Longitudinal normative standards for cognitive tests and composites using harmonized data from two Wisconsin AD-risk-enriched cohorts

INTRODUCTION

Published norms are typically cross-sectional and often are not sensitive to preclinical cognitive changes due to dementia. We developed and validated demographically adjusted cross-sectional and longitudinal normative standards using harmonized outcomes from two Alzheimer's disease (AD) risk-enriched cohorts.

METHODS

Data from the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center were combined. Quantile regression was used to develop unconditional (cross-sectional) and conditional (longitudinal) normative standards for 18 outcomes using data from cognitively unimpaired participants (N = 1390; mean follow-up = 9.25 years). Validity analyses (N = 2456) examined relationships between percentile scores (centiles), consensus-based cognitive statuses, and AD biomarker levels.

RESULTS

Unconditional and conditional centiles were lower in those with consensus-based impairment or biomarker positivity. Similarly, quantitative biomarker levels were higher in those whose centiles suggested decline.

DISCUSSION

This study presents normative standards for cognitive measures sensitive to pre-clinical changes. Future directions will investigate potential clinical applications of longitudinal normative standards.

HIGHLIGHTS

Quantile regression was used to construct longitudinal norms for cognitive tests. Poorer percentile scores were related to concurrent diagnosis and Alzheimer's disease biomarkers. A ShinyApp was built to display test scores and norms and flag low performance.

CSF Biomarkers in Longitudinal Alzheimer Disease Cohorts: Pre-Analytic Challenges

BACKGROUND

The sensitivity of amyloid to pre-analytic factors complicates cerebrospinal fluid (CSF) diagnostics for Alzheimer disease. We report reliability and validity evidence for automated immunoassays from frozen and fresh CSF samples in an ongoing, single-site research program.

METHODS

CSF samples were obtained from 2 Wisconsin cohorts (1256 measurements; 727 participants). Levels of amyloid beta 1-42 (Aβ42), phosphorylated tau 181 (pTau181), and total tau (tTau) were obtained using an Elecsys cobas e 601 platform. Repeatability and fixed effects of storage tube type, extraction method, and freezing were assessed via mixed models. Concordance with amyloid positron emission tomography (PET) was investigated with 238 participants having a temporally proximal PET scan.

RESULTS

Repeatability was high with intraclass correlation (ICC) ≥0.9, but tube type strongly affected measurements. Discriminative accuracy for PET amyloid positivity was strong across tube types (area under the curve [AUC]: Aβ42, 0.87; pTau181Aβ42 , 0.96), although optimal thresholds differed.

CONCLUSIONS

Under real-world conditions, the Elecsys platform had high repeatability. However, strong effects of pre-analytic factors suggest caution in drawing longitudinal inferences.

Relationships of Cognitive Measures with Cerebrospinal Fluid but Not Imaging Biomarkers of Alzheimer Disease Vary between Black and White Individuals

OBJECTIVE

Biomarkers of Alzheimer disease vary between groups of self-identified Black and White individuals in some studies. This study examined whether the relationships between biomarkers or between biomarkers and cognitive measures varied by racialized groups.

METHODS

Cerebrospinal fluid (CSF), amyloid positron emission tomography (PET), and magnetic resonance imaging measures were harmonized across four studies of memory and aging. Spearman correlations between biomarkers and between biomarkers and cognitive measures were calculated within each racialized group, then compared between groups by standard normal tests after Fisher's Z-transformations.

RESULTS

The harmonized dataset included at least one biomarker measurement from 495 Black and 2,600 White participants. The mean age was similar between racialized groups. However, Black participants were less likely to have cognitive impairment (28% vs 36%) and had less abnormality of some CSF biomarkers including CSF Aβ42/40, total tau, p-tau181, and neurofilament light. CSF Aβ42/40 was negatively correlated with total tau and p-tau181 in both groups, but at a smaller magnitude in Black individuals. CSF Aβ42/40, total tau, and p-tau181 had weaker correlations with cognitive measures, especially episodic memory, in Black than White participants. Correlations of amyloid measures between CSF (Aβ42/40, Aβ42) and PET imaging were also weaker in Black than White participants. Importantly, no differences based on race were found in correlations between different imaging biomarkers, or in correlations between imaging biomarkers and cognitive measures.

INTERPRETATION

Relationships between CSF biomarkers but not imaging biomarkers varied by racialized groups. Imaging biomarkers performed more consistently across racialized groups in associations with cognitive measures. ANN NEUROL 2024;95:495-506.

Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals

Importance

Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases.

Objective

To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories.

Design, Setting, and Participants

Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points.

Exposures

Individuals WODCI at baseline scan.

Main Outcomes and Measures

Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid β (Aβ), and future cognitive decline were assessed.

Results

In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aβ positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7).

Conclusions and Relevance

The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.

Unraveling diurnal and technical variability in cerebral hemodynamics from neurovascular 4D-Flow MRI

Neurovascular 4D-Flow MRI enables non-invasive evaluation of cerebral hemodynamics including measures of cerebral blood flow (CBF), vessel pulsatility index (PI), and cerebral pulse wave velocity (PWV). 4D-Flow measures have been linked to various neurovascular disorders including small vessel disease and Alzheimer's disease; however, physiological and technical sources of variability are not well established. Here, we characterized sources of diurnal physiological and technical variability in cerebral hemodynamics using 4D-Flow in a retrospective study of cognitively unimpaired older adults (N = 750) and a prospective study of younger adults (N = 10). Younger participants underwent repeated MRI sessions at 7am, 4 pm, and 10 pm. In the older cohort, having an MRI earlier on the day was significantly associated with higher CBF and lower PI. In prospective experiments, time of day significantly explained variability in CBF and PI; however, not in PWV. Test-retest experiments showed high CBF intra-session repeatability (repeatability coefficient (RPC) =7.2%), compared to lower diurnal repeatability (RPC = 40%). PI and PWV displayed similar intra-session and diurnal variability (PI intra-session RPC = 22%, RPC = 24% 7am vs 4 pm; PWV intra-session RPC = 17%, RPC = 21% 7am vs 4 pm). Overall, CBF measures showed low technical variability, supporting diurnal variability is from physiology. PI and PWV showed higher technical variability but less diurnal variability.

Whole genome methylation sequencing in blood identifies extensive differential DNA methylation in late-onset dementia due to Alzheimer's disease

INTRODUCTION

DNA microarray-based studies report differentially methylated positions (DMPs) in blood between late-onset dementia due to Alzheimer's disease (AD) and cognitively unimpaired individuals, but interrogate < 4% of the genome.

METHODS

We used whole genome methylation sequencing (WGMS) to quantify DNA methylation levels at 25,409,826 CpG loci in 281 blood samples from 108 AD and 173 cognitively unimpaired individuals.

RESULTS

WGMS identified 28,038 DMPs throughout the human methylome, including 2707 differentially methylated genes (e.g., SORCS3, GABA, and PICALM) encoding proteins in biological pathways relevant to AD such as synaptic membrane, cation channel complex, and glutamatergic synapse. One hundred seventy-three differentially methylated blood-specific enhancers interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.

DISCUSSION

WGMS identifies differentially methylated CpGs in known and newly detected genes and enhancers in blood from persons with and without AD.

HIGHLIGHTS

Whole genome DNA methylation levels were quantified in blood from persons with and without Alzheimer's disease (AD). Twenty-eight thousand thirty-eight differentially methylated positions (DMPs) were identified. Two thousand seven hundred seven genes comprise DMPs. Forty-eight of 75 independent genetic risk loci for AD have DMPs. One thousand five hundred sixty-eight blood-specific enhancers comprise DMPs, 173 of which interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.

A comparison of story-recall metrics to predict hippocampal volume in older adults with and without cognitive impairment

Objective: Process-based scores of episodic memory tests, such as the recency ratio (Rr), have been found to compare favourably to, or to be better than, most conventional or "traditional" scores employed to estimate memory ability in older individuals (Bock et al., 2021; Bruno et al., 2019). We explored the relationship between process-based scores and hippocampal volume in older adults, while comparing process-based to traditional story recall-derived scores, to examine potential differences in their predictive abilities. Methods: We analysed data from 355 participants extracted from the WRAP and WADRC databases, who were classified as cognitively unimpaired, or exhibited mild cognitive impairment (MCI) or dementia. Story Recall was measured with the Logical Memory Test (LMT) from the Weschler Memory Scale Revised, collected within twelve months of the magnetic resonance imaging scan. Linear regression analyses were conducted with left or right hippocampal volume (HV) as outcomes separately, and with Rr, Total ratio, Immediate LMT, or Delayed LMT scores as predictors, along with covariates. Results: Higher Rr and Tr scores significantly predicted lower left and right HV, while Tr showed the best model fit of all, as indicated by AIC. Traditional scores, Immediate LMT and Delayed LMT, were significantly associated with left and right HV, but were outperformed by both process-based scores for left HV, and by Tr for right HV. Conclusions: Current findings show the direct relationship between hippocampal volume and all the LMT scores examined here, and that process-based scores outperform traditional scores as markers of hippocampal volume.

Apolipoprotein E moderates the association between non-APOE polygenic risk score for Alzheimer's disease and aging on preclinical cognitive function

INTRODUCTION

Variation in preclinical cognitive decline suggests additional genetic factors related to Alzheimer's disease (eg, a non-APOE polygenic risk score [PRS]) may interact with the APOE ε4 allele to influence cognitive decline.

METHODS

We tested the PRS × APOE ε4 × age interaction on preclinical cognition using longitudinal data from the Wisconsin Registry for Alzheimer's Prevention. All analyses were fitted using a linear mixed-effects model and adjusted for within individual/family correlation among 1190 individuals.

RESULTS

We found statistically significant PRS × APOE ε4 × age interactions on immediate learning (P = 0.038), delayed recall (P < 0.001), and Preclinical Alzheimer's Cognitive Composite 3 score (P = 0.026). PRS-related differences in overall and memory-related cognitive domains between people with and without APOE ε4 emerge around age 70, with a much stronger adverse PRS effect among APOE ε4 carriers. The findings were replicated in a population-based cohort.

DISCUSSIONS

APOE ε4 can modify the association between PRS and cognition decline.

HIGHLIGHTS

APOE ε4 can modify the association between polygenic risk scores (PRSs) and longitudinal cognition decline, with the modifying effects more pronounced when the PRS is constructed using a conservative P threshold (eg, P < 5e-8 ). The adverse genetic effect caused by the combined effect of the currently known genetic variants is more detrimental among APOE ε4 carriers around age 70. Individuals who are APOE ε4 carriers with high PRSs are the most vulnerable to the harmful effects caused by genetic burden.

Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans

STUDY OBJECTIVES

Given the established racial disparities in both sleep health and dementia risk for African American populations, we assess cross-sectional and longitudinal associations of self-report sleep duration (SRSD) and daytime sleepiness with plasma amyloid beta (Aβ) and cognition in an African American (AA) cohort.

METHODS

In a cognitively unimpaired sample drawn from the African Americans Fighting Alzheimer's in Midlife (AA-FAiM) study, data on SRSD, Epworth Sleepiness Scale, demographics, and cognitive performance were analyzed. Aβ40, Aβ42, and the Aβ42/40 ratio were quantified from plasma samples. Cross-sectional analyses explored associations between baseline predictors and outcome measures. Linear mixed-effect regression models estimated associations of SRSD and daytime sleepiness with plasma Aβ and cognitive performance levels and change over time.

RESULTS

One hundred and forty-seven participants comprised the cross-sectional sample. Baseline age was 63.2 ± 8.51 years. 69.6% self-identified as female. SRSD was 6.4 ± 1.1 hours and 22.4% reported excessive daytime sleepiness. The longitudinal dataset included 57 participants. In fully adjusted models, neither SRSD nor daytime sleepiness is associated with cross-sectional or longitudinal Aβ. Associations with level and trajectory of cognitive test performance varied by measure of sleep health.

CONCLUSIONS

SRSD was below National Sleep Foundation recommendations and daytime sleepiness was prevalent in this cohort. In the absence of observed associations with plasma Aβ, poorer self-reported sleep health broadly predicted poorer cognitive function but not accelerated decline. Future research is necessary to understand and address modifiable sleep mechanisms as they relate to cognitive aging in AA at disproportionate risk for dementia.

CLINICAL TRIAL INFORMATION

Not applicable.

Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes.

Elevated CSF angiopoietin-2 correlates with blood-brain barrier leakiness and markers of neuronal injury in early Alzheimer's disease

Breakdown of the neurovascular unit is associated with blood-brain barrier (BBB) leakiness contributing to cognitive decline and disease pathology in the early stages of Alzheimer's disease (AD). Vascular stability depends on angiopoietin-1 (ANGPT-1) signalling, antagonised by angiopoietin-2 (ANGPT-2) expressed upon endothelial injury. We examined the relationship between CSF ANGPT-2 and CSF markers of BBB leakiness and core AD biomarkers across three independent cohorts: (i) 31 AD patients and 33 healthy controls grouped according to their biomarker profile (i.e., AD cases t-tau > 400 pg/mL, p-tau > 60 pg/mL and Aβ42 < 550 pg/mL); (ii) 121 participants in the Wisconsin Registry for Alzheimer's Prevention or Wisconsin Alzheimer's Disease Research study (84 participants cognitively unimpaired (CU) enriched for a parental history of AD, 20 participants with mild cognitive impairment (MCI), and 17 with AD); (iii) a neurologically normal cohort aged 23-78 years with paired CSF and serum samples. CSF ANGPT-2, sPDGFRβ, albumin and fibrinogen levels were measured by sandwich ELISA. In cohort (i), CSF ANGPT-2 was elevated in AD and correlated with CSF t-tau and p-tau181 but not Aβ42. ANGPT-2 also correlated positively with CSF sPDGFRβ and fibrinogen - markers of pericyte injury and BBB leakiness. In cohort (ii), CSF ANGPT-2 was highest in MCI and correlated with CSF albumin in the CU and MCI cohorts but not in AD. CSF ANGPT-2 also correlated with CSF t-tau and p-tau and with markers of neuronal injury (neurogranin and α-synuclein) and neuroinflammation (GFAP and YKL-40). In cohort (iii), CSF ANGPT-2 correlated strongly with the CSF/serum albumin ratio. Serum ANGPT-2 showed non-significant positive associations with CSF ANGPT-2 and the CSF/serum albumin ratio. Together, these data indicate that CSF and possibly serum ANGPT-2 is associated with BBB leakiness in early AD and is closely related to tau pathology and neuronal injury. The utility of serum ANGPT-2 as a biomarker of BBB damage in AD requires further study.

Characterizing the emergence of amyloid and tau burden in Down syndrome

INTRODUCTION

Almost all individuals with Down syndrome (DS) will develop neuropathological features of Alzheimer's disease (AD). Understanding AD biomarker trajectories is necessary for DS-specific clinical interventions and interpretation of drug-related changes in the disease trajectory.

METHODS

A total of 177 adults with DS from the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) underwent positron emission tomography (PET) and MR imaging. Amyloid-beta (Aβ) trajectories were modeled to provide individual-level estimates of Aβ-positive (A+) chronicity, which were compared against longitudinal tau change.

RESULTS

Elevated tau was observed in all NFT regions following A+ and longitudinal tau increased with respect to A+ chronicity. Tau increases in NFT regions I-III was observed 0-2.5 years following A+. Nearly all A+ individuals had tau increases in the medial temporal lobe.

DISCUSSION

These findings highlight the rapid accumulation of amyloid and early onset of tau relative to amyloid in DS and provide a strategy for temporally characterizing AD neuropathology progression that is specific to the DS population and independent of chronological age.

HIGHLIGHTS

Longitudinal amyloid trajectories reveal rapid Aβ accumulation in Down syndrome NFT stage tau was strongly associated with A+ chronicity Early longitudinal tau increases were observed 2.5-5 years after reaching A.

Associations between recall of proper names in story recall and CSF amyloid and tau in adults without cognitive impairment

Neuropsychological measures sensitive to decline in the preclinical phase of Alzheimer's disease are needed. We previously demonstrated that higher amyloid-beta (Aβ) assessed by positron emission tomography in adults without cognitive impairment was associated with recall of fewer proper names in Logical Memory story recall. The current study investigated the association between proper names and cerebrospinal fluid biomarkers (Aβ42/40, phosphorylated tau181 [pTau181], neurofilament light) in 223 participants from the Wisconsin Registry for Alzheimer's Prevention. We assessed associations between biomarkers and delayed Logical Memory total score and proper names using binary logistic regressions. Sensitivity analyses used multinomial logistic regression and stratified biomarker groups. Lower Logical Memory total score and proper names scores from the most recent visit were associated with biomarker positivity. Relatedly, there was a 27% decreased risk of being classified Aβ42/40+/pTau181+ for each additional proper name recalled. A linear mixed effects model found that longitudinal change in proper names recall was predicted by biomarker status. These results demonstrate a novel relationship between proper names and Alzheimer's disease-cerebrospinal fluid pathology.

Midlife sensory and motor functions improve long-term predictions of cognitive decline and incidence of cognitive impairment

INTRODUCTION

We aimed to assess whether midlife sensory and motor functions improve risk prediction of 10-year cognitive decline and impairment when added to risk prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS).

METHODS

Longitudinal data of N = 1529 (mean age 49 years; 54% women) Beaver Dam Offspring Study (BOSS) participants from baseline, 5 and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function improves CAIDE or FRS risk predictions of 10-year cognitive decline or cognitive impairment incidence using logistic regressions.

RESULTS

Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved areas under the curve for cognitive decline and impairment models.

DISCUSSION

Including midlife sensory and motor function improved risk predictions of long-term cognitive decline and impairment in middle-aged to older adults. Sensory and motor assessments could contribute to cost-effective and non-invasive screening tools that identify high-risk individuals earlier to target intervention and prevention strategies.

Highlights

Sensory and motor measures improve risk prediction models of cognitive decline.Sensory and motor measures improve risk prediction models of cognitive impairment.Prediction improvements were strongest in midlife (adults < 55 years of age).Sensory and motor changes may help identify high-risk individuals early.

Midlife sensory and motor functions improve prediction of blood-based measures of neurodegeneration and Alzheimer's disease in late middle-age

INTRODUCTION

We assessed whether midlife sensory and motor functions added to prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS) improve risk predictions of 10-year changes in biomarkers of neurodegeneration and Alzheimer's disease.

METHODS

Longitudinal data of N = 1529 (mean age 49years) Beaver Dam Offspring Study participants from baseline, 5-year, and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function measures improves CAIDE or FRS risk predictions of 10-year incidence of biomarker positivity of serum-based neurofilament light chain (NfL) and amyloid beta (Aβ)42/Aβ40 using logistic regression.

RESULTS

Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved NfL and Aβ42/Aβ40 positivity predictions in adults above the age of 55.

DISCUSSION

Including midlife sensory and motor function improved long-term biomarker positivity predictions. Non-invasive sensory and motor assessments could contribute to cost-effective screening tools that identify individuals at risk for neurodegeneration early to target interventions and preventions.

Highlights

Sensory and motor measures improve risk prediction models of neurodegenerative biomarkersSensory and motor measures improve risk prediction models of AD biomarkersPrediction improvements were strongest in late midlife (adults >55 years of age)Sensory and motor assessments may help identify high-risk individuals early.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

Genomic loci influence patterns of structural covariance in the human brain

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities

Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow.

Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors

Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.

Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease

INTRODUCTION

A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest.

METHODS

We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n = 137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation.

RESULTS

We identified 61 proteins significantly associated with the AT category (P < 5.46 × 10-5 ) and 636 significant protein-biomarker associations (P < 6.07 × 10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n = 717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers.

DISCUSSION

These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD.

HIGHLIGHTS

Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.

Assessing the Biological Mechanisms Linking Smoking Behavior and Cognitive Function: A Mediation Analysis of Untargeted Metabolomics

(1) Smoking is the most significant preventable health hazard in the modern world. It increases the risk of vascular problems, which are also risk factors for dementia. In addition, toxins in cigarettes increase oxidative stress and inflammation, which have both been linked to the development of Alzheimer's disease and related dementias (ADRD). This study identified potential mechanisms of the smoking-cognitive function relationship using metabolomics data from the longitudinal Wisconsin Registry for Alzheimer's Prevention (WRAP). (2) 1266 WRAP participants were included to assess the association between smoking status and four cognitive composite scores. Next, untargeted metabolomic data were used to assess the relationships between smoking and metabolites. Metabolites significantly associated with smoking were then tested for association with cognitive composite scores. Total effect models and mediation models were used to explore the role of metabolites in smoking-cognitive function pathways. (3) Plasma N-acetylneuraminate was associated with smoking status Preclinical Alzheimer Cognitive Composite 3 (PACC3) and Immediate Learning (IMM). N-acetylneuraminate mediated 12% of the smoking-PACC3 relationship and 13% of the smoking-IMM relationship. (4) These findings provide links between previous studies that can enhance our understanding of potential biological pathways between smoking and cognitive function.

Gut inflammation associated with age and Alzheimer's disease pathology: a human cohort study

Age-related disease may be mediated by low levels of chronic inflammation ("inflammaging"). Recent work suggests that gut microbes can contribute to inflammation via degradation of the intestinal barrier. While aging and age-related diseases including Alzheimer's disease (AD) are linked to altered microbiome composition and higher levels of gut microbial components in systemic circulation, the role of intestinal inflammation remains unclear. To investigate whether greater gut inflammation is associated with advanced age and AD pathology, we assessed fecal samples from older adults to measure calprotectin, an established marker of intestinal inflammation which is elevated in diseases of gut barrier integrity. Multiple regression with maximum likelihood estimation and Satorra-Bentler corrections were used to test relationships between fecal calprotectin and clinical diagnosis, participant age, cerebrospinal fluid biomarkers of AD pathology, amyloid burden measured using 11C-Pittsburgh compound B positron emission tomography (PiB PET) imaging, and performance on cognitive tests measuring executive function and verbal learning and recall. Calprotectin levels were elevated in advanced age and were higher in participants diagnosed with amyloid-confirmed AD dementia. Additionally, among individuals with AD dementia, higher calprotectin was associated with greater amyloid burden as measured with PiB PET. Exploratory analyses indicated that calprotectin levels were also associated with cerebrospinal fluid markers of AD, and with lower verbal memory function even among cognitively unimpaired participants. Taken together, these findings suggest that intestinal inflammation is linked with brain pathology even in the earliest disease stages. Moreover, intestinal inflammation may exacerbate the progression toward AD.

Comparison of the 10-, 14- and 20-Item CES-D Scores as Predictors of Cognitive Decline

The association between depressive symptomatology and cognitive decline has been examined using the Centre for Epidemiologic Studies-Depression Scale (CES-D); however, concerns have been raised about this self-report measure. Here, we examined how the CES-D total score from the 14- and 10-item versions compared to the 20-item version in predicting progression to cognitive decline from a cognitively unimpaired baseline. Data from 1054 participants were analysed using ordinal logistic regression, alongside moderator and receiver-operating characteristics curve analyses. All baseline total scores significantly predicted progression to cognitive decline. The 14-item version was better than the 20-item version in predicting consensus diagnosis, as shown by their AICs, while also showing the highest accuracy when discriminating between participants by diagnosis at last visit. We did not find sex to moderate the relationship between CES-D score and cognitive decline. Current findings suggest the 10- and 14-item versions of the CES-D are comparable to the 20-item version, and that the 14-item version may be better at predicting longitudinal consensus diagnosis compared to the 20-item version.

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

BACKGROUND

Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical.

METHODS

Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination).

RESULTS

Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone.

CONCLUSION

Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.

A comparison of diagnostic performance of word-list and story recall tests for biomarker-determined Alzheimer's disease

BACKGROUND

Wordlist and story recall tests are routinely employed in clinical practice for dementia diagnosis. In this study, our aim was to establish how well-standard clinical metrics compared to process scores derived from wordlist and story recall tests in predicting biomarker determined Alzheimer's disease, as defined by CSF ptau/Aβ42 ratio.

METHODS

Data from 295 participants (mean age = 65 ± 9.) were drawn from the University of Wisconsin - Madison Alzheimer's Disease Research Center (ADRC) and Wisconsin Registry for Alzheimer's Prevention (WRAP). Rey's Auditory Verbal Learning Test (AVLT; wordlist) and Logical Memory Test (LMT; story) data were used. Bayesian linear regression analyses were carried out with CSF ptau/Aβ42 ratio as outcome. Sensitivity analyses were carried out with logistic regressions to assess diagnosticity.

RESULTS

LMT generally outperformed AVLT. Notably, the best predictors were primacy ratio, a process score indexing loss of information learned early during test administration, and recency ratio, which tracks loss of recently learned information. Sensitivity analyses confirmed this conclusion.

CONCLUSIONS

Our study shows that story recall tests may be better than wordlist tests for detection of dementia, especially when employing process scores alongside conventional clinical scores.

Cross-sectional associations of CSF tau levels with Rey's AVLT: A recency ratio study

OBJECTIVE

The preeminent in vivo cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are amyloid β 1-42 (Aβ42), phosphorylated Tau (p-tau), and total Tau (t-tau). The goal of this study was to examine how well traditional (total and delayed recall) and process-based (recency ratio [Rr]) measures derived from Rey's Auditory Verbal Learning test (AVLT) were associated with these biomarkers.

METHOD

Data from 235 participants (Mage = 65.5, SD = 6.9), who ranged from cognitively unimpaired to mild cognitive impairment, and for whom CSF values were available, were extracted from the Wisconsin Registry for Alzheimer's Prevention. Bayesian regression analyses were carried out using CSF scores as outcomes, AVLT scores as predictors, and controlling for demographic data and diagnosis.

RESULTS

We found moderate evidence that Rr was associated with both CSF p-tau (Bayesian factor [BFM] = 5.55) and t-tau (BFM = 7.28), above and beyond the control variables, while it did not correlate with CSF Aβ42 levels. In contrast, total and delayed recall scores were not linked with any of the AD biomarkers, in separate analyses. When comparing all memory predictors in a single regression, Rr remained the strongest predictor of CSF t-tau levels (BFM = 3.57).

CONCLUSIONS

Our findings suggest that Rr may be a better cognitive measure than commonly used AVLT scores to assess CSF levels of p-tau and t-tau in nondemented individuals. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

CSF metabolites associated with biomarkers of Alzheimer's disease pathology

Introduction

Metabolomics technology facilitates studying associations between small molecules and disease processes. Correlating metabolites in cerebrospinal fluid (CSF) with Alzheimer's disease (AD) CSF biomarkers may elucidate additional changes that are associated with early AD pathology and enhance our knowledge of the disease.

Methods

The relative abundance of untargeted metabolites was assessed in 161 individuals from the Wisconsin Registry for Alzheimer's Prevention. A metabolome-wide association study (MWAS) was conducted between 269 CSF metabolites and protein biomarkers reflecting brain amyloidosis, tau pathology, neuronal and synaptic degeneration, and astrocyte or microglial activation and neuroinflammation. Linear mixed-effects regression analyses were performed with random intercepts for sample relatedness and repeated measurements and fixed effects for age, sex, and years of education. The metabolome-wide significance was determined by a false discovery rate threshold of 0.05. The significant metabolites were replicated in 154 independent individuals from then Wisconsin Alzheimer's Disease Research Center. Mendelian randomization was performed using genome-wide significant single nucleotide polymorphisms from a CSF metabolites genome-wide association study.

Results

Metabolome-wide association study results showed several significantly associated metabolites for all the biomarkers except Aβ42/40 and IL-6. Genetic variants associated with metabolites and Mendelian randomization analysis provided evidence for a causal association of metabolites for soluble triggering receptor expressed on myeloid cells 2 (sTREM2), amyloid β (Aβ40), α-synuclein, total tau, phosphorylated tau, and neurogranin, for example, palmitoyl sphingomyelin (d18:1/16:0) for sTREM2, and erythritol for Aβ40 and α-synuclein.

Discussion

This study provides evidence that CSF metabolites are associated with AD-related pathology, and many of these associations may be causal.

Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk

INTRODUCTION

Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes.

METHODS

We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants.

DISCUSSION

The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses.

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.

Optimal combinations of CSF biomarkers for predicting cognitive decline and clinical conversion in cognitively unimpaired participants and mild cognitive impairment patients: A multi-cohort study

INTRODUCTION

Our objective was determining the optimal combinations of cerebrospinal fluid (CSF) biomarkers for predicting disease progression in Alzheimer's disease (AD) and other neurodegenerative diseases.

METHODS

We included 1,983 participants from three different cohorts with longitudinal cognitive and clinical data, and baseline CSF levels of Aβ42, Aβ40, phosphorylated tau at threonine-181 (p-tau), neurofilament light (NfL), neurogranin, α-synuclein, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), glial fibrillary acidic protein (GFAP), YKL-40, S100b, and interleukin 6 (IL-6) (Elecsys NeuroToolKit).

RESULTS

Change of modified Preclinical Alzheimer's Cognitive Composite (mPACC) in cognitively unimpaired (CU) was best predicted by p-tau/Aβ42 alone (R2 ≥ 0.31) or together with NfL (R2  = 0.25), while p-tau/Aβ42 (R2 ≥ 0.19) was sufficient to accurately predict change of the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) patients. P-tau/Aβ42 (AUC ≥ 0.87) and p-tau/Aβ42 together with NfL (AUC ≥ 0.75) were the best predictors of conversion to AD and all-cause dementia, respectively.

DISCUSSION

P-tau/Aβ42 is sufficient for predicting progression in AD, with very high accuracy. Adding NfL improves the prediction of all-cause dementia conversion and cognitive decline.

Cognitive trajectories diverge by genetic risk in a preclinical longitudinal cohort

INTRODUCTION

We sought to characterize the timing of changes in cognitive trajectories related to genetic risk using the apolipoprotein E (APOE) score, a continuous measure of Alzheimer's disease (AD) risk. We also aimed to determine whether that timing was different when genetic risk was measured using an AD polygenic risk score (PRS) that contains APOE.

METHODS

We analyzed trajectories (N ≈1135) for four neuropsychological composite scores using mixed effects regression for longitudinal change across APOE scores and PRS of participants in the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults aged 40 to 70 at baseline, with a median participant follow-up time of 7.8 years.

RESULTS

We found a significant non-linear age-by-APOE score interaction in predicting cognitive decline. Cognitive trajectories diverged by APOE score at approximately 65 years of age. A 0.5 standard deviation difference in cognition between extreme percentiles of the PRS was predicted to occur 1 to 2 years before that of the APOE score.

DISCUSSION

Cognitive decline differs across time and APOE score. Estimates did not substantially shift with the AD PRS.

HIGHLIGHTS

The apolipoprotein E (APOE) score, a continuous measure, accounts for non-linear genetic risk of Alzheimer's disease. Non-linear age interacts with the APOE score to affect cognition. Cognitive decline starts to differ by APOE score levels at approximately age 65. Cognitive decline timing by polygenic risk (including APOE) is similar to APOE alone.

Feasibility of virtual Alzheimer's biomarker disclosure: Findings from an observational cohort

Introduction

Increased availability of Alzheimer's disease (AD) biomarker tests provides older adults with opportunities to seek out and learn results. We evaluated the feasibility of virtually returning AD biomarker results.

Methods

Trained study clinicians disclosed amyloid positron emission tomography (PET) results and provided dementia risk-reduction counseling via televideo to cognitively unimpaired participants already enrolled in AD research (n = 99; mean age ± SD: 72.0 ± 4.8; 67% women; 95% White; 28% amyloid elevated).

Results

Our study demonstrated acceptable levels of retention (93%), compliance (98%), adherence (98%), clinician competence (97%), education comprehension (quiz scores 14/15), and virtual visit functionality (rating 9.4/10). Depression, anxiety, and suicidality remained low and did not differ by amyloid result.

Discussion

Virtual return of amyloid PET results to cognitively unimpaired research participants is feasible and does not result in increased psychological symptoms. Technological barriers for some participants highlight the need for flexibility. These findings support the use of televideo in AD biomarker disclosure, although our study sample and design have important limitations for generalizability.

Plasma Aβ42/40 and cognitive variability are associated with cognitive function in Black Americans: Findings from the AA-FAIM cohort

Introduction

It is critical to develop more inclusive Alzheimer's disease (AD) research protocols to ensure that historically excluded groups are included in preclinical research and have access to timely diagnosis and treatment. If validated in racialized groups, plasma AD biomarkers and measures of subtle cognitive dysfunction could provide avenues to expand diversity in preclinical AD research. We sought to evaluate the utility of two easily obtained, low-burden disease markers, plasma amyloid beta (Aβ)42/40, and intra-individual cognitive variability (IICV), to predict concurrent and longitudinal cognitive performance in a sample of Black adults.

Methods

Two hundred fifty-seven Black participants enrolled in the African Americans Fighting Alzheimer's in Midlife (AA-FAIM) study underwent at least one cognitive assessment visit; a subset of n = 235 had plasma samples. Baseline IICV was calculated as the standard deviation across participants' z scores on five cognitive measures: Rey Auditory Verbal Learning Test Delayed Recall, Trail Making Test Parts A and B (Trails A and B), and Boston Naming Test. Using mixed effects regression models, we compared concurrent and longitudinal models to baseline plasma Aβ42/40 or IICV by age interactions. PrecivityAD assays quantified baseline plasma Aβ42/40.

Results

IICV was associated with concurrent/baseline performance on several outcomes but did not modify associations between age and cognitive decline. In contrast, plasma Aβ42/40 was unrelated to baseline cognitive performance, but a pattern emerged in interactions with age in longitudinal models of Trails A and B and Rey Auditory Verbal Learning Test total learning trials. Although not significant after correcting for multiple comparisons, low Aβ42/40 was associated with faster cognitive declines over time.

Discussion

Our results are promising as they extend existing findings to an Black American sample using low-cost, low-burden methods that can be implemented outside of a research center, thus supporting efforts for inclusive AD biomarker research.

Apolipoprotein E moderates the association between Non-APOE Polygenic Risk Score for Alzheimer's Disease and Aging on Preclinical Cognitive Function

INTRODUCTION

Variation in preclinical cognitive decline suggests additional genetic factors related to Alzheimer's disease (e.g., a non-APOE polygenic risk scores [PRS]) may interact with the APOE ε4 allele to influence cognitive decline.

METHODS

We tested the PRS×APOE ε4×age interaction on preclinical cognition using longitudinal data from the Wisconsin Registry for Alzheimer's Prevention. All analyses were fitted using a linear mixed-effects model and adjusted for within individual/family correlation among 1,190 individuals.

RESULTS

We found statistically significant PRS×APOE ε4×age interactions on immediate learning (P=0.038), delayed recall (P<0.001), and Preclinical Alzheimer's Cognitive Composite 3 score (P=0.026). PRS-related differences in overall and memory-related cognitive domains between people with and without APOE ε4 emerge around age 70, with a much stronger adverse PRS effect among APOE ε4 carriers. The findings were replicated in a population-based cohort.

DISCUSSION

APOE ε4 can modify the association between PRS and cognition decline.

Cerebral hemodynamics comparison using transcranial doppler ultrasound and 4D flow MRI

Introduction: Age-related changes in cerebral hemodynamics are controversial and discrepancies may be due to experimental techniques. As such, the purpose of this study was to compare cerebral hemodynamics measurements of the middle cerebral artery (MCA) between transcranial Doppler ultrasound (TCD) and four-dimensional flow MRI (4D flow MRI). Methods: Twenty young (25 ± 3 years) and 19 older (62 ± 6 years) participants underwent two randomized study visits to evaluate hemodynamics at baseline (normocapnia) and in response to stepped hypercapnia (4% CO₂, and 6% CO₂) using TCD and 4D flow MRI. Cerebral hemodynamic measures included MCA velocity, MCA flow, cerebral pulsatility index (PI) and cerebrovascular reactivity to hypercapnia. MCA flow was only assessed using 4D flow MRI. Results: MCA velocity between the TCD and 4D flow MRI methods was positively correlated across the normocapnia and hypercapnia conditions (r = 0.262; p = 0.004). Additionally, cerebral PI was significantly correlated between TCD and 4D flow MRI across the conditions (r = 0.236; p = 0.010). However, there was no significant association between MCA velocity using TCD and MCA flow using 4D flow MRI across the conditions (r = 0.079; p = 0.397). When age-associated differences in cerebrovascular reactivity using conductance were compared using both methodologies, cerebrovascular reactivity was greater in young adults compared to older adults when using 4D flow MRI (2.11 ± 1.68 mL/min/mmHg/mmHg vs. 0.78 ± 1.68 mL/min/mmHg/mmHg; p = 0.019), but not with TCD (0.88 ± 1.01 cm/s/mmHg/mmHg vs. 0.68 ± 0.94 cm/s/mmHg/mmHg; p = 0.513). Conclusion: Our results demonstrated good agreement between the methods at measuring MCA velocity during normocapnia and in response to hypercapnia, but MCA velocity and MCA flow were not related. In addition, measurements using 4D flow MRI revealed effects of aging on cerebral hemodynamics that were not apparent using TCD.

Normative Cerebral Hemodynamics in Middle-aged and Older Adults Using 4D Flow MRI: Initial Analysis of Vascular Aging

Background Characterizing cerebrovascular hemodynamics in older adults is important for identifying disease and understanding normal neurovascular aging. Four-dimensional (4D) flow MRI allows for a comprehensive assessment of cerebral hemodynamics in a single acquisition. Purpose To establish reference intracranial blood flow and pulsatility index values in a large cross-sectional sample of middle-aged (45-65 years) and older (>65 years) adults and characterize the effect of age and sex on blood flow and pulsatility. Materials and Methods In this retrospective study, patients aged 45-93 years (cognitively unimpaired) underwent cranial 4D flow MRI between March 2010 and March 2020. Blood flow rates and pulsatility indexes from 13 major arteries and four venous sinuses and total cerebral blood flow were collected. Intraobserver and interobserver reproducibility of flow and pulsatility measures was assessed in 30 patients. Descriptive statistics (mean ± SD) of blood flow and pulsatility were tabulated for the entire group and by age and sex. Multiple linear regression and linear mixed-effects models were used to assess the effect of age and sex on total cerebral blood flow and vessel-specific flow and pulsatility, respectively. Results There were 759 patients (mean age, 65 years ± 8 [SD]; 506 female patients) analyzed. For intra- and interobserver reproducibility, median intraclass correlation coefficients were greater than 0.90 for flow and pulsatility measures across all vessels. Regression coefficients β ± standard error from multiple linear regression showed a 4 mL/min decrease in total cerebral blood flow each year (age β = -3.94 mL/min per year ± 0.44; P < .001). Mixed effects showed a 1 mL/min average annual decrease in blood flow (age β = -0.95 mL/min per year ± 0.16; P < .001) and 0.01 arbitrary unit (au) average annual increase in pulsatility over all vessels (age β = 0.011 au per year ± 0.001; P < .001). No evidence of sex differences was observed for flow (β = -1.60 mL/min per male patient ± 1.77; P = .37), but pulsatility was higher in female patients (sex β = -0.018 au per male patient ± 0.008; P = .02). Conclusion Normal reference values for blood flow and pulsatility obtained using four-dimensional flow MRI showed correlations with age. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Steinman in this issue.

Association of Age at Menopause and Hormone Therapy Use With Tau and β-Amyloid Positron Emission Tomography

Importance

Postmenopausal females represent around 70% of all individuals with Alzheimer disease. Previous literature shows elevated levels of tau in cognitively unimpaired postmenopausal females compared with age-matched males, particularly in the setting of high β-amyloid (Aβ). The biological mechanisms associated with higher tau deposition in female individuals remain elusive.

Objective

To examine the extent to which sex, age at menopause, and hormone therapy (HT) use are associated with regional tau at a given level of Aβ, both measured with positron emission tomography (PET).

Design, Setting, and Participants

This cross-sectional study included participants enrolled in the Wisconsin Registry for Alzheimer Prevention. Cognitively unimpaired males and females with at least 1 18F-MK-6240 and 11C-Pittsburgh compound B PET scan were analyzed. Data were collected between November 2006 and May 2021.

Exposures

Premature menopause (menopause at younger than 40 years), early menopause (menopause at age 40-45 years), and regular menopause (menopause at older than 45 years) and HT user (current/past use) and HT nonuser (no current/past use). Exposures were self-reported.

Main Outcomes and Measures

Seven tau PET regions that show sex differences across temporal, parietal, and occipital lobes. Primary analyses examined the interaction of sex, age at menopause or HT, and Aβ PET on regional tau PET in a series of linear regressions. Secondary analyses investigated the influence of HT timing in association with age at menopause on regional tau PET.

Results

Of 292 cognitively unimpaired individuals, there were 193 females (66.1%) and 99 males (33.9%). The mean (range) age at tau scan was 67 (49-80) years, 52 (19%) had abnormal Aβ, and 106 (36.3%) were APOEε4 carriers. There were 98 female HT users (52.2%) (past/current). Female sex (standardized β = -0.41; 95% CI, -0.97 to -0.32; P < .001), earlier age at menopause (standardized β = -0.38; 95% CI, -0.14 to -0.09; P < .001), and HT use (standardized β = 0.31; 95% CI, 0.40-1.20; P = .008) were associated with higher regional tau PET in individuals with elevated Aβ compared with male sex, later age at menopause, and HT nonuse. Affected regions included medial and lateral regions of the temporal and occipital lobes. Late initiation of HT (>5 years following age at menopause) was associated with higher tau PET compared with early initiation (β = 0.49; 95% CI, 0.27-0.43; P = .001).

Conclusions and Relevance

In this study, females exhibited higher tau compared with age-matched males, particularly in the setting of elevated Aβ. In females, earlier age at menopause and late initiation of HT were associated with increased tau vulnerability especially when neocortical Aβ elevated. These observational findings suggest that subgroups of female individuals may be at higher risk of pathological burden.

Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer's disease pathology

Modifiable factors can influence the risk for Alzheimer's disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer's prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologies for AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.

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.

Incidental Findings from 16,400 Brain MRI Examinations of Research Volunteers

BACKGROUND AND PURPOSE

Incidental findings are discovered in neuroimaging research, ranging from trivial to life-threatening. We describe the prevalence and characteristics of incidental findings from 16,400 research brain MRIs, comparing spontaneous detection by nonradiology scanning staff versus formal neuroradiologist interpretation.

MATERIALS AND METHODS

We prospectively collected 16,400 brain MRIs (7782 males, 8618 females; younger than 1 to 94 years of age; median age, 38 years) under an institutional review board directive intended to identify clinically relevant incidental findings. The study population included 13,150 presumed healthy volunteers and 3250 individuals with known neurologic diagnoses. Scanning staff were asked to flag concerning imaging findings seen during the scan session, and neuroradiologists produced structured reports after reviewing every scan.

RESULTS

Neuroradiologists reported 13,593/16,400 (83%) scans as having normal findings, 2193/16,400 (13.3%) with abnormal findings without follow-up recommended, and 614/16,400 (3.7%) with "abnormal findings with follow-up recommended." The most common abnormalities prompting follow-up were vascular (263/614, 43%), neoplastic (130/614, 21%), and congenital (92/614, 15%). Volunteers older than 65 years of age were significantly more likely to have scans with abnormal findings (P < .001); however, among all volunteers with incidental findings, those younger than 65 years of age were more likely to be recommended for follow-up. Nonradiologists flagged <1% of MRIs containing at least 1 abnormality reported by the neuroradiologists to be concerning enough to warrant further evaluation.

CONCLUSIONS

Four percent of individuals who undergo research brain MRIs have an incidental, potentially clinically significant finding. Routine neuroradiologist review of all scans yields a much higher rate of significant lesion detection than selective referral from nonradiologists who perform the examinations. Workflow and scan review processes need to be carefully considered when designing research protocols.

The relationship of insulin resistance and diabetes to tau PET SUVR in middle-aged to older adults

BACKGROUND

Insulin resistance (IR) and type 2 diabetes have been found to increase the risk for Alzheimer's clinical syndrome in epidemiologic studies but have not been associated with tau tangles in neuropathological research and have been inconsistently associated with cerebrospinal fluid P-tau181. IR and type 2 diabetes are well-recognized vascular risk factors. Some studies suggest that cardiovascular risk may act synergistically with cortical amyloid to increase tau measured using tau PET. Utilizing data from largely nondemented middle-aged and older adult cohorts enriched for AD risk, we investigated the association of IR and diabetes to tau PET and whether amyloid moderated those relationships.

METHODS

Participants were enrolled in either the Wisconsin Registry for Alzheimer's Prevention (WRAP) or Wisconsin Alzheimer's Disease Research Center (WI-ADRC) Clinical Core. Two partially overlapping samples were studied: a sample characterized using HOMA-IR (n=280 WRAP participants) and a sample characterized on diabetic status (n=285 WRAP and n=109 WI-ADRC). IR was measured using the homeostasis model assessment of insulin resistance (HOMA-IR). Tau PET employing the radioligand 18F-MK-6240 was used to detect AD-specific aggregated tau. Linear regression tested the relationship of IR and diabetic status to tau PET standardized uptake value ratio (SUVR) within the entorhinal cortex and whether relationships were moderated by amyloid assessed by amyloid PET distribution volume ratio (DVR) and amyloid PET positivity status.

RESULTS

Neither HOMA-IR nor diabetic status was significantly associated with tau PET SUVR. The relationship between IR and tau PET SUVR was not moderated by amyloid PET DVR or positivity status. The association between diabetic status and tau PET SUVR was not significantly moderated by amyloid PET DVR but was significantly moderated by amyloid PET positivity status. Among the amyloid PET-positive participants, the estimated marginal tau PET SUVR mean was higher in the diabetic (n=6) relative to the nondiabetic group (n=88).

CONCLUSION

Findings indicate that IR may not be related to tau in generally healthy middle-aged and older adults who are in the early stages of the AD clinicopathologic continuum but suggest the need for additional research to investigate whether a synergistic relationship between type 2 diabetes and amyloid is associated with increased tau levels.

Plasma phosphorylated tau-217 in preclinical Alzheimer’s disease

An accurate blood test for Alzheimer’s disease that is sensitive to preclinical proteinopathy and cognitive decline has clear implications for early detection and secondary prevention. We assessed the performance of plasma phosphorylated tau 217 (pTau217) against brain PET markers of amyloid ([11C]-labeled Pittsburgh compound B (PiB)) and tau ([18F]MK-6240), and its utility for predicting longitudinal cognition. Samples were analyzed from a subset of participants with up to 8 years follow-up in the Wisconsin Registry for Alzheimer’s Prevention (WRAP; 2001-present; plasma 2011-present), a longitudinal cohort study of adults from midlife, enriched for parental history of Alzheimer’s disease. Participants were a convenience sample who volunteered for at least one PiB scan, had usable banked plasma, and were cognitively unimpaired at first plasma collection. Study personnel who interacted with participants or samples were blind to amyloid status. We used mixed effects models and receiver-operator characteristic curves to assess concordance between plasma pTau217 and PET biomarkers of Alzheimer’s disease, and mixed effects models to understand the ability of plasma pTau217 to predict longitudinal performance on WRAP’s preclinical Alzheimer’s cognitive composite (PACC-3). The primary analysis included 165 people (108 women; mean age = 62.9  ±  6.06; 160 still enrolled; 2 deceased; 3 discontinued). Plasma pTau217 was strongly related to PET-based estimates of concurrent brain amyloid (β^ = 0.83 (0.75, 0.90), p &lt; .001). Concordance was high between plasma pTau217 and both amyloid PET (area under the curve = 0.91, specificity = 0.80, sensitivity = 0.85, positive predictive value = 0.58, negative predictive value = 0.94) and tau PET (area under the curve = 0.95, specificity = 1, sensitivity = 0.85, positive predictive value = 1, negative predictive value = 0.98). Higher baseline pTau217 levels were associated with worse cognitive trajectories (β^pTau×age = -0.07 (-0.09, -0.06), p &lt; .001). In a convenience sample of unimpaired adults, plasma pTau217 levels correlate well with concurrent brain Alzheimer’s disease pathophysiology and with prospective cognitive performance. These data indicate that this marker can detect disease before clinical signs and thus may disambiguate presymptomatic Alzheimer’s disease from normal cognitive aging.

Associations between self-reported sleep patterns and health, cognition and amyloid measures: results from the Wisconsin Registry for Alzheimer's Prevention

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.

Age at natural menopause impacts cerebrovascular reactivity and brain structure

Menopause is associated with adverse changes in vascular health coinciding with an increased risk of stroke and vascular cognitive impairment. However, there is significant variation in the age at menopause. The present study examined how the age at natural menopause impacts cerebrovascular reactivity and structural biomarkers of brain aging. Thirty-five healthy postmenopausal women were classified as early-onset menopause (Early; n = 19, age at menopause: 47 ± 2 yr) or later-onset menopause (Late; n = 16, age at menopause: 55 ± 2 yr). Middle cerebral artery blood velocity (MCAv), mean arterial blood pressure (MAP), and end-tidal carbon dioxide (ETCO2) were recorded during a stepped hypercapnia protocol. Reactivity was calculated as the slope of the relationship between ETCO2 and each variable of interest. Brain volumes and white matter hyperintensities (WMHs) were obtained with 3T MRI. Resting MAP was greater in the Early group (99 ± 9 mmHg) compared with the Late group (90 ± 12 mmHg; P = 0.02). Cerebrovascular reactivity, assessed using MCAv, was blunted in the Early group (1.87 ± 0.92 cm/s/mmHg) compared with the Late group (2.37 ± 0.75 cm/s/mmHg; P = 0.02). Total brain volume did not differ between groups (Early: 1.08 ± 0.07 L vs. Late: 1.07 ± 0.06 L; P = 0.66), but the Early group demonstrated greater WMH fraction compared with the Late group (Early: 0.36 ± 0.14% vs. Late: 0.25 ± 0.14%; P = 0.02). These results suggest that age at natural menopause impacts cerebrovascular function and WMH burden in healthy postmenopausal women.

The recency ratio assessed by story recall is associated with cerebrospinal fluid levels of neurodegeneration biomarkers

Recency refers to the information learned at the end of a study list or task. Recency forgetting, as tracked by the ratio between recency recall in immediate and delayed conditions, i.e., the recency ratio (Rr), has been applied to list-learning tasks, demonstrating its efficacy in predicting cognitive decline, conversion to mild cognitive impairment (MCI), and cerebrospinal fluid (CSF) biomarkers of neurodegeneration. However, little is known as to whether Rr can be effectively applied to story recall tasks. To address this question, data were extracted from the database of the Alzheimer's Disease Research Center at the University of Wisconsin - Madison. A total of 212 participants were included in the study. CSF biomarkers were amyloid-beta (Aβ) 40 and 42, phosphorylated (p) and total (t) tau, neurofilament light (NFL), neurogranin (Ng), and α-synuclein (a-syn). Story Recall was measured with the Logical Memory Test (LMT). We carried out Bayesian regression analyses with Rr, and other LMT scores as predictors; and CSF biomarkers (including the Aβ42/40 and p-tau/Aβ42 ratios) as outcomes. Results showed that models including Rr consistently provided best fits with the data, with few exceptions. These findings demonstrate the applicability of Rr to story recall and its sensitivity to CSF biomarkers of neurodegeneration, and encourage its inclusion when evaluating risk of neurodegeneration with story recall.

Effect of Pathway-specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-related Biomarkers among Asymptomatic Individuals

Background

Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan.

Objective

In this study, we leveraged 10 years of longitudinal data from initially cognitively unimpaired individuals in the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways.

Methods

PRS and p-PRSs with and without apolipoprotein E ( APOE ) were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and global/domain-specific cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers for beta-amyloid 42 (Aβ42), Aβ42/40 ratio, total tau, and phosphorylated tau in a subset. Replication analyses were performed in an independent sample.

Results

We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of p-PRSs/PRS on rate of change in cognition, beta-amyloid, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded.

Conclusion

In addition to APOE , the p-PRSs can predict age-dependent changes in beta-amyloid, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating beta-amyloid and tau, long before the onset of clinical symptoms.

Identifying clinically useful biomarkers in neurodegenerative disease through a collaborative approach: the NeuroToolKit

BACKGROUND

Alzheimer's disease (AD) is a complex and heterogeneous disease, which requires reliable biomarkers for diagnosis and monitoring disease activity. Preanalytical protocol and technical variability associated with biomarker immunoassays makes comparability of biomarker data across multiple cohorts difficult. This study aimed to compare cerebrospinal fluid (CSF) biomarker results across independent cohorts, including participants spanning the AD continuum.

METHODS

Measured on the NeuroToolKit (NTK) prototype panel of immunoassays, 12 CSF biomarkers were evaluated from three cohorts (ALFA+, Wisconsin, and Abby/Blaze). A correction factor was applied to biomarkers found to be affected by preanalytical procedures (amyloid-β1-42, amyloid-β1-40, and alpha-synuclein), and results between cohorts for each disease stage were compared. The relationship between CSF biomarker concentration and cognitive scores was evaluated.

RESULTS

Biomarker distributions were comparable across cohorts following correction. Correlations of biomarker values were consistent across cohorts, regardless of disease stage. Disease stage differentiation was highest for neurofilament light (NfL), phosphorylated tau, and total tau, regardless of the cohort. Correlation between biomarker concentration and cognitive scores was comparable across cohorts, and strongest for NfL, chitinase-3-like protein-1 (YKL40), and glial fibrillary acidic protein.

DISCUSSION

The precision of the NTK enables merging of biomarker datasets, after correction for preanalytical confounders. Assessment of multiple cohorts is crucial to increase power in future studies into AD pathogenesis.

Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and SNP data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-driven neuroimaging phenotypes.

Liver-Specific Polygenic Risk Score Is Associated with Alzheimer's Disease Diagnosis

BACKGROUND

Our understanding of the pathophysiology underlying Alzheimer's disease (AD) has benefited from genomic analyses, including those that leverage polygenic risk score (PRS) models of disease. The use of functional annotation has been able to improve the power of genomic models.

OBJECTIVE

We sought to leverage genomic functional annotations to build tissue-specific AD PRS models and study their relationship with AD and its biomarkers.

METHODS

We built 13 tissue-specific AD PRS and studied the scores' relationships with AD diagnosis, cerebrospinal fluid (CSF) amyloid, CSF tau, and other CSF biomarkers in two longitudinal cohort studies of AD.

RESULTS

The AD PRS model that was most predictive of AD diagnosis (even without APOE) was the liver AD PRS: n = 1,115; odds ratio = 2.15 (1.67-2.78), p = 3.62×10-9. The liver AD PRS was also statistically significantly associated with cerebrospinal fluid biomarker evidence of amyloid-β (Aβ42:Aβ40 ratio, p = 3.53×10-6) and the phosphorylated tau:amyloid-β ratio (p = 1.45×10-5).

CONCLUSION

These findings provide further evidence of the role of the liver-functional genome in AD and the benefits of incorporating functional annotation into genomic research.

Development, initial validation, and application of a visual read method for [18F]MK-6240 tau PET

Background

The positron emission tomography (PET) radiotracer [18F]MK-6240 exhibits high specificity for neurofibrillary tangles (NFTs) of tau protein in Alzheimer's disease (AD), high sensitivity to medial temporal and neocortical NFTs, and low within-brain background. Objectives were to develop and validate a reproducible, clinically relevant visual read method supporting [18F]MK-6240 use to identify and stage AD subjects versus non-AD and controls.

Methods

Five expert readers used their own methods to assess 30 scans of mixed diagnosis (47% cognitively normal, 23% mild cognitive impairment, 20% AD, 10% traumatic brain injury) and provided input regarding regional and global positivity, features influencing assessment, confidence, practicality, and clinical relevance. Inter-reader agreement and concordance with quantitative values were evaluated to confirm that regions could be read reliably. Guided by input regarding clinical applicability and practicality, read classifications were defined. The readers read the scans using the new classifications, establishing by majority agreement a gold standard read for those scans. Two naïve readers were trained and read the 30-scan set, providing initial validation. Inter-rater agreement was further tested by two trained independent readers in 131 scans. One of these readers used the same method to read a full, diverse database of 1842 scans; relationships between read classification, clinical diagnosis, and amyloid status as available were assessed.

Results

Four visual read classifications were determined: no uptake, medial temporal lobe (MTL) only, MTL and neocortical uptake, and uptake outside MTL. Inter-rater kappas were 1.0 for the naïve readers gold standard scans read and 0.98 for the independent readers 131-scan read. All scans in the full database could be classified; classification frequencies were concordant with NFT histopathology literature.

Discussion

This four-class [18F]MK-6240 visual read method captures the presence of medial temporal signal, neocortical expansion associated with disease progression, and atypical distributions that may reflect different phenotypes. The method demonstrates excellent trainability, reproducibility, and clinical relevance supporting clinical use.

Highlights

A visual read method has been developed for [18F]MK-6240 tau positron emission tomography.The method is readily trainable and reproducible, with inter-rater kappas of 0.98.The read method has been applied to a diverse set of 1842 [18F]MK-6240 scans.All scans from a spectrum of disease states and acquisitions could be classified.Read classifications are consistent with histopathological neurofibrillary tangle staging literature.