bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging biofluid markers as a real‐time window to understand molecular drivers of sex differences in AD clinical trials
Authors: Casaletto Kaitlin B. 
Published: January 2025

AbstractWomen account for almost two‐thirds of Alzheimer’s disease (AD) cases, yet evidence significantly less clinical benefit from recently deployed amyloid‐lowering therapies. To close this disparity gap, there is an urgent need to identify biological drivers of sex differences in the manifestation and clinical response to AD therapeutics. A recent review of multi‐omic studies of AD reported >75% of studies showed female‐specific changes at the molecular level (vs. 20% showing male‐specific changes), including enrichment in innate and adaptive immune system changes. However, the majority of these studies rely on brain tissue, which lacks temporal resolution needed to address questions related to real‐time biological responses to treatment. We propose that deep molecular phenotyping of human biofluids [blood, cerebrospinal fluid (CSF)] may offer a key window to understand in‐vivo biological signatures driving sex differences in response to AD therapies. Technological advancements in biofluid quantification now enable early, scalable detection of AD biology and have been used to show target engagement for recent amyloid antibody therapies. Both Lecanemab and Donanemab show significant improvements in CSF and plasma phosphorylated tau (p‐tau) and GFAP, for instance. Yet, despite p‐tau and GFAP evidencing sex differences in converging observational studies, clinical trials have not historically sex disaggregated their data. Newer high‐throughput platforms now allow capture of >thousands of analytes from one human biofluid sample. These approaches are shedding light on novel pathways implicated in AD, evidence cross‐tissue utility, and may allow dynamic quantification of the molecular signatures that change with AD treatment in a person‐specific manner. Human in‐vivo proteomic studies in other diseases highlight their utility for disentangling sex‐differences biology. For instance, a recent study examining the most commonly used medications in adults identified hormonal contraceptives as having the single largest effect on the plasma proteome. In cardiovascular disease, large‐scale plasma proteomics have identified differential pathways underlying cardiac disease in men versus women and identified novel molecular targets that may explain sex differences in response to heart failure treatments. In this session, we will underscore the opportunity to leverage in‐vivo biofluid analytics to develop a sex‐aware understanding of AD therapeutics.
The association of birth in the Stroke Belt and neuroimaging brain biomarkers in a cohort of older Black Americans
Authors: Lor Yi , George Kristen M. , Peterson Rachel , Gutierrez Sirena , Posis Alexander Ivan B. , Decarli Charles , Barnes Lisa L. , Gilsanz Paola , Whitmer Rachel A. 
Published: January 2025

AbstractBackgroundHaving ever lived in the southeastern United States, a region referred to as the Stroke Belt (SB), is associated with higher dementia incidence and poorer late‐life cognition. We assessed whether birth in the SB was associated with late‐life MRI‐based regional brain volumes among racially/ethnically diverse older adults who are long‐term residents of Northern California.MethodKHANDLE and STAR are harmonized cohort studies of long‐term members (ages ≥65 and ≥50, respectively) of an integrated healthcare delivery system. A sub‐sample of participants received MRI imaging, which included regional gray matter and ventricle volumes and total white matter hyperintensities (WMH). The analytic subsample was limited to US‐born Black participants given so few from other ethno‐racial groups were born in the SB. Self‐reported state of birth was dichotomized as birth in the SB or non‐SB. Linear regression models analyzed associations of SB birth with twelve MRI regions of interest, standardized for total cranial volume (except free water and fractional anisotropy). All models adjusted for age at MRI scan, sex, parental education, and own education. Sensitivity analyses were performed in those aged ≥65.ResultOf 304 participants (mean age=70.8, SD=8.5), one‐third (n=117) were born in the SB (Table 1). Those born in the SB were older (mean age=75.4±7.6), less likely to be college educated (33% vs. 41.5%), and less likely to have parents with a high school diploma (21.4% vs 38.9%). Birth in the SB was associated with smaller parietal cortex volume (β=‐1.82; 95% CI=‐3.31, ‐0.33) (Table 2; Model 2), which remained significant for those who were ≥65 years old (Model 3). Birth in the SB was associated with lower log‐transformed WMH (β=‐0.41; 95% CI=‐0.78, ‐0.03) among those aged ≥65 (Model 3). The associations of other MRI‐derived brain volumes and cognition and cognitive change were null.ConclusionBlack Americans born in the SB had lower parietal cortex volumes, but also lower WMH volumes in late life. Parietal cortical thinning has been linked with cardiovascular risk, which may warrant further investigation into mechanisms of the association of cardiovascular risk and brain health in those born in the SB.
Reduced plasma Aß42/40 in individuals with SCD predicts increasing plasma p‐Tau 181
Authors: Göschel Laura , Koertvelyessy Peter , Hoede Patty , Teunissen Charlotte , Flöel Agnes 
Published: January 2025

AbstractBackgroundIn Alzheimer’s disease (AD), the decline of plasma Aß42/40 occurs before cognitive decline, presenting a potential early screening tool. However, the factors leading to the progression of the disease, specifically the increase in plasma p‐Tau 181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), remain unclear. This study investigates whether perceived cognitive impairment is associated with downstream biomarker changes in individuals with decreasing Aß42/40.MethodPlasma was longitudinally collected from a study population of cognitively healthy controls (HC, n=21) and individuals with subjective cognitive decline (SCD, n=32) for up to five time points over up to five years. Plasma biomarkers were measured using Simoa HD‐X (Billerica, USA) with the commercially available kits NEUROLOGY 4‐PLEX E and p‐Tau 181 advantage kit V2. A 2‐means cluster analysis classified the participants as Aß decliners/non‐decliners based on their plasma Aß42/40 change (difference between plasma Aß42/40 at the first visit and last visit). The self‐reported Everyday Cognition (ECOG) and Multifactorial Memory Questionnaire (MMQ) provided two continuous measures of subjective cognition. Using linear mixed models, we examined z‐scaled longitudinal plasma p‐Tau 181, GFAP and NfL for Aß decliners and non‐decliners with a diagnosis of SCD (model 1), elevated scores in ECOG (model 2) or decreased scores in MMQ (model 3).ResultThe cluster analysis separated the participants into Aß decliners (plasma Aß42/40 change=‐0.5sd, n=22) and non‐decliners (Aß change=0.2sd, n=31). Model 1 showed a substantial difference in longitudinal p‐Tau 181 in Aß decliners for HC vs. SCD (estimated mean difference=‐0.19sd, p<0.001). A yearly increase of plasma p‐Tau 181 in Aß decliners was found only for SCD (0.10sd [0.03; 0.18], p=0.008) but not HC (‐0.09sd [‐0.17; ‐0.01], p=0.028) participants. Neither model 2 nor model 3 showed relevant effects of ECOG or MMQ on longitudinal plasma p‐Tau 181, GFAP or NfL, in neither Aß decliners nor non‐decliners.ConclusionOur findings suggest a predictive value of the diagnosis SCD for pathologic progression in participants with declining plasma Aß42/40. Our study contributes to a better understanding of early pathological changes of AD and highlights the use for a multi‐modal diagnostic approach involving both objective biomarkers and professional evaluation.
A head‐to‐head comparison between plasma p‐tau217 and tau‐PET for predicting future cognitive decline among cognitively unimpaired individuals
Authors: Ossenkoppele Rik , Salvadó Gemma , Janelidze Shorena , Binette Alexa Pichet , Therriault Joseph , Jonaitis Erin M. , Palmqvist Sebastian , Mattsson‐Carlgren Niklas , Stomrud Erik , Bourgeat Pierrick , Dore Vincent , Masters Colin L , Johnson Sterling C. , Villeneuve Sylvia , Rosa‐Neto Pedro , Rowe Christopher C. , Hansson Oskar 
Published: January 2025

AbstractBackgroundAn accurate prediction of Alzheimer’s disease (AD) progression is important for patient management and optimization of participant selection for trials. Here, we compared and combined plasma p‐tau217 and tau‐PET measures for predicting longitudinal cognitive decline and clinical progression in cognitively unimpaired participants.MethodWe included 982 participants from six independent cohorts (AiBL, BioFINDER‐1, BioFINDER‐2, TRIAD, PREVENT‐AD and WRAP; Table 1) with available plasma p‐tau217 and tau‐PET measures (measured less than one‐year apart), being either amyloid‐positive or amyloid‐negative. Biomarker and cognitive data were z‐scored by cohort using cognitively unimpaired CSF/PET amyloid‐negative participants as reference for a unified analysis. We performed linear mixed models (for predicting cognitive decline on the mPACC and MMSE) and Cox‐proportional hazards models (to assess progression to MCI or dementia), testing among both amyloid‐negative and amyloid‐positive individuals. We entered baseline plasma p‐tau217, and tau‐PET uptake in the medial temporal lobe (MTL) or in the temporal neocortex individually, and also performed combined plasma/PET models. Age, sex, years of education and cohort were used as covariates.ResultAll individual tau biomarkers significantly predicted cognitive decline for both mPACC (R2p‐tau217=0.27, R2MTL‐tau=0.31, R2neotemporal‐tau=0.28, Figure 1) and MMSE (R2p‐tau217=0.12, R2MTL‐tau=0.16, R2neotemporal‐tau=0.19, Figure 2). The best model for predicting mPACC change included plasma p‐tau217 and MTL tau‐uptake (R2=0.32, pcomparison<0.001), while for MMSE change included plasma p‐tau217 and tau‐uptake in the temporal neocortex (R2=0.20, pcomparison≤0.007). Progression to MCI or dementia was also best predicted when including both plasma p‐tau217 (HR[95%CI]=1.29[1.14,1.47], p<0.001) and MTL tau‐uptake (HR[95%CI]=1.39[1.25,1.54], p<0.001, c‐index=0.83). Analyses by individual cohorts showed similar trends.ConclusionOur data suggest that plasma p‐tau217 is a suitable screening method for clinical trials in CU populations given its logistic advantages. In scenarios where a more refined prediction of cognitive decline is mandated, Tau‐PET (preferably in a combined algorithm with plasma p‐tau217) would be the methodology of choice.
MRI Assessment of Healthy Aging Trajectories in the Marmoset Brain
Authors: Szczupak Diego , Bhik‐Ghanie Rebecca , Zhang Bei , Papoti Daniel , Campos Vinicius , Dubberley Lauren R , Hitchens T Kevin , Yeh Fang‐Cheng , Schaeffer Lauren K Hayrynen , Carter Gregory W , Rizzo Stacey J Sukoff , Schaeffer David J , Silva Afonso C 
Published: January 2025

AbstractBackgroundThe common marmoset (Callithrix jacchus) is an important animal model in neuroscience and neurological diseases (e.g., Alzheimer’s disease ‐ AD), as they present primate‐specific evolutionary features such as an expanded frontal cortex. We established a new consortium with funding support from the National Institute on Aging to generate, characterize, and validate MArmosets as Research MOdels of AD (MARMO‐AD). This consortium develops and studies gene‐edited marmoset models carrying genetic risk for AD, comparing them against wild‐type aging marmosets from birth throughout their lifespan, using non‐invasive longitudinal assessments. Here, we aim to characterize healthy aging trajectories of regional brain volume in a population of marmosets.MethodsWe imaged a cohort of 59 marmosets (45 males, 14 females) across the lifespan (8 to 150 months) using a dedicated 9.4T 30cm bore MRI scanner (Bruker BioSpin Corp, Billerica). The animals were anesthetized under isoflurane and maintained under normal physiological conditions. High‐resolution (250 µm isotropic) T1‐, T2‐, and diffusion‐weighted structural MRI were acquired. The brain images were aligned and registered to the Marmoset Brain Mapping V3 template. The brain was segmented into cortical (CTX) and subcortical (SUB CTX) grey matter, white matter (WM), and cerebral spinal fluid (CSF), and voxel‐based‐morphometry was used to quantify regional brain volume in the left and right hemispheres.ResultsWe discovered a decrease in grey matter volume in both males and females with age (Figure 1), reflected by the reduction in several cortical and subcortical brain regions in both sexes. Overall, we discovered that age affects female marmoset brains (38 CTX and 5 SUB CTX regions) more than males (15 CTX and 2 SUB CTX regions). We found no significant age‐dependent changes in WM and CSF.ConclusionsOur work is the first to thoroughly describe the normal aging of the marmoset brain, a valuable model for age‐related neuropathologies (e.g., AD). This research will establish normative baselines for changes in regional marmoset brain volume with aging that will be used to evaluate our genetically engineered marmoset models of AD, which is the goal of the MARMO‐AD consortium.
Medial temporal lobe subregional atrophy patterns in presymptomatic and symptomatic genetic frontotemporal lobar degeneration
Authors: Gaynor Leslie S , Yballa Claire , Cobigo Yann , Mejía‐Perez Jhony Alejandro , Wuestefeld Anika , Wisse Laura E.M. , Forsberg Leah K. , Heuer Hilary W. , Rosen Howard J. , Boxer Adam L. , Boeve Brad F. , Kantarci Kejal , Staffaroni Adam M. , Joie Renaud La 
Published: January 2025

AbstractBackgroundMedial temporal lobe (MTL) atrophy is an early feature of multiple neurodegenerative diseases. In genetic frontotemporal lobar degeneration (FTLD, i.e. individuals carrying GRN, MAPT, or C9orf72 mutations), MTL atrophy can occur 10‐15 years before symptom onset. We aimed to better characterize MTL atrophy patterns in presymptomatic and symptomatic genetic FTLD using a multi‐atlas segmentation pipeline that allows precise measurement of MTL subregions.MethodParticipants included a diagnostically mixed sample of familial FTLD mutation carriers (MAPT: N=87; C9orf72: N=117; GRN: N=65) and 142 non‐carrier family member controls from the ALLFTD study cohort (Table 1). T1‐weighted MRIs were preprocessed using a multi‐atlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS]) to segment the amygdala, anterior and posterior hippocampus, and MTL cortices: entorhinal cortex (ERC), perirhinal cortex or Brodmann areas (BA) 35 and 36, and parahippocampal cortex (PHC). Following rigorous quality control and manual correction (Figure 1), we assessed bilateral volume differences in mutation carriers compared to controls, adjusted for age, sex, and total intracranial volume. Analyses were conducted separately for symptomatic (FTLD‐Clinical Dementia Rating Global Score&ge;0.5) and presymptomatic (Global Score=0) mutation carriers.ResultOut of 413 scans, 317 (76.8%) segmentations passed quality control while 94 (22.8%) needed some manual edits—this was more common in symptomatic than presymptomatic carriers (32% versus 15%, p=0.001). Three scans were excluded (<1%; 2 complete scans, 1 for selected subregions) due to insufficient landmark visibility in symptomatic GRN and MAPT carriers. In symptomatic carriers, all MTL subregions demonstrated reduced volume compared to controls, although MAPT carriers exhibited particularly marked atrophy, especially in anterior MTL subregions (Table 2; amygdala, ERC, BA35, hippocampus). Presymptomatic MAPT and C9orf72 carriers also exhibited significant atrophy of primarily anterior MTL cortices, while presymptomatic GRN carriers only exhibited significantly smaller ERC volume compared to controls.ConclusionMTL atrophy is present in genetic FTLD across mutation carriers, even at the presymptomatic stage. Anterior MTL subregions, which are also susceptible to neuropathologic accumulation in early Alzheimer’s disease and Limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), tend to be more vulnerable than posterior subregions. Unsurprisingly, MAPT carriers show the greatest MTL atrophy compared to controls across groups.
Predictive accuracy of plasma markers for Alzheimer’s disease, cerebrovascular disease, and cognition in a population‐based study
Authors: Neitzel Julia , Streiber Anna M , Ma Yuan , Ho Phuong Thuy Nguyen , Wolters Frank J. , Hofman Albert , Bos Daniel , Vernooij Meike W. 
Published: January 2025

AbstractBackgroundValidating the predictive value of plasma markers for Alzheimer’s disease, cerebrovascular disease and cognitive dysfunction in older adults representative of primary care settings, is needed to guide prevention and treatment decisions.MethodAt baseline, single molecule array plasma measures of Aβ42/40, pTau217, pTau181, GFAP and NfL were collected from 625 dementia‐free participants from the population‐based Rotterdam Study (mean age 63 years [range 54‐84], 51% women). After a mean follow‐up time of seven years [range 5‐9], participants underwent amyloid 18F‐florbetaben PET, brain MRI, and cognitive assessment. We investigated cross‐sectional associations between basic sample characteristics and plasma markers using linear/logistic regression. We estimated how accurately single plasma markers at baseline predicted amyloid‐PET positivity, high white matter hyperintensity burden (i.e. volume in 4th quartile) and low cognitive performance at follow‐up (i.e. composite score in 1st quartile) using receiver operating characteristic curve analysis. Predictive performance between different models was compared with DeLong test. We further identified the most parsimonious multi‐plasma marker model based on the lowest Akaike information criterion.ResultOlder participants had more abnormal plasma markers. Women showed higher GFAP, but lower pTau217 and 181 levels than men. APOE4 carriership was associated with more abnormal Ab42/40 and pTau217 levels. Education was not related to plasma markers. At follow‐up, 102 participants (16%) were amyloid‐PET positive. The area under the curve (AUC) for amyloid‐PET positivity using a base model containing age, sex, APOE4, and follow‐up time was 0.83 (Figure 1). Predictive accuracy significantly improved upon adding to the base model either GFAP (AUC=0.85), Aβ42/40 (AUC=0.87), or pTau217 (AUC=0.89; all p[DeLong]<0.05; Figure 1). AUC improved further to 0.92 for the most parsimonious model including all plasma markers (p[DeLong]<0.001). Using cutoffs based on Youden’s index, we estimated that 6.2 PET scans were needed to obtain one amyloid‐PET positive individual after screening with the base model. This number decreased to 4.7 or 2.8 when pTau217 or all plasma markers were considered. No plasma marker model seemed to outperform the base model for predicting high white matter hyperintensities or low cognitive performance.ConclusionPlasma pTau217, Aβ42/40 and GFAP levels markedly improved the prediction of amyloid‐PET positivity in the general population
Linking the estimated time of onset of low locus coeruleus integrity to the estimated time of onset of elevated entorhinal tau
Authors: Jacobs Heidi I.L. , Betthauser Tobey J. , Becker Alex , Riphagen Joost M. , Papp Kathryn V , Price Julie C , Rentz Dorene M , Sperling Reisa A , Johnson Keith A 
Published: January 2025

AbstractBackgroundEstimating the time course of locus coeruleus integrity changes is important for a better understanding of the pathophysiological cascade and for identifying the optimal window of opportunity for prevention trials. We used samples iterative local approximation (SILA) to determine the individual estimated time of onset of low LC integrity and related this to early cortical tau deposition and cognitive decline.Methods101 individuals from the Harvard Aging Brain Study+ with longitudinal 3T MRI‐LC imaging, 18F‐Flortaucipir (FTP)‐PET imaging (n=92 with longitudinal data), longitudinal cognitive assessments and baseline PiB‐PET imaging were included (mean age: 69.97 years (SD: 12.46); 62 females; Table 1). LC intensity was derived by normalizing the LC to the pontine reference and averaging 5‐voxel‐clusters with the highest intensities (GMM‐based cut‐off: <1.34 = LC+). FTP‐burden was quantified in the entorhinal cortex (cerebellar grey reference region, partial volume corrected, GMM‐based cut‐off: >1.41 SUVr = EC+). SILA was used to model trajectories of LC intensity and EC FTP separately. Time to onset of LC+ was correlated with baseline entorhinal tau and neocortical amyloid. Repeated measures correlations related the time to onset to LC+ to longitudinal entorhinal FTP and longitudinal PACC scores. Time to onset to LC+ and elevated EC+ were correlated to each other.Results75.25% (n=76) of the individuals were considered LC+ (Figure 1A) and 40.22% (n=37) was EC+ (Figure 2A). Being closer to the LC+ time to onset was correlated with higher entorhinal FTP (r=0.34, p<0.001), but not with neocortical PiB (r=0.09, p=0.42; Figure 1B‐C). Moving closer to the time to onset to LC+ was associated with faster accumulation of entorhinal FTP (r=0.40, p<0.001), and faster cognitive decline (r=‐0.39, p<0.001; Figure 1D‐E). The LC+/EC+ onset trajectories were positively correlated (r=0.23, p=0.025; Figure 2B), and 36% of the individuals was LC‐EC‐, 3% LC‐EC+, 50% LC+EC‐ and 36% LC+EC+, and the time between LC+EC‐ to LC+EC+ was 6.06 years (SD:3.15; Figure 2C).ConclusionsLC integrity imaging allows for temporal modeling and our data suggests that LC integrity precedes accumulation of entorhinal tau by on average 6 years. Future work will evaluate the impact of risk and protective factors on these trajectories.
Aging, beta‐amyloid deposition, and brain functional connectivity decline
Authors: Yi Dahyun , Chumin Evgeny J. , Byun Min Soo , Cha Woo‐Jin , Ahn Hyejin , Kim Yu Kyeong , Kang Koung Mi , Sohn Chul‐Ho , Risacher Shannon L. , Sporns Olaf , Nho Kwangsik , Saykin Andrew J. , Lee Dong Young ,   KBASE
Published: January 2025

AbstractBackgroundChanges in brain network organization are influenced by aging. Accumulation of amyloid‐beta (Aβ) and neurodegeneration in the neocortex are also expected to alter neuronal networks. Therefore, we examined the relationship between aging and brain functional connectivity (FC), as well as the effect of brain Aβ on this relationship.MethodResting state functional MRI (rsfMRI) from 594 participants spanning age and diagnostic severity of AD from the Korean Brain Aging Study for the Early Diagnosis and Prediction of AD (KBASE) was preprocessed as previously described in studies conducted at the Indiana AD Research Center (Chumin 2021, 2023). Cortical FC data from 200 regions (Schaefer 2018) grouped into 7 canonical resting state networks (RSN; Yeo 2011) was used to compute a network segregation measure (ratio of within‐ to between‐network connectivity (Chan 2014); here used as an index of FC) across all RSNs. Additionally, a subsample of older participants was classified as Aβ positive or negative based on global amyloid in Centiloid units (Klunk 2015).ResultIntrinsic network connectivity was reduced with increasing age beginning in young adulthood (Fig, left), resulting in a dedifferentiated, or less segregated, network architecture (t = ‐4.79, p = 0.000002). The relationship between age and network segregation was significant in the Aβ negative group (t = ‐4.09, p = 0.00005); however, such relationship was not found in the Aβ positive group (Fig, right). Fitted Aβ values were significantly different (Welch Two Sample t‐test: p < 2.2e‐16).ConclusionThis preliminary study elucidates age‐related decline of brain FC, quantified as network segregation, from young adulthood to late‐life, wherein RSN communication become less coherent, manifesting as a degeneration of FC structure. Such age‐related reduction pattern of brain connectivity appears disappear under the presence of pathological Aβ deposition in brain.