Determining clinically meaningful decline in preclinical Alzheimer disease

Sample size estimates for biomarker-based outcome measures in clinical trials in autosomal dominant Alzheimer's disease

INTRODUCTION

Alzheimer disease (AD)-modifying therapies are approved for treatment of early-symptomatic AD. Autosomal dominant AD (ADAD) provides a unique opportunity to test therapies in presymptomatic individuals.

METHODS

Using data from the Dominantly Inherited Alzheimer Network (DIAN), sample sizes for clinical trials were estimated for various cognitive, imaging, and CSF outcomes. Sample sizes were computed for detecting a reduction of either absolute levels of AD-related pathology (amyloid, tau) or change over time in neurodegeneration (atrophy, hypometabolism, cognitive change).

RESULTS

Biomarkers measuring amyloid and tau pathology had required sample sizes below 200 participants per arm (examples CSF Aβ42/40: 47[95 %CI 25,104], cortical PIB 49[28,99], CSF p-tau181 74[48,125]) for a four-year trial in presymptomatic individuals (CDR=0) to have 80 % power (5 % statistical significance) to detect a 25 % reduction in absolute levels of pathology, allowing 40 % dropout. For cognitive, MRI, and FDG, it was more appropriate to detect a 50 % reduction in rate of change. Sample sizes ranged from 250 to 900 (examples hippocampal volume: 338[131,2096], cognitive composite: 326[157,1074]). MRI, FDG and cognitive outcomes had lower sample sizes when including indivduals with mild impairment (CDR=0.5 and 1) as well as presymptomatic individuals (CDR=0).

DISCUSSION

Despite the rarity of ADAD, presymptomatic clinical trials with feasible sample sizes given the number of cases appear possible.

Sample size estimates for biomarker-based outcome measures in clinical trials in autosomal dominant Alzheimer's disease

INTRODUCTION

Alzheimer disease (AD)-modifying therapies are approved for treatment of early-symptomatic AD. Autosomal dominant AD (ADAD) provides a unique opportunity to test therapies in presymptomatic individuals.

METHODS

Using data from the Dominantly Inherited Alzheimer Network (DIAN), sample sizes for clinical trials were estimated for various cognitive, imaging, and CSF outcomes. Sample sizes were computed for detecting a reduction of either absolute levels of AD-related pathology (amyloid, tau) or change over time in neurodegeneration (atrophy, hypometabolism, cognitive change).

RESULTS

Biomarkers measuring amyloid and tau pathology had required sample sizes below 200 participants per arm (examples CSF Aβ42/40: 47[95%CI 25,104], cortical PIB 49[28,99], CSF p-tau181 74[48,125]) for a four-year trial in presymptomatic individuals (CDR=0) to have 80% power (5% statistical significance) to detect a 25% reduction in absolute levels of pathology, allowing 40% dropout. For cognitive, MRI, and FDG, it was more appropriate to detect a 50% reduction in rate of change. Sample sizes ranged from 250-900 (examples hippocampal volume: 338[131,2096], cognitive composite: 326[157,1074]). MRI, FDG and cognitive outcomes had lower sample sizes when including indivduals with mild impairment (CDR=0.5 and 1) as well as presymptomatic individuals (CDR=0).

DISCUSSION

Despite the rarity of ADAD, presymptomatic clinical trials with feasible sample sizes given the number of cases appear possible.

Cognitive aging outcomes are related to both tau pathology and maintenance of cingulate cortex structure

INTRODUCTION

Successful cognitive aging is related to both maintaining brain structure and avoiding Alzheimer's disease (AD) pathology, but how these factors interplay is unclear.

METHODS

A total of 109 cognitively normal older adults (70+ years old) underwent amyloid beta (Aβ) and tau positron emission tomography (PET) imaging, structural magnetic resonance imaging (MRI), and cognitive testing. Cognitive aging was quantified using the cognitive age gap (CAG), subtracting chronological age from predicted cognitive age.

RESULTS

Lower CAG (younger cognitive age) was related to slower decline in episodic memory, multi-domain cognition, and atrophy of the midcingulate cortex (MCC). Lower entorhinal cortical tau was linked to slower decline in episodic memory, multi-domain cognition, and hippocampal atrophy.

DISCUSSION

These results suggest that aging outcomes may be influenced by two independent pathways: one associated with tau accumulation, affecting primarily memory and hippocampal atrophy, and another involving tau-independent structural preservation of the MCC, benefiting multi-domain cognition over time.

HIGHLIGHTS

Younger cognitive age (lower cognitive age gap [CAG]) is related to slower cognitive decline. Lower CAG is linked to slower midcingulate cortex (MCC) atrophy. Reduced tau in the entorhinal cortex is related to less hippocampal atrophy and cognitive decline. Structural preservation of the MCC benefits multi-domain cognition over time. Two independent pathways influence cognitive aging: tau accumulation and MCC preservation.

Robust, fully-automated assessment of cerebral perivascular spaces and white matter lesions: a multicentre MRI longitudinal study of their evolution and association with risk of dementia and accelerated brain atrophy

BACKGROUND

Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. However, it is unknown whether PVS can predict dementia risk and brain atrophy trajectories in participants without dementia, as longitudinal studies on PVS are scarce and current methods for PVS assessment lack robustness and inter-scanner reproducibility.

METHODS

We developed a robust algorithm to automatically assess PVS count and size on clinical MRI, and investigated 1) their relationship with dementia risk and brain atrophy in participants without dementia, 2) their longitudinal evolution, and 3) their potential use as a screening tool in simulated clinical trials. We analysed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1 ± 9.7 years-old, 56.6% women) from three publicly available observational studies on ageing and dementia (the Alzheimer's Disease Neuroimaging Initiative, the National Alzheimer's Coordinating Centre database, and the Open Access Series of Imaging Studies). Clinical and MRI data collected between 2004 and 2022 were analysed with consistent methods, controlling for confounding factors, and combined using mixed-effects models.

FINDINGS

Our fully-automated method for PVS assessment showed excellent inter-scanner reproducibility (intraclass correlation coefficients >0.8). Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers differed significantly in participants without dementia who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants at low risk of dementia based on our PVS markers enhanced the power of the trial independently of Alzheimer's disease biomarkers.

INTERPRETATION

These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia.

FUNDING

US National Institutes of Health.

Serum biomarkers as prognostic markers for Alzheimer's disease in a clinical setting

INTRODUCTION

Blood-based glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau (pTau) have shown promising prognostic potential in Alzheimer's disease (AD), but their applicability in clinical settings where comorbidities are prevalent remains uncertain.

METHODS

Simoa assays quantified GFAP, NfL, and pTau181 in retrospectively retrieved prediagnostic serum samples from 102 AD patients and 21 non-AD controls.

RESULTS

Higher serum GFAP levels predicted earlier clinical presentation and faster subsequent Mini-Mental State Examination decline in AD patients. Serum NfL levels were increased in patients with arterial hypertension (AHT), kidney dysfunction, and a history of stroke and only demonstrated predictive value for time to clinical AD presentation after adjustment for these comorbidities. Serum pTau181 instability during long-term storage at -20°C prevented its prognostic evaluation in retrospectively retrieved serum samples.

DISCUSSION

Serum GFAP is a robust prognostic marker for AD progression, whereas NfL is impacted by various comorbidities, which complicates the interpretation of its prognostic value.

Highlights

Serum GFAP levels predict time to clinical AD presentation.Serum NfL levels are increased by hypertension, kidney disease, and stroke history.Prognostic value of serum NfL in AD is only evident after comorbidity correction.Serum levels of GFAP, but not NfL, increase over time within prediagnostic AD stages.

Assessing the clinical meaningfulness of slowing CDR-SB progression with disease-modifying therapies for Alzheimer's disease

INTRODUCTION

For many patients and caregivers, a major goal of disease-modifying treatments (DMTs) for Alzheimer's disease (AD) dementia is to extend independence in instrumental and basic activities of daily living (IADLs and BADLs). The goal of this study was to estimate the effect of treatments on the time remaining independent in IADLs and BADLs.

METHODS

Participants at the Knight Alzheimer Disease Research Center (Knight ADRC) who met eligibility criteria for recent DMT trials were studied: age ≥60 years at baseline, clinical diagnosis of very mild or mild AD dementia (global Clinical Dementia Rating [CDR] score 0.5 or 1), biomarker confirmation of amyloid pathology, and at least one follow-up CDR assessment within 5 years. For IADLs, a subset of the Functional Assessment Questionnaire (FAQ) was examined that rated the degree of independence in the following: paying bills, driving, remembering medications and appointments, and preparing meals. For BADLs, the Personal Care domain of the CDR was used. Mixed-effects logistic and ordinal regression models were used to examine the relationship between CDR Sum of Boxes (CDR-SB) and the individual functional outcomes and their components. The change in CDR-SB over time was estimated with linear mixed-effects models.

RESULTS

A total of 282 participants were followed for an average of 2.9 years (standard deviation [SD] 1.3 years). For 50% of individuals, loss of independence in IADLs occurred at CDR-SB >4.5 and in BADLs at CDR-SB >11.5. For individuals with a baseline CDR-SB = 2, treatment with lecanemab would extend independence in IADLs for 10 months (95% confidence interval [CI] 4-18 months) and treatment with donanemab in the low/medium tau group would extend independence in IADLs by 13 months (95% CI 6-24 months).

DISCUSSION

Independence in ADLs can be related to CDR-SB and used to demonstrate the effect of AD treatments in extending the time of independent function, a meaningful outcome for patients and their families.

Highlights

We estimated time to loss of independence for people with AD dementiaEstimating time to loss of independence can help with clinical decision-makingDisease-modifying treatments for AD dementia can extend independence.

Novel techniques for early diagnosis and monitoring of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is the most common neurodegenerative disorder, which is characterized by a progressive loss of cognitive functions. The high prevalence, chronicity, and multimorbidity are very common in AD, which significantly impair the quality of life and functioning of patients. Early detection and accurate diagnosis of Alzheimer's disease (AD) can stop the illness from progressing thereby postponing its symptoms. Therefore, for the early diagnosis and monitoring of AD, more sensitive, noninvasive, straightforward, and affordable screening tools are needed.

AREAS COVERED

This review summarizes the importance of early detection methods and novel techniques for Alzheimer's disease diagnosis that can be used by healthcare professionals.

EXPERT OPINION

Early diagnosis assists the patient and caregivers to understand the problem establishing reasonable goals and making future plans together. Early diagnosis techniques not only help in monitoring disease progression but also provide crucial information for the development of novel therapeutic targets. Researchers can plan to potentially alleviate symptoms or slow down the progression of Alzheimer's disease by identifying early molecular changes and targeting altered pathways.

Multimodal neuroimaging biomarkers and subtle cognitive decline in a population-based cohort without dementia

BACKGROUND

The relationship between subtle cognitive decline and Alzheimer's disease (AD) pathology as measured by biomarkers in settings outside of specialty memory clinics is not well characterized.

OBJECTIVE

To investigate how subtle longitudinal cognitive decline relates to neuroimaging biomarkers in individuals drawn from a population-based study in an economically depressed, small-town area in southwestern Pennsylvania, USA.

METHODS

A subset of participants without dementia (N = 115, age 76.53 years ± 6.25) from the Monongahela Youghiogheny Healthy Aging Team (MYHAT) study completed neuroimaging including magnetic resonance imaging (MRI) measures of AD-signature region cortical thickness and white matter hyperintensities (WMH), Pittsburgh compound B (PiB)-positron emission tomography (PET) for amyloid-β (Aβ) deposition, and [18F]AV-1451-PET for tau deposition. Neuropsychological evaluations were completed at multiple timepoints up to 11 years prior to neuroimaging. Aβ positivity was determined using a regional approach. We used linear mixed models to examine neuroimaging biomarker associations with retrospective cognitive slopes in five domains and a global cognitive composite.

RESULTS

Among Aβ(+) participants (38%), there were associations between (i) tau Braak III/IV and language decline (p < 0.05), (ii) cortical thickness and both memory decline (p < 0.001) and global cognitive decline (p < 0.01), and (iii) WMH and decline in executive function (p < 0.05) and global cognition (p < 0.05). Among Aβ(-) participants, there was an association between tau Braak III/IV and decline on tests of attention/psychomotor speed (p < 0.05).

CONCLUSIONS

These findings confirm an Aβ-dependent early AD biomarker pathway, and suggest a possible Aβ-independent, non-AD process underlying subtle cognitive decline in a population-based sample of older adults without dementia.

Evaluating clinical meaningfulness of anti-β-amyloid therapies amidst amyloid-related imaging abnormalities concern in Alzheimer's disease

Alzheimer's disease is the most prevalent form of dementia in the elderly, which is clinically characterized by a gradual and progressive deterioration of cognitive functions. The central and early role of β-amyloid in the pathogenesis of Alzheimer's disease is supported by a plethora of studies including genetic analyses, biomarker research and genome-wide association studies in both familial (early-onset) and sporadic (late-onset) forms of Alzheimer's. Monoclonal antibodies directed against β-amyloid demonstrate slowing of the clinical deterioration of patients with early Alzheimer's disease. Aducanumab, lecanemab and donanemab clinical trials showed slowing of Alzheimer's disease progression on composite scores by 25-40% based on the measure used. Anti-β-amyloid antibodies can cause side effects of bleeding and swelling in the brain, called amyloid-related imaging abnormalities. Amyloid-related imaging abnormalities typically occur early in treatment and are often asymptomatic, and though in rare cases, they can lead to serious or life-threatening events. The aim of this review is to evaluate the clinical meaningfulness of anti-β-amyloid therapies amidst amyloid-related imaging abnormalities concern in Alzheimer's disease.

Predicting the Progression of Mild Cognitive Impairment to Alzheimer's Dementia Using Recurrent Neural Networks With a Series of Neuropsychological Tests

BACKGROUND AND PURPOSE

The prevalence of Alzheimer's dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression.

METHODS

Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer's Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline.

RESULTS

The experimental results confirmed that the Preclinical Alzheimer's Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916.

CONCLUSIONS

Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

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.

Assessing the clinical meaningfulness of slowing CDR-SB progression with disease-modifying therapies for Alzheimer disease

INTRODUCTION

For many patients and caregivers, a major goal of disease-modifying treatments (DMT) for Alzheimer disease (AD) dementia is to extend independence in instrumental and basic activities of daily living (IADLs and BADLs). The goal of this study was to estimate the effect of treatments on the time remaining independent in IADLs and BADLs.

METHODS

Participants at the Knight Alzheimer Disease Research Center were selected who were potentially eligible for recent DMT trials: age ≥ 60 years at baseline, clinical diagnosis of very mild or mild AD dementia (global Clinical Dementia Rating® (CDR®) score 0.5 or 1), biomarker confirmation of amyloid pathology, and at least one follow-up CDR assessment within 5 years. For IADLs, a subset of the Functional Assessment Questionnaire (FAQ) was examined that rated the degree of independence in the following: paying bills, driving, remembering medications and appointments, and preparing meals. For BADLs, the Personal Care domain of the CDR was used. Mixed-effects logistic and ordinal regression models were used to examine the relationship between CDR Sum Boxes (CDR-SB) and the individual functional outcomes and their components. The change in CDR-SB over time was estimated with linear mixed effects models.

RESULTS

282 participants were followed for an average of 2.9 years (SD 1.3 years). For 50% of individuals, loss of independence in IADLs occurred at CDR-SB>4.5 and in BADLs at CDR-SB>11.5. For individuals with a baseline CDR-SB=2, treatment with lecanemab would extend independence in IADLs for 10 months (95% CI 4-18 months) and treatment with donanemab in the low/medium tau group would extend independence in IADLs by 13 months (95% CI 6-24 months).

DISCUSSION

Independence in ADLs can be related to CDR-SB and used to demonstrate the effect of AD treatments in extending the time of independent function, a meaningful outcome for patients and their families.

Amyloid-β but not tau accumulation is strongly associated with longitudinal cognitive decline

OBJECTIVE

Alzheimer's disease (AD) pathology is featured by the extracellular accumulation of amyloid-β (Aβ) plaques and intracellular tau neurofibrillary tangles in the brain. We studied whether Aβ and tau accumulation are independently associated with future cognitive decline in the AD continuum.

METHODS

Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) public database. A total of 1272 participants were selected based on the availability of Aβ-PET and CSF tau at baseline and of those 777 participants with follow-up visits.

RESULTS

We found that Aβ-PET and CSF tau pathology were related to cognitive decline across the AD clinical spectrum, both as potential predictors for dementia progression. Among them, Aβ-PET (A + T- subjects) is an independent reliable predictor of longitudinal cognitive decline in terms of ADAS-13, ADNI-MEM, and MMSE scores rather than tau pathology (A - T+ subjects), indicating tau accumulation is not closely correlated with future cognitive impairment without being driven by Aβ deposition. Of note, a high percentage of APOE ε4 carriers with Aβ pathology (A+) develop poor memory and learning capacity. Interestingly, this condition is not recurrence in terms of the ADNI-MEM domain when adding APOE ε4 status. Finally, the levels of Aβ-PET SUVR related to glucose hypometabolism more strongly in subjects with A + T- than A - T+ both happen at baseline and longitudinal changes.

CONCLUSIONS

In conclusion, Aβ-PET alone without tau pathology (A + T-) measure is an independent reliable predictor of longitudinal cognitive decline but may nonetheless forecast different status of dementia progression. However, tau accumulation alone without Aβ pathology background (A - T+) was not enough to be an independent predictor of cognitive worsening.

Healthy lifestyle and cognitive decline in middle-aged and older adults residing in 14 European countries

Studies examining lifestyle and cognitive decline often use healthy lifestyle indices, making it difficult to understand implications for interventions. We examined associations of 16 lifestyles with cognitive decline. Data from 32,033 cognitively-healthy adults aged 50-104 years participating in prospective cohort studies of aging from 14 European countries were used to examine associations of lifestyle with memory and fluency decline over 10 years. The reference lifestyle comprised not smoking, no-to-moderate alcohol consumption, weekly moderate-plus-vigorous physical activity, and weekly social contact. We found that memory and fluency decline was generally similar for non-smoking lifestyles. By contrast, memory scores declined up to 0.17 standard deviations (95% confidence interval= 0.08 - 0.27) and fluency scores up to 0.16 standard deviations (0.07 - 0.25) more over 10 years for those reporting smoking lifestyles compared with the reference lifestyle. We thus show that differences in cognitive decline between lifestyles were primarily dependent on smoking status.

Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts

Amyloid-beta (Aβ) toxic oligomers are critical early players in the molecular pathology of Alzheimer's disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aβ oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95-1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aβ oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.

How donanemab data address the coverage with evidence development questions

The Centers for Medicare & Medicaid Services (CMS) established a class-based National Coverage Determination (NCD) for monoclonal antibodies directed against amyloid for Alzheimer's disease (AD) with patient access through Coverage with Evidence Development (CED) based on three questions. This review, focused on donanemab, answers each of these CED questions with quality evidence. TRAILBLAZER-ALZ registration trials are presented with supporting literature and real-world data to answer CED questions for donanemab. TRAILBLAZER-ALZ registration trials demonstrated that donanemab significantly slowed cognitive and functional decline in amyloid-positive early symptomatic AD participants, and lowered their risk of disease progression while key safety risks occurred primarily within the first 6 months and then declined. Donanemab meaningfully improved health outcomes with a manageable safety profile in an early symptomatic AD population, representative of Medicare populations across diverse practice settings. The donanemab data provide the necessary level of evidence for CMS to open a reconsideration of their NCD. HIGHLIGHTS: Donanemab meaningfully improved outcomes in trial participants with early symptomatic Alzheimer's disease. Comorbidities in trial participants were consistent with the Medicare population. Co-medications in trial participants were consistent with the Medicare population. Risks associated with treatment tended to occur in the first 6 months. Risks of amyloid-related imaging abnormalities were managed with careful observation and magnetic resonance imaging monitoring.

A critical appraisal of blood-based biomarkers for Alzheimer's disease

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

New precision medicine avenues to the prevention of Alzheimer's disease from insights into the structure and function of γ-secretases

Two phase-III clinical trials with anti-amyloid peptide antibodies have met their primary goal, i.e. slowing of Alzheimer's disease (AD) progression. However, antibody therapy may not be the optimal therapeutic modality for AD prevention, as we will discuss in the context of the earlier small molecules described as "γ-secretase modulators" (GSM). We review here the structure, function, and pathobiology of γ-secretases, with a focus on how mutations in presenilin genes result in early-onset AD. Significant progress has been made in generating compounds that act in a manner opposite to pathogenic presenilin mutations: they stabilize the proteinase-substrate complex, thereby increasing the processivity of substrate cleavage and altering the size spectrum of Aβ peptides produced. We propose the term "γ-secretase allosteric stabilizers" (GSAS) to distinguish these compounds from the rather heterogenous class of GSM. The GSAS represent, in theory, a precision medicine approach to the prevention of amyloid deposition, as they specifically target a discrete aspect in a complex cell biological signalling mechanism that initiates the pathological processes leading to Alzheimer's disease.

Post-translational modifications linked to preclinical Alzheimer's disease-related pathological and cognitive changes

INTRODUCTION

In this study, we leverage proteomic techniques to identify communities of proteins underlying Alzheimer's disease (AD) risk among clinically unimpaired (CU) older adults.

METHODS

We constructed a protein co-expression network using 3869 cerebrospinal fluid (CSF) proteins quantified by SomaLogic, Inc., in a cohort of participants along the AD clinical spectrum. We then replicated this network in an independent cohort of CU older adults and related these modules to clinically-relevant outcomes.

RESULTS

We discovered modules enriched for phosphorylation and ubiquitination that were associated with abnormal amyloid status, as well as p-tau181 (M4: β = 2.44, p < 0.001, M7: β = 2.57, p < 0.001) and executive function performance (M4: β = -2.00, p = 0.005, M7: β = -2.39, p < 0.001).

DISCUSSION

In leveraging CSF proteomic data from individuals spanning the clinical spectrum of AD, we highlight the importance of post-translational modifications for early cognitive and pathological changes.

Genetic Risk for Alzheimer's Disease Alters Perceived Executive Dysfunction in Cognitively Healthy Middle-Aged and Older Adults

Background

Subjective cognitive complaints (SCC) may be an early indicator of future cognitive decline. However, findings comparing SCC and objective cognitive performance have varied, particularly in the memory domain. Even less well established is the relationship between subjective and objective complaints in non-amnestic domains, such as in executive functioning, despite evidence indicating very early changes in these domains. Moreover, particularly early changes in both amnestic and non-amnestic domains are apparent in those carrying the Apolipoprotein-E ɛ4 allele, a primary genetic risk for Alzheimer's disease (AD).

Objective

This study investigated the role of the ɛ4 allele in the consistency between subjective and objective executive functioning in 54 healthy, cognitively intact, middle-aged and older adults.

Methods

Participants (Mage = 64.07, SD = 9.27, range = 48-84; ɛ4+ = 18) completed the Frontal Systems Behavior Scale (FrSBe) Executive Dysfunction Scale (EXECDYS) to measure subjective executive functioning (SEF) and multiple executive functioning tasks, which were condensed into a single factor.

Results

After accounting for age, depression, and anxiety, objective executive functioning performance significantly predicted SEF. Importantly, ɛ4 moderated this effect. Specifically, those carrying the ɛ4 allele had significantly less accurate self-awareness of their executive functioning compared to ɛ4 non-carriers.

Conclusions

Utilizing an approach that integrates self-evaluation of executive functioning with objective neurocognitive assessment may help identify the earliest signs of impending cognitive decline, particularly in those with genetic risk for AD. Such an approach could sensitively determine those most prone to future cognitive decline prior to symptom onset, when interventions could be most effective.

Modeling of Parkinson's Disease Progression and Implications for Detection of Disease Modification in Treatment Trials

Background

Objectively measuring Parkinson's disease (PD) signs and symptoms over time is critical for the successful development of treatments aimed at halting the disease progression of people with PD.

Objective

To create a clinical trial simulation tool that characterizes the natural history of PD progression and enables a data-driven design of randomized controlled studies testing potential disease-modifying treatments (DMT) in early-stage PD.

Methods

Data from the Parkinson's Progression Markers Initiative (PPMI) were analyzed with nonlinear mixed-effect modeling techniques to characterize the progression of MDS-UPDRS part I (non-motor aspects of experiences of daily living), part II (motor aspects of experiences of daily living), and part III (motor signs). A clinical trial simulation tool was built from these disease models and used to predict probability of success as a function of trial design.

Results

MDS-UPDRS part III progresses approximately 3 times faster than MDS-UPDRS part II and I, with an increase of 3 versus 1 points/year. Higher amounts of symptomatic therapy is associated with slower progression of MDS-UPDRS part II and III. The modeling framework predicts that a DMT effect on MDS-UPDRS part III could precede effect on part II by approximately 2 to 3 years.

Conclusions

Our clinical trial simulation tool predicted that in a two-year randomized controlled trial, MDS-UPDRS part III could be used to evaluate a potential novel DMT, while part II would require longer trials of a minimum duration of 3 to 5 years underscoring the need for innovative trial design approaches including novel patient-centric measures.

ADCOMS sensitivity versus baseline diagnosis and progression phenotypes

BACKGROUND

The Alzheimer's Disease COMposite Score (ADCOMS) is more sensitive in clinical trials than conventional measures when assessing pre-dementia. This study compares ADCOMS trajectories using clustered progression characteristics to better understand different patterns of decline.

METHODS

Post-baseline ADCOMS values were analyzed for sensitivity using mean-to-standard deviation ratio (MSDR), partitioned by baseline diagnosis, comparing with the original scales upon which ADCOMS is based. Because baseline diagnosis was not a particularly reliable predictor of progression, individuals were also grouped into similar ADCOMS progression trajectories using clustering methods and the MSDR compared for each progression group.

RESULTS

ADCOMS demonstrated increased sensitivity for clinically important progression groups. ADCOMS did not show statistically significant sensitivity or clinical relevance for the less-severe baseline diagnoses and marginal progression groups.

CONCLUSIONS

This analysis complements and extends previous work validating the sensitivity of ADCOMS. The large data set permitted evaluation-in a novel approach-by the clustered progression group.

Artificial Intelligence in Eye Movements Analysis for Alzheimer's Disease Early Diagnosis

As the world's population ages, Alzheimer's disease is currently the seventh most common cause of death globally; the burden is anticipated to increase, especially among middle-class and elderly persons. Artificial intelligence-based algorithms that work well in hospital environments can be used to identify Alzheimer's disease. A number of databases were searched for English- language articles published up until March 1, 2024, that examined the relationships between artificial intelligence techniques, eye movements, and Alzheimer's disease. A novel non-invasive method called eye movement analysis may be able to reflect cognitive processes and identify anomalies in Alzheimer's disease. Artificial intelligence, particularly deep learning, and machine learning, is required to enhance Alzheimer's disease detection using eye movement data. One sort of deep learning technique that shows promise is convolutional neural networks, which need further data for precise classification. Nonetheless, machine learning models showed a high degree of accuracy in this context. Artificial intelligence-driven eye movement analysis holds promise for enhancing clinical evaluations, enabling tailored treatment, and fostering the development of early and precise Alzheimer's disease diagnosis. A combination of artificial intelligence-based systems and eye movement analysis can provide a window for early and non-invasive diagnosis of Alzheimer's disease. Despite ongoing difficulties with early Alzheimer's disease detection, this presents a novel strategy that may have consequences for clinical evaluations and customized medication to improve early and accurate diagnosis.

Treating Alzheimer's Disease: Focusing on Neurodegenerative Consequences

Neurodegenerative disorders involve progressive dysfunction and loss of synapses and neurons and brain atrophy, slowly declining memories and cognitive skills, throughout a long process. Alzheimer's disease (AD), the leading neurodegenerative disorder, suffers from a lack of effective therapeutic drugs. Decades of efforts targeting its pathologic hallmarks, amyloid plaques and neurofibrillary tangles, in clinical trials have produced therapeutics with marginal benefits that lack meaningful clinical improvements in cognition. Delivering meaningful clinical therapeutics to treat or prevent neurodegenerative disorders thus remains a great challenge to scientists and clinicians. Emerging evidence, however, suggests that dysfunction of various synaptogenic signaling pathways participates in the neurodegenerative progression, resulting in deterioration of operation/structure of the synaptic networks involved in cognition. These derailed endogenous signaling pathways and disease processes are potential pharmacological targets for the therapies. Therapeutics with meaningful clinical benefit in cognition may depend on the effectiveness of arresting and reversing the neurodegenerative process through these targets. In essence, promoting neuro-regeneration may represent the only option to recover degenerated synapses and neurons. These potential directions in clinical trials for AD therapeutics with meaningful clinical benefit in cognitive function are summarized and discussed.

A Stable and Scalable Digital Composite Neurocognitive Test for Early Dementia Screening Based on Machine Learning: Model Development and Validation Study

BACKGROUND

Dementia has become a major public health concern due to its heavy disease burden. Mild cognitive impairment (MCI) is a transitional stage between healthy aging and dementia. Early identification of MCI is an essential step in dementia prevention.

OBJECTIVE

Based on machine learning (ML) methods, this study aimed to develop and validate a stable and scalable panel of cognitive tests for the early detection of MCI and dementia based on the Chinese Neuropsychological Consensus Battery (CNCB) in the Chinese Neuropsychological Normative Project (CN-NORM) cohort.

METHODS

CN-NORM was a nationwide, multicenter study conducted in China with 871 participants, including an MCI group (n=327, 37.5%), a dementia group (n=186, 21.4%), and a cognitively normal (CN) group (n=358, 41.1%). We used the following 4 algorithms to select candidate variables: the F-score according to the SelectKBest method, the area under the curve (AUC) from logistic regression (LR), P values from the logit method, and backward stepwise elimination. Different models were constructed after considering the administration duration and complexity of combinations of various tests. Receiver operating characteristic curve and AUC metrics were used to evaluate the discriminative ability of the models via stratified sampling cross-validation and LR and support vector classification (SVC) algorithms. This model was further validated in the Alzheimer's Disease Neuroimaging Initiative phase 3 (ADNI-3) cohort (N=743), which included 416 (56%) CN subjects, 237 (31.9%) patients with MCI, and 90 (12.1%) patients with dementia.

RESULTS

Except for social cognition, all other domains in the CNCB differed between the MCI and CN groups (P<.008). In feature selection results regarding discrimination between the MCI and CN groups, the Hopkins Verbal Learning Test-5 minutes Recall had the best performance, with the highest mean AUC of up to 0.80 (SD 0.02) and an F-score of up to 258.70. The scalability of model 5 (Hopkins Verbal Learning Test-5 minutes Recall and Trail Making Test-B) was the lowest. Model 5 achieved a higher level of discrimination than the Hong Kong Brief Cognitive test score in distinguishing between the MCI and CN groups (P<.05). Model 5 also provided the highest sensitivity of up to 0.82 (range 0.72-0.92) and 0.83 (range 0.75-0.91) according to LR and SVC, respectively. This model yielded a similar robust discriminative performance in the ADNI-3 cohort regarding differentiation between the MCI and CN groups, with a mean AUC of up to 0.81 (SD 0) according to both LR and SVC algorithms.

CONCLUSIONS

We developed a stable and scalable composite neurocognitive test based on ML that could differentiate not only between patients with MCI and controls but also between patients with different stages of cognitive impairment. This composite neurocognitive test is a feasible and practical digital biomarker that can potentially be used in large-scale cognitive screening and intervention studies.

Decision making in clinical trials: Interim analyses, innovative design, and biomarkers

The efficient and accurate execution of clinical trials testing novel treatments for Alzheimer's disease (AD) is a critical component of the field's collective efforts to develop effective disease-modifying treatments for AD. The lengthy and heterogeneous nature of clinical progression in AD contributes to the challenges inherent in demonstrating a clinically meaningful benefit of any potential new AD therapy. The failure of many large and expensive clinical trials to date has prompted a focus on optimizing all aspects of decision making, to not only expedite the development of new treatments, but also maximize the value of the information that each clinical trial yields, so that all future clinical trials (including those that are negative) will contribute toward advancing the field. To address this important topic the Alzheimer's Association Research Roundtable convened December 1-2, 2020. The goals focused around identifying new directions and actionable steps to enhance clinical trial decision making in planned future studies.

Donanemab in Early Symptomatic Alzheimer Disease: The TRAILBLAZER-ALZ 2 Randomized Clinical Trial

Importance

There are limited efficacious treatments for Alzheimer disease.

Objective

To assess efficacy and adverse events of donanemab, an antibody designed to clear brain amyloid plaque.

Design, Setting, and Participants

Multicenter (277 medical research centers/hospitals in 8 countries), randomized, double-blind, placebo-controlled, 18-month phase 3 trial that enrolled 1736 participants with early symptomatic Alzheimer disease (mild cognitive impairment/mild dementia) with amyloid and low/medium or high tau pathology based on positron emission tomography imaging from June 2020 to November 2021 (last patient visit for primary outcome in April 2023).

Interventions

Participants were randomized in a 1:1 ratio to receive donanemab (n = 860) or placebo (n = 876) intravenously every 4 weeks for 72 weeks. Participants in the donanemab group were switched to receive placebo in a blinded manner if dose completion criteria were met.

Main Outcomes and Measures

The primary outcome was change in integrated Alzheimer Disease Rating Scale (iADRS) score from baseline to 76 weeks (range, 0-144; lower scores indicate greater impairment). There were 24 gated outcomes (primary, secondary, and exploratory), including the secondary outcome of change in the sum of boxes of the Clinical Dementia Rating Scale (CDR-SB) score (range, 0-18; higher scores indicate greater impairment). Statistical testing allocated α of .04 to testing low/medium tau population outcomes, with the remainder (.01) for combined population outcomes.

Results

Among 1736 randomized participants (mean age, 73.0 years; 996 [57.4%] women; 1182 [68.1%] with low/medium tau pathology and 552 [31.8%] with high tau pathology), 1320 (76%) completed the trial. Of the 24 gated outcomes, 23 were statistically significant. The least-squares mean (LSM) change in iADRS score at 76 weeks was -6.02 (95% CI, -7.01 to -5.03) in the donanemab group and -9.27 (95% CI, -10.23 to -8.31) in the placebo group (difference, 3.25 [95% CI, 1.88-4.62]; P < .001) in the low/medium tau population and -10.2 (95% CI, -11.22 to -9.16) with donanemab and -13.1 (95% CI, -14.10 to -12.13) with placebo (difference, 2.92 [95% CI, 1.51-4.33]; P < .001) in the combined population. LSM change in CDR-SB score at 76 weeks was 1.20 (95% CI, 1.00-1.41) with donanemab and 1.88 (95% CI, 1.68-2.08) with placebo (difference, -0.67 [95% CI, -0.95 to -0.40]; P < .001) in the low/medium tau population and 1.72 (95% CI, 1.53-1.91) with donanemab and 2.42 (95% CI, 2.24-2.60) with placebo (difference, -0.7 [95% CI, -0.95 to -0.45]; P < .001) in the combined population. Amyloid-related imaging abnormalities of edema or effusion occurred in 205 participants (24.0%; 52 symptomatic) in the donanemab group and 18 (2.1%; 0 symptomatic during study) in the placebo group and infusion-related reactions occurred in 74 participants (8.7%) with donanemab and 4 (0.5%) with placebo. Three deaths in the donanemab group and 1 in the placebo group were considered treatment related.

Conclusions and Relevance

Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab significantly slowed clinical progression at 76 weeks in those with low/medium tau and in the combined low/medium and high tau pathology population.

Trial Registration

ClinicalTrials.gov Identifier: NCT04437511.

Clinical effects of Lewy body pathology in cognitively impaired individuals

There is poor knowledge about the clinical effects of Lewy body (LB) pathology in patients with cognitive impairment, especially when coexisting with Alzheimer's disease (AD) pathology (amyloid-β and tau). Using a seed amplification assay, we analyzed cerebrospinal fluid for misfolded LB-associated α-synuclein in 883 memory clinic patients with mild cognitive impairment or dementia from the BioFINDER study. Twenty-three percent had LB pathology, of which only 21% fulfilled clinical criteria of Parkinson's disease or dementia with Lewy bodies at baseline. Among these LB-positive patients, 48% had AD pathology. Fifty-four percent had AD pathology in the whole sample (17% of mild cognitive impairment and 24% of patients with dementia were also LB-positive). When examining independent cross-sectional effects, LB pathology but not amyloid-β or tau, was associated with hallucinations and worse attention/executive, visuospatial and motor function. LB pathology was also associated with faster longitudinal decline in all examined cognitive functions, independent of amyloid-β, tau, cognitive stage and a baseline diagnosis of dementia with Lewy bodies/Parkinson's disease. LB status provides a better precision-medicine approach to predict clinical trajectories independent of AD biomarkers and a clinical diagnosis, which could have implications for the clinical management of cognitive impairment and the design of AD and LB drug trials.

Cognitive effects of Lewy body pathology in clinically unimpaired individuals

α-Synuclein aggregates constitute the pathology of Lewy body (LB) disease. Little is known about the effects of LB pathology in preclinical (presymptomatic) individuals, either as isolated pathology or coexisting with Alzheimer's disease (AD) pathology (β-amyloid (Aβ) and tau). We examined the effects of LB pathology using a cerebrospinal fluid α-synuclein-seed amplification assay in 1,182 cognitively and neurologically unimpaired participants from the BioFINDER study: 8% were LB positive, 26% Aβ positive (13% of those were LB positive) and 16% tau positive. LB positivity occurred more often in the presence of Aβ positivity but not tau positivity. LB pathology had independently negative effects on cross-sectional and longitudinal global cognition and memory and on longitudinal attention/executive function. Tau had cognitive effects of a similar magnitude, but these were less pronounced for Aβ. Participants with both LB and AD (Aβ and tau) pathology exhibited faster cognitive decline than those with only LB or AD pathology. LB, but not AD, pathology was associated with reduced sense of smell. Only LB-positive participants progressed to clinical LB disease over 10 years. These results are important for individualized prognosis, recruitment and choice of outcome measures in preclinical LB disease trials, but also for the design of early AD trials because >10% of individuals with preclinical AD have coexisting LB pathology.

Genetic Moderation of the Association of β-Amyloid With Cognition and MRI Brain Structure in Alzheimer Disease

BACKGROUND AND OBJECTIVES

There is considerable heterogeneity in the association between increasing β-amyloid (Aβ) pathology and early cognitive dysfunction in preclinical Alzheimer disease (AD). At this stage, some individuals show no signs of cognitive dysfunction, while others show clear signs of decline. The factors explaining this heterogeneity are particularly important for understanding progression in AD but remain largely unknown. In this study, we examined an array of genetic variants that may influence the relationships among Aβ, brain structure, and cognitive performance in 2 large cohorts.

METHODS

In 2,953 cognitively unimpaired participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer disease (A4) study, interactions between genetic variants and 18F-Florbetapir PET standardized uptake value ratio (SUVR) to predict the Preclinical Alzheimer Cognitive Composite (PACC) were assessed. Genetic variants identified in the A4 study were evaluated in the Alzheimer Disease Neuroimaging Initiative (ADNI, N = 527) for their association with longitudinal cognition and brain atrophy in both cognitively unimpaired participants and those with mild cognitive impairment.

RESULTS

In the A4 study, 4 genetic variants significantly moderated the association between Aβ load and cognition. Minor alleles of 3 variants were associated with additional decreases in PACC scores with increasing Aβ SUVR (rs78021285, β = -2.29, SE = 0.40, p FDR = 0.02, nearest gene ARPP21; rs71567499, β = -2.16, SE = 0.38, p FDR = 0.02, nearest gene PPARD; and rs10974405, β = -1.68, SE = 0.29, p FDR = 0.02, nearest gene GLIS3). The minor allele of rs7825645 was associated with less decrease in PACC scores with increasing Aβ SUVR (β = 0.71, SE = 0.13, p FDR = 0.04, nearest gene FGF20). The genetic variant rs76366637, in linkage disequilibrium with rs78021285, was available in both the A4 and ADNI. In the A4, rs76366637 was strongly associated with reduced PACC scores with increasing Aβ SUVR (β = -1.01, SE = 0.21, t = -4.90, p < 0.001). In the ADNI, rs76366637 was associated with accelerated cognitive decline (χ2 = 15.3, p = 0.004) and atrophy over time (χ2 = 26.8, p < 0.001), with increasing Aβ SUVR.

DISCUSSION

Patterns of increased cognitive dysfunction and accelerated atrophy due to specific genetic variation may explain some of the heterogeneity in cognition in preclinical and prodromal AD. The genetic variant near ARPP21 associated with lower cognitive scores in the A4 and accelerated cognitive decline and brain atrophy in the ADNI may help to identify those at the highest risk of accelerated progression of AD.

A robust harmonization approach for cognitive data from multiple aging and dementia cohorts

INTRODUCTION

Although many cognitive measures have been developed to assess cognitive decline due to Alzheimer's disease (AD), there is little consensus on optimal measures, leading to varied assessments across research cohorts and clinical trials making it difficult to pool cognitive measures across studies.

METHODS

We used a two-stage approach to harmonize cognitive data across cohorts and derive a cross-cohort score of cognitive impairment due to AD. First, we pool and harmonize cognitive data from international cohorts of varying size and ethnic diversity. Next, we derived cognitive composites that leverage maximal data from the harmonized dataset.

RESULTS

We show that our cognitive composites are robust across cohorts and achieve greater or comparable sensitivity to AD-related cognitive decline compared to the Mini-Mental State Examination and Preclinical Alzheimer Cognitive Composite. Finally, we used an independent cohort validating both our harmonization approach and composite measures.

DISCUSSION

Our easy to implement and readily available pipeline offers an approach for researchers to harmonize their cognitive data with large publicly available cohorts, providing a simple way to pool data for the development or validation of findings related to cognitive decline due to AD.

Electroencephalography and mild cognitive impairment research: A scoping review and bibliometric analysis (ScoRBA)

Mild cognitive impairment (MCI) is often considered a precursor to Alzheimer's disease (AD) and early diagnosis may help improve treatment effectiveness. To identify accurate MCI biomarkers, researchers have utilized various neuroscience techniques, with electroencephalography (EEG) being a popular choice due to its low cost and better temporal resolution. In this scoping review, we analyzed 2310 peer-reviewed articles on EEG and MCI between 2012 and 2022 to track the research progress in this field. Our data analysis involved co-occurrence analysis using VOSviewer and a Patterns, Advances, Gaps, Evidence of Practice, and Research Recommendations (PAGER) framework. We found that event-related potentials (ERP), EEG, epilepsy, quantitative EEG (QEEG), and EEG-based machine learning were the primary research themes. The study showed that ERP/EEG, QEEG, and EEG-based machine learning frameworks provide high-accuracy detection of seizure and MCI. These findings identify the main research themes in EEG and MCI and suggest promising avenues for future research in this field.

Expectations and clinical meaningfulness of randomized controlled trials

Alzheimer's disease (AD) clinical trials are designed and powered to detect the impact of a therapeutic intervention, and there has been considerable discussion on what constitutes a clinically meaningful change in those receiving treatment versus placebo. The pathology of AD is complex, beginning many years before clinical symptoms are detectable, with multiple potential opportunities for therapeutic engagement. Introducing treatment strategies early in the disease and assessing meaningful change over the course of an 18-month clinical trial are critical to understanding the value to an effective intervention. With new clinical trial data expected soon on emerging therapeutics from several AD studies, the Alzheimer's Association convened a work group of experts to discuss key considerations for interpreting data from cognitive and functional measures and what is considered a clinically meaningful benefit or meaningful slowing of this fatal disease. Our expectations of outcomes from therapeutic interventions in AD may need to be modified.

Harmonizing the preclinical Alzheimer cognitive composite for multicohort studies

OBJECTIVES

Studies are increasingly examining research questions across multiple cohorts using data from the preclinical Alzheimer cognitive composite (PACC). Our objective was to use modern psychometric approaches to develop a harmonized PACC.

METHOD

We used longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and Australian Imaging, Biomarker and Lifestyle Study of Ageing (AIBL) cohorts (n = 2,712). We further demonstrated our method with the Anti-Amyloid Treatment of Asymptomatic Alzheimer's Disease (A4) Study prerandomized data (n = 4,492). For the harmonization method, we used confirmatory factor analysis (CFA) on the final visit of the longitudinal cohorts to determine parameters to generate latent PACC (lPACC) scores. Overlapping tests across studies were set as "anchors" that tied cohorts together, while parameters from unique tests were freely estimated. We performed validation analyses to assess the performance of lPACC versus the common standardized PACC (zPACC).

RESULTS

Baseline (BL) scores for the zPACC were centered on zero, by definition. The harmonized lPACC did not define a common mean of zero and demonstrated differences in baseline ability levels across the cohorts. Baseline lPACC slightly outperformed zPACC in the prediction of progression to dementia. Longitudinal change in the lPACC was more constrained and less variable relative to the zPACC. In combined-cohort analyses, longitudinal lPACC slightly outperformed longitudinal zPACC in its association with baseline β-amyloid status.

CONCLUSIONS

This study proposes procedures for harmonizing the PACC that make fewer strong assumptions than the zPACC, facilitating robust multicohort analyses. This implementation of item response theory lends itself to adapting across future cohorts with similar composites. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Blood biomarkers for Alzheimer's disease in clinical practice and trials

Blood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.

Prediction of Longitudinal Cognitive Decline in Preclinical Alzheimer Disease Using Plasma Biomarkers

Importance

Alzheimer disease (AD) pathology starts with a prolonged phase of β-amyloid (Aβ) accumulation without symptoms. The duration of this phase differs greatly among individuals. While this disease phase has high relevance for clinical trial designs, it is currently unclear how to best predict the onset of clinical progression.

Objective

To evaluate combinations of different plasma biomarkers for predicting cognitive decline in Aβ-positive cognitively unimpaired (CU) individuals.

Design, Setting, and Participants

This prospective population-based prognostic study evaluated data from 2 prospective longitudinal cohort studies (the Swedish BioFINDER-1 and the Wisconsin Registry for Alzheimer Prevention [WRAP]), with data collected from February 8, 2010, to October 21, 2020, for the BioFINDER-1 cohort and from August 11, 2011, to June 27, 2021, for the WRAP cohort. Participants were CU individuals recruited from memory clinics who had brain Aβ pathology defined by cerebrospinal fluid (CSF) Aβ42/40 in the BioFINDER-1 study and by Pittsburgh Compound B (PiB) positron emission tomography (PET) in the WRAP study. A total of 564 eligible Aβ-positive and Aβ-negative CU participants with available relevant data from the BioFINDER-1 and WRAP cohorts were included in the study; of those, 171 Aβ-positive participants were included in the main analyses.

Exposures

Baseline P-tau181, P-tau217, P-tau231, glial fibrillary filament protein, and neurofilament light measured in plasma; CSF biomarkers in the BioFINDER-1 cohort, and PiB PET uptake in the WRAP cohort.

Main Outcomes and Measures

The primary outcome was longitudinal measures of cognition (using the Mini-Mental State Examination [MMSE] and the modified Preclinical Alzheimer Cognitive Composite [mPACC]) over a median of 6 years (range, 2-10 years). The secondary outcome was conversion to AD dementia. Baseline biomarkers were used in linear regression models to predict rates of longitudinal cognitive change (calculated separately). Models were adjusted for age, sex, years of education, apolipoprotein E ε4 allele status, and baseline cognition. Multivariable models were compared based on model R2 coefficients and corrected Akaike information criterion.

Results

Among 171 Aβ-positive CU participants included in the main analyses, 119 (mean [SD] age, 73.0 [5.4] years; 60.5% female) were from the BioFINDER-1 study, and 52 (mean [SD] age, 64.4 [4.6] years; 65.4% female) were from the WRAP study. In the BioFINDER-1 cohort, plasma P-tau217 was the best marker to predict cognitive decline in the mPACC (model R2 = 0.41) and the MMSE (model R2 = 0.34) and was superior to the covariates-only models (mPACC: R2 = 0.23; MMSE: R2 = 0.04; P < .001 for both comparisons). Results were validated in the WRAP cohort; for example, plasma P-tau217 was associated with mPACC slopes (R2 = 0.13 vs 0.01 in the covariates-only model; P = .01) and MMSE slopes (R2 = 0.29 vs 0.24 in the covariates-only model; P = .046). Sparse models were identified with plasma P-tau217 as a predictor of cognitive decline. Power calculations for enrichment in hypothetical clinical trials revealed large relative reductions in sample sizes when using plasma P-tau217 to enrich for CU individuals likely to experience cognitive decline over time.

Conclusions and Relevance

In this study, plasma P-tau217 predicted cognitive decline in patients with preclinical AD. These findings suggest that plasma P-tau217 may be used as a complement to CSF or PET for participant selection in clinical trials of novel disease-modifying treatments.

Meaningful Clinical Changes in Alzheimer Disease Measured With the iADRS and Illustrated Using the Donanemab TRAILBLAZER-ALZ Study Findings

Purpose of Review

To provide relevant background of the Integrated Alzheimer's Disease Rating Scale (iADRS), with examples, to assist the reader with the interpretation of iADRS findings from the TRAILBLAZER-ALZ study.

Recent Findings

The iADRS is an integrated measure of global Alzheimer disease (AD) severity for use in the clinical trial environment. It provides a single score that captures commonalities across cognitive and functional ability domains, reflecting disease-related impairment, while minimizing noise not related to disease progression that may exist within each domain. In AD, disease-modifying therapies (DMTs) are expected to slow the rate of clinical decline, changing the trajectory of disease progression. The overall percent slowing of disease progression with treatment is a more informative outcome of effect than absolute point differences between treatment and placebo groups at any given time point because the latter is influenced by treatment period and disease severity. The TRAILBLAZER-ALZ trial was a phase 2 study designed to evaluate the safety and efficacy of donanemab in participants with early symptomatic AD; the primary outcome measure was the change from baseline to 76 weeks on the iADRS. In the TRAILBLAZER-ALZ study, donanemab slowed disease progression by 32% at 18 months (p = 0.04 vs placebo), demonstrating clinical efficacy. At the patient level, one can assess whether the DMT effect is clinically meaningful by estimating the threshold of change consistent with clinically meaningful worsening; based on the TRAILBLAZER-ALZ findings, treatment with donanemab would delay reaching this threshold by approximately 6 months.

Summary

The iADRS is capable of accurately describing clinical changes associated with disease progression and detecting treatment effects and is an effective assessment tool for use in clinical trials of individuals with early symptomatic AD.

Rationale for the selection of dual primary endpoints in prevention studies of cognitively unimpaired individuals at genetic risk for developing symptoms of Alzheimer's disease

BACKGROUND

There is a critical need for novel primary endpoints designed to detect early and subtle changes in cognition in clinical trials targeting the asymptomatic (preclinical) phase of Alzheimer's disease (AD). The Alzheimer's Prevention Initiative (API) Generation Program, conducted in cognitively unimpaired individuals at risk of developing AD (e.g., enriched by the apolipoprotein E (APOE) genotype), used a novel dual primary endpoints approach, whereby demonstration of treatment effect in one of the two endpoints is sufficient for trial success. The two primary endpoints were (1) time to event (TTE)-with an event defined as a diagnosis of mild cognitive impairment (MCI) due to AD and/or dementia due to AD-and (2) change from baseline to month 60 in the API Preclinical Composite Cognitive (APCC) test score.

METHODS

Historical observational data from three sources were used to fit models to describe the TTE and the longitudinal APCC decline, both in people who do and do not progress to MCI or dementia due to AD. Clinical endpoints were simulated based on the TTE and APCC models to assess the performance of the dual endpoints versus each of the two single endpoints, with the selected treatment effect ranging from a hazard ratio (HR) of 0.60 (40% risk reduction) to 1 (no effect).

RESULTS

A Weibull model was selected for TTE, and power and linear models were selected to describe the APCC score for progressors and non-progressors, respectively. Derived effect sizes in terms of reduction of the APCC change from baseline to year 5 were low (0.186 for HR = 0.67). The power for the APCC alone was consistently lower compared to the power of TTE alone (58% [APCC] vs 84% [TTE] for HR = 0.67). Also, the overall power was higher for the 80%/20% distribution (82%) of the family-wise type 1 error rate (alpha) between TTE and APCC compared to 20%/80% (74%).

CONCLUSIONS

Dual endpoints including TTE and a measure of cognitive decline perform better than the cognitive decline measure as a single primary endpoint in a cognitively unimpaired population at risk of AD (based on the APOE genotype). Clinical trials in this population, however, need to be large, include older age, and have a long follow-up period of at least 5 years to be able to detect treatment effects.

How can secondary dementia prevention trials of Alzheimer's disease be clinically meaningful?

After clinical trial failures in symptomatic Alzheimer's disease (AD), our field has moved to earlier intervention in cognitively normal individuals with biomarker evidence of AD. This offers potential for dementia prevention, but mainly low and variable rates of progression to AD dementia reduce the usefulness of trials' data in decision making by potential prescribers. With results from several Phase 3 secondary prevention studies anticipated within the next few years and the Food and Drug Administration's recent endorsement of amyloid beta as a surrogate outcome biomarker for AD clinical trials, it is time to question the clinical significance of changes in biomarkers, adequacy of current trial durations, and criteria for treatment success if cognitively unimpaired patients and their doctors are to meaningfully evaluate the potential value of new agents. We argue for a change of direction toward trial designs that can unambiguously inform clinical decision making about dementia risk and progression.

Tau positron emission tomography in preclinical Alzheimer's disease

Rates of tau accumulation in cognitively unimpaired older adults are subtle, with magnitude and spatial patterns varying in recent reports. Regional accumulation also likely varies in the degree to which accumulation is amyloid-β-dependent. Thus, there is a need to evaluate the pattern and consistency of tau accumulation across multiple cognitively unimpaired cohorts and how these patterns relate to amyloid burden, in order to design optimal tau end points for clinical trials. Using three large cohorts of cognitively unimpaired older adults, the Anti-Amyloid Treatment in Asymptomatic Alzheimer's and companion study, Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (n = 447), the Alzheimer's Disease Neuroimaging Initiative (n = 420) and the Harvard Aging Brain Study (n = 190), we attempted to identify regions with high rates of tau accumulation and estimate how these rates evolve over a continuous spectrum of baseline amyloid deposition. Optimal combinations of regions, tailored to multiple ranges of baseline amyloid burden as hypothetical clinical trial inclusion criteria, were tested and validated. The inferior temporal cortex, fusiform gyrus and middle temporal cortex had the largest effect sizes of accumulation in both longitudinal cohorts when considered individually. When tau regions of interest were combined to find composite weights to maximize the effect size of tau change over time, both longitudinal studies exhibited a similar pattern-inferior temporal cortex, almost exclusively, was optimal for participants with mildly elevated amyloid β levels. For participants with highly elevated baseline amyloid β levels, combined optimal composite weights were 53% inferior temporal cortex, 31% amygdala and 16% fusiform. At mildly elevated levels of baseline amyloid β, a sample size of 200/group required a treatment effect of 0.40-0.45 (40-45% slowing of tau accumulation) to power an 18-month trial using the optimized composite. Neither a temporal lobe composite nor a global composite reached 80% power with 200/group with an effect size under 0.5. The focus of early tau accumulation on the medial temporal lobe has resulted from the observation that the entorhinal cortex is the initial site to show abnormal levels of tau with age. However, these abnormal levels do not appear to be the result of a high rate of accumulation in the short term, but possibly a more moderate rate occurring early with respect to age. While the entorhinal cortex plays a central role in the early appearance of tau, it may be the inferior temporal cortex that is the critical region for rapid tau accumulation in preclinical Alzheimer's disease.

Assessing What Matters to People Affected by Alzheimer's Disease: A Quantitative Analysis

INTRODUCTION

In this phase of the ongoing What Matters Most study series, designed to evaluate concepts that are meaningful to people affected by Alzheimer's disease (AD), we quantified the importance of symptoms, impacts, and outcomes of AD to people at risk for or with AD and care partners of people with AD.

METHODS

We administered a web-based survey to individuals at risk for or with AD (Group 1: unimpaired cognition with evidence of AD pathology; Group 2: AD risk factors and subjective cognitive complaints/mild cognitive impairment; Group 3: mild AD) and to care partners of individuals with moderate AD (Group 4) or severe AD (Group 5). Respondents rated the importance of 42 symptoms, impacts, and outcomes on a scale ranging from 1 ("not at all important") to 5 ("extremely important").

RESULTS

Among the 274 respondents (70.4% female; 63.1% white), over half of patient respondents rated all 42 items as "very important" or "extremely important," while care partners rated fewer items as "very important" or "extremely important." Among the three patient groups, the minimum (maximum) mean importance rating for any item was 3.4 (4.6), indicating that all items were at least moderately to very important. Among care partners of people with moderate or severe AD, the minimum (maximum) mean importance rating was 2.1 (4.4), indicating that most items were rated as at least moderately important. Overall, taking medications correctly, not feeling down or depressed, and staying safe had the highest importance ratings among both patients and care partners, regardless of AD phase.

CONCLUSION

Concepts of importance to individuals affected by AD go beyond the common understanding of "cognition" or "function" alone, reflecting a desire to maintain independence, overall physical and mental health, emotional well-being, and safety. Preservation of these attributes may be key to understanding whether interventions deliver clinically meaningful outcomes.

Lecanemab in Early Alzheimer's Disease

BACKGROUND

The accumulation of soluble and insoluble aggregated amyloid-beta (Aβ) may initiate or potentiate pathologic processes in Alzheimer's disease. Lecanemab, a humanized IgG1 monoclonal antibody that binds with high affinity to Aβ soluble protofibrils, is being tested in persons with early Alzheimer's disease.

METHODS

We conducted an 18-month, multicenter, double-blind, phase 3 trial involving persons 50 to 90 years of age with early Alzheimer's disease (mild cognitive impairment or mild dementia due to Alzheimer's disease) with evidence of amyloid on positron-emission tomography (PET) or by cerebrospinal fluid testing. Participants were randomly assigned in a 1:1 ratio to receive intravenous lecanemab (10 mg per kilogram of body weight every 2 weeks) or placebo. The primary end point was the change from baseline at 18 months in the score on the Clinical Dementia Rating-Sum of Boxes (CDR-SB; range, 0 to 18, with higher scores indicating greater impairment). Key secondary end points were the change in amyloid burden on PET, the score on the 14-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog14; range, 0 to 90; higher scores indicate greater impairment), the Alzheimer's Disease Composite Score (ADCOMS; range, 0 to 1.97; higher scores indicate greater impairment), and the score on the Alzheimer's Disease Cooperative Study-Activities of Daily Living Scale for Mild Cognitive Impairment (ADCS-MCI-ADL; range, 0 to 53; lower scores indicate greater impairment).

RESULTS

A total of 1795 participants were enrolled, with 898 assigned to receive lecanemab and 897 to receive placebo. The mean CDR-SB score at baseline was approximately 3.2 in both groups. The adjusted least-squares mean change from baseline at 18 months was 1.21 with lecanemab and 1.66 with placebo (difference, -0.45; 95% confidence interval [CI], -0.67 to -0.23; P<0.001). In a substudy involving 698 participants, there were greater reductions in brain amyloid burden with lecanemab than with placebo (difference, -59.1 centiloids; 95% CI, -62.6 to -55.6). Other mean differences between the two groups in the change from baseline favoring lecanemab were as follows: for the ADAS-cog14 score, -1.44 (95% CI, -2.27 to -0.61; P<0.001); for the ADCOMS, -0.050 (95% CI, -0.074 to -0.027; P<0.001); and for the ADCS-MCI-ADL score, 2.0 (95% CI, 1.2 to 2.8; P<0.001). Lecanemab resulted in infusion-related reactions in 26.4% of the participants and amyloid-related imaging abnormalities with edema or effusions in 12.6%.

CONCLUSIONS

Lecanemab reduced markers of amyloid in early Alzheimer's disease and resulted in moderately less decline on measures of cognition and function than placebo at 18 months but was associated with adverse events. Longer trials are warranted to determine the efficacy and safety of lecanemab in early Alzheimer's disease. (Funded by Eisai and Biogen; Clarity AD ClinicalTrials.gov number, NCT03887455.).

The treatment of sleep dysfunction to improve cognitive function: A meta-analysis of randomized controlled trials

OBJECTIVE

This meta-analysis of randomized controlled trials (RCTs) evaluates if treating sleep disturbances improves cognitive function over at least 12 weeks.

METHODS

Multiple data sources were searched until November 1, 2021. RCTs were included if they examined the effect of an intervention (behavioral or medical) on sleep and cognition in an adult sample with sleep disturbances and had an intervention duration and follow-up of at least 12 weeks. Two independent reviewers located 3784 studies; 16 satisfied the inclusion criteria. Primary outcomes included the broad cognitive domains of visual processing, short-term memory, long-term storage and retrieval, processing speed, and reaction time.

RESULTS

Most trials were conducted in participants with obstructive sleep apnea (OSA; N = 13); the most studied intervention was continuous positive airway pressure (CPAP; N = 10). All RCTs were 12 months in duration or less. The estimates of mean pooled effects were not indicative of significant treatment effect for any primary outcome. Although the interventions reduced daytime sleepiness (Hedge's g, 0.51; 95% confidence interval, 0.29-0.74; p < 0.01), this did not lead to cognitive enhancement.

CONCLUSIONS

Overall, there was insufficient evidence to suggest that treating sleep dysfunction can improve cognition. Further studies with longer follow-up duration and supporting biomarkers are needed.

Cerebrospinal fluid levels of fatty acid-binding protein 3 are associated with likelihood of amyloidopathy in cognitively healthy individuals

Introduction

Fatty acid-binding protein 3 (FABP3) is a biomarker of neuronal membrane disruption, associated with lipid dyshomeostasis-a notable Alzheimer's disease (AD) pathophysiological change. We assessed the association of cerebrospinal fluid (CSF) FABP3 levels with brain amyloidosis and the likelihood/risk of developing amyloidopathy in cognitively healthy individuals.

Methods

FABP3 levels were measured in CSF samples of cognitively healthy participants, > 60 years of age (n = 142), from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL).

Results

FABP3 levels were positively associated with baseline brain amyloid beta (Aβ) load as measured by standardized uptake value ratio (SUVR, standardized β = 0.22, P = .009) and predicted the change in brain Aβ load (standardized β = 0.32, P = .004). Higher levels of CSF FABP3 (above median) were associated with a likelihood of amyloidopathy (odds ratio [OR] 2.28, 95% confidence interval [CI] 1.12 to 4.65, P = .023).

Discussion

These results support inclusion of CSF FABP3 as a biomarker in risk-prediction models of AD.

The Alzheimer's Association appropriate use recommendations for blood biomarkers in Alzheimer's disease

Blood-based markers (BBMs) have recently shown promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD), as well as to improve the design of interventional trials. Here we discuss in detail further research needed to be performed before widespread use of BBMs. We already now recommend use of BBMs as (pre-)screeners to identify individuals likely to have AD pathological changes for inclusion in trials evaluating disease-modifying therapies, provided the AD status is confirmed with positron emission tomography (PET) or cerebrospinal fluid (CSF) testing. We also encourage studying longitudinal BBM changes in ongoing as well as future interventional trials. However, BBMs should not yet be used as primary endpoints in pivotal trials. Further, we recommend to cautiously start using BBMs in specialized memory clinics as part of the diagnostic work-up of patients with cognitive symptoms and the results should be confirmed whenever possible with CSF or PET. Additional data are needed before use of BBMs as stand-alone diagnostic AD markers, or before considering use in primary care.

Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer's trial selection and disease monitoring

Blood biomarkers indicative of Alzheimer's disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4-6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer's Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.

DNA methylation-based measures of biological aging and cognitive decline over 16-years: preliminary longitudinal findings in midlife

DNA methylation-based (DNAm) measures of biological aging associate with increased risk of morbidity and mortality, but their links with cognitive decline are less established. This study examined changes over a 16-year interval in epigenetic clocks (the traditional and principal components [PC]-based Horvath, Hannum, PhenoAge, GrimAge) and pace of aging measures (Dunedin PoAm, Dunedin PACE) in 48 midlife adults enrolled in the longitudinal arm of the Adult Health and Behavior project (56% Female, baseline AgeM = 44.7 years), selected for discrepant cognitive trajectories. Cognitive Decliners (N = 24) were selected based on declines in a composite score derived from neuropsychological tests and matched with participants who did not show any decline, Maintainers (N = 24). Multilevel models with repeated DNAm measures within person tested the main effects of time, group, and group by time interactions. DNAm measures significantly increased over time generally consistent with elapsed time between study visits. There were also group differences: overall, Cognitive Decliners had an older PC-GrimAge and faster pace of aging (Dunedin PoAm, Dunedin PACE) than Cognitive Maintainers. There were no significant group by time interactions, suggesting accelerated epigenetic aging in Decliners remained constant over time. Older PC-GrimAge and faster pace of aging may be particularly sensitive to cognitive decline in midlife.

Amyloid-associated increases in soluble tau relate to tau aggregation rates and cognitive decline in early Alzheimer's disease

For optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, we need to better understand the pathophysiological cascade of Aβ- and tau-related processes. Therefore, we set out to investigate how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with PET and subsequent cognitive decline across the Alzheimer's disease (AD) continuum. Using human cross-sectional and longitudinal neuroimaging and cognitive assessment data, we show that in early stages of AD, increased concentration of soluble CSF p-tau is strongly associated with accumulation of insoluble tau aggregates across the brain, and CSF p-tau levels mediate the effect of Aβ on tau aggregation. Further, higher soluble p-tau concentrations are mainly related to faster accumulation of tau aggregates in the regions with strong functional connectivity to individual tau epicenters. In this early stage, higher soluble p-tau concentrations is associated with cognitive decline, which is mediated by faster increase of tau aggregates. In contrast, in AD dementia, when Aβ fibrils and soluble p-tau levels have plateaued, cognitive decline is related to the accumulation rate of insoluble tau aggregates. Our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD, before widespread insoluble tau aggregates.

Axonal degeneration and amyloid pathology predict cognitive decline beyond cortical atrophy

BACKGROUND

Cortical atrophy is associated with cognitive decline, but the association is not perfect. We aimed to identify factors explaining the discrepancy between the degree of cortical atrophy and cognitive decline in cognitively unimpaired elderly.

METHODS

The discrepancy between atrophy and cognitive decline was measured using the residuals from a linear regression analysis between change in whole brain cortical thickness over time and change in a cognitive composite measure over time in 395 cognitively unimpaired participants from the Swedish BioFINDER study. We tested for bivariate associations of this residual measure with demographic, imaging, and fluid biomarker variables using Pearson correlations and independent-samples t-tests, and for multivariate associations using linear regression models. Mediation analyses were performed to explore possible paths between the included variables.

RESULTS

In bivariate analyses, older age (r = -0.11, p = 0.029), male sex (t = -3.00, p = 0.003), larger intracranial volume (r = -0.17, p < 0.001), carrying an APOEe4 allele (t = -2.71, p = 0.007), larger white matter lesion volume (r = -0.16, p = 0.002), lower cerebrospinal fluid (CSF) β-amyloid (Aβ) 42/40 ratio (t = -4.05, p < 0.001), and higher CSF levels of phosphorylated tau (p-tau) 181 (r = -0.22, p < 0.001), glial fibrillary acidic protein (GFAP; r = -0.15, p = 0.003), and neurofilament light (NfL; r = -0.34, p < 0.001) were negatively associated with the residual measure, i.e., associated with worse than expected cognitive trajectory given the level of atrophy. In a multivariate analysis, only lower CSF Aβ42/40 ratio and higher CSF NfL levels explained cognition beyond brain atrophy. Mediation analyses showed that associations between the residual measure and APOEe4 allele, CSF Aβ42/40 ratio, and CSF GFAP and p-tau181 levels were mediated by levels of CSF NfL, as were the associations with the residual measure for age, sex, and WML volume.

CONCLUSIONS

Our results suggest that axonal degeneration and amyloid pathology independently affect the rate of cognitive decline beyond the degree of cortical atrophy. Furthermore, axonal degeneration mediated the negative effects of old age, male sex, and white matter lesions, and in part also amyloid and tau pathology, on cognition over time when accounting for cortical atrophy.