bluuebunny/crossref_metadata_2025 huggingface dataset:
Soluble TREM2 drives earliest amyloid‐related p‐tau increase in Alzheimer’s disease but attenuates neurodegeneration in advanced disease
Authors: Biel Davina , Ewers Michael , Suárez‐Calvet Marc , Hager Paul , Rubinski Anna , Dewenter Anna , Steward Anna , Roemer Sebastian Niclas , Haass Christian , Brendel Matthias , Franzmeier Nicolai
Published: December 2022

Background

Alzheimer’s disease (AD) is characterized by Aβ and tau accumulation, microglial activation, metabolic brain changes, neurodegeneration, and cognitive decline. Studies found both detrimental and protective effects of microglial activation on AD progression, hence neuroinflammation may be a double‐edged sword in AD, which is critical for clinical trials aiming to modulate microglial activation. Here, we used CSF sTREM2 as a proxy of microglial activation to investigate disease stage‐dependent drivers of microglial activation in AD and its associations with the development of tau, metabolic brain changes, and neurodegeneration.

Methods

We included 271 ADNI participants, including cognitively normal (n=71) and mild cognitively impaired (n=200) participants with available CSF Aβ1‐42, p‐tau181, sTREM2, as well as amyloid‐PET and FDG‐PET. To determine disease stage, we stratified patients into Aβ CSF+/PET‐ (early Aβ‐accumulators, n=70) and Aβ CSF+/PET+ (late Aβ‐accumulators, n=201). A subset of 21/75 early/late Aβ‐accumulators had available longitudinal p‐tau181 and sTREM2 assessments, based on which we calculated annual sTREM2 and p‐tau181 change rates. Using linear models and mediation analyses we tested disease stage‐specific associations between amyloid‐PET (centiloid), p‐tau181 and sTREM2, and between sTREM2 and metabolic brain changes (FDG‐PET) or neurodegeneration (grey matter volume), controlling for age, sex, education, and diagnosis.

Results

We found that higher centiloid was associated with cross‐sectional and longitudinal increases in p‐tau181 and sTREM2 in early Aβ‐accumulators, while in late Aβ‐accumulators, only a cross‐sectional association between centiloid and p‐tau181 was observed (Fig.1A+B). In early Aβ‐accumulators, sTREM2 fully mediated the association between centiloid and p‐tau181 (55% mediation) as well as longitudinal p‐tau181 increase (71% mediation) (Fig.1C+D). Higher sTREM2 was associated with higher FDG‐PET in early Aβ‐accumulators but with lower FDG‐PET in late Aβ‐accumulators (Fig.2A+B), in line with our previous findings that activated microglia consume glucose. In exploratory analyses, sTREM2 attenuated effects of higher p‐tau181 on hippocampal atrophy in late Aβ‐accumulators (n=155, T=2.215, p=0.031).

Conclusion

Earliest Aβ accumulation is associated with elevated sTREM2‐related microglial activation ensuing increases in p‐tau181 and glucose metabolism, whereas higher microglial activation in late Aβ‐accumulators attenuates hippocampal atrophy. Our findings have clinical implications as they suggest that targeting enhancement of microglial activation may have opposing effects on disease progression, depending on disease stage.
On the origin of a potential clearance marker: The contribution of enlarged perivascular fluid diffusion to an MRI derived proxy of interstitial fluid
Authors: van der Thiel Merel M. , Roos Nathalie A. , Drenthen Gerhard S. , Voorter Paulien H.M. , Feiweier Thorsten , Ramakers Inez H.G.B. , Backes Walter H. , Jansen Jacobus F.A.
Published: December 2022

Background

IntraVoxel Incoherent Motion (IVIM) MRI can detect the diffusion of cerebral interstitial fluid (ISF) (D
int) and its volume fraction (f
int), which has the potential as a proxy of cerebral waste clearance. fint has been suggested to both be driven by fluid diffusivity within enlarged perivascular spaces (ePVS) ‐ transporting fluid from the subarachnoid space into the parenchyma ‐ and the ISF between the parenchymal cells. Both factors play a crucial role in soluble protein clearance, e.g., Amyloid‐Beta (Aβ).

This study simultaneously aims to verify the contribution of ePVS fluid diffusivity to fint and highlights the ability to specifically assess ePVS fluid diffusion in the cerebrum using a non‐invasive MR method.

Method

Twenty neurotypical elderly subjects (Table 1) underwent ultra‐high field MRI (7T research system, Siemens Healthcare GmbH, Erlangen, Germany) (Table 2).

The intermediate diffusion components (Dint) in the range 1.5*10‐3< Diffusivity<4.0*10‐3 mm2/s were calculated using spectral analysis (Fig.1). The relative signal contribution of Dint was quantified by fint.

ePVS were segmented from the enhanced perivascular contrast images (Fig.2). Median fint values were extracted from ePVS and non‐ePVS voxels within the basal ganglia (BG).

fint and Dint values from within the ePVS mask were compared with values from surrounding non‐ePVS voxels in the BG using Wilcoxon Signed Ranks Tests.

Result

Figure 3 contains a graphic summary of the statistical comparison of Dint and fint values from the ePVS and non‐ePVS voxels in the BG. Higher Dint and fint values are observed in the ePVS compared to the non‐ePVS tissue.

Conclusion

The current study identified a higher IVIM‐derived proxy of ISF within the ePVS compared to surrounding non‐ePVS tissue, confirming that ePVS indeed contribute to the waste clearance marker fint.

ePVS are fluid‐filled spaces surrounding cerebral blood vessels, in which ISF diffusivity is less restricted. This explains the higher Dint values in ePVS compared to non‐ePVS.

Furthermore, this study suggests a potential method to investigate diffusivity within the microscopic ePVS, independent of the ISF diffusivity between parenchymal cells. In patients with Alzheimer’s disease, this method could be applied to investigate alterations in ISF diffusivity which could be representative of potential Aβ blockages in ePVS.
A new approach for estimating and quantifying disease‐modification in Alzheimer’s disease clinical trials
Authors: Raket Lars Lau
Published: December 2022

Background

The standard methodology for estimating treatment effects in Alzheimer’s disease clinical trials has remained unchanged for decades. With an increasing focus on disease‐modifying treatments, there are opportunities for developing more powerful methods for detecting such types of treatment effects and quantifying them in more interpretable ways.

Methods

The Progression Model for Repeated Measures (PMRM) was developed as an alternative to the Mixed Model for Repeated Measures (MMRM). The assumptions and flexibility of the PMRM are like the MMRM except treatment effects are handled differently (Figure 1). The PMRM estimates treatment effects as time‐delays/slowing of progression relative to the control group while the MMRM estimates treatment effects as point differences/reduction in decline on the outcome scale at a given visit. Because the unit of the treatment effect is shared with the time variable, PMRMs can simultaneously handle multiple outcomes in a natural and efficient manner. The power and interpretability of the PMRM was compared to the MMRM and other methods in a range of scenarios based on simulated and historical clinical trial data.

Results

The PMRM was found to produce accurate and interpretable estimates of treatment effects across a range of simulated scenarios. Using CDR‐SB as an outcome, the PMRM produced the overall highest power to detect treatment effects across all simulated scenarios compared to all studied approaches. When treatment effects were simulated as time delays or slowing of progression, the PMRM offered substantial power gains compared to the MMRM. Using CDR‐SB, ADAS‐cog and ADCS‐ADL as multivariate outcomes, the PMRM was found to outperform models that combined the information in the outcome using the global test statistic and iADRS.

Conclusion

The PMRM offers advantages in terms of interpretation and meaningful quantification of treatment effects, also in situations where the average decline observed in the control group is small. PMRMs can seamlessly include multiple outcome measures to estimate a single treatment effect and it was found that PMRMs offered substantially increased power to detect slowing of disease progression compared to conventional methods using both single and multiple outcome measures.
A predictive coding framework of allostatic interoceptive overload to comprehend frontotemporal dementia
Authors: Migeot Joaquín , Signorelli Camilo Miguel , Duran‐Aniotz Claudia , Piguet Olivier , Ibáñez Agustin
Published: December 2022

Background

Recent allostatic‐interoceptive predictive coding theories propose that efficient regulation of the internal milieu is necessary to correctly anticipate the needs required to overcome environmental challenges before they arise. These theories are based on neurocognitive models of allostatic load and interoceptive processes, dimensions convergently affected in behavioral variant frontotemporal dementia. Nevertheless, this neurodegenerative disease has not been previously framed within such framework.

Method

We propose the hypothesis that behavioral variant frontotemporal dementia may be characterized by an imbalance of the predictive allostatic‐interoceptive system, with manifestations across psychological, cerebral, cardiocerebral and peripheral dimensions. Further, we propose a set of theory‐driven predictions in behavioral variant frontotemporal dementia, which could be subsumed into a dimensional framework integrating neurocognitive and physiological markers into a multimodal assessment of allostatic interoceptive priors.

Result

Under such framework, cognitive and behavioral impairments of behavioral variant frontotemporal dementia would be predicted by structural and connectivity deficits among critical allostatic interoceptive brain’ hubs, altered electrophysiological activity, and allostatic overload, jointly yielding meaningful associations with clinical manifestations.

Conclusion

Such framework could help to further understand the hallmarks behavioral and physiopathological dysregulations of behavioral variant frontotemporal dementia within a predictive coding account, strengthening clinical models integrating its neurological and psychiatric manifestations.
Heterogeneity in normal aging: longitudinal trajectories of grey matter
Authors: Lorenzon Giulia , Poulakis Konstantinos , Mohanty Rosaleena , Kivipelto Miia , Eriksdotter Maria , Ferreira Daniel , Westman Eric
Published: December 2022

Background

In dementia research, the role of aging is usually de‐trended as a confounder, implying implicit assumptions on the nature of controls. In fact, normal aging brings about structural and functional damage, possibly reflecting brain resistance and resilience, unrelated to overt cognitive impairment (1). The aim of this exploratory study is to predict longitudinal trajectories of brain change in healthy elderly, based on their heterogeneous patterns at baseline, to uncover potentially lost information and link brain, cognitive and biological profiles. To our knowledge, it´s the first study investigating this in healthy aging.

Method

Cortical volumes and subcortical thickness were assessed through MRI from 307 healthy elderly from ADNI, JADNI and AIBL initiatives. We applied cross‐sectional clustering using unsupervised random forest (2), followed by multivariate mixture of generalized mixed effect model (3) to predict individual trajectories and group them based on similarities. The longitudinal clustering was replicated in the separate cohorts for validity check.

Result

4 different clusters were identified, which statistically differ for musculoskeletal comorbidities. Cluster 1 shows the healthiest brain and cognitive profile at the age of 60, but it deteriorates the most across time. Conversely, cluster 3 presents the worst grey and white matter profiles at 60, and the greatest cognitive decline over time. However, showing only minimal brain change, cluster 3 resembles brain resistance, whereas cluster 1 seems compatible with cognitive resilience.

Conclusion

These different trajectories suggest the possibility of identifying resilient and resistant individuals already from healthy aging. Clinically, this promotes environmental protective factors and early diagnosis. Methodologically, this warns on the heterogeneity of healthy “controls” in experimental designs.
Pilot Randomized‐Controlled Trial of Social Ballroom Dancing in Dementia‐At‐Risk Older Adults
Authors: Blumen Helena M , Ayers Emmeline , Wang Cuiling , Ambrose Ann F , Jayakody Shanika Oshadi , Verghese Joe
Published: December 2022

Background

Executive functions (EF) such as planning, problem‐solving, and organization are often impaired in Alzheimer’s disease (AD). This pilot trial examined the safety and efficacy of social ballroom dancing for improving EF in older adults at increased risk for AD and related dementias. We hypothesized that the added social and cognitive demands of ballroom dancing would lead to greater intervention‐related changes in EF than a traditional aerobic activity (treadmill‐walking) – because it furthers neuroplasticity.

Method

A single‐blind pilot randomized controlled trial (clinicaltrials.gov: NCT03475316) contrasted 6‐months (90 minutes twice a week) of social ballroom dancing with 6 months (90 minutes twice a week) of treadmill walking in dementia‐at‐risk older adults. Dementia‐at‐risk was defined as a memory impairment screen score of ≥3 and ≤6, and/or an AD‐8 dementia screening interview score of ≥1. A composite EF score generated from digit‐symbol substitution (DSST), flanker interference, and walking‐while‐talking tasks was the primary outcome. Functional neuroplasticity during fMRI‐adapted versions of these EF tests were secondary outcomes. The intention‐to‐treat principle was applied to all linear‐mixed effects analyses.

Result

Twenty‐five participants were randomized between June 2019 and March 2020. The mean age was 76.45 years. 66% were women, 48% White/Caucasian, 24% Black/African‐American and 20% Hispanic/Latino. Sixteen participants (8 in each study arm) completed the intervention prior to study termination due to COVID‐19. The most common (mild) adverse event was falls (social dancing = 4; treadmill walking = 1), but no falls occurred during intervention sessions. No serious study‐related adverse events were reported. No between‐group differences were observed on the composite EF measure – although social dancing generated greater improvements on DSST than treadmill walking (6.57 correct items more; SE = 2.77, 95% CI = .46; 12.67, p = .02. No between‐group differences were observed in functional activation/deactivation patterns during EF tasks. Hippocampal volume, however, showed less atrophy following social dancing arm than treadmill walking (SE = 109.42; 95% CI = 58.29; 487.22, p = .01).

Conclusion

Social ballroom dancing is a safe intervention for dementia‐at‐risk older adults. This clinical trial provides preliminary evidence that social dancing improves performance on one test of EF (DSST), and promotes hippocampal neuroplasticity – but these findings need to be confirmed in larger clinical trials.
Composite SUVR: a new method for boosting Alzheimer’s disease monitoring and diagnostic performance, applied to tau PET
Authors: Saguer Isaac Llorente , Busche Marc A , Oxtoby Neil P
Published: December 2022

Background

Abnormal brain tau protein accumulation is strongly linked to multiple neurodegenerative disorders. Currently, brain tau pathology is quantified in vivo using tau PET by calculating the Standardized Uptake Value Ratio (SUVR) of target and reference regions of interest (ROIs).

Recent work (Schwarz et al., 2021) in Alzheimer’s Disease (AD) explored various target and reference ROIs to report performance of SUVR as a biomarker for diagnosis, disease monitoring, and clinical trial efficacy/eligibility (sample size estimate, SSE). Here we introduce a new method and biomarker: Composite SUVR (CUVR).

Methods

We analyzed longitudinal SUV data from ADNI in the available 103 participants having three or more tau PET scans ([18F]AV‐1451): 58 cognitively normal (CN); 21 mild cognitive impairment; 24 probable AD. In the spirit of SUVR and statistical ROIs (Chen, et al., NeuroImage 2010), we calculate CUVR as the SUV ratio of two composite regions. Our novel method is that the composite regions are determined by a genetic algorithm that searches the possible 3^96 combinations of regions from FreeSurfer’s default atlas. We compare performance of SUVR with CUVR.

Performance metrics follow Schwarz et al.: a linear mixed‐effects model quantifies longitudinal group separation by tau accumulation rate (t statistic between fixed effects for CN and AD) and longitudinal precision (model residuals’ standard deviation). CUVR and SUVR values were log‐transformed before model fitting.

We calculated SSE for a hypothetical clinical trial designed for 80% power to reduce tau PET accumulation by 20% (vs. placebo) in non‐CN individuals.

Results

Our method identified a CUVR biomarker involving 60 regions. Figure‐1 shows the vast performance improvement of CUVR versus the best‐performing SUVR (inferior‐temporal target; eroded subcortical white matter reference). Group separation improved by 2.9x (t = 9.57 vs 3.32); longitudinal precision by 6.5x (residual std = 0.331% vs 2.14%); and CUVR required a smaller sample size by 3.9x (83 vs 318).

Conclusions

Our simple data‐driven approach discovered a new tau PET biomarker called CUVR. Experimental results show state‐of‐the‐art longitudinal group separation, longitudinal precision, and clinical trial enrichment. The remarkable performance improvements provide compelling evidence for using CUVR for both eligibility and efficacy in Alzheimer’s disease clinical trials, particularly of anti‐tau therapies.
Accessible and meaningful engagement for people living with dementia when transitioning arts activities online
Authors: Christensen Justin , MacRitchie Jennifer , Timmers Renee
Published: December 2022

Background

With opportunities for self‐expression and enjoyment, creative arts activities can offer many benefits for people living with dementia including improving health and wellbeing. During the COVID‐19 pandemic, arts organizations have had to transition activities previously involving face‐to‐face interactions to remote delivery. Aiming to understand the accommodations that have been made for people living with dementia (PLWD) to access arts activities through technology, we conducted a survey with arts‐workers involved in the remote delivery.

Method

A survey using a mixture of qualitative and quantitative questions was distributed online to arts workers delivering activities remotely for PLWD in the UK during the COVID‐19 pandemic. These included what types of activities were employed, how the activities changed due to remote access (including motivations for access), what tools were used, what technological support there was for access, and how this affected the number of people they were able to reach with these activities.

Results

Twenty‐seven arts workers (mean age = 47 SD = 6.4) delivering music (23 respondents), arts (8), crafts (4), dance (6), drama (3), and word‐based activities (1) responded. The main tools used included: Zoom, YouTube Live, Microsoft Teams, and Facebook Live. Several themes emerged from the thematic analysis of open‐ended responses: i) gaining a sense of community, finding structure and purpose, and combatting against physical isolation were perceived to be major motivations for people living with dementia, ii) creating opportunities for choosing, contributing input, and sharing was important, and iii) changes in access resulted from the shift to remote delivery such as difficulty for PLWD to interact through technology, user setup and maintenance needs, and the possibility for geographic expansion of the remote service.

Conclusions

The findings highlight the diverse, individual needs of people living with dementia in group arts participation, while still prioritizing their motivations for participation including sense of community, structure, purpose, and combatting against feelings of isolation during the pandemic. Particularly successful remote activities gave opportunities for meaningful contribution and had a multitude of possibilities for access for PLWD.
Prodromal FTD ‐ what do we know about it and what do we still have to learn?
Authors: Ducharme Simon
Published: December 2022

Background

Frontotemporal dementia (FTD) is a complex disease that can initially present with subtle symptoms across several domains including behavior, cognitive/language, psychiatric and motor. This heterogenous prodromal phase is preceded by a slowly progressive presymptomatic accumulation of biological changes. With the emergence of new potential therapeutic agents for genetic forms, there is a need for robust clinical characterization and diagnostic definitions of these disease phases.

Method

We performed a systematic literature review on the current state of the science on prodromal FTD and provide expert consensus recommendations on diagnostic definitions.

Result

The preclinical phase should extend from the first signs of protein misfolding to the first FTD symptoms, however we lack molecular biomarkers to characterize this stage, with maybe the exception of C9orf72 expansion cases. In genetic mutation carriers it is uncertain if a ‘no disease’ phase exists, or if there is a neurodevelopmental component. To account for all possible clinical presentations, the definition of the prodromal stage of FTD needs to include the possibility of symptoms emerging with behavioral/psychiatric, cognitive and/or motor features. We subsume these features under the term mild cognitive and/or behavioral and/or motor impairment due to FTD (MCBMI‐FTD). MCBMI‐FTD needs to include psychiatric symptoms outside of typical bvFTD criteria as potential initial prodromal manifestations of FTD in genetic mutation carriers, however this would not be applicable in sporadic cases given the lack of specificity of such symptoms.

Conclusion

Characterizing the preclinical and prodromal stages of FTD is crucial for disease detection and patient stratification for future clinical trials. However, several issues remain including the need to develop molecular biomarkers to better characterize the preclinical phase and more accurate models to predict symptom onset.
Effects of optogenetic locus coeurleus stimulation on functional connectivity in a rat model of Alzheimer’s disease
Authors: Kelberman Michael , Anumba Nmachi , Smith Corrie , Pan Wen Ju , Clavijo Perrin G , Marriott Alexia , Kim Ellen , Keilholz Shella , Weinshenker David
Published: December 2022

Background

Activity of the locus coeruleus (LC) influences behaviors that go awry in prodromal Alzheimer’s disease (AD), and these abnormalities coincide with early accumulation of hyperphosphorylated tau in the LC. LC stimulation changes global functional connectivity, but it is unknown how AD‐like neuropathology affects the LC’s ability to regulate brain state. Therefore, we combined optogenetics and functional magnetic resonance imaging (fMRI) in the TgF344‐AD rats that develop endogenous hyperphosphorylated tau in the LC prior to amyloid or tau pathology in forebrain regions.

Methods

At 2 months of age, TgF344‐AD rats and wild‐type (WT) littermates were infused intra‐LC with a ChR2‐mCherry or an mCherry virus under the noradrenergic‐specific PRSx8 promoter (n=3/group). 2‐4 weeks prior to fMRI, rats were implanted with an optic fiber targeting the LC, and functional stimulation was confirmed using pupillometry. At approximately 6 months, rats underwent fMRI scans with and without 2Hz optogenetic stimulation. During scanning, rats were intubated and subcutaneously given 1.5mg/kg*hr pancuronium while anesthetized with 1.3% isoflurane. fMRI scans were gradient echo EPI (TR=1.25s) and obtained using a 9.4T Bruker Animal MRI scanner. Data were preprocessed using a custom Rodent Whole‐Brain fMRI Data Preprocessing Toolbox. Functional connectivity matrices were generated in MATLAB using Pearson’s linear correlations between parcellated regions of interest (ROI). Histograms were generated in MATLAB by collecting the fisher z‐transformed correlation coefficients across all ROIs for the averages of each group.

Results

Pupillometry confirmed optogenetic activation of the LC in ChR2 animals but not mCherry controls. Similar functional connectivity was observed between Tg and WT animals. We next subtracted baseline fisher z‐transformed correlation coefficients from those during 2Hz stimulation within each genotype to determine whether LC stimulation shifted functional connectivity. Across all groups, effects of 2Hz LC stimulation were negligible.

Conclusions

Tg and WT rats had similar resting‐state functional connectivity at 6 months, and 2Hz LC optogenetic stimulation did not impact functional connectivity. However, functional connectivity deficits progress with age in this strain, and the 2Hz stimulation falls within normal LC pacemaker firing (∼0.5‐2Hz). Therefore, future work will incorporate different stimulation frequency, patterns, and older rats.
Empirical pathological staging and subtyping of TDP‐43 proteinopathies
Authors: Young Alexandra L. , Vogel Jacob W , Robinson John , McMillan Corey T , Ossenkoppele Rik , Wolk David A. , Irwin David J. , Elman Lauren , Grossman Murray , Lee Virginia M‐Y , Lee Eddie B , Trojanowski John Q , Hansson Oskar
Published: December 2022

Background

Pathological aggregation of tar DNA‐binding protein 43 (TDP‐43) in the brain is the primary cause of many cases of frontotemporal lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS) and limbic‐predominant age‐related TDP‐43 encephalopathy (LATE). It is therefore imperative to establish empirical staging systems to characterize and distinguish stereotypical patterns and commonplace deviations of different TDP‐43 proteinopathies.

Method

We use ordinal ratings of TDP‐43 burden from 19 brain regions to perform data‐driven disease progression modeling (SuStaIn) to find the most likely trajectories for FTLD‐TDP (n = 108), ALS (n = 137) and LATE (n = 283) from the CNDR Brain Bank at the University of Pennsylvania. Subtype number was defined using cross‐validated information criterion. Each individual was assigned a subtype and stage. Multivariate OLS models tested differences between subtypes. Stages were compared to age and existing staging schemes. Cross‐validated logistic regression was used for 3‐way classification using SuStaIn information only.

Result

SuStaIn provided data‐driven staging of TDP‐43 proteinopathies complementing previously described human‐defined staging schema, further providing additional detail (Fig1A‐C; Fig3A‐C). SuStaIn also identified two distinct subtypes within FTLD‐TDP and a further two within ALS (Fig1D). FTLD‐TDP subtypes differed in TDP‐43 type and Alzheimer’s disease pathology (Table1); ALS subtypes were differentiated by age (Table 2) and by antemortem clinical characteristics. No subtypes were observed for the LATE group. Progression along data‐driven stages was positively associated with age in LATE individuals, but negatively associated with age in individuals with FTLD‐TDP (Fig2). Using only regional TDP‐43 severity, our data driven model could distinguish individuals diagnosed with ALS, FTD or LATE with a cross‐validated balanced precision of 0.93 and balanced recall of 0.92, and these metrics improved to 0.95 and 0.96 when combined with a logistic regression model (Fig3). Very little stage overlap was found between FTLD‐TDP and LATE, but stages that did overlap showed subtly different patterns (Fig4)

Conclusion

We provide an empirical pathological staging system for ALS, FTLD‐TDP and LATE, which is sufficient for staging and accurate classification. We demonstrate that there is substantial heterogeneity amongst ALS and FTLD‐TDP progression patterns, whilst LATE exhibits a homogeneous progression pattern.
Do Sex Differences Exist in Cognitive Function in Patients with Atrial Fibrillation?
Authors: Wood Kathryn A. , Han Feier , Ko Yi‐An , Wharton Whitney
Published: December 2022

Background

Atrial fibrillation (AF) is a risk factor for mild cognitive impairment (MCI) and dementia. To address sex differences in AF‐related MCI, we examined disease prevalence and progression among adults with and without AF in the National Alzheimer’s Coordinating Center (NACC) cohort.

Method

Data freeze/extraction of NACC data (N = 43,746) took place March 2021. Participants with ≥ 3 annual visits, diagnostic data, and AF status (self‐reported or diagnosed) were included. Diagnostic categories were normal, MCI, and dementia. Multinomial logistic regression and Cox proportional hazard model were used to examine association between AF and baseline cognitive diagnosis and time to progression in cognitive diagnosis, respectively. Covariates included age, sex, race, education, BMI, smoking, depression, hypertension, diabetes, hypercholesterolemia, heart failure, stroke, and sleep apnea. Interactions with sex were examined in all models.

Result

4,593 participants had AF at baseline (46% female, mean age 78.5 years, 81% White, 8% Black, 11% other ethnicities). AF is associated with higher odds of having MCI (OR 3.43 [1.48, 7.91] in females; OR 1.73 [0.81, 3.71] in males) and dementia (OR 3.00 [1.22, 7.38] in females; OR 2.60 [1.16, 5.81] in males) at baseline. Among the 13,683 subjects included in the survival analysis, 4066 (30%) progressed from normal cognition to MCI and 2895 (21%) developed dementia (2434 [18%] AD) with median follow‐up of 4 years. Women with AF had higher risk of disease progression (HR 1.21 [1.04, 1.40]) compared to women without AF, but the association was not significant in men (HR 0.96 [0.83, 1.11]). AF was significantly associated with faster transition from normal cognition to MCI (HR 1.17 [1.03, 1.33]) and from MCI to vascular dementia (HR 2.51 [1.63, 3.85]) but not MCI to AD.

Conclusion

This is the first study to examine sex differences in rate of cognitive change in patients with AF. Women with AF are at higher risk of MCI and dementia with more rapid trajectories to dementia than women without AF or men with or without AF. Identification of those at highest risk of cognitive decline will inform future interventions to prevent or slow AF‐related MCI and AD.
Comparative prevalence of mild cognitive impairment of Alzheimer’s Disease sub‐type in Adult Ugandans living with HIV and demographically matched HIV‐negative controls
Authors: Ezeamama Amara E. , Sikorskii Alla , Boivin Michael , Zalwango Sarah K , Nakasujja Noeline , Rubin Leah H , Giordani Bruno
Published: December 2022

Background

Prevalence rate of mild cognitive impairment (MCI) and Alzheimer’s dementia (AD) in cART treated people living with HIV (PWH) is unknown.

Method

277 PWH and 189 HIV‐negative Ugandan adults matched by age, sex, and residence were neuropsychologically evaluated i. Impairment in seven domains ‐ including immediate recall, memory and learning (delayed recall, recognition) and others, were defined. Cognitive status – i.e., not impaired, asymptomatic impairment (ANI), minor neurocognitive disorder (MND) or HIV‐associated dementia (i.e., HAD, if HIV+), was defined according to Frascatti criteria. Cognitive dysfunction of the AD subtype was defined per Bondi et al. (2014); MCI included moderate (i.e. ≥1 SD worse in ≥2 tests) or pronounced (i.e. >2.0 SD worse in ≥1 tests) cognitive impairments without functional limitation. AD ‐ i.e., ≥1 pronounced impairment in recognition/delayed recall accompanied with functional limitation. Differences in MCI and AD by HIV status and odds ratios with 95% confidence intervals (CI) were calculated stratified by age (<60 vs. ≥60 years).

Result

Among adults cognitively unimpaired (26.1%) or with ANI (27.8%), amnestic MCI rate was 28.9% (60/204) among PWH and 14.7% (21/133) among HIV‐ controls (OR = 2.18, 95%CI:1.25, 3.84). Similarly, among adults with MND/HAD, prevalent AD was 38.7% (29/75) among PWH and 23% (14/61) among HIV‐ controls (OR = 2.11, 95%CI:0.99, 4.50). Among cognitively unimpaired/ANI affected individuals <60 years old, amnestic MCI prevalence was 16.2% for community controls and 30.3% for PWH (OR = 1.9, 95%CI:1.02, 3.60). Among individuals classified as MND or HAD, prevalent AD was 16.3% for HIV‐ controls vs. 38.6% for PWH (OR = 3.23, 95% CI: 1.23, 8.52) . Among adults 60+ years old with ANI/no impairment, prevalent amnestic MCI was 14.7% for community controls and 41.9% for PWH (OR = 4.04, 95%CI:1.23, 13.40) but the prevalence of AD was identical at 38.9% each for HIV+ and for HIV‐ controls 60+ years old with MND/HAD.

Conclusion

Ugandan PWH are at increased risk for being diagnosed with MCI/AD, and they may be diagnosed at a younger age than HIV‐negative Ugandans. These data highlight the importance of MCI/AD screening in PWH and the need to avail PWH with interventions to mitigate MCI/AD risk.
Examining cerebrovascular burden across the cognitive continuum in older adults with and without evidence of amyloidosis
Authors: Rivera‐Rivera Leonardo A , Cody Karly Alex , Betthauser Tobey J , Koscik Rebecca Langhough , Jonaitis Erin M. , Cadman Robert V. , Hermann Bruce P , Rowley Howard A. , Carlsson Cynthia M. , Chin Nathaniel A. , Eisenmenger Laura , Johnson Sterling C. , Johnson Kevin M
Published: December 2022

Background

This work characterized cerebrovascular health in human subjects spanning the cognitive spectrum with and without presence of Aβ using different neuroimaging techniques (Fig1).

Methods

Subjects (n=70) were clinically characterized into four groups: cognitively unimpaired (CU), CU‐Declining (at‐risk of progressing to clinical mild MCI based on traditional neuropsychological data), clinical MCI, and clinical dementia (Fig2). MRI:
Vascular imaging: Whole‐brain 4D‐Flow data were acquired to characterize cerebrovascular health. pCASL with three post labeling delays was used to provide transit time corrected CBF maps. Structural imaging: T1‐weighted and T2‐FLAIR images were also collected for quantification of intracranial, hippocampal and white matter hyperintensity volumes. Hemodynamic measurements were extracted from intracranial arteries including the petrous ICAs, BA, MCAs, and veins SSS. Quantified flow parameters included: total cerebral blood flow, trans‐capillary pulse wave delay, and flow pulsatility index (PI). Trans‐capillary pulse wave delay was defined as the time shift between arterial and venous cardiac waveforms. PET: Aβ burden was assessed using 11C‐PiB PET imaging. Amyloid positivity (A‐, A+) was established as mean cortical PiB DVR >1.16. For A+ participants, amyloid time (i.e., estimated duration A+) was estimated using the sampled iterative local approximation algorithm. Differences were assessed using ANOVA followed by post‐hoc analysis (P<0.05 significance).

Results

Micro‐vascular tissue perfusion was statically higher in A+/CU when compared to other A+ groups in the GM, WM, and hippocampus (Fig3 and 4). Trans‐capillary pulse wave delay was statistically longer in A+/CU when compared to A+/CU‐Declining, A+/MCI, and A+/dementia (Fig5A). For A‐ groups trans‐capillary pulse wave delay was similar; yet, flow PI was statistically higher in A‐/CU‐Declining and A‐/MCI when compared to A‐/CU in the ICAs and MCAs (Fig5 C, D). Flow PI in A+/CU was higher than in A‐/CU.

Conclusions

Decreased micro‐vascular tissue perfusion and shorter trans‐capillary pulse wave delay in A+ subjects with cognitive alterations (e.g. CU‐Declining, MCI, Dementia) compared to A+/CU indicates decreased metabolism and increased small vessel stiffness may contribute to cognitive decline and/or are induced by amyloidosis. In contrast, for A‐ subjects significant differences in arterial flow pulsatility index between A‐/CU, CU‐Declining, and MCI suggests macro‐vascular arterial stiffness contributes to cognitive decline.
Modeling gene expression on the X chromosome in the brain for transcriptome‐wide association studies
Authors: Zhang Xueyi , Guo Shengru , Naj Adam C. , Below Jennifer , Kunkle Brian W. , Dumitrescu Logan , Martin Eden R. , Bush William S.
Published: December 2022

Background

Analysis of sex chromosomes is under‐reported in Alzheimer’s disease (AD) studies. As we gain more knowledge of disease associations and tissue‐specific regulatory effects of autosomal loci, there is a growing interest in building prediction models of gene expression in the brain to model the cumulative functions of non‐coding variants on the sex chromosomes. Transcriptome‐wide Association Studies (TWAS) can identify disease‐associated genes using these prediction models built for specific tissues by integrating genotype, imputed gene expression, and phenotype information. A key challenge of this approach for sex chromosome analysis is how to model copy number differences between males and females: genetic variants on the X chromosome are hemizygous for males, while females are heterozygous or homozygous diploid.

Method

We explore modeling approaches on the X chromosome using WGS and RNA‐seq data in 13 Brain sub‐regions retrieved from the GTEx project, currently restricting analyses to males. We used elastic‐net regression, with a balanced LASSO‐ridge penalty (mixing parameter α=0.5), as recommended by Wheeler et al. 2016. We tuned the penalization parameter λ for each gene in each tissue and assessed the model performance. There are 2392 genes on chromosome X, with only approximately 800 genes expressed in each GTEx brain tissue. SNPs (MAF>0.05) within the gene’s 1M bp flanking window were used to train the model. We used mean squared error to determine the penalization parameter and select the best models.

Result

We built 761 prediction models in 13 Brain sub‐regions on the expression of 503 genes. For example, we fit the prediction model of Gene COL4A6 (ENSG00000197565) in the Cortex, using 89 males. 83 cis‐SNPs were kept in the final model (λ=0.015). The model R2 is 0.20, suggesting that 20% of the variance of expression levels in males can be explained.

Conclusion

These models predict the cis‐regulated gene expression on the X chromosome in males. We can then use these estimated gene expression weights to impute male expression levels to identify (putative) causal genes for AD with TWAS.
Detection of cognitive impairment from eSAGE cognitive data using machine learning
Authors: Kawakami Ryoma A , Scharre Douglas W. , Ning Xia
Published: December 2022

Background

Alzheimer’s disease is a neurodegenerative disease that affects many people worldwide. Many cognitive screening tests are available, with one example being eSAGE – a self‐administered exam (Scharre et al., 2017)1. eSAGE is a valid and reliable cognitive assessment tool to detect mild cognitive impairment or early dementia. It has been implemented as an app in BrainTest®, with sample screenshots in Figure 1. While eSAGE provides diagnostic results of its own, there is a potential to apply machine learning methods to the responses to obtain better diagnostic results.

Method

eSAGE results1 and behavioral data from BrainTest® were obtained for 69 subjects, each with a diagnosis of normal cognition, mild cognitive impairment, or dementia. 84 metrics were extracted, including the time that subjects spent on each test page, and drawing speed and line straightness from the construction test problems (Table 1). The hypothesis was that cognitive impaired subjects would show different behavioral patterns (e.g., spend more time on questions, change answers often) compared to those of normal cognition. Different machine learning methods including logistic regression and gradient boosting are built over the metrics to classify between cognitive impairment and normal cognition.

Result

Logistic regression classifies those with cognitive impairment vs normal cognition with a recall of 100% and ROC of 75.32% and classifies those with MCI vs normal cognition with a recall of 76% and ROC of 79.45% (Table 2). The most important features (those highest weighted metrics used to differentiate the diagnostic classification) for both these classifications were similar (Table 3). Individuals with normal cognition had, on average, longer connected line segments (not lifting their finger off the tablet) when performing the Modified Trails B task (Figure 1). They also spent less time completing their verbal fluency and picture naming tasks (Table 3). See Table 2 and 3 for other findings.

Conclusion

Behavioral features extracted from self‐administered eSAGE with the BrainTest® app are predictive of cognitive impairment diagnosis by logistic regression and gradient boosting. Important features identified suggest executive processing time lengthens as one progresses from normal to impaired cognition.

Reference

1Scharre et al. (2017). Alzheimer’s Research & Therapy, 9, 44.
An examination of the usability of the Mayo Test Drive remote cognitive testing platform in older adults with and without cognitive impairment
Authors: Patel Jay S , Christianson Teresa J. , Karstens Aimee J , Stricker John L , Kremers Walter K. , Jack Clifford R. , Knopman David S. , Mielke Michelle M. , Petersen Ronald C. , Stricker Nikki H.
Published: December 2022

Background

Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based platform for self‐administered assessment for novel (Stricker Learning Span) and open access (Symbols Test) cognitive measures with previously demonstrated validity and reliability. Our study aim was to examine the usability of MTD, defined as the extent to which MTD was used to achieve the desired study goal of completing a testing session among participants willing to engage in an all‐remote study.

Methods

248 Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center participants were invited to participate in this ancillary, uncompensated remote pilot study via email. To examine 1) willingness to participate in a remote cognitive assessment study and 2) usability of MTD, the initiation and completion rates of MTD were examined by cognitively unimpaired (CU; n = 142) and cognitively impaired (CI; n = 106) groups (see Figure 1). These rates and other factors associated with MTD feasibility were further explored across age in CU (i.e., 50‐69, 70‐79, and 80+ years) and specific diagnostic groups in CI (i.e., individuals with dementia, mild cognitive impairment (MCI), and possible MCI).

Results

Session completion rate (usability) was 98% across all participants who chose to participate, and, surprisingly, completion rates did not vary by age or diagnostic groups (p =.69; see Table 1). As expected, more individuals chose to participate in the CU (77%) versus CI (52%) group (p < .001). In terms of feasibility, individuals over 80 and with CI were more likely to have some contact with the study coordinator. Use of smartphones decreased with age, with most CU individuals over 70 using a personal computer (69‐73%; Table 2).

Conclusions

Though the CI group was less likely to choose to participate than the CU group, out of those that did choose to participate the rate of completion was 98%. This demonstrates high usability of MTD. Study coordinator support and a flexible testing platform is critical for facilitating participation in remote testing across the aging population, and more supports and incentives may be needed for individuals with cognitive impairment to improve participation rates.
Fear and avoidance of memory loss is associated with lower levels of psychosocial functioning and quality of life in older adults
Authors: Farina Francesca R. , Pavithra Pavithra , Bennett Marc P , Lenaert Bert , Griffith James W
Published: December 2022

Background

Dementia is one of the most feared diseases associated with aging. Although some level of fear can motivate protective strategies, too much fear can be harmful and maladaptive. We examined fear and avoidance of memory loss and their relationship to psychosocial and lifestyle factors associated with dementia risk in a community‐dwelling sample of older adults.

Method

Participants were 230 adults (112 female) aged 55 years and older (61.3 ± 5.2). Questionnaires were administered to measure fear and avoidance of memory loss, perceived memory failures, depression, sleep disturbance, engagement in social activities and quality of life. We hypothesized that fear and avoidance of memory loss would positively predict perceived memory failures, depressive symptoms and sleep disturbance, and negatively predict social engagement and quality of life.

Result

Fear and avoidance of memory loss did not significantly differ by age or sex. People with a family history of dementia reported higher fear (ps < .02, ds = .4), but not avoidance scores. Fear scores were significantly associated with increased self‐reported memory failures and sleep disturbance, and lower quality of life and social functioning, after adjusting for anxiety and memory performance (βs > .8, ps < .03). Inclusion of avoidance scores improved the predictive power of all models except sleep; avoidance was associated with reduced quality of life and social functioning, and increased memory failures and depression (βs > .9, ps < .03).

Conclusion

Fearful anticipation and avoidance of memory loss is associated with poorer psychosocial functioning and quality of life. Based on these results, we propose a model whereby excessive fear of memory loss motivates withdrawal from social and cognitively demanding activities that can protect against and compensate for dementia risk. Findings have practical implications for psychological and lifestyle interventions, which could allay multiple modifiable risk factor pathways.
Comparing cerebrovascular disease diffusion MRI markers using post‐mortem and longitudinal imaging data
Authors: Raghavan Sheelakumari , Przybelski Scott A. , Kamykowski Michael G. , Reid Robert I. , Lesnick Timothy G. , Murray Melissa E. , Reichard Ross R. , Graff‐Radford Jonathan , Nguyen Aivi T. , Knopman David S. , Mielke Michelle M. , Jack Clifford R. , Petersen Ronald C. , Vemuri Prashanthi
Published: December 2022

Background

Diffusion MRI (dMRI) based quantification of microstructural changes in white matter (WM) are increasingly proposed to measure cerebrovascular disease (CVD) related changes. Our objective was to compare the proposed dMRI markers using postmortem neuropathologic CVD data and then evaluate the predictors of longitudinal dMRI markers using serial scans.

Method

We identified n=51 participants (mean age: 83.8 years, 63% males) with ante‐mortem dMRI and postmortem CVD evaluation and n=718 participants (mean age: 71.1 years, 56% males) with at least two dMRI scans from the population‐based sample of Mayo Clinic Study of Aging. We computed dMRI measures proposed for measuring CVD: Free Water (FW), Fractional Anisotropy (FA) adjusted for FW (FAadj), Peak width Skeletonized Mean Diffusivity (PSMD), and FA of the genu of corpus callosum (Genu‐FA). We used the FW and PSMD (PSMD release 1.8.1) kits from the MarkVCID consortium.

Using weighted linear regression models with adjustments for MRI scan time to death, we evaluated associations between the baseline dMRI and two pathology CVD scores: Strozyk (represents the presence and number of macroscopic lesions) and Kalaria (represents the summary score of vessel wall modifications) scales. We ran linear mixed effect models with all available serial dMRI measures as outcomes and vascular risk (measured by the number of cardiovascular and metabolic conditions‐CMC), baseline imaging measures (amyloid and white matter hyperintensities (WMH)) and their interaction with time as key predictors.

Result

Most dMRI markers were predictors of postmortem CVD pathology (Table 1). In longitudinal dMRI models, terms associated with amyloid explained little variability in dMRI (<1%) (Table 2). WMH was a significant predictor of baseline and decline in dMRI measures with WMH explaining a considerable percentage of variability in FW (34%) and PSMD (28%). Vascular risk measures were significant predictors of three out of the four dMRI measures.

Conclusion

The diffusion measures proposed as surrogate markers of CVD map reasonably well to CVD pathological scales and do not change substantially as a function of baseline amyloidosis. Our findings shed light on variability in the proposed diffusion markers using postmortem data and longitudinal imaging data. Further work is needed to evaluate their clinical utility.