ApoE Research Articles

The structural integrity of anterior‐temporal and posterior‐medial brain regions in Alzheimer’s disease and Parkinson’s disease: Effects of APOEε4, p‐tau181 and Aβ42

AbstractBackgroundAlzheimer’s disease (AD) and Parkinson’s disease (PD) are two distinct neurodegenerative brain conditions associated with varying degrees of cognitive impairment, including an overlapping amnestic phenotype. At autopsy, APOEe4 and AD proteinopathies are associated with dementia severity in both AD and PD. The extent to which in‐vivo AD biomarkers are associated with memory and underlying regional brain volume in AD and PD patients is under‐investigation. Here, we focused on plasma biomarker associations with anterior‐temporal and posterior‐medial regions that are known to accumulate tau and Aß in AD.MethodNeuroimaging, biomarker, genetic and cognitive data were collected from 244 patients through the Ontario Neurodegenerative Disease Research Initiative (MeanAge = 68.96; 41% women; 35%APOE‐e4‐carriers). Based on clinical diagnostic criteria, three groups were formed: i)AD with mild cognitive impairment or dementia(ADMCI/ADD;N = 120), ii)PD with MCI or dementia(PDMCI/PDD;N = 76) and iii)PD with normal cognition(PD‐NC;N = 48). Linear regressions assessed clinical diagnosis differences in the volumetric integrity of a priori regions: anterior‐temporal(ATN; including amygdala, fusiform gyrus, and ITG) and posterior‐medial(PMN; including PCC, parahippocampal cortex and precuneus;Fig1). Differences on related item recognition memory and associative memory was examined via the FaceName Association Task. APOE(e4‐/e4+), p‐tau181‐UGOT and Aß42 associations between ATN/PMN and item recognition/associative memory outcomes were estimated. Diagnostic*APOEe4*ptau181 interactions were tested. Age, sex, education and ICV were covaried.ResultBackground characteristics showed that the ADMCI/ADD group exhibited the oldest age and the highest frequency of female sex and e4‐carriership. ADMCI/ADD and PDMCI/PDD, but not PD‐NC, exhibited elevated ptau181 and Aß42 relative to a healthy control group. Both ADMCI/ADD and PDMCI/PDD groups exhibited PMN and ATN degradation, as well as memory impairment, relative to the PD‐NC(Fig2A‐B). Plasma p‐tau181 was associated with ATN and PMN, as well as associative memory(Fig3A). APOEe4 was associated with PMN only, as well as item recognition(Fig3B). Diagnostic*APOEe4*ptau181 interactions were not significant. Post‐hoc analysis showed significant p‐tau181xAPOEe4 interactions on item recognition and total white matter hyperintensity(WMH;Fig3C). Aß42 was not associated with outcomes.ConclusionVolumes of the ATN and PMN are lower in cognitively impaired AD and PD patients with higher p‐tau and/or APOEe4‐carriership. P‐tau and APOEe4 may work synergistically to promote domain‐specific memory impairment and WMH burden in both AD and PD.

Plasma Alzheimer biomarkers in the 1946 British birth cohort: predicting conversion to amyloid PET positivity over a two‐year follow‐up period

AbstractBackgroundIn the Insight 46 sub‐study of the 1946 British birth cohort we investigated concordance of baseline plasma biomarkers (age 71) with cerebral amyloid PET status at two time‐points (ages 71 and 73).MethodBaseline plasma samples were tested using Simoa (Quanterix) commercial (NfL, GFAP, Aβ42, Aβ40, p‐tau181V2) and homebrew digital immunoassays (p‐tau181, p‐tau231: University of Gothenburg; NT1 tau: Harvard University). Logistic regression and ROC analysis were used to assess concordance of single biomarkers with cerebral amyloid PET status at each timepoint, defined as 18F‐florbetapir SUVR> = 1.071 normalized to whole cerebellum without partial volume correction (13 centiloids). Areas under the curve were compared to that from the base model (age, sex, APOE ε4 carrier status) using De Long tests. Combinations of the top five biomarkers that had singly significantly improved on the base model were compared using Akaike Information Criteria (AIC). Differences between biomarker values across the three amyloid PET groups (both scans negative, baseline negative and follow‐up positive, both positive) were assessed using Kruskal‐Wallis ANOVA and post hoc Dunn’s tests with Bonferroni correction.ResultBaseline assessment of 502 individuals (mean age 70.7 years (s.d. 0.7), 51% male, 29.6% APOE ε4 carriers) yielded 432 individuals with plasma and amyloid PET available at the first timepoint (19.4% PET‐positive) and 336 at the second timepoint (25.3% PET‐positive). No single biomarker outperformed the base model in predicting amyloid PET status at either timepoint. However, each of Aβ40/42, all the p‐tau biomarkers, NT1 tau, and GFAP improved base model performance at both timepoints (Table 1). A model combining base model covariates with Aβ40/42, p‐tau181 homebrew and GFAP gave the best fit for follow‐up amyloid PET status, (AIC 292, compared with the base model AIC of 355 ‐ Table 2). Individuals who converted from PET‐negative to positive had higher median values of p‐tau181 (both assays) and p‐tau231 at baseline than those who remained amyloid PET‐negative (Figure 1).ConclusionCombining baseline plasma Aβ40/42, p‐tau181 and GFAP gave the best prediction of amyloid PET status over 2‐year follow‐up. Individuals who converted from amyloid PET‐negative to positive had higher values of p‐tau181 and p‐tau231 than those who remained PET‐negative.

Modifiable dementia risk factor associations with AT(N) biomarkers: Findings from the European Prevention of Alzheimer’s Dementia study

AbstractBackgroundThere is strong evidence that targeting modifiable risk factors can maintain and improve cognitive function, as well as reducing risk for Alzheimer’s disease (AD) and other forms of dementia. Further, a discrete AT(N) profile exists for hallmark biomarkers: amyloid β (A), p‐tau (T) and neurodegeneration (N), to discriminate between AD and non‐AD pathological changes. Despite evidence of a biologically defined AD continuum and modifiable risk amelioration, there is a paucity of studies investigating modifiable risk factors with respect to AT(N) biomarkers. The aim of this study was to investigate how modifiable risk factors relate to the three hallmark AT(N) biomarkers of AD.MethodParticipants were drawn from the European Prevention of Alzheimer’s Disease (EPAD): a prospective, multicentre, pan‐European cohort study. Eligible participants underwent clinical and neurological assessments, brain magnetic resonance imaging, cerebrospinal fluid (CSF) collection, neuropsychological assessment and completed a variety of demographic, clinical, medical history and lifestyle surveys for 10 binary modifiable risk variables. Data were analysed via the NeuroToolKit Application (NTKApp, BetaVersion, 2022). Generalized additive models with penalized regression splines were used to model the associations between modifiable risk factor adherence and AT(N) biological criterion: A (CSF amyloid‐β 42 [Aβ42 pg/mL]); T (CSF phosphorylated‐tau 181 [p‐tau 181 pg/mL]); N (total hippocampal volume [mm3]).ResultOf the 2737 participants included, 56% were female (n = 1526), 39% had at least one APOE ε4 allele (n = 1598), with an average age of 66.0 years and 14.4 years of education. Adjusting for age, sex and APOE carrier status: age, APOE and traumatic brain injury (TBI) were significantly associated with CSF Aβ42; age, APOE, body mass index (BMI) and exercise were significantly associated with CSF p‐tau181; and age, sex and education were significantly associated with total hippocampal volume.ConclusionModifiable risk factors of less education, less exercise, TBI and higher BMI were all significantly associated with increased AD biomarker burden. Our results support previous studies identifying associations between modifiable risk factors and AD and suggest that early intervention strategies focused on education and lifestyle factors and improvements in prevention and treatment of TBI may modify risk profiles associated with cognitive decline.

Feature extraction by orthonormal projective non‐negative matrix factorization and longitudinal association between brain atrophy patterns and Alzheimer’s disease

AbstractBackgroundOrthonormal projective non‐negative matrix factorization (OPNMF) was a recently developed approach for feature extraction techniques of neuroimaging data. However, there has been few studies applying this to brain MRI to better characterize the anatomic changes seen in Alzheimer’s Disease (AD) and correlate these patterns with cognitive changes.MethodWe applied OPNMF with refinement to identify distinct spatial components of voxel‐wise volume loss in the structural MRI (3D T1 MPRAGE images) of subjects with AD (N = 109, mean age = 74.6 (7.9), ADNI2) relative to healthy young controls (N = 104, mean age = 24.0 (2.9), ABIDE1). Non‐negative least squares (NNLS) was then used to extract non‐negative coefficients representing subject‐specific quantitative measures of regional atrophy. This calculation of coefficients was extended to images not used for component discovery which also included Mild Cognitive Impairment (MCI) and controls. To investigate the cross‐sectional and longitudinal associations between cognitive assessments scores and regional atrophy severity in different diagnostic groups, we used multiple linear regression models and liner mixed‐effects models with random intercepts and slopes controlled for age, sex, educational level, APOE ε4 genotypes were utilized. A validation analysis was performed using ADNI3 images.ResultWe derived 6 atrophy components upon the same training set and there was a sharp decrease in the magnitude of the reconstruction error gradient when moving from 5 components to 6 components, and the components have meaningful interpretation. In the whole cohort, atrophy in 5 of the 6 regions was significantly associated with all three cognitive scores. There is evidence of overall positive trends between diagnosis group and atrophy severity changing rate in all 6 regions. The increased atrophy in all 6 regions was associated with decreases in MMSE and MOCA scores and increases in CDRSB scores in the whole cohort as well as in LMCI cohort. From the validation analysis, we showed that our result from OPNMF is stable in atrophy pattern discovery.ConclusionWe developed a robust pipeline for detecting spatially distinct atrophy components in AD and associated these atrophy patterns with cognitive changes which may help us better characterize the underlying pathology of types of AD and other dementias on MRI.

Neurofibrillary tangle distribution in posterior cortical atrophy and early‐onset Alzheimer disease

AbstractBackgroundEarly onset sporadic Alzheimer’s disease (AD) sometimes presents with non‐memory symptoms attributed to relatively greater neocortical than hippocampal tau neurofibrillary tangle (NFT) density. Posterior cortical atrophy (PCA) is a variant of AD presenting with visuospatial deficits and atrophy of the occipital cortex, yet the pathologic underpinning is poorly understood.MethodWe examined brains of 50 patients with early onset (age<65 y.), autopsy‐confirmed AD from the UCSD Alzheimer’s Disease Research Center, 12 of whom were clinically diagnosed with PCA. Immunohistochemistry for tau was performed in the hippocampus (HP), midfrontal cortex (MF), and occipital cortex (OC), and the density of NFTs was measured.ResultPCA and non‐PCA patients did not significantly differ in age (63.35±4.59 y. at death) or sex (40% female). The APOE ε4 allele was much less frequent in PCA (p = 0.002). While the PCA group was less impaired on the MMSE (p = 0.01), they performed comparably on the CDR sum‐of‐boxes. The OC NFT density did not differ between the groups; however, the OC/HP (p = 0.04) and OC/MF (p = 0.008) ratios demonstrate that PCA cases had relatively greater OC pathology than non‐PCA patients. Across the groups, age at symptom onset was inversely associated with OC NFT density (p = 0.01) and the OC/HP NFT ratio (p = 0.008), such that earlier onset was associated with greater OC NFT burden. Visuospatial performance, measured by the Block Design test, was associated with the OC NFT density (p = 0.006), as well as the OC/HP (p = 0.007) and OC/MF NFT ratios (p = 0.03), with the effects remaining significant when restricting to non‐PCA participants. In contrast, memory performance measured by the Logical Memory Immediate Recall measure was only associated with HP NFT density (p = 0.02).ConclusionDespite differences in the predominance of early visuospatial symptoms, PCA and non‐PCA patients did not differ in OC tangle density, with some of the highest densities in non‐PCA patients. However, the degree of visuospatial impairment was associated with the OC/HP NFT ratio across both groups. Results suggest that greater memory impairment in the non‐PCA patients associated with a higher HP tangle density may moderate the predominance of visuospatial impairment so that they do not receive a formal PCA diagnosis.

Macular vessel density in the superficial plexus is not associated to cerebrovascular damage in non‐demented individuals: data from the NORFACE cohort

AbstractBackgroundOptical Coherence Tomography angiography (OCT‐A) is a novel tool that allows the detection of retinal vascular changes. The comparison of OCT‐A measures with brain vascular burden is essential to validate the former as a surrogate of cerebrovascular damage and biomarker of cognitive decline. We aimed to investigate the association of macular vessel density (VD) in the superficial plexus assessed by OCT‐A with measures of cerebrovascular pathology quantified by brain magnetic resonance imaging (MRI) in a cohort of non‐demented individuals.MethodClinical, demographical, APOE ε4 status, amyloid status, OCT‐A and brain MRI data from non‐demented participants of the FACEHBI and BIOFACE studies were included. We analyzed the association of macular VD in four quadrants (superior, nasal, inferior and temporal) with brain vascular burden using the Fazekas scale scores (dichotomized in two categories, 0‐1 vs 2‐3), assessed in a logistic regression analysis, and the volume of white matter hyperintensities (WMH) quantified by Freesurfer assessed in a multiple regression analysis. We additionally explored the associations of macular VD with hippocampal volume, ventricles volume and Alzheimer Disease cortical signature (ADCS) thickness assessed in a multiple regression analysis. All analyses were adjusted for age and dyslipidemia.ResultThe study cohort comprised 188 participants: 89 with subjective cognitive decline (SCD) and 99 with mild cognitive impairment (MCI). Logistic regression analysis showed no significant differences of regional macular VD between the two Fazekas groups (all, p>0.05). Multiple regression analysis showed no significant association of regional macular VD with the volume of WMH (all, p>0.05). Macular VD in the nasal and inferior quadrants were positively associated with hippocampal volume (p = 0.009 and p = 0.021, respectively), but no association was detected with ventricles volume or ADCS thickness (both p>0.05).ConclusionOur study showed that retinal vascular measures (regional macular VD in the superficial vascular plexus) assessed by OCT‐A were not associated with brain vascular damage quantified by the Fazekas scale and the WMH burden n in a cohort of non‐demented research participants with SCD and MCI.

Investigating Potential Racial Differences in Dementia‐Related Plasma Biomarkers

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

Blood‐based biomarkers of Alzheimer disease as measured by a mass spectrometry assay are as accurate as CSF tests

AbstractBackgroundEspecially because disease‐modifying treatments (DMTs) for Alzheimer disease (AD) are likely to become more available soon, highly accurate AD blood tests for use in clinical diagnosis are critically needed. Although amyloid PET scans and cerebrospinal fluid (CSF) tests are highly accurate in the identification of individuals with brain amyloidosis, blood tests are likely the only test modality that will enable an adequate scale of AD biomarker testing. Mass spectrometry‐based AD blood tests have consistently demonstrated very high performance.MethodsResearch participants enrolled in studies at the Knight Alzheimer Disease Research Center who underwent amyloid PET and measurement of established CSF biomarkers of AD with Lumipulse automated assays were included. The presence and severity of dementia was evaluated with the Clinical Dementia Rating® (CDR®) and Clinical Dementia Rating Sum of Boxes (CDR‐SB). Plasma samples collected at the same session as CSF underwent analysis for specific phosphorylated and non‐phosphorylated tau species with an immunoprecipitation‐mass spectrometry assay. Plasma T217 occupancy was calculated as the percent of phosphorylated to non‐phosphorylated tau at threonine 217.ResultsThe study cohort included 337 individuals with an average age of 69.8 ± 8.3 years (mean ± standard deviation); 175 (52%) were female, 128 (38%) were APOE ε4 carriers, 112 (33%) were amyloid PET positive, and 50 (15%) were cognitively impaired. Classification accuracy of amyloid PET status was equivalent for plasma T217 occupancy (AUC 0.973) and CSF Aβ42/Aβ40 (AUC 0.970), (p = 0.72 for the difference). Interestingly, plasma T217 occupancy more accurately classified individuals as cognitively impaired (CDR>0) or cognitively unimpaired (CDR 0), with an AUC of 0.876 versus 0.814 for CSF Aβ42/Aβ40 (p = 0.006 for the difference). Further, plasma T217 occupancy was better correlated with dementia severity as measured by the CDR‐SB (Spearman ρ = 0.455 versus ‐0.338 for CSF Aβ42/Aβ40, p = 0.02).ConclusionPlasma T217 occupancy as measured by mass spectrometry had equivalent classification accuracy of amyloid PET status compared to Lumipulse CSF Aβ42/Aβ40. Notably, plasma T217 occupancy was more strongly associated with cognitive impairment and dementia severity than CSF Aβ42/Aβ40. Overall, these data suggest that some AD blood tests have equivalent or better performance characteristics than clinically used CSF tests.

Plasma phosphorylated tau 181 and modifiable risk factors for dementia in a large scale cohort of Australian older adults

AbstractBackgroundUp to 40% of dementia cases could be prevented by addressing modifiable risk factors. Alzheimer’s disease (AD), the most common form of dementia, is preceded by up to decades of silent pathological change providing an ideal window for early detection and intervention. In this study, our objective was to examine the associations between modifiable risk factors and plasma phosphorylated p‐tau 181, a hallmark biomarker of early AD.MethodParticipants were recruited from the Island Study Linking Ageing and Neurodegenerative Disease (ISLAND), a prospective public health initiative in Tasmania, Australia’s southernmost island state. ISLAND participants were invited to complete a set of surveys online: a questionnaire on dementia risk factor adherence, demographic surveys and cognitive tests via the Cambridge Neuropsychological Test Automated Battery (CANTAB); Paired Associates Learning (PAL) and Spatial Working Memory (SWM). At four clinics across the state, participants also provided blood samples for measurement of plasma phosphorylated p‐tau 181 and genotyping for APOE.ResultA total of 738 participants (mean age 65.41 years, mean education 17.36 years, 71.8% female, 26.4% ε4+) took part in the study. We found gender‐specific effects on cognition, whereby identifying as male was associated with significantly lower learning ability (PAL) whilst identifying as female was associated with significantly lower executive function (SWM). In multivariate linear models, increasing alcohol consumption (measured in standard drinks per week) was significantly associated with lower plasma p‐tau 181. In adjusted models, no other modifiable risk factors examined were associated with p‐tau 181. Increasing age, identifying as male and possessing at least one APOE ε4 allele were all associated with higher plasma concentrations of p‐tau 181ConclusionHigher alcohol consumption, higher age, identifying as male and having an APOE ε4 allele were all associated with lower plasma phosphorylated tau 181. This contributes to evidence that both modifiable and non‐modifiable dementia risk factors are related to the biological precedents of AD. These associations were related to gender and genetics, therefore a panel of modifiable and non‐modifiable variables should be included in screening or diagnostic testing for pre‐clinical AD. More research is needed regarding specific alcohol types and biomarkers of AD.

Sex differences in white matter bundle properties across menopausal transition states

AbstractBackgroundWomen develop Alzheimer’s disease (AD) at a 2:1 rate compared to men. Changes associated with menopause exacerbate a midlife bioenergetic crisis that, when unsuccessfully resolved, leads to white matter degradation and ultimately brain atrophy. Understanding how white matter structural properties differ between sexes and evolve over midlife transitions may provide insight into the exacerbated AD risk for women. Here, we report differences in white matter bundle properties comparing pre‐ (n = 40, 44.1±3.34y), peri‐ (n = 60, 49.6±3.90y), and post‐menopausal women (n = 70, 56.0±4.12y) to age‐matched males.MethodDiffusion weighted MRI was acquired for each participant. Data were preprocessed with QSIPrep and analyzed using a fixel‐based approach implemented in MRtrix (v. 3.0.3). Fiber density (FD), cross‐section (FC), and a combined density/cross‐section metric (FDC) were compared between sexes after controlling for age, education, APOE ε4 carrier status, and total brain volume (FC and FDC only). Continuous covariates were standardized to 2 standard deviations. Analyses were conducted using connectivity‐enhanced fixel‐based permutation analyses and thresholded at family‐wise error corrected p<0.05.ResultPre‐, peri‐, and post‐ menopausal women exhibited greater FD and FDC in the corpus callosum, inferior occipto‐frontal fasciculus, cortico‐spinal, and cingulum bundles. By contrast, males had greater fiber cross section in the splenium of the corpus callosum (compared to pre‐), (compared to peri‐), and in fibers near the left uncinate fasciculus and inferior longitudinal fasciculus (compared to both peri‐ and post‐menopausal women). After controlling for age, education, total brain volume, and APOE ε4 carrier status, a smaller cluster of fibers in the left splenium survived multiple comparisons correction demonstrating greater fiber cross‐section in post‐menopausal women compared to peri‐menopausal women.ConclusionWomen across menopausal transition states exhibited greater fiber density than their age‐matched male counterparts in commissural and association tracts, which agrees with previous work demonstrating stronger inter‐hemispheric connections in women. However, peri‐ and post‐menopausal females exhibited 4‐8% decrease in fiber cross section in uncinate fasciculus fibers, which have been implicated in Alzheimer’s related cognitive decline. These findings suggest that reductions in white matter cross‐section, particularly in regions associated with Alzheimer’s disease, may begin for women in menopause and be an early indicator of neurodegenerative risk.

Association Between HSV‐1 and Risk of Alzheimer’s Disease Detected by a Propensity‐Score Matched Case Design

AbstractBackgroundHerpes simplex virus 1 (HSV‐1) is a neurotropic and neuroinvasive species that can enter the brain triggering inflammation and an immune response, increasing the risk of Alzheimer disease (AD). Previously, we found a significant association between HSV‐1 and AD in whole‐exome sequencing (WES) data (OR = 3.69, P = 6.71×10−4) but not whole‐genome sequenced (WGS) data (OR = 0.92, P = 0.27) from the AD Sequencing Project (ADSP).MethodTo understand this discrepancy, and to better control for the numerous covariates and technical differences that influenced viral quantity, we created a novel algorithm using propensity score analysis (PSA) which permits analysis of observational study data comparable to a randomized controlled trial. WGS reads from 6,541 AD cases and 6,855 controls from the ADSP (including 7,395 non‐Hispanic Whites, 2,961 African Americans, and 3,040 Caribbean Hispanics) that did not align to the human genome were mapped to viral reference sequences and quantified. Propensity scores were derived for 7,619 individuals with at least one HSV‐1 read and 5,777 individuals lacking any HSV‐1 reads using a binary treatment indicator for HSV‐1 status. We applied forward stepwise regression including known confounders (APOE ε4 status, sex, age, tissue source (blood or brain), population ancestry, sequencing center, and PCR amplification) to identify other potential confounders and/or interactions and quadratic terms for creating propensity scores. We tried several matching algorithms to generate matched sets of individuals with and without HSV‐1. Utilizing the best quality matched set, we evaluated the association of AD with HSV‐1 status using a weighted generalized linear model.ResultThe final regression model included terms for the covariates mentioned above that were available for most of the original sample (5828 AD cases and 6487 controls). We found a significant association between HSV‐1 and AD (OR = 1.10, P = 0.02).ConclusionResults from WGS data confirm our previous findings obtained from WES data and support the hypothesis that HSV‐1 is associated with an increased AD risk, highlighting the utility of PSA for analyzing association of risk factors with complex disorders like AD. Further studies are needed to replicate this finding in other ancestral populations and explain the lack of association in WGS data.

Examination of plasma YKL‐40 as a clinical biomarker for Alzheimer’s disease

AbstractBackgroundBlood biomarkers represent a potential non‐invasive and cost‐effective strategy for the clinical detection and monitoring of neurodegenerative conditions including Alzheimer’s disease (AD). YKL‐40 is a secreted glycoprotein associated with inflammatory processes, and elevated cerebrospinal fluid levels have been observed in AD and other neurodegenerative conditions. Fewer studies have examined plasma YKL‐40. We examined relationships between plasma YKL‐40 and clinical indices of AD in a large cross‐sectional sample from a clinical cohort registry.MethodThe sample included 569 participants from the Boston University Alzheimer’s Disease Research Center, including participants with normal cognition (NC; n = 235), mild cognitive impairment due to suspected AD (MCI; n = 181), and AD dementia (n = 153). Blood plasma samples were analyzed using standard ELISA methods; values were log transformed and standardized into z‐scores. Cross‐sectional analyses investigated the relationships between YKL‐40 and clinical indices of functioning including diagnostic status, dementia severity (on the Clinical Dementia Rating scale [CDR]), and neuropsychological test performance. Age, sex, education, race, and APOE ε4 carrier status were included as covariates in all analyses.ResultNo significant differences in plasma YKL‐40 were observed between participants with NC, MCI, and AD dementia after accounting for covariates. The comparison between MCI and dementia was marginally significant (p = .07), with an adjusted mean difference of Z = 0.19. For participants with dementia (CDR scores 1‐3), non‐significant trends were observed for relationships between plasma YKL‐40 values and dementia severity, including for Sum of Boxes (Pearson partial correlation: r = .14, p = .10) and Total Score (ordinal logistic regression: OR = 1.38; 95% CI: [0.98,1.93]), p = .06. Modest but significant correlations were observed between YKL‐40 and performance on 4/12 neuropsychological tests including Animal Fluency (r = ‐.10), Vegetable Fluency (r = ‐.09), and Neuropsychological Assessment Battery List Learning Trials 1‐3 (r = ‐.10) and Short Delay (r = ‐.12).ConclusionPlasma YKL‐40 biomarker levels were modestly related to neuropsychological assessments of language and memory but not significantly related to cognitive diagnosis of AD or dementia severity. This biomarker may reflect underlying inflammatory processes in the context of AD. However, the use of plasma YKL‐40 to assess the presence and severity of AD in a larger cross‐sectional sample size, and using a multiple biomarker approach, warrant further study.

Comparison of subjective cognitive decline and polygenic risk score in the prediction of all‐cause dementia, Alzheimer’s disease and vascular dementia

AbstractBackgroundSubjective cognitive decline (SCD) and polygenic risk scores (PRS) have both been shown to be associated with the risk of developing dementia. However, it is of interest whether they can improve the established and well‐validated cardiovascular risk factors aging and dementia (CAIDE) model and how their predictive abilities compare.MethodsSCD and PRS were assessed and determined in a large, population‐based cohort study. In this study, the CAIDE model was applied to a sub‐sample of 5,360 study participants and evaluated for the outcomes of all‐cause dementia, Alzheimer’s disease (AD) and vascular dementia (VD) by calculating Akaike’s information criterion (AIC) and the area under the curve (AUC). The improvement of the CAIDE model by SCD and PRS was further examined using the net reclassification improvement (NRI) method and integrated discrimination improvement (IDI). Besides evaluations in the total sample, predictive abilities were evaluated in the mid‐life and late‐life sub‐cohort.ResultsDuring 17 years of follow‐up, 410 participants were diagnosed with dementia, including 139 AD and 152 VD diagnoses. Overall, the CAIDE model showed high discriminative ability for all outcomes reaching AUCs of 0.785, 0.793 and 0.789 for all‐cause dementia, AD, and VD, respectively. Adding information on SCD to the CAIDE model led to a significant increase in NRI for all‐cause dementia (4.4%, p = 0.0401) and VD (7.7%, p = 0.0095). In contrast, prediction models for AD further improved when PRS was added to the model (NRI, 8.4%, p = 0.0257). The latter became more substantial when applied to the mid‐life sub‐group (50‐64 years), achieving an NRI of 19.6% (p = 0.0075). When APOE ε4 carrier status was included in CAIDE model 2, the discriminative ability of the basic CAIDE model increased, and SCD and PRS did not further improve the prediction.ConclusionWhile PRS significantly improved the prediction of the CAIDE model for AD, information on SCD increased its discriminative ability for all‐cause dementia and VD. In contrast to PRS, information on SCD can be assessed more efficiently, and thus models including SCD can be more easily transferred to the clinical setting. Nevertheless, the two variables seem negligible if APOE ε4 carrier status is available.

Plasma biomarkers, memory impairment, and imaging measures of Alzheimer’s disease in American Indians

AbstractBackgroundAlzheimer’s disease (AD) is best defined in vivo using quantifiable, objective markers reflecting amyloid deposition (A), pathologic tau (T), and neurodegeneration (N). However, gold standards for ATN (imaging or cerebrospinal proteins) are expensive, invasive, and/or impractical in low resource settings. Circulating proteins offer a practical alternative. Candidate plasma markers include amyloid‐β (Aβ40&42), phosphorylated tau‐181 (ptau), glial fibrillary protein (GFAP), and neurofilament light chain (NfL). However, no such markers have been evaluated in American Indians.MethodThe Strong Heart Study recruited 401 American Indians over 3 states in 2017‐2019 for MRI, cognitive testing, and clinical examination. MRI included T1 sequences, which were processed using FreeSurfer to quantify structural volumes. Neuropsychological testing incuded California Verbal Learning Test, which was operationalized into categories of memory impairment using indices of learning and recall. Plasma samples were sent to University of Gothenburg for Simoa Quanterix assay. Statistics included descriptive summary; multivariate regression; and receiver operating characteristic analysis.ResultThe study population was mean age 78 (SD 4.7, range 70‐95); majority female (71%); and 21% APOE ε4 allele carriers. An estimated 31% had any memory impairment (13.8% retrieval, 6.5% storage, 10.7% encoding). Median plasma marker values were: ptau 5.0pg/mL (range: 1.5‐442), Aβ40 128pg/mL (116‐175), Aβ42 8.2pg/mL (6.7‐9.7), GFAP 150pg/mL (0‐651), and NfL 31.6pg/mL (9.7‐343); median Aβ42:40 ratio 0.06. Comparing APOEε4 carriers to non‐carriers (Table1), ptau was +12%, Aβ40 ‐0.8%, Aβ42 ‐8.4%, Aβ4240 ‐16.7% (P = 0.006), GFAP +16.1%, NfL +3.2%, but only Aβ4240 was significant. Linear regressions with brain volumes identified significant associations for Aβ42, Aβ40, GFAP, and NfL (but not ptau) with ventricle, cortical, and overall volume; NfL was also associated with entorhinal and hippocampal volume. GFAP and ptau were significantly higher in those with memory encoding deficit; NfL higher with encoding or retrieval deficit (Table2). Although not significant, Aβ40 was lower with storage deficit, and Aβ42 with encoding or storage deficit. AUC range for plasma markers to discriminate memory impaired from intact: 0.4‐0.6.ConclusionThese data are a first look at ATN plasma markers in a population‐based cohort of American Indians, an underrepresented group in AD research. Future research should address generalizability and measurement validity.

Identification of Necessary Plasma Biomarkers for Prediction of Alzheimer’s Disease Neuropathologic Change

AbstractBackgroundPlasma biomarkers for Alzheimer’s disease (AD) such as phosphorylated tau protein 181 (p‐tau 181), neurofilament light chain (NfL), amyloid‐β 42/40 ratio (Aβ42/40), and glial fibrillary acidic protein (GFAP) have shown high performance in the discrimination of those with clinical mild cognitive impairment (MCI) or dementia from cognitively unimpaired individuals, but few population‐based autopsy studies have evaluated the neuropathological correlates of plasma biomarkers.MethodWe utilized a population‐based prospective study of 350 participants with autopsy and antemortem plasma biomarker data. Plasma biomarkers Aβ42/40 ratio, p‐tau181, GFAP, and NfL were measured using Quanterix Simoa assays. We predicted AD neuropathological change (ADNC), Braak staging, and neuritic plaque score using these plasma biomarkers and investigated the added utility of cognitive and demographic information. We utilized a variable selection procedure in cross‐validated (CV) logistic regression models by minimizing the Bayesian Information Criterion to identify the best set of predictors for a given outcome among plasma biomarkers, demographic variables, and neuropsychological tests included in the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo‐PACC).ResultADNC was best predicted with plasma GFAP, NfL, p‐tau181 biomarkers along with APOE ε4 carrier status and Mayo‐PACC cognitive score (CV AUC = 0.821). Braak staging was best predicted using plasma GFAP, p‐tau181, and cognitive scores (CV AUC = 0.788). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p‐tau181, GFAP, and NfL biomarkers (CV AUC = 0.778). Inclusion of plasma biomarkers demonstrated significantly better prediction of Braak staging (p<0.01) and neuritic plaque score (p<0.01), but not ADNC (p = 0.13), when compared to models that included only cognitive and demographic information. Univariate models consistently underperformed in comparison to multivariate models.ConclusionPlasma biomarkers can provide valuable predictive information about the presence of AD pathology, which can facilitate earlier recognition and diagnosis of AD. Incorporation of demographic and cognitive variables along with plasma variables in multivariable models will improve prediction accuracy of AD pathology, specifically Braak staging and ADNC.

Characterization of data‐driven cognitive and amyloid‐beta phenotypes in older Veterans

AbstractBackgroundWithin older Veterans, multiple factors may contribute to cognitive difficulties. Beyond Alzheimer’s disease (AD), military‐related exposures leading to vascular disease (e.g., agent orange), posttraumatic stress disorder (PTSD), and traumatic brain injury (TBI) may also impact cognition. This study aimed to derive groups based on objective cognition, subjective cognition, and amyloid burden, and then compare groups on demographic, clinical, and biomarker characteristics.MethodA hierarchical cluster analysis was conducted on 233 Vietnam‐Era Veterans without dementia from the Department of Defense‐Alzheimer’s Disease Neuroimaging Initiative. Variables entered in the cluster analysis included: immediate and delayed memory, language, and attention/executive functioning domain scores; subjective cognitive decline (SCD) severity; and cortical amyloid PET SUVR. A discriminate function analysis (DFA) tested the extent to which the individual variables predicted cluster‐group membership. ANOVAs and chi‐squared tests examined demographic, clinical, and biomarker characteristics by group.ResultCluster analysis identified 4 groups: Group 1 with high cognition, low SCD, and average amyloid (n = 41); Group 2 with average cognition, average SCD, and low amyloid (n = 121); Group 3 with low attention/executive functioning, average SCD, and high amyloid (n = 28); and Group 4 with low memory/language, high SCD, and average amyloid (n = 43; Figure 1). The DFA correctly classified 88.8% of participants. Group 3 had the greatest proportion of APOE ε4 carriers and individuals with TBI, highest tau burden, and lowest hippocampal volume. Group 4 had the fewest years of education, highest proportion of Hispanic/Latino participants, PTSD, and worst sleep quality. Groups did not differ on age, depressive symptoms, hypertension, or substance use (Table 1).ConclusionWithin Vietnam‐Era Veterans, there were high and average cognition groups (Groups 1 and 2), both with low amyloid burden. Group 3 was most consistent with biological AD, yet attention/executive function was the lowest score. The complexity of older Veterans’ co‐morbid conditions may interact with AD pathology to show attention/executive dysfunction (rather than memory) as a prominent early symptom. Group 4 had the worst cognitive scores and highest SCD despite low amyloid; education, PTSD symptoms, sleep quality, and perhaps sociocultural factors may be contributing to this profile. Future work will investigate longitudinal cognitive and functional declines by group.

Participating in leisure time physical activity across adulthood and later‐life brain health: 30 years follow‐up in 1946 British Birth Cohort

AbstractBackgroundWe assess if, and at which ages during 30 years of adulthood, undertaking leisure time physical activity (LTPA) is associated with brain health at age 70, and to what extent brain health metrics explain the positive association between LTPA and later‐life cognition.MethodParticipants from the British 1946 birth cohort prospectively reported LTPA five times between ages 36 and 69. Metrics were categorised into: not active (no participation/month); active (participated once or more/month); and summed. Participants underwent 18F‐florbetapir Aβ‐PET and MRI at age 70 (n = 468, 49% female). Regression analyses examined associations between LTPA metrics and later‐life brain health including Aβ‐PET, TIV‐adjusted brain, hippocampal and log‐transformed‐white matter hyperintensity (WMH) volume, adjusting for sex, scan age, childhood cognition, education, and childhood socioeconomic position. Effect modification by sex and APOE‐ε4 were examined. The relationship between cumulative LPTA and later‐life cognition (Addenbrooke’s cognitive Examination (ACE‐III)) was assessed adjusting for brain health measures.ResultParticipation in LTPA was associated with better brain health at age 70. For brain volume and WMH volume, the strongest associations were with LTPA at age 69 (Figure 1). Being active in one or more period across adulthood was linked to larger hippocampal volume (Figure 1); this relationship was modified by APOE‐ε4 (p<0.01), with a stronger effect shown in ε4 carriers (Figure 2). LTPA at age 43 was also associated with larger hippocampal volumes. There was no evidence of associations with amyloid status. The positive association between cumulative LTPA and better cognition was not attenuated by any of the brain health measures (Figure 3).ConclusionWe provide evidence that LTPA across adulthood is linked to brain health at age 70; being active throughout adulthood was associated with larger hippocampal volume, particularly in APOE ε4 carriers; and being active in later‐life was linked to less WMH and larger brain volume at age 70. However, these brain health metrics did not explain the relationship between LPTA and better cognitive scores, suggesting that these pathways may not underlie the inferred cognitive benefit at this age. Our findings warrant further research to shed light on the mechanisms of physical activity as a potential disease‐modifying intervention of brain health.

Amyloidosis at Putamen Predicts Vulnerability to Alzheimer’s Disease

AbstractBackgroundUsing merely cortical amyloid burden in a binary approach was commonly adopted for determining if an individual is under AD pathology in both clinical trials and basic research. Subcortical amyloid, compared to cortical amyloid, showed a larger inter‐subject heterogeneity, which may provide valuable insights to their vulnerability to Alzheimer’s disease beyond cortical amyloid.MethodA total of 1344 individuals from ADNI database had 18F‐AV45 amyloid PET scans available. Regional AV45 signal was computed by averaging the signal from gray matter voxels in each region and then normalized to the mean signal in the composite reference region [1, 2]. The cortical AV45 was averaged over extensive regions consisting of frontal, anterior/posterior cingulate, lateral parietal, and lateral temporal regions. The AV45 signal in the subcortex, including putamen and caudate, were also computed. Only the participants under AD pathology, determined based on cortical amyloid positivity, were included in the analysis. The association analysis between subcortical AV45 and cognition was conducted before and after adjusting cortical AV45. A linear fitting of cortical AV45 and AV45 at putamen was conducted and participants were categorized into high (HighP), middle (MidP) and low (LowP) putamen amyloid group thresholded with ±0.5 standardized residuals. Statistical analysis was carried out to evaluate the difference of clinical diagnosis, hippocampal volume and APOE ε4 genotype. The relevance of amyloid at putamen with the rate of cognitive decline was examined.ResultPutamen, compared to caudate, had a stronger association with ADAS‐cog13 and MoCA, such an association remained exist after adjusting cortical AV45. Despite distinct AV45 at putamen, participants in LowP, MidP and HighP groups had no cortical AV45 difference. The AV45 at putamen was significantly higher in individuals with more ε4 alleles (ε4 homozygous > ε4 heterozygous > non‐ ε4) and more advance clinical stages (Dementia > MCI > CN). The individuals with higher AV45 at putamen had smaller hippocampal volume and faster cognitive decline.ConclusionOur finding suggested that amyloidosis at putamen is a valuable imaging marker beyond cortical amyloid in predicting if a participant is more vulnerable to Alzheimer’s dementia.

Sexual dimorphisms in longitudinal associations of the blood lipidome with cognitive decline in Alzheimer’s disease

AbstractBackgroundLate‐onset Alzheimer’s disease (AD) is the leading cause of dementia with neither cure nor a clearly understood disease trajectory. Previous studies have shown cross‐sectional and longitudinal associations of the blood lipidome and AD. We previously reported on significant sex differences in the associations of lipids with AD biomarkers and it has been suggested that such sex differences may result in distinct trajectories of AD progression. We performed an association study of sex‐stratified longitudinal lipidomics data with cognitive function to further characterize sexual dimorphisms in lipidomic manifestations of AD.MethodWe used a subset of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset: 1349 individuals (745 males and 604 females) with blood samples and clinical data collected at 10 time points with intervals of 6 to12 months (4145 samples total). We analyzed 749 lipid species measured by quantitative LC‐MS lipidomics profiling (Baker Heart and Diabetes Institute, Melbourne, Australia). We calculated linear mixed models (LMMs) and generalized additive mixed models (GAMMs) to analyze time‐resolved associations between lipids and two composite cognitive scores (ADNI memory and executive function) while adjusting for age, sex (pooled analysis only), BMI, HDL‐C, total cholesterol, copies of APOE ε4, years of education as well as significant medication effects.ResultWe observed a significant difference in lipid concentrations between males and females in line with previous studies, however, these differences were not fully consistent across diagnostic groups. In longitudinal association analyses, we found a substantial fraction of lipid species to have significant sex‐specific associations with cognitive function, which were not observed in the pooled analysis. These lipids were distributed across several lipid classes with enrichment in phosphatidylcholines (PC), phosphatidylethanolamines (PE) and triglycerides (TG). Comparisons between LMMs and GAMMs further indicated that some lipids might have a nonlinear relationship with cognitive trajectories.ConclusionOur results suggest that there are substantial sex differences in longitudinal associations of the blood lipidome with cognitive decline resulting in complex and partially nonlinear relationships. The highlighted lipid pathways can serve as a starting point to better characterize sex‐specific molecular changes linked to cognitive decline in AD.

Plasma amyloid‐β, total tau, and neurofilament light chain across the Alzheimer clinical spectrum: a population‐based study

AbstractBackgroundPlasma biomarkers have emerged as a promising approach for defining mild cognitive impairment (MCI) and Alzheimer’s disease (AD). We aimed to characterize Alzheimer’s plasma biomarkers across the clinical continuum of AD, and to assess their ability to differentiate between MCI, AD, and normal cognition.MethodThis population‐based study engaged 1446 rural‐dwelling older adults (age≥60 years, 61.0% women) derived from Multimodal Interventions to Delay Dementia and Disability in Rural China study; of these, 902 were defined with normal cognition, 402 with MCI, and 142 with AD according to the international criteria. Plasma amyloid‐beta (Aβ), total‐tau (t‐tau), and neurofilament light chain (NfL) concentrations were analysed using Simoa platform. Data were analysed using the logistic and general linear models, and receiver operating characteristic (ROC) analysis.ResultPlasma concentrations of Aβ40, Aβ42, t‐tau, and NfL were significantly increased with age (P<0.01). Women had higher plasma Aβ2 (age‐adjusted β = 0.62; 95%CI = 0.30‐0.94), Aβ42/Aβ40 ratio (0.19; 0.01‐0.36) and lower NfL concentrations (‐0.11; ‐0.16‐ ‐0.06). Plasma Aβ42 (age‐ and sex‐adjusted β = ‐0.73; ‐1.15‐ ‐0.31) and Aβ42/Aβ40 ratio (‐0.51; ‐0.74‐ ‐0.29) were lower in APOE ε4 carriers than that in non‐carriers. Plasma Aβ40 and Aβ42/Aβ40 ratio showed an increased and decreased trend, respectively, across AD clinical spectrum. Plasma t‐tau and t‐tau/Aβ42 ratio were higher in people with AD than those with MCI or normal cognition. Plasma NfL was increased across the AD clinical continuum and outperformed other Alzheimer’s biomarkers in differentiating AD from normal cognition (area under the ROC curve [AUC] = 0.75). However, all of these plasma biomarkers performed poorly to distinguish MCI from normal cognition (AUC<0.60). When adding plasma NfL to the basic model that included age, sex, education, and APOE genotype, the AUC was 0.87 for differentiating between AD and normal cognition, 0.79 between AD and MCI, and 0.64 between MCI and normal cognition.ConclusionAge, sex, and APOE genotype should be considered in clinical interpretation of Alzheimer’s plasma biomarkers. Plasma Aβ, t‐tau, and NfL concentrations differ across the cognitive continuum, but plasma NfL, which starts to elevate in the early stages of AD development, appears to be superior than plasma Aβ and t‐tau for defining cognitive continuum in old age.