Segmented Linear Mixed Model Analysis Reveals Association of the APOEɛ4 Allele with Faster Rate of Alzheimer's Disease Dementia Progression

Interrupted Learning across the Lifespan

Continued learning opportunities are important for adaptation across the lifespan. Interrupted learning (e.g., "summer slide") is a known, critical issue for childhood education. This perspective piece proposes that adulthood could be a period of prolonged interrupted learning with reduced learning opportunities, despite the known importance of lifelong learning. This idea goes beyond calls for healthy older adults to lead an active life to maintain cognitive abilities and to maintain basic functional skills by highlighting important lifespan circumstances that may hinder or facilitate adaptation in new and changing environments. We explore how research on interrupted learning in childhood could be applied to later adulthood and how changes in learning are viewed differently for children and adults. In addition, research on increasing abilities during childhood generally focuses on specific skills (e.g., reading, math), whereas cognitive aging research focuses on more general cognitive abilities related to attention and memory. Finally, given that interrupted learning occurs unevenly across different ages, abilities, and resources, more can be investigated in terms of who interrupted learning affects across the lifespan, and the neural underpinnings of interrupted learning. Acknowledging and addressing interrupted learning across the lifespan may promote long-term thriving and avoid preventable deficits and decline.

Retrosplenial hypometabolism precedes the conversion from mild cognitive impairment to Alzheimer's disease

INTRODUCTION

Not all individuals who experience mild cognitive impairment (MCI) transition through progressive stages of cognitive decline at the same rate, if at all. Previous observational studies have identified the retrosplenial cortex (RSC) as an early site of hypometabolism in MCI which seems to be predictive of later transition to Alzheimer's disease (AD).

METHODS

We examined N = 399 MCI subjects with baseline 18F-fluorodeoxyglucose positron emission tomography. Subjects were classified based on whether their diagnosis converted from MCI to AD.

RESULTS

Whole-brain metabolism was decreased in converters (MCI-AD). This effect was more prominent at the RSC, where MCI-AD subjects showed even greater hypometabolism. Observations of RSC hypometabolism and its utility in predicting transition from MCI-AD withstood statistical analyses in a large retrospective study.

DISCUSSION

These results point to the utility of incorporating RSC hypometabolism into predictive models of AD progression risk and call for further examination of mechanisms underlying this relationship.

HIGHLIGHTS

Not all individuals who develop MCI will progress to AD. Individuals with MCI who progress to AD show early whole-brain hypometabolism. Early hypometabolism is particularly prominent at the RSC.

A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease

The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been developed, current therapies can only delay disease progression rather than halt it entirely. Therefore, the early detection of MCI and the identification of MCI patients at high risk of progression to AD remain urgent unmet needs in the super-aged era. This study utilized transcriptomics data from cognitively unimpaired (CU) individuals, MCI, and AD patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort and leveraged machine learning models to identify biomarkers that differentiate MCI from CU and also distinguish AD from MCI individuals. Furthermore, Cox proportional hazards analysis was conducted to identify biomarkers predictive of the progression from MCI to AD. Our machine learning models identified a unique set of gene expression profiles capable of achieving an area under the curve (AUC) of 0.98 in distinguishing those with MCI from CU individuals. A subset of these biomarkers was also found to be significantly associated with the risk of progression from MCI to AD. A linear mixed model demonstrated that plasma tau phosphorylated at threonine 181 (pTau181) and neurofilament light chain (NFL) exhibit the prognostic value in predicting cognitive decline longitudinally. These findings underscore the potential of integrating machine learning (ML) with transcriptomic profiling in the early detection and prognostication of AD. This integrated approach could facilitate the development of novel diagnostic tools and therapeutic strategies aimed at delaying or preventing the onset of AD in at-risk individuals. Future studies should focus on validating these biomarkers in larger, independent cohorts and further investigating their roles in AD pathogenesis.

Integrated partially linear model for multi-center studies with heterogeneity and batch effect in covariates

The design of multi-center study is increasingly used for borrowing strength from multiple research groups to obtain broadly applicable and reproducible study findings. Regression analysis is widely used for analyzing multi-group studies, however, some of the large number of regression predictors are nonlinear and/or often measured with batch effects in many large scale collaborative studies. Also, the group compositions of the nonlinear predictors are potentially heterogeneous across different centers. The conventional pooled data analysis ignores the interplay between nonlinearity and batch effect, group composition heterogeneity, measurement error and other data incoherence in multi-center setting that can cause biased regression estimates and misleading outcomes. In this paper, we propose an integrated partially linear regression model (IPLM) based analysis to account for the predictor's nonlinearity, general batch effect, group composition heterogeneity, high-dimensional covariates, potential measurement-error in covariates, and combinations of these complexities simultaneously. A local linear regression based approach is employed to estimate the nonlinear component and a regularization procedure is introduced to identify the predictors' effects that can be either homogeneous or heterogeneous across groups. In particular, when the effects of all predictors are homogeneous across the study centers, the proposed IPLM can automatically reduce to one single parsimonious partially linear model for all centers. The proposed method has asymptotic estimation and variable selection consistency including high-dimensional covariates. Moreover, it has a fast computing algorithm and its effectiveness is supported by numerical simulation studies. A multi-center Alzheimer's disease research project is provided to illustrate the proposed IPLM based analysis.

Lower mortality risk in APOE4 carriers with normal cognitive ageing

Abnormal cognitive ageing, including dementia, poses serious challenges to health and social systems in ageing populations. As such, characterizing factors associated with abnormal cognitive ageing and developing needed preventive measures are of great importance. The ε4 allele of the Apolipoprotein E gene (APOE4) is a well-known genetic risk factor for late-onset Alzheimer's disease. APOE4 carriers are also at elevated risk of cardiovascular diseases which are associated with increased risk of cognitive impairment. On the other hand, APOE4 is known to be associated with reduced risk of multiple common types of cancer-a major age-related disease and leading cause of mortality. We conducted the first-ever study of APOE4's opposing effects on cognitive decline and mortality using competing risk models considering two types of death-death with high-amounts versus low-amounts of autopsy-assessed Alzheimer's neuropathology. We observed that APOE4 was associated with decreased mortality risk in people who died with low amounts of Alzheimer's-type neuropathology, but APOE4 was associated with increased mortality risk in people who died with high amounts of Alzheimer's-type neuropathology, a major risk factor of cognitive impairment. Possible preventive measures of abnormal cognitive ageing are also discussed.

Interaction between KLOTHO-VS Heterozygosity and APOE ε4 Allele Predicts Rate of Cognitive Decline in Late-Onset Alzheimer's Disease

KLOTHO-VS heterozygosity (KL-VShet+) promotes longevity and protects against cognitive decline in aging. To determine whether KL-VShet+ mitigates Alzheimer's disease (AD) progression, we used longitudinal linear-mixed models to compare the rate of change in multiple cognitive measures in AD patients stratified by APOE ε4 carrier status. We aggregated data on 665 participants (208 KL-VShet-/ε4-, 307 KL-VShet-/ε4+, 66 KL-VShet+/ε4-, and 84 KL-VShet+/ε4+) from two prospective cohorts, the National Alzheimer's Coordinating Center and the Alzheimer's Disease Neuroimaging Initiative. All participants were initially diagnosed with mild cognitive impairment, later developed AD dementia during the study, and had at least three subsequent visits. KL-VShet+ conferred slower cognitive decline in ε4 non-carriers (+0.287 MMSE points/year, p = 0.001; -0.104 CDR-SB points/year, p = 0.026; -0.042 ADCOMS points/year, p < 0.001) but not in ε4 carriers who generally had faster rates of decline than non-carriers. Stratified analyses showed that the protective effect of KL-VShet+ was particularly prominent in male participants, those who were older than the median baseline age of 76 years, or those who had an education level of at least 16 years. For the first time, our study provides evidence that KL-VShet+ status has a protective effect on AD progression and interacts with the ε4 allele.

Neuropathology-Independent Association Between APOE Genotype and Cognitive Decline Rate in the Normal Aging-Early Alzheimer Continuum

Background and Objectives

We previously found that the APOE genotype affects the rate of cognitive decline in mild-to-moderate Alzheimer disease (AD) dementia independently of its effects on AD neuropathologic changes (ADNC) and copathologies. In this study, we tested the hypothesis that the APOE alleles differentially affect the rate of cognitive decline at the normal aging-early AD continuum and that this association is independent of their effects on classical ADNC and copathologies.

Methods

We analyzed APOE associations with the cognitive trajectories (Clinical Dementia Rating scale Sum of Boxes [CDR-SOB] and Mini-Mental State Examination [MMSE]) of more than 1,000 individuals from a national clinicopathologic sample who had either no, mild (sparse neuritic plaques and the Braak neurofibrillary tangle [NFT] stage I/II), or intermediate (moderate neuritic plaques and the Braak NFT stage III/IV) ADNC levels at autopsy via 2 latent classes reverse-time longitudinal modeling.

Results

Carrying the APOEε4 allele was associated with a faster rate of cognitive decline by both CDR-SOB and MMSE relative to APOEε3 homozygotes. This association remained statistically significant after adjusting for ADNC severity, comorbid pathologies, and the effects of ADNC on the slope of cognitive decline. Our modeling strategy identified 2 latent classes in which APOEε4 carriers declined faster than APOEε3 homozygotes, with latent class 1 members representing slow decliners (CDR-SOB: 76.7% of individuals, 0.195 vs 0.146 points/y in APOEε4 vs APOEε3/ε3; MMSE: 88.6% of individuals, -0.303 vs -0.153 points/y in APOEε4 vs APOEε3/ε3), whereas latent class 2 members were fast decliners (CDR-SOB: 23.3% of participants, 1.536 vs 1.487 points/y in APOEε4 vs APOEε3/ε3; MMSE: 11.4% of participants, -2.538 vs -2.387 points/y in APOEε4 vs APOEε3/ε3). Compared with slow decliners, fast decliners were more likely to carry the APOEε4 allele, younger at initial visit and death, more impaired at initial and last visits, and more likely to have intermediate (vs none or mild) ADNC levels, as well as concurrent Lewy bodies and hippocampal sclerosis at autopsy.

Discussion

In a large national sample selected to represent the normal aging-early AD continuum, the APOEε4 allele is associated with a modest but statistically significant acceleration of the cognitive decline rate even after controlling for its effects on ADNC and comorbid pathologies.

Linear Mixed Model Analysis of Polygenic Hazard Score on Verbal Memory Decline in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a chronic, progressive, degenerative disease characterized by cognitive dysfunction, including verbal memory loss. Studies were lacking in examining the longitudinal effect of polygenic hazard score on the Rey Auditory Verbal Learning Test-Delayed Total (AVDELTOT) score (a common measure of verbal memory). A key step in analyzing longitudinal changes in cognitive measures using a linear mixed model (LMM) is choosing a suitable covariance structure.

OBJECTIVES

The study aims to determine the association between the polygenic hazard score and the AVDELTOT score accounting for repeated measures (the covariance structure).

METHODS

The AVDELTOT scores were collected at baseline, 12 months, 24 months, 36 months, and 48 months from 283 participants with AD, 347 with cognitive normal, and 846 with mild cognitive impairment in the Alzheimer's Disease Neuroimaging Initiative. The Bayesian information criterion statistic was used to select the best covariance structure from 10 covariance structures in longitudinal analysis of AVDELTOT scores. The multivariable LMM was used to investigate the effect of polygenic hazard score status (low vs. medium vs. high) on changes in AVDELTOT scores while adjusted for age, gender, education, APOE-ε4 genotype, and baseline Mini-Mental State Examination score.

RESULTS

One-way analysis of variance revealed significant differences in AVDELTOT scores, Mini-Mental State Examination scores, and polygenic hazard scores among AD diagnoses at baseline. Bayesian information criterion favored the compound symmetry covariance structure in the LMM analysis. Using the multivariate LMM, the APOE-ε4 allele and high polygenic hazard score value was significantly associated with AVDELTOT declines. Significant polygenic hazard score status by follow-up visit interactions was discovered.

CONCLUSION

Our findings provide the first evidence of the effect of polygenic hazard score status and APOE-ε4 allele on declines in verbal memory in people with AD.

Investigating the temporal pattern of neuroimaging-based brain age estimation as a biomarker for Alzheimer's Disease related neurodegeneration

Neuroimaging-based brain-age estimation via machine learning has emerged as an important new approach for studying brain aging. The difference between one's estimated brain age and chronological age, the brain age gap (BAG), has been proposed as an Alzheimer's Disease (AD) biomarker. However, most past studies on the BAG have been cross-sectional. Quantifying longitudinal changes in an individual's BAG temporal pattern would likely improve prediction of AD progression and clinical outcome based on neurophysiological changes. To fill this gap, our study conducted predictive modeling using a large neuroimaging dataset with up to 8 years of follow-up to examine the temporal patterns of the BAG's trajectory and how it varies by subject-level characteristics (sex, APOEɛ4 carriership) and disease status. Specifically, we explored the pattern and rate of change in BAG over time in individuals who remain stable with normal cognition or mild cognitive impairment (MCI), as well as individuals who progress to clinical AD. Combining multimodal imaging data in a support vector regression model to estimate brain age yielded improved performance over single modality. Multilevel modeling results showed the BAG followed a linear increasing trajectory with a significantly faster rate in individuals with MCI who progressed to AD compared to cognitively normal or MCI individuals who did not progress. The dynamic changes in the BAG during AD progression were further moderated by sex and APOEɛ4 carriership. Our findings demonstrate the BAG as a potential biomarker for understanding individual specific temporal patterns related to AD progression.

Apolipoprotein E4 Effects a Distinct Transcriptomic Profile and Dendritic Arbor Characteristics in Hippocampal Neurons Cultured in vitro

The APOE gene is diversified by three alleles ε2, ε3, and ε4 encoding corresponding apolipoprotein (apo) E isoforms. Possession of the ε4 allele is signified by increased risks of age-related cognitive decline, Alzheimer's disease (AD), and the rate of AD dementia progression. ApoE is secreted by astrocytes as high-density lipoprotein-like particles and these are internalized by neurons upon binding to neuron-expressed apoE receptors. ApoE isoforms differentially engage neuronal plasticity through poorly understood mechanisms. We examined here the effects of native apoE lipoproteins produced by immortalized astrocytes homozygous for ε2, ε3, and ε4 alleles on the maturation and the transcriptomic profile of primary hippocampal neurons. Control neurons were grown in the presence of conditioned media from Apoe -/- astrocytes. ApoE2 and apoE3 significantly increase the dendritic arbor branching, the combined neurite length, and the total arbor surface of the hippocampal neurons, while apoE4 fails to produce similar effects and even significantly reduces the combined neurite length compared to the control. ApoE lipoproteins show no systemic effect on dendritic spine density, yet apoE2 and apoE3 increase the mature spines fraction, while apoE4 increases the immature spine fraction. This is associated with opposing effects of apoE2 or apoE3 and apoE4 on the expression of NR1 NMDA receptor subunit and PSD95. There are 1,062 genes differentially expressed across neurons cultured in the presence of apoE lipoproteins compared to the control. KEGG enrichment and gene ontology analyses show apoE2 and apoE3 commonly activate expression of genes involved in neurite branching, and synaptic signaling. In contrast, apoE4 cultured neurons show upregulation of genes related to the glycolipid metabolism, which are involved in dendritic spine turnover, and those which are usually silent in neurons and are related to cell cycle and DNA repair. In conclusion, our work reveals that lipoprotein particles comprised of various apoE isoforms differentially regulate various neuronal arbor characteristics through interaction with neuronal transcriptome. ApoE4 produces a functionally distinct transcriptomic profile, which is associated with attenuated neuronal development. Differential regulation of neuronal transcriptome by apoE isoforms is a newly identified biological mechanism, which has both implication in the development and aging of the CNS.

Mapping cerebral atrophic trajectory from amnestic mild cognitive impairment to Alzheimer's disease

Alzheimer's disease (AD) patients suffer progressive cerebral atrophy before dementia onset. However, the region-specific atrophic processes and the influences of age and apolipoprotein E (APOE) on atrophic trajectory are still unclear. By mapping the region-specific nonlinear atrophic trajectory of whole cerebrum from amnestic mild cognitive impairment (aMCI) to AD based on longitudinal structural magnetic resonance imaging data from Alzheimer's disease Neuroimaging Initiative (ADNI) database, we unraveled a quadratic accelerated atrophic trajectory of 68 cerebral regions from aMCI to AD, especially in the superior temporal pole, caudate, and hippocampus. Besides, interaction analyses demonstrated that APOE ε4 carriers had faster atrophic rates than noncarriers in 8 regions, including the caudate, hippocampus, insula, etc.; younger patients progressed faster than older patients in 32 regions, especially for the superior temporal pole, hippocampus, and superior temporal gyrus; and 15 regions demonstrated complex interaction among age, APOE, and disease progression, including the caudate, hippocampus, etc. (P < 0.05/68, Bonferroni correction). Finally, Cox proportional hazards regression model based on the identified region-specific biomarkers could effectively predict the time to AD conversion within 10 years. In summary, cerebral atrophic trajectory mapping could help a comprehensive understanding of AD development and offer potential biomarkers for predicting AD conversion.

Cognitive Function among World Trade Center-Exposed Community Members with Mental Health Symptoms

The World Trade Center Environmental Health Center (WTC EHC), is a federally designated clinical center of excellence for surveillance and treatment of WTC disaster exposed community members (WTC Survivors). Cognitive impairment (CI) has been extensively described in WTC responders and a concern for progressive impairment in all WTC disaster exposed groups has been raised. Cognitive status, however, has not been systematically characterized in the WTC Survivor population. We describe cognitive status in a subgroup of the Survivor population referred for mental health evaluation (N = 480) in the WTC EHC as measured by scores on the Montreal Cognitive Assessment (MoCA) instrument, and examine their association with WTC exposures and individual-level covariates including PTSD and depression screening inventory scores. In regression analyses, probable cognitive impairment (MoCA score < 26) was found in 59% of the study subjects and was significantly associated with age, race/ethnicity, education, income, depression and PTSD scores. Being caught in the dust cloud on 11 September 2011 was significantly associated with cognitive impairment even after controlling for the above. These data suggest an association with cognitive dysfunction in WTC Survivors with exposure to the toxic dust/fumes and psychological stress from the 9/11 terrorist attack and warrant further systematic study.

Genetic polymorphisms of apolipoprotein E in nonarteritic anterior ischemic optic neuropathy

PURPOSE

To elucidate the potential role of genetic polymorphisms of apolipoprotein E (APOE) in nonarteritic anterior ischemic optic neuropathy (NAION) and the association between APOE and NAION-induced ocular impairments.

METHODS

A total of 73 NAION patients and 73 sex- and age-matched healthy controls were recruited for the study. Genomic DNA was isolated from peripheral blood samples. The alleles and genotypes of APOE were explored. The interaction between APOE and medical comorbidities was assessed by the multifactor dimensionality reduction (MDR) method. Among 81 affected eyes of NAION patients, an additional association study of APOE isoforms with visual impairments was carried out.

RESULTS

The allele and genotype frequencies for APOE showed significant differences when comparing NAION cases and controls. Multivariate analysis adjusted for age, sex, hypertension, dyslipidemia, diabetes mellitus, cardiovascular disease, and cerebrovascular disease revealed that the ε3/ε4 genotype (OR = 3.86, 95% CI = 1.13-13.25, p = 0.032) and ε4 allele (OR = 3.55, 95% CI = 1.05-11.99, p = 0.041) were strong independent risk factors for NAION. Compared to eyes with the ε3/ε3 + ε2/ε4 genotype, individuals with the ε4/ε4 + ε3/ε4 genotype had worse visual field defects (VFDs) and thinner macular ganglion cell complex (mGCC) thicknesses with larger focal loss of volume (FLV) and general loss of volume (GLV). Compared to ε4 noncarriers, ε4 carriers also tended to have more serious VFD and mGCC loss.

CONCLUSIONS

APOE polymorphisms conferred a significant risk of NAION and were significantly related to ocular impairments caused by NAION.

Association between the APOE gene polymorphism and lipid profile and the risk of atrial fibrillation

Background

The relationship between the APOE gene polymorphism and lipid profiles and atrial fibrillation (AF) remains controversial. The current study purposed to investigate how the APOE gene SNPs (rs429358 and rs7412) and lipid profile are associated with the risk for AF among the Hakka population in southern China.

Methods

Finally, 1367 patients were enrolled in this study, including 706 participants with AF (41 ~ 98 years old, 58.64 % male) and 661 non-AF subjects (28 ~ 95 years old, 59.46 % male). The collected data included baseline characteristics, medical history, laboratory tests and echocardiography parameters. A general linear model (two-way analysis of variance (ANOVA)) and Tukey post-hoc tests were applied to identify an APOE allele, AF group, and interaction effect on lipid profiles. Logistic regression analysis was performed to identify risk factors for AF.

Results

For AF group, the most common genotype was E3/E3 (53.82 %), followed by E3/E4 (28.19 %), E2/E3 (13.60 %), E4/E4 (1.98 %), E2/E4 (1.84 %) and E2/E2 (0.57 %). The two-way ANOVA followed by the Tukey procedure showed the following: the lipid levels depended significantly on AF and APOE allele groups for TG, TC, LDL-C and Apo-B (all P < 0.001), and statistically significant interactions between AF and APOE allele were observed in the above 4 variables (all P < 0.05). Multivariate regression analysis indicated that age ≥ 65years (P < 0.001), high diastolic blood pressure (DBP ≥ 90mm Hg, P = 0.018), a high levels of total cholesterol (TC ≥ 5.2mmol/L, P < 0.001) and triglyceride (TG ≥ 1.7mmol/L, P = 0.028), but not the two SNPs of the APOE gene (rs7412 and rs429358) (OR 1.079, P = 0.683), were significant independent risk factors for AF in the study population.

Conclusions

The principal findings of this study showed that individuals at high risk for AF were those over 65 years of age, higher DBP as well as high levels of TC and TG among the southern China Hakka population. The levels of TG, TC, LDL-C and Apo-B depended significantly on AF and APOE allele groups, and statistically significant interactions between AF and APOE allele were observed in the above 4 variables, although the APOE gene SNPs (rs429358 and rs7412) were no significant risk for AF incidence. Further investigation is needed to elucidate whether other SNPs of the APOE gene have a bearing on AF incidents.

Absence of Apolipoprotein E is associated with exacerbation of prion pathology and promotes microglial neurodegenerative phenotype

Prion diseases or prionoses are a group of rapidly progressing and invariably fatal neurodegenerative diseases. The pathogenesis of prionoses is associated with self-replication and connectomal spread of PrP^Sc, a disease specific conformer of the prion protein. Microglia undergo activation early in the course of prion pathogenesis and exert opposing roles in PrP^Sc mediated neurodegeneration. While clearance of PrP^Sc and apoptotic neurons have disease-limiting effect, microglia-driven neuroinflammation bears deleterious consequences to neuronal networks. Apolipoprotein (apo) E is a lipid transporting protein with pleiotropic functions, which include controlling of the phagocytic and inflammatory characteristics of activated microglia in neurodegenerative diseases. Despite the significance of microglia in prion pathogenesis, the role of apoE in prionoses has not been established. We showed here that infection of wild type mice with 22L mouse adapted scrapie strain is associated with significant increase in the total brain apoE protein and mRNA levels and also with a conspicuous cell-type shift in the apoE expression. There is reduced expression of apoE in activated astrocytes and marked upregulation of apoE expression by activated microglia. We also showed apoE ablation exaggerates PrP^Sc mediated neurodegeneration. Apoe^−/− mice have shorter disease incubation period, increased load of spongiform lesion, pronounced neuronal loss, and exaggerated astro and microgliosis. Astrocytes of Apoe^−/− mice display salient upregulation of transcriptomic markers defining A1 neurotoxic astrocytes while microglia show upregulation of transcriptomic markers characteristic for microglial neurodegenerative phenotype. There is impaired clearance of PrP^Sc and dying neurons by microglia in Apoe^−/− mice along with increased level of proinflammatory cytokines. Our work indicates that apoE absence renders clearance of PrP^Sc and dying neurons by microglia inefficient, while the excess of neuronal debris promotes microglial neurodegenerative phenotype aggravating the vicious cycle of neuronal death and neuroinflammation.