bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metabolomics Analysis of the MIND Study Informs about Metabolic Benefit and Heterogeneity among Individuals‐ A Precision Medicine Approach for Diet Interventions
Authors: MahmoudianDehkordi Siamak , Voigt‐Zuwala Robin M , Dhana Klodian , Labus Jennifer S , Mohanty Ipsita , Agarwal Puja , Morris Martha Clare , Barnes Lisa L. , Sacks Frank , Batra Richa , Kastenmuller Gabi , Keshavarzian Ali , Kaddurah‐Daouk Rima ,   Alzheimer's Gut Microbiome Project Consortium (AGMP)
Published: January 2025

AbstractBackgroundMetabolomics captures net influences of exposome, diet, gut microbiome, and genome, informing about individuality and how we respond to interventions. Applications of metabolomics in pharmacology are starting to enable a Systems Pharmacology approach, where the outcome of a treatment is considered to evolve from effects on complex molecular networks, enabling insights into response variations. We bring the power of these approaches to the study of the MIND, a Mediterranean DASH diet for prevention of cognitive decline. We evaluate if metabolomics can reveal beneficial metabolic effects linked to improved cognition in all participants or subgroups of individuals.MethodsSerum samples were collected from participants enrolled in the MIND trial at the Rush University Medical Center site. Participants were randomized to either the MIND diet or control diet group for three years with study visits, cognitive testing, and sample collection occurring at baseline, Years 1, 2, and 3. A total of 746 serum samples from 243 participants were profiled using targeted and non‐targeted metabolomics, lipidomics, metagenomics, and foodomics approaches. The longitudinal effects of the diet on the metabolome were evaluated.ResultsWe identified metabolic signatures of participants on the MIND diet that were unique compared to the control diet. Major changes in lipid metabolism including ceramides, sphingomyelins, PUFAs, and plasmalogens were noted along with changes in energy metabolism and one carbon metabolism (Figure 1). Food components and exposome‐related metabolites were changed. For example, tryptophan betaine (lower in cognitive dysfunction) was increased in the MIND diet group with strongest effects in individuals with low levels at baseline. Additionally, glycoprotein acetyls (GlycA, an inflammation marker associated with AD, cognitive decline, reduced brain volume) was decreased in the MIND diet group compared to controls. Detailed mapping of influences on the gut microbiome are being defined and linked to changes in metabolome.ConclusionThe metabolomics data highlighted alterations in metabolism in response to MIND diet. These alterations suggest metabolic benefit for cognitive function and inflammation based on big metabolomics data in ADNI and other cohorts. The variation among individuals seen in our analysis warrants stratification of people enrolled in the MIND study before final conclusions are made on its outcome.
Optimizing referral pathways to a community based organization for early‐stage Alzheimer’s and dementia Cognitive Stimulation Therapy services
Authors: Shivers Stephani , Tiede Lauren , Ehrhardt Annabess , Cisek Edward , Curbeam Deanna , Lepore Michael 
Published: January 2025

AbstractCommunity‐based organizations (CBOs) are an essential part of dementia service delivery to people living with dementia (PLWD) and family caregivers (CG) impacted by Alzheimer’s and other dementias, however use of CBO services particularly by PLWD is limited. Referral of PLWD to CBOs by health systems (HS) and health care providers (HCPs) is a common way that PLWD come to use CBO services, but integration between CBOs and HS/HCPs is inconsistent. For example, referrals to CBOs might come from HS/HCPs or from other CBOs, these referrers might provide referrals for a single program or for multiple different programs, and the referrers might be physicians, social workers, case managers, or other clinicians. Aiming to advance effective integration with the broader constellation of HS/HCPs and CBOs, CaringKind, a CBO providing dementia services, examined the outcomes of referrals from different clinical contexts and different referral sources. This program analysis leverages CaringKind’s referral data and information on enrollment and participation in CaringKind’s Cognitive Stimulation Therapy (CST) program, which receives referrals as one of many programs available in standard operating procedures, and receives referrals in the context of a pragmatic trial with no other program options.Drawing on referrals to CaringKind for CST over the course of an 18‐month period, we calculated the rates of conversion from CST referral to CST participant to count successful referrals. We then compared the successful referral rates in standard operations with the successful referral rates in the pragmatic trial. Results show the percentage of successful referrals from physicians in the pragmatic trial compared to providers in standard practice. Lessons learned on the referral pathway process including the impact of re‐education to identify the most appropriate patients for CST will be highlighted. Participant outcomes and completion rates gathered for program evaluation will also be shared.
Unveiling Insight: Autopsy findings on Alzheimer’s Disease Clinical Trial Participants and the multifaceted existence of comorbid pathologies
Authors: Coskun Elif PINAR , Barber Justin M , Abner Erin L. , Schmitt Frederick A , Goldstein Larry B , Van Eldik Linda J. J. , Nelson Peter T , Jicha Gregory A 
Published: January 2025

AbstractBackgroundThe presence of multiple comorbid pathologic features in late‐onset dementia has been well documented across cohort studies that incorporate autopsy evaluation. It is likely that such mixed pathology potentially confounds the results of interventional trials that are designed to target a solitary pathophysiologic mechanism in Alzheimer’s disease and related dementias (ADRD).MethodThe UK ADRC autopsy database was screened for participants who had previously engaged in therapeutic interventional trials for Alzheimer’s disease, vascular cognitive impairment, dementia, and/or ADRD prevention trials from 2005 to the present. Sixty‐five cases (out of a total n = 534) were engaged in clinical trials for the prevention or treatment of ADRD. Pathologic features studied included b‐amyloid, tau, a‐synuclein, TDP‐43, and cerebrovascular disease using conventional rating scales.ResultAutopsy cases for those who previously engaged in clinical trials did not differ significantly from those that were trial‐naïve for demographic, genetic (ApoE), or clinical characteristics except for CDR global scores that were lower for past trial participants (p<0.05). Comorbid pathologies were common across study types with a mean of 3 pathologic features/participant, 17% with quadruple misfolded proteinopathy (QMP; Ab+tau+synuclein+ TDP43). Yet only 10% of MCI/AD trial participants demonstrated a “pure” disease state that was targeted by the study intervention.ConclusionIn our study, approximately 2 out of 3 ADRD trial participants had comorbid mixed pathologic features. Understanding the heterogeneity of pathologies seen in clinical trial participants may allow improved inclusion/exclusion criteria based on clinical features and the rational use of antemortem biomarkers to stratify the likelihood of mixed comorbid pathology. In addition, the recognition will allow the usage of combination therapy for future interventional strategies. Such insights may also enable improved power analyses and statistical designs that may be able to adjust for the confounds of such mixed pathologic disease states that are common in ADRD clinical trials.
Latent Representation Learning of Cortical Atrophy using BERT‐based Foundation Model
Authors: An Heeyun , Kim Jiyun , Seong Joon‐Kyung , Lee Wha Jin 
Published: January 2025

AbstractBackgroundThe assessment of cortical thickness through structural magnetic resonance imaging (MRI) reveals various cortical atrophy patterns, delivering crucial insights into the extent of neurodegeneration. Numerous studies have focused on these thickness values to construct models for diverse neurodegeneration‐related tasks, such as classifying disease groups, staging progression, or predicting progression speed. However, these tasks require substantial training datasets tailored to each specific task, necessitating the development of new task‐specific models. We aimed to establish a foundational model using pre‐trained BERT, integrating context‐aware deep latent representations derived from a large cohort of unlabeled cortical atrophy data, to address these challenges.MethodWe collected 10,450 T1‐weighted MRI images within the ADNI dataset. Cortical thickness was derived using FreeSurfer across 68 regions based on the Desikan‐Killiany atlas. Emplying the BERT model, we applied its self‐attention capabilities to encode deep bidrectional representations of the data. The model is pre‐trained with 8,360 unlabeled cortical thickness data through self‐supervised learning, predicting randomly masked thickness values. Subsequently, we fine‐tuned this pre‐trained model with only one additional output layer using a supervised approach, employing independent data subsets for three challenging downstream classification tasks: (1) mild cognitive impairment (MCI) and Alzheimer’s dementia (AD), (2) MCI converters (C‐MCI) and non‐converters (N‐MCI) within 3 years, and (3) Aβ‐positive and negative cases. During fine‐tuning, demographic information encoded by one layer was also incorporated for classification purposes.ResultTable 1 provides demographic details of the subset data for fine‐tuning, showing comparable trends in each set of information, except for MMSE in the MCI and AD comparison. Table 2 outlines our model's performance on three downstream classification tasks. Despite training with a relatively limited amount of data, our model demonstrated competitive performance with state‐of‐the‐art methods, achieving 85% accuracy on the classification of MCI and AD, 85% of C‐MCI and N‐MCI, and 69% of Aβ‐positive and negative.ConclusionThis study introduces the novel cortical atrophy foundation model, demonstrating competitive performance even with a limited dataset across diverse challenging tasks. The model's performance in predictive tasks highlights its potential applicability for various nerodegeneration‐related challenges, paving the way for advanced AI applications within the realm of neurodegenerative diseases.
Accounting for White Matter Uptake Improves Between‐Tracer Agreement in Amyloid PET
Authors: Chen Yinghua , Protas Hillary D. , Luo Ji , Li Shan , Sohankar Javad , Ghisays Valentina , Lee Wendy , Wu Teresa , Reiman Eric M. , Chen Kewei , Su Yi 
Published: January 2025

AbstractBackgroundDifferent PET tracers can be used to measure neuritic amyloid plaque deposition in human brain. While mean cortical‐to‐cerebellar standard uptake value ratios (SUVRs) generated using different radiotracer methods can be transformed into Centiloid measurements to facilitate comparisons among the resulting amyloid plaque measurements, the level of agreement as measured by the strength of the correlation between the measurements does not change. In this study, paired 18F‐labeled (i.e., florbetapir, florbetaben, flutemetamol, and NAV4694) and 11C PiB radiotracers from the same research participants to test the hypothesis that the correlation between amyloid plaque measurements derived using different radiotracers can be improved by accounting for variability in white matter uptake.MethodFor all four 18F‐labeled radiotracers, paired 18F‐radiotracer and PiB‐derived PET images were downloaded from the Centiloid project (www.gaain.org/centiloid‐project). An in‐house image‐analysis pipeline was used to generate mean cortical‐to‐cerebellar SUVRs (MC‐SUVRs) from every PET image. Two approaches to account for white matter contributions to MC‐SUVR in the inherently low‐resolution PET images: 1) a linear regression approach to account for white matter contributions using a FreeSurfer‐defined UnsegmentedWhiteMatter SUVR; and 2) a regional spread function (RSF)‐based partial volume correction (PVC) technique. Pearson’s correlation coefficient was used to assess the agreement between F18 tracer‐based measure and PIB. Steiger’s test was used to determine whether accounting for white matter signal significantly improves agreement.ResultAccounting for white matter signal improved the agreement between each 18F radiotracer‐based MC‐SUVR and the corresponding PiB‐derived MC‐SUVR. Using the regression approach, the correlations with PiB SUVRs were significantly improved for florbetapir (p<0.0001) and flutemetamol (p=0.03) but did not reach significance for florbetaben and NAV4694. For the PVC‐based approach, correlations with PiB SUVRs were significantly greater for all four 18F‐tracers (p<0.05).ConclusionThe relationship between mean cortical measurement of amyloid plaque burden using different PET tracers can be significantly improved by accounting for differences in white matter uptake. Additional studies are needed to optimize this approach and account for any other potential confounds.
Impact of free later life formal university education on longitudinal modifiable risk factors, cognition and plasma phosphorylated tau 181
Authors: Roccati Eddy , Bindoff Aidan , Kitsos Alex , Alty Jane E , Collins Jessica M , King Anna E , Doherty Kathleen , Vickers James C 
Published: January 2025

AbstractBackgroundPrevious research has focused on early‐life education to reduce dementia risk, yet there is great potential for enhancing cognitive reserve in later‐life through educational interventions, even for people with low early‐life educational attainment. In 2019, we launched ISLAND (Island Study Linking Ageing and Neurodegenerative Disease) Campus, offering free university study to participants, with flexible in‐person/online learning models removing educational, socioeconomic and geographical barriers. After four years, here we investigate our core hypothesis: that engagement in later life education leads to improvements in modifiable risk factors for dementia, cognition and plasma biomarkers.MethodISLAND Campus participants were matched on age and gender to non‐Campus participants via propensity score method, with optimal matching based on logistic regression. Participants completed online surveys on background health, demographics, modifiable dementia risk via customised Dementia Risk Profile (DRP) and provided a blood sample for APOE genotyping and plasma phosphorylated‐tau (p‐tau) 181. Cognition was measured online via the validated Cambridge Neuropsychological Test Automated Battery Paired Associates Learning (PAL) and Spatial Working Memory (SWM) tasks. Impact of the opt‐in educational intervention was tested in R via ANCOVA.ResultIncluded were 986 participants (intervention = 493, control = 493), mean age 61.2 years, 71.2% female, 11.7 mean years of education, 23.9% APOE e4+. Intervention and control participants were similar on socioeconomic status, location of residence, p‐tau and APOE e4 presence, however intervention participants had significantly higher history of prior university study completion (76.1%) than controls (59.8%). Intervention participants enrolled in a variety of university degrees, the most common were Diploma of Family History (n = 103, 20.8%), Diploma of Arts (n = 74, 15.0%) and Diploma of Fine Arts (n = 52, 10.6%). Over four years of follow‐up, intervention participants significantly improved episodic memory (PAL) and their risk factor profiles as measured via the DRP (p <0.001), indicating a significant change towards lower dementia risk.ConclusionWe found free later‐life university education was associated with improvements in modifiable dementia risk factors over time and cognition. Intervention participants displayed significantly higher baseline education than control participants, therefore later life educational interventions should be targeted at individuals with lower baseline education.
causal effects of air pollution on dementia: a mendelian randomized study
Authors: GUO YUNYUN , Sindi Shireen , Wang Rui , Middleton Lefkos T , Kivipelto Miia 
Published: January 2025

AbstractBackgroundThe 2017 Lancet Commission on Dementia Prevention, Intervention and Care included air pollution in the list of potential risk factors for dementia. Air pollution has been associated with an increased risk of dementia in observational studies, but the causal relationship remains unclear. In this study, we used a two‐sample Mendelian randomisation (MR) analysis to assess the causal relationship between PM2.5, PM10, NO2 and NOX exposure and the occurrence of dementia, including Alzheimer’s disease (AD), vascular dementia, Lewy body dementia, and frontotemporal dementia.MethodWe extracted 5 single nucleotide polymorphisms associated with PM2.5, 22 single nucleotide polymorphisms associated with PM10, 6 single nucleotide polymorphisms associated with NO2 and 8 single nucleotide polymorphisms associated with NOX as instrumental variables from a genome‐wide association study based primarily on European ancestry. Summary‐level statistics were obtained from the Dementia GWAS database and the FinnGen consortium. MR estimation was based on the inverse variance weighting (IVW) method as the primary method, supplemented by the MR‐Egger and weighted median (WM) methods. Finally, multiple validity tests and sensitivity analyses were performed to obtain robust and valid estimates.ResultAccording to the IVW method, we found a positive association between PM10 and AD risk (OR: 2.03, 95% CI: 1.06‐ 3.89, p = 0.03); NO2 may increase the risk of AD (OR: 14.41, 95% CI: 10.95‐ 18.97, p = 0.04). However, there is insufficient evidence that PM2.5 and NOX are associated with an increased risk of future dementia.ConclusionOur study suggests that PM10 and NO2 are causally associated with AD risk. PM10 and NO2 may increase the risk of AD in people of European origin. More animal experiments or population‐based observational studies with long follow‐up are needed in the future to explore the intrinsic mechanisms of PM10, NO2 and AD.
Adherence to the MIND Diet and Cognition in Older Adults: A Post‐hoc Analysis of the MIND Trial
Authors: Dhana Klodian , Agarwal Puja , Ventrelle Jennifer , Liu Xiaoran , Tangney Christy C , Carey Vincent J , Aggarwal Neelum T. , Arfanakis Konstantinos , Barnes Lisa L. 
Published: January 2025

AbstractBackgroundThe MIND randomized clinical trial demonstrated that the effect of the 3‐year MIND diet intervention on cognition was no different than the calorie‐restricted usual diet in overweight, non‐demented, older adults. However, compliance with dietary interventions may have differed among the participants within the intervention groups. We assessed the adherence to MIND diet (MIND score) and and evaluated the association with global cognition.MethodThis study include 551 individuals with MIND diet score, covariates, and cognitive assessment at baseline and year 3. The MIND diet score (range 0‐14; a higher score reflects a healthier diet) was computed at baseline and during the follow‐up from responses to the 144‐item validated FFQ, and the average within individuals across the follow‐up was calculated. In addition, we computed the absolute (year 3 ‐ baseline) and relative change [((year 3 ‐ baseline)/baseline)*100]. Global cognition was derived from a standardized 12‐test cognitive battery. Regression models were adjusted by age, sex, race, APOE e4, education, cognitive activities, physical activity, BMI, total energy intake, and diet assignment group.ResultHigher adherence to the MIND diet across the study period was associated with significant improvements in global cognition scores. In the multivariable‐adjusted model, a 1‐point increase in the MIND diet score was associated with 0.027 (95%CI 0.004, 0.051) SD units higher in a 3‐year change in the global cognitive score. Compared to individuals with lower MIND diet scores (i.e., the first tertile), those in the third tertile had 0.140 (95%CI 0.033, 0.247) SD units higher in a 3‐year change in the global cognitive score. Similar associations were noted when we compared the relative changes of the MIND diet score with a 3‐year change in the global cognitive score. These associations (i.e., average MIND score, absolute, and relative changes) with cognition were not different between dietary interventions (P for interaction > 0.4).ConclusionAdherence to the MIND diet varied across individuals in the MIND trial. A higher MIND diet score during 3 years of dietary interventions was associated with better cognitive performance in older adults.
Información de la Enfermedad de Alzheimer para Latinos: A Study Framework for Alzheimer’s Genetic Risk Disclosure in an Urban, Latino Population
Authors: Rodriguez Sophia , Caro Daniela Diaz , Wetmore John Brandon , Godinez Jonathan D , Camarillo Itzel A , Goldman Jill S , Uhlmann Wendy R. , Ferber Rebecca , Blasco Drew , Caban Maria , Leu Cheng‐Shiun , Abraido‐Lanza Ana F , Lantigua Rafael A. , Chung Wendy K , Roberts J. Scott , Siegel Karolynn , Ottman Ruth 
Published: January 2025

AbstractBackgroundThe IDEAL study is a randomized clinical trial investigating the psychosocial, behavioral, and cognitive impacts of genetic risk disclosure for late‐onset Alzheimer’s disease (LOAD) among Latinos.MethodsWe used address‐based sampling in northern Manhattan to recruit Latinos aged 40‐64 for a community‐based survey and clinical trial. Data collection encompasses demographics, Alzheimer’s disease (AD) family history, knowledge and beliefs about AD and genetics, current mental health status, acculturation, impact of COVID‐19, familism, fatalism, caregiver status, and prior AD genetic testing. Eligible participants are invited to complete an education session and provide informed consent before receiving genetic testing for APOE, a key LOAD predictor. The clinical trial component will include 400 participants, who are randomized to learn their LOAD risk by age 85 based on either Latino ethnicity and family history alone or the same factors plus APOE genotype. Risk information is provided through semi‐structured genetic counseling sessions. Psychological impacts, health‐related behavioral changes, and memory performance are evaluated six weeks, nine months, and fifteen months post‐dislosure via surveys and in‐depth qualitative interviews.ResultsFrom 91,433 invited households, 5,542 (6.1%) responded, and 2,087 (2.3%) were eligible and completed the Baseline survey. Most were 40‐49 years old (41.2%), women (70.5%), identified as Dominican (53.7%), had some college education (63.2%), and completed the survey in English (74.6%). About half reported a family history of AD (48.6%).ConclusionThis study addresses gaps in understanding of impacts of AD genetic risk disclosure among Latinos and contributes valuable insights through its mixed‐methods approach.