Tau Biomarkers Research Articles

CSF β-Amyloid and Tau Biomarker Changes in Veterans With Mild Traumatic Brain Injury.

Moderate-to-severe traumatic brain injuries (TBI) have been reported to increase the risk of Alzheimer disease (AD). Whether mild TBI (mTBI) in veterans confers a similar increased risk of AD is less known. This study investigated early AD changes using CSF biomarkers in veterans with blast mTBI. This was a cross-sectional case-control study of veterans with mTBI and non-mTBI veterans and civilians from 2 study sources. Blast-mTBI veterans had at least 1 war zone blast or combined blast/impact mTBI meeting Veterans Affairs (VA) and Department of Defense (DoD) criteria for mTBI. Non-mTBI participants had no lifetime history of TBI. All participants underwent standardized clinical and neuropsychological assessments and lumbar puncture for collection of the CSF. CSF biomarkers were measured using MesoScale Discovery assays for Aβ40 and Aβ42 and INNOTEST ELISAs for phosphorylated tau181 (p-tau181) and total tau (t-tau). Our sample comprised 51 participants with mTBI and 85 non-mTBI participants with mean (SD) ages 34.0 (10.1) and 33.5 years (8.9), respectively. All participants but 1 (99%) were male. Differences in CSF AD biomarkers between mTBI and non-mTBI groups were age dependent and most pronounced at older ages (omnibus test p ≤ 0.08). At age 50 years, the mTBI group had lower mean [95% CI] CSF Aβ42 and Aβ40 than the non-mTBI group by 154 [-12 to 319] and 1864 [610-3,118] pg/mL, respectively. By contrast, CSF p-tau181 and t-tau mean levels remained relatively constant with age in participants with mTBI, while tending to be higher at older ages for the non-mTBI group. The mTBI group also demonstrated poorer cognitive performance at older ages (omnibus p < 0.08): at age 50 years, the mean TMT-B time was higher by 34 seconds [10-58] and the mean CVLT-II short-delay recall was lower by 4.2 points [1.9-6.6]. Poorer verbal memory and verbal fluency performance were associated with lower CSF Aβ42 (p ≤ 0.05) in older participants. CSF Aβ levels decreased in middle-aged veterans with blast-related mTBI. These data suggest that chronic neuropathologic processes associated with blast mTBI share properties in common with pathogenic processes known to portend AD onset, thus raising concern that veterans with blast-related mTBI may develop a dementing disorder later in life.

On the road to biological blood diagnosis of Alzheimer's disease?

The growing number of people suffering from Alzheimer's disease (AD) represents a major public health problem. The diagnosis of AD is multidisciplinary and involves the use of amyloid and tau biomarkers measured in cerebrospinal fluid. Recent advances in analytical techniques now allow us to measure these biomarkers in blood. Blood biomarkers offer particularly promising potential for early, minimally invasive detection of AD, as well as for differential diagnosis of dementia and patient follow-up. The aim of this review is to provide an overview of current and candidate blood biomarkers for AD, their informative value, and their potential to be integrated into clinical practice in the near future.

The diagnostic and prognostic value of tau-PET in amnestic MCI with different FDG-PET subtypes.

Mild cognitive impairment presenting with an amnestic syndrome (aMCI) and amyloid positivity is considered due to AD. Many subjects, however, can show an overall very slow progression relevant for differential diagnosis, prognosis, and treatment. This study assessed PET biomarkers, includingbrain glucose metabolism, tau, and amyloid load, in a series of comparable aMCI at baseline, clinically evaluated at follow-up. We included 72 aMCI subjects from Geneva Memory Center (N = 31) and ADNI cohorts (N = 41), selected based on available FDG-PET, tau-PET, amyloid-PET, and clinical follow-up (2.3 years ± 1.2). A data-driven algorithm classified brain metabolic patterns into subtypes that were then compared for clinical and PET biomarker measures and cognitive decline. Voxel-wise comparisons were performed both with FDG-PET and tau-PET data. The algorithm classified three metabolic subtypes, namely "Hippocampal-sparing with cortical hypometabolism" (Type1; N = 27), "Hippocampal and cortical hypometabolism" (Type 2; N = 23), and "Medial temporal hypometabolism" (Type 3; N = 22). Amyloid positivity and tau accumulation in the medial temporal and neocortical regions characterized Type 1 and Type 2, whereas Type 3 showed no significant tau pathology, variable amyloid positivity, and stability at follow-up. All tau-positive patients, independently of the FDG-based subtype, showed faster cognitive decline. aMCI subjects can differ in metabolic patterns, tau and amyloid pathology, and clinical progression. Here, we complemented with PET tau biomarker the specific brain hypometabolic patterns at the individual level in the prodromal phase, contributing to the patient's classification. Tau PET is the most accurate biomarker in supporting or excluding the AD diagnosis in aMCI across metabolic subtypes and also predicting the risk of decline.

Plasma p-tau212 antemortem diagnostic performance and prediction of autopsy verification of Alzheimer’s disease neuropathology

Blood phosphorylated tau (p-tau) biomarkers, including p-tau217, show high associations with Alzheimer’s disease (AD) neuropathologic change and clinical stage. Certain plasma p-tau217 assays recognize tau forms phosphorylated additionally at threonine-212, but the contribution of p-tau212 alone to AD is unknown. We developed a blood-based immunoassay that is specific to p-tau212 without cross-reactivity to p-tau217. Here, we examined the diagnostic utility of plasma p-tau212. In five cohorts (n = 388 participants), plasma p-tau212 showed high performances for AD diagnosis and for the detection of both amyloid and tau pathology, including at autopsy as well as in memory clinic populations. The diagnostic accuracy and fold changes of plasma p-tau212 were similar to those for p-tau217 but higher than p-tau181 and p-tau231. Immunofluorescent staining of brain tissue slices showed prominent p-tau212 reactivity in neurofibrillary tangles that co-localized with p-tau217 and p-tau202/205. These findings support plasma p-tau212 as a peripherally accessible biomarker of AD pathophysiology.

Higher levels of brain injury biomarker tau are associated with unfavorable outcomes in patients supported with ECMO following cardiac arrest

AimWe sought to determine if higher plasma levels of brain injury biomarkers neurofilament light (NfL), phosphorylated tau 181 (pT181), tau, and ubiquitin C-terminal hydrolase L1 (UCHL1) were associated with unfavorable outcomes in children supported on extracorporeal membrane oxygenation (ECMO) with and without preceding cardiac arrest. MethodsWe conducted a secondary analysis of a two-center prospective observational study of ECMO patients 0-<18 years. Plasma concentrations of NfL, pT181, tau, and UCHL1 were measured on ECMO days 1, 2 and 3. Unfavorable outcome was defined as in-hospital mortality or discharge Pediatric Cerebral Performance Category (PCPC) >2 with decline from baseline PCPC among survivors. ResultsAmong 88 children on ECMO, mean tau levels were significantly higher on each of the first three ECMO days in children who underwent extracorporeal cardiopulmonary resuscitation (ECPR) compared to those with non-ECPR cardiac arrest or with no cardiac arrest preceding ECMO. Higher ECMO day 1 tau levels were significantly associated with increased hazard of unfavorable outcome in unadjusted (HR, 1.35, 95% CI 1.09–1.66) and adjusted (HR, 1.42; 95% CI 1.13–1.79) models. Higher levels of NfL or pT181 were not associated with increased hazard for unfavorable outcome in multivariable models.UCHL1 values were outside of detectable limits and thus deferred from analysis. ConclusionsLevels of tau were significantly associated with increased hazard of death or unfavorable neurologic outcome in unadjusted and adjusted models. Biomarkers of brain injury, particularly tau, may aid in detection of neurologic injury and neuroprognostication in patients on ECMO with and without preceding cardiac arrest.

Highly sensitive detection of the neurodegenerative biomarker Tau by using the concentration effect of the pyro-electrohydrodynamic jetting

It is largely documented that neurodegenerative diseases can be effectively treated only if early diagnosed. In this context, the structural changes of some biomolecules such as Tau, seem to play a key role in neurodegeneration mechanism becoming eligible targets for an early diagnosis. Post-translational modifications are responsible to drive the Tau protein towards a transition phase from a native disorder conformation into a preaggregation state, which then straight recruits the final fibrillization process. Here, we show for the first time the detection of pre-aggregated Tau in artificial urine at femto-molar level, through the concentration effect of the pyro-electrohydrodynamic jet (p-jet) technique. An excellent linear calibration curve is demonstrated at the femto-molar level with a limit of detection (LOD) of 130 fM. Moreover, for the first time we show here the structure stability of the protein after p-jet application through a deep spectroscopic investigation. Thanks to the small volumes required and the relatively compact and cost-effective characteristics, this technique represents an innovative breakthrough in monitoring the early stage associated to neurodegeneration syndromes in different scenarios of point of care (POC) and such as for example in long-term human space exploration missions.

BDNF Val66Met moderates episodic memory decline and tau biomarker increases in early sporadic Alzheimer's disease.

Allelic variation in the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism has been shown to moderate rates of cognitive decline in preclinical sporadic Alzheimer's disease (AD; i.e., Aβ + older adults), and pre-symptomatic autosomal dominant Alzheimer's disease (ADAD). In ADAD, Met66 was also associated with greater increases in CSF levels of total-tau (t-tau) and phosphorylated tau (p-tau181). This study sought to determine the extent to which BDNF Val66Met is associated with changes in episodic memory and CSF t-tau and p-tau181 in Aβ + older adults in early-stage sporadic AD. Aβ + Met66 carriers (n = 94) and Val66 homozygotes (n = 192) enrolled in the Alzheimer's Disease Neuroimaging Initiative who did not meet criteria for AD dementia, and with at least one follow-up neuropsychological and CSF assessment, were included. A series of linear mixed models were conducted to investigate changes in each outcome over an average of 2.8years, covarying for CSF Aβ42, APOE ε4 status, sex, age, baseline diagnosis, and years of education. Aβ + Met66 carriers demonstrated significantly faster memory decline (d = 0.33) and significantly greater increases in CSF t-tau (d = 0.30) and p-tau181 (d = 0.29) compared to Val66 homozygotes, despite showing equivalent changes in CSF Aβ42. These findings suggest that reduced neurotrophic support, which is associated with Met66 carriage, may increase vulnerability to Aβ-related tau hyperphosphorylation, neuronal dysfunction, and cognitive decline even prior to the emergence of dementia. Additionally, these findings highlight the need for neuropsychological and clinicopathological models of AD to account for neurotrophic factors and the genes which moderate their expression.

Clinical variables contributing to the identification of biologically defined subgroups within cognitively unimpaired and mild cognitive impairment individuals.

A lack of consensus exists in linking demographic, behavioral, and cognitive characteristics to biological stages of dementia, defined by the ATN (amyloid, tau, neurodegeneration) classification incorporating amyloid, tau, and neuronal injury biomarkers. Using a random forest classifier we investigated whether 27 demographic, behavioral, and cognitive characteristics allowed distinction between ATN-defined groups with the same cognitive profile. This was done separately for three cognitively unimpaired (CU) (112 A-T-N-; 46 A+T+N+/-; 65 A-T+/-N+/-) and three mild cognitive impairment (MCI) (128 A-T-N-; 223 A+T+N+/-; 94 A-T+/-N+/-) subgroups. Classification-balanced accuracy reached 39% for the CU and 52% for the MCI subgroups. Logical Delayed Recall (explaining 16% of the variance), followed by the Alzheimer's Disease Assessment Scale 13 (14%) and Everyday Cognition Informant (10%), were the most relevant characteristics for classification of the MCI subgroups. Race and ethnicity, marital status, and Everyday Cognition Patient were not relevant (0%). The demographic, behavioral, and cognitive measures used in our model were not informative in differentiating ATN-defined CU profiles. Measures of delayed memory, general cognition, and activities of daily living were the most informative in differentiating ATN-defined MCI profiles; however, these measures alone were not sufficient to reach high classification performance.

ALZHEIMER DISEASE: WHAT’S NEW, WHAT’S TRUE?

Alzheimer’s Disease (AD) is a devastating disorder estimated to affect 55 million individuals worldwide with 6.2 million cases in the US. AD is a significant clinical problem and numbers are only expected to increase. Alzheimer’s disease is characterized by structural changes in the brain including abnormal amyloid beta (Aβ) and neurofibrillary tau aggregation, neuroinflammation, and neuronal death. There is no effective treatment for AD and AD-related dementia (ADRD). For decades, the hypothesis that brain deposition of the amyloid-beta (Aβ) peptide initiates AD has dominated research and clinical trials. However, the FDA- approved antibody treatments targeting Aβ have yet to show convincing evidence for slowing the progression of disease symptomatology3, including no benefit to women and ApoE4 carriers over a period of 1.5 years4. Treatment failures can be attributed, at least in part, to an incomplete understanding of the pathogenic mechanisms of AD, which underscores the urgent need to examine alternative pathogenic mechanisms and therapeutic targets for AD. AD has been increasingly recognized as a multifactorial and heterogeneous disease with multiple contributors to its pathophysiology, where neuroinflammation is considered one of the cardinal features of AD. Traditionally, the pathways of Aβ production and neuroinflammation have been considered independently; however, recent studies suggest that these processes may converge to promote the pathology associated with AD. Surmounting evidence supports chronic dysregulation in inflammatory and immune pathways as drivers of AD neurodegeneration and provides insights into possible microbial mechanisms involved in the onset and progression of AD. Mounting evidence implicates gut microbiome dysbiosis in AD, even at the preclinical/asymptomatic and prodromal stages of the disease. Links have been made between the gut microbiome and established biomarkers of AD, including Aß, ApoE status, and tau. Further, links between the gut microbiota and brain connectivity, as measured by functional magnetic resonance imaging (fMRI), have recently emerged but are poorly understood in AD. Our research group previously demonstrated cerebrovascular dysfunction in prodromal AD, correlated with cognitive dysfunction. Specifically, reduced cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) are associated with lower cognitive functioning in prodromal AD. Findings from our recent cross-sectional study indicate that pro-inflammatory gut bacteria more abundant in prodromal AD are associated with reduced CBF and CVR and elevated arterial transit time (ATT). Conversely, beneficial gut bacteria, more abundant in normal controls, are associated with better CBF and CVR and shorter ATT. Further, we identified the bile acid and lipid metabolism modifying organism and the oral pathogen (causes gingivitis and periodontal disease), to be differentially abundant in prodromal AD and CU cohorts, respectively. These results are undeniably promising for the future of AD in many ways including novel mechanistic discovery, non-invasive diagnostic testing, and novel treatment targets.

CSF Extracellular Vesicle Aβ42 and Tau/Aβ42 Ratio Are Associated with Cognitive Impairment in Older People with HIV.

HIV-associated neurocognitive disorders (HAND) remain prevalent despite viral suppression on antiretroviral therapy (ART). Older people with HIV (PWH) are also at risk for amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). β-amyloid (Aβ) and Tau biomarkers are associated with aMCI/AD, but their relationship to HAND is unclear. Given the role of extracellular vesicles (EVs) in age-related neurological disorders, we investigated soluble and EV-associated Aβ42, total Tau, NFL, GFAP, ICAM-1, VCAM-1, and CRP in relation to cognitive impairment in PWH. Plasma and CSF EVs were isolated from 184 participants (98 PWH on ART and 86 HIV- controls). Biomarkers were measured using Meso Scale Discovery assays. The median age of PWH was 53 years, and 52% were diagnosed with mild forms of HAND. PWH had increased plasma NFL (p = 0.04) and CSF Aβ42 (p = 0.0003) compared with HIV- controls but no significant difference in Tau or EV-associated forms of these markers. CSF EV Aβ42 was decreased (p = 0.0002) and CSF EV Tau/Aβ42 ratio was increased (p = 0.001) in PWH with HAND vs. no HAND, while soluble forms of these markers showed no significant differences. Decreased CSF EV Aβ42 (p < 0.0001) and an increased CSF EV Tau/Aβ42 ratio (p = 0.0003) were associated with lower neurocognitive T scores in age-adjusted models; an optimal model included both CSF EV Aβ42 and plasma NFL. Levels of soluble, but not EV-associated, ICAM-1, VCAM-1, and CRP were increased in PWH with HAND vs. no HAND (p < 0.05). These findings suggest that decreased Aβ42 and an increased Tau/Aβ42 ratio in CSF EVs are associated with cognitive impairment in older PWH, and these EV-associated biomarkers may help to distinguish aMCI/AD from HIV-related cognitive disorders in future studies.

Association of Sleep Duration and Change Over Time With Imaging Biomarkers of Cerebrovascular, Amyloid, Tau, and Neurodegenerative Pathology.

Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration, and (V)ascular neuroimaging markers of Alzheimer disease. Two Framingham Heart Study overlapping samples were studied: participants who underwent 11C-Pittsburg Compound B amyloid and 18F-flortaucipir tau PET imaging and participants who underwent an MRI. MRI metrics estimated neurodegeneration (total brain volume) and cerebrovascular injuries (white matter hyperintensities [WMHs] volume, covert brain infarcts, free-water [FW] fraction). Self-reported sleep duration was assessed and split into categories both at the time of neuroimaging testing and approximately 13 years before: short ≤6 hours. average 7-8 hours, and long ≥9 hours. Logistic and linear regression models were used to examine sleep duration and neuroimaging metrics. The tested cohort was composed of 271 participants (age 53.6 ± 8.0 years; 51% male) in the PET imaging sample and 2,165 participants (age 61.3 ± 11.1 years; 45% male) in the MRI sample. No fully adjusted association was observed between cross-sectional sleep duration and neuroimaging metrics. In fully adjusted models compared with consistently sleeping 7-8 hours, groups transitioning to a longer sleep duration category over time had higher FW fraction (short to average β [SE] 0.0062 [0.0024], p = 0.009; short to long β [SE] 0.0164 [0.0076], p = 0.031; average to long β [SE] 0.0083 [0.0022], p = 0.002), and those specifically going from average to long sleep duration also had higher WMH burden (β [SE] 0.29 [0.11], p = 0.007). The opposite associations (lower WMH and FW) were observed in participants consistently sleeping ≥9 hours as compared with people consistently sleeping 7-8 hours in fully adjusted models (β [SE] -0.43 [0.20], p = 0.028; β [SE] -0.019 [0.004], p = 0.020). Each hour of increasing sleep (continuous, β [SE] 0.12 [0.04], p = 0.003; β [SE] 0.002 [0.001], p = 0.021) and extensive increase in sleep duration (≥2 hours vs 0 ± 1 hour change; β [SE] 0.24 [0.10], p = 0.019; β [SE] 0.0081 [0.0025], p = 0.001) over time was associated with higher WMH burden and FW fraction in fully adjusted models. Sleep duration change was not associated with PET amyloid or tau outcomes. Longer self-reported sleep duration over time was associated with neuroimaging biomarkers of cerebrovascular pathology as evidenced by higher WMH burden and FW fraction. A longer sleep duration extending over time may be an early change in the neurodegenerative trajectory.

Mechanistic modeling of tau biomarkers for amyloid load. A Quantitative Systems Pharmacology study of amyloid‐tau interaction.

AbstractBackgroundRecent clinical trials with amyloid antibodies have suggested a beneficial effect on cognitive scales after clearing most of the amyloid load. Interestingly, substantial reduction in plasma or CSF tau biomarkers were documented providing interesting insights into the amyloid‐tau interactions in the human AD patient.MethodWe developed a Quantitative Systems Pharmacology (QSP) platform for late MCI‐prodromal AD subjects that combined an earlier published Physiology‐Based Pharmacokinetic (PBPK)‐ QSP model of amyloid aggregation with a novel QSP model describing the impact of amyloid monomers on glutamatergic and nicotinic neurotransmission and neuronal firing, the neuronal activity‐dependent tau release, subsequent tau uptake in the afferent neuron and dynamics of tau biomarkers in CSF and plasma.ResultThe combined model quantitatively reproduced (1) the cortical hyperactivity and higher tau biomarker levels associated with increasing amyloid deposition in observational studies, (2) the differential decrease in CSF and plasma tau biomarkers in clinical trials with various amyloid antibodies. Dynamics of monomeric brain Ab40 and Ab42 and their effect on neuronal firing, rather than reduction in SUVR can better explain the clinically observed changes in CSF or plasma tau between aducanumab, lecanemab, donanemab and gantenerumab. The range of commonly used comedications and common dopaminergic and serotonergic genotype variants affecting neuronal activity can partially explain the variability of tau biomarkers response as downstream effects of amyloid removal.ConclusionThis study suggests a direct link between amyloid dynamics and plasma / CSF tau levels through modulation of neuronal activity. The calibrated QSP model sets the stage for modeling long‐term effects of amyloid therapy on tau pathology progression and identification of optimal trial design for combination therapies.

Lecanemab: Amyloid Reduction and Evidence of Downstream Biomarker Modification

AbstractBackgroundLecanemab is a humanized IgG1 monoclonal antibody that targets soluble aggregated Aβ species (protofibrils) which has demonstrated robust brain fibrillar amyloid reduction and slowing of clinical decline in a Phase 3 Study in early AD (Study 301). The objective of this analysis is to report biomarker results from Study 301.MethodsStudy 301 was a double‐blind, randomized, placebo‐controlled study of 1875 patients with early AD randomized to 10 mg/kg IV lecanemab or placebo for 18 months of treatment. Plasma, CSF, and imaging biomarkers of amyloid, tau, neurodegeneration, and gliosis were assessed.ResultsLecanemab met all primary and key secondary clinical endpoints with a high degree of statistical significance. Lecanemab improved markers of amyloid with reduction of brain amyloid by PET in as early as 3 months and improvement in CSF Aß42 and plasma Aß42/40. Biomarkers of tau showed improvement in CSF and plasma p‐tau181, and slowing of tau accumulation relative to placebo in the medial temporal regions by tau PET. For biomarkers of neurodegeneration and gliosis, there was improvement in CSF t‐tau, CSF neurogranin, and plasma GFAP. There were no significant differences in CSF or plasma Nf‐L between lecanemab and placebo. Volumetric MRI results were inconsistent, with reduced hippocampal atrophy on lecanemab, but greater cortical volume loss relative to placebo, possibly “pseudoatrophy” related to amyloid mobilization.ConclusionsLecanemab treatment resulted in significant reduction in amyloid plaques and a slowing of clinical decline. Improvements in biomarkers of amyloid, tau, neurodegeneration, and gliosis provide a biological basis for the treatment effects consistent with disease modification.

Telomeres are associated with markers and regions sensitive to aging and not Alzheimer’s disease in cognitively unimpaired older adults

AbstractBackgroundTelomeres (protective chromosomal ends) gradually shorten over the lifespan and have been associated with the development of age‐related diseases such as Alzheimer’s disease (AD). Most studies use median telomere length as a biomarker of cellular aging, but their dysfunction is rather reflected by the load of short telomere. No study to date has assessed the links between the percentage of short telomeres (ST) and blood, neuroimaging markers of aging, neurodegeneration, amyloid and tau pathologies in healthy elderly.MethodBaseline data from 125 cognitively unimpaired older adults (65 to 83 years old; mean ± SD: 68.9 ± 2.8) from the Age‐Well trial (NCT02977819), who completed multimodal neuroimaging and blood sampling, were analyzed. Neuroimaging data included structural T1‐weighted MRI, T2‐weighted high‐resolution scan of the hippocampus, DKI, FDG‐PET and AV45‐PET (perfusion and amyloid load). ST, as well as neurodegeneration, amyloid, and tau biomarkers (NFL, GFAP, Aß42/40 ratio and pTau181) were measured in blood samples. Multiple linear regressions between ST and each marker were conducted corrected for age, sex, education and body mass index. Additional adjustments for APOE and amyloid status were made. Statistical significance was set to p&lt;0.05, except for voxelwise analyses (puncorrected&lt;0.005, kuncorrected = 500 voxels).ResultST was associated with lower white matter integrity (measured by kurtosis fractional anisotropy (kFA)) in prefrontal and temporal regions (Fig.1), and with the hippocampal subiculum volume, but not with total gray matter volume, mean kurtosis, glucose metabolism, brain perfusion or amyloid load; nor with blood markers of neurodegeneration, amyloid, or tau. Additional adjustments for APOE/amyloid status gave similar results.ConclusionTelomere dysfunctions were associated with lower white matter integrity in regions vulnerable to aging, but not to AD, nor with neurodegeneration, amyloid or tau biomarkers, and neither with AD risk factors (APOE or amyloid status). When we focused on the hippocampus, a specific link was found with the subiculum volume, an hippocampal subfield known to be the most sensitive to aging, which is not the case in AD. These results give further evidence for the tight connection between cellular and cerebral aging, but not with AD in cognitively unimpaired older adults.

Telomeres are associated with markers and regions sensitive to aging and not Alzheimer’s disease in cognitively unimpaired older adults

AbstractBackgroundTelomeres (protective chromosomal ends) gradually shorten over the lifespan and have been associated with the development of age‐related diseases such as Alzheimer’s disease (AD). Most studies use median telomere length as a biomarker of cellular aging, but their dysfunction is rather reflected by the load of short telomere. No study to date has assessed the links between the percentage of short telomeres (ST) and blood, neuroimaging markers of aging, neurodegeneration, amyloid and tau pathologies in healthy elderly.MethodBaseline data from 125 cognitively unimpaired older adults (65 to 83 years old; mean ± SD: 68.9 ± 2.8) from the Age‐Well trial (NCT02977819), who completed multimodal neuroimaging and blood sampling, were analyzed. Neuroimaging data included structural T1‐weighted MRI, T2‐weighted high‐resolution scan of the hippocampus, DKI, FDG‐PET and AV45‐PET (perfusion and amyloid load). ST, as well as neurodegeneration, amyloid, and tau biomarkers (NFL, GFAP, Aβ42/40 ratio and pTau181) were measured in blood samples. Multiple linear regressions between ST and each marker were conducted corrected for age, sex, education and body mass index. Additional adjustments for APOE and amyloid status were made. Statistical significance was set to p&lt;0.05, except for voxelwise analyses (puncorrected&lt;0.005, kuncorrected = 500 voxels).ResultST was associated with lower white matter integrity (measured by kurtosis fractional anisotropy (kFA)) in prefrontal and temporal regions (Fig.1), and with the hippocampal subiculum volume, but not with total gray matter volume, mean kurtosis, glucose metabolism, brain perfusion or amyloid load; nor with blood markers of neurodegeneration, amyloid, or tau. Additional adjustments for APOE/amyloid status gave similar results.ConclusionTelomere dysfunctions were associated with lower white matter integrity in regions vulnerable to aging, but not to AD, nor with neurodegeneration, amyloid or tau biomarkers, and neither with AD risk factors (APOE or amyloid status). When we focused on the hippocampus, a specific link was found with the subiculum volume, an hippocampal subfield known to be the most sensitive to aging, which is not the case in AD. These results give further evidence for the tight connection between cellular and cerebral aging, but not with AD in cognitively unimpaired older adults.

Utilization and future of biomarkers in biofluid as outcome measures in clinical trials for Alzheimer’s disease: a systematic review

AbstractBackgroundIn recent years, the availability of biofluid markers in Alzheimer’s disease (AD) has increased substantially, but it is unclear to what extend these are applied to support drug development. Therefore, we provide an overview of biofluid biomarker use within trials.MethodTo identify how fluid biomarkers are used in clinical trials, we performed a search (8‐FEB‐2022) on www.clinicaltrials.gov, using the search term ‘Alzheimer’s disease’, and selected trials aimed at disease modification starting from 1‐JAN‐2017 to 1‐JAN‐2022. Biofluid markers and their purpose in each trial were described. Results are summarized by trial phase, target class, and endpoint information.ResultWe identified 186 trials of which 44% used biofluid markers. 15% of phase 1 trials, 15% of phase 2 trials, and 6% of phase 3 and 4 trials employ fluid biomarkers as primary outcome (Figure 1). Blood and CSF biomarkers were used equally frequent. CSF biomarkers for Aβ, Tau, and other biomarkers were employed in 21%, 25%, and 16% of the 186 trials, respectively. Blood biomarkers for Aβ, Tau, and other biomarkers were used in 14%, 13%, and 23% of the trials, respectively. Moving further in the drug development phases, contribution of classic AD biomarkers increased, especially in CSF. Overall, a combination of Aβ, Tau and other biomarkers was used most frequent. 25% of the trials use biofluid target engagement markers. Target engagement marker use is most prominent in amyloid and tau targeting drugs. Lack of target engagement markers is most prominent in synaptic plasticity/neuroprotection, neurotransmitter receptor, vasculature, epigenetic regulators, proteostasis, gut‐brain axis targeting drugs.ConclusionThere exists a need for new fluid biomarkers, to reflect pathology which can be used in certain target classes where there currently is a lack of fluid biomarkers. To support future use biofluid markers as surrogate outcomes, research into the specific pathological processes they reflect and their correlation with cognition is warranted. This can pave the way into implementation of surrogacy biomarkers in AD clinical trials.

Lessons from neuropathology to inform on fluid biomarkers of amyloid and tau

AbstractFluid biomarkers of amyloid and tau, including measures in both cerebrospinal fluid and plasma, have been used extensively in clinical and translational studies of Alzheimer’s disease and other neurodegenerative diseases. These biomarkers are now also increasingly used in clinical practice to inform on diagnosis and prognosis. Despite a successful development of new biomarkers with high diagnostic accuracy for Alzheimer’s disease, the exact relationship between fluid biomarkers and underlying pathological changes in the brain of patients with neurodegenerative diseases have long been unclear.Multimodal studies that integrate state‐of‐the‐art fluid biomarkers with neuropathological measurements are now beginning to inform on the exact relationship between alterations in soluble protein levels and underlying pathological changes. These findings have broad implications for the optimal use of fluid amyloid and tau biomarkers in clinical practice, research, and development of drugs targeting specific neuropathological mechanisms.This talk will highlight recent key findings in this field, discuss remaining challenges, and point out future directions for research.

Investigating Potential Racial Differences in Dementia‐Related Plasma Biomarkers

AbstractBackgroundBlack self‐identified individuals are disproportionately affected by dementia, a phenomenon best attributable to differences in social determinants of health (SDOH). Plasma protein levels can serve as antemortem indicators of dementia pathology; recent findings indicate potential race‐specific differences in these biomarkers of tau and non‐tau pathologies between Black self‐identified or White individuals.MethodsThis sample included 568 participants (77, 13.56% Black self‐identified, Table 1) from the Boston University Alzheimer’s Disease and Research Center (BUADRC). Participants completed a battery of neuropsychological tests and cognitive diagnoses were made during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using ELISA methods for YKL‐40 levels and using Simoa platform for phosphorylated tau (p‐tau 181, p‐tau231), total‐tau, glial fibrillary acidic (GFAP), and neurofilament light chain (NfL) levels. ANCOVAs tested for a cross‐sectional association between racial identity and each plasma biomarker and stratified by cognitive impairment status with covariates for age, education (in years), sex assigned at birth, and APOE ε4 carrier status. Cox proportional‐hazards models were used for longitudinal analyses of the interaction effect between racial identity and plasma biomarkers in the risk for conversion from normal cognition (NC) to mild cognitive impairment (MCI) and reversion from MCI to NC.ResultsBaseline YKL‐40 was lower among Black self‐identified participants (adjusted mean diff = 0.37 SD, p&lt;.001); this association was particularly salient within the MCI group (adjusted mean diff = 0.62 SD, p&lt;.001). The longitudinal analysis revealed interaction effects between race and GFAP for risk for conversion from NC to MCI and reversion from MCI to NC. Among White participants, higher GFAP predicted increased risk for conversion from NC to MCI and lower levels predicted reversion. However, no significant effects were found among Black self‐identified participants; these findings might be limited by sample size (n = 18) resulting from the high occurrence of baseline MCI diagnoses and subsequent lack of conversion or reversion among Black self‐identified participants.ConclusionIn the context of an unrepresentative sample, we found trivial differences in plasma biomarkers between Black self‐identified and White participants. Recruitment of Black self‐identified participants representative of the population and further exploration of SDOH is essential in understanding the disproportionate risk for dementia carried by Black self‐identified individuals.

Biofluid phospho‐tau with subthreshold tau‐PET predicts higher rates of tau accumulation: implications for secondary prevention trials

AbstractBackgroundAn important end‐point for disease‐modifying treatments is to target the accumulation of tau. This highlights the need to determine which individuals are most likely to accumulate tau in the future. Different biomarkers of tau become abnormal at different stages of Alzheimer’s disease and capturing the evolution of tau pathology in its entirety will rely on multi‐modal assessments. Here, we examine longitudinal changes in tau accumulation associated with elevated CSF p‐tau and tau‐PET biomarkers.MethodA total of 231 amyloid‐positive (A+) individuals from the BioFINDER‐2 study were categorised into groups based on cut‐offs for abnormal CSF p‐tau217 (P) and [18F]RO948 tau‐PET (T), yielding groups of tau‐concordant‐negative (A+P‐T‐;n = 30), tau‐discordant (A+P+T‐;n = 48) and tau‐concordant‐positive (A+P+T+;n = 18) individuals. In addition, 135 amyloid‐β‐negative, unimpaired individuals served as controls. Differences in regional tau‐PET between groups were assessed using general‐linear models, adjusted for age, sex, clinical‐diagnosis and (for cognitive measures) education. We additionally assessed the effects on cortical thickness and cognition. Mean follow‐up time was ∼2 years.ResultIn the A+P+T‐ group, even though below the threshold for positivity, tau‐PET was higher at baseline than in the control and A+P‐T‐ groups, while cortical thickness and cognition were not different between these groups. For the A+P+T+ group, tau‐PET was higher, and cortical thickness, and cognition were lower at baseline than for controls, A+P‐T‐ and A+P+T‐. Longitudinal increase in tau‐PET was faster in the A+P+T‐ group than in controls and A+P‐T‐, primarily in the medial‐temporal lobe. The A+P+T+ group showed a faster rate of tau‐PET compared to controls and A+P‐T‐ (across the entire brain), and compared to A+P+T‐ (primarily neocortex). There were no differences in cortical thinning or cognitive decline between controls, A+P+T‐ and A+P‐T‐. The A+P+T+ group showed faster cortical thinning and cognitive decline compared to controls, A+P‐T‐ and A+P+T‐.ConclusionThe A+P+T‐ group only shows tau accumulation and no cortical thinning or cognitive decline, and therefore represents an interesting population for early intervention in the AD pathological process, preventing downstream effects. The A+P+T+ group shows fast and widespread tau accumulation and will, therefore, show the greatest beneficial effect of tau‐targeted treatment but already shows cortical thinning and cognitive decline at baseline.

PROGNOSTIC VALUE OF AT(N) CLASSIFICATION IN CSF USING CLUSTERING ANALYSIS

AbstractBackgroundThe biological definition of Alzheimer’s disease (AD) and the use of biomarkers according to the AT(N) system may improve the clinical characterization of patients and the sequence of events during the clinical course. However, some studies have raised challenges in the clinical application of AT(N) system. Unbiased, data‐driven techniques such as unsupervised machine learning may help optimize it. We aimed to optimize the classification using unsupervised machine learning algorithms (clustering analysis).MethodWe included 421 patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort and 165 from our centre. We included subjective memory complaints (SMC), early mild cognitive impairment due to AD (EMCI), late MCI due to AD (LMCI) and MCI without evidence of neurodegeneration (MCI‐NN) patients according to clinical manifestations, neuropsychological test and CSF biomarkers from our center and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. We clustered the biomarkers separately and all together using the KMeans algorithm for each cohort and compared them in terms of diagnosis, AT(N) system, biomarker values distribution, and risk of progression to dementia.ResultThe optimal number of clusters for all the biomarkers together was three. These clusters differed significantly in both cohorts according to diagnosis, AT(N) categories, biomarker values distribution, and progression to dementia. We found amyloid biomarkers to be more dichotomic, while Tau biomarkers were more continuous. Intergroup comparisons revealed the following groups: 1) non‐defined or unrelated to AD subjects, with no risk of progression to dementia; 2) early stages and/or more delayed risk of conversion to dementia subjects, and 3) more severe cognitive impairment subjects within the early stages of AD and with faster progression to dementia. Findings were largely similar between the two cohorts.ConclusionThis new 3‐group classification, developed with a data‐driven approach, represents a novel perspective to assess the risk of conversion to dementia in a much more simplified way and is complementary to the AT(N) system classification