral frontal and parietal lobes showing associations of rare variants of RELB with cortical amyloid burden. CONCLUSIONS: Rare variants within genes spanning the APOE region are significantly associated with LOAD-related CSF Aβ1-42 and neuroimaging biomarkers after adjusting for APOE genotype. These findings warrant further investigation and illustrate the role of next generation sequencing and quantitative endophenotypes in assessing rare variants which may help explain missing heritability in AD and other complex diseases.Item Association Between Anticholinergic Medication Use and Cognition, Brain Metabolism, and Brain Atrophy in Cognitively Normal Older Adults(American Medical Association, 2016-06-01) Risacher, Shannon Leigh; McDonald, Brenna C.; Tallman, Eileen F.; West, John D.; Farlow, Martin R.; Unverzagt, Fredrick W.; Gao, Sujuan; Boustani, Malaz; Crane, Paul K.; Petersen, Ronald C.; Jack, Clifford R.; Jagust, William J.; Aisen, Paul S.; Weiner, Michael W.; Saykin, Andrew J.; Department of Radiology and Imaging Sciences, School of MedicineIMPORTANCE: The use of anticholinergic (AC) medication is linked to cognitive impairment and an increased risk of dementia. To our knowledge, this is the first study to investigate the association between AC medication use and neuroimaging biomarkers of brain metabolism and atrophy as a proxy for understanding the underlying biology of the clinical effects of AC medications. OBJECTIVE: To assess the association between AC medication use and cognition, glucose metabolism, and brain atrophy in cognitively normal older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Indiana Memory and Aging Study (IMAS). DESIGN, SETTING, AND PARTICIPANTS: The ADNI and IMAS are longitudinal studies with cognitive, neuroimaging, and other data collected at regular intervals in clinical and academic research settings. For the participants in the ADNI, visits are repeated 3, 6, and 12 months after the baseline visit and then annually. For the participants in the IMAS, visits are repeated every 18 months after the baseline visit (402 cognitively normal older adults in the ADNI and 49 cognitively normal older adults in the IMAS were included in the present analysis). Participants were either taking (hereafter referred to as the AC+ participants [52 from the ADNI and 8 from the IMAS]) or not taking (hereafter referred to as the AC- participants [350 from the ADNI and 41 from the IMAS]) at least 1 medication with medium or high AC activity. Data analysis for this study was performed in November 2015. MAIN OUTCOMES AND MEASURES: Cognitive scores, mean fludeoxyglucose F 18 standardized uptake value ratio (participants from the ADNI only), and brain atrophy measures from structural magnetic resonance imaging were compared between AC+ participants and AC- participants after adjusting for potential confounders. The total AC burden score was calculated and was related to target measures. The association of AC use and longitudinal clinical decline (mean [SD] follow-up period, 32.1 [24.7] months [range, 6-108 months]) was examined using Cox regression. RESULTS: The 52 AC+ participants (mean [SD] age, 73.3 [6.6] years) from the ADNI showed lower mean scores on Weschler Memory Scale-Revised Logical Memory Immediate Recall (raw mean scores: 13.27 for AC+ participants and 14.16 for AC- participants; P = .04) and the Trail Making Test Part B (raw mean scores: 97.85 seconds for AC+ participants and 82.61 seconds for AC- participants; P = .04) and a lower executive function composite score (raw mean scores: 0.58 for AC+ participants and 0.78 for AC- participants; P = .04) than the 350 AC- participants (mean [SD] age, 73.3 [5.8] years) from the ADNI. Reduced total cortical volume and temporal lobe cortical thickness and greater lateral ventricle and inferior lateral ventricle volumes were seen in the AC+ participants relative to the AC- participants. CONCLUSIONS AND RELEVANCE: The use of AC medication was associated with increased brain atrophy and dysfunction and clinical decline. Thus, use of AC medication among older adults should likely be discouraged if alternative therapies are available.Item Association of plasma and cortical beta-amyloid is modulated by APOE ε4 status.(Elsevier, 2014-01) Swaminathan, Shanker; Risacher, Shannon L.; Yoder, Karmen K.; West, John D.; Shen, Li; Kim, Sungeun; Inlow, Mark; Foroud, Tatiana; Jagust, William J.; Koeppe, Robert A.; Mathis, Chester A.; Shaw, Leslie M.; Trojanowski, John Q.; Soares, Holly; Aisen, Paul S.; Petersen, Ronald C.; Weiner, Michael W.; Saykin, Andrew J.; Department of Radiology and Imaging Sciences, IU School of MedicineBackground: APOE ε4’s role as a modulator of the relationship between soluble plasma beta-amyloid (Aβ) and fibrillar brain Aβ measured by Pittsburgh Compound-B positron emission tomography ([11C]PiB PET) has not been assessed. Methods: Ninety-six Alzheimer’s Disease Neuroimaging Initiative participants with [11C]PiB scans and plasma Aβ1-40 and Aβ1-42 measurements at time of scan were included. Regional and voxel-wise analyses of [11C]PiB data were used to determine the influence of APOE ε4 on association of plasma Aβ1-40, Aβ1-42, and Aβ1-40/Aβ1-42 with [11C]PiB uptake. Results: In APOE ε4− but not ε4+ participants, positive relationships between plasma Aβ1-40/Aβ1-42 and [11C]PiB uptake were observed. Modeling the interaction of APOE and plasma Aβ1-40/Aβ1-42 improved the explained variance in [11C]PiB binding compared to using APOE and plasma Aβ1-40/Aβ1-42 as separate terms. Conclusions: The results suggest that plasma Aβ is a potential Alzheimer’s disease biomarker and highlight the importance of genetic variation in interpretation of plasma Aβ levels.Item Automated and manual hippocampal segmentation techniques: Comparison of results, reproducibility and clinical applicability(Elsevier, 2019) Hurtz, Sona; Chow, Nicole; Watson, Amity E.; Somme, Johanne H.; Goukasian, Naira; Hwang, Kristy S.; Morra, John; Elashoff, David; Gao, Sujuan; Petersen, Ronald C.; Aisen, Paul S.; Thompson, Paul M.; Apostolova, Liana G.; Biostatistics, School of Public HealthBACKGROUND: Imaging techniques used to measure hippocampal atrophy are key to understanding the clinical progression of Alzheimer's disease (AD). Various semi-automated hippocampal segmentation techniques are available and require human expert input to learn how to accurately segment new data. Our goal was to compare 1) the performance of our automated hippocampal segmentation technique relative to manual segmentations, and 2) the performance of our automated technique when provided with a training set from two different raters. We also explored the ability of hippocampal volumes obtained using manual and automated hippocampal segmentations to predict conversion from MCI to AD. METHODS: We analyzed 161 1.5 T T1-weighted brain magnetic resonance images (MRI) from the ADCS Donepezil/Vitamin E clinical study. All subjects carried a diagnosis of mild cognitive impairment (MCI). Three different segmentation outputs (one produced by manual tracing and two produced by a semi-automated algorithm trained with training sets developed by two raters) were compared using single measure intraclass correlation statistics (smICC). The radial distance method was used to assess each segmentation technique's ability to detect hippocampal atrophy in 3D. We then compared how well each segmentation method detected baseline hippocampal differences between MCI subjects who remained stable (MCInc) and those who converted to AD (MCIc) during the trial. Our statistical maps were corrected for multiple comparisons using permutation-based statistics with a threshold of p < .01. RESULTS: Our smICC analyses showed significant agreement between the manual and automated hippocampal segmentations from rater 1 [right smICC = 0.78 (95%CI 0.72-0.84); left smICC = 0.79 (95%CI 0.72-0.85)], the manual segmentations from rater 1 versus the automated segmentations from rater 2 [right smICC = 0.78 (95%CI 0.7-0.84); left smICC = 0.78 (95%CI 0.71-0.84)], and the automated segmentations of rater 1 versus rater 2 [right smICC = 0.97 (95%CI 0.96-0.98); left smICC = 0.97 (95%CI 0.96-0.98)]. All three segmentation methods detected significant CA1 and subicular atrophy in MCIc compared to MCInc at baseline (manual: right pcorrected = 0.0112, left pcorrected = 0.0006; automated rater 1: right pcorrected = 0.0318, left pcorrected = 0.0302; automated rater 2: right pcorrected = 0.0029, left pcorrected = 0.0166). CONCLUSIONS: The hippocampal volumes obtained with a fast semi-automated segmentation method were highly comparable to the ones obtained with the labor-intensive manual segmentation method. The AdaBoost automated hippocampal segmentation technique is highly reliable allowing the efficient analysis of large data sets.Item Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology(Oxford University Press, 2022) Morris, John C.; Weiner, Michael; Xiong, Chengjie; Beckett, Laurel; Coble, Dean; Saito, Naomi; Aisen, Paul S.; Allegri, Ricardo; Benzinger, Tammie L. S.; Berman, Sarah B.; Cairns, Nigel J.; Carrillo, Maria C.; Chui, Helena C.; Chhatwal, Jasmeer P.; Cruchaga, Carlos; Fagan, Anne M.; Farlow, Martin; Fox, Nick C.; Ghetti, Bernardino; Goate, Alison M.; Gordon, Brian A.; Graff-Radford, Neill; Day, Gregory S.; Hassenstab, Jason; Ikeuchi, Takeshi; Jack, Clifford R.; Jagust, William J.; Jucker, Mathias; Levin, Johannes; Massoumzadeh, Parinaz; Masters, Colin L.; Martins, Ralph; McDade, Eric; Mori, Hiroshi; Noble, James M.; Petersen, Ronald C.; Ringman, John M.; Salloway, Stephen; Saykin, Andrew J.; Schofield, Peter R.; Shaw, Leslie M.; Toga, Arthur W.; Trojanowski, John Q.; Vöglein, Jonathan; Weninger, Stacie; Bateman, Randall J.; Buckles, Virginia D.; Dominantly Inherited Alzheimer Network; Alzheimer’s Disease Neuroimaging and Initiative; Neurology, School of MedicineThe extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.Item Comparison of CSF phosphorylated tau 181 and 217 for cognitive decline(Wiley, 2022) Mielke, Michelle M.; Aakre, Jeremiah A.; Algeciras-Schimnich, Alicia; Proctor, Nicholas K.; Machulda, Mary M.; Eichenlaub, Udo; Knopman, David S.; Vemuri, Prashanthi; Graff-Radford, Jonathan; Jac, Clifford R., Jr.; Petersen, Ronald C.; Dage, Jeffrey L.; Neurology, School of MedicineIntroduction: The prognostic utility of cerebrospinal fluid (CSF) phosphorylated tau 217 (p-tau217) and p-tau181 is not understood. Methods: Analyses included 753 Mayo Clinic Study on Aging participants (median age = 71.6; 57% male). CSF amyloid beta (Aβ)42 and p-tau181 were measured with Elecsys immunoassays. CSF p-tau181 and p-tau217 were also measured with Meso Scale Discovery (MSD). We used Cox proportional hazards models for risk of mild cognitive impairment (MCI) and linear mixed models for risk of global and domain-specific cognitive decline and cortical thickness. Analyses were stratified by elevated brain amyloid based on CSF Aβ42 or amyloid positron emission tomography for those with imaging. Results: CSF p-tau217 was superior to p-tau181 for the diagnosis of Alzheimer's disease (AD) pathology. CSF MSD p-tau181 and p-tau217 were associated with risk of MCI among amyloid-positive individuals. Differences between CSF p-tau measures predicting cortical thickness were subtle. Discussion: There are subtle differences for CSF p-tau217 and p-tau181 as prognostic AD markers.Item Comparison of Plasma Phosphorylated Tau Species With Amyloid and Tau Positron Emission Tomography, Neurodegeneration, Vascular Pathology, and Cognitive Outcomes(American Medical Association, 2021) Mielke, Michelle M.; Frank, Ryan D.; Dage, Jeffrey L.; Jeromin, Andreas; Ashton, Nicholas J.; Blennow, Kaj; Karikari, Thomas K.; Vanmechelen, Eugene; Zetterberg, Henrik; Algeciras-Schimnich, Alicia; Knopman, David S.; Lowe, Val; Bu, Guojun; Vemuri, Prashanthi; Graff-Radford, Jonathan; Jack, Clifford R., Jr.; Petersen, Ronald C.; Neurology, School of MedicineImportance: Cerebrospinal fluid phosphorylated tau (p-tau) 181, p-tau217, and p-tau231 are associated with neuropathological outcomes, but a comparison of these p-tau isoforms in blood samples is needed. Objective: To conduct a head-to-head comparison of plasma p-tau181 and p-tau231 measured on the single-molecule array (Simoa) platform and p-tau181 and p-tau217 measured on the Meso Scale Discovery (MSD) platform on amyloid and tau positron emission tomography (PET) measures, neurodegeneration, vascular pathology, and cognitive outcomes. Design, setting, and participants: This study included data from the Mayo Clinic Study on Aging collected from March 1, 2015, to September 30, 2017, and analyzed between December 15, 2020, and May 17, 2021. Associations between the 4 plasma p-tau measures and dichotomous amyloid PET, metaregion of interest tau PET, and entorhinal cortex tau PET were analyzed using logistic regression models; the predictive accuracy was summarized using area under the receiver operating characteristic curve (AUROC) statistic. Of 1329 participants without dementia and with p-tau181 and p-tau217 on MSD, 200 participants with plasma p-tau181 and p-tau231 on Simoa and magnetic resonance imaging and amyloid and tau PET data at the same study visit were eligible. Main outcomes and measures: Primary outcomes included amyloid (greater than 1.48 standardized uptake value ratio) and tau PET, white matter hyperintensities, white matter microstructural integrity (fractional anisotropy genu of corpus callosum and hippocampal cingulum bundle), and cognition. Results: Of 200 included participants, 101 (50.5%) were male, and the median (interquartile range [IQR]) age was 79.5 (71.1-84.1) years. A total of 177 were cognitively unimpaired (CU) and 23 had mild cognitive impairment. Compared with amyloid-negative CU participants, among amyloid-positive CU participants, the median (IQR) Simoa p-tau181 measure was 49% higher (2.58 [2.00-3.72] vs 1.73 [1.45-2.13] pg/mL), MSD p-tau181 measure was 53% higher (1.22 [0.91-1.56] vs 0.80 [0.66-0.97] pg/mL), MSD p-tau217 measure was 77% higher (0.23 [0.17-0.34] vs 0.13 [0.09-0.18] pg/mL), and Simoa p-tau231 measure was 49% higher (20.21 [15.60-25.41] vs 14.27 [11.27-18.10] pg/mL). There were no differences between the p-tau species for amyloid PET and tau PET metaregions of interest. However, among CU participants, both MSD p-tau181 and MSD p-tau217 more accurately predicted abnormal entorhinal cortex tau PET than Simoa p-tau181 (MSD p-tau181: AUROC, 0.80 vs 0.70; P = .046; MSD p-tau217: AUROC, 0.81 vs 0.70; P = .04). MSD p-tau181 and p-tau217 and Simoa p-tau181, but not p-tau231, were associated with greater white matter hyperintensity volume and lower white matter microstructural integrity. Conclusions and relevance: In this largely presymptomatic population, these results suggest subtle differences across plasma p-tau species and platforms for the prediction of amyloid and tau PET and magnetic resonance imaging measures of cerebrovascular and Alzheimer-related pathology.