bluuebunny/crossref_metadata_2025_split huggingface dataset:
ApoE genotype and hippocampus have heterogenic influence on diagnosis and cognitive performance in the UCD ADRC longitudinal diversity cohort
Authors: Min Eva , Farias Sarah Tomaszewski , Johnson David K , Jin Lee‐Way , Maillard Pauline , Fletcher Evan , Whitmer Rachel A. , Decarli Charles 
Published: January 2025

AbstractBackgroundThe UCD ADRC longitudinal diversity cohort consists of individuals from diverse backgrounds including White, Black African or Hispanic/Latino Americans that vary in cognitive ability from normal to dementia. Prior studies show differences in the pathological substrate of dementia in this group1 as well as the relationship between MRI measures and cognition2. Prior work also indicates differential influence of ApoE genotype on dementia by race3. For this study, we analyzed the influence of ApoE genotype and hippocampal volume on episodic memory performance and clinical syndrome of normal (NL), mild cognitive impairment (MCI) or dementia as a group and stratified by race/ethnicity.MethodMethods of participant recruitment and assessment for the UCD ADRC have been previously described4 Clinical syndrome was determined by a multispecialty group and coded according the UDS5. Episodic memory was measured by the SENAS6. Hippocampus was quantified using published methods7. Multivariate linear and logistic regressions were used to assess the relationships between ApoE4 genotype, diagnosis, cognition, and hippocampal volume for the entire group in addition to stratified analyses for each ethnoracial group. All analyses were adjusted for age, sex, and education (and race/ethnicity as needed).ResultSubject characteristics are summarized in Table 1. In brief, this is a cohort diverse in race/ethnicity, cognitive ability, and educational achievement. For the entire group, odds ratios for ApoE4 prevalence were significantly higher comparing NL to MCI (1.7, p = 0.002), NL to Dementia (3.1, p <0.001) and MCI to dementia (1.7, p = 0.004). ApoE4 (Table 2) was also significantly associated with smaller hippocampus (ß = ‐0.14, p<0.001)) and poorer memory (ß = ‐0.21, p<0.001). In models where hippocampus is included, both measures are associated with episodic memory and syndrome. Different results were found for the stratified analysis where ApoE4 was not associated with syndrome or episodic memory among Blacks (Table 3). Hippocampal volume was also not associated with ApoE among Hispanic/Latinos.ConclusionThe relationship between ApoE genotype, hippocampus, syndrome, and memory performance is variable by ethnoracial background with only White participants showing associations of ApoE with both hippocampal volume and cognition. Further evaluation is needed to understand possible causes for these differences.
A diffusion kurtosis MRI signature of subjective cognitive decline
Authors: Flaherty Ryn , Sui Yu Veronica , Li Mu , Ardelean Ana , Rusinek Henry , Masurkar Arjun V. , Lazar Mariana 
Published: January 2025

AbstractBackgroundDiffusion weighted imaging (DWI) of brain white matter is better at predicting future cognitive decline and medial temporal lobe atrophy than cerebrospinal fluid biomarkers in subjective cognitive decline (SCD)1. However, few studies have investigated gray matter DWI in SCD, despite the importance of regional gray matter changes as a biomarker for Alzheimer’s Disease and related dementias.Method316 cognitively normal participants from Cam‐CAN2 (123 SCD) older than 55 were included in the analysis. Participants were placed in the SCD group if they endorsed problems with their memory. Imaging data was collected on a 3T Siemens Trio scanner2. Diffusion imaging included 0, 1000 and 2000 s/mm2 b‐values and 30 gradient directions, and were processed using MrTrix3, PyDesigner, and AMICO to apply diffusion tensor (DTI), diffusion kurtosis (DKI), and neurite orientation density and dispersion (NODDI) models. FreeSurfer with T1w and T2w images was used to segment subcortical and cortical regions (Figure 1B&C), then calculate regional volume and cortical thickness. Segmentations were also registered to diffusion images to generate regional averages of the diffusion metrics. Uncorrected p<0.05 according to Wilcoxon tests were considered significant.ResultThe metric with the most regional group differences was kurtosis fractional anisotropy (KFA) from DKI, an indicator of structural complexity. KFA was significantly lower in SCD in 17 of 84 gray matter regions, including hippocampus (Figure 2‐3B). DTI showed reduced fractional anisotropy (Figure 2‐3C) and increased mean diffusivity (Figure 2‐3D) in SCD, but for fewer regions than KFA. NODDI showed increased free water (Figure 2‐3E), increased orientation dispersion (Figure 2‐3F), and increased neurite density (Figure 3G) in SCD. Volume and thickness were higher in SCD in 5 regions, but lower in 3 regions (Figure 2‐3A). Only KFA showed group differences in hippocampus.ConclusionKFA was more sensitive to SCD and more consistent than regional gray matter volume, cortical thickness, and all other diffusion metrics. This may indicate KFA is a biomarker signature of SCD across the whole brain gray matter.References:• Selnes P, Aarsland D, Bjornerud A, et al. J Alzheimers Dis. 2013;33(3):723‐36.• Shafto MA, Tyler LK, Dixon M, et al. BMC Neurol. 2014;14(1):1‐25.
NODDI measures of microstructural integrity in medial temporal lobe white matter pathways are associated with Alzheimer's disease pathology and cognitive outcomes
Authors: Parker Dana M , Adams Jenna N. , Kim Soyun , McMillan Liv , Yassa Michael A. 
Published: January 2025

AbstractBackgroundDiffusion tensor imaging has traditionally been used to assess white matter (WM) integrity in Alzheimer’s disease (AD). However, the tensor model is limited in modeling complex WM structure. Neurite Orientation Dispersion and Density Imaging (NODDI), a cutting‐edge technique applied to multishell diffusion MRI, can offer more precise insights into microstructural features of WM integrity. We assessed whether NODDI more sensitively detects AD‐related changes in medial temporal lobe (MTL) WM than traditional tensor metrics.Method199 older adults with multishell diffusion MRI from ADNI3 (mean age = 75; 60% female; cognitively unimpaired, n=121; cognitively impaired MCI/dementia, n=78) were analyzed. Tensor metrics of fractional anisotropy (FA) and mean diffusivity (MD), as well as NODDI metrics of Neurite Density Index (NDI) and orientation dispersion Index (ODI), were calculated for MTL WM tracts (JHU Atlas: hippocampal cingulum, fornix column/body, fornix/stria terminalis, and uncinate; Figure 1). A subset of participants received 18F‐florbetapir or 18F‐florbetaben to measure Aß (n = 146; converted to Centiloids), 18F‐flortaucipir to measure tau (n=135), and neuropsychological testing including the Clinical Dementia Rating Sum of Boxes (CDR‐SB) and memory composite score (ADNI‐MEM).ResultNODDI measures in MTL tracts were more strongly correlated with cognitive performance and AD pathology than standard tensor measures (Figure 2). For example, entorhinal tau was strongly associated with NDI in the cingulum hippocampus (r=‐0.375; p<0.001) and the uncinate (r=‐0.373; p<0.001), and with ODI in the fornix ST (r =‐0.288; p=0.004). Both ODI and NDI across the majority of tracts were associated with CDR‐SB and ADNI‐MEM (see Figure 2). In contrast, FA in any MTL tract was not significantly correlated with either tau or global amyloid‐beta, while MD in MTL tracts showed limited correlations with pathology or cognition.ConclusionNODDI metrics offer additional insights about MTL WM integrity in AD that were previously missed due to the limitations of DTI analyses. These results highlight the sensitivity of NODDI applied to multishell diffusion MRI acquisitions to further investigate how WM degeneration contributes to cognitive decline.
Residential Neighborhood Disadvantage and Amyloid Positivity: Findings from IDEAS
Authors: Windon Charles , Tsoy Elena , Livaudais‐Toman Jennifer , Hanna Lucy , Gatsonis Constantine , Carrillo Maria C. , Apgar Charles , Dilworth‐Anderson Peggye , Karliner Leah , Hillner Bruce E , Neilands Torsten B , Palmer Nynikka , Possin Katherine L , Stewart Anita L. , Whitmer Rachel A. , Wilkins Consuelo H. , Rabinovici Gil D. 
Published: January 2025

AbstractBackgroundResidence in a disadvantaged neighborhood (e.g., high poverty rate, poor housing, etc.) is associated with greater dementia risk and possibly greater postmortem Alzheimer’s pathology. It remains unknown if neighborhood disadvantage is associated with in vivo beta‐amyloid positron emission tomography (PET) for Alzheimer’s. We examined this using data from the Imaging Dementia Evidence for Amyloid Scanning (IDEAS) study.MethodsIDEAS captured >18,000 PET scans among cognitively impaired Medicare beneficiaries from 595 US dementia clinics between 2016‐2018. We defined neighborhood disadvantage using Area Deprivation Index (ADI), a validated composite of 17 social determinants measures captured in American Community Survey and US Census data. IDEAS participant zip code data was linked to census block group for ADI value calculation through geocoding. Association between visual interpretation of PET in IDEAS (positive/negative) and state‐level ADI (1‐10; 10 being greatest disadvantage) was examined via logistic regression controlling for covariates (age, sex, education, level of impairment (MCI vs dementia), race/ethnicity, comorbid conditions) with cluster adjusted standard errors by practice location.ResultsAmong 13,961 cognitively impaired participants, 61.6% were amyloid positive, 56.5% had MCI, and 50.4% were female (Table 1). The majority (90.2%) were non‐Latino White with 4.7% Latino, 3.2% Black, and 1.9% Asian representation (Table 1). Participants were highly educated (68.1% beyond high school) and 31.0% (4,333/13,961) resided in neighborhoods of greater disadvantage (ADI > 6) (Figure 1). Greater ADI was associated with lower odds of amyloid positivity (aOR 0.61, 95% CI 0.51‐0.73, p<.001 for ADI 10 vs ADI 2 and aOR 0.87, 0.76‐1.00, p .051 for ADI 2 vs. ADI 1(ref)). Latino (aOR 0.62, 0.48‐0.80, p<.001), Black (aOR 0.58, 0.48‐0.72, p<.001), and Asian (aOR 0.42, 0.31‐0.58, p<.001) identity was associated with lower odds of amyloid positivity along with multiple comorbidities (Table 2).ConclusionWe observed a relationship between residence in a more disadvantaged neighborhood (higher ADI) and lower rates of amyloid positivity. Given this finding and known association between neighborhood disadvantage and postmortem AD pathology, it is possible non‐amyloid pathology also contributes towards cognitive impairment among individuals from disadvantaged neighborhoods and among diverse groups. This has implications for clinical use of novel amyloid lowering therapies.
Does socioeconomic status modify the association between glycemic level and MRI markers of ADRD risk in middle‐aged adults?
Authors: Kraal A. Zarina , McFarlane Hugh V. , Pyne Jeffrey D. , Turney Indira C. , Lao Patrick J. , Mazen Jessica , Brickman Adam M. , Manly Jennifer J. 
Published: January 2025

AbstractBackgroundHigh glycemic levels, indexed by hemoglobin A1c (HbA1c), heighten risk for Alzheimer’s Disease and Related Dementias (ADRD). Previous studies suggest that high HbA1c and low socioeconomic status (SES) may be associated with MRI markers of ADRD risk, including lower cortical thickness and greater white matter hyperintensities (WMH). The weathering hypothesis suggests that the stress of low SES accelerates and exacerbates physiological deterioration, leading to worsening health outcomes. However, the role of SES as a potential moderator of the associations between HbA1c and MRI markers of ADRD is underdeveloped. We hypothesized that higher HbA1c and lower SES are associated with MRI markers of ADRD risk, and the association between HbA1c and MRI markers is stronger among individuals with low SES.MethodParticipants were middle‐aged adults in the Offspring Study of Racial and Ethnic Disparities in Alzheimer’s Disease (N = 616; age = 54.5±10.6; 68.6% Latinx, 21.2% Non‐Latinx Black, 7.2% Non‐Latinx White; 65.6% women). HbA1c level was determined from blood assays. MRI markers included cortical thickness of AD signature regions and log‐transformed WMH. Confirmatory factor analysis estimated SES from self‐reported income and education. Structural equation models quantified main and interaction effects of HbA1c and SES on MRI markers, adjusting for age, sex, and prediabetes/type 2 diabetes.ResultThere were no main or interaction effects of HbA1c and SES on either MRI marker, independent of covariates. However, examination of moderation by each SES indicator showed that higher HbA1c was associated with lower cortical thickness among participants with high income (unstandardized estimate = ‐0.0214, SE = 0.0107, 95%CI[‐0.0424, ‐0.0003]). Effect estimates were similar in analyses restricted to individuals with prediabetes and type 2 diabetes (n = 250; age = 58.1±9.0; 72.8% Latinx, 23.6% Non‐Latinx Black, 3.7% Non‐Latinx White; 68.8% women).ConclusionHbA1c‐related effects on markers of ADRD risk in middle‐age may occur via neurodegenerative processes. Associations involving cerebrovascular pathways warrant further investigation. Examination of other indicators of SES (e.g., occupation, wealth, debts) and region‐specific WMH may help clarify the role of SES in modifying the link between glycemic level and brain health.
Genetic predisposition to AD and inflammation determine vulnerable brain regions to air pollution
Authors: Vilor‐Tejedor Natalia , Genius Patricia , Rodríguez‐Fernández Blanca , Anastasi Federica , Cirach Marta , Nieuwenhuijsen Mark , Minguillón Carolina , Esteller Manel , Navarro Arcadi , Gispert Juan Domingo 
Published: January 2025

AbstractBackgroundThe 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.MethodsA total of 1,153 individuals from the ALFA cohort, many within the Alzheimer’s continuum, with available genotyping, air pollution estimation and magnetic resonance imaging were included (62.6% women, average age 55,6 years). Land use regression models were used to estimate individual levels of air pollution, including nitrogen oxide (NO2) and particulate matter (PM2.5, PM10), at the participants’ residential addresses. Functional genetic scores, including plasma pQTLs for inflammatory markers (PRS‐CCL2, PRS‐IL6, PRS‐CCL19), CSF pQTLs for AD pathology (PRS‐Aß42, PRS‐ptau), genetic predisposition to clinical AD (PRS‐AD), and APOE‐e4 carriership, were assessed. General linear models, corrected for age at MRI visit, sex and years of education, were computed to assess the main effects of air pollution on brain volumes. Modifiable genetic effects in gene‐environment interaction models were investigated.ResultsIndividuals at higher genetic predisposition to AD and APOE‐e4 carriers exhibited increased vulnerability to air pollution, particularly in temporal and frontal regions [Figure 1A]. Individuals with high genetic predisposition for inflammatory markers showed distinct patterns of vulnerability, particularly affecting regions within the parietal and limbic lobes, with notable impact on hippocampal volumes and the subfields within the hippocampal formation [Figure 1B]. Finally, as pollution levels increased, reduction in transverse temporal volumes was observed in individuals at high risk of AD and altered CCL2 protein plasma levels [Figure 2]. Multiple comparison corrections were performed within brain lobes by regions.ConclusionsOur results suggested a differential impact of air pollution on brain structure, modulated by genetic predisposition to AD and inflammation. This underscores the importance of considering genetic information when assessing the neurological impact of environmental exposures. These findings pave the way for more personalized approaches in public health interventions, and highlight the need for targeted strategies to mitigate the impact of environmental factors on neurological health.
Locus Coeruleus Neuroimaging compared Voxel by Voxel to Histology‐ a postmortem human validation study
Authors: LaMore Tia , Huang Shuo , Marinho Pedro Burlacchini S. , Chen Yuheng , Li Song Hua , Lee Wing Hung , Carreira Luzia Lima , Rodriguez Roberta Diehl , Otaduy Maria Concepción Gracía , Shi Yonggang , Grinberg Lea T. 
Published: January 2025

AbstractBackgroundNeuropathological studies indicate that locus coeruleus(LC) volume decreases in Alzheimer’s disease(AD) by 8% at each stage, (from Braak 0‐1), whereas in normal aging, the LC remains unchanged. These changes make LC volumetry by neuroimaging a promising way to track AD progression even before symptoms appear. However, LC’s small size and location make it prone to imaging artifacts. To assess the accuracy of neuroimaging sequences designed for LC volumetry, we used an in‐house histological computational method to compare histology and neuroimaging on a voxel‐by‐voxel basis.MethodWe investigated three cases (two Braak 1s, and a Braak 5). The whole brain underwent 7T MRI postmortem, pre‐autopsy, at the University of Sao Paulo. Upon autopsy, the brains were processed at UCSF and the histological LC was 3D reconstructed. In parallel, the GRE and TFL MRI sequence LCs were segmented (Fig 1). We applied affine& spline registration to match histology to MRI‐T1 volumes(voxel size = 0.75mm)(Fig 1). To measure registration accuracy, we calculated DICE coefficients using T1 visible structures (Fig 2). Next, we analyzed the percentage overlap of voxels to investigate how accurately MRI sequences detected histology LC borders.ResultOverall, the DICE values for brainstem registration are high. Table 1 shows the overlapping percentages that are quite low, from 2.5%‐23%. For our Braak 1 cases, the least overlap of GRE MRI and histology LC borders is in rostral region, while in both TFL and GRE sequence for the Braak 5 case, the least LC overlap was in the caudal region (Table 1).ConclusionThese results suggest that accurately detecting LC borders using MRI remains a challenging task due to small size, imaging artifacts, and neuromelanin dependency, which is low at baseline in caudal LC. However, our overlap results did match previous findings on specific regional LC volume loss seen rostrally in early AD, despite no neuronal loss, and in later stages of AD, volume loss caudally. This points to the MRI LC signal being potentially clinically useful for disease monitoring. Our study will continue to examine the MRI signal picked up in the LC across Braak as regions of LC degeneration shift compared to the histology counterpart.
Estimating the time between Aβ positivity and elevated regional tau in preclinical AD
Authors: Coath William , Betthauser Tobey J. , Teague Jordan P , Arstad Erik , Awais Ramla , Sander Kerstin , Scott Catherine J , Thomas David L , Dickson John , Markiewicz Pawel J , Barkhof Frederik , Schöll Michael , Richards Marcus , Fox Nick C , Cash David M , Schott Jonathan M 
Published: January 2025

AbstractBackgroundUnderstanding when Aß positive cognitively normal individuals develop tau pathology has important implications for treatment with anti‐Aß therapies. We employed a changepoint regression approach to estimate time from Aß‐PET positivity to regionally elevated tau‐PET in a population‐based cohort of primarily cognitively unimpaired individuals.MethodParticipants from Insight 46 (1946 British birth cohort) underwent two [18F]florbetapir Aß‐PET scans and a sub‐sample enriched for Aß were also scanned with [18F]MK‐6240 tau‐PET, characteristics are presented in Table 1. Age at Aß‐PET positivity, defined through Gaussian mixture modelling (GMM) as >12 Centiloids, was estimated using the SILA algorithm (Betthauser et al. 2022). Tau‐PET SUVRs from a temporal‐meta, Braak I‐VI and 34 bilateral FreeSurfer7 regions were calculated 90‐110 mins post‐injection using an inferior cerebellar grey matter reference region. Tau‐PET positivity cutpoints for each region were defined using the 99th percentile of the lower distribution from GMM. For each region, we tested changepoints in the slope of the linear regression between tau‐PET SUVR and time from estimated Aß positivity with Bonferroni correction (5% significance,p<.001).ResultAt tau‐PET scan, 90 individuals (60%) were >0 years from estimated Aß positivity. There was a statistically significant difference in slopes before and after the changepoint for all composite regions excluding Braak VI (Figure 1). Changepoint estimates show that tau accumulation started ∼2.5yrs after estimated Aß positivity in Braak stages I‐III; and ∼10‐12.5yrs for Braak stages IV‐V, and the temporal‐meta region (Figure 2A). Regional estimates broadly followed Braak stages for 16/36 regions showing significant evidence of change in slopes (Figure 2B). Tau positivity rates before changepoints did not exceed 5%, whereas post‐changepoint tau positivity rates were between ∼10% and ∼50%. Regions with later changepoints tended to exhibit higher post‐changepoint slopes with greater uncertainty.ConclusionElevated tau‐PET signal occurs ∼2.5 years after estimated age of Aß onset in Braak stages I‐III and ∼10‐12.5 years in temporal‐meta and Braak stages IV‐V, with uncertainty within these groupings. These estimates for later Braak stages are consistent with results from previous work on the timing of positive tau PET visual reads. These findings may have implications for determining the optimal time to administer Aß immunotherapies in asymptomatic individuals.
A novel fMRI memory paradigm designed for brain imaging studies in early Alzheimer’s Disease
Authors: Joshi Himanshu , Sivakumar PT , Venkatasubramanian Ganesan , John John P , Thompson Paul M. 
Published: January 2025

AbstractBackgroundWe present the results of a task‐based fMRI study in early Alzheimer’s disease(mild cognitive impairment, MCI and mild Alzheimer’s disease, AD) using a novel‐fMRI memory paradigm suitable for use in patients with significant cognitive impairment having difficulties with remembering complex instructions.MethodThe study samples comprised 65 patients with early AD(MCI n = 42; 21 males; mild AD n = 23; 16 males) and 26(14 males) elderly cognitively healthy control(eCHC) participants. The incidental encoding phase of the paradigm(7 minutes) comprised 110 trials of common objects(55 living and 55 non‐living trials which included 4 objects repeated 6 times each and 1 object repeated 5 times) while the intentional retrieval phase of the paradigm(7 minutes) comprised 55 trials of the 5 objects encoded during the previous phase(repeated 11 times each), and 55 new objects. Task‐based fMRI acquisitions were performed on a Philips Ingenia 3‐T MRI scannerand data was analysed using FEAT(FMRI Expert Analysis Tool) correcting for age, gender, education, and total brain volume.ResultSignificantly increased activations spread across bilateral fronto‐parietal and occipital cortices were noted during incidental encoding of both ‘living’ and ‘non‐living’ stimuli in MCI when compared to eCHC and in mild AD when compared to MCI. However, reduced activations spread across bilateral central and parietal opercular cortices as well as frontal, temporal and parietal brain regions were noted during the intentional retrieval phase in response to both ‘memory’ and ‘non‐memory’ stimuli in MCI when compared to eCHC and in mild AD when compared to MCI.ConclusionThe increased brain activations of brain regions involved in during the incidental encoding phase reflects effortful encoding of novel stimuli in patients with early AD. The brain regions that showed reduced activations during the intentional retrieval phase have been previously reported to be involved in various processes that underlie retrieval of previously encoded memory traces. The results of the study support the utility of this novel‐fMRI memory paradigm as a tool suitable for brain imaging research in cognitively impaired research participants.