bluuebunny/crossref_metadata_2025 huggingface dataset:
Changes in neighborhood disadvantage over 18 years contributes to racial disparities in later‐life cognition
Authors: Sol Ketlyne , Esposito Michael , Clarke Philippa , Zahodne Laura B.
Published: December 2022

Background

Neighborhood disadvantage (NDis) is a well‐studied contextual and local indicator of Black‐White health disparities, including cognitive health. Trajectories of NDis are less commonly studied but may be important for understanding how investment and disinvestment in neighborhoods with predominately Black residents may contribute to disparities in cognitive aging. This study characterizes 18‐year trajectories of NDis and examines whether trajectories of NDis mediate Black‐White disparities in cognitive function.

Method

This study of 480 non‐Hispanic Black (NHB) and White (NHW) older adults (Mage = 63.9; 55% Black) were drawn from the Michigan Cognitive Aging Project (MCAP), a regionally‐representative, prospective longitudinal study of older adults in the Detroit metropolitan area. Participants’ current addresses were geocoded and linked to historical neighborhood data from the National Neighborhood Data Archive (NaNDA). Yearly measures of NDis from 2000 to 2017 reflect a composite of four indicators of disadvantage (proportions of: female headed families with children; households with public assistance; families below the federal poverty level; adults unemployed). First, a latent class growth analysis (LCGA) was used to determine distinct types of 18‐year NDis trajectories across 1,344 census tracts in the six counties represented in the sample. Next, path analysis was used to quantify the extent to which the identified classes of NDis trajectory mediated the association between race and global cognition, which was operationalized as a composite of five cognitive domain factor scores (i.e., episodic memory, executive function, processing speed, language, and visuospatial ability). Mediation models adjusted for age, sex/gender, and education.

Result

LCGA indicated three classes of NDis trajectories: persistently high disadvantage (PHD: 9%), high and increasing disadvantage (HID; 16%), and persistently low disadvantage (PLD; 75%). NHB participants were more likely to live in PHD or HID neighborhoods, which were each associated with worse global cognition. NDis trajectories explained 12% of the Black‐White disparity in global cognition. HID was a stronger mediator of cognitive disparities than PHD.

Conclusion

Disinvestment in neighborhoods may contribute to racial disparities in global cognition among adults transitioning to late life. This study highlights the value of examining risk and resilience factors at the neighborhood level in research on ADRD inequalities.
Characterizing Amyloid Responsive Microglia in a Cognitively Resilient Patient with Alzheimer’s Disease Neuropathologic Change: A Case Report
Authors: Nguyen Aivi T. , Przybelski Scott A. , Lesnick Timothy G. , Ramanan Vijay K , Petersen Ronald C. , Graff‐Radford Jonathan , Knopman David S. , Jack Clifford R. , Dickson Dennis W. , Van Deerlin Vivianna M , Lee Eddie B , Reichard Ross R. , Vemuri Prashanthi
Published: December 2022

Background

Cognitive resilience, the discrepancy observed in individuals with high Alzheimer’s disease (AD) neuropathology and near‐normal cognition, is a growing area of study, wherein multiple factors are responsible. Currently, the role of the microglial activation in cognitive resilience is unknown. Herein described is a case report characterizing the amyloid responsive microglia (ARM) in an 88‐year‐old male decedent homozygous for APOE E4, clinically cognitively intact, and found to have AD neuropathologic change (ADNC) upon autopsy.

Method

The participant was enrolled in the Mayo Clinic Study of Aging (MCSA) and continuously followed for 14 years from 73‐ to 87‐years‐old, wherein serial MRI and clinical assessments were obtained. An autopsy was performed upon death, and routine neuropathologic sections were taken. Formalin‐fixed, paraffin‐embedded sections were stained with H&E, and single immunohistochemistry was performed using antibodies against tau (AT8), beta‐amyloid (6F3D), alpha‐synuclein (LB509), TDP‐43 (pS409/410), and CD163 (10D6). Digital image analysis was performed on dorsolateral prefrontal cortex sections scanned at 40x (Leica GT450). ARM (CD163% area) and beta‐amyloid (% area) measurements were obtained using QuPath threshold classifiers. Descriptive statistics were performed (Graphpad).

Result

The decedent was an 88‐year‐old male, homozygous for APOE E4, with a history of three cardiovascular and metabolic conditions, and lifelong smoking. His MMSE (average 28/30) and global cognition (average ‐0.51) were relatively stable (Figure 1), with no clinical concerns for cognitive impairment. Cortical thickness was normal (temporal meta‐ROI>3 mm) on four serial MRIs. The participant reported high cognitive, physical activities, and education‐occupation scores (upper quartile for the 70+ population). Neuropathologic evaluation was notable for severe cerebral amyloid angiopathy, high ADNC (A3B3C3), and remote microinfarcts. CD163‐positive ARM were observed in the neocortices and perivascular spaces, and the ARM:beta‐amyloid ratio was 0.26 (Figure 1). This ARM:beta‐amyloid ratio trended upwards (>90th percentile) compared to APOE E4/E4‐matched‐ and age‐matched controls provided from the University of Pennsylvania.

Conclusion

This case report demonstrates a cognitively resilient individual with an elevated ARM:amyloid ratio. Conversely, lower ARM ratios were observed in a cognitively impaired cohort, raising the possibility ARM may associate with cognition. ARM may represent a protective and phagocytic population, and further studies correlating microglia, cognition, and putative mechanism are required.
Reliability of BBB water exchange rate assessed by diffusion‐prepared pseudo‐continuous ASL (DP‐pCASL): Preliminary results from the Cognitive Recovery After Elective Surgery (CREATES) Study
Authors: Shao Xingfeng , Wang Danny JJ , Boxerman Jerrold , Schlett Wesley J , Cosgriff Mads P , Daiello Lori A
Published: December 2022

Background

Impaired blood‐brain barrier (BBB) function is hypothesized to be an important mechanism in the development of perioperative neurocognitive disorders (postoperative delirium and postoperative cognitive impairment), as well as in the onset and progression of Alzheimer’s (AD) and cerebrovascular disease. Non‐contrast neuroimaging methods have shown promise for detecting subtle alterations in BBB permeability; however, test‐retest reliability has not been well‐established. Here we report preliminary results for BBB water exchange rate (kw ) values from a novel diffusion‐prepared 3D pseudo‐continuous arterial spin labeling (DP‐pCASL) protocol with two different post‐labeling delays (PLD), and compared test‐retest reliability results with the original approach with a single PLD.

Method

The DP‐pCASL pulse sequence (resolution=3.5x3.5x8mm3, 10 slices) has been previously described (Shao X, et al., 2019). kw was calculated from the ratio of intra‐ and extra‐vascular perfusion signals using the original protocol with 1‐PLD [1.8 sec]; and the new protocol with 2‐PLDs [1.8 and 2.1 sec]. Total scan time was 15 minutes.

Participants were healthy older adult controls enrolled in Cognitive Recovery After Elective Surgery (CREATES) study, a longitudinal study of relationships between BBB dysfunction and perioperative neurocognitive disorders following major elective surgery. Seventeen participants (11 females, age=78.5±5.4 yrs) underwent test‐retest MRI scans (∼30 days apart) on a Siemens 3T Prisma Fit system (Erlangen, Germany). kw maps were normalized into the MNI space, and regional analysis was performed for cortical gray/white matter, frontal/temporal/parietal areas, and nine subcortical brain regions. Test‐retest reliability was evaluated by intra‐class correlation coefficients (ICC).

Result

Whole brain and regional kw values were calculated for the two protocols (Table 1). Test‐retest reliability increased using the 2‐PLD protocol. Whole brain kw ICC was 0.7 (good reliability; reference range, 0.5‐0.74) vs. 0.87 (excellent reliability; reference range, ≥ 0.75) for 1‐PLD and 2‐PLD protocols, respectively (Figure 1). ICC values increased across all brain regions with the 2‐PLD protocol (Figure 2).

Conclusion

In a modest sample of cognitively healthy older adults, we found that measurement reliability of whole brain and regional kw values was notably improved by using the 2‐PLD DP‐pCASL protocol. These preliminary findings warrant confirmation in larger cohorts with and without late‐life cognitive disorders.
Establishing a Type 2 Diabetes phenotype in APPxhQC transgenic mice expressing N‐terminally modified pGlu Aβ peptides.
Authors: Babalola Joshua Adekunle , Loeffler Tina , Schilcher Irene , Breznik Livia , Rabl Roland , Sideromenos Spyridon , Flunkert Stefanie , Prokesch Manuela , Hoefler Gerald , Hutter‐Paier Birgit
Published: December 2022

Background

Alzheimer’s disease (AD) is a debilitating neurodegenerative disease characterized by the accumulation of amyloid beta (Aβ) plaques in the brain. Aβ peptides are commonly subjected to post‐translational modifications like truncation known to play pivotal role in Aβ plaque aggregation. N‐terminally truncated Aβ peptides containing pyroglutamatic acid (pGlu) catalyzed by glutaminyl cyclase (QC) e.g., pGlu3‐Aβ (3‐40/42) are the major Aβ peptide fragments within the core of the neuritic plaques and correlate with disease severity and progression. Type 2 diabetes (T2D) is one of the major risk factors associated with AD and compelling evidence supports the notion that insulin resistance, a key feature of T2D, is involved in AD‐type neurodegeneration. Hence, in this study, we aim to establish a T2D phenotype in APPxhQC transgenic using low‐dose Streptozocin injection in combination with high fat diet (HFD).

Methods

APPxhQC mice, crossbreds of APPSL and hQC mice, were used. APPSL mice express human APP751 with the Swedish and the London mutation on a C57Bl/6RccHsd background. hQC mice on B6CBAF1/J background express human glutaminyl cyclase (QC) enzyme. The cross‐breeding results in an increased generation of N‐terminal modified pGlu Aβ peptides. To establish a T2D phenotype, 8‐9 months old APPxhQC transgenic mice were allocated to 4 treatment groups receiving: standard chow diet, HFD, standard chow diet in combination with streptozocin injections and HFD in combination with streptozocin injections. The intraperitoneal glucose tolerance test (ipGTT) and intraperitoneal insulin tolerance test (ipITT) were performed at 6 and 7 weeks after the initiation of the diet, as a relevant parameter of T2D progression.

Results

Streptozocin‐injected mice maintained on HFD had the least tolerance to injected glucose as shown by ipGTT. Impaired glucose clearance was observed at 15, 30, 60 and 120 mins after intraperitoneal glucose injection (2g/kg). Also, impaired glucose clearance at 15 mins after intraperitoneal insulin injection (0.75U/kg) was observed in the same group.

Conclusion

Combination of high‐fat diet and streptozocin injections leads to the development of robust T2D symptoms in APPxhQC transgenic mice. Current experiments are focusing on combinational effects of T2D and post‐translationally modified amyloid peptides in AD progression and pathophysiology.
The Relationship between Vascular Risk Factors and White Matter Structural and Vascular Imaging Metrics
Authors: Kim Donghoon , Hughes Tim M. , Kim Jeongchul , Harvey Danielle J. , Lockhart Samuel N. , Craft Suzanne , Baker Laura D. , Whitlow Christopher T. , Okonmah‐Obazee Stephanie E. , Hugenschmidt Christina E , Bobinski Matthew , Jung Youngkyoo
Published: December 2022

Background

Vascular risk factors are associated with cerebral small vessel disease and dementia pathology and reduced WM integrity is correlated with the severity of cognitive impairment in dementia. We have investigated if vascular risk factors are related to white matter structural and vascular imaging metrics. Imaging metrics include intracellular volume fraction (ICVF), white matter hyperintensities (WMH), and cerebrovascular measures such as cerebral blood flow (CBF), cerebrovascular reactivity (CVR), and arterial transit time (ATT).

Method

Sixty‐four subjects (Table 1) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core cohort underwent MRI, including T2 FLAIR, neurite orientation dispersion and density imaging (NODDI), pseudo‐continuous ASL (PCASL). CVR was measured as a percent of increased CBF during a hypercapnic respiratory paradigm. ATT and resting CBF were obtained from a multi‐TI PCASL sequence. ICVF was obtained from NODDI. Head size adjusted WM total lesion volume (TLV) was calculated using SPM12‐LST2 toolbox with T2‐FLAIR image. Linear regression models were performed to examine if CBF, CVR, ATT, ICVF, or TLV are related to the risk factors or cognitive status adjusted covariates: age, sex, and years of education. A covariates adjusted logistic regression estimated weighting factors for each interrelated vascular imaging parameter to create novel cerebrovascular functional composites for each vascular risk group and mild cognitive impairment (MCI) group. The factor score p‐values were also calculated from two‐sample t‐tests with the cerebrovascular composite. The entire analyses were performed within the whole brain WM.

Result

In the whole brain WM, hypertension subjects (p=0.031) showed higher CVR (Figure 1). T2DM subjects (p=0.007) showed higher WM TLV (Figure 2). T2DM and MCI subjects showed lower ICVF than normal subjects did (Figure 3). Based on the weights of each cerebrovascular parameter in the composite (Table 2), the effects of CBF and CVR are stronger in hypertension group while all three cerebrovascular measures had substantial contribution to cognition status.

Conclusion

Each risk factor and cognitive status differently affected WM structural and vascular dynamic imaging parameters. The findings warrant further investigations of contributions of vascular risk factors to the structural and vascular abnormalities in dementia.
Posterior hippocampal redundancy: A marker of non‐pathological brain aging
Authors: Blujus Jenna K , Oh Hwamee
Published: December 2022

Background

Several neural mechanisms underlying brain resilience to Alzheimer’s disease (AD) have been proposed, including redundant neural connections between the posterior hippocampi and all other brain regions (pHipp‐redundancy), and global functional connectivity of the left frontal cortex (gLFC). It remains unclear whether these two mechanisms confer resilience to AD pathologies through similar or distinctive mechanisms. We examined if redundancy, measured through graph theory, underlies the neuroprotective effects of both pHipp‐redundancy and gLFC connectivity in the early stage of AD pathologies.

Method

From the ADNI database, 370 CN and MCI participants were utilized. Aβ‐positivity (Aβ+) was defined as PET AV45 SUVR normalized to cerebellum greater than 1.11. Resting state data were preprocessed using fMRIprep. Network graphs were constructed with 263 functional ROIs as nodes and z‐transformed correlations between each node as edges. Redundancy was calculated by summing the direct and indirect paths (path lengths=1‐4) between each hippocampal region (i.e., anterior and posterior hippocampal regions, bilaterally and LFC) and its 262 connections. Group differences (Aβ‐status, diagnosis) were computed in R using non‐parametric ANCOVA models with 10,000 permutations. Regression analyses were conducted to examine if Aβ‐status and diagnosis moderated the relationship between SUVR and redundancy. Models covaried for age, sex, education, and APOE4.

Result

Across CN and MCI, Aβ‐ had higher bilateral pHipp‐redundancy than Aβ+ (p’s<.034). Diagnosis significantly moderated the relationship between SUVR and left pHipp‐redundancy (B=16143.0, p=.042). CN exhibited a stronger negative relationship between SUVR and left pHipp‐redundancy than MCI (B=‐20161.59, t=3.08, p<.001). Finally, in CN, Aβ‐status significantly moderated the relationship between SUVR and right aHipp‐redundancy (B=59345.0, p=.012), showing that in Aβ‐ CN, redundancy decreased with higher SUVR (B=‐60532.07, t=2.82, p=.01), while in Aβ+ CN, redundancy remained the same as SUVRs increased. No relationships between Aβ‐status and redundancy, and interactions between SUVR and Aβ‐status or diagnosis, were significant in LFC.

Conclusion

Together, these findings suggest that bilateral pHipp‐redundancy may reflect normal brain aging without Aβ, rather than resilience in pathological aging, and a distinctive mechanism of brain aging from that of gLFC connectivity in the progression of AD.
Associations between brain iron deposition and structural Alzheimer’s disease signature in cognitively unimpaired adults
Authors: Stankeviciute Laura , Falcon Carles , Operto Grégory , Rojas Santiago , Grau‐Rivera Oriol , Garcia Marina , Shekari Mahnaz , Niñerola‐Baizán Aida , Perissinotti Andrés , Minguillón Carolina , Fauria Karine , Molinuevo Jose Luis , Zetterberg Henrik , Blennow Kaj , Suárez‐Calvet Marc , Cacciaglia Raffaele , Gispert Juan Domingo
Published: December 2022

Background

Iron dyshomeostasis appears to be an early event in the Alzheimer’s continuum. However, little is known how incipient cerebral iron deposition affects brain structure and function in cognitively unimpaired (CU) individuals. Here, we assessed the relationship between mean intensities in subcortical nuclei, a proxy measure for iron content, and regional cortical thickness as well as brain metabolism in middle‐aged CU individuals and sought for interactions with biomarkers of Alzheimer’s pathology.

Method

We included 288 CU adults from the ALFA+ cohort (Table 1). Mean intensities were quantified from T2‐weighted magnetic resonance images in 18 a priori defined subcortical nuclei. Due to the high correlations among regional intensities, we performed a principal component analysis to obtain a single measurement of cerebral iron load (Table 2). Cortical thickness (CT) of the “Alzheimer’s disease (AD) signature” composite region of interest (ROI) was assessed using FreeSurfer v6.0. [18F]fluorodeoxyglucose (FDG) PET scans were used to calculate the standardized uptake value ratio (SUVr) within a meta ROI. We created separate general linear models where cortical thickness and PET meta‐ROIs were the dependent variables, while the first principal component (PC1), age, sex, APOE‐ε4 status, and education level were entered as predictors. In additional models, CSF levels of amyloid‐beta ratio (Aβ42/40) and phosphorylated tau (p‐tau) were entered as covariates. We also tested the interaction between PC1 and CSF Aβ42/40 and pTau status. Statistical significance was set at p<0.05.

Result

PC1 explained 47.64% of the variance of mean intensities in subcortical regions with lower values denoting higher iron concentration. Lower PC1 values were negatively associated with AD‐signature thickness (p=0.004), but not with brain glucose metabolism in the meta ROI (p=0.936). (Table 3. Figure 1). These results remained unchanged once AD core CSF biomarkers were entered into the model. No significant interactions with abnormal levels of CSF Aβ or p‐Tau were revealed with AD‐signature thickness or brain metabolism.

Conclusion

In CU individuals, higher content of iron deposition is associated with reduced thickness, but not glucose metabolism, in cortical areas that typically show atrophy early in the Alzheimer’s continuum. This association was not modified by the presence of altered biomarkers of AD pathology.
Relationship between [18F]flortaucipir PET visual patterns and neurodegeneration
Authors: Heeman Fiona , Moscoso Alexis , Camacho Valle , van Essen Martijn , Grothe Michel J. , Lin Li , Mainta Isminni , Ribaldi Federica , Devous Michael D. , Pontecorvo Michael J. , Frisoni Giovanni B , Garibotto Valentina , Schöll Michael
Published: December 2022

Background

The introduction of tau positron emission tomography (PET) ligands has allowed for the in vivo assessment of tau pathology in Alzheimer’s disease (AD). The recent development and FDA approval of [18F]flortaucipir (FTP) reader guidelines has enabled standardized visual assessment of FTP PET scans as showing negative, moderate or advanced AD tau patterns, thereby facilitating implementation of FTP scans in clinical practice. Although various studies have reported associations between regional FTP signal and neurodegeneration, the relationship between the standardized visual FTP AD patterns and markers of neurodegeneration has not yet been studied. This study aims to understand how FTP AD visual patterns relate to markers of neurodegeneration from structural MRI and FDG‐PET scans. Specifically, it focusses on characterizing regional neurodegeneration associated with the moderate AD pattern, both in cognitively normal (CN) and cognitively impaired participants (CI).

Method

Participants from five cohorts were included: the Alzheimer’s Disease Neuroimaging Initiative, Harvard Aging Brain Study, A4 study, the Geneva Memory Clinic cohort and AVID’s A05 study. These cohorts include CN participants, mild cognitively impaired and AD dementia patients who have available FTP, MRI and/or FDG scans, a subset also received follow‐up MRI scans. Furthermore, Centiloid values are available for all participants to quantitatively determine amyloid‐β (Aβ) positivity. All FTP scans are currently independently evaluated by three trained readers, blinded to clinical and imaging information. Majority read is used to assign scans to the negative, moderate or advanced AD tau pattern groups.

Result

A total of 1948 participants underwent baseline FTP PET and MRI scans, a subset of 462 participants also underwent FDG‐PET scans. Between‐group differences in MRI‐ and FDG‐derived patterns of neurodegeneration are evaluated cross‐sectionally. In addition, the value of FTP AD patterns for predicting longitudinal neurodegeneration using MRI‐derived atrophy measures is assessed using Linear Mixed Models. All analyses are conducted separately for CN and CI participants, as well as stratified by Aβ (positive vs. negative) status. NB. Results of these analyses will be presented during the conference.

Conclusion

This study will contribute to our understanding of the clinical relevance and prognostic value of the moderate and advanced FTP AD patterns in CN and CI individuals.
Greater AD prediction accuracy is obtained using hippocampal grading over hippocampal volume
Authors: Morrison Cassandra , Dadar Mahsa , Shafiee Neda , Collins D Louis
Published: December 2022

Background

To develop new Alzheimer’s disease (AD) treatments, diagnostic tools must be applied before too much irreversible neurodegeneration occurs. One of the key features used to identify AD neurodegeneration is hippocampal (HC) volume. However, prediction accuracy using HC volume is not high enough to be implemented in clinical and research settings. The goal of this study was to compare prediction accuracy of HC volume and HC grading, a method that measures local morphological similarity of the HC to a library of NC and AD subjects.

Methods

Participants were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and were included if they had a baseline diagnosis of either healthy older adult (cognitively normal, CN) or AD and baseline MRI scans. A total of 841 older adults met the inclusion criteria (513 CN and 328 AD). A second analysis examining the 388 amyloid positive participants was also completed (179 CN and 209 AD). A previously validated MRI analysis method (SNIPE) was used for HC grading (Coupe et al., 2012) and a similar non‐local patch‐based method was used to segment the HC to obtain volumes (Coupe et al. 2010). HC volumes provided by ADNI using Freesurfer were also analyzed for comparison. Age, sex, and either SNIPE grading, SNIPE volume, or Freesurfer volumes were used as features in three support vector machines to classify participants as either CN or AD, using a 10‐fold cross validation.

Results

Using SNIPE grading, 88% accuracy was obtained when classifying CN from AD. SNIPE volume, generated 76% accuracy, while Freesurfer HC volume resulted in 67% accuracy when distinguishing CN from AD. The second analysis of only the amyloid positive participants yielded accuracies of 87% (SNIPE Grading), 77% (SNIPE volume), and 52% (Freesurfer volume).

Conclusion

HC grading, as measured by SNIPE, provides much higher accuracy at classifying CN from AD than both patch‐based HC segmentation volumes or Freesurfer HC volumes. These findings suggest that HC grading may be a useful tool at successfully predicting AD. The ability to correctly differentiate between groups who are amyloid positive is important for improving participant selection in clinical trials.
Modules of genotypic variance reflect heterogeneity across TDP‐43 proteinopathies
Authors: Spencer Barbara E , Irwin David J. , Van Deerlin Vivianna M , Lee Eddie B , Elman Lauren , Quinn Colin , Grossman Murray , Wolk David A. , McMillan Corey T
Published: December 2022

Background

TAR DNA‐binding protein (TDP‐43) proteinopathies yield a variety of neurodegenerative conditions including amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD), and hippocampal sclerosis of aging (HS‐Aging). However, the contribution of both shared and disparate single nucleotide polymorphisms (SNPs) to phenotypic presentations is unclear. We hypothesize that shared genetic variation may drive susceptibility across diseases while disparate genetic variation may contribute to our understanding of disease‐specific drivers.

Method

We compared the relative associations of GWAS summary statistics for ALS, FTLD‐TDP, and HS‐Aging using weighted correlation analysis to identify data‐driven modules of highly correlated SNPs. A gene ontology enrichment analysis for biological processes was performed separately for each identified module. Enrichment was determined by overrepresentation test. Module SNPs were used to construct polygenic risk scores (PRS). PRS were tested for association with neuropathological diagnosis in an independent sample of autopsy‐confirmed individuals.

Result

We identified 493,591 SNPs commonly genotyped across ALS, FTLD‐TDP, and HS‐Aging GWAS summary statistics, and the top 1% of these were selected for analysis. We identified five modules: three modules associated with a single GWAS phenotype, ALS (M1, containing 1,907 SNPs), FTLD‐TDP (M2, containing 1,727 SNPs), and HS‐Aging (M3, containing 1,031 SNPs), as well as two modules associated with the phenotypic pairs, ALS‐FTLD (M4, 140 SNPs) and FTLD‐HS (M5, containing 129 SNPs). The top 10 overrepresented pathways by fold enrichment that met FDR p<.05 include processes related to nervous system development, including neuron projection and axon guidance, and the regulation of synapse organization and assembly in M1‐ALS and M2‐FTLD‐TDP. Notably, M1‐ALS uniquely includes pathways involved in skeletal muscle satellite cell activation as well as metabolic processes, which have known dysfunction in ALS. Pathways related to neurogenesis were uniquely observed in M3‐HS‐Aging. A PRS was calculated for M1‐ALS and we observed a significantly higher dosage of risk in a neuropathologically‐defined sample of primary ALS (n=131) than primary FTLD‐TDP cases (n=110; d=.27, p=.04).

Conclusion

Examining genotypes revealed modules of both shared and disparate correlated SNPs across phenotypes associated with TDP‐43 proteinopathies which have biologically plausible pathway and neuropathological associations. We suggest that genetic variation across TDP‐43 proteinopathies may contribute to individual‐level presentations of these syndromes.
Cross‐Platform Synaptic Network Analysis of Alzheimer’s Disease Contextualizes Proteomic Targets for Functional Validation
Authors: Herskowitz Jeremy H , Walker Courtney K , Seyfried Nicholas T.
Published: December 2022

Background

Cognitive decline in Alzheimer’s disease (AD) correlates well with the extent of tau pathology and synapse or dendritic spine loss. Thus, studying synaptic processes may aid in the identification of new therapeutic targets that limit cognitive decline. The entorhinal cortex (EC) is an initial site of tau tangle formation, from which tau can propagate to other brain regions through synaptic connections. We developed a pipeline whereby dendritic spine density and morphology as well as synaptic tau measurements from the EC were incorporated into a synaptic proteomic network to identify mechanisms of synaptic pathology in AD patients.

Method

Golgi‐stained dendrites from postmortem human BA28 EC were imaged using high‐resolution brightfield microscopy and digitally reconstructed in 3D for morphometric analysis. Synaptosome fractions were isolated from the same BA28 samples. Levels of synaptosome and insoluble phosphorylated tau were measured by ELISA. Additionally, liquid chromatography coupled with tandem mass spectrometry‐based proteomics was performed on synaptosomes. Weighted Gene Co‐Expression Network Analysis (WGCNA) was used to generate a synaptic network of protein co‐expression modules. Module expression was correlated with dendritic spine measurements and phospho‐tau levels to guide selection of proteins for validation in model systems. Validation experiments were performed in neurons and Neuro‐2a cells, using a CRISPR activation system for target gene upregulation.

Result

Spine density in the EC is reduced in AD, but not in cognitively normal individuals with AD pathology (CAD) cases. AD cases exhibit more synaptosomal pS396 tau than CAD cases. Module expression was correlated with dendritic spine density and morphology. We identified TWF2 as a hub protein of Module 16, which is positively correlated with thin spine length. Twf2 upregulation increased thin spine length in cultured neurons. Module expression was then correlated with phospho‐tau levels. We identified PPP1R7 as a hub protein of Module 24, which is inversely correlated with synaptosomal pS396 tau in human EC.

Conclusion

We demonstrate that incorporating orthogonal cellular and molecular measurements into a proteomic network enables unbiased identification of proteins functionally involved in regulating those traits. Beyond elucidating synaptic processes in AD, this pipeline offers a blueprint to better contextualize omics‐based targets with relevant biological mechanisms.
Hippocampal subregional thinning related to tau pathology in early stages of Alzheimer’s disease
Authors: Berron David , Baumeister Hannah , Diers Kersten , Reuter Martin , Xie Long , Olsson Emil , Andersson Felix , Wisse Laura EM , Strandberg Olof , Smith Ruben , Stomrud Erik , Hansson Oskar
Published: December 2022

Background

Subregions in the medial temporal lobe (MTL) are affected early by Alzheimer’s disease (AD) pathology and subject to grey matter atrophy. Measuring the earliest AD‐related atrophy in the hippocampus is challenging as region‐of‐interest (ROI) analyses of hippocampal subregional volumes collapse across voxels within anatomical subregions. PET imaging studies, however, report accumulation of tau pathology between anatomical subregions in the earliest disease stages (Berron et al., 2021) fitting reports from the neuropathological literature (Lace et al., 2019; Ravikumar et al., 2021). Thus, sensitive in vivo methods of point‐wise structural measures are needed in order to detect the earliest hippocampal thinning in AD along the anterior‐posterior as well as the medial‐lateral hippocampal axis.

Method

Here we analyzed data from 76 amyloid‐beta negative (Ab‐) cognitively normal (CN), 46 Ab+ CN individuals and 25 Ab+ patients with mild cognitive impairment (MCI) from the BioFINDER‐2 study, who underwent 7 Tesla T2‐weighted structural magnetic resonance imaging, tau positron emission tomography imaging (using 18F‐RO‐948) and cognitive assessments. First, we segmented hippocampal subfields and extrahippocampal subregions. Second, we calculated point‐wise hippocampal thickness estimates (Diers et al.) of hippocampal subfields subiculum, cornu ammonis (CA)1, CA2 and CA3 on the level of the hippocampal body. Thirdly, we extracted local tau‐PET SUVR from Area 35 (A35), entorhinal cortex and amygdala. Finally, we assessed relationships between hippocampal local thickness and tau accumulation as well as cognitive performance.

Result

Our analyses revealed earliest hippocampal thinning associated with tau accumulation in an area spanning the boundary of subiculum and CA1 at the level of the anterior hippocampal body. Ab+ MCI patients showed more posterior thinning in comparison to Ab‐ CU participants. Median thickness in an ROI comprising vertices with A35 tau‐related thinning (A35‐TauThinning‐ROI) was significantly lower in MCI Ab+ and tended to be lower in CU Ab+ compared to CU Ab‐. Higher median thickness in the hippocampal A35‐TauThinning‐ROI, but not whole CA1 nor subiculum thickness, was associated with better 10‐Word‐Delayed‐Recall and higher PACC scores.

Conclusion

Our results suggest that tau‐related thinning of hippocampal subregions can be observed already in early disease stages. Tau‐related point‐wise thickness measures were more sensitive compared to volumetric measures of anatomical subregions.
The Alzheimer’s Cell Atlas (TACA): A single‐cell type transcriptomics and network pathobiology map for target identification and drug repurposing in Alzheimer’s disease and related dementia
Authors: Zhou Yadi , Xu Jielin , Hou Yuan , Bekris Lynn M. , Pieper Andrew A. , Cummings Jeffrey , Leverenz James B. , Cheng Feixiong
Published: December 2022

Background

Recent advances in massive single‐cell/nucleus (sc/sn) transcriptomic data have great potential for identification of cell‐type specific Alzheimer’s disease (AD) pathobiology, as well as target discovery for drug repurposing.

Method

We designed and implemented a multimodal omics analytic framework for the processing of sc/sn transcriptomic datasets, analyses of gene expression, pathobiology, cell‐cell communications with results presentation, interpretation, and translation. We performed an exhaustive search of cell type‐specific gene/protein network modules and cell‐cell interaction networks using our recently compiled ligand‐receptor and the human protein‐protein interactome networks. Furthermore, we developed a web portal with comprehensive visualization tools, such as cell and gene expression viewers, volcano plot and protein‐protein interaction network for differentially expressed genes (DEGs), ligand‐receptor interaction network for cell‐cell interactions, and heatmap for drug perturbation profiles cell type‐specific DEGs.

Result

We created The Alzheimer’s Cell Atlas (TACA, available at https://taca.lerner.ccf.org). In this endeavor, we compiled an AD brain cell atlas consisting of more than one million cells/nuclei from 20 datasets, covering major brain regions (cortex, hippocampus, cerebellum, etc.) and cell types (astrocytes, microglia, neurons, oligodendrocytes, etc.). We also conducted over 1,000 DE comparisons of these datasets to reveal cell‐type specific gene expression alterations. Major comparison types are (i) case vs healthy control; (ii) sex‐specific differential expression, (iii) genotype‐driven DE (i.e., APOE4/4 vs. APOE3/3; TREM2 R47H vs. common variants) analysis; and (iv) others. In addition, each comparison was followed by human protein‐protein interactome network module analysis, pathway enrichment analysis, and gene‐set enrichment analysis. For drug screening, we conducted gene set enrichment analysis for all comparisons with over 700,000 drug perturbation profiles connecting more than 12,000 human genes and 13,000 drugs/compounds. A total of over 300 analyses of cell‐cell interactions against 6,000 experimentally validated ligand‐receptor interactions were also conducted. We then generated summaries for the genes (for target identification) and drugs (for drug repurposing) from all analyses in sex‐specific and cell type‐specific manners.

Conclusion

We envision that TACA will be a highly valuable resource for both basic and translational research in AD, as it provides abundant information for AD pathobiology and actionable systems biology tools for therapeutic discovery.
Histopathologic Brain Age Estimation via Context‐aware Attention‐based Deep Multiple Instance Learning
Authors: Marx Gabriel A.
Published: December 2022

Background

While a large list of age‐related changes have been described in the human brain, the extent to which they represent the result of common pathological reactions versus signatures of underlying brain aging remains unclear. One approach to sorting out the relative importance of the myriad of changes is deep learning, which has emerged as a powerful tool for image analysis and computer vision. However, large digitized whole slide image datasets from human aging brains have not been previously available.

Method

In this study, we leveraged a large novel collection of uniformly processed digitized human post‐mortem brain tissue sections to create a histological brain age estimation model. We further investigated the effect of cognitive impairment and exogenous stress on the model. This was accomplished by developing a context‐aware attention‐based deep multiple instance learning model on 702 human brain tissues sections (age range 50‐110 yr) from the hippocampus stained with Luxol Fast Blue counterstained with hematoxylin and eosin (LH&E) on a brain age estimation task.

Result

Our model estimated brain age within a mean absolute error of 6.2 years. Learned attention weights corresponded to neuroanatomical regions known to be vulnerable to age‐related change. We found that deviations from our estimated histopathologic brain age significantly correlated with the clinical marker of cognitive status (p=0.042). In addition, we found evidence of significantly accelerated age (p=1.12x10‐23) in a cohort of subjects with a neuropathological diagnosis of chronic traumatic encephalopathy (CTE), a neurodegenerative disease caused by mild yet repetitive traumatic brain injury, that displays features that overlap with aging.

Conclusion

These data indicate that estimated histopathologic age can be used as a reliable pathologic correlate to identify factors that contribute to accelerated or decelerated brain aging.
Alzheimer’s Disease‐Related Polygenic Risk Score Profiles and Brain Proteinopathies
Authors: Katsumata Yuriko , Abner Erin L , Kryscio Richard J , Schmitt Frederick A , Fardo David W. , Nelson Peter T
Published: December 2022

Background

Genome‐wide association studies (GWAS) have identified more than 70 genetic loci significantly associated with Alzheimer’s disease (AD). AD‐associated genetic variants have been mapped to biological pathways including endocytosis, oxidative stress, immune response, synaptic plasticity, lipid metabolic, apoptotic process, and amyloid‐beta formation. These diverse biological pathways may be differentially responsible for brain pathologies and combinations of proteinopathies. Pathway‐specific polygenic risk scores (PRSs) are useful to estimate an individual’s genetic liability according to well‐characterized biologic pathways. In this study, we investigated differences in AD‐PRSs calculated by biological pathways in different brain proteinopathies.

Method

Participant data comprised autopsied volunteers from the National Alzheimer’s Coordinating Center (NACC) database linked to Alzheimer’s Disease Genetics Consortium (ADGC) genotype data. We obtained Gene Ontology (GO) terms listed for Homo sapiens and mapped genes to each of the GO terms. Of 18,826 GO terms, 7,300 biological processes were extracted among those constructed of 3 or more genes. We also obtained AD‐related GWAS summary statistics from Kunkle et al. (2019; PMID 30820047). We then extracted single nucleotide polymorphisms (SNPs) with p<0.5 that were not located near the APOE loci. We examined the associations between biological pathway‐specific PRSs and proteinopathies using the Kruskal Wallis non‐parametric test.

Result

ADGC genotype data were available for 1,610 NACC participants. There were 4,866 biological processes that had GWAS summary statistics from at least five SNPs. The distributions of “negative regulation of amyloid‐beta formation” PRSs were significantly different between A scores (Thal phase ratings for Aβ distribution: A0 = Phase 0, A1 = Phase 1 or 2, A2 = Phase 3, and A3 = Phase 4 or 5). The top three biological processes for B score (Braak NFT stage: B0 = Stage 0, B1 = Stage I or II, B2 = Stage III or IV, and B3 = Stage V or VI) were “cell differentiation”, “signal transduction”, and “protein transport”. There was no significant biological pathway associated with TDP‐43 or Lewy body pathologies.

Conclusion

Distinct brain proteinopatholies are likely caused by disruption of unique, albeit correlated, biological pathways. Further studies that integrate genetic information with PRSs may elucidate the mechanisms underlying brain proteinopathies.
Impaired glucose tolerance in Mild Cognitive Impairment is associated with lower brain amyloid on PET
Authors: Lockhart Samuel N. , Rundle Melissa M. , Okonmah‐Obazee Stephanie E. , Sai Kiran K. Solingapuram , Whitlow Christopher T. , Williams Benjamin J. , Bateman James R. , Hughes Tim M. , Craft Suzanne
Published: December 2022

Background

Among community‐dwelling older adults with mild cognitive impairment (MCI), there exists little knowledge regarding how metabolic function impacts brain amyloid pathology (measured using PET) and cognitive status.

Method

This study explored, in participants diagnosed with MCI enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core, markers of baseline metabolic risk (Oral Glucose Tolerance Testing of blood glucose 120‐minute post challenge; OGTT‐2h), amyloid deposition by global PiB PET SUVr and disease subtype (MCI with and without amnestic symptoms) at a subsequent visit, as well as genetic (APOE‐ε4 carrier status) and demographic variables (age, sex, education). Consensus diagnosis of MCI was adjudicated by a panel of experts close in time to PET. OGTT‐2h>140 mg/dL indicates impaired glucose tolerance (IGT).

Result

59 MCI participants underwent OGTT at initial visit (39 normoglycemic, 20 IGT), and amyloid PET at a later visit (mean delay=362days). N=55 also had APOE genotype determined. PiB SUVR was not statistically different (p=.15) between MCI‐NG (1.51) and MCI‐IGT (1.33). However, in models controlling for age, sex, years education, and time between OGTT and PET, glycemic status was significantly associated (p=.007) with amyloid, such that MCI‐IGT had lower SUVR. APOE‐ε4 status did not attenuate this effect (glycemic status p=.011). A similar significant association was present for continuous OGTT‐2h values before (p=.006) and after (p=.02) controlling for APOE‐ε4 status, with higher OGTT‐2h associated with lower SUVR. Scatterplots of the negative association between OGTT‐2h and PiB SUVR are presented in Figure 1 (before [a] and after stratifying by APOE‐ε4 status [b]). Associations between glycemic status and PiB SUVR were similar when restricting to participants with amnestic symptoms (i.e., MCI‐A or MCI‐MDA; n=52), before (p=.008) and after controlling for APOE‐ε4 status (p=.012). In none of these analyses was an interaction term of APOE‐ε4 status and the glycemic variable significant (p’s>.23).

Conclusion

Among community‐dwelling participants with MCI, elevated OGTT‐2h and IGT are associated with lower PiB SUVR. Participants with IGT, at the same level of cognition (MCI), have lower brain amyloid. In these MCI‐IGT participants, factors other than amyloid may be driving MCI status.
CSF biomarkers for Alzheimer Disease are associated with spatial cognition in cognitively normal older adults
Authors: Coughlan Gillian T , DeSouza Brennan , Zhukovsky Peter , Hornberger Michael , Grady Cheryl , Buckley Rachel F.
Published: December 2022

Background

Spatial cognition has emerged as a promising cognitive fingerprint for the detection of Alzheimer’s disease (AD). Despite evidence that spatial cognition is highly sensitive to AD dementia and is apparent even in adults at‐genetic‐risk of AD, the association between spatial cognition and AD biomarkers in cognitively normal adults is unknown.

Method

This study leverages data from the European Prevention of Alzheimer’s Dementia Consortium, a multinational observational study of clinically normal adults initiated in 2016 that includes two digital spatial paradigms: The Supermarket Task (SMT)and the Four Mountains Task (4MT;Fig1). Using a mixed model approach with random intercepts, we investigated cross‐sectional associations between cerebrospinal fluid (CSF) β‐amyloid1‐42 (Aβ1‐42) and phosphorylated tau (p‐tau181) with task performance (N = 1672; mean age = 68.08[SD = 6.96]).

Result

Five hundred and forty‐nine (32.8%) participants had abnormal levels of CSF Aβ1‐42 and p‐tau181. Across the whole sample, higher p‐tau181 concentrations were associated with greater spatial disorientation from the starting location on the SMT (r = ‐0.449, p = <0.001). There was a small association with CSF Aβ1‐42(r = 1.984, p = 0.003; Fig2A‐B). Higher levels of CSF p‐tau181 were associated with more 4MT feature memory errors (r = ‐0.570, p<0.001). There was also a main effect of Aβ1‐42 on 4MT performance (r = 0.301, p = <0.001; Fig2C‐D). Entorhinal cortex and hippocampal volumes both predicted better performance on both tasks (r’s = 0.37‐0.57; Fig3). Post hoc analyses revealed a significant interaction between sex and hippocampal volume, indicating that the association between hippocampal volume and recall of environmental features was stronger in males than females. Finally, volume of the entorhinal cortex, but not the hippocampus, mediated the relationship between p‐tau181 and performance on both spatial tasks (Fig4).

Conclusion

Our results suggest that spatial tasks are sensitive to CSF p‐tau181 and to a lesser extent Aβ1‐42 in preclinical AD. Given the well‐validated digital platform that these tasks are founded on, these tools provide access to racially and ethnically diverse individuals for preclinical AD trial registries via unsupervised assessment.