Browsing by Author "Dage, Jeffrey L."

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    Alzheimer’s Disease Plasma Biomarker Results from across 14 Alzheimer’s Disease Research Centers
    (Wiley, 2025-01-09) Russ, Kristen A.; Asthana, Sanjay; Johnson, Sterling C.; Wilson, Rachael E.; Craft, Suzanne; Register, Thomas C.; Lockhart, Samuel N.; Nairn, Angus C.; Strittmatter, Stephen M.; van Dyck, Christopher H.; Foroud, Tatiana M.; Dage, Jeffrey L.; Neurology, School of Medicine
    Background: The Alzheimer’s Disease Center Fluid Biomarker (ADCFB) Initiative samples are analyzed centrally at NCRAD for AD plasma biomarkers. When combining NACC accessible data from across centers, biofluid biomarker data must be evaluated carefully. This will become more critical with the implementation of disease modifying therapies. Methods: Beta amyloid 1‐42 (Aβ42) and beta amyloid 1‐40 (Aβ40) were analyzed utilizing the Neurology 4‐Plex E kits on a Quanterix Simoa HD‐X. All assays were performed according to manufacturer’s instructions. NACC data from participants 65 or older was combined with biomarker results into one data set. Samples with PET results from the same visit as the blood collection were utilized for this analysis (n=114). Results: Data for amyloid and tau PET was used along with Aβ42/40 ratios to assess the area under the curve (AUC) for this data set (Figure 1). Amyloid PET and Tau PET by Aβ42/40 ROC analysis including age and APOE4 carrier status showed lower than expected AUCs (both 0.72). A subset of data (n=90) was analyzed using participants that were not on any FDA‐approved drugs for AD. This had no effect on AUCs for amyloid or tau PET by Aβ42/40 ratios. Distribution of Aβ42/40 ratios across sites showed a single site had a subset of very high Aβ42/40 ratios (n=8) in comparison to other sites. After removal of the Aβ42/40 outliers from the specific site from the data set, diagnostic accuracies of Aβ42/40 for both Amyloid PET (AUC=0.77) and Tau PET (AUC=0.76) were increased. More investigation into the exact cause of the outliers is necessary, but Aβ42/40 elevations independent from other biomarkers have been seen in clinical trials of Solanezumab and some other Aβ targeting antibodies. Conclusion: To avoid errors in data analysis when using shared data, it is important to track clinical trial co‐enrollment and drug type within ADCs at NACC. As FDA‐approved treatments become available or co‐enrollment of AD drug trials at centers occurs, it is critical to carefully track participant variables and review biofluid biomarker data when it is being combined across centers or studies.
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    Alzheimer’s Disease Polygenic Risk in the LEADS Cohort
    (Wiley, 2025-01-03) Nudelman, Kelly N.; Pentchev, Julian V.; Jackson, Trever; Eloyan, Ani; Dage, Jeffrey L.; Foroud, Tatiana M.; Hammers, Dustin B.; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; LEADS Consortium; Medical and Molecular Genetics, School of Medicine
    Background: Currently, it is unclear to what extent late‐onset Alzheimer’s disease (AD) risk variants contribute to early‐onset AD (EOAD). One method to clarify the contribution of late‐onset AD genetic risk to EOAD is to investigate the association of AD polygenic risk scores (PRS) with EOAD. We hypothesize that in the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS), EOAD participants will have greater PRS than early‐onset amyloid‐negative cognitively‐impaired participants (EOnonAD) and controls, and investigate the association of AD PRS with age of disease onset (AoO) and cognitive performance. Methods: GWAS data was generated for LEADS participants, including those with EOAD, EOnonAD, and controls, with the Illumina Global Screening Array. A PRS was calculated using the 31 SNPs and weights published previously by Desikan et al. (2017) for LEADS participants with imputed GWAS data (N = 369). Logistic regression models including age, sex, PRS, and genetic ancestry principal components were tested to identify predictors of EOAD (N = 210) vs. EOnonAD (N = 69) and controls (N = 89). ANCOVA models were used to assess group differences in PRS scores. Kaplan‐Meier regression was used to assess differences in EOAD AoO for tertile‐binned PRS groups. Within EOAD, pre‐calculated cognitive domain scores for speed and attention, working memory, episodic memory, language, and visuospatial performance were assessed for correlation with PRS. Results: The AD PRS was a predictor of EOAD (p = 0.014), with the model explaining 10.5% of variance (X2 = 40.971, p<0.001). EOAD participants had higher PRS scores (mean = 0.0012, standard deviation (SD) = 0.015) compared to EOnonAD and controls (mean = ‐0.0018, SD = 0.015) (F = 6.602, p = 0.011). Survival analysis indicated no significant differences in EOAD AoO between PRS groups (X2 = 3.396, p = 0.183). In the EOAD group, PRS was associated with cognitive scores for speed and attention (r = 0.204, p = 0.007), language (r = 0.230, p = 0.002), and visuospatial performance (r = 0.166, p = 0.037). Conclusions: In the LEADS cohort, AD PRS is a predictor for EOAD, and is associated with cognitive performance, but does not predict EOAD AoO. This suggests that while late onset AD‐associated genetic variants contribute to disease risk and processes, they do not account for a large portion of disease risk, and do not explain differences in disease AoO in the LEADS cohort.
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    Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS)
    (Wiley, 2023) Cho, Hanna; Mundada, Nidhi S.; Apostolova, Liana G.; Carrillo, Maria C.; Shankar, Ranjani; Amuiri, Alinda N.; Zeltzer, Ehud; Windon, Charles C.; Soleimani-Meigooni, David N.; Tanner, Jeremy A.; Heath, Courtney Lawhn; Lesman-Segev, Orit H.; Aisen, Paul; Eloyan, Ani; Lee, Hye Sun; Hammers, Dustin B.; Kirby, Kala; Dage, Jeffrey L.; Fagan, Anne; Foroud, Tatiana; Grinberg, Lea T.; Jack, Clifford R.; Kramer, Joel; Kukull, Walter A.; Murray, Melissa E.; Nudelman, Kelly; Toga, Arthur; Vemuri, Prashanthi; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph; Mendez, Mario; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily J.; Salloway, Stephen; Sha, Sharon; Turner, Raymond Scott; Wingo, Thomas S.; Wolk, David A.; Koeppe, Robert; Iaccarino, Leonardo; Dickerson, Bradford C.; La Joie, Renaud; Rabinovici, Gil D.; LEADS Consortium; Neurology, School of Medicine
    Introduction: We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). Methods: We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification. Results: 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. Discussion: LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. Highlights: 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.
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    Amyloid‐PET in patients with a clinical diagnosis of sporadic early‐ versus late‐onset AD: comparison of the LEADS and ADNI cohorts
    (Wiley, 2025-01-09) Lagarde, Julien; Maiti, Piyush; Schonhaut, Daniel R.; Zhang, Jiaxiuxiu; Soleimani-meigooni, David N.; Zeltzer, Ehud; Windon, Charles; Raya, Maison Abu; Vrillon, Agathe; Hammers, Dustin B.; Dage, Jeffrey L.; Nudelman, Kelly N.; Eloyan, Ani; Koeppe, Robert A.; Landau, Susan M.; Carrillo, Maria C.; Touroutoglou, Alexandra; Vemuri, Prashanthi; Dickerson, Bradford C.; Apostolova, Liana G.; Rabinovici, Gil D.; La Joie, Renaud; LEADS Consortium, Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Background: Large‐scale studies comparing sporadic early‐onset AD (EOAD, age<65) and late‐onset AD (LOAD, age≥65) are lacking. We compared amyloid‐PET outcomes (positivity rate and amyloid burden) between patients clinically diagnosed with sporadic EOAD vs LOAD, leveraging data from the Longitudinal Early‐Onset AD Study (LEADS) and the Alzheimer’s Disease Neuroimaging Initiative 3 (ADNI3). Method: 731 patients meeting the 2011 NIA‐AA criteria for AD dementia or MCI were included (505 early‐onset from LEADS, 226 late‐onset from ADNI3, Table 1). All participants underwent amyloid‐PET with [18F]Florbetaben or [18F]Florbetapir. Amyloid positivity was centrally determined by a process involving a visual read by a trained expert and PET‐only quantification; in case of a discrepancy, a read from an independent physician acted as a tiebreaker. Logistic regressions in each cohort examined relations between amyloid positivity and age, sex, MMSE and APOE4 genotype. Amyloid burden was independently quantified in Centiloids using an MRI‐based pipeline. Mean Centiloids in LEADS and ADNI were compared with two‐way ANOVA, for visually positive and visually negative scans. Result: Amyloid positivity rate was higher in LEADS (76%) than ADNI (64%, p<0.001, Figure 1A). Lower MMSE and APOE4 genotype increased odds of amyloid positivity in both cohorts, although the APOE4 effect was stronger in ADNI than LEADS (OR=10.1 versus 2.4, p=0.007, Table 2). Amyloid positivity was more common in females across cohorts, but this effect was only statistically significant in LEADS (Table 2). Centiloids were bimodally distributed in both cohorts, although the separation between positive and negative scans was more prominent in LEADS (Figure 1B). Visually positive scans had significantly higher Centiloids in LEADS than in ADNI, whereas no cohort difference was observed for visually negative scans (Figure 1C). Sensitivity analyses showed that this effect was driven by patients with MCI (CDR≤0.5; Figure 1D‐E). Conclusion: The lower amyloid positivity rate in ADNI might be due to AD‐mimicking pathologies being more common at an older age. The higher amyloid burden in early‐onset, amyloid‐positive patients could reflect younger patients being diagnosed later in the disease course compared to typical, late‐onset patients. Alternatively, younger patients might tolerate higher neuropathology burden due to higher brain reserve or fewer co‐pathologies.
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    Asian Cohort for Alzheimer's Disease (ACAD) pilot study on genetic and non-genetic risk factors for Alzheimer's disease among Asian Americans and Canadians
    (Wiley, 2024) Ho, Pei-Chuan; Yu, Wai Haung; Tee, Boon Lead; Lee, Wan-Ping; Li, Clara; Gu, Yian; Yokoyama, Jennifer S.; Reyes-Dumeyer, Dolly; Choi, Yun-Beom; Yang, Hyun-Sik; Vardarajan, Badri N.; Tzuang, Marian; Lieu, Kevin; Lu, Anna; Faber, Kelley M.; Potter, Zoë D.; Revta, Carolyn; Kirsch, Maureen; McCallum, Jake; Mei, Diana; Booth, Briana; Cantwell, Laura B.; Chen, Fangcong; Chou, Sephera; Clark, Dewi; Deng, Michelle; Hong, Ting Hei; Hwang, Ling-Jen; Jiang, Lilly; Joo, Yoonmee; Kang, Younhee; Kim, Ellen S.; Kim, Hoowon; Kim, Kyungmin; Kuzma, Amanda B.; Lam, Eleanor; Lanata, Serggio C.; Lee, Kunho; Li, Donghe; Li, Mingyao; Li, Xiang; Liu, Chia-Lun; Liu, Collin; Liu, Linghsi; Lupo, Jody-Lynn; Nguyen, Khai; Pfleuger, Shannon E.; Qian, James; Qian, Winnie; Ramirez, Veronica; Russ, Kristen A.; Seo, Eun Hyun; Song, Yeunjoo E.; Tartaglia, Maria Carmela; Tian, Lu; Torres, Mina; Vo, Namkhue; Wong, Ellen C.; Xie, Yuan; Yau, Eugene B.; Yi, Isabelle; Yu, Victoria; Zeng, Xiaoyi; St. George-Hyslop, Peter; Au, Rhoda; Schellenberg, Gerard D.; Dage, Jeffrey L.; Varma, Rohit; Hsiung, Ging-Yuek R.; Rosen, Howard; Henderson, Victor W.; Foroud, Tatiana; Kukull, Walter A.; Peavy, Guerry M.; Lee, Haeok; Feldman, Howard H.; Mayeux, Richard; Chui, Helena; Jun, Gyungah R.; Ta Park, Van M.; Chow, Tiffany W.; Wang, Li-San; Medical and Molecular Genetics, School of Medicine
    Introduction: Clinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non-genetic/lifestyle factors impact this multi-ethnic population. Methods: The ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese. Results: ACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception. Discussion: ACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit > 5000 participants to identify genetic and non-genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness. Highlights: The Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under-investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.
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    Association Between Age and Cognitive Severity in Early‐Onset AD: Extension of preliminary findings in the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS)
    (Wiley, 2025-01-03) Hammers, Dustin B.; Eloyan, Ani; Taurone, Alexander; Thangarajah, Maryanne; Kirby, Kala; Wong, Bonnie; Dage, Jeffrey L.; Nudelman, Kelly N.; Carrillo, Maria C.; Rabinovici, Gil D.; Dickerson, Bradford C.; Apostolova, Liana G.; LEADS Consortium; Neurology, School of Medicine
    Background: Widespread cognitive impairments have previously been documented in Early‐Onset Alzheimer’s Disease (EOAD) relative to cognitively normal (CN) same‐aged peers or those with cognitive impairment without amyloid pathology (Early‐Onset non‐Alzheimer’s Disease; EOnonAD; Hammers et al., 2023). Prior preliminary work has similarly observed worse cognitive performance being associated with earlier ages in EOAD participants enrolled in the Longitudinal Early‐Onset Alzheimer’s Disease Study (LEADS; Apostolova et al., 2019). It is unclear, however, if these age effects are seen across early‐onset conditions, and whether cognitive discrepancies among diagnostic groups are uniform across the age spectrum. The objective of the current study is to more‐extensively examine the impact of age‐at‐baseline on cognition within LEADS, with emphasis placed on the influence of diagnostic group on these associations. Method: Expanded cross‐sectional baseline cognitive data from 573 participants (CN, n = 97; EOAD, n = 364; EOnonAD, n = 112) enrolled in the LEADS study (aged 40‐64) were analyzed. Multiple linear regression analyses were conducted to investigate associations between age‐at‐baseline and cognition for each diagnostic group – and their interaction among diagnoses – controlling for gender, education, APOE ε4 status, and disease severity. Result: See Table 1 for demographic characteristics of our sample. Linear regression showed a significant interaction effect for the cognitive domain of Executive Functioning (p = .002). Specifically, while the EOAD group displayed a positive relationship between age‐at‐baseline and Executive Functioning performance (β = 0.08, p = .02; Figure 1), the CN group displayed a negative relationship (β = ‐0.04, p = .008) and the EOnonAD group displayed no relationship (β = ‐0.01, p = .50). A similar main‐effect for age was observed for the EOAD group when examining Visuospatial Skills (β = 0.12, p = .04), however no other age effects were evident across other diagnostic groups or cognitive domains (Episodic Memory, Language, or Speed/Attention; Table 2). Conclusion: Building off preliminary work, our results suggest that executive functioning may be disproportionately impacted earlier in the disease course in participants with EOAD relative to other diagnostic groups. This finding appears to be unique to executive functioning, as it was absent in other cognitive domains and remained after accounting for disease severity. This highlights the need for further investigation into executive dysfunction early in the course of EOAD.
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    Association between BrainAGE and Alzheimer's disease biomarkers
    (Wiley, 2025-02-27) Abughofah, Yousaf; Deardorff, Rachael; Vosmeier, Aaron; Hottle, Savannah; Dage, Jeffrey L.; Dempsey, Desarae; Apostolova, Liana G.; Brosch, Jared; Clark, David; Farlow, Martin; Foroud, Tatiana; Gao, Sujuan; Wang, Sophia; Zetterberg, Henrik; Blennow, Kaj; Saykin, Andrew J.; Risacher, Shannon L.; Radiology and Imaging Sciences, School of Medicine
    Introduction: The brain age gap estimation (BrainAGE) method uses a machine learning model to generate an age estimate from structural magnetic resonance imaging (MRI) scans. The goal was to study the association of brain age with Alzheimer's disease (AD) imaging and plasma biomarkers. Methods: One hundred twenty-three individuals from the Indiana Memory and Aging Study underwent structural MRI, amyloid and tau positron emission tomography (PET), and plasma sampling. The MRI scans were processed using the software program BrainAgeR to receive a "brain age" estimate. Plasma biomarker concentrations were measured, and partial Pearson correlation models were used to evaluate their relationship with brain age gap (BAG) estimation (BrainAGE = chronological age - MRI estimated brain age). Results: Significant associations between BAG and amyloid and tau levels on PET and in plasma were observed depending on diagnostic categories. Discussion: These findings suggest that BAG is potentially a biomarker of pathology in AD which can be applied to routine brain imaging. Highlights: Novel research that uses an artificial intelligence learning tool to estimate brain age. Findings suggest that brain age gap is associated with plasma and positron emission tomography Alzheimer's disease (AD) biomarkers. Differential relationships are seen in different stages of disease (preclinical vs. clinical). Results could play a role in early AD diagnosis and treatment.
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    Association of Donanemab Treatment With Exploratory Plasma Biomarkers in Early Symptomatic Alzheimer Disease: A Secondary Analysis of the TRAILBLAZER-ALZ Randomized Clinical Trial
    (American Medical Association, 2022) Pontecorvo, Michael J.; Lu, Ming; Burnham, Samantha C.; Schade, Andrew E.; Dage, Jeffrey L.; Shcherbinin, Sergey; Collins, Emily C.; Sims, John R.; Mintun, Mark A.; Neurology, School of Medicine
    Importance: Plasma biomarkers of Alzheimer disease may be useful as minimally invasive pharmacodynamic measures of treatment outcomes. Objective: To analyze the association of donanemab treatment with plasma biomarkers associated with Alzheimer disease. Design, setting, and participants: TRAILBLAZER-ALZ was a randomized, double-blind, placebo-controlled clinical trial conducted from December 18, 2017, to December 4, 2020, across 56 sites in the US and Canada. Exploratory biomarkers were prespecified with the post hoc addition of plasma glial fibrillary acidic protein and amyloid-β. Men and women aged 60 to 85 years with gradual and progressive change in memory function for at least 6 months were included. A total of 1955 participants were assessed for eligibility. Key eligibility criteria include Mini-Mental State Examination scores of 20 to 28 and elevated amyloid and intermediate tau levels. Interventions: Randomized participants received donanemab or placebo every 4 weeks for up to 72 weeks. The first 3 doses of donanemab were given at 700 mg and then increased to 1400 mg with blinded dose reductions as specified based on amyloid reduction. Main outcomes and measures: Change in plasma biomarker levels after donanemab treatment. Results: In TRAILBLAZER-ALZ, 272 participants (mean [SD] age, 75.2 [5.5] years; 145 [53.3%] female) were randomized. Plasma levels of phosphorylated tau217 (pTau217) and glial fibrillary acidic protein were significantly lower with donanemab treatment compared with placebo as early as 12 weeks after the start of treatment (least square mean change difference vs placebo, -0.04 [95% CI, -0.07 to -0.02]; P = .002 and -0.04 [95% CI, -0.07 to -0.01]; P = .01, respectively). No significant differences in plasma levels of amyloid-β 42/40 and neurofilament light chain were observed between treatment arms at the end of treatment. Changes in plasma pTau217 and glial fibrillary acidic protein were significantly correlated with the Centiloid percent change in amyloid (Spearman rank correlation coefficient [R] = 0.484 [95% CI, 0.359-0.592]; P < .001 and R = 0.453 [95% CI, 0.306-0.579]; P < .001, respectively) following treatment. Additionally, plasma levels of pTau217 and glial fibrillary acidic protein were significantly correlated at baseline and following treatment (R = 0.399 [95% CI, 0.278-0.508], P < .001 and R = 0.393 [95% CI, 0.254-0.517]; P < .001, respectively). Conclusions and relevance: Significant reductions in plasma biomarkers pTau217 and glial fibrillary acidic protein compared with placebo were observed following donanemab treatment in patients with early symptomatic Alzheimer disease. These easily accessible plasma biomarkers might provide additional evidence of Alzheimer disease pathology change through anti-amyloid therapy. Usefulness in assessing treatment response will require further evaluation.
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    Association of Plasma P-tau217 and P-tau181 with clinical phenotype, neuropathology, and imaging markers in Alzheimer’s disease and frontotemporal lobar degeneration: a retrospective diagnostic performance study
    (Elsevier, 2021) Thijssen, Elisabeth H.; La Joie, Renaud; Strom, Amelia; Fonseca, Corrina; Iaccarino, Leonardo; Wolf, Amy; Spina, Salvatore; Allen, Isabel E.; Cobigo, Yann; Heuer, Hilary; VandeVrede, Lawren; Proctor, Nicholas K.; Lago, Argentina Lario; Baker, Suzanne; Sivasankaran, Rajeev; Kieloch, Agnieszka; Kinhikar, Arvind; Yu, Lili; Valentin, Marie-Anne; Jeromin, Andreas; Zetterberg, Henrik; Hansson, Oskar; Mattsson-Carlgren, Niklas; Graham, Danielle; Blennow, Kaj; Kramer, Joel H.; Grinberg, Lea T.; Seeley, William W.; Rosen, Howard; Boeve, Bradley F.; Miller, Bruce L.; Teunissen, Charlotte E.; Rabinovici, Gil D.; Rojas, Julio C.; Dage, Jeffrey L.; Boxer, Adam L.; Advancing Research and Treatment for Frontotemporal Lobar Degeneration investigators; Neurology, School of Medicine
    Background: Plasma tau phosphorylated at threonine 217 (p-tau217) and plasma tau phosphorylated at threonine 181 (p-tau181) are associated with Alzheimer's disease tau pathology. We compared the diagnostic value of both biomarkers in cognitively unimpaired participants and patients with a clinical diagnosis of mild cognitive impairment, Alzheimer's disease syndromes, or frontotemporal lobar degeneration (FTLD) syndromes. Methods: In this retrospective multicohort diagnostic performance study, we analysed plasma samples, obtained from patients aged 18-99 years old who had been diagnosed with Alzheimer's disease syndromes (Alzheimer's disease dementia, logopenic variant primary progressive aphasia, or posterior cortical atrophy), FTLD syndromes (corticobasal syndrome, progressive supranuclear palsy, behavioural variant frontotemporal dementia, non-fluent variant primary progressive aphasia, or semantic variant primary progressive aphasia), or mild cognitive impairment; the participants were from the University of California San Francisco (UCSF) Memory and Aging Center, San Francisco, CA, USA, and the Advancing Research and Treatment for Frontotemporal Lobar Degeneration Consortium (ARTFL; 17 sites in the USA and two in Canada). Participants from both cohorts were carefully characterised, including assessments of CSF p-tau181, amyloid-PET or tau-PET (or both), and clinical and cognitive evaluations. Plasma p-tau181 and p-tau217 were measured using electrochemiluminescence-based assays, which differed only in the biotinylated antibody epitope specificity. Receiver operating characteristic analyses were used to determine diagnostic accuracy of both plasma markers using clinical diagnosis, neuropathological findings, and amyloid-PET and tau-PET measures as gold standards. Difference between two area under the curve (AUC) analyses were tested with the Delong test. Findings: Data were collected from 593 participants (443 from UCSF and 150 from ARTFL, mean age 64 years [SD 13], 294 [50%] women) between July 1 and Nov 30, 2020. Plasma p-tau217 and p-tau181 were correlated (r=0·90, p<0·0001). Both p-tau217 and p-tau181 concentrations were increased in people with Alzheimer's disease syndromes (n=75, mean age 65 years [SD 10]) relative to cognitively unimpaired controls (n=118, mean age 61 years [SD 18]; AUC=0·98 [95% CI 0·95-1·00] for p-tau217, AUC=0·97 [0·94-0·99] for p-tau181; pdiff=0·31) and in pathology-confirmed Alzheimer's disease (n=15, mean age 73 years [SD 12]) versus pathologically confirmed FTLD (n=68, mean age 67 years [SD 8]; AUC=0·96 [0·92-1·00] for p-tau217, AUC=0·91 [0·82-1·00] for p-tau181; pdiff=0·22). P-tau217 outperformed p-tau181 in differentiating patients with Alzheimer's disease syndromes (n=75) from those with FTLD syndromes (n=274, mean age 67 years [SD 9]; AUC=0·93 [0·91-0·96] for p-tau217, AUC=0·91 [0·88-0·94] for p-tau181; pdiff=0·01). P-tau217 was a stronger indicator of amyloid-PET positivity (n=146, AUC=0·91 [0·88-0·94]) than was p-tau181 (n=214, AUC=0·89 [0·86-0·93]; pdiff=0·049). Tau-PET binding in the temporal cortex was more strongly associated with p-tau217 than p-tau181 (r=0·80 vs r=0·72; pdiff<0·0001, n=230). Interpretation: Both p-tau217 and p-tau181 had excellent diagnostic performance for differentiating patients with Alzheimer's disease syndromes from other neurodegenerative disorders. There was some evidence in favour of p-tau217 compared with p-tau181 for differential diagnosis of Alzheimer's disease syndromes versus FTLD syndromes, as an indication of amyloid-PET-positivity, and for stronger correlations with tau-PET signal. Pending replication in independent, diverse, and older cohorts, plasma p-tau217 and p-tau181 could be useful screening tools to identify individuals with underlying amyloid and Alzheimer's disease tau pathology.
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    Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health‐related comorbidities in a community‐dwelling cohort
    (Wiley, 2024) Rudolph, Marc D.; Sutphen, Courtney L.; Register, Thomas C.; Whitlow, Christopher T.; Solingapuram Sai, Kiran K.; Hughes, Timothy M.; Bateman, James R.; Dage, Jeffrey L.; Russ, Kristen A.; Mielke, Michelle M.; Craft, Suzanne; Lockhart, Samuel N.; Neurology, School of Medicine
    Introduction: We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. Methods: We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). Results: Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. Discussion: eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. Highlights: Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.