bluuebunny/crossref_metadata_2025 huggingface dataset:
The association between sleep restlessness and neuroimaging biomarkers of Alzheimer’s Disease in mid‐life to older adults and patients
Authors: Kholghi Mahnoosh , Fazlollahi Amir , Lupton Michelle K , Bourgeat Pierrick , Zhang Qing , Martin Nicholas G , Breakspear Michael , Fripp Jurgen ,   PISA (Prospective Imaging Study of Aging: Genes, Brain and Behaviour)
Published: June 2023

Background

Recent research demonstrates a bidirectional relationship between sleep and Alzheimer’s Disease (AD) pathology, with supporting evidence that changes in sleep pattern occurs from the preclinical stage of AD. The cooccurrence of sleep disturbances and amyloid‐beta (Aβ) accumulation suggests the importance of monitoring sleep patterns in adults that are at high‐risk of developing AD later in life. We first investigated whether resting heart rate (RHR) and nocturnal sleep restlessness (NSR) are different in cognitively impaired (CI) and cognitively unimpaired (CU) mid‐life to older adults. We also examined any association of these sleep characteristics with hippocampus volume (HV) and Aβ, as neuroimaging biomarkers of AD, regardless of the cognitive status.

Method

107 middle to old age (46‐75 years old) adults (age 61.5±6.5, 74 Females, 64 APOE ε4 carriers, and 88 CU) underwent 3T MRI and PET scans as part of the Prospective Imaging Study of Ageing (PISA) study. A ballistocardiograph sleep monitoring device was used to track their RHR and NSR for approximately 5 months after their PET scan. NSR was quantified by total time in bed, total duration and number of bed‐exits, and multi‐episodic sleep. HV was normalised using total intracranial volume, and Aβ load was calculated in Centiloid scale (CL) with Aβ positivity defined as CL>20. Generalised Linear Models were used to examine the relationship between sleep and imaging biomarkers. Age, gender, BMI, APOE, and years of education were used as independent covariates.

Result

CIs spent more time in bed (p = 0.002) and had more bed‐exits (p = 0.009) than CUs. However, no significant difference was found on RHR and multi‐episodic sleep between CUs and CIs. Individuals with higher Aβ load, regardless of their cognitive status, had lower RHR (p = 0.04) and more bed‐exits (p = 0.04), and spent more time in bed (p = 0.01). Also, individuals with smaller HV frequently exited the bed during the night (p = 0.03) and spent more time in bed (p = 0.003).

Conclusion

Individuals with cognitive impairment experienced higher levels of NSR with frequent bed‐exits and more time in bed. Also, these sleep characteristics were significantly associated with the Centiloid value, Aβ status, and HV, regardless of the cognitive status.
Microglia show distinct tau associated subpopulations along tau spreading in human Alzheimer’s disease
Authors: Wachter Astrid , Woodbury Maya E. , Abdourahman Aicha , Bennett Rachel E , Lin Gen , Kwon Taekyung , Liao Fan , Pastika Timothy , Tamm Joseph A. , Venkat Nandini , Yanamandra Kiran , Grinberg Yelena , Kummer Markus P. , Das Sudeshna , Dellovade Tammy L. , Karran Eric H , Langlois Xavier , Ried Janina S , Serrano‐Pozo Alberto , Talanian Robert V. , Biber Knut , Hyman Bradley T.
Published: June 2023

Background

In Alzheimer’s disease (AD) progression, amyloid beta load uniformly increases across the brain cortex, while neurofibrillary tangles progressively spread in a stereotypical pattern from entorhinal to visual cortex. AD is known to have a strong genetic link to microglia and recently, expression profiling at single cell resolution has identified disease‐associated microglia populations with differential amyloid‐beta vs. tau pathology association in human AD brain. However, prior human studies focusing on microglia included a limited number of donors and/or cells per donor, and how microglial transcriptomes change with progression of tau pathology remains largely unknown.

Method

Using single nuclei RNA sequencing, we profiled 337,512 microglia from 32 donors across 4 pathology groups (no to severe pathology) and five brain regions along the tau spreading pathway (entorhinal cortex, Brodmann Area 20, Brodmann Area 46, secondary visual cortex, and primary visual cortex) to investigate their cellular heterogeneity as a function of disease progression. Phospho‐Tau231 and HT7‐HT7 aggregated tau levels of adjacent tissue were assessed for quantification of tau pathology.

Result

We confirmed previously described microglial populations across all profiled regions and identified cluster associations with tau levels, which mirrored the expected stereotypical progression across brain regions. Integrative analysis showed high similarity of microglia subtypes across regions, but interestingly also revealed entorhinal cortex and late tau pathology enriched clusters. Genes upregulated in early vs. late tau‐affected regions at severe pathology stage, but not in healthy brain, were found to be enriched in DNA repair and replication processes as well as immune response activation, while downregulated genes corresponded to glial cell differentiation and gliogenesis.

Conclusion

This study constitutes a high‐quality resource of microglia phenotypes in a previously unmet sample size with regard to both donors and cells per donor, well characterized by quantitative readouts for tau pathology association across tau spreading regions. We foresee this study will contribute to a better understanding of how microglial phenotypes can be targeted during the progression of tau pathology in AD, while further work is required to distinguish causality from consequence.
Expression of proteins involved in mitochondrial fusion, fission and energy production is altered by age, sex and Alzheimer’s disease
Authors: Aeschlimann Pascale C , Lane Emma L , Gee Julia M , Kidd Emma J
Published: June 2023

Background

Age is the biggest risk factor for Alzheimer’s disease (AD) but being female also increases risk with ∼63% of AD patients being female. This sex difference could partly be explained by menopause‐related oestrogen deficiencies during ageing. Oestrogen is neuroprotective and it is highly probable this deficiency after the menopause affects neuronal survival and contributes to the onset of AD. Oestrogen receptors are found in mitochondria and evidence suggests that the neuroprotective effect of oestrogen involves supporting mitochondrial function. The clear link between mitochondrial dysfunction and the pathophysiology of AD suggests a decrease in the beneficial effects of oestrogen on mitochondrial function after the menopause would have serious consequences. We hypothesise that alterations in oestrogen, due to ageing and the menopause, affect mitochondrial function and contribute to the increased susceptibility of women to AD.

Method

Levels of mitochondrial proteins, dynamin‐related protein‐1 (DRP‐1), mitofusin‐1/2 (Mfn1/2), mitochondrial dynamin‐like GTPase (OPA1) and the electron transport chain (ETC) complexes 1‐5, were measured using immunoblotting in frontal cortical brain samples from young (20‐36), middle‐aged (40‐53) and old (64‐99) men and women with no history of dementia and in AD patients (Braak stage 5/6, 69‐92 age).

Result

In female AD brains a significant decrease was observed in Mnf1 and DRP‐1 compared to age‐matched females and in OPA1 in male AD compared to old male brains. Mnf2 and ETC complex 3 (cytochrome reductase) were significantly increased in female AD compared to male AD brains. DRP‐1 was significantly decreased in old males compared to middle‐aged males, while ETC complex 2 (succinate dehydrogenase) was significantly increased in old females compared to young females.

Conclusion

We demonstrate for the first time age, sex and disease differences in the expression of proteins involved in various aspects of mitochondrial function including fusion, fission and energy production. These changes could underlie previous findings showing a range of mitochondrial abnormalities in AD brains and support the ‘mitochondrial cascade hypothesis’ that mitochondrial dysfunction is the primary event causing β‐amyloid deposition, synaptic degeneration, and NFT formation (Swerdlow et al., J. Alz. Dis. 2010 20:Suppl 2, 265‐79.). Our findings could partly explain female vulnerability to AD development.
Objective assessment of sleep parameters using multimodal AX3 data in older participants
Authors: Kalantari Elaheh , Monica Ciro Della , Revell Victoria Louise , Atzori Giuseppe , Hilton Adrian , Skeldon Anne C , Dijk Derk‐Jan , Kouchaki Samaneh
Published: June 2023

Background

Sleep disturbances are both risk factors for and symptoms of dementia. Current methods for assessing sleep disturbances are largely based on either polysomnography (PSG) which is costly and inconvenient, or self‐ or care‐giver reports which are prone to measurement error. Low‐cost methods to monitor sleep disturbances longitudinally and at scale can be useful for assessing symptom development. Here, we develop deep learning models that use multimodal variables (accelerometers and temperature) recorded by the AX3 to accurately identify sleep and wake epochs and derive sleep parameters.

Method

Eighteen men and women (65‐80y) participated in a sleep laboratory‐based study in which multiple devices for sleep monitoring were evaluated. PSGs were recorded over a 10‐h period and scored according to established criteria per 30 sec epochs. Tri‐axial accelerometers and temperature signals were captured with an Axivity AX3, at 100Hz and 1Hz, respectively, throughout a 19‐h period, including 10‐h concurrent PSG recording and 9‐h of wakefulness. We developed and evaluated a supervised deep learning algorithm to detect sleep and wake epochs and determine sleep parameters from the multimodal AX3 raw data. We validated our results with gold standard PSG measurements and compared our algorithm to the Biobank accelerometer analysis toolbox. Single modality (accelerometer or temperature) and multimodality (both signals) approaches were evaluated using the 3‐fold cross‐validation.

Result

The proposed deep learning model outperformed baseline models such as the Biobank accelerometer analysis toolbox and conventional machine learning classifiers (Random Forest and Support Vector Machine) by up to 25%. Using multimodal data improved sleep and wake classification performance (up to 18% higher) compared with the single modality. In terms of the sleep parameters, our approach boosted the accuracy of estimations by 11% on average compared to the Biobank accelerometer analysis toolbox.

Conclusion

In older adults without dementia, combining multimodal data from AX3 with deep learning methods allows satisfactory quantification of sleep and wakefulness. This approach holds promise for monitoring sleep behaviour and deriving accurate sleep parameters objectively and longitudinally from a low‐cost wearable sensor. A limitation of our current study is that the participants were healthy older adults: future work will focus on people living with dementia.
Re‐evaluation of the genetic role of a rare APOE variant (L28P; APOE*4Pittsburgh) in late‐onset Alzheimer disease
Authors: Fan Kang‐Hsien , Aslam Muhammad Muaaz , Francis Lily , Bedison Margaret A , Lawrence Elizabeth C , Acharya Vibha , Snitz Beth E , Ganguli Mary , DeKosky Steven T , Lopez Oscar L. , Feingold Eleanor , Kamboh M. Ilyas
Published: June 2023

Background

A rare missense APOE variant (L28P; APOE*4Pittsburgh) has been reported to be a risk factor for Alzheimer’s disease (AD). However, sinceL28P has been observed only among APOE*4 carriers, its independent genetic association is uncertain. In this study, we re‐evaluated this association in a large case‐control sample of 15,762 U.S. Whites aged ≥60 years and investigated its independent effect.

Method

Samples were derived from three sources: University of Pittsburgh, Alzheimer’s Disease Sequencing Project and the Gingko Evaluation Memory Study. Due to variation in the age distribution between cases and controls in the three studies, each study sample was analyzed separately, and the results then combined by meta‐analysis. To distinguish the independent effect of L28P from APOE*4, we restricted the analysis to subjects with the APOE 3/4 genotype, as L28P has been observed only in the heterozygous state in the APOE*4‐background and 3/4 is the most common genotype containing the APOE*4 allele.

Result

A total of 80 L28P heterozygotes were observed in the combined case‐control sample, all in those containing only the APOE*4 allele, confirming the complete linkage disequilibrium between the two sites. The age‐ and sex‐adjusted meta‐analysis odds ratio (OR) was 2.87 (95% CI: 1.34 – 6.13; p = 0.0066). There were a total of 4,138 cases and controls with the 3/4 genotype. The age‐ and sex‐adjusted meta‐analysis OR was 1.53 (95% CI: 0.70 – 3.36; p = 0.28). The lack of significance is mainly due to the low power with the ∼4,100 sample size (12% power at α = 0.80), as compared to the required sample size of ∼151,000 to detect an OR of 1.5 at α = 0.80.

Conclusion

Even with non‐significant p‐value, the OR of 1.53 among 3/4 subjects suggests that the effect of L28P on AD risk is independent of APOE*4. Our genetic finding is reinforced by an earlier experimental finding showing that this mutation leads to significant structural and conformational alterations in ApoE and can induce functional defects associated with neuronal Aβ42 accumulation and oxidative stress (J Biol Chem 2014; 289:12931). Additional studies in cell‐based systems and animal models will help to delineate its functional significance in the AD etiology.
The APOEε4 allele exacerbates the transcriptomic responses to Aβ plaques and neurofibrillary tangles in Alzheimer’s disease
Authors: Li Zhaozhi , Wachter Astrid , Alla Srinija , Noori Ayush , Abdourahman Aicha , Tamm Joseph A. , Woodbury Maya E. , Talanian Robert V. , Biber Knut , Karran Eric H , Das Sudeshna , Hyman Bradley T. , Serrano‐Pozo Alberto
Published: June 2023

Background

Microglia, astrocytes, and neurons undergo profound functional alterations in response to amyloid‐β (Aβ) plaques and neurofibrillary tangles (NFTs) in Alzheimer’s disease (AD). Recent studies using human induced pluripotent stem cell‐derived glial cells and neurons, APOE knock‐in mice, and human brain bulk RNA‐seq have implicated the APOE genotype in these changes, but lack spatial information with respect to Aβ plaques and NFTs. Here we tested the hypotheses that (1) transcriptomic differences between AD and control subjects are maximum within and near Aβ plaques and NFT‐bearing neurons; (2) Aβ plaques and NFTs are associated with distinct transcriptomic changes; and (3) the APOE genotype differentially impacts the transcriptomic changes associated with Aβ plaques and NFTs in the AD brain.

Method

Laser capture microdissection (LCM) in cryostat sections was performed from superior temporal gyrus (BA22) cortex of human AD (n = 10, including n = 5 APOEε4/ε4, n = 4 APOEε3/ε3, and n = 1 APOEε3/ε4) and age‐ and sex‐matched controls (n = 8). Thioflavin‐S‐positive Aβ plaques, the 50 µm halo around them, NFTs with the 50 µm halo around them, and areas far (>50 µm) from plaques and NFTs were laser‐capture microdissected and subjected to RNA‐sequencing to identify differentially expressed genes (DEGs).

Result

Aβ plaques had a greater impact on the transcriptome than NFTs (i.e., higher number of DEGs, both upregulated [logFC>0, unadj. P‐value<0.05: 2,623 vs. 1,230 genes; adj. P‐value<0.05: 1,152 vs. 0 genes] and downregulated [logFC>0, unadj. P‐value<0.05: 2,563 vs. 1,056 genes; adj. P‐value<0.05: 827 vs. 0 genes]) relative to control cortex. Aβ plaques were characterized by upregulated microglial and downregulated neuronal genes, whereas NFTs had primarily downregulated neuronal genes. A gradient of Aβ plaques > plaque halo > NFTs > far areas was evident, with upregulation of neuroinflammation and downregulation of synaptic neurotransmission and energy metabolism‐related gene sets. Comparing APOEε4 and APOEε3 age‐ and sex‐matched homozygotes revealed greater changes in APOEε4 homozygotes across locations.

Conclusion

Aβ plaques and, to a lesser extent, NFTs, concentrate the bulk of transcriptomic changes in the AD cortex. The APOEε4 allele is associated with greater microglial and neuronal transcriptomic responses to Aβ plaques and NFTs, compared to APOEε3 carriers. These findings will inform future spatial transcriptomics studies.
Brain reserve is associated with cognition in AD and MCI patients with different vascualr risk factors status
Authors: Lee Wei‐Ju , Chen Ting‐Bin , Chen Hung‐Chieh , Yang Yu‐Hsiu
Published: June 2023

Background

Dementia due to Alzheimer’s disease (AD) is the major type of dementias in the world. In addition to amyloid plaques and neurofibrillary tangles, cerebrovascular disease is another important pathophysiological cause of AD. Cerebrovascular disease is highly associated with vascular risk factors (VRFs). Well‐treated VRFs might decrease the risk and progression of AD. However, findings on the impact of VRFs treatment status on cognitive decline after the diagnosis of AD established are unclear, and there is no direct evidence supporting well‐treated VRFs can slow down the AD progression.

Method

This study recruited mild cognitive impairment (MCI) and mild AD patients (CDR = 0.5 or 1) with at least one VRF from at Taichung Veteran General Hospital. The treatment status of the VRFs was identified and all participants were evaluated by a standard neuropsychological test battery. We collected the participants’ brain MRI done within one year and performed Apolipoprotein E genotyping. FreeSurfer was used for structural MRI reconstruction and calculated total gray matter volume, hippocampus volume, and AD signature cortical thickness. Cerebrovascular lesions, including perivascular spaces in centrum semiovale, basal ganglia and presence of lobar cerebral microbleeds (LCMBs), and the volume of white matter hyperintensities were estimated by visual rating scales and Lesion Segmentation Tool for Statistical Parametric Mapping. We analyzed the relationships among the treatment status of VRFs, neuropsychological tests, and brain MRI.

Result

We recruited 61 patients in this study. Four patients refused to keep involving the study, 6 patients were not compatible with the criteria of MCI and AD after neuropsychiatric testing, and 4 patients’ brain MRI images cannot be analyzed after quality checked. The remaining 47 patients (15 MCI patients and 32 AD patients) constituted the final sample for analysis. The patients with well‐controlled VRFs present with similar cognitive function compared to the patients with partially‐controlled VRFs even though the more severe hippocampal atrophy was noted in the patients with well controlled VRFs. The severity of white matter hyperintensities and other cerebrovascular lesions are not correlated with the cognitive function in MCI and AD patients.

Conclusion

Brain reserve in the AD and MCI patients with well‐controlled VRFs might contribute cognitive function
Role of dopaminergic agonists on full‐length tau protein aggregation
Authors: Martic Sanela , Camilus Nayomi S
Published: June 2023

Background

Globally, a number of individuals who live with Alzheimer’s disease (AD), an incurable and debilitating disease, is increasing. Tau protein has a structural role, maintains integrity of microtubules and is one of the underlying causes of the tauopathies [1]. It is unfolded and highly soluble under physiological conditions. Dopamine receptor agonists have been used to target motor symptoms of AD [2] but there is a gap in knowledge on how these compounds play a role in tau protein aggregation.

Method

Herein, we propose to evaluate the use of a unique class of multivalent inhibitors with various moieties (catechol, non‐catechol, biphenyl, piperazine, and thiazole) [3] as potential inhibitors for in vitro full‐length tau protein aggregation induced by heparin. Fluorescence aggregation assay, transmission electron microscopy and 4,4′‐Dianilino‐1,1′‐binaphthyl‐5,5′‐disulfonic acid dipotassium salt (Bis‐ANS) fluorescence spectroscopy were used to obtain IC50 values, characterize the aggregation morphologies and evaluate the hydrophobicity of tau aggregates, respectively.

Result

The catechol containing compounds, D‐519 and D‐520, prevented aggregation of tau whereas the non‐catechol and thiazole containing compounds (D‐264 and D‐636) were poor inhibitors. Based on the inhibitors’ density function theory calculations, effective aggregation inhibitors are characterized by their high polarity and polarizability.

Conclusion

Data indicate that small molecule inhibitors may be useful therapeutics targeting tau aggregation related neurodegenerative diseases.

References:

[1] a. Andronesi, O. C., Bergen, M. V., Biernat, J., Seidel, K., Griesinger, C., Mandelkow, E., & Baldus, M. (2008). Characterization of Alzheimer’s‐like paired helical filaments from the core domain of tau protein using solid‐state NMR spectroscopy. Journal of the American Chemical Society, 130(18), 5922‐5928.;

b. Jeganathan, S., Hascher, A., Chinnathambi, S., Biernat, J., Mandelkow, E. M., & Mandelkow, E. (2008). Proline‐directed pseudo‐phosphorylation at AT8 and PHF1 epitopes induces a compaction of the paperclip folding of Tau and generates a pathological (MC‐1) conformation. Journal of Biological Chemistry, 283(46), 32066‐32076.

[2] Martorana, A. et al. (2013). Dopamine D2‐agonist Rotigotine effects on cortical excitability and central cholinergic transmission in Alzheimer’s disease patients. Neuropharmacology, 64, 108‐113.

[3] Ziu, I. et al. (2020). The multifunctional dopamine D2/D3 receptor agonists also possess inhibitory activity against the full‐length tau441 protein aggregation. Bioorganic & Medicinal Chemistry, 28(18), 115667.
NIH Toolbox‐Cognition performance of older persons with normal hearing, cochlear implant candidates, and cochlear implant users
Authors: Perrin Cameron K , Levin Joseph M , Schvartz‐Leyzac Kara C , Watson Gabrielle S , Giordani Bruno , Pfingst Bryan E
Published: June 2023

Background

A history of hearing loss is associated with lower scores on cognitive tests, as well as with incident Mild Cognitive Impairment and Alzheimer’s disease. In order to compare hearing adaptation in older age, we used iPad‐based testing to assess older healthy controls and older persons with two distinct approaches to hearing correction: one group with cochlear implants and another comprised of individuals with hearings aids awaiting cochlear implants. Speech recognition in noise is a common measure of hearing accuracy and reflects effectiveness of both hearing aids and implants. We expected to find that better speech recognition scores would relate to higher levels of cognitive performance across the groups.

Method

Participants were 54 individuals over 65 years of age (cochlear implants, n = 28; implant candidates using hearing aids n = 12; and normal hearing, n = 14), recruited through the University of Michigan Medical Center. All participants completed a speech in noise task and the NIH Toolbox‐Cognition battery (NIHTB‐CB) adapted for individuals with hearing loss. All scores from the NIHTB‐CB were corrected for education, age, race, and gender.

Result

For speech recognition, all groups performed significantly differently from each other (F = 57.408, p < 0.001), with the normal hearing group performing the best and the pre‐implant group performing the worst. For NIHTB‐CB scores, the only difference found was lower performance for the cochlear implant group compared to the normal‐hearing group on the Picture Vocabulary subtest (F = 3.417, p = 0.041). Duration of hearing loss was not correlated with cognitive performance on any of the tasks.

Conclusion

Overall, as expected, there were significant differences between groups on speech recognition. However, controls and all groups with hearing loss performed essentially equally well on all aspects of the adapted NIHTB‐CB. This suggests that in cases where hearing is partially corrected with a hearing aid or cochlear implant and tests are adapted for patients with hearing loss, group differences in cognition are not clearly evident, even when groups differed in speech perception. We hypothesized that duration of hearing loss may have driven the differences noted in vocabulary knowledge, however this was not supported in the results.

Supported by NIH#R01DC015809‐03S1 and P30AG072931.
Genetic association study of Alzheimer’s disease through whole genome tiling analysis
Authors: Bao Jingxuan , Lee Brian N , Zaranek Sarah Wait , Lee Matthew , Shivakumar Manu , Wen Junhao , Chen Jiong , Wen Zixuan , Yang Shu , Huang Heng , Saykin Andrew J. , Thompson Paul M , Davatzikos Christos , Kim Dokyoon , Zaranek Alexander Wait , Shen Li ,   for the Alzheimer’s Disease Neuroimaging Initiative and the AI4AD Initiative
Published: June 2023

Background

Numerous GWAS studies of Alzheimer’s disease (AD) have identified over 70 AD risk variants using SNP‐based genotyping or sequencing data. Recently, a new whole‐genome tiling (WGT) representation of whole‐genome sequencing (WGS) data has been proposed to enable an innovative definition of an individual’s genome; this WGT representation can support supervised and unsupervised machine learning. In this study, we perform a new AD GWAS study on the WGT representation of the ADNI WGS data.

Methods

The detailed description, genome tiling pipeline, and a publicly available example of WGT data are available at: https://curii.co/su92l‐j7d0g‐swtofxa2rct8495. In our analysis, we first performed quality control, imputation, and one‐hot encoding of tile variants (Fig. 1). Then, for each genome tile, we used the likelihood ratio test to compare two logistic regression models to get a single p‐value, where a full model used the tile variants and covariates to predict disease status, and a null model used only covariates including age, sex, education, APOE4, and first 20 PCs. Participants included 1,504 subjects (1,032 cases and 472 controls). In comparison, set‐based GWAS analysis was performed using PLINK 1.9 on ADNI SNP‐based WGS data.

Results

8,560,743 tiles passed the QC process and were included in our analysis. The likelihood ratio test yielded 35,582 significant tiles with Bonferroni correction. A set‐based GWAS comparative study among all significant tiles using SNP‐based WGS data identified 1,535 sets with at least one significant SNP variant. Among 1,535 sets, 1,066 sets passed uncorrected p≤0.05; 115 sets passed p≤0.005; and 15 sets passed p≤0.0005 (Fig. 2).

Conclusions

Our initial investigation of the tiling data shows that the WGT representation has promising power for identifying significant tiles that cannot be detected using the SNP representation. Complementary to the genotype values examined in traditional SNP analysis, the WGT analysis focuses on examining the haplotype variants within each tile and can capture the interaction pattern among SNPs within the haplotype. This initial AD GWAS study on WGT data demonstrates the promise of the tile representation for revealing novel genetic risk and protective factors in AD.
APOE4 and confluent WMH have a synergistic effect on episodic memory impairment in prodromal dementia
Authors: Kumar Dilip , Yatawara Chathuri , Wang Brian Zhiyang , Wong Benjamin , Tan Yi Jayne , Zailan Fatin Zahra , Ng Kok Pin , Kandiah Nagaendran
Published: June 2023

Background

White matter hyperintensities (WMH) are a known risk factor for cognitive decline (C.Puzo el. al. 2019). While the ε4 allele of apolipoprotein E gene (APOE4) is another risk factor for cognitive decline in concomitance with WMH (D.Tsuang et. al. 2013), it remains unclear how APOE4 affects the relationship between WMH and cognitive decline, specifically in the prodromal stage of dementia. Our objective was thus to determine how APOE4 moderates the relationship between WMH and cognition in prodromal dementia.

Method

216 participants with prodromal dementia underwent magnetic resonance imaging (MRI), neuropsychological testing (global and domain‐specific), cardiovascular risk factor assessments and APOE genotyping. Visual ratings for WMH as well as total and lobar WMH volumes were quantified. Moderation analysis was performed to determine the influence of APOE4 on the relationship between WMH and performance on global and domain‐specific cognitive measures (executive function, episodic memory, attention, language) in moderation analysis (Figure 1). The role of confluent and non‐confluent WMH subtype on cognition was additionally studied using moderation analysis and logistic regression (Figure 1).

Result

APOE4 carriers (n = 49) had poorer memory and higher global WMH (p = 0.04), temporal WMH (p = 0.01) and occipital WMH (p = 0.02) compared to APOE4 non‐carriers (n = 167). APOE4 strengthened the relationship between higher total WMH burden and worse episodic memory performance (Fig.2a). At the lobar WMH level, APOE4 strengthened associations between frontal, temporal, parietal and occipital WMH and episodic memory performance (Fig.2b, Fig.2c, Fig.2d, and Fig.2e) with large sized effects (β). APOE4 did not interact with either total or lobar WMH to predict worse cognition in other cognitive domains. Moreover, APOE4 strengthened the relationship between frontal WMH with episodic memory in the confluent WMH subgroup (Fig.2f). Logistic regression model showed memory impairment was 4.81 times more likely to develop in patients carrying APOE4 and with confluent WMH compared to APOE4 non‐carriers and those with non‐confluent WMH (OR 4.81, β 1.57, p<0.01).

Conclusion

The impact of WMH on memory may be strongest in APOE4 carriers at the prodromal dementia stage. Clinicians targeting WMH would need to consider the APOE4 allele and WMH severity status to strategize cognitive interventions.
NMDA receptor and APOE in Alzheimer’s disease: searching for connections
Authors: Escamilla Sergio
Published: June 2023

Background

NMDA receptor (NMDAR) malfunctioning has been claimed as a crucial event in Alzheimer’s disease (AD), the most common form of dementia. While synaptic NMDAR activation leads to synaptic plasticity, extrasynaptic NMDAR activation leads to excitotoxicity, mitotoxicity and cell death. In the late onset form of AD, the APOE4 allele is the main genetic risk factor. Our aim is to study the influence of apoE4 on NMDAR function.

Method

We isolated synaptic and extrasynaptic membranes from APOE genotyped frontal cortex samples, from AD and non‐demented subjects. We studied the levels of NMDAR subunits GluN2B and GluN2A. We also evaluated the GluN2B phosphorylation at sites Y1472 and Y1336, associated to synaptic and extrasynaptic membrane location, respectively. We are also developing hiPSC‐derived cortical neurons from APOE genotyped AD and non‐AD subjects.

Result

At synaptic membranes, we found lower levels of GluN2B, Glun2A and pY1472‐GluN2B in AD respect to non‐demented patients. Inside the AD group, APOE4‐frontal cortex showed lower levels of GluN2B respect to non‐APOE4. At extrasynaptic membranes, no changes in GluN2B and Glun2A levels were observed, but phosphorylation at Y1336‐GluN2B was higher in AD respect to that in control. These results suggest that in AD, NMDAR are more likely to be found at the extrasynaptic membranes, where specific phosphorylation retain these subunits to those membranes. The lowest levels of NMDAR at the AD synapsis were found in APOE4 subjects.

Conclusion

We found that the APOE4 allele seems to compromise NMDAR levels and phosphorylation in a different manner in synaptic vs extrasynaptic membranes in the AD patients. We try to understand the mechanisms that govern these status using iPSC‐derived neurons. Understansing the relation between the NMDAR and apoE in AD could lead to new therapteutical approaches.
Linguistic metrics of semantic fluency relate to longitudinal cortical thinning in older adults without dementia: The SMART‐MR study
Authors: Vonk Jet M.J. , Beran Magdalena , Zwartbol Maarten H.T. , Ghaznawi Rashid , Hendrikse Jeroen , Geerlings Mirjam I. ,   UCC‐SMART‐Study Group
Published: June 2023

Background

The need persists for sensitive, low‐cost, and high‐access cognitive markers to complement biomarker information in the earliest stages of Alzheimer’s disease. Sensitive cognitive markers may be derived from information at the item level of neuropsychological tests. We investigated if item‐level metrics add information beyond total score in the relationship of semantic fluency—generating as many words as possible of a category in a given time frame—to cortical thinning across eight years in middle‐aged to older adults without dementia.

Method

Participants were part of the SMART‐MR cohort (n = 251, age = 59.6±8.6, 19.5% women), designed to investigate brain changes in individuals with arterial disease, which puts them at high risk for dementia. Global cortical thickness was derived from MRI scans at two visits approximately eight years apart. Item‐level metrics were derived from linguistic databases: mean log lexical frequency (how often a word occurs in our language) and mean age of acquisition (AoA; at what age a word was learned) of words generated on a 2‐minute semantic (animal) fluency task (Fig 1). We calculated residualized item‐level scores representing the deviation in the item‐level metric from what is expected based on the total score to account for collinearity. Linear regression models—adjusted for age, sex/gender, education, and history of stroke—analyzed the relationship between total score or item‐level metrics as determinants and cortical thickness at follow‐up as the outcome, adjusting for baseline level.

Result

Total score alone was not related to cortical thinning at follow‐up (β = ‐.023[‐.001;.000], p = .466). However, a higher‐than‐expected mean lexical frequency (β = ‐.065[‐.054;‐.002], p = .033) and lower‐than‐expected mean AoA (β = .066[.001;.019], p = .033) were related to more cortical thinning at follow‐up. An alternative analytic approach to capture change, using the difference in cortical thickness between visits without baseline adjustment, yielded similar results.

Conclusion

Alternative item‐level metrics of semantic fluency, as opposed to the traditional total score, related to future neurodegeneration in high‐risk individuals without a dementia diagnosis. The results seem robust across two different item‐level metrics and two different analytic approaches. Valuable item‐level information could be leveraged for accurate identification of the earliest stages of clinical Alzheimer’s disease, in addition to biomarker evidence, for intervention and timely diagnosis.
Discovery of potential Alzheimer’s disease key biomarkers based on bioinformatics analysis
Authors: Silva‐Lucero Maria del Carmen , Rivera‐Osorio Jared , Lopez‐Toledo Gustavo , Gomez‐Virgilio Laura , Cardenas‐Aguayo Maria del Carmen
Published: June 2023

Background

Alzheimer’s disease (AD) is a neurodegenerative disorder and the most common cause of dementia in the elderly. AD is characterized by short‐term to long‐term memory loss, confusion, mood changes, and language difficulties. Numerous studies have focused on the dysregulated genes in AD, but the pathogenesis is still unknown. The underlying risk factors remain largely unclear. The discovery of more accurate AD biomarkers will allow early detection and development of new treatments. Recently bioinformatics has become a relevant research tool for biomedicine. In this study, we explored differential expressed genes (DEGs) potentially involved in the pathogenesis of AD.

Method

Open access databases of RNA microarrays of tissue from brain and peripheral blood of AD patient, were analyzed after background correction and data normalization; Limma package was used for Differential expression Analysis (DEA) throw statistical R programming language. Data were corrected with the Benjamini and Hochberg approach, and the genes with p values equal to or less than 0.05 were considered significant. The direction of change in gene expression was determined by its variation in the “log2‐fold change” between controls and patients. We performed a functional enrichment analysis of GO using goana and topGO‐Limma.

Result

With the Brain tissue database, we obtained 17 down regulated genes (DR) and 81 up regulated genes (UR). Functional enrichment analysis of DEGs showed UR pathways: behavior, nervous systems process, post synapses, enzyme binding, while DR were: cellular component organization, RNA metabolic process, protein‐containing complex, nucleoside triphosphatase activity and RNA binding. The blood tissue database showed 850 genes DR and 693 genes UR. The functional enrichment analysis of these DEGs showed UR pathways: regulation of transcription by RNA polymerase‐II and RNA processing, while DR were: cell development and synapses. Finally, the intersection of the DEGs in the two databases showed 3 genes shared between the brain and blood.

Conclusion

Our in‐silico analysis of brain and blood databases identified several UR and DR genes; the detection of these genes could provide new insight into potential therapies for AD. However, more research is needed to validate these potential new biomarkers and correlate them with the clinical data at different AD stages.
Physical activity and functional status in older adults: Mediating effect of cognitive function
Authors: Jin Yeonju , Hreha Kimberly , Hong Ickpyo
Published: June 2023

Background

Older adults who participate in social activities have more active lifestyles which has been shown to improve their quality of life (Acree et al., 2006). Generally instrumental activities of daily living (IADL) require aspects of social participation (e.g., cooking and managing finances) (Guo & Sapra, 2020). A previous study reported that physical and cognitive functions are positively associated with functional status in IADLs (Yam & Marsiske, 2013). In addition, since physical activity is associated with cognitive function, active participation in physical activity is recommended to maintain and improve cognitive function. While a number of studies have investigated the relationship between physical activity, cognitive function, and IADL, it is not clear if cognitive function acts as a mediator between physical activity and functional status equation. The aim of this study was to examine the relationship between physical activity and IADL and to clarify the mediating effect of cognitive function.

Method

A retrospective cross‐sectional design that analyzed the association between physical activities and IADL and the mediating effects of cognitive function. We retrieved 3,980 people from the 6 million recipients eligible for the Korean health insurance and benefits, between years 2002 and 2015. The included people in this analysis are 60 years and older and have completed the physical activity questionnaire. We estimated the indirect effect of physical activities through cognitive function on IADL performance.

Result

The average age of the participants was 81.6 years (SD = 5.5), and 72.74% were female. There were a direct effect of high‐intensity exercise on IADL (β = 0.04, 95% CI: 0.01, 0.07) and an indirect effect of high‐intensity exercise through cognitive function (β = 0.05; 95% CI: 0.04, 0.07). In addition, there were a direct effect of moderate‐intensity exercise and IADL (β = 0.04, 95% CI: 0.01, 0.07) and an indirect effect of moderate‐intensity exercise through cognitive function (β = 0.05; 95% CI: 0.04, 0.07).

Conclusion

The study indicated that there were positive relationships between physical activities, cognitive function and IADL. In addition, there was a mediating effect of cognitive function on the relationship between physical activities and IADL.
PET‐validated EEG‐machine learning algorithm predicts brain amyloid pathology in pre‐dementia Alzheimer’s disease
Authors: Kim Nam Heon , Park Ukeob , Yang Dong Won , Choi Seong Hye , Youn Young Chul , Kang Seung Wan
Published: June 2023

Background

Currently positron emission tomography (PET) is used as the initial or sole biomarker of β‐amyloid (Aβ) brain pathology, which may inhibit Alzheimer’s disease (AD) drug development and clinical use due to cost, access, and tolerability. Machine learning (ML)‐based EEG biomarkers may address these challenges. Previous studies have confirmed their ability to accurately discriminate between normal, mild cognitive impairment (MCI) and Alzheimer’s dementia. However, few quantitative EEG (QEEG) biomarkers have been validated with Aβ PET. We developed a QEEG‐ML algorithm to predict brain Aβ pathology among subjective cognitive decline (SCD) and MCI patients, and validated it using Aβ PET.

Method

EEG (19‐channel, eye‐closed, resting‐state) and Aβ PET data were collected from 311 subjects with SCD (Aβ+: N = 36, Aβ‐: N = 160) or MCI (Aβ+: N = 54, Aβ‐: N = 61). We randomly excluded data for 76 subjects (SCD, Aβ+: N = 7, Aβ‐: N = 28; MCI, Aβ+: N = 6, Aβ‐: N = 7) for use in subsequent verification. QEEG absolute power, relative power, power ratio, and connectivity between channels (iCoherence) comprised the input features, from which the most relevant predictive features were identified using several methods (Random Forest Importance (GBM, XGB), ElasticNet, Whitney‐Mann). We then trained four ML algorithms (SVM, Logistic, KNN, Naive Bayes, Random Forest(GBM/XGB)) using each relevant feature set, yielding 24 models (4 sets * 6 algorithms). The 76 validation data sets were input into each model to compare their performance.

Result

The best‐performing model (random forest importance * SVM) showed 82.9% accuracy, 90.9% sensitivity, 76.7% specificity, and 75% positive predictive value in discriminating Aβ+ from Aβ‐, regardless of MCI/SCD. In MCI alone, the model showed 82.1% accuracy, 90.0% sensitivity, 78.9% specificity, and 81.8% positive predictive value. In SCD alone, it showed, 81.1% accuracy, 92.3% sensitivity, 75% specificity, and 66.7% positive predictive value.

Conclusion

These findings suggest that our novel ML‐based QEEG biomarker can accurately predict the presence of brain Aβ plaque. Additional benefits of such a biomarker include reduced expense, wide availability, and high‐throughput screening and response monitoring. Future studies will assess utility as primary AD screens, adjunctive use with PET, and as a support in clinical rationales for Aβ PET and treatment choice in AD.
Dynamic functional brain networks in Alzheimer’s disease and healthy ageing
Authors: Rubido Nicolas , Vuksanovic Vesna ,   Swansea University Medical School
Published: June 2023

Background

Brain network analysis from resting‐state functional MRI (fMRI) has helped us to understand cortical activity in dementia. Likewise, dynamic brain networks' analysis, which takes into account temporal fluctuations in the resting‐state fMRI signal, has helped to reveal patterns of activity, usually averaged out by the conventional functional network analysis. These patterns of activity, or dynamic networks, reveal transient (meta‐stable) dynamics. Dynamic functional networks analysis from fMRI data has shown a potential to unveil clinically relevant information.

Method

Resting‐state fMRI from 187 participants belonging to Alzheimer’s Disease (AD) and cognitively‐normal Healthy Elderly (HE) from the ADNI‐3 database were analysed. Functional network was constructed from fMRI signal of the 120 cortical and sub‐cortical regions of the Jülich Atlas for each participants, and averaged across the two study groups. Dynamic functional connectivity is calculated using sliding window approach and compared to conventional (‘static’) functional connectivity within each study group and between them.

Result

Significant differences when comparing AD with HE individuals were found in the dynamic, but not static functional networks. These differences were restricted to the white matter regions, and to the inferior and superior parietal, and somatosensory cortices.

Conclusion

Our results demonstrate the existence of common and distinct patterns of static and dynamic brain connectivity in HE and AD, which highlight the importance of including non‐stationary information into the brain network analysis in Alzheimer’s disease.

References:

Vuksanović V, Hövel P. Dynamic changes in network synchrony reveal resting‐state functional networks. Chaos. 2015 Feb; 25(2):023116 [https://doi.org/10.1063/1.4913526].

Moguilner S, García AM, Perl YS, Tagliazucchi E, Piguet O, Kumfor F, Reyes P, Matallana D, Sedeño L, Ibáñez A. Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes: A multicenter study. Neuroimage. 2021 Jan 15; 225:117522 [https://doi.org/10.1016/j.neuroimage.2020.117522].

Acknowledgments: This work was supported by the Roland Sutton Academy Trust (Grant No. 13688)
Diffusion MRI subnetwork efficiency is associated with cognitive resilience to AD pathology in cognitively unimpaired older adults at risk of AD dementia
Authors: Qiu Ting , Liu Zhen‐Qi , Strikwerda‐Brown Cherie , St‐Onge Frederic , Binette Alexa Pichet , Descoteaux Maxime , Villeneuve Sylvia ,   the PREVENT‐AD Research Group
Published: June 2023

Background

While higher levels of Aβ and tau pathology are typically associated with more pronounced cognitive decline in Alzheimer’s disease (AD), some older adults exhibit normal cognition even with a substantial burden of AD pathology. This phenomenon is known as ‘cognitive resilience’. The potential role of structural connectivity in cognitive resilience remains inconclusive. The present study tested whether higher global efficiency in structural brain networks moderate the relationship between AD pathology and cognitive performance in the preclinical phase of AD.

Method

We studied 118 cognitively normal older adults from the family history enriched Prevent‐AD cohort. Diffusion‐weighted MRI was used to measure the structural connectome, PET to measure global Aβ (18F‐NAV4694) and entorhinal tau (18F‐Flortaucipir) pathology, and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) to evaluate cognitive performance. We first used graph theory analyses to calculate global efficiency of networks known to be affected in early AD (i.e., limbic and default mode network (DMN)). Then multiple linear regressions were performed to examine relationships between Aβ / tau pathology, cognitive performance, and global efficiency of the two subnetworks. Interaction analyses were used to examine whether network efficiency attenuates the relationships between AD pathology and cognitive performance.

Result

As expected, higher levels of Aβ and tau pathology in the brain were associated with worse cognitive performance in individuals at risk of AD (Figure 1). Higher entorhinal tau pathology was also associated with lower global efficiency in the limbic network (Figure 2). Subsequent interaction analyses showed that global efficiency in the limbic moderated the relationships between AD pathology and cognitive performance. Specifically, higher global efficiency was associated with an attenuated effect of both amyloid and tau pathology on delayed memory performance (Figure 3).

Conclusion

Individuals with higher global efficiency in the limbic structural network exhibit better memory performance at a given level of AD pathology in preclinical stages of the disease. Structural network properties of the brain may play an important role in maintaining cognitive performance in the face of AD pathology, and could serve as a potential biomarker for cognitive resilience.