bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross‐cohort epigenome‐wide association study in Alzheimer’s disease risk and related traits
Authors: Milicic Lidija , Vacher Michael , Porter Tenielle , Dore Vincent , Bourgeat Pierrick , Doecke James D. , Shishegar Rosita , Maruff Paul , Masters Colin L. , Rowe Christopher C. , Villemagne Victor L , Laws Simon M. 
Published: January 2025

AbstractBackgroundEpigenome‐wide association studies (EWAS) have identified multiple loci that are differentially methylated in Alzheimer’s disease (AD). However, for complex diseases such as AD, single methylation sites associated with disease and disease‐related traits have relatively low effect sizes. At the genetic level, measures of cumulative genetic risk, such as polygenetic risk scores, have yielded success in risk prediction as well as in association and interaction studies. Such approaches have the potential to be directly transferred to DNA methylation data.MethodThis study utilised data from two well‐characterised longitudinal cohort studies, the Australian Imaging, Biomarker and Lifestyle (AIBL) study (n=707) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI; n=620) and aimed to investigate the association between peripheral blood DNA methylation, at CpG sites across the epigenome, and eight AD‐related phenotypes: AD risk, MRI‐derived brain volumetric measures (hippocampal, ventricle, grey and white matter volumes), PET derived brain Aβ‐amyloid burden (as a continuous and binary (high/low) variable) and cognition (Pre‐Alzheimer’s Cognitive Composite (PACC)). Each trait‐specific EWAS was first undertaken in the AIBL cohort, and eight trait‐specific methylation risk scores (MRS) were then developed using summary statistics. An additional MRS was also developed using an elastic net machine learning method. MRSs were then validated within and across traits in the ADNI cohort.ResultNominally significant associations were observed between CpG sites within several of the EWAS that were performed; however, no individual CpG sites remained significant after FDR correction. Several MRSs were associated with AD risk after correction for the false discovery rate.ConclusionWhile this study adds to the growing literature supporting the role of MRSs in AD‐related traits, it suggests that there are limited associations of individual epigenome‐wide CpG sites with cognitive and neuroimaging traits using the methods undertaken in this study. Future studies with larger cohort sizes and phenotypically rich datasets will help to confirm these findings and potentially elucidate further associations.
Racial differences in neuropathology and cognitive abilities
Authors: Suemoto Claudia Kimie , Leite Renata Elaine Paraizo , Paes Vitor Ribeiro , Rodriguez Roberta Diehl , Justo Alberto Fernando Oliveira , Naslavsky Michel Satya , Zatz Mayana , Pasqualucci Carlos Augusto , Nitrini Ricardo , Ferriolli Eduardo , Jacob‐Filho Wilson , Grinberg Lea T. 
Published: January 2025

AbstractBackgroundRacial differences in dementia prevalence and incidence were found with higher dementia burden in African descendants. Previous neuropathological studies were conducted mostly in white participants in convenience samples. Further studies in diverse populations are important to foster the understanding of race differences in dementia pathology. We aimed to compare the frequencies of neuropathological lesions between black and white participants and the association of cognitive abilities and race in an autopsy study.MethodIn a cross‐sectional community‐based autopsy study, samples were collected at the Biobank for Aging Studies from 2004 to 2023. A family member reported the deceased’s race. The frequency of neurodegenerative and cerebrovascular lesions was evaluated using immunohistochemistry and hematoxylin‐eosin staining in 13 selected cerebral areas. We also examined the association between cognitive abilities with the Clinical Dementia Rating Scale and race. Neuropathologists were blinded to cognitive outcomes. To examine the associations of race with neuropathology and cognitive abilities, we used regression models adjusted for age, sex, education, clinical variables, and apolipoprotein E genotyping.ResultIn 1,815 participants, the mean age was 74.0±12.5 years old, 50% were women, 34% were black, the mean education was 4.7±4.1 years, and 35% had cognitive impairment. Small vessel disease (SVD) (OR = 1.74, 95% CI = 1.29‐2.35, p<0.0001), siderocalcinosis (OR = 1.70, 95% CI = 1.23‐2.34, 0.001), and neuropathological comorbidity (OR = 1.35, 95% CI = 1.12‐1.63; p = 0.001) were more frequent in blacks compared to whites, while neuritic plaques were less frequent (OR = 0.61, 95% CI = 0.44‐0.83, p = 0.002). Likewise, AD diagnosis was more frequent in whites (Whites: 39%; Blacks: 33%), while vascular dementia was more common among black participants (Whites: 24%; Blacks: 32%). Race was not associated with cognitive abilities, nor was an effect modifier in the association between neuropathology and cognition.ConclusionIn a large community‐based autopsy study, AD pathology was more frequent in whites, while vascular pathology and neuropathological comorbidity were more frequent in blacks. Cognitive abilities were similar between race groups, and race was not an effect modifier in the associations of cognition with neuropathologies. Further neuropathological studies in diverse samples are needed to understand race disparities in dementia burden.
Heritability of plasma biomarkers for Alzheimer’s Disease: A Nuclear Twin Family Design
Authors: Rousset Rebecca Z. , den Braber Anouk , Wilson David H , Teunissen Charlotte , de Geus Eco J.C. 
Published: January 2025

AbstractBackgroundPlasma biomarkers may be a non‐invasive and cost‐effective tool for diagnosing Alzheimer’s Disease. Promising markers include amyloid‐β‐42/40 ratio (Aβ‐42/40), glial fibrillary acidic protein (GFAP), and neurofilament‐light (NfL). Not much is known about what genetic and environmental factors influence and potentially confound these biomarker levels. We aimed to determine the proportion of genetic (heritability) and environmental contributions on Aβ‐42/40, NfL, and GFAP plasma levels.MethodMale and female twins, their parents, and up to two siblings were included (n=6516, Table 1). Plasma samples were analyzed on the Simoa HDx analyzer using the Neurology 4‐Plex E advantage kit (Quanterix). Biomarker levels were adjusted for age and sex. A twin‐only 5‐zygosities model was used to examine sex differences in genetic and environmental effects. A nuclear twin family design (NTFD) was used to estimate the proportional contributions of genetic, shared and unique environment. Shared environmental factors were broken down into environment shared by siblings, by twins only, or by parents and offspring.ResultNo sex differences in contributions to the variance in biomarker levels were found. The NTFD showed that 16% of the variance in plasma Aβ‐42/40 was explained by genetic effects and 84% by unshared environment. For NfL, 30% of variance in plasma levels was explained by genetic effects, 27% by sibling‐shared environment, and 43% by unshared environment. For GFAP, 45% of the variance in plasma levels was explained by genetic effects, 17% by sibling‐shared environment, and 38% by unshared environment.ConclusionThe heritability of plasma Aβ‐42/40 was low, while the heritability of NfL and GFAP levels was moderate. The low heritability of Aβ‐42/40 is a mismatch with the high heritability of Alzheimer’s Disease (60‐80%), suggesting this plasma ratio might be susceptible to environmental confounding. The importance of sibling‐shared environment could be a reflection of a generational effect. If members of a generation (siblings) are collectively more exposed to a factor which influences their plasma levels, that would make them resemble each other more than they resemble the previous generation (parents). This findings are not definitive proof of confounding, but are a first step in identifying possible confounders.
Parental history of dementia does not confound the association between depression and decline in cognitive status
Authors: Guilliams Chad , Abner Erin L. 
Published: January 2025

AbstractBackgroundParental history of dementia may lead to participation bias and has been largely replaced in analyses with genetic markers such as APOEe4. We studied how the inclusion of parental history of dementia affects associations between depression and cognitive status.MethodParticipants without dementia were stratified by cognitive and depression status at their initial study visit (“baseline”): normal cognition without depression (n = 7,592), normal cognition with depression (n = 2,346), MCI without depression (n = 2,280), and MCI with depression (n = 1,525). Logistic regression and Fine and Gray models, with death of the participant treated as a competing event, were used to analyze whether parental history of dementia affects the association between depression and cognitive status at baseline (n = 20,796) and over time. Fine and Gray models were used for participants with normal cognition at baseline and then again for NACC participants with MCI at baseline to estimate associations for the conversion to MCI or dementia respectively. Models included APOEe4 dose, participant demographics (age, sex, race, and education), in addition to self‐reported depression and depressive symptoms.ResultThe adjusted odds of MCI were increased for those with depression at baseline, OR = 2.51 (95% CI: 2.36‐2.68), and inclusion of parental history of dementia in the logistic regression analysis slightly strengthened the association (OR = 2.55 [2.39‐2.73]). Selection bias was evident, as participants reporting both parents with dementia had the lowest adjusted odds of cognitive impairment (OR 0.65, 95% CI: 0.57‐0.73) compared to no reported parental history. In the competing risk analysis, among those with normal cognition at baseline, those with depression had an increased risk of converting to MCI or dementia, subdistribution hazard ratio (sHR) = 1.47 (95% CI: 1.31‐1.64). However, inclusion of parental history of dementia did not alter the estimates significantly in any of the Fine and Gray models.ConclusionThere may be substantial heterogeneity among NACC participants with and without parental history of dementia. In our longitudinal analysis, parental history of dementia did not alter the association between depression and conversion to worse cognitive status. This suggests parental history of dementia may lead to differences in participation but may not confound longitudinal associations of interest.
Update on the current state of speech and language testing in Alzheimer's Disease
Authors: Dhareshwar Shloka , Mineur Ruby , Lewis Courtney , Kane Melissa , Maruff Paul , Vogel Adam P 
Published: January 2025

AbstractBackgroundScreening and disease monitoring are two core challenges of disease management in Alzheimer's Disease (AD). Digital speech and language features have shown promise as clinical outcomes in related disorders.MethodsWe reviewed how speech digital markers are currently used in AD, focusing on how behaviours are connected to underlying disease pathology.ResultThe rate of cognitive decline can be predicted by poor performance on language tests. The capacity of current language tests to distinguish between those with mild cognitive impairment (MCI) and healthy controls is limited. In some cases, disease progression can only be detected when significant changes in severity occur. Poor standardisation and limited clinical data are currently restricting communication outcomes uptake in clinical trials. The potential advantages of speech analytics and mobile health technology lie in their cost‐effectiveness, accessibility (non‐invasiveness), and automated analytical protocols. They have the capacity to improve assessment procedures, enhance screening and provide meaningful outcomes in clinical settings.ConclusionHigh‐dimensional data can be collected by automatically and objectively analysing speech. Developments in machine learning, signal processing and natural language processing techniques will further optimise outcomes.
Care staff perspectives of clinically meaningful outcomes of supportive care programs for persons with dementia in Kentucky: A qualitative multiple case study
Authors: Reschke‐Hernandez Alaine E. , Vasil Martina , King Emma G. , Woolums Carson 
Published: January 2025

AbstractBackgroundEmerging research suggests that complementary and supportive care programs, such as music therapy, show positive short‐term impacts (e.g., purposeful engagement, positive emotions) on persons with dementia who live in care facilities. However, barriers exist in understanding clinically meaningful outcomes (i.e., noticeable, valuable changes in a person’s life) in more advanced dementia and reliably documenting enduring outcomes within demanding care structures. This research aims to address these gaps by exploring clinically meaningful outcomes of such nonpharmacological programs from the perspective of clinical care staff.MethodBecause healthcare policies vary across the United States, this qualitative multiple case study is bound to Kentucky. This focus facilitates in‐depth analysis and description in the context of the state healthcare system. Care staff (e.g., certified nursing assistants) develop intimate knowledge of each person they care for, how they respond to various types of care, and the impact of such responses on the care environment. We are examining multiple cases (six) to reflect the care landscape within Kentucky and are using maximum variation sampling to ensure diverse identities and care experiences are represented. Data sources from each case are: (a) two interviews, (b) six weekly journal entries, (c) one site observation, and (d) publicly available facility information. Analysis involves rich case description, case‐wise thematic analysis, and cross‐case thematic analysis following Creswell’s (2013) data analysis spiral: (1) reading and memoing, (2) describing and interpreting data into codes and themes, (3) interpreting the data, and (4) representing and visualizing the data.ResultsTo have transferability of results, readers must be able to gain an in‐depth understanding of each case. Therefore, planned enrollment (January to April 2024) is 6 care staff from non‐profit and for‐profit facilities across rural, suburban, and urban areas of Kentucky. Active data collection begins in February, and results are expected by July 2024.ConclusionThe care needs of persons with dementia are high and require nonpharmacological options to maximize well‐being. Identifying ways to reliably document clinically meaningful outcomes without burdening caregivers is crucial to advance evidence‐based care. Results will provide insights into these challenges and transfer to the broader dementia care landscape.
Optimizing composite PET measurements for tracking longitudinal tau accumulation
Authors: Protas Hillary D. , Ghisays Valentina , Luo Ji , Sohankar Javad , Lee Wendy , Devadas Vivek , Chen Kewei , Reiman Eric M. , Su Yi 
Published: January 2025

AbstractBackgroundTangle burden, one of the hallmarks of Alzheimer’s Disease, is thought to accumulate and spread throughout the brain in a distinctive pattern starting from the entorhinal cortex following Braak stages as characterized in neuropathological studies. Longitudinal tau PET allows us to investigate in vivo the tau spread in an individual and substantial heterogeneity has been observed in the pattern of tau spread. In this analysis, we examine the statistical power of tau PET measurements in tracking disease progression using data from the ADNI cohort.MethodThe tau PET measures used in this study included conventional SUVR measures as well as graph theory based network strength measures as we previously reported (Protas 2023). We calculate the slopes of both regional SUVR and strength in 41 MCI and 71 CU participants who had one year, and/or two year follow‐up. Statistical power was assessed as the sample size needed to detect a 25% reduction in the rate of tau accumulation, and the power analysis was done for CU and MCI participants separately. The optimal composite measures (from combining up to 6 FreeSurfer ROIs) were determined based on two criteria: 1) having minimal tau accumulation (calculated sample size > 10000) in the A‐ group to ensure we are looking at AD related accumulation, and 2) having the smallest sample size in the A+ group.ResultStrength in amygdala, entorhinal, fusiform, rostral anterior cingulate, frontal pole and transverse temporal regions gives optimal sample sizes of 172 in A+ CU. In CU A+, SUVR in amygdala, lateral occipital and middle temporal produced an optimal sample size of 230. In MCI, for strength, the sample size is 193(A+) in an optimized region including cuneus, inferior temporal, postcentral, rostral anterior cingulate, and superior parietal. With SUVR the optimal region in MCI was entorhinal and middle temporal with a sample size of 263(A+).ConclusionThe optimal composite regional SUVR/strength measure varies depending on the target population and typically combines both early and late Braak stages. Further study is needed to confirm this finding using larger datasets.
Comparative analysis of clinical endpoint progression rates in sporadic Alzheimer’s disease and Down Syndrome‐related Alzheimer’s disease
Authors: Rafii Michael , Nicodemus‐Johnson Jessie , Hendrix Suzanne B. , Wagg Jonathan , Fournier Nicolas , Sol Olivier , Delpretti Saskia , Rongere Julien , Rudaz‐Kohler Claude , Kosco‐Vilbois Marie , Pfeifer Andrea , Streffer Johannes , Mendonca Nuno , Wassom Mitchell , Kirkham Zayne 
Published: January 2025

AbstractBackgroundClinical assessments utilized in trials to measure progression in sporadic Alzheimer’s disease (SAD) such as the MMSE, ADAS‐Cog, CDR‐SB and ADCS‐ADL are well established. Distinct assessments are utilized for Down Syndrome‐related Alzheimer’s disease (DSAD). Although these assessments are less well established, they probe comparable domains of cognition and function. We quantitatively compared progression rates for SAD assessments with comparable DSAD composite assessments and explored their utility in clinical trials.MethodsThe MMSE, ADAS‐Cog, CDR‐SB and ADCS‐ADL were mapped to comparable DSAD composite endpoints. Longitudinal data were sourced from the ADNI (SAD: n = 464) and ABC‐DS (DSAD: n = 393). Clinical endpoint progression rates were quantified as Mean to Standard Deviation Ratios (MSDR) of change across a unit time and derived using a model‐based approach. MSDRs were compared across populations and assessments. Clinical trial sample sizes were estimated to detect treatment effects using DSAD assessments.ResultsSensitivity of progression rate (MSDR) to baseline Amyloid PET was apparent for many DSAD composite measures. Sensitivity to progression for DSAD composite endpoints in the total ABC‐DS population at 18 months for MMSE, ADAS‐Cog, CDR‐SB and ADCS‐ADL were ‐0.32, ‐0.29, ‐0.40, and ‐0.22, respectively. Individuals with higher baseline Amyloid levels had increased sensitivity to progression with MSDRs at 18 months of ‐0.45, ‐0.33, ‐0.49, and ‐0.36. Power calculations of the most progressive measure in the total ABC‐DS population at 18 months (CDR‐SB DS composite; MSDR 0.4) indicate that assuming a 1:1 active: placebo ratio, 60% slowing and a dropout rate of 20%, the total sample size needed to reach an alpha of 0.05 at 80% power would be 548 subjects. Sample sizes for detecting treatment effects were reduced markedly with higher baseline Amyloid; CDR‐SB DS composite MSDR ‐0.49 requires 352 and 200 individuals total assuming 60 and 80% slowing over 18 months, respectively.ConclusionsConverging evidence demonstrates that DSAD progresses similarly to SAD. Here, we observe similar progression on composites of cognition and function between SAD and DSAD. Importantly, significantly smaller sample sizes will be required to detect treatment effects in DSAD populations when enriched for higher baseline Amyloid PET.
gamma‐secretase modulation: from bench to clinic
Authors: Rynearson Kevin 
Published: January 2025

AbstractCerebral beta‐amyloid accumulation is the key initiator of Alzheimer’s disease (AD) pathology. Most familial early‐onset AD mutations in the APP, PSEN1/2 genes increase the ratio of Abeta42:Abeta40, which drives beta‐amyloid accumulation in the brain. In 2001, the late Steve Wagner, Maria Kounnas, and I directed an agnostic high‐throughput screen for compounds that would reverse the Abeta42:Abeta40, ratio, and discovered the first non‐NSAID (second generation) gamma secretase modulators (GSM) at TorreyPines Therapeutics. Since then, in academia, we designed several novel structures similar to, but distinct from our original GSMs with predicted higher aqueous solubility. These compounds were then developed in the Wagner and Tanzi labs at UCSD and MGH, respectively with funding from the NIH and Cure Alzheimer’s Fund. Importantly, unlike gamma secretase inhibitors, our GSMs do not inhibit γ‐secretase activity, i.e. do not significantly inhibit NOTCH cleavage (up to 25 uM), but, instead, allosterically modulate gamma secretase activity, reducing generation of Aβ42 and to a lesser extent Aβ40, while enhancing production of Aβ37 and Aβ38, with IC50’s in the low nanomolar range. The preclinical development of our GSM’s evolved into four distinct chemical classes and involved testing over 1000 analogs, leading to our main clinical candidate, GSM776890, for which an IND has been submitted to the FDA (sponsored by Acta Pharmaceuticals, Boston). GSM776890 exhibits robust time‐ and dose‐dependent efficacy in both acute and chronic studies across various species, including a transgenic AD mouse model. GSM776890 displayed a >40‐fold safety margin in rats, with no observed adverse effects to the 50% effective AUC or AUC effective, which is needed to reduce Aβ42 levels by 50% in rat brain (Rynearson et al. JEM, 2021). Given the recent success of Abeta immunotherapy in clinical trials, GSM776890 represents an oral molecule alternate to managing beta‐amyloid levels as means for preventing and treating AD.