bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance of a smell identification test vs. the mini‐mental status exam for the detection of dementia and cognitive impairment among ethnically diverse persons with cognitive concerns in primary care
Authors: Luchsinger Jose A. , Valdez Lenfis , Rosario Dahiana , Eimicke Joseph P , Silver Stephanie A , Kong Jian X , Teresi Jeanne , Goldberg Terry E. , Devanand Davangere
Published: January 2025

Background

Early detection of dementia and cognitive impairment is recommended for persons 65 years and older during wellness primary care visits. The importance of early detection has increased with the availability of new treatments for early Alzheimer's disease (AD). However, there is no clear approach for early detection in primary care. Odor identification deficits predict AD in epidemiological studies and may be useful for early detection. Our objective was to compare the accuracy of a short odor identification test with a short cognitive screening test for the detection of dementia and cognitive impairment in elderly persons with cognitive concerns.

Method

This was a cross‐sectional study of 600 participants 65 years and older, without known mild cognitive impairment (MCI) or dementia, with cognitive concerns, attending primary care practices in New York City. The odor identification test was the Brief Smell Identification Test (BSIT). The comparator test was the Mini Mental Status Exam II (MMSE). Cognitive diagnoses were made using the National Alzheimer’s Coordinating Center Uniform Data set (NACC‐UDS) version 3 forms with slight modifications by a diagnosis consensus committee. Test performance was compared using Receiver Operating Characteristic analyses.

Result

The mean age of the sample was 72.65 ± 6.31 years, 73.3% were female, 63.3% were Hispanic, 17.5% non‐Hispanic Black, and 27.0% non‐Hispanic White; 23.5% had normal cognition, 27.6% had cognitive impairment‐not mild cognitive impairment (MCI), 31.1% had amnestic MCI, 5.6% had non‐amnestic MCI, and 12% had dementia. The MMSE was superior to the BSIT in detecting dementia (AUC 0.89 vs 0.78, p =0.0007, Figure Panel A) and any cognitive impairment (AUC 0.79 vs 0.63, p <0.0001, Figure Panel B). Combining abnormal scores in the BSIT (< 9) to MMSE (< 24) improved the MMSE’s specificity (0.98 combined vs. 0.92 MMSE alone) and positive predictive value (PPV) in detecting cognitive impairment (0.98 combined vs. 0.95 MMSE alone).

Conclusion

The MMSE was superior to the BSIT in detecting dementia and cognitive impairment in primary care but using both tests improved specificity and PPV for identifying persons with subjective complaints needing further cognitive and biomarker evaluation.
Longitudinal changes in cognition in relation to PET biomarkers
Authors: Hartley Sigan L
Published: January 2025

Background

Adults with Down syndrome (DS) begin accumulating extracellular brain amyloid‐beta (Aβ) plaques in the decade or two preceding symptomatic Alzheimer’s disease (AD). The present study examined the time course of cognitive impairments cross‐sectionally and across two time points (spaced 32 months) in relation to Aβ chronicity (i.e., estimated years to or from reaching Aβ positivity [Aβ+], defined as 18 Centiloids.

Methods

Analyses included 167 participants with DS (M age = 38.91, SD = 8.41) in the Alzheimer Biomarker Consortium – Down Syndrome (ABC‐DS). Participants completed baseline PET scans using [11C]PiB or [18F]florbetapir and were administered the modified Cued Recall Test (mCRT) and Down Syndrome Mental Status Examination (DSMSE). A study partner completed the National Task Group‐Early Detection Screen for Dementia (NTG‐EDSD). A clinical case consensus approach, blind to neuroimaging data, was used to classify participants as cognitively stable, mild cognitive impairment (MCI), dementia, or unable to determine. Methods were repeated 32 months later. A sampled iterative local approximation algorithm modeled Aβ trajectories longitudinally and assigned each participant a chronicity value, representing timeline to Aβ+ (i.e., Aβ+ = 18 Centiloids) or post Aβ+ (Zammit et al., 2023).

Results

Mixed model Linear regressions showed significant quadradic associations between Aβ chronicity and cognitive performance, both at baseline (Figure 1) and across the 32 months (Figure 2). Using broken stick regression models, declines in mCRT scores began 3.41 years following Aβ+ in longitudinal models, with a decline of 1.35 (95% confidence interval ‐1.85 to ‐0.89) points per year. On average, participants with MCI were estimated to be 7.40 (SD = 6.68) years post Aβ+ and those with dementia were 12.72 (SD = 5.61) years post Aβ+ 9 (Figure 3).

Conclusion

Within‐person memory declines on the mCRT begin at 3 to 4 years following Aβ+ (i.e. Centiloids Aβ+) in DS. After this change point, declines in mCRT were estimated at 1.35 points per year. On average, adults with DS with MCI were 7.4 years post Aβ+ and those with dementia were 12.7 years post Aβ+. Characterizing the timeline of Aβ+ relative to AD symptomology in natural history studies offers estimates for guiding clinical AD trials.
Utility of plasma p‐tau217 as a secondary outcome for clinical trials across AD continuum
Authors: Ferreira Pamela C.L. , Bellaver Bruna , Povala Guilherme , Aguzzoli Cristiano Schaffer , Ferrari‐Souza João Pedro , Leffa Douglas Teixeira , Lussier Firoza Z , Madeiros Marina Scop , Zalzale Hussein , Rohden Francieli , Soares Carolina , Abbas Sarah , Bauer‐Negrini Guilherme , Karim Helmet T. , Hong Chang Hyung , Roh Hyun Woong , Tudorascu Dana , Karikari Thomas K , Snitz Beth E. , Son Sang Joon , Pascoal Tharick A.
Published: January 2025

Background

Blood‐based biomarkers offer a cost‐effective and simple alternative for clinical use in the context of Alzheimer's disease (AD). It has already been shown that plasma phosphorylated tau at threonine 217 (p‐tau217) is associated with amyloid (Aβ), neurofibrillary tau tangles, and cognitive decline. Longitudinal studies confirmed its ability to track AD progression. Therefore, the aim of this study is to evaluate the potential utility of changes in plasma p‐tau217 as secondary outcome in clinical trials across the AD spectrum.

Method

We included 189 individuals with available plasma p‐tau217 measurements at two time points (24 months follow‐up) across two cohorts:[MYHAT‐NI, population‐based(USA): 51 Cognitively Unimpaired(CU); BICWALZS, memory clinic(South Korea): 135 Cognitively Impaired(CI) individuals], all with baseline Aβ‐PET. Plasma p‐tau217 was quantified using the ALZpath assay. We used linear regression to investigate p‐tau217 association with cognitive decline. Effect size was determined by biomarker mean change divided by the standard deviation. We also estimated the sample size required to detect a 25% drug effect on p‐tau217 reduction with 80% power at a significance level of 0.05.

Result

Baseline and longitudinal changes in p‐tau217 were significantly associated with cognitive decline independently of Aβ status in both CU and CI individuals (Table 1). Functionally, individuals classified with mild dementia (CDR‐SB>4.5) showed greater and pronounced annual changes in p‐tau217 compared to the other groups (Figure 1A). Notably, Aβ+ individuals presented a higher effect size for p‐tau217 changes in both CU(0.79) and CI(0.74) groups, compared to the whole population (Figure 2B). The sample size required for a clinical trial including of Aβ+ individuals were 1,276 for CU and 940 for the CI. Cost analysis revealed that in trials recruiting CU Aβ+ individuals targeting tau pathology using p‐tau217 as a secondary outcome was 1.5, 3.7, and 3.9 times more cost‐effective than 18F‐MK‐6240 tau‐PET, 18F‐Flortaucipir tau‐PET, and p‐tau181, respectively (Figure 2). Similarly, in trials with CI Aβ+ participants, p‐tau217 was 1.5 times less expensive than [18F]‐MK‐6240 tau‐PET, and 3.7 times less than [18F]‐Flortaucipir tau‐PET.

Conclusion

Our results demonstrated that changes in plasma p‐tau217 is associated with cognitive decline across the AD continuum. Furthermore, p‐tau217 shows promise as a secondary outcome in AD clinical trials.
Cortical and subcortical p‐tau density in CTE: Comparison to Alzheimer’s disease
Authors: Sconzo Daniel , Alosco Michael L. , Groh Jenna R. , Tripodis Yorghos , Daneshvar Daniel H. , Nowinski Christopher , Palmisano Joseph N. , Martin Brett , Mez Jesse , Crary John F. , Alvarez Victor E. , Huber Bertrand Russell , McKee Ann C. , Stein Thor D. , Cherry Jonathan D
Published: January 2025

Background

The unique lesion of chronic traumatic encephalopathy (CTE) is the perivascular deposition of hyperphosphorylated tau at the depth of the cortical sulci. The distribution and molecular composition of p‐tau is distinct from Alzheimer’s disease (AD), but differential diagnostic challenges remain. Understanding disease differences in regional density of p‐tau will inform differential diagnosis and interpretation of in vivo biomarkers. Here, we compared autopsy‐confirmed CTE and AD across cortical and subcortical measurements of p‐tau density.

Method

The sample included 109 brain donors with stage III/IV CTE, and 109 age (+/‐ 3 years) and sex similar brain donors with autopsy‐confirmed AD. While the original sample was similar, there is missing data across regions due to older cases not having AT8 stains. CTE was neuropathologically diagnosed using published criteria. NIA‐Reagan was used for AD. Neuropathologists used semi‐quantitative rating scales (0=none, 3=severe) to evaluate p‐tau severity in the dorsolateral frontal cortex (DLFC), inferior orbital frontal cortex (IFC), superior temporal cortex (STC), inferior parietal cortex (IPC), CA1, CA2, and CA4, entorhinal cortex (EC), and amygdala. Digital slide scanning of AT8 tissue was done for quantitative assessment of p‐tau density in the DLFC, STC, IPC, CA1, CA2/3, CA4, and calcarine cortex. Regression and analysis of variance models compared disease groups on each outcome, controlling for age.

Result

On the semi‐quantitative rating scales, those with autopsy‐confirmed CTE had greater p‐tau severity in the CA4‐hippocampus compared with AD (OR=4.43, p=0.003); in contrast, AD had greater p‐tau severity in the CA1‐hippocampus (OR=0.07), EC (OR=0.10), and amygdala (OR=0.24) (ps<0.05). There were no differences for the CA2‐hippocampus. Regarding cortical regions, those with AD had greater p‐tau severity on the DLFC, IFC, STC, and IPC (ORs=0.03‐0.16, ps<0.05). A similar pattern was found for the quantitative p‐tau density data: CTE had greater p‐tau density in CA4‐ (marginal mean difference=7.45) and CA2/3 (marginal mean difference=9.86) (ps<0.01) and AD had higher density of p‐tau across the other regions (i.e., DLFC, IPC, STC, calcarine).

Conclusion

Compared with AD, CA4‐hippocampus was most affected in CTE. AD had greater p‐tau density across cortical regions. Findings inform neuropathological differential diagnosis and interpretation of in vivo biomarkers in CTE and AD.
The Effect of Sex‐Differences on the Relationship Between White Matter Hyperintensity, Cerebrovascular Reactivity, and Fluid Biomarkers
Authors: Bahrani Ahmed A , Jiang Yang , Powell David K , Katsumata Yuriko , Nahvi Azadeh , Lee Tiffany , Gold Brian T , Goldstein Larry B , Wilcock Donna M. , Jicha Gregory A , Nelson Peter T , Norris Christopher M.
Published: January 2025

Background

Alzheimer’s disease (AD) and vascular cognitive impairment and dementia (VCID) are the predominant types of dementia in older adults, associated with memory loss and cognitive deficits. White matter hyperintensities (WMH) are linked to both AD and VCID. Astrocytes play a crucial role in WM integrity, encompassing functions like neuroinflammation, oxidative stress, and Aβ clearance. Poorly reactive astrocytes could lead to implications, like WMH or vascular damage. This study aims to explore sex‐differences effect on the correlation between fluid biomarkers, WMH, and cerebrovascular reactivity (CVR).

Method

Twenty‐seven participants (mean age 76.8±6.4 years, Female=15) preliminary data were collected from UK‐ADRC/MarkVCID cohorts. A correlation test was employed to examine sex‐differences based on the correlation of fluid inflammatory (GFAP, IL6, IL8, IL10), angiogenic (TDP‐43, and PlGF) biomarkers, and Aβ40 and 42, to global and regional CVR and WMH.

Results

We observed several sex‐differences: the female group showed a significant correlation between WMH at occipital lobe and IL6 (P=0.031), IL10 (P=0.036), and GFAP (P=0.037), while male group only showed a significant correlation between Aβ42 and WMH at the occipital lobe (P=0.039). CVR data of the female group exhibited a correlation at the parietal lobe (right‐hemisphere) and IL8 (P=0.037) and Aβ40 (P=0.038) and between Aβ40 and CVR temporal lobe (right‐hemisphere, P=0.021). The male group showed a significant correlation between IL6 and CVR at the occipital lobe (left‐hemisphere, P=0.012. Generally, the female group showed higher mean values for all biomarkers except for IL10 and PIGF, but only significant at GFAP and TDP43. Additionally, the correlation test adjusted for age and sex showed that TDP‐43 had a significant correlation with WMH in the temporal (P=0.041), occipital (P=0.024), and parietal (P=0.024) lobes, while GFAP displayed a significant correlation only with WMH in the frontal lobe (P=0.013).

Conclusions

Despite the small sample size, which warrants expansion in future studies, we observed interesting findings of sex‐differences in specific brain regions in relation to fluid biomarkers. These biomarkers may arise, in part, from reactive astrocytes, commonly found near many brain lesions, including WM pathology. Further studies are needed to gain deeper insight into astrocyte activities in diseases associated with WMH and CVR, like AD.
Machine‐learning analysis of real‐world multimodal data collected autonomously at home detects dementia as precisely as a traditional composite scale
Authors: Rueda‐Delgado Laura M , Buick Alison R , Nolan Hugh , Rowe James B , Murphy Brian
Published: January 2025

Background

Current tools for Alzheimer's disease screening and staging used in clinical research (e.g. ACE‐3, ADAS‐Cog) require substantial face‐to‐face time with trained professionals, and may be affected by subjectivity, "white coat syndrome" and other biases. Alzheimer's symptomology is multi‐factorial and varies day‐to‐day. To enable stratification for precision treatments, more effective composite endpoints are required, with accurate quantification of functional impairment in individual domains. Ideally these would be measured objectively and frequently in real‐world contexts to improve validity, and to reduce clinical burden in trial and care settings.

Method

We present a machine‐learning stratification analysis using data from the Cumulus real‐world multi‐domain neuroassessment platform, in CNS101, a year‐long study designed with a consortium of 10 pharma companies. Participants completed a range of tablet‐based functional tasks with wake EEG, and separately recorded EEG during sleep. This cross‐sectional analysis uses 1111 sessions from repeated sampling with 101 participants (47 patients with mild Alzheimer’s type dementia, and 54 corresponding controls, recruited across 7 sites in the UK), during an early two‐week burst period of autonomous at‐home use. Bagging of decision trees was used to compare the power of different data sources in discriminating dementia from neurotypical states. This algorithm is widely used for its performance across learning tasks (linear and non‐linear), and heterogeneous datasets of differing size, levels of noise, and collinearity. For each set of input data, 100 classifiers were trained and evaluated (10‐fold cross‐validation in each of 10 random partitions), and the mean Area Under the Curve (AUC) of sensitivity/specificity trade‐off was calculated.

Result

A full set of 691 multimodal features yielded a classifier with AUC performance of 0.953 and error rate 4.7% – compared to AUC of 0.955 and error rate 4.5% for the set of 13 ADAS‐Cog subscores. While individual modalities/domains all performed above chance, the 50 features from Cumulus cognitive tasks alone had an AUC performance of 0.951.

Conclusion

Patients using digital technology autonomously in the home can yield data that matches the discriminative power of a traditional clinician‐administered composite scale. This can enable objective precision measurement of disease severity at scale
Associations between Later‐life Cerebrovascular Reactivity and Brain Structure and Cognitive Decline: A Longitudinal Study in an Aging Cohort with Varying Dementia Risks
Authors: Wang Congxiyu , Patel Raihaan , Jobbins Lucy , Reid Graham , Hobden Georgina , Mackay Clare E , Ebmeier Klaus P , Kivimäki Mika , Singh‐Manoux Archana , Bulte Daniel , Suri Sana
Published: January 2025

Background

Cerebrovascular reactivity (CVR) is implicated in the progression of dementia, though the underlying mechanisms is not understood. This study examines the relationships between CVR and brain structure and cognitive decline, moderated by mid‐life dementia risk.

Method

163 participants from the Whitehall‐II cohort underwent neuropsychological testing and MRI, including T1‐weighted, FLAIR, and DTI sequences, at two phases (Phase‐I: mean age=68.2±4.4; Phase‐II: mean age=76.9±4.5). CVR was quantified via BOLD response to 5% CO2 only at Phase‐II. Linear regression tested the Phase‐II and Phase‐I to Phase‐II associations between CVR and brain and cognitive outcomes (Table 1), alongside its interaction with dementia risks. Post‐hoc analysis clarified the extent of these associations among different risk groups.

Result

Tables 2 and 3 list significant cross‐sectional and longitudinal results, respectively. At Phase‐II, global CVR was positively associated with volume of left nucleus accumbens, and temporoparietal junction (p<0.03). Parietal CVR was positively associated with left hippocampus volume (p=0.03). These associations were more pronounced in the low‐risk group. Temporal CVR was related to thalamus volume (p<0.05) across all participants, with associations of the right thalamus exclusive to the high‐risk group (p=0.03). Longitudinally, lower global and regional CVR at Phase‐II was linked to greater reduction in temporoparietal junction volume (p<0.04). In high‐risk individuals, lower frontal, parietal, or global CVR was linked to larger volume declines in total grey matter or right thalamus respectively (p<0.05). Across all participants, lower parietal CVR at follow‐up was linked to greater FA reductions and RD increases between examinations in the corpus callosum (p=0.02) and to greater declines in FA and increases in MD, RD, and L1 in the cingulum bundle (p<0.04), with these effects being more pronounced in the low‐risk group. At Phase‐II, lower parietal and temporal CVR was associated with worse fluency and intelligence, respectively, in high‐risk individuals (p<0.05). Lower frontal CVR was linked to more executive function decline in the low‐risk group over‐time (p=0.03).

Conclusion

This study highlights the differential impacts of global and regional CVR on brain structure and cognitive changes dependent on mid‐life dementia risks, which provides evidence for CVR as a potential biomarker for dementia and age‐related cognitive change.
Late‐life hypertension acts together with amyloid‐β pathology to promote memory loss
Authors: Ros Lucas Uglione Da , Ferrari‐Souza João Pedro , Hauschild Lucas Augusto , de Bastiani Marco Antônio , Lussier Firoza Z , Rahmouni Nesrine , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Macedo Arthur C. , Chamoun Mira , Bezgin Gleb , Benedet Andrea L. ,   Alzheimer's Disease Neuroimaging Initiative (ADNI), Pascoal Tharick A. , Rosa‐Neto Pedro , Zimmer Eduardo R.
Published: January 2025

Background

Midlife hypertension (HTN) is a known risk factor for Alzheimer's disease (AD). However, it remains to be elucidated whether the effect of late‐life HTN is also present. Here, we aimed to assess the associations of late‐life HTN and amyloid‐β pathology (Aβ) with longitudinal changes in global cognition and different domains in cognitively unimpaired (CU) individuals.

Method

We evaluated 475 CU individuals of over 65 years of age from the ADNI cohort, with available baseline medical data and CSF Elecsys biomarkers (Aβ1‐42 and p‐tau181), as well as longitudinal clinical assessments with neuropsychological testing (up to 6 years). We used global cognitive tests, as well as composite scores for memory, executive function and language domains as outcomes. We replicated all the analyses in 162 CU individuals of over 65 years of age from the TRIAD cohort with baseline clinical data and [18F]NAV4694 positron emission tomography (PET) for Aβ, as well as longitudinal clinical assessments with neuropsychological testing (up to 3 years). The presence or absence of HTN was defined based on medical history. In addition, individuals were classified as Aβ+ or Aβ‐ based on CSF p‐tau181/Aβ1‐42 (ADNI) or Aβ‐PET (TRIAD).

Result

Linear mixed‐effects (LME) models showed that HTN and Aβ acted together to promote longitudinal global cognitive decline (ADNI: HTN X Aβ X Time, β = ‐0.44, p = 0.001, Figure 1a; TRIAD: HTN X Aβ X Time, β =‐0.62, p = 0.001). Interestingly, additional analyses demonstrated that HTN and Aβ joint effects were observed on the decline of memory function (ADNI: HTN X Aβ X Time, β = ‐0.05, p = 0.012, Figure 1b; TRIAD: HTN X Aβ X Time, β = ‐0.64, p < 0.001), but not for executive function or and language (Figure 1c, ADNI: p = 0 .6767 and TRIAD: p = 0.797 and Figure 1d, ADNI: p = 0.8961 and TRIAD: p = 0.327, respectively).

Conclusion

In CU individuals at increased risk for AD, late‐life HTN confers increased risk for cognitive decline, particularly in memory function. Further research is needed to understand the mechanisms involved and how treating hypertension in this population may mediate this risk.
Estimating the time between Aβ positivity and elevated regional tau in preclinical AD
Authors: Coath William , Betthauser Tobey J. , Teague Jordan P , Arstad Erik , Awais Ramla , Sander Kerstin , Scott Catherine J , Thomas David L , Dickson John , Markiewicz Pawel J , Barkhof Frederik , Schöll Michael , Richards Marcus , Fox Nick C , Cash David M , Schott Jonathan M ,   the Insight 46 team
Published: January 2025

Background

Understanding when Aβ positive cognitively normal individuals develop tau pathology has important implications for treatment with anti‐Aβ therapies. We employed a changepoint regression approach to estimate time from Aβ‐PET positivity to regionally elevated tau‐PET in a population‐based cohort of primarily cognitively unimpaired individuals.

Method

Participants from Insight 46 (1946 British birth cohort) underwent two [18F]florbetapir Aβ‐PET scans and a sub‐sample enriched for Aβ were also scanned with [18F]MK‐6240 tau‐PET, characteristics are presented in Table 1. Age at Aβ‐PET positivity, defined through Gaussian mixture modelling (GMM) as >12 Centiloids, was estimated using the SILA algorithm (Betthauser et al. 2022). Tau‐PET SUVRs from a temporal‐meta, Braak I‐VI and 34 bilateral FreeSurfer7 regions were calculated 90‐110 mins post‐injection using an inferior cerebellar grey matter reference region. Tau‐PET positivity cutpoints for each region were defined using the 99th percentile of the lower distribution from GMM. For each region, we tested changepoints in the slope of the linear regression between tau‐PET SUVR and time from estimated Aβ positivity with Bonferroni correction (5% significance, p<.001).

Result

At tau‐PET scan, 90 individuals (60%) were >0 years from estimated Aβ positivity. There was a statistically significant difference in slopes before and after the changepoint for all composite regions excluding Braak VI (Figure 1). Changepoint estimates show that tau accumulation started ∼2.5yrs after estimated Aβ positivity in Braak stages I‐III; and ∼10‐12.5yrs for Braak stages IV‐V, and the temporal‐meta region (Figure 2A). Regional estimates broadly followed Braak stages for 16/36 regions showing significant evidence of change in slopes (Figure 2B). Tau positivity rates before changepoints did not exceed 5%, whereas post‐changepoint tau positivity rates were between ∼10% and ∼50%. Regions with later changepoints tended to exhibit higher post‐changepoint slopes with greater uncertainty.

Conclusion

Elevated tau‐PET signal occurs ∼2.5 years after estimated age of Aβ onset in Braak stages I‐III and ∼10‐12.5 years in temporal‐meta and Braak stages IV‐V, with uncertainty within these groupings. These estimates for later Braak stages are consistent with results from previous work on the timing of positive tau PET visual reads. These findings may have implications for determining the optimal time to administer Aβ immunotherapies in asymptomatic individuals.
Early and Genetic Biomarkers in Alzheimer's Disease: Role of Metabolism and Neuroinflammation in the Cognition of Coastal Peruvians
Authors: Zegarra‐Valdivia Jonathan Adrian , Arana‐Nombera Harold Alessandro , Perez‐Fernandez Leandro Aron , Casimiro‐Arana Milagros del Rocio , Alamo‐Medina Reyna Elizabeth , Gallegos‐Manayay Viviana Nayelli , Oliva‐Piscoya María del Rosario , Abanto‐Saldaña Eduardo Sebastián , Vásquez‐Zuñe Nobuko , Ordinola Maria Celinda Cruz , Manrique Carmen Paredes
Published: January 2025

Background

Alzheimer's Disease (AD) has been associated with neurocognitive, metabolic, and neuroinflammatory alterations. Currently, there are no useful biomarkers in low‐resource countries, and genetic risk/protection factors in Peruvians are unknown.

Objective: To establish the first serum bank in the northern part of the country for the analysis of participants with mild cognitive impairment (MCI) or AD. This will enable the identification of a profile of risk/protection factors in the Peruvian population. We will also analyze the interaction between levels of neurocognition, IGF‐I, and neuroinflammation as potential biomarkers for early detection of cerebral deterioration.

Method

This is a quantitative, cross‐sectional, retrospective case‐control study. We will identify the neurocognitive profile and serum biomarkers (IGF‐I, TNF‐α, interleukins) of adult participants (>50 years old), both healthy individuals and those previously identified and diagnosed with MCI or AD by a specialist (neurologist, geriatrician, or psychiatrist).

Results

This is an ongoing project; to date, we have assessed over 100 participants aged 50 and above. We are in the process of evaluating both control subjects and patients with Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). We aim to continue our assessments and complete blood sample collections throughout the year.

Conclusion

This study proposes to create the first serum bank for the study of genetic and non‐genetic biomarkers associated with dementia in the northern part of the country. We will use the triad of IGF‐1, neuroinflammation, and neurocognition biomarkers for early diagnosis in MCI and AD. Additionally, this will enable new genetic studies to identify risk/protection factors in Peruvians.
The use of MRI, FDG‐PET and CSF biomarkers in young‐onset cognitive disorders: real‐world clinical evidence on the concordance of investigations
Authors: Whitmore Molly J , Gilmartin Christopher G S , Tench Christopher , Mukaetova‐Ladinska Elizabeta , Hosseini Akram A.
Published: January 2025

Background

Cognitive disorders are clinical diagnoses informed by history, cognitive testing and investigations including MRI, FDG‐PET and CSF biomarkers. These investigations do not always correlate however. This study sought to investigate the concordance between MRI, FDG‐PET and CSF biomarkers with final diagnosis in a real‐world clinical context.

Method

This is a prospective longitudinal cohort study (CogNID, NCT03861884, IRAS 250525) of a referral cognitive neurology NHS service (n=345). MRI and FDG‐PET at assessment were appraised for whether they were suggestive of the final diagnosis. An interim analysis was performed on a quality assured dataset of those aged ≥40 and <70 years old.

Result

Cohort characteristics: 40≤age<70 (n=265), MRI results available (n=245), FDG‐PET available (n=129), CSF analysis available (n=104). Interim results (n=77): Kappa coefficient of concordance of 0.15 (95% CI 0.03‐0.28) between MRI and FDG‐PET for suggestion of final diagnosis, demonstrating a poor level of agreement. MRI at time of assessment was suggestive of final diagnosis in 48% of cases and FDG‐PET in 56%. The positive predictive value for a final diagnosis of Alzheimer’s Disease based on CSF analysis in keeping with Alzheimer’s continuum was 64%, with a negative predictive value of 75%.

Conclusion

Investigations must be viewed holistically in combination with a clinical history and cognitive examinations. Initial results at time of assessment are often not indicative of the final diagnosis, and may be discordant. Follow‐up and repeat investigations where appropriate are critical for improving diagnostic accuracy.

*CG&MW are joint first authors
Post‐mortem MR imaging of tau pathology – a pilot study
Authors: Sumra Vishaal , Spring Shoshana , Botelho Owen , Nieman Brian , Sled John G , Tartaglia Maria Carmela , Kovacs Gabor G.
Published: January 2025

Background

In‐vivo detection of neuropathology is critical for early diagnosis of neurodegenerative diseases. Post‐mortem brain magnetic resonance imaging (MRI) of pathological protein inclusions could further our ability to detect them in vivo and correlate MRI parameters to histopathological substrates. In this post‐mortem study, we aimed to identify MRI correlates of neurodegenerative disease pathology in a brain with various forms of proteinopathies.

Method

One large cortical section containing the temporal cortex, hippocampus and thalamus was used from an 82‐year‐old male patient, with chronic traumatic encephalopathy (CTE), Alzheimer’s disease (AD), TDP‐43, aging related tau astrogliosis (ARTAG) and cerebral amyloid angiopathy (CAA) pathologies. The post‐mortem tissue sample was scanned using high‐resolution Rapid Acquisition with Relaxation Enhancement (RARE) and multi‐gradient echo (MGE) sequences on an 11.7 Tesla MRI (Bruker, Germany). RARE scan parameters were as follows: field of view: 97.2 x 86.4 x 28.8 mm, rep time: 2 s, RARE factor: 8, echo time: 48 ms, echo spacing: 12 ms, 225 μm isotropic resolution. Tissue samples were subsequently sectioned (0.004 mm thick slices) and stained using AT8 – for Tau, GFAP – for astrogliosis and H&E/Luxol – for distinguishing gray (GM) and white matter (WM) and PERLS – for extracellular iron.

Result

Post‐mortem MRI allowed for clear visualization of WM and GM structures. Decreased cell density in WM as visualised on H&E stained slices was associated with hyperintensities on T2w images and decreased measured R2*. AT8 immunoreactivity in GM and WM was associated with hyperintensities on T2w images and decreased measured R2*.

Conclusion

High‐resolution MRI of post‐mortem tissue allowed for visualization of fine WM‐GM details, as well as hyperintensities in areas that potentially correspond to increased densities of tau pathology and decreased WM density. Further studies are needed to investigate the potential for high‐resolution post‐mortem MRI to visualize the pathological process in neurodegenerative diseases.
The HOPE4MCI study: AGB101 treatment reduces entorhinal cortex atrophy in patients with amnestic mild cognitive impairment due to Alzheimer’s Disease who are ApoE‐4 non‐carriers
Authors: Rani Nisha , Mohs Richard , Gallagher Michela , Bakker Arnold
Published: January 2025

Background

Hippocampal hyperactivity is a hallmark of prodromal Alzheimer’s disease (AD) that predicts progression in patients with amnestic mild cognitive impairment (aMCI). AGB101 is an extended‐release formulation of levetiracetam in the dose range previously demonstrated to normalize hippocampal activity and improve cognitive performance in aMCI. The HOPE4MCI clinical trial used a 78‐week protocol to assess progression in amyloid‐positive patients with MCI due to AD. Mohs et al. (2024) reported the clinical/cognitive results showing that ApoE‐4 non‐carriers had a more favorable treatment effect of AGB101 over the 78‐week duration of the study. Here we report effects of AGB101 on biomarkers of AD in those patients.

Methods

Forty‐four participants who completed the 78‐week protocol were ApoE‐4 non‐carriers. Structural MRI scans obtained in the study at baseline and after 78 weeks were analyzed using the Automated Segmentation of Hippocampal Subfields (ASHS) software providing volume measures of key structures of the medial temporal lobe relevant to AD progression. Blood samples collected at 78 weeks in the study were also analyzed for plasma biomarkers in those participants.

Results

Treatment with AGB101 significantly reduced atrophy in the left entorhinal cortex (p < 0.05) compared to placebo. Reduced atrophy in the entorhinal cortex was significantly correlated with the change in CDR‐SB score (r = ‐0.511) over 78 weeks, as well as with biomarkers of neurodegeneration neurofilament light (NfL; r = ‐0.382) and glial fibrillary acidic protein (GFAP; r = ‐0.398) collected at completion of the protocol.

Conclusion

As reported in Mohs et al. (2024), progression on the primary clinical/cognitive endpoint of the Clincial Dementia Rating Scale Sum of Boxes score (CDR‐SB) occurred over the 78‐week protocol in the HOPE4MCI study and non‐carriers of ApoE4 treated with AGB101 showed a substantially more favorable effect than carriers. Here we report that treatment with AGB101, in those participants significantly reduced atrophy of the entorhinal cortex. That reduction in atrophy was significantly coupled with the change in CDR‐SB and with plasma biomarkers of disease. These exploratory analyses would be consistent with a reduction in neurodegeneration in the non‐carriers of ApoE4 treated with AGB101 prior to a clinical diagnosis of dementia.
Physical activity pattern mediating the relationship between genetic variants and AD‐like brain atrophy
Authors: Xu Hanxiang , Mu Shizhuo , Bao Jingxuan , Davatzikos Christos , Shou Haochang , Shen Li
Published: January 2025

Background

Studies have shown physical activity (PA) patterns are heritable traits and are correlated with several known genetic risk factors including APOE, the best‐known gene associated with Alzheimer’s Disease (AD). SPARE‐AD was a previously developed machine learning index known to be sensitive to AD‐like brain atrophy. However, the relationship between genetic variants, physical activity patterns and AD‐related neuroimaging features have yet been extensively studied due to the lack of appropriate data and statistical methods for handling complex multimodal data. To bridge this gap, we perform a high‐dimensional mediation analysis to decompose the pathway from known genetic variants to AD‐like brain atrophy through accelerometry‐based physical activity patterns.

Method

We obtained genetic, accelerometry and neuroimaging data from UK Biobank (n=13,425). SPARE‐AD index was calculated from structural MRI data. Genetic variants were selected by GWAS using SAIGE with SPARE‐AD index as the outcome, adjusting for years of education, age, gender and the first 10 principal components as covariates. The 7‐day accelerometry data were summarized into conventional statistics such as average total log activity counts (TLAC) and percent of moderate‐to‐vigorous PA (MVPA), and data‐driven features derived using functional Principal Component Analysis. We performed high‐dimensional Bayesian mediation analysis (BAMA) to preliminarily identify the physical activity patterns with non‐zero indirect effect of genetic variants on SPARE‐AD. The mediation effect was later confirmed by significant associations between exposure (genetic variant) and mediator (physical activity pattern) using univariate analysis.

Result

GWAS of SPARE‐AD identified 22 unique SNPs (p<=5e‐8). These SNPs and 154 physical activity features were included in our mediation analyses. We identified 128 significant (SNP, PA, SPARE‐AD) mediation relationships (one example shown in Figure 1). Most of the SNPs are located on AMPD3 gene, which is associated with energy metabolism. Among all the identified mediators, lower TAC and MVPA were identified to be associated with higher SPARE‐AD, and positive indirect effects on the association between SNPs and SPARE‐AD.

Conclusion

We found several significant pathways, where physical activity measures could mediate genetic effects on AD‐related brain atrophy. This could provide insights for developing personalized behavioral intervention strategies that mitigate potential genetic risks.
Alzheimer’s Disease Plasma Biomarker Results from across 14 Alzheimer’s Disease Research Centers
Authors: Russ Kristen A. , Asthana Sanjay , Johnson Sterling C. , Wilson Rachael E , Craft Suzanne , Register Thomas C. , Lockhart Samuel N. , Nairn Angus C , Strittmatter Stephen M , van Dyck Christopher H. , Foroud Tatiana M. , Dage Jeffrey L.
Published: January 2025

Background

The Alzheimer’s Disease Center Fluid Biomarker (ADCFB) Initiative samples are analyzed centrally at NCRAD for AD plasma biomarkers. When combining NACC accessible data from across centers, biofluid biomarker data must be evaluated carefully. This will become more critical with the implementation of disease modifying therapies.

Methods

Beta amyloid 1‐42 (Aβ42) and beta amyloid 1‐40 (Aβ40) were analyzed utilizing the Neurology 4‐Plex E kits on a Quanterix Simoa HD‐X. All assays were performed according to manufacturer’s instructions. NACC data from participants 65 or older was combined with biomarker results into one data set. Samples with PET results from the same visit as the blood collection were utilized for this analysis (n=114).

Results

Data for amyloid and tau PET was used along with Aβ42/40 ratios to assess the area under the curve (AUC) for this data set (Figure 1). Amyloid PET and Tau PET by Aβ42/40 ROC analysis including age and APOE4 carrier status showed lower than expected AUCs (both 0.72). A subset of data (n=90) was analyzed using participants that were not on any FDA‐approved drugs for AD. This had no effect on AUCs for amyloid or tau PET by Aβ42/40 ratios. Distribution of Aβ42/40 ratios across sites showed a single site had a subset of very high Aβ42/40 ratios (n=8) in comparison to other sites. After removal of the Aβ42/40 outliers from the specific site from the data set, diagnostic accuracies of Aβ42/40 for both Amyloid PET (AUC=0.77) and Tau PET (AUC=0.76) were increased. More investigation into the exact cause of the outliers is necessary, but Aβ42/40 elevations independent from other biomarkers have been seen in clinical trials of Solanezumab and some other Aβ targeting antibodies.

Conclusion

To avoid errors in data analysis when using shared data, it is important to track clinical trial co‐enrollment and drug type within ADCs at NACC. As FDA‐approved treatments become available or co‐enrollment of AD drug trials at centers occurs, it is critical to carefully track participant variables and review biofluid biomarker data when it is being combined across centers or studies.
Plasma biomarkers of neurodegeneration in the brain (UCH‐L1 and NfL) become exponentially higher with age from early childhood, and treatment of Alzheimer’s disease participants with granulocyte‐macrophage colony‐stimulating factor (GM‐CSF) lowers age‐associated levels of plasma UCH‐L1 by six decades
Authors: Sillau Stefan H , Coughlan Christina M , Ahmed Md. Mahiuddin , Nair Kavita V , Araya Paula , Galbraith Matthew D. , Bettcher Brianne M , Espinosa Joaquin M. , Chial Heidi J , Epperson Neill , Boyd Timothy D. , Potter Huntington
Published: January 2025

Background

Increasing age is the greatest risk factor for age‐associated cognitive decline (AACD) and, especially in females, for developing Alzheimer’s disease (AD). Mechanisms underlying this connection are unknown, but neuronal loss and brain atrophy accompany aging and AD and likely contribute to cognitive deficits. There are currently no means to measure neuronal cell death during life and no means to prevent it. Inflammation is also correlated with AD pathogenesis and aging (‘inflammaging’), but whether inflammation causes and/or is a response to neurodegeneration is unknown.

Treatment of mouse models of AD with GM‐CSF reverses amyloid deposition and normalizes cognition, and GM‐CSF treatment improves cognition in aged wild‐type mice. A published double‐blind placebo‐controlled phase II trial showed that three weeks of treatment with recombinant human GM‐CSF (sargramostim) in mild‐to‐moderate AD participants improved cognition (MMSE) and blood biomarkers of amyloid, Tau, and neurodegeneration. Together, these results suggest that GM‐CSF may slow or halt the neuronal damage in aging and/or AD that causes cognitive deficits.

Method

Plasma concentrations of ubiquitin C‐terminal hydrolase‐L1, UCH‐L1, a measure of neuronal cell loss, neurofilament light (NfL), a measure of axonal damage, and GFAP, a measure of inflammation/astrogliosis, were assessed cross‐sectionally in 317 healthy control participants between age 2 and 85 using the Quanterix SIMOA platform. The resulting age curves were compared to the results from the previously published clinical trial of sargramostim/GM‐CSF in participants with mild‐to‐moderate AD.

Result

The concentrations of human plasma proteins released from dying/damaged neurons (UCH‐L1 and NfL) showed an exponential increase from age 2‐85 and rise more in females. Plasma GFAP concentrations are exponentially higher after age 40, following neurodegeneration. Treatment of AD participants in the GM‐CSF/sargramostim trial halted neuronal cell death, based on the reduction in plasma UCH‐L1 concentrations to levels equivalent to those of five‐year‐old healthy controls. The ability of GM‐CSF treatment to reduce neuronal apoptosis was confirmed in the hippocampi of aged TgF344‐AD rats, a model recapitulates all human AD brain neuropathology.

Conclusion

These findings suggest that age‐associated exponential increases in neurodegeneration may underlie the contribution of aging to cognitive decline, including in AD, and that GM‐CSF/sargramostim treatment may halt these effects.
The Association between Hepatic fat and Neuroinflammation in Midlife Obesity
Authors: Dolatshahi Mahsa , Rahmani Farzaneh , Commean Paul K. , Kasani Sara Hosseinzadeh , Naghashzadeh Mahshid , Lloyd LaKisha , Nguyen Caitlyn , McBee‐Kemper Abby , Weeks Jake , Ceriani Lael , Mittendorfer Bettina , Sirlin Claude , Song Sheng‐Kwei , Benzinger Tammie L.S. , Ippolito Joseph E. , Morris John C. , Raji Cyrus A.
Published: January 2025

Background

Obesity in midlife, body mass index (BMI) of 30 kg/m2 or higher, is recognized as a contributor to Alzheimer disease (AD) later in life. Adiposity in visceral tissues such as liver is associated with increased systemic inflammation and impaired cognition. In this study, we aimed to investigate the relationship between MRI‐derived Positron Density Fat Fraction (PDFF) and brain histology and neuroinflammation using Diffusion Basis Spectrum Imaging (DBSI) in cognitively normal midlife individuals.

Method

In total, 67 cognitively normal middle‐aged participants (Age: 50.02±6.00 years, female: 65.7%, obesity: 53.7%, BMI: 31.72±6.81 kg/m2) underwent brain and abdominal 3T MRI and metabolic assessment. Homeostatic Model Assessment for Insulin Resistance (HOMAIR) was used as for measuring insulin resistance. Using a trained U‐Net convolutional neural network (CNN) model, hepatic PDFF maps were calculated from conventional T1‐weighted images. The CNN included the Adam optimizer for training. A DBSI scheme with a total of 98 diffusion samplings was acquired. After eddy current and movement correction and removing non‐brain tissue, DBSI maps including fractional anisotropy (FA, overall integrity), axial diffusivity (AD, axonal injury), radial diffusivity (RD, myelin loss), restricted fraction (RF, inflammation cellularity), hindered fraction (HF, extracellular edema), and fiber fraction (FF, axonal density) maps were calculated using in‐house software scripted in MATLAB and Statistics Toolbox Release. DBSI‐derived maps were processed using a tract‐based spatial statistics (TBSS) pipeline to allow for whole‐brain white matter voxel‐wise analyses. Using the Randomize tool from FSL, the association of PDFF and HOMAIR with DBSI‐derived white matter skeleton, with age and sex as covariates, and a threshold of 0.05 for false‐discovery rate.

Result

There was a significant association between PDFF and HOMAIR (p<0.001), and obese individuals showed higher PDFF (p=0.02) but no difference in HOMAIR (p=0.12). We observed a significant positive association between PDFF and restricted fraction in widespread white matter tracts. There was no significant association between HOMAIR and DBSI measures.

Conclusion

Our results indicate the role of hepatic fat in increased inflammation‐related cellularity in the brain in cognitively normal midlife individuals. These findings suggest that excess hepatic fat can potentially increase the risk for Alzheimer disease and cognitive impairment at least partly through promoting neuroinflammation.
Histological evaluation of phospho‐epitopes within the core region of soluble and fibrillar tau
Authors: Abrahamson Eric E , Sehrawat Anuradha , Zeng Xuemei , Lafferty Tara K , Shao Lan , Karikari Thomas K , Ikonomovic Milos D
Published: January 2025

Background

Phosphorylated tau proteins accumulate in pathological aggregates which define neurodegenerative tauopathies, including Alzheimer’s disease (AD). Insight into the early stages of tau polymerization/aggregation, including early hyperphosphorylation events, is critical for identification of biomarkers of incipient disease as well as novel therapy targets.

Method

We analyzed postmortem tissue sections of hippocampus from AD cases and middle frontal gyrus from non‐AD cases with mainly 4R tau isoforms (progressive supranuclear palsy, PSP; corticobasal degeneration, CBD; aging related tau astrogliopathy, ARTAG) or 3R tau (Pick’s disease, PiD). Immunohistochemical and multiple fluorescence methods were used to assess the labeling patterns of antibodies directed to phospo‐epitopes within soluble non‐fibrillar tau core (pSer262), both soluble and fibril core (pSer356), or outside of either core region (pSer202/pThr205, pThr231).

Result

In sections of hippocampus from AD cases, pSer262 and pSer356 stained punctate/granular tau aggregates in pretangles while pSer202/pThr205 and pThr231 antibodies stained tau in pretangles as well as classic NFT, neuritic component of plaques, and neuropil threads. Both pSer262 and pSer356 signals co‐distributed with pSer202/pThr205 signal in pretangles but were rarely detected in pSer202/pThr205 immunoreactive classic NFT. In sections of middle frontal gyrus from PSP and CBD cases, tufted astrocytes and astrocytic plaques, respectively, were robustly labeled with the pSer202/pThr205 antibody but lacked significant immunoreactivity to pSer262 and pSer356 antibodies. Similarly, thorn shaped astrocytes in ARTAG cases were robustly labeled with the pSer202/pThr205 antibody but were weakly labeled with the pSer262 and pSer356 antibodies. Pick bodies were labeled robustly with the pSer202/pThr205 antibody, moderately with the pSer356 antibody, and weak and sparsely with the pSer262 antibody.

Conclusion

Antibodies directed against phosphorylated epitopes within core region of soluble and fibrillar tau distinguish hippocampal pretangles in AD and appear to have less affinity for tau pathology forms in non‐AD tauopathies. Thus, they may be novel biomarkers for detecting early stages of neurofibrillary pathology development in AD.