APOE Status Research Articles

Association between ABO genotypes and risk of dementia and neuroimaging markers: roles of sex and APOE status.

Whether the relationships between ABO blood genotypes (AA, AO, BB, BO, AB, and OO) and dementia are modified by gender and APOE status has been unclear. We used data from the UK Biobank, a population-based cohort study of 487,425 individuals. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) between ABO genotypes and risk of dementia. Multivariable linear regression models were used to estimate the relationship between ABO genotypes and MRI-based brain indices. Overall, 487,425 participants were included at baseline. After 34 million person-years follow up, 7,548 patients developed all-cause dementia. Before stratifying by sex and APOE status, compared to OO genotype, BB genotype was associated with increased risk of all-cause dementia (1.36, 1.03-1.80) and other types dementia (1.65, 1.20-2.28). After stratifying by sex, only in males, BB genotype was associated with higher risk of all-cause dementia (1.44, 1.02-2.09) and other types of dementia (1.95, 1.30-2.93). AB genotype in males was also associated with increased AD (1.34, 1.04-1.72). After further stratifying by APOE e4 status, BB genotype with two APOE e4 alleles showed even stronger association with all-cause dementia 4.29 (1.57, 11.72) and other types dementia (5.49, 1.70-17.69) in males. Also in males, AA genotype with one APOE e4 was associated with increased risks of all-cause dementia (1.27, 1.04-1.55), AD (1.45, 1.09-1.94) and other types dementia (1.40, 1.08-1.81). Linear regression models showed that in both sexes with APOE e4, AA genotype was associated with reduced total grey matter volume. Sex and APOE e4 carrier status modified the association between ABO genotypes and risk of dementia. In males, BB genotype was consistently associated with increased risk of dementia, especially in those with two APOE e4 alleles. Also, in males with one APOE e4, AA genotype might be linked to higher risk of dementia.

Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data.

In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the classical epidemiological predictor variables, data from multiple (omic) platforms are increasingly available. To integrate this wealth of information, we propose new methodology to combine both cooperative learning, a recent approach to leverage the predictive power of several datasets, and polygenic hazard score models. Polygenic hazard score models provide a practitioner with a more differentiated view of the predicted disease-free survival than the one given by merely a point estimate, for instance computed with a polygenic risk score. Our aim is to leverage the advantages of cooperative learning for the computation of polygenic hazard score models via Cox's proportional hazard model, thereby improving the prediction of the disease-free survival. In our experimental study, we apply our methodology to forecast the disease-free survival for Alzheimer's disease (AD) using three layers of data. One layer contains epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status and 10 leading principal components. Another layer contains selected genomic loci, and the last layer contains methylation data for selected CpG sites. We demonstrate that the survival curves computed via cooperative learning yield an AUC of around $0.7$, above the state-of-the-art performance of its competitors. Importantly, the proposed methodology returns (1) a linear score that can be easily interpreted (in contrast to machine learning approaches), and (2) a weighting of the predictive power of the involved data layers, allowing for an assessment of the importance of each omic (or other) platform. Similarly to polygenic hazard score models, our methodology also allows one to compute individual survival curves for each patient.

Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort.

We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N=299), mild cognitive impairment (MCI; N=192), or dementia (DEM; N=65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). Plasma biomarkers differed across diagnostic groups (DEM>MCI>CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. Plasma biomarkers differ across diagnostic groups (DEM>MCI>CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.

Differences in daily physical activity by Alzheimer's risk markers among older adults.

Daily physical activity patterns differ by Alzheimer's disease (AD) status and might signal cognitive risk. It is critical to understand whether patterns are disrupted early in the AD pathological process. Yet, whether established AD risk markers (β-amyloid (Aβ) or APOE-ε4) are associated with differences in objectively measured activity patterns among cognitively unimpaired older adults is unclear. Wrist accelerometry, brain Aβ (+/-), and APOE-ε4 genotype were collected in 106 (Aβ) and 472 (APOE-ε4) participants [mean age 76 (SD: 8.5) or 75 (SD: 9.2) years, 60% or 58% women] in the BLSA. Adjusted linear and function-on-scalar regression models examined whether Aβ or APOE-ε4 status was cross-sectionally associated with activity patterns (amount, variability, or fragmentation) overall and by time-of-day, respectively. Differences in activity patterns by combinations of Aβ and APOE-ε4 status were descriptively examined (n=105). There were no differences in any activity pattern by Aβ or APOE-ε4 status overall. Aβ+ was associated with lower total amount and lower within-day variability of physical activity overnight and early evening, and APOE-ε4 carriers had higher total amount of activity in the evening and lower within-day variability of activity in the morning. Diurnal curves of activity were blunted among those with Aβ+ regardless of APOE-ε4 status, but only when including older adults with MCI/dementia. Aβ+ in cognitively unimpaired older adults might manifest as lower amount and variability of daily physical activity, particularly during overnight/evening hours. Future research is needed to examine changes in activity patterns in larger samples and by other AD biomarkers.

Older adults at greater risk for Alzheimer’s disease show stronger associations between sleep apnea severity in REM sleep and verbal memory

BackgroundObstructive sleep apnea (OSA) increases risk for cognitive decline and Alzheimer’s disease (AD). While the underlying mechanisms remain unclear, hypoxemia during OSA has been implicated in cognitive impairment. OSA during rapid eye movement (REM) sleep is usually more severe than in non-rapid eye movement (NREM) sleep, but the relative effect of oxyhemoglobin desaturation during REM versus NREM sleep on memory is not completely characterized. Here, we examined the impact of OSA, as well as the moderating effects of AD risk factors, on verbal memory in a sample of middle-aged and older adults with heightened AD risk.MethodsEighty-one adults (mean age:61.7 ± 6.0 years, 62% females, 32% apolipoprotein E ε4 allele (APOE4) carriers, and 70% with parental history of AD) underwent clinical polysomnography including assessment of OSA. OSA features were derived in total, NREM, and REM sleep. REM-NREM ratios of OSA features were also calculated. Verbal memory was assessed with the Rey Auditory Verbal Learning Test (RAVLT). Multiple regression models evaluated the relationships between OSA features and RAVLT scores while adjusting for sex, age, time between assessments, education years, body mass index (BMI), and APOE4 status or parental history of AD. The significant main effects of OSA features on RAVLT performance and the moderating effects of AD risk factors (i.e., sex, age, APOE4 status, and parental history of AD) were examined.ResultsApnea–hypopnea index (AHI), respiratory disturbance index (RDI), and oxyhemoglobin desaturation index (ODI) during REM sleep were negatively associated with RAVLT total learning and long-delay recall. Further, greater REM-NREM ratios of AHI, RDI, and ODI (i.e., more events in REM than NREM) were related to worse total learning and recall. We found specifically that the negative association between REM ODI and total learning was driven by adults 60 + years old. In addition, the negative relationships between REM-NREM ODI ratio and total learning, and REM-NREM RDI ratio and long-delay recall were driven by APOE4 carriers.ConclusionGreater OSA severity, particularly during REM sleep, negatively affects verbal memory, especially for people with greater AD risk. These findings underscore the potential importance of proactive screening and treatment of REM OSA even if overall AHI appears low.

Assessment of neurovascular uncoupling: APOE status is a key driver of early metabolic and vascular dysfunction.

Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein Eε4 (APOEε4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection. PET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology. All hAPOE strains showed AD phenotype progression by 8months, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (↓ glucose uptake, ↑ perfusion) at 8 and 12months, while APOEε3/ε4 demonstrated Type-2 uncoupling (↑ glucose uptake, ↓ perfusion), while immunopathology confirmed cell specific contributions. This work highlights APOEε4 status in AD progression manifests as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker. We developed a novel analytical method to analyze PET imaging of 18F-FDG and 64Cu-PTSM data in both sexes of aging C57BL/6J, and hAPOEε3/ε3, hAPOEε4/ε4, and hAPOEε3/ε4 mice to assess metabolism-perfusion profiles termed neurovascular uncoupling. This analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (decreased glucose uptake, increased perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated significant Type-2 uncoupling (increased glucose uptake, decreased perfusion) by 8 months which aligns with immunopathology and transcriptomic signatures. This work highlights that there may be different mechanisms underlying age related changes in APOEε4/ε4 compared with APOEε3/ε4. We predict that these changes may be driven by immunological activation and response, and may serve as an early diagnostic biomarker.

The effect of the apolipoprotein E ε4 allele and olfactory function on odor identification networks.

The combination of apolipoprotein E ε4 (ApoE ε4) status, odor identification, and odor familiarity predicts conversion to mild cognitive impairment (MCI) and Alzheimer's disease (AD). To further understand olfactory disturbances and AD risk, ApoE ε4 carrier (mean age 76.38±5.21) and ε4 non-carrier (mean age 76.8±3.35) adults were given odor familiarity and identification tests and performed an odor identification task during fMRI scanning. Five task-related functional networks were detected using independent components analysis. Main and interaction effects of mean odor familiarity ratings, odor identification scores, and ε4 status on network activation and task-modulation of network functional connectivity (FC) during correct and incorrect odor identification (hits and misses), controlling for age and sex, were explored using multiple linear regression. Findings suggested that sensory-olfactory network activation was positively associated with odor identification scores in ε4 carriers with intact odor familiarity. The FC of sensory-olfactory, multisensory-semantic integration, and occipitoparietal networks was altered in ε4 carriers with poorer odor familiarity and identification. In ε4 carriers with poorer familiarity, connectivity between superior frontal areas and the sensory-olfactory network was negatively associated with odor identification scores. The results contribute to the clarification of the neurocognitive structure of odor identification processing and suggest that poorer odor familiarity and identification in ε4 carriers may signal multi-network dysfunction. Odor familiarity and identification assessment in ε4 carriers may contribute to the predictive value of risk for MCI and AD due to the breakdown of sensory-cognitive network integration. Additional research on olfactory processing in those at risk for AD is warranted.

Alzheimer’s and neurodegenerative disease biomarkers in blood predict brain atrophy and cognitive decline

BackgroundAlthough blood-based biomarkers have been identified as cost-effective and scalable alternatives to PET and CSF markers of neurodegenerative disease, little is known about how these biomarkers predict future brain atrophy and cognitive decline in cognitively unimpaired individuals. Using data from the Baltimore Longitudinal Study of Aging (BLSA), we examined whether plasma biomarkers of Alzheimer’s disease (AD) pathology (amyloid-β [Aβ42/40], phosphorylated tau [pTau-181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) were associated with longitudinal brain volume loss and cognitive decline. Additionally, we determined whether sex, APOEε4 status, and plasma amyloid-β status modified these associations.MethodsPlasma biomarkers were measured using Quanterix SIMOA assays. Regional brain volumes were measured by 3T MRI, and a battery of neuropsychological tests assessed five cognitive domains. Linear mixed effects models adjusted for demographic factors, kidney function, and intracranial volume (MRI analyses) were completed to relate baseline plasma biomarkers to baseline and longitudinal brain volume and cognitive performance.ResultsBrain volume analyses included 622 participants (mean age ± SD: 70.9 ± 10.2) with an average of 3.3 MRI scans over 4.7 years. Cognitive performance analyses included 674 participants (mean age ± SD: 71.2 ± 10.0) with an average of 3.9 cognitive assessments over 5.7 years. Higher baseline pTau-181 was associated with steeper declines in total gray matter volume and steeper regional declines in several medial temporal regions, whereas higher baseline GFAP was associated with greater longitudinal increases in ventricular volume. Baseline Aβ42/40 and NfL levels were not associated with changes in brain volume. Lower baseline Aβ42/40 (higher Aβ burden) was associated with a faster decline in verbal memory and visuospatial performance, whereas higher baseline GFAP was associated with a faster decline in verbal fluency. Results were generally consistent across sex and APOEε4 status. However, the associations of higher pTau-181 with increasing ventricular volume and memory declines were significantly stronger among individuals with higher Aβ burden, as was the association of higher GFAP with memory decline.ConclusionsAmong cognitively unimpaired older adults, plasma biomarkers of AD pathology (pTau-181) and astrogliosis (GFAP), but not neuronal injury (NfL), serve as markers of future brain atrophy and cognitive decline.

Associations between accelerometer-measured circadian rest-activity rhythm, brain structural and genetic mechanisms, and dementia.

Knowledge of how circadian rhythm influences brain health remains limited. We aimed to investigate the associations of accelerometer-measured circadian rest-activity rhythm (CRAR) with incident dementia, cognitive dysfunction, and structural brain abnormalities in the general population and underlying biological mechanisms. Fifty-seven thousand five hundred and two participants aged over 60 years with accelerometer data were included to investigate the association of CRAR with incidental dementia. Non-parametric CRAR parameters were utilized, including activity level during active periods of the day (M10), activity level during rest periods of the day (L5), and the relative difference between the M10 and L5 (relative amplitude, RA). Associations of CRAR with cognitive dysfunction and brain structure were studied in a subset of participants. Neuroimaging-transcriptomics analysis was utilized to identify the underlying molecular mechanisms. Over 6.86 (4.94-8.78) years of follow-up, 494 participants developed dementia. The risk of incident dementia was associated with decreasing M10 (hazard ratio [HR] 1.45; 95% conference interval [CI], 1.28-1.64) and RA (HR 1.37; 95% CI, 1.28-1.64), increasing L5 (HR 1.14, 95% CI 1.07-1.21) and advanced L5 onset time (HR 1.12; 95% CI, 1.02-1.23). The detrimental associations were exacerbated by APOE ε4 status and age (>65 years). Decreased RA was associated with lower processing speed (Beta -0.04; SE 0.011), predominantly mediated by abnormalities in subcortical regions and white matter microstructure. The genes underlying CRAR-related brain regional structure variation were enriched for synaptic function. Our study underscores the potential of intervention targeting at maintaining a healthy CRAR pattern to prevent dementia risk.

Clinical value of plasma ALZpath pTau217 immunoassay for assessing mild cognitive impairment

BackgroundAmong plasma biomarkers for Alzheimer’s disease (AD), pTau181 and pTau217 are the most promising. However, transition from research to routine clinical use will require confirmation of clinical performance in prospective...

1032 Association of Sleep Duration and APOE ε4 Status on Brain Regional Tau Deposition in Clinically Normal Older Adults

1032 Association of Sleep Duration and APOE ε4 Status on Brain Regional Tau Deposition in Clinically Normal Older Adults

Prospective memory performance in veterans with and without histories of mild traumatic brain injury: effect of the apolipoprotein E (APOE) ε4 genotype

ABSTRACT Objective Identifying factors that moderate cognitive outcomes following mild traumatic brain injury (mTBI) is crucial. Prospective memory (PM) is a cognitive domain of interest in mTBI recovery as it may be especially sensitive to TBI-related changes. Since studies show that genetic status – particularly possession of the apolipoprotein E (APOE) ε4 allele – can modify PM performance, we investigated associations between mTBI status and APOE-ε4 genotype on PM performance in a well-characterized sample of Veterans with neurotrauma histories. Methods 59 Veterans (mTBI = 33, Military Controls [MCs] = 26; age range: 24–50; average years post-injury = 10.41) underwent a structured clinical interview, neuropsychological assessment, and genotyping. The Memory for Intentions Test (MIST) measured PM across multiple subscales. ANCOVAs, adjusting for age and posttraumatic stress symptoms, tested the effects of mTBI status (mTBI vs. MC) and ε4 status (ε4+ vs. ε4−) on MIST scores. Results Veterans with mTBI history performed more poorly compared to MCs on the MIST 15-min delay (p=.002, ηp 2 =.160), Time Cue (p = .003, ηp 2 =.157), and PM Total (p = .016, ηp 2 =.102). Those with at least one copy of the ε4 allele performed more poorly compared to ε4- Veterans on the MIST 15-min delay (p = .011, ηp 2 =.113) and PM Total (p = .048, ηp 2 = .071). No significant interactions were observed between mTBI and APOE-ε4 status on MIST outcomes (ps>.25). Within the mTBI group, APOE-ε4+ Veterans performed worse than APOE-ε4− Veterans on the MIST 15-min delay subscale (p = .031, ηp 2 = .150). Conclusions mTBI history and APOE-ε4 genotype status were independently associated with worse PM performance compared to those without head injury histories or possession of the APOE-e4 genotype. Performance on the MIST 15-min delay was worse in Veterans with both risk factors (mTBI history and APOE-ε4 positivity). Findings suggest that genetic status may modify outcomes even in relatively young Veterans with mTBI histories. Future research examining longitudinal associations and links to neuroimaging and biomarker data are needed.

Impact of Short-Term Computerized Cognitive Training on Cognition in Older Adults With and Without Genetic Risk of Alzheimer's Disease: Outcomes From the START Randomized Controlled Trial

ObjectivesTo establish the impact of a 3-minute computerized cognitive training program (START) on cognition in older adults with and without genetic risk of Alzheimer's disease. DesignTwo-arm randomized controlled trial of the START program. Setting and ParticipantsRemote online trial in adults older than 50 taking part from home. MethodsThe trial compared the START program with placebo in 6544 people older than 50. Primary outcome was executive function measured through Trailmaking B, with other secondary cognitive measures. Genetic risk profile and ApoE4 status were determined by Illumina Array. ResultsSTART conferred benefit to executive function, attention, memory, and a composite measure, including in people with the ApoE4 genotype. Conclusions and ImplicationsThe 3-minute START task offers a means of supporting cognitive health in older adults and could be used at scale and within a precision medicine approach to reduce risk of cognitive decline in a targeted way.

Cost-Effectiveness of Lecanemab for Individuals With Early-Stage Alzheimer Disease.

Little is known regarding the cost-effectiveness of lecanemab (Leqembi), a monoclonal antibody approved by the US Food and Drug Administration in January 2023 for the treatment of mild cognitive impairment (MCI) or mild dementia due to Alzheimer disease (AD). This study aims to quantify the cost-effectiveness of lecanemab and how it varies based on the accuracy of AD testing and individuals' APOE ε4 status. Seven alternative test-treat-target strategies defined by combinations of testing approaches (PET, CSF, or plasma assay), treatment choices (standard of care [SoC] alone or lecanemab in addition to SoC), and targeting strategies (targeting APOE ε4 noncarriers or heterozygous patients or not) were compared. A hybrid decision tree-Markov cohort model was constructed with 5 states: (1) MCI (Clinical Dementia Rating-Sum of Boxes [CDR-SB] 0-4.5); (2) mild dementia (CDR-SB 4.6-9.5); (3) moderate dementia (CDR-SB 9.6-16); (4) severe dementia (CDR-SB >16); and (5) death. Effectiveness was measured by quality-adjusted life years and costs from third-party and societal perspectives were estimated in 2022 US dollars over a lifetime horizon. Among the 7 test-treat-target strategies, SoC alone was the optimal strategy from a cost-effectiveness perspective. Neither targeted lecanemab treatment nor treatment unrestricted by APOE ε4 genotype was cost-effective vs SoC alone, regardless of the test used to diagnose patients with early-stage AD. However, CSF assay followed by targeted treatment would become cost-effective if lecanemab is priced below $5,100 per year. These results were robust to the accuracy of diagnostic testing and rates of lecanemab discontinuation and adverse events. Neither targeted lecanemab treatment nor treatment unrestricted by APOE ε4 genotype is cost-effective vs SoC alone for patients with MCI or mild dementia due to AD. Lecanemab would be cost-effective in some settings if priced below $5,100 per year.

Plasma oxysterols are associated with serum lipids and dementia risk in older women.

Apolipoprotein E4 (APOE4) carriers' tendency toward hypercholesterolemia may contribute to Alzheimer's disease (AD) risk through oxysterols, which traverse the blood-brain barrier. Relationships between baseline plasma oxysterols, APOE status, serum lipids, and cognitive impairment risk were examined in 328 postmenopausal women from the Women's Health Initiative Memory Study. Women were followed for 25 years or until incident dementia or cognitive impairment. Levels of 24(S)-hydroxycholesterol (24-OHC), 27-hydroxycholesterol (27-OHC), and 24-OHC/27-OHC ratio did not differ by APOE status (p's>0.05). Higher 24-OHC and 27-OHC were associated with higher total, low density lipoprotein (LDL), non-high density lipoprotein (HDL), remnant, LDL/HDL, and total/HDL cholesterol and triglycerides (p's<0.05). Higher 24-OHC/27-OHC was associated with greater dementia risk (hazard ratio=1.51, 95% confidence interval:1.02-2.22), which interaction analyses revealed as significant for APOE3 and APOE4+, but not APOE2+ carriers. Less favorable lipid profiles were associated with higher oxysterol levels. A higher ratio of 24-OHC/27-OHC may contribute to dementia risk in APOE3 and APOE4+ carriers.

The Drug Burden Index Is Associated With Measures of Cognitive Function Among Older Adults in the Health, Aging, and Body Composition Study.

Anticholinergic and sedative medications affect cognition among older adults. The Drug Burden Index (DBI) is a validated measure of exposure to these medications, with higher DBI scores indicating higher drug burden. This ancillary analysis investigated the association between DBI and cognition assessed by the Modified Mini-Mental State Examination (3MS) and the Digit Symbol Substitution Test (DSST). The Health, Aging, and Body Composition Study was a prospective study of community-dwelling adults aged 70-79 years at enrollment. Using data from years 1, 5, and 10, DBI was calculated using medication data per participant. Linear mixed modeling was used to assess cross-sectional and longitudinal effects of DBI on 3MS and DSST. Adjusted models included biological sex, race, education level, APOE status, and death. Sensitivity analyses included testing the strength of the associations for each year and testing attrition due to death as a possible confounding factor via Cox-Proportional Hazard models. After adjustment, DBI was inversely associated with 3MS and DSST scores. These associations became stronger in each subsequent year. Neither DBI at year 1 nor within-person change in DBI were predictive of longitudinal declines in either cognitive measure. Sensitivity analyses indicated that DBI, 3MS, and DSST were associated with a greater risk of attrition due to death. Results suggest that in years when older adults had a higher DBI scores, they had significantly lower global cognition and slower processing speed. These findings further substantiate the DBI as a useful pharmacological tool for assessing the effect of medication exposure.

Selenotranscriptome network in Alzheimer’s disease

The interplay between selenoproteins, oxidative stress, and cell death pathways holds promise in unravelling novel therapeutic targets for Alzheimer’s disease (AD) in the future. Nonetheless, further comprehensive investigations are warranted to fully comprehend the precise contributions of selenoproteins in the aetiology and potential therapeutic strategies for Alzheimer’s disease. Previous work into gene expression networks in AD has included analysis of the entire transcriptome and, as of yet, has not yielded consistent insight into pathological pathways.1 Despite the comprehensive assessment of the transcriptome enabled by current technologies, one drawback of the whole transcriptome analysis is the risk of overlooking subtle yet significant variations in metabolic pathways.2 Thus, we aimed to assess gene expression of known selenoprotein and selenium-containing pathways in two different brain regions (dorsolateral prefrontal cortex (DPC) and posterior cingulate cortex (PCC)) across the AD spectrum. We used RNA sequencing data from The Rush University’s Religious Orders Study and Memory and Aging Project (ROSMAP) cohort available in the AD Knowledge Portal (https://www.synapse.org/).3 This study included data available for a total of 889 DPC and 647 PCC samples. Four pathological phenotypes were determined based on pathology (CERAD) and clinical (CDR) status: AD ([(+) pathology, (+) clinical], prodromal disease, corresponding to donors that have not received a clinical diagnosis despite the presence of pathological alterations ([(+) pathology, (−) clinical], controls ([(−) pathology, (−) clinical] and non-AD dementia [(+) pathology, (+) clinical]. This last group was excluded from the analysis as it is assumed they may have been misdiagnosed or presented with non-AD dementia. Six selenium or AD-related pathways were assessed, accounting for 421 unique genes. Group comparisons were performed using linear mixed modelling adjusted for age, sex, APOEe4 status and batch via DESeq2 package with Benjamini-Hochberg adjustment for multiple testing. A total of 18 genes significantly differed between AD and controls in both brain areas (same direction in both brain areas; P &lt; 0.05), including eight selenoprotein genes or genes directly associated with selenoprotein synthesis. Fifteen of them were also different (same direction) in PCC (seven selenoprotein/selenoprotein synthesis genes), and four were different in DPC (four selenoprotein/selenoprotein synthesis genes) between AD and prodromal. Only three genes significantly differed between prodromal and control samples (DPC), including the selenoprotein DIO3 and the transcription factor SP3. Our findings indicate a progressive change in gene expression across the different stages of AD. These findings shed light on critical genes involved in selenoprotein synthesis that play a role in AD pathogenesis. Restricting the analysis to a subset of pathways enabled the detection of smaller alterations between groups, which is particularly appropriate in trace element homeostasis, where small alterations may have significant downstream effects.

Sensitivity of the African neuropsychology battery memory subtests and learning slopes in discriminating APOE 4 and amyloid pathology in adult individuals in the Democratic Republic of Congo.

The current study examined the sensitivity of two memory subtests and their corresponding learning slope metrics derived from the African Neuropsychology Battery (ANB) to detect amyloid pathology and APOEε4 status in adults from Kinshasa, the Democratic Republic of the Congo. 85 participants were classified for the presence of β-amyloid pathology and based on allelic presence of APOEε4 using Simoa. All participants were screened using CSID and AQ, underwent verbal and visuospatial memory testing from ANB, and provided blood samples for plasma Aβ42, Aβ40, and APOE proteotype. Pearson correlation, linear and logistic regression were conducted to compare amyloid pathology and APOEε4 status with derived learning scores, including initial learning, raw learning score, learning over trials, and learning ratio. Our sample included 35 amyloid positive and 44 amyloid negative individuals as well as 42 without and 39 with APOEε4. All ROC AUC ranges for the prediction of amyloid pathology based on learning scores were low, ranging between 0.56-0.70 (95% CI ranging from 0.44-0.82). The sensitivity of all the scores ranged between 54.3-88.6, with some learning metrics demonstrating good sensitivity. Regarding APOEε4 prediction, all AUC values ranged between 0.60-0.69, with all sensitivity measures ranging between 53.8-89.7. There were minimal differences in the AUC values across learning slope metrics, largely due to the lack of ceiling effects in this sample. This study demonstrates that some ANB memory subtests and learning slope metrics can discriminate those that are normal from those with amyloid pathology and those with and without APOEε4, consistent with findings reported in Western populations.

Impact of age and apolipoprotein E ε4 status on regional white matter hyperintensity volume and cognition in healthy aging.

White matter hyperintensity (WMH) volume is a neuroimaging marker of lesion load related to small vessel disease that has been associated with cognitive aging and Alzheimer's disease (AD) risk. The present study sought to examine whether regional WMH volume mediates the relationship between APOE ε4 status, a strong genetic risk factor for AD, and cognition and if this association is moderated by age group differences within a sample of 187 healthy older adults (APOE ε4 status [carrier/non-carrier] = 56/131). After we controlled for sex, education, and vascular risk factors, ANCOVA analyses revealed significant age group by APOE ε4 status interactions for right parietal and left temporal WMH volumes. Within the young-old group (50-69 years), ε4 carriers had greater right parietal and left temporal WMH volumes than non-carriers. However, in the old-old group (70-89 years), right parietal and left temporal WMH volumes were comparable across APOE ε4 groups. Further, within ε4 non-carriers, old-old adults had greater right parietal and left temporal WMH volumes than young-old adults, but there were no significant differences across age groups in ε4 carriers. Follow-up moderated mediation analyses revealed that, in the young-old, but not the old-old group, there were significant indirect effects of ε4 status on memory and executive functions through left temporal WMH volume. These findings suggest that, among healthy young-old adults, increased left temporal WMH volume, in the context of the ε4 allele, may represent an early marker of cognitive aging with the potential to lead to greater risk for AD.

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer’s disease in patients with mild cognitive symptoms

BackgroundPredicting future Alzheimer’s disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be improved using entire brain images in deep learning (DL) models compared to using pre-defined brain regions.MethodsA cohort of 332 individuals with SCD/MCI were included from the Swedish BioFINDER-1 study. The goal was to predict longitudinal SCD/MCI-to-AD dementia progression and change in Mini-Mental State Examination (MMSE) over four years. Four models were evaluated using different predictors: (1) clinical data only, including demographics, cognitive tests and APOE ε4 status, (2) clinical data plus hippocampal volume, (3) clinical data plus all regional MRI gray matter volumes (N = 68) extracted using FreeSurfer software, (4) a DL model trained using multi-task learning with MRI images, Jacobian determinant images and baseline cognition as input. A double cross-validation scheme, with five test folds and for each of those ten validation folds, was used. External evaluation was performed on part of the ADNI dataset, including 108 patients. Mann-Whitney U-test was used to determine statistically significant differences in performance, with p-values less than 0.05 considered significant.ResultsIn the BioFINDER cohort, 109 patients (33%) progressed to AD dementia. The performance of the clinical data model for prediction of progression to AD dementia was area under the curve (AUC) = 0.85 and four-year cognitive decline was R2 = 0.14. The performance was improved for both outcomes when adding hippocampal volume (AUC = 0.86, R2 = 0.16). Adding FreeSurfer brain regions improved prediction of four-year cognitive decline but not progression to AD (AUC = 0.83, R2 = 0.17), while the DL model worsened the performance for both outcomes (AUC = 0.84, R2 = 0.08). A sensitivity analysis showed that the Jacobian determinant image was more informative than the MRI image, but that performance was maximized when both were included. In the external evaluation cohort from ADNI, 23 patients (21%) progressed to AD dementia. The results for predicted progression to AD dementia were similar to the results for the BioFINDER test data, while the performance for the cognitive decline was deteriorated.ConclusionsThe DL model did not significantly improve the prediction of clinical disease progression in AD, compared to regression models with a single pre-defined brain region.