bluuebunny/crossref_metadata_2025 huggingface dataset:
Inhibition of cPLA2 ameliorates memory deficits and reduces neuroinflammation in ApoE4‐TR mice
Authors: Wang Shaowei , Ebright Brandon , Sun Yi , Li Boyang , Asante Isaac , Louie Stan G , Yassine Hussein N.
Published: December 2022

Background

The activation of calcium‐dependent cytosolic phospholipase A2 (cPLA2) is involved in inflammatory signaling by promoting the conversion of arachidonic acid (AA) into eicosanoids, while catabolizing eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). We previously found higher cPLA2 activation correlated with increased pro‐inflammatory lipid metabolites in APOE4 brains. However, it is not known whether the inhibition cPLA2 will decrease neuroinflammation ApoE4‐mice.

Method

First, ApoE4 targeted replacement mice (ApoE4‐TR, n = 3, male, 4 months old) were treated daily with vehicle or the specific cPLA2 inhibitor ASB14780 (10 mg/kg, intraperitoneal) for three days. The brains were collected and analyzed using LC‐MS based lipidomics. Second, ApoE2‐TR (n = 14, 8M/6F), ApoE3‐TR (n = 12, 5M/7F) and ApoE4‐TR (n = 17, 8M/9F) mice were fed a low‐DHA diet starting at 6 months old. ApoE4 mice were treated daily for three weeks with vehicle (n = 8, 4M/4F) or 10mg/kg/day ASB14780 IP (n = 9, 5M/4F) starting at 14 months old. Behavioral tests were subsequently conducted on the mice, after which the brains were collected for lipidomic and biochemical analyses.

Result

IP ASB14780 was detected in brain tissue corresponding with decreases in pro‐inflammatory metabolites of AA after only 3 days treatment in ApoE4‐TR mice. In addition, long term ASB14780 treatment decreased brain cPLA2 phosphorylation levels and significantly increased brain EPA and DHA levels (p<0.01 for both) but did not change brain AA levels in ApoE4‐TR mice. Compared to ApoE3‐TR mice, untreated ApoE4‐TR mice had higher levels of inflammatory eicosanoids (e.g., prostaglandin E2, PGE2) resulting from AA metabolism. However, ASB14780 treatment decreased inflammatory metabolites in ApoE4‐TR mice. Additionally, ASB14780‐treatment was able to reduce microglia activation in ApoE4‐TR mice (p = 0.04 for hippocampus and p<0.01 for cortex). For behavioral experiments, ApoE4‐TR mice had significantly lower discrimination index compared to ApoE3‐TR mice at 15 months using the novel object recognition test (p = 0.029). Treatment with ASB14780 ameliorated the recognition deficits of ApoE4‐TR mice but the effects did not reach statistical significance (p = 0.15).

Conclusion

Our findings reveal inhibition of cPLA2 with ASB14780 could ameliorate eicosanoid‐driven neuroinflammation in ApoE4 mice, restoring synaptic dysfunction, and preventing behavioral deficits. cPLA2 represents a potential drug target to mitigate increased neuroinflammation with APOE4 and AD.
Neighborhood Deprivation and Mortality Risk among Medicare Beneficiaries with Alzheimer’s Disease and Related Dementia
Authors: Paley Joshua , Hernandez Inmaculada , Brown Joshua , Wu Yonghui , Bian Jiang , Anton Stephen , Guo Jingchuan
Published: December 2022

Background

Alzheimer’s Disease (AD) and Related Dementias (ADRD) is a class of progressive fatal degenerative diseases that presents multiple causations and outcomes related to its biological, medical, and social determinants of health (SDoH). Studies have extensively explored biological and medical factors, however, SDoH, which is known to contribute to structural inequities in health outcomes, is understudied. We aimed to study the association between neighborhood deprivation (an important SDoH measurement of socioeconomic disadvantage), and the risk of mortality among older adults diagnosed with AD/ADRD.

Method

Using a 5% random sample of national Medicare claims data, we identified individuals newly diagnosed with ADRD in 2006‐2013. The outcome of interest was all‐cause mortality. The exposure of interest was area deprivation index (ADI), a validated neighborhood deprivation measure that incorporates factors of poverty, education, housing, and employment. ADI was spatiotemporally linked to the study cohort using 9‐digit ZIP codes and index scores were classified into 6 categories: quartiles plus the 10th and 90th percentile. We applied generalized estimation equations to model an odds ratio (OR) of mortality across the ADI categories while adjusting for demographic and clinical factors. Subgroup analyses were modeled within urban and rural areas, respectively.

Results

We included 74,462 patients with ADRD diagnosis, with a mean age of 82 (SD: 8.2) years; 72.3% were women and 65.8% (n = 31218) died over a median follow‐up of 3.5 years. A dose‐gradient association between the ADI and all‐cause mortality was observed in the ADRD population, with the risk of mortality gradually increasing with greater deprivation (Table). The dose‐gradient association between ADI and mortality remained after stratifying by urban and rural areas. ADRD patients in rural areas had a higher mortality risk than those in urban areas (Table).

Conclusion

Our findings suggest neighborhood deprivation is an important risk factor of mortality among older adults with ADRD while accounting for individuals’ demographic and clinical characteristics. The current results underscore the need for the design and implementation of intervention and policy programs to address structural disparities in outcomes of ADRD patients.
Sex/Gender, Relationship Status, and Alzheimer’s and Related Dementia Diagnoses after Probable Dementia
Authors: Hanes Douglas William , Clouston Sean A.P.
Published: December 2022

Background

Differences by relationship status have been found in both cognitive‐assessment scores and prevalence and incidence rates for Alzheimer’s disease and related dementias (ADRD), but little is known about delayed and missed ADRD diagnoses after cognitive impairment emerges. Existing research has reported underdiagnosis for people of color, men, and people with less education.

Method

Using data from the Health and Retirement Study (2000‐2018), we analyzed associations between relationship status and time to ADRD diagnosis following probable dementia (PD). We examined risk of ADRD diagnosis by sex/gender and relationship status (married/partnered or single at the time of the first PD‐scoring assessment), adjusting for race/ethnicity, age, and education. Cox proportional hazards modeling was used to account for right‐censoring, with the risk period beginning at the time of the incident PD. Failure occurred when ADRD diagnosis was self‐reported. We also examined time until diagnosis among all participants with a recorded case of incident PD (N = 3,216 subjects: 9,540 observations). Restricted mean times to diagnosis and multivariable‐adjusted hazard ratios (aHR) with 95% Confidence Intervals (95% C.I.) were reported.

Result

Table 1 shows summary statistics; Table 2 provides hazard ratios; Table 3 shows mean times to diagnosis. Married/partnered women had the highest likelihood of receiving a diagnosis during the study period (HR: 1.197; 95% CI: 1.020‐1.360; p = <.001); single woman also had higher risk of diagnosis (HR: 1.178; 95% CI: 1.025–1.400; p = <.001). Mean time to diagnosis for men was 8.69 (±0.20); for women, 7.38 (±0.13). Singles received diagnoses sooner (7.32±0.135 years) than married/partnered people (8.39±0.169). Categorizing by sex/gender and relationship status, married/partnered women have the lowest mean times (7.00±0.148); single and married/partnered men’s mean times to diagnosis do not differ.

Conclusion

Relationship status is associated with women’s likelihood of reporting ADRD diagnosis and time to diagnosis, but not men’s. Further investigation is required to analyze potential sources of this disparity, including interactions with education, income, and insurance status, and additional gendered relationship, social, and familial factors.
Identifying delirium in advanced dementia in the ECT‐AD clinical trial
Authors: Lapid Maria I. , Forester Brent P. , Patrick Regan E. , Fong Tamara G. , Green Morgan E. , Harper David G. , Heintz Hannah L. , Hermida Adriana P. , McManus Kaitlin R. , Mueller Martina , Nykamp Louis J. , Petrides Georgios , Inouye Sharon K.
Published: December 2022

Background

Delirium and dementia are common causes of cognitive impairment in older adults and frequently co‐exist. Delirium is associated with poor clinical outcomes when comorbid with dementia. Identifying delirium superimposed on dementia (DSD) is clinically challenging given the overlap in symptoms, including inattention, cognitive impairment, and altered level of consciousness, especially in advanced stages of dementia. Recognition of delirium is also critical in ADRD (Alzheimer’s Disease and Related Dementias) clinical trials for both validity and safety reasons. The ECT‐AD study is one such trial investigating the safety and efficacy of electroconvulsive therapy (ECT) for treatment‐refractory agitation and aggression in individuals with advanced ADRD. Herein we review the Confusion Assessment Method (CAM) for identifying delirium in the ECT‐AD study.

Method

Inclusion criteria for ECT‐AD are hospitalized individuals diagnosed with ADRD (ages 55–89, MMSE ≤ 15) and refractory agitation/aggression, as measured by the Cohen‐Mansfield Agitation Inventory (CMAI). Procedures for detecting baseline and treatment‐emergent delirium involve a 3‐step approach conducted by raters trained in the CAM, which assesses inattention, disorganized thinking, altered levels of consciousness, and fluctuating mental status. Step 1 involves gathering information from nurse informants regarding the patient’s mental status over the past 24 hours. Step 2 involves collecting observational data through informal patient interaction (e.g., brief conversation). Step 3 is an objective assessment of cognitive status using the Severe Impairment Battery – 8 Item (SIB‐8), while also making qualitative observations about delirium features (e.g., level of consciousness). The rater then codes the CAM and determines delirium status based on these 3 steps.

Result

Of our 6 consented subjects, 1 experienced delirium detected by the CAM during the Randomization Phase. The subject received three positive CAMs on consecutive treatment days, citing change in mental status, inability to arouse, restlessness, psychomotor agitation, and swearing. ECT/S‐ECT was held each treatment day and the subject was withdrawn from the Randomization Phase.

Conclusion

Identifying DSD is challenging due to overlapping symptoms and the fluctuating nature of delirium. The CAM may be useful in this regard by using a multi‐step approach that incorporates observations from reliable informants, direct patient interactions, and structured cognitive assessments.
Identifying risk genes and therapeutics for Alzheimer’s disease through integration multi‐omics and drug‐perturbation signatures
Authors: Zhong Xue
Published: December 2022

Background

Alzheimer’s disease (AD) is a severe and irreversible neurodegenerative disease with no effective treatments currently available

Method

To better understand AD mechanisms and identify therapeutics, we collected AD GWAS loci from the largest meta‐analysis and incorporated multiple lines of genomic evidence, including human brain chromatin interaction map in microglia, brain cell‐type specific expression and gene‐gene interaction network, to infer high‐confidence risk genes (HRGs) at each GWAS locus. We then used the HRGs and network propagation to construct a genetic perturbation signature of AD, and queried a database of drug‐induced transcriptomic signatures (LINCS 1000) to evaluate compounds that are able to reverse the genetic perturbation signature.

Result

This resulted in 72 HRGs, which were further validated in multiple independent datasets of human microglia expression quantitative trait loci (eQTLs) and splicing quantitative trait loci (sQTLs), protein quantitative trait loci (pQTLs) in human brain, cerebrospinal fluid (CSF) and plasma, and genes of protein targets in brain and CSF associated with asymptomatic AD. Pathway analysis implicates the involvement of endocytosis and amyloid pathways, and highlights cellular compartments such as gamma‐secretase complex, NF‐kappaB complex, neurofibrillary tangle and endosome. Query of the genetic perturbation signature of AD against LINCS 1000 revealed several drugs that can reverse the genetic perturbation signature.

Conclusion

In conclusion, by incorporating multiple lines of evidence and resources, our study offers new insights into the pathological processes underlying AD and potential therapeutic drugs.
Tau Pathology in the Entorhinal‐Hippocampal Circuit
Authors: Ash Alyssa , Baek Sue Rim , Singh Sara , Snyder Jason
Published: December 2022

Background

The lateral entorhinal cortex (LEC) is the site of tau accumulation in early stages of Alzheimer’s disease and has projections downstream to the dentate gyrus (DG) of the hippocampus. The pathological form of tau has the ability to propagate across synapses, spreading to connected brain regions and correlating with memory deficits and synaptic loss. Downstream to the LEC, the hippocampal DG is the site of ongoing adult neurogenesis, with new granule neurons added showing enhanced plasticity and increased survival compared to older neurons. We are interested in examining the role of neuron age for vulnerability to tau pathology in the LEC‐DG circuit.

Method

We use a transgenic mouse model to label neurons born at different ages in the DG (development vs. adulthood) with a fluorescent reporter and inject a human Tau‐expressing virus, or control virus, into the LEC directly to mimic early, localized tau pathology. Following a 4‐month incubation, animals are tested for memory deficits specific to the LEC and hippocampus with Novel Object Recognition (NOR) and Novel Place Recognition (NPR) and tissue is immunohistochemically processed to analyze tau levels and cellular morphology in fluorescent‐labelled DG neurons. We assess synaptic changes in DG neurons via measuring dendritic spines, dendritic complexity and mossy fibre boutons.

Result

Our findings demonstrate that tau animals perform worse on NOR compared to healthy controls, while no difference is found for NPR. Morphological results show adult‐born neurons have an increase in thin dendritic spines and decrease in mushroom spines in tau animals relative to controls, as well as reduced mossy fibre bouton filopodia length.

Conclusion

Our initial results demonstrate the effect of tau on the LEC‐DG circuit, with altered synaptic structures and impaired memory performance under tau pathology.
The use of neuropsychiatric symptoms as biomarkers for a prodromal state among an electronic medical record cohort of neurodegenerative disorders
Authors: Clos Siara , Chabrashvili Tinatin
Published: December 2022

Background

Neuropsychiatric symptoms including anxiety, depression, psychosis, hallucinations, delusions, agitation, as well as sleep disturbances are associated with the development of dementia. We aim to show how they may be utilized as biomarkers of a prodromal state of neurodegenerative disorders.

Method

A cohort of Alzheimer’s disease (AD) and Dementia with Lewy body (DLB) patients was created using EPIC electronic medical record software. Data was compiled and analyzed using Microsoft Excel program.

Result

In our cohort of 5,784 AD patients, 1,721 (29.8%) held a diagnosis of anxiety, 2,727 (47.2%) depression, 2,231 (38.6%) psychosis, 165 (2.9%) hallucinations, 144 (2.5%) delusions, 376 (6.5%) agitation, and 1,242 (21.5%) sleep disturbance. Of 355 DLB patients, 110 (31.0%) had anxiety, 165 (46.5%) depression, 183 (51.6%) psychosis, 81 (22.8%) hallucinations, 18 (5.1%) delusions, 34 (9.6%) agitation, and 95 (26.8%) sleep disturbance. Of 81 patients with diagnoses of both AD and DLB, 36 (44.4%) had anxiety, 45 (55.6%) depression, 57 (70.4%) psychosis, 18 (22.2%) hallucinations, 7 (8.6%) delusions, 7 (8.6%) agitation, and 27 (33.3%) sleep disturbance. Many patients in the cohort held more than one neuropsychiatric diagnosis.

Conclusion

Neuropsychiatric symptoms have been shown to precede the onset of neurodegenerative disorders, including AD and DLB, by years to decades. Our study aims to demonstrate the use of neuropsychiatric symptoms as biomarkers for the future development of neurodegenerative disease.
Clinically normal elderly adults at genetic risk for sporadic Alzheimer’s disease have a path integration deficit
Authors: Colmant Lise , Bierbrauer Anne , Kunz Lukas , Axmacher Nikolai , Lefèvre Philippe , Hanseeuw Bernard J
Published: December 2022

Background

Alzheimer’s disease (AD) is associated with cognitive impairment, including spatial disorientation. Disorientation may be an early indicator of AD because spatial navigation relies on entorhinal cortex, the first cortical region affected by AD pathology. To test the hypothesis that spatial navigation declines in preclinical AD, we investigated age and genotype effects on a virtual path integration task, the "Apple Game" (Bierbrauer et al. 2020).

Method

Participants navigated in a virtual field and had to drop a basket to their initial location. Difficulty varied according to two parameters: (1) the number of interim locations (distractor) participants had to visit (0, 1, or 2); and (2) the presence or absence of a landmark. We recruited 145 clinically normal participants (MMSE>24/30, median age= 64). We genotyped the apolipoproteinE (APOE) gene, the ε4 allele of which is a risk factor for AD. We classified participants as E4 (n=41) if they had at least one ε4 allele and E3 (n=104) otherwise (table 1). We used linear mixed models to predict the drop error, i.e., the Euclidean distance between the correct and the actual drop location. The two components of the drop error, the angle and distance errors, were analyzed.

Results

The drop error increased with age. In trials with no distractor and no landmark, we observed higher drop error for E4 than E3 participants older than 70 years (fig.1), suggesting a deficit in pure path integration for oldest E4 carriers. This deficit was due to higher angle error (fig.2) rather than distance error (fig.3). In trials with distractors, performance dropped to chance level for all participants above 50 years (fig.4), suggesting the task was too difficult in general. In trials with landmark, the error was not influenced by the APOE genotype.

Conclusion

This spatial navigation task detected a deficit in pure path integration in elderly E4 carriers, when the task was not too difficult. The deficit may reflect an impairment in grid cells localized in the entorhinal cortex. Indeed, this group has probably the most AD neuropathology brain deposit. By contrast, landmark‐based navigation was impaired with age but not related to AD risk.
Tau protein spreads through functionally connected neurons in Alzheimer’s disease
Authors: Schoonhoven Deborah N , Coomans Emma M , Millan Ana P , van Nifterick Anne M , Visser Denise , Ossenkoppele Rik , Tuncel Hayel , van der Flier Wiesje M. , Golla Sandeep SV , Scheltens Philip , Hillebrand Arjan , van Berckel Bart NM , Stam Cornelis J , Gouw Alida A
Published: December 2022

Background

Recent studies in Alzheimer’s disease (AD) suggest that tau proteins spread through the brain following neuronal connections. Several mechanisms could be involved in this process: spreading between brain regions that interact strongly (functionally connected); through the pattern of anatomical connections (structural connectivity); or simple diffusion to spatially adjacent regions (Euclidean distance (EC)). We investigated this by modelling the tau‐spreading process on these different networks, and compared the modelled tau‐depositions with tau‐depositions at several stages of the AD continuum as measured with in‐vivo 18F‐flortaucipir PET.

Methods

We collected 10‐minutes eyes‐closed, whole‐head magnetoencephalography (MEG) recordings from 82 subjects (Table‐1) with and without Aβ‐pathology (CSF‐Aβ42 and/or amyloid‐PET) from the Amsterdam Dementia Cohort. Subjects were classed as controls (subjective cognitive decline (SCD) Aβ‐,n=25), preclinical AD (SCD Aβ+,n=16), mild cognitive impairment (MCI) due to AD (n=16) and probable AD dementia (n=25). Tau propagation was modelled as an epidemic process (susceptible‐infected (SI) model) on structural networks (Exponential Distance Rule (EDR) or EC), or functional networks (corrected‐amplitude envelope correlation (AEC‐c) in alpha (8‐13Hz) and beta (13‐30Hz) bands) derived from source‐reconstructed MEG data. The group‐level control network was used as backbone for the SI‐model to predict tau spread in the next stages of the AD continuum; parameters were tuned to produce an optimum correlation to the group‐specific tau propagation patterns as measured with dynamic 130‐minutes 18F‐flortaucipir PET, according to 50 regions‐of‐interest (ROIs) in an adjusted version of the probabilistic Hammers atlas. Tau propagation was modelled to start from one seed region (ROI14), which was selected based on its reliability to accurately measure tau deposition.

Result

The functional network predicted tau‐spread with highest accuracy in the preclinical AD stage (AEC‐c alpha r=0.59; AEC‐c beta r=0.58), followed by the structural network (r=0.45) and simple diffusion (r=0.44), Figure‐1, Figure‐2, Figure‐3. Prediction accuracy declined for the MCI and AD dementia stages (AEC‐c alpha r=0.50 and r=0.33; AEC‐c beta r=0.40 and r=0.37; structural r=0.29 and r=0.25; diffusion r=0.29 and r=0.25, respectively).

Conclusion

Using a relatively simple SI‐model we predicted tau propagation in preclinical AD with an accuracy of approximately 60%. Our results suggest that tau spreads through functional connections, rather than structural connections or simple diffusion.
The joint association of arteriosclerosis and plasma amyloid with cognitive function: the population‐based Rotterdam Study
Authors: Frentz Ingeborg , van Arendonk Joyce , Leeuwis Anna E , Vernooij Meike W. , van der Flier Wiesje M. , Bos Daniel , De Deyn Peter Paul , Wolters Frank J. , Ikram M. Arfan
Published: December 2022

Background

Alzheimer's disease and vascular brain injury are the most common causes of dementia, and are present jointly in 40% of individuals at time of death. Yet, the interaction between Alzheimer's and vascular pathology on cognition is largely undetermined. We studied the interaction between arteriosclerosis and plasma biomarkers of Alzheimer's disease on cognition in a general population without dementia.

Method

On stored plasma samples, obtained between 2002‐2005, we measured plasma levels of amyloid‐β40 and amyloid‐β42 by Simoa assay in 2252 participants of the population‐based Rotterdam Study (mean age: 68.9 years, 52% women). Arteriosclerosis was assessed using arterial calcification volumes that were quantified (semi‐)automatically on unenhanced computed tomography (CT). We captured the systemic burden of calcification, using a principal component analysis of calcification volumes in 4 different arterial vessel beds (intracranial and extracranial carotid arteries, coronary arteries and aortic arch). Cognitive assessment included the verbal fluency test, the letter‐digit substitution task, a 15‐word learning test, the Stroop test, and Purdue pegboard task. Global cognition (g‐factor) was calculated using a principal component analysis of these tests. We then determined the interaction between plasma amyloid‐β and calcification on cognitive performance, using multivariable linear regression models.

Result

Plasma levels of amyloid‐β and systemic arteriosclerosis were both associated with poorer cognitive performance. After mutual adjustment in multivariable models only calcification remained significantly associated (beta [95%CI] for g‐factor per 1‐SD increase in amyloid‐β40: ‐0.02 [‐0.07; 0.03]; amyloid‐β42: 0.03 [‐0.01; 0.08]; and calcification burden: ‐0.06 [‐0.09; ‐0.04]). The association between amyloid‐β and cognition was stronger in individuals with higher burden of calcification (Figure 1), particularly for amyloid‐β40 (interaction amyloid‐β40×calcification: p = 0.04; amyloid‐β42×calcification: p = 0.001). Results were broadly similar across cognitive tests. The observed interaction between amyloid‐β40 and calcification volume was most profound for calcification burden in the intracranial carotid artery and aortic arch.

Conclusion

Arteriosclerosis and amyloid‐β display synergistic effects on cognition in the general population. This interaction was more profound for amyloid‐β40 than for amyloid‐β42, suggesting our observations may relate particularly to amyloid angiopathy.
Genetic Data Identify Dual‐enrolled Participants in Alzheimer's Disease and Related Dementia (ADRD) Studies
Authors: Nudelman Kelly N. H. , Franklin Erin E. , Wyss Catharine M. , Jackson Trever , Bernhardt Haley , Case K. Rose , Lacy Kaci , Faber Kelley M. , Kukull Walter A. , Wang Li‐San , Saykin Andrew J. , Perrin Richard J. , Morris John C. , Weiner Michael W. , Foroud Tatiana M.
Published: December 2022

Background

It is not unusual for Alzheimer’s Disease (AD) Research Center (ADRC) participants to enroll in additional studies such as the AD Neuroimaging Initiative (ADNI). In such cases, shared access to neuropathologic biospecimens is important to both studies, but dual‐enrollment status is not always known to acting ADRC personnel, and currently there is no centralized method to track dual enrollment. For this study, we aimed to identify individuals enrolled in ADNI and an ADRC, and identify those with autopsy data available through an ADRC but not ADNI.

Method

GWAS data were obtained for ADRC participants (N=22,935) through the AD Genetics Consortium (ADGC) and for ADNI participants (N=2,048) through the Laboratory of NeuroImaging (LONI); data were compared in PLINK v1.9 by identity‐by‐descent (IBD). ADRC/ADNI matches were filtered for pi‐hat > 0.8. Genotype data from a custom‐96 SNP microarray for ADRC and ADNI samples banked at the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) were also compared to identify additional matches. Year of birth, sex, race, and ethnicity were compared within matches. Participant IDs from matches were reviewed for autopsy data available through the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) and from ADNI, to identify participants with autopsy data available through NACC but not ADNI. We generated counts for matches that had year of death, and among those, how many had neuropathology variables.

Result

We identified 364 pairs with matched genetic (pi‐hat>0.99) and available demographic data from GWAS data, and another 52 from NCRAD genotype data. Of these, 143 matched ADRC participants had a year of death. 98 of the 143 had autopsy variables in the NACC UDS. 44 of these 98 were included in the ADNI autopsy data set (2018 version) or pending integration by the ADNI Neuropathology Core (NPC). Thus, 54 ADRC brain donors could be reported to the ADRCs as dually‐enrolled in ADNI, providing the involved ADRCs the opportunity to share these biospecimens with the ADNI NPC.

Conclusion

This case study illustrates how identification of dually‐enrolled participants represents a unique opportunity to leverage data collected through multiple studies to enhance AD research.
Astrocyte specific chromatin accessibility differences in European vs African Alzheimer Disease brains
Authors: Celis Katrina , Griswold Anthony J. , Rajabli Farid , Whitehead Patrice L. , Hamilton‐Nelson Kara L. , Dykxhoorn Derek M. , Nuytemans Karen , Wang Liyong , Weintraub Sandra , Geula Changiz , Gearing Marla , Trojanowski John Q , Bennett David A , Pericak‐Vance Margaret A. , Young Juan J , Vance Jeffery M. , Flanagan Margaret E
Published: December 2022

Background

The APOE4 gene, the strongest genetic risk factor for late‐onset Alzheimer disease (AD), is highly expressed in astrocytes. The local ancestry (LA) region surrounding APOE4 (Chr19:44‐46Mb) is associated with increased AD risk for European (EU) compared to African (AF) APOE4 carriers. We previously demonstrated that APOE4 expression is higher in astrocytes from EU LA carrier brains using single nuclei RNA (snRNA) sequencing. We investigate whether chromatin accessibility differences could explain the APOE4 expression differences between ancestries.

Method

We performed snRNA and assays for transposase accessible chromatin sequencing (snATAC) in six EU and six AF APOE4 AD brains. Bioinformatic analysis was performed using Seurat for snRNA and ArchR for snATAC.

Result

94,411 and 60,306 nuclei were sequenced by snRNA and snATAC, respectively. Following data integration, we resolved 11 distinct cell type clusters. We confirmed that APOE4 expression in astrocytes was higher in EU (Fold change=1.51; p=1.01x10‐113) and that chromatin accessibility is indeed higher in EU astrocytes at the APOE4 promoter and surrounding LA. Genome‐wide, astrocytes had the most differentially accessible peaks between ancestries (N=12,518, 95% increased accessibility in EU) representing 2.1% of all peaks. Interestingly, chr19 had the most differentially accessible peaks between ancestries (N=964) with 98% increased accessibility in EU. (EU:245; AF:4) peaks were in the APOE4 LA region with 60% overlapping promoters. Pathway analysis of genes with increased chromatin accessibility in EU LA showed enrichment for lipoprotein assembly, remodeling, and clearance.

Conclusion

This study represents initial efforts to investigate underlying mechanisms that contribute to the differential expression demonstrated between AF and EU LA brains surrounding APOE4. Our results suggest that the increased EU APOE4 expression previously observed in EU AD LA APOE4 homozygotes relative to AF LA APOE4 homozygotes in astrocytes is at least partly due to increased EU astrocyte chromatin accessibility in the LA region.
BLSA Plasma Biomarkers and Prediction of Amyloid PET Status
Authors: An Yang , Bilgel Murat , Walker Keenan A , Moghekar Abhay , Resnick Susan M.
Published: December 2022

Background

It’s crucial to quantify and compare the accuracies of plasma biomarkers in predicting amyloid PET status.

Method

The sample included a cross‐sectional sample of 212 participants from Baltimore Longitudinal Study of Aging. Amyloid PET status was determined from Pittsburgh compound B (PiB) PET using a Gaussian mixture model (140 PiB– and 72 PiB+). Using the Quanterix SIMOA Neuro‐4‐plex, three plasma biomarkers (amyloid‐beta 42 to 40 ratio [Aβ42/Aβ40], glial fibrillary acidic protein [GFAP], and neurofilament light chain [NfL]) were evaluated. We used receiver operating characteristic (ROC) curve analysis to estimate area under the curve (AUC) for each of the three biomarkers in predicting amyloid PET status. AUC estimates were cross validated using leave‐one‐out method. Finally, from a set of potential features (i.e., the three plasma biomarkers, age and APOE‐ε4 carrier status), we applied stepwise logistic regression to find the best subset of features to predict amyloid PET status.

Result

Participant characteristics are presented in Table 1. Each of the 3 biomarkers performed better than a random classifier, with GFAP having the highest validated AUC (0.692), followed by Aβ42/Aβ40 (AUC=0.677), and NfL (AUC=0.625) (Figure 1). The only statistically significant AUC difference is between GFAP and NfL (p = 0.029) (Table 2). Based on stepwise logistic regression, the model with Aβ42/Aβ40, GFAP and APOE‐ε4 status was selected as the final model with a moderate AUC of 0.732 (Figure 2). Odds ratios associated with each predictor are reported in Table 3.

Conclusion

Of the three Quanterix SIMOA plasma biomarkers, Aβ42/Aβ40 and GFAP have similar AUCs and are better at predicting amyloid PET status compared with NfL, although all AUCs are modest. The final multivariable logistic regression model, which included Aβ42/Aβ40, GFAP and APOE‐ε4 status, had a modest AUC of 0.732. Future studies with larger samples and more biomarkers, especially p‐tau measure, will be necessary to develop better prediction models.
Generalized q‐sampling imaging‐based fiber tracking measures of white matter tracts in cognitive impairment
Authors: Duran Tugce , Bateman James R. , Williams Benjamin J. , Hughes Tim M. , Barcus Richard A. , Peavey Jeremy J. , Okonmah‐Obazee Stephanie E. , Whitlow Christopher T. , Craft Suzanne , Lockhart Samuel N.
Published: December 2022

Background

Diffusion magnetic resonance imaging (dMRI) is a non‐invasive technique for exploring white matter fiber organization of the brain. As traditional diffusion tensor imaging (DTI) methods may provide inaccurate descriptions of local crossing, kissing and diverging fibers, we examined generalized q‐sampling imaging (GQI), a novel method providing better directional and quantitative information using dMRI data from community‐dwelling older adults.

Method

We examined baseline dMRI data from 227 adults aged 71±8 on average from the Wake Forest Alzheimer’s Disease Research Center’s Clinical Core, who had baseline and year‐1 follow‐up global Clinical Dementia Rating (CDR) score of 0 (indicates normal cognitive function) and 0.5 (akin to mild cognitive impairment [MCI]). The primary outcome measure was cognitive migration status determined by CDR increase/decrease between baseline and follow‐up (mean difference=13.9 months), shown in Figure. We performed atlas‐based fiber tracking analysis using GQI in DSI Studio to generate normalized quantitative anisotropy (NQA), DTI fractional anisotropy (DTI_FA) and restricted diffusion (RDI) measures in several AD‐related white matter (WM) tracts: Corpus Callosum (CC), Fornix, Cingulum bundle/Parahippocampal tracts (CFP; CP; CPP), Uncinate Fasciculus (UF), Superior Longitudinal Fasciculus (SLF) and Inferior Fronto‐Occipital Fasciculus (IFOF). We performed multinomial logistic regression (MLR) models adjusted for age, sex, and education, using cognitive migration status as the outcome, and standardized GQI‐based diffusion indices sNQA, sRDI, and sDTI_FA as predictors.

Result

Table 1 lists the baseline demographics and biomarker characteristics for cognitive migration groups. MLR results in Table 2 show significant associations between diffusion indices and tracts for outcome 4 (Reversion) in reference to outcome 1 (stability of normal cognition). Decrease in sNQA in bilateral CP and right Fornix was significantly associated with higher odds of Reversion relative to the reference. Increase in sDTI_FA in left IFOF was associated with higher odds of reversion relative to reference. Decrease in sRDI in bilateral CFP, CPP, Fornix and UF and right CP was associated with higher reversion relative to reference.

Conclusion

In early trajectories of cognitive impairment, RDI may be a sensitive diffusion marker for cognitive reversion in several AD‐related WM tracts. Future work will validate these markers in other cognitive migration groups (negative migration and MCI stability).
Differential returns on education by ethnicity and nativity in a cohort of older white and Asian Americans
Authors: Hayes‐Larson Eleanor , Ikesu Ryo , Gee Gilbert C , Brookmeyer Ron , Whitmer Rachel A. , Gilsanz Paola , Mayeda Elizabeth Rose
Published: December 2022

Background

Asian Americans generally have lower risk of dementia than white Americans. Education likely protects against dementia via direct development of cognitive reserve and indirectly via income and material resources. However, the protective effects of education may be weaker among Asian Americans due to lower income returns among the foreign‐born. We hypothesized that: (1) the effects of education may be weaker among Asians than whites; (2) the effects of education are weaker among foreign‐born than US‐born individuals.

Method

We followed a cohort of 5,974 Chinese, 4,601 Filipino, 3,071 Japanese, and 131,762 white Kaiser Permanente Northern California members for incident dementia (2002‐2020). We estimated hazard ratios (HRs) with age‐ and sex‐adjusted Cox proportional hazards models to examine whether estimated effects of college education (versus less than college degree) on dementia incidence differed by race/ethnicity (Asian versus white) and nativity (US‐ versus foreign‐born). Models were run for Asian ethnicities pooled and separately due to potential subgroup heterogeneity.

Result

Mean baseline age was 71.3 years (standard deviation, SD 7.7), and mean follow‐up time was 9.5 years (SD 4.6). The estimated effect of college education appeared slightly more protective against dementia incidence among Asian Americans than whites (HR 0.84 95% CI [0.76‐0.92] in Asian Americans, 0.89 [0.86‐0.91] in whites; Figure). There was heterogeneity across Asian groups. The estimated effect of college education (versus less than college) was most protective in Chinese individuals (0.73 [0.62‐0.85]) and Filipinos (0.80 [0.67‐0.95]), but null in Japanese (1.02 [0.84‐1.23]). College education also appeared more protective in foreign‐born vs. US‐born Asian Americans but not whites. Nativity results were also driven by strong effect modification among Chinese participants; other Asian ethnic group estimates were imprecise.

Conclusion

Contrary to expectations, college education may confer slightly greater protection against dementia for Asian than white Americans, driven by differences among foreign‐born. Due to devaluing of education among immigrants, it is unlikely that social/material resources conferred by high education explain the greater protective effect in Asian Americans. However, there is substantial heterogeneity by Asian ethnicity, and additional work on the mechanisms driving differences by ethnicity and nativity (e.g. bilingualism, selective migration) is needed.
Multi‐contrast unbiased MRI template of a Parkinson’s disease population
Authors: Madge Victoria , Fonov Vladimir S , Xiao Yiming , Zou Lucy , Jackson Courtney , Postuma Ronald B , Dagher Alain , Fon Edward A , Collins D Louis
Published: December 2022

Background

Parkinson’s disease (PD) is a complex neurodegenerative disorder affecting regions such as the substantia nigra (SN), red nucleus (RN) and locus coeruleus (LC). Processing MRI data from patients with PD requires anatomical structural references for spatial normalization and structural segmentation. Extending our previous work (Xiao et al., 2015/17), we present multi‐contrast unbiased MRI templates of a larger population of 172 subjects using more modalities: T1w, T2*w, T1‐T2* fusion, R2*map, T2w, PDw, fluid‐attenuated inversion recovery (FLAIR), improved susceptibility‐weighted imaging (CLEAR‐SWI) (Eckstein et al., 2021), and neuromelanin‐sensitive MRI (NM).

Methods

Subjects were recruited through the Quebec Parkinson’s Network since December 2018 and are included in a database of PD patients, RBD patients, and age‐ and sex‐ matched healthy controls, complete with MRI data, motor, and cognitive evaluation scores. All raw MRI was QC’d, eliminating scans with artefacts, motion, or noise, resulting in 172 subjects (69 female; ages=39‐87). Using our previous methods (Fonov et al., 2011), a non‐linear unbiased average T1‐T2* fusion template was created in stereotaxic space. For the other contrasts, the subject’s linear contrast‐to‐T1‐T2* transformation was concatenated with the subject’s T1‐T2* non‐linear stereotaxic transformation to avoid multiple resamplings before voxel‐wise averaging of all subject data in the common template space.

Results

Figure 1 depicts the whole brain 1mm template. Figure 2 depicts a closeup of the 0.3 mm template of the midbrain. From both figures, the first eight contrasts were created from 172 subjects: 145 PD, 1 RBD, and 26 controls. The NM contrast was created from 121 subjects (59 female; ages=39‐87): 99 PD, 1 RBD, and 21 controls. The T1‐T2* fusion maps provide improved deep grey matter contrast from T2*w images, while maintaining cortical structure information from T1w images. R2* maps, T2w, PD2, FLAIR, and CLEAR‐SWI contrasts highlight deep grey structures including SN, RN, subthalamic nucleus (STN), putamen, and globus pallidum, while the NM contrast highlights NM‐rich regions of SN and LC.

Conclusion

Anatomical structural references are useful for structural segmentation and morphometric analyses between healthy controls, PD, and RBD patients in regions such as SN, RN, and LC to aid in early diagnosis and better understand disease prognosis.
Literacy, but not memory, is associated with hippocampal connectivity in illiterate adults
Authors: Resende Elisa de Paula França , Lara Vivian Proença , Santiago Ana Luisa Carvalho , Friedlaender Clarisse Vasconcelos , Rosen Howard J. , Grinberg Lea Tenenholz , Brown Jesse A. , Cobigo Yann , Silva Lênio Lúcio Gávio , de Souza Leonardo Cruz , Rincon Luciana Paula , Maciel Francisca I , Caramelli Paulo
Published: December 2022

Background

The role of hippocampal connectivity for good memory performance is well known in persons with high educational level. However, it is understudied the role of hippocampal connectivity in illiterate populations.

Methods

Thirty‐nine illiterate adults from Brazil underwent a literacy assessment, structural and resting state functional MRI and an episodic memory test (Free and Cued Selective Reminding Test). We correlated the hippocampal connectivity at rest with the free recall scores and the literacy scores. Analyzes were done in SPM 12, corrected for head motion and physiological BOLD signal.

Results

Participants were most female (66%) and black (79%) and the mean age was 49 years‐old (±13.9). The mean score on free recall was 27.2 (±10.7) out of 48 points and the mean literacy score was 34.9 (±21.1) out of 100 points. The median hippocampal gray matter volume was 2.4 [0.9, 2.3]cm3 in the left and 2.1 [2.1, 2.4] cm3 in the right side. There was a significant connectivity between both hippocampi and the precuneus and the ventral medial prefrontal cortex. However, this connectivity did not correlate with episodic memory scores, but the right hippocampal connectivity correlated with the literacy scores (R2 = 0.13, p = 0.014, CI 1.0‐1.0). Furthermore, the hippocampal gray matter volume did not correlate with memory scores.

Conclusions

Although we did not find a significant correlation between memory and the connectivity between both hippocampi and the precuneus and ventral medial prefrontal cortex, we found that this connectivity correlated with literacy scores on the right side. The lack of association with memory scores might be associated with low brain reserve in illiterate adults. The association between hippocampal connectivity and low literacy scores suggest a room for improvement if those adults learn how to read later in life.
Evaluating the biological variability of blood‐based biomarkers for use in clinical trials
Authors: Trombetta Bianca A. , Allen Shona W. , El‐Mufti Leena H. , Riley Misha M. , Ramirez Christopher E. , Weik Molly , Carlyle Becky C. , Kivisäkk Pia , Arnold Steven E.
Published: December 2022

Background

Blood‐based biomarkers offer the possibility of inexpensive, minimally invasive, and accessible diagnostic tools for Alzheimer’s Disease (AD). In the context of clinical trials, these biomarkers hold promise for subject stratification and monitoring the effects of therapeutic interventions. The day‐to‐day variability of these measures must be robustly characterized to determine which blood‐based biomarkers would be the most sensitive for detecting treatment‐related responses. In this study we evaluate biomarker performance in plasma and identify the most reliable candidates for clinical trials.

Method

EDTA plasma samples were collected from healthy controls (n=20, 50% female, mean age 56.03 ± 9.43 years) at baseline, 2 weeks, and 4 weeks. Singleplex ELISA and multiplex MesoScale Discovery (MSD) immunoassays were used to measure over 25 biomarkers that were selected for their relevance to dysregulated processes in AD and previously validated in cerebrospinal fluid (CSF). Technical performance was assessed by calculating intra‐ and inter‐plate coefficients of variation (CVs), analyzing dilution linearity, and evaluating freeze‐thaw stability. Biological intra‐individual variability was examined by calculating a biotemporal CV for each subject across the three timepoints.

Results

Most biomarkers were quantifiable in plasma and exhibited technical performance within our thresholds (intra‐ and inter‐plate CV < 15%). The biomarkers exhibited a range of freeze‐thaw stability, with mean CVs from 5.2% for Adiponectin, a regulator of glucose metabolism, to 30.2% for GRP78, an ER chaperone protein. Plasma levels were relatively stable across time (biotemporal CV < 20%) for several biomarkers, including 24‐OHC, VEGF‐D, Flt‐1, PlGF, sST2, and sTREM2. Several proteins exhibited significant variability over time (biotemporal CV > 20%), such as 8‐OHdG, GRP78, and YKL‐40.

Conclusion

Key metabolic, vascular, and inflammatory biomarkers were reliably measurable in the plasma of healthy individuals. Several markers exhibited substantial variability over a 2‐4 week time period, which should be taken into consideration when selecting appropriate markers for assessing drug‐target engagement. Designing future clinical trials with multiple baseline visits will allow us to establish biological variability metrics for each individual’s biomarker levels, providing greater confidence in determining treatment effects. Evaluating biomarker stability in other large‐scale subject populations will be necessary to best inform blood‐based biomarker selection for clinical trials.
Early detection of Alzheimer's disease subtypes in Amsterdam Dementia Cohort
Authors: Venkatraghavan Vikram , Kate Mara ten , Pijnenburg Yolande A.L. , Teunissen Charlotte E. , Barkhof Frederik , van der Flier Wiesje M. , Tijms Betty M.
Published: December 2022

Background

Heterogeneity in the atrophy profile and clinical presentation of Alzheimer’s disease (AD) is well documented in literature. Defining tangible data‐driven subtypes and detecting these subtypes early in an individual is paramount to devising precise intervention strategies. In this study, we estimated distinct data‐driven AD subtypes and their corresponding atrophy timelines from cross‐sectional data and used it for predicting the subtypes of preclinical and prodromal patients.

Method

1725 AD (age=66.8±8.4), 856 mild cognitively impaired (MCI, age=67.1±8.0), 672 subjective cognitive decline (SCD, age=61.4±10.2) with unknown or positive amyloid status, and 756 controls or SCD with negative amyloid status (CN, age=58.8±9.0) were selected from the Amsterdam Dementia Cohort. Baseline T1w MRIs were processed using Freesurfer and the volumes were selected after automatic quality check (Rosen, NeuroImage, 2018). AD patients in the cohort were used for identifying distinct subtypes using non‐negative matrix factorization (ten Kate, Brain, 2018). Sequences of regional abnormalities were modelled using discriminative event‐based model (Venkatraghavan, NeuroImage, 2021) to identify early atrophy regions in each subtype. The trained model was used to predict the subtypes of MCI and SCD patients. Lastly, we estimated disease severity scores for each individual in the subtype they belong in, based on their position along the respective atrophy timelines.

Result

We identified four AD subtypes: typical subtype (NAD=453(26.3%)), early frontal cortical atrophy (FCA) (NAD=475(27.5%)), early posterior cortical atrophy (PCA) (NAD=349(20.2%)), and early subcortical atrophy (SA) (NAD=362(21.0%)). 86(5.0%) AD patients did not belong in any of these subtypes. The atrophy timelines of each subtype are shown in Figure 1. The trained model predicted the subtypes in 653 MCI (NTypical=202, NFCA=188, NPCA=86, and NSA=177) and 380 SCD patients (NTypical=83, NFCA=158, NPCA=52, and NSA=87). 203 MCI and 292 SCD patients did not belong to any subtype. Individual severity score increased for worse disease stages in each subtype, as seen in Figure 1, validating both the predicted subtypes and the estimated timelines.

Conclusion

We identified four AD subtypes, their atrophy timelines, and used it for early detection of subtypes in MCI and SCD patients. Future work should focus on devising precision intervention strategy for patients in each subtype.