bluuebunny/crossref_metadata_2025_split huggingface dataset:
A polymorphism in RELN protects against amyloid‐driven tau pathology and cognitive decline in sporadic Alzheimer’s disease
Authors: Carello‐Collar Giovanna , Schlickmann Thomas Hugentobler , Ferrari‐Souza João Pedro , de Bastiani Marco Antônio , Cristino Alexandre Santos , Pascoal Tharick A. , Rosa‐Neto Pedro , Souza Diogo O. , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundA rare reelin gene variant (RELN‐COLBOS mutation) delayed dementia onset in almost 30 years in an autosomal dominant Alzheimer’s disease (ADAD) carrier. This patient presented with high amyloid‐ß (Aß) plaque load, but low tau accumulation, suggesting that this single‐nucleotide polymorphism (SNP) in RELN conferred a resilience not only to cognitive decline but also to tauopathy in ADAD. However, whether RELN SNPs are also protective in sporadic Alzheimer’s disease (AD) is yet to be determined. Thus, we sought to examine the impact of RELN SNPs on AD pathophysiology and cognitive deterioration in sporadic AD.MethodWe assessed 198 individuals [105 cognitively unimpaired (CU) and 85 cognitively impaired (CI)] from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with available data on RELN SNPs and amyloid‐ and tau‐PET measures ([18F]‐florbetaben/florbetapir and [18F]‐flortaucipir, respectively), Aß1‐42 and ptau181 in the CSF, and neuropsychological testing (Clinical Dementia Rating Sum of Boxes). We analyzed the effect of RELN SNPs carriership in the association between amyloid and tau burden through linear regression analysis and on cognitive decline according to CSF AT status through linear mixed‐effect model correcting for age, sex, and ApoEe4 status (Bonferroni’s adjusted p‐value < 0.05).ResultWe performed linear regression analysis in all the 235 RELN SNPs available on ADNI (Fig.1). We found RELN rs802787 protected against amyloid‐driven tau pathology (adj. p‐value < 0.001, Fig.2). Dividing individuals according to the CSF AT status, we observed that RELN rs802787 did not impact the rate of decline in cognition in A‐T‐ and A‐T+ individuals (Fig.3A‐B). By contrast, RELN rs802787 CSF A+T‐ individuals presented a slower cognitive decline (Fig.3C), which was not observed in A+T+ individuals (Fig.3D).ConclusionHere, we show RELN rs802787 carriers presenting high amyloid load have lower tau accumulation than non‐carriers. In addition, CSF A+T‐ RELN carriers presented a slower cognitive decline compared to non‐carriers. Our results suggest that RELN rs802787 carriership protects against amyloid‐driven tau pathology and cognitive deterioration in sporadic AD individuals. To the best of our knowledge, this is the first RELN SNP found to be protective against non‐familial AD.
Longitudinal beta‐amyloid measured with [C‐11]PiB accumulates at an accelerated rate in Down syndrome compared to neurotypical populations
Authors: McVea Andrew K , DiFilippo Alexandra H , McLachlan Max , Bettcher Brecca , Zammit Matthew D , Betthauser Tobey J. , Converse Alexander K , Murali Dhanabalan , Stone Charles K , Hartley Sigan L , Johnson Sterling C. , Tudorascu Dana , Laymon Charles M , Cohen Annie , Minhas Davneet S , Mathis Chester , Ances Beau , Zaman Shahid , Mapstone Mark , Head Elizabeth , Klunk William E , Handen Benjamin L , Christian Bradley T. 
Published: January 2025

AbstractBackgroundTrisomy 21 in Down syndrome (DS) is associated with an earlier accumulation of beta‐amyloid (Aß) plaques and a higher rate of Alzheimer’s Disease due to the triplication of the amyloid precursor protein gene. In this study we compare accumulation rates of Aß measured with [C‐11]PiB PET between large longitudinal cohorts of DS and neurotypical (NT) participants at a single site.MethodsParticipants imaged at the University of Wisconsin with =2 PiB scans and =2 years between scans were included in this study. DS participants were included from the Alzheimer’s Biomarker Consortium–DS (ABC‐DS) study (n = 57) and NT participants from studies enriched with familial risk for AD (n = 162) with several participants having 10+ years of PiB data. An identical imaging procedure was conducted for all subjects and reconstructed PET images were processed using a standardized pipeline and converted into SUVR images using the cerebellar grey matter reference region. Global PiB SUVR, defined by grey matter regions from the AAL atlas, was used as a metric for Aß deposition and input into a trajectory model (Betthauser, 2021) to estimate time from Aß(+) (SUVR = 1.40) for each scan (Fig. 1). Using this model the PiB data were normalized in time and then fit using the logistic growth curve () with t50 set to 0. Nonspecific binding (NS), found by taking the average SUVR of all Aß(‐) subject scans (n=491) at our site, and carrying capacity (K), represented by the highest total binding seen in any participant scanned, were set to 1.12 and 2.40 respectively. Aß accumulation rate (r) was calculated by fitting all normalized participant data across each population.ResultsRate of Aß accumulation for DS was 0.25±0.02 and 0.17±0.01/yr for NT, corresponding to 0.065 and 0.038 SUVR/yr respectively when becoming Aß(+). No overlap in 95% CI between the DS (0.21‐0.29) and NT (0.15‐0.19) populations was observed.ConclusionsThere was a faster rate of Aß accumulation observed in our DS cohort compared to NT by 47%. However, the high variability in Aß rates requires further investigation towards understanding how genetic and lifestyle factors contribute to this process.
Plasma ADRD biomarkers predict longitudinal declines in intra‐network functional brain connectivity, and baseline functional connectivity predicts longitudinal cognition
Authors: Dark Heather E , Shafer Andrea T , Cordon Jenifer , An Yang , Lewis Alexandria , Moghekar Abhay , Landman Bennett A. , Resnick Susan M. , Walker Keenan A. 
Published: January 2025

AbstractBackgroundAD is defined by cortical amyloid‐ß (Aß), tau neurofibrillary tangles, and neurodegeneration, pathological processes which may contribute to cognitive decline by altering large scale functional brain networks. To test this hypothesis, we examined whether plasma biomarkers of AD pathology (Aß42/40, phosphorylated tau [pTau‐181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) related to longitudinal changes in resting‐state functional connectivity (rsFC) in cognitively unimpaired participants from the Baltimore Longitudinal Study of Aging.MethodBaseline plasma biomarkers were measured with Quanterix SIMOA assays. Functional connectivity (3T resting‐state fMRI) was derived using a predefined cortical parcellation mask from which intra‐network connectivity from seven functional networks was extracted for each participant. Amyloid status (positive/negative) was defined using plasma Aß42/40 (Figure 1). Linear mixed effects models adjusted for age, sex, race, education, gray matter volume, and time‐covariate interactions were used to determine whether 1) baseline plasma biomarkers predicted longitudinal changes in rsFC, 2) the magnitude of the biomarker‐related rsFC changes differed by amyloid status, and 3) rsFC predicted longitudinal changes in cognition.ResultLongitudinal connectivity analyses (mean age±SD = 65.49±16.17) included 490 participants (1190 visits; mean follow‐up time = 4.31±1.68 years). Higher Aß42/40, GFAP, and NfL were associated with faster declines in rsFC within several networks (P‐range = 0.01‐0.04; Figure 2). Overall, plasma biomarker‐rsFC associations differed by amyloid status (P‐range = 0.01‐0.045). Among amyloid‐positive participants, lower levels of Aß42/40, and higher levels of GFAP, and NfL (Figure 2) were associated with faster declines in rsFC in the visual, dorsal and ventral attention, limbic, and frontoparietal networks (P range≤0.002‐0.04). There were no statistically significant associations between plasma biomarkers and rsFC change among amyloid‐negative participants. Among 760 participants with at least one rsFC scan (mean age±SD = 67.21±14.93; 1550 visits, follow‐up time = 3.94±1.60 years), we found that baseline rsFC in several networks predicted changes in cognition, e.g., working memory, verbal fluency, and visuospatial abilities (P range = 0.02‐0.049; Figure 3).ConclusionAmong cognitively normal individuals, plasma biomarkers of Aß42/40, astrogliosis, and neuronal injury are associated with future intra‐network functional brain changes, particularly in the context of elevated amyloid. Hypo‐ and hyper‐ intra‐network connectivity may drive changes in cognitive performance.
Tau accumulation mediates β‐amyloid effects on hippocampal atrophy and memory in early Alzheimer’s disease
Authors: Fernandez‐Lozano Sofia , Fonov Vladimir S , Therriault Joseph , Rahmouni Nesrine , Servaes Stijn , Stevenson Jenna , Poltronetti Nina Marguerita , Rosa‐Neto Pedro , Collins D Louis 
Published: January 2025

AbstractBackgroundWhile we know dementia in Alzheimer’s disease (AD) results from the accumulation of ß‐amyloid (Aß), tau pathology, and hippocampus atrophy (HC), it is still unclear how these factors impose cognitive decline.MethodWe used Structural Equation Models (SEM; lavaan R package) to explore the complex relationships between the neurobiological factors in the early stages preceding AD dementia in the TRIAD cohort. Our sample comprised 333 timepoints of neuropsychological evaluation (MoCA), structural MRI, Aß ([18F]AZD4694), and tau ([18F]MK6240) PET of cognitively healthy (NC) and mild cognitive impaired (MCI) participants. We measured neurodegeneration with an inverted HC‐to‐Ventricle ratio (HVR), i.e. 1‐HVR, an integrity measure composed of the ratio of the HC volume and the sum of the volumes of HC and the temporal horn of the lateral ventricle. We used a feature selection algorithm (Boruta R package) to select the most important Regions of Interest (ROIs) from the CerebrA atlas relating Aß & Tau to memory. We then used SEM to explore the mediation of Aß and Tau on HC‐atrophy and memory using 1) the average Aß & Tau SUVR of all ROIs and 2) separate models using the Aß & Tau SUVR for each of the ROIs. Age, sex and education were treated as covariates. For ease of comparison, we calculated the standardized coefficients in our models.ResultThe demographic data of our sample is presented in Table 1. The selected ROIs were: bilateral amygdala, hippocampus, and parahippocampal gyrus; right fusiform gyrus and orbitofrontal cortex (lateral and medial portions); and left middle temporal gyrus. The full SEM with all ROIs show full mediation between Aß, Tau and HC‐atrophy, and partial mediation between all biomarkers (Fig. 1). On the distinct models by ROI, Amyloid’s effect on MoCA is almost always indirect through Tau (Fig. 2).ConclusionWe show that, even in the early stages of AD, Aß aggregation alone has no effect on HC atrophy, and only a weak effect on cognitive decline; interactions with tau pathology is required to modulate the effects of Aß aggregation on both HC atrophy and memory loss.
CU PET Aβ and Tau Positive Individuals Show Impairment in MoCA Delayed Recall
Authors: Felix Cynthia , Ferreira Pamela C.L. , Rodrigues Matheus Scarpatto , Snitz Beth E. , Abbas Sarah , Oliveira Markley , Bauer‐Negrini Guilherme , Povala Guilherme , Lemaire Peter , Kollasserry Felix Joy , Medeiros Marina Scop , Soares Carolina , Rebok George , Aguzzoli Cristiano Schaffer , Bellaver Bruna , Lussier Firoza Z , Amaral Livia , Pascual Belen , Gordon Brian A. , Lowe Val J. , Oh Hwamee , soleimani‐meigooni David N. , Tudorascu Dana , Jagust William J. , Klunk William E , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick A. 
Published: January 2025

AbstractBackgroundIdentification of cognitively unimpaired (CU) individuals who may progress to mild cognitive impairment (MCI), is a pressing issue in the Alzheimer’s disease (AD) field, since therapeutic interventions may be more effective in the absence of cognitive impairment and neurodegeneration. CU individuals positive for amyloid and tau PET are very likely in the AD pathway. In out‐patient cognitive screening, we use rapid and simple tests such as The Montreal Cognitive Assessment (MoCA) ‐ a composite of executive, visuospatial, naming, attention, language, abstraction, delayed recall, and orientation performances. We hypothesize that sub‐categorizing the CU group based on the presence of amyloid (A) and tau (T) pathologies, as measured by PET, can reveal subtle cognitive deficits, even in a clinical test with low sensitivity such as MoCA.MethodWe included 88 CU [defined as CDR global score of 0] older adults with available head‐to‐head MK6240 tau‐PET and Flortaucipir tracers from the ongoing HEAD multi‐site observational study. They also underwent Amyloid PET imaging using PiB or NAV4694. MoCA testing was done around the imaging time. To increase similarity with clinical practice, Amyloid and Tau PET positivity was defined using visual reads. Based on tracer uptake status, we categorized the individuals into A‐T‐, A‐T+, A+T‐ and A‐T‐ groups. Unpaired t‐test and one‐way ANOVA were used to test for significant differences between groups.Result2‐tailed p‐values were significant between the A‐T‐ group and the A+T+ group for MoCA total score [p: 0.0025 and p: 0.0025]. When we stratified MoCA in the different cognitive domains, we found that the results were driven by MoCA (memory) Delayed Recall score [p: 0.0007 and p: 0.0162]. A‐T+ vs A+T+ was also significant [p: 0.0099] for MoCA Delayed Recall. Both tau tracers (MK6240 and Flortaucipir) showed similar performance for determining T+ and identifying cognitive decline.ConclusionMoCA, a simple and commonly administered in‐office neuropsychological test, can detect subtle cognitive dysfunction in CU older adults who are Aß and tau positive (A+/T+). These CU A+/T+ individuals are likely on the path to developing AD dementia.
Associations Between Sex‐ and APOE‐Specific Transcriptomic Signatures in Alzheimer's Disease and Imaging‐Derived Phenotypes: An AZ‐ADRC‐Research Education Scholars Team Science Project
Authors: Raikes Adam C. , Vitali Francesca , Hernandez Gerson D , Yin Fei 
Published: January 2025

AbstractBackgroundAge, female sex and the APOEe4 allele are among the top risk factors for developing late‐onset Alzheimer’s disease (LOAD). Precision medicine for AD drug development necessitates targeting specific biological pathways driving AD pathology. We previously identified LOAD‐associated transcriptomic signatures specific to both sex and APOE genotype. Here we extend these analyses to examine the association between these signatures and imaging‐derived phenotypes (IDPs).MethodBrain RNA‐Seq datasets from ROSMAP (syn8456637) were obtained from the RNA‐Seq Harmonization Study on AMP‐AD, including 369 frontal cortex samples from APOEe3/e3 and APOEe3/e4 individuals. Differentially expressed genes (DEGs, p‐value<0.01) between LOAD and cognitively normal controls were identified for each sex‐genotype. IDPs were generated from 1155 individuals in ROSMAP, with 62 overlapping the RNA‐Seq Harmonization Study. T1‐weighted MRIs were processed using Fastsurfer (v.2.0.4), and cortical thickness (CT) and subcortical volumes (SV) were computed. After multi‐site harmonization and covariate adjustment, effect sizes (Cohen’s d) for controls vs. AD were computed for each sex‐genotype pairing. Correlations between these effect sizes and median regional DEG expression from the Allen Human Brain Atlas were examined.ResultControls showed anticipated CT and SV patterns, though male APOEe4s exhibited greater CT in more regions. Higher median expression of up (female APOEe3/e3, male APOEe4) and down (female APOEe3/e3, male APOEe3/e3, male APOEe4) regulated DEGs correlated with less CT in AD patients (r=0.21‐0.41, p < 0.046). In APOEe4 carriers, higher median up (male, female) and down (female) DEG expression correlated with greater SV in AD patients (r=0.48‐0.57, p < 0.043). Greater median downregulated DEG expression in APOEe3/e3s correlated with smaller SV (r=0.56, p=0.021). Higher median APOE expression was correlated with less CT in AD patients across sex‐genotype pairings (r=0.38‐0.86, p < 0.002), lower SV (females, all genotypes), and greater SV (male APOEe3/e3). No associations between median DEG expression and CT were observed in female APOEe4 carriers.ConclusionOur analyses reveal novel sex and APOE genotype‐specific transcriptomic signatures associations with imaging‐derived features in LOAD. Our findings transcriptome signature specific CT and SV profiles that may inform therapeutic targets. The present analyses provide support the identification and use of risk‐factor specific biomarkers of target engagement for preventative and therapeutic interventions.
The Association between Hepatic fat and Neuroinflammation in Midlife Obesity
Authors: Dolatshahi Mahsa , Rahmani Farzaneh , Commean Paul K. , Kasani Sara Hosseinzadeh , Naghashzadeh Mahshid , Lloyd LaKisha , Nguyen Caitlyn , McBee‐Kemper Abby , Weeks Jake , Ceriani Lael , Mittendorfer Bettina , Sirlin Claude , Song Sheng‐Kwei , Benzinger Tammie L.S. , Ippolito Joseph E. , Morris John C. , Raji Cyrus A. 
Published: January 2025

AbstractBackgroundObesity in midlife, body mass index (BMI) of 30 kg/m2 or higher, is recognized as a contributor to Alzheimer disease (AD) later in life. Adiposity in visceral tissues such as liver is associated with increased systemic inflammation and impaired cognition. In this study, we aimed to investigate the relationship between MRI‐derived Positron Density Fat Fraction (PDFF) and brain histology and neuroinflammation using Diffusion Basis Spectrum Imaging (DBSI) in cognitively normal midlife individuals.MethodIn total, 67 cognitively normal middle‐aged participants (Age: 50.02±6.00 years, female: 65.7%, obesity: 53.7%, BMI: 31.72±6.81 kg/m2) underwent brain and abdominal 3T MRI and metabolic assessment. Homeostatic Model Assessment for Insulin Resistance (HOMAIR) was used as for measuring insulin resistance. Using a trained U‐Net convolutional neural network (CNN) model, hepatic PDFF maps were calculated from conventional T1‐weighted images. The CNN included the Adam optimizer for training. A DBSI scheme with a total of 98 diffusion samplings was acquired. After eddy current and movement correction and removing non‐brain tissue, DBSI maps including fractional anisotropy (FA, overall integrity), axial diffusivity (AD, axonal injury), radial diffusivity (RD, myelin loss), restricted fraction (RF, inflammation cellularity), hindered fraction (HF, extracellular edema), and fiber fraction (FF, axonal density) maps were calculated using in‐house software scripted in MATLAB and Statistics Toolbox Release. DBSI‐derived maps were processed using a tract‐based spatial statistics (TBSS) pipeline to allow for whole‐brain white matter voxel‐wise analyses. Using the Randomize tool from FSL, the association of PDFF and HOMAIR with DBSI‐derived white matter skeleton, with age and sex as covariates, and a threshold of 0.05 for false‐discovery rate.ResultThere was a significant association between PDFF and HOMAIR (p<0.001), and obese individuals showed higher PDFF (p = 0.02) but no difference in HOMAIR (p = 0.12). We observed a significant positive association between PDFF and restricted fraction in widespread white matter tracts. There was no significant association between HOMAIR and DBSI measures.ConclusionOur results indicate the role of hepatic fat in increased inflammation‐related cellularity in the brain in cognitively normal midlife individuals. These findings suggest that excess hepatic fat can potentially increase the risk for Alzheimer disease and cognitive impairment at least partly through promoting neuroinflammation.
White matter integrity is lower in non‐amnestic than amnestic Alzheimer's disease and differs by clinical syndrome
Authors: Phillips Jeffrey S , Adluru Nagesh , Chung Moo K , Radhakrishnan Hamsi , Olm Christopher A , Cook Philip A. , Gee James C. , Arezoumandan Sanaz , Cousins Katheryn A Q , Wolk David A , McMillan Corey T , Irwin David J 
Published: January 2025

AbstractBackgroundAmnestic mild cognitive impairment and Alzheimer’s disease (aAD) exhibit degeneration of white matter (WM) tracts preceding overt cognitive decline. However, WM changes in non‐amnestic AD (naAD) are understudied. We hypothesized patterns of WM degeneration would differ between aAD and naAD.MethodsWe compared WM degeneration, assessed by 30‐direction diffusion‐weighted imaging (DWI), in 41 individuals with aAD; 67 with naAD diagnoses including logopenic‐variant primary progressive aphasia (lvPPA), posterior cortical atrophy (PCA), behavioral variant AD (bvAD), and corticobasal syndrome (CBS); and 45 with normal cognition (Table 1). We performed deterministic tractography between 148 cortical/subcortical regions; connectivity was quantified by generalized fractional anisotropy (GFA). Tractwise GFA and regional grey matter (GM) volumes were converted to W‐scores adjusting for age and sex. We contrasted GFA between groups using regression models covarying for MMSE score. A mixed effects model was used to assess associations between tractwise GFA and volume of GM endpoints. Additionally, we computed the number of connected components in each person’s brain graph (i.e., number of subgraphs created by progressively stricter thresholds) across 100 GFA values. We contrasted this topological metric between groups and assessed its associations with MMSE and disease duration.ResultsGM volume was lower in naAD and aAD than controls (both p<0.0001) but did not differ between patient groups (p=0.81). aAD and naAD patients had shared WM degeneration in corpus callosum, cingulum, and inferior/superior longitudinal fasciculi; however, WM degeneration was more severe in naAD (Fig. 1). In lvPPA, WM degeneration was left‐lateralized; in PCA, GFA was reduced in bilateral parietal, occipital, and temporal areas (Fig. 2). Across groups, GM and WM degeneration were significantly associated [F(1,20442)=326.0, p<0.0001]. Topological analysis indicated naAD but not aAD patients had lower global connectivity than controls. A higher component number (indicating reduced connectivity) was associated with longer disease duration and lower MMSE.ConclusionAssociations between GM volume and GFA suggest WM degeneration in naAD is related to AD pathologic change and not an independent process. Greater WM disease in naAD than aAD was not attributable to GM atrophy or symptom severity. Finally, topological metrics may serve as objective markers of global disease progression.