bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardiometabolic profiles in children and adults with overweight and obesity and down syndrome
Authors: Oreskovic Nicolas M. , Baumer Nicole T. , Di Camillo Chiara , Cornachia Michelle , Franklin Catherine , Hart Sarah J. , Kishnani Priya S. , McCormick Andrew , Milliken Anna L. , Patsiogiannis Vasiliki , Pawlowski Katherine G. , Santoro Stephanie L. , Sargado Sabrina , Scoppola Vittorio , Torres Amy , Valentini Diletta , Vellody Kishore , Villani Alberto , Skotko Brian G.
Published: December 2022

Individuals with Down syndrome (DS) are at increased risk for being overweight/obese, but the associated cardiometabolic risk (CR) is not clear. Cross‐sectional anthropometric and clinical laboratory data from a multi‐site, international cohort of individuals with DS were analyzed to determine cardiometabolic risk by reporting observed distributions of cardiometabolic biomarkers in overweight/obese individuals with DS throughout the lifespan. Descriptive statistics and regression analyses by age categories determined the distributive percentiles for cardiometabolic biomarkers and tested for adiposity as a predictor of CR. Across seven DS clinics, data were collected on 240 patients between the ages of 3 and 63 years, with one quarter overweight and three quarters obese among children and nearly all adults being obese. In children and adults, most cardiometabolic biomarker profiles showed distributive values within normal ranges. Blood lipids were positively associated with body mass index (BMI) in children (high density lipid‐cholesterol, p = 0.01; low density lipid‐cholesterol, p = 0.02). Levels of hs‐CRP were elevated in both children and adults, with BMI positively associated with hs‐CRP in adults with DS (p = 0.04). Liver enzyme values were positively associated with BMI in children and adults. The data suggest that in contrast to the general population, in individuals with Down syndrome, being overweight and obese does not appear to confer a significantly increased risk for cardiometabolic disease by biomarker profile. Individuals with DS who are overweight/obese appear to have unique cardiometabolic profiles unrelated to adiposity, notable for increased hs‐CRP and normal HA1c levels.
Head‐to‐Head Comparison of Four Plasma Phospho‐Tau Immunoassays in the Neuropathological Diagnosis of Alzheimer’s Disease
Authors: Malek‐Ahmadi Michael H. , Ashton Nicholas J. , Karikari Thomas K , Beach Thomas G , Serrano Geidy E , Chen Yinghua , Chen Kewei , Ghisays Valentina , Hansson Oskar , Palmqvist Sebastian , Janelidze Shorena , Su Yi , Zetterberg Henrik , Dage Jeffrey L. , Blennow Kaj , Reiman Eric M.
Published: December 2022

Background

Plasma ptau is a promising indicator of amyloid‐β (Aβ) mediated tau pathophysiology. We previously characterized the ability of Lilly’s MesoScale Discovery (MSD)‐based plasma ptau217 and ptau181 assays to discriminate between those with and without the neuropathological diagnosis of Alzheimer’s disease (AD) in Banner research participants with near‐end‐of‐life blood samples and extensive postmortem neuropathological assessments. We now extend this work in a head‐to‐head comparison of those assays to the University of Gothenburg’s Single molecule array (Simoa)‐based plasma ptau181 and 231 assays.

Method

Assays were performed blindly in plasma samples acquired 1.0±0.7 years before death from up to 106 Banner research participants with and without cognitive impairment and different neuropathological diagnoses. ROC analyses were used to discriminate between those with and without the neuropathological diagnosis of AD and presence or absence of neuritic Aβ plaques. Spearman correlations were used to characterize their associations with mean cortical neuritic plaque counts and with mean cortical tau tangle counts in those with and without the diagnosis of AD or neuritic plaques.

Result

Lilly’s ptau217 assay was better than Lilly’s ptau181 and Gothenburg’s ptau231 and ptau181 assays in discriminating between the neuropathological diagnosis of Intermediate/High Likelihood versus Low Likelihood/No AD (respective AUCs=0.86, 0.67, 0.62 and 0.61), the diagnosis of High Likelihood versus Low Likelihood/No AD (AUCs=0.95, 0.83, 0.67 and 0.67), and presence or absence of neuritic Aβ plaques (AUCs=0.86, 0.70, 0.61 and 0.62). It also provided better indicators of mean cortical neuritic plaque (r’s=0.69, 0.35, 0.26 and 0.29) and tangle counts (r’s=0.73, 0.60, 0.19, ‐0.04) in those with the neuropathological diagnosis of AD or at least moderately frequent neuritic plaques (r’s=0.71, 0.59, 0.22, 0.01). The assays were not correlated with tangle counts in those without AD or neuritic plaques.

Conclusion

Lilly’s MSD‐based plasma ptau217 assay performed better than the other three ptau assays in the neuropathological diagnosis of AD, discriminating between those with and without neuritic Aβ plaques, and providing an indicator of Aβ‐related tau tangle burden. Banner Sun Health Research Institute's growing brain donation program resources could help characterize and compare blood‐based biomarkers in the neuropathological diagnosis of AD, Parkinson’s disease and related diseases.
Enhanced Machine Learning Classification of Cognitive Impairment with Multimodal Digital Biomarkers
Authors: Banks Russell E , Higgins Connor , Bates David , Gomes‐Osman Joyce Rios , Pascual‐Leone Alvaro , Tobyne Sean E
Published: December 2022

Background

Linus Health’s DCTclock™ is an FDA‐listed cognitive assessment solution capable of detecting early signs of cognitive decline. DCTclock digitizes the long‐standing pen‐and‐paper Clock Drawing Test (CDT) and captures a wide variety of cognitive and motor metrics during the entire drawing process. Multiple studies have validated the DCTclock’s ability to detect early cognitive impairment and improve on existing assessment methods (e.g., Souillard‐Mandar et al. 2015 & 2021, Rentz et al. 2021). Linus subsequently developed the Digital Clock and Recall (DCR™) assessment, which incorporates voice and delayed verbal recall alongside the DCTclock. The analysis below evaluated the added benefit of the DCR and the relationship between voice analytics and diagnosis.

Method

The DCR is being administered as part of the BioHermes‐Gap study. Data from 495 participants were used to correlate DCR or DCT with MMSE. A repeated‐measures ANOVA model was used to analyze speech and determine within‐subject differences between sessions (immediate repeat and delayed recall) on 40+ acoustic features extracted from 3‐word recall tasks of 664 older adults. Results were used to build Multilayer Perceptron Neural Networks (ANN) to assess the accuracy of combined acoustic features to classify cognitive status.

Result

DCR is more highly correlated with MMSE than the DCTclock (r=0.43 vs. 0.38). ANN results indicate that combining acoustic features with cognitive assessments achieves greater classification accuracy for healthy (AUC=0.95), MCI (0.93), and AD (0.97) groups than models including either acoustic features or cognitive assessments alone.

Conclusion

A multimodal machine learning investigation of cognitive state, DCR, which includes DCTclock and voice/speech features from delayed recall, increases the accuracy (sensitivity and specificity) of cognitive status classification.
What's in a name?
Authors: Doody Rachelle S.
Published: December 2022

Background

There is precedent in the AD field for confusion and dissonance due to the naming of clinical phenomena. Early on, Alzheimer's disease (AD) or Alzheimer's dementia could mean anyone with progressive dementia, and did not require the application of standardised criteria. As standardisation improved at the stage of dementia, the terms Mild Cognitive Impairment or Minimal Cognitive Impairment came into usage and the clinical conditions encompassed by these terms were variably named and defined in different nomenclature systems (eg., AAN, DSM, ICD) and required different criteria depending upon the definitions used by different academic working groups. A similar controversy now exists regarding the naming of individuals who have biological markers consistent with AD, but do not have any clinical symptoms or functional decline from baseline.

Method

Other speakers in this symposium will review the history and advocate for particular approaches to describing individuals who have AD biological markers bur are cognitively unimpaired. This presentation will respond to those arguments and bring in additional external perspectives from experience as a clinician treating patients, as a researcher performing non‐interventional trials, and a drug developer.

Result

The implications of naming the condition preclinical AD versus individuals at risk for AD will be explicated for clinical practice, general research, and clinical trials.

Conclusion

TBD.
Correlations and associations between fluid‐based and morphometric imaging biomarkers through interrogation and integration of data and analysis across two data platforms
Authors: Toga Arthur W. , Henscheid Nicholas , Pappas Ioannis , Cabeen Ryan P , Podichetty Jagdeep , Hobel Sam , Weber Christopher J. , Sivakumaran Sudhir , Romero Klaus
Published: December 2022

Background

The Global Alzheimer’s Association Interactive Network (GAAIN) and the Critical Path for Alzheimer’s Disease (CPAD) Consortium have undertaken a collaborative effort to establish a mechanism that can help evaluate the relationship between fluid‐based, morphometric imaging biomarkers and clinical trajectories of disease progression, across datasets and analyses pipelines housed by CPAD and GAAIN. Additionally, this collaboration will demonstrate the feasibility of bidirectional integration of data management models and will guide development of a federated image analysis pipeline model across these two platforms.

Method

To enable interoperability, GAAIN’s original architecture is expanded to accommodate the LONI brain structural imaging pipeline. Under this new framework, GAAIN researchers can initiate brain imaging‐related analyses on their servers directly from GAAIN’s graphical interface with the results integrating back into GAAIN for further analyses. Feasibility was demonstrated for the determination of correlations for CPAD’s biomarker and imaging volumetric data. GAAIN’s brain imaging pipeline was executed on CPAD data, allowing for quantification of volumetric images. In turn, blood and volumetric data were inserted in GAAIN allowing further evaluation and analyses.

Result

Based on the results, we provide guidelines for a future framework for a federated analysis model that can be utilized from GAAIN and CPAD to establish relationships between blood and brain markers. In this model, for a cohort of interest, analyses of relevant brain marker data can be remotely done in CPAD servers via GAAINs’ federated platform after which results can be inserted back to GAAIN alongside CPAD’s blood marker data. The full capabilities of this federated model will be explored in subsequent work.

Conclusion

As data sharing becomes increasingly prominent and mature, the partnership between GAAIN and CPAD will yield ever greater benefits and knowledge and will continue to grow and evolve in response to the changing Alzheimer’s disease landscape. As such, it represents a non‐exclusive door for researchers to make use of the data sets and advanced analytical tools and is intended to leverage the unique competencies of these organizations and lead to the continued evolution of bringing meaningful and high‐impact advances in Alzheimer’s disease.
From identification to implementation: state of the art in biomarkers for immune function in CSF and blood
Authors: Teunissen Charlotte E. , Boiten Walter , Hok‐A‐Hin Yanaika S.
Published: December 2022

Background

Brain immune activation, i.e. activation of microglia and astrocytes, is one of the earliest pathological features of Alzheimer’s disease (AD) pathology. It is likely a consequence of pathological aggregation of amyloid, and can have both detrimental and beneficial effects on multiple aspects of AD pathogenesis. Moreover, recent results show that peripheral immune activation may affect AD pathology and the progression of clinical symptoms as well. Accordingly, biomarkers of innate and adaptive immune activation, as measured in CSF and in blood, have been associated with pathologic status, cognitive decline, as well as increased risk of developing AD. Modulation of central and peripheral immune function offers a potentially promising therapeutic approach for treating AD. As such therapies continue to be developed, there will be an increasing need to noninvasively monitor the neuro‐immune response. If we want to target the brain immune‐cells, microglia or astrocytes, it is essential that we have biomarkers specifically tracing their activation and the concomitant pharmacological response. Developing blood based biomarkers for monitoring neuro‐immune activation is especially challenging given the abundance of immune proteins in blood which are often be indistinguishable from brain‐derived immune proteins.

Method

In this introductory presentation I will discuss recent developments in research to develop immune‐related fluid biomarkers.

Results

Recent proteomics studies and hypothesis‐driven approaches have detected promising changes in immune‐related biomarkers, reflecting either microglia (e.g. complement factors, sTREM2, sAXL) or astrocyte activation (GFAP, YKL‐40), in the CSF of AD patients, even in the earliest disease stages. For example, GFAP levels are increased in cognitively unimpaired persons with AD pathology and have prognostic value for cognitive decline. Using a proteomics approach, we identified clusters of patients with an increased CSF immune biomarker profile, indicating that these would benefit most from immune‐modulating therapy. In addition, recent RNA‐sequencing studies have shown disease related activation and senescence of microglia in both mice and man. We related these expression patterns to CSF proteomic datasets and revealed several potential biomarkers for disease‐associated microglia.

Conclusion

There are several interesting advancements in biomarker development for immune function that will be addressed in this FRS.
Suboptimal sleep efficiency and duration predicts rate of accumulation of Aβ‐ Amyloid in cognitively normal older adults
Authors: Pivac Louise N , Brown Belinda M , Sewell Kelsey R , Doecke James D , Villemagne Victor L , Dore Vincent , Weinborn Michael , Sohrabi Hamid R , Gardener Samantha L , Bucks Romola S , Masters Colin L , Rowe Christopher , Martins Ralph N , Rainey‐Smith Stephanie
Published: December 2022

Background

There is increasing evidence of a bidirectional relationship between suboptimal sleep and brain Aβ‐amyloid (Aβ) accumulation. Suboptimal sleep is suggested to both result from and contribute to the accumulation of brain Aβ. This study tested whether aspects of self‐reported sleep quality predict the longitudinal accumulation of brain Aβ.

Method

Linear mixed effect model analyses were conducted on 192 cognitively normal older adults (M = 73.8 years, SD = 5.8, 51.6% female). These individuals, drawn from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Ageing, had self‐reported sleep characteristics assessed at baseline and positron emission tomography‐determined brain Aβ burden measured over a minimum of three AIBL timepoints (range 33.3‐73.9 months). Analyses included random slopes and intercepts, interaction for apolipoprotein E (APOE) ε4 allele status and time, adjusting for sex and baseline age.

Result

Sleep duration of <5 hours and sleep efficiency of <65% both significantly forecast the longitudinal trajectory of Aβ accumulation in the whole cohort (sleep duration <5 hrs β = 4.70 ± 1.58, p = 0.003; sleep efficiency <65% β = 2.94 ± 0.91, p = 0.001) and in APOE ε4 non‐carriers (sleep duration <5 hrs β = 4.70 ± 1.53, p = 0.003; sleep efficiency <65% β = 2.90 ± 0.87, p = 0.001) but not in APOE ε4 carriers.

Conclusion

These findings indicate a role for self‐reported suboptimal sleep efficiency and duration in the accumulation of Alzheimer's disease neuropathology in cognitively normal individuals. Individuals with suboptimal sleep may benefit from an intervention to improve these sleep parameters to lessen future Alzheimer's risk. Our findings also suggest the potential utility of self‐report screening for sleep efficiency and duration as a predictor of risk of Aβ accumulation.
Impact of off‐target signal on longitudinal FTP quantification
Authors: Baker Suzanne L. , He Mark , Dominguez Pablo Aguilar , Landau Susan M. , Harrison Theresa M. , La Joie Renaud , Ward Tyler J. , Zhuang Kailin , Rabinovici Gil D. , Jagust William J.
Published: December 2022

Background

Despite off‐target signal, Flortaucipir (FTP) PET is useful for measuring tau in vivo. We previously showed in a cross‐sectional cohort of cognitively unimpaired (CU) amyloid negative (Aβ‐) individuals that the global cortical SUVR is highly correlated to putamen and thalamus SUVR, suggesting that there is substantial off‐target signal in the cortex. Here we explore the impact on off‐target signal on longitudinal FTP quantification.

Methods

A group of CUAβ‐ subjects scanned through ADNI and Lawrence Berkeley National Laboratory (LBNL) were used to define corrections for off‐target signal (derivation cohort) which were then applied to a separate longitudinal cohort of CUAβ‐, CUAβ+, and cognitively impaired (CI) Aβ+ subjects (Table 1). SUVRs were calculated using two possible reference regions (inferior cerebellar gray and supratentorial white matter) with or without partial volume correction (PVC). The relationship of off‐target signal between thalamus and cortex was estimated as the regression between thalamus and Braak IV‐VI in CUAβ‐ (figure 1) and then applied in the longitiduinal cohort to temporal meta and Braak ROIs to regress out the influence of the thalamic signal (figure 2). Hedges’ effect size was calculated between diagnosis groups with and without regressing out thalamic signal in the LBNL longitudinal cohort to examine effects in a smaller cohort.

Results

There was a significant correlation in cross‐sectional CUAβ‐ subjects between thalamus and Braak IV‐VI regardless of reference region and PVC (Figure 1). This correlation increased when comparing annual change between thalamus and Braak IV‐VI in longitudinal CUAβ‐ subjects (Figure 3). There was no significant difference across diagnosis groups in the longitudinal cohort between either baseline thalamus or annual change in thalamus. Correlation between annual change in thalamus and entorhinal cortex or meta temporal ROI were often significant (12/12 for inferior cerebellar gray reference region, 8/12 for white matter reference region, Figure 4). Effect size between diagnosis groups increased as a result of regressing out thalamic signal for all temporal meta ROI comparisons and for CUAβ+>CUAβ‐ and CIAβ+>CUAβ‐ in the entorhinal cortex (Figure 5).

Conclusion

When taking into account off‐target signal, it is possible to improve effect size of longitudinal FTP by ∼12%.
From FINGER to MET‐FINGER: metformin and lifestyle intervention for multimodal precision prevention of dementia
Authors: Kivipelto Miia , Barbera Mariagnese , de Jager Celeste A , Lehtisalo Jenni , Levak Nicholas , Middleton Lefkos T , Price Geraint J , Rydström Anders , Thunborg Charlotta , Mangialasche Francesca , Ngandu Tiia , Solomon Alina
Published: December 2022

Background

The positive results of the landmark Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability ‐ FINGER, 2‐year lifestyle‐based intervention and up to 11 years follow‐up ‐, followed by the Multimodal Preventive Trial for Alzheimer’s Disease ‐ MIND‐ADmini, 6‐month lifestyle‐based + medical food, up to 1‐year follow‐up ‐, provided the foundation to advance multimodal trials for dementia prevention within the World‐Wide FINGERS (WW‐FINGERS) network. Innovative trials should involve tailored approaches, combining non‐pharmacological and pharmacological interventions, to optimize interventions´ adherence and efficacy.

Method

Through a drug‐repurposing approach, metformin has been identified as a potential disease‐modifying drug for Alzheimer´s disease (AD) and dementia in subjects without type‐2 diabetes, with a robust pharmacological safety profile. Analysis on genetic factors (APOE, AD Polygenic‐Risk‐Score) and intervention effects from the FINGER trial indicated clear cognitive benefits in participants with genetic susceptibility to AD and dementia. Feasibility data (adherence, retention rate) from FINGER and MIND‐ADmini, including extended follow‐up data analysis, have informed the upgrade of the lifestyle‐based intervention implemented in MET‐FINGER.

Result

An update on the trial status will be presented. The MET‐FINGER phase‐IIb trial population includes an APOE‐enriched population of 600 subjects aged 60‐79 years, with increased risk of dementia due to modifiable risk factors. Participants are recruited in three countries (Finland, Sweden, United Kingdom), and randomized to either an upgraded FINGER lifestyle‐based intervention, alone or in association with metformin (up to 2000mg/day), or the reference group, which follows a self‐guided lifestyle program. MET‐FINGER trial outcomes are harmonized with WW‐FINGERS guidelines, and include cognition and biological measures to detect disease‐modifying effects of metformin.

Conclusion

MET‐FINGER pioneering trial leverages and expands on successful experiences from WW‐FINGERS core trials, embodying the next generation of clinical trials for dementia risk reduction and prevention within the framework of precision prevention. The MET‐FINGER trial protocol is the first in its kind, providing the basis for forthcoming trials combining non‐pharmacological and pharmacological interventions. MET‐FINGER results can inform AD drug development and reduce intervention failure rate of new trials.
Age‐at‐Onset and APOE Related Heterogeneity in the Clinical, Plasma Biomarker, and Neuropathologic Presentation of Alzheimer’s Disease (AD)
Authors: Smirnov Denis S. , Salmon David P. , Galasko Douglas R. , Goodwill Vanessa OF , Hansen Lawrence A , Edland Steven D. , Hiniker Annie OF
Published: December 2022

Background

Patients with sporadic early‐onset AD (EOAD) show less pronounced memory impairment, faster cognitive decline, and greater likelihood of focal cortical syndromes than those with later onset (LOAD), while often lacking the APOE ε4 allele classically associated with younger onset. This heterogeneity could arise from differences in the distribution of AD pathology or presence of concomitant pathologies.

Method

We examined clinical and cognitive heterogeneity in relation to age‐at‐onset, APOE genotype, and concomitant neuropathology (Lewy body, TDP‐43, and vascular) in patients with autopsy‐confirmed severe AD from the National Alzheimer’s Coordinating Center database (N=1750). In patients from the UCSD Alzheimer’s Disease Research Center (N=121) we examined how age‐related heterogeneity relates to differences in distribution of neurofibrillary tangle (NFT) pathology and plasma biomarkers of AD.

Result

Age‐at‐onset distribution in APOE ε4‐ patients was bimodal with best separation at age 63. Patients with EOAD (age ≤63) had faster cognitive and functional decline than LOAD regardless of APOE genotype; and were more likely to present with nonmemory cognitive complaints (OR=5.56, 99%CI: 3.32‐9.39), show greater executive dysfunction (β=2.59 SD, 99%CI: 2.10‐3.09), and receive a non‐AD clinical diagnosis (OR=1.54, 99%CI: 1.19‐1.97), particularly for ε4‐ EOAD (p’s<0.01, APOE × age‐at‐onset interactions). Despite this atypicality, groups did not differ in their high rates of AD biomarker positivity, and ε4‐ EOAD patients were most likely to have pure AD without concomitant pathology. TDP‐43 (OR=0.37; 99%CI: 0.18–0.72) and microvascular (OR=0.65; 99%CI: 0.47–0.88) pathology were less common in EOAD, while Lewy pathology was more common in ε4+ (OR=1.48; 99% CI, 1.02–2.17). Midfrontal NFT density was higher in EOAD than LOAD (β= 0.87 SD, 99%CI: 0.44‐1.29). Greater hippocampal NFT density was associated with APOE ε4+ (β=0.49 SD, 99%CI: 0.02‐0.96). Mediation analyses suggest that differences in midfrontal/hippocampal NFT ratio, rather than concomitant neuropathology, mediate the atypical cognitive profiles and decline of EOAD (p<0.01).

Conclusion

A relatively more neocortical NFT distribution, rather than concomitant non‐AD pathology, accounts for the atypical, non‐memory dominant clinical presentation and rapid progression in EOAD. This suggests that selective cortical vulnerability may explain the earlier‐than‐expected onset and atypical profile in these individuals without the APOE ε4 risk allele.
Verbal Fluency Performance in Older Adults on a Novel Computerized Test Battery
Authors: Baldo Juliana , Chok Jas M. , Lwi Sandy J. , Schendel Krista , Herron Tim , Curran Brian , Hall Kathleen , Blank Michael , Williams Garrett , Geraci Kristin , Pebler Peter , Sucich Gabriel , Woods David L.
Published: December 2022

Background

Previous studies have suggested that impaired verbal fluency is a sensitive measure of semantic impairment in dementia that appears several years prior to diagnosis. This early impairment has been associated with neural changes and altered activation in key regions of bilateral temporal and frontal cortex.

Method

In the current study, we report verbal fluency findings from a large group of healthy older adults (n = 270, ages 56–89) on a new computerized neuropsychological battery that utilizes advanced automatic speech recognition and transcription software. In an ongoing longitudinal study, we are testing healthy older participants on the California Cognitive Assessment Battery (CCAB) every six months for three years, in order to track changes in cognition associated with aging, including evolution of mild cognitive impairment (MCI) and dementia. The CCAB includes six semantic categories: Animals, vegetables, countries, sports, furniture, and fruit. Participants are given one minute per category to generate as many exemplars as possible. Online speech‐to‐text transcription was implemented using consensus automatic speech recognition (CASR) software, which utilizes six different speech recognition systems and chooses the most common transcription.

Result

Overall verbal fluency performance was significantly predicted by age. However, this effect depended on the semantic category. For example, females and more educated participants generated more exemplars for the category “countries.”

Conclusion

Findings from the current study enhance understanding of aging effects on verbal fluency and serve as a critical baseline against which to monitor alterations in performance that coincide with the development of MCI and dementia in older adults.
Identification of sex‐specific genetic variants associated with tau‐PET
Authors: Wang Xin , Broce‐Diaz Iris , Deters Kacie D , Fan Chun Chieh , Banks Sarah J.
Published: December 2022

Background

Abnormal tau deposition is an important pathological feature of AD. Important sex differences exist, with women showing greater tau deposition along the AD continuum compared to men. Our group has previously shown sex differences in the genetic risk associated with AD. However, whether specific genetic variants are associated with sex differences in tau aggregation remains unknown. This study aims to identify sex‐specific genetic variants associated with tau deposition.

Method

We included 493 subjects (women n = 246, men n = 247) from the ADNI‐3 study with genotyping data and [18F]Flortaucipir tau PET data. Genetic data underwent standard quality control procedures to remove single nucleotide polymorphisms (SNPs) with more than 5% missingness, failing the Hardy–Weinberg equilibrium test at p = 1 × 10−6 and minor allele frequency < 1%. Participants were all white and included irrespective of clinical diagnosis (CN, MCI and AD). We focused our analysis on genetic variants within 10 genes previously shown to have sex‐dependent effects in AD to reduce the burden of multiple comparisons: BIN1, MS4A6A, DNAJA2, FERMT2, APOC1, APOC1P1, FAM193B, C2orf47, TYW5, CR1. One‐way multivariate analysis of variance (MANOVA) was applied to identify genetic variants associated with tau PET data in three ROIs (composite regions of Braak1, Braak34 and Braak56 stages) in women and men separately. We controlled for age, scanner, amyloid status, APOE ε4 carriership, diagnosis (CN vs MCI vs AD), and the first 20 genetic principal components to adjust for population stratification. Bonferroni correction was applied within each gene based on the number of SNPs tested.

Result

Table 1 shows the significant genetic variants associated with tau PET. We identified three novel genetic loci associated with tau deposition specifically in women: DNAJA2 rs79711283, FERMT2 rs113357081 and TYW5rs74614106. In men, three loci within CR1: rs115096248, rs113698814, rs78150633 were found significantly associated with tau burden.

Conclusion

Our findings discovered sex‐specific genetic variants associated with tau deposition independent of APOE ε4, amyloid and clinical diagnosis. These results provide potential gene targets for understanding the mechanism of sex‐specific tau aggregation and developing sex‐specific gene‐guided precision prevention or therapeutic interventions for AD.
Associations of Amyloid, White Matter Hyperintensities, and Hippocampal Volume with Cognitive Trajectories in the Oldest‐Old: The 90+ Study
Authors: Wang Jingxuan , Ackley Sarah F , Woodworth Davis C. , Sajjadi S. Ahmad , Fletcher Evan , DeCarli Charles S. , Glymour M. Maria , Kawas Claudia H. , Corrada Maria M.
Published: December 2022

Background

Amyloid pathology, vascular disease pathology, and hippocampal atrophy are associated with cognitive trajectories in older adults. However, there is almost no prior evidence on how these pathologies influence cognition in the oldest‐old.

Method

We included 216 individuals from The 90+ Study, a longitudinal study of aging and dementia in people aged 90 years and older, who had 18F‐florbetapir PET and MRI imaging. We examined the association of amyloid, white matter hyperintensities (WMH) volume, and hippocampal volume (HV) with baseline cognition and longitudinal cognitive decline. Amyloid burden was measured using the standardized uptake value ratio (SUVR) in the precuneus/posterior cingulate with white matter mask as reference. WMH volume and HV were normalized by intracranial volume (IV) and normalized WMH were log‐transformed. SUVR and HV for each individual were Z‐scored using the sample mean and standard deviation. Global cognitive performance was measured by Mental State Examination (MMSE) and modified MMSE (3MS) tests, repeated every six months. We defined baseline (time=0) as the visit closest to the PET imaging and included all visits starting from one year before baseline (time=‐1). We used linear mixed‐effects models with a random intercept to estimate the effect of pathologies on cognitive trajectories. All models included baseline age, sex, education, APOE‐ε4, time, time squared, amyloid, WMH, HV, and interactions between linear time and pathology variables.

Result

At baseline, participants were 93.2 years old on average, 65.3% were females, 10.6% were APOE‐ε4 carriers, and 66.2% had normal cognition (Table 1). Higher HV was associated with higher MMSE and 3MS scores at baseline. Both lower amyloid burden and higher HV were associated with slower rate of cognitive decline longitudinally. WMH was not associated with baseline cognition or cognitive trajectory. Parameter estimates are shown in Table 2 and illustrative cognitive trajectories predicted for a 93.2‐year‐old female with APOE‐ε4 alleles and a college degree predicted at varying degrees of amyloid, HV, and WMH are shown in Figure 1.

Conclusion

Amyloid burden and HV are associated with longitudinal cognitive trajectories, highlighting the utility of amyloid and HV in predicting future cognitive decline for the oldest‐old.
Life’s Simple 7 cardiovascular risk score and rate of cognitive decline in preclinical dementia
Authors: Speh Andreja , Payton Nicola Maria , Kramberger Milica G. , Grande Giulia , Qiu Chengxuan , Winblad Bengt , Fratiglioni Laura , Bäckman Lars , Laukka Erika J
Published: December 2022

Background

We investigated whether vascular risk factors (VRFs), assessed with the Life’s Simple 7 (LS7) score, are associated with rate of cognitive decline in the preclinical dementia phase. We sought to test whether (1) poor LS7 further accelerates rate of cognitive decline in preclinical dementia or (2) the dementia process itself overshadows potential effects of LS7.

Method

This population‐based study included 1,449 participants aged ≥ 60 years (M = 69.99, SD = 9.25) from the Swedish National Study on Aging and Care‐Kungsholmen (SNAC‐K). Participants aged < 78 years at baseline (M = 65.03) were categorised into a young‐old group and those ≥ 78 years (M = 82.61) into an old‐old group. An extensive cognitive test battery (episodic memory, semantic memory, verbal fluency, and perceptual speed) was administered across 12 years. VRFs were assessed with the Life’s Simple 7 (LS7) score at baseline and included four behavioral (smoking, diet, physical activity, and body mass index) and three biological (plasma glucose, total serum cholesterol, and blood pressure) metrics. Participants were categorised into having poor or intermediate/optimal cardiovascular health. Preclinical dementia was defined as being dementia‐free at baseline and diagnosed with dementia (DSM‐IV criteria) at one of the follow‐up assessments. Level and change in cognitive performance as a function of LS7 categories and future dementia status were determined using linear mixed‐effects models.

Result

Participants in a preclinical dementia phase were more likely to have a poorer LS7 score initially compared to those who remained dementia‐free (p = 0.023). For young‐old individuals, poor diet was associated with an accelerated perceptual speed decline (β = ‐0.05, 95% CI ‐0.08 to ‐0.02) and a poor plasma glucose score was associated with faster rates of verbal fluency (β = ‐0.019, ‐0.09 to ‐0.01) and global cognitive (β = ‐0.028, ‐0.06 to 0.00) decline in preclinical dementia.

Conclusion

The association between VRFs and cognitive decline was most pronounced in young‐old individuals in a preclinical phase of dementia and driven mostly by diet and plasma glucose. Poor cardiovascular health may be associated with further acceleration of cognitive decline in preclinical dementia.
Differential effects of age and sex on medial temporal lobe networks revealed by longitudinal analyses across the adult lifespan
Authors: Chauveau Léa , Landeau Brigitte , Dautricourt Sophie , la Sayette Vincent De , Chetelat Gael , de Flores Robin
Published: December 2022

Background

The medial temporal lobe (MTL) is extensively connected to the rest of the brain through two specific networks which are particularly affected in Alzheimer’s disease (AD): the anterior‐temporal (AT) and posterior‐medial (PM) systems. As the specific and respective effects of age and sex on the functional integrity of these networks are still largely unknown, we sought to fill this gap using longitudinal data spanning the entire adult life.

Method

Longitudinal data from 215 cognitively unimpaired adults (aged 19‐85, including 113 females, followed‐up up to 47 months, 419 scans) were analysed. Seed‐based analyses were applied to resting‐state functional magnetic resonance imaging to generate connectivity maps (seeds: the perirhinal cortex for AT and the parahippocampal cortex for PM). The AT and PM networks were defined by comparing baseline maps from adults younger than 40 using a paired permutation t‐test with threshold‐free cluster enhancement (TFCE) and familywise error (FWE) correction (p<.05) (Figure 1). These masks were then used to extract the mean functional connectivity (FC) for each participant. The interaction effects between network, age and sex were investigated using linear mixed models.

Result

There was a significant interaction between age and networks (p<.001), with a decrease of FC with age in PM and an increase in AT (Figure 2). Sex differences were also observed within these two systems (p<.001), with males exhibiting higher FC than females in AT but lower FC in PM (Figure 3). Age‐related trajectories were not modulated by sex differences (p>.05) and were best described by a linear relationship according to model comparison testing different polynomials.

Conclusion

By encompassing the entire adult lifespan and assessing longitudinal changes, our study provides strong support that the two MTL networks display differential alterations in the context of aging, as well as sex differences. Since MTL connectivity has been described as particularly affected in the early stages of AD, and age and sex are risk factors, these findings may be helpful to enhance the clinical utility of such biomarkers for the early detection of AD‐related changes.
Steps towards the implementation of amyloid‐PET in memory clinics: AMYPAD Diagnostic and Patient Management Study
Authors: Altomare Daniele , van Maurik Ingrid S. , Caprioglio Camilla , Barkhof Frederik , Collij Lyduine E. , Scheltens Philip , van Berckel Bart NM , Alves Isadora Lopes , Garibotto Valentina , Moro Christian , Delrieu Julien , Molinuevo Jose Luis , Grau‐Rivera Oriol , Gispert Juan Domingo , Drzezga Alexander , Jessen Frank , Nordberg Agneta K , Walker Zuzana , Demonet Jean‐François , Gismondi Rossella , Farrar Gill , Stephens Andrew W , Berkhof Johannes , Frisoni Giovanni B
Published: December 2022

Background

Amyloid‐PET allows the assessment of amyloid deposition, one of the main hallmarks of Alzheimer’s disease. However, in most countries, this exam is not routinely used in clinical practice. Several studies have assessed physician‐centered outcomes, yet often without a randomized study design. In addition, the choice to reimburse amyloid‐PET depends also on its cost‐effectiveness and on the safety of the procedure of disclosure.

Method

We assessed physician‐centered outcomes, cost‐effectiveness, and amyloid‐PET result disclosure in the AMYPAD‐DPMS cohort. Participants were memory clinic patients with subjective cognitive decline plus (SCD+), mild cognitive impairment (MCI) or dementia from 8 European memory clinics. They were randomized into three study arms: ARM1, amyloid‐PET performed early in the diagnostic workup (within 1 month); ARM2, late in the diagnostic workup (after 8±2 months); or ARM3, if and when the managing physician chose to. To assess cost‐effectiveness, we collected information on participants’ use of healthcare resources (through patient diaries) and assessed health‐related outcomes (e.g. EQ‐5D‐5L, ICECAP‐O, Brief COPE, global cognition, anxiety, and depression) at different time points. Impact of disclosure in SCD+ was assessed through the collection of the Impact of Event Scale – Revised (IES‐R) questionnaire and the assessment of anxiety and depression (both before and after disclosure).

Result

88% of ARM3 participants underwent amyloid‐PET within 3 months, and the average time from baseline to prescribe amyloid‐PET was 46 (IQR=58) days. We observed that, after 3 months, a diagnosis with very high confidence (≥90%) was more frequent in participants who underwent an early amyloid‐PET (ARM1: 40%, 109/272) and in those for whom amyloid‐PET could be freely prescribed by the managing physicians (ARM3: 37%, 97/261) as compared to those who had not undergone amyloid‐PET yet (ARM2: 11%, 30/260; p<0.001). More than 2500 patient diaries and more than 100 IES‐R have been collected throughout the study. Preliminary results on health economics and impact of amyloid‐PET result disclosure in SCD+ will be presented.

Conclusion

Our results suggest that an early amyloid‐PET has a relevant clinical impact. Results on its cost‐effectiveness and the impact of disclosure of the result on cognitively unimpaired individuals might further contribute to its introduction into clinical practice.
Associations of Sensory and Motor Functions in Midlife with Longitudinal Blood‐Based Biomarker Levels of Alzheimer’s Disease and Neurodegeneration
Authors: Merten Natascha , Pinto Alex A , Paulsen Adam J , Schubert Carla R , Chappell Richard J. , Chen Yanjun , Hancock Laura M , Engelman Corinne D , Cruickshanks Karen J
Published: December 2022

Background

Dementia has a long preclinical phase and pathological fluid biomarker levels change decades before clinical symptoms. Thus, early detection of people at risk for neurodegenerative and pathological changes, especially in midlife, might improve future treatments and preventions. Sensory and motor changes are common in aging adults and may be early markers of neurodegeneration since they are associated with cognition and risk factors of neurodegeneration. However, their associations with blood‐based neurodegenerative and AD biomarkers are not yet known. We aimed to determine if midlife sensory and motor functions are associated with long‐term changes in blood‐based biomarkers of neurodegeneration and AD (neurofilament light chain(NfL), total tau(TT), and amyloid beta(Aβ)).

Method

This longitudinal study is based on n=1529 (54% women, mean age 49years) Beaver Dam Offspring Study (BOSS) participants. The BOSS started in 2005 and had 5‐year and 10‐year follow‐up exams. We assessed sensory (pure‐tone audiometry, contrast sensitivity, olfactory identification) and motor (Grooved Pegboard) function, plus multiple potential confounding risk factors at baseline. NfL, TT, Aβ42, and Aβ40 levels were analyzed in serum samples from all three waves (SIMOA, Quanterix). We used linear mixed‐effects models with baseline hearing, vision, olfaction, and motor function as determinant and repeated biomarker levels as outcome and adjusted for age, sex, education, random intercept, random slope (if model fit was improved), and other confounders. NfL and TT were log‐transformed. Due to sex interactions, Aβ42/Aβ40 models were sex‐stratified.

Results

Overall, NfL increased 3% and TT 1% per year. Aβ42/Aβ40 decreased 0.5/year in women and 0.24/year in men. Individuals with hearing and vision impairment showed faster NfL level increase over time (0.8%/year; CI 0.3,1.4;p=.004; 0.5%/year; CI ‐0.1,1;p=.09; respectively). Worse motor function was associated with faster NfL increase (0.4%/year per 20s test time; CI 0.2,0.7;p<.001). These effects compared to effects of 2‐3 months of aging. There were no significant associations with Aβ42/Aβ40 or TT.

Conclusion

We found associations between midlife sensory and motor functions and long‐term changes in NfL levels, a non‐specific marker of neurodegeneration, while there were no associations with AD‐specific biomarkers. Future studies with longer follow‐up should determine if sensory and motor changes are more reflective of general neurodegenerative than AD‐specific pathology.
Medial temporal atrophy in posterior cortical atrophy and its relationship to the cingulate island sign
Authors: Josephs Kennedy A , Pham Nha Trang Thu , Graff‐Radford Jonathan , Machulda Mary M. , Lowe Val J. , Whitwell Jennifer L
Published: December 2022

Background

Posterior cortical atrophy (PCA) is associated with hypometabolism on FDG‐PET and atrophy on MRI in the parietal and occipital lobes, and patients often show the cingulate island sign (CIS) whereby posterior cingulate metabolism is relatively spared compared to the precuneus and cuneus. It has been hypothesized that medial temporal sparing may be related to CIS in PCA. We aimed to assess the severity of medial temporal atrophy in PCA and determine whether the presence of a CIS is related to medial temporal sparing.

Method

Fifty‐five PCA patients underwent a 3T volumetric MRI and FDG‐PET. The degree and symmetry of medial temporal atrophy on MRI was visually assessed in both hemispheres using the five‐point Scheltens scale (0=normal; 1=mild; 2=moderate; 3=marked; 4=severe). Visual assessments of FDG‐PET coded the presence/absence of a CIS and whether the CIS was symmetric or asymmetric. Hippocampal volumes and a quantitative CIS were also measured. Associations between medial temporal atrophy scores and clinical measures were assessed using linear regression correcting for age.

Result

Medial temporal atrophy was most commonly mild (38% on the right, 40% on the left), followed by moderate (35% on the right, 29% on the left), and then no atrophy (18% on right, 25% on left). Marked or severe atrophy was only observed in 9% of patients on the right and 5% of patients on the left. Atrophy was asymmetric in 55%, and when asymmetric was most commonly worse on the right (76%). Greater medial temporal atrophy was associated with older age (p<0.001) and worse verbal episodic memory (p=0.008). The CIS was observed in 44% of the PCA patients and was asymmetric in 50% of these. The patients with a CIS showed greater medial temporal asymmetry (p=0.016), but did not show lower medial temporal atrophy scores, compared to those without a CIS. Hippocampal volumes were not associated with quantitative CIS.

Conclusion

Mild to moderate medial temporal atrophy is a common finding in PCA and is associated with worse memory impairment and older age. However, medial temporal sparing was not related to the presence of a CIS in PCA.
Development of an artificial intelligence approach that employs genomic and brain imaging features to improve the diagnosis of Alzheimer’s Disease (AD)
Authors: Zhuang Xiaowei , Young Richard , Tillett Richard , Cordes Dietmar , Oh Edwin
Published: December 2022

Background

In the past 20 years, genome wide association studies (GWAS) and brain imaging analyses have identified various genetic risk variants and structural brain differences between AD and cognitively normal (CN) subjects1–3. However, due to the relatively large and colinear feature space, it remains a challenge to use these variants and features to classify AD status at an individual level for personalized diagnosis, treatment, and prevention4. In this study, we applied a novel artificial intelligence‐based technique to transform both genomic and brain imaging features into 2D artificial images, and further utilized a deep convolutional neural network (CNN) to classify these artificial images5,6. Together, we show that the approach significantly improves the classification accuracy of AD subjects.

Methods

Participants were selected from the AD Neuroimaging Initiative. Table 1 details the samples and features for each classification analysis. Briefly, 808 subjects with 2451 single‐nucleotide‐variants (SNV) with p‐values<1e‐4 in previous AD‐GWAS1 were included in classification of AD using SNV features. For classification of AD using brain imaging features, 1625 structural magnetic resonance imaging (sMRI) images from 941 subjects were included as samples. Each T1‐weighted sMRI image was entered into the FreeSurfer pipeline7 to compute features of regional thicknesses, volumes, and surface areas. Next, every feature was normalized to a scale of 0‐255, and the entire feature set from every subject was transformed into a 2D artificial image5. A CNN classifier was then trained on 80% of the samples with internal validation and tested on the remaining 20% of the samples.

Results

Since our samples were significantly biased towards non‐AD subjects, both the area under the ROC curve (AUC) and the accuracy were reported in Table 2 to assess the performance of the classifier. As listed in Table 2, the artificial intelligence approach outperforms 10 other regular/popular classifiers in discriminating AD from non‐AD samples, with an accuracy and AUC of 70.99% and 0.64 for SNV features, 86.50% and 0.74 for sMRI features, and 91.60% and 0.85 for combined features.

Conclusion

Taken together, these results indicate that our approach can efficiently deal with large and colinear feature spaces to classify AD subjects more accurately at an individual level.