bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal trajectories in clinical progression of Alzheimer’s disease tau positron emission tomography subtypes
Authors: Rauchmann Boris‐Stephan , Ersoezlue Ersin , Luedecke Dorothea , Perneczky Robert
Published: December 2022

Background

Recent evidence suggests substantial heterogeneity in Alzheimer's disease (AD). Distinct subtypes have been identified using tau pet positron emissions tomography. There is only limited knowledge about the longitudinal cognitive and clinical trajectories of these subtypes.

Method

Three hundred and twenty‐one participants were included with 155 amyloid‐β (Aβ) negative and cognitively normal healthy controls (HC, 74 years, 85 female) and 166 Aβ positive patients with mild cognitive impairment or AD dementia (Alzheimer’s disease spectrum, ADS, 75 years, 76 female). We identified distinct subtypes using an unbiased, data‐driven and similarity‐based Louvain clustering algorithm, modified using a consensus method. Longitudinal trajectories in cognitive domain scores and clinical severity were compared between tau subtypes using mixed effect models.

Result

Four distinct tau PET imaging subtypes were identified, including a posterior, a limbic, a medio‐temoral lobe (MTL) sparing and a temporal subtype (Figure 1). In longitudinal analyses, the subtypes differed substantially in disease progression in the different cognitive domains, i.e. episodic memory, executive functioning, language and visual memory. The temporal subtype showed the steepest decline in visual memory and language, the medial temporal lobe sparing subtype showed only minor language degradation and the limbic subtype showed relatively preserved executive functioning but decline in all other cognitive domains. The MTLs was by far worst affected by clinical progression. The remaining subtypes showed only slight deterioration in clinical severity (Figure 2).

Conclusion

Our results suggest characteristic differences in longitudinal cognitive and clinical trajectories of the tau PET imaging subtypes. Analyzing the heterogeneity in AD using tau PET spatial distribution patterns, significantly improves our understanding of the biological underpinnings of individual differences in clinical presentation and progression. An in‐depth understanding of the subtype’s characteristics in the longitudinal trajectories contributes significantly to improved prevention strategies and individualized precision treatments.
Novel Wnt modulators for the treatment of Alzheimer’s disease
Authors: Li Yonghe , Caulfield Thomas R. , Macyczko Jesse R , Wang Na , Jia Lin , Shue Francis , Lu Wenyan , Zhao Jing , Martens Yuka A , Liu Chia‐Chen , Bu Guojun
Published: December 2022

Background

Alzheimer’s disease (AD) is the most common form of age‐related dementia characterized by the presence of amyloid‐β (Aβ) and tau pathologies leading to neurodegeneration and cognitive impairment. Wnt/β‐catenin signaling modulates multiple pathophysiological processes including synaptic plasticity, neuronal survival, neuroinflammation, Aβ production and tau phosphorylation, but this signaling pathway is greatly inhibited in the AD brain. Notably, two SNPs and an alternative splice variant of Wnt co‐receptor LRP6, which result in down‐regulation of Wnt/β‐catenin signaling, are associated with increased risk of developing AD. In addition, apoE4, the strongest risk factor of late‐onset AD, interacts with and decreases cell surface abundance of LRP6 in astrocytes. Studies from our laboratory have demonstrated that the level of LRP6 is significantly downregulated in human AD brains, and that deficiency in LRP6‐mediated Wnt/β‐catenin signaling leads to synaptic abnormalities and amyloid pathology in amyloid model mice. Therefore, LRP6 is an attractive therapeutic target for restoring Wnt/β‐catenin signaling in the AD brain.

Method

In our previous studies, we have discovered niclosamide, an FDA‐approved anthelminthic drug, inhibits Wnt/β‐catenin signaling via promoting LRP6 degradation. Herein, we demonstrated that CI‐994, an analog of niclosamide, exhibits opposite effects on LRP6 level and Wnt/β‐catenin signaling. Following structural optimization, we have generated a series of novel potent Wnt modulators.

Result

The leading compound W2A‐16 displays a good pharmacokinetic profile with high oral bioavailability and brain penetration. Importantly, W2A‐16 significantly activates Wnt/β‐catenin signaling and inhibits tau phosphorylation in AD patient‐specific iPSC‐derived cerebral organoids. Moreover, W2A‐16 attenuates amyloid pathology and gliosis and improves cognitive function in 5xFAD amyloid model mice. Further, W2A‐16 suppresses tau phosphorylation and neuroinflammation, attenuates body weight loss, and improves the survival of PS19 tauopathy mice.

Conclusion

Together, these findings demonstrate that W2A‐16 is a strong drug candidate for AD therapy.
Unique brain iron profiles associated with logopenic progressive aphasia and posterior cortical atrophy
Authors: Singh Neha Atulkumar , Arani Arvin , Graff‐Radford Jonathan , Senjem Matthew L. , Martin Peter R , Schwarz Christopher G. , Shu Yunhong , Cogswell Petrice M , Knopman David S. , Petersen Ronald C. , Lowe Val J. , Jack Clifford R. , Josephs Keith A , Whitwell Jennifer L
Published: December 2022

Background

Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating the local tissue magnetic susceptibility of every voxel. Dysregulation of neuronal iron has been correlated with typical Alzheimer’s disease (tAD), but little is known about iron distribution in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA).

Method

Eleven PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five‐echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions‐of‐interest across the brain using the Mayo Clinic Adult Lifespan Template. Hierarchical models were fit per‐region and per‐hemisphere to compare PCA and LPA to each other, to 20 healthy controls, and to 20 patients with tAD recruited by the Alzheimer’s Disease Research Center.

Result

Strong evidence (posterior probability>0.99) was observed for greater susceptibility in the left middle occipital gyrus and amygdala in both LPA and PCA, and in the right precuneus and inferior temporal gyrus in PCA compared to controls. Moderate evidence for greater susceptibility (posterior probability>0.90) was also observed in the left insula, inferior occipital gyrus, entorhinal cortex, and right inferior parietal gyrus and amygdala in both LPA and PCA, along with right angular gyrus and middle occipital gyrus in PCA and right insula and caudate in LPA, when compared to controls. Comparing between phenotypes, LPA showed moderate evidence for greater susceptibility in the caudate, hippocampus, substantia nigra, left supramarginal gyrus and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right precuneus compared to LPA. Both LPA and PCA showed moderate‐strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions.

Conclusion

Unique iron profiles were identified in LPA and PCA within cortical and subcortical structures. These changes are in line with disease‐related neurodegenerative changes in the clinical phenotypes, suggesting that QSM could be an informative marker to study iron deposition in these patients.
MRI‐guided Clustering of Alzheimer’s Disease patients: A post‐hoc analysis of Phase 3 Trial of Solanezumab for Mild Dementia Due to Alzheimer’s Disease
Authors: Petersen Kellen K. , Lipton Richard B. , Grober Ellen , Nallapu Bhargav Teja , Ezzati Ali
Published: December 2022

Background

Alzheimer’s disease (AD) is a phenotypically and pathologically heterogenous disorder. We used MRI in amyloid positive patients enrolled in the placebo arm of the Phase 3 Trial of solanezumab for mild dementia due to AD (EXPEDITION3) to identify more homogeneous subgroups based on variation in volumetrics.

Methods

We implemented the self‐organizing map algorithm on baseline volumetric MRI measures from nine brain regions of interest (ROIs) to cluster 1041 individuals enrolled in the placebo arm of the EXPEDITION3 trial. Volumetric MRI differences were compared among clusters. Demographics as well as baseline and longitudinal cognitive performance metrics were used to evaluate cluster characteristics.

Results

Three distinct clusters, with an overall silhouette coefficient of 0.383, were identified based on MRI volumetrics. Cluster 1 (N=400) had the largest baseline volumetric measures across all ROIs and the best cognitive performance at baseline (Table 1). Cluster 2 (N=269) had larger hippocampal and medial temporal lobe volumes, but smaller parietal lobe volumes in comparison with the third cluster (N=372) (Figure 1). Spider plots show the normalized test performance at baseline and follow‐up with larger values corresponding to worse test performance; Cluster 1 shows relatively little cognitive change (Figure 2). Spider plots of regional MRI volumes show smaller volumes for Clusters 2 and 3 relative to Cluster 1 and asymmetries that reflect regional differences in atrophy (Figure 2). The mean change from baseline to week 80 in the ADAS‐cog14 score for Clusters 1, 2, and 3 were 4.28 (SE=0.35), 10.14 (SE=0.51), and 7.90 (SE=0.43), respectively. Significant between‐group mean differences were observed between Clusters 1 and 2 (difference, 2.38; 95% CI, 1.85 to 2.91; P<0.001), Clusters 1 and 3 (difference, 1.93; 95% CI, 1.41 to 2.44; P<0.001), but not between Clusters 2 and 3 (difference, 0.45; 95% CI, ‐0.11 to 1.02; P=0.146) in ADAS‐cog14 (Figure 3).

Conclusions

Volumetric MRI can be used to identify homogenous clusters of amyloid positive individuals with mild dementia. The groups identified differ in baseline and longitudinal characteristics. Cluster 1 shows little ADAS‐cog14 change over the first 40 weeks of study on placebo treatment and may be unsuitable for identifying early benefits of treatment.
In Vivo Head‐To‐Head Comparison of [18F]GTP1 and [18F]PI2620 in Alzheimer’s Disease
Authors: Bohorquez Sandra Sanabria , Constantinescu Cristian , Manser Paul T , Gunn Roger N , Russell David S , Tonietto Matteo , Bullich Santiago , Stephens Andrew W , Mueller Andre , Klein Gregory , Teng Edmond , Pickthorn Karen
Published: December 2022

Background

Several radiotracers targeting tau pathology in Alzheimer’s disease (AD) are being used in human studies. Although abundant imaging characterization data exist for individual tracers there are only sparse in vivo data directly comparing tracers in head‐to‐head studies. As the use of tau PET increases, it is of paramount importance to enable multi‐tracer, multi‐center, multi‐national observational and therapeutic trials. We present the direct in vivo comparison of [18F]GTP1 and [18F]PI2620.

Methods

To date, 21 subjects (70±6 years; 12F) have completed imaging with both [18F]GTP1 and [18F]PI2620: 10 prodromal, 9 mild, one moderate AD subjects (Aβ+), and one Aβ‐ cognitively unimpaired subject. Thirty minutes images were acquired 60 and 45 min after [18F]GTP1 and [18F]PI2620 administration, respectively. SUVR was calculated using the inferior cerebellum and used to compare tau‐specific binding and off‐target signal characteristics between the two tracers. The choroid plexus was defined manually for each subject. The whole cortical gray (WCG) and cerebellum rims were defined using the gray and white‐matter SPM tissue segmentation images (Figure 1).

Results

Tracer distribution was similar for both tracers (Figures 2 and 3). Hammer atlas cortical SUVRs were linearly correlated (r2=0.88). Higher cortical [18F]PI2620 SUVR were observed in some subjects and regions (Figure 3). A lower SUVR correlation was observed in subcortical regions (r2=0.57). Regional comparisons are shown in Figure 4.

Conclusions

The tau pathology distribution was similar for both tracers although each tracer presents a distinct off‐target signal pattern. These preliminary results support the development of categorical and standardized quantification scales for using both tracers in future studies and bridging existing data sets.

Figure 1. Delineation of cortex and cerebellum rims. The combined gray and white matter SPM segmentations were binarized and the ventricles and internal CSF spaces filled to create a mask.

Figure 2. [18F]GTP1 and [18F]PI2620 SUVR images.

Figure 3. [18F]GTP1 and [18F]PI2620 SUVR in WCG and in vivo Braak regions.

Figure 4: [18F]GTP1 and [18F]PI2620 SUVR correlation in target cortical regions, and off‐target signal in choroid plexus (CP), WCG and cerebellum (CBL) rims, and subcortical structures (CAU: caudate; PUT: putamen; PAL: pallidum; THA: thalamus; NAc: nucleus accumbens; SN: substantia nigra) and centrum semiovale (WM).
Bio‐Hermes: A Validation Study to Assess a Meaningful Relationship Between Blood and Digital Biomarkers with Aβ PET Scans for Alzheimer’s Disease
Authors: Beauregard Douglas W. , Mohs Richard , Dwyer John , Hollingshead Sarah , Smith Katy , Bork Jason , Kerwin Diana R.
Published: December 2022

Background

The Global Alzheimer’s Platform Foundation® (GAP) has developed a biomarker study (Bio‐Hermes) that will compare results of blood and digital biomarker tests with the results of brain amyloid PET scans and traditional cognitive tests. The trial will enroll 1,000 participants across three cohorts: Healthy, MCI, and Mild AD. In addition, Bio‐Hermes has a discrete recruiting endpoint that requires enrollment of a minimum of 200 participants (20%) from traditionally underrepresented populations (Black/African American & Latino). Bio‐Hermes will generate a unique, well‐characterized, diverse sample set that will explore the utility of several leading biomarkers. This study will contribute to reducing the time and variability of therapeutic clinical trials in Alzheimer’s disease. Bio‐Hermes will generate a first of its kind, “head‐to‐head” comparison of a broad set of AD biomarkers.

Method

1. GAP activated 13 sites based on high productivity, access to a large AD population, commitment to recruiting traditionally underrepresented populations, and proof of COVID‐appropriate processes and SOPs.

2. 3 cohorts established:

• Cohort 1 – Healthy

• Cohort 2 – MCI verified

• Cohort 3 – Mild AD verified

3. Sites collect Aß 42/40, p‐Tau 181/217/231, NfL blood biomarkers, full gene sequencing, including APOE status, traditional cognitive tests, family history, medications, retinal scan, digital cognitive tests, and centrally read Aß PET scans.

4. Novel and focused recruitment efforts deployed to prioritize diverse representation.

Result

As of 1/27/2022:

1. 6% of enrollment goal achieved (686 out of 1,000)

• Cohort 1: 371 enrolled out of 400, (21% Aß Positive)

• Cohort 2: 244 enrolled out of 300, (34% Aß Positive)

• Cohort 3: 71 enrolled out of 300, (55% Aß Positive)

2. 19% from traditionally underrepresented populations

3. Screen fail rate of 15.9%

4. 208 participants enrolled in the Retispec Sub‐Study

Conclusion

Bio‐Hermes provides a well‐characterized, highly useful dataset including one of the most diversified populations in an AD study, illustrating that traditionally underrepresented populations can be successfully recruited. This study facilitates the discovery of potential biomarkers when compared to Aß PET and validates their predictive value for assessment/screening purposes. Bio‐Hermes is establishing a subset of potential participants for downstream AD therapeutic trials that will significantly lower screen fail rates.
Visualization of synaptic vesicle protein 2A in a rodent model of familial Alzheimer’s disease with a metabolically stable PET probe
Authors: Zheng Chao , Chen Baosheng , Toyonaga Takuya , Liu Michael , Nicholson LaShae , Deluca Kristin , Strittmatter Stephen M , Carson Richard E. , Huang Yiyun , Cai Zhengxin
Published: December 2022

Background

Synaptic loss is one of the hallmarks of Alzheimer’s disease (AD) and region‐specific changes in synaptic density is associated with a variety of neuropsychiatric diseases. Here, we investigated the expression levels of synaptic vesicle glycoprotein 2A (SV2A) in APP/PS1 and age‐matched wild‐type (WT) mice using [18F]SDM16, a novel, metabolically stable SV2A PET imaging probe.

Methods

The SV2A tracer [18F]SDM‐16 was synthesized according to previously published procedure [1]. PET scans with [18F]SDM‐16 were performed on a Focus‐220 scanner in APP/PS1 transgenic mice and WT controls. Regions of interest (ROIs) were extracted from the Ma‐Benveniste‐Mirrione mouse brain atlas and regional time‐activity curves (TACs) were obtained by applying template ROIs to the averaged PET images from 0‐90 min post‐injection (p.i.). Distribution volume ratio (DVR) values were generated using the simplified reference tissue model (SRTM), with brain stem as the reference region. Averaged SUV ratios (SUVRs) from 60‐90 min were calculated by using brain stem as reference region. Spatially normalized SUVR(BS) were assessed on a voxel‐by‐voxel basis in Matlab R2018 with Statistical Parametric Mapping.

Results

The mouse brain PET images showed ubiquitous uptake of [18F]SDM‐16. Regional TACs showed high brain uptake in the selected brain regions of mice (SUV up to 2.38), with a steady increase after tracer injection, before plateauing at 60‐90 min p.i. (Fig. 1a). DVR results correlated well with SUVR(BS) from 60‐90 min (R2 = 0.94, p < 0.0001). Compared with age‐matched WT controls, the averaged SUVR(BS) in the whole brain and hippocampus of APP/PS1 mice showed statistically significant lower values by 5.4% (p = 0.01) and 11% (p = 0.001), respectively (Fig. 1b). These results are consistent with those from previous reports using [11C]UCB‐J (4.0% decrease in hippocampus) and [18F]SynVesT‐1 (7.5% decrease in hippocampus) [2, 3]. Voxel‐based parametric analysis also showed a global decrease in tracer uptake in the APP/PS1 mice, with the most significant decrease in the hippocampus, which is consistent with the results from ROI‐based analysis.

Conclusions

We demonstrated that the radioligand [18F]SDM‐16 had high uptake in mouse brain, and APP/PS1 mice showed lower tracer uptake than WT mice, supporting the use of [18F]SDM‐16 in preclinical AD drug discovery and development.
APOE2 is associated with amyloid independent effects on tau PET signal in preclinical AD
Authors: Young Christina B , Kennedy Gabriel , Sperling Reisa A. , Buckley Rachel F. , Insel Philip S. , Greicius Michael D , Poston Kathleen L , Mormino Elizabeth C.
Published: December 2022

Background

Although APOE is strongly associated with risk of amyloid‐positivity during the preclinical stage of AD, less is known regarding independent effects on regional tau PET burden.

Method

We examined 385 Amyloid‐positive (A+) clinically unimpaired (CU) individuals that had APOE genotype available and additionally underwent amyloid (florbetapir) and tau (flortaucipir) PET imaging as part of the A4‐LEARN study (Table 1A, mean age=72.1±4.8). PET data were processed locally using FreeSurfer defined regions to quantify regional tau and combined to form a large cortical target composite for amyloid. Multiple regression was used to examine associations between APOE genotype (number of e2 and number of e4 modeled as two predictors) with global amyloid, regional tau (entorhinal, amygdala, and inferior temporal).

Result

Among the A+ group, each APOE2 allele was associated with a decrease of 0.045 SUVR while each APOE4 allele was associated with an increase of 0.068 SUVR units of global amyloid compared to the APOE3/3 group (Table 1B). APOE2 was significantly associated with reduced tau across medial temporal lobe ROIs whereas APOE4 was associated with elevated tau in the medial temporal lobe ROIs (Table 1B, Figure 1). Although continuous amyloid levels were associated both with APOE genotype, the total effect of both APOE2 and APOE4 dosage on tau PET was largely independent of continuous amyloid levels (Figure 2).

Conclusion

APOE genotype is related to early medial temporal lobe tau burden, independent of continuous amyloid burden within the A+ range. These findings highlight that APOE genotype influences heterogeneity in tau burden among individuals with preclinical AD.
Plasma amyloid β 42/40 associations on episodic memory: Moderations with depressive symptoms and marital status
Authors: So Mae Yue , Erickson Kelsey , Farias Sarah Tomaszewski , Olichney John M. , Jin Lee‐Way , DeCarli Charles S. , Sapkota Shraddha
Published: December 2022

Background

Plasma amyloid β (aβ) 42/40 is a non‐invasive and cost‐effective biomarker associated with aβ accumulation and cognitive performance in normal aging and Alzheimer’s disease. Recent studies have linked plasma aβ 42/40 to well established modifiable risk factors for dementia. Specifically, depressive symptoms (DS) and marital status have been associated with steeper cognitive decline and increased dementia onset. We examine whether the association between plasma aβ 42/40 and episodic memory (EM) is moderated by (1) DS, (2) marital status, and (3) additive risk of DS+ marital status.

Method

We used an ethnically and clinically diverse longitudinal cohort of older adults (n=473, mean baseline age=74.81(7.22) years, 60.5% women) from University of California, Davis‐Alzheimer’s Disease Research Center (Table 1). Statistical analyses included latent growth modeling to establish a latent EM growth model, and regression analyses to test independent associations and moderations with DS (measured with Geriatric Depression Scale; low<5/ high≥5), marital status (married/not married), and combined DS+marital status risk (low: low DS+married/intermediate: high DS+married or low DS+not married/high: high DS+not married). Age was centered at 75 years. Sex and education were included as covariates.

Result

Lower aβ42/40 was associated with lower EM performance and steeper decline (level: β=6.195, SE=3.065, p=0.041, slope: β=0.284, SE=0.134, p=0.034). DS and marital status independently moderated this association. Specifically, lower aβ42/40 was associated with (1) poorer EM performance in the high DS groups (n=80; level: β=8.914, SE=4.353, p=0.014) and (2) poorer EM performance and steeper decline in the married group (n=115; level: β=11.157, SE=4.477, p=0.013, slope: β=0.524, SE=0.219, p=0.017). The effects of these independent associations were magnified with combined DS + marital status. Specifically, lower aβ42/40 was associated with poorer EM performance and steeper decline in the low (n=62; level: β=15.445, SE=5.650, p=0.006, slope: β=0.642, SE=0.305, p=0.035) risk group but this association was absent in the intermediate (n=171) and high (n=56) groups.

Conclusion

The impact of amyloidosis, as measured by plasma aβ42/40 on cognition, may be more prominent in married older adults with low DS. Examining multimodal associations of non‐invasive plasma biomarkers with modifiable risk factors may identify older adults with high cognitive decline and dementia risk profiles.
THE GLUTAMATERGIC SYSTEM IN ALZHEIMER’S DISEASE: A SYSTEMATIC REVIEW WITH META‐ANALYSIS
Authors: Soares Carolina , das Ros Lucas U. , da Rocha Andreia Silva , Machado Luiza Santos , Bellaver Bruna , Zimmer Eduardo R.
Published: December 2022

Background

Glutamate is the most important excitatory neurotransmitter in the human brain, and the regulation of its homeostasis is of utmost importance for brain proper functioning. At the synapse level, glutamate binds to ionotropic (NMDAR, AMPAR and KAR) and metabotropic receptors (8 isoforms, mGluR1 to mGluR8). Also located at the glutamatergic synapse are the vesicular transporters (vGLUT), a synaptic marker, and glutamate transporters (GLT1), which are responsible for glutamate re‐uptake. Increases in the glutamate concentration in the synaptic cleft leads to a phenomenon called excitotoxicity, which causes progressive neuronal death. Nonetheless, glutamate excitotoxicity has been described as a common feature in neurodegenerative disorders, including Alzheimer’s Disease (AD). Multiple studies reported alterations in the glutamatergic system in the AD brain. Thus, considering the large number of publications, we sought to perform a systematic review with meta‐analysis to assess whether the glutamatergic system is consistently altered in AD patients.

Method

PubMed and Web of Science databases were searched for articles that evaluated glutamatergic system components in AD. Pooled effect sizes were determined with standardized mean differences using the Hedge G method with random effects.

Result

The search initially retrieved 6000 articles. Following exclusion criteria, 59 articles were included in this study. We found that regions typically affected with AD pathology presented reduced NMDAR subunit NR1 (p = 0.017, z = 2.38, i2 = 71.3%) (Figure 1), NR2A (p = 0.001, z = 3.38, i2 = 0%) (Figure 2), NR2B (p < 0.0001, z = 3.86, i2 = 0%) (Figure 3), AMPAR subunits GluA2/3 (p = 0.018, z = 2.36, i2 = 84.5%) (Figure 4). Conversely, we did not observe significant differences in the level of GLT1, vGLUT1, vGLUT2, AMPAR subunit GluA1 and mGluRs in postmortem brain tissue. Further analyses are in process to assess other glutamatergic components, as well sensitivity analysis considering risk of bias for each study.

Conclusion

In conclusion, the early results of this meta‐analysis suggest that changes in the glutamatergic system in AD are not generalized, but specifically related to ionotropic receptors.
Lower white matter hyperintensity is associated with lower mild behavioral impairment severity among pre‐dementia people with higher education attainment
Authors: Soo See Ann , Ng Kok Pin , Kumar Dilip , Saffari Seyed Ehsan , Kandiah Nagaendran
Published: December 2022

Background

Mild behavioral impairment (MBI) describes the emergence of neurobehavioral symptoms in later life as harbingers of neurodegeneration. Emerging evidence suggests that white matter hyperintensity (WMH), a known risk factor for cognitive impairment, is associated with MBI. Furthermore, education level which reflects cognitive reserve, influences the risk of dementia. However, the role of education levels on the relationship between WMH and MBI is unknown. Here, we aim to evaluate the effects of education levels on WMH and MBI among a pre‐dementia cohort from a memory clinic in Singapore.

Method

In this retrospective cross‐sectional study, 210 pre‐dementia participants (mean age 64.31, mean MMSE 27.77, mean education level 12.60, 37.6% males), underwent cognitive assessment, Magnetic Resonance Imaging (MRI) and completed the MBI‐checklist (MBI‐C) self‐report in National Neuroscience Institute Singapore from 2017 to 2021. Multiple linear regression models evaluated the main effects of WMH total ratings and years of education on MBI, while moderation analysis evaluated the effects of years of education with WMH on MBI. All analyses were controlled for age and sex.

Result

While education levels and WMH were not associated with MBI‐C total scores independently (p>0.05), we found that education levels moderated the effects of WMH on MBI‐C total score (β=0.269 , p=0.038). Specifically, higher education attainment is associated with lower MBI‐C total scores among individuals with lower burden of WMH; while higher MBI‐C total score is observed with higher education among people with high WMH burden (Figure 1).

Conclusion

Higher education attainment is associated with a lower risk of MBI when the WMH load is lower. Our findings support interventions to reduce WMH load in pre‐dementia people with higher education attainment to reduce MBI severity.
Davos Alzheimer’s Collaborative: Building a globally representative cohort through a technologically‐enabled approach
Authors: Au Rhoda , Joung Philip , Ho Jor Sam , Albastaki Omar , Thompson Louisa I , Low Spencer , Philippakis Anthony , Levey Allan I.
Published: December 2022

Background

In January 2021, the Davos Alzheimer’s Collaborative (DAC) was launched to develop precision solutions to reduce barriers to AD research for globally underrepresented populations, including older adults from any ethnic/racial group and/or the lowest resource settings. To meet this DAC vision, the Global Cohort Development (GCD) program has been establishing collaborations with existing cohort studies around the world to collect new digital cognitive and behavioral phenotypic data and harmonize digital data with existing cohort data. DAC is also creating open‐source data processing and advanced analytic tools, and building the infrastructure necessary to make these data broadly, but securely accessible to the scientific community.

Methods

Fifteen cohorts from 13 countries have joined GCD, representing 25,000+ individuals. Each cohort is deploying a protocol using a tablet to document AD‐related cognitive and behavioral symptoms across the disease continuum, as well as a smartphone for remote detection and continuous monitoring of incident changes in these symptoms.

Results

We will discuss the approach for launching a digital protocol across cohorts from multiple countries, where the participant mix varies in technology access and use, language, culture and education, and extensiveness of existing research infrastructure.

Conclusions

Global population level research requires a significant paradigm shift in traditional methodology including study design, assessment practices, data accessibility infrastructure and analytic approaches. Achieving global reach that works regardless of available resources and expertise will require major realignment for AD research to be representative of everyone, and clinical assessment and care relevant and equitable to anyone.
Building the Research Path for Identifying and Validating Cognition‐related Digital Biomarkers
Authors: Huang Li‐Kai , Kuan Yi‐Chun , Yang Cheng Chang , Kuo Po Chih , Hu Chaur‐Jong
Published: December 2022

Background

Cognitive dysfunction is a core feature of dementia spectrum disorders but simple screening tests are less sensitive to detect the deficits, especially in the very early stage of disease course using most standardized test instruments. This results in delayed discovery of disease onset and opportunity for early interventions that might be more effective in delaying or arresting progression. Digital phenotyping using a combination or hardware and software solutions provide potentially much more effective tools for helping clinicians identify subtle signs of cognition deficits and track them in a compressed timeline to confirm the accuracy of decreasing slope indicative of a neurodegenerative etiology.

Methods

Beginning in 2017, 1,866 participants were recruited from the Dementia Center, Shuang Ho Hospital, New Taipei City, Taiwan and will be invited to use a smartphone application to collect digital phenotypes including information processing speed, response accuracy, error detection, and multitasking capacity and vocal patterns, such as speech pitch, tone, rhythm. Additionally, four groups of 100 new participants each will be recruited; cognitive unimpaired (CU), subjective cognitive decline (SCD), mild cognitive impairment (MCI) and mild dementia. In addition to the smartphone applications, these 400 participants will undergo additional testing that include the cognitive abilities screening instrument (CASI), Clinical Dementia Rating (CDR), Cookie Theft Picture Description, Eye Tracking Test, and gait/balance.

Results

Digital phenotyping profiles will be constructed for the cohort and validated against the smaller sample to determine those metrics that can serve as actual digital biomarkers. For the smaller sample, additional multi‐dimensional profiles will be constructed that add gait parameters (step length, stride length, step width, foot angle) and eye‐tracking (visual fixation changes, speed, duration) and determine to what extent they increase differential diagnostic accuracy.

Conclusions

Digital assessment tools can be used for detecting changes in cognitively related behaviors associated with preclinical and early stage clinical dementia. Future research is needed to confirm the efficacy of these digital phenotypes to serve as digital biomarkers that have high prognostic and diagnostic accuracy.
The impact of hypertension on longitudinal cognitive decline in cognitively unimpaired individuals
Authors: Da Ros Lucas Uglione , Ferrari‐Souza João Pedro , Hauschild Lucas Augusto , Brum Wagner Scheeren , Bellaver Bruna , Leffa Douglas Teixeira , Ferreira Pamela C.L. , Bieger Andrei , De Bastiani Marco Antônio , Pascoal Tharick A , Zimmer Eduardo R.
Published: December 2022

Background

Mid‐life hypertension (HTN) is considered a risk factor for the development of clinical Alzheimer´s Disease (AD). Yet, it is not known whether late‐life hypertension relates to AD´s pathophysiology, with current literature being contradictory. We recently demonstrated that a vascular risk factor composite, which includes HTN, interact with the AD pathophysiology to promote cognitive decline. Here, we aimed to assess whether late‐life HTN alone and AD biomarkers interact to promote longitudinal cognitive decline, and if controlling the blood pressure affects this relationship.

Method

We evaluated 503 cognitively unimpaired (CU) individuals from the ADNI cohort, with available baseline medical data and cerebrospinal fluid (CSF) Elecsys biomarkers (Aβ1‐42 and p‐tau181), as well as longitudinal clinical assessments with neuropsychological testing (up to 6 years). Individuals with both Aβ1‐42 and p‐tau181 positivity were defined as having preclinical AD ((AT)+), and individuals with previous diagnosis of HTN or those taking anti‐hypertensive medication were considered HTN+. These participants were further divided based on two different measures of systolic blood pressure, being classified as controlled (C) if at least one of them was inferior to 140 mmHg, or non‐controlled (NC) if both measures were over 140 mmHg. The modified version of Preclinical Alzheimer’s Cognitive Composite (mPACC) was used as the outcome to evaluate the cognitive trajectory.

Result

Linear mixed‐effects (LME) models showed that HTN interacted with the AD pathophysiology to promote longitudinal cognitive decline (HTN X AD pathophysiology X Time, β= ‐0.45, p= 0.014), and when the individuals with HTN were further stratified between C and NC, we could see that this effect was seen only in the NC group (HTN+C X AD pathophysiology X Time, β= ‐0.29, p=0.13; Group HTN+NC X AD pathophysiology X Time, β= ‐0.79, p=0.002).

Conclusion

We observed that in CU individuals, HTN acted as a risk factor for cognitive decline in (AT)+ patients. Additionally, HTN + NC had an increased risk compared with HTN + C individuals. Thus late‐life HTN is a risk factor for the emerging of cognitive symptoms among the elderly and controlling the blood pressure may reduce this risk.
Combining high‐resolution ex vivo MRI and histopathology to identify medial temporal lobe atrophy patterns specific to tau pathology in Alzheimer’s Disease
Authors: Ravikumar Sadhana , Denning Amanda , Lim Sydney A , Chung Eunice , Ittyerah Ranjit , Wisse Laura EM , Xie Long , Das Sandhitsu R. , Robinson John , Schuck Theresa , Grossman Murray , Lee Eddie B , Tisdall Dylan M , Mizsei Gabor , Artacho‐Perula Emilio , Martin Maria Mercedes Iniguez de Onzono , Jimenez Mar Arroyo , Munoz Monica , Romero Francisco Javier Molina , Rabal Pilar Marcos , Sanchez Sandra Cebada , Gonzalez Jose Carlos Delgado , Prieto Rosa , Parada Marta Corcoles , Irwin David J. , Trojanowski John Q , Wolk David A. , Insausti Ricardo , Yushkevich Paul A.
Published: December 2022

Background

Tau pathology in the medial temporal lobe (MTL) is closely linked to neurodegeneration, and is an early pathological change associated with Alzheimer’s disease (AD). MRI measures of MTL neurodegeneration have proven to be sensitive to change during preclinical AD. Current measures are confounded by the presence of non‐AD pathologies (e.g., TDP‐43, ageing). Here, we combine ex vivo imaging with histopathological ratings of tau and TDP‐43 to identify fine‐grained MTL atrophy patterns specific to tau. Such an analysis could be used to define MTL “hotspots” where in vivo measures of neurodegeneration are expected to be strongly associated with tau, potentially enabling the development of biomarkers that are more effective during early AD clinical trials.

Method

Ex vivo MRI scans (0.2x0.2x0.2mm3, 9.4T) of human MTL specimens were combined using a customized registration approach to construct a 3D atlas. Using serial histology available in a subset of specimens (n = 11), MTL subregions in the atlas were labelled based on cytoarchitecture (Ravikumar et al., 2021) (Figure 1A). To perform thickness analysis, 29 specimens containing a primary diagnosis of AD or primary age‐related tauopathy were registered to the atlas (13 specimens were registered to the atlas during atlas construction, and 16 were registered to the atlas after it was constructed) (Figure 1B, Table 1). Using histopathology measures of tau and TDP‐43 pathology (based on contralateral sampling), we investigated the association between tau and thickness by fitting a linear model (with age/TDP‐43 as covariates) at each point along the MTL and SRLM surface.

Result

Pointwise thickness analysis reveals significant atrophy patterns in the transentorhinal region and SRLM. When excluding age from the model, stronger tau associations are observed in the SRLM, entorhinal cortex, and extending further towards Brodmann Area 35 (Figure 2).

Conclusion

Our findings are consistent with early Braak stages but suggest that covarying for age may be obscuring some associations due to tau since age and tau burden have a highly correlated relationship (Figure 3). In future work, quantitative maps of NFT burden will be mapped from serial pathology images into atlas space, allowing us to characterize NFT distribution in 3D (Yushkevich et al., 2021).
Posterior Cortical Atrophy: Primary Occipital Variant
Authors: Shir Dror , Graff‐Radford Jonathan , Machulda Mary M. , Pham Nha Trang Thu , Jack Clifford R. , Lowe Val J. , Whitwell Jennifer L , Josephs Keith A
Published: December 2022

Background

Posterior Cortical Atrophy (PCA) is one of the atypical Alzheimer’s Disease (AD) variants, characterized by predominant visuospatial and visuoperceptual deficits, with dorsal and ventral subtypes recognized clinically and radiographically. A third primary occipital (caudal) variant has been suggested. The objective of this study was to determine its demographics, clinical manifestations, and biomarker findings.

Method

Fifty‐two PCA patients with positive amyloid PET scans were investigated. Patients underwent neuropsychological assessment, 3T MRI imaging and FDG‐, amyloid‐ and tau‐PET scans. Regional FDG‐PET values were normalized to the pons and represented as z‐scores relative to a control population. Patients were divided into “primary occipital” and “other PCA” subgroups according to FDG‐PET defined criteria, with primary occipital defined as patients in which the z‐scores for occipital subregions were at least one standard deviation lower (i.e., more abnormal) than the z scores in all other brain regions. Global amyloid‐PET, temporoparietal FDG‐PET and temporal tau‐PET regions‐of‐interest (ROI) were calculated. Student’s T test and Fisher’s exact analyses were used to investigate differences in demographics, clinical findings, and imaging biomarkers across the two groups.

Result

Nine patients were classified as primary occipital; primary occipital patients were older (64.8±6.9 versus 59.3±6.8, p=0.034) and had more years of education (17.7±1.7 versus 15.1±2.6, p=0.007) compared to the other PCA patients. Clinical evaluation revealed worse performance for the primary occipital group on the Ishihara test for color perception (p<0.001), while the other PCA patients performed worse on the Western Aphasia Battery (WAB) praxis scale (p=0.005). Overall neuropsychiatric symptom burden as defined by the NPI‐Q was lower in the primary occipital group (p<0.001). The FDG‐PET meta‐ROI (weighted median uptake in angular gyrus, posterior cingulate, and inferior temporal ROIs, normalized to the pons and vermis) was higher in the primary occipital subtype (p=0.006), but no differences were observed in amyloid and tau‐PET.

Conclusion

Clinical and biomarker findings suggest primary occipital PCA is characterized by an older age at onset, more color perception dysfunction, less severe ideomotor apraxia and less hypometabolism in temporal‐parietal meta‐ROI compared to more established phenotypes.
Genetic Risk Score for Alzheimer’s Disease Predicts Brain Volume Differences in Mid‐ and Late‐life in UK Biobank Participants
Authors: Buto Peter , Swinnerton Kaitlin N. , La Joie Renaud , Zimmerman Scott C , Glymour M. Maria , Ackley Sarah F , Brenowitz Willa D
Published: December 2022

Background

Genetic risk variants for late‐onset Alzheimer’s disease (LOAD) predict brain atrophy, cognitive changes, and dementia onset in late‐life. Little is known about the association between LOAD genetic variants and regional brain volumes in middle aged adults. Further understanding of when associations emerge across mid‐to‐late‐life may point to the earliest manifestations of LOAD.

Method

We studied 41,435 UK Biobank participants aged 45‐80 who enrolled 2007‐2010, had no dementia at baseline, and subsequently underwent a brain MRI (3‐Tesla scanner). A genetic risk score for LOAD (LOAD‐GRS) was calculated as a weighted sum of 27 variants previously confirmed to be genome‐wide significant predictors of LOAD dementia including APOE. MR images underwent standardized quality control and data processing by UK Biobank. Volumes (both hemispheres combined) for 38 regions of interest (ROIs) were derived from Freesurfer (Version 6.0) packages for subcortical segmentation and cortical parcellation with the Desikan‐Killiany‐Tourville atlas. We examined associations of LOAD‐GRS with each ROI tested whether effects differed across age using linear regression with an interaction between age and LOAD‐GRS. A cross‐validated model determined the earliest age at which trends in MRI volume diverged between those with low compared to high LOAD‐GRS. All models adjusted for sex, genetic ancestry, and intracranial volume.

Result

Using a Bonferonni correction (p<0.05/38=0.0013]), 4 of 38 regional volumes had significant interactions between age and LOAD‐GRS, all indicating that for people with 1 SD higher genetic risk of LOAD, older age was more strongly associated with smaller brain volumes than among people with lower LOAD genetic risk. Significant regions included the amygdala (‐172.6 mm3/SD; 95%CI=‐176.7,‐168.5); hippocampus (‐351.9 mm3/SD; 95%CI=[‐359.9,‐343.9], nucleus accumbens (‐87.7 mm3/SD; 95%CI=‐89.4,‐86.0], and thalamus (‐526.4 mm3/SD; 95%CI=[‐538.2,‐514.6]. Best fitting model‐based age‐curves for people with high versus low LOAD‐GRS scores began to diverge around age 45 for the nucleus accumbens, hippocampus, and thalamus and after age 51 for the amygdala.

Conclusion

Genetic factors that increase risk of LOAD begin to predict lower brain volumes as early as middle age, decades prior to average age of dementia onset. Our findings prioritize particular brain regions that may help predict LOAD onset, including the hippocampus, amygdala, nucleus accumbens, and thalamus.
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 , Minguillon 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 p‐Tau 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.