bluuebunny/crossref_metadata_2025_split huggingface dataset:
Percentile‐based hippocampal volume MRI biomarker for distinguishing concomitant LATE and AD from pure LATE and pure AD
Authors: Mundada Nidhi S. , Lyu Xueying , McGrew Emily , Xie Long , Yushkevich Paul A. , Das Sandhitsu R. , Wolk David A 
Published: January 2025

AbstractBackgroundDue to the lack of in vivo molecular biomarkers for Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE), which commonly co‐occurs with Alzheimer’s disease (AD), it is challenging to identify patients with mixed AD/LATE pathology. Autopsy studies have suggested that AD patients with greater hippocampal atrophy are disproportionately enriched in having concomitant LATE. Here we define the lower quartile of hippocampal volume as a biomarker of possible LATE with AD.MethodWe identified 164 cognitively impaired participants from ADNI who had structural MRI, amyloid‐PET, and tau‐PET within 365 days. Patients were grouped based on hippocampal volume quartiles (adjusted for age and intracranial volume) and amyloid‐PET‐status into suspected 1) AD‐only (volume>50th‐percentile, amyloid‐positive), n = 100, 2) LATE‐only (volume<25th‐percentile, amyloid‐negative), n = 14, 3) AD+LATE (volume<25th‐percentile, amyloid‐positive), n = 50. 250 cognitively normal, amyloid‐negative participants were also included. Patterns of atrophy were examined to assess whether the AD+LATE group had features suggestive of LATE beyond hippocampal atrophy.ResultSuspected‐AD+LATE group had lower MMSE, CDR, and hippocampal volume and higher ITG‐tau‐SUVR compared to the suspected‐AD‐only group (Figure‐1A). Suspected‐AD‐only group showed predominant posterior hippocampal atrophy whereas LATE showed a more severe anterior hippocampal atrophy (Figure‐1B/2B). When compared to the AD‐only group, suspected LATE‐only and AD+LATE groups showed significantly lower thickness in ERC, PHC, BA35, BA36 (Figure‐2A); there were no differences between LATE‐only and AD+LATE groups. Suspected‐AD+LATE group showed features suggestive of LATE in prior work (Figure‐2B). Whole brain analysis demonstrated that in comparison to controls the suspected‐AD‐only group showed lower thickness in typical AD regions (posterior hippocampus and temporoparietal regions), suspected‐LATE‐only group showed lower thickness in more anterior MTL regions including temporal pole consistent with LATE pathology, whereas suspected‐AD+LATE group showed lower thickness in both AD‐ and LATE‐like regions (Figure‐3A). Assessing neurodegeneration driven due to non‐tau factors by controlling for ITG‐tau‐SUVR revealed similar atrophy patterns for both suspected LATE‐only and AD+LATE groups compared to the AD‐only group. Both groups showed decreased thickness isolated to anterior hippocampus extending into temporal pole (Figure‐3B).ConclusionUsing a simple hippocampal volume percentile‐based metric may enrich in patients with concomitant LATE on the AD continuum and could potentially be examined in the context of clinical trials and anti‐amyloid therapies.
Associations between deep category fluency phenotyping and early tau aggregation in the medial temporal lobe
Authors: Quenon Lisa , Leroy Emmanuelle , Clec'H Mélanie Le , Scemama Eva , Huyghe Lara , Colmant Lise , Salman Yasmine , Gérard Thomas , Malotaux Vincent , Dricot Laurence , Lhommel Renaud , Ivanoiu Adrian , Hanseeuw Bernard J 
Published: January 2025

AbstractBackgroundSemantic processing relies on temporal brain regions, including medial temporal lobe (MTL) structures, that are the first to be affected by tau pathology in Alzheimer’s disease (AD). A widely used task to assess semantic memory is the category fluency. Performance on this task was demonstrated to be impaired since the prodromal stage of AD and associated to the structural integrity of the MTL. However, the associations between category fluency measures and MTL tau burden have been rarely explored at the early stages of the disease.MethodSeventy‐five participants underwent [18F]MK6240 tau‐PET, magnetic resonance imaging and cognitive assessment including category fluency (animals, 2 minutes). Amyloid‐b (Ab) status was determined with lumbar punction or [18F]Flutemetamol Aβ‐PET (Ab+ for cerebrospinal fluid Ab level<437pg/ml or Centiloid≥20). Participants included 33 Ab‐ cognitively normal (CN), 15 Ab+ CN and 27 Ab+ MCI individuals (Table 1). In addition to the category fluency total score, the mean cluster size (cluster = group of words that are sequentially produced and all contained within a subcategory such as birds), the number of subcategories evoked (aggregating semantically related clusters), the mean size of subcategories and the number of switches between clusters were calculated. Associations between these metrics and MTL tau burden were assessed using Spearman‐rank coefficients and generalized linear models adjusting for age, sex and education.ResultOver the entire sample, associations were found between the MTL tau burden and the total score (rs = ‐0.44, p<.001, Figure 1), the mean cluster size (rs = ‐0.29, p = .047), and the mean size of subcategories (rs = ‐0.40, p = .002), even when controlling for age, sex and education (b = ‐5.06, SE = 1.62, p = .003; b = ‐0.33, SE = 0.16, p = .039; b = ‐0.46, SE = 0.15, p = .003, respectively). The number of switches (rs = ‐0.13, p = 1.0) and the number of subcategories (rs = ‐0.13, p = 1.0) were not associated to the MTL tau burden.ConclusionMTL tau burden was equivalently associated to the category fluency total score and two metrics relying more purely on semantic memory (mean size of clusters and subcategories). Given its critical role in conceptual knowledge and its involvement in the earliest stage of tauopathy, future work will analyze the associations between tau burden in the (peri)rhinal cortex and the category fluency metrics.
Advanced Imaging Modalities for ARIA Detection and Treatment Efficacy Monitoring in Lecanemab Therapy for Alzheimer’s Disease: A Collaborative Prospective Study
Authors: Okafor Jude‐Patrick Nnamdi , Stefanko Jacob , Jana Nayid , McCullough Austin A. , Jarman Stephen , Banks Jessica N , Joseph‐Mathurin Nelly , Knopp Edmond , Benzinger Tammie L.S. 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) poses a substantial healthcare challenge. Current immunotherapy targeting beta‐amyloid (Aβ) while representing a significant advancement, may be accompanied by potential complications such as amyloid‐related imaging abnormalities (ARIA). ARIA monitoring via high‐field MRI encounters logistical hurdles, exacerbated by regulatory demands for frequent MRI surveillance. This study investigates the integration of a portable ultra‐low field MRI into AD patient monitoring during immunotherapy to optimize ARIA detection, overall workflow and treatment outcomes.MethodThis prospective observational study recruits clinical patients with mild cognitive impairment due to Alzheimer disease underlying evaluation and monitoring for anti‐amyloid monoclonal antibody therapy. Baseline pre‐therapy 3T MRI will serve as a reference for subsequent imaging assessments. Participants undergo Hyperfine Swoop MRI scans at 0.064 tesla alongside their baseline and subsequent sessions, encompassing T1‐weighted, T2‐weighted, FLAIR, and DWI‐ADC sequences.Monitoring extends for 12 months after the initial clinic visit, enabling real‐time treatment response evaluation. Each participant will undergo ∼5 paired imaging visits, according to the therapy FDA label.ResultEffectiveness of high‐field and low‐field longitudinal imaging sessions will be compared for detection and evaluation of moderate and severe ARIA‐E (edema). A randomized, blinded assessment approach will be used to evaluate differences in radiologist assessment and treatment plan between field strengths. Patient imaging workflow improvement will be assessed using a survey.ConclusionThe Hyperfine Swoop MRI, with its portability and accessibility, shows promise as a cost‐effective alternative to the standard 3T MRI with the significant value‐added benefit of optimization of workflow. Further research is needed to confirm these benefits in larger cohorts and assess long‐term reliability. Overall, our study highlights the potential of innovative imaging technologies in improving patient care, monitoring neurodegenerative diseases thereby establishing a more equitable scheme for patient care.
Analysis of machine learning algorithms to aid in the diagnosis of early‐stage dementia
Authors: Carvalho Thiago , Santana Maira 
Published: January 2025

AbstractBackgroundDementia, including Alzheimer’s disease, represents a growing challenge for public health, with early diagnosis being crucial to delay or even prevent progression to more severe forms of dementia, allowing individuals to maintain a healthy life for as long as possible. It also enables patients and their families to plan ahead for future care and needs. However, diagnosing in the pre‐dementia phase is quite challenging, as early symptoms can be subtle, and there is no single test that can definitively diagnose the disease; diagnosis is made through a combination of clinical evaluation, cognitive tests, and imaging exams. The use of machine learning algorithms emerges as a promising approach to identify diagnoses of mild cognitive impairment (MCI), offering the ability to identify complex patterns in patient data that may not be easily perceptible to healthcare professionals. Therefore, the aim of this study is to assess the performance of artificial intelligence algorithms in identifying early‐stage dementia from slices of magnetic resonance imaging represented by shape and texture features.MethodTo this end, an experiment was conducted using the Random Forest and Support Vector Machine (SVM) classification algorithms, carried out on a database composed of magnetic resonance images of 984 individuals, divided into three classes: Alzheimer’s disease, Mild Cognitive Impairment and Normal Cognition, with the intention of classifying among these three classes and attempting to predict which one a brain image would belong to.ResultThe results of the experiment revealed that SVM did not perform well, achieving a maximum accuracy of only 23.65%, regardless of the configuration used. On the other hand, Random Forest demonstrated promising performance, reaching a maximum accuracy of 56.08% with 150 trees.ConclusionHowever, it is important to note that despite the progress made, there are still significant challenges to be overcome in the quest for accurate and reliable methods for early diagnosis of dementia through magnetic resonance imaging.
8‐week cognitive training intervention leads to improved mnemonic discrimination performance and near transfer from objects to scenes stimuli
Authors: Iliopoulos Panagiotis , Rong Boyan , Molloy Eóin N. , Cichy Radoslaw Martin , Maass Anne , Düzel Emrah 
Published: January 2025

AbstractBackgroundEpisodic memory declines in old age. Successful memory relies on the process of mnemonic discrimination (MD) to establish distinct representations. However, the scope for improvement in older adults’ cognitive performance using cognitive training is poorly understood. Here we investigated whether cognitive training leads to improvement in MD and whether the benefits transfer across different stimulus types, tasks and cognitive functionsMethod112 older adults (age M = 67.96, SD = 3.86) completed an 8‐week web‐based MD training intervention divided into 3 groups: one group training with object stimuli (OG), one group training with scene stimuli (SG), one active control group. The training was based on the object‐scene MD task which involves differentiating similar objects and scenes (‘lures’; correct response: ‘new’) from repeated items ('repeats’, correct response: ‘old’). Stimuli were first presented in a 2‐back set‐size: the first two stimuli were new images, while each of the subsequent two could be either a lure or a repeat trial. Then set‐size increased progressively across the training. Pre‐ and post‐training, the subjects performed a behavioral session including the 2‐back object‐scene MD task and several other transfer tasks. The latter included the mnemonic similarity task (MST; i.e. a different MD task), a pattern completion, working memory, spatial learning, and navigation task.ResultOur results show a training‐induced improvement in the object‐scene MD task performance but not the MST. We found a bias‐corrected performance improvement (d prime) driven by the correct lures. Compared to the control group, the OG improved their MD performance in objects while the SG improved in scenes, but only the OG showed near transfer improvement to the non‐trained category (i.e. scenes). We found no significant training effect in other transfer tasks.ConclusionAn 8‐week cognitive training intervention led to MD improvement in the trained task. We found a same modality improvement with the OG improving in objects and the SG in scenes, and evidence of near transfer from object to scenes but not vice versa. Cognitive training can lead to MD improvement in older adults. Longer‐duration interventions are needed to assess far‐transfer effects.
The Role of Sex in Post‐Mortem Neuropathology and Cognitive Decline
Authors: Dowd Rowan , Kamal Farooq , Dadar Mahsa , Oliver Michael , Morrison Cassandra 
Published: January 2025

AbstractBackgroundFemales tend to exhibit more Alzheimer’s disease (AD) pathology and have more clinical symptoms compared to males with similar levels of pathology. Post‐mortem studies in patients with AD have revealed that neuropathology is related to cognitive decline trajectories before death. However, what remains unclear is the intersection between sex differences in post‐mortem pathology and cognitive decline. These sex differences remain unstudied and may provide important treatment options in reducing pathology and delaying cognitive decline.Method1978 participants (females = 1354) from the RADC RUSH dataset with diagnoses at death including cognitively normal, mild cognitive impairment, and dementia were included. Pathological variables included neurofibrillary tangles (NFT), tangles, Braak staging, amyloid, and hippocampal sclerosis. Linear mixed models examined the relationship between pathology at death and rate of global cognitive decline before death between males and females.ResultAt death, females exhibited higher NFT burden (p<.001), tangles (p<.001), and Braak staging (p<.001) compared to males. Neither amyloid nor hippocampal sclerosis differed between males and females. Both females and males rate of global cognitive change was negatively associated with NFT burden (p<.001), tangles (p<.001), Braak staging (p<.001), amyloid burden (p<.001), with higher levels of pathology associating with worse cognitive decline. Only females exhibited a negative association between hippocampal sclerosis and worse cognition (p<.001). Importantly, the relationships between pathology and cognition were stronger for females than males for all pathology measures (see Fig. 1 for Braak example). To ensure the differences in rate of cognitive change associated with pathology between males and females were not due to differences in age or amount of pathology, a secondary analysis was completed on a subsample of males and females matched based on age and level of pathology. Results obtained were similar in terms of significance and effect size indicating that females are more negatively affected by AD‐related pathology.ConclusionPost‐mortem pathology is strongly associated with cognitive decline before death, with the relationship being stronger in females than males. To mitigate cognitive decline and alleviate stress on the healthcare system, targeting females earlier in the lifespan with interventions such as lifestyle modification reduce disparities in sex differences in AD incidence.
The X chromosome in Alzheimer’s Disease
Authors: Belloy Michael E. , Guen Yann Le , Stewart Ilaria , Herz Joachim , Sherva Richard , Zhang Rui , Merritt Victoria , Panizzon Matthew S. , Hauger Richard L. , Gaziano J. Michael , Logue Mark W. , Napolioni Valerio , Greicius Michael D ,   the VA Million Veteran Program
Published: January 2025

AbstractBackgroundThe X‐chromosome remains largely unexplored in Alzheimer’s disease (AD). To address this gap, we performed the first large‐scale X chromosome‐wide association study (XWAS) of AD.MethodThe study overview is shown in Figure 1A. We performed a meta‐analysis of XWAS in case‐control, family‐based, population‐based, and longitudinal AD‐related cohorts from the US Alzheimer’s Disease Genetics Consortium (ADGC) and Alzheimer’s Disease Sequencing Project (ADSP), the UK Biobank (UKB), the Finnish health registry (FinnGen), and the US Million Veterans Program (MVP). Genetic data were available from high‐density single‐nucleotide polymorphism (SNP) microarrays and whole‐genome sequencing (WGS). To identify potentially causal genes in associated risk loci, statistical colocalization was evaluated between the local genetic association signal for AD and the genetic association signal for molecular traits such as expression levels of genes within that locus (R‐v.4.2.1, coloc). We leveraged public datasets where quantitative trait loci (QTL) for expression and protein levels were available for the X chromosome in brain and non‐brain tissues.ResultThe XWAS included 1,152,284 non‐Hispanic White European ancestry subjects, including 138,558 cases (Figure 1A). 6 independent genetic loci passed X‐chromosome‐wide significance (Figure 1B), with 4 showing support for causal links between the genetic signal for AD and expression of nearby genes in brain and non‐brain tissues (Table.1). One of these 4 loci passed conservative genome‐wide significance, with its lead variant centered on an intron of SLC9A7 (OR = 1.054, 95%‐CI = [1.035, 1.075]) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes.ConclusionWe performed the first large‐scale XWAS of AD, which is simultaneously the largest genetic association study of AD to date. We identified several associated loci, with the strongest support for the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid beta accumulation. Overall, this study significantly advances our knowledge of AD genetics and may provide novel biological drug targets.
Evidence‐based Clinical Practice Guideline on the Use of Blood‐based Biomarkers in Alzheimer’s Disease: Presentation of Preliminary Evidence, and Opportunity for Public Comment
Authors: Hansson Oskar , Whitson Heather , Edelmayer Rebecca M. , Allen Laura A , Galasko Douglas R. , Karikari Thomas K , Okhravi Hamid , Paczynski Madeline , Schindler Suzanne E. , Suarez‐Calvet Marc , Teunissen Charlotte , Zetterberg Henrik , Mahinrad Simin , Pahlke Sarah , McAteer Mary Beth , Kahaleh Lara , Tampi Malavika 
Published: January 2025

AbstractBackgroundThe rapid development of blood‐based biomarkers (BBMs) has improved Alzheimer’s disease (AD) diagnostics with some tests now potentially suitable for clinical use. This aligns with the clinical availability of anti‐Aβ immunotherapies for early symptomatic AD, where BBMs can help address the increasing need for more rapid and early diagnosis. Clinical practice guidelines (CPG) can help guide healthcare professionals in incorporating BBMs into their clinical practice. The Alzheimer’s Association is collaborating with methodologists and a panel of 11 clinical and subject‐matter experts to develop a CPG for specialists, informed by a systematic review, on the use of BBMs for AD.MethodThe panel drafted several clinical questions prioritizing two questions on the use of BBMs in cognitively impaired or cognitively unimpaired individuals as the populations of immediate interest. Plasma p‐tau and Aβ biomarkers tests are index tests, and amyloid PET imaging, neuropathology, and CSF are reference standards. Experts in the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) approach are conducting a systematic review of the diagnostic accuracy of BBMs index tests by searching three databases (Pubmed, Embase, Cochrane Library) and will include assessments of the quality of collected evidence to inform the panel’s decision‐making process. Patients/caregivers and key external organizations will be engaged throughout.ResultThis session will cover preliminary evidence for answering the two clinical questions. At the time of abstract submission, the search strategy resulted in 880 titles/abstracts for the study selection process. Data abstraction, analysis, and evidence development are pending. Recommendations for answering clinical questions will be developed after July 2024, and all recommendations will be finalized and published by early 2025.ConclusionThe integration of BBMs into clinical care offers the potential to improve earlier and more accurate AD diagnosis for a broader patient population and expand access to new AD therapies. The development of evidence‐based CPGs is a critical step forward in optimizing and standardizing the clinical use of BBMs. As the field of AD diagnostics and treatment continues to evolve, this CPG on the use of BBMs for AD will expand and be regularly updated to include new target audiences/settings, patient populations, and associated evidence.
Implementing a biomarker‐enabled care pathway to accelerate identification of early‐stage Alzheimer’s disease in primary care
Authors: Borson Soo , Au Rhoda , Chodos Anna H , Gandy Sam E , Jain Holly , Kerwin Diana R. , Mintzer Jacobo , Monroe Stephanie , Robinson Delecia , Wilcock Donna M. , Mielke Michelle M. 
Published: January 2025

AbstractBackgroundNew blood‐based and digital biomarkers for Alzheimer’s disease (AD) make early detection possible at stages when novel, disease‐specific therapies are likely to be most effective. These approaches may offer less invasive, more cost‐effective alternatives to traditional methods such as cerebrospinal fluid (CSF) collection or positron emission tomography (PET) imaging for diagnosing and staging AD. Building care pathways leveraging blood‐based and digital biomarkers starts with understanding the current biomarker landscape and considering opportunities for widespread implementation in primary care clinical practice.MethodsA multidisciplinary team representing neurology, neuropsychology, geriatrics, primary care, epidemiology, laboratory programs, and patient advocacy was convened to review a summary of current biomarker research findings and discuss barriers and opportunities to implement biomarkers as part of an AD consensus‐driven clinical care pathway.ResultsThe emergence of biomarkers has shifted diagnosis from primarily clinical to a biological definition of AD. However, there is currently no consensus on where biomarkers fit within an AD care pathway and when they should be utilized in primary care or dementia specialist care settings.We found a relative paucity of published data on biomarker test accuracy in diagnosis outside tightly controlled research settings, limiting guidance around how results should be interpreted and managed in real‐world care settings. Evidence gaps are especially pressing for heterogeneous, diverse populations under‐represented in AD research.New biomedical therapies specific to the pathobiology of AD are driving research on blood and digital biomarkers to inform optimal ways to accelerate identification. As most individuals with AD are not evaluated by specialists, accurate and usable information about the place of biomarkers in the diagnosis and treatment of cognitive impairment must reach primary careConclusionsWith growing interest in the promise of non‐invasive biomarkers to improve detection, differentiation, and diagnosis of AD, new research is needed to generate real‐world evidence about their performance across populations, how to interpret results, and how best to use them in patient management. Effective educational strategies are needed to disseminate high‐quality evidence that engages primary care and healthcare delivery systems in implementing optimal clinical pathways. More detailed learnings for successful care pathway implementation will be shared.