bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alpha Synuclein co‐pathology is associated with faster Ab‐related tau accumulation in Alzheimer’s disease
Authors: Roemer Sebastian Niclas , Dehsarvi Amir , Steward Anna , Dewenter Anna , Pescoller Julia , Wagner Fabian , Levin Johannes , Brendel Matthias , Höglinger Günter , Franzmeier Nicolai 
Published: January 2025

AbstractBackgroundLewy body pathology consisting of aggregated alpha‐Synuclein (a‐Syn) is the hallmark pathology in Parkinson’s disease, yet a‐Syn aggregates are also commonly observed post‐mortem as a co‐pathology in Alzheimer’s disease (AD) patients. Preclinical research has shown that a‐Syn can amplify Ab‐associated tau seeding and aggregation, hence a‐Syn co‐pathology may contribute to the Ab‐induced progression of tau pathology in AD. To address this, we combined a novel CSF‐based RT‐QuIC seed‐amplification assay to determine a‐Syn positivity, with PET‐neuroimaging in a large patient cohort ranging from cognitively normal to dementia, to determine whether a‐Syn co‐pathology accelerates Ab‐driven tau accumulation.MethodIn 261 Ab‐positive vs. 272 Ab‐negative subjects ranging from cognitively normal to dementia we employed amyloid‐PET, Flortaucipir tau‐PET and a CSF‐based a‐Syn RT‐QuIC assay for in vivo detection of abnormal a‐Syn aggregation. A subset of 136 Ab‐positive vs. 102 Ab‐negative subjects had longitudinal tau‐PET across ∼2.5years. Using linear regression, we tested whether a‐Syn positivity was linked to stronger Ab‐related tau aggregation (i.e. interaction a‐Syn x amyloid‐PET on tau‐PET).ResultPrevalence of a‐Syn positivity rose across increasing clinical severity and was particularly pronounced in Ab+ (i.e. CN/MCI/Dementia=20/23/47%) vs. Ab‐ subjects (i.e. CN/MCI/Dementia=15/10/29%), suggesting that a‐Syn co‐pathology is more common in clinically advanced AD (chi‐squared‐test, p<0.001). When testing the interaction between a‐Syn and global amyloid‐PET, we found that a‐Syn positivity was associated with stronger Ab‐related tau deposition (Figure 1A, p<0.001), and faster Ab‐related tau accumulation rates (Figure 1B, p=0.010) in typical tau vulnerable brain regions (i.e. temporal meta ROI), adjusting for age and sex. Regional analyses confirmed that higher regional amyloid‐PET was associated with stronger temporal‐lobe tau deposition (Figure 2A) and faster tau accumulation in downstream regions (Figure 2B) in a‐Syn positive individuals. In addition, there was an independent effect of a‐Syn positivity on faster temporal lobe tau accumulation rates controlling for age, sex and global amyloid, suggesting that a‐Syn may also independently contribute to tau aggregation (Figure 3).Conclusiona‐Syn co‐pathology as detected by CSF seed‐amplification assays is more common at clinically advanced AD and related to faster Ab‐related tau aggregation. This suggests that a‐Syn co‐pathology may actively contribute to AD‐related tau accumulation and therefore contribute to dementia development.
Cerebellar white matter in musicians: Less is more?
Authors: Ghosh Aishwarya , Malo Palash K , Singh Sadhana , Issac Thomas Gregor 
Published: January 2025

AbstractBackgroundMusical activity is known to act as a cognitive reserve and protect the brain against age‐related cognitive decline. The neural correlates of music perception and processing has been linked to the cerebellum, which is also known to be implicated in musical‐training related plasticity. These insights led us to explore the differences in cerebellar volumes between musicians and non‐musicians.MethodWe selected 29 cognitively healthy older adults, from the Tata Longitudinal Study of Aging (TLSA) cohort, who were identified and divided into two groups: musicians (vocalists), who were formally trained for more than five years (n=13) and non‐musicians, who had no or less than five years of training (n=16). Brain imaging was performed using a 3 Tesla MRI system and cerebellar volumes were obtained by voxel‐based morphometry. The volumetric differences between male and female musicians were analysed using Mann‐Whitney U test. Generalized Linear Regression Model (GLM) was used to compare musicians to non‐musicians.ResultThere was no significant difference between musicians and non‐musicians with respect to age (58.97±9, 57.83±5.31) and years of education (16.08±1.89, 16.06±4.20). Mann‐Whitney U test revealed a significant difference in the right cerebellar cortex (p=0.011), left cerebellar cortex (p=0.030) and left cerebellar White Matter (WM) (p=0.030) between male and female musicians with males having greater volume in each case. After adjusting for the Total Intracranial Volumes, GLM revealed musicians to have significantly less WM volumes in both left [β= ─777.86 (C.I. 95%); p=0.039] as well as right [β= ─1105.45 (C.I. 95%); p=0.011) cerebellum. Further, increase in years of involvement with music was positively correlated with right WM volume (0.197) and negative correlated with volumes of the right cerebellar cortex (─0.228), left cerebellar cortex (─0.257) and left cerebellar WM (─0.057), although not statistically significant.ConclusionIt is surprising to note lower cerebellar volumes in musicians. The concept of meta‐plasticity might be used to explain the current findings which are in line with previous studies where musicians with extensive training since an early age were found to have smaller cerebellar volumes.
Understanding Cognition of Indian Superagers Through Handgrip Strength Examination
Authors: Roy Dwaiti , S Monisha , Issac Thomas Gregor 
Published: January 2025

AbstractBackgroundPhysiological and mental functions decline as the person ages. However, studies have found that a group of people who are more than 80 years have better cognitive functioning than their peers and also similar to 2‐3 decades younger counterpart group. These people are termed as “Superagers”. Earlier research has revealed that handgrip strength can predict frailty and eventually decline in cognition in healthy individuals. It is important to determine the patterns of functioning and risk factors of these superagers to ensure a greater quality of life for them in the future. Therefore, this study aims to look for the patterns of handgrip strength among the superagers in comparison to the typical agers.MethodThe analysis was done using baseline data from Tata Longitudinal Study of Aging (CBR‐TLSA) cohort. From this cohort, 65 octogenarians were identified. The cognition was assessed through Addenbrooke’s Cognitive Examination (ACE III) and Trail Making Test‐B(TMT‐B) The superagers were classified from these octogenarians based on Northwestern Criteria: having equal to or greater score in memory test than the 50‐65 gender and education matched age group and scores of tests of other cognitive domains not less than 1 SD compared to the same age group. Handgrip strength was measured by Camry EH101 hand dynamometer.ResultsAmong 65 octogenarians 14 were identified as superagers from the TLSA cohort based on the Northwestern Criteria. The educational level was higher in superager group (p=0.022). They also exhibited higher handgrip strength in both right and left hand in trial 1 (p=0.001, p=0.003 respectively) as well as in trial 2 (p=0.001, p=0.001 respectively).ConclusionThe results indicate a higher level of handgrip strength in superagers in both right and left hand. This indicates that there is less chance of frailty in superagers which in turn points to a lower risk of developing cognitive deficit.
Global Research Integration Platform (GRIP): Open‐source Digital Voice Processing Toolkit
Authors: Karjadi Cody , Ding Huitong , Searls Edward , Peterson Julia , Gifford Katherine A. , Pratap Abhishek , Ang Ting Fang Alvin , Au Rhoda 
Published: January 2025

AbstractBackgroundProducing speech is a cognitively complex task and can be collected through devices such as handheld recorders, tablets, and smartphones. Digital voice data can also capture information at a granular millisecond‐level precision and serve as a widespread tool to collect cognitively relevant data in almost any diverse real‐world environments.Digital voice recordings of spoken responses to neuropsychological test questions have been collected through the Framingham Heart Study (FHS) since 2005. The methods to analyze voice recordings were initially labor and time‐intensive approaches that were significant barriers to fully realizing the scientific objective of using speech and language as an alternative approach to cognitive assessment.MethodsThrough a collaboration with the Global Research Integration Platform (GRIP) and FHS, we leveraged existing open–source tools to create a digital voice processing toolkit that can be used by the general scientific community. GRIP is modularizing this toolkit to allow for seamless integration into various sites worldwide with low‐to‐high levels of technical experience.Table 1 lists the initial open‐source tools we tested on 9,253 audio recordings collected on 5,399 FHS participants. Each open‐source tool has a Python Github repository that we leveraged.ResultsWith minimal manual intervention, we generated prosodic, spectral, cepstral, and sound quality features from the ComParE‐2016 feature set via openSMILE. We produced 65 LLDs (low‐level descriptors) every 10 milliseconds over a 60‐millisecond window and 6373 features generated by applying several statistical functionals to the LLDs.We segmented speakers via pyannote.audio and analyzed 9 acoustic and linguistic PRAAT features and 6373 openSMILE features in the context of a cognitive status classification task. Via Whisper, we generated timestamped transcriptions from both FHS and additional U.S. and international cohorts. We have noted difficulties in language detection and decreased transcription performance for non‐English speakers and English speakers with accents.We have used these data in numerous studies relating digital voice to AD related outcomes.ConclusionDigital voice is a prime candidate for scalable collection of cognitively relevant information. The modularized toolkit being developed will provide scaled non‐proprietary post‐processing of digital voice data that can be seamlessly integrated by users worldwide with low‐to‐high levels of technical experience.
Proteomics analysis characterizing new markers related to Aβ plaques and tau tangles pathologies
Authors: Binette Alexa Pichet , Wennström Malin , Strandberg Olof , Mathys Hansruedi , Tsai Li‐Huei , Mattsson‐Carlgren Niklas , Stomrud Erik , Janelidze Shorena , Vogel Jacob W. , Hansson Oskar 
Published: January 2025

AbstractBackgroundSeveral studies have recently emerged describing relationships between cerebrospinal fluid (CSF) proteins and beta‐amyloid (Aβ) and tau pathology. While these studies have primarily characterized Alzheimer’s disease (AD) proteinopathies using CSF markers, positron emission tomography (PET) more accurately captures these pathologies, especially fibrillar tau pathology. Our objective was to identify the main proteins strongly associated with AD pathology measured by PET, and to further investigate their cellular role using postmortem transcriptomics and immunohistochemistry.MethodWe included 604 BioFINDER‐2 participants with CSF measurements of proteins (Olink Explore3072) at baseline, and Aβ‐PET and tau‐PET at baseline and longitudinally. We fitted linear regressions between protein levels as outcome and (1) global Aβ‐PET and temporal meta‐ROI tau‐PET SUVR or (2) their rate of change as independent variables. Enrichment analyses were performed to characterize biological processes related to the set of significant proteins. Single‐nuclei sequencing datasets were used to investigate cell‐type specificity and differential gene expression of the main proteins in relation to AD pathology.ResultAnalyses were restricted to 127 differentially abundant proteins that we previously identified as related to AD (manuscript in revision). ITGAM and SMOC1 showed the strongest associations with Aβ‐PET load, with SMOC1 being the only protein showing an association in Aβ‐positive participants only (Figure 1a). SMOC1 was mainly expressed in oligodendrocyte precursor cells (OPCs), and ITGAM in microglia (Figure 1b). In a large single‐nuclei human dataset, SMOC1 gene expression was increased with greater AD pathology primarily in OPCs (Figure 2), and immunohistochemistry revealed accumulation in Aβ plaques (Figure 3). Higher baseline tau‐PET and greater longitudinal change were associated with a set of 15 proteins, particularly in Aβ‐positive participants (Figure 1a). Such tau‐related proteins were mainly expressed in neurons (Figure 1b) and enriched for two terms associated with glycolysis, from which the key contributing genes were ENO1, ENO2 and GPI. In single‐nuclei sequencing data, ENO1 and ENO2 gene expression were increased with greater tau tangle pathology primarily in neurons (Figure 2).ConclusionThrough comprehensive proteomics analysis of CSF proteins recently found to be associated with AD, we identified differential associations with Aβ plaques and tau tangles, and further corroborated such findings in postmortem data.
The effects of the novel phosphodiesterase 9 (pde9) inhibitor E2027 (irsenontrine) on CSF proteomics profile in amyloid positive and amyloid negative Lewy Body Dementia
Authors: Vermunt Lisa ,   Sjors G.J.G. in ’t Veld, Koel‐Simmerlink Marleen JA , Ye Yuanqing , Saxena Satya , Irizarry Michael C. , Sachdev Pallavi , Teunissen Charlotte 
Published: January 2025

AbstractBackgroundIrsenontrine (e2027) is a potent and selective PDE9 inhibitor that increases cellular cGMP which is important for glutamatergic synaptic function. Irsenontrine was investigated to improve cognition in Lewy Body Dementia (LBD; DLB and PDD), and recent phase 2 study data suggests that irsenontrine could be more effective in DLB patients without amyloid copathology. Here, we evaluated differential change from baseline levels in proteins associated with cGMP pathway in DLB participants without amyloid co‐pathology (DLB A‐) compared to DLB participants with amyloid co‐pathology (DLB A+). We next evaluated the affected biological pathways.MethodWe employed proximity extension analysis (PEA) proteomics in all available paired pre‐ and post‐treatment CSF samples of a translational medicine trial of E2027 (Figure 1A). This set included six DLB A‐ patients (CSF Lumipulse Ab42/40 cut‐off 0.057) and nine DLB CSF A+ patients with a mean±sd age of 76±6 years and 67% male. We assessed the treatment effect per DLB group by paired Wilcoxon tests of pre‐ vs post‐treatment (1) protein levels (p<0.05) and (2) individual pathway enrichment z‐scores based on 189 KEGG pathways (p<0.05).ResultFollowing E2027 treatment, CSF protein changes were apparent in both groups (DLB A‐ 10 proteins increased, and 32 decreased; DLB A+ 16 proteins increased, and 27 decreased; Figure 1B/C). We found that more pathways were affected in DLB A‐ (5 pathways), compared to DLB A+ (3 pathways), and several of these were related to the mechanism of action, including an increase in Pantothenate and CoA biosynthesis z‐scores in both groups, and lower GABAergic synapse in DLB A‐ only (Figure 1D/E).ConclusionThis global proteomics analyses in DLB clinical trial samples presents that, despite the small number of participants treated with E2027, there were changes in proteins related to the mechanism of action, as indicated by Pantothenate and CoA biosynthesis increase, which amongst others factors related to glutamate metabolism. In addition, multiple proteins and pathways were differentially affected between the DLB A‐ and A+ group, which could lead to improved understanding of differential clinical treatment response in DLB patients.
Longitudinal posterior‐medial functional connectivity changes with age and Alzheimer’s pathology are differentially related to memory performance depending on APOE genotype
Authors: Fischer Larissa , Molloy Eóin N. , Adams Jenna N. , Tremblay‐Mercier Jennifer , Remz Jordana , Binette Alexa Pichet , Villeneuve Sylvia , Maass Anne ,   PREVENT‐AD Research Group
Published: January 2025

AbstractBackgroundThe posterior‐medial network is crucial for episodic memory. However, the medial temporal lobe (MTL) and posteromedial cortex (PMC) regions are vulnerable to aging and early Alzheimer’s disease (AD). Both processes might elicit distinct early functional connectivity (FC) changes which could be detrimental or protective/ compensatory regarding cognition. However, this is not well understood. We hypothesized that resting‐state FC strength between key regions (Figure 1a) would decrease with age and memory decline without AD pathology (A‐T‐) but increase with early AD pathology.MethodWe analysed longitudinal 3‐Tesla resting‐state fMRI data from cognitively unimpaired older adults (OA; PREVENT‐AD cohort). We assessed FC at baseline and after 24 months (FU24) in i) CSF or PET Aβ‐ and tau‐negative OA (A‐T‐, N=96, 63±5years, 70 female, 28 APOE4) and ii) Aβ and p‐tau CSF‐characterized OA with available longitudinal p‐tau181/Aβ1‐42 ratio (N=65, 63±5years, 45 female, 22 APOE4). First, we investigated effects of age, APOE genotype and p‐tau181/Aβ1‐42 ratio on FC controlling for sex and education. Second, we tested the association between baseline FC or change in FC and change in delayed memory recall in multiple regression analyses.ResultIn A‐T‐ OA, FC decreased mainly between regions within the PMC subnetwork over 24 months (Figure 1b). Higher baseline FCwithin‐PMC was related to increasing memory performance over time (p = 0.047; Figure 2a). Longitudinally, increasing FCMTL‐mPFC was associated with increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.016; Figure 2b). In CSF‐characterized OA, p‐tau181/Aβ1‐42 ratio at baseline and FU24 was related to increasing FCMTL‐PMC over time (Figure 3a). Higher baseline FCMTL‐PMC was associated with longitudinally increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.028; Figure 3b).ConclusionOur results provide novel longitudinal evidence incorporating age, APOE, Aβ and tau indicating specific memory‐related FC changes in cognitively unimpaired OA. APOE moderated the effects of FC strength on change in episodic memory performance. Higher FCMTL‐PMC and increasing FCMTL‐mPFC seem to be detrimental in APOE4 carriers but beneficial in APOE4 non‐carriers. Importantly, this effect was observed in A‐T‐ OA, hinting that APOE genotype may affect FC earlier than AD‐related pathology.
Prevalence of cerebrospinal fluid AT biomarker profiles according to APOE genotype and across age in persons without dementia
Authors: van der Velden Jolien , Vos Stephanie J. B. , Tijms Betty M. , Oomens Julie Elisabeth , Maserejian Nancy N , Visser Pieter Jelle , Jansen Willemijn J. ,   Amyloid Biomarker Study Group
Published: January 2025

AbstractBackgroundAmyloid‐b deposition and tau tangle formation are the key pathologies of Alzheimer’s disease (AD). The presence of these pathologies in cerebrospinal fluid (CSF) biomarkers is used for a biological diagnosis of AD. It remains unclear how the prevalence of AT biomarker profiles depends on apolipoprotein E (APOE) genotype. A better understanding of the AT biomarker profiles across APOE genotypes and age in the pre‐dementia stages will help inform strategies to prevent or delay AD progression in those with different APOE genotypes.MethodsParticipants with normal cognition (NC; n = 4356) or mild cognitive impairment (MCI; n = 3997) were selected from 45 studies that participated in the Amyloid Biomarker Study based on availability of data on age, CSF amyloid‐b42 (A), CSF phosphorylated tau 181 (T), and APOE genotype (e2e2, e2e3, e2e4, e3e3, e3e4, e4e4). Based on (ab)normal values for A (data‐driven) and T (center‐specific cutoffs) participants were placed into one of four AT biomarker profiles: A‐T‐, A+T‐, A‐T+, or A+T+. A Markov‐Chain‐Monte‐Carlo generalized linear mixed model was performed separately for NC and MCI to evaluate the association of AT profile frequency with age and APOE genotype. Center was included as random effect.ResultsThe NC and MCI groups had an average age of 65.1 years (SD = 10.8; 59% female) and 69.3 years (SD = 8.4; 48% female) respectively. Most participants had APOE e3e3 genotype (NC 56%, MCI 45%; Table 1). In both groups, the association of AT profiles with APOE genotype changed across age (both p < .001; Figure 1), except for participants with NC and APOE e2e2 genotype. For NC with APOE e2e3 and e3e3 genotypes, A‐T+ was more frequent in older age than A+T‐ or A+T+. In APOE e3e4 and e4e4 genotypes A+T‐ frequency plateaued around 65 years of age, while A+T+ frequency strongly increased. For MCI, A+T+ was most frequent with aging across APOE e2e4, e3e3, e3e4, and e4e4 genotypes.ConclusionFrequencies of AT biomarker profiles changed substantially across APOE genotypes and age in NC and MCI. Studies recruiting participants based on AT biomarker profiles should take age and APOE genotype into account.
Bitter effect of a Sweet Disease‐ Exploring Cognitive dysfunction in Prediabetes from an Aging cohort
Authors: Issac Thomas Gregor , G Sandhya , Menon Anjana J , Diwakar Latha , Sundarakumar Jonas S. 
Published: January 2025

AbstractBackgroundIndia is unfortunately the “Diabetes Capital” of the world with estimated 101 million and 136 million patients suffering from diabetes and prediabetes respectively. Prediabetes is a transition state between euglycemia and diabetes. Although diabetes is associated with cognitive decline, studies that link prediabetes and cognition have been scarce and inconclusive especially from the Low and Middle Income (LMIC) countries. Therefore, the current study attempts to explore the relationship between prediabetes and cognition.Methods531 participants aged ≥ 45 years, recruited by CBR‐TLSA (Tata Longitudinal Study of Ageing) were included in this study. Glycosylated Haemoglobin (HbA1c) levels was utilized to categorise the participants into healthy, prediabetes and diabetes based on the American Diabetes Association (ADA), 2017 criteria. Among these participants, 65 were healthy and 234 were prediabetic. The remaining 232 participants with Diabetes were excluded and directed towards appropriate care pathways. The COGNITO (Computerized Assessment of Adult Information Processing) neuropsychological test battery was utilized to assess the cognitive functioning. Generalized Linear Model (GLM) was performed between prediabetes status and cognition after adjusting for confounding variables.ResultsThe estimated prevalence of prediabetes in our elderly cohort is 44%. After adjusting for ApoE status, GLM analysis revealed that healthy participants performed better in semantic association (B = 0.314, 95% CI (0.047, 0.582), p = 0.021) and name‐face recognition (B = 1.644, 95% CI (0.516, 2.77), p = 0.004) tasks when compared to prediabetics. Subsequently, after adjusting for age, gender, years of education and ApoE status, it was observed that the scores of semantic association (B = 0.290, 95% CI (0.025, 0.556), p = 0.032) and name‐face recognition (B = 1.390, 95% CI (0.260, 2.520), p = 0.016) tasks were higher among healthy participants.ConclusionThis study emphasizes the deleterious effect of a potentially modifiable risk factor like prediabetes. Participants with prediabetes performed poorer in memory and language related cognitive tasks. If diagnosed early, interventions aimed at improving prediabetes could potentially prevent or delay the progression to both minor and major neurocognitive disorders.