ApoE Research Articles

APOE genotype, cognition and dementia: mediation of ε2 and ε4 effects by structural brain imaging markers in a population‐based study

AbstractBackgroundInsight into APOE‐mediated pathways is important to unravel pathophysiology and identify therapeutic targets against late‐life cognitive decline and dementia. However, ante‐mortem studies on the mediated effect of APOE on cognition and dementia through different disease markers on structural brain imaging remain scarce, in particular for APOE‐ε2.MethodWe included all dementia‐free participants from the population‐based Rotterdam Study, who routinely underwent cognitive assessment and brain MRI between 2005‐2009, and were followed‐up for incident dementia until 1‐1‐2020. We standardized hippocampal volume (HV) and volume of white matter hyperintensities (WMH), and performed causal mediation analyses to quantify the mediation effects (i.e., natural direct effect, natural indirect effect and percentage mediated) of APOE ε4 and ε2 carriership on cognition operationalized as g‐factor and incident dementia, with ε3/ε3‐carriers as a reference group. We adjusted all models for potential mediator‐outcome confounders (i.e., demographics, education, cardiovascular factors) and for intracranial volume.ResultAmong 5,510 participants (mean age: 65.0[±10.9] years, 55.0% women), 3,244 were ε3/ε3‐homozygotes, 709 ε2‐carriers, and 1,557 ε4‐carriers. During a median 11 years follow‐up, 349 participants developed dementia, of whom 148/1,557 ε4‐carriers (9.5%), 172/3,244 ε3/ε3‐carriers (5.3%) and 29/709 ε2‐carriers (4.1%). APOE‐genotype was not significantly associated with hippocampal volume (Figure 1), whereas those carrying APOE ε2 or ε4 tended to have a slightly higher volume of white matter hyperintensities (Figure 2). In total, 4% of the effect of ε4, and 7% of the ε2‐effect on cognition were mediated by HV. The percentage of the effect on cognition mediated through WMH was 18% for ε4 and 0% for ε2. For incident dementia, there was little to no evidence of mediation by either HV (ε4: 3%; ε3: 0%) or WMH (ε4: 1%; ε3: 0%), which was consistent in sensitivity analyses stratified by duration of follow‐up and by age (≥75 years).ConclusionIn this population‐based cohort study, we found that one fifth of the effect of APOE‐ε4 on cognition was mediated by WMH, compared to only 4% by lower HV. For dementia, however, we found no significant mediation effects of both HV and MWH, suggesting the involvement of alternative pathways through which APOE exerts its effect on dementia.

Disparity in Resilience: The role of educational attainment and APOE ε4 in Alzheimer Disease in a Puerto Rican cohort

Disparity in Resilience: The role of educational attainment and <i>APOE ε4</i> in Alzheimer Disease in a Puerto Rican cohort

APOE ε4 is associated with risk of clinical Alzheimer’s Disease Dementia independent of Hispanic ethnicity

APOE ε4 is associated with risk of clinical Alzheimer’s Disease Dementia independent of Hispanic ethnicity

Effects of APOE e4 and Neuropathological Diagnoses on Neuropsychiatric Symptoms: Mediation Analyses and Likely Causation in an Integrated NACC Database

AbstractBackgroundOur goal in this study was to identify paths from APOE e4 to neurobehaviors itemized on a neuropsychiatric inventory that involved neuropathologies associated with e4 (amyloid, tau, cerebral amyloid angiopathy, and Lewy bodies) or cognition mediators (memory or global cognitive status), as well as direct paths from e4 to cognition or neurobehaviors.MethodA total of 1199 cases with available neurobehavioral, cognition and neuropathological data were included. We then conducted a series of causal mediation analyses in R in which e4 always served as the independent variable and Neuropsychiatric Inventory (NPI) neurobehavioral items, when included in the mediation, the outcome. Neuropathologies or cognition served as mediators.ResultMultiple significant indirect paths from e4 through neuropathologies to neurobehaviors were identified. More refined analyses indicated that neuritic plaques and Braak stage, but not extent of diffuse amyloid plaques, drove the findings. A significant direct effect of e4 to memory was also identified. Additionally, Lewy body disease, when treated as an exposure, had a direct effect on hallucinations in keeping with known features of the disease.ConclusionWe found strong evidence for partial mediation of NPI symptoms by cognition, suggesting that cognitive limitations that may have influenced understanding (or misunderstanding) the environment with impacts on maladaptive behavior. In addition, neuritic amyloid plaque levels and Braak stage, but not diffuse amyloid plaque extent, were key in NPI mediated associations suggesting the possibility that synaptic failure play an important role in multiple neurobehavioral symptoms in dementia, including psychosis. Last, we found strong evidence that e4 may have direct effects on cognition when we used verbal episodic memory as an outcome, suggesting that medial temporal regions that support memory may be sensitive to non‐amyloidogenic and non‐tau related pathophysiological processes.

Impact of regional MAPT, APOE, and Aβ on tau propagation in Alzheimer’s disease: Insights from a connectome‐based simulation model

AbstractBackgroundTau pathology, a hallmark of Alzheimer’s disease (AD), is thought to spread cell‐to‐cell via axonal connections, beginning focally before expanding throughout the brain. This study uses computational models to investigate the interplay between network spread and regional vulnerability in influencing tau spread, focusing specifically on MAPT and APOE genes, and Aβ plaques.Method66 regional (Desikan‐Killiany atlas) tau‐PET standardized uptake value ratio (SUVR) values were extracted from participants in the Swedish BioFINDER‐2 study: 429 cognitively normal (CN), 91 subjective cognitive decline (SCD), 168 mild cognitive impairment (MCI), and 182 AD. Values were adjusted for mean choroid plexus signal and converted to tau‐positive probabilities using two‐component Gaussian mixture models. The Susceptible‐Infectious‐Recovered (SIR) model (Fig. 1A) was employed to simulate tau spread through brain networks measured using structural connectivity from young individuals. We examined the roles of MAPT, APOE, and Aβ in tau propagation by parameterizing them regionally to influence tau synthesis, clearance, spreading, or misfolding. Regional MAPT and APOE were extracted from Allen Brain Atlas, and Aβ from Aβ‐PET. Performance of both baseline models (connectivity‐only) and models incorporating regional biological information were evaluated based on their ability to reconstruct observed regional tau levels. Performance was evaluated across the whole sample and groups based on diagnosis, APOE e4 carriage and Aβ positivity.ResultThe SIR model recapitulates observed tau patterns, suggesting connectivity‐based propagation in early‐stage regions (Fig. 1B, C). Allowing regional MAPT to moderate normal tau synthesis improved the model fit overall, and for all groups except CN or Aβ‐ participants (Fig. 2,3). Regional APOE or Aβ information did not enhance the model performance overall (Fig. 2B, C). However, allowing regional APOE to moderate tau clearance showed better performance in APOE e4 carriers vs. non‐carriers, and allowing regional Aβ to moderate tau spread improved performance compared to baseline model among Aβ+ individuals (Fig. 3).ConclusionOur results suggest that brain connectivity explains early temporal lobe tau spread patterns, while regional intrinsic (MAPT) and disease‐related (Aβ) susceptibility may influence spread of tau into other regions at later stages. Future work will test other hypotheses of tau spread by refining this model with additional biological information.

APOE rare missense variants in Japan

AbstractBackgroundAPOE is well recognized to be the most influential susceptibility gene for Alzheimer’s disease (AD). For the wild‐type allele, e3, it is known that the e4 allele is a risk for AD, while the e2 allele is protective. Recently, genetic analyses with Caucasians have reported the critical associations between APOE rare missense variants (RMVs) and AD, and their importance has been pointed out in terms of disease pathogenesis of AD. For example, the Christchurch (rs121918393, p.R136S [CGC &gt; AGC]) and the Jacksonville (rs199768005, p.V236E [GTG &gt; GAG]) variants can be mentioned. Since there have been no such analyses or reports yet in East Asians, including Japanese, we designed this study.ObjectiveTo identify APOE RMVs in a Japanese population.MethodThrough the Tohoku Medical Megabank Organization (ToMMo) with a cohort of healthy Japanese community residents, APOE variant data were obtained from 3,307 subjects (1,810 females, and 1,497 males; mean age 55.9 years [standard deviation 14.1]) over 20 years old. Rare variants with amino acid substitutions were selected from them. The human genome database, Ensemble Human (GRCh38.p14), was searched to obtain the allelic frequency data of identified RMVs by populations. We also investigated the association with APOE common alleles, e2, e3, and e4, in the background of RMV carriers.ResultA total of 176 variants were identified in and around APOE in an approximately 7.2 kb genomic region in the ToMMo cohort. Of these, 14 were RMVs, including those previously reported. Four RMVs were found to be very rare, which were not found in the 1000 Genomes or gnomAD exomes/genomes databases. The 13 RMVs were inferred to be under the wild‐type allele, e3, as background.ConclusionThrough this survey, it became clear that there are RMVs of APOE that are unique to the Japanese population. In the future, we will expand the analysis to a discovery project on a scale of tens of thousands of individuals, including our subjects (n = approx. 2,500) collected so far. For the newly discovered RMVs, we plan to investigate their effects on the metabolism of amyloid beta and tau proteins in relation to AD.

Do Alzheimer Disease genetic loci influence the risk of Age‐Related Macular Degeneration?

AbstractBackgroundAlzheimer’s Disease (AD) and Age‐Related Macular Degeneration (AMD) are two age related neurodegenerative diseases that share multiple characteristics, including deposition of amyloid beta. In AD, amyloid plaque accumulation contributes to neurological dysfunction, while in AMD amyloid is a component of the hallmark retinal drusen complexes that lead to degeneration of central vision. Both diseases have significant and opposite risk due to the APOE e4 and e2 alleles. Investigation into other potential genetic similarities between the two diseases is warranted.MethodsVariants from the recent AMD meta‐analysis (Fritsche et al., 2016) and AD meta‐analysis (Bellenguez et al., 2022) were utilized to generate genetic risk scores (GRS) in an Amish founder population. 1293 individuals (1120 controls and 173 cases) were included in the AD analysis and 654 individuals were included in the AMD analysis (334 controls and 320 cases). AMD‐only and AD‐only GRSs were applied separately to both AMD and AD. We then combined both the AMD and AD variants into a single GRS applied to each disease. We subsequently removed AD SNPs sequentially from the GRS to identify any AD variants that might improve the association with AMD.ResultsAs expected, the AD‐only GRS successfully predicted AD (p = 0.01). However, the AMD‐only GRS was less successful in predicting AMD (p = 0.145). The combined AD/AMD GRS was more successful in predicting AMD (p = 0.12) than the AMD‐only GRS, while AD prediction decreased in performance (p = 0.67) compared to the AD‐only GRS. The sequential analysis identified thirteen AD variants that improved the AMD‐only GRS when combined with the AMD variants (p = 0.06).ConclusionsWhile the AD‐only GRS was most successful in predicting AD, the AD/AMD GRS outperformed the AMD‐only GRS in predicting AMD. These results suggest that several AD loci in addition to APOE may also influence AMD.

Associations between BDNF Val66Met and tau‐PET and episodic memory performance in sporadic AD

AbstractBackgroundIn the presence of abnormally high amyloid (Aβ+), carriage of the brain‐derived neurotrophic factor (BDNF) Val66Met polymorphism Met allele (Met66) is associated with faster clinical disease progression, greater neuronal loss and faster rate of CSF total‐tau and p‐tau181 compared to matched Val66 Aβ+ homozygotes. Aβ levels are unaffected by carriage of Met66. This suggests reduced neurotrophic support may accelerate Aβ‐related neuronal dysfunction and cognitive decline. We aimed to clarify the role of BDNF Val66Met in moderating region‐specific neurofibrillary tangle (NFT) formation in the brain in sporadic Alzheimer’s disease (AD).MethodData from 26 Aβ+ older adult Met66 carriers and 68 Val66 homozygotes enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were included in the analysis if they had at least one tau‐PET scan, Aβ‐PET scan, and neuropsychological assessment available. Participants were not excluded based on disease stage. ANCOVAs were conducted to determine, cross‐sectionally, whether levels of tau‐PET tracer retention at each Braak stage, episodic memory performance (measured on ADNI’s memory composite), and Aβ levels differed between Met66 carriers and Val66 homozygotes at the time of their first tau‐PET scan. Aβ levels, APOE ε4 status, sex, age, baseline diagnosis, and years of education were included as covariates.ResultAβ+ Met66 carriers showed significantly greater tracer retention in the entorhinal cortex (i.e., Braak 1) compared to Val66 homozygotes (p=.03), with the magnitude of this difference moderate (d=0.39; Table 1). There were no significant differences between Met66 carriers and Val66 homozygotes in tracer retention across all other Braak stages, episodic memory performance or Aβ levels (Table 1).ConclusionThe greater tau‐PET tracer retention in the entorhinal cortex in Met66 carriers may reflect their greater NFT pathology relative to Val66 homozygotes during early stages of AD. This is consistent with previous observations of higher levels of CSF total‐tau and p‐tau181 in Aβ+ Met66 carriers, both in sporadic AD and autosomal dominant AD. Together, these findings support the hypothesis suggesting that loss of neurotrophic support, associated with Met66 carriage, may confer greater vulnerability to Aβ‐related neurodegeneration compared to Val66 homozygosity.

Proteomic dementia risk assessment in adults with diabetes

AbstractBackgroundThe prevalence of dementia among adults with diabetes represents a significant health challenge. Current dementia risk assessment tools are not tailored to the diabetic population. This study aims to develop more precise dementia risk predictive models for patients with diabetes using extensive blood proteomics.MethodThis prospective cohort study utilized UK Biobank data, encompassing baseline assessments from 2006 to 2010 and follow‐up until September 1, 2023. Excluding individuals with pre‐existing dementia, we included 3015 participants with diabetes and they had available Olink blood proteomics data (approximately 3000 proteins). Feature selection was conducted using a least absolute shrinkage and selection operator (LASSO) regression, and Generalized Linear Models (GLM) were applied to create a proteomic risk model. This model was trained on a tested cohort of 2111 diabetic adults and validated on an additional 904 individuals.ResultOur model, incorporating 48 proteins, outperformed conventional clinical dementia risk assessment tools, including demographic factors (age, sex, education year, APOE ε4 status) and cognitive assessments. In the validation cohort, the model's receiver operating characteristic area under the curve value was 0.83, significantly higher than the 0.56 to 0.73 range for clinical models (Figure 1). The protein models showed effective calibration in the validation cohort (Figure 2). Participants were divided into four groups based on predicted risk, and the results showed that the higher the level of predicted risk, the greater the risk of dementia (Figure 3). Mendelian randomization suggested a causal link between several proteins and dementia, like apolipoprotein E. Pathway analysis emphasized proteins related to the extracellular matrix, endopeptidase inhibition, and neuron projection.ConclusionOur proteomic risk model has high predictive accuracy in identifying dementia risk in adults with diabetes. Because this model uses only blood proteins, it is easier to generalize to the general population and thus easier to guide preventive care in patients with diabetes.

Plasma insulin is an early biomarker of amyloid‐β pathology in Alzheimer’s disease

AbstractBackgroundEvidence suggests that type 2 diabetes (T2D) is an independent risk factor for Alzheimer's disease (AD), sharing similar pathophysiological traits like impaired insulin signaling. However, how plasma insulin changes with AD key pathologies and its diagnostics value remain unclear.MethodA total of 304 participants were included in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), assessing plasma insulin and cerebrospinal fluid (CSF) AD pathology. We explored the cross‐sectional and longitudinal associations between plasma insulin and AD pathology and compared their associations across different AD clinical and pathological stages. We also explored the potential diagnostic value of plasma insulin on AD pathology using the receiver operating characteristic (ROC) curves.ResultIn the non‐demented group, A+ participants (e.g., as reflected by CSF Aβ42) exhibited significantly reduced plasma insulin levels compared to non‐demented A‐ participants (P &lt; 0.001). Furthermore, A+T‐ participants (e.g., as reflected by CSF Aβ42 and CSF p‐tau181) had lower plasma insulin levels than A‐T‐ participants in the non‐dementia group (P = 0.002). No significant differences were observed in the dementia group (Figure 1). In addition, a notable positive correlation was found between plasma insulin levels and CSF Aβ42 (P &lt; 0.001) in all participants. When stratified by clinical status and pathological status, this association only existed in the A‐ group (P = 0.002) and the non‐demented group (P &lt; 0.001) (Figure 2). Moreover, plasma insulin at baseline was significantly associated with longitudinal changes in CSF Aβ42 (P = 0.02), while baseline CSF Aβ42 was not associated with longitudinal changes in plasma insulin (Figure 3). Regarding the diagnostical value, plasma insulin alone demonstrated acceptable accuracy in distinguishing A+ from A‐ individuals in the whole participants (area under the curve [AUC]=0.61) and more prominent in the non‐dementia group (AUC = 0.65) than in the dementia group (AUC = 0.52). When added age, sex, and APOE ε4 status were as predictors, the AUC of plasma insulin reached 0.8 in the whole participants.ConclusionThese findings pinpoint the association between plasma insulin and early Aβ pathology in the early stages of AD, suggesting that plasma insulin can serve as an early biomarker of Aβ pathology.

Head‐to‐head evaluation of leading blood tests for amyloid pathology

AbstractBackgroundBlood tests that accurately determine the presence of amyloid pathology are critically needed. Compared to amyloid PET and CSF tests, blood tests are less expensive, less invasive, more accessible, and highly scalable. The Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium evaluated the accuracies of leading AD blood tests in classifying amyloid PET status.MethodAssays from C2N Diagnostics (Aβ42, Aβ40, p‐tau217, p‐tau217 ratio [phosphorylated to non‐phosphorylated tau at position 217]), Fujirebio Diagnostics (Aβ42, Aβ40, p‐tau217), ALZPath (p‐tau217), Janssen (p‐tau217), Roche Diagnostics (Aβ42, Aβ40, p‐tau181, GFAP, NfL), and Quanterix (Aβ42, Aβ40, p‐tau181, GFAP, NfL) were run on plasma samples from ADNI participants with corresponding florbetapir‐PET scans. Unadjusted logistic regression models were constructed for each measure or combination of measures from each assay platform. The classification accuracies of the plasma biomarker measures for amyloid PET status (Centiloids&gt;20) were assessed with receiver operating characteristic area under the curve (AUC) analyses and compared using DeLong’s tests.ResultThe cohort included data from 392 individuals with a median age of 78.1 years; 193 (49.2%) were female; 132 (33.7%) were APOE ε4 carriers; 191 (48.7%) were amyloid PET positive; and 192 (49.0%) were cognitively impaired (Clinical Dementia Rating&gt;0), (Table 1). Models with high classification accuracies for amyloid PET status included the C2N p‐tau217 ratio + Aβ42/Aβ40 (AUC 0.929 [95% confidence intervals 0.902‐0.956]) and Fujirebio p‐tau217 + Aβ42/Aβ40 (0.911 [0.882‐0.940]), (Table 2). The AlzPath p‐tau217 (0.885 [0.851‐0.920]), Janssen p‐tau217 (0.882 [0.848‐0.916]), Roche p‐tau181 + Aβ42/Aβ40 + GFAP + NfL (0.873 [0.838‐0.909]), and Quanterix p‐tau181 + Aβ42/Aβ40 + GFAP + NfL (0.808 [0.763‐0.854]) models had lower accuracies than the C2N p‐tau217 ratio + Aβ42/Aβ40 model (p = 0.0006, 0.0006, 0.0006, and &lt;0.0001, respectively), (Figure 1). In 122 individuals with CSF Roche Elecsys p‐tau181/Aβ42 data, the classification accuracy for amyloid PET status was 0.915 (0.864‐0.967).ConclusionIn this head‐to‐head study, logistic regression models of C2N p‐tau217 ratio + Aβ42/Aβ40 and Fujirebio p‐tau217 + Aβ42/Aβ40 were among the most accurate in classifying amyloid PET status. The classification accuracies of the blood tests for tau PET status, brain atrophy status, and clinical dementia symptoms will also be assessed.

Modelling Small Vessel Disease Using Regional MRI Markers, and Mediating Effects on Cognitive Decline

AbstractBackgroundThe location of proposed brain MRI markers of small vessel disease (SVD) might reflect their pathogenesis and may translate into differential associations with cognition. We derived regional MRI markers of SVD and studied: (i) associations with cognitive performance, (ii) patterns most likely to reflect underlying SVD, (iii) mediating effects on the relationships of age and cardiovascular disease (CVD) risk with cognition.MethodIn 891 participants from The Multi‐Ethnic Study of Atherosclerosis, we segmented enlarged perivascular spaces (ePVS), white matter hyperintensities (WMH) and microbleeds (MBs) using deep learning‐based algorithms, and calculated white matter (WM) microstructural integrity measures of fractional anisotropy (FA), trace (TR) and free water (FW) using automated DTI‐processing pipelines. Measures of global and domain‐specific cognitive performance were derived from a comprehensive cognitive evaluation based on the UDS v3 neuropsychological battery.ResultMean (SD) age was 73.6 (7.9) years; 474 (53%) participants were women. In generalized linear models adjusted for demographics, vascular risk factors, and APOE ε4 carriership, higher basal ganglia ePVS count was associated with worse global, language, and attention cognitive performance (Table 1). Higher periventricular WMH volume was associated with worse global, delayed memory, language, phonemic, and attention performance. Higher WM FA was associated with better global, delayed memory, language, and attention performance. Higher WM TR was associated with worse global, delayed memory, language, phonemic, and attention performance. Exploratory factor analysis revealed that basal ganglia ePVS (standardized loading=0.51), thalamus ePVS (0.43), periventricular WMH (0.85), subcortical WMH (0.65), and WM FA (‐0.73) and TR (0.84) loaded onto the same factor, likely reflecting underlying SVD. Structural equation models demonstrated that SVD mediated the effect of age on cognition (β[95%CI]= ‐0.071[‐0.088,‐0.053]) through the pathways: Age→SVD→Cognition (‐0.044[‐0.063,‐0.026]) and Age→SVD→Brain Atrophy→Cognition (‐0.006[‐0.012,‐0.002]) – Figure 1, and the effect of CVD risk on cognition (‐0.028[‐0.044,‐0.012]) through the pathways: CVD Risk→SVD→Cognition (‐0.021[‐0.031,‐0.013]) and CVD Risk→SVD→Brain Atrophy→Cognition (‐0.007[‐0.012,‐0.003]) – Figure 2.ConclusionThe location of the proposed MRI markers of SVD likely reflects distinct etiopathogenic substrates and should be considered when examining associations with cognitive or other health‐related outcomes. SVD mediates the relationships of age and CVD risk with cognition via both atrophy‐related and unrelated pathways.

A generalizable data‐driven model of atrophy heterogeneity and progression in a memory clinic setting

AbstractBackgroundMemory clinic patients are a heterogeneous population representing various aetiologies of pathological aging. It is unknown if divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer’s disease (AD) patients, are prevalent and clinically meaningful in this group of older adults.MethodTo uncover atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to structural MRI data from 813 participants (mean ± SD age = 70.67 ± 6.07 years, 52% females) from the DELCODE cohort. Participants were cognitively unimpaired (CU; n = 285) or patients with subjective cognitive decline (SCD; n = 342), mild cognitive impairment (MCI; n = 118), or dementia of the Alzheimer’s type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid AD biomarkers, and domain‐specific cognitive performance. PACC‐5 trajectories over up to 240 weeks were examined. Clinical trajectories (PACC‐5 scores and MCI conversion rates) in only CU and SCD participants were analysed. SuStaIn modelling was repeated in participants from the Swedish BioFINDER‐2 study for replication and generalizability testing.ResultLimbic‐predominant and hippocampal‐sparing atrophy subtypes were identified (Figure 1). Limbic‐predominant atrophy first affected the medial temporal lobes, followed by further temporal and, finally, the remaining cortical regions. This subtype was related to older age, more pathological AD biomarkers, APOE ε4 carriership, and an amnestic cognitive impairment. Hippocampal‐sparing atrophy initially occurred outside the temporal lobe and spared the medial temporal lobe until advanced stages. This atrophy pattern also affected individuals with positive AD biomarkers and was associated with more generalised cognitive impairment. Limbic‐predominant atrophy, in all and in only unimpaired participants, was linked to more negative longitudinal PACC‐5 slopes than observed in participants without or with hippocampal‐sparing atrophy (Figure 2) and increased the risk of MCI conversion.In BioFINDER‐2, analogous atrophy subtypes and cognitive correlates were identified. Group‐ and subject‐level model generalizability were excellent, indicating reliable performance in novel data (Figure 3).ConclusionThe proposed model is a promising tool for capturing heterogeneity among older adults at early at‐risk states for AD in applied settings. The implementation of atrophy subtype‐ and stage‐specific end‐points may increase the statistical power of pharmacological trials targeting early AD.

Perceived adverse maternal control during childhood and striatal volume in healthy older adults: Differences between APOE ε4 carriers and non‐carriers

Perceived adverse maternal control during childhood and striatal volume in healthy older adults: Differences between APOE ε4 carriers and non‐carriers

The genetic landscape of early and late-onset Alzheimer’s disease: A review

Abstract Alzheimer’s disease(AD) is a multifactorial neurodegenerative disorder characterized by the progressive loss of neurons and synaptic dysfunction, primarily affecting the cortex and hippocampus. The etiology of AD is complex, involving the continuous and intricate interaction between genetic and non-genetic environmental factors. Genetic predisposition plays a significant role, with approximately 60-80% of AD risk attributed to hereditary factors. Familial early-onset AD(EOAD), with autosomal-dominant mutations in APP, PSEN1, and PSEN2, represents about 1-5% of cases and typically manifests before age 65. Rare autosomal-recessive mutations, like A673V(APP gene), are also implicated. Late-onset AD(LOAD), more common, is influenced by a combination of genetic and environmental factors, with the APOE ε4 allele being a major risk factor. Protective factors, such as the APOE ε2 allele and rare mutations like Ala673Thr, can reduce AD risk. The interplay between genetic variants, environmental influences, and pathological processes underpins the disease’s progression. This study highlights the importance of understanding the genetic and non-genetic determinants of AD to advance personalized treatment and early detection strategies. Future research and personalized medicine approaches are essential for mitigating AD risks and improving management outcomes.

Leveraging a Novel Phenotype to Identify Complex Traits and Biological Pathways Associated with Resilience to Alzheimer’s Disease

AbstractBackgroundPrevious models of resilience to Alzheimer’s Disease (AD) have relied on cross‐sectional designs and inclusion of measures of neuropathology. Here, we present a novel modeling approach incorporating longitudinal data and the use of APOE and higher order interaction terms to approximate neuropathological resilience, vastly increasing participant diversity and statistical power. We validate this approach and report novel genetic associations with neuropathological resilience.MethodLeveraging 20,513 participants (Table 1), we explored the genetics of resilience metrics using mixed‐effects regressions across ancestries. We conducted GWAS on four resilience metrics: two in a “silver” model, which benefit from a larger sample size and did not include neuropathology at autopsy, and two in a “gold” model, which incorporate neuropathology at autopsy. These models were built in all diagnoses and separately in cognitively unimpaired (CU) at baseline participants. Silver‐gold meta‐analyses were conducted to maximize statistical power. Models adjusted for age, sex, APOE ε4 allele count, presence of the APOE ε2 allele and all covariate interactions with interval (years from baseline). Residual cognitive resilience was quantified from residuals in three cognitive domains (memory, executive function, and language). Post‐GWAS analyses included gene and pathway tests using MAGMA and genetic correlation with 65 traits using GNOVA.ResultSilver and gold resilience metrics were highly correlated (0.77‐0.88) and showed positive genetic covariance (0.01‐0.13). We identified negative correlations of resilience with multiple sclerosis and neuropsychiatric traits, including Tourette syndrome and schizophrenia (all PFDR&lt;2.6×10−2; Figure 1). Furthermore, we observed three significant pathway associations with resilience: metabolism of amino acids and derivatives in the silver all participants meta‐analysis, negative regulation of transforming growth factor beta production in the silver CU at baseline meta‐analysis, and the SARS pathway in the gold CU at baseline meta‐analysis (all PFDR&lt;5.0×10−2). Finally, we identified a locus on chromosome 17 associated with resilience that approached genome‐wide significance (top SNP: rs757022, MAF = 0.18, b = 0.08, P = 1.1×10−7; Figure 2).ConclusionUsing novel, longitudinal modeling approaches, we identified multiple biological pathways and complex traits associated with resilience to AD as well as genetic loci approaching genome‐wide significance. Our findings indicate that silver standard modeling approaches can complement current gold standard methods to accelerate genetic discovery.

ABCA7 high‐risk genotype predicts working memory decline among older cognitively healthy African Americans

AbstractBackgroundAlzheimer's disease (AD) is a neurodegenerative disease characterized by progressive cognitive decline1. APOE‐ε4 has been identified as the most prevalent genetic risk factor for the early onset of AD, while ABCA7‐80 (rs115550680) has been shown to have a stronger effect size than the APOE‐ε4 allele and is associated with the development of late‐onset of AD among African Americans2,3. Although the efficiency of executive functions declines with age, some basic attentional functions and preserved knowledge may help mitigate the effects of aging on working memory4. Nevertheless, the impact of APOE ε4 and ABCA7‐80 genotypes on attention and executive function in preclinical AD remains unclear5. This study investigated the influence of APOE ε4 and ABCA7‐80 genotypes on working memory among cognitively unimpaired older African Americans.MethodParticipants were drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans conducted at Rutgers University–Newark. 838 participants (ages ≥ 60) completed saliva collection for genotyping and neuropsychological battery for cognitive assessment with a fraction repeating each assessment multiple times as part of returning visits. Simple linear mixed models were applied for longitudinal statistical analysis.ResultABCA7‐80 high‐risk genotype was found to be a risk factor for decreased cognitive performance, as assessed by Trail Making Test Part A (ß = 5.819, p = 0.030) and Part B (ß = 39.964, p &lt; 0.001), Digit Span Total (ß = ‐2.092, p= 0.045), Controlled Oral Word Association (ß = ‐4.708, p = 0.019), as well as a significant association with increased depression.ConclusionThe ABCA7‐80 high‐risk genotype may indicate early working memory declines in preclinical AD and may serve as a predictive biomarker among cognitively impaired older African Americans.

Extensive antagonistic genetic underpinnings of sex disparities in Alzheimer’s disease and hypertension

AbstractBackgroundThe Alzheimer’s Association reports that more than two‐thirds of the approximately 5 million Alzheimer’s disease (AD) cases in the USA are women. With studies suggesting a high genetic heritability for AD, gaining a better understanding of the genetic architecture underlying sex disparities in AD and its risk factors could enhance the understanding of their mechanisms.MethodWe conducted genome‐wide association studies (GWAS) and pleiotropic meta‐analysis of AD and its risk factor—hypertension—in men and women of European ancestry. The AD GWAS focused on 168,962 men (including 6,229 cases) and 199,668 women (including 7,628 cases) from 10 cohorts. The hypertension GWAS included 177,597 men (96,835 cases) and 205,482 women (88,861 cases) from eight of the 10 AD cohorts. Sex‐specific associations were characterized by the Wald chi‐square test and Fisher’s method, and their significance was assessed at a false discovery rate q‐value of 5% or less.ResultGWAS of AD and hypertension identified 176 and 195 loci, respectively, on all chromosomes with the differences in the effects between sexes attaining q&lt;0.05. Associations with AD were of the same directions in men and women only in one—the APOE gene—locus, with significantly larger adverse effect for the ε4‐encoding rs429358 polymorphism in women (β = 1.35, CI = 1.30‐1.41) than men (β = 1.16, CI = 1.10‐1.22). Associations with hypertension were of the same directions in each sex in 74 of 195 loci on all chromosomes, except chromosome 14. The ε4 allele showed no association with hypertension in either sex. No significant differences between sexes in the significant protective associations with AD and hypertension were identified for the ε2 allele. Our analyses revealed seven pleiotropic loci mapped to COL24A1, MGC4859‐PHF14, MFHAS1‐ERI1, SBF2, KICS2, BCL11B, and RPAP1 gene clusters characterized by the differences in the associations with AD and hypertension between sexes at q&lt;0.05. In three underlined clusters, the associations with hypertension were of the same direction in men and women.ConclusionAlthough the APOE ε4 allele partly underlies AD‐related sex disparities, the most substantial contribution comes from antagonistic relationships between genes and AD in men and women. Sex‐specific pleiotropic loci suggest contribution of hypertension to these AD‐related sex disparities.

Ruminococcus‐based metagenomic‐brain signature linked to cognitive performance and Alzheimer’s disease markers

AbstractBackgroundThe aim of this study was to identify a gut microbial signature associated with patterns of gray matter volume in AD, and to validate the microbial signature by testing it against measures of AD pathology and cognitive performance. Prior literature suggests that microbial species involved in bile acid production and inflammation may be implicated in the microbial signature.MethodThe sample comprised 204 Microbiome in Alzheimer’s Risk Study participants (22 AD, 10 MCI, and 172 CN; 129 Females, 78 APOE+) from the Wisconsin Alzheimer’s Disease Research Center and Wisconsin Registry for Alzheimer’s Prevention. With shotgun metagenomic sequencing data and regional gray matter volumes calculated using T1‐weighted neuroimaging (Destrieux, Harvard Oxford subcortical atlases), sparse partial least squares regression was used to determine correlated sets of microbial features and gray matter regions that maximally explained the variance in the two datasets. General linear models were then used to link the derived microbial signature with an aggregated score of cognitive performance (PACC3), an estimated cognitive score (ADAS‐Cog‐13) derived using participants’ serum lipidomics, and amyloid and tau positivity status.ResultGreater abundance of 14 microbial features dominated by Ruminococcus species was associated (r=0.39, p=7.7e‐09) with greater volume in 13 regions dominated by the hippocampus, amygdala, and temporal regions, which are implicated in AD (Figure 1). This relationship was especially strong among APOE ε4 carriers. Higher scores on the microbial signature (associated with higher gray matter volume) were also associated with pTau negative status, and with better performance on the PACC3 and estimated ADAS‐Cog‐13.ConclusionWith roles in producing secondary bile acids and short chain fatty acids, Ruminococcus species may benefit the gut mucosal barrier and abrogate inflammatory mechanisms. This study suggests these microbes could protect against neurotoxic processes including tau hyperphosphorylation, resulting in preserved cortical volume and better cognitive performance.Funding: Alzheimer Gut Microbiome Project, NIA U19 AG063744

APOE ε4 genotype confers risk for Alzheimer Disease in Cuban Americans

APOE ε4 genotype confers risk for Alzheimer Disease in Cuban Americans