bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cortical neurodegeneration influences annual posterior white matter hyperintensity progression
Authors: Moyano Jose Bernal , Menze Inga , Yakupov Renat , Peters Oliver , Priller Josef , Schneider Anja , Fliessbach Klaus , Wiltfang Jens , Jessen Frank , Buerger Katharina , Perneczky Robert , Teipel Stefan , Laske Christoph , Spottke Annika , Heneka Michael T. , Schreiber Stefanie , Düzel Emrah , Ziegler Gabriel 
Published: January 2025

AbstractBackgroundFor over three decades, the concomitance of cortical neurodegeneration and white matter hyperintensities (WMH) has sparked discussion about their coupled temporal dynamics (Garnier‐Crussard et al. 2023). Longitudinal evidence supporting this hypothesis remains nonetheless scarce (Ter Telgte et al. 2018).We integrated surface‐based morphometry and bivariate latent change score modelling (BLCSM) to examine interrelationships between individual WMH and cortical thickness changes over a one‐year period in cognitively unimpaired participants.MethodWe analysed baseline and 12‐month follow‐up data from cognitively unimpaired DELCODE participants (n=393; median age 70.31 [IQR 66.06‐74.87] years; 52% females). We used T2w FLAIR and T1w MPRAGE data to segment WMH (LST; Schmidt and Wink 2019) and estimate cortical thicknesses (CAT12; Gaser et al., n.d.).Using BLCSM in a vertex‐wise fashion, we tested whether baseline WMH volumes predicted cortical thinning rates and whether baseline cortical thickness predicted WMH volumes increases (Figure 1). Due to the posterior dominance of WMH in AD (Bernal et al. 2023), we focussed on parietal and occipital WMH. All models included age, sex, years of education, and total cardiovascular risk factors as covariates on baseline and change scores. We log‐10 transformed WMH volumes and corrected WMH volumes and thicknesses measurements for TICV via residualisation. We finally tested for moderation effects of CSF‐derived Aβ42/40 and pTau181 on cross‐domain coupling.ResultBLCSM generally provided good data fits (RMSEA≤0.05, CFI≥0.095, SRMR≤0.05) across all analyses.The mean thickness across precuneal and superiorparietal cortices at baseline predicted the progression of WMH better than any other cortical region (Figure 2B; βThick→ΔWMH=‐0.051, SE=0.011, Z=‐4.535, p‐value<0.001). This was especially evident with lower CSF‐derived Aβ42/40 (βThick*Aβ42/40→ΔWMH=0.176, SE=0.053, Z=3.309, p‐value=0.001).WMH volume at baseline explained, in part, the level of thinning of parts of the fusiform cortex (Figure 2D; βWMH→ΔThick=‐0.139, SE=0.028, Z=‐5.030, p‐value<0.001). This interrelationship was moderated by CSF‐derived pTau181 (βWMH*pTau181→ΔThick=‐0.144, SE=0.053, Z=‐2.711, p‐value=0.007).ConclusionCortical thinning and WMH progression may be mutually reinforcing processes that become reciprocally coupled prior to any detectable cognitive deficits. Hallmark AD proteins appear to moderate their interrelationships.
Brain‐based predictions of cardiovascular risk factors in midlife populations at risk of dementia
Authors: Cao Bolin , Deng Feng , Qi Qing , Dounavi Maria‐Eleni , Muniz‐Terrera Graciela , Malhotra Paresh , Koychev Ivan , O'Brien John T , Ritchie Craig , Lawlor Brian , Naci Lorina 
Published: January 2025

AbstractBackgroundDementia, particularly Alzheimer's disease (AD), is a significant public health concern, with midlife emerging as a critical period for preventive intervention (Livingston, 2017). Dementia's heterogeneity renders single risk factor insufficient for accurate identification of individuals at risk (Stephen, 2021). Multifactorial risk scores, such as the cardiovascular risk factors, aging, and dementia (CAIDE) score (Kivipelto, 2006), which include both cardiovascular (blood pressure, cholesterol, BMI, physical inactivity) and non‐modifiable factors (age, sex, APOE ε4 genotype), are vital in assessing dementia risk. This study, using the network‐based statistic (NBS)‐Predict model (Serin, 2021), aimed to explore the functional brain architecture associated with these risk factors, aiding in personalized prevention and intervention strategies for dementia.MethodResting‐state fMRI data, CAIDE, cardiovascular and non‐modifiable risk scores, and lifetime of experiences questionnaire (LEQ) data were analyzed from 585 healthy participants (females/males=207/378, mean age=50.9) in the PREVENT‐Dementia study (Ritchie, 2023). Using the Dosenbach atlas, functional connectivity (FC) matrices were constructed post‐data preprocessing. The NBS‐Predict model, employing a linear support vector machine with 10‐fold cross‐validation, feature selection at p<0.05, and 1000 permutations, predicted CAIDE, cardiovascular, and non‐modifiable risk scores (Figure 1). A hierarchical regression model assessed the impact of midlife LEQ score on FC linked to cardiovascular risk factors, with LEQ scores, age, sex, education years, and mean framewise displacement as independent variables.ResultNBS‐Predict models significantly predicted the CAIDE (r=0.214, p<0.001), cardiovascular (r=0.201, p<0.001), and non‐modifiable (r=0.237, p<0.001) risk factors scores. Similar FC patterns were observed between the CAIDE and cardiovascular risk scores, particularly involving the somatomotor and cingulo‐opercular networks (Figure 2a), contrasting with distinct patterns for non‐modifiable risk factors. The non‐specific LEQ score positively correlated with FC in regions affected by cardiovascular risk factors (β=0.001, p=0.017).ConclusionThe study demonstrated a significant overlap in FC patterns between CAIDE and cardiovascular risk factors in midlife, distinct from patterns associated with non‐modifiable risk. This suggested different neurobiological pathways influencing dementia risk in midlife, emphasizing the importance of personalized dementia prevention strategies. The findings highlighted the positive impact of an active and engaged lifestyle on brain health, reinforcing the need for early intervention targeting cardiovascular health for dementia risk reduction.
Genetic predisposition to clinical AD and AD pathology is differentially associated with baseline and 3‐year period change for specific AD‐related markers
Authors: Genius Patricia , Rodríguez‐Fernández Blanca , Shekari Mahnaz , Sánchez‐Benavides Gonzalo , López‐Martos David , Minguillon Carolina , Esteller Manel , Navarro Arcadi , Gispert Juan Domingo , Vilor‐Tejedor Natalia ,   for the ALFA study
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by early changes in brain structure and cognitive function before the age of onset. This study investigated whether the genetic load for clinical AD and AD pathology predicts AD‐related brain and cognitive changes over a 3‐year period, targeting the preclinical phase in cognitively unimpaired (CU) middle‐aged individuals.MethodThe sample of the study was defined by 429 CU middle‐aged participants at risk of AD from the ALFA+ nested cohort with available information on genetics, brain imaging markers and cognitive data [Table 1]. A subset of them had information at two‐time points (N=367) [Figure 1]. Genetic predisposition for clinical AD (PRSAD and PRSADnoAPOE) and AD pathology (PRSAβ42‐CSF and PRSpTau‐CSF) were calculated. We used linear regression models to assess the association between each PRS and global amyloid PET deposition expressed in Centiloids, AD Dickerson MRI‐signature, hippocampal volume and cognitive outcomes, at baseline and rate of change over visits after controlling for confounders. PET and MRI outcomes were defined as the annual rate of change. Cognitive outcomes were z‐scores of the two‐time points difference. Models were adjusted for time between visits.ResultAt baseline, higher genetic predisposition to clinical AD was associated with increased amyloid‐PET levels and higher average thickness of AD‐affected regions. Additionally, higher PRSAD was associated with reduced AD‐related cognitive performance and worse language [Figure 2]. Over the three‐year period, AD‐genetic load predicted higher annual amyloid accumulation in the brain, independently of APOE. Conversely, genetic predisposition to higher CSF Aβ42 levels predicted lower annual rate of change for Centiloids. PRSAD was also associated with annual reduction of hippocampal volume. Finally, genetic predisposition to AD beyond the APOE region was associated with executive functioning rate of change [Figure 2].ConclusionThe results of this study showed the role of genetic predisposition to AD, affecting amyloid PET deposition, brain structure changes, and cognitive decline. These findings emphasized the importance of considering a comprehensive range of genetic markers in risk assessments for AD, particularly in its early stages, and highlight the potential of personalized genetic approaches to enhance predictions and interventions in the management of AD.
Greater subjective cognitive decline is associated with higher plasma Alzheimer’s disease biomarkers in cognitively normal Hispanics living in Miami, FL
Authors: Barker Warren W , Pinero Yaimara Gonzalez , Velasquez Karen , Gonzalez Joanna , Velez‐Uribe Idaly , Herrera Mileidys , Duara Ranjan , Salmon David P. , Galasko Douglas R. , Marquine Maria J. , Zlatar Zvinka 
Published: January 2025

AbstractBackgroundSubjective cognitive decline (SCD), or a person’s perception of changes in their cognitive abilities, has been identified as a possible early marker of preclinical Alzheimer’s disease (AD) in non‐Hispanic Whites; however, research is lacking about the clinical utility of SCD in diverse populations. This study investigated the associations of self and informant reports of SCD, plasma biomarker profiles of AD, and objective cognitive performance in Hispanic older adults living in Miami.MethodHispanic participants enrolled in the 1Florida Alzheimer’s Disease Research Center who completed neuropsychological testing and blood draws for biomarker analysis were eligible. Plasma biomarkers included phosphorylated tau (p‐tau217 and p‐tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The Subjective Cognitive Decline Questionnaire self (MyCog) and informant (TheirCog) versions were used to assess SCD. Cognitive tests included the Montreal Cognitive Assessment (MoCA) and the Craft story 21 verbatim immediate (Craft‐Im) and delayed recall (Craft‐Del). Relationships between plasma biomarkers, cognitive performance, and SCD were explored using Spearman's rank correlation, with an uncorrected p‐value of 0.05.ResultThe cohort included 52 Hispanics (age 73.3±7.3 years; education 15.2±3.0 years; 63% female; 96% from Cuba or South America) with a consensus diagnosis of cognitively normal (CN, n=17) or mild cognitive impairment (MCI, n=35). Among CN participants (Tables 1 and 2), greater MyCog scores were significantly associated with higher p‐tau217 (rs=0.68), p‐tau181 (rs=0.58) and lower MoCA scores (rs=‐0.48). Greater TheirCog scores were significantly associated with higher p‐tau181 (rs=0.58) and lower MoCA scores (rs=‐0.52). Among MCI participants (Tables 1 and 2), greater MyCog scores were associated with lower p‐tau181 (rs=‐0.37). There were significant correlations between various cognitive test scores and p‐tau217 (MoCA, rs=‐0.50; CraftIm, rs=‐0.44) and NfL (CraftIm, rs=‐0.34; CraftDel, rs=‐0.33).ConclusionGreater self and informant reported SCD are related to higher AD plasma biomarker load and worse cognition in a small sample of CN Hispanics, suggesting potential clinical utility. Self‐reported SCD was inversely related to plasma biomarkers in those with MCI, suggesting loss of insight. Larger and more diverse longitudinal studies are needed to elucidate if CN Hispanics with elevated SCD and AD plasma biomarkers progress to MCI and AD.
Untargeted plasma proteomics nominates a novel set of plasma biomarkers for Alzheimer’s disease in African Americans
Authors: Kuchenbecker Lindsey A , Reddy Joseph S. , Heckman Michael G. , Lucas John A. , Ertekin‐Taner Nilüfer , Graff‐Radford Neill R , Carrasquillo Minerva M. 
Published: January 2025

AbstractBackgroundPlasma biomarker development is of increasing interest due to improved accessibility compared to established diagnostic modalities for Alzheimer’s disease (AD). However, current plasma biomarker candidates have not been tested comprehensively in diverse populations, and these markers represent only a fraction of pathways perturbed in AD. Therefore, there is a need to identify novel plasma biomarkers that account for both disease heterogeneity and patient diversity. This study seeks to address these knowledge gaps through untargeted plasma biomarker discovery in African Americans (AA), an underrepresented group in AD research despite having a higher risk of developing AD compared to non‐Hispanic Whites.MethodsUntargeted proteomics were performed using the SomaScan 7k assay on plasma samples from AA study participants clinically diagnosed as AD (n=142) or cognitively unimpaired (CU, n=144). Linear regression models adjusted for age, sex, and batch were implemented to identify differentially expressed proteins (DEPs). APOE was additionally adjusted for in a sensitivity analysis. DEPs with the lowest q‐values were selected as predictors in a receiver operating characteristic (ROC) analysis to assess their accuracy to discriminate AD versus CU individuals.ResultsA total of 153 DEPs were identified (q<0.05) when adjusting for age, sex, and batch, and 100 DEPs were identified when additionally adjusting for APOE. Of the 66 proteins overlapping between these models, SERPINA3, C7, IGFBP‐2, DKK3, SMOC1, and ACES had the lowest q‐values and were included in a ROC model adjusted for age, sex, and APOE. That model classified AD versus CU with an area under the curve (AUC) of 0.87 (95%CI: 0.83‐0.91), a 10.4% improvement over the base model including age, sex, and APOE (AUC=0.78; 95%CI: 0.72‐0.83). Despite the unbiased selection of proteins included in the ROC model, all selected proteins have been associated with AD and implicated in related functional pathways such as neuroinflammation, synaptic function, and insulin signaling.ConclusionThis preliminary plasma biomarker panel demonstrates the potential diagnostic capabilities of biomarker discovery through untargeted proteomics. Future directions include validation of findings in external datasets, concomitant assessment of p‐tau217, and evaluation of machine learning models to define the optimal diagnostic and predictive set of plasma protein biomarkers for AD in AA.
The ADIS study: Early Diagnosis of Alzheimer's Disease by Immune Profiling of Cytotoxic Lymphocytes and Recording of Sleep Disturbances
Authors: Val‐Guardiola Andrea , Martínez Neus Falgàs , Krix Sophia , Lage‐Rupprecht Vanessa , Nevo Uri , Kirsch Stefan , Yoles Eti , Tort‐Merino Adrià , Balasa Mircea , Antonell Anna , Lladó Albert , Baruch Kuti , Moradi Soraya , Bintener Christophe , István Nagy , Fröhlich Holger , Sanchez‐Valle Raquel 
Published: January 2025

AbstractBackgroundSleep‐wake alterations are common symptoms in Alzheimer’s Disease (AD) associated with faster cognitive decline. Noradrenaline dysfunction and neuroinflammation have been proposed as potential driving mechanisms. The ADIS project aims to study the relationship between sleep‐wake patterns, immune signatures (peripheral blood cytotoxic lymphocytes), and noradrenergic markers across the AD spectrum.MethodThe project aims to recruit a total of 75 participants from the Hospital Clínic de Barcelona, including healthy controls (with normal values of plasma pTau), mild cognitive impairment due to AD (MCI), and AD Dementia (AD) confirmed by CSF biomarkers (Figure 1). All subjects will complete a comprehensive neuropsychological battery and Altoida digital assessment. Sleep‐wake phenotypes will be assessed by sleep questionnaires (Pittsburg Sleep Quality Questionnaire, PSQI, and Epworth Sleepiness Scale, ESS) and 2‐week actigraphy (Motion Wath 8 device). Noradrenaline levels and neuroinflammation markers in CSF will be measured. Immune phenotyping (cytometry, immune activation assays, scRNA/TCR sequencing) of peripheral blood mononuclear cells (PBMC) will be performed. In addition, selected participants will participate on the study's Advisory Board.ResultTo date, we have recruited 25 healthy controls, 25 MCI, and 23 AD participants who performed a total of 67 neuropsychological testings, 47 Altoida assessments, 34 CSF noradrenaline measurements, 65 actigraphy monitoring, and 59 isolation of PBMC. There were no age or gender differences between groups (Table 1). As expected, MMSE was lower in MCI/AD than controls (p<0.01). PSQI and ESS showed no differences, but preliminary analyses of 28 (10 HC, 14 MCI, 4 AD) actigraphy recordings showed that MCI and AD had a greater sleep latency than controls (p<0.05). As expected, preliminary analyses of 34 participants, including 21 MCI and 13 AD, showed similar noradrenaline levels. Further analyses will be performed, including the correlation between immune/noradrenaline markers and clinical data in an increased sample size.ConclusionSleep questionnaires might have a poor performance in identifying sleep alterations in MCI/AD individuals. Digitally assessed sleep‐wake patterns might help to detect sleep alterations. A deeper understanding of the role of biological mechanisms, such as immunologic profiles or noradrenergic dysfunction, driving sleep alteration is warranted.
Spousal care partners have increased levels of anxiety, depression and blood short chain fatty acids
Authors: Zuo Zhiyi , Arbab Zunaira , Shan Weiran , Jain Avani , Gallagher Virginia , Reilly Shannon , D’Abreu Anelyssa , Manning Carol A 
Published: January 2025

AbstractBackgroundSpousal care partners to people with dementia (PWD) have a higher rate of depression and anxiety when compared to similar age controls. Previous studies have suggested a role of gut microbiota in the pathophysiology of neuropsychiatric symptoms and Alzheimer’s disease (AD). Thus, our study aims to: (1) determine the presence and severity of depression and anxiety in care partners of PWD, and (2) determine the concentrations of short chain fatty acids (SCFA), which are mainly produced by gut microbiota and are important in mediating gut microbiota effects, in the blood of care partners of PWD.MethodsThree groups of participants were recruited for this cross‐sectional study: healthy controls, patients with AD and their spousal care partners. We used the Beck Depression Inventory (BDI‐II) to assess the presence and severity of depression, the State‐Trait Anxiety Inventory to evaluate care partner distress, and repeatable battery for the assessment of neuropsychological status (RBANS) for cognitive assessment. Their blood and feces were harvested.ResultsWe recruited 53 participants: 15, 21 and 17 participants in the control, care partner and AD groups, respectively. Patients with AD had lower mean (SD) total RBANS scores [69 (16)] than controls [110 (11)] (P < 0.001) and care partners [111 (13)] (P < 0.001). Patients with AD and their care partners had higher state and trait anxiety scores than controls (Fig. 1). Care partners had the highest BDI scores (Fig. 2). Care partners had higher concentrations of acetic acid, propionic acid and butyric acid in the blood than those in the control group (Fig. 3).ConclusionsSpousal care partners had evidence of increased levels of depression, anxiety, and concentrations of SCFAs relative to controls. Our results suggest that care partners to PWDs have gut microbiota different from that of controls, which may be related to their elevated anxiety and depression.
Polygenic risk for schizophrenia predicts dopamine‐related grey matter volume alterations in people with Alzheimer’s disease and psychotic symptoms
Authors: Manca Riccardo , Venneri Annalena 
Published: January 2025

AbstractBackgroundPsychotic symptoms may manifest in Alzheimer’s disease (AD), especially in advanced disease stages and in patients with higher polygenic risk scores for schizophrenia (SCZ‐PRS). Such genetic risk seems also to influence grey matter volume (GMV) alterations in patients with psychosis. Since multiple neurotransmitter systems, namely dopamine (DA) and serotonin (5‐HT), have been implicated in psychosis, the aim of this study was to investigate whether a SCZ‐PRS may explain variance in the association between GMV and the cerebral distribution of DA and 5‐HT.MethodEight‐hundred ADNI participants with genetic data were selected for this study: 203 cognitively unimpaired (CU) and 597 people with AD. Patient were divided into psychotic (PT‐PS, n = 121) and non‐psychotic (PT‐NP, n = 476) based on available NPI‐Q data. A SCZ‐PRS was calculated for each participant using a Bayesian approach. T1‐weighted MRI scans were pre‐processed with SMP12 and JuSpace to extract Fisher’s z‐transformed individual correlation coefficients between GMV and PET atlases for DA and 5‐HT receptors/transporters. General linear models were used to test the association between the SCZ‐PRS and GMV‐neurotransmitter correlation coefficients (p < 0.05). Analyses were replicated in a sub‐sample of amyloid‐positive participants.ResultThe SCZ‐PRS was negatively associated with correlations coefficients between GMV and the D2 dopaminergic receptor (D2r) in the whole sample (β = ‐0.016, p = 0.023) and in the PT‐PS group (β = ‐0.037, p = 0.030). However, the latter association was significant only when analyses were restricted to amyloid‐positive participants (Figure 1). In the PT‐NP group, the SCZ‐PRS was negatively associated with correlations coefficients between GMV and two 5‐HT receptors (5‐HT1b: β = ‐0.014, p = 0.027; 5‐HT2a: β = ‐0.013, p = 0.038). No between‐group differences in SCZ‐PRSs were found.ConclusionThe SCZ‐PRS was differentially associated with GMV alterations linked to either DA, in PT‐PS, or 5‐HT, in PT‐NP, that are both neurotransmitters previously implicated in psychotic symptoms. However, the influence of SCZ‐PRS on DA‐related GMV loss appears to be primarily relevant to psychotic manifestations in AD. These findings suggest that future innovative pharmacological interventions targeting the DA system may be beneficial to treat psychosis in AD.