APOE Ε4 Carrier Status Research Articles

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.

Sex Differences on Tau, Astrocytic and Neurodegeneration Plasma Biomarkers

AbstractBackgroundSex differences have consistently been identified on autopsy, neuroimaging, and cerebrospinal fluid outcomes related to Alzheimer’s disease (AD). Mechanisms for these associations are unclear. Blood‐based biomarkers are practical alternatives for the investigation of mechanisms of AD, in addition to accurate disease detection and monitoring. The objective of this study was to examine sex differences across a panel of blood‐based plasma biomarkers in participants with and without cognitive impairment due to AD.MethodsThe sample included 567 participants (248 males, 319 females) from the Boston University AD Research Center (BUADRC). Participants completed a battery of neuropsychological tests. Cognitive diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. All participants had at least one blood draw between 2008 and 2018 at the BUADRC. Plasma samples were analyzed using Simoa for phosphorylated tau (p‐tau181), total tau (t‐tau), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). Linear regression models tested associations between sex and each plasma biomarker, controlling for age, racial identity, education, and APOE ε4 carrier status. Analyses were repeated stratified by APOE ε4 carrier and CDR status.Results Table 1 shows sample characteristics (mean age = 74.41, 13.3% Black/African American). As shown in Table 2, the multivariable linear regressions showed significant sex effects for plasma GFAP, such that females had higher plasma GFAP levels than males (p<.001). Among APOE ε4 carriers (n = 223) and participants with a CDR≥1 (n = 111), the associations with GFAP remained and the magnitude of associations were stronger compared to APOE ε4 non‐carriers and those with a CDR<1. Figure 1 shows plots of the association between sex and each plasma biomarker. There were no other sex effects across the other plasma biomarkers in the entire sample or when stratified by APOE ε4 carrier or CDR status.ConclusionsFemales had higher plasma GFAP levels than males regardless of APOE ε4 status and cognitive status. Reactive astrocyte processes associated with neurodegenerative diseases can be measured by plasma GFAP. Biological differences in these processes may explain observed associations between sex and risk for AD. The study highlights the dynamic utility of plasma biomarkers for the study of AD and longitudinal analyses of this cohort are planned.

Positron emission tomography (PET) imaging of neuroinflammation in healthy and Alzheimer disease participants using TSPO tracers

AbstractBackgroundAlzheimer’s disease (AD) is the most common type of dementia. In addition to the widely recognized accumulation of amyloid and tau protein being the core pathology of AD, neuroinflammation is another cause of brain dysfunction and structural change. Expression of translocator protein (TSPO) on the outer mitochondrial membrane of activated microglia is strongly associated with neuroinflammation. With the development of TSPO positron emission tomography (PET) tracer, we were able to evaluate neuroinflammation non‐invasively in a clinical cohort of AD spectrum.MethodCognitively impaired patients (including AD and mild cognitive impairment (MCI)) and cognitively normal controls (CN) were recruited from single dementia clinic. [18F]FEPPA, the second‐generation PET ligand specifically binds TSPO was synthesized fully automated. Structural brain MRI and functional PET imaging were performed simultaneously with a PET/MR scanner (SIGNA, GE Company, USA). Kinetic analyses were performed using PMOD 4.2 modeling software. Total distribution volume (VT) in each ROI, including frontal, temporal, inferiolateral parietal, occipital, hippocampus and cerebellum, were derived from a two‐tissue compartment model (2‐TCM). In addition, APOE and rs6971 polymorphism genotyping were conducted in all subjects. Mann‐Whitney U Tet, Kruskal‐Wallis Test and linear correlation were performed.ResultA total of 39 participants (23 males and 16 females) participated, including 13 cognitively normal, 9 with MCI and 17 with Alzheimer’s disease. The rs6971 genotype had no significant effect on [18F]FEPPA binding to TSPO. The amount of TSPO expression was independent of age, gender, and APOE ε4 carrier status. The VT of each ROI did not differ significantly between cognitive groups. VT of frontal, temporal, inferiolateral parietal and occipital lobe were all negatively correlated with MMSE, Boston Naming Test and Trial Making A performance. However, such association was not observed between VT of hippocampus and cognitive tests.ConclusionAlthough there was no difference between TSPO expression in each ROI among cognitive groups, we still observed that higher TSPO expression in the cortex was associated with worse performance in certain cognitive tests. This implied that the increase in neuroinflammation was related to the decline of cognitive performance regardless of cognitive diagnosis.

Tau pathway‐based gene analysis in the Alzheimer’s disease continuum identifies CLU and FYN associated with tau deposition on PET in a Korean Cohort

AbstractBackgroundAbnormal tau protein aggregation and spreading in the brain is closely linked to cognitive impairment and neurodegeneration in Alzheimer’s disease (AD). The role of genetic variation in brain tau aggregation has not been fully elucidated. Here, we performed pathway‐based candidate gene association analysis to identify novel genes associated with brain tau deposition on PET in a well‐characterized Korean AD continuum Cohort.MethodWe analyzed data for 145 older adults (69 cognitively normal (CN), 38 mild cognitive impairment (MCI), and 38 AD) from the Korean Brain Aging Study for the Early Diagnosis and Prediction of AD (KBASE). We selected 15 candidate genes related to both tau pathways and AD, curated from existing pathway databases, literature mining, and genome‐wide association study findings. We performed gene‐based association analysis of tau deposition measured by 18F‐AV‐1451 PET scans using PLINK. In addition, we performed whole brain voxel‐wise association analysis of identified single nucleotide polymorphisms (SNPs) to investigate their topographic distributions of differences in tau deposition across the whole brain using SPM12. We examined the interaction of the identified SNPs with APOE ε4 carrier status.ResultGene‐based analysis identified CLU and FYN as significantly associated with tau deposition after adjusting for multiple testing. The most significant signals originated from rs149413552 in CLU and rs57650567 in FYN. A voxel‐wise analysis for the two SNPs showed that individuals carrying at least one minor allele demonstrated greater tau throughout the temporal, parietal, and frontal lobes than individuals having no minor alleles (Fig. 1). The two SNPs were associated with greater cortical atrophy of AD‐signature regions and worse global cognition. rs149413552 in CLU was also associated with longitudinal decline in global cognition and immediate verbal memory over two years. APOE ε4 and the two SNPs appeared to exert additive effects on tau levels (Fig. 2). An interaction between rs57650567 in FYN and APOE ε4 carrier status was observed (Fig. 2)Conclusion CLU and FYN may play a specific role in tau pathophysiology. These risk genes may prove useful for biomarker and therapeutic development. Larger and multiethnic studies are needed to confirm these findings and to determine generalizability across populations.

Evaluating brain age as a marker of autosomal dominant Alzheimer disease progression

AbstractBackgroundEstimates of “brain‐predicted age” quantify apparent brain age compared to normative trajectories of neuroimaging features. Brain‐predicted age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD). We used a previously‐trained model (DeepBrainNet [DBN], Bashyam et al., 2020), which requires minimal MRI pre‐processing, to predict brain age in the Dominantly Inherited Alzheimer Network (DIAN) and evaluated brain age as a marker of ADAD progression.MethodWe used DBN to predict brain age from minimally‐processed, whole‐brain T1 structural MRI scans in 265 ADAD mutation‐carriers (MCs) and 183 non‐carrier controls (NCs). We then tested whether the brain age gap (BAG; difference between predicted and true age) differed as a function of mutation and cognitive status, or estimated years until symptom onset (EYO), and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid‐ß‐42/40), phosphorylated tau (CSF and plasma pTau‐181), neurodegeneration (CSF and plasma neurofilament light [NFL]), and cognition (global neuropsychological composite and CDR‐sum of boxes). Finally, we compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of mutation variants (APP vs. PSEN1 before or after codon 200), APOE E4 carrier status, sex, and education.ResultDBN accurately predicted age in DIAN (Figure 1A). BAG was elevated in symptomatic and asymptomatic MCs, compared to NCs, beginning around ‐10 EYO (Figure 1B,C). BAG, hippocampal volume, and a cortical thickness summary followed similar trajectories across EYO (Figure 1D). BAG was positively associated with PiB PET, CSF and plasma pTau, and CSF and plasma NFL, and was associated with worse cognitive scores, especially in symptomatic MCs (Figure 2). BAG was most elevated in MCs with a PSEN1 mutation before codon 200, but did not differ as a function of APOE, sex, or education (Figure 3).ConclusionWe extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG tracks well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, DBN‐based BAG offers unique benefits in simplicity of data processing and interpretation.

The moderating effect of APOE E4 on the association of plasma biomarkers with markers of cognition and brain health in Alzheimer’s disease

AbstractBackgroundDue to low success rates in clinical trials for Alzheimer’s disease (AD), there is a need to apply precision medicine approaches, such as stratifying based on APOE genotype, in order to assess its effects on outcome measures. Herein, we aim to better understand how plasma biomarkers of AD and neurodegenerative pathology are associated with cognition and neurodegeneration in APOE E4 carriers compared to non‐carriers.MethodPatients from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) diagnosed with AD were included (n = 126, age = 71.0±8.2, 55%M). Plasma concentrations of Aβ40 and Aβ42 (Aβ42/40 ratio), glial fibrillary acidic protein (GFAP), neurofilament light (NfL) and phosphorylated‐tau181 (p‐tau181) were measured using Simoa assays. Composite cognitive domain scores (attention & working memory, executive function, language, memory, and visuospatial function) were computed from a comprehensive neuropsychological assessment. Volumes of regional grey matter, ventricular cerebrospinal fluid, white matter hyperintensities, perivascular spaces, lacunes and strokes were extracted from 3T structural MRI sequences using the SABRE pipeline. Linear regression models with an interaction term, controlling for age, sex and education were used to test the moderating effect of the APOE E4 allele on the association of plasma biomarkers with cognitive and MRI variables. When interaction effects were significant, post‐hoc models stratified by APOE E4 carrier status and controlling for age, sex and education were assessed.ResultThe APOE E4 allele moderated the association of GFAP, NfL and p‐tau181 with memory. Further stratification revealed that higher levels of GFAP, NfL and p‐tau181 were all associated with worse memory only in APOE E4 carriers. APOE E4 was also found to moderate the association of GFAP and p‐tau181 with many imaging markers. Further stratification revealed that higher levels of GFAP were associated with increased white matter hyperintensities, ventricular expansion and grey matter atrophy (temporal lobe, occipital lobe, hippocampus, basal ganglia and thalamus) only in APOE E4 carriers. Higher levels of p‐tau181 were also associated with increased temporal, parietal, and hippocampal atrophy only in APOE E4 carriers.ConclusionPlasma biomarkers, especially GFAP and p‐tau181, appear to be significantly more predictive of memory deficits and brain neurodegeneration in APOE E4 carriers compared to non‐carriers in AD.

Genome‐wide association meta‐analysis identifies a novel LRBA locus for brain age acceleration in two independent Korean Cohorts

AbstractBackgroundAging is a key risk factor for Alzheimer’s disease (AD) and has a significant structural impact on the brain. Machine learning approaches have been developed to estimate the biological age of the brain from MRI scans. Here, we performed genome‐wide association (GWA) analysis of accelerated brain aging in two independent Korean AD cohorts.MethodParticipants included 1,738 Korean older adults from two independent cohorts that consisted of preclinical and clinical stages of AD (n = 1,209 from the K‐ROAD cohort (Korea‐Registries to Overcome and Accelerate Dementia Research Project) and n = 529 from the KBASE cohort (Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease)). Brain age was estimated from structural MRI scans using brainageR. Brain age acceleration (predicted brain age ‐ chronological age) was calculated for each participant. Genetic variants associated with brain age acceleration were assessed after accounting for age, sex, APOE e4 carrier status, and diagnosis. Meta‐analysis was performed using METAL, followed by transcriptomic analysis. Polygenic risk scores for brain age acceleration were calculated with PRS‐CS using GWAS meta‐analysis summary statistics, followed by molecular imaging analysis.ResultGWA meta‐analysis identified six intronic SNPs in the LRBA (Lipopolysaccharide responsive Beige‐like Anchor) locus on chromosome 4 as significantly associated with brain age acceleration with the most significant signal at rs7699001 (Fig. 1; p<5´10−8). LRBA is highly expressed in the brain, especially in microglia. The LRBA gene is differentially expressed in AD compared to cognitively normal older adults. rs7699001 was associated with expression levels of the LRBA gene in tissue from several organs including brain. rs7690001 has been reported to be associated with inferior parietal cortical thickness in non‐Hispanic whites (p = 5´10−3). Polygenic risk scores of brain age acceleration in the K‐ROAD cohort were significantly associated with amyloid‐β deposition measured from amyloid PET scans (Fig. 2; p = 2.7´10−4).Conclusion LRBA is a novel genetic risk factor for brain aging in the Korean population with relevance for AD. The microglial LRBA protein may be involved in phagocytosis, which has been implicated in aging processes and AD progression. Replication in other populations and mechanistic follow‐up studies are warranted.This work was supported by U01AG072177.

Exposure‐response modeling to describe the change in brain amyloid following lecanemab administration in patients with early Alzheimer’s disease

AbstractBackgroundLecanemab is a humanized IgG1 monoclonal antibody that binds with high affinity to Aβ soluble protofibrils. Lecanemab has been tested as a disease‐modifying treatment for early Alzheimer’s disease in two clinical studies (NCT01767311 and CLARITY‐AD, NCT03887455). As part of these studies, amyloid PET scans were collected in a subset of patients, demonstrating that lecanemab leads to pronounced reduction in brain amyloid.MethodA model describing the relationship between serum lecanemab exposure and brain amyloid reduction from baseline was developed using data pooled from Phase 2 and 3 studies. Individual serum lecanemab exposure was estimated using a population PK model and correlated with amyloid PET using an indirect response model, with a lecanemab‐dependent increase in the degradation rate of amyloid, introduced as linear function. The model was parametrized in terms of baseline amyloid load, elimination rate constant for amyloid removal (Kout) and exposure effect (DESLP). Inter‐subject variability was estimated for each of the model parameters. Covariates were included in the model using a forward‐inclusion (p<0.01) /backwards‐elimination (p<0.001) approach.ResultA total of 4129 observations from 1088 subjects were included in the dataset. The model estimate of Kout was 0.0496 yr−1 (95% confidence interval: 0.0206, 0.0827), suggesting a re‐accumulation half‐life of brain amyloid of ∼14 years. APOE4 carrier status (homozygous and heterozygous together) was a statistically significant predictor of baseline amyloid (APOE4 noncarriers: 65 CL; APOE4 carriers: 83 CL). Age was a significant covariate on DESLP, with older patients removing amyloid at a faster rate than younger patients. None of the other covariates explored, including presence of antidrug antibodies or baseline MMSE score, had a statistically significant effect on any model parameter.ConclusionAn exposure‐response model has been developed that describes the change in brain amyloid over time during treatment with lecanemab and after stopping lecanemab treatment. This model provides additional insights into factors that may drive differences in the rate of brain amyloid removal between patients.

Associations of NREM Slow Wave Activity and Regional in‐vivo tau PET deposition in black and white community‐dwelling cognitively normal older‐adults with normal sleep

AbstractBackgroundIn this proof‐of‐concept study, we examined whether NREM slow wave activity (SWA) is associated with regional in‐vivo tau deposition; and whether race‐specific differences exist in this association, in clinically normal older adults with normal sleep, in the context of Aβ.MethodThis was a cross‐sectional analysis of baseline data from 21 community‐dwelling cognitively normal older‐adults with normal sleep. Participants were matched on age, sex, BMI, and APOE4 carrier status in a 1:3 ratio, blacks: whites. Normal sleep was defined as 6‐9 h of total sleep time and absence of AHI4%>15 and AHI4%>5 with sleepiness. SWA was defined as power between 0.5‐4.0 Hz during NREM with NREM cycles characterized as stages NREM 2‐3 of ≥15 min. terminated by rapid eye movement (REM) or wakefulness of ≥5 min. Tau burden was assessed using 18F‐PI2620. Linear mixed‐effects models with random intercept and slope were used to assess associations between NREM SWA, and regional in‐vivo tau PET deposition, respectively, controlling for Aβ, age, BMI, sex, APOE4‐status, education and other sleep variables.ResultOf the 21 participants, 7 (33.3%) were black, 12 (57.1%) were women and 5 (24%) were APOE4 carriers. The mean (SD) age, and education were 69.1 (5.5), and 17.2 (3.8) years respectively. NREM SWA was associated with tau deposition in the entorhinal cortex, inferior and middle temporal ROIs, including gray matter neocortical ROIs i.e., anterior ventral striatum, orbitofrontal, precuneus, superior frontal, lateral temporal and posterior cingulate gyrus cortices (p <.01 for all). Racial differences existed in the entorhinal cortex, and inferior and middle temporal ROIs, including the lateral temporal, parietal, precuneus and posterior cingulate gyrus cortices (p <.02 for all), with black participants having lower tau levels relative to white participants. Divergent NREM SWA and tau associations were observed in the entorhinal cortex, precuneus, and inferior and middle temporal ROIs with NREM SWA negatively correlated with tau‐PET levels in whites and positively correlated in blacks.ConclusionRacial differences in physiological sleep features, uniquely associated with tau levels in the brain, may reflect one mechanism of how sociocultural factors, often through behavioral processes, become physiologically expressed as increased AD‐risk in blacks.

Brain age gap, dementia risk factors and cognition in middle age

AbstractBackgroundBrain Age Gap (BAG) represents the difference between an individual’s predicted age, derived from machine learning models trained on neuroimaging data, and their chronological age. BAG has been associated with dementia and cognition in old age. Less is known relating BAG to dementia risk‐factors or cognitive performance in middle‐age.MethodCognitively healthy, middle‐aged (40‐59 years) subjects from PREVENT‐Dementia had an array of neuropsychological, neuroimaging and genetic assessments. Brain Ages were predicted from T1‐weighted 3T MRI scans. Cognition was assessed using COGNITO. Multiple linear robust regression models tested hypotheses that: (i) BAG is positively associated with dementia risk‐factors; (ii) increased BAG is associated with worse cognition; (iii) longitudinal BAG change is positively associated with longitudinal cognitive deterioration. A range of machine learning algorithms with nested cross‐validation was used to assess whether BAG and cognition could predict each other.Result552 middle‐aged participants (median age 52.8 years) had all baseline assessments; 68 had amyloid PET data and 138 had longitudinal data. Median BAG was ‐2.0 years with a range from ‐21.2 to 18.4 years (Figure 1). BAG in middle‐age was associated with hypertension (p = 0.007) and alcohol intake (p = 0.008) but not APOE4 carrier status (p = 0.14) or amyloid centiloids (p = 0.53). BAG was not associated with cognitive performance either cross‐sectionally (p = 0.74) or longitudinally (p = 0.30), and there was no added predictive value between BAG and cognition. More education was associated with better cognition (p = 4.7×10−11) but not with BAG (p = 0.32).ConclusionEven in midlife, substantial inter‐individual heterogeneity exists in the extent to which brains have aged. BAG in middle‐age is associated with modifiable dementia risk‐factors, suggesting that lifestyle risk‐factor modification needs to start at, or before, midlife to optimise brain health. BAG in middle‐age was not associated with risk‐factors for Alzheimer’s disease (APOE4, amyloid deposition) or cognitive performance, despite there being a plausible and expected association between more education and better cognitive performance. These results are important for understanding brain‐age in middle‐aged populations who might be the target of future dementia‐preventing therapies.

APOE4 Carrier Status Modifies Alzheimer’s Disease Plasma Biomarker Concentrations in Healthy Adults Over 85 Years Old

AbstractBackgroundMany blood‐based biomarkers have been thoroughly investigated in the context of Alzheimer’s disease (AD) and other dementias. However, few studies have examined these biomarkers in healthy seniors in the absence of dementia or other age associated morbidities. Investigating biomarkers in a healthy geriatric population allows for the identification of novel biological associations that might otherwise be masked by presence of disease. This study will investigate the effect of APOE genotype on plasma biomarkers of AD to determine whether carrying the APOE4 allele, which increases risk of AD, modifies biomarker concentrations in healthy seniors. Plasma biomarkers analyzed include: amyloid beta 42/40 (Aβ42/40), phosphorylated tau‐181 (p‐tau‐181), neurofilament light (NF‐L), and glial fibrillary acidic protein (GFAP).Methods370 plasma specimens from the Super Seniors study, which enrolled participants ≥85 years old who have never been diagnosed dementia, cancer, diabetes, cardiovascular or major pulmonary disease; were used. Biomarkers were analysed on the Quanterix Simoa HD‐X analyzer using commercial Neurology 4‐plex E and p‐tau‐181 assays. Group comparisons were performed using a Mann‐Whitney test for continuous variables and a Fisher’s exact test for categorical variables. The association between APOE genotype and biomarker concentration was analyzed using multivariable linear regression.Results80 (22%) participants were APOE4 carriers (E3E4 N = 71, E4E4 N = 3, E2E4 N = 6) and 290 (73%) were non‐carriers (E2E2 N = 3, E2E3 N = 58, E3E3 N = 229). No significant differences were found between APOE4 carriers and non‐carriers in age (p = 0.3215), sex (p>0.9999), or mini mental state exam scores (p = 0.1327). In APOE4 carriers, Aβ42/40 is lower (0.0596 vs 0.0618 pg/ml, p = 0.0462), and p‐tau‐181 (3.24 vs 2.78 pg/ml, p = 0.0069) and GFAP (196 vs 172 pg/ml, p = 0.0474) are higher than in non‐APOE4 carriers. NF‐L had no significant difference between carrier status (p = 0.1188). After adjusting for age and sex, p‐tau‐181 remains significantly associated with APOE4 carrier status (β = 0.066, p = 0.0112), while Aβ42/40 and GFAP no longer have significant associations.Conclusionsp‐tau‐181 concentration is associated with APOE4 genotype in healthy seniors, making it an important variable to account for in future analysis.

Fully automated ApoE4 assay in plasma and the estimation of the APOE polymorphism

AbstractBackgroundApolipoprotein E (ApoE) is a major cholesterol carrier that supports lipid transport and injury repair in the brain. APOE polymorphic alleles are the main genetic determinants of Alzheimer disease (AD) risk: individuals carrying the ε4 allele are at increased risk of AD compared with those carrying the more common ε3 allele, whereas the ε2 allele decreases risk. Moreover, it has been reported that the APOE4 haplotype has a dose‐dependent association with an increased risk of amyloid‐related imaging abnormalities (ARIA) in individuals receiving disease‐modifying therapy (DMT) for AD. Therefore, the importance of APOE genotyping or phenotyping and its expanding clinical role in dementia field has been highlighted. Here, we developed fully automated chemiluminescence enzyme‐immunoassay (CLEIA) kits for ApoE4 and pan‐ApoE, and evaluated its diagnostic concordance with the APOE genotyping.MethodApoE4 and pan‐ApoE assays for fully automated platform, LUMIPULSE, are a two‐step sandwich CLEIA with a specific treatment process to extract the antigen from the lipid surface in plasma samples during the 1st immunoreaction. The turnaround time for each reaction is within 30 minutes. Healthy volunteers’ samples were used for the measurement of ApoE4 and pan‐ApoE with CLEIA or the PCR‐Restriction fragment length polymorphism (PCR‐RFLP) analysis for the APOE polymorphism. The study design was approved by the ethics committee at H.U. Group Holdings, Inc in the 2022 fiscal year (22‐012‐01).ResultThe ApoE4 kit specifically detected the ApoE4 concentration in plasma samples, and could distinguish ApoE polymorphism. Moreover, the polymorphism could be classified clearly by the ratio of ApoE4 and Pan‐ApoE amount in plasma.ConclusionThe new CLEIA ApoE4 and pan‐ApoE assay robustly distinguishes among APOE4 carrier status in plasma. Assessing ApoE isoform by CLEIA may help not only clarify ApoE metabolism, but also ARIA risk.

Associations of NREM Slow Wave Activity and Regional in‐vivo tau PET deposition in black and white community‐dwelling cognitively normal older‐adults with normal sleep

AbstractBackgroundIn this proof‐of‐concept study, we examined whether NREM slow wave activity (SWA) is associated with regional in‐vivo tau deposition; and whether race‐specific differences exist in this association, in clinically normal older adults with normal sleep, in the context of Aß.MethodThis was a cross‐sectional analysis of baseline data from 21 community‐dwelling cognitively normal older‐adults with normal sleep. Participants were matched on age, sex, BMI, and APOE4 carrier status in a 1:3 ratio, blacks: whites. Normal sleep was defined as 6‐9 h of total sleep time and absence of AHI4%>15 and AHI4%>5 with sleepiness. SWA was defined as power between 0.5‐4.0 Hz during NREM with NREM cycles characterized as stages NREM 2‐3 of = 15 min. terminated by rapid eye movement (REM) or wakefulness of = 5 min. Tau burden was assessed using 18F‐PI2620. Linear mixed‐effects models with random intercept and slope were used to assess associations between NREM SWA, and regional in‐vivo tau PET deposition, respectively, controlling for Aß, age, BMI, sex, APOE4‐status, education and other sleep variables.ResultOf the 21 participants, 7 (33.3%) were black, 12 (57.1%) were women and 5 (24%) were APOE4 carriers. The mean (SD) age, and education were 69.1 (5.5), and 17.2 (3.8) years respectively. NREM SWA was associated with tau deposition in the entorhinal cortex, inferior and middle temporal ROIs, including gray matter neocortical ROIs i.e., anterior ventral striatum, orbitofrontal, precuneus, superior frontal, lateral temporal and posterior cingulate gyrus cortices (p <.01 for all). Racial differences existed in the entorhinal cortex, and inferior and middle temporal ROIs, including the lateral temporal, parietal, precuneus and posterior cingulate gyrus cortices (p <.02 for all), with black participants having lower tau levels relative to white participants. Divergent NREM SWA and tau associations were observed in the entorhinal cortex, precuneus, and inferior and middle temporal ROIs with NREM SWA negatively correlated with tau‐PET levels in whites and positively correlated in blacks.ConclusionRacial differences in physiological sleep features, uniquely associated with tau levels in the brain, may reflect one mechanism of how sociocultural factors, often through behavioral processes, become physiologically expressed as increased AD‐risk in blacks.

The Effects of Sex and APOE4 Genotype on Longitudinal Changes in White Matter Integrity Differ by Diagnostic Group Along the Spectrum of Alzheimer’s Disease

AbstractBackgroundSex and APOE ε4 (APOE4) are well‐established risk factors for Alzheimer’s disease (AD), with female ε4‐carriers at greatest risk. Uncovering the neurobiological substrates of sex and genetic effects in AD is critical to improve prevention, intervention, and treatment monitoring. While changes to white matter (WM) integrity are commonly noted in the progression of AD, it is unclear if these changes are further modulated by sex and APOE4 status. In the current study, we examined the effects of sex and APOE4 carrier status on WM integrity, both cross‐sectionally and longitudinally, across the AD continuum.MethodA total of 457 participants (233 cognitively normal (CN), 167 mild cognitive impairment (MCI), and 57 AD; 223 females; 187 APOE ε4‐carriers) was selected from the ADNI database, based on the availability two diffusion MRI (dMRI) sessions. The dMRI data were processed using FSL’s TBSS pipeline to quantify the degree of fractional anisotropy (FA). Annualized FA change maps were created to measure voxel‐wise WM change over time. The effect of sex, APOE4‐carrier status, diagnosis, and their interactions, on cross‐sectional and longitudinal WM integrity were assessed by FSL’s randomise and cluster‐level correction, controlling for age.ResultAt baseline, females exhibited greater FA than males in the fornix, right inferior fronto‐occipital fasciculus, left inferior and superior longitudinal fasciculus, while males showed greater FA in the left corticospinal tract. Additionally, there were widespread differences across the skeleton by diagnosis, with FA decreasing stepwise across the continuum (CN>MCI>AD). There were no APOE4‐related differences in baseline WM integrity. Longitudinally, a three‐way interaction between diagnosis, APOE4, and sex emerged within the corpus collasum, left anterior thalamic radiation, left corticospinal tract, left uncinate fasciculus, and left inferior and superior longitudinal fasciculus. Posthoc analyses revealed that within the AD group, but not CN or MCI groups, females underwent greater WM degeneration than males among nonε4‐carriers, while males showed greater WM degeneration than females among ε4‐carriers.ConclusionThese findings suggest that increased risk associated with sex and APOE4 genotype may change and interact with the progression of AD. Future studies are warranted to examine the contribution of cerebrovascular risk factors to AD progression in male ε4‐carriers.

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.

Exploring the Utility of Biofluid‐Based Biomarkers in Early‐Onset Alzheimer’s Disease

AbstractBackgroundOne goal of the longitudinal early onset Alzheimer’s disease study (LEADS) is to define fluid biomarker characteristics of early‐onset Alzheimer’s disease (EOAD). In this mid‐study cross sectional analysis, participants have undergone clinical and cognitive assessments, magnetic resonance imaging (MRI), positron emission tomography (PET), lumbar puncture, and blood draws. There is limited data available concerning comprehensive analysis of fluid biomarkers in an EOAD population and this study represents first results from the mid‐study analysis of a large multi‐site cohort.MethodLEADS is an observational study with N = 371 subjects included in the mid‐study analysis (N = 165 with CSF and N = 324 with plasma biomarker data). CSF levels of Aβ1‐40, Aβ1‐42, tTau, pTau181, VILIP‐1, SNAP‐25, neurogranin (Ng), neurofilament light chain (NfL), and YKL‐40 were measured by immunoassay. Plasma levels of Aβ1‐40, Aβ1‐42, NfL, pTau231, and glial fibrillary acid protein (GFAP) were measured by immunoassay. Differences by diagnostic group and Spearman’s correlations with cognitive measures (MOCA, CDR‐SB, ADAS‐Cog) were evaluated for each fluid biomarker. Diagnostic accuracies were determined using area under the curve of receiver operating characteristics curve analysis which included APOE4 carrier status, age and sex in logistic regression models.ResultLevels of CSF Aβ42/40, pTau181, tTau, SNAP25, and Ng in the EOAD group were significantly different from both cognitively normal and early‐onset non‐AD dementia groups; CSF NfL, YKL‐40 and VILIP‐1 did not vary by diagnosis. The combination of APOE ε4 carrier status, age, sex and CSF Aβ42/40 and pTau181 (Figure 1A) or plasma Aβ42/40 and pTau231 (Figure 1B) separated the EOAD group from CN and EOnonAD with Area Under the ROC curves of 0.99 and 0.89 respectively. The diagnostic accuracies of plasma Aβ42/40 or pTau231 were 0.80 and 0.86 respectively. In the pooled analysis, all CSF biomarkers except SNAP25 were correlated with cognition (Figure 2A). Within the EOAD group only CSF Aβ42/40, NfL, Ng, and SNAP25 were correlated with at least one cognitive measure (Figure 2B).ConclusionThis study provides the first comprehensive analysis of fluid biomarkers in sporadic EOAD and will inform clinical trial designs that incorporate fluid biomarkers in patient selection, or as biomarker endpoints.

The effect of APOEƐ4 on neurocognitive decline is accentuated by female sex and menopause: Identification of mitigating interventions

AbstractBackgroundTwo thirds of those living with AD are female. Age‐standardised AD prevalence is consistently higher at all ages over 70 years in women versus men. The aetiology of the accelerated neurophysiological decline in females is poorly understood. Here we investigate the independent and interactive impact of APOE4 carrier status and menopause.MethodTargeted replacement (APOE3‐TR and APOE4‐TR) rodent models and human cohort studies (European Prevention of Alzheimer’s Dementia (EPAD) and UK Biobank (UKB)) were used to investigate the impact of APOE4, menopause and hormone replacement therapy (HRT) on cognition, brain volumes (assessed by MRI), omega‐3 fatty acid status and synaptic function. In rodents, menopause is elicited by the administration of 4‐vinylcyclohexene diepoxide (VCD), which induces a human‐like “perimenopausal” phenotype, whilst maintaining ovarian tissue integrity.ResultsIn EPAD, using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test battery, HRT use in APOE4 only was associated with higher overall cognition and (delayed) memory scores and larger entorhinal and amygdala volumes in APOE4 only. Earlier HRT introduction was associated with larger hippocampal volumes. In UKB, HRT use was associated with improved memory in APOE4/E4. In mice, VCD administration reduced recognition memory, brain docosahexaenoic acid (DHA, omega‐3 fatty acid) levels, and altered synaptic plasticity biomarkers in APOE4‐TR animals, which was mitigated by DHA supplementation (1).ConclusionAn increased penetrance of the APOE4 genotype during the menopausal transition is likely to contribute to the higher incident AD in females, and in APOE4 females versus non‐carriers. HRT and DHA intervention during the menopausal transition, as a critical window of opportunity, may represent effective strategies to support cognitive health into older age in this ‘at‐risk’ (APOE4 female) group, which typically represent 12% of Caucasian populations compared and 33‐50% of AD.1. Pontifex MG et al., FASEB J. 2021 May;35(5):e21583

Butyrylcholinesterase Kalow variant reduces age‐of‐onset of Alzheimer Disease in apolipoprotein ɛ4 carriers

AbstractBackgroundPrevious investigations suggest carrier status for Karlow‐variant single‐nucleotide polymorphism (SNP) of butyrylcholinesterase (BCHE‐K) is associated with an earlier age‐at‐onset of AD in APOE4 carriers.MethodIn 45 mild AD patients, 50‐74 years, recruited into a clinical trial (NCT03186989), baseline characteristics were evaluated by BCHE‐K and APOE4 allelic status. Hypothesis tested that age‐at‐diagnosis of AD in APOE4 carriers was lowered in BCHE‐K carriers. Exploratory investigations conducted of associations of neuroimaging (ventricular and hippocampal volumes) and CSF biomarkers of amyloid (Aβ42), tau (p‐tau181), and neurodegenerative (NfL, Ng, PSD‐95) pathologies and glial activation (YKL‐40, GFAP, MCP‐1) across gender and genotype subgroups.ResultIn APOE4 carriers (N = 33), mean age‐at‐diagnosis of AD in BCHE‐K carriers (N = 11) was 6.4 years earlier than in BCHE‐K non‐carriers (N = 22, p < 0.001). In APOE4 non‐carriers (N = 12) there was no similar influence of BCHE‐K, but men (N = 8) had an age‐at‐diagnosis about 11 years earlier than women (N = 4). In APOE4 carriers, accumulation of amyloid and tau pathologies was slightly greater and ∼6 years earlier in BCHE‐K carriers versus non‐carriers. APOE4 allele frequency‐dependent increase in amyloid pathology observed with highest amyloid burden in APOE4 homozygotes that contrasted with lowest tau burden. Multiple regression analyses demonstrated that factors associated with amyloid accumulation included APOE4 carrier status (p < 0.05), larger total brain ventricle volume (p < 0.05), less synaptic injury (PSD‐95, p = 0.01; Ng, p < 0.001), and less tau (t‐tau and p‐tau181, p < 0.01). Factors associated with tau pathology included higher neuroaxonal damage (NfL, p = 0.002), higher synaptic injury (Ng, p <0.001; PSD‐95, p < 0.001), and higher glial activation (YKL‐40, p = 0.01). Phenotypic spectrum observed from predominant amyloid and limbic‐amnestic, exemplified by APOE4 homozygotes with BCHE‐K, to predominant tau, limbic‐sparing and multi‐domain cognitive impairment, exemplified in older women non‐carriers of APOE4 and BCHE‐K.ConclusionIn mild AD APOE4 carriers aged < 75 years, the mean age‐at‐diagnosis of AD was reduced by about 6 years in BCHE‐K carriers relative to non‐carriers. Relationships between biomarkers of amyloid and tau pathologies, neurodegeneration and glial activation, and putative cortical cholinergic denervation, suggested an age‐, gender‐ and genotype‐dependent phenotypic spectrum.

Association between known Alzheimer’s disease risk loci and in vivo brain amyloid pathology in a Korean Cohort

AbstractBackgroundMost genome‐wide association studies (GWAS) of Alzheimer’s disease (AD) have been conducted in populations of European ancestry. It is important to determine if known AD‐related variants from these studies are associated with AD biomarkers. Therefore, we investigated the association between known AD risk loci and in vivo brain Aβ deposition in older Korean adults.MethodParticipants (n = 503) from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s disease (KBASE) were analyzed. Older adults who were cognitively normal (CN), had mild cognitive impairment (MCI) or AD dementia (264 CN, 148 MCI, 91 AD) underwent comprehensive assessments including 11C‐PiB‐PET/MRI and blood sampling. Among 76 AD‐related target single nucleotide polymorphisms (SNPs) with genetic evidence compiled by the AD Sequencing Project (ADSP), 38 SNPs with minor allele frequency (MAF)>1% were extracted from TOPMed‐based imputed GWAS genotyping data in KBASE. We employed exploratory univariable logistic regression analysis with Aβ positivity as the dependent variable for each SNP. Then, SNPs with a significance level of p<0.05 were subjected to confirmatory multivariable logistic regression analysis, adjusting for age and sex, with Bonferroni correction.ResultIn the first step of exploratory analyses, we discovered significant differences in Aβ positivity rates between carriers and noncarriers of minor allele of several loci, including rs16824536 in MME, rs11218343 in SORL1, rs4985556 in IL34, rs4277405 in ACE and rs3851179, located in the intergenic region between EED and PICALM. The subsequent confirmatory analysis found an association between these variants and Aβ positivity after adjusting age and sex (Table 1). Notably, the negative association of rs3851179 with Aβ positivity remained significant after correcting for multiple comparisons and after controlling for APOE4 carrier status, age, and sex (OR 0.529, 95% CI 0.345–0.813).ConclusionWe identified associations between several known AD risk loci and Aβ positivity on PET. rs3851179, demonstrated a robust association with in vivo brain Aβ positivity that was independent of APOE4 status. Our findings suggest that rs3851179 may be protective for in vivo Aβ accumulation. Additionally, the findings are needed to be replicated in other populations with different ancestries.

A novel analytic approach to examine the relationship between APOE4 allele status and CSF complement‐related proteins and signaling pathways

AbstractBackgroundThe mechanisms by which the APOE4 allele contributes to AD risk are unclear. Here, we tested the hypothesis that in cognitively normal adults, APOE4 allele is associated with a decrease in complement‐related proteins and downregulation of complement‐related pathways.MethodUntargeted LC‐MS/MS proteomics was conducted on CSF samples (n = 118) from APOE3/3, APOE3/4 and APOE4/4 individuals over age 60, with groups matched on age and sex. We developed a novel analytic approach (which we term “up/down analysis”) based on the directional consistency of the β‐coefficients from a linear model for the intensities of peptides mapping to a given protein with respect to APOE4 carrier status (APOE4‐/ APOE4+). The analysis involves two steps: 1) The direction of the beta‐coefficient (positive/up or negative/down) for the level of each peptide (the outcome variable) due to APOE4 carrier status was derived from linear regression models adjusting for age, sex, and study. 2) These β‐coefficients were tallied for all peptides from a given protein (i.e. number of positive/up versus negative/down β‐coefficients). We then tested the probability under a binomial distribution that the distribution of up versus down peptides from each protein would be as, or more extreme than what we found, with a = 0.05. Pathway enrichment analysis (using p‐values from binomial tests) was conducted using GAGE and functional annotations based on KEGG. We used Benjamini‐Hochberg for multiple comparison correction.ResultWe found 158 proteins for which the direction of peptide intensity was consistently up (+β‐coefficient) or down (‐β‐coefficient) with respect to APOE4 status beyond what would be expected by chance. Of these 158 proteins, 37 were from the complement pathway. Pathway enrichment analysis further supports the role of the complement system; as the top differentially expressed pathway (FDR <0.05) was related to complement signaling.ConclusionOur results suggest that APOE4 carriers have lower CSF levels of key complement cascade proteins, which has previously been viewed as an indicator of complement activation. These results may provide insights into the mechanisms by which APOE4 and associated complement‐related proteins and signaling pathways ultimately contribute to increased AD risk.