ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes

Prediction of cognitive conversion within the Alzheimer's disease continuum using deep learning

BACKGROUND

Early diagnosis and accurate prognosis of cognitive decline in Alzheimer's disease (AD) is important to timely assignment to optimal treatment modes. We aimed to develop a deep learning model to predict cognitive conversion to guide re-assignment decisions to more intensive therapies where needed.

METHODS

Longitudinal data including five variable sets, i.e. demographics, medical history, neuropsychological outcomes, laboratory and neuroimaging results, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort were analyzed. We first developed a deep learning model to predicted cognitive conversion using all five variable sets. We then gradually removed variable sets to obtained parsimonious models for four different years of forecasting after baseline within acceptable frames of reduction in overall model fit (AUC remaining > 0.8).

RESULTS

A total of 607 individuals were included at baseline, of whom 538 participants were followed up at 12 months, 482 at 24 months, 268 at 36 months and 280 at 48 months. Predictive performance was excellent with AUCs ranging from 0.87 to 0.92 when all variable sets were considered. Parsimonious prediction models that still had a good performance with AUC 0.80-0.84 were established, each only including two variable sets. Neuropsychological outcomes were included in all parsimonious models. In addition, biomarker was included at year 1 and year 2, imaging data at year 3 and demographics at year 4. Under our pre-set threshold, the rate of upgrade to more intensive therapies according to predicted cognitive conversion was always higher than according to actual cognitive conversion so as to decrease the false positive rate, indicating the proportion of patients who would have missed upgraded treatment based on prognostic models although they actually needed it.

CONCLUSIONS

Neurophysiological tests combined with other indicator sets that vary along the AD continuum can improve can provide aid for clinical treatment decisions leading to improved management of the disease.

TRAIL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT00106899 (Registration Date: 31 March 2005).

Successes and failures: the latest advances in the clinical development of amyloid-β-targeting monoclonal antibodies for treating Alzheimer's disease

INTRODUCTION

The amyloid cascade hypothesis postulated that the accumulation of amyloid-β (Aβ) was the first step of the Alzheimer's disease (AD) pathological process. Effective reduction of Aβ plaque load by numerous drug candidates, among which anti-Aβ monoclonal antibodies, has produced discussible clinical successes and several failures. It was questioned whether Aβ may be the principal AD pathogenic factor and a valid therapeutic target and if targeting Aβ different species could make the difference.

AREAS COVERED

This review article summarized successes and failures of anti-Aβ monoclonal antibody therapy for AD, delineating the latest advances for their clinical development also according to their target engagement and downstream biomarkers.

EXPERT OPINION

The preliminary success of the recent Phase III randomized clinical trials (RCTs) of lecanemab, donanemab, and remternetug, and lessons learned from the failure of previous anti-Aβ monoclonal antibodies RCTs, provided critical evidence to support the role of Aβ in AD pathogenesis. The loss of free Aβ instead of an Aβ toxicity may promote AD neuropathology. Cerebrospinal fluid analyses (i.e. increases in Aβ1-42) may indicate a potential benefit of anti-Aβ monoclonal antibodies in AD and downstream biomarkers should be considered for providing comprehension in cognitive and clinical efficacy of future AD RCTs.

Diagnostic utility of brain MRI volumetry in comparing traumatic brain injury, Alzheimer disease and behavioral variant frontotemporal dementia

BACKGROUND

Brain MRI with volumetric quantification, MRI volumetry, can improve diagnostic delineation of patients with neurocognitive disorders by identifying brain atrophy that may not be evident on visual assessments.

OBJECTIVE

To investigate diagnostic utility of MRI volumetry in traumatic brain injury (TBI), early-onset Alzheimer disease (EOAD), late-onset Alzheimer disease, and behavioral variant frontotemporal dementia (bvFTD).

METHOD

We utilized 137 participants of TBI (n = 40), EOAD (n = 45), LOAD (n = 32), and bvFTD (n = 20). Participants had 3D T1 brain MRI imaging amendable to MRI volumetry. Scan volumes were analyzed with Neuroreader. One-way ANOVA compared brain volumes across diagnostic groups. Discriminant analysis was done with leave-one-out cross validation on Neuroreader metrics to determine diagnostic delineation across groups.

RESULT

LOAD was the oldest compared to other groups (F = 27.5, p < .001). There were no statistically significant differences in sex (p = .58) with women comprising 54.7% of the entire cohort. EOAD and LOAD had the lowest Mini-Mental State Exam (MMSE) scores compared to TBI (p = .04 for EOAD and p = .01 for LOAD). LOAD had lowest hippocampal volumes (Left Hippocampus F = 13.1, Right Hippocampus F = 7.3, p < .001), low white matter volume in TBI (F = 5.9, p < .001), lower left parietal lobe volume in EOAD (F = 9.4, p < .001), and lower total gray matter volume in bvFTD (F = 32.8, p < .001) and caudate atrophy (F = 1737.5, p < .001). Areas under the curve ranged from 92.3 to 100%, sensitivity between 82.2 and 100%, specificity of 78.1-100%. TBI was the most accurately delineated diagnosis. Predictive features included caudate, frontal, parietal, temporal lobar and total white matter volumes.

CONCLUSION

We identified the diagnostic utility of regional volumetric differences across multiple neurocognitive disorders. Brain MRI volumetry is widely available and can be applied in distinguishing these disorders.

Alzheimer's disease: a review on the current trends of the effective diagnosis and therapeutics

The most prevalent cause of dementia is Alzheimer's disease. Cognitive decline and accelerating memory loss characterize it. Alzheimer's disease advances sequentially, starting with preclinical stages, followed by mild cognitive and/or behavioral impairment, and ultimately leading to Alzheimer's disease dementia. In recent years, healthcare providers have been advised to make an earlier diagnosis of Alzheimer's, prior to individuals developing Alzheimer's disease dementia. Regrettably, the identification of early-stage Alzheimer's disease in clinical settings can be arduous due to the tendency of patients and healthcare providers to disregard symptoms as typical signs of aging. Therefore, accurate and prompt diagnosis of Alzheimer's disease is essential in order to facilitate the development of disease-modifying and secondary preventive therapies prior to the onset of symptoms. There has been a notable shift in the goal of the diagnosis process, transitioning from merely confirming the presence of symptomatic AD to recognizing the illness in its early, asymptomatic phases. Understanding the evolution of disease-modifying therapies and putting effective diagnostic and therapeutic management into practice requires an understanding of this concept. The outcomes of this study will enhance in-depth knowledge of the current status of Alzheimer's disease's diagnosis and treatment, justifying the necessity for the quest for potential novel biomarkers that can contribute to determining the stage of the disease, particularly in its earliest stages. Interestingly, latest clinical trial status on pharmacological agents, the nonpharmacological treatments such as behavior modification, exercise, and cognitive training as well as alternative approach on phytochemicals as neuroprotective agents have been covered in detailed.

Astrocyte reactivity is associated with tau tangle load and cortical thinning in Alzheimer's disease

BACKGROUND

It is not fully established whether plasma β-amyloid(Aβ)42/Aβ40 and phosphorylated Tau181 (p-Tau181) can effectively detect Alzheimer's disease (AD) pathophysiology in older Chinese adults and how these biomarkers correlate with astrocyte reactivity, Aβ plaque deposition, tau tangle aggregation, and neurodegeneration.

METHODS

We recruited 470 older adults and analyzed plasma Aβ42/Aβ40, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) using the Simoa platform. Among them, 301, 195, and 70 underwent magnetic resonance imaging, Aβ and tau positron emission tomography imaging. The plasma Aβ42/Aβ40 and p-Tau181 thresholds were defined as ≤0.0609 and ≥2.418 based on the receiver operating characteristic curve analysis using the Youden index by comparing Aβ-PET negative cognitively unimpaired individuals and Aβ-PET positive cognitively impaired patients. To evaluate the feasibility of using plasma Aβ42/Aβ40 (A) and p-Tau181 (T) to detect AD and understand how astrocyte reactivity affects this process, we compared plasma GFAP, Aβ plaque, tau tangle, plasma NfL, hippocampal volume, and temporal-metaROI cortical thickness between different plasma A/T profiles and explored their relations with each other using general linear models, including age, sex, APOE-ε4, and diagnosis as covariates.

RESULTS

Plasma A+/T + individuals showed the highest levels of astrocyte reactivity, Aβ plaque, tau tangle, and axonal degeneration, and the lowest hippocampal volume and temporal-metaROI cortical thickness. Lower plasma Aβ42/Aβ40 and higher plasma p-Tau181 were independently and synergistically correlated with higher plasma GFAP and Aβ plaque. Elevated plasma p-Tau181 and GFAP concentrations were directly and interactively associated with more tau tangle formation. Regarding neurodegeneration, higher plasma p-Tau181 and GFAP concentrations strongly correlated with more axonal degeneration, as measured by plasma NfL, and lower plasma Aβ42/Aβ40 and higher plasma p-Tau181 were related to greater hippocampal atrophy. Higher plasma GFAP levels were associated with thinner cortical thickness and significantly interacted with lower plasma Aβ42/Aβ40 and higher plasma p-Tau181 in predicting more temporal-metaROI cortical thinning. Voxel-wise imaging analysis confirmed these findings.

DISCUSSION

This study provides a valuable reference for using plasma biomarkers to detect AD in the Chinese community population and offers novel insights into how astrocyte reactivity contributes to AD progression, highlighting the importance of targeting reactive astrogliosis to prevent AD.

Lessons learned from the failure of solanezumab as a prospective treatment strategy for Alzheimer's disease

INTRODUCTION

In the last decade, the efforts conducted for discovering Alzheimer's Disease (AD) treatments targeting the best-known pathogenic factors [amyloid-β (Aβ), tau protein, and neuroinflammation] were mostly unsuccessful. Given that a systemic failure of Aβ clearance was supposed to primarily contribute to AD development and progression, disease-modifying therapies with anti-Aβ monoclonal antibodies (e.g. solanezumab, bapineuzumab, gantenerumab, aducanumab, lecanemab and donanemab) are ongoing in randomized clinical trials (RCTs) with contrasting results.

AREAS COVERED

The present Drug Discovery Case History analyzes the failures of RCTs of solanezumab on AD. Furthermore, the authors review the pharmacokinetics, pharmacodynamics, and tolerability effect of solanezumab from preclinical studies with its analogous m266 in mice. Finally, they describe the RCTs with cognitive, cerebrospinal fluid and neuroimaging findings in mild-to-moderate AD (EXPEDITION studies) and in secondary prevention studies (A4 and DIAN-TU).

EXPERT OPINION

Solanezumab was one of the first anti-Aβ monoclonal antibodies to be tested in preclinical and clinical AD showing to reduce brain Aβ level by acting on soluble monomeric form of Aβ peptide without significant results on deposits. Unfortunately, this compound showed to accelerate cognitive decline in both asymptomatic and symptomatic trial participants, and this failure of solanezumab further questioned the Aβ cascade hypothesis of AD.

The clinical importance of suspected non-Alzheimer disease pathophysiology

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

The relation of a cerebrospinal fluid profile associated with Alzheimer's disease with cognitive function and neuropsychiatric symptoms in sporadic cerebral amyloid angiopathy

BACKGROUND

Patients with sporadic cerebral amyloid angiopathy (sCAA) frequently report cognitive or neuropsychiatric symptoms. The aim of this study is to investigate whether in patients with sCAA, cognitive impairment and neuropsychiatric symptoms are associated with a cerebrospinal fluid (CSF) biomarker profile associated with Alzheimer's disease (AD).

METHODS

In this cross-sectional study, we included participants with sCAA and dementia- and stroke-free, age- and sex-matched controls, who underwent a lumbar puncture, brain MRI, cognitive assessments, and self-administered and informant-based-questionnaires on neuropsychiatric symptoms. CSF phosphorylated tau, total tau and Aβ42 levels were used to divide sCAA patients in two groups: CAA with (CAA-AD+) or without a CSF biomarker profile associated with AD (CAA-AD-). Performance on global cognition, specific cognitive domains (episodic memory, working memory, processing speed, verbal fluency, visuoconstruction, and executive functioning), presence and severity of neuropsychiatric symptoms, were compared between groups.

RESULTS

sCAA-AD+ (n=31; mean age: 72 ± 6; 42%, 61% female) and sCAA-AD- (n=23; 70 ± 5; 42% female) participants did not differ with respect to global cognition or type of affected cognitive domain(s). The number or severity of neuropsychiatric symptoms also did not differ between sCAA-AD+ and sCAA-AD- participants. These results did not change after exclusion of patients without prior ICH.

CONCLUSIONS

In participants with sCAA, a CSF biomarker profile associated with AD does not impact global cognition or specific cognitive domains, or the presence of neuropsychiatric symptoms.

Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases

Cerebrospinal fluid (CSF) biomarkers reflect brain pathophysiology and are used extensively in translational research as well as in clinical practice for diagnosis of neurological diseases, e.g., Alzheimer's disease (AD). However, CSF biomarker concentrations may be influenced by non-disease related inter-individual variability. Here we use a data-driven approach to demonstrate the existence of inter-individual variability in mean standardized CSF protein levels. We show that these non-disease related differences cause many commonly reported CSF biomarkers to be highly correlated, thereby producing misleading results if not accounted for. To adjust for this inter-individual variability, we identified and evaluated high-performing reference proteins which improved the diagnostic accuracy of key CSF AD biomarkers. Our reference protein method attenuates the risk for false positive findings, and improves the sensitivity and specificity of CSF biomarkers, with broad implications for both research and clinical practice.

Impact of amyloid and tau positivity on longitudinal brain atrophy in cognitively normal individuals

BACKGROUND

Individuals on the preclinical Alzheimer's continuum, particularly those with both amyloid and tau positivity (A + T +), display a rapid cognitive decline and elevated disease progression risk. However, limited studies exist on brain atrophy trajectories within this continuum over extended periods.

METHODS

This study involved 367 ADNI participants grouped based on combinations of amyloid and tau statuses determined through cerebrospinal fluid tests. Using longitudinal MRI scans, brain atrophy was determined according to the whole brain, lateral ventricle, and hippocampal volumes and cortical thickness in AD-signature regions. Cognitive performance was evaluated with the Preclinical Alzheimer's Cognitive Composite (PACC). A generalized linear mixed-effects model was used to examine group × time interactions for these measures. In addition, progression risks to mild cognitive impairment (MCI) or dementia were compared among the groups using Cox proportional hazards models.

RESULTS

A total of 367 participants (48 A + T + , 86 A + T - , 63 A - T + , and 170 A - T - ; mean age 73.8 years, mean follow-up 5.1 years, and 47.4% men) were included. For the lateral ventricle and PACC score, the A + T - and A + T + groups demonstrated statistically significantly greater volume expansion and cognitive decline over time than the A - T - group (lateral ventricle: β = 0.757 cm3/year [95% confidence interval 0.463 to 1.050], P < .001 for A + T - , and β = 0.889 cm3/year [0.523 to 1.255], P < .001 for A + T + ; PACC: β =  - 0.19 /year [- 0.36 to - 0.02], P = .029 for A + T - , and β =  - 0.59 /year [- 0.80 to - 0.37], P < .001 for A + T +). Notably, the A + T + group exhibited additional brain atrophy including the whole brain (β =  - 2.782 cm3/year [- 4.060 to - 1.504], P < .001), hippocampus (β =  - 0.057 cm3/year [- 0.085 to - 0.029], P < .001), and AD-signature regions (β =  - 0.02 mm/year [- 0.03 to - 0.01], P < .001). Cox proportional hazards models suggested an increased risk of progressing to MCI or dementia in the A + T + group versus the A - T - group (adjusted hazard ratio = 3.35 [1.76 to 6.39]).

CONCLUSIONS

In cognitively normal individuals, A + T + compounds brain atrophy and cognitive deterioration, amplifying the likelihood of disease progression. Therapeutic interventions targeting A + T + individuals could be pivotal in curbing brain atrophy, cognitive decline, and disease progression.

Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets

BACKGROUND

While the amyloid/tau/neurodegeneration (ATN) framework has found wide application in Alzheimer's disease research, it is unclear if thresholds obtained using distinct thresholding methods are concordant within the same dataset and interchangeable across cohorts.

OBJECTIVES

To investigate the robustness of data-driven thresholding methods and ATN profiling across cohort datasets.

DESIGN AND SETTING

We evaluated the impact of thresholding methods on ATN profiles by applying five commonly-used methodologies across cohort datasets. We assessed the generalizability of disease patterns discovered within ATN profiles by clustering individuals from different cohorts who were assigned to the same ATN profile.

PARTICIPANTS AND MEASUREMENTS

Participants with available CSF amyloid-β 1-42, phosphorylated tau, and total tau measurements were included from eleven AD cohort studies.

RESULTS

We observed high variability among obtained ATN thresholds, both across methods and datasets that impacted the resulting profile assignments of participants significantly. Clustering participants from different cohorts within the same ATN category indicated that identified disease patterns were comparable across most cohorts and biases introduced through distinct thresholding and data representations remained insignificant in most ATN profiles.

CONLUSION

Thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling and affect its sensitivity and specificity. Thresholds are likely not directly interchangeable between independent cohorts. To apply the ATN framework as an actionable and robust profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and a validation of results is crucial.

Tau PET burden in Brodmann areas 35 and 36 is associated with individual differences in cognition in non-demented older adults

Introduction

The accumulation of neurofibrillary tau tangles, a neuropathological hallmark of Alzheimer's disease (AD), occurs in medial temporal lobe (MTL) regions early in the disease process, with some of the earliest deposits localized to subregions of the entorhinal cortex. Although functional specialization of entorhinal cortex subregions has been reported, few studies have considered functional associations with localized tau accumulation.

Methods

In this study, stepwise linear regressions were used to examine the contributions of regional tau burden in specific MTL subregions, as measured by 18F-MK6240 PET, to individual variability in cognition. Dependent measures of interest included the Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini Mental State Examination (MMSE), and composite scores of delayed episodic memory and language. Other model variables included age, sex, education, APOE4 status, and global amyloid burden, indexed by 11C-PiB.

Results

Tau burden in right Brodmann area 35 (BA35), left and right Brodmann area 36 (BA36), and age each uniquely contributed to the proportion of explained variance in CDR-SB scores, while right BA36 and age were also significant predictors of MMSE scores, and right BA36 was significantly associated with delayed episodic memory performance. Tau burden in both left and right BA36, along with education, uniquely contributed to the proportion of explained variance in language composite scores. Importantly, the addition of more inclusive ROIs, encompassing less granular segmentation of the entorhinal cortex, did not significantly contribute to explained variance in cognition across any of the models.

Discussion

These findings suggest that the ability to quantify tau burden in more refined MTL subregions may better account for individual differences in cognition, which may improve the identification of non-demented older adults who are on a trajectory of decline due to AD.

Profiling and predicting distinct tau progression patterns: An unsupervised data-driven approach to flortaucipir positron emission tomography

INTRODUCTION

How to detect patterns of greater tau burden and accumulation is still an open question.

METHODS

An unsupervised data-driven whole-brain pattern analysis of longitudinal tau positron emission tomography (PET) was used first to identify distinct tau accumulation profiles and then to build baseline models predictive of tau-accumulation type.

RESULTS

The data-driven analysis of longitudinal flortaucipir PET from studies done by the Alzheimer's Disease Neuroimaging Initiative, Avid Pharmaceuticals, and Harvard Aging Brain Study (N = 348 cognitively unimpaired, N = 188 mild cognitive impairment, N = 77 dementia), yielded three distinct flortaucipir-progression profiles: stable, moderate accumulator, and fast accumulator. Baseline flortaucipir levels, amyloid beta (Aβ) positivity, and clinical variables, identified moderate and fast accumulators with 81% and 95% positive predictive values, respectively. Screening for fast tau accumulation and Aβ positivity in early Alzheimer's disease, compared to Aβ positivity with variable tau progression profiles, required 46% to 77% lower sample size to achieve 80% power for 30% slowing of clinical decline.

DISCUSSION

Predicting tau progression with baseline imaging and clinical markers could allow screening of high-risk individuals most likely to benefit from a specific treatment regimen.

The Healthy Brain Initiative (HBI): A prospective cohort study protocol

BACKGROUND

The Health Brain Initiative (HBI), established by University of Miami's Comprehensive Center for Brain Health (CCBH), follows racially/ethnically diverse older adults without dementia living in South Florida. With dementia prevention and brain health promotion as an overarching goal, HBI will advance scientific knowledge by developing novel assessments and non-invasive biomarkers of Alzheimer's disease and related dementias (ADRD), examining additive effects of sociodemographic, lifestyle, neurological and biobehavioral measures, and employing innovative, methodologically advanced modeling methods to characterize ADRD risk and resilience factors and transition of brain aging.

METHODS

HBI is a longitudinal, observational cohort study that will follow 500 deeply-phenotyped participants annually to collect, analyze, and store clinical, cognitive, behavioral, functional, genetic, and neuroimaging data and biospecimens. Participants are ≥50 years old; have no, subjective, or mild cognitive impairment; have a study partner; and are eligible to undergo magnetic resonance imaging (MRI). Recruitment is community-based including advertisements, word-of-mouth, community events, and physician referrals. At baseline, following informed consent, participants complete detailed web-based surveys (e.g., demographics, health history, risk and resilience factors), followed by two half-day visits which include neurological exams, cognitive and functional assessments, an overnight sleep study, and biospecimen collection. Structural and functional MRI is completed by all participants and a subset also consent to amyloid PET imaging. Annual follow-up visits repeat the same data and biospecimen collection as baseline, except that MRIs are conducted every other year after baseline.

ETHICS AND EXPECTED IMPACT

HBI has been approved by the University of Miami Miller School of Medicine Institutional Review Board. Participants provide informed consent at baseline and are re-consented as needed with protocol changes. Data collected by HBI will lead to breakthroughs in developing new diagnostics and therapeutics, creating comprehensive diagnostic evaluations, and providing the evidence base for precision medicine approaches to dementia prevention with individualized treatment plans.

Operationalizing selection criteria for clinical trials in Alzheimer's disease: Biomarker and clinical considerations

Alzheimer's disease (AD) staging criteria lack standardized, empirical description. Well-defined AD staging criteria are an important consideration in protocol design, influencing a more standardized inclusion/exclusion criteria and defining what constitutes meaningful differentiation among the stages. However, many trials are being designed on the basis of biomarker features and the two need to be coordinated. The Alzheimer's Association Research Roundtable (AARR) Spring 2021 meeting discussed the implementation of preclinical AD staging criteria, and provided recommendations for how they may best be incorporated into clinical trials research. Discussion also included what currently available tools for global clinical trials may best define populations in preclinical AD trials, and if are we able to differentiate preclinical from clinical stages of the disease. Well-defined AD staging criteria are key to improving early detection, diagnostics, clinical trial enrollment, and identifying statistically significant clinical changes, and researchers discussed how emerging blood biomarkers may help with more efficient screening in preclinical stages.

The Healthy Brain Initiative (HBI): A prospective cohort study protocol

Background

The Health Brain Initiative (HBI), established by University of Miami's Comprehensive Center for Brain Health (CCBH), follows racially/ethnically diverse older adults without dementia living in South Florida. With dementia prevention and brain health promotion as an overarching goal, HBI will advance scientific knowledge by developing novel assessments and non-invasive biomarkers of Alzheimer's disease and related dementias (ADRD), examining additive effects of sociodemographic, lifestyle, neurological and biobehavioral measures, and employing innovative, methodologically advanced modeling methods to characterize ADRD risk and resilience factors and transition of brain aging.

Methods

HBI is a longitudinal, observational cohort study that will follow 500 deeply-phenotyped participants annually to collect, analyze, and store clinical, cognitive, behavioral, functional, genetic, and neuroimaging data and biospecimens. Participants are ≥50 years old; have no, subjective, or mild cognitive impairment; have a study partner; and are eligible to undergo magnetic resonance imaging (MRI). Recruitment is community-based including advertisements, word-of-mouth, community events, and physician referrals. At baseline, following informed consent, participants complete detailed web-based surveys (e.g., demographics, health history, risk and resilience factors), followed by two half-day visits which include neurological exams, cognitive and functional assessments, an overnight sleep study, and biospecimen collection. Structural and functional MRI is completed by all participants and a subset also consent to amyloid PET imaging. Annual follow-up visits repeat the same data and biospecimen collection as baseline, except that MRIs are conducted every other year after baseline.

Ethics and expected impact

HBI has been approved by the University of Miami Miller School of Medicine Institutional Review Board. Participants provide informed consent at baseline and are re-consented as needed with protocol changes. Data collected by HBI will lead to breakthroughs in developing new diagnostics and therapeutics, create comprehensive diagnostic evaluations, and provide the evidence base for precision medicine approaches to dementia prevention with individualized treatment plans.

Prevalence and Clinical Implications of a β-Amyloid-Negative, Tau-Positive Cerebrospinal Fluid Biomarker Profile in Alzheimer Disease

Importance

Knowledge is lacking on the prevalence and prognosis of individuals with a β-amyloid-negative, tau-positive (A-T+) cerebrospinal fluid (CSF) biomarker profile.

Objective

To estimate the prevalence of a CSF A-T+ biomarker profile and investigate its clinical implications.

Design, Setting, and Participants

This was a retrospective cohort study of the cross-sectional multicenter University of Gothenburg (UGOT) cohort (November 2019-January 2021), the longitudinal multicenter Alzheimer Disease Neuroimaging Initiative (ADNI) cohort (individuals with mild cognitive impairment [MCI] and no cognitive impairment; September 2005-May 2022), and 2 Wisconsin cohorts, Wisconsin Alzheimer Disease Research Center and Wisconsin Registry for Alzheimer Prevention (WISC; individuals without cognitive impairment; February 2007-November 2020). This was a multicenter study, with data collected from referral centers in clinical routine (UGOT) and research settings (ADNI and WISC). Eligible individuals had 1 lumbar puncture (all cohorts), 2 or more cognitive assessments (ADNI and WISC), and imaging (ADNI only) performed on 2 separate occasions. Data were analyzed on August 2022 to April 2023.

Exposures

Baseline CSF Aβ42/40 and phosphorylated tau (p-tau)181; cognitive tests (ADNI: modified preclinical Alzheimer cognitive composite [mPACC]; WISC: modified 3-test PACC [PACC-3]). Exposures in the ADNI cohort included [18F]-florbetapir amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose PET (FDG-PET), and cross-sectional tau-PET (ADNI: [18F]-flortaucipir, WISC: [18F]-MK6240).

Main Outcomes and Measures

Primary outcomes were the prevalence of CSF AT biomarker profiles and continuous longitudinal global cognitive outcome and imaging biomarker trajectories in A-T+ vs A-T- groups. Secondary outcomes included cross-sectional tau-PET.

Results

A total of 7679 individuals (mean [SD] age, 71.0 [8.4] years; 4101 male [53%]) were included in the UGOT cohort, 970 individuals (mean [SD] age, 73 [7.0] years; 526 male [54%]) were included in the ADNI cohort, and 519 individuals (mean [SD] age, 60 [7.3] years; 346 female [67%]) were included in the WISC cohort. The prevalence of an A-T+ profile in the UGOT cohort was 4.1% (95% CI, 3.7%-4.6%), being less common than the other patterns. Longitudinally, no significant differences in rates of worsening were observed between A-T+ and A-T- profiles for cognition or imaging biomarkers. Cross-sectionally, A-T+ had similar tau-PET uptake to individuals with an A-T- biomarker profile.

Conclusion and Relevance

Results suggest that the CSF A-T+ biomarker profile was found in approximately 5% of lumbar punctures and was not associated with a higher rate of cognitive decline or biomarker signs of disease progression compared with biomarker-negative individuals.

Anti-Amyloid Immunotherapies for Alzheimer's Disease: A 2023 Clinical Update

The amyloid cascade hypothesis is a useful framework for therapeutic development in Alzheimer's disease (AD). Amyloid b1-42 (Aβ) has been the main target of experimental therapies, based on evidence of the neurotoxic effects of Aβ, and of the potential adverse effects of brain Aβ burden detected in humans in vivo by positron emission tomography (PET). Progress on passive anti-amyloid immunotherapy research includes identification of antibodies that facilitate microglial activation, catalytical disaggregation, and increased flow of Aβ from cerebrospinal fluid (CSF) to plasma, thus decreasing the neurotoxic effects of Aβ. Recently completed phase 2 and 3 trials of 3rd generation anti-amyloid immunotherapies are supportive of their clinical efficacy in reducing brain Aβ burden and preventing cognitive decline. Data from recent trials implicate these agents as the first effective disease-modifying therapies against AD and has led to the US Food and Drug Administration (FDA) recent approval of aducanumab and lecanemab, under an accelerated approval pathway. The clinical effects of these agents are modest, however, and associated with amyloid-related imaging abnormalities (ARIA). Testing the effects of anti-Aβ immunotherapies in pre-symptomatic populations and identification of more potent and safer agents is the scope of ongoing and future research. Innovations in clinical trial design will be the key for the efficient and equitable development of novel anti-Aβ immunotherapies. The progress in the field of AD therapeutics will bring new clinical, logistical, and ethical challenges, which pose to revolutionize the practice of neurology, dementia care, and preventive cognitive healthcare.

Detection and treatment of Alzheimer's disease in its preclinical stage

Longitudinal multimodal biomarker studies reveal that the continuum of Alzheimer's disease (AD) includes a long latent phase, referred to as preclinical AD, which precedes the onset of symptoms by decades. Treatment during the preclinical AD phase offers an optimal opportunity for slowing the progression of disease. However, trial design in this population is complex. In this Review, we discuss the recent advances in accurate plasma measurements, new recruitment approaches, sensitive cognitive instruments and self-reported outcomes that have facilitated the successful launch of multiple phase 3 trials for preclinical AD. The recent success of anti-amyloid immunotherapy trials in symptomatic AD has increased the enthusiasm for testing this strategy at the earliest feasible stage. We provide an outlook for standard screening of amyloid accumulation at the preclinical stage in clinically normal individuals, during which effective therapy to delay or prevent cognitive decline can be initiated.

Exploring the ATN classification system using brain morphology

BACKGROUND

The NIA-AA proposed amyloid-tau-neurodegeneration (ATN) as a classification system for AD biomarkers. The amyloid cascade hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (amyloid-conversion first, tau-conversion second, N-conversion last) and alternative progressions using voxel-based morphometry (VBM) in a large cross-sectional MRI cohort.

METHODS

We used baseline data of the DELCODE cohort of 437 subjects (127 controls, 168 SCD, 87 MCI, 55 AD patients) which underwent lumbar puncture, MRI scanning, and neuropsychological assessment. ATN classification was performed using CSF-Aβ42/Aβ40 (A+/-), CSF phospho-tau (T+/-), and adjusted hippocampal volume or CSF total-tau (N+/-). We compared voxel-wise model evidence for monotonic decline of gray matter volume across various sequences over ATN groups using the Bayesian Information Criterion (including also ROIs of Braak stages). First, face validity of the ACH transition sequence A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was compared against biologically less plausible (permuted) sequences among AD continuum ATN groups. Second, we evaluated evidence for 6 monotonic brain volume progressions from A-T-N- towards A+T+N+ including also non-AD continuum ATN groups.

RESULTS

The ACH-based progression A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was consistent with cognitive decline and clinical diagnosis. Using hippocampal volume for operationalization of neurodegeneration (N), ACH was most evident in 9% of gray matter predominantly in the medial temporal lobe. Many cortical regions suggested alternative non-monotonic volume progressions over ACH progression groups, which is compatible with an early amyloid-related tissue expansion or sampling effects, e.g., due to brain reserve. Volume decline in 65% of gray matter was consistent with a progression where A status converts before T or N status (i.e., ACH/ANT) when compared to alternative sequences (TAN/TNA/NAT/NTA). Brain regions earlier affected by tau tangle deposition (Braak stage I-IV, MTL, limbic system) present stronger evidence for volume decline than late Braak stage ROIs (V/VI, cortical regions). Similar findings were observed when using CSF total-tau for N instead.

CONCLUSION

Using the ATN classification system, early amyloid status conversion (before tau and neurodegeneration) is associated with brain volume loss observed during AD progression. The ATN system and the ACH are compatible with monotonic progression of MTL atrophy.

TRIAL REGISTRATION

DRKS00007966, 04/05/2015, retrospectively registered.

The Clinical Application of Optimized AT(N) Classification in Alzheimer’s Clinical Syndrome (ACS) and non-ACS Conditions

We aimed to assess the utility of AT(N) classification in clinical practice. We measured the cerebrospinal fluid levels of amyloid-β (Aβ) 42, Aβ40, phosphorylated tau, total tau, and neurofilament light chain (NfL) in samples from 230 patients with Alzheimer's clinical syndrome (ACS) and 328 patients with non-ACS. The concordance of two A-markers (i.e., Aβ42 alone and the Aβ42/Aβ40 ratio) was not significantly different between the ACS (87.4%) and non-ACS (74.1%) groups. However, the frequency of discordant cases with A_Aβ42-alone+/A_Aβ-ratio- was significantly higher in the non-ACS (23.8%) than in the ACS group (7.4%). The concordance of two N-markers (i.e., total tau and NfL) was 40.4% in the ACS group and 24.4% in the non-ACS group. In the ACS samples, the frequency of biological Alzheimer's disease (i.e., A+T+) in N_tau+ cases was 95% while that in N_NfL+ cases was 65%. Reflecting Aβ deposition and neurodegeneration more accurately, we recommend the use of AT(N) classification defined by cerebrospinal fluid A_Aβ-ratioTN_NfL in clinical practice.

Initial levels of β-amyloid and tau deposition have distinct effects on longitudinal tau accumulation in Alzheimer's disease

BACKGROUND

To better assist with the design of future clinical trials for Alzheimer's disease (AD) and aid in our understanding of the disease's symptomatology, it is essential to clarify what roles β-amyloid (Aβ) plaques and tau tangles play in longitudinal tau accumulation inside and outside the medial temporal lobe (MTL) as well as how age, sex, apolipoprotein E (APOE) ε4 (APOE-ε4), and Klotho-VS heterozygosity (KL-VShet) modulate these relationships.

METHODS

We divided the 325 Aβ PET-positive (A+) participants into two groups, A+/T- (N = 143) and A+/T+ (N = 182), based on the threshold (1.25) of the temporal meta-ROI 18F-flortaucipir (FTP) standardized uptake value ratio (SUVR). We then compared the baseline and slopes of A+/T- and A+/T+ individuals' Aβ plaques and temporal meta-ROI tau tangles with those of A-/T- cognitively unimpaired individuals (N = 162) without neurodegeneration. In addition, we looked into how baseline Aβ and tau may predict longitudinal tau increases and how age, sex, APOE-ε4, and KL-VShet affect these associations.

RESULTS

In entorhinal, amygdala, and parahippocampal (early tau-deposited regions of temporal meta-ROI), we found that baseline Aβ and tau deposition were positively linked to more rapid tau increases in A+/T- participants. However, in A+/T+ individuals, the longitudinal tau accumulation in fusiform, inferior temporal, and middle temporal cortices (late tau-deposited regions of temporal meta-ROI) was primarily predicted by the level of tau tangles. Furthermore, compared to older participants (age ≥ 65), younger individuals (age < 65) exhibited faster Aβ-dependent but slower tau-related tau accumulations. Additionally, compared to the KL-VShet- group, KL-VShet+ individuals showed a significantly lower rate of tau accumulation associated with baseline entorhinal tau in fusiform and inferior temporal regions.

CONCLUSION

These findings offer novel perspectives to the design of AD clinical trials and aid in understanding the tau accumulation inside and outside MTL in AD. In particular, decreasing Aβ plaques might be adequate for A+/T- persons but may not be sufficient for A+/T+ individuals in preventing tau propagation and subsequent downstream pathological changes associated with tau.

Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum

BACKGROUND

The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear.

OBJECTIVE

To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points.

METHODS

We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up.

RESULTS

In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12.

CONCLUSION

These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.

Cerebrospinal Fluid Alzheimer's Disease Biomarker Patterns of Change Prior to the Onset of Mild Cognitive Impairment

BACKGROUND

Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are altered many years before the onset of clinical symptoms of mild cognitive impairment (MCI). Incorporating clinical symptom onset time into biomarker modeling may enhance our understanding of changes preceding MCI.

OBJECTIVE

Using a new analytical approach, we examined patterns of biomarker change prior to MCI symptom onset among individuals who progressed from normal cognition to MCI, stratified based on the age of symptom onset. We also analyzed biomarker patterns of change among participants who remained cognitively normal, and examined potential modifiers of biomarker trajectories, including demographics and apolipoprotein E (APOE) status.

METHODS

Analyses included 93 participants who progressed from normal cognition to MCI and 186 participants who remained cognitively normal, over an average follow-up period of 16.2 years. CSF biomarkers, including Aβ42, Aβ40, total tau (t-tau), and phosphorylated tau181 (p-tau181), were measured using the fully automated Lumipulse assays.

RESULTS

Among participants who progressed to MCI, Aβ42/Aβ40 decreased, and t-tau and p-tau181 increased. For participants who did not progress to MCI, CSF biomarkers showed relatively stable patterns. In both progressors and non-progressors, APOE4 carriers showed lower Aβ 42/Aβ40 levels (compared to non-carriers) at each point of the mean curves. Among non-progressors, APOE4 carriers had higher levels of p-tau181, p-tau181/(Aβ 42/Aβ40), and t-tau/(Aβ 42/Aβ 40). Additionally, among those who did not progress, female sex was associated with higher levels of t-tau, p-tau181, t-tau/(Aβ 42/Aβ 40), and p-tau181/(Aβ 42/Aβ 40).

CONCLUSIONS

These findings suggest that this analytic approach may provide additional insights into biomarker changes during early phases of AD.

Reconceptualization of the Erlangen Score for the Assessment of Dementia Risk: The ERlangen Score

BACKGROUND

The established Erlangen Score (ES) for the interpretation of cerebrospinal fluid (CSF) biomarkers in the diagnostics of Alzheimer's disease (AD) uses markers of amyloidopathy and tauopathy, equally weighted to form an easy-interpretable ordinal scale. However, these biomarkers are not equally predictive for AD.

OBJECTIVE

The higher weighting of the Aβ42/Aβ40 ratio, as a reconceptualized ERlangen Score (ERS), was tested for advantages in diagnostic performance.

METHODS

Non-demented subjects (N = 154) with a mean follow up of 5 years were assigned to a group ranging from 0 to 4 in ES or ERS. Psychometric trajectories and dementia risk were assessed.

RESULTS

The distribution of subjects between ES and ERS among the groups differed considerably, as grouping allocated 32 subjects to ES group 2, but only 2 to ERS group 2. The discriminative accuracy between the ES (AUC 73.2%, 95% CI [64.2, 82.2]) and ERS (AUC 72.0%, 95% CI [63.1, 81.0]) for dementia risk showed no significant difference. Without consideration of the Aβ42/Aβ40 ratio in ES grouping, the optimal cut-off of the ES shifted to ≥2.

CONCLUSIONS

The ERS showed advantages over the ES in test interpretation with comparable overall test performance, as fewer cases were allocated to the intermediate risk group. The established cut-off of ≥2 can be maintained for the ERS, whereas it must be adjusted for the ES when determining the Aβ42/Aβ40 ratio.

Design, synthesis, and preliminary evaluation of [18F]-aryl flurosulfates PET radiotracers via SuFEx methods for β-amyloid plaques in Alzheimer's disease

[18F]BAY-94-9172, [18F]AV-45, and [18F]GE-067 were FDA approved positron emission tomography (PET) imaging radiotracer of β-amyloid plaques (Aβ) in Alzheimer's disease (AD). However, the radiochemical synthesis requires multi-step reactions and complex procedure. Recently, a protocol for radiochemical synthesis of sulfur fluoride exchange (SuFEx) using ultrafast 19F/18F isotopic exchange had been reported. We developed three pairs of novel 18F-labeled radiotracers by the "SuFEx" method for PET imaging Aβ plaques. The 18F labeling reaction can be completed quickly (30 s) at room temperature and purified using solid-phase extraction (SPE). The radiochemical purity (RCP) of the products was all greater than 95 %. In vitro fluorescent staining using Aβ-transgenesis mice section preliminary verified the affinity of tracers with Aβ. Competitive binding assay displayed high affinity of tracers for towards artificial Aβ1-42 aggregates (Ki values ranging from 3.53 ± 0.39 to 42.0 ± 4.24 nM). In vivo biodistribution and Micro-PET imaging showed that [18F]-Sulfur Fluoride β-Amyloid ([18F]SFA 1-6) could penetration the blood-brain barrier (BBB) in wild-type mice, and [18F]SFA 5-6 had a high initial brain uptake value (3.65 ± 0.9 % and 5.07 ± 0.1 % ID/g, respectively) and a fast washout (Brain uptake2 min/60 min = 4.15 and 4.61, respectively) from the brain. In vitro autoradiography demonstrated the affinity of the [18F]SFA 5-6 to Aβ plaques in AD human brain tissues. Our results suggested that [18F]SFA maybe a potential PET radiotracers for detecting Aβ in Alzheimer's disease.

CSF Alzheimer Disease Biomarkers: Time-Varying Relationships With MCI Symptom Onset and Associations With Age, Sex, and ApoE4

BACKGROUND AND OBJECTIVES

This study aimed to examine whether baseline CSF measures of Alzheimer disease (AD)-related pathology are associated with the time to onset of mild cognitive impairment (MCI) and whether these associations differ by age, sex, Apolipoprotein E (ApoE4) status, and proximal (≤7 years) vs distal (>7 years) time to symptom onset.

METHODS

Measures of amyloid (Aβ1-42 and Aβ1-40), phospho-tau (ptau181), and total tau (t-tau) were determined from CSF samples obtained at baseline from participants in an ongoing longitudinal project, known as the Biomarkers for Older Controls at Risk for Alzheimer Disease study (BIOCARD) study. The fully automated, Lumipulse G immunoassay was used to analyze the specimens. Cox regression models were used to examine the relationship of baseline biomarker levels with time to symptom onset of MCI and interactions with age, sex, and ApoE allelic status in subjects who progressed from normal cognition to MCI.

RESULTS

Analyses included 273 participants from the BIOCARD cohort, who were cognitively normal and predominantly middle-aged at baseline, and have been followed for an average of 16 years (max = 23.6). During follow-up, 94 progressed to MCI (median time to symptom onset = 6.9 years). In Cox regression models, elevated ptau181 and t-tau levels were associated with time to MCI symptom onset if it occurred within 7 years of baseline (HR 1.386 and 1.329; p = 0.009 and 0.017, respectively), while a lower Aβ42/Aβ40 ratio was associated with symptom onset if it occurred >7 years from baseline (HR 0.596, p = 0.003). There were also significant 3-way CSF × age × sex interactions for ptau181 and Aβ42/Aβ40, with follow-up analyses indicating that associations between these biomarkers and progression to MCI were stronger among men than among women, but this difference between sexes diminished with increasing age.

DISCUSSION

The lengthy follow-up of BIOCARD participants permitted an examination of time-varying associations between CSF AD biomarkers with MCI symptom onset and the influence of sex, baseline age, and ApoE4 genotype on these associations. These factors may inform clinical trial enrollment strategies, or trial duration and outcomes, which may use these measures as surrogate markers of treatment response.

Alzheimer’s Disease Diagnosis Based on the Amyloid, Tau, and Neurodegeneration Scheme (ATN) in a Real-Life Multicenter Cohort of General Neurological Centers

Background: The ATN scheme was proposed as an unbiased biological characterization of the Alzheimer’s disease (AD) spectrum, grouping biomarkers into three categories: brain Amyloidosis-A, Tauopathy-T, Neurodegeneration-N. Although this scheme was mainly recommended for research, it is relevant for diagnosis. Objective: To evaluate the ATN scheme performance in real-life cohorts reflecting the inflow of patients with cognitive complaints and different underlying disorders in general neurological centers. Methods: We included patients (n = 1,128) from six centers with their core cerebrospinal fluid-AD biomarkers analyzed centrally. A was assessed through Aβ 42/Aβ 40, T through pTau-181, and N through tTau. Association between demographic features, clinical diagnosis at baseline/follow-up and ATN profiles was assessed. Results: The prevalence of ATN categories was: A-T-N-: 28.3% ; AD continuum (A + T-/+N-/+): 47.8% ; non-AD (A- plus T or/and N+): 23.9% . ATN profiles prevalence was strongly influenced by age, showing differences according to gender, APOE genotype, and cognitive status. At baseline, 74.6% of patients classified as AD fell in the AD continuum, decreasing to 47.4% in mild cognitive impairment and 42.3% in other neurodegenerative conditions. At follow-up, 41% of patients changed diagnosis, and 92% of patients that changed to AD were classified within the AD continuum. A + was the best individual marker for predicting a final AD diagnosis, and the combinations A + T+(irrespective of N) and A + T+N+had the highest overall accuracy (83%). Conclusion: The ATN scheme is useful to guide AD diagnosis real-life neurological centers settings. However, it shows a lack of accuracy for patients with other types of dementia. In such cases, the inclusion of other markers specific for non-AD proteinopathies could be an important aid to the differential diagnosis.

Different AT(N) profiles and clinical progression classified by two different N markers using total tau and neurofilament light chain in cerebrospinal fluid

Background

The AT(N) classification was proposed for categorising individuals according to biomarkers. However, AT(N) profiles may vary depending on the markers chosen and the target population.

Methods

We stratified 177 individuals who participated in the Japanese Alzheimer's Disease Neuroimaging Initiative by AT(N) classification according to cerebrospinal fluid (CSF) biomarkers. We compared the frequency of AT(N) profiles between the classification using total tau and neurofilament light chain (NfL) as N markers (AT(N)_tau and AT(N)_NfL). Baseline characteristics, and longitudinal biological and clinical changes were examined between AT(N) profiles.

Results

We found that 9% of cognitively unimpaired subjects, 49% of subjects with mild cognitive impairment, and 61% of patients with Alzheimer's disease (AD) dementia had the biological AD profile (ie, A+T+) in the cohort. The frequency of AT(N) profiles substantially differed between the AT(N)_tau and AT(N)_NfL classifications. When we used t-tau as the N marker (AT(N)_tau), those who had T- were more frequently assigned to (N)-, whereas those who had T+were more frequently assigned to (N)+ than when we used NfL as the N marker (AT(N)_NfL). During a follow-up, the AD continuum group progressed clinically and biologically compared with the normal biomarker group in both the AT(N)_tau and AT(N)_NfL classifications. More frequent conversion to dementia was observed in the non-AD pathological change group in the AT(N)_tau classification, but not in the AT(N)_NfL classification.

Conclusions

AT(N)_tau and AT(N)_NfL in CSF may capture different aspects of neurodegeneration and provide a different prognostic value. The AT(N) classification aids in understanding the AD continuum biology in various populations.

Amyloid-β levels and cognitive trajectories in non-demented pTau181-positive subjects without amyloidopathy

Phosphorylated Tau181 (pTau181) in cerebrospinal fluid (CSF) and recently in plasma has been associated with Alzheimer's disease. In the absence of amyloidopathy, individuals with increased total Tau levels and/or temporal lobe atrophy experience no or only mild cognitive decline compared with biomarker-negative controls, leading to the proposal to categorize this constellation as Suspected non-Alzheimer disease pathophysiology (SNAP). We investigated whether the characteristics of SNAP also applied to individuals with increased CSF-pTau181 without amyloidopathy. In this long-term observational study, 285 non-demented individuals, including 76 individuals with subjective cognitive impairment and 209 individuals with mild cognitive impairment, were classified based on their CSF-levels of pTau181 (T), total Tau (N), Amyloid-beta-(Aβ)-42 and Aβ42/Aβ40 ratio (A) into A + T+N±, A + T-N±, A-T + N±, and A-T-N-. The longitudinal analysis included 154 subjects with a follow-up of more than 12 months who were followed to a median of 4.6 years (interquartile range = 4.3 years). We employed linear mixed models on psychometric tests and region of interest analysis of structural MRI data. Cognitive decline and hippocampal atrophy rate were significantly higher in A + T+N ± compared to A-T + N±, whereas there was no difference between A-T + N ± and A-T-N-. Furthermore, there was no significant difference between A-T + N ± and controls in dementia risk (Hazard ratio 0.3, 95% confidence interval [0.1, 1.9]). However, A-T + N ± and A-T-N- could be distinguished based on their Aβ42 and Aβ40 levels. Both Aβ40 and Aβ42 levels were significantly increased in A-T + N ± compared to controls. Long term follow-up of A-T + N ± individuals revealed no evidence that this biomarker constellation was associated with dementia or more severe hippocampal atrophy rates compared to controls. However, because of the positive association of pTau181 with Aβ in the A-T + N ± group, a link to the pathophysiology of Alzheimer´s disease cannot be excluded in this case. We propose to refer to these individuals in the SNAP group as "pTau and Aβ surge with subtle deterioration" (PASSED). The investigation of the circumstances of simultaneous elevation of pTau and Aβ might provide a deeper insight into the process under which Aβ becomes pathological.

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets

Pooling multiple neuroimaging datasets across institutions often enables improvements in statistical power when evaluating associations (e.g., between risk factors and disease outcomes) that may otherwise be too weak to detect. When there is only a single source of variability (e.g., different scanners), domain adaptation and matching the distributions of representations may suffice in many scenarios. But in the presence of more than one nuisance variable which concurrently influence the measurements, pooling datasets poses unique challenges, e.g., variations in the data can come from both the acquisition method as well as the demographics of participants (gender, age). Invariant representation learning, by itself, is ill-suited to fully model the data generation process. In this paper, we show how bringing recent results on equivariant representation learning (for studying symmetries in neural networks) instantiated on structured spaces together with simple use of classical results on causal inference provides an effective practical solution. In particular, we demonstrate how our model allows dealing with more than one nuisance variable under some assumptions and can enable analysis of pooled scientific datasets in scenarios that would otherwise entail removing a large portion of the samples. Our code is available on https://github.com/vsingh-group/DatasetPooling.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1-42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.

Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline

BACKGROUND AND OBJECTIVES

Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD).

METHODS

We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker.

RESULT

We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%-19%). N biomarkers were modestly to moderately correlated (range r -0.28 - 0.58). Serum NfL and GFAP correlated most strongly (r 0.58, p < 0.01). T-tau was strongly correlated with p-tau (r 0.89, p < 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11-2.09]; 1.51 [1.05-2.17]; 1.50 [1.04-2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β -0.17 to -0.11, p < 0.05), but only HV remained associated beyond Aβ and p-tau (β -0.13 [SE 0.04]; p < 0.05).

DISCUSSION

In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.

A Multi-Dimensional Comparison of Alzheimer's Disease Neurodegenerative Biomarkers

BACKGROUND

In the 2018 AT(N) framework, neurodegenerative (N) biomarkers plays an essential role in the research and staging of Alzheimer's disease (AD); however, the different choice of N may result in discordances.

OBJECTIVE

We aimed to compare different potential N biomarkers.

METHODS

We examined these N biomarkers among 1,238 participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) in their 1) diagnostic utility, 2) cross-sectional and longitudinal correlations between different N biomarkers and clinical variables, and 3) the conversion risk of different N profiles.

RESULTS

Six neurodegenerative biomarkers changed significantly from preclinical AD, through prodromal AD to AD dementia stage, thus they were chosen as the candidate N biomarkers: hippocampal volume (HV), 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET), cerebrospinal fluid (CSF), total tau (T-tau), plasma neurofilament light chain (NFL), CSF NFL, and CSF neurogranin (Ng). Results indicated that FDG-PET not only had the greatest diagnostic utility in differentiating AD from controls (area under the curve: FDG-PET, 0.922), but also had the strongest association with cognitive scores. Furthermore, FDG-PET positive group showed the fastest memory decline (hazard ratio: FDG-PET, 3.45), which was also true even in the presence of amyloid-β pathology. Moreover, we observed great discordances between three valuable N biomarkers (FDG-PET, HV, and T-tau).

CONCLUSION

These results underline the importance of using FDG-PET as N in terms of cognitive decline and AD conversion, followed by HV, and could be a great complement to the AT(N) framework.

Plasma p-tau231, p-tau181, PET biomarkers and cognitive change in older adults

OBJECTIVE

To evaluate novel plasma p-tau231, p-tau181 as well as Aβ₄₀ and Aβ₄₂ assays as indicators of tau and Aβ pathologies measured with positron emission tomography (PET), and their association with cognitive change, in cognitively unimpaired older adults.

METHODS

In a cohort of 244 older adults at risk of AD owing to a family history of AD dementia, we measured single molecule array (Simoa)-based plasma tau biomarkers (p-tau231, p-tau181), Aβ₄₀ and Aβ₄₂ with immunoprecipitation mass spectrometry, and Simoa NfL. A subset of 129 participants underwent amyloid-β (¹⁸ F-NAV4694) and tau (¹⁸ F-flortaucipir) PET assessments. We investigated plasma biomarker associations with Aβ and tau PET at the global and voxel level and tested plasma biomarker combinations for improved detection of Aβ-PET positivity. We also investigated associations with 8-year cognitive change.

RESULTS

Plasma p-tau biomarkers correlated with flortaucipir binding in medial temporal, parietal and inferior temporal regions. P-tau231 showed further associations in lateral parietal and occipital cortices. Plasma Aβ_42/40 explained more variance in global Aβ-PET binding than Aβ₄₂ alone. P-tau231 also showed strong and widespread associations with cortical Aβ-PET binding. Combining Aβ_42/40 with p-tau231 or p-tau181 allowed for good distinction between Aβ-negative and -positive participants (AUC range 0.81-0.86). Individuals with low plasma Aβ_42/40 and high p-tau experienced faster cognitive decline.

INTERPRETATION

Plasma p-tau231 showed more robust associations with PET biomarkers than p-tau181 in pre-symptomatic individuals. The combination of p-tau and Aβ_42/40 biomarkers detected early AD pathology and cognitive decline. Such markers could be used as pre-screening tools to reduce the cost of prevention trials. This article is protected by copyright. All rights reserved.

Association of the ATN Research Framework With Clinical Profile, Ccognitive Decline, and Mortality in Patients With Dementia With Lewy Bodies

BACKGROUND AND OBJECTIVES

The ATN framework has been developed to categorize biological processes within the Alzheimer's disease (AD) continuum. Since AD pathology often coincides with dementia with Lewy Bodies (DLB), we aimed to investigate the distribution of ATN profiles in DLB and associate ATN-profiles in DLB to prognosis.

METHODS

We included 202 DLB patients from the Amsterdam Dementia Cohort (68±7yrs, 19%F, MMSE: 24±3, DAT-SPECT abnormal: 105/119). Patients were classified into eight profiles according to the ATN framework, using CSF Aβ₄₂ (A), CSF p-tau (T) and medial temporal atrophy scores (N). We compared presence of clinical symptoms in ATN profiles and used linear mixed models to analyze decline on cognitive tests (follow-up 3±2yrs for n=139). Mortality risk was assessed using Cox proportional hazards analysis. Analyses were performed on both the eight profiles, as well as three clustered categories (normal AD biomarkers, non-AD pathologic change, AD continuum).

RESULTS

Fifty (25%) DLB patients had normal AD biomarkers (A-T-N-), 37 (18%) had non-AD pathologic change (A-T+N-: 10%/A-T-N+: 6%/A-T+N+: 3%) and 115 (57%) were classified within the AD continuum (A+T-N-: 20%/A+T+N-: 16%/A+T-N+: 10%/A+T+N+: 9%). A+T+N+ patients were older and least often had RBD symptoms. Parkinsonism was more often present in A+T-, compared to A-T+ (independent of N). Compared to patients with normal AD biomarkers, patients in A+ categories showed steeper decline on memory tests and higher mortality risk. Cognitive decline and mortality did not differ between non-AD pathologic change and normal AD biomarkers.

DISCUSSION

In our DLB cohort, we found clinically relevant associations between ATN categories and disease manifestation. Patients within the AD continuum had steeper cognitive decline and shorter survival. Implementing the ATN framework within DLB patients aids in subtyping patients based on underlying biological processes and could provide targets for future treatment strategies, e.g. AD modifying treatment. Expanding the framework by incorporating markers for alpha-synucleinopathy would improve the use of the framework to characterize dementia patients with mixed pathology, which could enhance proper stratification of patients for therapeutic trials.

Association Between Late-Life Neuropsychiatric Symptoms and Cognitive Decline in Relation to White Matter Hyperintensities and Amyloid Burden

BACKGROUND

Neuropsychiatric symptoms (NPS) among cognitively normal older adults are increasingly recognized as risk factors for cognitive decline and impairment. However, the underlying mechanisms remain unclear.

OBJECTIVE

To examine whether biomarkers of Alzheimer's disease (amyloid burden) and cerebrovascular disease (white matter hyperintensity (WMH) volume) modify the association between NPS and cognitive decline among cognitively unimpaired older adults.

METHODS

Analyses included 193 cognitively unimpaired participants (M age = 70 years) from the BIOCARD study, including 148 with PET amyloid and WMH biomarker data. NPS were measured with Neuropsychiatric Inventory and Geriatric Depression Scale scores. Linear mixed effects models were used to examine the association between baseline NPS and longitudinal cognitive trajectories (M follow-up = 3.05 years), using separate models for global, episodic memory, and executive function cognitive composite scores. In a subset of individuals with biomarker data, we evaluated whether WMH or cortical amyloid burden modified the relationship between NPS and cognitive change (as indicated by the NPS×biomarker×time interactions).

RESULTS

Higher baseline NPS were associated with lower executive function scores, but not a faster rate of decline in executive function. NPS symptoms were unrelated to the global or episodic memory composite scores, and there was little evidence of a relationship between NPS symptoms and cognitive change over time. The associations between NPS and cognitive decline did not differ by amyloid or WMH burden, and NPS were unrelated to amyloid and WMH burden.

CONCLUSION

These results suggest that the effect of neuropsychiatric symptoms on executive dysfunction may occur through mechanisms outside of amyloid and cerebrovascular disease.

The probabilistic model of Alzheimer disease: the amyloid hypothesis revised

The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.

Age, vascular disease, and Alzheimer's disease pathologies in amyloid negative elderly adults

Background

We recently reported that CSF phosphorylated tau (p-Tau₁₈₁) relative to Aβ₄₀ (CSF p-Tau/Aβ₄₀ ratio) was less noisy and increased associations with Alzheimer’s disease (AD) biomarkers compared to CSF p-Tau₁₈₁ alone. While elevations of CSF p-Tau/Aβ₄₀ can occur in amyloid-β (Aβ) negative (Aβ-) individuals, the factors associated with these elevations and their role in neurodegeneration and cognitive decline are unknown. We aim to explore factors associated with elevated tau in CSF, and how these elevated tau are related to neurodegeneration and cognitive decline in the absence of Aβ positivity.

Methods

We examined relationships between CSF p-Tau/Aβ₄₀, and CSF Aβ₄₂/Aβ₄₀, Aβ PET, and white matter hyperintensities (WMH) as well as vascular risk factors in 149 cognitively unimpaired and 52 impaired individuals who were presumably not on the Alzheimer’s disease (AD) pathway due to negative Aβ status on both CSF and PET. Subgroups had ¹⁸F-fluorodeoxyglucose (FDG) PET and adjusted hippocampal volume (aHCV), and longitudinal measures of CSF, aHCV, FDG PET, and cognition data, so we examined CSF p-Tau/Aβ₄₀ associations with these measures as well.

Results

Elevated CSF p-Tau/Aβ₄₀ was associated with older age, male sex, greater WMH, and hypertension as well as a pattern of hippocampal atrophy and temporoparietal hypometabolism characteristic of AD. Lower CSF Aβ₄₂/Aβ₄₀, higher WMH, and hypertension but not age, sex, Aβ PET, APOE-ε4 status, body mass index, smoking, and hyperlipidemia at baseline predicted CSF p-Tau/Aβ₄₀ increases over approximately 5 years of follow-up. The relationship between CSF p-Tau/Aβ₄₀ and subsequent cognitive decline was partially or fully explained by neurodegenerative measurements.

Conclusions

These data provide surprising clues as to the etiology and significance of tau pathology in the absence of Aβ. It seems likely that, in addition to age, both cerebrovascular disease and subthreshold levels of Aβ are related to this tau accumulation. Crucially, this phenotype of CSF tau elevation in amyloid-negative individuals share features with AD such as a pattern of metabolic decline and regional brain atrophy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00913-5.

Abnormal tau in amyloid PET negative individuals

We examined the characteristics of individuals with biomarker evidence of tauopathy but without β-amyloid (Aβ) (A-T+) in relation to individuals with (A+T+) and without (A-T-) evidence of Alzheimer's disease (AD). We included 561 participants with Aβ and tau PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We compared A-T- (n = 316), A-T+ (n = 63), and A+T+ (n = 182) individuals on demographics, amyloid, tau, hippocampal volumes, and cognition. A-T+ individuals were low on apolipoprotein E ɛ4 prevalence (17%) and had no evidence of subtly elevated brain Aβ within the negative range. The severity of tau deposition, hippocampal atrophy, and cognitive dysfunction in the A-T+ group was intermediate between A-T- and A+T+ (all p < 0.001). Tau uptake patterns in A-T+ individuals were heterogeneous, but approximately 29% showed tau deposition in the medial temporal lobe only, consistent with primary age-related tauopathy and an additional 32% showed a pattern consistent with AD. A-T+ individuals also share other features that are characteristic of AD such as cognitive impairment and neurodegeneration, but this group is heterogeneous and likely reflects more than one disorder.

Plasma p-tau181 Level Predicts Neurodegeneration and Progression to Alzheimer's Dementia: A Longitudinal Study

Background: Plasma-based biomarkers would be potential biomarkers for early diagnosis of Alzheimer's disease (AD) because they are more available and cost-effective than cerebrospinal fluid (CSF) or neuroimaging. Therefore, we aimed to evaluate whether phosphorylated tau181 (p-tau181) in plasma could be an accurate AD predictor.

Methods: Participants from the ADNI database included 185 cognitively unimpaired subjects with negative Aβ (CU–), 66 subjects with pre-clinical AD (CU with positive Aβ), 164 subjects with mild cognitive impairment with negative Aβ (MCI–), 254 subjects with prodromal AD (MCI with positive Aβ), and 98 subjects with dementia. Multiple linear regression models, linear mixed-effects models, and local regression were used to explore cross-sectional and longitudinal associations of plasma p-tau181 with cognition, neuroimaging, or CSF biomarkers adjusted for age, sex, education, and APOE genotype. Besides, Kaplan–Meier and adjusted Cox-regression model were performed to predict the risk of progression to dementia. Receiver operating characteristic analyses were performed to evaluate the predictive value of p-tau181.

Results: Plasma p-tau181 level was highest in AD dementia, followed by prodromal AD and pre-clinical AD. In pre-clinical AD, plasma p-tau181 was negatively associated with hippocampal volume (β = −0.031, p-value = 0.017). In prodromal AD, plasma p-tau181 was associated with decreased global cognition, executive function, memory, language, and visuospatial functioning (β range −0.119 to −0.273, p-value < 0.05) and correlated with hippocampal volume (β = −0.028, p-value < 0.005) and white matter hyperintensity volume (WMH) volume (β = 0.02, p-value = 0.01). In AD dementia, increased plasma p-tau181 was associated with worse memory. In the whole group, baseline plasma p-tau181 was significantly associated with longitudinal increases in multiple neuropsychological test z-scores and correlated with AD-related CSF biomarkers and hippocampal volume (p-value < 0.05). Meanwhile, CU or MCI with high plasma p-tau181 carried a higher risk of progression to dementia. The area under the curve (AUC) of the adjusted model (age, sex, education, APOE genotype, and plasma p-tau181) was 0.78; that of additionally included CSF biomarkers was 0.84.

Conclusions: Plasma p-tau181 level is related to multiple AD-associated cognitive domains and AD-related CSF biomarkers at the clinical stages of AD. Moreover, plasma p-tau181 level is related to the change rates of cognitive decline and hippocampal atrophy. Thus, this study confirms the utility of plasma p-tau181 as a non-invasive biomarker for early detection and prediction of AD.

Falls: a marker of preclinical Alzheimer disease: a cohort study protocol

INTRODUCTION

Progression to symptomatic Alzheimer disease (AD) occurs slowly over a series of preclinical stages. Declining functional mobility may be an early indicator of loss of brain network integration and may lead to an increased risk of experiencing falls. It is unknown whether measures of functional mobility and falls are preclinical markers of AD. The purpose of this study is to examine (1) the relationship between falls and functional mobility with AD biomarkers to determine when falls occur within the temporal progression to symptomatic Alzheimer disease, and (2) the attentional compared with perceptual/motor systems that underlie falls and functional mobility changes seen with AD.

METHODS AND ANALYSIS

This longitudinal cohort study will be conducted at the Knight Alzheimer Disease Research Center. Approximately 350 cognitively normal participants (with and without preclinical AD) will complete an in-home visit every year for 4 years. During each yearly assessment, functional mobility will be assessed using the Performance Oriented Mobility Assessment, Timed Up and Go, and Timed Up and Go dual task. Data regarding falls (including number and severity) will be collected monthly by self-report and confirmed through interviews. This study will leverage ongoing neuropsychological assessments and neuroimaging (including molecular imaging using positron emission tomography and MRI) performed by the Knight Alzheimer Disease Research Center. Relationships between falls and biomarkers of amyloid, tau and neurodegeneration will be evaluated.

ETHICS AND DISSEMINATION

This study was approved by the Washington University in St. Louis Institutional Review Board (reference number 201807135). Written informed consent will be obtained in the home prior to the collection of any study data. Results will be published in peer-reviewed publications and presented at national and international conferences.

TRIAL REGISTRATION NUMBER

NCT04949529; Pre-results.

Risk of dementia in APOE ε4 carriers is mitigated by a polygenic risk score

INTRODUCTION

We investigated relationships among genetic determinants of Alzheimer's disease (AD), amyloid/tau/neurodegenaration (ATN) biomarkers, and risk of dementia.

METHODS

We studied cognitively normal individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort and SCIENCe project. We examined associations between genetic variants and ATN biomarkers, and evaluated their predictive value for incident dementia. A polygenic risk score (PRS) was calculated based on 39 genetic variants. The APOE gene was not included in the PRS and was analyzed separately.

RESULTS

The PRS and APOE ε4 were associated with amyloid-positive ATN profiles, and APOE ε4 additionally with isolated increased tau (A-T+N-). A high PRS and APOE ε4 separately predicted AD dementia. Combined, a high PRS increased while a low PRS attenuated the risk associated with ε4 carriers.

DISCUSSION

Genetic variants beyond APOE are clinically relevant and contribute to the pathophysiology of AD. In the future, a PRS might be used in individualized risk profiling.

Developing the ATX(N) classification for use across the Alzheimer disease continuum

Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.

Cortical correlates in upright dynamic and static balance in the elderly

Falls are the second most frequent cause of injury in the elderly. Physiological processes associated with aging affect the elderly's ability to respond to unexpected balance perturbations, leading to increased fall risk. Every year, approximately 30% of adults, 65 years and older, experiences at least one fall. Investigating the neurophysiological mechanisms underlying the control of static and dynamic balance in the elderly is an emerging research area. The study aimed to identify cortical and muscular correlates during static and dynamic balance tests in a cohort of young and old healthy adults. We recorded cortical and muscular activity in nine elderly and eight younger healthy participants during an upright stance task in static and dynamic (core board) conditions. To simulate real-life dual-task postural control conditions, the second set of experiments incorporated an oddball visual task. We observed higher electroencephalographic (EEG) delta rhythm over the anterior cortex in the elderly and more diffused fast rhythms (i.e., alpha, beta, gamma) in younger participants during the static balance tests. When adding a visual oddball, the elderly displayed an increase in theta activation over the sensorimotor and occipital cortices. During the dynamic balance tests, the elderly showed the recruitment of sensorimotor areas and increased muscle activity level, suggesting a preferential motor strategy for postural control. This strategy was even more prominent during the oddball task. Younger participants showed reduced cortical and muscular activity compared to the elderly, with the noteworthy difference of a preferential activation of occipital areas that increased during the oddball task. These results support the hypothesis that different strategies are used by the elderly compared to younger adults during postural tasks, particularly when postural and cognitive tasks are combined. The knowledge gained in this study could inform the development of age-specific rehabilitative and assistive interventions.

Neurodegeneration, Alzheimer's disease biomarkers, and longitudinal verbal learning and memory performance in late middle age

This study examined the effect of neurodegeneration, and its interaction with Alzheimer's disease (AD) cerebrospinal fluid biomarkers, on longitudinal verbal learning and memory performance in cognitively unimpaired (CU) late middle-aged adults. Three hundred and forty-two CU adults (cognitive baseline mean age = 58.4), with cerebrospinal fluid and structural MRI, completed 2-10 (median = 5) cognitive assessments. Learning and memory were assessed using the Rey Auditory Verbal Learning Test (RAVLT). We used sequential comparison of nested linear mixed effects models to analyze the data. Model selection preserved a significant ptau181/Aβ42 × global atrophy × age interaction; individuals with less global atrophy and lower ptau181/Aβ42 levels had less learning and delayed recall decline than individuals with more global atrophy and/or higher levels of ptau181/Aβ42. The hippocampal volume × age × ptau181/Aβ42 interaction was not significant. Findings suggest that in a sample of CU late middle-aged adults, individuals with AD biomarkers, global atrophy, or both evidence greater verbal learning and memory decline than individuals without either risk factor.

Prognostic value of amyloid/tau/neurodegeneration (ATN) classification based on diagnostic cerebrospinal fluid samples for Alzheimer's disease

Objective

The primary study objective of this retrospective academic memory clinic-based observational longitudinal study was to investigate the prognostic value of a cerebrospinal fluid (CSF)-based ATN classification for subsequent cognitive decline during the 3 years following lumbar puncture in a clinical, real-life setting. The secondary objective was to investigate the prognostic value of CSF biomarkers as continuous variables.

Methods

Data from 228 patients (median age 67 (47–85) years), who presented at the Neurology Memory Clinic UZ/KU Leuven between September 2011 and December 2016, were included with a follow-up period of up to 36 months. Patients underwent a CSF AD biomarker test for amyloid-beta 1–42 (Aβ₄₂)_, hyperphosphorylated tau (p₁₈₁-tau) and total tau (t-tau) in the clinical work-up for diagnostic reasons. Patients were divided into ATN classes based on CSF biomarkers: Aβ₄₂ for amyloid (A), p₁₈₁-tau for tau (T), and t-tau as a measure for neurodegeneration (N). Based on retrospective data analysis, cognitive performance was evaluated by Mini Mental State Examination (MMSE) scores every 6 months over a period up to 36 months following the lumbar puncture. The statistical analysis was based on linear mixed-effects modeling (LME).

Results

The distribution in the current clinical sample was as follows: A−/T−/N− 32.02%, A+/T−/N− 33.33%, A+/T+/N+ 17.11%, A+/T−/N+ 11.84%, A−/T−/N+ 4.39%, A−/T+/N+ 1.32% (3 cases), with no cases in the A−/T+/N− and A+/T+/N− class. Hence, the latter 3 classes were excluded from further analyses. The change of MMSE relative to A−/T−/N− over a 36-month period was significant in all four ATN classes: A+/T+/N+ = − 4.78 points on the MMSE; A−/T−/N+ = − 4.76; A+/T−/N+ = − 2.83; A+/T−/N− = − 1.96. The earliest significant difference was seen in the A+/T+/N+ class at 12 months after baseline. The effect of ATN class on future cognitive decline was confirmed for a different set of CSF thresholds. All individual baseline CSF biomarkers including the Aβ₄₂/t-tau ratio showed a significant correlation with subsequent cognitive decline, with the highest correlation seen for Aβ₄₂/t-tau.

Conclusion

ATN classification based on CSF biomarkers has a statistically significant and clinically relevant prognostic value for the course of cognitive decline in a 3-year period in a clinical practice setting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00817-4.

Longitudinal Cognitive and Biomarker Measurements Support a Unidirectional Pathway in Alzheimer's Disease Pathophysiology

BACKGROUND

Amyloid-β (Aβ) likely plays a primary role in Alzheimer's disease pathogenesis, but longitudinal Aβ, tau, and neurodegeneration (A/T/N) measurements in the same individuals have rarely been examined to verify the temporal dynamics of these biomarkers.

METHODS

In this study, we investigated the temporal ordering of Aβ, tau, and neurodegeneration using longitudinal biomarkers in nondemented elderly individuals. A total of 395 cognitively unimpaired individuals and 204 individuals with mild cognitive impairment (320 [53%] were female) were classified into 8 A±/T±/N± categories according to the abnormal (+)/normal (-) status of Aβ (¹⁸F-florbetapir or ¹⁸F-florbetaben) positron emission tomography (PET), ¹⁸F-flortaucipir PET, and adjusted hippocampal volume (aHCV). Follow-up Aβ PET, tau PET, and aHCV measurements at 0.6 to 4.1 years were available for 35% to 63% of the sample. Baseline Aβ, tau, and aHCV were compared between different A/T/N profiles. We investigated the associations of baseline and longitudinal Aβ, tau, and neurodegeneration in relation to one another continuously.

RESULTS

Among T- participants, tau was higher for A+/T-/N- individuals compared with the A-/T-/N- group (p = .02). Among N- participants, neurodegeneration was worse among A+/T+/N- individuals compared with the A-/T-/N- group (p = .001). High baseline Aβ was associated (p < .001) with subsequent tau increase and high baseline tau was associated (p = .002) with subsequent aHCV decrease, whereas high tau and low aHCV at baseline were not associated with subsequent Aβ increase.

CONCLUSIONS

These findings define a sequence of pathological events in Alzheimer's disease that support a current model of Alzheimer's disease pathogenesis in which Aβ appears early, followed by deposition of abnormal tau aggregates and subsequent neurodegeneration.