bluuebunny/crossref_metadata_2025 huggingface dataset:
Volumes of specific substructures within the Amygdala and Hippocampus are impacted by brain amyloid‐β
Authors: Murali Leema , Charil Arnaud , Reilhac Anthonin , Qi Xin
Published: January 2025

Background

Reductions in medial temporal lobe (MTL) volume, particularly in the amygdala and hippocampus, are present in early Alzheimer's disease (AD). We explore the correlations between hippocampal and amygdalar subfield volumes and brain amyloid‐β (Aβ) accumulation using T1‐weighted structural MRI and amyloid PET data from ADNI and Eisai clinical trials.

Method

We used FreeSurfer (v7.2.0) and a high‐resolution MRI‐based probabilistic atlas using Bayesian inference to measure volumes of hippocampal and amygdalar sub‐structures in one of Eisai’s clinical trial cohorts and ADNI (3113 and 1443 subjects), mostly with MCI due to AD (>80% and 45%, respectively). In Eisai’s clinical cohort, Aβ positivity was established through a concordance between PET visual assessment and Centiloids (CL), using a threshold of 32.21. In ADNI, Aβ positivity was defined by CL using a threshold of 20. We first evaluated correlations between baseline CL and volumes of hippocampus and amygdala substructures. For predicting brain amyloid burden, machine learning models, including stochastic gradient boosting, were applied in conjunction with cognitive and demographic information.

Result

In Eisai’s clinical cohort, amygdalar subfields were more strongly correlated (p<0.05) with global amyloid levels than hippocampal subfields. Global amyloid is inversely associated with amygdala and hippocampal volumes, with the strongest correlations being with the amygdala accessory basal nucleus (left ‐0.41. right ‐0.40). This regional association with global amyloid is more significant than with the entire amygdala (left ‐0.36, right ‐0.35, p<0.05). Both the whole hippocampus (‐0.36) and its subfields (hippocampal GC‐ML‐DG (Granule Cell (GC) and Molecular Layer (ML) of the Dentate Gyrus (DG))‐body, subiculum‐body, and tail) showed equivalent correlations with global amyloid levels.

Machine learning models indicated that hippocampal/amygdalar subfields are better predictors of amyloid positivity than MTL volumes (increase in AUC from 66% to 70% (p<0.05)), which improved to 78% when adding ApoE4. Consistent with the results of the correlational analyses, the accessory‐basal nucleus, and hippocampal tail and fissure were among the top predictors in this model.

Conclusion

This analysis emphasizes the importance of specific hippocampal and amygdalar substructures that are impacted by amyloid in early AD, with implications for staging and disease progression monitoring.
Longitudinal changes in neuroimaging markers of small vessel disease: Implications for clinical trials
Authors: Lao Patrick J. , Edwards Natalie C. , Flores‐Aguilar Lisi , Rizvi Batool , Smith Anna C. , Tudorascu Dana , Rosas H. Diana , Yassa Michael A. , Handen Benjamin L , Christian Bradley T. , Gutierrez Jose , Wilcock Donna M. , Head Elizabeth , Brickman Adam M.
Published: January 2025

Background

Adults with Down syndrome (DS) overproduce amyloid precursor protein, develop amyloid plaques at an early age, and are diagnosed with Alzheimer’s disease (AD) dementia at a high frequency. There is emerging evidence that cerebrovascular disease is elevated across the AD continuum in older adults with DS, independent of age and vascular risk, around the same time as amyloid and tau, but the regional rates of accumulation within individuals are unknown.

Method

Adults with DS from the multisite Alzheimer’s Biomarker Consortium‐Down Syndrome study (ABC‐DS; n=78; age=50±6; 40% women) have two timepoints of T2 FLAIR MRI (1.2±0.6 years apart) quantified as white matter hyperintensity volume (WMH), which represents ischemic small vessel disease. Participants underwent consensus diagnosis at both timepoints (59% Cognitively‐Stable at both timepoints, 9% Cognitively‐Stable to MCI‐DS, 8% MCI‐DS at both timepoints, 14% MCI‐DS to AD, 10% AD at both timepoints). The annual rate of change in frontal, temporal, parietal, and occipital WMH volume was assessed, adjusting for baseline WMH volume.

Result

The annual rate of change in frontal WMH was not significantly different by diagnosis. The annual rate of change in temporal (0.7 [0.4, 1.1], p<0.001) and in occipital WMH (1.6 [0.7, 2.5], p=0.0008) was faster in the group that remained AD at both timepoints compared to the group that remained Cognitively‐Stable at both timepoints. The annual rate of change in parietal WMH was greater in the group that progressed from MCI‐DS to AD (0.6 [0.1, 1.0], p=0.02) and in the group that remained AD at both timepoints (1.1 [0.6, 1.7], p=0.0002) compared to the group that remained Cognitively‐Stable at both timepoints.

Conclusion

In adults with DS, parietal WMH accumulates fastest in those that progress to or have a diagnosis of AD, while temporal and occipital WMH accumulate fastest in those with a diagnosis of AD. Posteriorly distributed WMH may have specificity for AD progression in adults with DS with implications for anti‐amyloid therapeutics that have cerebrovascular side effects.
A simple measure of voluntary control of breathing is an effective physio‐marker for differentiating MCI from mild AD patients and MCI/AD patients from cognitively normal controls
Authors: Marmarelis Vasilis , Chui Helena C , Billinger Sandra A , Joe Elizabeth B , Shin Dae , Hashem Suhaib , Rizko Jasmin , Hazen Emily , Cardim Danilo , Zhang Rong
Published: January 2025

Background

Control of breathing is known to be adversely affected by cognitive impairment, often associated with sleep apnea or disordered breathing during sleep in MCI/AD. The origin of this disorder is thought to be in the dysfunction of the respiratory control centers of the brainstem or in the impaired afferent signaling from cortical regions. Continuous breathing data were collected in a multi‐center study in Los Angeles (USC), Kansas City (KUMC) and Dallas (UT‐SWMC), and used to compute respiratory rate variability (RRV) to test the hypothesis that voluntary control of breathing is impaired in MCI and mild AD patients relative to cognitively normal controls, and whether this impairment is more severe in mild AD than MCI patients.

Method

The collected continuous breathing data were used to compute the RRV as the standard deviation of breath‐to‐breath respiratory rate variations during metronome‐guided slow‐paced breathing (6 breaths per minute) over 5 minutes under supine resting conditions for each of 61 MCI, 32 mild AD patients and 78 age/sex‐matched cognitively normal controls. The computed RRV was used to quantify and compare the voluntary control of breathing for all participants.

Result

The resulting p‐values of mean‐difference t‐tests were:

• Controls vs. MCI patients: 0.304 (0.145) vs. 0.393 (0.222), p = 0.0039

• Controls vs. AD patients: 0.304 (0.145) vs. 0.561 (0.258), p = 2.4E‐06

• Controls vs. MCI & AD patients: 0.304 (0.145) vs. 0.451 (0.247), p = 1.7E‐06

• MCI vs. AD patients: 0.393 (0.222) vs. 0.561 (0.258), p = 0.0014

The results are shown in Figure 1 as box‐whisker plots. The p‐values showed significant mean‐differences in all four cases, with comparisons against mild AD patients showing greater differentiation. The observed mean RRV values showed stratification of impairment: 0.393 for MCI vs 0.561 for mild AD, relative to 0.304 for controls.

Conclusion

Quantitative analysis of a simple measure of voluntary control of breathing during metronome‐guided slow‐paced breathing under supine resting conditions showed significant mean‐differences between 61 MCI patients, 32 mild AD patients and 78 age/sex‐matched cognitively normal controls (see Figure 1), suggesting that the RRV physio‐marker has the potential to aid in the diagnosis of MCI and mild AD.
Validation of Clinical Decision Support Recommendations of a Digital Cognitive Assessment by Expert Cognitive Neurologists
Authors: Jannati Ali , Toro‐Serey Claudio , Gomes‐Osman Joyce Rios , Morrow William Isaiah , Ciesla Marissa C , Banks Russell , Bates David , Tobyne Sean , Showalter John , Pascual‐Leone Alvaro
Published: January 2025

Background

Disease‐modifying treatments for Alzheimer’s disease highlight the need for early detection of cognitive decline. However, most primary care providers do not currently perform routine cognitive testing, in part due to a lack of time and resources to administer and interpret the tests. Brief, self‐scoring, and sensitive digital cognitive assessments, such as the Linus Health Core Cognitive Evaluation (CCE)–which includes the Digital Clock and Recall (DCR™) and the Life and Health Questionnaire (LHQ)–can automatically provide medically‐informed recommendations that can address this need. Here we evaluate the clinical appropriateness of the recommendations generated by this clinical decision support (CDS) tool to guide the diagnosis of cognitive impairment by primary care providers (PCPs).

Method

The CDS tool uses data from the CCE to list potential medical concerns and recommend pathways toward formal diagnosis and/or care. We conducted a retrospective expert‐review study in June 2023 to evaluate the nine CDS pathways for patients aged 55 and above. Experts were five board‐certified cognitive neurologists affiliated with academic institutions. We calculated the median ratings (on a scale of 1 to 9, where 9 is high appropriateness) for the nine CDS pathways across raters. A rating of 7 or above was deemed clinically appropriate.

Result

All 7 pathways related to cognitive impairment received a clinically appropriate rating (median = 7, SD = 0.3, range=7‐8). Pathways below the appropriateness threshold included the one for Green DCR scores (i.e., cognitively unimpaired; median = 6, SD = 0.87) and a preliminary Lecanemab eligibility pathway (median = 5, SD = 1.10).

Conclusion

Pathways and the cognition‐related recommendations generated by the CDS tool of the Linus Health CCE are clinically appropriate, as rated by this initial survey of board‐certified, academic cognitive neurologists. The findings indicate the clinical utility of digital cognitive assessments such as the CCE for guiding the PCPs’ approach to diagnosis and management of patients with cognitive impairment.
Unique gut microbiome signatures associated with physical and cognitive function
Authors: Nair Sridevi U , Lin Yi , Jain Shalini , Chaudhari Diptaraj S , Shukla Rohit , Kumar Vivek , Mankowski Robert T , Meng Hongdao , Buford Thomas W , Kuchel George A , Yadav Hariom , Consortium MiaGB
Published: January 2025

Background

Emerging studies suggest the interaction of the gut microbiome with physical and cognitive function. However, it remains unknown whether the same microbiome is linked with both functions and/or if they are unique.

Method

Utilizing data and samples from the Microbiome in Aging Gut and Brain (MiaGB) Consortium cohort, we assessed the whole genome gut microbiome metagenomics in 113 older adults (mean age 72 years [39 male and 74 female]) with high and low physical functions (measured using Short Physical Performance Battery [SPPB]) and cognitive function (measure using Montreal Cognitive Assessment [MoCA]). Based on the SPPB score, participants were categorized into low (score: 3‐9) and high (score: 10‐12) physical function groups, while based on MoCA score, mild cognitive impaired (MCI; MoCA:18‐25) and cognitively healthy (MoCA: 26‐30).

Result

We observed the presence of distinct and specific microbiome signatures that are uniquely associated with the low and high physical functioning groups, as opposed to those specific to cognitive functioning. Specifically, in low physical functioning group Bacteroidacea and Rikenellaceae were increased and Clostridiaceae were decreased compared to high physical functioning group. On the other hand, Streptococcaceae decreased in low cognitive function group compared to cognitively healthy people. Increase in the ratio of Firmicutes ‐Bacteroidetes was specific for physical activity, whereas the increase in the ratio of Actinobacteria‐Proteobacteria was specific for cognitive function.

Conclusion

Differentiating unique and specific microbiome signatures for physical function and cognitive function represents significant progress in the field of the gut‐brain axis. Our results support the distinct impact of the microbiome to impact the gut‐muscle axis versus the gut‐brain axis; and opens the doors for further comprehensive studies to determine the causal role of the microbiome in physical and cognitive functions, as well as its potential to be a biomarker for predicting the risk of decline in these functions in older adults – two of the most debilitating public health problems in older adults.
Evaluating the Role of Kidney Function and Comorbidities in Observed Racial/Ethnic Differences in Blood‐based Biomarkers of Neurodegeneration: Results from the Einstein Aging Study (EAS)
Authors: Garza Angel Garcia De La , Wang Cuiling , Derby Carol A. , Lipton Richard B. , Zetterberg Henrik , Engeland Christopher G. , Katz Mindy J.
Published: January 2025

Background

Recent research reveals that Alzheimer’s Disease blood‐based biomarkers (BBB) are influenced by demographics as well as kidney function and comorbidities. Data on differences in BBBs by race and ethnicity are sparse. We examined whether racial/ethnic differences in BBBs persist after controlling for kidney function and comorbidities.

Methods

Analyses included data from 274 EAS participants (mean age 77.57, SD 5.01, 67.5% Female, 46.4% Non‐Hispanic‐White, 41.2% Non‐Hispanic Black, 12.4% Hispanic). BBBs included β‐amyloid (Aβ40, Aβ42), Aβ42:Aβ40 ratio, pTau181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Estimated glomerular filtration rate (eGFR) was calculated using either age‐sex‐race‐adjusted (eGFR‐ASR) or age‐sex‐adjusted (eGFR‐AS) creatinine equations (Inker et al., 2021 NEJM). History of hypertension, diabetes, stroke, myocardial infarction, angina, and congestive heart failure were ascertained by self‐report. Linear regression was used to assesses race/ethnic differences in BBBs adjusted for age, sex, BMI, and MCI status. Further models adjusted for eGFR‐AS, eGFR‐ASR, and comorbidities. Non‐Hispanic Whites were treated as the reference group.

Results

Initial models indicated significantly lower Aβ40 in non‐Hispanic Black and Hispanic (global p = 0.014) individuals and lower Aβ42 in non‐Hispanic Black (global p = 0.005) individuals compared to non‐Hispanic Whites. Further adjustment for using eGFR‐ASR attenuated racial/ethnic differences for Aβ40 (p = 0.099) and Aβ42 (p = 0.038), while adjustment using eGFR‐AS did not. We observed lower levels of NfL in non‐Hispanic Blacks and Hispanics (p = 0.003) adjusting for age, sex, BMI, and eGFR‐AS but not when adjusting for eGFR‐ASR. Both eGFR‐ASR and eGFR‐AS were negatively significantly associated with all BBBs. None of the comorbidities were significantly associated with any of the BBBs, and adjusting for comorbidities did not impact the observed racial/ethnic differences.

Conclusion

Race/ethnic differences in Aβ40 and Aβ42 levels persisted after adjusting for eGFR‐AS and comorbidities. Race differences in BBBs were reduced in magnitude when adjusting for eGFR‐ASR, but not when adjusting for eGFR‐AS. Future research should pursue adjustment using the more accurate cystatin‐C eGFR equation to determine whether race differences persist. Understanding these biomarker level differences across various races/ethnicities is crucial for the future of personalized and effective diagnosis, progression monitoring, and treatment of Alzheimer's Disease.
Different functional structures of the brainstem according to dementia subtypes
Authors: Gi Kim Seul
Published: January 2025

Background

The extent of neurofibrillary changes, one of the pathological hallmarks of AD, correlates with the severity of AD in dementia. The brainstem is known to be the site of neurofibrillary changes in the early stages of Alzhimer’s disease. The neurotransmitter system in the brainstem processes information from subcortical and cortical circuits affect to various cognitive and behavioral responses in the cerebral cortex. This study aims to investigate we cluster the brainstem with respect to how they connect to the cortex and focus on the brainstem cluster of differences according to the subtypes of AD.

Method

We acquired the resting state fMRI data from 137 patients with several dementia types (96 females, mean age = 70.31 ± 7.13), which were collected from the BICWALZS (Biobank Innovation for chronic Cerebrovascular disease With ALZheimer's disease Study). They were divided into four dementia subtype groups: subjective cognitive decline(SCD) mild cognitive impairment(MCI)‐β‐amyloid negative(MCI‐), MCI‐β‐amyloid positive (MCI+), and AD (N=33). For physiological denoising in functional neuroimaging data of the brainstem, we used FSL's ICA‐AROMA, a data‐driven denoising approach. We extracted each regional‐mean time series using Schaefer 200 atlas and voxel‐wise time series of brainstem. A functional connectivity matrix is composed of the brainstem‐to‐cortex that regressed out dominant pattern, which is the weights of the connectivity across all 200 cortical regions that the brainstem had. Then we clustered the brainstem based on modularity according to the extent of connectivity similarity between the brainstem and cortex via connectivity matrix profiles. Finally, our study focused that comparison the pattern of clustering according to the subtypes of AD.

Results

We found that each community in the brainstem is a group with a similar pattern of functional connectivity to the cortex. Different brainstem communities are observed in the distinct in accordance with the subtypes of AD, suggesting that in each disease group can characterize specific brainstem communities with functional connectivity to the cerebral cortex.

Conclusion

Different patterns of clusters in different subgroups of dementia may explain functional abnormalities in the brainstem as dementia progresses. The future study will characterize each connection between clusters of brainstem and cortical regions
Evaluation of a person‐centred care model for persons living with dementia in the hospital rehabilitation setting using the RE‐AIM framework
Authors: Burley Claire V , Williams Anna , Maiden Genevieve , Reyes Patricia , Cook Jacquelene , Brodaty Henry , Chenoweth Lynnette
Published: January 2025

Background

One in four persons living with dementia are admitted to hospital, presenting challenges to them, their carers and staff. Despite global evidence demonstrating the clinical and cost‐effectiveness of person‐centered care (PCC), it is not yet business as usual across healthcare settings. We used multi‐level stakeholder input to implement Kitwood’s PCC model into a sub‐acute setting.

Methods

Between June 2021 to June 2023, the PCC model was implemented and evaluated using the Consolidated Framework for Implementation Research (CFIR) and quantitative and qualitative methods to address the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE‐AIM) framework. Key stakeholders and a strong governance structure including persons living with dementia, family caregivers, clinicians, nurses, hospital leaders, community partners, government officials and policy makers, informed all aspects of implementation and evaluation. Co‐primary outcome measures were delirium and agitation. Data were collected pre‐, post‐ and 6‐months following PCC education.

Results

Reach: Ninety nursing, medical and allied health staff (93% of hospital staff) completed online and/or in‐person PCC education; eight senior staff leaders completed in‐person PCC education and took on the role of ‘PCC Champion’ to support staff in implementing PCC. Effectiveness: Significant improvements (all p<.05) were observed in outcomes for persons living with dementia: delirium (phi = 0.73), incidents/injuries (phi = 0.99), psychotropic medication use (phi = 0.09), and readmissions (phi = 0.25). No change was observed for agitation. Adoption: Staff knowledge of and confidence in delivering PCC significantly improved (both p<.005). A significantly higher number of positive (person‐centered) interactions was observed following education (p = 0.000, phi = 0.60), though there was also a high number of neutral interactions. Implementation: PCC education delivery could and was efficiently adapted as required to unplanned crises (i.e. COVID‐19 pandemic). Maintenance: Six‐month follow‐up data showed staff maintained improved PCC knowledge and confidence (both p<.005). However, only three of the eight PCC Champions remained. Suggested modifications to aspects of the model include adopting reflective feedback processes with staff, PCC education for non‐clinical staff, reducing online content to fewer modules, and adapting the education to suit specific cultural groups.

Conclusions

The successful translation of a PCC education model into a sub‐acute rehabilitation setting during a global pandemic has implications for policy and practice.
Does the Current Evidence for Lecanemab Mechanism Support a Rationale for Continued Lecanemab Dosing?
Authors: Selkoe Dennis J. , Dhadda Shobha , Irizarry Michael C. , Kramer Lynn D
Published: January 2025

Alzheimer’s disease pathophysiology is believed to involve various abnormalities, including those of amyloid beta (Ab) peptide and tau processing, inflammation, oxidative stress, and vascular risk factors. Aβ peptides exist in a dynamic continuum of conformational states from monomeric Aβ, to soluble progressively larger Aβ assemblies that include a range of low molecular weight oligomers to higher molecular weight protofibrils, and finally to insoluble fibrils (plaques). Various lines of evidence support the “amyloid hypothesis” that Aβ plays a central role in the pathogenesis of AD, and several immunotherapies have been developed to interact with this cascade in various different places which may reduce the number of soluble aggregates and insoluble Aβ fibrils deposited in the brain. Lecanemab is a novel humanized immunoglobulin G1 (IgG1) anti‐amyloid monoclonal antibody with highest affinity for Aβ protofibrils, a particularly toxic Aβ species. Lecanemab distinguishes itself from other anti‐amyloid antibodies in that it selectively targets large soluble protofibrils relative to monomers (greater than 1000‐fold over Aβ monomers), with preferential activity over insoluble fibrils (up to 10‐fold over fibrils). In the phase 3 Clarity AD study, lecanemab demonstrated a consistent slowing of decline over 18 months in clinical (global, cognitive, functional, and quality of life) outcomes which if used early in the clinical paradigm has shown to slow disease progression for up to 30 months, and reduction in brain amyloid in early Alzheimer’s disease. Herein, we will highlight the mechanism‐based rationale for continued lecanemab dosing, providing both the current supportive evidence and outstanding questions. Relevant Alzheimer’s disease background will be discussed, including the impact of the latest diagnostic criteria. We will share insights on Alzheimer’s disease pathophysiology, including how the ongoing/chronic nature of the disease requires continuous therapy. In addition, we will review the latest data on lecanemab mechanism and overview of the mechanistic rationale for development of lecanemab Aβ immunotherapy. The role of tau aggregates, a predictive biomarker for the emergence of neurodegeneration, will be explored. Additional insights on continued dosing based on current knowledge of lecanemab mechanism will be shared. An overview of the mechanistic differences and their implications among anti‐amyloid antibodies will be presented.
Generalizability of demographic and genetic variable interactions with amyloid driving tau burden in a heterogeneous group of cognitively normal older adults: A multi‐cohort study
Authors: Harrison Theresa M. , Ward Tyler J. , Chadwick Trevor , Taggett Jacinda , Baker Suzanne L. , Braskie Meredith N , Landau Susan M. , Jagust William J. ,   the U.S. POINTER Study Group, the Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

Background

Efforts to increase heterogeneity in cohorts of cognitively normal older adults with Alzheimer’s disease (AD) neuroimaging biomarkers have resulted in large datasets with differing characteristics. It is unclear whether associations between AD biomarkers and key demographic and genetic factors are generalizable across heterogeneous cohorts.

Method

PET and MR scans from cognitively normal older adults aged >55 in the Berkeley Aging Cohort Study (BACS), ADNI, the Health and Aging Brain Study‐Health Disparities (HABS‐HD) and POINTER Imaging were processed using harmonized pipelines. Global beta‐amyloid (Aβ) burden was quantified in centiloids (CL). Tau‐PET SUVRs in entorhinal cortex (ERC) and a temporal MetaROI were z‐scored using tracer‐specific reference cohorts of cognitively normal, Aβ‐ adults aged 60‐70yrs. Key demographic and genetic data (sex, race/ethnicity and APOE genotype) were obtained for each cohort and harmonized. Robust linear models predicting tau burden were used to test for interactions between these variables and continuous Aβ in a pooled sample and in cohort‐specific models. Cohort and age were covariates.

Result

A total of 2,114 cognitively normal older adults were included across 4 cohorts which differed on many characteristics (Table 1). In pooled analyses, there was a sex by Aβ interaction on ERC (but not MetaROI) tau such that women had disproportionately more tau as Aβ increased (Table 2; Figure 1 shows raw data). In models focused on race/ethnicity, non‐Hispanic white individuals had more tau as Aβ increased compared to Black individuals. In models predicting ERC or MetaROI tau, e3/e4 or e4/e4 (versus e3/e3) individuals had higher tau as Aβ increased, respectively. Age and global Aβ were significant predictors in all models. In cohort‐specific analyses, findings were inconsistently replicated such that some results from the pooled sample were not observed in any individual cohort, and some cohort‐specific results were not observed in the pooled sample (Table 2).

Conclusion

In a combined cohort analysis, sex, race/ethnicity and APOE interacted with Aβ on tau burden in unimpaired older adults. However, there was little between‐cohort consistency in associations between sex, race/ethnicity, APOE, and AD biomarkers, suggesting that cohort heterogeneity and statistical power have major influence on the observation of these effects.
Genetic predisposition to AD and inflammation determine vulnerable brain regions to air pollution
Authors: Vilor‐Tejedor Natalia , Genius Patricia , Rodríguez‐Fernández Blanca , Anastasi Federica , Cirach Marta , Nieuwenhuijsen Mark , Minguillón Carolina , Esteller Manel , Navarro Arcadi , Gispert Juan Domingo
Published: January 2025

Background

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

Methods

A total of 1,153 individuals from the ALFA cohort, many within the Alzheimer’s continuum, with available genotyping, air pollution estimation and magnetic resonance imaging were included (62.6% women, average age 55,6 years). Land use regression models were used to estimate individual levels of air pollution, including nitrogen oxide (NO2) and particulate matter (PM2.5, PM10), at the participants’ residential addresses. Functional genetic scores, including plasma pQTLs for inflammatory markers (PRS‐CCL2, PRS‐IL6, PRS‐CCL19), CSF pQTLs for AD pathology (PRS‐Aβ42, PRS‐ptau), genetic predisposition to clinical AD (PRS‐AD), and APOE‐ε4 carriership, were assessed. General linear models, corrected for age at MRI visit, sex and years of education, were computed to assess the main effects of air pollution on brain volumes. Modifiable genetic effects in gene‐environment interaction models were investigated.

Results

Individuals at higher genetic predisposition to AD and APOE‐ε4 carriers exhibited increased vulnerability to air pollution, particularly in temporal and frontal regions [Figure 1A]. Individuals with high genetic predisposition for inflammatory markers showed distinct patterns of vulnerability, particularly affecting regions within the parietal and limbic lobes, with notable impact on hippocampal volumes and the subfields within the hippocampal formation [Figure 1B]. Finally, as pollution levels increased, reduction in transverse temporal volumes was observed in individuals at high risk of AD and altered CCL2 protein plasma levels [Figure 2]. Multiple comparison corrections were performed within brain lobes by regions.

Conclusions

Our results suggested a differential impact of air pollution on brain structure, modulated by genetic predisposition to AD and inflammation. This underscores the importance of considering genetic information when assessing the neurological impact of environmental exposures. These findings pave the way for more personalized approaches in public health interventions, and highlight the need for targeted strategies to mitigate the impact of environmental factors on neurological health.
Achieving micron‐level precision MR‐Histology correlation for validating Alzheimer’s disease biomarkers in the human hippocampus
Authors: Wang Yixin , Ho William Hai Dang , Huszar Istvan N. , Taghavi Hossein Moein , Nirschl Jeffrey , Leventis Samantha , Schlömer Philip , Axer Markus , Shao Wei , Rusu Mirabela , DiGiacomo Phillip , Georgiadis Marios , Zeineh Michael
Published: January 2025

Background

MRI offers potential noninvasive detection of Alzheimer's micropathology. The AD hippocampus exhibits microscopic pathological changes such as tau tangles, iron accumulation and late‐stage amyloid. Validating these changes from ultra‐high‐resolution ex‐vivo MRI through histology is challenging due to nonlinear 3D deformations between MRI and histological samples. We aim to address the challenge by a pipeline (Figure 1) for precise alignment of post‐mortem MRI data with histological images.

Method

A human hippocampal specimen was dissected from a formalin‐fixed human brain and divided into hippocampal head and tail. We obtained high‐resolution multi‐echo gradient echo ex vivo MRI of each using a 7T Bruker scanner. The specimens were paraffin‐embedded and sectioned using a Leica Histocore Nanocut R microtome. An optical image of the tissue block's surface was captured before each section was cut (Blockface image) using a polarized filter at Brewster’s angle. The obtained 2D blockface images were aligned and filtered into 3D blockface volumes. These were registered with MRI using either Tensor Image Registration Library (TIRL) with Modality Independent Neighbourhood Descriptor, or ANTs SyN registration. Subsequently, the 2D MRI slices corresponding to the stained histology slides were identified in the 3D volume and underwent 2D deformable registration with TIRL or ANTs. To quantify the registration accuracy, we segmented hippocampal volumes into white matter, grey matter, and dentate gyrus for MRI, blockface, and histology data separately.

Result

When comparing 3D MR and blockface 3D image segmentations (Figure 2, top), the average Dice similarity coefficient of hippocampal head and tail were 86.2% and 86.76% with TIRL, and 83.91% and 78.26% with ANTs SyN. Evaluating 2D MR registration to histological images, TIRL achieves the average Dice coefficient of 94.12% and 96.95%. ANTs performs marginally better across the whole tissue mask, but TIRL shows superior performance in the internal features (Table 1). High‐fidelity alignment shows very small features such as focal hypointensities (Figure 2, bottom, blue circles) and the dentate granule cell layer (orange arrows).

Conclusion

Our advanced correlative MRI‐histology pipeline achieves micron‐level precision coregistration methods at micron‐scale precision, propelling the development of MRI‐based AD biomarkers.
A lower plasma odd chain fatty acids composition accompanies a significant increase in the desaturase index in Alzheimer’s disease
Authors: Jose Joby , Fonteh Alfred N.
Published: January 2025

Background

Odd‐chain fatty acids (OCFA) are gut microbiota‐derived metabolites that are important in energy generation, neuronal signaling, and memory. Since the composition of the gut microbiota affects cognitive function, we hypothesize that plasma saturated OCFA composition may be altered in AD compared to cognitively healthy older adults.

Method

Older adults (>65 years) were recruited, and demographic and neurological data obtained in an ongoing brain‐aging project. Participants were classified as cognitively healthy (CH) or clinically probable AD (AD) based on a comprehensive neuropsychological assessment. Overnight fasting plasma was collected, and unesterified fatty acids were extracted using acidified ethyl acetate. Plasma saturated OCFA (sOCFA: FA 5:0, FA 7:0, FA 9:0, FA 11:0, FA 13:0, FA 15:0, FA 17:0 & FA 19:0) and monounsaturated OCFA (mOCFA: FA 11:1, FA 13:1, FA 15:1, FA 17:1 & FA 19:1) compositions were measured using liquid chromatography tandem mass spectrometry after derivatization with dimethylaminophenacyl bromide (DmPABr). OCFA compositions were determined as a percentage (± SD, 95% CI) of 42 fatty acids detected in plasma, and the CH to AD differences were determined using Mann‐Whitney tests.

Result

Eight sOCFAs (FA 5:0‐FA 19:0) and five mOCFAs (FA 11:1‐FA 19:1) were detected and quantified in plasma. The findings indicated a general trend of decreased sOCFA in AD plasma as compared to CH plasma (Figure 1). The total sOCFA composition in CH (0.24 ± 0.18, 0.09–0.39, n = 8) was higher than in AD (0.1 ± 0.07, ‐0.09–0.25, n= 4, p= 0.0545). The desaturase index (ratio of mOCFA to sOCFA) for FA:11, FA:13, FA:17, and FA:19 was significantly higher in AD than in CH (Figure 2). The total CH (0.52 ± 0.14, 0.41‐0.64) desaturase index was significantly lower (p< 0.05) than in AD (0.86 ± 0.32, 0.34‐1.38).

Conclusion

These data suggest that AD participants have a lower plasma sOCFA composition, which may be due to enhanced conversion of sOCFA to mOCFA, as evidenced by a higher desaturase index in AD compared to CH. Therefore, measurement of plasma sOCFA can be used to monitor AD‐associated lipid metabolism and pathways linked to microbiome status.
Comparison of local amyloid PET uptake patterns between black and white participants in the GAP Bio‐Hermes study
Authors: Wolz Robin , McGinnity Colm J , Joules Richard , Hughes Lynne , Mohs Richard , Dwyer John , Beauregard Douglas W.
Published: January 2025

Background

Amyloid status is a core marker of Alzheimer’s disease and can be defined qualitatively through expert neuroradiologist visual read and quantitively through SUVR analysis. We investigate differences in amyloid status classification between racial groups.

Method

We analysed data from 944 participants enrolled in the Global Alzheimer’s Platform (GAP) Bio‐Hermes trial. After exclusion of technical failures (N=9), subgroups in the ‘Non‐Hispanic or Latino’ population were defined as follows: Group 1 ('Black or African American') and Group 2 (‘White’; see Table 1).

Result

GCA SUVR was not statistically different between Groups 1/2 for pooled data. Figure 1a reveals that Aβ‐ participants in Group 1 had notably less occurrence of lower GCA SUVR values compared with Group 2, which resulted in a higher mean SUVR, driving the significant group difference observed between Aβ‐ participants (p<0.001).

Aβ+ fraction based on visual read was 24% in Group 1 and 37% in Group 2; these fractions change to 38% and 41% respectively with a threshold of GCA SUVR > 1.1.

Significant group differences were observed for Aβ‐ participants in the SUVRs for Grothe Stages 2, 3, and 4 (p <0.001, Figure 1b).

In Aβ‐ subjects, statistically significantly higher SUVR was observed in ‘Black or African American’ participants (Group 1) compared to ‘White’ participants (Group 2) for the caudate, medial temporal, parietal and frontal lobes (p < 0.05 with Bonferroni correction).

Conclusion

Our findings suggest there may be differences in patterns of amyloid deposition between racial groups that may confound quantitative and visual classification of amyloid status. Further study is required to understand a potential impact on determining amyloid state for populations under‐represented in the definition of current criteria.
All WMH are not of purely vascular origin: existence of AD‐related WMH
Authors: Garnier‐Crussard Antoine , Chételat Gael
Published: January 2025

White matter hyperintensities (WMH) are highly prevalent in aging and Alzheimer’s disease (AD) and typically attributed to vascular damage and cerebral small vessel disease. Yet, several lines of evidence from the literature emphasize the heterogeneity in the mechanisms leading to WMH, notably in AD, suggesting that WMH may be partly attributable to AD.

Thus, firstly, neuropathological studies demonstrate heterogeneity in WMH histology, with indications of a link between tau pathology, Wallerian degeneration, and WMH severity. Secondly, in AD, WMH are an early event, partly independent of vascular risk factors, suggesting a specific AD‐related pathway leading to WMH. Thirdly, WMH topography in AD differs from age‐related WMH, globally mirroring patterns of neurodegeneration. Fourthly, genetic studies and biomarker analyses further support the association between AD and WMH. Potential mechanisms for AD‐related WMH are Wallerian degeneration due to proteinopathies (tau and amyloid) and neuroinflammation – in addition to vascular mechanisms, including the contribution of cerebral amyloid angiopathy.

Building upon this evidence, we propose an alternative hypothesis challenging the exclusive vascular origin of WMH. This alternative hypothesis posits that, beyond purely vascular AD‐independent WMH, a subset of WMH, termed AD‐related WMH, is linked to AD pathology (see Figure 1).

To test the hypothesis of distinct etiologies for WMH in AD (vascular versus AD‐related), we extracted the signal within the WMH from different neuroimaging modalities (T1 and T2 MRI, AV45 and FDG PET) in 142 participants (IMAP cohort), and i) performed cluster analyses to reveal distinct clusters representing WMH with varied properties; and ii) compared clinical groups (cognitively unimpaired/impaired) or amyloid status (positive/negative) to highlight AD‐related differences in WMH signals. Our findings offer initial support for our hypothesis; they show for instance higher T1 and lower T2 intra‐WMH signal in the frontal and parietal lobe in amyloid positive compared to amyloid negative participants (Figure 2).

In conclusion, we advocate for a nuanced perspective of WMH etiology in AD, going beyond traditional vascular origins and acknowledging the potential contributions of AD‐related mechanisms. A comprehensive interpretation of WMH will undoubtedly advance our understanding of AD pathology and guide more effective diagnostic and therapeutic approaches.
The generalizability of proposed reference values of plasma neurofilament light chain level in Thai healthy population
Authors: Supaksirakol Paramee , Hemachudha Pasin , Hiransuthikul Akarin , Luechaipanit Watayuth , Haethaisong Thanaporn , Chongsuksantikul Adipa , Hemachudha Thiravat , Thanapornsangsuth Poosanu
Published: January 2025

Background

Aging is an established confounding factor influencing the plasma levels of neurofilament light chain (NfL). While age‐specific cutoff values for NfL in healthy Caucasian populations have been documented, the potential variations in ethnically and socioeconomically underrepresented populations remain underexplored. This study aims to evaluate the acceptability of proposed NfL cutoff values in the healthy Thai population.

Method

The study included 233 healthy participants aged 18 years and above, drawn from the Comprehensive Geriatric Clinic at King Chulalongkorn Memorial Hospital, the Cognitive Aging Cohort, and controlled participants from various studies in Bangkok, Thailand. Plasma NfL levels were quantified using the single molecule array (Simoa®) NF‐light™ Advance kit. Utilizing reference threshold from previous studies (Simrén et al., 2022 and Bornhorst et al., 2022), the proportion of participants with NfL levels exceeding the proposed cutoff values were compared with the expected values. Age‐specific cutoffs were also determined using a methodology similar to previous studies.

Result

Among the participants (72.5% females, median age 65 (IQR: 56.0‐69.0), median Montreal Cognitive Assessment 27 (IQR: 25.0‐28.0), median Mini‐Mental State Examination 29.0 (IQR: 28.0‐30.0) and median education level 16.0 years (IQR: 16.0‐18.0)), plasma NfL levels exceeded the 95th percentile reference from Simrén et al. in 12% (95% CI: 8.1‐16.9%) and Bornhorst et al. in 9% (95% CI: 5.7‐13.4%). These proportions, along with their confidence intervals, surpassed the expected values of 5%. Quantile regression was employed to provisionally visualize the age‐specific NfL threshold among the Thai population (Figure 1).

Conclusion

Preliminary findings suggest that age‐specific cutoff values established from healthy Caucasian populations may not be universally applicable in Thailand. Factors such as ethnicity and social determinants of health may introduce confounding factors to the blood levels or pose negative effects on brain ageing. Given the increasing significance of NfL as a biomarker for various neurological diseases, there is a critical need to establish reference values for plasma NfL in diverse settings, particularly in lower‐income countries.
Association between Blood‐based Biomarkers of Alzheimer's disease and Endothelial Function with Mild Behavioral Impairment in a Southeast Asian Population ‐ Biomarkers and Cognition Study, Singapore BIOCIS
Authors: Leow Yi Jin , Sandhu Gurveen Kaur , Vipin Ashwati , Tanoto Pricilia , Azam Mohammed Adnan , Zailan Fatin Zahra , Lee Faith Phemie Hui En , Ghildiyal Smriti , Liew Shan Yao , Tan Isabelle Yu Zhen , Kandiah Nagaendran
Published: January 2025

Background

Behavioural changes are among the first symptoms noticeable to the person themselves as they begin to experience cognitive decline. Blood‐based biomarkers could potentially be a less invasive and easily detectable biomarker for early identification of Alzheimer's disease and dementia. However, the contributions and pathobiology of blood biomarkers to disease trajectory and prevalence in Asians requires further definition. We examined the association between blood‐based markers(BBM) of Alzheimer's disease and neuropsychiatric symptoms(NPS) in a multi‐ethnic Southeast Asian population.

Method

1296 participants were recruited from the community living in Singapore. 713 were cognitively unimpaired (CU), 583 with mild cognitive impairment (MCI), and overall, the mean age=61.27 years, mean education=14.46years with 39.8% males. Participants underwent blood biomarker tests of Apolipoprotein (APOE) ε4, Aβ oligomers (Oaβ), Neurofilament Light Chain (NfL), Amyloid Peptides(Aβ)42, Aβ40, Phosphorylated Tau at position 181(P‐Tau181), Brain‐derived neurotrophic factor(BDNF), Vascular endothelial growth factor(VEGF) as well as self‐reported questionnaires using the Depression Anxiety Stress Scales(DASS) and Mild Behavioural Impairment‐Checklist(MBI‐C).

Result

In the MCI group, Aβ42(estimate‐0.55; 95% CI[‐0.95, ‐0.15]; p=0.01), Aβ40 (estimate ‐0.361; 95% CI[‐0.72, ‐0.01]; p=0.04), pTau181 (estimate ‐0.484; 95% CI[0.93, ‐0.04]; p=0.03), were significantly associated with overall MBI‐C. Furthermore, Aβ42 was associated with MBI‐C‐interest (estimate ‐0.341; 95% CI[‐0.568, ‐0.114]; p=0.03), and MBI‐C‐control (estimate ‐0.359; 95% CI[‐0.632, ‐0.086]; p=0.01), Aβ40 was associated with MBI‐C‐interest (estimate ‐0.279; 95% CI[‐0.475, ‐0.082]; p=0.005) and MBI‐C‐beliefs (estimate ‐0.077; 95% CI[‐0.153, ‐0.001]; p=0.046), pTau181 was associated with MBI‐C‐social (estimate ‐0.177; 95% CI[‐0.311, ‐0.043]; p=0.01), and BDNF was associated with stress (estimate ‐0.233; 95% CI[‐0.432, ‐0.034]; p=0.022). Interestingly, VEGF was significantly associated with MBIC‐interest (estimate 0.12; 95% CI[0.000, 0.239]; p=0.05) and MBIC‐beliefs (estimate 0.039; 95% CI[0.001,0.078]; p= 0.044).

Conclusion

BBM and NPS were elevated in the MCI group compared to CU. Aβ42, Aβ40, pTau181, NfL, BDNF and VEGF were associated with NPS in community‐dwelling individuals free of dementia. Impairments in neurovascular regulation can lead to neurological and psychiatric symptoms. VEGF might serve as a biomarker for certain neuropsychiatric conditions.
Deciphering the Synergy Between Amyloid‐Beta and Tau Pathologies in Preclinical Alzheimer's Disease
Authors: Zamani Jafar , Vahid Amirali , Gozdas Elveda , Hosseini Hadi , Lab C‐Brain ,   Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, 94304, USA
Published: January 2025

Background

The extracellular deposition of amyloid‐beta (Aβ) and intracellular aggregation of hyperphosphorylated tau proteins stand as histopathological hallmarks of Alzheimer's disease (AD). The spatial‐temporal relationship between the Aβ pathway and tau pathophysiology in AD, plays a crucial role in comprehending the pathogenesis and progression of AD. Understanding the interrelationship between Aβ and tau, is crucial to elucidate the failure of previous therapeutic strategies and understanding AD progression and will inform the next generation of clinical trials. We employed a robust machine learning approach to predict entorhinal tau levels, using Aβ SUVR‐identified pattern. Subsequently, we employed the identified Aβ SUVR pattern to predict long‐term hippocampal volume and Preclinical Alzheimer Cognitive Composite (PACC) cognitive measurement at five‐year follow‐up, as indicators of neurodegeneration and cognitive decline, respectively.

Method

We analyzed PET measures for amyloid and tau in a cohort of 509 participants, 233 participants (104 Aβ+, 129 Aβ−) from ADNI as training data and 276 participants (93 Aβ+, 183 Aβ−) from Harvard Aging Brain Study (HABS) as an independent test set. We employed support vector regression (SVR) as a machine learning regression method for predicting entorhinal tau levels based on Aβ SUVR pattern. Feature‐selection and cross validation were performed to build and train the model using ADNI training data and the performance of the model was tested using independent HABS data. We also tested if the trained SVR model can successfully predict hippocampal volume and PACC scores at 5‐year follow‐up using baseline Aβ SUVR pattern. We constructed separate predictive models for Aβ+ and Aβ‐ subjects.

Result

The SVR model trained on ADNI Aβ data successfully predicted entorhinal tau, future hippocampal volume and PACC scores in an independent HABS dataset with a correlation accuracy of 0.50, 0.68 and 0.55, respectively (Figure 1). Particularly, Aβ load in the medial orbitofrontal and rostral middle frontal regions contributed the most to predicting entorhinal tau and future hippocampal volume and cognitive outcomes (Figure 2).

Conclusion

Our study indicates that amyloid load in medial prefrontal regions may signal subsequent tau accumulation in the entorhinal cortex, and future neurodegeneration and cognitive decline, suggesting its potential role as a marker for AD progression.