Browsing by Subject "Plasma biomarkers"
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Item 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 MedicineIntroduction: 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.Item 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 MedicineIntroduction: 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.Item Characterization of pre-analytical sample handling effects on a panel of Alzheimer's disease–related blood-based biomarkers: Results from the Standardization of Alzheimer's Blood Biomarkers (SABB) working group(Wiley, 2022) Verberk, Inge M. W.; Misdorp, Els O.; Koelewijn, Jannet; Ball, Andrew J.; Blennow, Kaj; Dage, Jeffrey L.; Fandos, Noelia; Hansson, Oskar; Hirtz, Christophe; Janelidze, Shorena; Kang, Sungmin; Kirmess, Kristopher; Kindermans, Jana; Lee, Ryan; Meyer, Matthew R.; Shan, Dandan; Shaw, Leslie M.; Waligorska, Teresa; West, Tim; Zetterberg, Henrik; Edelmayer, Rebecca M.; Teunissen, Charlotte E.; Neurology, School of MedicineIntroduction: Pre-analytical sample handling might affect the results of Alzheimer's disease blood-based biomarkers. We empirically tested variations of common blood collection and handling procedures. Methods: We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze–thawing. We measured amyloid beta (Aβ)42 and 40 peptides with six assays, and Aβ oligomerization-tendency (OAβ), amyloid precursor protein (APP)699-711, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), total tau (t-tau), and phosphorylated tau181. Results: Collection tube type resulted in different values of all assessed markers. Delayed plasma centrifugation and storage affected Aβ and t-tau; t-tau was additionally affected by centrifugation temperature. The other markers were resistant to handling variations. Discussion: We constructed a standardized operating procedure for plasma handling, to facilitate introduction of blood-based biomarkers into the research and clinical settings.Item Correction: Diagnostic and prognostic performance to detect Alzheimer's disease and clinical progression of a novel assay for plasma p-tau217(BMC, 2022-06-13) Groot, Colin; Cicognola, Claudia; Bali, Divya; Triana‑Baltzer, Gallen; Dage, Jeffrey L.; Pontecorvo, Michael J.; Kolb, Hartmuth C.; Ossenkoppele, Rik; Janelidze, Shorena; Hansson, Oskar; Neurology, School of MedicineErratum for: Diagnostic and prognostic performance to detect Alzheimer's disease and clinical progression of a novel assay for plasma p-tau217. Groot C, Cicognola C, Bali D, Triana-Baltzer G, Dage JL, Pontecorvo MJ, Kolb HC, Ossenkoppele R, Janelidze S, Hansson O. Alzheimers Res Ther. 2022 May 14;14(1):67. doi: 10.1186/s13195-022-01005-8. PMID: 35568889Item Diagnostic and prognostic performance to detect Alzheimer's disease and clinical progression of a novel assay for plasma p-tau217(BMC, 2022-05-14) Groot, Colin; Cicognola, Claudia; Bali, Divya; Triana‑Baltzer, Gallen; Dage, Jeffrey L.; Pontecorvo, Michael J.; Kolb, Hartmuth C.; Osssenkoppele, Rik; Janelidze, Shorena; Hansson, Oskar; Neurology, School of MedicineBackground: Recent advances in disease-modifying treatments highlight the need for accurately identifying individuals in early Alzheimer's disease (AD) stages and for monitoring of treatment effects. Plasma measurements of phosphorylated tau (p-tau) are a promising biomarker for AD, but different assays show varying diagnostic and prognostic accuracies. The objective of this study was to determine the clinical performance of a novel plasma p-tau217 (p-tau217) assay, p-tau217+Janssen, and perform a head-to-head comparison to an established assay, plasma p-tau217Lilly, within two independent cohorts. METHODS: The study consisted of two cohorts, cohort 1 (27 controls and 25 individuals with mild-cognitive impairment [MCI]) and cohort 2 including 147 individuals with MCI at baseline who were followed for an average of 4.92 (SD 2.09) years. Receiver operating characteristic analyses were used to assess the performance of both assays to detect amyloid-β status (+/-) in CSF, distinguish MCI from controls, and identify subjects who will convert from MCI to AD dementia. General linear and linear mixed-effects analyses were used to assess the associations between p-tau and baseline, and annual change in Mini-Mental State Examination (MMSE) scores. Spearman correlations were used to assess the associations between the two plasma measures, and Bland-Altmann plots were examined to assess the agreement between the assays. Results: Both assays showed similar performance in detecting amyloid-β status in CSF (plasma p-tau217+Janssen AUC = 0.91 vs plasma p-tau217Lilly AUC = 0.89), distinguishing MCI from controls (plasma p-tau217+Janssen AUC = 0.91 vs plasma p-tau217Lilly AUC = 0.91), and predicting future conversion from MCI to AD dementia (plasma p-tau217+Janssen AUC = 0.88 vs p-tau217Lilly AUC = 0.89). Both assays were similarly related to baseline (plasma p-tau217+Janssen rho = -0.39 vs p-tau217Lilly rho = -0.35), and annual change in MMSE scores (plasma p-tau217+Janssenr = -0.45 vs p-tau217Lillyr = -0.41). Correlations between the two plasma measures were rho = 0.69, p < 0.001 in cohort 1 and rho = 0.70, p < 0.001 in cohort 2. Bland-Altmann plots revealed good agreement between plasma p-tau217+Janssen and plasma p-tau217Lilly in both cohorts (cohort 1, 51/52 [98%] within 95%CI; cohort 2, 139/147 [95%] within 95%CI). Conclusions: Taken together, our results indicate good diagnostic and prognostic performance of the plasma p-tau217+Janssen assay, similar to the p-tau217Lilly assay.Item Head-to-head comparison between plasma p-tau217 and flortaucipir-PET in amyloid-positive patients with cognitive impairment(BMC, 2023-09-22) Mundada, Nidhi S.; Rojas, Julio C.; Vandevrede, Lawren; Thijssen, Elisabeth H.; Iaccarino, Leonardo; Okoye, Obiora C.; Shankar, Ranjani; Soleimani‑Meigooni, David N.; Lago, Argentina L.; Miller, Bruce L.; Teunissen, Charlotte E.; Heuer, Hillary; Rosen, Howie J.; Dage, Jeffrey L.; Jagust, William J.; Rabinovici, Gil D.; Boxer, Adam L.; La Joie, Renaud; Neurology, School of MedicineBackground: Plasma phosphorylated tau (p-tau) has emerged as a promising biomarker for Alzheimer's disease (AD). Studies have reported strong associations between p-tau and tau-PET that are mainly driven by differences between amyloid-positive and amyloid-negative patients. However, the relationship between p-tau and tau-PET is less characterized within cognitively impaired patients with a biomarker-supported diagnosis of AD. We conducted a head-to-head comparison between plasma p-tau217 and tau-PET in patients at the clinical stage of AD and further assessed their relationships with demographic, clinical, and biomarker variables. Methods: We retrospectively included 87 amyloid-positive patients diagnosed with MCI or dementia due to AD who underwent structural MRI, amyloid-PET (11C-PIB), tau-PET (18F-flortaucipir, FTP), and blood draw assessments within 1 year (age = 66 ± 10, 48% female). Amyloid-PET was quantified in Centiloids (CL) while cortical tau-PET binding was measured using standardized uptake value ratios (SUVRs) referenced against inferior cerebellar cortex. Plasma p-tau217 concentrations were measured using an electrochemiluminescence-based assay on the Meso Scale Discovery platform. MRI-derived cortical volume was quantified with FreeSurfer. Mini-Mental State Examination (MMSE) scores were available at baseline (n = 85) and follow-up visits (n = 28; 1.5 ± 0.7 years). Results: Plasma p-tau217 and cortical FTP-SUVR were correlated (r = 0.61, p < .001), especially in temporo-parietal and dorsolateral frontal cortices. Both higher p-tau217 and FTP-SUVR values were associated with younger age, female sex, and lower cortical volume, but not with APOE-ε4 carriership. PIB-PET Centiloids were weakly correlated with FTP-SUVR (r = 0.26, p = 0.02), but not with p-tau217 (r = 0.10, p = 0.36). Regional PET-plasma associations varied with amyloid burden, with p-tau217 being more strongly associated with tau-PET in temporal cortex among patients with moderate amyloid-PET burden, and with tau-PET in primary cortices among patients with high amyloid-PET burden. Higher p-tau217 and FTP-SUVR values were independently associated with lower MMSE scores cross-sectionally, while only baseline FTP-SUVR predicted longitudinal MMSE decline when both biomarkers were included in the same model. Conclusion: Plasma p-tau217 and tau-PET are strongly correlated in amyloid-PET-positive patients with MCI or dementia due to AD, and they exhibited comparable patterns of associations with demographic variables and with markers of downstream neurodegeneration.Item Hippocampal-subfield microstructures and their relation to plasma biomarkers in Alzheimer's disease(Oxford University Press, 2022) Shahid, Syed Salman; Wen, Qiuting; Risacher, Shannon L.; Farlow, Martin R.; Unverzagt, Frederick W.; Apostolova, Liana G.; Foroud, Tatiana M.; Zetterberg, Henrik; Blennow, Kaj; Saykin, Andrew J.; Wu, Yu-Chien; Neurology, School of MedicineHippocampal subfields exhibit differential vulnerabilities to Alzheimer's disease-associated pathology including abnormal accumulation of amyloid-β deposition and neurofibrillary tangles. These pathological processes extensively impact on the structural and functional interconnectivities of the subfields and may explain the association between hippocampal dysfunction and cognitive deficits. In this study, we investigated the degree of alterations in the microstructure of hippocampal subfields across the clinical continuum of Alzheimer's disease. We applied a grey matter-specific multi-compartment diffusion model (Cortical-Neurite orientation dispersion and density imaging) to understand the differential effects of Alzheimer's disease pathology on the hippocampal subfield microstructure. A total of 119 participants were included in this cross-sectional study. Participants were stratified into three categories, cognitively normal (n = 47), mild cognitive impairment (n = 52), and Alzheimer's disease (n = 19). Diffusion MRI, plasma biomarkers and neuropsychological test scores were used to determine the association between the microstructural integrity and Alzheimer's disease-associated molecular indicators and cognition. For Alzheimer's disease-related plasma biomarkers, we studied amyloid-β, total tau and neurofilament light; for Alzheimer's disease-related neuropsychological tests, we included the Trail Making Test, Rey Auditory Verbal Learning Test, Digit Span and Montreal Cognitive Assessment. Comparisons between cognitively normal subjects and those with mild cognitive impairment showed significant microstructural alterations in the hippocampal cornu ammonis (CA) 4 and dentate gyrus region, whereas CA 1-3 was the most sensitive region for the later stages in the Alzheimer's disease clinical continuum. Among imaging metrics for microstructures, the volume fraction of isotropic diffusion for interstitial free water demonstrated the largest effect size in between-group comparisons. Regarding the plasma biomarkers, neurofilament light appeared to be the most sensitive biomarker for associations with microstructural imaging findings in CA4-dentate gyrus. CA 1-3 was the subfield which had stronger correlations between cognitive performance and microstructural metrics. Particularly, poor performance on the Rey Auditory Verbal Learning Test and Montreal Cognitive Assessment was associated with decreased intracellular volume fraction. Overall, our findings support the value of tissue-specific microstructural imaging for providing pathologically relevant information manifesting in the plasma biomarkers and neuropsychological outcomes across various stages of Alzheimer's disease.Item Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community-engaged approach in the Alzheimer's Disease Neuroimaging Initiative 4(Wiley, 2023) Weiner, Michael W.; Veitch, Dallas P.; Miller, Melanie J.; Aisen, Paul S.; Albala, Bruce; Beckett, Laurel A.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R., Jr.; Jagust, William; Landau, Susan M.; Morris, John C.; Nosheny, Rachel; Okonkwo, Ozioma C.; Perrin, Richard J.; Petersen, Ronald C.; Rivera-Mindt, Monica; Saykin, Andrew J.; Shaw, Leslie M.; Toga, Arthur W.; Tosun, Duygu; Trojanowski, John Q.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50-60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022. Methods: ADNI4 will recruit URPs using community-engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50-60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in-clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials. Results and discussion: ADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.Item Plasma biomarkers combinations for prescreening rapid amyloid accumulation in cognitively unimpaired individuals at‐risk of Alzheimer’s disease(Wiley, 2025-01-09) Contador, José; Milà-Alomà, Marta; Escalante, Armand González; Ashton, Nicholas J.; Shekari, Mahnaz; Ortiz-Romero, Paula; Karikari, Thomas K.; Vanmechelen, Eugeen; Day, Theresa A.; Dage, Jeffrey L.; Zetterberg, Henrik; Gispert, Juan Domingo; Blennow, Kaj; Suarez-Calvet, Marc; Neurology, School of MedicineBackground: Alzheimer’s disease (AD) blood biomarkers alone can detect amyloid‐β (Aβ) pathology in cognitively unimpaired (CU) individuals. We assessed whether combining different plasma biomarkers improves the detection of Aβ‐positivity and identifies rapid amyloid deposition in CU individuals. Method: CU participants from the ALFA+ cohort were included. Among them, 361 had CSF Aβ42/40 and 328 amyloid PET‐scans [194 with two longitudinal scans; mean interval=3.35 (0.56) years]. Plasma Aβ42/40, p‐tau181, p‐tau231, GFAP, NfL (Simoa‐based) and p‐tau217 and t‐tau (MSD‐based) were measured at baseline (Table 1). We used simple and multiple logistic models to estimate Aβ‐positivity (defined as CSF Aβ42/40<0.071 or amyloid‐PET>12 Centiloids) or Aβ accumulation rate (“Fast accumulators” defined as >3 Centiloids/year). The model contained plasma biomarkers and demographics (age and sex) as covariates. We selected as "best model" (BM) that with lowest AIC. We defined parsimonious models as those with an AUC not significantly different (DeLong test) from BM or from each other yet outperforming single biomarkers and/or demographics models (FDR corrected). For the positive agreement closest to 90%, we calculated savings in lumbar punctures and amyloid PET‐scans. Result: For CSF Aβ‐positive detection, BM included plasma Aβ42/40, p‐tau181, p‐tau217, p‐tau231, GFAP and t‐tau (AUC=0.84). All simpler biomarkers combinations included plasma Ab42/40 and p‐tau231 (Table 2A). For PET Ab‐positive detection, BM included plasma Aβ42/40, p‐tau181, p‐tau217, GFAP, NFL and age (AUC=0.88). All simpler biomarkers combinations included plasma Ab42/40 and p‐tau217 (Table 2B). Regarding fast accumulators’ detection, plasma p‐tau217 was the single biomarker with the highest performance (AUC=0.70). BM included plasma Aβ42/40, p‐tau217, p‐tau231 and GFAP (AUC= 0.76). BM and the plasma Aβ42/40, p‐tau217 and GFAP (AUC=0.75) combination were the only models that outperformed the age and sex combination and single biomarkers, except for plasma p‐tau217, Aβ42/40 (AUC=0.69) or GFAP (AUC=0.68) alone (Table 2C). The combination of biomarkers could save up to 11% of lumbar punctures or 44% of amyloid‐PET to detect Ab‐positive CU individuals and 16% amyloid‐PETs to detect fast Aβ‐accumulation compared to the best single plasma biomarker (Table 2). Conclusion: In CU individuals, diverse combinations of plasma biomarkers detect Aβ‐positivity and future Aβ‐accumulation with high accuracy and can lead to substantial cost savings in AD detection.Item Plasma biomarkers predict amyloid pathology in cognitively normal monozygotic twins after 10 years(Oxford University Press, 2023-02-04) den Braber, Anouk; Verberk, Inge M. W.; Tomassen, Jori; den Dulk, Ben; Stoops, Erik; Dage, Jeffrey L.; Collij, Lyduine E.; Barkhof, Frederik; Willemsen, Gonneke; Nivard, Michel G.; van Berckel, Bart N. M.; Scheltens, Philip; Visser, Pieter Jelle; de Geus, Eco J. C.; Teunissen, Charlotte E.; Neurology, School of MedicineBlood-based biomarkers could prove useful to predict Alzheimer's disease core pathologies in advance of clinical symptoms. Implementation of such biomarkers requires a solid understanding of their long-term dynamics and the contribution of confounding to their association with Alzheimer's disease pathology. Here we assess the value of plasma amyloid-β1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein to detect early Alzheimer's disease pathology, accounting for confounding by genetic and early environmental factors. Participants were 200 monozygotic twins, aged ≥60 years with normal cognition from the european medical information framework for Alzheimer's disease study. All twins had amyloid-β status and plasma samples available at study enrolment. For 80 twins, additional plasma samples were available that had been collected approximately 10 years prior to amyloid-β status assessment. Single-molecule array assays were applied to measure amyloid-β1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein. Predictive value of and longitudinal change in these biomarkers were assessed using receiver operating characteristic curve analysis and linear mixed models. Amyloid pathology could be predicted using blood-based biomarkers obtained at the time of amyloid status assessment (amyloid-β1-42/1-40: area under the curve = 0.65, P = 0.01; phosphorylated-tau181: area under the curve = 0.84, P < 0.001; glial fibrillary acidic protein: area under the curve = 0.74, P < 0.001), as well as using those obtained 10 years prior to amyloid status assessment (amyloid-β1-42/1-40: area under the curve = 0.69, P = 0.03; phosphorylated-tau181: area under the curve = 0.92, P < 0.001; glial fibrillary acidic protein: area under the curve = 0.84, P < 0.001). Longitudinally, amyloid-β1-42/1-40 levels decreased [β (SE) = -0.12 (0.01), P < 0.001] and phosphorylated-tau181 levels increased [β (SE) = 0.02 (0.01), P = 0.004]. Amyloid-β-positive individuals showed a steeper increase in phosphorylated-tau181 compared with amyloid-β-negative individuals [β (SE) = 0.06 (0.02), P = 0.004]. Also amyloid-β-positive individuals tended to show a steeper increase in glial fibrillary acidic protein [β (SE) = 0.04 (0.02), P = 0.07]. Within monozygotic twin pairs, those with higher plasma phosphorylated-tau181 and lower amyloid-β1-42/1-40 levels were more likely to be amyloid-β positive [β (SE) = 0.95 (0.26), P < 0.001; β (SE) = -0.28 (0.14), P < 0.05] indicating minimal contribution of confounding by genetic and early environmental factors. Our data support the use of amyloid-β1-42/1-40, phosphorylated-tau181 and glial fibrillary acidic protein as screening tools for Alzheimer's disease pathology in the normal aging population, which is of importance for enrolment of high-risk subjects in secondary, or even primary, prevention trials. Furthermore, these markers show potential as low-invasive monitoring tool of disease progression and possibly treatment effects in clinical trials.