bluuebunny/crossref_metadata_2025 huggingface dataset:
Does socioeconomic status modify the association between glycemic level and MRI markers of ADRD risk in middle‐aged adults?
Authors: Kraal A. Zarina , McFarlane Hugh V. , Pyne Jeffrey D. , Turney Indira C. , Lao Patrick J. , Mazen Jessica , Brickman Adam M. , Manly Jennifer J.
Published: January 2025

Background

High glycemic levels, indexed by hemoglobin A1c (HbA1c), heighten risk for Alzheimer’s Disease and Related Dementias (ADRD). Previous studies suggest that high HbA1c and low socioeconomic status (SES) may be associated with MRI markers of ADRD risk, including lower cortical thickness and greater white matter hyperintensities (WMH). The weathering hypothesis suggests that the stress of low SES accelerates and exacerbates physiological deterioration, leading to worsening health outcomes. However, the role of SES as a potential moderator of the associations between HbA1c and MRI markers of ADRD is underdeveloped. We hypothesized that higher HbA1c and lower SES are associated with MRI markers of ADRD risk, and the association between HbA1c and MRI markers is stronger among individuals with low SES.

Method

Participants were middle‐aged adults in the Offspring Study of Racial and Ethnic Disparities in Alzheimer’s Disease (N = 616; age = 54.5±10.6; 68.6% Latinx, 21.2% Non‐Latinx Black, 7.2% Non‐Latinx White; 65.6% women). HbA1c level was determined from blood assays. MRI markers included cortical thickness of AD signature regions and log‐transformed WMH. Confirmatory factor analysis estimated SES from self‐reported income and education. Structural equation models quantified main and interaction effects of HbA1c and SES on MRI markers, adjusting for age, sex, and prediabetes/type 2 diabetes.

Result

There were no main or interaction effects of HbA1c and SES on either MRI marker, independent of covariates. However, examination of moderation by each SES indicator showed that higher HbA1c was associated with lower cortical thickness among participants with high income (unstandardized estimate = ‐0.0214, SE = 0.0107, 95%CI[‐0.0424, ‐0.0003]). Effect estimates were similar in analyses restricted to individuals with prediabetes and type 2 diabetes (n = 250; age = 58.1±9.0; 72.8% Latinx, 23.6% Non‐Latinx Black, 3.7% Non‐Latinx White; 68.8% women).

Conclusion

HbA1c‐related effects on markers of ADRD risk in middle‐age may occur via neurodegenerative processes. Associations involving cerebrovascular pathways warrant further investigation. Examination of other indicators of SES (e.g., occupation, wealth, debts) and region‐specific WMH may help clarify the role of SES in modifying the link between glycemic level and brain health.
Genetic predisposition to AD and inflammation determine vulnerable brain regions to air pollution
Authors: Vilor‐Tejedor Natalia , Genius Patricia , Rodríguez‐Fernández Blanca , Anastasi Federica , Cirach Marta , Nieuwenhuijsen Mark , Minguillón Carolina , Esteller Manel , Navarro Arcadi , Gispert Juan Domingo
Published: January 2025

Background

The detrimental effects of air pollution on health are well‐documented, yet its impact on brain structure in the early asymptomatic stages of Alzheimer’s disease (AD) remains under‐explored. This study investigated the relationship between air pollution and brain imaging features, focusing on the moderating role of genetic factors associated with AD and inflammation.

Methods

A total of 1,153 individuals from the ALFA cohort, many within the Alzheimer’s continuum, with available genotyping, air pollution estimation and magnetic resonance imaging were included (62.6% women, average age 55,6 years). Land use regression models were used to estimate individual levels of air pollution, including nitrogen oxide (NO2) and particulate matter (PM2.5, PM10), at the participants’ residential addresses. Functional genetic scores, including plasma pQTLs for inflammatory markers (PRS‐CCL2, PRS‐IL6, PRS‐CCL19), CSF pQTLs for AD pathology (PRS‐Aß42, PRS‐ptau), genetic predisposition to clinical AD (PRS‐AD), and APOE‐e4 carriership, were assessed. General linear models, corrected for age at MRI visit, sex and years of education, were computed to assess the main effects of air pollution on brain volumes. Modifiable genetic effects in gene‐environment interaction models were investigated.

Results

Individuals at higher genetic predisposition to AD and APOE‐e4 carriers exhibited increased vulnerability to air pollution, particularly in temporal and frontal regions [Figure 1A]. Individuals with high genetic predisposition for inflammatory markers showed distinct patterns of vulnerability, particularly affecting regions within the parietal and limbic lobes, with notable impact on hippocampal volumes and the subfields within the hippocampal formation [Figure 1B]. Finally, as pollution levels increased, reduction in transverse temporal volumes was observed in individuals at high risk of AD and altered CCL2 protein plasma levels [Figure 2]. Multiple comparison corrections were performed within brain lobes by regions.

Conclusions

Our results suggested a differential impact of air pollution on brain structure, modulated by genetic predisposition to AD and inflammation. This underscores the importance of considering genetic information when assessing the neurological impact of environmental exposures. These findings pave the way for more personalized approaches in public health interventions, and highlight the need for targeted strategies to mitigate the impact of environmental factors on neurological health.
Locus Coeruleus Neuroimaging compared Voxel by Voxel to Histology‐ a postmortem human validation study
Authors: LaMore Tia , Huang Shuo , Marinho Pedro Burlacchini S. , Chen Yuheng , Li Song Hua , Lee Wing Hung , Carreira Luzia Lima , Rodriguez Roberta Diehl , Otaduy Maria Concepción Gracía , Shi Yonggang , Grinberg Lea T.
Published: January 2025

Background

Neuropathological studies indicate that locus coeruleus(LC) volume decreases in Alzheimer’s disease(AD) by 8% at each stage, (from Braak 0‐1), whereas in normal aging, the LC remains unchanged. These changes make LC volumetry by neuroimaging a promising way to track AD progression even before symptoms appear. However, LC’s small size and location make it prone to imaging artifacts. To assess the accuracy of neuroimaging sequences designed for LC volumetry, we used an in‐house histological computational method to compare histology and neuroimaging on a voxel‐by‐voxel basis.

Method

We investigated three cases (two Braak 1s, and a Braak 5). The whole brain underwent 7T MRI postmortem, pre‐autopsy, at the University of Sao Paulo. Upon autopsy, the brains were processed at UCSF and the histological LC was 3D reconstructed. In parallel, the GRE and TFL MRI sequence LCs were segmented (Fig 1). We applied affine& spline registration to match histology to MRI‐T1 volumes(voxel size = 0.75mm)(Fig 1). To measure registration accuracy, we calculated DICE coefficients using T1 visible structures (Fig 2). Next, we analyzed the percentage overlap of voxels to investigate how accurately MRI sequences detected histology LC borders.

Result

Overall, the DICE values for brainstem registration are high. Table 1 shows the overlapping percentages that are quite low, from 2.5%‐23%. For our Braak 1 cases, the least overlap of GRE MRI and histology LC borders is in rostral region, while in both TFL and GRE sequence for the Braak 5 case, the least LC overlap was in the caudal region (Table 1).

Conclusion

These results suggest that accurately detecting LC borders using MRI remains a challenging task due to small size, imaging artifacts, and neuromelanin dependency, which is low at baseline in caudal LC. However, our overlap results did match previous findings on specific regional LC volume loss seen rostrally in early AD, despite no neuronal loss, and in later stages of AD, volume loss caudally. This points to the MRI LC signal being potentially clinically useful for disease monitoring. Our study will continue to examine the MRI signal picked up in the LC across Braak as regions of LC degeneration shift compared to the histology counterpart.
Estimating the time between Aβ positivity and elevated regional tau in preclinical AD
Authors: Coath William , Betthauser Tobey J. , Teague Jordan P , Arstad Erik , Awais Ramla , Sander Kerstin , Scott Catherine J , Thomas David L , Dickson John , Markiewicz Pawel J , Barkhof Frederik , Schöll Michael , Richards Marcus , Fox Nick C , Cash David M , Schott Jonathan M
Published: January 2025

Background

Understanding when Aß positive cognitively normal individuals develop tau pathology has important implications for treatment with anti‐Aß therapies. We employed a changepoint regression approach to estimate time from Aß‐PET positivity to regionally elevated tau‐PET in a population‐based cohort of primarily cognitively unimpaired individuals.

Method

Participants from Insight 46 (1946 British birth cohort) underwent two [18F]florbetapir Aß‐PET scans and a sub‐sample enriched for Aß were also scanned with [18F]MK‐6240 tau‐PET, characteristics are presented in Table 1. Age at Aß‐PET positivity, defined through Gaussian mixture modelling (GMM) as >12 Centiloids, was estimated using the SILA algorithm (Betthauser et al. 2022). Tau‐PET SUVRs from a temporal‐meta, Braak I‐VI and 34 bilateral FreeSurfer7 regions were calculated 90‐110 mins post‐injection using an inferior cerebellar grey matter reference region. Tau‐PET positivity cutpoints for each region were defined using the 99th percentile of the lower distribution from GMM. For each region, we tested changepoints in the slope of the linear regression between tau‐PET SUVR and time from estimated Aß positivity with Bonferroni correction (5% significance,p<.001).

Result

At tau‐PET scan, 90 individuals (60%) were >0 years from estimated Aß positivity. There was a statistically significant difference in slopes before and after the changepoint for all composite regions excluding Braak VI (Figure 1). Changepoint estimates show that tau accumulation started ∼2.5yrs after estimated Aß positivity in Braak stages I‐III; and ∼10‐12.5yrs for Braak stages IV‐V, and the temporal‐meta region (Figure 2A). Regional estimates broadly followed Braak stages for 16/36 regions showing significant evidence of change in slopes (Figure 2B). Tau positivity rates before changepoints did not exceed 5%, whereas post‐changepoint tau positivity rates were between ∼10% and ∼50%. Regions with later changepoints tended to exhibit higher post‐changepoint slopes with greater uncertainty.

Conclusion

Elevated tau‐PET signal occurs ∼2.5 years after estimated age of Aß onset in Braak stages I‐III and ∼10‐12.5 years in temporal‐meta and Braak stages IV‐V, with uncertainty within these groupings. These estimates for later Braak stages are consistent with results from previous work on the timing of positive tau PET visual reads. These findings may have implications for determining the optimal time to administer Aß immunotherapies in asymptomatic individuals.
A novel fMRI memory paradigm designed for brain imaging studies in early Alzheimer’s Disease
Authors: Joshi Himanshu , Sivakumar PT , Venkatasubramanian Ganesan , John John P , Thompson Paul M.
Published: January 2025

Background

We present the results of a task‐based fMRI study in early Alzheimer’s disease(mild cognitive impairment, MCI and mild Alzheimer’s disease, AD) using a novel‐fMRI memory paradigm suitable for use in patients with significant cognitive impairment having difficulties with remembering complex instructions.

Method

The study samples comprised 65 patients with early AD(MCI n = 42; 21 males; mild AD n = 23; 16 males) and 26(14 males) elderly cognitively healthy control(eCHC) participants. The incidental encoding phase of the paradigm(7 minutes) comprised 110 trials of common objects(55 living and 55 non‐living trials which included 4 objects repeated 6 times each and 1 object repeated 5 times) while the intentional retrieval phase of the paradigm(7 minutes) comprised 55 trials of the 5 objects encoded during the previous phase(repeated 11 times each), and 55 new objects. Task‐based fMRI acquisitions were performed on a Philips Ingenia 3‐T MRI scannerand data was analysed using FEAT(FMRI Expert Analysis Tool) correcting for age, gender, education, and total brain volume.

Result

Significantly increased activations spread across bilateral fronto‐parietal and occipital cortices were noted during incidental encoding of both ‘living’ and ‘non‐living’ stimuli in MCI when compared to eCHC and in mild AD when compared to MCI. However, reduced activations spread across bilateral central and parietal opercular cortices as well as frontal, temporal and parietal brain regions were noted during the intentional retrieval phase in response to both ‘memory’ and ‘non‐memory’ stimuli in MCI when compared to eCHC and in mild AD when compared to MCI.

Conclusion

The increased brain activations of brain regions involved in during the incidental encoding phase reflects effortful encoding of novel stimuli in patients with early AD. The brain regions that showed reduced activations during the intentional retrieval phase have been previously reported to be involved in various processes that underlie retrieval of previously encoded memory traces. The results of the study support the utility of this novel‐fMRI memory paradigm as a tool suitable for brain imaging research in cognitively impaired research participants.
The HOPE4MCI study: AGB101 treatment reduces entorhinal cortex atrophy in patients with amnestic mild cognitive impairment due to Alzheimer's Disease who are ApoE‐4 non‐carriers
Authors: Rani Nisha , Mohs Richard , Gallagher Michela , Bakker Arnold
Published: January 2025

Background

Hippocampal hyperactivity is a hallmark of prodromal Alzheimer’s disease (AD) that predicts progression in patients with amnestic mild cognitive impairment (aMCI). AGB101 is an extended‐release formulation of levetiracetam in the dose range previously demonstrated to normalize hippocampal activity and improve cognitive performance in aMCI. The HOPE4MCI clinical trial used a 78‐week protocol to assess progression in amyloid‐positive patients with MCI due to AD. Mohs et al. (2024) reported the clinical/cognitive results showing that ApoE‐4 non‐carriers had a more favorable treatment effect of AGB101 over the 78‐week duration of the study. Here we report effects of AGB101 on biomarkers of AD in those patients.

Methods

Forty‐four participants who completed the 78‐week protocol were ApoE‐4 non‐carriers. Structural MRI scans obtained in the study at baseline and after 78 weeks were analyzed using the Automated Segmentation of Hippocampal Subfields (ASHS) software providing volume measures of key structures of the medial temporal lobe relevant to AD progression. Blood samples collected at 78 weeks in the study were also analyzed for plasma biomarkers in those participants.

Results

Treatment with AGB101 significantly reduced atrophy in the left entorhinal cortex (p < 0.05) compared to placebo. Reduced atrophy in the entorhinal cortex was significantly correlated with the change in CDR‐SB score (r = ‐0.511) over 78 weeks, as well as with biomarkers of neurodegeneration neurofilament light (NfL; r = ‐0.382) and glial fibrillary acidic protein (GFAP; r = ‐0.398) collected at completion of the protocol.

Conclusion

As reported in Mohs et al. (2024), progression on the primary clinical/cognitive endpoint of the Clincial Dementia Rating Scale Sum of Boxes score (CDR‐SB) occurred over the 78‐week protocol in the HOPE4MCI study and non‐carriers of ApoE4 treated with AGB101 showed a substantially more favorable effect than carriers. Here we report that treatment with AGB101, in those participants significantly reduced atrophy of the entorhinal cortex. That reduction in atrophy was significantly coupled with the change in CDR‐SB and with plasma biomarkers of disease. These exploratory analyses would be consistent with a reduction in neurodegeneration in the non‐carriers of ApoE4 treated with AGB101 prior to a clinical diagnosis of dementia.
Hippocampal degeneration is associated with GFAP levels in individuals with vascular dementia independently of amyloidosis
Authors: Oliveira Markley , Bellaver Bruna , Lussier Firoza Z , Ferreira Pamela C.L. , Povala Guilherme , Leffa Douglas Teixeira , Bauer‐Negrini Guilherme , Rodrigues Matheus Scarpatto , Abbas Sarah , Zalzale Hussein , Rohden Francieli , Felix Cynthia , Soares Carolina , Saha Pampa , Ruppert Emma Patrice , Machado Vitor Hugo , da Rocha Andreia Silva , Tudorascu Dana , Benedet Andrea L. , Ashton Nicholas J. , Tissot Cécile , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Rahmouni Nesrine , Hong Chang Hyung , Roh Hyun Woong , Zimmer Eduardo R. , Blennow Kaj , Zetterberg Henrik , Karikari Thomas K , Rosa‐Neto Pedro , Son Sang Joon , Pascoal Tharick A.
Published: January 2025

Background

Vascular cognitive impairment/dementia (VD) is the second most prevalent cause of dementia following Alzheimer's disease (AD). VD is characterized by the progression of white matter hyperintensity burden (WMH) and associated neurodegeneration. GFAP, a biomarker for reactive astrogliosis, is associated with Aß pathology and mediates tau‐pathology in preclinical AD. However, the association of GFAP levels with the markers associated with VD is poorly understood.

Method

We assessed 796 participants from a research cohort (TRIAD: 355) and a memory clinic cohort (BICWALZ: 441) that were divided into four groups according to their Aß (Aß+/Aß‐) and WMH status (WMH+/WMH‐). WMH values were corrected by intracranial volume, and cutoffs were determined based on the highest WMH value within 50% of the individuals with the lowest WMH rate in the CU Aß‐ group. Biomarker mean level differences between groups were estimated via Ancova Tukey’s test, and linear regressions accounting for age, sex, and cognitive status were used to estimate the association.

Result

For TRIAD, WMH+/Aß+ individuals exhibit higher levels of plasma GFAP when compared to all groups except WMH‐/Aß+, with no differences in NfL levels and hippocampal volume between groups (Fig. 1A). In BICWALZ, only hippocampal volume differs between groups with lower levels observed in both WMH‐/Aß‐ and WMH‐/Aß+ (Fig. 1B’’). The association of GFAP and NfL was observed in all groups (Fig. 2A, 2B’). On the other hand, hippocampal degeneration was associated with higher GFAP levels in individuals with abnormal WMH and absence of Aß burden in both cohorts (Fig. 3A: TRIAD: ß= ‐0.3036; p= 0.0195; Fig. 3B’: BICWALZ: ß= ‐0.1791; p= 0.0125).

Conclusion

Our findings suggest that astrocyte reactivity, as indicated by plasma GFAP levels, plays a significant role in the hippocampal atrophy observed in patients with vascular disease. These results suggest that therapies targeting astrocyte reactivity could potentially alleviate progressive cognitive deficits commonly found in patients with chronic vasculopathy.
Exploring the effects of using multiple different cerebellar reference regions to improve tau‐PET harmonization ‐ The HEAD Study
Authors: Bauer‐Negrini Guilherme , Povala Guilherme , Bellaver Bruna , Lussier Firoza Z , Tissot Cécile , Tsai Hsin‐Yeh , Amaral Livia , Ferreira Pamela C.L. , Tudorascu Dana , Jagust William J. , Klunk William E , Lowe Val J. , soleimani‐meigooni David N. , Oh Hwamee , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick A.
Published: January 2025

Background

Tau‐PET tracers have been used to diagnose and stage Alzheimer’s disease. However, different tau tracers present distinct patterns of binding throughout the brain, challenging the harmonization of their results. We hypothesize that the choice of a reference region can impact the harmonization of the tau‐PET standardized uptake value ratio (SUVR). In this context, we aimed to explore how different cerebellar reference regions impact the association between [18F]Flortaucipir and [18F]MK‐6240 SUVR values.

Method

We studied 185 individuals across the aging and AD spectrum with head‐to‐head Flortaucipir and MK‐6240 tau PET (HEAD Study). SUVRs were processed to a common 8mm FWHM using 15 different reference regions defined in the spatially unbiased atlas template of the cerebellum (SUIT) (Diedrichsen, 2009). Regression models investigated the association between Flortaucipir and MK‐6240 using multiple combinations of reference regions. R2 statistic was used to estimate goodness‐of‐fitting.

Result

225 combinations of associations Flortaucipir and MK‐6240 SUVR were tested, where the SUVRs are not necessarily quantified using the same reference region. Figure 1 presents the top 25 strongest and 25 weakest associations, ordered based on the coefficient of determination (R²). Flortaucipir and MK‐6240 exhibited the most robust associations when the inferior cerebellar gray matter or Crus I were employed for SUVR determination (R2 = 0.89, Figure 1‐2). Conversely, combinations incorporating the fastigial region consistently yielded weaker associations between the two tracers (R2<0.70, Figure 1‐2).

Conclusion

Interestingly, we showed that the inferior cerebellum, when used for both tracers, serves as a robust reference region for determining the most similar SUVRs for Flortaucipir and MK‐6240. Notably, these two regions have been commonly utilized in previous studies involving these tau tracers. Our results imply that the inferior cerebellum could be the optimal reference region for research aimed at harmonizing tau PET tracers using statistical scales.
Unraveling Alzheimer’s Disease Heterogeneity: A Comparative Analysis Using HYDRA and CHIMERA
Authors: An Gordon , Benzinger Tammie L.S. , Sotiras Aristeidis , Gordon Brian A.
Published: January 2025

Background

Alzheimer’s Disease can present with heterogenous neurodegenerative patterns. In order to optimize clinical trials and personalized medicine, the identification and characterization of diverse pathological brain patterns associated with AD have become paramount. Optimal approaches to identify such heterogeneity are unknown. The present study employed two distinct clustering approaches, namely HYDRA and CHIMERA, to delineate the spatial pattern of brain atrophy attributable to AD. Methods were applied to MRI scans from the Open Access Series of Imaging Studies (OASIS‐4) project.

Methods

HYDRA uses a convex polytope formed by multiple linear hyperplanes that correspond to various pathological patterns, capturing disease subtypes. CHIMERA assesses the pathological transition by transforming NC distribution to separate transformations matching the disease distribution. While both identify spatial patterns, the distinction lies in HYDRA’s discriminative analysis of disease subtypes and CHIMERA’s generative nature on disease progression through distribution matching.

Results

Both approaches identified two patterns, or subtypes (Figure 1) with similar CDR results (Figure 2). All subtypes demonstrate marked atrophy within the medial temporal areas, notably the hippocampus. Disparities are evident when assessing subtypes: Subtype‐2 across both methods shows pronounced variations in regions such as superior frontal, middle temporal, parietal cortex, and precuneus, areas paramount in AD pathology. Conversely, HYDRA’s Subtype‐1 highlights subtle differences in temporal cortex relative to its Subtype‐2. CHIMERA’s Subtype‐1, while mirroring its Subtype‐2 pattern, is less intensified, suggesting an earlier AD stage. Collectively, these patterns concur with recognized AD neuropathological trajectories, pinpointing regions initially impacted in progression. In addition, an in‐depth exploration of subsequent analysis including a longitudinal data evaluation to observe the progression of these patterns over time is slated for later investigation.

Conclusion

Our findings demonstrate data‐driven approaches to derive clinically meaningful patterns of neurodegeneration. A parallel evaluation of both approaches accentuates the robustness of clustering techniques, revealing consistent and overlapping insights into the intricate pathological landscapes of AD. This convergence in findings bolsters confidence in the reliability of such analytical tools in AD research.
Digital Interventions in Neuro‐Rehabilitation: Gotcha! app‐based therapy for proper name anomia in people with dementia
Authors: Badalova Aygun
Published: January 2025

Background

Proper name anomia is a common experience that can become amplified in patients with a diagnosis of dementia (PWD). The Gotcha! app aims to provide practice‐based therapy for PWD to relearn the names of key people in their lives. It has been developed using the principles of errorless learning and spaced retrieval, which have previously been shown to improve the remembering the familiar people’s names and benefit the relationship between the PWD and their loved ones. (Clare et al, 1999, 2000, 2003).

Methods

Gotcha! is a digital confrontation naming therapy app which enables patients to train one face per day by using photos of the person whose name is to be trained. We employed a single‐case experimental design with weekly testing of free‐naming in both six‐week blocks (pre therapy and therapy). During the therapy, a novel speech verifier is used to provide real‐time feedback (Barbera et al. 2020). Two analyses method is used to investigate the behavioural data: 1) within‐subject non‐parametric analysis using Tau‐U metric (Parker et al. 2011); 2) a parametric group analysis using an ANOVA.

Results

The trial is ongoing. Results from the first 20 subjects show: 1) Tau‐U. 80% showed a positive trend with better naming during the training phase with 8/20 reaching statistical significance. 2) ANOVA demonstrated a significant effect at the group level of training>baseline phase, F (1,19) = 13.18, p = 0.01

Conclusion

App‐based proper name anomia retraining works for the majority of PWD in our trial thus far. Being able to freely recall and produce the name of a relative or loved one has a big impact on people’s lives.
Multivariate sleep health and cognitive functions in healthy older adults: results from partial least square correlation analysis
Authors: Qin Shuo , Ng Eric Kwun Kei , Soon ChunSiong , Chua XinYu , Zhou Juan Helen , Koh Woon‐Puay , Chee Michael Wei‐Liang
Published: January 2025

Background

Past studies examining sleep‐cognition relationships mostly employed univariate approaches, which are subject to problems such as multicollinearity and multiple comparisons. Further, results from small sample univariate analyses are difficult to compare, precluding the identification of the aspects of sleep health associated with a particular cognitive domain(s). The current study used a multivariate approach to identify key sleep metrics and cognitive domains that contribute to the maximum sleep‐cognition covariance in healthy older adults. From the reduced list of sleep metrics and cognitive domains, novel associations between different aspects of sleep health and cognitive domains can be uncovered.

Method

The current study is part of the ongoing SG70: Toward Healthy Longevity in Singapore study, which aims to comprehensively assess factors that affect aging health in over 1000 Singaporean older adults. From the SG70 study, 440 healthy older adults wore an Oura Ring (OuraHealth OY) for 14‐30 days. Twenty‐three metrics encompassing 4 major aspects of objective sleep health: duration, timing, regularity, and continuity were extracted (Figure 1). Cognition was assessed using a comprehensive battery that encompassed 7 domains. The overall covariance between sleep and cognition was examined by a partial least square correlation (PLSC) analysis. Sleep metrics and cognitive domains that contributed significantly to significant PLSC components were identified by bootstrapping.

Result

PLSC analysis identified a component that explained 68% of covariance between sleep and cognition matrices (r = 0.17, p<0.001). Bootstrapping tests further identified 10 sleep continuity and regularity metrics and 4 corresponding cognitive domains that contributed significantly to the observed covariance (Figure 2). Post‐hoc univariate analyses showed that sleep continuity metrics correlated with speed of processing, while sleep regularity metrics correlated with verbal memory, visual‐spatial ability, executive functions, and speed of processing (Figure 3).

Conclusion

Our results suggest that sleep continuity and regularity may be more sensitive markers of impairments across multiple cognitive domains in healthy aging compared to sleep duration and timing. In addition, they support the utility of multivariate analyses in uncovering significant association patterns between sleep and cognition.
Mayo Normative Studies: regression‐based normative data for remote self‐administration of the Stricker Learning Span, Symbols Test and Mayo Test Drive Screening Battery Composite for ages 33‐100 and validation in MCI and dementia
Authors: Stricker Nikki H. , Frank Ryan D. , Boots Elizabeth A. , Fan Winnie Z. , Christianson Teresa J. , Kremers Walter K. , Stricker John L. , Machulda Mary M. , Lucas John A. , Hassenstab Jason J. , Graff‐Radford Jonathan , Vemuri Prashanthi , Jack Clifford R. , Knopman David S. , Petersen Ronald C.
Published: January 2025

Background

Few normative data for computerized measures administered in unsupervised remote environments are available. We aimed to determine what variables to include in normative models for remote self‐administered assessments, develop normative data for measures administered through Mayo Test Drive (MTD, a multi‐device remote cognitive assessment platform) and evaluate application of norms.

Method

1240 adults ages 33‐100 (96% White) from the Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center met normative sample inclusion criteria that included a concordant Cognitively Unimpaired (CU) diagnosis (3 independent raters all diagnosed CU) and CDR = 0 (see Table 1 for sample characteristics). Raw test scores were converted to normalized scaled scores. We derived regression‐based normative data that adjusted for age, age2, sex and education (base model); alternative models are also provided (age+age2+sex; age+ age2). We evaluated whether additional model terms beyond the base model were needed using an a priori cut‐off of 1% variance improvement in adjusted R2 over and above the base model. We examined rates of low test performance defined as performance below ‐1 SD in independent validation samples (n = 167 concordant CU, n = 64 mild cognitive impairment (MCI), n = 14 dementia). Rates are considered significantly different than expected when 95% confidence intervals (CIs) do not include the expected 14.7% base rate frequency.

Result

No additional potential model terms met our a priori cut‐off for inclusion beyond the base model (see Table 2), including other quadratic and cubic terms or interactions, device type, response input type, potential session interference, and national area deprivation index (ADI available in subset; N = 776). Application of norms showed expected rates of low test performance among CU participants (95% CI includes expected base rate) and significantly greater than expected rates of low test performance for all variables in MCI (e.g., 62.5% for composite) and dementia (e.g., 71.4% for composite; see Table 3).

Conclusion

Typical normative models appear appropriate for remote self‐administered measures and are sensitive to cognitive impairment. Device type and response input did not explain enough variance to warrant inclusion in normative models but are important for individual level interpretation. Future work will improve representation of individuals from under‐represented groups.
Setting a Baseline for Normal Cognitive Aging with Lexical Concreteness – A Corpus Linguistic Approach
Authors: Han Kunmei
Published: January 2025

Background

Identifying language variation in healthy aging speakers is important for understanding normal cognitive aging. Setting a baseline of normal aging languages in the first place is necessary for the evaluation of language performances of old adults. Lexical concreteness, a well‐studied psycholinguistic parameter, has been used to detect semantic memory‐related deficits. For example, people with semantic dementia were found to display reduced lexical concreteness (Breedin et al., 1994). Healthy old adults, however, are less studied in terms of the concreteness pattern in their speech. This study examines lexical concreteness of free speech samples of normal aging speakers age between 60 – 80 in Singapore.

Method

We collected about 15‐min free speech from 243 English‐speaking, cognitively healthy Singaporeans (133 women, 110 men) age above 60 years old. Demographic variables (age, gender, education, and number of languages spoken) were uncorrelated with each other. Speeches were transcribed by native Singapore English speakers and tagged with part‐of‐speech (PoS) information. We calculated global lexical features including speech rate (in minutes), lexical diversity (Moving‐Average Type‐Token Ratio), and PoS distribution (count per 100 tokens). Then we calculated concreteness (Brysbaert et al., 2014) of major content words for every individual. The relation between age and lexical measures was examined with Spearman’s correlation test.

Result

Results of the statistical analysis show that healthy old adults speak slower (𝜌 = ‐0.14, p = .03) with more concrete nouns (𝜌 = 0.14, p = .03) and adjectives (𝜌 = 0.18, p< .05) than younger speakers. PoS distribution and verb concreteness (all p> .05) remain stable in the aging process.

Conclusion

Our speech sample revealed a general trend of elderly speech – reduced speech rates and increased lexical concreteness. The significant positive association between age and lexical concreteness in free speeches of health old adults was found for the first time, providing corroborative evidence for the link between concreteness and semantic memory. We also found a dissociation between nouns and verbs, consistent with neuropsychological literatures that nouns and verbs are encoded in different areas of the brain (Vigliocco et al., 2011). In sum, measuring lexical concreteness in natural speech data can provide circumstantial evidence for evaluating cognitive aging.
A Brief Digital Neuropsychological Protocol – I: Using Artificial Intelligence Assisted Technology to Assess Process and Errors
Authors: Libon David J. , Swenson Rodney , Tobyne Sean , Price Catherine C. , Lamar Melissa , Cosentino Stephanie , Banks Russell , Jannati Ali , Showalter John , Bates David , Pascual‐Leone Alvaro
Published: January 2025

Background

There is an urgent need for neuropsychological screening tests that are easily deployed and reliable. We have developed a digital neuropsychological screening protocol that is administered on a tablet, automatically scored using artificial intelligence, and requires approximately 10 minutes to administer. This tablet‐administered protocol assesses the requisite neurocognitive constructs associated with emergent neurodegenerative illness

Method

The digital protocol was administered to 77 ambulatory care/ memory clinic patients (Table1). The protocol is comprised of a 6‐word version of the Philadelphia (repeatable) Verbal Learning Test [P(r)VLT], three trials of 5 digits backward (BDST), and the ‘animal' fluency test. The protocol provides a panel of six traditional measures as would be obtained using paper/ pencil tests and manual scoring of (P[r]VLT free recall/ recognition hits, backward digit span, ‘animal' fluency output); a variety of outcome measures quantifying errors and the process used to bring tests to fruition; and two separate, norm‐referenced summary scores measuring executive control and memory.

Result

Cluster analysis using the panel of 6 traditional measures classified participants into normal (nl = 23), amnestic MCI (aMCI = 17), dysexecutive MCI (dMCI = 23), and dementia (dementia = 23) groups. Subsequent analyses of error and process variables operationally defined key features associated with amnesia including rapid forgetting such as (P[r]VLT immediate free recall trial 2 vs. delay free recall (aMCI & dementia < dMCI & nl; p< 0.001), the production of extra‐list intrusion errors (dementia > nl; p< 0.002); profligate responding to recognition foils (aMCI & dementia > dMCI & nl; p< 0.001); key features underlying reduced executive measures (i.e., BDST perseveration/ related errors (dMCI & dementia > aMCI & nl, < 0.050); and the strength of semantic association from successive ‘animal' fluency responses (nl & dMCI > dementia; p< 0.028). The novel executive and memory index scores dissociated all four groups from each other (p< 0.014).

Conclusion

This digitally administered and scored protocol yields patterns of impaired performance similar to paper/ pencil tests. The availability of both traditional and error/ process measures suggests that subtle, nuanced indications of early emergent illness may be identified in a fast, efficient, yet comprehensive way.
Optimizing the Assessment of Self‐Perceived Cognitive Functioning for Predicting Mild Cognitive Impairment: Integrating Traditional Methods with Daily Digital Diary Assessments: Results from the Einstein Aging Study (EAS)
Authors: Garza Angel Garcia De La , Mogle Jacqueline A. , Wang Cuiling , Katz Mindy J. , Derby Carol A. , Cameron Jack , Lipton Richard B. , Rabin Laura , Sliwinski Martin J.
Published: January 2025

Background

Ecological momentary assessments (EMA) are increasingly used to monitor self‐perceived memory and cognitive difficulties. We investigate how traditional self‐reported, recall based assessments of cognitive difficulties correlate with EMA measures. We identify factors explaining shared variance between measures from the 40‐item version of the Cognitive Change Index (CCI) and from EMA daily diaries, and factors explaining unique variance in each assessment. We compare EMA and CCI individually, as well as factors derived from both assessments, in predicting incident mild cognitive impairment (MCI).

Methods

In neuropsychologically unimpaired Einstein Aging Study participants, we collected daily digital diary data on 18 cognitive lapses and their perceived disruption of everyday function over 14 days. Additionally, we assessed the conventional recall‐based indicators using the paper‐and‐pencil CCI, referencing both current ability and change over five years. Bayesian Canonical Correlation Analysis (BCCA) was employed to identify factors explaining the relationship between EMA and CCI, and factors explaining the unique variance in each. Separate Cox regressions were employed to assess whether baseline standardized CCI total scores, total number of cognitive lapses reported on EMA, and factors derived from the BCCA, were associated with the incidence of MCI after adjusting for age, gender, race/ethnicity, and depression status.

Results

Analyses included 205 community‐dwelling participants (mean age = 77.11, SD = 4.78, 66.82% female, 53.17% white) without MCI at baseline. We identified one shared factor between CCI‐40 and EMA that explains 69% of CCI‐40 variability and 12% of EMA variability (canonical correlation = 0.58). We also found two factors unique to EMA explaining 32% and 27% of the variance. The shared CCI‐EMA factor (HR = 1.56, 95% CI = 1.11‐2.19, p = 0.0017), and total CCI‐40 scores (HR = 1.60, 95% CI = 1.14‐2.25, p = 0.011), significantly predicts MCI incidence at any follow‐up. Neither of total number of cognitive lapses reported on EMA nor BCCA factors unique to EMA significantly predict incidence MCI.

Conclusions

Results suggest that traditional assessments and EMA measurements of memory and cognitive difficulties provide both shared and unique information. This information could be harnessed using advanced data analysis techniques to improve the prediction of incident MCI.
From glia to cytokine signatures across the Alzheimer's spectrum
Authors: Malpetti Maura , Swann Peter , Chouliaras Leonidas , Jones P Simon , Mak Elijah , Bevan‐Jones W Richard , Su Li , Fryer Tim D , Hong Young T , Aigbirhio Franklin I , O'Brien John T , Rowe James B
Published: January 2025

Background

Early neuroinflammation is involved in pathophysiology of Alzheimer’s Disease (AD) and contributes to faster clinical decline. Thus, neuroinflammation has emerged as a promising therapeutic target for dementia. However, a better understanding of the interaction between central and peripheral inflammation in human disease and in vivo biomarkers are required for successful clinical trials. Here we assess inflammatory patterns of serum cytokines and their relationship with central inflammation as quantified by TSPO PET (PK11195) in participants on the aging‐AD spectrum.

Method

Blood samples were obtained from 56 participants, including30 controls, 22 patients with MCI and 14 with AD) Serum cytokines were quantified using the MesoScale Discovery V‐Plex‐Human Cytokine panel. We applied a Principal Component Analysis (PCA) across all participants to identify inflammatory profiles, which were compared across groups with ANOVA and post hoc tests. Individual scores of the resulting components were correlated with regional TSPO PET binding potentials, as index of microglial activation, and cognitive impairment (MMSE scores).

Result

Analyses on 30 identified 2 components (explaining 19.4 % and 10.8% of the variance, respectively). Both components were strongly represented by pro‐inflammatory cytokines (Figure 1A). One‐way analyses of variance on the first component could not detected statistically significant differences across the groups (χ2(2)=1.69, p=0.193), while individual scores of Component 2 (χ2(2)=8.46, p<0.001) were statistically higher in patients with AD as compared to patients with MCI and to controls (Figure 1B). Correlation analyses with regional TSPO PET values identified positive widespread associations with individual Component 2 scores in frontal, temporal and parietal regions (r > 0.250, p < 0.05; while associations with Component 1 where limited to the anterior frontal/temporal regions (Figure 1C). Individual scores of Component 2 but not Component 1 were significantly associated with worse cognitive performance (lower MMSE; r = ‐0.315, p = 0.01).

Conclusion

Our approach identified proinflammatory blood signatures that relate to central inflammation and cognitive impairment across the aging‐AD spectrum. These findings encourage the combination of TSPO imaging and blood‐based markers to clarify the interaction between peripheral and central inflammation in AD, and to identify promising therapeutic targets. "
Brain disease Research Infrastructure for Data Gathering and Exploration (BRIDGE): A government‐led platform for standardized data collection, longitudinal monitoring, and sharing of Korean data sources for brain disorders
Authors: Seo Junwoo , Oh Sujung , Kang Eunjee , Kang Danbee
Published: January 2025

Background

Brain diseases complexity have necessitated advanced research platforms for better understanding, treatment, and prevention strategies. However, existing brain disease registries face limitations such as incomplete variable sets, lack of standardization, insufficient linkage to external databases, absence of integrated platforms for comprehensive data collection, and lack of continuity. To address these challenges, the Korea National Institute of Health initiated the Brain disease Research Infrastructure for Data Gathering and Exploration (BRIDGE), a national prospective platform designed to overcome the shortcomings of current registries.

Method

The BRIDGE platform includes a Longitudinal Study of Early onset dementia And Family members (LEAF) cohort, a Longitudinal/cohort Study of Patients with Late Onset Dementia (LLOD) cohort, a Community‐based cohort study of High‐risk individuals for Dementia (COHD) cohort, and a Longitudinal Study of Patients with Parkinson’s Disease (LoPD) cohort. The standardized variables included sociodemographic variables, health behaviors, medical history, activities of daily living, behavioral, and psychological problems, cognitive function, disease‐related symptoms, quality of life (QoL), sleep, depression scale, caregiver burden, physical health, blood tests, olfactory function testing, orthostatic blood pressure changes, genetic testing, nerve conduction studies, and neuroimaging. In addition, the BRIDGE platform will1 be linked to the Korean National Health Insurance Service (K‐NHIS) database.

Result

From May 2021 to December 2023, 3,505 participants were registered, with an average age of 69 years and 59.9% female. The LEAF cohort had the lowest K‐MMSE score and the highest Clinical Dementia Rating (CDR) score. The LOPD cohort had the lowest QoL scores. When compared to the age‐sex‐matched general population from Korea National Health and Nutrition Examination Survey (KNHANES), patients with brain disease were less likely to work, had lower income and had significantly lower QoL.

Conclusion

By addressing gaps in data collection, standardization, and considering a wide range of impacts, the BRIDGE database offers new pathways for understanding and combating complex brain conditions. As the project progresses, it has the potential to significantly influence scientific understanding and policymaking in the field of brain health.
Everyday Cognition Scale Predicts Longitudinal Progression in Paired Associated Learning: Unsupervised Online Setting from the Brain Health Registry
Authors: Kang Jaemyeong , Manjavong Manchumad , Jin Chengshi , Diaz Adam , Ashford Miriam T. , Eichenbaum Joseph , Thorp Emily , Wragg Elizabeth , Zavitz Kenton , Cormack Francesca K , Aaronson Anna , Miller Melanie J. , Mackin Scott R , Tank Rachana , Landavazo Bernard , Truran‐Sacrey Diana , Farias Sarah Tomaszewski , Weiner Michael W. , Nosheny Rachel L.
Published: January 2025

Background

Online platforms are an efficient means to detect early cognitive decline, but few studies have investigated the relationship between remotely collected subjective cognitive change and cognitive decline. We hypothesized that the Everyday Cognition Scale (ECog), a subjective change measure, predicts longitudinal change in cognition in Brain Health Registry (BHR), an online registry for neuroscience research.

Method

From the BHR database, we included participants aged 55+ who completed both the baseline ECog and repeated administrations of the CANTAB® Paired Associates Learning (PAL) test. Both self‐reported ECog (Self‐ECog) and study partner ECog (SP‐ECog), and two PAL scores (first attempt memory score [FAMS] and total errors adjusted [TEA]) were assessed. We used multiple ECog scoring outputs, based on previously established cut‐offs for likely impairment (Self‐ECog positive [total score ≥1.31], SP‐ECog positive [total score ≥1.36], and ECog consistent [any item≥3]). A linear mixed effects model was employed to assess the effect of baseline ECog on longitudinal change in PAL. Additionally, logistic regression models were used to assess the ability of ECog to identify ‘decliners’, who exhibited the worst PAL progression slopes corresponding to the fifth percentile and below.

Result

The study included a total of 16,683 participants, who were followed for 11.49±11.53 months. Both Self‐ECog positive (estimate = ‐0.01, p<0.0019) and Self‐ECog consistent (estimate = ‐0.008, p<0.0085) were significant predictors for longitudinal change in PAL FAMS after adjusting for age, gender, education, race, depression, family history of Alzheimer’s disease (AD), taking AD medication, and self‐reported impairment. Those who were SP‐ECog positive (Odds ratio [95% confidence interval] = 1.760 [1.143–2.667]) and SP‐ECog consistent (2.021 [1.344–3.021]) had higher probability of being decliners based on PAL FAMS. Regarding the prediction of PAL TEA decliner, both Self‐ECog consistent (1.248 [1.043–1.494]) and Self‐ECog total (1.287 [1.054–1.557]) were associated with higher odds of being decliners.

Conclusion

In the BHR’s unsupervised online setting, ECog demonstrated utility in predicting longitudinal progression in PAL scores, both in terms of continuous changes and when dichotomized as a decliner. Online, self‐administered measures of subjective cognitive change, together with objective neuropsychological test results have great potential to identify individuals with cognitive impairments.