bluuebunny/crossref_metadata_2025_split huggingface dataset:
Markers of atrophy progression in patients with young‐onset cognitive complaints not due to Alzheimer’s Disease
Authors: Carbone Chiara , Balboni Erica , Luchetti Ludovico , Urbano Teresa , Beltrami Daniela , Maramotti Riccardo , Tondelli Manuela , Gallingani Chiara , Gasparini Federico , Vinceti Giulia , Marti Alessandro , Chiari Annalisa , Zamboni Giovanna 
Published: January 2025

AbstractBackgroundIn clinical settings, the prognosis of patients with subtle cognitive complaints and no imaging evidence of neurodegeneration is often challenging, especially in conditions unrelated to Alzheimer’s Disease (AD). We aimed to identify which baseline indicators can help in the clinical decision‐making process of patients with Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) without AD pathology, by identifying those with faster brain atrophy for their age.MethodYoung‐onset SCD and MCI patients (symptoms ≤65yo) were recruited. At baseline we administered neuropsychological assessment and anxiety/depression questionnaires to patients, while the Neuropsychiatric Inventory for behavioural symptoms to caregivers. Patients also underwent Magnetic Resonance Imaging (MRI) and serum neurofilaments light‐chain (NfLs) measurement, other than a (18F)Flutemetamol‐PET (amy‐PET) or lumbar puncture for collection of cerebrospinal fluid (CSF) NfLs, b‐amyloid1‐42, b‐amyloid1‐42/1‐40, total‐, and phosphorylated‐tau. After 18 months, MRI was repeated. Single‐subject percentage of brain volume change was calculated using the FMRIB Software Library tool SIENA and compared to the longitudinal change observed in healthy controls (Battaglini et al., 2019). Patients exceeding the 95th percentile of normative values were categorized as having non‐physiological progressive atrophy. All variables and biomarkers were added in logistic and spline regression analyses with age, sex, education, and global cognitive status (i.e., Mini‐Mental State Examination – MMSE) as covariates, performed with Stata18.ResultAmong the 75 patients recruited, 20 were excluded because of a CSF/amy‐PET suitable for AD; of the remaining 55, atrophy progressed in 18 while 37 had physiological brain volume changes. Low baseline performance in attentional‐executive (i.e., Frontal Assessment Battery) and language (i.e., phonemic, semantic, alternate fluency) tests were predictors of progressive atrophy, over and above baseline MMSE and demographical variables. Furthermore, caregiver‐reported apathy, along with elevated levels of serum NfLs, were indicative of a greater‐than‐expected change in brain volume after 18 months.ConclusionIn the assessment of young‐onset SCD and MCI patients, poor performance on attentional‐executive and language tests and high levels of serum NfLs, combined with apathy, should be considered markers for faster progression of brain atrophy in the short‐term future (18‐months), over and above the global cognitive status. Patients with these features should be monitored closely.
Early phase Amyloid‐PET reproduces metabolic signatures of cognitive decline in Parkinson's disease
Authors: Heron Campbell Le , Aye William , Stark Megan , Horne Kyla‐Louise , Myall Daniel J , Pitcher Toni , Almuqbel Mustafa , Keenan Ross , Dalrymple‐Alford John C , Anderson Tim J , Melzer Tracy R 
Published: January 2025

AbstractBackgroundEstablishing practical and effective diagnostic pathways for people with cognitive impairment is a crucial international research priority. Traditional (late‐phase) analysis of an amyloid‐beta (Aβ) PET scan (∼90 minutes after radiotracer injection) provides important information about the presence/absence of underlying Alzheimer’s pathology, but no information about brain metabolism/perfusion. Recent work suggests that amyloid‐beta PET tracer uptake shortly after injection (‘early‐phase’) closely reflects brain metabolism and perfusion. Parkinson’s disease (PD), the second most common neurodegenerative disease worldwide, serves as a model disorder in which cognitive impairment occurs across a spectrum, is not specifically associated with underlying brain amyloid status, and has known patterns of altered metabolism and perfusion associated with cognitive decline. We investigated the utility of early‐phase 18F‐Florbetaben Aβ PET (eFBB) uptake as a surrogate marker of cerebral perfusion/metabolism in people with PD. We hypothesised that eFBB uptake would reproduce characteristic patterns of hypometabolism and hypoperfusion associated with cognitive decline in PD, irrespective of late‐phase Aβ status, and positively correlate with a direct measure of cerebral perfusion – ASL MRI.Method115 closely phenotyped PD patients across the spectrum of cognitive impairment underwent dual‐phase (early and late) Aβ PET, structural and perfusion (ASL) MRI, and neuropsychological assessments. Multiple linear regression models compared eFBB uptake with 1) cognitive performance and 2) ASL‐MRI perfusion, correcting for multiple comparisons by family‐wise error correction (threshold‐free cluster enhancement).ResulteFBB uptake significantly correlated with cerebral perfusion across widespread cortical and subcortical regions (r = 0.15‐0.49, p < 0.005, Figure 2). Reduced eFBB uptake was significantly associated with poorer cognitive performance in brain regions previously linked to hypometabolism‐associated cognitive decline in PD: parieto‐occipital regions, middle and inferior temporal gyri, prefrontal cortex and the thalamus (all p < 0.05, Figure 1). These findings were independent of amyloid status.ConclusioneFBB uptake is a reliable surrogate measure for cerebral perfusion/metabolism in a predominantly Aβ negative group. It provides complimentary information to the late‐phase Aβ scan, and can add value whether the late phase is positive or negative. Such dual‐phase PET imaging approaches show significant promise in streamlining diagnostic pathways for people with cognitive impairment.
Isolated Amyloid‐β biomarker positivity: Alzheimer's disease in a mixed pathologies context?
Authors: Ioannou Konstantinos , Abdullaieva Khadidzha , Bluma Marina , Religa Dorota , Rodriguez‐Vieitez Elena , Chiotis Konstantinos ,   Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundThe in vivo amyloid‐β (A) and tau (T) biomarkers have been validated against the respective neuropathological burden of amyloid‐β plaques and neurofibrillary tangles. We aimed to assess the impact of mixed pathologies on the interpretation of AT biomarker system.MethodA subset of 71 ADNI participants with available neuropathological data and ante‐mortem cerebrospinal fluid (CSF) sampling was analyzed. The median delay between CSF sampling and death was 3.12 years (interquartile range 1.44‐5.11). AT status was determined based on CSF positivity for Aβ42 (A+; ≤981 pg/mL) and p‐tau181 (T+; >24.3 pg/mL). Linear mixed‐effects models were employed to assess the interaction of AT status with longitudinal cognitive scores. A medically trained investigator evaluated the medical history and medication use records. The neuropathological burden was assessed by the ADNI Neuropathology Core according to standard procedures. Chi‐squared statistics (α=0.05) were used to compare the frequency of clinical and neuropathological diagnoses across AT profile groups.ResultFour AT profile groups were identified: n=37 A+T+, 14 A+T‐, 10 A‐T+, and 10 A‐T‐. Both A+ groups exhibited significantly lower cognitive scores and declined significantly faster in episodic memory and executive domains over time than A‐ groups. The frequencies of psychiatric/neurological diagnoses and cerebrovascular disease risk factors were similar across groups. A+T+ and A+T‐ individuals were significantly more likely to be prescribed Alzheimer’s disease medications than A‐ individuals. The frequency of Alzheimer’s disease neuropathological change (ADNC) declined in a stepwise fashion across AT groups (A+T+ 100%; A+T‐ 71%; A‐T+ 40%; A‐T‐ 30%), and significant differences were detected between A+ and A‐ groups and within the A+ subgroups. In case of ADNC evidence, A+T‐ compared to A+T+ individuals exhibited significantly higher frequency of mixed pathologies (70% vs. 28%). Neocortical Lewy body pathology, extensive substantia nigra neurodegeneration, and argyrophilic grain disease were significantly more frequent in the A+T‐ than A+T+ individuals.ConclusionDespite indistinguishable clinical phenotypes, A+T‐ and A+T+ groups showed distinct differences at autopsy, with higher mixed pathology burden in the A+T‐ group. Cognitive decline in A+T‐ individuals may be associated with the additional impact of mixed pathologies rather than being exclusively linked to AD neuropathology.
Diffusion Kurtosis Imaging provide complementary information over structural MRI in the assessment of hippocampal subfields in patients with cognitive decline
Authors: Pavan Tommaso , Pievani Michela , Ribaldi Federica , Jovicich Jorge , Garibotto Valentina , Frisoni Giovanni B. , Jelescu Ileana O 
Published: January 2025

AbstractBackgroundHippocampal atrophy is an established biomarker of neurodegeneration in Alzheimer's disease, affecting specific subfields (De Flores, La Joie and Chételat, 2015). In this study, we used 7T MRI and advanced diffusion MRI (dMRI) to investigate the relationship between hippocampal subfield volumes and microstructure and assess their sensitivity to cognitive impairment.MethodSeventeen cognitively impaired (CI; age: 69±8, M/F: 12/5, MMSE: 28) and 22 cognitively unimpaired subjects (CU; age: 62±10, M/F: 6/16) were recruited in the context of the COSCODE project (Ribaldi et al., 2021). MRI was performed at 7 Tesla, including a high resolution T2w FSE sequence for hippocampal segmentation and multi‐shell diffusion MRI sequence for kurtosis tensor imaging (DKI, Jensen and Helpern, 2010) fitting. Hippocampal subfields were segmented using Automated Segmentation of Hippocampal Subfields (ASHS) package. Microstructure analysis included DTI and DKI (Figure 1). Mean values for each diffusion metric were calculated in subfields of the ASHS atlas (Xie et al. 2016). Subfield volumes were normalised by the total intracranial volume while dMRI metrics were residualized by age via a linear regression trained only on CU and then correlated to the volumetric data across within each group (statistical significance: p<0.05). Lasso logistic regression was used to identify the metrics that better discriminated CI from CU.ResultFew hippocampal subfields’ volumes correlated with dMRI metrics (Figure 2). In the CU group, DG volume showed negative associations with diffusion metrics, primarily RD (r:‐0.59, p=0.007), MD(r:‐0.56, p=0.012), MK(r:‐0.46, p=0.043) and AK(r:‐0.62, p=0.005). In the CI group, negative correlations between BA35 (r:‐0.70, p=0.008) and CA3 (r:‐0.57, p=0.041) volumes were found with AK. When discriminating CI from CU, the logistic regression found the ERC volume as the most important metric, followed by the MK of the DG, and AK of CA2 (Figure 3).ConclusionThe disconnection between dMRI metrics and volumetric measures and the selection of DKI metrics in discriminating CI from CU participants suggest that DKI metrics may act as complementary biomarkers to subfield volumes for early detection of cognitive impairment.
ATNPD to improve detection of concomitant Alzheimer’s pathology in autopsy‐confirmed Parkinson’s disease
Authors: Cousins Katheryn A Q , Bayram Ece , Galasko Douglas R. , Hwang Kristy S , Shaw Leslie M. , Irwin David J , Coughlin David G 
Published: January 2025

AbstractBackgroundIn Parkinson’s disease (PD), concomitant Alzheimer’s disease (AD) pathologic change (ADNC) is common and results in altered motor and cognitive phenotypes. However, detection of PD with AD (PD+AD) using biofluid markers is challenging. While decreased cerebrospinal fluid (CSF) β‐amyloid 1‐42 (Aβ42) strongly reflects β‐amyloid burden, PD subjects typically harbor lower CSF phosphorylated tau 181 (p‐tau181) and total tau (t‐tau) levels than healthy controls, which complicates detection of tau tangles and neurodegeneration. We previously tested PD‐specific application of the β‐amyloid/tau/neurodegeneration framework (ATNPD); combining CSF Aβ42, CSF p‐tau181, and serum neurofilament light (NfL) in a living PD cohort. ATNPD, using a lower CSF p‐tau181 cutpoint, predicted cognitive decline. However, ATNPD cutpoints still must be validated against autopsy assessments of ADNC as gold‐standard. Here, we compare biomarker strategies in all available autopsy‐confirmed PD from the Parkinson’s Progression Markers Initiative (PPMI).MethodsEighteen PD participants with autopsy‐confirmed Lewy body disease and antemortem biofluid were available for analysis (Table 1). PD+AD included high/intermediate ADNC (n=9); PD without AD (PD; n=9) included not/low ADNC. Cerebral cortical atrophy determined neurodegeneration (mild/moderate vs. none). CSF was assayed for Aβ42 (n=14), p‐tau181 (n=17), and t‐tau (n=17) using Roche cobas e 601; p‐tau181/Aβ42 and t‐tau181/Aβ42 ratios were calculated. Serum NfL was assayed using Simoa Quanterix (n=18). Biofluid measurements closest to autopsy were selected. Receiver operating characteristic (ROC) analyses with bootstrapping tested discrimination of PD+AD from PD using CSF biomarkers, and of neurodegeneration from not using CSF t‐tau and serum NfL.ResultsROC cutpoints for CSF Aβ42, p‐tau181, and serum NfL were equivalent to ATNPD cutpoints, while p‐tau181 and t‐tau were lower than published AD‐cutpoints (Table 2). CSF p‐tau181/Aβ42, t‐tau181/Aβ42, Aβ42 and serum NfL had high area under the curve (AUC>0.80; Table 2A,2B). In contrast, CSF p‐tau181 and t‐tau demonstrated poor discrimination (Table 2A) and no difference between groups (Table 1), potentially due in part to low sample size. A chi‐square test confirmed classification is improved using ATNPD and AD‐cutpoints (χ2=14, p=0.0015; Figure 1).ConclusionsPD‐specific biomarker strategies/cutpoints are needed to maximize detection of concomitant ADNC, but must be validated in larger autopsy cohorts.
Unlocking the benefits of higher educational attainment on cognitive performance in Alzheimer’s disease
Authors: Cai Yue , Fang Lili , Li Anqi , Zhou Xin , Yang Jie , Guo Tengfei ,   Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

AbstractBackgroundPrevious cross‐sectional studies suggest that higher educational attainment (EA) may mitigate cognitive decline in Alzheimer’s disease (AD). This study systematically investigated the association between EA and longitudinal cognitive decline across various domains and explored its connections with β‐amyloid (Aβ) plaque, tau tangle, gray matter volume (GMV) and glucose metabolism in AD.MethodWe analyzed Aβ‐PET (A), tau‐PET (T), and 3D T1‐MRI images (N) from the ADNI cohort to identify 58 A+/T‐, 77 A+/T+, and 84 cognitively unimpaired (CU) participants without evidence of AD pathology and neurodegeneration (A‐/T‐/N‐/CU). All participants had longitudinal cognitive assessments covering the Preclinical Alzheimer Cognitive Composite (PACC), memory, executive function, language and visuospatial function. Additionally, a subset of 67 individuals had FDG‐PET images. Participants were divided into High‐Edu and Low‐Edu subgroups based on the median years of education of the whole cohort (16 years). Baseline and follow‐up cognitive measurements in various domains were compared between High‐Edu and Low‐Edu individuals. Furthermore, the association of EA, GMV, FDG, Aβ plaque, tau tangle, and cognitive changes were investigated.ResultSlower cognitive decline was specifically observed in PACC and language domains of the A+/T+ group among High‐Edu individuals compared to Low‐Edu individuals (Figure 1). The mediation analysis demonstrated that higher EA attenuated PACC decline through greater GMV in the middle temporal gyrus (MTG) and higher glucose metabolism in the left parahippocampal gyrus. Additionally, it mitigated language decline through greater GMV and glucose metabolism in the left inferior temporal gyrus. Furthermore, slower PACC and language decline in High‐Edu individuals was fully mediated through lower tau tangles in the MTG and left superior temporal gyrus (STG), rather than through an Aβ‐associated pathway (Figure 2). A four‐variable mediation analysis further confirmed that tau tangles and GMV in the MTG independently mediated the association between EA and PACC decline (Figure 3).ConclusionThese findings suggest that higher EA has a prominent protective effect in mitigating PACC and language decline among A+/T+ individuals. The protective effects of higher EA are mediated through the maintenance of greater GMV (or FDG) and lower tau tangles, and these pathways independently contribute to the attenuation of PACC and language decline.
A Model for Implementing Psychotherapy for Individuals with Cognitive Impairments
Authors: Johnson Adrienne L , Wyman Mary F. , Chin Nathaniel A. 
Published: January 2025

AbstractIndividuals with Mild Cognitive Impairment (MCI) and dementia are at greater risk for mental health conditions including depression and anxiety than those without cognitive impairments.1,2 Non‐pharmacological interventions are considered first‐line to address these problems, but access to psychotherapy services for these groups remains limited. Adapted evidence‐based therapy approaches, including Cognitive Behavioral Therapy (CBT)3‐5 and Acceptance and Commitment Therapy (ACT)6 are effective for treating comorbid mental health conditions in populations with cognitive impairments. We report on the implementation of psychotherapy services for patients with MCI and Mild Dementia within the Memory Assessment Clinic of a large academic healthcare system in Midwest U.S. Pre‐implementation process included identifying a clinic champion to support adoption and observing current clinic flow by the practitioner (a licensed Clinical Health Psychologist with expertise treating patients with neurological issues) to determine logistics. Referrals were initially solely provided by the clinic champion, then opened to the entire clinic with pre‐determined eligibility guidelines: recent MCI or Mild Dementia diagnosis, comorbid anxiety or depressive symptoms, and lack of rapid forgetting in during medical examination. Therapy patients were seen on a short‐term basis (6‐8, 45‐minute sessions) to maximize access for as many patients as possible, using CBT or ACT‐based therapy modalities. Therapy content was tailored and person‐centered but included (in chronological order): evaluation of cognitive capacities to leverage during therapy, identification of treatment goals, identification of problematic cognitions/behaviors, introduction of new treatment content/coping skills (one topic/session), assign homework assignments using learned skills, evaluation of homework effectiveness and roadblocks. The initial session was in‐person to facilitate comprehensive evaluation and build rapport, and family caregivers were included as indicated. Follow‐up sessions were provided in‐person or via telehealth. Barriers to implementation included incorrect use of referral process, lack of provider knowledge of new services, and limited provider availability. Facilitators included developing a wait list for referred patients and regular education to providers with written details of the service (e.g., referral process and eligibility; waitlist duration). Similar strategies have been used in other health systems and suggest the feasibility of incorporating psychological treatment for cognitively impaired patients as part of a multi‐component treatment model.
Contrasting the Association of episodic memory using traditional neuropsychological test and acoustic features with PET imaging markers
Authors: Sunderaraman Preeti , Lyu Chenglin , Young Christina B. , Karjadi Cody , Mormino Elizabeth , Sidelinger Lauren , Devine Sherral A. , Kolachalama Vijaya B. , Lin Honghuang , Au Rhoda 
Published: January 2025

AbstractBackgroundPreclinical measures of Alzheimer’s disease (AD) risk include markers of amyloid and tau measured via PET scans and decline in verbal memory. Audio features from recorded speech collected during neuropsychological testing offer an alternative for monitoring preclinical AD symptoms that is nonintrusive, economical, and scalable but warrants further validation. This study aims to examine whether there is a stronger association between acoustic metrics and PET imaging biomarkers compared to a traditional verbal memory test.MethodsThis study involved 196 Framingham Heart Study dementia‐free participants with available acoustic, as well as PET amyloid and tau imaging data (refer to Table 1 for demographics). For each participant, 65 acoustic features were extracted from speech samples recorded during the Wechsler's Memory Scale Logical Memory immediate (LMI) and delayed (LMD) recall tests, utilizing OpenSMILE for feature extraction. Multiple regression analyses were performed with a global composite score for PET amyloid, or PET tau for five regions (entorhinal, amygdala, parahippocampal, inferiortemporal, putamen) that were examined individually as outcomes. LMI, LMD, acoustic features derived from LMI and from LMD recorded voice segments were related to AD PET biomarkers in each regression model. Age, sex, education level, and APOE status were used as covariates for all analysis. Models using tau as outcome were adjusted for global amyloid.ResultsAfter adjusting for multiple comparisons using FDR (significance set at 0.5), among the 65 acoustic features, the Mel‐frequency cepstral coefficient (p=0.01) and audio spectral features of the acoustic features derived from LMD (p=0.02) were most strongly associated with inferiotemporal tau region (see Table 2). No traditional measure of LMI or LMD was significantly related to any AD PET biomarker.ConclusionsIn a group that was clinically asymptomatic for dementia/AD, only digital measures were associated with AD tau biomarker. These findings suggest that digital voice features have increased sensitivity to detect those at AD risk compared to traditional cognitive tests and have potential to serve as a biomarker of AD. Future studies in diverse populations are needed to test the robustness of these findings.