bluuebunny/crossref_metadata_2025_split huggingface dataset:
The direct effect of type 2 diabetes on neurodegenerative processes in the absence of other cardiovascular risk factors
Authors: Nowell Joseph , Gentleman Steve , Edison Paul 
Published: January 2025

AbstractBackgroundDiabetes is associated with an increased risk of developing neurodegenerative conditions, including Alzheimer’s disease. Abnormal insulin signalling can lead to impaired phosphorylation of protein kinase B and activation of phosphatidylinositol 3‐kinase, resulting in hyperphosphorylation of tau and activation of inflammatory pathways. However, people living with diabetes commonly exhibit comorbid cardiovascular risk, which are also linked with cognitive decline. Here we sought to establish the influence of diabetes on global brain atrophy in the absence of comorbid cardiovascular disease.MethodParticipants diagnosed with diabetes and a matched sample of non‐diabetic control participants were enrolled from the UK biobank database. To reduce the influence of confounding risk factors, diabetic and control participants with additional cardiovascular risk were excluded. Participants diagnosed with cardiovascular/heart problems including high blood pressure, cardiac arrest, stroke, and angina were excluded. Non‐diabetic controls were matched based on age, sex and APOE genotype to enhance statistical precision. Voxel‐based morphometry was performed on T1‐weighted structural magnetic resonance images to evaluate the macrostructural changes associated with diabetes across the cortex. A voxel‐wise t‐test was performed between diabetic and non‐diabetic controls implemented on FSL.ResultA total of 503 diabetic participants and a matched sample of 503 control participants met the inclusion criteria and were enrolled on the study. Even in the absence of comorbid cardiovascular disease, participants with diabetes exhibited widespread reductions in grey matter volume in comparison to non‐diabetic participants. Volumetric reductions were demonstrated in 97% of grey matter (volume = 191605 mm³), indicating neurodegeneration in all major brain lobes. Reductions of brain volume in diabetic participants remained following family‐wise error correction.ConclusionIn the absence of other comorbid cardiovascular diseases, type 2 diabetes mellitus induces widespread neurodegeneration in cortical regions. Impairment to insulin signalling and the initiation of the inflammation response may initiate neurodegenerative processes resulting in the loss of brain cells. The widespread nature of atrophy indicates the potential risk for future cognitive impairment. Targeting molecular mechanisms involved in diabetes, including insulin resistance and inflammation, are important to prevent the development of neurodegenerative conditions. This exemplifies the potential for antidiabetic agents for the treatment of neurodegenerative diseases.
Our youth, our compass: families walking with younger‐onset dementia shine light on stigma
Authors: Cose Diana Shulla , Fitzgerald Stephanie , LaFleur Patti , Ruge Bree 
Published: January 2025

AbstractPurposeFor youth walking with a parent’s younger‐onset dementia diagnosis, our voices are the softest, yet our journey is often the hardest. We are helping to open the shades and bring light. We are telling the stories of our Mother’s and our Father’s. We are the survivors who choose to advocate for a more just world for our families. Through the EmpowermentPLUS Model, we are bringing strength to stigma.Project PlanThe three components of the EmpowermentPLUS Model include (1) recognize, (2) respond, and (3) empowerx2. For example, when I feel I am experiencing stigma as a daughter of my parent living with dementia–at a family party, grocery store, park or hospital, I am (A) able to recognize it, and (B) I have the tools to respond, rather than responding with fight, flight, or freeze and (C) the last piece is that my mindful and informed response empowers me as a daughter, and the PLUS symbolizes that the person who triggered the stigma is also empowered by being educated.OutcomesDuring our international Youth Summit, with support from Alzheimer’s Society of Canada, Alzheimer’s Disease International and London School of Economics, nearly 100 youth worldwide shared personal stories of when they experienced stigma as a younger family walking with dementia, and we taught the EmpowermentPLUS Model as a way to grapple and dismantle it.ConclusionWe are building our alliance of empowered young ambassadors, and expect more than 200 youth at Lorenzo’s Youth Summit 2024. Our Founding Executive Director, Diana Shulla Cose, and another member of our Lorenzo’s House community will share the youth voices and details of Lorenzo’s House strength to stigma work.
Differences in amyloid positivity rates among racial groups with cognitive impairment in a suburban‐rural Southeast community
Authors: Chacon Eduardo Garcia , Woodring Annalise C , Crane Monica K 
Published: January 2025

AbstractBackgroundUnderrepresented racial and ethnic groups have higher rates of clinical dementia symptoms and are given clinical diagnoses of Alzheimer’s disease without confirmatory AD biomarkers.MethodWe compared amyloid PET positivity in cohort of all rural and suburban Southeastern participants from a single clinical practice who met appropriate‐use criteria for amyloid PET imaging between January 2020‐December 2024. We used a paired nominal date test McNemar test to compare amyloid PET positivity proportions between matched racial and ethnic groups and multivariable logistic regression to assess the odds of having a positive amyloid PET scan.ResultData from 94 individuals (6 Asian/Pacific Islander(Other), 42 Black, 7 Hispanic, and 39 White) with MCI or dementia and amyloid PET were analyzed between April 2020 and December 2023. The median (range) age of participants was 75 (68‐82) years; 51 participants (54.3%) were female and 43 (45.7%) were male. For patient amyloid status, 49 participants (52.1%) had a validated negative amyloid result, and 45 participants (47.9%) had a validated positive amyloid result. In the optimal 1:1 matching analysis (n = 81, White participants had a greater proportion of positive amyloid PET scans analyzed but did not achieve statistical significance when compared with Black participants (24 of 39; 61.5%; 95% CI, 0.38‐0.72 vs 14 of 42; 33.3%; 95% CI, 0.19‐0.51, respectively) p>0.05. In the adjusted model, the odds of having a positive amyloid PET scan were lower for Black participants (OR, 0.313; 95% CI, 0.126‐0.776; P =0.012), and Hispanic participants (OR, 0.33; 95% CI, 0.163‐4.253; P>0.05) compared with White participants.ConclusionThe proportion of amyloid positive PET scan was greater among White as compared with Black and Hispanic participants when controlling for social and demographic factors. These findings may reflect differences in underlying pathology and raises concern that other factors may be contributing to higher levels of cognitive impairment in underrepresented groups.
The role of neurofilaments light chain in discriminating behavioral variant frontotemporal dementia from non‐neurodegenerative mimics
Authors: Gallingani Chiara , Vinceti Giulia , Carbone Chiara , Tondelli Manuela , Salvatori Davide , Salemme Simone , Bedin Roberta , Urbano Teresa , Luchetti Ludovico , Gentile Giordano , Battaglini Marco , Chiari Annalisa , Zamboni Giovanna 
Published: January 2025

AbstractBackgroundThe measurement of serum and cerebrospinal fluid (CSF) neurofilaments light chain (NfLs) has been proven promising in differentiating the behavioral variant frontotemporal dementia (bvFTD) from non‐neurodegenerative mimics, including primary psychiatric disorders and non‐progressive cognitive/behavioral changes. However, studies on this topic are based on clinical diagnosis, which remains challenging and potentially confounded by the overlapping clinical phenotypes. We investigated the role of NfLs in this field by classifying patients based on the presence/absence of pathological longitudinal brain volume changes.MethodWe prospectively recruited subjects with early‐onset (< 65 yo) mild cognitive/behavioral impairment suggestive of potential bvFTD. At baseline they underwent neuropsychological assessment, magnetic resonance imaging (MRI) brain imaging, and CSF and serum collection for NfLs measurement. They were followed‐up clinically and repeated the MRI scan at 18 months. Single‐subject yearly percentage brain volume change (PBVC/y) was calculated using the FMRIB Software Library tool SIENA and compared to normative values. Subjects with a PBVC/y exceeding the 95th normative percentile were classified as Progressive, in line with a bvFTD diagnosis. Otherwise, they were indicated as Non‐Progressive, suggestive of a non‐neurodegenerative condition. Differences in NfLs levels between Progressive and Non‐Progressive individuals and their predictive value were evaluated through non‐parametric tests and univariate logistic regression models.Result30 patients were recruited: 19 were classified as Non‐Progressive and 11 as Progressive. Both CSF and serum NfLs values were significantly higher in patients with atrophy progression compared to the stable ones (2992,27 vs 558,53 pg/dl, p < 0.001; 55,91 vs 13,47 pg/dl, p < 0.001). Higher serum NfLs levels at baseline were predictors of atrophy progression (p = 0.041, OR = 1.301), whereas only a trend of significance was seen for CSF NfLs (p = 0.055, OR = 1.006). A cut‐off of 21.5 pg/dl for serum NfLs differentiated the two groups with 81.82% sensitivity and 94.74% specificity (AUC = 0.949); a cut‐off of 972 pg/dl for CSF NfLs yielded discriminative sensitivity of 81.82% and specificity of 100% (AUC = 0.928).ConclusionWe confirmed that NfLs measurement in biological fluids at baseline is a reliable biomarker to discriminate between bvFTD patients and non‐neurodegenerative mimics, objectively distinguished based on longitudinal atrophy progression.
Biological Aging and the Motoric Cognitive Risk Syndrome
Authors: Sathyan Sanish , Oh Hamilton Se‐Hwee , Emmeline Ayers , Rutledge Jarod , Adhikari Dristi , Gao Tina , Milman Sofiya , Wyss‐Coray Tony , Barzilai Nir , Verghese Joe 
Published: January 2025

AbstractBackgroundMotoric Cognitive Risk (MCR) syndrome is a predementia syndrome characterized by slow gait and subjective cognitive concerns. Individuals with MCR are at high risk of transitioning to both Alzheimer's disease (AD) and vascular dementia. With chronological age, the incidence of MCR increases and MCR cases exhibit a higher prevalence of age‐associated diseases. Biological age reflects an individual's accumulated physiological condition captured by changes at the epigenetic (DNA methylation) as well as proteomic levels (protein expression). Aging varies between individuals and at organ‐specific level within an individual. Our objectives were to (1) examine associations between biological age acceleration and MCR, (2) to identify organs that are aging at faster rate in MCR using novel organ‐specific clocks, and (3) impact of biological aging with mortality in MCR.MethodWe measured 4,265 proteins in plasma collected at baseline in the LonGenity cohort (n=1,025, Age ≥65 years) – utilizing the SomaScan proteomic assay. Machine learning models were used to derive biological age predictors at the individual level from all the proteins. Organ‐specific ages for 11 organs were also computed from the organ‐specific plasma proteome. Participants were characterized as fast and slow agers based on these clocks. Age acceleration measures were regressed against prevalent and incident MCR using logistic and cox models, respectively. Associations with biological aging were validated using an epigenetic clock (DNAm GrimAge) in HRS (n=1,043).ResultFaster biological aging derived from the proteomic clock were associated with prevalent MCR as well as incident MCR. Prevalent MCR was most strongly associated with accelerated aging in muscles (p<0.001) and the heart (p<0.01). Brain, liver, kidney, and immune age acceleration was also nominally associated with prevalent MCR (p<0.05). Participants with both MCR and accelerated aging had the highest risk of mortality, as indicated by proteomic and epigenetic clocks in LonGenity (HR = 3.38) and HRS (HR = 2.47), respectively.ConclusionAccelerated aging is a hallmark of MCR and have an impact on aging of multiple organs. Older individuals with MCR and accelerated aging are at highest risk of mortality. Biological age acceleration may be an important modifiable dementia risk factor.
Association of sleep network functional connectivity with hyperexcitability and cognition in Alzheimer’s disease
Authors: Moguilner Sebastian , Berezuk Courtney , Bender Alex C , Pellerin Kyle R , Gomperts Stephen , Cash Sydney , Sarkis Rani A , Lam Alice D 
Published: January 2025

AbstractBackgroundSleep disturbances are common in Alzheimer's disease (AD) and occur at early stages. Hyperexcitability also arises during sleep and can lead to epileptiform activity and seizures that impact memory consolidation. The underlying mechanisms of sleep disturbances and hyperexcitability in AD pathology remain unclear but are likely associated with changes in brain networks and altered functional connectivity (FC).MethodUsing ambulatory scalp EEG recordings, we examined 33 cognitively normal healthy older adult controls (HC), 36 individuals with early clinical stages of AD without history or risk factors for epilepsy (AD‐NoEp), and 14 individuals with early clinical stages of AD who developed epilepsy related to Alzheimer's (AD‐Ep). The analysis involved analyzing FC measures such as amplitude envelope correlation with leakage correction, coherence‐based measures, and graph theory to examine FC across sleep‐wake stages, frequency bands, and its associations with cognitive performance.ResultWe found specific FC changes in Alzheimer's during sleep stages and frequency bands, including increased gamma connectivity during N2 sleep (N2‐gamma), increased delta connectivity during REM‐delta, and decreased alpha connectivity in N2‐alpha and REM‐alpha. AD‐Ep showed a distinct network signature compared to AD‐NoEp, with changes in sleep‐stage and frequency band combinations not observed in AD‐NoEp and reversal of FC changes associated with AD‐NoEp. Specific measures (N2‐gamma, REM‐alpha, Awake‐theta, and Awake‐delta connectivity) were linked to longitudinal global cognitive decline in AD. Machine learning algorithms using combinations of awake and asleep FC features accurately distinguished AD‐NoEp from HC (AUCroc = 0.905) and AD‐Ep from AD‐NoEp (AUCroc = 0.881). Moroever, we identified "fast cognitive decliners" among AD participants with high classification performance (AUCroc = 0.865).ConclusionThe results highlight specific changes in sleep network functional connectivity in AD, offering insights for disease monitoring and finding therapeutic targets.
Harmonized Tractometry Visualizes Alzheimer’s Disease Effects on the Brain’s White Matter Tract Microstructure
Authors: Chandio Bramsh Q , Reina Julio E Villalon , Nir Talia M , Thomopoulos Sophia I , Feng Yixue , Benavidez Sebastian M , Jahanshad Neda , Harezlak Jaroslaw , Garyfallidis Eleftherios , Thompson Paul M. 
Published: January 2025

AbstractBackgroundDiffusion MRI (dMRI) metrics of brain microstructure offer valuable insight into Alzheimer’s disease (AD) pathology; recent reports have identified dMRI metrics that (1) tightly link with CSF or PET measures of amyloid and tau burden; and (2) mediate the relationship between CSF markers of AD and delayed logical memory performance, commonly impaired in early AD [1,2].To better localize white matter tract disruption in AD, our BUndle ANalytic (BUAN) [3] tractometry pipeline allows principled use of statistical methods to map factors affecting microstructural metrics along the 3D length of the brain’s fiber tracts. Here, we extended BUAN to pool data from multiple scanning protocols/sites ‐ using a new harmonized tractometry approach, based on ComBat [4,5], a widely‐used harmonization method modeling variations in multi‐site datasets due to site‐ and scanner‐specific effects.MethodWe illustrate the effects of integrating ComBat into our BUAN tractometry pipeline. Analyzing Alzheimer’s Disease Neuroimaging Initiative (ADNI3) [6] data, we examined the impact of mild cognitive impairment (MCI) and AD on 38 white matter tracts, comparing results with and without harmonization.We analyzed data from 730 ADNI3 participants, scanned with seven dMRI protocols. After data preprocessing with the ADNI3 protocol [7,8], BUAN extracted 38 bundles and created along‐tract bundle profiles for microstructural metrics: FA, MD, AD, and RD (see Figure 1 for full names). ComBat was applied to each point in bundle profiles to correct for scanner protocol effects and linear mixed models (LMM) were used to study the group differences in MCI and AD versus cognitively healthy controls (CN).ResultHarmonized BUAN maps reveal AD and MCI effects throughout specific tracts (e.g., the left cingulum and right arcuate fasciculus; Figure 1, bottom panel). ComBat harmonization enhanced the sensitivity to detect group differences compared to LMM without scanner correction. Adding data ‐ even from different scanner protocols ‐ boosted power (Figure 2f‐g).ConclusionIn this application of harmonization in neurodegenerative tractometry analysis, we integrated ComBat into BUAN tractometry to merge dMRI data from diverse scanning protocols and sites. Future research will examine various ComBat versions and deep‐learning approaches to track AD pathology effects on the brain’s neural circuitry.
Universal tau PET scale (Uniτ) – The HEAD Study
Authors: Povala Guilherme , Bauer‐Negrini Guilherme , Bellaver Bruna , Lussier Firoza Z , Amaral Livia , Ferreira Pamela C.L. , Zatt Bruno , Tudorascu Dana , Lopresti Brian J , Jagust William J. , Klunk William E , Lowe Val J. , soleimani‐meigooni David N. , Oh Hwamee , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Pascoal Tharick A. 
Published: January 2025

AbstractBackgroundThe HEAD study aims to collect a large dataset of multiple tau‐PET tracers to provide robust anchor values for tau‐PET harmonization. Here, we tested the hypothesis that anchoring two tau tracer uptake values using head‐to‐head measurements has the potential to generate an accurate universal tau‐PET scale, named Uniτ(tau).MethodsWe assessed 200 individuals across the aging and AD spectrum (Training: HEAD data freeze 2.0, n=185; Testing: UPitt dataset (Gogola et al.), n=15) with [18F]Flortaucipir and [18F]MK‐6240 tau‐PET. SUVRs were processed to a common 8mm FWHM, with inferior cerebellar gray matter as the reference region (Pascoal et al.). Uniτ explored two anchoring/harmonization methods. First, we examined within‐tracer anchoring by creating anchor values based on the mean SUVR of Youngs (<25 years) and 95th percentile voxels from cognitively impaired individuals. Second, we explored within‐ plus between‐tracer anchoring, employing linear (e.g., piecewise) and non‐linear regressions. To address the inherent problem of discontinuity of piecewise transformations, we implemented two smoothing methods at the inflection point between equations, transforming them into a continuous function.ResultsUniτ scale anchoring within‐tracer resulted in similar estimates for high values, but less accurate in the lower range (Figure 1,2). Anchoring within‐ plus between‐tracer improved estimate consistency, with the piecewise transformation generating the best results. The piecewise smoothing equation yielded estimates comparable to those obtained from the piecewise method without smoothing. This allowed for the use of a single formula. In addition, this leads to more robust results when the goal is to study longitudinal changes in the scale (data not shown). UPitt testing dataset showed similar results to the training set (Figure 3).ConclusionOur preliminary findings suggest that anchoring tau‐PET values both within and between tracers has the potential to harmonize tau‐PET tracers, while preserving their characteristics. Currently, piecewise smoothing is the preferred method for Uniτ, but we are continuously fine‐tuning scale parameters as we acquire more data. The final scale parameters will be determined based on extensive training and testing data from multiple tracers. This cautious methodology holds the promise of delivering reliable, robust, and reproducible results, ensuring safe usage of the scale in clinical trials, and potentially paving the way for future use in clinical practice.
Feasibility of the Linus Health’s life and health questionnaire in primary‐care settings
Authors: Ciesla Marissa C , Haas Brendan , Gomes‐Osman Joyce Rios , Banks Russel , Jannati Ali , Showalter John , Pascual‐Leone Alvaro 
Published: January 2025

AbstractIntroductionCompelling evidence from longitudinal trials demonstrates that adopting certain lifestyles, especially in midlife to early late life, can reduce the risk of dementia, reduce the severity of the associated disability, and decrease progression to dementia in individuals with mild cognitive impairment by as much as 40%. The Life and Health Questionnaire (LHQ) is a 32‐item questionnaire – written at a 6th‐grade reading level – that captures information related to potentially modifiable lifestyle and psychosocial risk factors, and protective factors for cognitive decline and dementia. The objective of this study was to gain insights into the feasibility of the LHQ in primary care settings by evaluating the influence of cognition, age, and education on the LHQ completion times.MethodsWe analyzed 1826 LHQ surveys between June and October 2023. Mann‐Whitney U tests were used to compare average LHQ completion times in relation to cognitive status as measured by the Digital Clock and Recall (DCR™), age, and education.ResultsThe average time to complete the LHQ among all patients was 4.8 minutes (median = 4.2 ± 2.4). Average LHQ completion times showed a gradual increase as DCR scores decreased (increasing cognitive impairment; mean = 3.5 and 6 minutes for DCR scores 5 and 0, respectively; p<0.05). There were no statistically significant differences in LHQ completion times as patient age increased. Those with higher education levels had significantly shorter average LHQ completion times (p<0.01).ConclusionThe LHQ is a brief survey capturing dementia risk and protective factors that takes an average of 4.8 minutes to complete. Completion time is lengthened with lower education levels and greater cognitive impairment to an average of 6 min. These results indicate the feasibility of the LHQ to be performed in primary‐care settings given its brief completion time.