bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Effects of Ethnicity, Sex, and APOE Status on Markers of Inflammation
Authors: Contreras Joey A , Aslanyan Vahan , Ortega Nancy E , Pa Judy 
Published: January 2025

AbstractBackgroundAlzheimer’s Disease (AD) is the most common form of dementia and is considered to disproportionately affect underserved populations like Hispanics/Latinos. Most research available with AD markers such as inflammation and APOE4 has been conducted in predominantly White cohorts, leaving a dearth of knowledge relating APOE4 and inflammation in Hispanic/Latinos. Recent research also suggests inflammation and AD risk may be sex‐specific. This study investigated the effects of race/ethnicity, sex/gender, and APOE4 on inflammatory markers.MethodUsing data from the Health and Aging Brain Study‐Health Disparities (HABS‐HD), we assessed group differences between APOE4 status, ethnicity, and sex on anti‐inflammatory marker interleukin‐10 covarying for age and education.ResultThe dataset included 817 Mexican Americans (65% women, 18% APOE4 carrier, mean age±SD=63.21±8.04 years) and 746 white participants (54% women, 30% APOE4 carrier, mean age±SD=68.59±8.70 years) (Table 1). We found two‐way interactions between sex and race/ethnicity (p=0.03) on IL‐10, driven by higher IL‐10 levels in Mexican American men; sex and APOE4 status (p=0.001), driven by higher IL‐10 among APOE4 carriers in men; and race/ethnicity and APOE4 status (p=0.001), driven by higher IL‐10 levels APOE4 carriers among Mexican Americans (Figure 1A,B and C respectively).ConclusionIL‐10 is an important anti‐inflammatory modulator of glial activation, preventing inflammation‐mediated neuronal degeneration under pathological conditions. It has multiple immunoregulatory effects such as in ability to inhibit the production of several inflammatory cytokines. These findings support previous studies demonstrating heightened systemic inflammation in APOE4 carriers, but little has been shown regarding their relationship with gender and ethnicity. This finding suggests the importance of examining differences that may exist between APOE4, sex, and inflammatory markers in Hispanics/Latinos. Future work will examine other inflammatory markers.
Assessing the association between cholinergic integrity and cognitive performance in adults with Down Syndrome using cholinergic anatomy and [18F]‐FEOBV PET
Authors: Russell Jason K , Conley Alexander C , Boyd Brian , Schlossberg Rachel , Stranick Allison , Rosenberg Adam J , Acosta Lealani Mae Y. , Rafii Michael , Shokouhi Sepideh , Newhouse Paul A 
Published: January 2025

AbstractBackgroundTriplication of the amyloid precursor protein in individuals with Down Syndrome (DS) produces an increased risk for the development of Alzheimer's disease (AD). Declining cholinergic integrity plays a role in the cognitive deficits observed in late‐onset AD. In the present study, we assess the relationship between basal forebrain volume or [18F]‐FEOBV uptake and cognitive performance in adults with DS.Method188 individuals from the ABC‐DS cohort (U01AG051406; U01AG051412; U19AG068054) were assessed cross‐sectionally. Basal forebrain volumes were calculated from T1 MRIs using the ScLimbic FreeSurfer pipeline. Ten individuals were recruited as part of a TRC‐DS sub‐study (25‐55 years old) or de novo (18‐24 years old), where they underwent MRI imaging and [18F]‐FEOBV PET imaging. Regional [18F]‐FEOBV SUVRs were calculated using PetSurfer. Participants from both studies underwent numerous cognitive assessments. Linear regressions were performed between cognitive performance and regional [18F]‐FEOBV SUVR or basal forebrain volume correcting for intellectual disability.ResultIn the ABC‐DS cohort, the Down Syndrome Mental State Exam (DSMSE) total score was positively associated with basal forebrain volume (p<0.05), and total free recall on the cued recall task was positively associated with left basal forebrain volume (p=0.0027). In the TRC‐DS sub‐study, [18F]‐FEOBV uptake in the right amygdala, right rostral anterior cingulate cortex, and left transverse temporal cortex were positively associated with DSMSE total score (p<0.05). In the cued recall task, [18F]‐FEOBV uptake in the left cuneus and right entorhinal cortexes and the isthmus of the right cingulate cortex was negatively associated with total free recall (p<0.05).ConclusionIn the ABC‐DS cohort, increased cholinergic integrity predicted improved performance on the DSMSE and cued recall task. Regional [18F]‐FEOBV uptake can indicate which areas of cholinergic innervation are important for these different cognitive tasks. Increased regional [18F]‐FEOBV uptake predicted improved performance on the DSMSE, with the object memory and apraxia sub‐scores displaying the largest effect sizes. Interestingly, increased [18F]‐FEOBV uptake predicted decreased free recall in the cued recall task. This unexpected result may indicate upregulation of the vesicular acetylcholine transporter in this non‐demented DS cohort or may be spurious due to the small cohort. Increased sample size will further elucidate this effect.
Clinical Performance of Plasma Aβ42/Aβ40, p‐tau217 and Neurofilament Light in Sporadic Frontotemporal Dementia Spectrum Disorders with subsequent comparison of pathology
Authors: Rajbanshi Binita , Heuer Hilary W. , VandeVrede Lawren , Ljubenkov Peter A. , Lago Argentina Lario , Araujo Igor Prufer Q C , Staffaroni Adam M. , Petrucelli Leonard , Gendron Tania F , Rosen Howard J. , Boeve Brad F. , Bateman Randall J. , Rojas Julio C. , Boxer Adam L. ,   ALLFTD Consortium
Published: January 2025

AbstractBackgroundIdentification of useful fluid biomarkers is expected to advance frontotemporal dementia spectrum disorders (FTD) care and therapeutic development. The clinical utility of emerging plasma Amyloid, Tau, and Neurodegeneration (ATN) biomarkers in FTD remains unexplored. This study analyzed ATN patterns by sporadic FTD phenotype, based on amyloid beta1‐42 (Aβ1‐42), amyloid beta1‐40 (Aβ1‐40), phospho‐tau217 (p‐tau217), and neurofilament (NfL) plasma concentrations.MethodThe present study included 625 participants enrolled in ALLFTD (46% female, median age 61 ± 12 years) for whom biomarker data were available. Plasma Aβ1‐42/Aβ1‐40 measures were determined by immunoprecipitation‐mass spectrometry whereas plasma p‐tau217 and NfL concentrations were respectively determined by electrochemiluminescence‐ and fluorescence‐based immunoassays. Biomarker concentrations were compared by phenotype and disease severity with ANOVA. Their diagnostic performance was tested with Receiver Operating Characteristic (ROC) curves, and biomarker relationships with measures of clinical severity were tested through linear regressions controlling for age, sex, and APOE genotype.ResultHigher plasma p‐tau217 and p‐tau217/Aβ1‐42, levels were observed in logopenic primary progressive aphasia (lvPPA) and amnestic dementia (AmD) cohorts, compared to other FTD groups. These biomarkers were not associated with disease severity but were affected by APOE4 genotype. High plasma NfL level was observed in fully symptomatic patients compared to controls, and as a function of disease severity. Plasma Aβ1‐42/Aβ1‐40 level was not different between phenotypes and was not affected by clinical severity. P‐tau217 level, but not Aβ1‐42/Aβ1‐40 or NfL levels showed high discrimination of lvPPA and AmD from other phenotypes (AUC = 0.87 (95% CI 0.77 – 0.96, p < 0.0001, 73% sensitivity, 92% specificity). The p‐tau217/Aβ1‐42 ratio improved this discrimination (AUC = 0.9, 95% CI 0.83 – 1, p < 0.0001, 77% sensitivity, 94% specificity). Plasma Aβ1‐42/Aβ1‐40, p‐tau217, NfL, p‐tau217/Aβ1‐42, p‐tau217/NfL, and (Aβ1‐42 x p‐tau217)/NfL were associated with cognitive (MoCA, CVLT), motor (UPDRS), and social behavior (RSMS) performances at baseline.ConclusionPlasma p‐tau217/Aβ1‐42 identifies, with high specificity, two phenotypes associated with Alzheimer’s disease: lvPPA and AmD. Pending molecular neuroimaging and neuropathological confirmation, this biomarker could be of value to identify primary Alzheimer’s disease pathology or co‐pathology associated with Alzheimer’s disease when sporadic FTD is suspected.
Discovery of region‐specific lipid biomarkers characterized by distinct changes over time in the brains of APPsw mice
Authors: McIntire Laura Beth , Wartchow Krista Minéia , Costa Ana Paula , Krumsiek Jan , Mares Jason , Menon Vilas , Lazarian Artur , Bartelo Nicholas , Dartora William 
Published: January 2025

AbstractBackgroundAlzheimer's disease (AD) is associated with impaired lipid metabolism in the brain. To identify the specific regions where pathological change to cell functionality occurs, a spatial investigation of regional lipid dysregulation is needed.MethodWe measured untargeted spatial lipidomics using Desorption Electrospray Ionization (DESI) mass spectrometry in the brains of mice from two genotypes, wild type (WT) and APPsw, an AD mouse model overexpression amyloid precursor protein (APP). We generated a longitudinal profile of these mice at ages 6 months, 12 months, and 22 months. We computationally segmented brain regions defined by the Allen Mouse Brain Atlas to discover region‐specific differential lipid biomarkers across age and genotype. We developed “Spatial Lipidomics Analysis Tool” (SLAT), a computational framework which identifies statistically differential ions between age and genotype in a region‐specific manner, and applied this to our data. Independently of SLAT, we applied K‐means clustering to lipidomics as an unbiased approach to find regions in whole brains that may drive the development of disease. We applied K‐means clustering to log2 fold changes (log2FC) to find groups of significant ions reported by SLAT characterized by similar changes in abundance in APPsw mice over time compared to 6 months WT mice.ResultWe identified the globus pallidus (GP) as having multiple significantly differential lipids between WT and APPsw samples. However, whole brain analysis was unable to identify significant differential ions between genotypes, demonstrating the advantage of region‐specific‐analysis. Additionally, the GP was found to drive clustering for specific ages and genotypes. Longitudinal analysis of significant GP ions revealed multiple groups of ions with coordinated changes in ion intensity over time. The group of ions with the greatest temporal changes had a 0.50 log2FC increase from 6 to 12 months, followed by a 0.63 log2FC decrease from 12 to 22 months, on average.ConclusionOur results illustrate lipid biomarkers specific to the GP which may have potential use for the diagnosis and prognosis of AD. The development of SLAT as a partially automated pipeline to analyze longitudinal data with different phenotypes can be utilized as a tool for discovery of disease‐specific mechanisms from spatial lipidomics and metabolomics data.
The association between plasma amyloid β and a risk of conversion from mild cognitive impairment to Alzheimer’s disease dementia
Authors: Kaneko Naoki , Kimura Noriyuki , Masuda Teruaki , Ataka Takuya , Takeuchi Tsukasa , Ito Temmei , Tasai Hideaki , Miyagawa Takehiko , Iwamoto Shinichi , Matsubara Etsuro 
Published: January 2025

AbstractBackgroundAbnormal amyloid‐β (Aβ) deposition in the brain has been defined as the earliest pathological change of Alzheimer disease (AD). Immunoprecipitation coupled with MALDI‐TOF MS (IP‐MS) has previously revealed that APP669–711/Aβ1–42 ratio, Aβ1–40/Aβ1–42 ratio, and a combination of these two biomarkers (a composite biomarker) in human plasma correlates highly with SUVR obtained from amyloid PET. In this work, we investigate the usefulness of plasma Aβ biomarkers at baseline in predicting the conversion to AD dementia.MethodPlasma samples were obtained from participants with mild cognitive impairment (MCI) in community‐based cohort. One‐hundred seven samples measured with IP‐MS were analyzed to evaluate a risk of conversion from MCI to AD dementia. Amyloid positivity was assessed using 11C‐PiB PET based on a threshold of a standardized uptake value ratio of 1.2.ResultAmong 107 MCI participants, 28 converted to AD dementia within seven years and 61 remained stable at the MCI state for seven years or longer. Others converted to non‐AD dementia or dropped out within seven years. The MCI participants who converted to AD dementia (MCI‐AD) showed higher baseline plasma Aβ biomarker values than stable MCI (p < 0.001). ROC analysis demonstrated high AUC (0.860, for the composite biomarker; 0.825 for the Aβ1‐40/Aβ1‐42; 0.828 for the APP669‐711/Aβ1‐42) in discriminating between MCI‐AD and stable MCI. The risk of AD conversion was significantly differed among low, intermediate and high groups categorized by the composite biomarker level (p<0.0001, Log‐rank test). In Cox regression analysis, the high and intermediate groups were associated with increased risk of AD dementia compared to the low group (the hazard ratio (HR) = 6.51 for the intermediate group and the HR = 10.33 for the high group).ConclusionOur results suggested that the Aβ composite biomarker was associated with the risk of the conversion from MCI to AD dementia. In addition, the time from MCI to AD conversion was differed dependent on the level of the Aβ composite biomarker. The Aβ composite biomarker might be useful in predicting the conversion from MCI to AD dementia.
Individual variation in proteomic cascades along the Alzheimer’s disease spectrum
Authors: Vogel Jacob W. , Vilkaite Gabriele , Binette Alexa Pichet , Hristovska Ines , Xiao Yu , Mastenbroek Sophie E. , Rittmo Jonathan , Janelidze Shorena , Palmqvist Sebastian , Salvadó Gemma , Smith Ruben , Stomrud Erik , Strandberg Olof , Young Alexandra L. , Ossenkoppele Rik , Mattsson‐Carlgren Niklas , Hansson Oskar 
Published: January 2025

AbstractBackgroundCerebrospinal fluid (CSF) proteomics allows for characterization of multiple disease‐related biological processes in vivo. These processes likely occur along temporal cascades mirroring disease evolution. This study describes interindividual variation in these cascades, in the context of Alzheimer’s disease.MethodParticipants were recruited from the Swedish BioFINDER‐2 study, diagnosed as cognitively normal (n=251; CN), subjective cognitive decline (SCD; n=129), mild cognitive impairment (MCI; n=134) or Alzheimer’s dementia (AD; n=159). All MCI and AD were β‐amyloid (Aβ)‐positive via CSF Aβ42/40 ratio. CSF was sequenced with the Olink Explore 3072 panel, resulting in 1331 proteins after quality control. All participants also underwent [18F]RO948 tau‐PET scans. Age, sex, and the first non‐disease‐related principal components (n=3) were regressed from the proteomic data. A bootstrapped hierarchical clustering approach extracted and annotated ten networks of co‐expressed proteins (Figure 1A). Networks with univariate relationships to Aβ, tau or diagnosis (n=7) were submitted to the Subtype and Stage Inference (SuStaIn) algorithm (Figure 1B). SuStaIn assigned participants to a subtype and stage based on sequential abnormality of proteomic network expression. Regression models assessed SubtypeXStage interactions on regional tau‐PET or MMSE, adjusting for age, sex and diagnosis.ResultA two‐subtype model best fit the data (Table 1). N=244 showed normal protein network levels (S0). Subtype‐1 (S1) showed early and sustained abnormality in vascular (P3) and chemokine (P0) networks, followed by increasing abnormality of a nucleotide‐metabolism network (P9). Subtype‐2 (S2) showed increasing abnormality in lysosomal (P1) and immune (P2) networks (Figure 1C). CN were more likely to be S0 (𝛘2=23.2, p<0.001) and a lower stage (F=20.5, p<0.001), but S1 and S2 did not differ by diagnosis (Figure 2A). S0 and S2 showed decreased tau‐PET load compared to other groups (Figure 2C). Subtype*stage interactions showed S2 participants had less tau‐PET load and higher MMSE scores at more advanced stages compared to S1 (Figure 2C‐E).ConclusionTwo proteomic cascades emerged along the AD continuum, with one accompanying relatively lower tau levels and preserved cognition. Longitudinal follow‐up will reveal if this cascade is indicative of increased vulnerability or resilience of AD pathology.
Association of Plasma Protein Risk Score and Risk of Cognitive Impairment in the Framingham Heart Study
Authors: Rehman Habbiburr , Ang Ting Fang Alvin , Tao Qiushan , Au Rhoda , Farrer Lindsay A. , Qiu Wei Qiao , Zhang Xiaoling 
Published: January 2025

AbstractBackgroundPlasma‐based biomarkers are emerging as a new diagnostic tool for Alzheimer’s disease (AD) with high accuracy and low cost. Whether aggregated plasma protein risk score (PPRS) derived from a single sample could be useful for diagnosis of incident mild cognitive impairment (MCI) and AD is uncertain. This study aims to understand the association between PPRS and future risk of AD related outcomes.MethodWe included Framingham Heart Study (FHS) Offspring cohort participants with plasma aptamer based SOMAscan proteomics assay data at exam 5. After excluding subjects who were have missing data for AD risk factors (age, sex, education and APOE ɛ4) and had other‐types of dementia, 1523 participants (cognitive normal (CN)=1258, MCI=137, AD=128) were considered for the primary analyses. The Cox model with LASSO penalty was used to build the PPRs for AD and MCI. The association of PPRS for AD risk was tested for outcomes of MCI/AD incidence (mean follow‐up=23.06 years), brain volume, and blood AD biomarkers.ResultWe identified 279 proteins for inclusion in the MCI PPRS and 103 proteins for inclusion in the AD PPRS. The MCI PPRS had a hazard ratio (HR) of 1.79 [4.99, 7.37] and the discriminating power (C‐index) was 0.86, and after including risk factors C‐index was 0.88. The AD PPRS had a HR of 1.79 [4.86,7.33] and the C‐index was 0.89 and after including the risk factors the power of the model was improved (C‐index=0.92). The chance of developing AD for a CN participant at age 80 years with in 20 years with high AD PPRS was 85% and with low AD PPRS was 15%. Brain volume distribution using 8 variables was significantly decreasing with increasing level of MCI PPRS (p‐value<0.001 for 5 variables) and AD PPRS (p‐value<0.001 for all 8 variables). The increased levels of MCI PPRS (p‐value<0.001) and AD PPRS (p‐value<0.001) were also significantly associated with increased plasma p‐tau181.ConclusionThis study suggests that aggregated protein risk scores from plasma samples can be used to predict future risk of MCI and AD, thus serving as a potential screening tool for early intervention to prevent AD or slow its progression.
Plasma dicarboxylic acids as indicators of impaired energy metabolism and lipid oxidation associated with pre‐symptomatic Alzheimer’s disease
Authors: Jose Joby , Fonteh Alfred N. 
Published: January 2025

AbstractBackgroundDicarboxylic acids (DCAs) are critically important for intermediate metabolism. Since mitochondrial dysfunction and energy dysregulation are associated with AD pathology, we hypothesize that fluctuations in plasma DCAs would accompany AD pathology.MethodIn an ongoing brain‐aging study, we recruited older adults (>65 years) classified as cognitively healthy (CH) after neuropsychological testing. Based on the CSF biomarker analysis, we further categorized them as CH participants with normal biomarker levels (CH‐A‐T‐N‐) and CH participants with AD‐like pathological biomarker levels (CH‐A+T*N‐) having a high risk of cognitive decline (presymptomatic AD). We collected plasma from the participants and extracted DCAs using ethyl acetate. We derivatized the DCAs using dimethylaminophenacyl bromide (DmPABr) to reverse the DCA polarity and enhance the sensitivity of detection. DCA levels were quantified using isotope dilution liquid chromatography mass spectrometry with multiple reaction monitoring of C3‐C22 DCAs. The group differences between CH‐A‐T‐N‐ and CH‐A+T*N‐ were calculated using Mann‐Whitney comparison tests.ResultDistribution studies revealed that most of the dicarboxylic acids in the plasma samples (n = 4) are short‐chain (≈80%) and medium‐chain DCAs (≈15%), while long‐chain DCAs make less than 5% (Figure 1). We compared the distribution of plasma DCAs in CH‐A‐T‐N‐ versus CH‐A+T*N‐ and identified three groups. The DCA composition of group 1 DCAs (C4+C5) was lower in CH‐A+T*N‐ than in CH‐A‐T‐N‐. In contrast, the DCA levels of group 2 (C7+C8+C9) and group 3 (C14+C16+C18+C22) were higher in the CH‐A+T*N‐ plasma compared to CH‐A‐T‐N‐. Using ROC, significant differences in the AUC were shown for each of the three groups (Figure 2). The group differences resulted in significantly higher group 1/group 2 and group 1/group 3 ratios in CH‐A‐T‐N‐ compared to CH‐A+T*N‐ (Figure 3).ConclusionWe identified 14 DCA species in plasma and showed that their plasma composition varied with AD biomarker levels. DCAs associated with energy (group 1) were higher in CH‐A‐T‐N‐ than in CH‐A+T*N‐, while DCAs linked with longer‐chain fatty acid oxidation (group2 & 3) were higher in CH‐A+T*N‐ than in CH‐A‐T‐N‐. These data suggest that there is dysregulation of DCA metabolism in pre‐symptomatic AD, and plasma levels of DCAs can be used as biomarkers of early‐stage AD.
Preliminary Validation of a Structural Magnetic Resonance Imaging Metric for Differential Diagnosis of Frontotemporal Lobe Dementias
Authors: Kress Gavin T , Popa Emily S. , Thompson Paul M. , Bookheimer Susan Y. , Thomopoulos Sophia I , Ching Christopher RK , Zheng Hong , Merrill David A. , Raji Cyrus A. , Panos Stella E. , Siddarth Prabha , Bramen Jennifer E. 
Published: January 2025

AbstractBackgroundAD‐NeuroScore is a validated metric that summarizes Alzheimer’s disease (AD)‐specific atrophy and can detect AD early, benchmark disease severity, predict and monitor AD progression, and can aid in testing the efficacy of therapeutic interventions using a single number (Kress, 2023). It meets criteria for translatability by using clinically available regional brain volumes as input (Ahdidan, 2015; Cavedo, 2022) and having patient and model‐level interpretability (Pinto, 2022). Also, features can be reviewed by a neuroradiologist (Larson, 2019). Scores are harmonized for intracranial volume, age, sex, and scanner model, improving workflows for longitudinal patient tracking. The objective of this study is to examine whether AD‐NeuroScore can be used in the differential diagnosis of AD and FTD dementia subtypes.MethodCognitively normal (CN) individuals and patients with a mild cognitive impairment (MCI), AD, behavioral variant (bv)‐FTD, semantic variant (sv)‐FTD, and progressive nonfluent aphasia (pnfa)‐FTD diagnoses were drawn from the ADNI and NIFD cohort studies. Eighty‐four cortical and subcortical regional volumes were estimated from T1‐weighted MR images using FreeSurfer. AD‐NeuroScore uses a modified Euclidean‐inspired distance function to calculate differences between individuals and a CN template based on regional brain volumes associated with cognitive decline (Kress, 2023). Validation used an experimental cohort (Table 1) and tested sensitivity to differentiating CN, MCI, and AD from FTD‐subtypes (bv, sv, and pnfa) using pairwise t‐tests and an alpha=0.001, Bonferroni corrected. Area under the curve (AUC) was calculated. Results were benchmarked against adjusted hippocampal volume (AHV), an NIA‐AA diagnostic biomarker for AD (Jack, 2018), which was also harmonized for intracranial volume, age, sex, and scanner.ResultBoth AD‐NeuroScore and AHV distinguished between AD and svFTD and pnfaFTD variants. AD‐NeuroScore better differentiated svFTD from AD than AHV (Table 2; Figure 1). AHV performed as well or qualitatively better than AD‐NeuroScore at distinguishing AD from pnfaFTD. Neither AD‐NeuroScore nor AHV differentiated AD and bv‐FTD.ConclusionAD‐NeuroScore differentiated between AD, svFTD, and pnfaFTD and overall, performed equivalently to or better than AHV. Performance and utility in longitudinal tracking may be improved by creating FTD variant scores using with a focus on regions specific to FTD subtypes.