bluuebunny/crossref_metadata_2025 huggingface dataset:
Validation of QyScore® White Matter Hyperintensity (WMH) U‐Net segmentation algorithm against expert manual consensus and comparison with currently available state‐of‐the‐art methods
Authors: Gordon Elizabeth , Villa Luca , Guizard Nicolas , Tran Philippe
Published: January 2025

Background

Detection and quantification of White Matter Hyperintensities (WMH) are clinically important across multiple CNS disorders and neurodegenerative dementias. However, the prohibitively labor‐intensive nature of manual segmentation limits widespread clinical application. Accurate automated methods for segmenting WMH are needed to overcome this unmet clinical need.

Method

The validation cohort consisted of 129 individuals who had undergone T1‐weighted and T2‐FLAIR MR imaging. To ensure robust results, different scanners (30 GE, 26 Philips, 73 Siemens) and varied patient populations (including Alzheimer’s Disease (n=49), Frontotemporal dementia (n=5) and Multiple Sclerosis (n=45)) were included (Table 1A). The WMH_U‐Net algorithm included in QyScore®, an FDA‐approved and CE‐marked neuroimaging platform, automatically segmented WMH in each image set. These were compared to the gold‐standard consensus of three expert neuroradiologist manual segmentations. Next, a direct comparison of QyScore® WMH_U‐Net was run with six state‐of‐the‐art supervised and unsupervised segmentation methods (LST‐LGA and LPA, Lesion‐TOADS, lesionBrain, BIANCA and nicMSlesions) on a dedicated MS dataset (Table 1B) with default and optimized settings were available. Performance metrics included spatial overlap (Dice Similarity Coefficient (DSC) and F1 scores) and volume comparisons (intra‐class correlation coefficient (ICC) and absolute volume error (AVE, ml)).

Result

QyScore® WMH_U‐Net demonstrated good volume and spatial overlap (average DSC=0.66±0.2), especially with larger WMH load (15‐30ml: DSC=0.75±0.07) across the validation cohort. Optimizing and/or retraining LST‐LGA, BIANCA and nicMSlesions, improved their performances substantially; however, QyScore® WMH_U‐Net remained comparable with the optimized nicMSlesions, with better performance than the optimized LST‐LGA and BIANCA. Friedman test (ANOVA) revealed significantly better spatial (DSC: p=5.90x10‐21) and volumetric agreement (AVE: p=3.61x10‐6) between QyScore® WMH_U‐Net and the other methods (default settings). Wilcoxon signed‐rank post‐hoc analysis (Bonferroni corrected: p<0.0071) demonstrated QyScore® WMH_U‐Net significantly outperformed all methods for spatial and volumetric agreement (Table 2).

Conclusion

QyScore® WMH_U‐Net produced, robust and the most accurate WMH segmentations across multiple scanners and patient groups, supporting its widespread application for clinical routine practice. It is because it is using a U‐Net approach which is understood to be a fast method for image segmentation over more conventional computer vision methods.
The role of immune dysregulation of innate and adaptive immune cells in the prodromal and clinical stages of Parkinson’s disease
Authors: Mark Julian R , Wallings Rebecca L , Staley Hannah , Tansey Malu Gámez
Published: January 2025

Background

Peripheral blood mononuclear cells (PBMCs) were obtained from patients across different stages of Parkinson’s disease (PD) progression and stimulated ex vivo to develop biomarkers for predicting PD progression.

Method

PBMCs obtained at one time‐point from patients with moderate stage PD (>5 years after diagnosis) (n = 30), early stage PD (<5 years after diagnosis) (n = 27), prodromal PD (rapid‐eye‐movement sleep behavior disorder patients) (n = 14), and healthy controls (HCs) (n = 9) were isolated from whole blood and cryopreserved. Samples were thawed, then pan‐monocytes and T‐cell populations were isolated from PBMCs and subjected to treatment with vehicle or IFN‐γ. An additional treatment condition with CD3/28 magnetic beads was included for T‐cells. Cultured media was kept for evaluation of cell‐type specific cytokine release, and live cells were analyzed with flow cytometry for markers of immune activation, mitochondrial and lysosomal function, and LRRK2 expression and activity.

Result

In classical, intermediate, and non‐classical monocytes from HCs, expression of pRab10, LRRK2, and MHC‐II increases after treatment with ex vivo IFN‐γ stimulation. In CD4+ and CD8+ T‐cells from HCs, IFN‐γ and CD3/28 bead treatment caused increased expression of pRab10. CD3/28 magnetic beads, but not IFN‐γ, caused increased expression of CD137 and LRRK2, while also leading to reduced levels of acidified lysosomes. Studies are currently underway to analyze cells from PD and prodromal patients and evaluate cell‐type specific cytokine release in the conditioned media.

Conclusion

We have applied a validated ex vivo stimulation protocol using PBMCs from PD patients across different stages of disease to measure immune cell activation and cell‐type specific cytokine release. If our hypothesis is correct, we expect that immune cell subsets from PD patients will display a signature of dysregulated immune response to stimulation. Furthermore, we expect that prodromal PD patients will exhibit dysregulated peripheral immune responses compared to controls, including altered mitochondrial and lysosomal function and cytokine release.
Synapse loss in early‐ and late‐onset Alzheimer's Disease assessed by 18F‐SynVest‐1
Authors: he kun , Xie Fang , Huang Qi
Published: January 2025

Background

We aimed to investigate the loss of synaptic density in early‐onset and late‐onset Alzheimer's Disease.

Method

One hundred and eighty‐two participants underwent synaptic density PET with 18F‐SynVesT‐1. Including 23 early‐onset Alzheimer‘s Disease (EOAD), 58 late‐onset Alzheimer's Disease (LOAD), 16 EOnonAD, 28 LOnonAD, 31 younger normal control (age < 65) and 26 older normal control (age ⩾ 65). We analyzed the synaptic density loss in EOAD and LOAD relative to their control group respectively. Associations between age and synaptic loss were evaluated in different groups.

Result

EOAD and LOAD groups both displayed significant synaptic density across most areas of cerebrum cortex. Relative to LOAD group, EOAD group showed severer synaptic loss in Lateral Parietal lobe. In EOAD group, synaptic density in occipital lobe had positive association with age. While, in LOAD group, synaptic density in most areas of the cerebrum cortex had a negative association with age.

Conclusion

Our study suggested that the areas of synaptic loss were different between EOAD and LOAD.
The associations between sleep disturbances and allostatic load, and the role of sex, beta amyloid, and burnout history in a memory clinic sample: the Co‐STAR study
Authors: Adedeji Dickson Olusegun , Holleman Jasper , Kåreholt Ingemar , Solomon Alina , Kivipelto Miia , Sindi Shireen
Published: January 2025

Background

Several studies have investigated the link between sleep disturbances and allostatic load (AL), but the results are varied, and less is known about the associations in clinical samples. The goal of this study is to assess the associations between sleep disturbances and AL among memory clinic participants, and to examine differences according to sex, beta‐amyloid status and history of burnout status.

Method

The study was based on 146 memory clinic participants diagnosed with either Mild Cognitive Impairment (MCI) or Subjective Cognitive Impairment (SCI) in the Cortisol and Stress in Alzheimer’s Disease Study (Co‐STAR) (Sweden). Self‐reported sleep was measured using the Karolinska Sleep Questionnaire (KSQ). The AL index is a measure of chronic stress including blood‐based markers reflecting the neuroendocrine, immunological, metabolic, and cardiovascular systems, constructed using 16 biomarkers. Beta‐amyloid was measured from cerebrospinal fluid samples. History of burnout was self‐reported. Linear regressions were conducted to assess the associations between sleep disturbances and allostatic load, while adjusting for age, sex and sleep medications.

Result

Lower total sleep score (b=‐0.228, p= 0.028) and sleep apnea index (b=‐0.187, p= 0.046) correlated with higher AL index. In stratified analyses, lower total sleep score was associated with higher AL index in women (b=‐0.282, p= 0.049), while higher insomnia levels (b=‐0.295, p= 0.038) were linked to lower AL levels in men. AL was only associated with daytime sleepiness in participants with normal beta‐amyloid levels, where a lower daytime sleepiness score (b=‐0.298, p= 0.038) was linked to higher AL levels. Among those without a history of burnout, higher AL index correlated with lower total sleep score (b=‐0.249, p= 0.045), insomnia score (b=‐0.223, p= 0.045), difficulty waking up score (b=‐0.225, p= 0.038), and non‐restorative sleep index (b=‐0.221, p= 0.043).

Conclusion

This study shows varied associations between sleep disturbances and across different subgroups, highlighting the roles of age, sex, beta‐amyloid levels, and history of burnout in the associations. It may be of valuable importance to consider AL when evaluating sleep disturbances and implementing lifestyle interventions for the reduction of chronic stress and sleep disturbances to reduce the risk of cognitive decline.
Risk factor, neuropathological, and clinical correlates of perivascular spaces in brain donors exposed to repetitive head impacts
Authors: Mosaheb Sydney , Rodriguez Frances , Abdolmohammadi Bobak , Uretsky Madeline , Nowinski Christopher , Daneshvar Daniel H , Tripodis Yorghos , Martin Brett , Palmisano Joseph N. , Farris Chad , Huber Bertrand Russell , Stein Thor D. , McKee Ann C. , Mez Jesse , Romero Jose Rafael , Alosco Michael L.
Published: January 2025

Background

Enlarged perivascular spaces (ePVS) on MRI can signal impaired cerebral fluid clearance and predict dementia risk. Risk factors and biological correlates of ePVS are uncertain partially due to the lack of pathological correlation studies. Repetitive head impacts (RHI) from contact sports might represent one risk factor for ePVS, given their association with vascular pathologies and chronic traumatic encephalopathy (CTE), a neurodegenerative disease characterized by perivascular p‐tau aggregates. We examined risk factors, neuropathological, and clinical correlates of antemortem MRI ePVS among brain donors exposed to RHI.

Method

The sample included 104 brain donors exposed to RHI from the UNITE brain bank. Clinical MRIs were obtained through medical record requests. A stroke neurologist used established visual rating scales (0=no ePVS, 4= >40 ePVS) to rate ePVS in the centrum semiovale (CS‐ePVS) and basal ganglia (BG‐ePVS) on axial T2 (n=11, 10.6%) or T1 (n=93, 89%). ePVS were coded as low (1/2) or high burden (3/4). Neuropathological diagnoses were made using established criteria. Years of football served as a proxy for duration of RHI. Antemortem dementia diagnoses were made through consensus conferences. Regression‐based analyses tested the association between ePVS with years of football play, various neuropathologies, dementia status and FAQ. Analyses controlled for years from MRI scan to death.

Result

Sample characteristics are in Table 1. The most common pathological diagnosis was CTE (n=71, 68%). 34 (32.7%) and 13 (12.5%) had high CS‐ePVS and BG‐ePVS burden, respectively. More years of football play was associated with greater CS‐ (OR=1.12, 95% CI=1.03‐1.22, p=0.01) and BG‐ePVS (OR=1.12, 95 CI=1.01‐1.24, p=0.03). Effect sizes remained when age at MRI was included for both CS‐ and BG‐ePVS (OR=1.09) but statistical significance was diminished. Greater CS‐ePVS was associated with more severe CTE, arteriosclerosis, atherosclerosis, cerebral amyloid angiopathy and Lewy body disease (Table 2). BG‐ePVS was only associated with arteriosclerosis. Greater CS‐ePVS were associated with increased odds for having dementia diagnosis (OR=5.41, 95% CI=1.42‐20.54, p=0.01). Clinical and pathological correlations were not statistically significant when age at MRI was included.

Conclusion

Enlarged PVS might be long‐term MRI consequences of exposure to RHI, but their age independent pathological and clinical correlates in this setting remain uncertain.
The Cerebellum Plays a Protective Role in Cognitive Aging and Disease: Insights from a Multi‐Cohort Study
Authors: Uquillas Federico d’Oleire , Sefik Esra , Seidlitz Jakob , Merriman Jewel , Zhang Veronica , Kislin Mikhail , Cohen Jonathan D , Alexander‐Bloch Aaron , Bethlehem Richard A.I. , Sepulcre Jorge , Wang Samuel S.‐H. , Vannini Patrizia , Gomez Jesse ,   the Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

Background

Studying brain reserve — the brain’s resilience to age‐related changes or damage — is crucial for understanding protective mechanisms against cognitive decline. The cerebellum may be a key region in brain reserve, but it has been historically understudied. This investigation delves into this critical area within the largest aging multi‐cohort to date.

Methods

Data were sourced from the Human Connectome Project‐Aging (n=708, 36‐100yrs), UK Biobank (n=45,013, 44‐81yrs), and ADNI (n=1,441, 56‐95yrs). ADNI participants were cognitively normal, had mild cognitive impairment, or Alzheimer’s disease (AD) dementia. We examined associations between cerebellar tissue volume, age, Montreal Cognitive Assessment (MOCA) scores, global PET amyloid burden, and APOE genotype. Statistical models included sex and estimated intracranial volume (eTIV) as covariates, with adjusted household income considered when available.

Results

Spatial analysis of HCP‐Aging data revealed that aging unfolds heterogeneously across the cerebellum; posterior portions of the cerebellum (Crus I) showed greater effects than anterior regions (Lobule I‐III) (Bonferroni‐corrected, p<0.05). MOCA scores were associated with higher tissue density in the cerebellum (p<0.0001), as much as neocortex, and MOCA scores coupled most strongly with posterior cerebellar cortex, overlapping frontoparietal, ventral attention, and default mode network representations. Strikingly, greater volume in this MOCA‐related cerebellar cortex signature protected against aging‐related cognitive decline (p=0.029). We validate tissue aging results in the UK Biobank – again, posterior cerebellum demonstrated the greatest aging effect (p<0.0001), and individuals with greater cerebellar volumes showed less decline in processing speed and executive function (Trails Making‐B time: p=0.001; Digit Symbol Substitution score: p=0.038). Across all ADNI diagnostic groups, AD patients with low amyloid‐beta burden (Aβ‐) exhibited the strongest cerebellar association with MOCA (volume x group, Aβ‐ AD: p=0.00004). In Aβ‐ individuals, APOE genotype interacted with cerebellar volume on MOCA, with ε4/ε4 carriers showing the greatest effect (volume x APOE, ε4/ε4: p=0.017).

Conclusions

Our large‐scale study demonstrates the cerebellum’s critical role in mitigating patterns of cognitive decline. This protection persists until significant amyloid burden, especially in APOE ε4/ε4 carriers, reshaping our understanding of reserve and AD risk. The cerebellum’s integral contribution to brain reserve has substantial implications for aging populations and should be a focus of future clinical research.
Does the association between white matter hyperintensity severity and Alzheimer’s disease indicate a primary role of cerebrovascular disease in Alzheimer’s disease pathogenesis?
Authors: Brickman Adam M.
Published: January 2025

White matter hyperintensities (WMH) are areas of increased lucency visualized on T2‐weighted magnetic resonance imaging (MRI), including fluid attenuated inversion recovery (FLAIR) sequences. Over the past 15 years we have been examining WMH in studies of cognitive aging among clinical, community‐based, and populations at genetic risk to understand the role of vascular brain injury in Alzheimer’s disease (AD) onset, symptom progression, and pathogenesis. Our findings suggest that regional WMH, particularly when distributed in posterior areas, increase risk for clinical AD and contribute to the clinical course of the disease, even among genetic population with relatively low rates of vascular risk factor, like adults with Down syndrome and with autosomal dominant genetic mutations for AD. While these observations suggest a role of endogenous cerebrovascular disease as a driver or core feature of AD, there has been considerable discussion about the underlying pathophysiology of WMH. Some authors argue that WMH in the context of AD reflect white matter changes secondary to neurodegeneration (so‐called “Wallerian degeneration”). We have argued against this possibility based on four observations. First, experimental data from animal models of vascular brain injury suggest that hypoperfusion injury gives rise white matter injury and downstream tau pathology and neurodegeneration. Second, the anatomical distribution of WMH in AD more closely aligns with the brain’s perfusion patterns and the vulnerability of whatershed regions to changes in blood supply and small vessel injury than with proximity to cortical neuronal injury. Third, the temporal evolution of WMH in the context of AD suggests a contribution of WMH that precedes expected neurodegenerative changes. Finally, we do not view an observed relationship between WMH and risk factors, such as hypertension, as a requirement to establish a cerebrovascular basis of WMH; rather, in total, findings suggest an “endogenous” cerebrovascular component, perhaps mediated by inflammatory changes, genetics, or blood brain barrier breakdown. Understanding the pathophysiological basis of WMH with respect to underlying vasculature may point to novel directions for disease prevention or intervention.
Intelligent dementia friendly environment: A Preliminary Study on the Feasibility of Integrating Assistive Humanoid Robots, Wearable Sensors, and Spatial Technology for maintaining quality of life
Authors: Khan Arshia A , Das Rupak Kumar , Imtiaz Rana Z
Published: January 2025

Background

Integrating humanoid robots, wearable sensors, and spatial technology into an intelligent dementia‐friendly living space is crucial for tailoring personalized and supportive environments, thereby addressing the unique needs of individuals affected by dementia and maintaining quality of life.[1‐10].

Methods

We programmed Pepper, a humanoid robot, for independent verbal communication to interact, tell jokes, and offer medications. To validate our assistive robot integrated with a sensor‐based system, we built a specifically designed living space optimized for sensor functionality and conducted a 90‐minute study involving 32 healthy participants. The participants performed various activities after consenting, filling pre and post‐experiment surveys and pre, during, and post‐sensor readings. The activities comprised of administration of a placebo sugar pill by the robot, treadmill exercises following the Bruce submaximal treadmill protocol, engagement in cognitively stimulating activities, wandering detection using spatial sensors, media presentation to induce higher arousal state, performance of some daily tasks such as preparing short meals, folding towels, cleaning the floor, and an interaction with the robot. These activities aimed to assess sensor functionality, simulate real‐world scenarios, and monitor physiological responses during various tasks, contributing to the evaluation of the integrated sensor system.

Various physiological data, including Electrodermal Activity (EDA), blood pressure, and Electrocardiogram (EKG), were gathered using distinct wearable sensors throughout the experiment. To gauge the subjective experiences of participants, two surveys were employed: the Presentation survey, conducted during the International Affective Digital Sound (IADS) presentation, and the Post‐Study survey, distributed on paper after the study’s completion.

Results

By incorporating pressure sensors in chairs and the robot’s emotion detection system, participants' moods were accurately assessed, aligning with self‐reported moods in 95% of cases. Furthermore, door sensors consistently identified exiting behavior, and wall‐mounted PIR sensors successfully recognized wandering behavior. Wearable sensors, such as EDA and blood pressure sensors, in conjunction with robot interactions, detected physiological changes during diverse activities, with the most notable impact observed during interactions with the robot.

Conclusion

The findings suggest that an intelligent living space specifically designed for dementia care can effectively preserve the quality of life for affected individuals, particularly through robot interactions, showcasing promising effectiveness.
Identifying Five Dominant Dimensions of Neurodegeneration in Brain Aging through Deep Learning: Correlations with Clinical and Genetic Measures
Authors: Yang Zhijian , Wen Junhao , Erus Guray , Davatzikos Christos ,   the iSTAGING consortium
Published: January 2025

Background

Brain aging is a complex process influenced by various genetic, lifestyle, and environmental factors, as well as by age‐related and often co‐existing pathologies. MRI and AI methods have been instrumental in understanding neuroanatomical changes that occur during aging in large and diverse populations.

Method

We leveraged Surreal‐GAN, a state‐of‐the‐art deep representation learning method, to elucidate the heterogeneity of brain aging by deriving dominant dimensions (patterns) of brain changes and examining their associations with various clinical and genetic factors. Our analysis utilized structural MRIs, clinical variables, and imputed genotype data from a diverse cohort of 49,482 individuals across 11 studies.

Result

Surreal‐GAN identifies five dominant dimensions of neurodegeneration in brain aging: R1, subcortical atrophy; R2, MTL atrophy; R3, parieto‐temporal atrophy; R4: diffuse cortical atrophy; and R5: perisylvian atrophy (Figure 1a). Individuals express varying but non‐exclusive levels of these patterns, quantified by respective R‐indices. The five R‐indices demonstrate positive correlations with each other, with R5 showing the strongest associations with white matter lesion volumes (WMH) and chronological age (Figure 1bc). Clinically, MCI/dementia participants exhibit significantly advanced R‐indices, particularly in R2, R3, and R5. Schizophrenia and Parkinson’s disease participants demonstrate severe aging effects in R3. R5 is associated with neuropsychiatric diseases and other chronic conditions (Figure 2a). Among the dementia‐associated dimensions, R2 displays stronger associations with memory impairment, while R3 is more closely associated with executive dysfunction (Figure 2b). In contrast to R2 and R3, R5 reveals weaker associations with amyloid and tau, but stronger associations with various other CSF biomarkers related to hemostatic and inflammatory mechanisms (Figure 2c). Genetically, GWAS identifies 73 genomic loci significantly associated with R1‐5 (Figure 3a). Previously identified SNPs correlate with various relevant clinical traits, including R5 loci that show associations with cardiovascular and neuropsychiatric conditions and WMH (Figure 3b). Additionally, the R1 dimension correlates with a gene set linked to the response to cortisol.

Conclusion

This study characterized the neuroanatomical heterogeneity related to the aging process by offering a 5‐dimensional representation system with five distinct brain signatures. It elucidates connections to demographics, pathology, and genetics, offering potential for personalized diagnostics, improved patient management, and enhanced precision in clinical trials.
The first year of amyloid immunotherapy in an academic dementia specialty practice
Authors: Paczynski Madeline , Schindler Suzanne E. , Musiek Erik S. , Holtzman David M. , Benzinger Tammie L.S. , Dow Alan , Namazie‐Kummer Sheyda J , Posey Zachary J , Woodfin Carson , Ellington Dawn , Morris John C. , Snider B. Joy
Published: January 2025

Implementation of amyloid‐lowering treatments in clinical care for early symptomatic Alzheimer disease (AD) raises many challenges. The Memory Diagnostic Center (MDC), the dementia specialty practice associated with Barnes‐Jewish Hospital/Washington University School of Medicine (BJH/WUSM), has 16 clinicians (12 physicians and 4 advanced practice providers) who see over 2,000 patients with memory disorders per year. BJH is the academic flagship of BJC HealthCare (BJC), an integrated health system in St. Louis, Missouri. Leadership of BJC/WUSM and MDC staff met regularly for two years in anticipation of amyloid‐lowering treatments becoming available. BJC/WUSM decided not to offer aducanumab (Aduhelm®) but did approve use of lecanemab (Leqembi®) after it received FDA approval in July 2023. Providing amyloid‐lowering treatments required coordination with BJC administration, neuroradiology, infusion centers and the clinical practice. Patients meeting appropriate use criteria were identified prior to approval of lecanemab. The requirement for AD biomarkers led to an increase in referrals to our lumbar puncture clinic prior to ∼30/month; there was less increase in referrals for AD blood tests or amyloid PET scans. The first patient received lecanemab within 6 weeks of FDA approval. Barriers to treatment included limited availability of appropriate MRI imaging, lack of reimbursement for AD blood tests and amyloid PET, limited capacity of infusion centers, and issues with private insurers. The MDC developed an on‐call system for response to infusion reactions and other adverse events and a tracking system for infusions and monitoring MRIs. We are developing registries and mechanisms in the electronic medical record to alert Emergency Department providers that patients on lecanemab being evaluated for stroke could be at increased risk of bleeding from thrombolytic therapies. Increasing capacity for patient assessments, biomarker testing, infusions, and follow‐up appointments has required adding advanced practice providers and office staff and presents challenges for reimbursement. As of January 2024, 80 MDC patients had received at least one lecanemab infusion and about 30 are undergoing evaluation to initiate treatment. Ongoing challenges include extending amyloid immunotherapy beyond the academic medical center, which will require training neurologists throughout the BJC system and developing sustainable staffing and billing models for management of amyloid‐lowering treatments.
Detection of Amyloid Status and Preclinical Alzheimer's Disease Using Cognivue Clarity, An Adaptive Psychophysics Computerized Cognitive Battery in The Bio‐Hermes Study
Authors: Galvin James E , Kleiman Michael J , Estes Paul W. , Harris Heather M. ,   Cognivue, Inc.
Published: January 2025

Background

An easy and reliable method for detection of Alzheimer's Disease (AD) and mild cognitive impairment (MCI) is critical for clinical trial enrollment. In the era of amyloid‐lowering therapies, there is a need to identify individuals likely to have amyloid to enrich recruitment and lower costs related to amyloid PET. In addition, a subset of cognitively normal individuals have amyloid deposition (Preclinical AD) but to date there is no cognitive assessment or screening method that can detect these individuals in the absence of expensive biomarkers. Cognivue Clarity is an adaptive psychophysics computerized cognitive assessment generating a global score and 10 subtest scores.

Methods

As part of the Bio‐Hermes study, sponsored by the Global Alzheimer’s Platform Foundation, Cognivue Clarity was administered to 964 individuals who also had amyloid PET, plasma amyloid and tau measures, ApoE genotyping, MMSE, Functional Activities Questionnaire (FAQ), and Rey Auditory Verbal Learning Task (RAVLT). Cognivue Clarity performance was compared between (1) clinically‐defined, (2) biomarker‐defined, and (3) clinicopathological‐defined groups.

Results

The sample had a mean age of 72.0 ± 6.7y, 15.5 ± 2.7y education, 55.9% females and 23.0% individuals from underrepresented groups. Clinical groups included 42.8% Healthy, 31.6% MCI, and 25.5% Probable AD. Amyloid PET was positive in 62.7%. Clinicopathological groups included 33.5% Healthy, 10.3% Preclinical AD, 27.2% MCI/AD, and 29.1% non‐AD. While Cognivue, MMSE, FAQ, and RAVLT scores were different between impaired vs unimpaired and amyloid positive vs amyloid negative individuals, only Cognivue Clarity was different between Healthy vs Preclinical AD (p=.009). Three subtests [Shape Discrimination (p=.002), Visual Salience (p=.005), Adaptive Motor Control (p=.004)] and their mean (p<.001) differentiated True Controls from Preclinical AD with an area under the curve of 0.634 (95%CI:0.570‐0.698, p<.001) and were moderately correlated with Amyloid PET Centiloid (r=‐.308) and pTau217 (r=‐.315). ApoE carriers had lower scores than non‐carriers (p=.02).

Conclusions

Cognivue Clarity, a 10‐minute computerized cognitive battery, can detect individuals with cognitive impairment and identify individuals likely to have amyloid positivity. Cognivue Clarity is the first test able to identify individuals with Preclinical AD. This has great potential as an enrichment strategy for AD clinical trials testing amyloid‐lowering therapies and AD prevention.
Progression of functional brain complexity in longitudinal Alzheimer's diseases
Authors: Zhang Ru , Aksman Leon M. , Wijesinghe Dilmini , Ringman John M , Wang Danny JJ , Jann Kay
Published: January 2025

Background

Reduced complexity of resting‐state fMRI has been associated with mild cognitive impairment (MCI) and Alzheimer's diseases (AD) in cross‐sectional cohorts. However, the trajectory of complexity in AD progression remains unknown. We conducted complexity analyses in a longitudinal AD dataset.

Method

We used demographic, clinical, T1 structural, and resting‐state fMRI (rsfMRI) data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The final sample included 210 subjects in Group CN (remaining cognitively normal), 27 subjects in Group CNtoMCI (converted from CN to MCI), and 32 subjects in Group MCItoAD (converted from MCI to AD). The three groups matched in terms of sex, education, and age of their first rsfMRI scan (Table 1).

Standard image preprocessing was performed in the CONN toolbox. Multiscale entropy (MSE) for number of temporal scales a = 6 (0.33‐0.05Hz) was computed for each of fourteen meta regions of interest (meta‐ROIs). The area under a curve across all scales was calculated to reflect complexity for each meta‐ROI.

A linear mixed effects (LME) model was implemented to evaluate group differences in complexity and altered rates of progression of complexity across groups.

Result

The LME model revealed significantly lower rsfMRI‐complexity in Group MCItoAD as compared to Group CN in the prefrontal, cingulate, and insula (t = ‐3.019 to ‐2.669, p = 0.003 to 0.008, Benjamini‐Hochberg (BH) corrected with false discovery rate < 0.05, Figure 1(A), 1(C), & Table 2). Additionally, rsfMRI‐complexity decayed significantly faster in Group CNtoMCI than in Group CN in the prefrontal, superior frontal, inferior frontal, lateral temporal, and medial temporal lobe (t = ‐2.417 to ‐2.093, p < 0.05, uncorrected, Figure 1(B), 1(D), & Table 2). By contrast, complexity decayed significantly faster in Group MCItoAD relative to Group CN only in the prefrontal (t = ‐2.338, p < 0.05, uncorrected, Figure 1(B), 1(D), & Table 2).

Conclusion

The affected regions were mainly the frontal and temporal cortices which was consistent with the hypothesis of decline in executive functions and memory in AD. It demonstrates the potential of complexity analysis as an early AD biomarker.
Predicting cognitive function from multimodal mesoscale neuroimaging data
Authors: Duchesne Simon , Potvin Olivier , Dieumegarde Louis
Published: January 2025

Background

Our objective was to assess individual and joint relationships between various mesoscale indicators of brain health (e.g., neuronal, metabolic, and vascular integrity) and cognitive function.

Method

We used 7224 timepoint measures originating from 1825 participants of the ADNI study who were cognitively healthy or with mild cognitive impairment at initial assessment. Cognitive function outcomes were test results on the Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS‐Cog), the Rey auditory Verbal Learning Test immediate recall (RAVLTi), the Rey auditory Verbal Learning Test delayed recall (RAVLTd), the Trail Making Test A (Trail a), and the Trail Making Test B (Trail b) tasks. Four families of markers were used. First were three families of mesoscale neuroimaging assessed by MRI for 88 brain regions: 1. Neuronal integrity was estimated by FreeSurfer 6.0 produced volumes extracted from T1‐weighted (T1w) images; 2. Neurite integrity was estimated through T1w/T2‐weighted MRI ratios; 3. Cerebral metabolism integrity was measured by synthetic fluorodeoxyglucose‐positron emission tomography, generated by a model based on a latent‐space regularized generative adversarial net from T1w MRIs. Secondly, 4. Systemic markers of vascular health‐related factors were included in the model (history of cardiovascular diseases, alcohol abuse, smoking history, systolic and diastolic blood pressure, history of hypertension, type 2 diabetes, Hachinski score).

Cross‐sectional and future cognitive outcomes were all predicted in a single machine learning model using all combinations of predictor families at baseline, time interval between outcomes and baseline as long as sex and education. Three types of regression models were tested (Ridge, Partial Least Squares and Support Vector).

Result

Individually, neuronal and metabolism integrity were the best predictors of cognitive function (Figure 1; R2: .15‐.35 and MAE in Z score: .08‐.23). The combination of two or more mesoscale brain health markers improved predictions, with the best combination being neuronal integrity with metabolism (Figures 2‐3; mean R2: .28; mean MAE: .12). However, increasing the number of markers led to similar results.

Conclusion

While the prediction of cognition improved with a combination of brain health mesoscale markers, a plateau seems to be reached after combining two families.
PTPRS is a novel marker for early tau pathology and synaptic integrity in Alzheimer’s disease
Authors: Poirier Alexandre , Picard Cynthia , Labonté Anne , Aubry Isabelle , Auld Daniel L. , Zetterberg Henrik , Blennow Kaj , Tremblay Michel L. , Poirier Judes
Published: January 2025

Background

Synaptic dysfunction is a central pathologic feature of Alzheimer’s disease (AD), with synaptic loss even preceding neuronal loss in specific brain regions. In healthy individuals, synaptic function and plasticity are orchestrated through the complex integration of signaling inputs generated by cell surface receptors.

Methods

In this study, we investigate the role of one such receptor, protein tyrosine phosphatase receptor sigma (PTPRS), in the context of Alzheimer’s disease. Publicly available datasets (BRAINEAC, ROSMAP, ADC1) and a cohort of asymptomatic but “at risk” individuals (PREVENT‐AD) were used to explore the relationship between PTPRS and various Alzheimer’s disease biomarkers.

Results

We identified that PTPRS rs10415488 variant C shows features of neuroprotection against early phospho (181)‐tau pathology (p<0.005) and synaptic degeneration (GAP‐43, p<0.001) in Alzheimer’s disease. In brain tissues, PTPRS protein abundance was significantly correlated with the quantity of two markers of synaptic integrity: SNAP25(R2=0.20, p < 0.0001) and SYT‐1(R2=0.12, p < 0.0001). We also found the presence of sexual dimorphism for PTPRS, with higher CSF concentrations in males (p<0.001) than females. Male carriers for variant C exhibit a 10‐month delay in the onset of AD (p <0.05). One molecular function of PTPRS we chose to explore is macrophagy, given the implication of this biological process in the response against neurodegeneration. Macrophagy‐associated LC3 immunoreactivity occurs in most dystrophic neurites in AD and co‐localized with abnormal P‐tau in most neurofibrillary tangles. In the ROSMAP subjects, LC3 cortical protein levels were found to be significant reduced in C carriers

Conclusions

PTPRS acts as a soluble, secreted neuroprotective receptor, found in the extracellular space in Alzheimer’s disease. These findings also highlight the functional importance of synaptic plasticity in the protection against neurodegenerative diseases.
Metabolic Dysfunction and Alzheimer’s Disease Risks in African Americans
Authors: Mondal Tanmoy , Johnson Jheannelle , Sur Tapas Kumar , Loffredo Christopher A. , Cotin Sharleine T. , Sahota Jasneet , Korbe Brent E. , Nunlee‐Blnad Gail , Ghosh Somiranjan Ghosh
Published: January 2025

Background

Metabolic diseases like chronic Type 2 Diabetes Mellitus (T2DM) are now a serious global health concern In the United States. African Americans (AA) are being affected at a disproportionate rate with the condition compared to other ethnic groups, yet there are relatively few studies that have specifically focused on this group. Our previous findings have suggested that AA patients with T2DM had gene expression signals associated with Alzheimer’s Disease (AD). The current pilot study aimed to examine the amyloidogenic processing pathways (APP) and cholesterol biosynthesis‐related marker genes in the circulation of clinically identified T2DM AA patients in the Washington DC area.

Method

A total of 12 confirmed T2DM AA patients and matched healthy controls were recruited from a regional hospital's outpatient departments, with sociodemographic and medical details obtained for analysis. Whole blood was collected in DNA/RNA Shield™ Blood Collection Tube for RNA extraction and isolation. The APP and cholesterol biosynthesis‐related gene expression patterns were examined using profiler array gene expression (qRT‐PCR). The affected pathways were identified using Ingenuity Pathway Analysis (IPA).

Result

We identified Amyloid Processing, Neuroinflammation Signaling, ERB4 Signaling, Interleukin signaling, and nNos signaling as the top canonical pathways. The top diseases and their functions were Metabolic disease, Neurological disease, Organismal Injury and Abnormalities, Psychological disorders, and cardiovascular diseases. APP, CDK5R1, PSENEN, and MAPT were the key genes that were differentially expressed (≥2‐fold change at p <0.05) in APP pathways, with PHLPP2, IL33, APP, CRP, & TAC1 as the top upstream regulators.

Conclusion

The results suggest that T2DM may influence the risk of developing AD in AA patients. Further studies on larger multi‐ethnic populations would be of interest to validate and extend these findings. Information from such biochemical and genetic studies will be crucial to the development of therapeutic targets to assess future AD risks.
Inflammatory Architecture of Frailty in the Realm of Alzheimer's Disease and Related Dementias
Authors: Chen Jiachen , Doyle Margaret F , Cao Yumeng , Ragab Ahmed , Murabito Joanne M , Lunetta Kathryn L.
Published: January 2025

Background

As a risk factor for Alzheimer's disease and related dementias (ADRD) in older adults, inflammatory mechanisms underlying physical frailty remain incompletely elucidated. This study aimed to characterize the inflammatory architecture of frailty and explore predictive implications of inflammatory signatures of frailty on ADRD.

Method

The study included 741 Framingham Heart Study Offspring cohort participants (52% female, mean 60 years range 40 to 85), dementia‐free at Exam 7 (1998‐2001), followed for incident dementia over 15.8 years on average. The sample was randomly split 50/50 into discovery and validation sets. A total of 209 circulating inflammatory markers including peripheral immune cells and inflammatory biomarkers were measured at Exam 7, with Fried frailty index assessed at Exam 8 (2005‐2008). Using frailty and its 5 components as outcomes, LASSO was conducted on inflammatory markers adjusted for covariates in discovery set. Inflammatory signatures were generated by summing the product of regression coefficients and marker levels for each participant. Pairwise associations between 6 signatures and incident dementia/AD were conducted by Cox models in validation set, with FDR ≤0.05 declaring significance.

Result

A total of 48 inflammatory markers were involved in signatures: 9 protein biomarkers (4E‐BP1, ADA, CCL3, CD40, CDCP1, HGF, IL‐10RB, IL‐12B, and IL‐17C) and 4 immune cells (CD4 T helper cells, CD4+FoxP3+, CD8+FoxP3+, and TREM2+ NCM) contributed to at least two signatures. In the validation set a handgrip‐strength‐specific signature was significantly associated with incident dementia (HR=0.50, 95%CI: (0.32, 0.76), FDR=0.01) and incident AD (HR=0.44, 95%CI: (0.25, 0.76), FDR=0.01), a walking speed‐specific signature was associated with incident dementia (HR=14.30, 95%CI: (3.67, 55.73), FDR=<0.01) and incident AD (HR=13.95, 95%CI: (2.65, 73.49), FDR=0.01). An unintended weight loss‐specific signature was significantly associated with incident dementia (HR=3.45, 95%CI: (1.09, 10.94), FDR=0.05), and exhaustion‐specific signature was associated with incident dementia (HR=4.12, 95%CI: (1.59, 10.69), FDR=0.01) and incident AD (HR=5.73, 95%CI: (1.84, 17.90), FDR=0.01), and overall frailty signature was associated with incident dementia (HR=2.33, 95%CI: (1.13, 4.84), FDR=0.04) and incident AD (HR=2.82, 95%CI: (1.08, 7.37), FDR=0.05).

Conclusion

Frailty‐implicated signatures unveil inflammatory markers related to the biology of frailty and ADRD. Future replication studies are needed to inform ADRD prediction signatures.
PhysicOmics: Combining MR physics, proteomics, and transcriptomics to study cerebral aging and neurodegeneration
Authors: Bae Jonghyun , Gong Zhaoyuan , Guo Alex , Laporte John P , Faulkner Mary E , Bouhrara Mustapha
Published: January 2025

Background

Neuroimaging‐based evidence suggests that changes in cerebral tissue determinants, including axonal density and myelin content, are associated with aging and neurodegenerative diseases. While neuroimaging markers show strong association with physiological changes, direct validation of their specificity remains challenging. Histology provides useful information for validation, however, faces limitations including denaturation of the sample during preparation. However, in the era of omics, validation of neuroimaging markers becomes accessible with dataset from various biological measurements. We provide two examples of validations of our MR physics‐based markers of myelin water fraction (MWF), a surrogate of myelin content, and neurite density index (NDI), a proxy of axonal density, using proteomics and transcriptomics (Figure 1).

Method

Association between neurofilament light chain (NfL) and NDI:

58 participants (age=21‐83yrs.) underwent our multishell diffusion imaging protocol for NDI determination using C‐NODDI. Blood was collected at the time of MRI to quantify the NfL level, a biomarker of axonal integrity, using Simoa assays. The association between NDI and NfL was evaluated using a multiple linear regression analysis.

Association between myelin gene expression and MWF:

132 subjects (age=22‐94yrs.) underwent our relaxometry protocol for MWF determination using BMC‐mcDESPOT. Further, microarray data were obtained from the Allen Human Brain Atlas, providing gene expression data from 6 healthy donors. Using Pearson correlations, we assessed the association between regional MWF measurements (averaged across participants) and regional gene expressions, with a focus on Myelin Basic Protein (MBP) and transcription factors involved in myelin synthesis.

Result

Figure 2 shows strong negative regional correlations between NfL and NDI derived using C‐NODDI. Further, we found strong positive correlations between MWF and genes involved in myelin production (Figure 3).

Conclusion

Given the strong correlations between NfL or MBP and NDI or MWF, this work provides evidence of the specificity of these MRI biomarkers of axonal density and myelin content, making C‐NODDI and BMC‐mcDESPOT powerful and relevant MR methods for clinical investigations and trials. While further investigations are still required in the context of neurodegeneration, our work demonstrates the potential of combining MR physics and omics to delve deeper into the neurobiological and molecular mechanisms underlying aging and age‐related diseases.
Long‐Term Impact of Amyloid PET in Memory Clinic Diagnostic Workup: A Matched Cohort Study on Healthcare Costs, Institutionalisation, and Mortality Risk
Authors: van der Veere Pieter J. , Broulíková Hana M. , Hoogland Jeroen , van Harten Argonde C. , van Maurik Ingrid S. , van de Giessen Elsmarieke , Berkhof Johannes , van der Flier Wiesje M.
Published: January 2025

Background

We hypothesise that improved diagnostic precision, operationalised by adding amyloid positron emission tomography (PET) to the diagnostic work‐up in a memory clinic, is beneficial for long‐term health and healthcare cost outcomes. We investigated whether a more precise diagnosis influenced institutionalisation and mortality incidence trajectories, and annual healthcare costs over a period up to eight years.

Method

Between October 2014 and December 2016, patients from the Amsterdam Dementia Cohort were offered an amyloid‐PET as part of their diagnostic work‐up. Those who received an amyloid‐PET were propensity‐score matched to participants without a PET, creating two balanced groups containing 442 patients each (Table 1; 64±8yrs, 40%F, 43% dementia). Statistics Netherlands provided healthcare costs for six years, institutionalisation for seven years, and mortality data for eight years of follow‐up. Institutionalisation and mortality incidence were calculated, and mean costs were bootstrapped. Healthcare costs were first evaluated as annual total cost and subsequently disaggregated into the following categories: primary care, hospital‐related care, mental health care, aid products, medication, homecare, and institutionalisation.

Result

The amyloid‐PET and no‐PET groups had distinct institutionalisation and mortality incidence trajectories (Figure 1). The difference in institutionalisation was most pronounced three years after the diagnosis with 11% institutionalisation in the amyloid‐PET group (95% confidence interval [CI]: 8%‐14%, n=50), compared to 20% in the no‐PET group (15%‐25%, n=95, p=0.002). Subsequently, the difference attenuated to 28% (24%‐33%, n=118) vs. 33% (27%‐38%, n=135, p=0.28) after six years. Mortality incidences started to converge after four and merged after six years. Annual healthcare costs were €3968 (CI:1177‐6942, Table 2) lower in the amyloid‐PET group. This difference was mostly attributable to the categories of institutionalisation costs (€‐3361; CI:‐5929 to ‐918) and primary care (€‐99; CI:‐195 to ‐7).

Conclusion

A more precise diagnosis through an amyloid‐PET positively influenced the incidence trajectories of institutionalisation and mortality, with the largest differences observed in the first three to four year after the diagnosis. Our findings suggest a more precise diagnosis could lead to more efficient and tailored primary care and to postponed institutionalisation. Less time spent in institutional care was also identified as a main driver of lower healthcare costs.