bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plasma biomarkers of neurodegeneration in the brain (UCH‐L1 and NfL) become exponentially higher with age from early childhood, and treatment of Alzheimer’s disease participants with granulocyte‐macrophage colony‐stimulating factor (GM‐CSF) lowers age‐associated levels of plasma UCH‐L1 by six decades
Authors: Sillau Stefan H , Coughlan Christina M , Ahmed Md. Mahiuddin , Nair Kavita V , Araya Paula , Galbraith Matthew D. , Bettcher Brianne M , Espinosa Joaquin M. , Chial Heidi J , Epperson Neill , Boyd Timothy D. , Potter Huntington 
Published: January 2025

AbstractBackgroundIncreasing age is the greatest risk factor for age‐associated cognitive decline (AACD) and, especially in females, for developing Alzheimer’s disease (AD). Mechanisms underlying this connection are unknown, but neuronal loss and brain atrophy accompany aging and AD and likely contribute to cognitive deficits. There are currently no means to measure neuronal cell death during life and no means to prevent it. Inflammation is also correlated with AD pathogenesis and aging (‘inflammaging’), but whether inflammation causes and/or is a response to neurodegeneration is unknown.Treatment of mouse models of AD with GM‐CSF reverses amyloid deposition and normalizes cognition, and GM‐CSF treatment improves cognition in aged wild‐type mice. A published double‐blind placebo‐controlled phase II trial showed that three weeks of treatment with recombinant human GM‐CSF (sargramostim) in mild‐to‐moderate AD participants improved cognition (MMSE) and blood biomarkers of amyloid, Tau, and neurodegeneration. Together, these results suggest that GM‐CSF may slow or halt the neuronal damage in aging and/or AD that causes cognitive deficits.MethodPlasma concentrations of ubiquitin C‐terminal hydrolase‐L1, UCH‐L1, a measure of neuronal cell loss, neurofilament light (NfL), a measure of axonal damage, and GFAP, a measure of inflammation/astrogliosis, were assessed cross‐sectionally in 317 healthy control participants between age 2 and 85 using the Quanterix SIMOA platform. The resulting age curves were compared to the results from the previously published clinical trial of sargramostim/GM‐CSF in participants with mild‐to‐moderate AD.ResultThe concentrations of human plasma proteins released from dying/damaged neurons (UCH‐L1 and NfL) showed an exponential increase from age 2‐85 and rise more in females. Plasma GFAP concentrations are exponentially higher after age 40, following neurodegeneration. Treatment of AD participants in the GM‐CSF/sargramostim trial halted neuronal cell death, based on the reduction in plasma UCH‐L1 concentrations to levels equivalent to those of five‐year‐old healthy controls. The ability of GM‐CSF treatment to reduce neuronal apoptosis was confirmed in the hippocampi of aged TgF344‐AD rats, a model recapitulates all human AD brain neuropathology.ConclusionThese findings suggest that age‐associated exponential increases in neurodegeneration may underlie the contribution of aging to cognitive decline, including in AD, and that GM‐CSF/sargramostim treatment may halt these effects.
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.
Histological evaluation of phospho‐epitopes within the core region of soluble and fibrillar tau
Authors: Abrahamson Eric E , Sehrawat Anuradha , Zeng Xuemei , Lafferty Tara K , Shao Lan , Karikari Thomas K , Ikonomovic Milos D 
Published: January 2025

AbstractBackgroundPhosphorylated tau proteins accumulate in pathological aggregates which define neurodegenerative tauopathies, including Alzheimer’s disease (AD). Insight into the early stages of tau polymerization/aggregation, including early hyperphosphorylation events, is critical for identification of biomarkers of incipient disease as well as novel therapy targets.MethodWe analyzed postmortem tissue sections of hippocampus from AD cases and middle frontal gyrus from non‐AD cases with mainly 4R tau isoforms (progressive supranuclear palsy, PSP; corticobasal degeneration, CBD; aging related tau astrogliopathy, ARTAG) or 3R tau (Pick’s disease, PiD). Immunohistochemical and multiple fluorescence methods were used to assess the labeling patterns of antibodies directed to phospo‐epitopes within soluble non‐fibrillar tau core (pSer262), both soluble and fibril core (pSer356), or outside of either core region (pSer202/pThr205, pThr231).ResultIn sections of hippocampus from AD cases, pSer262 and pSer356 stained punctate/granular tau aggregates in pretangles while pSer202/pThr205 and pThr231 antibodies stained tau in pretangles as well as classic NFT, neuritic component of plaques, and neuropil threads. Both pSer262 and pSer356 signals co‐distributed with pSer202/pThr205 signal in pretangles but were rarely detected in pSer202/pThr205 immunoreactive classic NFT. In sections of middle frontal gyrus from PSP and CBD cases, tufted astrocytes and astrocytic plaques, respectively, were robustly labeled with the pSer202/pThr205 antibody but lacked significant immunoreactivity to pSer262 and pSer356 antibodies. Similarly, thorn shaped astrocytes in ARTAG cases were robustly labeled with the pSer202/pThr205 antibody but were weakly labeled with the pSer262 and pSer356 antibodies. Pick bodies were labeled robustly with the pSer202/pThr205 antibody, moderately with the pSer356 antibody, and weak and sparsely with the pSer262 antibody.ConclusionAntibodies directed against phosphorylated epitopes within core region of soluble and fibrillar tau distinguish hippocampal pretangles in AD and appear to have less affinity for tau pathology forms in non‐AD tauopathies. Thus, they may be novel biomarkers for detecting early stages of neurofibrillary pathology development in AD.
The relationship between neighborhood disadvantage and the brain age gap
Authors: Martin Yolana C , Adluru Nagesh , Nair Veena A. , Prabhakaran Vivek , Alexander Andrew L , Johnson Sterling C. , Asthana Sanjay , Powell W. Ryan , Kind Amy J.H. , Bendlin Barbara B. 
Published: January 2025

AbstractBackgroundAccelerated aging is strongly linked to adverse social exposome and accelerated aging of the brain may be a dementia risk factor. Machine‐learning can estimate the biological “brain age” from neuroimages, which provides complementary information to the chronological/calendar age. The difference between biological and chronological age is referred to as the “brain age gap.” The Area Deprivation Index is a metric representing 17 indicators of neighborhood level poverty, education, employment, and physical environment, and provides a robust measure of the social exposome. The purpose of this work was to test the relationship between neighborhood‐level disadvantage and accelerated brain aging using brain age gap estimates in a Wisconsin cohort.MethodBrain age was estimated using T1‐weighted MR images from 1052 participants enrolled in the Wisconsin Registry for Alzheimer’s Prevention or Wisconsin Alzheimer’s Disease Research Center studies. Brain age was estimated using a publicly available deep learning model called the two‐stage‐age‐network (TSAN) that was pre‐trained on >4000 scans from OASIS, ADNI‐I, and PAC‐2019 datasets. Average brain age was used when multiple images were available at the same time point. Participants’ addresses were geolinked to their statewide ranking of neighborhood disadvantage using a time‐concordant ADI. Participants were binned by quintile based on state ADI rank, where Quintile 5 comprised of participants with highest ADI (Table 1). In the analyses, Quintile 5 was compared to a grouped category of Quintiles 1‐4. A marginal means test was conducted on a fitted one‐way ANOVA model to assess differences in mean brain age gaps between Quintile 5 and Quintiles 1‐4. The ANOVA model used quintile as a fixed effect predictor variable of brain age gap and a random effect of participant ID to account for participants with multiple visits.ResultThe mean brain age gap for Quintile 5 was 0.96 years (‐0.79, 2.71), and for Quintiles 1‐4 was 0.27 years (‐0.12, 0.66) (Figure 1).ConclusionThis analysis found that the mean brain age gap does not significantly differ between Quintile 5 and Quintiles 1‐4 (p≤0.45), however statistical power was low given very broad confidence intervals. Future work will test for longitudinal effects and incorporate a larger sample.
Biomarker Evaluation in Young Onset Dementia from Diverse Populations
Authors: Barragan Eden V. , Heuer Hilary W. , Nosheny Rachel L. , Camacho Monica R. , Navarra Krista , Aisen Paul S. S. , Rahman‐Filipiak Annalise , Roberts J. Scott , Ajayi Adeyinka , Byrd Desiree , Mindt Monica Rivera , Rabinovici Gil D. , Boxer Adam L. 
Published: January 2025

AbstractBackgroundEarly onset dementia (EOD) affects people at the peak of their personal and professional responsibilities and economic productivity. Alzheimer’s disease (AD) and Frontotemporal Dementia (FTD) are the most common EOD etiologies in Non‐Latinx White adults (NLW). Black and Latinx older adults bear a disproportionate burden of dementia compared to NLW, likely due to vulnerabilities that confer increased risk, such as cardiovascular factors, socioeconomic stressors, and structural racism. Little is known, however, about the prevalence and causes of EOD in Black, Latinx, and other diverse populations (DP) because most EOD studies have primarily recruited NLW individuals. Many barriers impede research participation in DP, but community‐engaged research (CER) strategies to collect diagnostic data, like blood‐based biomarkers and digital assessments, may increase access and convenience of research participation in DP.MethodThe BEYONDD study (www.beyonddproject.org), a new NIH‐funded study, is recruiting 200 DP individuals to evaluate the use of remote assessments and the impact of returning diagnostic information to participants as a more accessible research framework to understand the etiology of EOD in DP. Participants are recruited using CER strategies and screened via online platform for eligibility (age 40‐64, with concerns about cognitive or behavioral function). Participants complete the following procedures remotely and receive gift cards after completion: online questionnaires, self‐administered tablet‐based cognitive testing (Brain Health Assessment), and an in‐home blood draw for standard labs and plasma biomarkers of AD and neurodegeneration (Aβ and P‐tau217 ratios, NfL). Participants can learn their results remotely or in person. Participants are invited for more comprehensive onsite evaluation at one of 10 BEYONDD clinical centers, followed by appropriate referral to other NIH‐funded research programs.ResultThe study has recruited its first participants. Early participant feedback suggests that remote, accessible procedures may increase DP engagement and participation in EOD research. We expect substantial enrollment by July and will report initial results and plans for refinement of study procedures.ConclusionThe importance of surmounting historic barriers to DP participation in EOD research is clear. We plan to build on the experience of this project to improve DP enrollment into ongoing and future observational research and clinical trials.
Characterizing plasma biomarkers of Alzheimer’s disease in three non‐human primate species: marmosets, titi monkeys, and capuchins
Authors: Rothwell Emily S. , Lau Allison , Sosnowski Meghan , Bales Karen L. , Brosnan Sarah , Silva Afonso C , Rizzo Stacey J Sukoff 
Published: January 2025

AbstractBackgroundStudies of aging in non‐human primates are important to elucidate primate‐specific mechanisms underlying human aging, including pathological trajectories like Alzheimer’s disease (AD). Evidence of AD‐like brain aging has been reported across the primate order including amyloid beta (AB) deposits, but blood‐based biomarkers are less well‐studied. The goal of this project was to explore the use of validated assays for plasma biomarkers in two new non‐human primate species: coppery titi monkeys (Plecturocebus cupreus) and brown capuchins (Sapajus apella). We aimed to 1) assess the utility of the assay, 2) establish normative values, and 3) explore age‐related differences in biomarker levels. For each species, we assessed biomarkers sensitive to physiologic aging and pathological conditions including neurodegeneration/neuronal injury (neurofilament light chain, NfL), neuroinflammation (glial fibrillary acidic protein, GFAP), neuropathology (AB40, AB42, pathological tau).MethodPlasma samples were obtained from males and females of adult common marmosets (Callithrix jacchus) (n=85), titi monkeys (n= 33), and capuchins (n=19), and evaluated using MesoScale Discovery (MSD): AB Peptide 4G8 Panel & Neurology Panel 1multi‐plex ELISAs. Samples from genetically engineered marmosets with early onset familial mutations in the presenilin 1 (PSEN1) gene were included as positive controls and benchmarks (Sukoff Rizzo et. al, 2023).ResultAB40, AB42, Tau, GFAP, and NfL were detectable in plasma from titi monkeys and capuchins. Biomarker levels across ages of each species had comparative values and overlapping ranges with wildtype (WT) adult marmosets. Consistent with previous data PSEN1 knock‐in marmosets had the expected increase in plasma AB42 relative to WT, with some individuals of each species showing naturally elevated levels. For both marmosets and titis, NfL was found to increase with advancing age. Titi monkeys also showed increases in AB40 and GFAP with age.ConclusionThe present data are the first to demonstrate normative values for plasma biomarkers of neurodegeneration, neuroinflammation, and neuropathology in capuchin and titi monkeys. Preliminary results show comparative values and aging trajectories across three species of non‐human primates. Ongoing studies are evaluating additional individuals and species, to longitudinally track aging which will facilitate understanding primate‐specific mechanisms underlying healthy human aging as well as AD.
Associations of cerebral amyloid and tau with neurocognitive performance: Findings from the 90+ Study
Authors: Fletcher Evan , Sapkota Shraddha , Martinez Oliver , Corrada María M. M. , Woodworth Davis C. , Sajjadi S. Ahmad , Decarli Charles 
Published: January 2025

AbstractBackgroundAssociations between cognition and brain markers of amyloid, tau, and neurodegeneration are poorly understood in the oldest‐old (>90 years) compared to younger populations. Prior work suggests that the link between neuropathology and cognition may become weaker in advanced old age, reducing the applicability of accepted biomarker cascade models of Alzheimer’s disease progression. Addressing this question in the oldest‐old is challenging, partly due to limited data and methodological challenges of neuroimaging analysis. In this study, we examine the associations of (1) cerebral amyloid and tau, (2) amyloid and cognitive performance, and (3) tau and cognitive performance, in the overall group and as stratified by amyloid positivity.MethodParticipants were from the oldest‐old cohort from the 90+ Study at University of California, Irvine (N=98; mean age at assessment=92.04 years; %female=53,). We used MRI‐free analyses of PET imaging to investigate the relations among amyloid (AV45), tau (AV1451) in Braak regions 1/2, 3/4 and 5/6, and cognitive measure (Mini‐Mental State Exam [MMSE]). Native PET images were warped directly to an appropriate PET template, yielding SUVRs computed using cerebellar reference means. Amyloid positivity used an SUVR cutoff of 1.11, computed over a standard index region. All regressions were controlled for age, sex, education, and Apolipoprotein E status.ResultGroup characteristics are in Table 1. In the amyloid positive group (N=61), we found significant associations for amyloid with tau in Braak 1/2 (p=0.03; Figure 1), and MMSE (p=0.045; Figure 2). Associations of MMSE with tau Braak regions varied (Braak 1/2: p=0.086, Braak 3/4: p=0.018, Braak 5/6: p=0.061; Figure 3). We observed no significant associations in the full cohort or in the amyloid negative group.ConclusionMRI‐free PET processing yielded results in the oldest‐old that are consistent with expected relations among amyloid, tau and cognition. Accurate SUVR measurement requires rigorous template registration and quality control. All significant associations occurred in the amyloid positive group, showing expected relations of amyloid to cognition and early Braak stage tau, and tau to cognition, consistent with accepted models. However, small sample size limited our findings. Further studies are needed to clarify the applicability of amyloid‐tau models in this age group.
Association between Default Mode Network Connectivity Compared Between Two Tau Tracers (Flortaucipir vs. MK6240) – HEAD Study
Authors: Karim Helmet T. , Povala Guilherme , Bauer‐Negrini Guilherme , Lussier Firoza Z , Pascual Belen , Gordon Brian A. , Lowe Val J. , Oh Hwamee , soleimani‐meigooni David N. , Rosa‐Neto Pedro , Jagust William J. , Klunk William E , Baker Suzanne L. , Pascoal Tharick Ali 
Published: January 2025

AbstractBackgroundDefault mode network (DMN) resting state connectivity has been correlated with heightened amyloid and tau – hallmarks of Alzheimer's Disease (AD). Tau is postulated to impact a meta‐temporal area including DMN‐associated regions like amygdala, entorhinal cortex, fusiform gyrus, parahippocampus, inferior temporal, and middle temporal gyrus. We recruited individuals with varying cognitive status to undergo resting state connectivity and imaging with two tau tracers (Flortaucipir and MK6240). We investigated the association between DMN connectivity and both global and regional (meta‐temporal) tau.MethodsWe studied 149 adults who were young cognitively healthy (n=10, 21‐25 years, 5F), older cognitively healthy (n=85, 50‐83 years, 51F), had MCI (n=43, 53‐84 years, 23F), or had AD (n=11, 62‐84, 6F). All individuals underwent resting state imaging and PET imaging with both Flortaucipir and MK6240 tau tracers. Resting data was preprocessed and DMN connectivity was estimated using bilateral posterior cingulate gyrus as region of interest. Tau tracer uptake was preprocessed (Pascoal. et al), and voxel‐wise standardized uptake value ratio (SUVR) was computed using inferior cerebellar gray matter as reference. We computed universal and meta‐temporal uptake for both tracers. We conducted four voxel‐wise associations between DMN connectivity and uptake in each tracer. We corrected for multiple comparisons using SnPM13 to estimate non‐parametric p‐values (10,000 permutations), we used a cluster forming threshold of p=0.001 and corrected for multiple comparisons by controlling the family‐wise error rate (FWE) at p=0.05.ResultsGreater universal Flortaucipir uptake was associated with lower within‐network DMN connectivity (bilateral posterior cingulate, precuneus, angular/supramarginal gyrus, and inferior parietal) but greater between‐network DMN connectivity (superior parietal, postcentral gyrus; Figure 1A). Greater universal MK6240 uptake was associated only with greater DMN‐cerebellum connectivity (Figure 1B). Greater meta‐temporal Flortaucipir was associated with lower within‐network DMN connectivity similar to universal uptake with addition of medial prefrontal cortex and middle temporal gyrus (Figure 2A). Greater meta‐temporal MK6240 was only associated with greater DMN‐superior parietal connectivity (Figure 2B).ConclusionsThese preliminary findings show that uptake using different tau tracers may lead to varying conclusions on association with connectivity. This may have implications for understanding the role of tau in altering resting state connectivity findings.