bluuebunny/crossref_metadata_2025 huggingface dataset:
Brain EV‐Bound Proteins in Blood as a Robust Biomarker for Accurate Classification of Tau Tangles in the Brain
Authors: Ho Nicholas RY
Published: January 2025

Background

Brain derived Extracellular Vesicles (EVs) was isolated from blood and their containing pthogenic proteins were quantified to develop a biomarker signature for the classification of Tau aggregation in the brain.

Method

Brain derived EVs and their cargo were measured directly in the plasma of patients with AD and determined to be Tau‐PET positive (visual read) (n=10) and other age matched healthy controls (n = 22) at one time‐point. AD pathogenic proteins bound to EVs were quantified by in‐house custom developed immunoassays.

Result

A signature of a variety brain derived EV bound total tau, P‐T231‐tau, and P‐S396‐tau was able to accurately classify Tau‐PET positive AD patients from healthy controls (AUC: 0.88 – 0.93)

Conclusion

Brain derived EV bound total tau, P‐T231‐tau, and P‐S396‐tau in blood show good potential as biomarkers to classify Tau aggregation in the brain
Self‐awareness impairment in Alzheimer’s Disease: Its Impact on Decision‐Making for Aging in Place
Authors: Compagne Charline , Trimaille Helene , Magnin Eloi , Tannou Thomas
Published: January 2025

Alzheimer’s disease significantly impacts decision‐making abilities, potentially increasing risk‐taking behaviors and complicating the process of aging‐in‐place, particularly in cases of anosognosia (self‐awareness impairment). To understand how this affects patient and caregiver perspectives, we conducted a qualitative study to identify arguments used by older patients with Alzheimer’s disease and their family caregivers about aging‐in‐place. We included 18 dyads, each comprising an older adult living at home with mild dementia and their family caregiver. The older adults' arguments in favor of aging‐in‐place were primarily centered on maintaining a sense of safety and comfort through familiar surroundings and relationships, as well as preserving independence and lifestyle habits, which contribute to stability in their daily lives. Despite recognizing memory loss, many minimized or overlooked the associated risks in their thoughts about aging in place. Caregivers, while supportive of the desire for aging in place, emphasized the need for adaptability in daily functioning and proactive planning for foreseeable challenges. They advocated for external support strategies, including professional assistance, technology use, routine adaptations, and legal protective measures. Our study highlights the profound impact of anosognosia on the loss of adaptability, potentially undermining preventive strategies for aging in place. A deeper understanding of these factors is crucial for professionals in developing care and service plans tailored to individual needs. Such knowledge is vital in facilitating discussions and negotiations around care strategies, ensuring they address the needs and concerns of both patients and caregivers in the context of Alzheimer’s disease.
Enhancing the Wellbeing of Family Dementia Caregivers: The Impact of Gamification in the MapHabit Program
Authors: Gore Janelle , Montgomery Brittany
Published: January 2025

Background

The number of caregivers providing care for a family member or friend is on the rise. Dementia caregivers experience higher levels of stress and burden than caregivers of other chronic diseases due to the physical and emotional demands, and long duration of care provided. Thus, innovative tools are needed to aid in reducing caregiver stress and burden. MapHabit, is a novel mobile health assistive technology tool designed to support families affected by dementia by providing daily schedules and step‐by‐step visual routines and cues called maps, aiding the person living with dementia (PLWD) to complete various activities of daily living (ADLs). With repeated use of these maps, persons with memory impairment have reported an improvement in memory and caregivers have reported reduced stress and burden. Gamified features were integrated into MapHabit to evaluate whether cognitive engagement activities could improve an individual’s motivation to consistently engage with MapHabit. Building upon the demonstrated impact of MapHabit, this study explores the effects of implementing gamified features within the application to enhance the reduction of caregiver stress.

Methods

A modified Zarit Burden Interview was used to assess caregiver burden. The Mini Mental State Examination was used to evaluate the cognitive function of the PLWD. Scores from the respective assessments were calculated based on the respective scale’s scoring guide for pre‐ and post assessments. Scores were then compared to determine the stress and an improvement in memory of the PLWD.

Results

Thirteen participants engaged in the MapHabit with Gamification group for 6‐weeks. About 69% of caregivers reported a reduction in stress and burden post study and 69% of PLWD reported an improvement in memory. Preliminary findings suggest the introduction of gamification in the MapHabit program may aid in reducing caregiver stress and burden.

Conclusion

This research has implications for the ongoing development of dementia support programs, emphasizing the potential of gamification as a supplementary tool to enhance the engagement of existing interventions supporting families affected by dementia.
Complement C1q is Associated with sTREM2, GFAP and Alzheimer’s Pathology: the ADNI & CABLE Study
Authors: Sheng Ze‐Hu , Wang Zhibo , Ma Lingzhi , Wang Zuo‐teng , Guo Fan , Tan Lan
Published: January 2025

Background

Complement C1q, the initiator of the classical pathway of the complement system, is activated during Alzheimer’s disease (AD) development and progression and is especially associated with the β‐amyloid and tau pathology. However, whether C1q influences AD pathology by modulating glial cell communication is unclear.

Method

Alzheimer’s Disease Neuroimaging Initiative (ADNI, N = 217) was used to explore the association between cerebrospinal fuid (CSF) C1q, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), Glial fbrillary acidic protein (GFAP), and AD biomarkers. Chinese Alzheimer’s Biomarker and LifestylE (CABLE, N = 535) study was used to explore the association between plasma C1q, CSF sTREM2, GFAP, and AD biomarkers. Causal mediation analysis was conducted through 10,000 bootstrapped iterations to explore the mediating effect of sTREM2/GFAP on association between C1q and AD pathology.

Result

We found that CSF C1q was positively associated with CSF sTREM2, GFAP and AD core biomarkers (Aβ42; phosphorylated‐tau, p‐tau; and total tau, t‐tau) at baseline, and was also significantly related to CSF t‐tau and ADAS‐13 in longitudinal analysis. Moreover, mediation analysis revealed that CSF C1q modulated the level of CSF sTREM2 and contributed to tau pathology (as measured by CSF p‐tau/ t‐tau). In addition, Aβ pathology (as measured by CSF Aβ42) affected the development of tau pathology (as measured by CSF p‐tau) partly by modifying the levels of CSF C1q and CSF sTREM2. Furthermore, the plasma C1q was also significantly associated with CSF sTREM2.

Conclusion

Our fndings provide evidence to suggest that Complement C1q is linked to sTREM2 and mediates the correlation between Aβ pathology to tau pathology. It indicates that Complement C1q may be a major factor in the spreading from Aβ pathology to tau pathology in AD.
Association Between Mean Corpuscular Volume and Cognitive Function in Community‐Dwelling Older Adults ‐ An 11‐year Cohort Study
Authors: Yen Pei‐Yu , Chiou Jen‐Ming , Chen Yen‐Ching , Chen Jen‐Hau
Published: January 2025

Background

The mean corpuscular volume (MCV) is a common parameter in routine blood tests. Larger MCV tends to be more fragile and pose challenges in passing through capillaries, leading to a diminished capacity for oxygen and nutrient supply to the brain thus impacting cognitive function. Limited studies have explored the association between MCV and cognitive impairment with inconsistent results. This study aimed to investigate the association between MCV and cognitive function in community‐dwelling older adults.

Method

This 11‐year cohort study (2011‐2022) included 530 non‐demented older adults (aged above 65) from the ongoing Taiwan Initiative for Geriatric Epidemiological Research at baseline (2011 to 2013) with four biennial follow‐ups. Global cognition was assessed by the Taiwanese version of the Montreal Cognitive Assessment. Domain‐specific cognition, including memory, attention, verbal fluency, and executive function, was assessed by a battery of neuropsychiatric tests. Blood data were collected, including MCV, red blood cell distribution width, hemoglobin, platelet, and vitamin B12. The cutoff of MCV was determined by the turning point obtained from the generalized additive model. This study utilized a generalized linear mixed model to analyze the association between MCV and cognitive function adjusted for age, sex, years of education, apolipoprotein E ε4 status, years of follow‐up, and other blood parameters.

Result

The average age of the participants is 72.68 years, with females comprising 53.40%. As the follow‐up time increased, older adults with larger baseline MCV (>93.0 fL) exhibited a significantly poor performance of memory (immediate free recall: = ‐0.028, p = 0.021; delayed free recall: = ‐0.039, p = 0.002; delayed theme recall: = ‐0.041, p = 0.003), and attention (digit span forward: = ‐0.028, p = 0.027). Additionally, an interaction was found between MCV and age on global cognition (p interaction=0.008).

Conclusion

Over time, increased MCV was associated with poor domain‐specific cognition. MCV may potentially serve as an early indicator for assessing cognitive impairment. Larger and longer‐term studies are needed to clarify their temporal relationship and underlying mechanism.
Salivary lactoferrin levels decrease in Alzheimer's disease patients
Authors: Bunprakop Saowalak , Ruchisrisarod Chanida , Luechaipanit Watayuth , Hemachudha Thiravat , Thanapornsangsuth Poosanu
Published: January 2025

Background

Alzheimer’s disease (AD) is referred as one of the most common causes of dementia and frailty. To address this impending public health crisis, there is a critical need to identify simple and reliable biomarkers for early AD diagnosis. Recent research has highlighted the potential utility of salivary lactoferrin (Lf) as a promising biomarker for AD diagnosis. In this study, we aim to assess salivary Lf levels in early‐stage AD patients in comparison to nondemented elderly controls with the goal of further elucidating the diagnostic utility of this biomarker, Lf may be a good biomarker candidate for initial and clinically.

Method

A total of 212 patients were included in the study. Saliva samples were collected from nondemented elderly controls (n = 151) and early‐stage AD patients (n = 61). The diagnosis of AD was made clinically using the current guidelines (Jack et al., 2018; Dubois et al., 2021). All patients were diagnosed by PET or plasma phosphorylated tau 181 (P‐tau181), 71 patients including clinical and the Clinical Dementia Rating (CDR). Salivary Lf levels were compared between the two groups and the diagnostic performance of Lf was evaluated in these early‐stage patients.

Result

Among 212 participants included, 139 (65.6%) were female. The median age was 67 years. Salivary Lf levels decreased significantly among early‐stage AD patients (9.02 ug/ml) compared to controls (26.07 ug/ml; P<0.001). Salivary Lf showed moderate correlation with plasma P‐tau181 (Spearman Rho=‐0.472, P<0.001) (Figure 1). For diagnosing AD in early‐stage patients, salivary Lf levels demonstrated an area under the curve of 0.88 (95% confidence interval 0.83‐0.93).

Conclusion

The main findings of this study are that salivary Lf levels decreased significantly in early‐stage AD patients in comparison to nondemented elderly controls, diagnostic performance of salivary Lf is substantial. The hypothesis that immune alterations and brain infections might play an initial role in the development of AD pathology. our hypothesis would determine salivary Lf would be an easy and cheap biomarker that could potentially make it an attractive option for population‐wide screening and early identification of undiagnosed individuals with AD in its early stages.
Investigating differences in white matter fibre bundle alterations between amnestic Alzheimer’s disease and LATE: A fixel‐based analysis
Authors: Lebrun Aurélie , Lagarde Julien , Leprince Yann , Olivieri Pauline , Bottlaender Michel , Sarazin Marie
Published: January 2025

Background

Typical Alzheimer’s disease (AD) and Limbic‐predominant Age‐related TDP‐43 Encephalopathy (LATE) are two neurodegenerative diseases that present with a similar initial amnestic clinical phenotype but have distinct proteinopathies. AD is characterised by ß‐amyloid plaques and intraneuronal neurofibrillary tangles, while LATE is characterised by abnormal neuronal TDP‐43 protein. With reference to the prion‐like hypothesis regarding the propagation of proteinopathies, investigating white matter fibre bundle alterations could provide new insights into the propagation pathways of specific proteinopathies. Because both AD and LATE have a similar initial limbic phenotype but are distinguished by their proteinopathies, they represent a good model to analyse whether white matter fibre bundle alterations differ according to the pathophysiology. We investigated these alterations in AD and presumed LATE using high quality diffusion MRI and fixel‐based analysis.

Method

We included AD patients (n=27, CDR≤1), presumed LATE patients (n=18, CDR≤1), and controls HC (n=19) using strict pathophysiological criteria, including CSF biomarkers, amyloid and tau PET imaging, and the absence of clinical atypia after two years of follow‐up. Both AD (MMSE=24.5) and LATE (MMSE=24.4) exhibited equivalent episodic memory impairment and hippocampal volume. Using multi‐shell diffusion MRI, we first computed a whole‐brain fixel‐based analysis controlling for age, sex, MMSE, and intracranial volume to explore differences in FD (fibre density), FC (fibre‐bundle cross‐section) and FDC (fibre density and cross‐section) between groups, and to identify tracts of interest. We then reconstructed the identified tracts and performed tract‐based analyses with the same covariates to compare (i) AD versus HC, (ii) LATE versus HC, and (iii) AD versus LATE.

Result

We found that both AD and LATE exhibited white matter alterations in tracts of the temporal and limbic lobes (ventral cingulum, inferior longitudinal fasciculus, uncinate fasciculus, temporopulvinar bundle of Arnold). In addition, LATE patients showed more spatially extended alterations in callosal fibres and in fibres of the cerebello‐thalamo‐cortical tract that end near the pre‐supplementary motor area.

Conclusion

White matter fibre bundle alterations in AD and LATE exhibit differenciable patterns that are consistent with the staging system of tau or TDP‐43 accumulation. These findings also shed light on the temporopulvinar bundle of Arnold, that we found significantly altered in both diseases.
Multi‐atlas fully automated segmentation of the locus coeruleus in in vivo neuromelanin‐sensitive MRI
Authors: de Flores Robin , Blanchard Thaïs , Foyard Emilie , Naveau Mikaël , Delcroix Nicolas , Landeau Brigitte , Yushkevich Paul A. , Chételat Gael ,   Medit‐Ageing Research Group
Published: January 2025

Background

Locus coeruleus (LC) imaging using neuromelanin‐sensitive (NM) MRI sequences is a promising biomarker for detecting early Alzheimer’s Disease (AD). Although automatic approaches have been developed to estimate LC integrity by measuring its intensity, these techniques most often rely on a single template built in a standardized space and/or depend on a number of voxels to be accounted that is defined a priori. Thus, these algorithms make it impossible to perform direct volumetric analyses and do not properly account for inter‐individual anatomical variability. To fill this gap, our aim was to develop a new multi‐atlas fully automated segmentation method using the Automatic Segmentation of Hippocampal Subfields (ASHS) software.

Method

We used baseline data from 102 unimpaired older adults (mean age: 73.72 ± 3.5 years; mean education: 13.25 ± 3.1 years; 58 women, 44 men) from the Age‐Well randomized controlled trial for whom high‐resolution NM MRI (T1‐w with magnetization transfer; 0.3x0.3x0.75mm3) and standard T1‐w MRI (1x1x1mm3) were available. The LC were manually segmented in 30 randomly selected participants on NM MRI, and the standard T1‐w MRI, NM MRI and bilateral segmentations were fed into the ASHS training pipeline to generate an atlas. This new atlas was applied to the 72 remaining subjects to segment the LC and we assessed the effects of age, sex and education on both i) LC intensity (normalized by the intensity of the pons) and ii) LC volume (normalized by the total intracranial volume).

Result

Five‐fold cross‐validation experiments revealed high accuracy of the automatic segmentation relative to manual segmentation (Dice coefficient = 0,83 ± 0,04). LC intensity was significantly higher in women than in men (F=13.61, p<0.001) while no associations with age (β=‐0.0002, p=0.86) or education (β=0.002, p=0.16) were found. In contrast, LC volume was not different between men and women (F=0.21, p=0.65) but tended to be negatively associated with age (β=‐0.15, p=0.06) and education (β=‐0.19, p=0.06).

Conclusion

Overall, this new method allows to automatically and accurately segment the LC, and offers the opportunity to measure its integrity both in terms of intensity and volume. This is of importance since these two metrics might provide complementary information about the integrity of the LC.
Deciphering Alzheimer's Disease Complexity: Integrative Analysis of CSF Proteomic and Lipidomic Data through Dimensionality Reduction
Authors: García‐González Pablo , Puerta Raquel , Dehairs Jonas , de Rojas Itziar , Montrreal Laura , Pytel Vanesa Verónica , Marquié Marta , Rosende‐Roca Maitee , Emon Asif , Smets Bart , Orellana Adelina , Tárraga Lluís , Boada Mercè , Swinnen Johannes V , Fernández Victoria , Socorro Alfredo Cabrera , Ruiz Agustin
Published: January 2025

Background

Alzheimer’s Disease (AD) is a complex disorder and much of its etiopathology is still unknown. Here, we applied dimensionality reduction methods to disentangle cyptic patterns in CSF proteomic and lipidomic data.

Method

We studied 1121 CSF samples using targeted lipidomics based on liquid chromatography (LC)‐MS/MS (mass spectrometry), generated by Lipometrix (Lueven, Belgium), and proteomic data generated by Somalogic (Boulder, Colorado) using the SOMAscan 7k Assay. We independently computed the principal components for the proteomic and lipidomic datasets using good quality lipids (N=388) and proteins (N=2469). CSF samples were obtained by lumbar punctures at ACE Alzheimer Center (Barcelona, Spain), including patients at different points of the dementia continuum (SCD, MCI and dementia). Principal components were calculated using the princomp() function in R.

Result

PC1 explained a substantial fraction of the variance in lipidomic (∼40%) and proteomic (∼60%) datasets and was highly correlated between both omics (R2=0.43; p=2.3·10‐138, Figure 1). We explored the association profile of the PCs to AD risk factors (age, sex, APOE, PRS, diabetes, hypertension, dyslipidemia, BMI), endophenotypes (abeta, tau), disease progression and total protein in the CSF. PC1, as well as the individual lipid species, were strongly associated with abeta, tau and total CSF protein levels (Figure 2). Finally, we conducted a GWAS of the first 20 lipidomic and proteomic PCs. PC1 displayed a GWS signal at chr3q28 in both omics. This region has been previously linked with CSF tau levels and brain morphology. Subsequent lipidomic PCs were associated with variants in the FADS1/FADS2 locus, while other proteomic PCs were associated with variants in the APOE locus (Figure 3).

Conclusion

Our findings revealed a shared major contributor to the variance in CSF between lipidomic and proteomic data, which is related to the tau, abeta and total protein signature, and identified a QTL associated to both the lipidomic and proteomic PC1. Accounting for this major variance contributor may enhance future studies involving CSF biomarkers. Subsequent principal components had specific association profiles to AD risk factors and endophenotypes.
Addressing Unmet Precision Requirements through Improved Automatic Identification of Cerebral Microbleeds
Authors: Jeon Younghoon , Yoo Roh‐Eul , Baek Min Seok , Seong Joon‐Kyung , Choi Seung Hong , Lee Wha Jin
Published: January 2025

Background

Cerebral microbleeds (CMBs) hold significant clinical relevance, linked to elevated risks of hemorrhages, cognitive decline, and mortality. Notably, with the recent advancement in Alzheimer’s treatments, the number of CMBs serves as a crucial safety indicators to assess the risk and occurrence of amyloid‐related imaging abnormalities. However, the commonly utilized manual detection process is time‐consuming and labor‐intensive, prompting the development of various automated detection models. But, most of them are composed of a two‐track system for candidate retrieval and false positive (FP) reduction, resulting in low precision.

Method

Susceptibility‐weighted images (SWI) were obtained from 250 participants enrolled in the Seoul National University dementia cohort, with 200 and 50 images allocated to the training and test set, respectively. CMBs were segmented manually based on expert radiologist assessments. Only 75 images in the training set and 29 images in the test set revealed the presence of CMBs. For our analysis, we employed 3D‐nnUNet, an segmantic segmentation model, training it through 5‐fold cross validation. The segmented regions were analyzed for CMB counting, focusing on morphological features. External validation was performed using 15 images from Wonju Severance Christian Hospital.

Result

Our model exhibited a concurrent high true positive rate (TPR) of 81.4% and precision of 84.9%. This performance remained consistent across different severities of CMB occurrences, with the best perfomance observed in subjects with five or fewer CMBs (TPR of 92.7% and precision of 84.6%). Additionally, even among non‐CMB subjects, the model demonstrated strong perfomance, yielding an average of 0.23 FPs. External validation confirmed model robustness with a TPR of 86.4% and precision of 79.2% (Table 1). Classification of the severity groups regarding the number of CMBs (None, 1∼4, 5∼10, and >10) revealed an overall accuracy of 87% in the non‐CMB and the test set (Figure 1).

Conclusion

This study introduces a novel single‐channel automated CMB detection model using SWI. Our model successfully tackles a notable challenge found in previous automatic CMB counting models, balancing a high TPR with more reliable precision. It underscores its applicability for accurately stratifying CMB severities in clinical contexts, including eligibility assessment for anti‐beta amyloid antibody treatment in AD.
Empowering Better End of Life Dementia Care (EMBED‐Care): Co‐design of a digital holistic assessment and clinical decision support framework
Authors: Davies Nathan , Ellis‐Smith Clare , Gillam Juliet , Aworinde Tofunmi , Kenten Charlotte , Evans Catherine , Sampson Elizabeth L
Published: January 2025

Background

People with dementia have complex palliative care needs including psycho‐social, physical and spiritual; however, they are often unmet. It is important to empower people with dementia, family caregivers and professionals to work together to better assess and monitor ongoing needs. This study aimed to co‐design and test the feasibility of an integrated model of palliative dementia care to support holistic assessment and decision making for care in the community and care homes (assisted living facilities).

Method

Using a systematic and iterative approach we co‐designed the EMBED‐Care framework, a holistic assessment and clinical decision support system hosted on a digital application. Using framework analysis we synthesised evidence from systematic reviews, large data, and a cohort study to identify unmet palliative care needs and concerns of people living with dementia. We presented the data in workshops, using nominal group techniques with people with dementia, family caregivers, and care professionals, to identify targets, components, and design of the framework. We conducted user testing with all groups to refine the framework. We co‐designed training and support to implement the framework, including bitesize animated videos, manuals, in‐person training sessions, local champions, and a telephone support system. The framework is currently being tested in a feasibility trial in two care homes and two community nursing teams.

Result

The framework consists of five components: holistic assessment using the Integrated Palliative Outcome Scale for People with Dementia (IPOS‐Dem); alert system linked to IPOS‐Dem scores, priority setting; clinical decision support tools; and training programme. The IPOS‐Dem helps identify areas of concern and unmet need, providing opportunities for shared decision making and identify priorities of care. Each concern is linked to a decision support tool to support decision making and to address priorities. Alerts and reminders communicate concerns among teams and carers. A desktop version (dashboard) is available for professionals to view all their residents/patients, including IPOS‐Dem results, allowing symptom tracking. Findings from the feasibility study will be presented.

Conclusion

This is the first intervention to link IPOS‐Dem with practical decision support to help break down the complexity of palliative dementia care, providing the right care at the right time.
Functional brain network organization supports cognitive function in patients with Alzheimer’s Disease‐related pathological burden and brain atrophy
Authors: Zhang Ziwei , Chan Micaela , Winter‐Nelson Ezra , Wig Gagan S
Published: January 2025

Background

Alzheimer’s disease (AD) is defined by the accumulation of Aβ plaques and tau neurofibrillary tangles. The consequences of these pathologies include neurodegeneration and cognitive dysfunction. However, the process by which AD pathologies leads to cognitive impairment remains unclear. Some individuals can harbor pathological burden yet be cognitively unimpaired; these observations have led to ideas about cognitive reserve (Stern, Lancet, 2012).

Dominant models of AD biomarkers do not include direct measures of brain function. To address this gap, we tested whether resting‐state brain system segregation explains discrepancies between AD‐related pathology, structural atrophy, and cognitive function. System segregation changes across the adult lifespan, is stratified in relation to life course exposures, and relates to cognitive function (Wig, Trends in Cognitive Sciences, 2017).

Method

Participants were recruited through the Alzheimer’s Disease Neuroimaging Initiative. Cognitive impairment was quantified using clinical dementia rating (CDR). The participant group included 184 healthy (CDR=0) adults, 101 very mild dementia (CDR=0.5), 24 mild dementia (CDR=1) and 2 moderate dementia (CDR=2) patients (age range: 55–96 years).

Functional brain networks were generated using resting‐state fMRI time series. Network edges were defined as correlations between time series of each pair of nodes. Brain system segregation was calculated to quantify functional brain network organization for each participant (Chan et al., PNAS, 2014).

Result

Multiple linear regression analyses were used to test whether Aβ and tau relate to brain system segregation, with age, gender, education, and head motion included as covariates. Neither Aβ nor tau burden was associated with brain system segregation (Aβ: p=0.45; tau: p=0.55).

Among individuals exhibiting positive pathological burden (either Aβ, tau, or both) based on cut‐off values, individuals with higher system segregation were less cognitively impaired (Aβ+: p=0.007; tau+: p=0.021; Aβ and tau+: p=0.03).

Finally, system segregation explained unique variance with respect to CDR status over and above Aβ, tau, and cortical thickness. Brain system segregation was negatively related to CDR status (p=0.003), while accounting for these other factors.

Conclusion

Functional brain network organization supports observations of cognitive reserve, and explains unique variance with respect to AD‐related cognitive impairment independent of AD‐related pathology and neurodegeneration.
Prognostic value of a novel plasma pTau217 assay for amyloid accumulation in healthy elderly
Authors: Meyer Steffi De , Luckett Emma S. , Schaeverbeke Jolien , Laere Koen Van , Vanbrabant Jeroen , Vanmechelen Eugeen , Dupont Patrick , Molfetta Guglielmo Di , Zetterberg Henrik , Ashton Nicholas J. , Poesen Koen , Vandenberghe Rik
Published: January 2025

Background

The performance of blood‐based phosphorylated tau (pTau) immunoassays to detect asymptomatic Alzheimer’s disease (AD) has important implications for therapeutic trials. pTau217 is often recommended as the preferred epitope due to its high fold changes in AD. The current study investigates the ability of a novel pTau217 assay to predict the dynamic phase of amyloid‐β (Aβ) accumulation in comparison to the best‐performing pTau181 assay.

Methods

Plasma pTau217 was quantified by the ALZPath Simoa assay at the University of Gothenburg in 109 cognitively unimpaired older adults (Flemish Prevent‐AD Cohort KU Leuven [F‐PACK] cohort). All subjects underwent baseline plasma sampling and longitudinal Aβ‐PET (median time interval = 6 years). For a subset of 72 subjects, pTau181 was quantified by the Homebrew ADx Simoa assay. Linear mixed‐effects models were used to calculate subject‐specific Aβ change and to assess the age‐, sex and APOE‐corrected predictive value of pTau species for Aβ change, which was assessed in a global and voxelwise manner. Accumulators were defined as having an Aβ rate of change z‐score > 1.5 (based on mean & standard deviation within the Aβ‐ subset). Performance to detect Aβ accumulators was assessed through receiver operating characteristic analyses. Plasma biomarkers were converted to z‐scores for effective comparison. Pearson correlations were calculated between pTau181 and pTau217.

Results

Plasma pTau217 levels were higher in Aβ accumulators than non‐accumulators with an area under the curve (AUC) of 0.69 (95%CI 0.58‐0.81). Moreover, higher pTau217 predicted steeper Aβ accumulation (βs=0.57, P<.001). Plasma levels of pTau217 strongly correlated with those of pTau181 (r=0.93, Figure 1). In the subgroup with matching pTau181 data, pTau181 was also higher in Aβ accumulators than non‐accumulators with an AUC of 0.68 (95%CI 0.53‐0.84), which was comparable to pTau217 (AUC=0.76; PDeLong=.12) or a multibiomarker model including both pTau species (AUC=0.80; PDeLong=.15) in the same subset (Figure 2A). pTau181 demonstrated comparable associations with Aβ accumulation in terms of both strength (βs=0.53, 95%CI 0.21–0.81 for pTau181 versus βs =0.48 for pTau217 in this subset) and spatial distribution (Figure 2B).

Conclusions

The novel ALZPath pTau217 assay predicted Aβ accumulation in asymptomatic elderly with comparable performance to the ADx pTau181 assay.
An experimental approach to disentangle neurodevelopmental and current factors of influence on brain and cognition: an intervention twin study
Authors: Walhovd Kristine B , Markus Sneve H , Sørensen Øystein , Bråthen Anne Cecilie Sjøli , Falch Emilie Sogn , Garrido Pablo F. , Kransberg Jonas , Slivka Maksim , Alatorre‐Warren José‐Luis , Overbye Knut , Czajkowski Nikolai Olavi , Fjell Anders M
Published: January 2025

Background

Neurodevelopmental origins of functional variation through the lifespan are acknowledged, but pathways need to be identified. The objectives of the project Set‐to‐change is to test whether and how early life environmental factors and genetic makeup regulate brain and cognition and its change, as well as neurocognitive plasticity in response to training through the lifespan.

Method

Preliminary analyses for the first months are presented. We investigate differences in brain and cognition and their change, in adult mono‐ (MZ) and dizygotic (DZ) twins (total n ∼220 individuals, age range 16‐79 years, mean 36), with varying degrees of prenatal environmental variance, as indexed by their extent of discordance in birth weight (BW). Half of the sample trained in a novel navigation intervention utilizing true locomotion in virtual reality, assessed with brain MRI and cognitive measures at pre‐ and post‐ 10 weeks intervention in an AB/BA crossover design. Effects of training on hippocampus volume are analyzed using generalized additive mixed models (GAMM4) accounting for condition (pre‐train, post‐train, post‐rest), sex, age (smooth), time, and time x age. Anatomical brainprints from T1 and T2W scans are used to assess effects of genetic (MZ/DZ) and early environmental (birth weight; BW) differences.

Results

Preliminary analyses indicate a positive effect of training on hippocampal volumes. Differences in behavioral level reached in training, related to differences in BW among MZ twins, but the higher BW twin tended to train more. Using “brainprints” (Valizadeh et al. Sci Rep 2018, 8, 5611) from multicontrast MRI data, we observed that across 10 weeks, self‐similarity was high and could be used for perfect identification of one self and MZ twin, DZ‐similarity also identifiable. Brainprint similarity at baseline varied as a function of BW in MZ twins (Figure 1). BW discordance in MZ twins (n for analysis: 27 pairs) related to degree of functional plasticity, as measured by more whole brain connectome change after training being higher with higher BW.

Conclusion

Twin designs sampling early and current life environmental conditions experimentally, may further enhance our understanding of the impact of early life factors on current outcomes and in adulthood.
Imaging the impact of early and late life risk factors on the brain: a comparison
Authors: Gordon Brian A.
Published: January 2025

Background

Alzheimer disease (AD) is a chronic progressive neurodegenerative disorder that presents with cognitive dysfunction, memory loss, language difficulties, emotion dysregulation, and the eventual loss of motor function and death. Magnetic resonance imaging (MRI) shows early atrophy in the medial temporal lobes, which then spreads to the posterior temporal lobe, parietal lobe, and finally the frontal lobe with relative sparing of the sensorimotor cortex. Social disadvantage has been shown to have potentially additive impacts on aging trajectories.

Over the first years of life the brain undergoes rapid expansion and maturation. Whereas sensory regions are relatively stable from birth, there is tremendous change in the temporal, parietal, and frontal regions which are responsible for higher order cognitive function. This change is paralleled by the development of motor, language, emotion regulation, and executive function. Early life events such as low birth weight, poverty, and adversity can impact neurodevelopment, including cortical expansion and connectivity.

Given this mirroring between regional brain development and degeneration, researchers have hypothesized a “last in first out” mechanism underlying progressive neurodegeneration, but minimum direct comparisons have been performed. longitudinally studies older adults.

Methods

This work brings together unique cohorts spanning the two ends of the lifespan. The Early Life Adversity, Biological Embedding (eLABE) study scans infants scanned longitudinally between birth and age three years of age. The Charles F. and Joann Knight ADRC and ADNI longitudinal follow middle and older‐aged individuals. Structural change is estimated a unique multimodal surface matching (MSM) pipeline that estimates the deformation of pairwise cortical surfaces to estimate cortical expansion or atrophy over time. Analyses will include all children with longitudinal MRI data as well as longitudinal MRI data to characterize healthy aging, individuals who convert to AD, as well as longitudinal change in within individuals with an AD diagnosis.

Results

Preliminary results in each cohort (Figure 1) demonstrate highly similar spatial patterns between early life development and AD related cortical thinning.

Conclusions

Although there has long been speculation that there is a reciprocity between regions that develop in childhood and those vulnerable to age and disease related decline, this work test this theory.
Adult lifespan neurodegeneration is associated with memory decline independent of amyloid deposition
Authors: Roe James M , Jagust William J. , Landau Susan M. , Harrison Theresa M. , Grydeland Håkon , Slivka Maksim , Alatorre‐Warren José‐Luis , Sørensen Øystein , Walhovd Kristine B , Fjell Anders M , Vidal‐Piñeiro Didac , Wang Yunpeng
Published: January 2025

Background

Current models of AD posit neurodegeneration and cognitive decline occur downstream in a pathophsyiological cascade initiated by amyloid (Aβ), yet lifespan research suggests the brain regions and cognitive functions impacted most by AD exhibit the steepest, steady decline rates across life. We hypothesised adult lifespan neurodegeneration in AD‐vulnerable brain regions would predict memory decline rates detectable in healthy adults as they age, independent of Aβ.

Method

We combined MRI scans across three large longitudinal cohorts of cognitively healthy adults (age 30‐96 years) to estimate brain change relative to the change expected given a person’s age (2‐14 timepoints; 4125 scans of 1027 individuals; cohorts: LCBC, the Berkeley Aging Cohort Study [BACS]; ADNI [stable cognitively healthy]). We similarly estimated episodic memory change, as measured by the California Verbal Learning Test (LCBC and BACS; 2356 observations of 601 individuals). Using a set of features we previously determined classifies AD patients from controls (AUC=.952), we ran multivariate models to test associations between brain structure change and memory change. Specifically, we calculated the principal component of change across different subsets of brain features using a sliding window through AD feature importance, iteratively testing its association with memory change. In a subset with PET data (537 Aβ observations of 262 individuals), we tested whether brain‐memory change associations were independent of Aβ. Finally, we tested the spatial correlation between adult lifespan brain change rates in only Aβ‐negative individuals (adults >40 years confirmed Aβ‐negative at every timepoint) and an AD‐control effect size based on change.

Result

Associations between brain structure change and memory change were detectable in healthy adult lifespan data (p=7.0e‐10), present in comparatively young adults (in 30–65‐year‐olds), and strongest in regions changing faster in AD. Correcting for Aβ did not attenuate brain‐memory change associations, though Aβ was independently associated with more memory decline (p=2.7‐3). The spatial correlation between adult lifespan change rates (in Aβ‐negative) and accelerated change in AD was r=.74, p=10‐63.

Conclusion

Our results show neurodegeneration in AD‐sensitive regions exists independently of Aβ, and that such changes are not benign, but track with more memory decline across the healthy adult lifespan.
Association between education and multimodal neuroimaging in men and women across the lifespan
Authors: Gonneaud Julie , TURPIN Anne‐Laure , Vivien Denis , la Sayette Vincent De , Chételat Gael ,   Medit‐Ageing Research Group
Published: January 2025

Background

Education has been associated with reserve mechanisms and lower dementia risk, but the literature shows inconsistent results on the association between education and brain outcomes across the lifespan. Considering that both dementia risk and education are likely to differ between sexes, our study aims at understanding the association between education and brain outcomes across the lifespan and whether it differs by sex.

Method

In 207 healthy individuals (110women) aged 19‐84 years old (47.98±18.75), we investigated the association between years of education and multimodal neuroimaging (structural‐MRI, FDG‐PET, Florbetapir‐PET) and how this association was modulated by age and sex. Analyses were restricted to regions involved in Alzheimer’s disease and/or reserve mechanisms (hippocampal volume, temporoparietal metabolism, neocortical amyloid, anterior and posterior cingulate cortices [ACC/PCC] for each modality).

Result

There was no main effect of years of education on neuroimaging (ps>.09) nor interaction between education and the other variables. However, exploratory interactions conducted within young (18‐40), middle‐aged (40‐60) and older (60+yo) groups separately showed that, only in the older group, sex interacted with education on ACC volume, revealing that education was associated with greater volume only in older women (Figure; pinteraction=.006). Complementary analyses conducted in an independent and larger sample of older adults (n=135, 83women, >65yo) in whom lifestyle was assessed retrospectively, suggest that midlife and late‐late‐life mental engagement, more than early‐life engagement (reflecting mainly education), are related to greater brain outcomes in late‐life (ACC volume, PCC amyloid burden, ACC metabolism). We assessed the moderative effect of sex on these associations and found that the association between grey matter volume and occupation (midlife engagement) was mainly driven by women (pinteraction=.02). The interaction between early‐life engagement and sex on ACC volume highlighted in the main cohort was replicated, yet at a trend‐level (pinteraction=.08).

Conclusion

Our study suggests that education is not strongly associated with age‐related differences in structure, metabolism or amyloid burden. Older women with higher levels of education, however, showed higher ACC volumes. These results suggest that education could promote brain reserve in late life in a sex‐dependent manner. Future studies should investigate the mechanisms behind these differences in brain reserve.
The impact of polygenic risks on neurotransmitter‐related grey matter atrophy in Alzheimer’s disease
Authors: Manca Riccardo , Mitolo Micaela , Bacalini Maria Giulia , Capellari Sabina , Venneri Annalena
Published: January 2025

Background

Tau protein tangles have been recently shown to accumulate in multiple brainstem nuclei in pre‐cortical Alzheimer’s disease (AD) stages. The impact of neurotransmission alterations on brain atrophy and their genetic correlates in AD remain unexplored. Therefore, the aims of this study were: 1) to investigate associations between grey matter (GM) loss across the AD continuum and the distribution of multiple neurotransmitter receptors/transporters; 2) to investigate the impact of polygenic risk scores for AD (PRSs) on such associations.

Method

T1‐weighted MRI scans, genetic and clinical data were selected for 800 ADNI participants (age = 74.1±7.6; M = 55.3%) including 203 cognitively unimpaired older adults (CU), 442 with mild cognitive impairment (MCI) and 155 with AD. GM atrophy was investigated in MCI and AD groups, compared with CU. JuSpace was used to calculate correlations between GM atrophy and the distribution of several neurotransmitters. Two PRSs, with (AD‐PRS) and without APOE (AD‐PRSnoAPOE) were calculated using a Bayesian approach and investigated as predictors of the strength of correlation between GM volume (GMV) and neurotransmitters in general linear models.

Result

GM atrophy was primarily in medio‐temporal areas in MCI, while was widespread in AD participants. In both groups, atrophy was negatively associated with serotoninergic and dopaminergic receptors/transporters. In the whole sample, AD‐PRS and AD‐PRSnoAPOE were negatively associated with the strength of correlation between GMV and 2 serotonin receptors (5‐HT1a and 5‐HT4). AD‐PRS was also associated with GMV‐FDOPA (negatively) and with GMV‐5‐HT1b (positively) correlation coefficients. In amyloid positive participants, AD‐PRS was associated with GMV‐5‐HT1b (b = 0.012, p < 0.001) and AD‐PRSnoAPOE with GMV‐5‐HT4 (b = ‐0.013, p < 0.001) correlation strength only.

Conclusion

GM loss due to AD may be particularly affected by the alterations in inhibitory serotoninergic and in presynaptic dopaminergic activity, that are known to affect acetylcholine function and memory decline. Such alterations appear to be driven by polygenic risk for AD, with potential specific effects dependent on APOE genotype and amyloid status. Investigating further the impact of AD‐PRS on various neurotransmitter‐related neural alterations may help clarifying neuropathological changes in pre‐clinical AD and support early detection of people at risk of dementia.
Demonstration of an open‐source toolbox for network spreading models: regional amyloid burden promotes tau production in Alzheimer's disease
Authors: Thompson Elinor , Schroder Anna , He Tiantian , Legouhy Antoine , Zhao Xin , Cole James H. , Oxtoby Neil P , Alexander Daniel C ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

Background

Connectome‐based models of disease propagation are used to probe mechanisms of pathology spread in neurodegenerative disease. We present our network spreading model toolbox that allows the user to compare model fits across different models and parameters. We apply the toolbox to assess whether local amyloid levels affect production of pathological tau.

Methods

Data: Regional tau‐PET and amyloid‐PET SUVRs from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study were downloaded in September 2023 (demographics in Figure 1). Subjects were separated into groups based on AT disease stage: 1) amyloid‐negative, tau‐negative; 2) amyloid‐positive, tau‐negative; 3) amyloid‐positive, tau‐positive. Positivity thresholds were defined using Gaussian mixture modelling. Data were averaged within groups to produce stage‐specific maps.

Spreading models

We compared three models: the network diffusion model, Fisher‐Kolmogorov‐Petrovsky‐Piscounov (FKPP) and weighted‐FKPP models (Figure 2). Previously we showed that weighting the production rate of FKPP with regional vectors improves the model fit by accounting for different regional characteristics (He et al, MICCAI 2023). Here, we demonstrate this new “weighted‐FKPP” model, using regional amyloid as the fixed production weight. Models were initialised with unity pathology in a bilateral seed region, zero elsewhere.

Parameter optimisation

Free parameters were fitted using Gaussian processes optimisation (α and seed region).

NDM toolbox

All models are available in our toolbox: https://github.com/ethompson93/network_spreading_models.

Null Modelling

we repeated the weighted‐FKPP model optimisation with a distribution of 100 randomly shuffled amyloid maps to demonstrate the spatial significance of the amyloid weighting.

Result

Adding amyloid weighting to the production term in the FKPP model improved the model fit to the data for each group. The reduction in squared model residuals with the weighted FKPP model was significant only in the amyloid‐positive tau‐positive group (Figure 3). For all groups, the results from the FKPP weighted with amyloid had significantly improved model fit (Pearson’s R) compared to the null model (all p‐values<1×10‐10).

Conclusion

Using our toolbox, we found that incorporating regional amyloid levels improves pathology‐spreading model fit to measured tau‐PET data, particularly at later stages of AD. This supports the hypothesis that amyloid promotes tau aggregation.