Browsing by Author "Blennow, Kaj"
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Item Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure(Wiley, 2024) Tranfa, Mario; Lorenzini, Luigi; Collij, Lyduine E.; Vállez García, David; Ingala, Silvia; Pontillo, Giuseppe; Pieperhoff, Leonard; Maranzano, Alessio; Wolz, Robin; Haller, Sven; Blennow, Kaj; Frisoni, Giovanni; Sudre, Carole H.; Chételat, Gael; Ewers, Michael; Payoux, Pierre; Waldman, Adam; Martinez-Lage, Pablo; Schwarz, Adam J.; Ritchie, Craig W.; Wardlaw, Joanna M.; Domingo Gispert, Juan; Brunetti, Arturo; Mutsaerts, Henk J. M. M.; Meije Wink, Alle; Barkhof, Frederik; Radiology and Imaging Sciences, School of MedicineObjective: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults. Methods: Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. Results: AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. Interpretation: Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.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 Amyloid polymorphisms constitute distinct clouds of conformational variants in different etiological subtypes of Alzheimer's disease(National Academy of Sciences, 2017-12-05) Rasmussen, Jay; Mahler, Jasmin; Beschorner, Natalie; Kaeser, Stephan A.; Häsler, Lisa M.; Baumann, Frank; Nyström, Sofie; Portelius, Erik; Blennow, Kaj; Lashley, Tammaryn; Fox, Nick C.; Sepulveda-Falla, Diego; Glatzel, Markus; Oblak, Adrian L.; Ghetti, Bernardino; Nilsson, K. Peter R.; Hammarström, Per; Staufenbiel, Matthias; Walker, Lary C.; Jucker, Mathias; Pathology and Laboratory Medicine, School of MedicineThe molecular architecture of amyloids formed in vivo can be interrogated using luminescent conjugated oligothiophenes (LCOs), a unique class of amyloid dyes. When bound to amyloid, LCOs yield fluorescence emission spectra that reflect the 3D structure of the protein aggregates. Given that synthetic amyloid-β peptide (Aβ) has been shown to adopt distinct structural conformations with different biological activities, we asked whether Aβ can assume structurally and functionally distinct conformations within the brain. To this end, we analyzed the LCO-stained cores of β-amyloid plaques in postmortem tissue sections from frontal, temporal, and occipital neocortices in 40 cases of familial Alzheimer's disease (AD) or sporadic (idiopathic) AD (sAD). The spectral attributes of LCO-bound plaques varied markedly in the brain, but the mean spectral properties of the amyloid cores were generally similar in all three cortical regions of individual patients. Remarkably, the LCO amyloid spectra differed significantly among some of the familial and sAD subtypes, and between typical patients with sAD and those with posterior cortical atrophy AD. Neither the amount of Aβ nor its protease resistance correlated with LCO spectral properties. LCO spectral amyloid phenotypes could be partially conveyed to Aβ plaques induced by experimental transmission in a mouse model. These findings indicate that polymorphic Aβ-amyloid deposits within the brain cluster as clouds of conformational variants in different AD cases. Heterogeneity in the molecular architecture of pathogenic Aβ among individuals and in etiologically distinct subtypes of AD justifies further studies to assess putative links between Aβ conformation and clinical phenotype.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 Association between plasma tau and postoperative delirium incidence and severity: a prospective observational study(Elsevier, 2021) Ballweg, Tyler; White, Marissa; Parker, Margaret; Casey, Cameron; Bo, Amber; Farahbakhsh, Zahra; Kayser, Austin; Blair, Alexander; Lindroth, Heidi; Pearce, Robert A.; Blennow, Kaj; Zetterberg, Henrik; Lennertz, Richard; Sanders, Robert D.; Medicine, School of MedicineBackground: Postoperative delirium is associated with increases in the neuronal injury biomarker, neurofilament light (NfL). Here we tested whether two other biomarkers, glial fibrillary acidic protein (GFAP) and tau, are associated with postoperative delirium. Methods: A total of 114 surgical patients were recruited into two prospective biomarker cohort studies with assessment of delirium severity and incidence. Plasma samples were sent for biomarker analysis including tau, NfL, and GFAP, and a panel of 10 cytokines. We determined a priori to adjust for interleukin-8 (IL-8), a marker of inflammation, when assessing associations between biomarkers and delirium incidence and severity. Results: GFAP concentrations showed no relationship to delirium. The change in tau from preoperative concentrations to postoperative Day 1 was greater in patients with postoperative delirium (P<0.001) and correlated with delirium severity (ρ=0.39, P<0.001). The change in tau correlated with increases in IL-8 (P<0.001) and IL-10 (P=0.0029). Linear regression showed that the relevant clinical predictors of tau changes were age (P=0.037), prior stroke/transient ischaemic attack (P=0.001), and surgical blood loss (P<0.001). After adjusting for age, sex, preoperative cognition, and change in IL-8, tau remained significantly associated with delirium severity (P=0.026). Using linear mixed effect models, only tau (not NfL or IL-8) predicted recovery from delirium (P<0.001). Conclusions: The change in plasma tau was associated with delirium incidence and severity, and resolved over time in parallel with delirium features. The impact of this putative perioperative neuronal injury biomarker on long-term cognition merits further investigation.Item 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 MedicineBackground: 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.Item Associations of 18F‐RO‐948 Tau PET with Fluid AD Biomarkers, Centiloid, and Cognition in the Early AD Continuum(Wiley, 2025-01-09) Shekari, Mahnaz; González Escalante, Armand; Milà-Alomà, Marta; Falcon, Carles; López-Martos, David; Sánchez-Benavides, Gonzalo; Brugulat-Serrat, Anna; Niñerola-Baizán, Aida; Ashton, Nicholas J.; Karikari, Thomas K.; Lantero Rodriguez, Juan; Snellman, Anniina; Day, Theresa A.; Dage, Jeffrey L.; Ortiz-Romero, Paula; Tonietto, Matteo; Borroni, Edilio; Klein, Gregory; Kollmorgen, Gwendlyn; Quijano-Rubio, Clara; Vanmechelen, Eugeen; Minguillón, Carolina; Fauria, Karine; Perissinotti, Andrés; Molinuevo, Jose Luis; Zetterberg, Henrik; Blennow, Kaj; Grau-Rivera, Oriol; Suárez-Calvet, Marc; Gispert, Juan Domingo; Neurology, School of MedicineBackground: Fluid biomarkers provide a convenient way to predict AD pathophysiology. However, few studies have focused on determining associations with tau neurofibrillary tangle pathology in the early preclinical AD continuum, relevant to prevention strategies. Methods: Ninety‐nine cognitively unimpaired individuals from the ALFA+ cohort with valid 18F‐RO‐948 and 18F‐flutemetamol PET, T1‐weighted MRI, cognition, CSF, and plasma biomarkers were included. Participants were initially categorized into AT stages using CSF‐based pre‐established cut‐off values [1]. Regional SUVR of 18F‐RO‐948 PET was calculated in entorhinal(BraakI/II), limbic(BraakIII/IV), and neocortical(BraakV/VI) regions using the inferior cerebellum as reference region as well as with the CenTAURz. Regional positivity thresholds per Braak stage were calculated as the median+2SD of the CSF A‐T‐ group. Amyloid PET was quantified using Centiloids. Pearson correlations were calculated between regional 18F‐RO‐948 SUVRs and AD biomarkers. ROC analyses adjusted for age, sex, and APOE‐ε4 performed to evaluate the capacity of biomarkers in predicting BraakI/IIPositive. Four progressive PET‐derived AT groups were defined using Centiloid and tau PET positivity cut‐offs (A‐T‐, AGZT‐, A+T‐ and A+T+; with A‐ CL<12, 12≤AGZ<38 and A+ CL≥38 [2], and T+ BraakI/II>1.35) and between‐stage differences in z‐scored biomarkers evaluated using a Kruskal‐Wallis tests. Results: Table 1 shows demographic information of participants. Nine(9.09%) participants were BraakI/IIPositive, seven(7.07%) BraakIII/IVPositive and one(1.01%) BraakV/VIPositive. Two BraakIII/IVPositive participants were BraakI/IINegative, deviating from the Braak hierarchical model. CSF biomarker correlations with BraakI/II SUVR (Figure 1‐A) ranged from r=0.24(ttau) to r=0.57(ptau217) and plasma (Figure 1‐B) from r=0.30(ptau217) to r=0.49(ptau181). Correlations survived adding age+sex+APOE‐ε4 in the model (Figure 1‐C&D). CSF ptau181/Aβ42, ptau217 and ptau205 showed an AUC≥0.93 to predict BraakI/IIPositive, and plasma ptau181, ptau181/Aβ42 and ptau217 had an AUC≥0.84. Centiloid positivity threshold for BraakI/IIPositive was 38.14CL. Plasma ptau181, ptau181/Aβ42, and CSF ptau205, ptau217, and ptau235 reached a mean z‐score>2 for the PET‐derived A+T+ group (Figure 2) which was associated with lower cognitive scores for executive function (p=0.03), attention (p=0.05), and the PACC (p=0.01). Conclusion: 18F‐RO‐948 PET conformed to the Braak hierarchical model for most tau‐positive participants. Fluid AD biomarkers showed moderate associations with tau PET SUVR. Plasma biomarkers showed good capacity to predict BraakI/IIPositive and track fibrillary amyloid and tau pathological changes in the early preclinical AD continuum.Item Blood biomarkers for Alzheimer’s disease in clinical practice and trials(Springer Nature, 2023) Hansson, Oskar; Blennow, Kaj; Zetterberg, Henrik; Dage, Jeffrey; Neurology, School of MedicineBlood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.Item Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape(Elsevier, 2023) Hampel, Harald; Hu, Yan; Cummings, Jeffrey; Mattke, Soeren; Iwatsubo, Takeshi; Nakamura, Akinori; Vellas, Bruno; O’Bryant, Sid; Shaw, Leslie M.; Cho, Min; Batrla, Richard; Vergallo, Andrea; Blennow, Kaj; Dage, Jeffrey; Schindler, Suzanne E.; Neurology, School of MedicineTimely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.Item Cerebrospinal fluid glial fibrillary acidic protein provides differential diagnostic value in some forms of dementias(Wiley, 2025-01-09) Eriksson, Pontus; Skillback, Tobias; Kern, Silke; Jönsson, Linus; Blennow, Kaj; Eriksdotter, Maria; Zetterberg, Henrik; Neurology, School of MedicineBackground: Glial fibrillary acidic protein (GFAP) is a marker of cerebral astrogliosis and occasionally elevated in patients with dementia. GFAP in cerebrospinal fluid (CSF), is routinely requested in referrals to neurochemistry laboratories; however, its ability to differentiate dementias and diagnostic capability is unclear. Our aim was to elucidate this, using two large datasets. Method: First, GFAP data measured since 2015 was retrieved from the database of the Clinical Neurochemistry Laboratory at the Sahlgrenska University hospital. We then cross‐referenced with the Swedish dementia registry (SveDem). Here, information on ten different diagnoses such as early onset AD (EAD [<65 years]), late onset AD (LAD [≥65 years]), Parkinson disease with dementia (PDD), vascular dementia (VaD) and frontotemporal dementia (FTD), each with specific diagnostic criteria, were retrieved. The GFAP data was log10‐transformed, followed by an analysis of covariance (ANCOVA) and a subsequent post‐hoc Tukey’s test, with GFAP as dependent variable, diagnosis as independent variable and sex and age as covariates. Result: In total, 1912 individuals (mean [SD] age, 71.9 [8.2] years; 52% male), were included. Lower log10‐transformed GFAP concentrations were seen in PDD (mean [SD], 2.68, [0.28] pg/mL), than in EAD, LAD, VaD and FTD; here, mean concentrations of 2.76 (0.24), 2.89 (0.23), 2.89 (0.32) and 2.76 (0.25) pg/mL were observed, respectively. In the post hoc analysis, GFAP differentiated VaD from EAD (p<0.001). PDD concentrations were significantly different from VaD (p<0.001) and LAD (p<0.001). Further, it also differentiated FTD from VaD (p=0.006) and LAD (p=0.001). Conclusion: CSF GFAP could on a group level help differentiate VaD from EAD, FTD and PDD. Also, it could differentiate PDD from LAD. These results bear potential clinical relevance, where clinicians in some uncertain cases could use this marker as a differential tool.