bluuebunny/crossref_metadata_2025 huggingface dataset:
The association between IGF‐1 plasma levels and Alzheimer's disease in the Alzheimer’s Disease Neuroimaging Initiative study
Authors: Ross Jermaine , Cha Yoonjeong , Kagalwala Mohamedi
Published: January 2025

Background

Insulin‐like Growth Factor‐1 (IGF‐1) and its receptor (IGF‐1R) are known to play a role in biological aging. Several studies have explored the correlation between serum levels of IGF‐1 and Alzheimer's‐related dementia (AD). However, conflicting reports exist regarding whether elevated or reduced IGF‐1 levels increase the risk of AD. The focus of this study is to investigate the relationship between IGF‐1 and AD participates in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study.

Methods

We analyzed calculated readouts from biomarkers assessed in the study performed by Biomarkers Consortium Plasma Proteomics Project and made available in the ADNI online repository. The study analyzed plasma samples taken from ADNI participants at baseline and 12 months after enrollment. The samples were processed using a 190‐analyte multiplex immunoassay panel, which included a plasma readout for IGF‐1, measured in ng/mL for all 556 subjects. A Cohen's kappa value was calculated to determine an optimal cutoff for distinguishing AD cases compared to controls. A standard t‐test was performed to assess significance between groups.

Result

At baseline, univariate analysis using a t‐test revealed a significant increase in IGF‐1 plasma levels in AD subjects compared to cognitively normal controls (p < 0.05). We also observed higher IGF‐1 levels in mild cognitive impairment (MCI) subjects compared to controls (p < 0.05). There was no significant difference between MCI and AD subjects. These findings are consistent with previous reports showing higher levels of IGF‐1 in animal models of AD, including transgenic mice expressing mutant human amyloid precursor protein and presenilin‐1. The optimal cutoff that maximizes Cohen's Kappa is >9.8 ng/mL of IGF‐1. In contrast, we did not observe any notable difference in IGF‐1 levels in either AD vs normal or MCI vs normal comparisons after 12 months, suggesting a potential temporal nature of the biomarker.

Conclusions

In this study, we found a significant but transient relationship between IGF‐1 and Alzheimer’s‐related dementia. Given current focus on the development of blood‐based biomarkers, these results highlight a putative biomarker for stratifying Alzheimer’s risk, but additional work is required to understand the temporal aspect of IGF‐1 during disease progression.
Development and Preliminary Feasibility of a Translatable Volumetric Brain Age Metric
Authors: Kress Gavin T , Iglesias Juan Eugenio , Cole James H. , Popa Emily S. , Siddarth Prabha , Bramen Jennifer E.
Published: January 2025

Background

Brain aging (BA) involves the gradual deterioration of brain systems and is associated with chronological age (CA). Measures of BA have been validated and adopted in aging and neurological disease research (Biondo, 2022; Eickhoff, 2021) and could be a useful clinical tool. BA predicts CA in healthy adults (Cole, 2017) and accelerated BA precede Alzheimer’s disease (AD) symptoms (Elliott, 2021). Current BA estimations rely on the acquisition of high‐quality neuroimaging data and complex, computationally expensive analysis workflows, creating obstacles for clinical translation. This study aims to develop an easily implementable workflow for BA where inputs are clinically relevant features derived from heterogeneously acquired magnetic resonance imaging (MRI) using the SynthSeg tool.

Method

Thirty‐two regional volumes from T1‐weighted MRIs from 56,505 participants (mean age=63.6; 44‐82; SD=7.52) were segmented using the SynthSeg tool. This tool analyzes clinically acquired, heterogenous inputs and requires minimal processing power, memory, and time. Only z‐transformed SynthSeg‐derived measures were included to allow investigations into confounds. Performance evaluation included three filter‐based feature selection approaches (Fischer’s Score, Information Gain, and Correlation Coefficient) combined with seven machine learning (ML) algorithms including linear regression (LR), 2nd‐order polynomial regression (2PR), Gaussian process regression (GPR), Decision Tree (DT), Random Forest (RF), a Convolutional Neural Network (CNN) treating age as a continuous variable, and as a categorical measure. Ability to predict CA was assessed through 10‐fold cross validation, each with an independent 90‐10 training‐testing split, and regression analysis between predicted and CA using an alpha=0.001.

Result

Feature selection demonstrated that each structural feature contained unique information for predicting CA. All seven ML algorithms significantly predicted CA (Table 1). 2PR performed the best overall with LR and GPR following closely behind (Figure 1). Both the categorical and numerical CNN performed slightly worse, but still significantly better than the RF and DT

Conclusion

The association between CA and volumetric‐BA estimates derived from SynthSeg segmented data supports the potential validity of this approach. However, its simplicity may increase translatability. Future directions of this work are to improve performance. The long‐term goal of this work is to develop and validate local volumetric‐BA (as opposed to global volumetric‐BA) metrics.
Free water is a sensitive predictor of future white matter lesions
Authors: Maillard Pauline , Fletcher Evan , Martinez Oliver , Singh Baljeet , Sandoval Francisco , Fan Audrey P. , Farias Sarah Tomaszewski , Decarli Charles
Published: January 2025

Background

Cerebrovascular disease features as the most common comorbidity in older individuals with dementia. White matter (WM) injury identified through white matter hyperintensities (WMH) on FLAIR represents evident late‐stage pathophysiological manifestations of CVD. This study aims to assess the role of baseline microstructural WM integrity, using free water (FW), a measure from diffusion tensor imaging (DTI), in predicting WMH growth dynamic.

Methods

Our study includes 271 individuals (age: 76±7, 60% female) from the UCD ADRC longitudinal cohort who underwent an MRI exam at two different date (mean time±SD: 2.7±1.2 years). We tracked individual lesions between baseline and follow‐up. Briefly, for each participant, distinct WMH region were labeled on their baseline and follow‐up scans, coregistered into the FSL template space. All lesions were then placed into three categories: 1) baseline WMH that do not get larger over time were labeled stagnant WMH, 2) baseline WMH that grow larger over time were labeled growing WMH, and (3) WMH identified only on follow‐up scans were labeled noncontiguous incident WMH. DTI‐derived mean signal of Free Water (FW) was computed for each individual WMH region at baseline, as well as within the normal appearing WM (NAWM). Using a linear mixed‐effect model, we investigated differences in baseline FW according each WMH tissue category and NAWM. Analyses were adjusted for age and sex.

Results

At baseline, FW signal was found to be lower within NAWM as compared with growing WMH (b=‐0.11, pvalue< 0.001, see Figure 1) and stagnant WMH (b=‐0.13, pvalue< 0.001), and also with incident WMH (b=‐0.096, pvalue< 0.001) suggesting that WM tissue where incident WMH are to emerge over time is already injured as compared to normal WM. Baseline FW for stagnant WMH was significantly higher than for growing (b=0.027, pvalue< 0.001) and incident WMH (b=0.038, pvalue< 0.001). Baseline FW for incident WMH was not found to be significantly different from baseline FW in growing WMH (b=0.011, pvalue=0.078).

Conclusion

Our results suggest that local FW measures predict the future incidence as well as the growth dynamic of lesions over time and emphasize the sensitivity of FW as a biomarker of early CVD‐related WM injury.
Association between blood biomarkers of vascular endothelial dysfunction and brain glucose metabolism in long COVID
Authors: da Silva Ana Paula Bornes , Machado Luiza Santos , Siebert Marina , Silveira Maiele Dornelles , Borelli Wyllians Vendramini , Senger Joana Emilia , da Ros João Pedro Uglione , Jotz Arthur Viana , de Mello Guilherme Bastos , Kadan Matheus Fakhri , Radaelli Graciane , Ferrari‐Souza João Pedro , de Bastiani Marco Antônio , Povala Guilherme , Matushita Cristina Sebastião , Soder Ricardo Benardi , Schumacher‐Schuh Artur Francisco , Pascoal Tharick A. , Souza Diogo O. , Lourenco Mychael V , de Paula Faria Daniele de Paula , Coutinho Artur Martins , daCosta Jaderson Costa , de Souza Débora Guerini , Zimmer Eduardo R.
Published: January 2025

Background

COVID‐19, identified as the greatest health concern of the century, is associated with vascular inflammation and endothelial activation, resulting in multisystemic damage, including to the central nervous system (CNS). Recent investigations indicate a link between endothelial dysfunction, neurological changes, and the development of the so‐called long‐COVID. Molecules expressed in the endothelium such as P‐selectin, E‐selectin, and VEGF‐A, increased under inflammatory injury, may be associated with conditions like brain injuries and neurodegenerative diseases. These markers may remain altered in the organism for months after the acute episode of COVID and may be related to long‐term neurological disorders. This study aims to identify associations between biomarkers of endothelial dysfunction and brain glucose metabolism in individuals with long‐COVID.

Methods

A total of 39 individuals presenting with long‐COVID and 10 healthy controls (HC) underwent brain [18F]FDG‐PET imaging. Standardized uptake value ratio maps were generated using the [18F]FDG‐PET global mean. Using an ELISA Multiplex assay, we measured P‐selectin, E‐selectin, and VEGF‐A in plasma samples. Voxel‐wise linear regressions models accounting for age, gender, and years of education were used to evaluate the association between the interaction biomarker*group and the brain glucose metabolism.

Results

The analyses showed that the interaction between P‐selectin and group presents positive association clusters in the right isthmus of the corpus callosum, thalamus, and left lingual gyrus (Figure 1). In this model, we also observed negative association clusters in the lingual gyrus bilaterally, the left inferior occipital gyrus, and the flocculonodular lobe (posterior cerebellum) (Figure 2). The linear regression analysis with the interaction between VEGFA or E‐selectin and group did not present a significant association with [18F]FDG‐PET signal.

Conclusion

The results provide preliminary insights into the complex interactions between endothelial dysfunction and cerebral glucose metabolism in long‐COVID. The regions presenting significant associations are involved in cognition, memory, sensory and motor function, language and visual processing, indicating a potential widespread brain vascular response. Additional studies are needed for a comprehensive understanding of these relationships in long‐COVID.
Early Identification of Alzheimer’s Disease with a Machine Learning‐Enabled Digital Cognitive Assessment: Concurrent Detection of Cognitive Impairment and Amyloid‐Beta PET Status
Authors: Jannati Ali , Thompson Karl , Toro‐Serey Claudio , Higgins Connor , Banks Russell , Showalter John , Bates David , Tobyne Sean , Pascual‐Leone Alvaro
Published: January 2025

Background

Maximizing the benefits of disease‐modifying treatments (DMTs) for Alzheimer’s disease (AD) requires early identification of cognitive impairment and abnormal brain amyloid‐beta (Aβ) status. Either one alone is insufficient. Additionally, clinical trials of DMTs are impeded by high screen failure rates and costly prescreening. Thus, an efficient and cost‐effective solution to streamline the process of early AD identification is urgently needed. This study aimed to assess the accuracy of a brief digital cognitive assessment, the Linus Health Digital Clock and Recall (DCR), to identify cognitive impairment and predict brain Aβ status.

Method

930 participants (mean age 72.0±6.7; 56.8% female; 23% minorities) in the Bio‐Hermes‐001 study were classified as cognitively unimpaired, mild cognitive impairment, or probable Alzheimer’s dementia, and 35.1% were Aβ+ on 18F‐florbetapir PET scan. A DCR‐based algorithm (LinusAD) used age, APOE status, drawing metrics, speech and acoustic features, and temporal‐spatial features of stylus manipulation. LinusAD was compared with MMSE and blood‐based biomarkers (BBMs) Lilly pTau‐217, Quanterix pTau‐181, C2N Aβ42/40, and C2N Amyloid Probability Score (APS). Superiority or non‐inferiority was established if 95% confidence interval of the bootstrapped AUC difference between two tests was higher than or within ΔAUC±0.1.

Result

Cognitive‐impairment identification by the DCR (AUC=0.85) was superior to Aβ42/40, pTau‐181, and pTau‐217 (AUCs=0.63, 0.66, 0.72) and non‐inferior to RAVLT and MMSE (AUCs=0.89, 0.82). Aβ‐status prediction by LinusAD (AUC=0.882) was equivalent to BBMs (AUC range: 0.775–0.887; average AUC=0.82) and superior to MMSE (AUC=0.71) (see Table and Figure). Combining the DCR with Aβ42/40, pTau‐181, and pTau‐217 improved their Aβ‐status prediction performance to AUCs of 0.882, 0.835, and 0.905, respectively.

Conclusion

The 3‐minute DCR was superior to BBMs in detecting cognitive impairment and boosted their Aβ‐PET prediction ability to levels comparable to CSF biomarkers of AD. Digital cognitive assessments that leverage AI process metrics, such as the DCR, enable cost‐effective integration into multi‐step clinical workflows to prioritize the most suitable patients for BBM testing, DMTs, and decrease high screen‐failure rates in AD clinical trials.
Psoas Muscle Sarcopenia Predicts Brain Volume Loss on MRI in 7,149 Individuals
Authors: Raji Cyrus A. , Meysami Somayeh , Hashemi Sam , Garg Saurabh , Akbari Nasrin , Gouda Ahmed , Chodakiewitz Yosef Gavriel , Nguyen Thanh Duc , Niotis Kellyann , Merrill David A. , Attariwala Rajpaul
Published: January 2025

Background

Sarcopenia has been linked to brain atrophy and there is lack of information on specific muscle groups that may contribute to this link. The psoas muscles are sensitive to sarcopenia and thus may sensitively relate to brain aging and Alzheimer disease risk.

Method

This study utilized 7,149 healthy individuals across four sites (Mean age 53.06 ± 12.95 years, age range 18‐97 years; 48% women; 52% men; 38% non‐white) were scanned on 1.5T MR machines with a whole‐body protocol. Whole body sequences included coronal T1 for segmentation of psoas muscle volumes. Deep learning with FastSurfer on 3D T1 volumetric MPRAGE trained on 134 participants aged 27‐66 segmented 96 brain regions. Partial correlation analysis was done on psoas muscle volumes and brain regions controlling for sex and total intracranial volume to determine if lower psoas muscle volumes correlated to brain atrophy. Multiple comparisons were accounted for using the Bonferroni Method.

Result

Lower psoas muscle volumes demonstrated a statistically partial correlation to lower gray matter (rp = ‐0.164, p = 2.66×10−43) and white matter volumes (rp = ‐0.171, p = 4.39×10−47). The frontal lobe exhibited a negative correlation (rp = ‐0.172, p = 1.30×10−47), identical to the temporal lobe (rp = ‐0.172, p = 1.21×10−47). Negative correlations were also noted in the parietal lobe (rp = ‐0.119, p = 8.72×10−23), and occipital lobe (rp = ‐0.139; p = 2.89×10−31). The hippocampus also showed a statistically significant negative correlation (rp = ‐0.145, p = 7.65×10−34), as did the posterior cingulate (rp = ‐0.162, p = 5.20×10−42) and the precuneus (rp = ‐0.101, p = 1.34×10−16). The cerebral ventricles showed a non‐significant negative correlation (rp = ‐0.025, p = 0.345).

Conclusion

We demonstrate a significant correlation between lower psoas muscle volume and brain volume loss, including AD risk regions such as the hippocampus and precuneus. These MRI findings underscore the importance of muscle health in relation to brain integrity. The volume of the psoas, which is involved in basic leg flexion activities such as walking, could be a crucial indicator of brain health and Alzheimer risk.
Immunomagnetic Separation and Magnetic‐Susceptibility‐Based Quantification of AD Biomarkers Using Ultra‐Magnetic Iron Oxide Nanorod Agent Magfiniti®
Authors: Li Yuancheng , Mao Hui , Padelford Jonathan , Ma Hedi
Published: January 2025

Background

Enriching and detecting Alzheimer’s disease (AD) biomarkers in cerebral spinal fluid (CSF) or blood samples are increasingly applied in the AD diagnosis and monitoring of disease progression and treatment response. The accuracy of these processes is dependent on the sensitivity and specificity of capturing and quantifying AD biomarkers, e.g., Aβ40 and Aβ42, in the samples. This report introduces a new immunomagnetic separation based biomarker detection system, which employs AD‐biomarker‐targeting peptide functionalized ultra‐magnetic iron oxide nanorods Magfiniti® to rapidly capture and separate AD biomarkers, coupled with measurement of change of the magnetic susceptibility upon capturing AD biomarkers.

Method

The colloidal stability over 24 hours and magnetic separation efficiency of Magfiniti® were determined using UV‐Vis spectroscopy. The capacity of Magfiniti® in avoiding non‐specific protein adsorption, with Dynabeads® as a control, was examined by incubating with human serum followed by quantifying adsorbed proteins. Synthetic γ‐AApeptides with proved targeting effect for Amyloid beta peptide 1‐40 (Aβ40) and 1‐42 (Aβ42) were conjugated to Magfiniti® for detecting Aβ40 and Aβ42 spiked in human serum (100 to 2000 pg/mL). After a 30‐min incubation with serum samples, γ‐AApeptide‐conjugated Magfiniti® with captured biomarkers were magnetically separated (10 min), washed (2X) with and re‐dispersed in PBS. Biomarker‐bound Magfiniti® were then measured for the AC magnetic susceptibility (χ’) using a XacQuan II AC susceptometer, with blank Magfiniti® with the same concentration measured as the baseline. The linear correlations between the difference of magnetic susceptibility (Δχ’) and Aβ concentrations were evaluated by the coefficient of determination (R2).

Result

Magfiniti® were stably dispersed in water, with >95% separated magnetically in 5 min. Magfiniti® exhibited minimal adsorptions by serum proteins (∼5 µg/mg Fe) with the incubation time varying from 5 to 60 min, whereas proteins on Dynabeads® ranged from 61.3 ± 12.7 to 223.3 ± 22.5 µg/mg Fe, as the incubation time increased. Excellent linear correlations (R2=0.9999) between Δχ’ and Aβ concentrations with standard deviations <1% were achieved, when Δχ’ were measured at the AC frequencies of 500, 1000, and 2000 Hz.

Conclusion

The Magfiniti®‐based AD biomarker measurement may provide an alternative approach for liquid biopsy of AD using routinely collected blood samples.
Delayed blood arrival partially mediates the association between arterial dilatation and cerebral small vessel disease
Authors: Robb W Hudson , Zhang Panpan , Shah Krish U , Houston Michelle L. , Shashikumar Niranjana , Shashikumar Niranjana , Pechman Kimberly R. , Liu Dandan , Davis L. Taylor , Jefferson Angela L. , Hohman Timothy J.
Published: January 2025

Background

Cerebral arterial dilatation, signifying outward vascular remodeling, is linked to a higher risk of Alzheimer’s disease and a higher burden of white matter hyperintensities (WMH). Arterial dilatation may disrupt cerebral hemodynamics and lead to delayed blood arrival to the brain, which is itself linked to an increased burden of WMH. We examined if arterial dilatation was associated with blood arrival timing and if blood arrival timing mediated the effect of arterial dilatation on WMH burden.

Methods

Vanderbilt Memory and Aging Project participants free of clinical dementia or stroke at enrollment (n=249, 73±8 years, 85% cognitively unimpaired, 41% female) underwent multimodal 3T brain magnetic resonance imaging. Internal carotid artery (ICA) and basilar artery (BA) arterial inner diameters were quantified by an expert rater using vessel wall imaging. An established marker of blood arrival timing, the arterial spin labeling spatial coefficient of variation (ASL‐sCoV), was quantified using pseudo‐continuous ASL. Higher ASL‐sCoV indicates slower blood arrival. WMH burden was quantified using semi‐automated methods. Linear regressions related ICA and BA inner diameters to ASL‐sCoV and log‐transformed WMH burden in anterior and posterior arterial territories, individually. Models were adjusted for age, sex, race/ethnicity, cognitive status, Framingham Stroke Risk Profile, intracranial volume, and apolipoprotein E‐ε4 status. We also assessed if ASL‐sCoV mediated associations between arterial diameters and WMH burden.

Results

Larger ICA inner diameter was associated with higher anterior ASL‐sCoV (p=1.7x10‐8) and higher anterior WMH burden (p=9.6x10‐5). Anterior ASL‐sCoV partially mediated the association between ICA inner diameter and anterior WMH burden (proportion mediated=15%, p=0.04). Larger BA inner diameter was associated with higher posterior ASL‐sCoV (p=1.3x10‐8) but not with higher posterior WMH burden (p=0.06).

Conclusions

Our study illustrates novel links between cerebral vascular structure, cerebrovascular hemodynamics, and vascular brain pathology. Because most of the effect of arterial dilatation on WMH burden was not mediated through blood arrival timing, future work will consider other potential mediators, such as arterial stiffness.
Microvascular physiology differs in older adults with varying vascular risk and white matter lesion burden
Authors: Gassner Gabriele M , Damestani Nikou L , Yadav Shrikanth M , Wheeler Natalie S , Jacoby John R , Mellen Sarah F , Maina Katherine N , Salat David H , Juttukonda Meher R
Published: January 2025

Background

White matter lesions (WMLs) are common with aging and are prevalent in AD, but the underlying physiology as well as associations with conventional vascular risk factors are not yet fully understood. In this study, we investigated the relationship between vascular risk factors and microvascular physiology (i.e., oxygen supply and oxygen extraction fraction), and their association with WML burden in older adults.

Method

Study design: Typically‐aging older adults between 60–80 years (n=42) were enrolled and categorized as ‘high’ (VRF+; n=27) or ‘low’ vascular risk (VRF−; n=15) based on medication use, clinical diagnosis, and disease‐specific markers of four modifiable conditions: hypertension, diabetes, hyperlipidemia, and overweight. Participants were further subdivided into ‘high’ or ‘low’ WML burden based on positive or negative residuals from a regression of WML burden against age.

Hemodynamic imaging: Magnetic resonance imaging (MRI) data was acquired using pseudo‐continuous arterial spin labeling (ASL) for cerebral blood flow (CBF) and T2‐relaxation‐under‐spin‐tagging (TRUST) MRI for oxygen extraction fraction (OEF). Cerebral blood blow (CBF) was computed using a two‐compartment model and with accounting for arterial transit time. Cerebral oxygen supply was computed as the product of CBF, arterial oxygen saturation, and the oxygen transport capacity of blood. Venous oxygenation was derived from TRUST, and OEF was computed as the relative ratio between arterial oxygen saturation (from pulse oximetry) and venous oxygenation.

Result

Participants did not differ in oxygen supply, but OEF was significantly higher in VRF+ (39.22%) versus VRF− (35.2%) individuals (p = 0.02; Figure 1). Within the VRF+ group, no differences were observed in oxygen supply or OEF were found when comparing high versus low lesion burden individuals. Within the VRF− group, no differences in oxygen supply were observed, but OEF was significantly lower in the high lesion burden (30.4%) compared to the low lesion burden (37.6%) subgroup (p = 0.01; Figure 2).

Conclusion

Our findings suggest that lower OEF may represent a marker of impaired physiology associated with WML burden in the absence of conventional vascular risk factors. Such impairment could arise from disturbed capillary transit patterns, and future work will investigate these mechanisms.
Dynamic Resting State Functional Connectivity in Cognitive Resilience of Alzheimer's Disease
Authors: Liu Lin , Zhu Yalin , Li Anqi , Fang Lili , Ma Shaohua , Guo Tengfei
Published: January 2025

Background

Alzheimer's disease (AD) is characterized by a decline in cognitive abilities, with cognitive resilience (CR) denoting the capacity of AD patients to withstand such declines. Prior studies have linked the segregation of functional networks with cognitive resilience in AD. The emergence of dynamic functional connectivity (dFC) is a notable advancement in the assessment of brain network dynamics of CR features in AD.

Methods

Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity of CR features in 164 AD participants into reference group of 96 with cognitive unimpairments (CU) and CR group of 68 with high CR. The specific calculation formula is in Figure 2, because the formula cannot be added to the text.

Results

Figure 1 A‐B illustrates the flow chart used to calculate the separation coefficient within and between brain networks. Upon comparing the high cognitive elasticity group with the control group, we observed a significant decrease in the separation coefficient within and between the SMN, DMN, SUB, and CN brain networks in the high cognitive elasticity group (Figure 1C‐D).

Conclusions

Through dFC features pertinent to CR can be obtained and have been corroborated in different clinical diagnosis groups and cognitive function scores.
Maya Angelou Center for Health Equity Caregiver College (MC2): Focus Group Feedback from Tier 1 and Tier 3 Counties in North Carolina
Authors: Caban‐Holt Allison M. , Fortune Doreen Rone , Sanderlin Ashley H. , Whitaker‐Brown Charlene , Artis Ruby Tonnette , Starks Takiyah D. , Lloyd Shawnta , Gregory Ashley , Byrd Goldie S.
Published: January 2025

Background

Black/African American (AA) caregivers of patients with Alzheimer’s disease (AD) and related disorders can play a critical role in maintaining patient health. AD caregivers who face economic challenges may have less access to resources that may reduce caregiver burden they experience. The North Carolina Department of Commerce ranks the state’s 100 counties based on economic well‐being and assigns the most distressed counties as Tier 1, and least distressed as Tier 3. Focus groups were conducted to determine the needs of Black/AA AD caregivers in a Tier 1 and a Tier 3 county.

Method

The Maya Angelou Center for Health Equity Caregiver College (MC2) is an educational program that aims to improve informal caregivers’ knowledge of AD. Focus groups were conducted with community stakeholders in Wilson (Tier 1) and Mecklenburg (Tier 3) counties in North Carolina. Focus group attendees were engaged in discussion on topics including a review of local resources to support caregiving, challenges that AD caregivers face, educational needs of caregivers and preferred format of an MC2 event.

Result

Focus group participants (N = 15; Wilson = 8, Mecklenburg = 7) are African American (100%), with professional and community roles including clergy, caregivers, nursing, teaching, manager, community health worker, and local city officials. Findings suggest that significant needs in a Tier 1 county include lack of geriatric∖AD specialists, few caregiver support resources, and little qualified in‐home care assistance. In a Tier 3 county, structural barriers and physical access to resources were named as difficulties. Common issues for both counties included confusion by what insurance plans cover. The design for MC2 was requested as a 1‐day format in the Tier 3 County because of a large population of working caregivers, whereas in the Tier 1 County a multi‐day MC2 format was recommended due to the perception that people in the county would benefit more from a more intensive AD educational event.

Conclusion

Needs in Tier 1 and Tier 3 counties differed, however, both groups need help navigating medical insurance. Results will be used to customize the MC2 events to meet the expressed needs of the stakeholders in each county.
Investigating intimate partner violence as a dementia risk factor through co‐creation of research design and knowledge translation deliverables with survivors and sector partners
Authors: Wellington Cheryl L
Published: January 2025

Background

Approximately 30% of women worldwide experience intimate partner violence (IPV). Although as many as 92% report impacts to the head and/or strangulation that raise clinical suspicion of brain injury (BI), there are no evidence‐based methods to document IPV‐BI in this vulnerable population, no clinical practice guideline, and insufficient understanding about long‐term risks including Alzheimer’s Disease and Related Dementias (ADRD). Although traumatic brain injury (TBI) is an established ADRD risk factor, little is known about attributable risk of ADRD due to IPV in either military or civilian populations. Our study aims to improve diagnosis of BI in survivors of IPV in a manner sensitive to the needs of this vulnerable population, and to raise awareness of the importance of considering IPV‐BI as a potential ADRD risk factor.

Methods

We were recently approved by the USA Department of Defence to launch a prospective observational study that leverages collaborative research at three clinical sites in British Columbia Canada that reach ethnically and geographically diverse participants. We will assess acute and chronic plasma biomarkers as diagnostic tools and will also use an integrated knowledge translation (iKT) framework including community participation to deliver a living clinical practice guideline for IPV‐BI and trauma‐informed guidance for ADRD researchers to specifically ask about IPV in clinical history.

Results

Thus far, we have worked with multiple stakeholders to co‐create a novel Case Report Form suitable for use in real‐life clinics to collect IPV history including head impact and strangulation events, and have pilot data on several plasma biomarkers relevant to ADRD that, for some cases, suggest IPV may lead to accelerated brain aging and biomarker patterns consistent with AD.

Conclusions

We will discuss how extensive feedback from persons with lived experience and stakeholder groups was essential to design a feasible community‐based study, as common data elements now almost routine in ADRD and TBI studies needed to be reworked to consider the unique needs of IPV survivors in participating in research.
Basal Ganglia Mechanical Stiffness is Associated with Fluid Intelligence in Amnestic Mild Cognitive Impairment
Authors: Kramer Mary K , Delgorio Peyton L , Diano Alexa M , McIlvain Grace , Twohy Kyra E , Bailey Olivia M , Cohen Matthew L. , Lanzi Alyssa M , Martens Christopher R. , Johnson Curtis L
Published: January 2025

Background

Magnetic resonance elastography (MRE) is an MRI technique that uses mild, externally applied vibrations to quantify the mechanical properties of tissues in vivo. MRE measures, such as stiffness, have been shown to be sensitive to changes in brain health with aging and neurodegeneration. Here we used MRE to characterize differences in brain mechanical properties between individuals with amnestic mild cognitive impairment (aMCI) and cognitively unimpaired subjects (CU).

Method

A cohort of 67 cognitively unimpaired subjects (21M/46F; 60‐82y) and a cohort of 34 subjects with aMCI (11M/23F; 60‐89y) completed an MRE scan to assess their brain mechanical properties. From this, we quantified basal ganglia (BG) stiffness in each subject including the caudate, pallidum, putamen, and nucleus accumbens. Subjects also completed the NIH toolbox cognition battery from which we examined fluid cognition composite score, which reflects logic and reasoning skills.

Result

We found a significant group difference in stiffness of the basal ganglia (BG). Interestingly, aMCI subjects had significantly higher BG stiffness than CUs (2.99 vs. 2.89 kPa, p<0.05; Figure 1). Within the aMCI group, BG stiffness was positively correlated with fluid cognitive score (r = 0.48, p<0.01; Figure 2), where higher scores were associated with greater stiffness; the same relationship in the CU group was not statistically significant.

Conclusion

Higher BG stiffness found in the aMCI group may reflect aspects of aMCI pathology and progression that MRE can sensitively detect. Most MRE studies report that healthy brains are associated with higher stiffness than those with neurodegenerative pathology, with our previous work showing that aMCI participants had softer hippocampi than age‐matched CUs (Delgorio, 2023). Our findings in the BG are surprising in this context but may indicate a compensatory mechanism that occurs during early progression of aMCI and results in increased stiffness, which was previously suggested by Murphy (2016). Here we also provide the first evidence that higher BG stiffness in aMCI is associated with better cognitive function, which further points to higher stiffness being compensatory rather than pathological. The neurobiological basis of this compensatory increase in BG stiffness of aMCI subjects requires further study but could be influenced by acute neuroinflammatory processes.
Hippocampal Functional Organization Mediates the Impact of the Cortical Iron on the Cognition in Women with Suspected Coronary Microvascular Dysfunction
Authors: Silemek Arzu C Has , Wertheimer Jeffrey C , Wei Janet , Dumitrascu Oana M , Kremen Sarah , Xie Yibin , Li Debiao , Nelson Michael D , Tan Zaldy S , Merz Noel Bairey , Sati Pascal , Gao Wei
Published: January 2025

Background

Women with suspected coronary microvascular dysfunction (CMD) may be at higher risk of experiencing cognitive decline due to cerebral small vessel disease, a known contributor to Alzheimer’s disease and related dementias (ADRD). A potential underlying mechanism that could accelerate this cognitive decline is the accumulation of brain tissue iron, which has been previously linked to changes in brain function potentially caused by oxidative stress and cell death. Therefore, we aim to elucidate whether a similar mechanism could affect women with suspected CMD by investigating the potential role of iron deposition on the brain’s functional organization and its effect on cognition using advanced magnetic resonance imaging (MRI).

Material and Methods

Twenty‐seven women with suspected CMD [Age; median (range) = 54 (29‐76)], drawn from ongoing cohorts (3R01HL146158‐04S1,3U54AG065141‐04S1), underwent a 3T MRI protocol, including submillimeter T2* 3‐dimensional echo‐planar‐imaging for assessing iron deposition with high‐resolution quantitative susceptibility mapping (QSM) and resting‐state fMRI (rs‐fMRI). Iron content was quantified by total‐generalized‐variation based QSM analysis. Functional integrity was determined via graph theoretical approach (i.e., nodal degree). Cognitive assessment was also performed using the NIH Toolbox. Mediation analysis was conducted using Python Statsmodels.

Results

Most of the women with suspected CMD showed lower performance in processing speed, working memory, executive function, and attention (Figure‐1A). We found a significant association between elevated iron levels in paracentral gyrus and lower functional connectivity in left hippocampus (p = 0.005, adjusted‐r2 = 0.19) (Figure‐1B). Elevated iron level in the paracentral gyrus showed an impact on cognitive performance in the domains of executive function and attention (p<0.0001, coefficient = 531.09) as well as language functions and crystalized abilities (p = 0.036, coefficient = 362.45), mediated by functional connectivity in the left hippocampus (indirect effect on executive function / language: p = 0.034 / 0.038, coefficient = ‐254.54 /‐ 213.06) (Figure‐1C).

Conclusions

Our results suggest that changes in hippocampal functional organization are associated with cortical iron deposition and mediate its impact on cognitive performances. These changes may increase the risk of cognitive decline/ADRD or in women with suspected CMD. Future research in a larger cohort with a longitudinal design is necessary to validate and expand upon these findings.
Sex‐specific risk profiles associated with Alzheimer’s disease markers in cognitively unimpaired older adults
Authors: Touron Edelweiss , Wirth Miranka , Binette Alexa Pichet , Demnitz‐King Harriet , Collette Fabienne , Poisnel Géraldine , Vivien Denis , la Sayette Vincent De , Marchant Natalie L , Chételat Gael , Gonneaud Julie
Published: January 2025

Background

Despite evidence that sex can modulate Alzheimer’s disease (AD) risk, whether risk factors are similarly related to AD markers in women and men remains largely unexplored. We aimed to assess how a combination of potentially modifiable risk factors are associated with cognitive and pathological markers of AD in older women and men.

Method

We included 135 cognitively unimpaired older adults ( = 65 years old, 83 women; Table 1) from the Age‐Well trial (NCT02977819; baseline data) with multidomain assessments of modifiable risk factors, including cardiovascular (body mass index, systolic blood pressure, LDL cholesterol), lifestyle (complex mental activity throughout life, physical activity, diet), and psychological (quality of life, depressive and anxiety symptoms, rumination, worry). AD markers included the Preclinical Alzheimer Cognitive Composite‐5 (PACC‐5), a measure of global cognition sensitive to AD‐related decline, and multimodal neuroimaging and blood sampling providing measures of hippocampal volume (MRI), brain perfusion in temporo‐parietal regions, neocortical amyloid burden (PET) and p‐tau181 (plasma). Multivariate partial least squares analyses were used to assess relationships between combinations of risk factors and AD hallmarks (cognition, neurodegeneration, amyloid and tau) in women and men separately.

Result

In women, a combination of lower quality of life and complex mental activity throughout life and higher levels of anxiety and worry, was associated with lower PACC‐5 scores and higher p‐tau181 levels (p = .002, 60.5% of variance explained; Fig.1). In men, two significant latent variables emerged. Lower systolic blood pressure, adherence to a Mediterranean diet and quality of life, and higher levels of anxiety and worry, were associated with higher hippocampal volume and lower brain perfusion in regions sensitive to AD (p = .022, 45.2% of the variance explained; Fig.2A); while lower levels of quality of life and complex mental activity throughout life were associated with worse PACC‐5 scores and higher neocortical amyloid deposition and p‐tau181 levels (p = .023, 35.9% of the variance explained; Fig.2B).

Conclusion

These preliminary findings suggest that the modifiable factors that could influence AD markers may differ by sex in cognitively unimpaired older adults. Pending replication in larger and independent cohorts, these results highlight the need to consider sex specificities in prevention strategies.
Understanding the mechanisms of lateral parietal memory modulation in Alzheimer's Disease
Authors: Slayton Matthew A , McAllister Margaret L , Rothrock Jane , Belhadj Sarrah , Gillette Kirsten D , Hovhannisyan Mariam , Cabeza Roberto , Davis Simon W
Published: January 2025

Background

Alzheimer’s Disease (AD) is characterized by progressive impairment of cognition and memory, including the loss of episodic memory. The use of non‐invasive brain stimulation therapies to modulate memory encoding processes is a promising avenue for potential treatment. Previous studies have shown that the use of Transcranial Magnetic Stimulation (TMS) applied to lateral parietal cortex can improve memory in older adults who have received a diagnosis of Mild Cognitive Impairment. This effect may be driven by the modulation of connectivity between parietal cortex and the hippocampus, structures which support the encoding of semantic information into memory. And yet, while modulation of cortical‐hippocampal connectivity helps to establish a systems‐level explanation for the parietal memory benefit for TMS, it does not explain the benefit on the level of memory representation—i.e., the most basic evidence we have of what visual and semantic information underlies memory formation. Previous work from our lab has found that TMS can change memory representations in the hippocampus.

Method

Here we present new data from a study applying this approach to MCI, using rTMS to an individualized site in parietal cortex to boost memory function, while monitoring daily changes in behavior and brain physiology over the course of three days. Immediately after rTMS, patients perform a semantic encoding task where they view everyday objects while fMRI is collected, after which they complete recognition memory tasks. To ask whether memory performance improvements are driven by the modulation of visual or semantic information in the brain, we use Representational Similarity Analysis (RSA), a computational method that can reveal the changes in visual and semantic representations over the course of TMS.

Result

Consistent with the role of lateral parietal cortex as a hub for the processing of abstract knowledge, we show that semantic representations show greater TMS‐related changes and are more directly associated with improvements in memory success, whereas visual representations are not.

Conclusion

Increasing the representation of abstract knowledge is a potential underlying mechanisms by which neuromodulation boosts episodic memory in MCI, which may lead to reliable clinical applications of noninvasive brain stimulation in AD.
Comparison of cerebrospinal fluid and plasma oxidative stress biomarkers
Authors: de la Colina Adrian Noriega , Charisis Sokratis , Ntanasi Eva , Mamalaki Eirini , Skaperda Zoi , Kouretas Demetrios , Scarmeas Nikolaos
Published: January 2025

Background

Numerous studies have highlighted the role of oxidative stress in Alzheimer's disease (AD) development. Yet, the alignment of systemic and central oxidative stress biomarkers is unclear across diverse populations in the AD continuum. This study aims to assess protein damage levels in plasma and cerebrospinal fluid (CSF) within the AD continuum.

Methods

One hundred forty participants without clinical dementia (47 with Mild Cognitive Impairment [MCI] and 93 cognitively unimpaired) from a memory clinic cohort underwent examination for central (CSF) and systemic (plasma) markers of oxidative stress. We measured Total Antioxidant Capacity (TAC), reduced glutathione (GSH), thiobarbituric acid reactive substances (TBARS), and reducing power (RP) using standard laboratory techniques and absorbance spectrophotometry (Hitachi U‐1500). Pearson’s correlations were employed to determine the congruence between the same biomarkers of oxidative stress in CSF and plasma. Factor analysis was performed to ascertain how many antioxidant dimensions they represent.

Results

Table 1 outlines participants' baseline characteristics. Pearson’s correlation analysis for the entire sample revealed no congruence between CSF and plasma in TAC (r=+.087) and GSH (r=.‐.161), while CSF and plasma RP (r=.+385*) and TBARS (r=‐.216*) were correlated (Figure 1). Upon analyzing group‐level data, the cognitively unimpaired group showed congruence between CSF and plasma for GSH (r.=‐.279*) and TBARS (r=‐.287*) but not for TAC (r=+.191) and RP (r=+.202). In the MCI group, only RP (r.=+.640*) demonstrated congruence between CSF and plasma. Factor analysis with CSF biomarkers identified two components in the whole sample (Figure 2). Dimension 1= GSH, and Dimension 2=TAC, TBARS, and RP. Factor analysis with plasma identified as well two components: Dimension 1=RP and GSH, Dimension 2=TBARS and TAC. The factor analysis for the MCI group revealed the presence of a single component for CSF biomarkers, while there were two components for plasma: Dimension 1=RP and TBARS, Dimension 2=TAC and GSH.

Conclusion

Oxidative stress biomarker patterns differ across the AD continuum. RP demonstrates the most reliability, while TAC is the least. GSH and TBARS plasma and CSF measurements are negatively associated in the cognitively unimpaired, but not in the MCI population. Understanding oxidative biomarker evolution can enhance our comprehension of their role in AD and age‐related disorders.
Synergic effect of tau tangles and cortical thinning on cognitive decline in aging and Alzheimer's disease
Authors: Trudel Lydia , Therriault Joseph , Rahmouni Nesrine , Aumont Etienne , Wang Yi‐Ting , Servaes Stijn , Macedo Arthur C. , Chan Tevy , Arias Jaime Fernandez , Hall Brandon J , Hosseini Seyyed Ali , Socualaya Kely Monica Quispialaya , Mathotaarachchi Sulantha , Stevenson Jenna , Lussier Firoza Z , Gauthier Serge , Pascoal Tharick A. , Rosa‐Neto Pedro
Published: January 2025

Background

Tau burden has been found to be involved in brain atrophy during aging, especially in regions such as the parahippocampal gyrus. However, how tau levels at baseline are associated with trajectories of tau accumulation, cortical thinning and cognitive impairment remains poorly understood. The goal of this study was to assess tau rate of change in patients between baseline Tau+ and Tau‐ patients. We also aimed to determine if tau status at baseline or rate of accumulation of tau interacted with the rate of cortical thinning of the parahippocampal regions, leading to an increased rate of change in cognition.

Method

We assessed 133 participants from the TRIAD cohort (mean age = 68.5 ± 8.9, 85 females) with at least two visits with tau‐PET using [18F]MK6240 and cortical thickness extracted using FreeSurfer 7. Average time between visits was 25.6 months. Patients were classified according to clinical status, Amyloid‐ß status and tau status at baseline (CU AB‐Tau‐, CU AB+Tau‐, CU AB+Tau+, MCI AB+Tau‐, MCI AB+Tau+, AD AB+Tau+). The tau‐PET rate of change was calculated for each participant, voxelwise and with temporal meta‐ROI. The MMSE rate of change was calculated to quantify cognitive decline over follow‐up period. We assessed the voxelwise relationship between baseline tau status and tau‐PET rate of change.

Results

We found a voxelwise positive association between rate of accumulation of tau and tau status at baseline in both anterior temporal lobes. Furthermore, we found an interaction effect between tau‐PET at baseline and parahippocampal rate of atrophy on MMSE rate of change (standardized ß = 0.48, p < 0.0001).

Conclusion

Our results suggest that tau status at baseline might impact the rate of accumulation of tau, and that higher baseline levels of tau interact with cortical thinning of parahippocampal regions, leading to faster rates of cognitive decline. Our results emphasize the importance of preventing tau burden to prevent faster pace of cognitive decline during the disease’s trajectory.